EFFECT OF DRYING AND REWETTING AND FREEZING AND …
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UNIVERSIDAD DE LA FRONTERA Facultad de Ingeniería y Ciencias
Programa de Doctorado en Ciencias de Recursos Naturales
EFFECT OF DRYING AND REWETTING AND FREEZING
AND THAWING CYCLES ON SOIL CARBON
SEQUESTRATION IN A HUMID TEMPERATE FOREST
SOIL: UNDERLYING MECHANISMS
FRANCISCO JOSÉ NÁJERA DE FERRARI TEMUCO – CHILE
2020
DOCTORAL THESIS IN FULFILLMENT OF THE REQUERIMENTS FOR THE DEGREE DOCTOR OF SCIENCES IN NATURAL RESOURCES
EFFECT OF DRYING AND REWETTING AND FREEZING
AND THAWING CYCLES ON SOIL CARBON
SEQUESTRATION IN A TEMPERATE RAIN FOREST SOIL:
UNDERLYING MECHANISMS
This thesis was carried out under the supervision of Dr. FRANCISCO JAVIER MATUS BAEZA, belonging to the Department of Chemical Sciences and Natural Resources of the University of La Frontera, and is submitted for review by the members of the examining commission
FRANCISCO JOSÉ NÁJERA DE FERRARI ….…...….……………………………… ………………………………………. Dr. Andres Quiroz C. Dr. Francisco Matus B. DIRECTOR DEL PROGRAMA DE (Supervisor) DOCTORADO EN CIENCIAS DE RECURSOS NATURALES ……………………………………… Ph.D. Michaela Dippold (Advisor)
……………………………………… Ph.D. Jens Boy (Advisor)
……………………………………… Dr. Oscar Seguel
……………………………………….
Dra. María Cristina Diez J.
……………………………………….
Dr. Fernando Borie B.
………..…….…….…………………
Ph.D. Yakov Kuzyakov ...........................................................
Dra. Mónica Rubilar D. DIRECTORA ACADEMICA DE POSTGRADO UNIVERSIDAD DE LA FRONTERA
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…Gracias a la Vida.
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Acknowledgments
First of all, I would like to thank Dr. Francisco Matus for all the guidance, conversation
philosophy, and deep understanding of writing and development's scientific processes.
Second, to the committee of this thesis, Ph.D. Michaela Dippold, Ph.D. Jens Boy, Ph.D.
Yakov Kuzyakov and Dr. Oscar Seguel for their constant support during this process. My
special thanks to Dra. Carolina Merino, for endless enthusiasm to encourage me to finish this
work and to my friends and Earthshape field team Ph.D. (c) Moritz Koester and Ph.D. (c)
Svenja Stock. This research was supported by the priority research program of the German
Science Foundation (DFG) SPP-1803 "Earthshape: Earth Surface Shaping by Biota" (Project
Root Carbon K.U. 1184/36-1). The scholarship program from Leibniz Universität Hannover
IP@Leibniz a for a research stay in Leibniz. The national doctoral scholarship CONICYT
N° 21160957, and the regular project FONDECYT Nº 1170119 of the ANIT from the
Chilean government. Important recognition to the Chilean National Park Service (CONAF)
the access to the sample locations and in situ support of our research. Finally, my recognition
to Daniela y Diego Mendoza, Jose Parada, Dr. Ignacio Jofré, and all the people of the
Conservation and Dynamic of Volcanic Soils Laboratory-UFRO and the people of the
BIOREN-UFRO. Special thanks to Ph.D. Callum Banfield, Karin, Schmidt, and Sussan
Enzmann from the Soil Science Department and the people of KOSI and LARI isotope
laboratories of Georg-August Universität Göttingen.
I will be eternally grateful to all of you…
Summary and thesis outline 1
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Soil microbial respiration is one of the most intriguing outcomes of climate change processes. Its 3
variability has a significant impact on the overall ecosystem functions and greenhouse gasses 4
(GHG) emissions. The effect of freezing and thawing (F/T) and drying and wetting (D/W) cycles 5
are one of the main drivers of soil organic carbon (C) mineralization. This effect was addressed in 6
the General Introduction of this thesis (Chapter I), where it was hypothesized that the frequent F/T 7
and D/W cycles disrupt soil aggregates releasing formerly protected particulate organic matter 8
(POM), namely free POM fraction (fPOM) for microbial consumption. The addition of fresh soil 9
organic matter organic matter (SOM) to soil generates a priming effect PE (acceleration or 10
retardation of SOM turnover measured as CO2 effluxes). The PE will occur taken different 11
direction (positive or negative) by the effect of F/T or D/W cycles. Positive PE means a native soil 12
organic carbon (SOC) loss, while negative PE can offset the soil C lost by the fresh C incorporation 13
on soil. This hypothesis was tested in the upper layer of a loamy soil from an ancient humid 14
temperate rainforest dominated by (Araucaria araucana (Molina) K. Koch) in Nahuelbuta National 15
Park, Chile (37°47′ S, 72°59′ W . The soil is characterized as an Inceptisol, pHH2O >4, bulk density 16
0.8 Mg m-3, SOC 10 %, total N 0.5 %, and a high exchangeable Al 69 % of the base saturation. 17
Three experiments were carried out: First a D/W cycles (-5 bars/field capacity) with 13C- 18
lignocellulose applied to undisturbed soil samples were conducted including a soil with substrate 19
addition, but without cycles (No cycles) and other control soil with no cycles and substrate addition. 20
D/W was applied in four occasions in incubations at 5 °C and 25 °C incubation. The effect on C of 21
macro- (> 250-µm ), micro- (53-250-µm) and Silt+clay (< 53-µm) aggregates size and particulate 22
organic matter (POM): light (fPOM <1.6 g cm-3), occluded (oPOM 1.6-2.0 g cm-3) and heavy (Hf 23
>2.0 g cm-3) fractions were determined (Chapter II). A second incubation experiment with 14C 24
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glucose and 13C lignocellulose evaluated the effect of F/T (-18/20 ºC) and D/W (-5 bars /field 25
capacity) in four occasions on C of soil aggregates and POM fractions (Chapter III). A third and 26
final incubation experiment was conducted. It was hypothesized that F/T and D/W cycles of non C 27
added soil, increase the extracellular enzymatic activity linked to the decomposition of different 28
SOC quality released from macroaggregates with a shift in the microbial community (Chapter IV). 29
The activity of eight microbial exoenzymes related to SOM mineralization were determined. After 30
incubation, the SOM quality was assessed by thermogravimetric analysis and Fourier Transformed 31
Infrared (FTIR) spectroscopy. The changes in microbial communities were determinate by DGGE 32
analysis. 33
The results in Chapter II indicates that the CO2 efflux increased three times at 25 ºC 34
compared to 5 ºC, decreasing with an increasing number of D/W cycles. Priming effect (PE) was 35
markedly negative, i.e., high amount of labeled CO2 was released from the fresh C input rather 36
from native SOC, being more negative with D/W cycles than the No cycles treatment. Most CO2 37
effluxes come from fPOM from disrupted macroaggregates. In Chapter III, the added glucose and 38
lignocellulose followed different pathways of decomposition. High proportion of added glucose 39
was found in Silt+clay aggregates size, while lignocellulose derived C was allocated at macro and 40
microaggregate size as occluded, oPOM. Both, F/T and D/W produced negative PE, however F/T 41
cycles caused more marked effects, i.e., a preferential C use). In Chapter IV, the results indicated 42
that D/W decompose labile SOC faster than the soil with F/T cycles or the soil with No cycle. 43
There was less intensity peak of polysaccharides and lignin with D/W cycles than any other 44
treatment coinciding with previous results where F/T was more drastic treatments to release labile 45
C from disrupted aggregates Peroxidase enzymes increased with D/W cycles and glycine 46
aminopeptidase with F/T cycles related to the increases of O2 produced by frequent D/W compared 47
with F/T and No cycles. This was in line with decomposition of lignocellulose fPOM derived C 48
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shown in Chapter II and III. These results were also supported due to cellulolytic bacteria increased 49
with peroxidase exoenzyme with D/W cycles as indicated by DGGE. In general, the results 50
indicate that the exiting microbial communities are well adapted to the studied soil showing similar 51
shift in the community after F/T or D/W cycles. Overall, F/T and D/W caused a positive net SOC 52
balance (gain of SOC)) including No cycles, after 28 days of incubation. However, this conclusion 53
needs to be taken cautiously since the C substrate used in this study is rather different from the 54
litterfall found in this forest ecosystem. We conclude that F/T and D/W cycles are not equivalent 55
disrupting events. Even though both caused a negative PE by preferential C use by microbial 56
community with increased exoenzyme to decompose fPOM materials released from 57
macroaggregate at high temperature. Our findings indicate that and increase in frequency of D/W 58
cycles due to climate change will play a key role to keep the SOC content by decreasing the 59
accumulation of newly formed SOC in soils of Nahuelbuta National park. 60
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Keywords: Soil Priming effect, Drying/Rewetting cycles, Freezing/thawing cycles, Isotopic 62
carbon.63
Abbreviation 64
65
TE terrestrial ecosystems 66
D/W drying and wetting cycles 67
F/T freezing and thawing cycles 68
OM organic matter 69
SOM Soil organic matter 70
SOC soil organic carbon 71
POM Particulate organic matter 72
fPOM free particulate organic matter 73
oPOM occluded particulate organic matter 74
Hf organic matter heavy fraction 75
TCO2 total CO2 efflux 76
SCO2 soil derived CO2 efflux 77
LCO2 lignocellulose derived CO2 efflux 78
GCO2 glucose derived CO2 efflux 79
80
PE Priming effect 81
MB microbial biomass 82
CUE carbon use efficiency 83
SUE substrate use efficiency 84
TGA Thermogravimetric analysis 85
FTIR Fourier transformed infrared analysis 86
AP acid phosphatase 87
BG b-glucosidase 88
CBH cellobiohydrolase 89
GAP glycine aminopeptidase 90
LAP leucine aminopeptidase 91
NAG N-acetyl-b-D-glucosaminidase 92
PPO polyphenol oxidase 93
POD peroxidase 94
DGGE Denaturing gradient gel electrophore95
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TABLE OF CONTENTS 97 98 99 Agradecimientos / acknowledgements i
Summary and keywords ii
Abbreviations iv
Table of contents vi
1. CHAPTER I. GENERAL INTRODUCTION 1
1.1 Soil organic matter decomposition 2
1.2 Soil organic matter stabilization 4
1.3 Effect of drying/wetting and freezing/thawing cycles 7
1.4 Soil microbial responses to Drying/wetting and Freezing/thawing cycles 8
1.5 Study site: Nahuelbuta national park 9
1.6 Hypothesis 12
1.7 Objectives 12
2. CHAPTER II: Effects of drying/rewetting on soil aggregate dynamics
and implications for organic matter turnover. Published in Biology and
Fertility of Soil (2020) Najera, F., Dippold, M.A., Boy, J. Seguel, O.,
Koester, M., Stock, S., Merino, C., Kuzyakov, Y., Matus, F.
https://doi.org/10.1007/s00374-020-01469-6
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2.1 Abstract 15
2.2 Introduction 17
2.3 Materials and Methods 19
2.3.1. Study site and sampling 19
2.3.2. Microcosm experiment 20
2.3.3. CO2 sampling 22
2.3.4. Aggregate size classes 22
2.3.5. Organic matter density fraction 23
2.3.6. Priming effect 23
2.3.7. Soil analyses 24
2.3.8. 13C/12C isotope ratio 24
2.3.9. Substrate use efficiency 25
2
2.3.10. Statistical analyses 25
2.4 Results 26
2.4.1. Aggregates size classes 26
2.4.2. Density fractionation 28
2.4.3. CO2 effluxes 29
2.4.3. Priming effect 31
2.4.3. Microbial biomass and substrate use efficiency 31
2.5 Discussion 33
2.5.1. Aggregates and particulate organic matter 33
2.5.2. CO2 efflux 34
2.5.2. Priming effect 35
2.6 Conclusions 36
2.7 Acknowledgements 37
2.8 Funding information 37
CHAPTER III: Freezing/Thawing And Drying/Wetting Cycles Effects On
Glucose (14C) And Lignocellulose (13C) Decomposition And Carbon
Sequestration(2021) Najera, F., Dippold, M.A., Boy, J. Seguel, O., Koester, M.,
Stock, S., Merino, C., Kuzyakov, Y., Matus, F. (submitted Applied soil Ecology)
38
3.1 Abstract 39
3.2 Introduction 41
3.3 Material and methods 42
3.3.1. Incubation setup 43
3.3.2. Microbial biomass, soil aggregate, and density fractionation 44
3.3.3. Decomposition of glucose and lignocellulose 45
3.3.4. Net carbon distribution in soil aggregates and particulate organic
matter 46
3.3.5. Glucose and lignocellulose carbon decomposition 46
3.3.6. Soil CO2 efflux rates 48
3.3.7. Drying/wetting and freezing/thawing cycles influence organic
carbon in soil aggregate and particulate organic matter 48
3.3.8. Carbon use efficiency 48
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3.3.9. Net organic carbon balance 48
3.3.10. Statistical analysis 49
3.4. Results 49
3.4.1. Organic carbon distribution of particulate organic matter and soil
aggregates 49
3.4.2. Organic carbon in aggregates and particulate organic matter as
affected by drying/ wetting or freezing/ thawing 51
3.4.3. CO2 effluxes 52
3.4.4. Microbial biomass and carbon use efficiency 55
3.4.5. Net organic carbon balance 55
3.5 Discussion 56
3.5 Acknowledgments 59
CHAPTER IV: Freezing/hawing and drying/wetting cycles on microbial
communities and enzyme activities in humid temperate forest. Najera, F., Jofré,
I., Dippold, M.A., Boy, J. Koester, M., Stock, S., Merino, C., Kuzyakov, Y.,
Matus, F. (In preparation).
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4.1 Abstract 61
4.2 Introduction 62
4.3 Methodology 64
4.3.1. Study site 64
4.3.2. Incubation experiment 65
4.3.3. Thermogravimetry and differential scanner calorimetry 65
4.3.4. Attenuated total reflectance Fourier transform infrared
spectroscopy (ATR-FTIR) 66
4.3.5. Extracellular enzyme activity 66
4.3.6. Cellulolytic bacteria counting 67
4.3.7. Bacterial community profile 68
4.3.8. Statistical analysis 69
4.4 Results 69
4.4.1 Soil organic matter quality 69
4.4.2 Exoenzyme activity 73
4
4.4.3 Cellulolytic bacteria count 74
4.4.3 Bacterial community profile 75
4.5 Discussion 76
4.6 conclusions 79
5 CHAPTER V. "General discussion, conclusions, and future directions" 80
5.1 General discussion 81
5.2 Aggregate size classes, soil carbon, and POM fractions 81
5.3 Soil CO2 fluxes 82
5.4 Priming effect 82
5.5 Soil microbial dynamics 83
5.6 General conclusions 85
5.3 Perspectives 86
REFERENCES 88
FIGURES AND TABLES
Chapter I
Figure 1. Nahuelbuta National park precipitation monthly data (2001-2019).
Data from CR2. 10
Figure 2. a) Trends of annual precipitation observed in rain gauge stations in
Chile between 1979 and 2014. Time series of annual mean precipitation in
central Chile based on (b) rain gauge observation and (c) SST-forced GCM
simulation. Dashed lines indicate the corresponding linear precipitation trend
from 1979 to 2014. Box in figure 1 a shows domain. Geophysical Research
Letters, Volume: 43, Issue: 1, Pages: 413-421, First published: 17 December
2015, DOI: (10.1002/2015GL067265) used for regional average.
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Chapter II 14
Figure 1. Schematic illustration of the impact of drying/rewetting (D/W) events
on the soil C dynamics and CO2 efflux after fresh C addition. D/W cycles
breakdown soil macroaggregates and release labile particulate organic matter
(fPOM) that was formerly protected. Increasing number of D/W cycles raises
microbial respiration from decomposition of new organic matter of the POM
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5
fraction rather than using older, more stabilized OM, thus generating a negative
PE.
Figure 2. Microcosms chambers (acrylic materials) setup for the drying and
rewetting cycles and CO2 collection. Note: The top of the main chamber has a
small additional chamber to which several irrigation needles were connected to
apply the irrigation water uniformly.
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Figure 3. Proportional change effect of aggregate size classes (macroaggregates
>250 µm; microaggregates 250-53 µm and silt+clay size <53 µm) shown by
subtracting the treatment with constant soil moisture to the treatments with 1 or 4
D/W cycles. Soils amended with lignocellulose are displayed after 27 days of
incubation at 5 ºC (left) and 25 ºC (right), whereas relative weight (a and b), total
C content (c and d) and lignocellulose-derived 13C incorporation (e and f) of the
aggregate size classes is shown. Bars indicate standard errors of the means.
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Figure 4. Proportional change effect of organic matter particles (POM) from the
entire soil, OM fraction from the different aggregates was reunited as: light
fraction < 1.6 g cm -3 (fPOM), occluded fraction 1.6-2.0 g cm-3 (oPOM), heavy
fraction > 2.0 g cm-3 (Hf) shown by subtracting the treatment with 1 or 4 D/W
cycles and with constant soil moisture to the treatments 0 cycles. Soils amended
with lignocellulose after 27 days of incubation at 5 ºC and 25 ºC are presented
regarding the relative weight of the OM fraction (a and b), their total C content (c
and d) and their lignocellulose-derived 13C incorporation (e and f). Bars indicate
standard errors of the means
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Figure 5. Total CO2 evolved during 27 days of incubation at 5 ºC (a) and 25 ºC
(b) from soil with lignocellulose addition and D/W (0-cycles, 1-cycle and 4-
cycles). Dry period (∆) started on day 3 and continued for another 3 days of
incubation. The wet period (∇) started on day 6 until next drying. 13CO2 efflux
through 27 days of incubation at 5 ºC (c) and 25 ºC (d). Small bas on the data
point indicates standard errors of the mean. Large bars indicate the least
significant differences (LSD) (p < 0.05).
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Figure 6. Priming effect (PE) through 27 days of incubation at 5 ºC (a) and 25
ºC (b) for soil with lignocellulose addition. Dry period (∆) started on day 3 and 30
6
continued for another 3 days of incubation. The wet period (∇) started on day 6
until next drying. Relative priming effect as affected by drying and rewetting
(PEc), calculated as the difference between 1 or 4 cycles and 0 cycles, is shown
for 27 days of incubation at 5 ºC (c) and 25 ºC (d) for soil with lignocellulose
addition. Small bas on the data point indicates standard errors of the mean. Large
bars indicate the least significant differences (LSD) (p < 0.05).
Figure 7. Substrate use efficiency (SUE) of 13C-lignocellulose at 5 ºC (a) and 25
ºC (b) estimated after 27 days of incubation of the D/W treatments 0-cycles, 1-
cycle and 4-cycles. Small bas indicates standard errors of the mean. Large bars
indicate the least significant differences (LSD) (p < 0.05).
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Chapter III
Figure 1. Conceptual representation of the soil carbon (C) stock accumulation
(positive net carbon balance) from lignocellulose and glucose derived C
remaining in temperate forest soil of Araucaria Araucana after 28 days
incubation. The negative priming effect is represented by the native CO2 effluxes
from the control soil without substrate addition and the native CO2 from
lignocellulose and glucose drying/wetting, freezing/thawing no cycles treated
soil.
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Figure 2 Soil organic carbon, lignocellulose derived carbon and glucose derived
carbon after drying and wetting (D/W), freezing and thawing (F/T), and no
cycles (No cycles) at the end of 28 days incubation in (A) macroaggregates
(2000-250-µm), (B) microaggregates (250-53-µm) and (C) Silt-clay size
aggregate (<53-µm) distributed in particulate organic matter density fractions
(POM): light fraction (Lf <1.6 g cm-3); occluded fraction (Of 1.6-2.0 g cm-3) and
a heavy fraction (Hf >2.0 g cm-3). Whiskers bars are the standard error of the
means. Different letters within the column indicate significant differences at p
<0.05.
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Figure 3. Net CO2 effluxes obtained by the difference between freezing/thawing
(F/T) or drying/wetting (D/W) and no cycles (No cycles) after 28 days of
incubation. Whiskers bars in each column indicates the standard error of the
mean (p <0.05).
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Figure 4 Total CO2 effluxes from (A) soil organic carbon (SOC), (B)
lignocellulose, (C) glucose derived C, (D) priming effect (PE) from
lignocellulose, and (D) PE from glucose after four cycles of drying/wetting
(D/W) and freezing/ thawing (F/T). Drying or freezing is indicated by ▽ and
wetting or thawing by D. Whiskers bars indicate standard error of the mean
(SEM) (p<0.05).
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Fig. 5 Net priming effect (PE) obtained by the difference between
freezing/thawing (F/T) or drying/rewetting (D/W) and no cycles (No cycles)
after 28 days of incubation. Whiskers bars indicate standard error of the mean
(SEM) (p<0.05).
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Chapter IV
Figure 1. Thermogravimetric analysis (TG) of soil organic matter. The top
panel is the differential scanner colorimetry indicates the Heat flow (mV g-1
ºC-1) being the release or retention of heat from soil changes before weight
loss by combustion and evaporation of organic and mineral soil compounds.
Edo-up indicates endothermic reactions are represented as the curve toward
positive values. Meddle panel is the first derivative of TG, weight loss (mg g-
1 ºC-1). Bottom panel, the weight loss (%). Lines in 200 and 450 ºC indicate a
separated zone where different soil components are lost (endo-up means
endothermic reaction has positive y-axis direction).
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Figure 2. Attenuated total reflectance Fourier transform infrared (ATR-
FTIR) spectra of soil after 4 D/W (red line), 4 F/T (Blue line) cycles, and soil
with No cycles (black line). The peaks indicate different organic compounds
in soil.
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Figure 3. Figure 3. Exoenzyme activity on the soil after one and four drying and
wetting cycles (D/W), four freezing and thawing (F/T) cycles and No cycles
(Control). Different letters indicate a significant difference within each panel (p
<0.05).
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Figure 4. Colonies forming Unities (CFU) after D/W and F/T cycles were
applied a) total CFU g soil-1;b) cellulolytic CFU bacteria g soil-1; c) proportion
(%) cellulolytic CFU bacteria of total microbial counting.
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Figure 5. Colonies forming Unities (CFU) on CMC medium of growing after
D/W and F/T cycles, picture of microbial colonies after four D/T cycles (A), one
D/W cycle (B); four F/T cycles (C) and soil No cycles (D) applied (control),
Halos indicate cellulosic microbial communities have grown.
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Figure 6. DGGE analysis related to exoenzyme activity of soil. The soils with
drying and wetting cycles (1 DR and 4 D/W), freezing and thawing cycles (4FT)
and no cycles applied (Control). Acid phosphatase (AP), b-glucosidase (BG),
cellobiohydrolase (CBH), glycine aminopeptidase (GAP), Leucine
aminopeptidase (LAP), N-acetyl-b-D-glucosaminidase (NAG), Polyphenol
oxidase (PPO) Peroxidase (POD).
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Tables
Chapter II
Table 1. Properties and standard deviation (±) of studied soil (0-8 cm depth). 20
Table 2. Total recovery (%) of soil weight, soil C and labelled C after dry
sieving. 26
Table 3. Total microbial biomass C (MB-C), MB-13C and standard error of the
mean (±) of four replicates. Different low case letters in each column and within
each temperature indicate significant differences (p < 0.05). Different capital
letters in each column and between temperatures indicate significant differences
(p < 0.05).
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Chapter III
Table 1. Microbial biomass carbon (MBC) expressed in mg kg-1 and carbon use
efficiency (CUE) in soils after freeze and thawing (F/T), drying and wetting
(D/W), and no cycles (No cycle).
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Table 2. Net carbon balance obtained by the difference between the priming
effect and substrate derived carbon C. Symbol ± is the standard error of the
mean. Low case letters least significative differences (p <0.05) within cycles
applied.
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Chapter IV
Table 1. Extracellular enzymes are assessed in soil and their abbreviations,
functions, corresponding substrates, and substrate concentrations. 67
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101
102
103
104
CHAPTER I 105
106
General Introduction 107
108
2
The intensification in frequency and magnitude of climatic events as drying/rewetting (D/W) and 109
freezing/thawing F/T) cycles will strongly influence carbon (C) and nitrogen (N) emissions from 110
terrestrial ecosystems (TE) (IPCC, 2013; Frank et al., 2015). Under this scenario, soil gases such 111
as carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) will increase their emissions to 112
the atmosphere as a result of changes in soil biophysical conditions (Kim et al., 2012; Shi et al., 113
2014). 114
Many factors control CO2 emission in ecosystems, which are difficult to separate because 115
its covariation in the soil (Unger et al., 2012). For example, it has been reported that greenhouse 116
gases (GHG) do not always increase with increasing temperature because of not all mechanisms 117
are fully understood (Kim et al., 2012). Therefore, SOM pools related to the temperature-sensitive 118
are far from simplistic interpretations (Davidson and Janssens, 2006). Another example, it has been 119
suggested that the duration of the CO2 efflux in response to rainfall events depends on the C 120
availability (Fernandez et al., 2006). The variation of soil moisture may also induce structural 121
changes in the chemical and physical soil properties and microorganism communities (Vicca et al., 122
2014). It is estimated that prolonged drought in summer or frost in winter periods and subsequent 123
rewetting are the combined factors that will reduce the C accumulation in the soil in all ecosystems 124
on an annual scale (Matzner and Borken, 2008; Borken and Matzner, 2009). This effect will 125
directly affect the flow of soil gas emissions (Jarvis et al., 2007) and the microorganism community 126
(Meisner et al., 2015) and ultimately the soil organic matter decomposition. 127
Soil organic matter decomposition 128
129
Drying and Freezing reduce the availability of organic and inorganic soluble substrates and 130
decreases the mobility of extracellular enzymes (Borken and Matzner, 2009). It may cause a 131
breakdown of soil aggregates exposing formally protected soil organic matter (SOM) within 132
3
aggregates to microbial attack (Appel, 1998; Adu and Oades, 1978; Oztas and Fayertorbay, 2003). 133
These processes will directly affect the soil gas efflux through acceleration or deacceleration of 134
soil microbial respiration (Jarvis et al., 2007). After rewetting, an increase of gas fluxes will occur 135
by the well-known Birch effect (Birch, 1958). The decomposition turnover of particulate organic 136
matter (POM), which are recognizable structures such as root and fungi tissues, increases. These 137
effluxes decline with successive D/W events due to a limited pool of labile C substrates (Fernández 138
et al., 2006; Schimel and Mikan, 2005; Goldberg et al., 2008). Prolonged summer drought and 139
subsequent rewetting will reduce soil C pool and N mineralization (Borken and Matzner, 2009). 140
The acceleration/deceleration turnover rate of the SOM after the input of fresh C results in a closely 141
related Birch phenomenon termed priming effect (PE) (Bingemann et al., 1953). The PE is a short-142
term lived phenomenon where the turnover of SOM is accelerated (positive PE) or retarded 143
(negative PE) (Kuzyakov et al., 2000; Kuzyakov, 2010; Garcia-Pausas and Paterson., 2011). The 144
PE is determined by collecting the total CO2 efflux from the enriched soil with 13C or 14C input 145
(Jarvis et al., 2007). Hence, the PE is positive if the amount of non-labeled CO2 from treated soil 146
is higher than that of the control soil (without fresh C input). On the contrary, the PE is negative 147
when the CO2 from the control soil is higher. Although PE is defined as a short-term phenomenon, 148
Fontaine et al. (2011) demonstrated that this could be a long-lasting effect after the initial C inputs 149
decomposition, especially if the input is a complex substrate. So, the PE is significantly related to 150
the composition of the POM fraction where microbes are stimulated to consume it triggering the 151
CO2 efflux from the soil subject to environmental constraints (Magid and Kjægaard, 2001; 152
Gregorich et al., 2006). Similar biochemical composition of the fresh substrate added to the soil is 153
related to a positive PE because of the metabolic pathways of different microorganism successions 154
(Liu et al., 2017; van der Wal and de Boer, 2017). 155
4
Drying and rewetting cycles affect carbon diffusivity in soil aggregates. This affects in turn 156
the carbon supply to microorganisms, impacting on the CO2 efflux and carbon storage (Manzoni 157
et al., 2012). Soil microbial respiration is one of the most intriguing process outcomes on climate 158
change, and its variability has a significant influence on the overall functions of ecosystems and 159
ultimately on GHG emissions (Houghton et al., 1990; Corti et al., 2002; Lal, 2004; Vicca et al., 160
2014). Potential SOM management play a key role on global warming but it still challenging 161
(Stockmann et al., 2013). This is because the PE affects has been studied without integrating all 162
geophysical factors that determine the SOC level.. Only in the last decade the PE has been 163
invocated as a general phenomenon that should be part of comprehensive studies of C simulation 164
models including factors such as C-input rate, nutrient level and C-input frequency. Thus, there is 165
a need for an integrative hypothesis of the factors and processes underlying D/W and F/T cycles 166
on SOM level to finally predict GHG emissions. 167
168
Soil organic matter stabilization 169
170
Soil organic matter can be preserved due to freezing temperatures, low O2 content, and high 171
moisture content in TE (Kim et al., 2012). Decomposition of SOM follows, in general terms, the 172
temperature sensitivity of Arrhenius law (1896). Mineralization rates from recalcitrant organic 173
materials will show large Q10 values (SOM turnover twice for every 10 °C increases). These Q10 174
values mean that the stable SOM pool will be decomposed due to changes in temperature by its 175
intrinsic recalcitrance biochemical properties (Sinha and Cherkauer, 2010). Some C models assume 176
that this temperature sensitivity to decomposition is identical for all types of SOM (Burke et al., 177
2003). Nevertheless, studies show that the decomposition from pulses of labile organic materials 178
(coming from litter input) exhibits a lower value of Q10 (Boy et al., 2016). They indicate that 179
5
intrinsic temperature sensitivities of decay and microbial responses to temperature regime is still 180
needed to predict the respiration of particular soils against warming. (Davidson and Janssens, 2006; 181
Billings and Ballantyne, 2013). Studies report the GHG not always increases with increasing 182
temperature, and not all the mechanisms that drive gas fluxes are fully understood (Kim et al., 183
2012). Models illustrate that aggregate mean pore size is a crucial factor determining gas diffusion 184
rate and regulates aerobic and anaerobic microbial community composition and function under 185
various environmental conditions (Ebrahimi and Or, 2016). We need to combine the interplay of 186
stabilization and destabilization including the PE as a function of temperature and soil moisture to 187
elucidate the SOM sensitivity to decomposition as affected by D/W and F/T (Sierra et al., 2012). 188
The recalcitrant pool of SOM is typified as organic compounds that may be difficult to 189
decompose owing to their specific chemical structure (Trumbore, 2009). Despite this, SOM 190
mineralization proceeds at a much slower rate than the decomposition of plant and animal residues 191
from which these compounds are formed (Kemmitt et al., 2008). Schmidt et al. (2011) pointed out 192
that SOM decomposition is controlled first by biological and environmental conditions and second 193
by the carbon-based inputs' molecular structures. Furthermore, the model's output shows that the 194
low-quality substrates (high C:N ratio and high in lignin content) are more sensitive to changes in 195
temperature (Sierra et al., 2012). Carbon release as CO2 covary with other factors like mineralogy, 196
clay content, aggregation, or soil water content (Davidson and Janssens, 2006). Therefore, small 197
climate changes could significantly affect the release of soil microbial-derived CO2 (Billings and 198
Ballantyne, 2013). Also, it is still known little about how adsorption and desorption of C onto 199
mineral surfaces respond to climatic variability (Davidson, 2015) related to the recalcitrance of 200
molecular structure. The stable soil organic C (on average 83%) is associated with the soil mineral 201
phase rather than recalcitrant (Matus, 2021; Mikuta et al., 2006; Schmidt et al., 2011). 202
6
Physical protection of SOM is other stabilization mechanism by the inaccessibility of 203
decomposers to SOM due to the spatial separation between the substrate and microorganisms and 204
its exoenzymes intra- or inter -aggregates. (Six et al., 2000, 2002). Tisdall and Oades (1982) 205
proposed a hierarchy classification of the soil aggregates. Macroaggregates (>250 µm) in diameter 206
are management-dependent, and microaggregates (<250 µm) in diameter are independent of 207
management. In general, several mechanisms of physical stabilization are defined: (1) A 208
biochemical protected C pool, with a prolonged turnover rate. (2) A silt-and clay protected C pool, 209
the hydrolysable pool that under cultivation is lost. (3) An intra-aggregate -protected C pool 210
(iPOM), and (4) The unprotected free labile C pool (fPOM) as a source of nutrients. These last two 211
pools depend on climatic and management conditions. (Denef et al., 2001a,b). 212
Inhibition of microbial activity and C availability is related to soil mineralogy and clay type 213
in soils, acting on C sequestration at different climate conditions (Sollins et al., 1996; Doetterl et 214
al., 2015). The formation of organo-mineral complexes is important in SOM storage (Lawrence et 215
al., 2015; Song et al., 2014). Only a few studies have related PE and mineralogy (Fontaine et al., 216
2007). Rasmussen et al. (2006; 2007) found that SOM in the amorphous clays exhibits retardation 217
of SOM turnover. Secondary kaolin clay formation and the presence of extremely reactive Al and 218
Fe-hydroxides were strongly correlated with the long-term stability of SOM (Martins et al., 1982; 219
Zunino et al., 1982; Matus et al., 2008; Garrido and Matus, 2012; Calabi-Floody et al., 2015; 220
Merino et al., 2015; Lawrence et al., 2015). 221
222
Effect of drying/wetting and freezing/thawing 223
224
Colloidal soil organic matter can flocculate within aggregates given stability to the soil structure 225
(Sollins et al., 1996). However, the aggregate stability is sensitive to changes in land use, carbonate 226
7
levels, and soil texture (Elliot, 1986, Ontl et al., 2015). Six et al. (2000) concluded that the 227
incorporation and stabilization of occluded POM into microaggregates within macroaggregate and 228
free microaggregates under no-tillage is a dominant factor for protecting the fine-sized fraction of 229
POM. These incorporation processes are determined by D/W and thawing cycles (Denef et al., 230
2001a). 231
Denef et al. (2001b) indicate that D/W cycles will allow the accessibility to microbial attack 232
increasing CO2 fluxes. However, the microbial contributions generally decreased over time due to 233
a reduction in soil C content (Shi et al., 2014) and the apparent progressive preservation of SOM 234
(Borken and Matzer, 2009), making it difficult to predict the direction of respiration fluxes (Billings 235
and Ballantyne, 2013). In contrast, plate et al. (2009) did not find correlation with soil structure 236
and CO2 effluxes in disrupted isolated soil aggregates. This variability could be because the 237
aggregate properties influencing fluxes, such as anaerobiosis and nutrient availability, are 238
inevitably changed upon aggregates isolation (Six and Paustian, 2014). 239
There is an agreement that a simple empirical relationship of temperature and moisture with 240
GHG emissions found in one individual site may not be found in another, because geographical 241
and temporal variation (Hibbard et al., 2005). A large study in Chile, across different climes and 242
soils, indicate that climatic aspect as precipitation and temperature were only secondary predictors 243
for C storage. In contrast, mineralogy and soil texture were the primary drivers for C accumulation 244
in the different ecosystems (Doetterl et al., 2015). However, soil properties and mineralogy could 245
not explain the soil C sequestration and have a minor effect within intermediate density fraction 246
(Sollins et al., 1996). The need to assess the significance of soil physicochemical and biotic factors 247
simultaneously is essential (Barto et al., 2010) to predict the soil C storage in response to D/W and 248
F/T cycles, and especially to quantifying the primiable soil C fraction, vulnerable to climate change 249
(Davidson, 2015). 250
8
251
Soil microbial responses to Drying/wetting and Freezing/thawing 252
253
Microorganisms have developed several strategies to adapt and face the ever-changing availability 254
of water and heavily rely on soil moisture (Schimel et al., 2007; Tecon and Or, 2017). The diffusive 255
transport of substrates and extracellular enzymes and the active or passive mobility of 256
microorganisms slows down with decreasing water potential and thickness of the water film 257
(Borken and Matzner 2009; Miura et al., 2019). The microorganism can adapt to changing climatic 258
conditions. This adaptation might slowdown the rate of SOC lost (as CO2 efflux), induced by D/W 259
(de Nijs et al., 2019). Drought/freezing increased microbial resilience but not resistance, suggesting 260
that the exposure to D/W cycles restructure microbial communities to quick response to 261
rewetting/thawing and to use C with high efficiency during the perturbation (Koponen and Bååth, 262
2016; de Nijs et al., 2019). The frequency and intensity of the disturbance influence how long 263
microbial communities persist (Evans and Wallenstein, 2012). However, there is still incomplete 264
knowledge of processes connecting SOM humification, destabilization, and the mineral interaction 265
linked to CO2 fluxes. Historically drier sites could leave a legacy effect on microbial functions 266
(Leizeaga et al., 2020), and no effect should be observed. Studies using distinct soils and methods 267
have always reported inconsistent effects of F/T and D/W cycles on microorganisms and microbial 268
biomass, showing either an increase (Sistla and Schimel, 2013; Sørensen et al., 2018), a decrease 269
(Turner and Romeo, 2010), or no change at all (Bandick and Dick, 1999; Matzner and Borken, 270
2008). Moreover, an active microbial survival remains when soils are frozen (Koponen and Bååth, 271
2016; Bore et al., 2017). 272
9
In conclusion, integrative knowledge is needed to relate the drivers and mechanisms on 273
GHG fluxes from more developed soils, such as the influence of D/W and thawing cycles on C 274
availability of different C pools of SOM on microbial responses. 275
276
Study site: Nahuelbuta national park 277
278
This mountain chain extends for 175 km, between the Bio-Bio River (37°80' S) and the Imperial 279
River (38°85'09 S), with a maximum elevation of 1350 m. the NNP is located in 37°47′ S, 72°59′ 280
W. The soil will be from a south slope dominated by Araucaria trees (Araucaria araucana (Molina) 281
K. Koch)). Species-rich rainforests survived the glacier times (approx. 20,000 years BP), near the 282
northern limit of their present distribution. Rainfall was presumably higher during the glacial 283
period, and low temperatures were moderated by oceanic influences (Villagran 1990; Armesto et 284
al. 2001). Some areas in the Coastal Range between 38º and 40º remained free of periglacial 285
processes that affected the persistence of vegetation further south and in the proximity of Andean 286
glaciers (Smith-Ramírez 2004). These sectors produced high endemism, including species that only 287
exist in Nahuelbuta. Also, it is located in a climatic and biogeographic transition zone between the 288
warm savanna biome north of the Bío-Bío River and the extreme north of the Valdivian forest 289
biome, making it unique from other SNASPE units (CONAF, 2002). The land use of the park is 290
destined for the conservation of biodiversity and recreation, with minimum forest management and 291
low human impact. 292
Historical weather records (Figure 1 and 2) indicate that the mean annual temperature and 293
mean annual precipitation have decreased along with the coast of central Chile on two studies, 294
between 1985 to 2015 and 1976 to 2006 (Stolpe and Undurraga, 2016; Falvey and Garreaud, 2009; 295
Vullie et al., 2015). This data indicated an increase in the heat waves (Ferron et al., 2019) and the 296
10
severity and frequency of extended droughts periods (Boisier et al., 2015; Bozkurt et al., 2017) are 297
expected to occur. During the 2010–2015 period, a rainfall deficit ranging from 10% to 30% was 298
observed in nearly all seasons between Valparaiso and Araucania (Urrutia-Jalabert et al., 2018). 299
This tendency for drier conditions during the warmer months in central and south-central Chile will 300
likely result in an eventual southerly expansion of the Xeric conditions (Stolpe and Undurraga, 301
2016). 302
303
Figure 1: Nahuelbuta National park precipitation monthly data (2001-2019). Data from CR2. 304
305
Soil characterization (CIREN, 2002) Cerro Nahuel soil series: it is classified by USDA soil 306
taxonomy as Andic Dystrudepts (Inceptisol), moderately deep, from highly weathered granitic 307
rocks parental mineralogy in hill position. The topsoil texture is fine sandy loam, and in the subsoil, 308
it changes towards grayish brown sandy loam and high organic carbon content 11%, being 309
classified as Umbrisol by the International FAO soil classification (IUSS Working Group WRB, 310
2015). The pedon is well-drained and moderately permeable. Most sites have slopes higher than 311
30%, leaving soils slightly to somewhat undulated in the top positions (plateau). Samples were 312
0100200300400500600700800
04-01 01-04 10-06 07-09 04-12 12-14 09-17 06-20
prec
ipita
tion
(mm
mot
h-1 )
Date (month-year)
Nahulbuta National Park
11
taken from the top horizon firth 0-10 cm. of the forest soil between an not directly under Araucaria 313
trees. 314
315
Figure 2 (a) Trends of annual 316
precipitation observed in rain 317
gauge stations in Chile 318
between 1979 and 2014. 319
Time series of annual mean 320
precipitation in central Chile 321
based on (b) rain gauge 322
observation and (c) SST-323
forced GCM simulation. Dashed lines indicate the corresponding linear precipitation trend from 324
1979 to 2014. Box in figure 1 a shows domain. Geophysical Research Letters, Volume: 43, Issue: 325
1, Pages: 413-421, First published: 17 December 2015, DOI: (10.1002/2015GL067265) used for 326
regional average. 327
328
In the study area we evaluate the intensity (changes in soil temperature and moisture) and frequency 329
of D/W and T cycles on SOM decomposition (CO2 emission from the soil) and by the availability 330
of the incorporated C into macroaggregates (> 250 µm), linked to the coarse and fPOM fraction. 331
In contrast, in soils with less D/W and T intensity, microaggregates (< 250 µm) will stabilize the 332
main fraction of biodegradable C on occluded POM. 333
Drying/rewetting and thawing cycles cause mechanical disturbance exposing organic 334
materials from altered aggregates. According to the hierarchy aggregation theory, macroaggregates 335
would first be disturbed after D/W (Tisdall and Oades, 1982; Denef et al., 2001). The mechanical 336
12
disturbance will leave available organic matter microbial to attack, which will produce an increased 337
CO2 flux from new and formally protected organic matter. 338
339
The general hypothesis of the present study is: 340
That D/W and F/T cycles will expose formerly protected POM from soil aggregates, mainly 341
particulate organic matter, fPOM fraction consumed by the soil microorganism of a humid 342
temperate forest soil under climate change influence. Non-protected C preferred by 343
microorganisms will cause ongoing soil C turnover retardation, i.e., a negative PE. 344
345
The objectives of this thesis are: 346
1) To assess the effect of freezing/thawing and drying/rewetting cycles on CO2 soil efflux 347
from isotopically labeled substrate independence on soil temperature and moisture in 348
undisturbed/disturbed soil cores. 349
2) To evaluate the stabilization of particulate organic matter (POM) fraction from macro- 350
and micro-aggregate size class in a humid temperate forest from Nahuelbuta National 351
Park. 352
3) To determinate the effect of D/W and F/T on carbon use efficiency, microbial biomass, 353
exoenzyme activities, and microbial community. 354
355
The present objectives were fulfilled in Chapter II, Chapter III, and Chapter IV.A general 356
introduction is given in Chapter I, where the outline of this thesis is presented. The main results of 357
D/W and F/T events are discussed. 358
In Chapter II, the intensity of PE after 13C-lignocellulose substrate addition due to D/W 359
cycles in undisturbed soil cores at increasing temperatures (5 ºC and 20 ºC) was evaluated. The 360
13
selected site is a loamy soil sampled in intact cores from a humid temperate forest of Araucaria 361
araucana in the Nahuelbuta National Park, Araucania Region, Chile. In these experiments the CO2 362
flux was estimated from soil aggregates (macroaggregates, >250-µm; microaggregates, 250-53-363
µm and Silt+clay size aggregates, <53 µm) and POM fractions (light, fPOM <1.6 g cm-3; occluded, 364
oPOM 1.6-2.0 g cm-3 and heavy, Hf >2.0 g cm-3). 365
In Chapter III, the F/T, D/W, and No cycle (soil without cycles but with substrate) were 366
evaluated by comparing the impact of two sources of fresh C substrate, 13C-lignocellulose and 14C-367
glucose on soil aggregates and POM fractions at 20 ºC for 28 days. 368
In Chapter IV, an incubation experiment was installed to evaluate the F/T and D/W effect on 369
SOM quality, soil microbial communities, and exoenzyme responses during incubation of 28 days. 370
Finally, in Chapter V, the results of this thesis are discussed, and general conclusions and 371
perspectives are addressed. 372
373
14
374
CHAPTER II 375
376
Najera, F., Dippold, M.A., Boy, J. Seguel, O., Koester, M., Stock, 377
S., Merino, C., Kuzyakov, Y., Matus, F. (2020). Effects of 378
drying/rewetting on soil aggregate dynamics and implications for 379
organic matter turnover. Biology and Fertility of Soils 56, 893–380
905. 381
https://doi.org/10.1007/s00374-020-01469-6 382
383
384
385
15
Abstract 386
387
Drying and rewetting (D/W) of soil have significant impacts on soil organic matter (SOM) 388
turnover. We hypothesized that frequent D/W cycles would release the labile organic matter locked 389
away in soil aggregates, increasing the priming effect (PE) (acceleration or retardation of SOM 390
turnover after fresh substrate addition) due to preferential utilization by microbes. 13C-labelled 391
lignocellulose was added to the soil and the effects of 0, 1, or 4 cycles of D/W were evaluated at 5 392
°C and 25 °C after a 27-day incubation of undisturbed soil cores from a temperate forest (Araucaria 393
araucana canopy). Following the incubation, macroaggregates (>250 μm), microaggregates (250–394
53 μm), and silt+clay materials (<53 μm) were separated. For each aggregate size class, three 395
organic matter (OM) fractions (light (fPOM <1.6 g cm-3), occluded (oPOM 1.6–2.0 g cm-3), and 396
heavy (Hf > 2.0 g cm-3)) were determined. D/W cycles caused macroaggregates to increase and a 397
decrease in microaggregates (>15%) at warm temperatures, and preferential use of the novel 398
particulate organic matter (13C labelled), formerly protected fPOM. CO2 efflux was three times 399
higher at 25 °C than at 5 °C. The D/W cycles at 25 °C had a strong negative impact on cumulative 400
CO2 efflux, which decreased by approximately -30%, induced by a negative PE of -50 mg C kg-1 401
soil with 1 D/W cycle and -100 mg C kg-1 soil with 4 D/W cycles, relative to soil under constant 402
soil moisture. Increasing the temperature and the number of D/W cycles caused a decrease in 403
substrate use efficiency of particulate lignocellulose. In conclusion, D/W cycles at warm 404
temperatures accelerated OM turnover due to preferential use from fPOM, creating 405
macroaggregates at the expense of microaggregates. A novel pathway of OM release and PE due 406
to the D/W cycles is discussed. 407
408
16
Keywords Soil priming effect, Particulate soil organic matter, Drying and rewetting cycles, 409
Aggregate stability, Carbon turnover. 410
411
412
Figure 1 Schematic illustration of the impact of drying/rewetting (D/W) events on the soil C 413
dynamics and CO2 efflux after fresh C addition. D/W cycles breakdown soil macroaggregates 414
and release labile particulate organic matter (fPOM) that was formerly protected. Increasing 415
number of D/W cycles raises microbial respiration from decomposition of new organic matter 416
of the POM fraction rather than using older, more stabilized OM, thus generating a negative 417
PE. 418
419
420
421
17
Introduction 422
423
Drying/rewetting (D/W) cycles lead to gains or losses in soil carbon (C) from soil organic matter 424
(SOM), effects that are enhanced under extreme climatic events (Kim et al. 2012). However, soil 425
C turnover is dependent upon other environmental conditions, e.g., temperature (Davidson and 426
Janssens 2006). Small changes in mean annual temperature can have significant effects on soil CO2 427
release (Billings and Ballantyne 2013). Soil organic C turnover is further modified by topography, 428
vegetation, and soil type (Balser and Firestone 2005; Vargas et al. 2010). Other factors, such as 429
physical protection of organic matter (OM) (von Lützow et al. 2007) or the frequency of D/W 430
cycling during dry seasons, also play critical roles in soil C dynamics (Hibbard et al. 2005). 431
Cycles of D/W are assumed to affect the overall functions of soils in terrestrial ecosystems 432
and to affect soil emission of greenhouse gases such as CO2, methane, and nitrous oxides (Corti et 433
al. 2002; Lal 2004; Vicca et al. 2014). Increasingly frequent D/W cycles could therefore cause a 434
breakdown of aggregates (slacking), exposing the physically protected OM to microbial 435
decomposition (Adu and Oades 1978; Appel 1998; Oztas and Fayertorbay 2003). Greater 436
intensities of drought could intensify negative impacts on CO2 flow and microbial activity (Sinha 437
and Cherkauer 2010; Meisner et al. 2015). After rewetting, an increase in gas fluxes occurs via the 438
Birch effect (Birch 1958). The Birch effect is driven by the labile particulate organic matter (POM), 439
determined by density fractionation as the light fraction (fPOM <1.6 g cm-3), which consists mostly 440
of pieces of plant residue and fungal hyphae. These materials can be occluded POM (oPOM 1.6–441
2.0 g cm-3), protected by the aggregates (Christensen 1992; von Lützow et al. 2007). The CO2 442
efflux from the soil can decline with successive D/W events as a result of an increasingly limited 443
pool of labile substrates (Schimel and Mikan 2005; Fernández et al. 2006; Goldberg et al. 2008). 444
18
The addition of fresh organic matter to soils results in a C cycle phenomenon known as the 445
priming effect (PE) (Bingemann et al. 1953). The PE is a strong, short-term change in the turnover 446
of SOM caused by an input of fresh OM (Jenkinson et al. 1985; Kuzyakov et al. 2000). It is 447
calculated as the difference between unlabelled CO2 efflux and labelled CO2 from 13C- (or 14C) 448
added to the soil (Oades et al. 1988; Jarvis et al. 2007). Priming can be positive (acceleration) or 449
negative (retardation) depending on the quantity and quality of fresh input (Kuzyakov 2010; 450
Garcia-Pausas and Paterson 2011). Although the effect is considered a short-term phenomenon, 451
Fontaine et al. (2011) demonstrated that priming could have long-lasting effects. Hence, under 452
frequent D/W cycles, the PE can have a significant impact on the decomposition of OM fractions, 453
triggering CO2 efflux from native SOM in the ecosystem (Magid and Kjægaard 2001; Gregorich 454
et al. 2006). 455
In terms of the protection of OM in the aggregates, there is a hierarchical order from the 456
largest particles to the smallest particles (Tisdall and Oades 1982; Oades 1984; Six et al. 2000). 457
This protection is disrupted by D/W cycles (Denef et al. 2001a; 2001b), which increase the 458
accessibility of microorganisms to the soil C. Because the fPOM contains the highest amount of 459
labile C, providing a rich source of energy for microorganisms, disruption of the aggregates by 460
D/W cycles can result in high CO2 emissions (Mikha et al. 2005; Borken and Matzer 2009; Shi et 461
al. 2014). 462
A new perspective on C release and PE due to the D/W cycle is introduced in this study. 463
Drying and rewetting cycles are hypothesized to lead to the preferential use of new, unprotected, 464
and labile organic matter over native C, resulting in negative PE values. Quantifying this effect 465
under the application of 13C-labelled fPOM to soils will facilitate a) differentiating the degree of 466
physicochemical protection of the SOM in various aggregate size classes and b) estimating the 467
19
substrate use efficiency, i.e., the relative proportion of added fPOM-C that is incorporated into 468
microbial biomass. 469
Temperate forests in Chile have experienced increasing temperatures and more frequent 470
extreme climatic events, such as severe droughts (Garreaud et al. 2017; Urrutia-Jalabert et al. 471
2018). In light of the effects of these events on soil moisture content, it is important to understand 472
the impact of D/W on SOM turnover in these ecosystems. Three hypotheses were tested: i) priming 473
of native C is induced by the amendment of fresh C-input, but D/W cycles release OM, which 474
primarily consists of the fPOM from disrupted aggregates (Fig. 1). Therefore, comparing the 475
difference in the PE between 0 cycle and D/W cycles will allow us to quantify the effect of D/W 476
on the actual PE; ii) Native SOM decomposition will be retarded (negative PE) due to the 477
preferential use of new OM by microorganisms (Fig. 1); and, iii) a cumulatively more negative PE 478
is expected with an increased number of D/W cycles. The aim of this study was to evaluate the 479
effects of two frequencies of D/W events on the PE, soil aggregate size class distribution, and their 480
OM fractions, dependent upon temperature in a temperate forest soil. 481
482
Materials and Methods 483
484
Study site and sampling 485
486
Soil samples were collected from an Inceptisol (Soil Survey Staff 2014) developed under an ancient 487
temperate forest with a dominant tree canopy of Araucaria araucana (Molina) K. Koch in 488
Nahuelbuta National Park (37°47′ S, 72°59′ W), Chile. Important soil properties are provided in 489
Table 1, and a more detailed description of the site can be found in Bernhard et al. (2018) and Oeser 490
et al. (2018). Undisturbed cores (PVC 5 cm diameter x 5 cm length) were taken from the uppermost 491
20
soil horizons after litter removal. Cores were stored at 4 °C and immediately transported to the 492
laboratory of Agricultural Soil Science of Georg-August University of Göttingen, Germany. 493
Table 1 Properties and standard deviation (±) of studied soil (0-8 cm depth). 494
Variable Units Value
pH water 4.3±0.3 Acid soil (1:2.5 water) pH CaCl2 3.3±0.2 Acid soil (1:2.5) Soil C g kg-1 soil 106±9.9 Total soil carbon at 0-8 cm depth
Soil N g kg-1 soil 5.0±0.5 Total soil nitrogen 0-8 cm depth
Soil C:N 21 0-8 cm depth. Litter C:N 60 Araucaria araucana litter 0-2 cm Alp g kg-1 soil 6.4±2.2 Pyrophosphate extractable Al Fep g kg-1 soil 3.5±1.9 Pyrophosphate extractable Fe Alo g kg-1 soil 8.7+/-2.8 Oxalate extractable Al Feo g kg-1 soil 6.7±1.4 Oxalate extractable Fe Sio g kg-1 soil 0.3±0.2 Oxalate extractable Si Ald g kg-1 soil 12.2±1.6 Dithionite extractable Al Fed g kg-1 soil 4.7±0.3 Dithionite extractable Fe Alp/Alo 0.8 > 0.5 organo-mineral nature Alo+0.5Feo % 1.3 > 2 andic properties AlK cmol+ kg-1 6.8±2.5 Exchangeable Al CECe cmol+ kg-1 9.0±1.6 Effective cation exchange capacity
495
Microcosm experiment 496
497
CO2 effluxes were determined during the incubation period of 27 days. This timespan was selected 498
because D/W-induced differences in mineralization of fPOM were expected directly after the D/W 499
cycles (Schimel and Mikan 2005; Goldberg et al. 2008). The PE and substrate use efficiency (SUE) 500
(for details see below) were assessed to compare the microbial incorporation of the 13C-labelled 501
amendment into the new organic matter. Aggregate size distribution and density fractions from 502
21
each aggregate class were determined to categorize the SOM pools via different degrees of C 503
protection. 504
505
Figure 2 Microcosms chambers (acrylic materials) setup for the drying and rewetting 506
cycles and CO2 collection. Note: The top of the main chamber has a small additional chamber 507
to which several irrigation needles were connected to apply the irrigation water uniformly. 508
509
The microcosm experiment consisted of 28 undisturbed core samples (〜78.5 g dry soil, bulk 510
density 0.8 ± 0.1 Mg m-3) pre-incubated for 4 days at field capacity (0.34 m3 m-3, -33 kPa). 511
Following incubation, the cores were placed on a ceramic pressure plate within a closed acrylic 512
chamber, modified from Poll et al. (2010), and equipped with a septum for gas sampling (Fig. 2). 513
Briefly, approximately 3 mg of 13C uniformly labelled lignocellulose milled residue (maize 514
derived, isotopic purity 97 atm % 13C (IsoLife –Stable Isotope Labelled Plant Products for the Life 515
Sciences, Wageningen, Holland) were suspended in 10 ml of distilled water and spread uniformly 516
on top of each core using several injections with a syringe. Drying and rewetting cycles consisted 517
of 3 days of drying followed by 3 days of wetting. Dry conditions were achieved using a vacuum 518
pump (Leroy-SomerTM) from the bottom of the ceramic plate, reaching -80 kPa for 3 h. Rewetting 519
22
was conducted by watering the core soil on the top and leaving the soil to equilibrate for 30 min 520
until the moisture content reach field capacities. This was achieved using 12 needles connected to 521
another pump (model ISM404B, ISMATECTM). Microcosms received either one or four cycles. 522
Control soils with labelled lignocellulose additions were subjected to zero D/W cycles and 523
observed alongside the other treatments. In addition to determining the natural isotopic abundance 524
of 13C, moist soil cores without labelled lignocellulose additions were also incubated. All 525
treatments were replicated four times. 526
527
CO2 sampling 528
529
CO2 gas samples were collected during 27 days of incubation from the first day of each drying or 530
rewetting (12 h apart) period and thereafter, with one sample collected for each day until the next 531
drying. All samples were collected via a 10 ml syringe through the septum on top of the microcosm 532
container (Fig. 2). The gas samples were injected into a vacutainer (Exetainer, Labco Limited, 12 533
ml) and stored at 5 °C until measurement. After sampling, each acrylic flask was ventilated with 534
CO2-free air. At the end of the 27 day incubation period, the soil was carefully extracted from each 535
core for further analyses. 536
537
Aggregate size classes 538
539
Aggregate size distribution was determined by dry sieving. Soil was air-dried at 40 °C and sieved 540
through 250 μm and 53 μm meshes on the Vibratory Sieve Shaker AS 200 (Retsch, Germany) for 541
5 min, at an amplitude of 1.5 mm. Three aggregate size classes were obtained: macroaggregates 542
(>250 μm), microaggregates (250–53 μm), and silt+clay size particles (<53 μm). The D/W cycles 543
23
impact soil aggregate turnover, and differences in aggregate size composition between soils with 1 544
and 4 cycles and soils with constant moisture (0 cycle) were regarded as the proportional effects of 545
the D/W cycles. 546
547
Organic matter density fraction 548
549
Organic matter fractions were obtained by density fractionation from each aggregate size class 550
using sodium polytungstates (SPT) (Gunina and Kuzyakov 2014). Three OM density fractions 551
were obtained, dried at 40 °C, and weighed: light fraction (fPOM, < 1.6 g cm-3), occluded fraction 552
(oPOM, 1.6–2.0 g cm-3) and heavy fraction (Hf > 2.0 g cm-3). The effect of D/W on the gain 553
(negative values) or loss (positive values) of aggregate mass and its associated C was obtained 554
using the difference between the 0 cycle, which received labelled residue but no D/W cycling, and 555
the 1 cycle or 4 cycle treatments. For the aggregate calculations, the same subtraction for the 556
proportional change in the OM density fractions was utilized. 557
558
Priming effect 559
560
The priming effect (PE) was calculated as defined by Guenet et al. (2010): 561
562
𝑃𝐸 = $!!"#$"$%!&'()!*!!"#$"$"!&+"!
% × 𝑄#$%&'( −𝑄#)*' (1), 563
564
where Alignin, Asample, and Asoil represent the isotopic abundance of 13C-lignocellulose residue added 565
to the soil, the isotopic abundance of the CO2 from the amended soil core sample with labelled 566
24
lignocellulose, and the isotopic abundance of the CO2 from non-amended (natural) soil core 567
sample, respectively. Qsample and Qsoil represent the quantity of released CO2 in the microcosms 568
headspace of freshly C amended soil and the CO2 in the headspace of non-amended soil, 569
respectively. Equation 1 was used to calculate the priming of SOM induced by the amendment of 570
lignocellulose. The D/W cycles were assumed to release fPOM, which primarily consists of 571
lignocellulose. Therefore, the difference in PE between soil with D/W cycles and soil with no D/W 572
cycles allowed us to quantify the effect of D/W cycles on priming (PEc). 573
574
Soil analyses 575
576
Soil C and nitrogen (N) contents were determined by dry combustion using a CN Elemental 577
analyzer (CHN NA 1500, Carlo Erba). Microbial biomass C (MB-C) was determined by the 578
difference in extractable C in 0.5 M K2SO4 of fumigated (chloroform free of ethanol) and 579
unfumigated soils and multiplied by the factor 2.64, used by Vance et al. (1987a; 1987b). 580
581
The carbon isotope ratios (13C/12C) of all fractions, CO2, MB-C, and bulk soil samples were 582
measured at the Centre for Stable Isotope Research and Analysis (KOSI) of Georg-August-583
University of Göttingen, Germany. The CO2 concentration and the carbon-isotope ratio were 584
measured in a gas chromatograph combustion isotope ratio mass spectrometer (GC-C-IRMS). Soil 585
C contents were measured using an elemental analyzer (Vario EL II, Germany), and the isotopic 586
ratio was measured using an elemental analyzer in dual-element analysis mode (Carlo Erba 1108, 587
Milano, Italy). The C isotope ratio was expressed relative to the international Pee Dee Belemnite 588
(PDB) limestone standard as δ13C. 589
25
Substrate use efficiency 590
591
The SUE was calculated at the end of the incubation as the ratio between labelled microbial 592
biomass (13CB), 13CO2 respired, and 13CB (Spohn and Chodak 2015): 593
594
𝑆𝑈𝐸 = +,-.
+,- ,/- +,-. (2) 595
596
were SUE estimates the relative proportion of the labelled MB-C to respiration. 597
598
Statistical analysis 599
600
Two-way ANOVA was performed to analyze the effects of temperature and D/W cycles on CO2 601
efflux, PE, aggregate size, OM-C fraction, and microbial biomass-C and its 13C-lignocellulose 602
distribution. The normality of the variances was tested by the Shapiro-Wilk test, and the 603
homogeneity of variance was tested by Levene's test. The data abnormally distribution was log 604
transformed until comparison data presented similar variance. Least significant difference (LSD) 605
and post hoc Tukey tests (p < 0.05) were performed to compare mean values between variables. 606
All analyses were conducted using SPSS statistical software v23.0.0.0 (SPSS Inc., Chicago, IL, 607
USA). Figures were developed with DataGraph 4.3 Visual Data Tools, 2006-2018, Inc. 608
609
610
611
612
26
Results 613
614
Soil weight and C recovery (%) following dry sieving varied between 92% and 99%, respectively. 615
The recovery of soil labelled 13C fluctuated between 6% and 52%, and varied between 5% and 39% 616
in the 13C MB-C. Leachates were minimal and fluctuated between 0% and 7% (Table 2). The total 617
recovered lignocellulose-derived labelled 13C ranged from 73% to 99% (Table 2). 618
Table 2 Total recovery (%) of soil weight, soil C and labelled C after dry sieving. 619 Weight Soil C NB-13C-1 MB-13C2 13CO2 13C-leached Total
5 ºC
0- cycle 97 95 21 39 13 0 73 1-cycle 99 92 32 20 33 3 88 4-cycle 100 106 47 20 17 5 89 25 ºC
0-cycle 93 92 48 5 43 0 96 1-cycle 99 117 52 14 33 0.3 99 4-cycle 92 72 6.4 26 60 7 99
1Non-biomass 620
2Microbial biomass 621
622
Aggregate size classes 623
624
The D/W-induced change in the distribution of aggregate size classes and their C contents was 625
obtained by subtracting D/W 0 cycle results from the aggregate size class abundance from that of 626
the 1 or 4 D/W cycle treatment (Fig 3). Macroaggregates (>250 μm) were the most abundant 627
aggregate size class in the investigated soils (609–785 g kg-1), followed by microaggregates (250–628
53 μm) (201–308 g kg-1) and silt+clay particles (<53 μm) (12–23 g kg-1) (Table 1S, Supplementary 629
Materials). Drying and rewetting had minimal influence on the mass of the aggregate size classes 630
and their C content at 5 °C (Fig. 3a). At 25 °C, however, macroaggregate weight (Fig. 3b) and 631
27
labelled C (Fig. 3f) increased (positive value) after 1 D/W cycle, and no significant differences 632
were detected for 4 D/W cycles (Tables S4, Supplementary Materials). The same was true for 633
labelled C at 5 °C (Fig 3e). 634
635
Figure 3 Proportional change 636
effect of aggregate size classes 637
(macroaggregates >250 µm; 638
microaggregates 250-53 µm and 639
silt+clay size <53 µm) shown by 640
subtracting the treatment with 641
constant soil moisture to the 642
treatments with 1 or 4 D/W 643
cycles. Soils amended with 644
lignocellulose are displayed 645
after 27 days of incubation at 5 646
ºC (left) and 25 ºC (right), 647
whereas relative weight (a and 648
b), total C content (c and d) and 649
lignocellulose-derived 13C incorporation (e and f) of the aggregate size classes is shown. 650
Bars indicate standard errors of the means. 651
652
653
654
655
1-cycle4-cycles
a
Aggr
egate
(%)
−20
0
205 ºC
28
Density fractionation 656
657
Drying and rewetting cycles did influence the quantity of organic C, including labelled C (Fig. 4, 658
Table S2, S5, Supplementary Materials). The interaction between temperature and D/W cycles 659
influenced the distribution of C and lignocellulose-derived 13C among the various OM fractions 660
(Table S3, S5, supplementary Materials). The quantity of D/W cycles did not have significant 661
effects at 5 °C, but the total C and lignocellulose-derived 13C content always increased with 1 cycle 662
and decreased with 4 cycles at the expense of heavy fraction, which lost the respective mass or C 663
(Fig. 4). 664
Figure 4. Proportional change effect 665
of organic matter particles (POM) 666
from the entire soil, OM fraction from 667
the different aggregates was reunited 668
as: light fraction < 1.6 g cm -3 (fPOM), 669
occluded fraction 1.6-2.0 g cm-3 670
(oPOM), heavy fraction > 2.0 g cm-3 671
(Hf) shown by subtracting the 672
treatment with 1 or 4 D/W cycles and 673
with constant soil moisture to the 674
treatments 0 cycles. Soils amended 675
with lignocellulose after 27 days of 676
incubation at 5 ºC and 25 ºC are 677
presented regarding the relative 678
29
weight of the OM fraction (a and b), their total C content (c and d) and their lignocellulose-derived 679
13C incorporation (e and f). Bars indicate standard errors of the means. 680
681
CO2 effluxes 682
683
Soil respiration was responsive to temperature, as demonstrated by the accumulated total CO2 and 684
labelled 13CO2 efflux in the undisturbed cores (Table S6, Supplementary Materials). On average, 685
the total amount of CO2 released at 25 °C was approximately three times that released at 5 °C (Fig 686
5). The mineralization of lignocellulose-derived 13C was roughly 2.5 times higher at 25 °C than 687
that at 5 °C. 688
Figure 5 Total CO2 evolved during 689
27 days of incubation at 5 ºC (a) 690
and 25 ºC (b) from soil with 691
lignocellulose addition and D/W 692
(0-cycles, 1-cycle and 4-cycles). 693
Dry period (∆) started on day 3 and 694
continued for another 3 days of 695
incubation. The wet period (∇) 696
started on day 6 until next drying. 697
13CO2 efflux through 27 days of 698
incubation at 5 ºC (c) and 25 ºC (d). 699
Small bas on the data point indicates standard errors of the mean. Large bars indicate the least 700
significant differences (LSD) (p < 0.05). 701
30
D/W cycle effects were isolated at each temperature by one-way ANOVA. After day 18, the total 702
CO2 efflux was significantly higher for soils exposed to 1 D/W cycle than those exposed to 4 cycles 703
or provided with constant moisture content (0 cycle) at 5 °C (p < 0.05) (Fig. 5a). Lignocellulose 704
mineralization displayed the same pattern as the total CO2; it was higher in soils exposed to only a 705
single D/W cycle, compared with those experiencing 0 or 4 cycles (Fig 5c). Soil Incubated at 25 706
°C with no D/W cycles had a higher total CO2 efflux than those of soils with 1 or 4 D/W cycles 707
after 18 days of incubation (p < 0.05) (Fig. 5b). In the warmer soil, the release of lignocellulose 708
13C was the highest when exposed to 4 D/W cycles (cf. Fig. 5b and 5d). 709
710
Figure 6 Priming effect (PE) through 711
27 days of incubation at 5 ºC (a) and 712
25 ºC (b) for soil with lignocellulose 713
addition. Dry period (∆) started on day 714
3 and continued for another 3 days of 715
incubation. The wet period (∇) started 716
on day 6 until next drying. Relative 717
priming effect as affected by drying 718
and rewetting (PEc), calculated as the 719
difference between 1 or 4 cycles and 0 720
cycles, is shown for 27 days of 721
incubation at 5 ºC (c) and 25 ºC (d) for soil with lignocellulose addition. Small bas on the data 722
point indicates standard errors of the mean. Large bars indicate the least significant differences 723
(LSD) (p < 0.05). 724
31
Priming effect 725
726
The PE response varied with the temperature, and differences between D/W treatments began to 727
become evident after 18 days of incubation (Fig.6). Only the 0 D/W cycle soil at 5 °C showed a 728
positive PE, although it was not significantly different from zero PE; soils with D/W cycles showed 729
a negative PE, and the soil with 4 D/W cycles was the only treatment significantly different from 730
zero at the end of the incubation time (Fig. 6a). At 25 °C; however, the PE was always negative 731
and soils exposed to D/W, regardless of the number of cycles, showed the most negative values (p 732
< 0.05) (Fig. 6b). At 5 °C PEc, the differences between soil with 1 or 4 D/W cycles and 0 cycle 733
were significant between 0 and 18 days and at the end of the incubation (Fig. 6c). However, at 25 734
°C the differences were expressed from day 9 and were not perceptible at the end of the incubation 735
(Fig. 6d). 736
737
Microbial biomass and substrate use efficiency 738
739
Figure 7 Substrate use efficiency (SUE) of 740
13C-lignocellulose at 5 ºC (a) and 25 ºC (b) 741
estimated after 27 days of incubation of the 742
D/W treatments 0-cycles, 1-cycle and 4-743
cycles. Small bas indicates standard errors of 744
the mean. Large bars indicate the least 745
significant differences (LSD) (p < 0.05). 746
747
32
Temperature and D/W cycles had significant impacts on microbial biomass 13C incorporation (c.f 748
Table 2 and 3) and SUE (Table 3, Fig. 7 and Table S7, Supplementary Materials). High SUE 749
occurred preferentially under lower temperatures and was on average two times higher (p <0.05) 750
at 5 °C than at 25 °C (Fig. 7). Drying and rewetting had a decreased effect on SUE values at 5 °C 751
(Fig. 7a), but at 25 °C, D/W cycles did not induce any significant effects on SUE (Fig. 7b). 752
753
Table 3 Total microbial biomass C (MB-C), MB-13C and standard error of the mean (±) of 754
four replicates. Different low case letters in each column and within each temperature 755
indicate significant differences (p < 0.05). Different capital letters in each column and 756
between temperatures indicate significant differences (p < 0.05). 757
Drying and rewetting Microbial biomass C
Total MB-C MB-13C (mg C kg-1)
5 °C 0-cycle 456±61aA 15±4.0 aA 1-cycle 372±28 aB 7.5±1.0 bB 4-cycles 346±51 aB 7.6±3.0 bB
25 °C 0-cycle 317±48 aC 2.0±1.5 bD 1-cycle 313±25 aC 5.4±1.1 aC 4-cycles 345±57 aBC 9.8±4.0 aB
758
759
760
761
762
763
33
Discussion 764
765
Aggregates and particulate organic matter 766
767
Physical protection of SOM by aggregates is an important mechanism for C stabilization; 768
differentiating the degree of physicochemical protection afforded to the SOM by various aggregate 769
size classes remains challenging. Drying and rewetting cycles were investigated in terms of their 770
disruptive effects on the degradation and formation of macroaggregates (>250 μm) and 771
microaggregates at (250–-53 μm) (i.e., the macroaggregate turnover) and the associated C 772
dynamics in the respective aggregate size classes found in a temperate forest. Soil with D/W cycles 773
experienced accelerated macroaggregate turnover at the expense of the microaggregates size class, 774
particularly at warmer temperatures of 25 °C (Fig 3b). Generally speaking, we found strongly 775
contrasting effects between the two temperature treatments, indicating a systematic process 776
underlying influence of temperature. Although we did not determine the microbial community 777
composition, fungal growth could be significantly reduced at low temperatures and fungal hyphae 778
development could be stunted at higher temperatures. Fungi can function as binding agents in soil 779
(Denef et al. 2001a), and at high temperatures, fungi could represent a significant portion of the 780
microbial biomass and could have key function in building and stabilizing macroaggregates (Denef 781
et al. 2001a). After 27 days of incubation at 25 °C, the proportion of microaggregates’ weight (Fig. 782
3b), their C content (Fig. 3d), and lignocellulose-derived 13C (Fig 3f) decreased in soils exposed 783
after 4 D/W cycles, but the effect was not observed after 1 D/W cycle (Fig. 3b-f). Increasing the 784
number of D/W events could therefore have a negative impact on microaggregate formation, while 785
novel protected OM within macroaggregates could contribute to its formation. Density 786
fractionation indicated a depletion of the fPOM and an increase in Hf, supporting the acceleration 787
34
of macroaggregate turnover (Fig. 4b, d) and increasing the 13C fraction in the oPOM (Fig. 4f). 788
Microaggregates were depleted by accelerated turnover and the formation of new macroaggregates, 789
which only occurred in the short term under enhanced D/W cycles (Denef et al 2001a; Dorodnikov 790
et at. 2011; Gunina and Kuzyakov 2014). 791
792
CO2 efflux 793
794
Drying and rewetting cycles affected the cumulative C mineralization at 25 °C. The total CO2 795
emitted throughout the 27 days of incubation was strongly reduced compared to the CO2 produced 796
by soil at optimum moisture content (0 cycle). Thus, rewetting does not compensate for the lower 797
mineralization during drought periods but rather has a medium-term impact (Fig. 5). Cumulative 798
mineralization is linked to the intensity and duration of drying and the accessible pool of organic 799
C during drying and rewetting (Borken and Matzner 2009). Therefore, under field conditions, 800
increasing droughts could result in reduced C mineralization, whereas increasing spring/summer 801
precipitation could accelerate C losses from physically protected organic matter. In our laboratory 802
study, drying and rewetting cycles caused higher microbial respiration of new organic matter added 803
to the soil (Fig. 5). This effect for 13CO2 became evident after 15 days of incubation at both 804
temperatures (Fig 5 c and d). Araucaria araucana litter fall displayed a C:N ratio of 60 (Table 1) 805
with a high lignin:N ratio (70–90), which is generally associated with a low mineralization rate 806
(Diehl et al. 2003; Bertiller et al. 2006). The lignocellulose rich OM decomposed at a rate between 807
50 and 150 mg C kg soil-1 d-1, comparable to other rates determined through similar incubations of 808
Chilean forest soils (Matus et al. 2008; Muñoz et al. 2016) or Mediterranean forest soils (Almagro 809
et al. 2009; Guntiñas et al. 2013). Despite the recalcitrance of the fresh substrate, there was 810
significant C mineralization from this material, supported by the negative PE value (Fig. 6d). 811
35
Priming effect 812
813
At 5 °C, there was a small but significant PE induced by the lignocellulose amendment, while at 814
25 °C a stronger negative PE was produced. The PE was negatively correlated with respired 13C (r 815
= - 0.59, p <0.04, n= 12). This result indicates that when less organic C is consumed from native 816
SOM by microorganisms (negative PE), fresh 13C is mineralized. This correlation clearly 817
demonstrates the preferential C use of the substrate, which is, in this study, a representative 818
compound of the soil’s fPOM fraction. These results were also supported by the PEc, the difference 819
in PE between 1 or 4 cycles and 0 cycle (Fig. 6). In other studies, where complex OM was added 820
in the form of leaf and stem residues (13C-labelled wheat residues), the results also showed 821
intensive mineralization of the added OM, yielding a negative PE for extended periods (Shahbaz 822
et al. 2017); with the addition of other materials, a temporary negative PE (up to 40 days) was 823
observed (Wang et al. 2015), likely due to preferential utilization of the added substrate and thus a 824
pool substitution (Shahbaz et al. 2017). This mechanism was effectively revealed by the SUE, 825
particularly at 5 °C (Fig. 7), because the lignocellulose was incorporated into the microbial biomass 826
by a well-adapted microbial community (Borken and Matzer 2009). Soil microbial communities 827
are resilient and able to quickly recover after wetting in soils with high SOC stock (Canarini et al. 828
2017). At 25 °C, however, lignocellulose-derived C could be invested for highly energy demanding 829
processes, e.g., for enzyme synthesis, and less C was converted into structural cell components 830
(Ågren and Bosatta 1987; Blagodatsky et al. 2000; Davidson and Janssens 2006; Manzoni et al. 831
2012). This finding is in accordance with other studies, which obtained similar results i.e. a 832
decreasing C use efficiency with increasing temperature between 2 and 28 °C (Manzoni et al. 2012; 833
Qiao et al. 2019). This phenomenon can likely be associated with a change in metabolism rather 834
than a change in the microbial community structure (Manzoni et al. 2012; Bölscher et al. 2017; Di 835
36
Lonardo et al. 2017). When the number of D/W cycles was increased on undisturbed soil, fPOM 836
was negatively affected by warming and the acceleration of aggregate turnover. Warming and 837
aggregate turnover could have significant implications for temperate forests facing global change. 838
Faster macroaggregate turnover and depletion of fPOM may prevent large stabilized SOM from 839
decomposing, leading to a lack of C stabilization after repeated D/W cycles. 840
841
Conclusions 842
843
One drying-rewetting (D/W) cycle disrupted approximately 15% of the aggregates after 27 days. 844
The organic matter light fraction (fPOM, <1.6 g cm-3) released from aggregates disrupted by D/W 845
contained the most physically exposed C (microbially available) as compared to the other C pools. 846
This fPOM, which we traced by added 13C-labelled lignocellulose, was decomposed preferentially, 847
covering microbial energy demand but not converted to microbial biomass and therefore not 848
contributing to long-term stabilization in the form of necromass residues. Increasing the number of 849
D/W cycles caused a negative priming effect (PE), i.e., preferential utilization of the added 13C-850
labelled lignocellulose released by D/W cycles rather over other OM fractions. A new pathway is 851
proposed for C release by aggregate disruption, resulting in negative PE due to D/W cycling. This 852
scenario was reflected by low substrate use efficiency (SUE), i.e. microbes preferentially respiring 853
the accessible fPOM, particularly at a high temperature. Consequently, the D/W cycles at 25 °C 854
significantly increased microbial activity, which primarily regulated fPOM decomposition. 855
856
857
858
859
37
Acknowledgements 860
861
We are grateful to the Chilean National Park Service (CONAF) for providing access to the sample 862
locations. This study was partly funded by the National Commission of Research of Science and 863
Technology FONDECYT (grant N° 1170119). We are indebted to the Laboratory of Conservation 864
and Dynamics of Volcanic Soil, BIOREN-UFRO, and the Network of Extreme Environments 865
NEXER project from Universidad de La Frontera-Chile. Many thanks go to the team of the Stable 866
Isotope Center (KOSI) of Göttingen University. We acknowledge Leibniz University Hannover 867
and Georg-August University Gottingen, Germany, for hosting our research. We thank the 868
reviewers for providing helpful comments on the early version of this manuscript. The publication 869
was supported by the “RUDN University program 5-100”. 870
871
Funding information 872
873
This research was supported by the German Science Foundation (DFG) priority research program 874
SPP-1803 “Earthshape: Earth Surface Shaping by Biota” (Project Root Carbon KU 1184/36-1), the 875
scholarship program from Leibniz University Hannover IP@Leibniz for a research stay in Leibniz 876
and the national doctoral scholarship CONICYT N° 21160957, of the Chilean government. This 877
study was funded in part by the National Commission of Research of Science and Technology 878
FONDECYT (grant N° 1170119) and by the Network for Extreme Environmental Research 879
(NEXER), Universidad de La Frontera. 880
38
881
882
883
CHAPTER III 884
885
Francisco Nájera, Michaela Dippold, Jens Boy, Oscar 886
Seguel, Moritz Koester, Svenja Stock, Carolina Merino, 887
Yakov Kuzyakov, Francisco Matus (2021) 888 889
Freezing/thawing and drying/wetting cycles effect on 890
glucose (14C) and lignocellulose (13C) decomposition in 891
humid temperate forest soil (Summited to Applied 892
Soil Ecology) 893
894
895
896
897
39
Abstract 898
899
Freezing and thawing (F/T) and drying and wetting (D/W) can accelerate the particulate organic 900
matter (POM) decomposition because of macroaggregate (>250 µm) disruption and the release of 901
formerly protected POM fraction. We test these effects by adding 14C-glucose and 13C-902
lignocellulose to loamy soil from a humid temperate forest. We applied four F/T cycles (-18/20 ºC) 903
and D/W cycles (-5.0 bars/field capacity), but no cycle (No cycles) and a control soil without 904
addition was also regarded. CO2 efflux and priming effect (PE ), the acceleration or retardation of 905
soil organic carbon (SOC) mineralization were determined weekly during 28 days of incubation. 906
Density fractions (free, fPOM; occluded, oPOM; and heavy, Hf) from macroaggregates, 907
microaggregates (250-53-µm), and silt+clay aggregates size (<53-µm) was performed. Both F/T 908
and D/W decreased fPOM in the macroaggregate and the silt+clay, while in microaggregates, POM 909
fractions remained constant. Differences in oPOM were only recorded in bulk soil. F/T and D/W 910
decreased the Hf in the silt+clay, indicating that this aggregate size still released decomposable 911
SOC. After the first cycle, D/W lignocellulose derived CO2 was higher (50 mg kg-1), always higher 912
than F/T, and No cycles, having no differences amongst the last two. Glucose derived CO2 913
increased sharply until day three and thereafter, a slowdown in the accumulation. Both D/W and 914
F/T lignocellulose and glucose derived CO2 had negative PE, and the most depleted CO2 was 915
recorded for F/T cycles (125 mg kg-1) from lignocellulose followed by D/W and No cycles, while 916
D/W of glucose derive C generally did not show differences with the control soil. Although CUE 917
and MBC were not significant, the underlying mechanism PE was interpreted as preferential use 918
C substrate. By using the labeled SOC remaining, the net C balance could be calculated. Both 919
cycles treatments had a positive effect, but D/W caused less C gain (63 mg kg-1) than F/T cycles 920
(134 mg kg-1) and No cycles (80 mg kg-1). Here we propose a conceptual model (Fig. 1) where the 921
40
soil C stock is represented by a positive net carbon gain from lignocellulose and glucose derived C 922
remaining in temperate forest soil of Araucaria araucana to the negative priming effect after D/W 923
and F/T cycles. Our results supported the idea that F/T and D/W cannot be a comparable 924
phenomenon as some papers claims and that F/T had a less detrimental impact on native SOC than 925
D/W. 926
927
Keywords: Soil priming effect, Particulate organic matter, dual isotopic labeling, Organic matter 928
stability, Freezing/thawing cycles, Drying/wetting cycles. 929
930
Figure 1 Conceptual 931
representation of the soil 932
carbon (C) stock 933
accumulation (positive 934
net carbon balance) from 935
lignocellulose and 936
glucose derived C 937
remaining in temperate 938
forest soil of Araucaria 939
Araucana after 28 days 940
incubation. The negative priming effect is represented by the native CO2 effluxes from the control 941
soil without substrate addition and the native CO2 from lignocellulose and glucose drying/wetting, 942
freezing/thawing no cycles treated soil. 943
944
945
41
Introduction 946
947
The availability of organic C for soil microorganisms is highly heterogeneous in space and time 948
and is influenced by soil properties and climate conditions (Fernández et al., 2006; Meisner et al., 949
2015). F/T and D/W induce structural changes in chemical and physical soil properties that affect 950
the organic matter turnover and microbial community (Vicca et al., 2014). F/T and D/W cycles 951
disrupt soil aggregates and expose physically protected SOC to microbial consumption from 952
previously inaccessible ones. Particulate organic matter (POM), the recognizable plant and fungus 953
residues, is particularly influenced (Nájera et al., 2020; Kim et al., 2012). Density fractionation is 954
used to separated different POM fractions namely free (fPOM , < 1.6 g cm-3), occluded (oPOM, 955
1.6-2.0 g cm-3), and the heavy (Hf, > 2.0 g cm-3) (von Lützow et al., 2007; Poeplau et al., 2018). 956
Repeated F/T and D/W cycles occur several times over a year in temperate and cold climate 957
zones, and these events were identified as one of the primary mechanisms for efflux greenhouse 958
gas emissions (Koponen and Bååth, 2016; Manzoni et al., 2012). These events reduce the SOC 959
mineralization (Semenov et al., 2014) due to a reduction of macroaggregates (>250-µm) and 960
increasing microaggregates (< 250-µm) turnover (Denef et al., 2001a). The underlying mechanism 961
that determines these processes is poorly understood (Kim et al., 2012). 962
Birch effect (Birch, 1958) and priming effect (PE) (Bingemann et al., 1953) are related 963
mechanisms determining the SOC mineralization. The Birch effect is the burst of CO2 release due 964
to exposed former protected SOC caused by mechanical disruption of soil aggregates or brusque 965
changes on environmental conditions such as soil moisture, while the PE is the alteration of SOC 966
turnover due to a fresh C input (Kuzyakov, 2010; Garcia-Pausas and Paterson, 2011). Long-lasting 967
PE is influenced by substrate quality, C-input rates, and F/T and D/W cycles (Hibbard et al., 2005; 968
42
Shahbaz et al., 2017; Wang et al., 2015). Priming can be positive (acceleration) or negative 969
(deacceleration) depending on the factors as mentioned above (Wu et al., 2020; Kuzyakov, 2010; 970
Garcia-Pausas and Paterson, 2011), but also for the soil fertility level (Aye et al., 2018; Sullivan 971
and Hart, 2013), amount and soil types (Chenu et al., 2001; Liu et al., 2020). For example, easily 972
available C may suppress the native C mineralization (negative PE) than more complex substrates 973
(Di Lonardo et al., 2017). F/T or D/W may induce a constant depletion of the free POM-C fraction 974
in macroaggregates (Conant et al., 2008; Hartley et al., 2007; Tian et al., 2015) that results in a 975
negative PE (Najera et al., 2020). This effect can be achieved by adding glucose or more complex 976
substrate like lignocellulose for microbial metabolic activation (Mondini et al., 2006) after short-977
term incubation. 978
This study aimed to evaluate the effects of frequent F/T and D/W on the decomposition and 979
localization of C in different soil aggregates and POM fractions in humid temperate forest soil. The 980
CO2 efflux of unamended labeled C will be compared with amended soils using 14C-D-glucose and 981
decomposable 13C-lignocellulose. We hypothesize that induced negative PE by F/T or D/W cycles 982
is an ongoing process due to the preferential use of labile C consumption by rapid microbial growth. 983
Followed by an increase in the physically protected lignocellulose on soil aggregates and reducing 984
the fresh C and the fPOM availability due to frequent macroaggregate disruption. Therefore a 985
positive net soil C balance can be expected, represented in Fig 1, where D/W or F/T induces the 986
negative PE in a temperate forest soil of Araucaria araucana. 987
988
Materials and methods 989
990
The soil was collected from a temperate forest dominated by Araucaria tree (Araucaria araucana 991
(Molina) K. Koch) in Nahuelbuta National Park (37°47′ S, 72°59′ W) Araucanía region, Chile, and 992
43
is originated from granitic bedrock (Bernhard et al., 2018; Oeser et al., 2018). The soil is Inceptisol 993
(Soil Survey Staff, 2014), with the following characteristics: pH 4.3; Soil C 10.6 %; Soil N 0.5 %; 994
Sand 50.2 %; Silt: 23.6 %; Clay: 26.2 %; Bulk density 0.8 Mg m-3. A bulk sample from three 995
subsamples (5-10 cm) was collected and immediately transported to the laboratory in a refrigerated 996
box. The samples were cleaned, air dried, sieved (mesh market grade 10; 2000 µm), and stored for 997
further studies. The pF curves were measured (cm3 cm-3) between -330 hPa (field capacity) and -998
15,000 hPa (wilting point) by pressure plates. 999
1000
Incubation setup 1001
1002
Humid temperate forest soil was reconstituted on 100 cm3 metal rings filled with 75 g of air dry 1003
soil and slightly compacted to reach a 0.8 g cm-3 bulk density. Sixteen reconstituted soil samples 1004
(cores) were equilibrated (water bed) till field capacity and kept for two weeks at 5 ºC temperature 1005
as pre-incubation period. Soil cores were placed in 500 ml incubation vessels. Two sources of 1006
labeled organic matter were added at the beginning of the incubation with a syringe: i) 2 ml of 1007
dissolved 14C D-glucose, uniformly 14C labeled, with 50 kBq of activity per soil core, and ii) 8 mg 1008
of maize lignocellulose uniformly 13C labeled (isotopic purity 97 atm%, IsoLifeTM). Before use, 1009
the lignocellulose was grounded in a ball mill for 2 min at 300 rpm, and the powder material was 1010
suspended in 2 ml of deionized water. 1011
Soil cores were separated into four groups and added with labeled materials, and the 1012
following treatments were applied: i) four cycles of drying and wetting (F/T), ii) four cycles of 1013
freezing and thawing (F/T), iii) no cycles with substrate addition (No cycles), and iv) a control soil 1014
without cycles and substrate addition (Control). The soil was incubated at 20 ºC at room 1015
temperature. The freezing conditions were induced by placing the microcosms at -18 ºC for 12 1016
44
hours. After this time, thawing was at room temperature at the microcosms and was left there for 1017
six days till a cycle started. Freezing was induced 4 times at the beginning of days 3, 7, 9, 15, and 1018
21 of incubation. The drying conditions were conducted slowly on a ceramic plate by lowering the 1019
pressure to drop -5 bar during 12 hours (37 % of field capacity). The soil remained dry, in these 1020
conditions, for three days. After that, soils were weighted to determine the water loss. Wetting was 1021
achieved by adding demineralized water up to field capacity from the top core microcosm. Drying 1022
conditions were imposed on days 3, 9, 15, and 21, and wetting on days 6, 12, 18, and 24. The CO2 1023
was trapped in a vial containing 5.0 ml of 0.5 M NaOH and replaced at each sampling. Gas 1024
sampling was at 1, 3, 6, 12 hours on the firth’s days after both F/T or D/W cycles were applied and 1025
once a day for 5 days, till the next cycle started. The CO2 was also measured during the freezing 1026
period after 1, 3, and 6 h. Follow sampling, an aliquot of 0.6 ml from the NaOH solution was 1027
diluted in a ratio of 1:10 with deionized water to measure the CO2. The CO2 measurements were 1028
conducted on a non-dispersive infrared gas analyzer (NDIR) (Total carbon Analyzer TOC-L 1029
Shimadzu Corporation, Japan). A standard solution of Na2CO3, 400 mg kg-1, was used for 1030
calibration. The remaining NaOH trap was stored to determinate 13C and 14C on the CO2 flux. 1031
1032
Microbial biomass, soil aggregate, and density fractionation 1033
1034
After 28 days of incubation, the microbial biomass C was determined by the difference in 1035
extractable C in 0.05 M K2SO4 concentration of fumigated (chloroform free of ethanol) and non-1036
fumigated soils samples analyzed by dry combustion using a CN Elemental analyzer (CHN NA 1037
1500, Carlo Erba) and divided by 0.45 (Vance et al., 1987a, b). The total C content was expressed 1038
in mg kg-1 soil. 1039
45
The distribution of the soil aggregates size class was determined by dry sieving of air-dried 1040
soil with a mesh size of 250 and a 53 µm on a Vibratory Sieve Shaker AS 200 (Retsch, Germany) 1041
for 5 min (amplitude 1.5 mm). Thus, macroaggregates (>250 µm), microaggregates (250-53 µm), 1042
and the silt+clay aggregate size (<53 µm) fraction was separated. Particulate organic matter (POM) 1043
fractions were determined from each aggregate size class by densitometry using sodium 1044
polytungstate (SPT) (Gunina and Kuzyakov, 2014). Three fractions were obtained: light fraction 1045
(Lf, < 1.6 g cm-3), occluded fraction (Of, 1.6 - 2.0 g cm-3), and the heavy fraction (Hf, > 2.0 g cm-1046
3). The fractions were oven dried at 40 °C and weighed. The soil C in the aggregate in each density 1047
fraction was determined using a CN Elemental analyzer. 1048
1049
Decomposition of glucose and lignocellulose 1050
1051
To determine the labeled CO2 efflux originated from 14C D-glucose, 0.4 ml of NaOH-CO2 trapped 1052
solution was transferred to a new vial and mixed whit 1.6 ml of scintillation cocktail Rotiszint Eco 1053
Plus (Carl Roth, Germany). The 14C NaOH-CO2 trapped solution was mixed with the scintillation 1054
cocktail and measure using a 1450 LSC and Luminescence Counter MicroBeta TriLux (Perkin 1055
Elmer Inc., USA). The remaining glucose in the soil was determined in a super low-level liquid 1056
scintillation counter with α-β separation (Perkin Elmer Inc., USA). 1057
To determine, the C originated from the labeled 13C lignocellulose 4 ml of NaOH-CO2 1058
trapped solution was precipitated with 5.0 ml of 0.5 M SrCl2 aqueous solution to form strontium 1059
carbonate (SrCO3). The precipitated SrCO3 was isolated by centrifugation (2000 rpm) to remove 1060
the remaining NaOH, washed with millipore water till pH 7 was reached. Then, SrCO3 was oven 1061
dried at 60 ºC. About 1.0 g of dry SrCO3 was pelleted in tin caps to determine 13C using an 1062
elemental analyzer (NC 2500; CE Instruments, Milano, Italy) coupled with an isotopic ratio mass 1063
46
spectrometer (Delta Plus IRMS, Thermo Fisher Scientific, Bremen, Germany). The remaining 13C 1064
in soil was determined in each POM fractions. About 20 mg of pelleted POM materials were placed 1065
in a tin capsule and measured for 13CO2, as previously described. The 13C/12C isotope ratios were 1066
expressed by the international PDB (Peedee Belemnite; carbon) limestone 13C standard. 1067
1068
Net carbon distribution in soil aggregates and particulate organic matter 1069
1070
The net C distribution in macro-, micro, and silt+clay size aggregates and in the POM fractions 1071
was calculated for the effect of F/T and D/W cycles as the differences in the amount C from the 1072
soil with lignocellulose and glucose substrates and those without substrate additions and cycling 1073
imposed. 1074
1075
Glucose and lignocellulose carbon decomposition 1076
1077
The decomposition of added lignocellulose and glucose with cycles were calculated as: 1078
TCO. = LCO. + GCO. + SCO., (1) 1079
where: TCO2 is the total CO2, LCO2 the lignocellulose-derived CO2, GCO2 the glucose-derived 1080
CO2, and SCO2 the soil derived CO2, all expressed in mg kg-1. 1081
LCO. = (1 − α)(TCO. − GCO.), (2) 1082
SCO. = α(TCO. − GCO.), (3) 1083
where: α is the proportion of nonlabeled CO2 or the mineralization of native C (Guenet et al., 2010): 1084
α = /012313%/456708
/012313"/4910, (4) 1085
47
where: (Alignin) the isotopic abundance of lignocellulose residue, (Asample) is the isotopic abundance 1086
of SCO. and (Asoil) is the isotopic abundance of the SOC. 1087
The glucose-derived CO2 is calculated from the activity of 14C-D-glucose (disintegration 1088
per minute, DPM) (Blagodatskaya et al., 20011; Shahbaz et al., 2018): 1089
GCO. =A01234
A5348 TG, (5) 1090
where, A01234 is the activity of 14CO2, A534 is the activity of added glucose (TG, mg kg-1). 1091
The PE derived from both lignocellulose + glucose (PE) with the cycles is calculated as: 1092
PE = SCO. − CO.789:08; , (6) 1093
and the PE induced by glucose (𝑃𝐸'*<=)>(''?')#() as: 1094
PE;@A987B;;C;8DB = TCO. − LCO. − CO.789:08; , (7) 1095
and the PE induced by glucose (𝑃𝐸<'?>)#() (Blagodatskaya et al., 2007) as: 1096
PEA;C78DB = TCO. − GCO. − CO.789:08; , (8) 1097
where: CO2 control is the control soil without cycle and substrate addition). 1098
The PE of No cycles treatment (PENo cycles) is calculated from (6) and (7). So, the net 1099
effect of cycle on PE from lignocellulose (PE9B:;@A987B;;C;8DB) is calculated as: 1100
Net PElignocellulose = PE7E7;B;@A987B;;C;8DB − PEF87E;BD;@A987B;;C;8DB, (9) 1101
and glucose: 1102
Net PEglucose = PE7E7;BA;C78DB − PEF87E;BDA;C78DB, (10) 1103
Positive results from (8) and (9) are interpreted as native net C losses and negative values as 1104
preferential use of C substrate from fresh labeled lignocellulose or glucose. 1105
1106
1107
48
Soil CO2 efflux rates 1108
1109
The rate of CO2 per day for the total CO2 labeled CO2 and PE was calculated as: 1110
CO.ratio = G9(I:)"G9(I1)
(::":1), (11) 1111
where: xj and xi are the CO2 (mg kg-1) evolved between interval time tj and previous one ti (days). 1112
1113
Drying/wetting and freezing/thawing cycles influence organic carbon in soil aggregate and 1114
particulate organic matter 1115
1116
The difference of SOC, lignocellulose, and glucose derived C as affected by D/W or F/T cycles in 1117
various aggregates size or POM fractions by subtracting No cycles (with C substrates) in the same 1118
C pools were calculated. 1119
1120
Carbon use efficiency 1121
1122
The C use efficiency (CUE) was calculated at the end of 28 days of incubation, as the ratio between 1123
microbial biomass (MBC) divided by the sum of TCO2 and MBC (Spohn and Chodak, 2015): 1124
CUE = KLMNMO/-KLM
, (12) 1125
Net organic carbon balance 1126
1127
The net SOC balance (SOCB) was calculated as (Fontaine et al., 2004a): 1128
SOCL = (SOC5 + SOCG) − (SCO. − TCO.91:C01;) (13) 1129
49
where: SOCG and SOCL are the glucose and lignocellulose derived SOC remaining. 1130
1131
Statistical analysis 1132
1133
All data were tested for normal distribution by Shapiro-Wilk tests and Levene variance to 1134
determine variance homogeneity. Abnormally distributed data were square root transformed. A 1135
multivariable general linear model analysis was performed with repeated measurement two-way 1136
ANOVA to estimate differences in CO2 evolved from unamended and amended soils with and 1137
without labeled residues after four F/T and D/W treatments. A post hoc test (p < 0.05) of the least 1138
significant difference (LSD) was used to establish statistically mean differences amongst groups. 1139
Differences in MBC and CUE were analyzed by post hoc test of LSD to reveal mean differences 1140
if one-way ANOVA is significant (p <0.05). Differences between SOC, 13C-lignocellulose, and 1141
14C-glucose on POM density fraction and aggregates size classes were determined using similar 1142
statistical tools. Pearson’s and Tukey’s post hoc test (p < 0.05) correlations were performed. All 1143
analyses were performed using SPSS v23.0.0.0 statistical software (SPSS Inc., Chicago, IL, USA). 1144
1145
Results 1146
1147
Organic carbon distribution of particulate organic matter and soil aggregates 1148
1149
Aggregate and POM mass distribution were similar after 4 F/T, 4 D/W, or No cycles applied 1150
during 28 days of incubation (Fig. S1 Supplementary materials). However, macroaggregates were 1151
the highest in the soil with and without cycles, followed by microaggregates and silt+clay size 1152
50
aggregates. The Hf POM fraction’s mass portion was the highest, while oPOM and fPOM were 1153
similarly distributed (Fig S1, supplementary materials). 1154
Figure 2. Soil 1155
organic carbon, 1156
lignocellulose 1157
derived carbon 1158
and glucose 1159
derived carbon 1160
after drying and 1161
wetting (D/W), 1162
freezing and 1163
thawing (F/T), and 1164
no cycles (No 1165
cycles) at the end 1166
of 28 days 1167
incubation in (A) macroaggregates (2000-250-µm), (B) microaggregates (250-53-µm) and (C) Silt-1168
clay size aggregate (<53-µm) distributed in particulate organic matter density fractions (POM): 1169
light fraction (Lf <1.6 g cm-3); occluded fraction (Of 1.6-2.0 g cm-3) and a heavy fraction (Hf >2.0 1170
g cm-3). Whiskers bars are the standard error of the means. Different letters within the column 1171
indicate significant differences at p <0.05. 1172
1173
Unlike the mass distribution, the total amount of C obtained by combining the aggregate size 1174
classes was higher in macroaggregates in No cycles (Fig. S2, Supplementary materials). A similar 1175
a
a
a
aab b
b
a
b
Lign
ocel
lulo
se d
eriv
ed C
(mg
kg-1
)
D
0
8
16
24
30
a
aa
a
a
aa
a
a
Soi
l org
anic
C(g
kg-1
)
A
0
10
30
50
70Macroaggregates
a
a
a
aa
a
a
a
a
GHf > 2.0 g cm-3
OPOM 1.6-2.0 g cm-3
fPOM < 1.6 g cm-3
Glu
cose
der
ived
C(m
g kg
-1)
0
0.2
0.5
0.8
1.0
No cycles D/W F/T
51
amount of C was found for lignocellulose, and glucose derived C (Fig S2, supplementary 1176
materials). Full data presentation can be found in Supplementary material (Tables S1, S2, and S3). 1177
The distribution of soil C in various POM fractions within aggregate were highly variable, then 1178
few significant differences were recorded due to cycle effects (Fig. 2). The amount of POM 1179
fractions between aggregates, the SOC fPOM, were higher in macro- and micro- compared with 1180
the Silt+clay-aggregate. The fPOM glucose derived C was higher in Silt+clay size aggregates 1181
followed by micro- and macro-aggregates. The amount of C in the POM fraction derived from 1182
lignocellulose was equally distributed amongst soil aggregates size class (Fig. 2). 1183
1184
Organic carbon in aggregates and particulate organic matter as affected by drying/ wetting 1185
or freezing/ thawing 1186
1187
The difference of SOC, lignocellulose, and glucose derived C as affected by D/W or F/T cycles in 1188
various aggregates size or POM fractions by subtracting No cycles is shown (Fig. 3). 1189
Macroaggregates >250-µm were depleted in SOC, lignocellulose, and glucose derived C, while 1190
microaggregates <250-µm were C-enriched. Drying and wetting caused a more significant impact 1191
in lignocellulose derived C, although F/T did for glucose derived C and SOC in the bulk soil. 1192
Silt+clay size aggregates did not show consistent results. The effect of cycles on glucose derived 1193
C for POM fractions followed almost identical patter as aggregates counterparts, while 1194
lignocellulose derived C and SOC were partially consistent. 1195
1196
1197
1198
1199
52
Figure 3. Net CO2 effluxes 1200
obtained by the difference between 1201
freezing/thawing (F/T) or 1202
drying/wetting (D/W) and no cycles 1203
(No cycles) after 28 days of 1204
incubation. Whiskers bars in each 1205
column indicates the standard error 1206
of the mean (p <0.05). 1207
1208
1209
1210
1211
1212
1213
1214
1215
1216
CO2 effluxes 1217
1218
The cumulative CO2 for the total SOC showed that D/W, F/T, and No cycles were all below the 1219
control soil without cycles and substrate addition (Fig 4). Differences started on day 3 when the 1220
soil was wetting or thawing at the beginning of the first cycle (Fig. 4A). After that, the differences 1221
increased till the end of incubation (28 days), where the least CO2 efflux was obtained for F/T (283 1222
mg kg-1), followed by D/W (311 mg kg-1), No cycles (329 mg kg-1), and control soil (350 mg kg-1223
E
Glu
cose
der
ived
C(m
g kg
-1)
−10
−5
0
5
10
aggregatesMacro- Micro- Silt+clay
C
Lign
ocel
ullo
se d
eriv
ed C
(mg
kg-1
)
−35
−15
0
15
35
D/W cyclesF/T cycles
A
Soi
l org
anic
C(g
kg-1
)
−5
−2
0
2
5Aggretate size class
53
1). The cumulative lignocellulose derives C from D/W was always higher than F/T, while no 1224
significant differences were found with No cycles until day 6. After that, both curves start to 1225
deviate, and the soil with No cycle overlapped F/T until day 21. Subsequently, both curves, No 1226
cycle, and F/T parallel each other, but F/T was always lower (Fig 4B). Completely different is the 1227
case for glucose derived C. There was a sharp increase of cumulative CO2 until the bent point (4 1228
mg kg-1) for D/W followed by No cycle and F/T before starting the first drying or freezing from 1229
the beginning of incubation. Afterward, the curves paralleled with increased differences for F/T 1230
until the end of incubation (Fig. 4C). 1231
Figure 4. Total CO2 effluxes from (A) soil organic carbon (SOC), (B) lignocellulose, (C) glucose 1232
derived C, (D) priming effect (PE) from lignocellulose, and (D) PE from glucose after four cycles 1233
of drying/wetting (D/W) and freezing/ thawing (F/T). Drying or freezing is indicated by ▽ and 1234
wetting or thawing by D. Whiskers bars indicate standard error of the mean (SEM) (p<0.05). 1235
1236
Tota
l soi
l CO
2 ef
flux
(C m
g kg
-1)
ControlNo cyclesF/T cyclesD/W cycles
LSD (p<0.05)
A
0
100
250
400
Days0 3 9 15 21 28
Lign
ocel
lulo
se d
eriv
ed C
O2
(C m
g kg
-1)
LSD (p<0.05)
B
0
20
40
60
Days0 3 9 15 21 28
LSD (p<0.05)
D
PE
Lign
ocel
llulo
ce
(mg
kg-1
)
100
−50
−100
−150
Days0 3 9 15 21 28
PE
gluc
ose
(mg
kg-1
)
LSD (p<0.05)
E100
−50
−100
−150
Days0 3 9 15 21 28
LSD (p<0.05)
Glu
cose
der
ived
CO
2(C
mg
kg-1
)
C
0
2
5
7
Days0 3 9 15 21 28
54
The Priming effect for added lignocellulose was negative in the following order F/T > D/W = No 1237
cycles (Fig. 4D). Differences started after day 6 (end of the first cycle), then D/W and No cycles 1238
were similar with some differences, while F/T obtained the most intense negative PE (-112 mg kg-1239
1) after 28 days of incubation. Unlike lignocellulose derived C, the PE of glucose derived C 1240
followed a different pattern. Less intensity negative PE was recorded for F/T (-75 mg kg-1) followed 1241
by No cycle and D/W (Fig. 4D). 1242
The net PE, i.e., the difference of PE between lignocellulose or glucose derived C and the 1243
PE of No cycles as affected by D/W and F/T, showed positive PE for lignocellulose, but a strongly 1244
negative one for glucose derived C. (Fig. 5). 1245
1246
Figure 5. Net 1247
priming effect 1248
(PE) obtained by 1249
the difference 1250
between 1251
freezing/thawing 1252
(F/T) or 1253
drying/rewetting (D/W) and no cycles (No cycles) after 28 days of incubation. Whiskers bars 1254
indicate standard error of the mean (SEM) (p<0.05). 1255
1256
1257
1258
1259
1260
55
Microbial biomass and carbon use efficiency 1261
1262
Microbial biomass carbon and CUE were similar in the soil with F/T, D/W, or No cycles after 28 1263
days of incubation (Table 1). In general, the average of MBC was (620 mg kg-1) and for CUE 1264
(0.66) in the soil with F/T, D/W, or No cycles. 1265
1266 Table 1. Microbial biomass carbon (MBC) expressed in mg kg-1 and carbon use 1267
efficiency (CUE) in soils after freeze and thawing (F/T), drying and wetting (D/W), and 1268
no cycles (No cycle). 1269
No cycles D/W cycles F/T cycles MBC (mg kg-1) 621 ± 22 628 ± 41 613 ± 34
CUE1 0.65 ± 0.01 0.67 ± 0.02 0.68 ± 0.01 1 MBC/(CO2+MBC) 1270 1271
Net organic carbon balance 1272
1273
After applying two substrate sources and four cycles of F/T and D/W, the net soil C balance 1274
indicated a positive C storage in all cases, including No cycles after 28 days of incubation. F/T 1275
obtained +134 mg kg-1, D/W +63 mg kg-1 and No cycles +80 mg kg-1 soil (Table 2). 1276
1277
1278
1279
1280
1281
1282
1283
56
Table 2. Net carbon balance obtained by the difference between the priming effect 1284
and substrate derived carbon C. Symbol ± is the standard error of the mean. Low case 1285
letters least significative differences (p <0.05) within cycles applied. 1286
No cycles D/W cycles F/T cycles (mg kg-1 soil)
Lignocellulose Lignocellulose carbon-input (13C 97 atom %) 53.3 53.3 53.3
CO2 lignocellulose derived carbon 24.2 ± 3b 44.8± 5a 19.5 ± 4b Lignocellulose derived carbon in soil remaining (a) 17.4 ± 7a 8.1 ± 2a 18.3 ± 6a
Lignocellulose recovery (%) 78.0 99.2 71.0 Glucose Glucose carbon-input (14C) 10.1 10.1 10.1 CO2 Glucose derived carbon 5.7 ± 0.2a 6.4 ± 0.2a 4.4 ± 0.2b Glucose derived carbon in soil remaining (b) 1.8 ± 0.4a 1.7 ± 0.4a 2.1 ± 0.2a
Glucose recovery (%) 74.3 80.1 64.4 Priming effect1(c) -61 ± 6a -53 ± 8a -114 ± 11b Net C balance (a+b-c) +80.2 ± 6 +63 ± 6 +134 ± 5
1SCO2 – CO2control (see equation 6 in the text) 1287 1288
Discussion 1289
1290
The present study results supported the hypothesis that the induced negative PE by frequent F/T or 1291
D/W cycles leads microorganism to a preferential labile C use by rapid microbial growth from 1292
fPOM available from disrupted macroaggregate (Fig. 1). Supported by the rapid releases of CO2 1293
from the glucose derived C follow by stabilization at the end of the incubation period (Derrien et 1294
al., 2014). The microbial biomass C and CUE in soil with F/T and D/W cycles and soil with No 1295
cycles were similar at the end of 28 days of the incubation period (Table 1). These microbial 1296
biomass and CUE comparisons were also found in a broad range of soils with D/W cycles (Canarini 1297
57
et al., 2017) and F/T cycles (Bore et al., 2017; Song et al., 2017) indicating that the effect of a 1298
single substrate application decrease after the firths F/T or D/W cycle applied. 1299
After 28 days of incubation, there was a significant C release from macroaggregates and C 1300
enrichment at microaggregates. This effect was notorious for F/T in macroaggregates transferring 1301
materials to enrich microaggregates (Fig. 3). Similar results were found for fPOM fraction that 1302
decreased in macroaggregates and increased in microaggregates due to the increasing number of 1303
F/T and D/W cycles (Gale et al., 2000; Park et al., 2007). Disruptive process in soil aggregates 1304
creates cracking exposing SOC to new micro-fissures planes otherwise formerly protected against 1305
microbial attack (Denef et al., 2001a; Denef 2001b; Consentino et al., 2006; Six et al., 2000; von 1306
Lutzow et al., 2007). 1307
The negative PE was more intense for the C derived from lignocellulose than for the C 1308
derivative from glucose. In soil with D/W, the accumulated priming from glucose paralleled the 1309
control curve just below from the beginning to the incubation end. Whereas F/T was always well 1310
below the control soil, reflecting strong negative priming. This pattern can be explained because 1311
freezing events is a much more disturbing phenomenon than drying (Pardini et al., 1996)) and 1312
thawing generates a rapid microbial growth of short duration by rapidly consuming the necrosomes 1313
(dead biomass) and the remaining glucose C (Skogland et al., 1988). In opposition, lignocellulose 1314
was protected in macro-and micro-aggregates, which generate a slow microbial turnover 1315
prolonging the negative PE. The results were supported because F/T reduces the diffusivity of 1316
dissolved organic carbon (DOC) into macroaggregates. The last reduces microorganisms’ potential 1317
for DOC consumption (Zak et al., 1999). 1318
In conclusion, the substrate derives C decomposition decreased total respiration in response 1319
to negative PE due to preferential use of readily available C by soil microbes from fPOM rather 1320
than using the native SOC (Butterly et al., 2019; Liu et al., 2017; Manson-Jones et al., 2018; Tian 1321
58
et al., 2019). Glucose can be rapidly assimilated by microbes (Jagadamma et al., 2014) and thus 1322
can be fast consumed. Meanwhile, lignocellulose requires additional steps to decompose using 1323
extracellular enzymes to solubilize the fresh C materials (Fontaine et al., 2004b). Drying and 1324
wetting can accelerate the additional steps providing O2 diffusion (Dutta et al., 2015) and enzyme 1325
activity promoting the decomposition of lignocellulose (Canarini and Dijkstra, 2015). The 1326
application of two sources of C, glucose, and lignocellulose, clearly produced an additive effect 1327
(statistical interaction) represented by in a succession of microorganisms; first, those adapted to a 1328
labile C consumption (e.g., glucose) by r-strategist and another group K.-strategist adapted to the 1329
consumption of complex material (e.g., lignocellulose) (Fontaine et al. 2004a). 1330
Labeled substrate addition and F/T and D/W cycles generate a negative PE. The magnitude 1331
and directions of PE are possible only using labeled 14C and /or 13C (Fontaine et al. 2004a; Wang 1332
et al. 2015). In the present study, we did not find a positive PE except a small net positive priming 1333
when No cycle was subtracted. Positive PE indicates rapid CO2 effluxes from native SOC even 1334
though the ecosystem can still accumulate SOC (Matus et al. in preparation). Likewise, a negative 1335
PE can offset the soil C lost by the fresh C decomposition gain, for example, by dead microbial 1336
biomass accumulation (Qiao et al. 2013; Wu et al. 2020) (Fig. 1C). The net soil C balance 1337
indicated a C storage in all cases, including No cycles after 28 days of incubation, leading to the 1338
think that the humid temperate forests soil accumulates C stock. However, this conclusion is 1339
difficult since the substrate used in this investigation is very different from the quality litter found 1340
in this ecosystem (Nájera et al., 2020). We can only conclude that F/T cycle generates more marked 1341
negative PE by preferential C use compared to D/W cycle produced by the release of fPOM from 1342
disrupted macroaggregates. 1343
1344
1345
59
Acknowledgments 1346
1347
Special thanks to Karin Schmidt and Sussan Enzmann from the Soil Science Department and the 1348
people of KOSI and LARI isotope laboratories of Georg-August Universität Göttingen. We are 1349
grateful to the Chilean National Park Service (CONAF) for providing access to the sample 1350
locations and on-site support of our research. 1351
1352
Financial support 1353
1354
The authors acknowledge financial support from the German Science Foundation (DFG) priority 1355
research program SPP-1803 “EarhShape: Earth Surface Shaping by Biota” (Project Root Carbon 1356
N°6/2016 to 2019). To the national doctoral scholarship CONICYT N° 21160957, of the Chilean 1357
government. To the FONDECYT project Nº 1170119 and the Conservation and Dynamics of 1358
Volcanic Soil Laboratory of the Universidad de La Frontera and BIOREN-UFRO. The host 1359
universities of our research and financial support George-August University Gottingen and Leibniz 1360
University Hannover Germany. 1361
60
1362
1363
CHAPTER IV 1364
1365
1366
Freezing/hawing and drying/ wetting cycles on 1367
microbial communities and enzyme activities in 1368
humid temperate forest soil 1369
1370
(Paper in preparation) 1371 1372
1373
61
Abstract 1374
1375
Drying/rewetting (D/W) and freezing/thawing (F/T) events are one of the main drivers of soil 1376
carbon (C) turnover. The frequency of drought and freezing impact the biology and the physical 1377
soil conditions. Here we tested: i) D/W and F/T cycles will increase the SOM decomposition of 1378
easily available C due to an increase of extracellular enzymes and soil cellullobiotic bacterial 1379
communities and ii) The substrate quality plays a crucial role in SOC decomposition, so D/W and 1380
F/T release different type of SOC (labile C or more recalcitrant) due to ongoing macroaggregates 1381
disruption in this ecosystem. The thermogravimetric analysis (TGA) and Fourier Transformed 1382
Infrared (FTIR) spectroscopy to assess the quality of SOM were used. We also evaluated the 1383
enzyme activity (eight exoenzymes) related to SOM decomposition and the diversity of microbial 1384
communities by DGGE analysis. The TGA pyrolysis showed the highest weight loss of 1385
polysaccharides (high abundance) in D/W, and ART-FTIR showed the highest lignin signal 1386
intensity in F/T. Enzymes Peroxidase increased with D/W, and glycine aminopeptidase increased 1387
with F/T cycles. Cellulolytic bacteria (CFU) grew with D/W, closely related to the increase of 1388
peroxidase activity. DGGE analysis shows that D/W cycles have a critical effect on microbial 1389
communities, with a 15 % shift than F/T cycles similar to No cycles. Enzyme activity of POD (p 1390
<0.01) was the most important of the enzymes affecting the microbial structure. Our findings 1391
suggest a detrimental effect of climate change on this pristine forest soil organic matter 1392
accumulation. 1393
1394
1395
1396
1397
62
INTRODUCTION 1398
1399
The intensification in frequency and magnitude of climatic events as freezing/thawing (F/T) and 1400
drying/wetting (D/W) cycles will strongly influence carbon (C) emissions from the terrestrial 1401
ecosystem (IPCC, 2013; Frank et al., 2015). Soil microbial respiration is one of the most intriguing 1402
process outcomes on climate change, and its variability has a significant impact on the overall 1403
functions of ecosystems and greenhouse gasses (GHG) (Corti et al., 2002; Vicca et al., 2014). F/T 1404
and D/W cycles effect are still unclear on how temperature affects soil organic matter (SOM) 1405
responses, microbial dynamics, and enzyme activities (Song et al., 2017). F/T and D/W cycles are 1406
expected in temperate regions during the winter-spring season and could significantly influence 1407
soil functions, such as microbial responses that play a vital role in soil nutrients availability 1408
(Freppaz et al., 2007; Daou et al., 2016). When the temperature falls below 0 °C, freezing occurs, 1409
ice crystals can entrap or denature extracellular enzymes delaying their activity (Cao et al., 2003). 1410
Drying of soil causes enzymes to become restricted in thin water films, inducing denature or 1411
sorption over the solid phase (Miura et al., 2019). Studies using distinct soils and methods have 1412
always reported inconsistent effects of F/T and D/W cycles on microorganisms and microbial 1413
biomass, showing either increase (Sistla and Schimel, 2013; Sørensen et al., 2018), decreases 1414
(Turner and Romeo, 2010), or no net change (Bandick and Dick, 1999; Matzner and Borken, 2008). 1415
Even F/T causes microbial cell lysis and the release of their content into soils, and there is an active 1416
survival that remains when soils are frozen (Henry, 2007; Koponen and Bååth, 2016; Bore et al., 1417
2018). 1418
Freezing and Drying decrease gas emissions (Kim et al., 2012; Canarini et al., 2017) and 1419
reduce the availability of soil organic matter (SOM) to soil microorganisms (Borken and Matzner, 1420
63
2009). Wetting and thawing may cause the breakdown of soil aggregates exposing physically 1421
protected SOM to microbial attack (Denef et al., 2001; Oztas and Fayertorbay, 2003). These cycles 1422
release SOM, which is rapidly decomposed by the soil microorganisms causing a burst of C 1423
mineralization and CO2 release (Appel, 1998) the Birch effect (Birch, 1958). An increase of CO2 1424
flux from the soil is commonly observed after F/T or D/W cycles ascribed to a range of factors, 1425
including: (i) death and lysis of microbial cells and mesofauna; (ii) increased microbial metabolism 1426
and the use of energy during the production of stress compounds (e.g., cryo- and osmoprotectants), 1427
and (iii) changes in pH and ionic strength which increase SOM solubilization (Edwards and 1428
Cresser, 1992; Fierer and Schimel, 2002; Schimel et al., 2007). 1429
The mechanisms controlling SOM decomposition after F/T and D/W cycles could be more 1430
complicated in forest soils than in any other ecosystem (Shi et al., 2014). It is difficult to separate 1431
the collinear variation of factors controlling CO2 flux (Unger et al., 2012). For example, D/W cycles 1432
are closely related to the diffusivity and the C-supply to microorganism availability (Manzoni et 1433
al., 2012). Soil microbial respiration measured before and during F/T cycles was not related to the 1434
soil microbial biomass but controlled by substrate C availability and SOM quality (Jha et al., 1992; 1435
Feng et al., 2007). Therefore, substrate quality plays an essential role in the decomposition and 1436
chemical protection of SOM, as revealed by the Nájera et al. (2020; 2021) due to disruptive events 1437
such as D/W. Even so, soil warming alone did not stimulate microbial, and enzyme activity and 1438
respiration were reduced by the combination of warming in summer and soil freeze-thaw cycles in 1439
winter (Sørensen et al., 2018). Fernández et al. (2006) indicate that the C availability, rather than 1440
soil moisture, influenced the length of CO2 pulses in response to rain events; those can induce 1441
structural changes in soil chemical, physical properties, microorganism communities, or vegetation 1442
(Vicca et al., 2014). Consequently, there is an incomplete knowledge of the processes connecting 1443
SOM humification, destabilization, and the mineral interaction linked to CO2 fluxes. The present 1444
64
study evaluates the SOM quality, microbial biomass, and extracellular enzyme activities to observe 1445
the impact of F/T and D/W cycles influence on these parameters in a humid temperate ancient 1446
forest of Araucaria araucana 1447
The hypotheses were tested that i) D/W and F/T cycles will increase the SOM 1448
decomposition of easily available C due to an increase of extracellular enzyme and soil 1449
cellullobiotic bacterial communities and ii) The substrate quality play a key role in SOC 1450
decomposition, so D/W release labile C than F/T due to ongoing macroaggregates disruption due 1451
to frequent D/W event in this ecosystem 1452
1453
Methodology 1454
1455
Study site 1456
1457
The soil was collected from a temperate forest dominated by Araucaria tree (Araucaria araucana 1458
(Molina) K. Koch) in Nahuelbuta National Park (37°47′ S, 72°59′ W) Araucanía region, Chile, and 1459
is originated from granitic bedrock (Bernhard et al., 2018; Oeser et al., 2018). The soil is an 1460
Inceptisol (Soil Survey Staff, 2014), with the following characteristics: pH 4.3; Soil C 10.6 %; Soil 1461
N 0.5 %; Sand 50.2 %; Silt: 23.6 %; Clay: 26.2 %; Bulk density 0.8 Mg m-3. A bulk sample from 1462
3 subsamples (5-10 cm) was collected and immediately transported to the laboratory in a 1463
refrigerated box. The samples were cleaned, air dried, sieved (mesh market grade 10; 2000 µm), 1464
and stored for further studies. 1465
1466
1467
1468
65
Incubation experiment 1469
1470
The effect of D/W and F/T cycles on the temperate rainforest soil was evaluated on microbial 1471
biomass; 25 gr of air-dry soil in 50 ml falcon tubes were incubated at 25 °C. Preincubation for four 1472
days at field capacity (0.34 m3 m-3). Two treatments of cycles were tested. Drying/rewetting cycles 1473
consisted of 3 dry days followed by three days at field capacity. The dry conditions were achieved 1474
using a vacuum pump (Leroy-SomerTM) to reach -80 kPa for 3 hours from the top. Wetting started 1475
with watering of the soils from the top until field capacity was reached. Soil cores were separated 1476
into four groups and subjected to i)one or four D/W, ii) four F/T cycles, and iii) No cycles 1477
(Control). The soil was incubated at 20 ºC at room temperature. The freezing conditions were 1478
induced by placing the microcosms at -18 ºC for 12 hours over the night of day 3, 9, 15, and 21. 1479
The thawing was at room temperature during the same days. Drying conditions were conducted 1480
slowly on a ceramic plate by lowering the pressure to -5 bar during 12 hours, equivalent to a 1481
moisture content of 37 % of field capacity. The soil remained dry, in these conditions, for three 1482
days. After that, the soils were weighted to determine the water loss. Rewetting was achieved by 1483
adding demineralized water up to field capacity from the top of the microcosms jar. Drying 1484
conditions were imposed 3, 9, 15, and 21 days, and rewetting of soil at day 6, 12, 18, and 24, ending 1485
at 28 days of incubation. All treatments were replicated four times, and at the end of the incubation, 1486
it was destructive to assess soil quality and microbial activity. 1487
1488
Thermogravimetry and differential scanner calorimetry 1489
1490
Thermogravimetry (TG) analysis relates weight loss from a sample subjected to an increase in 1491
temperature in isobaric conditions. The differential scanner calorimetry (DSC) analysis consists of 1492
66
measuring the difference in heat flux recorded from the soil sample analyzed and the reference 1493
sample. Briefly, 20 mg oven dry (24 h at 40 ºC) were milled and heated in a range from 25 °C to 1494
700 °C at 15 °C min-1. Nitrogen was used as a carrier gas in a Differential Scanning Calorimetry 1495
DSC-4000, Perkin Elmer. 1496
During the measurement, both the sample and the reference material are subjected to the 1497
same temperature effect, determining the temperature change rate during the analysis. In practice, 1498
the recorded difference in heat fluxes corresponds to enthalpy changes as a function of temperature, 1499
whereas the peak areas corresponding to the heat of phase transitions occurring in the steel (Kargul 1500
et al., 2015). 1501
1502
Attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) 1503
1504
The effect of D/W and F/T cycles of soil was analyzed with an ATR-FTIR spectrophotometer 1505
(Tensor 27, Bruker Optics, Germany). Scans were done on the Near-infrared spectrum 3500 to 600 1506
cm-1. The scans had a resolution of 4 cm-1. Three major bands were analyzed: 3425-3200 1507
(Polysaccharides and water related), 1600-1635 (Lignin and aromatic component), and 1070 cm-1 1508
(cellulose like compounds). 1509
1510
Extracellular enzyme activity 1511
1512
The activity of extracellular enzymes was determined using colorimetric substrates (Allison, 2008) 1513
adapted from Sinsabaugh (1994). Soil samples were mixed with buffer acetate in sterile 100 ml 1514
jars and shaken for 30 min. Subsequently, the soil solution was shaken by hand before aliquots of 1515
50 μl were pipetted into black polystyrene 96-well microplates (Brand, Germany). Afterward, 50 1516
67
μl of buffer linked substrates, and 100 μl of the substrate solution, exoenzymes activity (μm g-1 h-1517
1), their functions, and substrate are presented in table 1. The activity was measured by a microplate 1518
reader (Victor 3 1420-050 Multi label Counter; extinction: 355 nm, emission: 450 nm for 1519
PPO/POD, and 405 nm for peptidases). 1520
1521 Table 1. Extracellular enzymes are assessed in soil and their abbreviations, functions, 1522 corresponding substrates, and substrate concentrations. 1523
Nº Enzyme Abbreviation
Function Substrate Substrate concentration
1 Acid phosphatase AP Mineralizes organic P into phosphate pNP-phosphate 5 mM
2 b-glucosidase BG Cellulose degradation pNP-β-glucopyranoside 5 mM
3 Cellobiohydrolase CBH Cellulose degradation pNP-cellobioside 2 mM
4 glycine aminopeptidase GAP
Catalyze the cleavage of amino acids from the amino terminus of protein or peptide substrates
glycine p-nitroanilide 5 mM
5 Leucine aminopeptidase LAP Peptide breakdown leucine p-
nitroanilide 5 mM
6 N-acetyl-b-D-glucosaminidase NAG Chitin degradation
pNP-β-N-acetylglucosamine
2 mM
7 Polyphenol oxidase PPO Degrades lignin and other aromatic
polymers pyrogallol and EDTA 50 mM
8 Peroxidase POD Catalyzes oxidation reactions L-DOPA 5 mM
1524
Cellulolytic bacteria counting 1525
1526
An analysis of the microbial content after F/T and D/W cycles focused on bacteria that use 1527
cellulose as a primary carbon source. After D/W and F/T cycles, counting of cellulolytic bacteria 1528
was performed in a Carboxy Methylcellulose agar (CMC), analyzed in triplicate. This medium 1529
facilitated the visual differentiation of bacteria strains that use cellulose as the principal carbon 1530
source. These bacterial colonies will present a degradation halo, with Congo red discoloration as 1531
68
an indicator (Hendricks et al., 1995). CMC (Carboxy Methyl Cellulose; g l-1) 5 g; K2HPO4, 1 g; 1532
MgSO4, 0.2 g; CaCl2, 5 mg; Fe2(SO4)3 and 15 g; agar. The pH was adjusted to 7, and the CMC 1533
solution was autoclaved for 15 min at 121 ºC, cooled, dispensed into sterile Petri dishes, air dried 1534
in a sterile condition, and stored at 4 ºC before use. From each treatment, 1 g of soil was suspended 1535
on 10 ml of NaCl 0.85% and a serial dilution at 10-4. Each dilution was recovered 100 µl and 1536
spreader in CMC agar, incubated at 30 ºC for 72 hours. At the end of the incubation, 5 ml of red 1537
Congo was added and incubated for 5 min, and the excess was discarded, then was added 3 ml of 1538
NaCl 2 M to clean the no bonded Congo red. Finally, the plate was incubated for 24 h at room 1539
temperature. Following incubation, total colonies and the colonies exhibiting clearing zones were 1540
counted as cellulolytic bacteria (CFU g-1). 1541
1542
Bacterial community profile 1543
1544
The bacterial community profile was conducted after 28 days of incubation to determine F/T and 1545
D/W influence. According to the manufacturer's instructions, the DNA was extracted in three 1546
replicates using Power Soil DNA Isolation Kit (QIAGEN, United States). DNA was quantified, 1547
and its purity was evaluated using the A260/A280 and A260/A230 ratios provided by 1548
MultiskanTM software. The DGGE analysis was performed using a DCode system (Bio-Rad 1549
Laboratories, Inc.). 16S rDNA fragments were amplified with primers GC-clamp-EUB f933 1550
(position 933-954) forward and EUB r1387 (position 1387-1368) reverse, which are specific for 1551
universally conversed bacterial 16S rDNA PCR Protocol were performed using; 5x GoTaq Flexi 1552
buffer Colorless 1x; MgCl2 25nM (1.5 nM) primer 1: EUBf 933-GC (GCACAAGCG 1553
GTGGAGCATGTGG) (GC-clamp, 5´-CGCCCGCCGCGCGCGGCGGGC-1554
GGGGCGGGGGCACGGGGGG) 1 nM (0.3 mM); Primer 2: EUBr1387 (GCCCGGGAACGTA-1555
69
TTCACCG) 1mM (0.3 nM), GoTag G2 Flexi DNA Polymerase (5u/uL) and DNA template at 5 1556
ng; water till 25 uL. Twenty-five µL of PCR products were loaded onto 6% (w/v) polyacrylamide 1557
gel with a 40:70 % gradient (urea and formamide). The electrophoresis was run for 16 h at 75 V. 1558
The gel was then stained with SYBR Gold (Molecular Probes, Invitrogen Co.) for 30 min and 1559
photographed on a UV transilluminator. The DGGE banding profiles Cluster as a dendrogram was 1560
carried out using Phoretix 1D analysis software (Clarke, 1993) (TotalLab Ltd., United Kingdom). 1561
The correlation between bacterial communities (biological parameters) and chemical soil 1562
properties (ecological parameters) was visualized by distance-based redundancy analysis (dbRDA) 1563
by using Primer 7+ Permanova software (Primer-E Ltd., Ivybridge, United Kingdom; Clarke, 1564
1993). 1565
1566
Statistical analysis 1567
1568
Conventional ANOVA to test for a significant difference in CO2 respiration and Priming Effect in 1569
soil aggregate size, POM fraction, and 13C-lignocellulose and 14C-glucose distribution from the 1570
destructive analyses at the end of incubation was done. Test LSD Post-hock was used to compare 1571
all pair mean differences at p<0.05. ANOVA analyses, correlations, and mean comparison (paired 1572
t-test) was conducted using the SPSS statistical software v11.0 package (SPSS Inc., Chicago, IL, 1573
USA) 1574
1575
RESULTS 1576
1577
Soil organic matter quality 1578
1579
70
The SOM quality was assessed by thermogravimetry, which determines the soil weight losses upon 1580
scaled heating between 25 ºC to 700 ºC. Soils with different organic matter compositions produce 1581
weight loss signals and heat flow signals at different intensities (Siewert, 2010). Soil 1582
thermogravimetry of four D/W or four F/W and no cycles are presented (figure 1). Heat flow (top 1583
panel) indicates a reaction that increases (endo) or release (Exo) temperature from the soil. The 1584
endo reaction shows a transformation of the compounds just before the soil loses weight (low). The 1585
middle panel of Figure 1 is the dynamic of soil weight loss, indicating the temperature that produces 1586
significant soil losses. Considerable weight loss and heat flow are observed in the soil with D/W 1587
or F/T cycles concerning the soil No cycles. The biodegradable components (200-450 ºC) had more 1588
weight loss in soils with four D/W and F/T cycles than the same soil with No cycles. The humified 1589
component and the organo-clay complex had a more pronounced loss on soils with four D/W cycles 1590
than four F/T cycles or No cycles (450-500 °C). Freezing/thawing and control soil showed similar 1591
behavior in this area. 1592
1593
1594
1595
1596
1597
1598
71
Figure 1. 1599
Thermogravimetric 1600
analysis (TG) of 1601
soil organic matter. 1602
The top panel (A) 1603
is the weight loss 1604
(%). (B) The 1605
differential scanner 1606
colorimetry 1607
indicates the Heat 1608
flow (mV g-1 ºC-1) being the release or retention of heat from soil changes before weight 1609
loss by combustion and evaporation of organic and mineral soil compounds. Edo-up 1610
indicates endothermic reactions are represented as the curve toward positive values. The 1611
derivative of TG, weight loss (mg g-1 ºC-1) (C). Lines in 200 and 450 ºC indicate a 1612
separated zone where different soil components are lost (endo-up means endothermic 1613
reaction has positive y-axis direction). 1614
1615
The proportion of total soil weight loss indicates that soil with No cycles (Control) lost weight 1616
was higher at the end of the incubation period, especially by the water loss, below 200 °C. the same 1617
soil with D/W or F/T cycles. Between 200 and 400, °C the weight lost for D/W cycles and F/T 1618
were similar (~12%. Between 450 and 650 ºC, the weight loss corresponds to the humified 1619
components and organo-mineral complex. The observed lost weight for treatments was similar 1620
(Figure 1). 1621
No-cyclesDrying/rewetting cyclesFreezing/thawing cycles
A
B
C
Wei
ght l
oss
(mg
g-1 m
in-1
)
−0.6
−0.4
−0.2
0
Hea
t Flo
w (m
v g-1
min
-1)
−15
−10
−5
0
5
Soi
l wei
ght l
oss
(%)
0
1
2
3
4
5
Temperature (ºC)50 100 150 200 250 300 350 400 450 500 550 600 650 700
72
Previous results were in line with those of soil transmittance measure by the Fourier 1622
Transform Infrared spectroscopy (ATR-FTIR). It analyzes four major vibrational bands of the soil 1623
with four D/W, four F/T, and No cycles (Figure 2). First, the band at 3425 cm-1 probably 1624
corresponded to OH structural water and showed less intensity with D/W cycles than in the F/T 1625
cycles or No cycles. The peak between 1640-1600 cm-1 likely related to aromatic C=O vibrations 1626
of COO anions and C=C stretching of aromatic C in lignin. Additionally, bands at 1490-1389 cm-1627
1 likely represented C-H of CH2 and CH3 stretching. Lastly, bands at 1033-1010 cm-1 probably 1628
represent C-OH stretching of polysaccharides (cellulose-like) peak between 2100-1900 cm-1 is 1629
linked to water in soil (Ellerbrock and Kaiser, 2005; Merino et al., 2017). Soil with D/W cycles 1630
shows different spectral intensity than the same soil with F/T and soil with No cycles indicating a 1631
change in OM content in soils. 1632
1633
Figure 2. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectra of 1634
soil after 4 D/W (red line), 4 F/T (Blue line) cycles, and soil with No cycles (black line). 1635
The peaks indicate different organic compounds in soil. 1636
1637
Polysaccharide, water
Lignin
polysaccharide, silicate4 F/T cycles4 D/W cyclesControl
Tran
smitt
ance
(%)
60
70
80
90
100
Wavenumber60012001800240030003500
73
Exoenzyme activity 1638
1639
Soil microbial exoenzyme: Acid phosphatase (AP), b-glucosidase (BG), cellobiohydrolase (CBH), 1640
glycine aminopeptidase (GAP), Leucine aminopeptidase (LAP), N-acetyl-b-D-glucosaminidase 1641
(NAG), Polyphenol oxidase (PPO) Peroxidase (POD) activity were measured at the end of the 28 1642
days on incubation. AP and PPO are not presented because this exoenzyme did not show activity 1643
on this soil. BG, CBH, and LAP did not show a significant difference (p <0.05) between cycles 1644
and the control soil, including one cycle of D/W (Figure 3). 1645
1646
Figure 3. Exoenzyme activity on the soil after one and four drying and wetting cycles 1647
(D/W), four freezing and thawing (F/T) cycles and No cycles (Control). Different letters 1648
indicate a significant difference within each panel (p <0.05). 1649
1650
Glycine aminopeptidase (GAP) decrease with four D/W cycles and was similar with one cycle 1651
D/W to the same soil with four F/T cycles and No cycles. N-acetyl-b-D-glucosaminidase 1652
(NAG) decreases with cycles applied on the soil, being found less in soil with D/W cycles and 1653
e)
b
b
a
ab
Act
ivity
(um
ol g
-1 h
-1)
0
0.2
0.4
0.6
4 D/R cycles 1 D/R cycle 4 F/T cycles Control
NAG
a)
aa
aa
Act
ivity
(um
ol g
-1 h
-1)
0
0.1
0.2
0.3
4 D/R cycles 1 D/R cycle 4 F/T cycles Control
BG b)
aa
a
a
Act
ivity
(um
ol g
-1 h
-1)
0
0.5
1.0
1.5
4 D/R cycles 1 D/R cycle 4 F/T cycles Control
CBH c)
b
ab
aba
Act
ivity
(um
ol g
-1 h
-1)
0
0.5
1.0
1.5
4 D/R cycles 1 D/R cycle 4 F/T cycles Control
GAP
f)
ab
ab
b
a
Act
ivity
(um
ol g
-1 h
-1)
0
10
20
30
4 D/R cycles 1 D/R cycle 4 F/T cycles Control
PODd)
a
a
a
a
Act
ivity
(um
ol g
-1 h
-1)
0
2
4
6
4 D/R cycles 1 D/R cycle 4 F/T cycles Control
LAP
74
F/T cycles than with No cycles. Polyphenol oxidase (PPO) Peroxidase (POD) activity increase 1654
with D/W cycles. 1655
1656
Cellulolytic bacteria count 1657
1658
1659
Figure 4. Colonies forming Unities (CFU) after D/W and F/T cycles were applied a) 1660
total CFU g soil-1;b) cellulolytic CFU bacteria g soil-1; c) proportion (%) cellulolytic 1661
CFU bacteria of total microbial counting. 1662
1663
The total number of bacteria that can catabolize cellulosic compounds (CFU) was higher with one 1664
D/W cycles, followed by four D/W cycles (Figure 4 A). A lower amount was found in similar CFU 1665
in the soil with F/T cycles and No cycles (Figure 4 B). The cellulolytic bacteria colonies were 1666
similar in the soil with cycles or with No cycles. The proportional analysis of cellulolytic bacteria 1667
indicates that it is an important group found in this soil. This proportion reaches about 60 % of the 1668
total CFU with F/T cycles and No cycles decreasing with D/W cycles (Figure 4 C). 1669
a
c)
b
a
c
cellu
loly
tic (%
)
0
20
40
60
80
100
4 D/W cycles 1 D/W cycles 4 F/T cycles Control
a
a a a
b)C
ellu
loly
tic (C
FU g
-1)
0
5×105
10×105
15×105
20×105
4 D/W cycles 1 D/W cycles 4 F/T cycles Control
b
a)a
c c
Tota
l (C
FU g
-1)
0
2×106
4×106
6×106
8×106
10×106
4 D/W cycles 1 D/W cycles 4 F/T cycles Control
75
1670
Figure 5. Colonies forming Unities (CFU) on CMC medium of growing after D/W and F/T 1671
cycles, picture of microbial colonies after four D/T cycles (A), one D/W cycle (B); four F/T 1672
cycles (C) and soil No cycles (D) applied (control), Halos indicate cellulosic microbial 1673
communities have grown. 1674
1675
Bacterial community profile 1676
1677
The bacterial profile indicates a 15 % microbial community shift induced by D/W and F/T cycles 1678
(Figure 5). DGGE gave us an indication of the microbial structure. In general, our results supported 1679
the hypothesis of this study. DGGE suggests that D/W cycles have an essential effect on microbial 1680
communities, and F/T was more similar to the soil No cycles. Enzyme activity of POD (p < 0.01) 1681
was the most important one affecting the microbial structure. 1682
A
B
C D
76
1683
1684
1685
1686
1687
1688
1689
1690
1691
1692
Figure 6. DGGE analysis related to exoenzyme activity of soil. The soils with drying and 1693
wetting cycles (1 DR and 4 D/W), freezing and thawing cycles (4FT) and no cycles applied 1694
(Control). Acid phosphatase (AP), b-glucosidase (BG), cellobiohydrolase (CBH), glycine 1695
aminopeptidase (GAP), Leucine aminopeptidase (LAP), N-acetyl-b-D-glucosaminidase 1696
(NAG), Polyphenol oxidase (PPO) Peroxidase (POD). 1697
1698
DISCUSSION 1699
1700
The effect of D/W and F/T cycles on the behavior of microbiological communities and composition 1701
were assessed. Organic matter decomposition was observed by a higher weight loss in the soil with 1702
D/W cycles, clay-related water, and labile organic matter forms. More weight loss was observed at 1703
a lower temperature for F/T cycles related to water-free or related to organic matter (Kučerík et al., 1704
2018). This results fully coincided with the results of Chapter II where the F/T showed a negative 1705
77
PE, i.e. a retardation of the turnover of the SOM with dominance in the mineralization of fresh C 1706
reflexed in the weight losses and transmittance plots (Figure 1 and 2). 1707
The humic colloids, including the mineral phase, soil pH, cation exchange capacity (CEC), 1708
exchange surface area, can be related to exoenzyme activity and its preservation (Burns, 1982; 1709
Frankenberger and Johanson, 1982). In our case, AP and PPO did not show activity because of the 1710
low pH and high exchangeable aluminum (Allison and Jastrow, 2006). Enzymes such as NAG, 1711
BG, and CBH may drive rapid C turnover in fPOM fractions, which retain high C concentrations 1712
only because they are derived from recent plant material inputs with high C: N and low mineral 1713
content (Allison and Jastrow, 2006). GAP activity decreases with four D/W cycles, which degrade 1714
the chitin-rich cell walls of dead fungi, especially mycorrhizal fungi (Guggenberger et al., 1999). 1715
On the other hand, wetting stimulated all enzyme activity as the results of Stock et al. (2019), 1716
indicating that drying events are more damaging than F/T cycles. 1717
The activity of NAG decreases with F/T and D/W cycles by decomposing the fPOM organic 1718
matter, increasing substrate availability. The LAP activity is more stable than NAG activity in soils 1719
(Zeng et al., 2016) that was noticed hereafter releasing SOM after D/W and F/T cycles. 1720
Our results shows that Drying/rewetting and F/T cycles increase POD activity by increasing 1721
gas exchange for oxidative reaction, the physical disruption of aggregates in soil, and increasing 1722
water availability after rewetting (Yordanova et al., 2004). Peroxidases are considering being stress 1723
enzymes as an antioxidant (Hajiboland, 2014). The effects of D/W cycles on exoenzymes activity 1724
were higher than F/T cycles (Miura et al., 2019). Fluctuations in water availability induce little 1725
changes in the soil enzyme content, and seasonal variations in enzymatic activities are low. 1726
Usually, they cannot be correlated with changes in microbial numbers (Skujins, 1976). The higher 1727
oxidative activities can limit soil organic matter accumulation (Sensibaugh, 2009) by mediating 1728
78
key processes in recalcitrant C turnover including lignin degradation (Orth and Tien, 1995), 1729
specially on soil with D/W cycles (Su et al., 2020). 1730
Soil microorganisms that catabolize plants' cellulosic material influence the flow of energy 1731
from plant material to higher trophic levels and, ultimately, release CO2 to the atmosphere 1732
(Hendricks et al., 1995). Deng and Tabatabai (1994) found similar results when air-dried or field-1733
moist soil samples were incubated, suggesting that cellulase enzymes play a role in the degradation 1734
of the native substrates. One D/W cycles had a greater CFU count, followed by 4 D/W cycles 1735
related to aggregate disruption and formerly protected organic matter release (Denef et al., 2001; 1736
Nájera et al., 2020), related to a high initial amount of SOM in soil and the preferential use of 1737
formerly protected SOM. 1738
The number and intensity of bands in the DGGE gel reflect at some level the number and 1739
relative abundance of dominant sequences from different populations under study. Thus, 1740
comparisons between different microbial communities can be achieved (Muyzer and Smalla, 1741
1998). Alternatively, the result indicates similarities in 85 % between soils (Figure 5). which will 1742
show the microbial structure. In general, our hypothesis is supported. DGGE suggests that D/W 1743
cycles have an essential effect on microbial communities, and F/T was more similar to the soil 1744
without cycles. Enzyme activity of POD (p < 0.01) was the most important of the enzymes affecting 1745
the microbial, and respect with to the structure of the bacterial community were AP and GAP on 4 1746
F/T cycles (p < 0.01). In general, our results supported the hypothesis of this study that (dbRDA) 1747
of the microbial communities is based on the DGGE profiles of total bacteria. The results showed 1748
that a 15 % difference in soil bacterial communities includes D/W cycles. 1749
The peroxidase (POD) activity increase in soil with D/W cycles related to the increase in 1750
SOM decomposition. D/W cycles had more decomposition than F/T cycles or No cycles, indicating 1751
a more significant amount of biodegradable organic matter or complex organic matter was 1752
79
available. Freezing/thawing cycles show a more significant NAG activity related to the 1753
decomposition of resenting residues and not protected OM (light fraction), an indication that cold 1754
weather limited substrate to microorganisms, increasing the consumption of new organic matter. 1755
POD increase with D/W cycles indicates that microorganisms release this enzyme that decompose 1756
preferentially new and less protected organic matter than already complexes with the mineral 1757
particle in soil. Further studies have to focus on the seasonal variation of exoenzyme, which 1758
manifests resistance to humidity, temperature, and environmental changes. 1759
1760
CONCLUSIONS 1761
1762
Drying/rewetting cycles significantly impacted the soil organic matter decomposition 1763
releasing labile C, probably from macroaggregates compared with F/T, as demonstrated by Nájera 1764
et al. (2020; 2021). This was also supported by the increased cellulolytic microbial communities 1765
grew together with exoenzymes as peroxidase activity. The cellulolytic bacterial had a higher 1766
increase with D/W cycles over F/T cycles and No cycles. The microbial communities changes 1767
were observed by DNA analysis where the soil with D/W had a 15 % shift concerning the soil with 1768
F/T cycles and No cycles. Our result indicates that the soil water cycles and the gas exchange are 1769
a significant driver of soil carbon decomposition. Microbial communities change with drying and 1770
rewetting, driving an increase in exoenzyme activity that can degrade complex organic compounds. 1771
Our findings suggest a detrimental effect of climate change on this pristine forest soil organic 1772
matter accumulation. In the same soil, a positive C balance (SOC gain) was established for both 1773
D/W and F/T by Nájera et al. (2020 and 2021), with labeled substrate quite different from the 1774
Araucaria litter for the adapted microorganisms. 1775
80
1776
1777
1778
1779
CHAPTER V 1780
1781
1782
1783
General discussion, concluding remarks, and future 1784
directions 1785 1786
1787
1788
81
This study tested the general hypothesis that F/T and D/W cycles on forest topsoil will drive a 1789
preferential use of new carbon from fPOM formerly protected by macroaggregates. First, 13C-1790
lignocellulose was applied, and four D/W cycles at two temperatures, 5 and 25 °C, were imposed 1791
(Chapter II). A second incubation experiment with two sources of fresh labeled C-input 1792
(lignocellulose and glucose) and four F/T and D/W cycles were applied (Chapter III). In both 1793
experiments (Chapter II and III), The CO2 efflux from isotopic carbon (12C, 13C, and 14C) was 1794
related to the priming effect from three density POM fractions (light, occluded, and heavy) in 1795
macro-, micro-aggregates, and silt+clay aggregates size. A third incubation experiment to 1796
determine the microbial exoenzyme activity, microbial community, and the released SOC's quality 1797
from macroaggregates after F/T and D/W applied was performed. Microbial community structure, 1798
thermogravimetry analysis of the SOM and ART-FTIR spectra were evaluated. Microbial 1799
composition was studied using DGGE and ART-FTIR to determine the SOC degradability 1800
(Chapter IV). 1801
1802
Aggregate size classes, soil carbon, and POM fractions 1803
1804
Our results indicated that D/W cycles drive the redistribution of POM density fractions, increasing 1805
the labile fPOM released for microbial consumption supporting the hypothesis that released 1806
formerly protected C from macroaggregates will provoke a negative PE. A decrease of fPOM by 1807
decomposition and reallocation were observed with a proportional increase of C in microaggregate, 1808
and organo-mineral Hf (Chapter II and III). Drying and wetting cycles promote the fPOM released 1809
by fractures and fissures of soil aggregates, which exposed the protected organic compounds to 1810
microbial attack (Dorodnikov et al., 2011, Gunina and Kuzyakov, 2014). These results were 1811
consistent with those obtained by the thermogravimetric analyses that indicated a significant 1812
82
weight loss with four D/W or four F/T cycles in the biodegradable component zone (200-400 ºC) 1813
in line negative PE observed (Chapter IV) 1814
1815
Soil CO2 fluxes 1816
1817
Drying and wetting and F/T cycles decreased the CO2 efflux after adding lignocellulose and 1818
glucose, causing a negative PE. The efflux reduction was due to the preferential C use of 1819
unprotected organic matter. Soil incubated at 25 ºC showed three times higher CO2 (labeled C) 1820
respiration than at 5 ºC, and a large proportion of this consumed C could be used as an energy 1821
source, e.g., for enzyme synthesis. Meanwhile, microbial biomass C and carbon use efficiency did 1822
not change with F/T and D/W, similar to the other results (Bölscher et al., 2017; Di Lonardo et al., 1823
2017; Liu et al., 2020; Manzoni et al., 2012, Qiao et al., 2019) 1824
As our hypothesis indicated, D/W cycles fissured and cracked aggregate, strongly 1825
influencing POM distribution and soil organic matter exposure to microbial decomposition, related 1826
to the observed results with thermogravimetric and FTIR analysis. Formally fPOM released 1827
triggered the enzymatic activation – all highly energy-demanding - that resulted in lower efficiency 1828
of substrate conversion to new biomass (Ågren and Bosatta 1987; Davison and Janssens 2006; 1829
Manzoni et al. 2012). 1830
1831
Priming effect 1832
1833
A negative PE was observed, influenced by the temperature that increases the CO2 efflux from the 1834
soil. At 5 ºC, there was no PE induced by the lignocellulose amendment. In comparison, at 25 ºC, 1835
the amendment of lignocellulose triggered a negative PE, and an increasing number of D/W cycles 1836
83
this effect was more marked. This negative PE shows that less C is consumed from native SOM by 1837
soil microorganisms. The "fresher" 13C is incorporated, clearly pointing towards the PE 1838
mechanisms of preferential substrate use of C (Butterly et al., 2016; Liu et al., 2017; Manson-Jones 1839
et al., 2018; Zhang et al., 2017). 1840
At 25 ºC, No cycles PE mineralized less C (70 mg C kg-1 soil) than the control soil without 1841
lignocellulose addition. This negative PE was also the case for the PE induced by cycles (PEc) that 1842
resulted after subtracting the PE observed at No cycle from the PE of treatments with 1 and 4 1843
cycles. In the second experiment, glucose accelerates the decomposition of lignocellulose residues 1844
(Dalenberg and Jager, 1981; Derrien et al., 2014; Shabaz et al., 2018) compared with the same soil 1845
with the only addition of lignocellulose (Nájera et al., 2020). In the two incubation experiments 1846
(Chapter II and III), although the CO2 evolved from D/W and F/H were consistently below the 1847
control soil without cycles, it could be that the negative priming effect observed is an artifact 1848
imposed by treatments. However, we believe this was not the case since the No Cycle treatment 1849
did not present significant differences with the control soil without application. Furthermore, the 1850
difference between the treatments that received substrates and No Cycle PEc corresponds to the 1851
net priming effect caused by the cycles, minimizing the difference of accumulated CO2 between 1852
the control soil and the treatments with cycles. 1853
Cycles did increase priming changing the direction at the end of the incubation. Wang et al. 1854
(2015) showed a temporary negative PE of up to 40 days of incubation, where a positive PE was 1855
observed, this was also observed in the second experiment were and PEc were positive for D/W 1856
cycles. 1857
1858
1859
1860
84
Soil microbial dynamics 1861
1862
Our results of D/W and F/T cycles affect microbial biomass, carbon use efficiency, exoenzyme 1863
activity, and microbial communities dynamic support the hypothesis of this study. We demonstrate 1864
that soil microbial communities had metabolic changes as a first response to water availability 1865
Carbon use efficiency did not change with F/T or D/W cycles because it is not associated with 1866
CO2 efflux or PE, but with microbial biomass (Liu et al., 2020). Soil incubated at 25 ºC showed 1867
three times higher CO2 (labeled C) respiration than at 5 ºC (Chapter II and III), and a large 1868
proportion of this consumed C could be used as an energy source, e.g., for enzymes synthesis 1869
(Blagodatsky et al. 2000). SOM quality had stronger control on CUE than stoichiometry at a large 1870
spatial scale (Takiri et al., 2018). CUE changes linked to temperature can most likely be associated 1871
with metabolism rather than differences in the microbial community (Bölscher et al., 2017; Di 1872
Lonardo et al., 2017). Moreover, D/W and F/T cycles applied in this study had an insufficient 1873
intensity to produce a shift in microbial communities at a significant level (Fierer and Schimel, 1874
2002). 1875
This study found that soil bacterial DNA analysis indicate a resilient microbial community 1876
with no more than 15 % change in soil with D/W and F/T cycles and 85% related to exoenzyme 1877
production on Nahuelbuta national park soil. This similarity related to the observed in 1878
Mediterranean climatic conditions (Borken and Matzner, 2009). Drying/wetting cycles increase 1879
POD exoenzyme activity that could be related to microbial antioxidant protection (Hajiboland, 1880
2014), gas exchange and physical disruption of soil aggregates (Yordanova et al., 2004), and 1881
formally protected organic matter release (Denef et al., 2001). Freezing/Thawing cycles did not 1882
show the same behavior because a temperature shock (Sinsabaugh, 2009) being closer to No cycles 1883
applied. Most of the measure exoenzymes did not change its activity, that could be because after 1884
85
rewetting, rising water availability stimulated potential activities (Stock et al., 2018). On these 1885
experiments cellulosic bacteria were related to POD activity. Cellulolytic bacteria colonies were 1886
resistant to incubation growing went total bacteria grow (D/W cycles). Increasing his proportion in 1887
the total colonies count in treatment were lest grown was assessed (F/T cycles and No cycles). Our 1888
results are in line with that drying-rewetting cycles have stronger effects on soil microbial 1889
communities and CO2 production than freezing-thawing cycles. This pattern is mediated by 1890
sustained changes in soil microbiome structures (Meisner et al., 2021). 1891
1892
General conclusion 1893
1894
Soil aggregates were affected by frequencies of D/W in humid temperate forest (Araucaria 1895
araucana) soils (Nahuelbuta National Park, Chile), where four cycles at 5 ºC and 25 ºC were 1896
applied. Approximately 15% of the aggregates were disrupted after 28 days of incubation of 1897
undisturbed soils added with 13C-lignocellulose. A second experiment with 13C-lignocellulose and 1898
14C- glucose was conducted where F/T and D/W were imposed. In both experiments, a negative 1899
priming effect, i.e., a retardation of SOC decomposition, was observed. Consequently, the D/W 1900
cycles at 25 ºC significantly increased microbial activity primarily from fPOM consumption 1901
released from macroaggregates. Freezing and thawing and D/W cycles decreased the total soil CO2 1902
efflux compared with the control and increased new organic matter (lignocellulose and glucose) 1903
decomposition. This increase was consistent with the rise of CO2 efflux of labeled labile carbon 1904
from macroaggregates discussed in Chapters II and III. The thermogravimetry analysis also 1905
supported this in Chapter IV. Freezing/thawing cycles show less total CO2, less glucose efflux, 1906
and greater exoenzyme (NAG) activity, related to the decomposition of new organic matter, POM 1907
(light fraction). Peroxidases increased with D/W cycles indicating that microorganisms released 1908
86
enzymes in response to the fresh energy coming from protected organic matter. Overall 1909
experiments, the negative PE found in all incubation conducted to a net gain of SOC, i.e., a positive 1910
C budget from lignocellulose and glucose -derived C soil remaining. The main results and findings 1911
of the influence of D/W and F/T on SOC decomposition in humid temperate forest soils were 1912
presented in two conceptual models discussed in Chapters II and III. These results indicate that 1913
D/W cycle frequency under climate change would influence a selection of unprotected and new 1914
carbon, increasing the distribution under more protected POM fractions. However, decreasing the 1915
total amount of C accumulation on soil from Nahuelbuta National park. 1916
1917
Perspectives 1918
1919
• D/W and F/T cycles on soil have to be evaluated in situ due to ecosystem dynamics, 1920
including different forest formation as sclerophylicus forest, deciduous Broad-leaved forest 1921
and evergreen forest on different climate across Chile, to assess the input variation on 1922
quality and quantity. 1923
• D/W and F/T cycles on soil with different mineralogy need to be evaluated in situ under 1924
different management and conservation status, to determinate the role of soil on carbon 1925
sequestration. Special case of volcanic and metamorphic soil where the conservation of 1926
natural ecosystems and productive land (agriculture and tree production) are found. 1927
• Isotopic tracers were an important tool to assess the organic matter decomposition This 1928
preferential use of C found in the present study need to be tested by the inclusion of other 1929
important nutrient (e.g., N or P) to development new knowledge on biochemical cycles. 1930
87
• The priming effect was essential to assess the time and dynamic of C consumption. The 1931
inclusion of PE in soil C models is urgent. 1932
• Further studies have to focus on microbial dynamics as changes on microbial communities 1933
changes, exoenzyme activity and persistence (K max; Vmax), under climate change 1934
scenarios. 1935
• The relationship between microbial biomass, PE, exoenzymes, and SOM with different 1936
quality is not well understood. We urgently need elucidate the lack of microbial response 1937
to D/R or F/T and carbon substrate use efficiency SUE. 1938
• It is necessary to characterize the microbial communities adapted to D/W or F/T cycles in 1939
soils to understand the changes in metabolic path ways. 1940
• Further analysis focused on identifying organic compounds related to DSC, TG and FTIR 1941
picks of labile and recalcitrant organic matter after F/T and D/W cycles applied are needed 1942
to assess soil organic matter quality changes. 1943
1944
1945
88
REFERENCES 1946
1947
Adu, J.K., Oades, J.M. (1978). Physical factors influencing decomposition of organic materials in 1948
soil aggregates. Soil Biology and Biochemistry, 10(2): 109–115. http://doi.org/10.1016/0038-1949
0717(78)90080-9 1950
Ågren, G.I., Bosatta. E. (1987). Theoretical analysis of the long-term dynamics of carbon and 1951
nitrogen in soils. Ecology, 68:1181–1189. https://doi.org/10.2307/1939202 1952
Allison, S.D., and Jastrow, J.D. (2006). Activities of extracellular enzymes in physically isolated 1953
fractions of restored grassland soils. Soil Biology and Biochemistry, 38(11): 3245–3256. 1954
https://doi.org/10.1016/j.soilbio.2006.04.011 1955
Allison Lab Protocol: Colorimetric Enzyme Assays, (2008). Steve Allison. Enzyme Assays for 1956
Fresh Litter and Soil Adapted from Bob Sinsabaugh Lab, 1994. 1957
Almagro, M., López, J., Querejeta, J.I., Martínez-Mena, M. (2009). Temperature dependence of 1958
soil CO2 efflux is strongly modulated by seasonal patterns of moisture availability in a 1959
Mediterranean ecosystem. Soil Biology and Biochemistry, 41: 594–605. 1960
https://doi.org/10.1016/j.soilbio.2008.12.021 1961
Appel, T. (1998). Non-biomass soil organic N — the substrate for N mineralization flushes 1962
following soil drying–rewetting and for organic N rendered CaCl2-extractable upon soil drying. 1963
Soil Biology and Biochemistry, 30 (10–11): 1445–1456. http://doi.org/10.1016/S0038-1964
0717(97)00230-7 1965
Armesto, J., Aravena, J. C., Villagrán, C., Pérez, C., Parker, G. (1995). Bosques templados de la 1966
Cordillera de la Costa. En J. Armesto, C. Villagrán, & M. Arroyo (Eds.), Ecología de los 1967
Bosques Nativos de Chile (Universita, pp. 199–213). Santiago, Chile. 1968
89
Arrhenius, S. (1896). On the Influence of Carbonic Acid in the Air upon the Temperature of the 1969
Ground Svante Arrhenius. Philosophical Magazine and Journal of Science, 5(41): 237-276. 1970
https://doi.org/10.1080/14786449608620846 1971
Aye, N.S., Butterly, C.R., Sale, R.W.G., Tang, C., (2018). Interactive effects of initial pH and 1972
nitrogen status on soil organic carbon priming by glucose and lignocellulose. Soil Biology and 1973
Biochemistry, 123: 33–44. https://doi.org/10.1016/j.soilbio.2018.04.027 1974
Balser, T., Firestone, M. (2005). Linking microbial community composition and soil processes in 1975
a California annual grassland and mixed-conifer forest. Biogeochemistry, 73: 395-415. 1976
https://doi.org/10.1007/s10533-004-0372-y 1977
Bandick, A., Dick, R.P. (1999). Field management effects on soil enzyme activities. Soil Biology 1978
and Biochemistry, 31, 1471-1479. https://doi.org/10.1016/S0038-0717(99)00051-6 1979
Barto, E.K., Alt, F., Oelmann, Y., Wilcke, W., Rilling M.C. (2010). Contributions of biotic and 1980
abiotic factors to soil aggregation across a land use gradient. Soil Biology and Biochemistry, 1981
42: 2316–2324. https://doi.org/10.1016/j.soilbio.2010.09.008 1982
Bernhard, N., Moskwa, L-M., Schmid, K., Oeser, R.A., Aburto, F., Bader, M., Baumann, K., von 1983
Blanckenburg, F., Boy, J., van den Brink, L., Brucker, E., Büdel, B., Canessa, R., Dippold, M., 1984
Ehlers, T., Fuentes, J.P., Godoy, R., Jung, P., Karsten, U., Köster, M., Kuzyakov, J., Leinweber, 1985
P., Neidhardt, H., Matus, F., Carsten Mueller, C.M., Oelmann, Y., Oses, R., Osses, P., Paulino, 1986
L., Samolov, E., Schaller, M., Schmid, M., Spielvogel, S., Spohn, M., Stock, S., Stroncik, N., 1987
Tielbörger, K., Übernickel, K., Scholten, T., Seguel, O., Wagner, D., Kühn, P. (2018). 1988
Pedogenic and microbial interrelations to regional climate and local topography: new insights 1989
from a climate gradient (arid to humid) along the Coastal Cordillera of Chile. Catena: 170, 335-1990
355. https://doi.org/10.1016/j.catena.2018.06.018 1991
90
Bertiller, M.B., Mazzarino, M.J., Carrera, A.L., Diehl, P., Satti, P., Gobbi, M., Sain, CL. (2006) 1992
Leaf strategies and soil N across a regional humidity gradient in Patagonia. Oecologia, 148: 1993
612– 624. https://doi.org/10.1007/s00442-006-0401-8 1994
Billings, S.A., Ballantyne IV, F. (2013). How interactions between microbial resource demands, 1995
soil organic matter stoichiometry, and substrate reactivity determine the direction and 1996
magnitude of soil respiratory responses to warming. Global Change Biology, 19: 90-102. 1997
https://doi.org/10.1111/gcb.12029 1998
Bingeman, C.W. Varner, J.E., Martin, W. P. (1953). The Effect of the Addition of Organic 1999
Materials on the Decomposition of an Organic Soil. Soil Science Society of America Journal, 2000
17: 34-38. https://doi.org/10.2136/sssaj1953.03615995001700010008x 2001
Birch, H. (1958). The effect of soil drying on humus decomposition and nitrogen availability. Plant 2002
Soil, 10: 9-31. https://doi.org/10.1007/BF01343734 2003
Blagodatsky, S., Heinemeyer, O., Richter, J. (2000). Estimating the active and total soil microbial 2004
biomass by kinetic respiration analysis. Biology and Fertility of Soils, 32: 73-81. 2005
https://doi.org/10.1007/s003740000219 2006
Blagodatskaya, E.V., Blagodatsky, S.A., Anderson, T.-H., Kuzyakov, Y. (2011). Priming effects 2007
in Chernozem induced by glucose and N in relation to microbial growth strategies. Applied Soil 2008
Ecology, 37: 95-105. https://doi.org/10.1016/j.apsoil.2007.05.002 2009
Blagodatskaya, E., Yuyukina, T., Blagodatsky, S., Kuzyakov, Y. (2011). Three-source-partitioning 2010
of microbial biomass and of CO2 efflux from soil to evaluate mechanisms of priming effects. 2011
Soil Biology and Biochemistry, 43: 778–786. http://dx.doi.org/10.1016/j.soilbio.2010.12.011 2012
Boisier, J.P., Rondanelli, R., Garreaud, R.D., Muñoz, F. (2015). Anthropogenic and natural 2013
contributions to the southeast Pacific precipitation decline and recent megadrought in central 2014
Chile. Geophysical Research Letters 43(1): 413-421. https://doi.org/10.1002/2015GL067265 2015
91
Bore, E.K., Apostel, C., Halicki, S., Kuzyakov, Y., Dippold, MA. (2017). microbial metabolism in 2016
soil at subzero temperatures: adaptation mechanisms revealed by position-specific 13C labeling. 2017
Frontiers in Microbiology, 8: 946. https://doi.org/10.3389/fmicb.2017.00946 2018
Borken, W., Matzner, E. (2009). Reappraisal of drying and wetting effects on C and N 2019
mineralization and fluxes in soils. Global Change Biology, 15(4): 808–824. 2020
http://doi.org/10.1111/j.1365-2486.2008.01681.x 2021
Bölscher, T., Paterson, E., Freitag, T., Thornton, B., Herrmann, A.M. (2017). Temperature 2022
sensitivity of substrate-use efficiency can result from altered microbial physiology without 2023
change to community composition. Soil Biology and Biochemistry, 109: 59-69. 2024
https://doi.org/10.1016/j.soilbio.2017.02.005 2025
Boy, J. Godoy, R. Shibistova, O. Boy, D. McCulloch, R. Andrino de la Fuente, A. Aguirre, M. 2026
Mikutta, R. Guggenberger, G. (2016). Successional patterns along soil development gradients 2027
formed by glacier retreat in the Maritime Antarctic, King George Island. Revista Chilena de 2028
Historia Natural :89-106. http://doi.org/10.1186/s40693-016-0056-8 2029
Burns, R.G. (1982). Enzyme activity in soil: Location and a possible role in microbial ecology. 2030
Soil Biology and Biochemistry, 14(5): 423–427. https://doi.org/10.1016/0038-0717(82)90099-2031
2 2032
Bozkurt, D., Rojas, M., Bolsier, J.P., Valdivieso, J. (2017). Climate change impacts on 2033
hydroclimatic regimens and extremes over Andean basis in Central Chile. Hydrology and Earth 2034
System Sciences. Pre-print. https://doi.org/10.5194/hess-2016-690. 2035
Butterly, C.R., Armstrong, R.D., Chen, D. Tang, C. (2019). Residue decomposition and soil carbon 2036
priming in three contrasting soils previously exposed to elevated CO2. Biology and Fertility of 2037
Soils, 55:17–29. http://doi.org/10.1007/s00374-018-1321-6 2038
92
Calabi-Floody, M. Rumpel, C. Velásquez, G. Violante, A. Bol, R. Condron, L. M. & Mora, M.L. 2039
(2015). Role of Nanoclays in Carbon stabilization in Andisols and Cambisols. Journal of Soil 2040
Science and Plant Nutrition, 15(3): 587-604. (2015). http://dx.doi.org/10.4067/S0718-2041
95162015005000026 2042
Canarini, A., Djkstra, F.A. (2015). Dry-rewetting cycles regulate wheat carbon rhizodeposition, 2043
stabilization and nitrogen cycling. Biology and Fertility of Soils, 81: 195-203. 2044
https://doi.org//10.1016/j.soilbio.2014.11.014. 2045
Canarini, A. Kiær, L.P. Djkstra, F.A. (2017). Soil carbon loss regulated by drought intensity and 2046
available substrate: A meta-analysis. Soil Biology and Biochemistry, 112: 90-99. 2047
https://doi.org/10.1016/j.soilbio.2017.04.020 2048
Cao, E., Chen, Y., Cui, Z., Foster, P.R. (2003). Effect of freezing and thawing rates on denaturation 2049
of proteins in aqueous solutions. Biotechnology and Bioengineering, 82: 684–690. 2050
https://doi.org/10.1002/bit.10612 2051
Chenu, C., Hassink, J., Bloem, J. (2001). Short-term changes in the spatial distribution of 2052
microorganisms in soil aggregates as affected by glucose addition. Biology and Fertility of Soils, 2053
34: 349–356 (2001). https://doi.org/10.1007/s003740100419 2054
Christensen, B.T. (1992). Physical fractionation of soil and organic matter in primary particle size 2055
and density separates. In: Stewart B.A. (eds) Advances in Soil Science. Advances in Soil 2056
Science, vol 20. Springer, New York, pp 1-90. https://doi.org/10.1007/978-1-4612-2930-8_1 2057
CIREN. (2002). Estudio agrológico IX Región. Descripciones de suelos. Materiales y símbolos. 2058
Publicación CIREN N° 122 p. 360 p. Centro de Información de Recursos Naturales (CIREN), 2059
Santiago, Chile. 2060
CONAF - Corporación Nacional Forestal. (2002). Plan de manejo del Parque Nacional 2061
Nahuelbuta. Región de la Araucanía, Temuco. 2062
93
Conant, R.T., Drijber, R.A., Haddix, M.L., Parton, W.J., Paul, E.A., Plante, A.F., Six, J., Steinweg, 2063
J.M. (2008). Sensitivity of organic matter decomposition to warming varies with its quality. 2064
Global Change Biology, 14: 868–877. https://doi.org/10.1111/j.1365-2486.2008.01541.x 2065
Consetino, d., Chenu, C., Le Bissonnais, Y. (2006). Aggregate stability and microbial community 2066
dynamics under drying–wetting cycles in a silt loam soil. Soil Biology and Biochemistry, 38(8): 2067
2053-2062. https://doi.org/10.1016/j.soilbio.2005.12.022 2068
Corti, G., Ugolini, F.C., Agnelli, A., Certini, G., Cuniglio, R., Berna, F., Fernández Sanjurjo, M.J. 2069
(2002). The soil skeleton, a forgotten pool of carbon and nitrogen in soil. European Journal of 2070
Soil Science, 53: 283-298. http://doi.org/10.1046/j.1365-2389.2002.00442.x 2071
Craine, J., Fierer, N., McLauchlan, K. (2010). Widespread coupling between the rate and 2072
temperature sensitivity of organic matter decay. Nature Geoscience, 3: 854–857. 2073
https://doi.org/10.1038/ngeo1009 2074
Dalenberg, J.W., Jager, G. (1981). Priming effect of small glucose additions to 14C-labeled soil. 2075
Soil Biology and Biochemistry, 13: 219- 223. http://doi.org/10.1016/0038-0717(81)90024-9 2076
Daou, L., Perissol, C., Luglia, M., Calvert, V., Criquet, S. (2016). Effect of drying-wetting or 2077
freezing-thawing cycles on enzymatic activities of different Mediterranean soils. Soil Biology 2078
and Biochemistry, 93: 142-149. https://doi.org/10.1016/j.soilbio.2015.11.006 2079
Davidson, E.A., Janssens, I.A. (2006). Temperature sensitivity of soil carbon decomposition and 2080
feedbacks to climate change. Nature, 440: 165–173. http://doi.org/10.1038/nature04514 2081
de Nijs, E.A., Hicks, L.C., Leizeaga, A., Tietema, A., Rousk, J. (2019). Soil microbial moisture 2082
dependences and responses to drying-rewetting: the legacy of 18 years drought. Global Change 2083
Biology. 25: 1005–15. https://doi.org/10.1111/gcb.14508 2084
Denef, K., Six, J., Paustian, K., and Merckx, R. (2001a). Importance of macroaggregate dynamics 2085
in controlling soil carbon stabilization: Short-term effects of physical disturbance induced by 2086
94
dry-wet cycles. Soil Biology and Biochemistry, 33(15): 2145–2153. 2087
http://doi.org/10.1016/S0038-0717(01)00153-5 2088
Denef, K., Six, J., Bossuyt, H., Frey, S. D., Elliott, E. T., Merckx, R., and Paustian, K. (2001b). 2089
Influence of dry-wet cycles on the interrelationship between aggregate, particulate organic 2090
matter, and microbial community dynamics. Soil Biology and Biochemistry, 33: 1599–1611. 2091
http://doi.org/10.1016/S0038-0717(01)00076-1 2092
Deng, S.P., and Tabatabai, M.A. (1994). Cellulase activity of soils. Soil Biology and Biochemistry, 2093
26(10): 1347–1354. https://doi.org/10.1016/0038-0717(94)90216-X 2094
Derrien, D., Plain, C., Courty, P.-E., Gelhaye, L., Moerdijk-Poortvliet, T.C.W., Thomas, F., 2095
Versini, A., Zeller, B., Koutika, L.-S., Boschker, H.T.S., Epron, D. (2014). Does the addition of 2096
labile substrate destabilise old soil organic matter?. Soil Biology and Biochemistry, 76: 149–2097
160. http://dx.doi.org/10.1016/j.soilbio.2014.04.030 2098
Di Lonardo, D.P., De Boer, W., Klein Gunnewiek, P.J.A., Hannula, S.E., Van der Wal, A. (2017). 2099
Priming of soil organic matter: Chemical structure of added compounds is more important than 2100
the energy content. Soil Biology and Biochemistry, 108: 41–54. 2101
https://doi.org/10.1016/j.soilbio.2017.01.017 2102
Diehl, P., Mazzarino, M.J., Funes, F., Fontenla, S., Gobbi, M., Ferrari, J. (2003). Nutrient 2103
conservation strategies in native Andean-Patagonian forests. Journal of Vegetation Science, 14: 2104
63–70. https://doi.org/10.1658/1100-9233(2003)014[0063:NCSINA]2.0.CO;2 2105
Dorodnikov, M., Kuzyakov, Y., Fangmeier, A., Wiesenberg, G. (2011). C and N in soil organic 2106
matter density fractions under elevated atmospheric CO2: Turnover vs. Stabilization. Soil 2107
Biology and Biochemistry, 43: 579-589. https://doi.org/10.1016/j.soilbio.2010.11.026 2108
95
Doetterl, S., Stevens, A., Six, J., Merckx, R., Oost, K. Van, Pinto, M. C., Boeckx, P. (2015). Soil 2109
carbon storage controlled by interactions between geochemistry and climate. Nature 2110
Geoscience, 8(10): 780–783. http://doi.org/10.1038/NGEO2516. 2111
Dutta, T., Carles-Brangarí, A., Fernàndez-Garcia, D., Rubol, S., Tirado-conde, J., Sanchez-Vila, 2112
X., 2015. Vadose zone oxygen (O2) dynamics during drying and wetting cycles: Ann artificial 2113
recharge laboratory experiment. Journal of Hydrology, 527: 151-159. 2114
https://doi.org/10.1016/j.jhydrol.2015.04.048 2115
Edwards A.C., Cresser M.S. (1992) Freezing and Its Effect on Chemical and Biological Properties 2116
of Soil. In: Stewart B.A. (eds) Advances in Soil Science, 18. Springer, New York, NY. 2117
https://doi.org/10.1007/978-1-4612-2844-8_2 2118
Ellerbrock, R.H., and Kaiser, M. (2005). Stability and composition of different soluble soil organic 2119
matter fractions - Evidence from δ13C and FTIR signatures. Geoderma, 128: 28–37. 2120
https://doi.org/10.1016/j.geoderma.2004.12.025 2121
Elliott, E.T. (1986). Aggregate structure and carbon, nitrogen, and phosphorus in native and 2122
cultivated soils. Soil Science Society of America Journal, 50: 627-633. 2123
http://doi.org/10.2136/sssaj1986.03615995005000030017x 2124
Evans, S.E., Wallenstein, M.D. (2012). Soil microbial community response to drying and 2125
rewetting stress: does historical precipitation regime matter?. Biogeochemistry. 109: 101–116. 2126
https://doi.org/10.1007/s10533-011-9638-3 2127
Falvey, M., Garrreaud, R. (2009). Regional cooling in a warming world: Recent temperature trends 2128
in the southeast Pacific and along the west coast of subtropical South America (1979–2006). 2129
Journal of Geophysical Research Atmospheres 114(D4). 2130
https://doi.org/10.1029/2008JD010519 2131
96
Feng, X., Nielsen, L.L., and Simpson, M.J. (2007). Responses of soil organic matter and 2132
microorganisms to freeze-thaw cycles. Soil Biology and Biochemistry, 39(8): 2027–2037. 2133
https://doi.org/10.1016/j.soilbio.2007.03.003 2134
Fernandez, D.P., Neff, J.C. Belnap, J. Reynolds, R. (2006). Soil Respiration in the Cold Desert 2135
Environment of the Colorado Plateau (USA): Abiotic Regulators and Thresholds 2136
Biogeochemistry, 78: 247. http://doi.org/10.1007/s10533-005-4278-0 2137
Feron, S., Cordero, R.R., Damiani, A., Lianillo,P.J., Jorquera, J., Sepulveda, E., Asencio, V., 2138
Laroza, D., Labbe, F., Carrasco, J., Torres G. (2019). Observations and Projections of Heat 2139
Waves in South America. Sci Rep 9, 8173 (2019). https://doi.org/10.1038/s41598-019-44614-4 2140
Fierer, N., Schimel, J.P. (2002). Effects of drying±rewetting frequency on soil carbon and nitrogen 2141
transformations. Soil Biology and Biochemistry, 34: 777-787. https://doi.org/10.1016/S0038-2142
0717(02)00007-X 2143
Fontaine, S., Mariotti, A., Abbadie, L. (2003). The priming effect of organic matter: a question of 2144
microbial competition?. Soil Biology and Biochemistry, 35: 837–843. 2145
https://doi.org/10.1016/S0038-0717(03)00123-8 2146
Fontaine, S., Bardoux, G., Abbadie, L., Mariotti, A. (2004a). Carbon input to soil may decrease 2147
soil carbon content. Ecology Letters, 7: 314-320. https://doi.org/10.1111/j.1461-2148
0248.2004.00579.x 2149
Fontaine, S., Bardoux, G., Benest, D., Verdier, B., Mariotti, A., Abbadie, L. (2004b). Mechanisms 2150
of the Priming Effect in a Savannah Soil Amended with Cellulose. Soil Science of American 2151
Journal, 68: 125-131. https://doi.org/10.2136/sssaj2004.0125 2152
Fontaine, S., Barot, S. (2005). Size and functional diversity of microbe populations control plant 2153
persistence and long-term soil carbon accumulation. Ecology Letters, 8: 1075–1087. 2154
https://doi.org/10.1111/j.1461-0248.2005.00813.x 2155
97
Fontaine, S. Barot, S. Barré, P. Bdioui, N. Mary, B. Rumpel. C. (2007). Stability of organic carbon 2156
in deep soil layers controlled by fresh carbon supply. Nature, 450 (7167): 277-280. 2157
http://doi.org/10.1038/nature06275 2158
Fontaine, S., Henault, C., Aamor, A., Bdioui, N., Bloor, J.M.G., Maire, V., Nary, B., Revaillot, S., 2159
Maron, P. (2011). Fungi mediate long term sequestration of carbon and nitrogen in soil through 2160
their priming effect. Soil Biology and Biochemistry, 43: 86–96. 2161
https://doi.org/10.1016/j.soilbio.2010.09.017 2162
Frank, D. Reichstein, M. Bahn, M. Thonicke, K. Frank, Machena M.D., Smith, P., van der Velde, 2163
M., Vicca, S., Babst, F., Beer, C., Buchmann, N., Canadell., J.G., Ciais, P., Cramer, W., Ibrom, 2164
A., Miglietta, F., Poulter, B., Ramming, A., Seneviratne, S.I., Walz, A., Wattenbach, M., Zavala, 2165
M.A., Zscheischler, J. (2015). Effects of climate extremes on the terrestrial carbon cycle: 2166
concepts, processes and potential future impacts. Research review. Global Change Biology, 21: 2167
2861-2880. http://doi.org/10.1111/gcb.12916. 2168
Frankenberger, W.T., and Johanson, J.B. (1982). Effect of pH on enzyme stability in soils. Soil 2169
Biology and Biochemistry, 14(5): 433–437. https://doi.org/10.1016/0038-0717(82)90101-8. 2170
Freppaz, M., Williams, B.L., Edwards, A.C., Scalenghe, R., Zanini, E. (2007). Simulating soil 2171
freeze/thaw cycles typical of winter alpine conditions: Implications for N and P availability, 2172
Applied Soil Ecology 35: 247–255. http://doi.org/10.1016/j.apsoil.2006.03.012 2173
Gale, W.J., Cambardella, C.A., Bailey, T.B. (2000). Root-derived carbon and the formation and 2174
stabilization of aggregates. Soil Science of American Journal, 64: 201-207. 2175
https://doi.org/10.2136/sssaj2000.641201x 2176
Garcia-Pausas, J., Paterson, E. (2011). Microbial community abundance and structure are 2177
determinants of soil organic matter mineralization in the presence of labile carbon. Soil Biology 2178
and Biochemistry, 43 (8): 1705-1713. http://doi.org/ 10.1016/j.soilbio.2011.04.016 2179
98
Garrido, E. and Matus, F. (2012). Are organo-mineral complexes and allophane content 2180
determinant factors for the carbon level in Chilean volcanic soils?. Catena, 92: 106-112. 2181
http://doi.org/10.1016/j.catena.2011.12.003 2182
Garreaud, R., C. Alvarez-Garreton, J. Barichivich, J. P. Boisier, D. A. Christie, M. Galleguillos, C. 2183
Le Quesne, J. McPhee, and M. Zambrano-Bigiarini. (2017). The 2010–2015 mega drought in 2184
Central Chile: impacts on regional hydroclimate and vegetation. Hydrology Earth System 2185
Science discussios, 21: 6307–6327. https://doi.org/10.5194/hess-2017-191 2186
Goldberg, S.D. Muhr, J. Borken, W. and Gebauer, G. (2008). Fluxes of climate-relevant trace gases 2187
between a Norway spruce forest soil and atmosphere during repeated freeze-thaw cycles in 2188
mesocosms, Journal of Soil Science and Plant Nutrition, 171: 729–739. http://doi.org/ 2189
10.1002/jpln.200700317 2190
Gregorich, E.G., Beare, M.H., McKim, U.F., Skjemstad, J.O. (2006). Chemical and Biological 2191
Characteristics of Physically Uncomplexed Organic Matter. Soil Science Society of America 2192
Journal, 70: 975-985. https://doi.org/10.2136/sssaj2005.0116 2193
Guenet, B., Danger, M., Abbadie, L., Lacroix, G. (2010). Priming effect: bridging the gap between 2194
terrestrial and aquatic ecology. Ecology, 91: 2850–2861. https://doi.org/10.1890/09-1968.1 2195
Guggenberger, G., Frey, S. D., Six, J., Paustian, K., and Elliott, E. T. (1999). Bacterial and Fungal 2196
Cell-Wall Residues in Conventional and No-Tillage Agroecosystems. Soil Science Society of 2197
America Journal, 63(5): 1188. https://doi.org/10.2136/sssaj1999.6351188x 2198
Gunina, A. and Kusyakov, Y. (2014). Pathways of litter C by formation of aggregates and SOM 2199
density fractions: Implications from 13C natural abundance. Soil Biology and Biochemistry, 71: 2200
95-104. https://doi.org/10.1016/j.soilbio.2014.01.011 2201
99
Guntiñas, M.E., Gil-Sotres, F., Leirós, M.C., Trasar-Cepeda, C. (2013). Sensitivity of soil 2202
respiration to moisture and temperature. Journal of Soil Science and Plant Nutrition, 13: 445-2203
461. http://dx.doi.org/10.4067/S0718- 95162013005000035 2204
Hajiboland, R. (2014). Chapter 1 - Reactive Oxygen Species and Photosynthesis, Editor(s): Parvaiz 2205
Ahmad, Oxidative Damage to Plants, Academic Press, 1-63. https://doi.org/10.1016/B978-0-2206
12-799963-0.00001-0. 2207
Hartley, I.P., Heinemeyer, A., Ineson, P. (2007). Effects of three years of soil warming and shading 2208
on the rate of soil respiration: substrate availability and not thermal acclimation mediates 2209
observed response. Global Change Biology, 13(8): 1761–1770. https://doi.org/10.1111/j.1365-2210
2486.2007.01373.x 2211
Hendricks, C. W., Doyle, J. D., Hugley, B. (1995). A new solid medium for enumerating cellulose-2212
utilizing bacteria in soil. Applied and environmental microbiology, 61(5): 2016–2019. 2213
https://doi.org/10.1128/AEM.61.5.2016-2019.1995 2214
Hibbard, K.A., Law, B.E., Reichstein, M., Sulzman, J. (2005). An analysis of soil respiration across 2215
northern hemisphere temperate ecosystems. Biogeochemistry, 73: 29–70. 2216
https://doi.org/10.1007/s10533-004-2946-0 2217
Houghton, J.T., Jenkins, G.J., Ephraums, J.J. (Eds.). (1990). Climate Change: The IPCC Scientific 2218
Assessment. Cambridge University Press, Cambridge, UK. 2219
IPCC, 2013: Climate Change (2013): The Physical Science Basis. Contribution of Working Group 2220
I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, 2221
T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and 2222
P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New 2223
York, NY, USA, 1535 pp. 2224
100
IUSS Working Group WRB, (2015). World reference base for soil resources 2014: International 2225
soil classification system for naming soils and creating legends for soil maps. Update 2015. 2226
World soil resources reports 106, Rome, 191 pp. 2227
Jagadamma, S., Mayes, M., Steinweg, J.M., Schaeffer, S.M. (2014). Substrate quality alters the 2228
microbial mineralization of added substrate and soil organic carbon. Biogeosciences, 11: 4665-2229
4678. https://doi.org/10.5194/bg-11-4665-2014 2230
Jarvis, P., Rey, A., Petsikos, C., Wingate, L., Rayment, M., Pereira, J., Banza, J., David, J., 2231
Miglietta, F., Borghetti, M., Manca, G., Valentini, R. (2007). Drying and wetting of 2232
Mediterranean soils stimulates decomposition and carbon dioxide emission: the "Birch effect." 2233
Tree Physiology, 27: 929–940. https://doi.org/10.1093/treephys/27.7.929 2234
Jenkinson, D.S., Fox, R.H., Rayner, J.H. (1985). Interactions between fertilizer nitrogen and soil 2235
nitrogen-the so-called ‘priming’ effect. European Journal of Soil Science, 36(3): 425-44. 2236
https://doi.org/10.1111/j.1365- 2389.1985.tb00348.x 2237
Jha, D.K., Sharma, G.D., and Mishra, R.R. (1992). Soil microbial population numbers and enzyme 2238
activities in relation to altitude and forest degradation. Soil Biology and Biochemistry, 24(8): 2239
761–767. https:/doi.org/10.1016/0038-0717(92)90250-2 2240
Jones, D.L., Cooledge, E.C., Hoyle F.C., Griffiths, R.I., Murphy, D.V. (2019). pH and 2241
exchangeable aluminum are major regulators of microbial energy flow and carbon use 2242
efficiency in soil microbial communities. Soil Biology and Biochemistry, 138: 107584. 2243
https://doi.org/10.1016/j.soilbio.2019.107584 2244
Kargul, T., Wielgosz, E., Falkus, J. (2015). Application of Thermal Analysis Tests Results in the 2245
Numerical Simulations of Continuous Casting Process. Archives of Metallurgy and Materials, 2246
60: 221- 225. http://doi.org/10.1515/amm-2015-0035 2247
101
Kemmitt, S.J. Wright, D. Murphy, D.V. Jones, D.L. (2008). Regulation of amino acid 2248
biodegradation in soil as affected by depth. Biology and Fertility of Soils, 44: 933-941. 2249
http://doi.org/10.1007/s00374-008-0278-2. 2250
Kim, D.G. Vargas, R. Bond-Lamberty, B. and Turetsky, M.R. (2012). Effects of soil rewetting and 2251
thawing on soil gas fluxes: A review of current literature and suggestions for future research. 2252
Biogeosciences, 9(7): 2459–2483. http://doi.org/10.5194/bg-9-2459-2012 2253
Koponen, H.T., Bååth, E. (2016). Soil bacteria growth after a freezing/thawing event. Soil Biology 2254
and Biochemistry, 100: 229-232. https://doi.org/10.1016/j.soilbio.2016.06.029 2255
Kucerik, J., Tokarrski, D., Damyan, M.S., Merbach, I., Siewer, C. (2018). Linking soil organic 2256
matter thermal stability with contents of clay, bound water, organic carbon, and nitrogen. 2257
Geoderma, 316: 38-46. https://doi.org/10.1016/j.geoderma.2017.12.001 2258
Kuzyakov, Y., Friedel, J.K., Stahr, K. (2000). Review of mechanisms and quantification of priming 2259
effects. Soil Biology and Biochemistry, 32: 1485–1498. https://doi.org/10.1016/S0038-2260
0717(00)00084-5 2261
Kuzyakov, Y. and Gavrichkova, O. (2010). REVIEW: Time lag between photosynthesis and 2262
carbon dioxide efflux from soil: a review of mechanisms and controls. Global Change Biology, 2263
16(12): 3386-3406. http://doi.org/10.1111/j.1365-2486.2010.02179.x 2264
Lal, R. (2004). Soil Carbon Sequestration Impacts on Global Climate Change and Food Security. 2265
Science, 304 (5677): 1623-1627. http://doi.org/10.1126/science.1097396 2266
Lawrence, C.R. Harden, J.W. Xu, X. Schulz, M.S. & Trumbore, S.E. (2015). Long-term controls 2267
on soil organic carbon with depth and time: A case study from the Cowlitz River 2268
Chronosequence, WA USA. Geoderma, 247-248: 73–87. 2269
http://doi.org/10.1016/j.geoderma.2015.02.005 2270
102
Leizeaga, A., Hicks, L.C., Manoharan, L., Hawkes, C.V., Rousk, J. (2020). Drought legacy affects 2271
microbial community trait distributions related to moisture along a savannah grassland 2272
precipitation gradient. Journal of Ecology. Early view. https://doi.org/10.1111/1365-2273
2745.13550 2274
Liu, X.-J.A., Sun, J., Mau, R.L., Finley, B.K., Compson, Z.G., van Gestel, N., Brown, J.R., 2275
Schwartz, E., Dijkstra, P., Hungate, B.A. (2017). Labile carbon input determines the direction 2276
and magnitude of the priming effect. Applied Soil Ecology 109: 7–13. 2277
https://doi.org/10.1016/j.apsoil.2016.10.002 2278
Liu, X-J.A., Finley, B.K., Mau, R.L., Schwartz, E., Dijkstra, P., Bowker, M.A., Hungate, B.A. 2279
(2020). The soil priming effect: consistent across ecosystems, elusive mechanisms. Soil Biology 2280
and Biochemistry, 140: 107617. https://doi.org/10.1016/j.soilbio.2019.107617 2281
Magid, J., Kjærgaard, C. (2001). Recovering decomposing plant residues from the particulate soil 2282
organic matter fraction: Size versus density separation. Biology and Fertility of Soils, 33: 252–2283
257. https://doi.org/10.1007/s003740000316 2284
Manson-Jones, K., Schmücker, N., Kuzyakov, Y. (2018). Contrasting effects of organic and 2285
mineral nitrogen challenge the N-mining hypothesis for soil organic matter priming. Soil 2286
Biology and Biochemistry 124: 38-46. https://doi.org/10.1016/j.soilbio.2018.05.024 2287
Manzoni, S. Schimel, J.P., Porporato, A. (2012). Responses of soil microbial communities to water 2288
stress: results from a meta-analysis. Ecology, 93(4): 930-938. https://doi.org/10.1890/11-0026.1 2289
Martins JP, Zunino H, Peirano P, Caiozzi M (1982). Decomposition of 14C-labeled lignin, model 2290
humic acid polymers, and fungal melanins in allophanic soils. soil biology and biochemistry, 2291
14: 289–293. https://doi.org/10.1016/0038-0717(82)90039-6 2292
103
Matzner E., Borken, W. (2008). Do freeze-thaw events enhance C and N losses from soils of 2293
different ecosystems? A review. European Journal of Soil Science, 59: 274–284. 2294
https://doi.org/10.1111/j.1365-2389.2007.00992.x 2295
Matus, F. (2021). Fine silt and clay content is the main factor defining maximal C and N 2296
accumulations in soils: A meta-analysis. Scientific Reports: 11: 1-17 doi.org/10.1038/s41598-2297
021-84821-6. 2298
Matus, F., Lusk, H., Maire, C. (2008). Effects of Soil Texture, Carbon Input Rates, and Litter 2299
Quality on Free Organic Matter and Nitrogen Mineralization in Chilean Rain Forest and 2300
Agricultural Soils. Communications in Soil Science and Plant Analysis, 39: 187-201. 2301
https://doi.org/10.1080/00103624.2017.1395447 2302
Meisner, A., Rousk, J., Bååth, E. (2015). Prolonged drought changes the bacterial growth response 2303
to rewetting. Soil Biology and Biochemistry, 88: 314–322. 2304
https://doi.org/10.1016/j.soilbio.2015.06.002 2305
Meisner, A., Snoek, B.L., Nesme, J., Dent, E., Jacquiod, S., Classen, A.T., Priemé, A. (2021). Soil 2306
microbial legacies differ following drying-rewettingand freezing-thawing cycles. The ISME 2307
Journal, 15: 1207–1221. https://doi.org/10.1038/s41396-020-00844-3 2308
Merino, C. Nannipieri, P. & Matus, F. (2015). Soil carbon controlled by plant, microorganism and 2309
mineralogy interactions. Journal of soil science and plant nutrition, 15(2): 321-332. 2310
http://dx.doi.org//10.4067/S0718-95162015005000030 2311
Merino, C., Fontaine, S., Palma, G., Matus, F. (2017). Effect of aluminum on mineralization of 2312
water extractable organic matter and microbial respiration in southern temperate rainforest soils. 2313
European Journal of Soil Biology, 82: 56–65. https://doi.org/10.1016/j.ejsobi.2017.08.003 2314
104
Mikha, M.M., Rice, C.W., Milliken, G.A. (2005). Carbon and nitrogen mineralization as affected 2315
by drying and wetting cycles. Soil Biology and Biochemistry, 37: 339-347. 2316
https://doi.org/10.1016/j.soilbio.2004.08.003 2317
Mikutta, R. Kleber, M. Torn, M.S. & Jahn, R. (2006). Stabilization of soil organic matter: 2318
association with minerals or chemical recalcitrance?. Biogeochemistry, 77: 25-56. 2319
http://doi.org/10.1007/s10533-005-0712-6. 2320
Miura, M., Jones, T.G., Hill, P.W., Jones, D.L. (2019). Freeze-thaw and dry-wet events reduce 2321
microbial extracellular enzyme activity, but not organic matter turnover in an agricultural 2322
grassland soil. Short communication. Applied Soil Ecology, 144: 196-199. 2323
https://doi.org/10.1016/j.apsoil.2019.08.002 2324
Mondini, C., Cayuela, M.L., Sanchez-Monedero, M.A., Roig, A., Brookes, P.C. (2006). Soil 2325
microbial biomass activation by trace amounts of readily available substrate. Biology and 2326
Fertility of Soils, 42: 542–549. https://doi.org/10.1007/s00374-005-0049-2 2327
Muñoz, C., Cruz, B., Rojo, F., Campos, J., Casanova, M., Doetterl, S., Boeckx, P., Zagal, E. (2016). 2328
Temperature sensitivity of carbon decomposition in soil aggregates along a climatic gradient. 2329
Journal of Soil Science and Plant Nutrition, 16: 461-476. http://dx.doi.org/10.4067/S0718-2330
95162016005000039 2331
Muyzer G, Smalla K. (1998). Application of denaturing gradient gel electrophoresis (DGGE) and 2332
temperature gradient gel electrophoresis (TGGE) in microbial ecology, Antonie Van 2333
Leeuwenhoek, 73: 127–14. https://doi.org/10.1023/A:1000669317571 2334
Najera, F., Dippold, M.A., Boy, J. Seguel, O., Koester, M., Stock, S., Merino, C., Kuzyakov, Y., 2335
Matus, F. (2020). Effects of drying/rewetting on soil aggregate dynamics and implications for 2336
organic matter turnover. Biology and Fertility of Soils, 56: 893–905. 2337
https://doi.org/10.1007/s00374-020-01469-6 2338
105
Oades, J.M. (1984). Soil organic matter and structural stability: mechanisms and implications for 2339
management. Plant and Soil, 76 (1-3): 319-337. http://doi.org/10.1007/BF02205590 2340
Oades, J.M. (1988). The retention of organic matter in soils. Biogeochemistry, 5(1): 35–2341
70. https://doi.org/10.1007/bf02180317 2342
Oeser, R., Stroncik, N., Moskwa, L., Bernhard, N., Schaller, M., Canessa, R., van den Brink, L., 2343
Köster, M., Brucker, E., Stock, S., Fuentes, J.P., Godoy, R., Matus, F., Oses, R., Osses, P., 2344
Paulino, L., Seguel, O., Bader, M.Y., Boy, J., Dippold, M., Ehlers, T., Kühn, P., Kuzyakov, Y., 2345
Leinweber, P., Scholten, T., Spielvogel, S., Spohn, M., Übernickel, K., Tielbörger, K., Wagner, 2346
D., von Blanckenburg, F. (2018). Chemistry and microbiology of the Critical Zone along a steep 2347
climate and vegetation gradient in the Chilean Coastal Cordillera. Catena, 170: 183–203. 2348
https://doi.org/10.1016/j.catena.2018.06.002 2349
Ontl, T.A. Cambardella, C.A. Schulte, L.A. & Kolka, R.K. (2015). Factors influencing soil 2350
aggregation and particulate organic matter responses to bioenergy crops across a topographic 2351
gradient. Geoderma, 255-256: 1–11. http://doi.org/10.1016/j.geoderma.2015.04.016 2352
Orth, A.B., Tien, M. (1995). Biotechnology of lignin degradation. Genetics and Biotechnology, 2353
Springer Berlin Heidelberg, Berlin, Heidelberg 287-302, 10.1007/978-3-662-10364-7_17 2354
Oztas, T., Fayetorbay, F. (2003). Effect of freezing and thawing processes on soil aggregate 2355
stability. Catena, 52: 1–8. http://doi.org/10.1016/S0341-8162(02)00177-7 2356
Plante, A.F. Six, J. Paul, E.A. & Conant, R.T. (2009). Does Physical Protection of Soil Organic 2357
Matter Attenuate Temperature Sensitivity?. Soil Science Society of America Journal, 73(4): 2358
1168. http://doi.org/10.2136/sssaj2008.0351 2359
Park, E.J., Sul, W.J., Smucker, A.J.M. (2007). Glucose additions to aggregates subjected to 2360
drying/wetting cycles promote carbon sequestration and aggregate stability. Soil Biology and 2361
Biochemistry, 39: 2758-2768. https//doi.org// 10.1016/j.soilbio.2007.06.007 2362
106
Pardini, G., Guidini, G., Pini, R., Regüés, D., Gallart, F. (1996). Structure and porosity of smectitic 2363
mudrocks as affected by experimental wetting—drying cycles and freezing-thawing cycles. 2364
Catena, 27: 149-165. https://doi.org/10.1016/0341-8162(96)00024-0 2365
Poeplau C., Don A., Six J., Kaiser M., Benbi D., Chenu C., Cotrufo M.F., Derrien D., Gioacchini 2366
P., Grand S., Gregorich E., Griepentrog M., Gunina A., Haddix M., Kuzyakov Y., Kühnel A., 2367
Macdonald L.M., Soong J., Trigalet S., Vermeire M.L., Rovira P., van Wesemael B., Wiesmeier 2368
M., Yeasmin S., Yevdokimov I., Nieder R. (2018). Isolating organic carbon fractions with 2369
varying turnover rates in temperate agricultural soils – A comprehensive method comparison. 2370
Soil Biology and Biochemistry, 125: 10-26. https://doi.org/10.1016/j.soilbio.2018.06.025 2371
Poll, C., Pagel, H., Devers-Lamrani, M., Martin-Laurent, F., Ingwersen, J., Streck, T., Kandeler, 2372
E. (2010). Regulation of bacterial and fungal MCPA degradation at the soil-litter interface. Soil 2373
Biology and Biochemistry, 42: 1879-1887. https://doi.org/10.1016/j.soilbio.2010.07.013 2374
Qiao, Y., Wang, J., Liang, G., Du, Z., Zhou, J., Zhu, C., Huang, K., Zhou, X., Luo, Y., Yan, L., 2375
Xia, J. (2019). Global variation of soil microbial carbon-use efficiency in relation to growth 2376
temperature and substrate supply. Scientific Reports, 9: 5621. https://doi.org/10.1038/s41598-2377
019-42145-6 2378
Rasmussen, C. Southard, R.J. Horwath, W.R. (2006). Mineral control of organic carbon 2379
mineralization in a range of temperate conifer forest soils. Global Change Biology, 12: 834–2380
847. http://doi.org/10.1111/j.1365-2486.2006.01132.x. 2381
Rasmussen, C. Southard, R.J. Horwath, W.R. (2007). Soil Mineralogy Affects Conifer Forest Soil 2382
Carbon Source Utilization and Microbial Priming. Soil Science Society of American Journal, 2383
71: 1141. http://doi.org/10.2136/sssaj2006.0375. 2384
107
Schimel, J.P., Mikan, C. (2005). Changing microbial substrate use in Arctic tundra soils through a 2385
freeze-thaw cycle. Soil Biology and Biochemistry, 37: 1411-1418. 2386
http://doi.org/10.1016/j.soilbio.2004.12.011 2387
Schimel, J., Balser, T., Wallenstein, M. (2007). Microbial stress-response physiology and its 2388
implications for ecosystem function. Ecology 88: 1386–1394. https://doi.org/10.1890/06-0219 2389
Schmidt, M.W.I. Torn, M.S. Abiven, S. Dittmar, T. Guggenberger, G. Janssens, I.A. Kleber, M. 2390
Kogel-Knabner, I. Lehmann, J. Manning, D.A.C. Nannipieri, P. Rasse, D.P. Weiner, S. 2391
Trumbore, S.E. (2011). Persistence of soil organic matter as an ecosystem property. Nature 2392
478: 49–56. http://doi.org/10.1038/nature10386. 2393
Semenov, V. M., Kogut, B. M., Lukin, S. M. (2014). Effect of repeated drying-wetting-freezing-2394
thawing cycles on the active soil organic carbon pool. Eurasian Soil Science, 47(4): 276–286. 2395
https://doi.org/10.1134/s1064229314040073 2396
Shahbaz, M., Kuzyakov, Y., Sanaullah, M., Heitkamp, F., Zelenev, V., Kumar, A., Blagodatskaya, 2397
E. (2017). Microbial decomposition of soil organic matter is mediated by quality and quantity 2398
of crop residues: mechanisms and thresholds. Soil Biology and Biochemistry, 53: 287-301. 2399
https://doi.org/10.1007/s00374-016-1174-9 2400
Shahbaz, M., Kumar, A., Kuzyakov, Y., Börjesson, G., Blagodatskaya, E. (2018). Priming effect 2401
induced by glucose and decaying plant residues on SOM decomposition: a three-source 13C/14C 2402
partition study. Soil Biology and Biochemistry, 121: 138-146. 2403
https://doi.org/10.1016/j.soilbio.2018.03.004 2404
Shi, Z. Thomey, M.L. Mowll, W. Litvak, M. Brunsell, N.A. Collins, S.L., Pockman, W.T., Smith, 2405
M.D., Knapp, A.K., Luo, Y. (2014). Differential effects of extreme drought on production and 2406
respiration: Synthesis and modeling analysis. Biogeosciences, 11(3): 621–633. 2407
http://doi.org/10.5194/bg-11-621-2014 2408
108
Siewert, C. (2010). Rapid Screening of Soil Properties using Thermogravimetry. Soil Science 2409
Society of America Journal, 68(5): 1656. https://doi.org/10.2136/sssaj2004.1656 2410
Sillanpää, M., and Webber, L. R. (1961). The Effect Of Freezing-Thawing And Wetting-Drying 2411
Cycles On Soil Aggregation. Canadian Journal of Soil Science, 41(2): 182–187. 2412
https://doi.org/10.4141/cjss61-024 2413
Sinsabaugh, R. L. (1994). Enzymic analysis of microbial pattern and process. Biology and Fertility 2414
of Soils, 17: 69-74. https://doi.org/10.1007/BF00418675 2415
Sinsabaugh, R.L., Hill, B.H., Follstad Shah, J.J. (2009). Exoenzymatic stoichiometry of microbial 2416
organic nutrient acquisition in soil and sediment. Nature, 462(7274): 795–798. 2417
https://doi.org/10.1038/nature08632 2418
Sierra, C.A. Müller, M. and Trumbore, S.E. (2012). Models of soil organic matter decomposition: 2419
The SoilR package, version 1.0, Geoscientific Model Development, 5(4): 1045–1060. 2420
http://doi.org/10.5194/gmd-5-1045-2012 2421
Sistla, S.A., Schimel, J.P. (2013). Seasonal patterns of microbial extracellular enzyme activities in 2422
an arctic tundra soil: Identifying direct and indirect effects of long-term summer warming. Soil 2423
Biology and Biochemistry, 66: 119-129. https://doi.org/10.1016/j.soilbio.2013.07.003 2424
Six, J., Elliott, E.T., Paustian, K. (2000). Soil macroaggregate turnover and microaggregate 2425
formation: A mechanism for C sequestration under no-tillage agriculture. Soil Biology and 2426
Biochemistry, 32: 2099–2103. https://doi.org/10.1016/S0038-0717(00)00179-6 2427
Six, J., Contant, R.T., Paul, A., Paustian, K. (2002). Stabilization mechanisms of soil organic 2428
matter: Implications for C-saturation of soils. Plant and Soil, 241: 155-176. 2429
https://doi.org/10.1023/A:1016125726789 2430
109
Six, J. Bossuyt, H. degryze, S. and Denef, K. (2004). Review: A history of research on the link 2431
between (micro)aggregates, soil biota, and soil organic matter dynamics. Soil & Tillage 2432
Research, 79: 7-31. http://doi.org/10.1016/j.still.2004.03.008. 2433
Six, J. & Paustian, K. (2014). Aggregate-associated soil organic matter as an ecosystem property 2434
and a measurement tool. Soil Biology and Biochemistry, 68: A4-A9. 2435
http://dx.doi.org/10.1016/j.soilbio.2013.06.014. 2436
Skogland, T., Lomeland, S., GoksØyr, J. (1988). Respiratory burst after freezing and thawing of 2437
soil: Experiments with soil bacteria. Soil Biology and Biochemistry, 20(6): 851-856. 2438
https://doi.org/10.1016/0038-0717(88)90092-2 2439
Skujins J. (1976) Extracellular enzymes in soil. CRC, Critical Reviews of Microbiology, 4(4): 383-2440
421. https://doi.org/10.3109/10408417609102304 2441
Smith-Ramírez, C., Armesto, J. J., & Valdovinos, C. (2005). Historia, biodiversidad y 2442
ecología de los bosques costeros de Chile. Editorial Universitaria. 2443
Soil Survey Staff. (2014). Keys to Soil Taxonomy, Twelfth Edition - NRCS – USDA. 2444
Sollins, P. Homann, P., Caldwell, B.A. (1996). Stabilization and destabilization of soil organic 2445
matter: Mechanisms and controls. Geoderma, 74(1-2): 65–105. http://doi.org/10.1016/S0016-2446
7061(96)00036-5 2447
Song, Z. Müller, K. & Wang, H. (2014). Biogeochemical silicon cycle and carbon sequestration in 2448
agricultural ecosystems. Earth-Science Review. 139: 268-278. 2449
http://doi.org/10.1016/j.earscirev.2014.09.009 2450
Song, Y. Zou, Y. Wang, G. Yu, X. (2017). Altered soil carbon and nitrogen cycles due to the freeze-2451
thaw effect: A meta-analysis. Soil Biology and Biochemistry, 109: 35-49. 2452
https://doi.org/10.1016/j.soilbio.2017.01.020 2453
110
Sørensen, P. O., Finzi, A. C., Giasson, M. A., Reinmann, A. B., Sanders-DeMott, R., Templer, P. 2454
H. (2018). Winter soil freeze-thaw cycles lead to reductions in soil microbial biomass and 2455
activity not compensated for by soil warming. Soil Biology and Biochemistry, 116: 39–47. 2456
https://doi.org/10.1016/j.soilbio.2017.09.026 2457
Spohn M, Chodak M (2015) Microbial respiration per unit biomass increases with carbon-to-2458
nutrient ratios in forest soils. Soil Biology and Biochemistry, 81: 128–133. 2459
https://doi.org/10.1016/j.soilbio.2014.11.008 2460
Stock, S.C., Köster, M., Dippold, M. A., Nájera, F., Matus, F., Merino, C., Boy, J., Spielvogel, S., 2461
Gorbushina, A., Kuzyakov, Y. (2019). Environmental drivers and stoichiometric constraints on 2462
enzyme activities in soils from rhizosphere to continental scale. Geoderma, 337: 973–982. 2463
https://doi.org/10.1016/j.geoderma.2018.10.030 2464
Stockmann, U. Adams, M.A. Crawford, J.W. Field, D.J. Henakaarchchi, N, Jenkins, M. Minasny, 2465
B. McBratney, A.B. de Remy de Courcelles, V. Singh, K. Wheeler, I. Abbott, L. Angers, D.A. 2466
Baldock, J. Bird, M. Brookes, P.C. Chenu, C. Jastrow, J.D. Lal, R. Lehmann, J. O'Donnell, A.G. 2467
Parton, W.J. Whitehead, D. Zimmermann, M. (2013). Review: The knowns, known unknowns 2468
and unknowns of sequestration of soil organic carbon. Agriculture, Ecosystems and 2469
Environment, 164: 80–99. http://doi.org/10.1016/j.agee.2012.10.001 2470
Stolpe N, Undurraga P. 2016. Long term climatic trends in Chile and effects on soil moisture and 2471
temperature regimes. Chilean journal of Agricultural Research, 76(4): 487-496. 2472
https://dx.doi.org/10.4067/S0718-58392016000400013 2473
Su, X., Su, X., Zhou, G., Du, Z., Yang, S., Ni, M., Qin, H., Huang, Z., Zhou, X., Deng, J. (2020). 2474
Drought accelerated recalcitrant carbon loss by changing soil aggregation and microbial 2475
communities in a subtropical forest, Soil Biology and Biochemistry 48: 107898. 2476
https://doi.org/10.1016/j.soilbio.2020.107898. 2477
111
Takiri, M., Wild, B., Schnecker, J., Mooshammer, M., Knoltscha, A., Lashchinskiy, N., Eloy 2478
Alves, R.J., Gentsch, N., Gittel; A., Mikutta, R., Wanek, W., Richtera, A. (2018). Soil organic 2479
matter quality exerts a stronger control than stoichiometry on microbial substrate use efficiency 2480
along a latitudinal transect. Soil Biology and Biochemistry, 121: 212-220. 2481
http://doi.org/10.1016/j.soilbio.2018.02.022 2482
Tecon, R., Or, D. (2017). Biophysical processes supporting the diversity of microbial life in soil. 2483
FEMS Microbiology Reviews, 41(5): 599–623. https://doi.org/10.1093/femsre/fux039 2484
Tian J., Pausch J., Yu G., Blagodatskaya E., Gao Y., Kuzyakov Y. (2015). Aggregate size and their 2485
disruption affect 14C-labeled glucose mineralization and priming effect. Applied Soil Ecology. 2486
90: 1-10. https://doi.org/10.1016/j.apsoil.2015.01.014 2487
Tian, P., Mason-Jones, K., Liu, S., Wang, Q., Sun, T. (2019). Form of nitrogen deposition affects 2488
soil organic matter priming by glucose and cellulose. Biology and Fertility of Soils, 55: 383–2489
391. https://doi.org/10.1007/s00374-019-01357-8 2490
Tisdall, J.M. and Oades, J.M. (1982). Organic matter and water-stable aggregates in soils. Journal 2491
of Soil Science, 33: 141–163. http://doi.org/10.1111/j.1365 2492
Turner, B.L., Romeo, T.E. (2010). Stability of hydrolytic enzyme activity and microbial 2493
phosphorous during storage of tropical rain forest soils. Soil Biology and Biochemistry, 42: 459-2494
465. https://doi.org/10.1016/j.soilbio.2009.11.029 2495
Trumbore, S. (2009). Radiocarbon and Soil Carbon Dynamics. Annual Review of Earth and 2496
Planetary Sciences, 37(1): 47–66. http://doi.org/10.1146/annurev.earth.36.031207.124300 2497
Unger, S. Máguas, C. Pereira, J. S. David, T. S., Werner, C. (2010). The influence of precipitation 2498
pulses on soil respiration e Assessing the "Birch effect" by stable carbon isotopes. Soil Biology 2499
and Biochemistry. 42(10): 1800–1810. http://doi.org/10.1016/j.soilbio.2010.06.019 2500
112
Urrutia-Jalabert, R., Gonzalez, M.E., Gonzalez-Reyes, A., Lara, A., Garreaud, R. (2018). Climate 2501
variability and forest fires in central and south-central Chile. Ecosphere, 9(4): e02171. 2502
https://doi.org/10.1002/ecs2.2171 2503
Vance, E.D., Brookes, P.C., Jenkinson, D.S. (1987a). Microbial biomass measurements in forest 2504
soils: the use of the chloroform fumigation-incubation method in strongly acid soils. Soil 2505
Biology and Biochemistry, 19: 697–702. https://doi.org/10.1016/0038-0717(87)90050-2 2506
Vance, E.D., Brookes, P.C., Jenkinson, D.S. (1987b). An extraction method for measuring soil 2507
microbial biomass C. Soil Biology and Biochemistry, 19: 703–707. 2508
https://doi.org/10.1016/0038- 0717(87)90052-6 2509
Vargas, R., Detto, M., Baldocchi, D.D., Allen, M.F. (2010), Multiscale analysis of temporal 2510
variability of soil CO2 production as influenced by weather and vegetation. Global Change 2511
Biology, 16: 1589–1605. https://doi.org/10.1111/j.1365-2486.2009.02111.x 2512
Vicca, S., Bahn, M., Estiarte, M., van Loon, E.E., Vargas, R., Alberti, G., Ambus, P., Arain, M.A., 2513
Beier, C., Bentley, L.P., Borken, W., Buchmann, N., Collins, S.L., de Dato, G., Dukes, J.C., 2514
Escolar, C., Fay, P., Guidolotti, G., Hanson, P.J., Kahmen, A., Kröel-Dulay, G., Ladreiter-2515
Knauss, T., Larsen, K.S., Lellei-Kovacs, E., Lebrija-Trejos, E., Maestre, F.T., Marhan, S., 2516
Marshall, M., Meir, P., Miao, Y., Muhr, J., Niklaus, P.A., Ogaya, R., Peñuelas, J., Poll, C., 2517
Rustad, L.E., Savage, K., Schindlbacher, A., Schmidt, I.K., Smith, A.R., Sotta, E.D., Suseela, 2518
V., Tietema, A., van Gestel, N., van Straaten, O., Wan, S., Weber, U., Janssens, I.A. (2014). 2519
Can current moisture responses predict soil CO2 efflux under altered precipitation regimes? A 2520
synthesis of manipulation experiments. Biogeosciences, 11: 2991-3013. 2521
https://doi.org/10.5194/bg-11-2991-2014 2522
Villagrán, C., y Armesto, J. (2005). Fitogeografía histórica de la Cordillera de la Costa de Chile. 2523
En C. Smith-Ramirez, J. J. Armesto, & C. Valdovinos (Eds.), Historia, biodiversidad y 2524
113
ecología de los bosques costeros de Chile. (Universita, pp. 105–123). Santiago, Chile. 2525
Recuperado a partir de http://www.sendadarwin.cl/espanol/wp-2526
content/uploads/2010/04/cap-5-villagran-armesto-2005.pdf 2527
Von Lützow, M., Kögel-Knabner, I., Ekschmitt, K., Flessa, H., Guggenberger, G., Matzner, E., 2528
Marschner, B. (2007). Soil fractionation methods: Relevance to functional pools and 2529
stabilization mechanisms. Soil Biology and Biochemistry, 39: 2183–2207. 2530
https://doi.org/10.1016/j.soilbio.2007.03.007 2531
Vullie, M., Franquist, E., Garreaud, R., Lavado Casimiro, W.S., Cáceras B. (2015). Impact of the 2532
global warming hiatus on Andean temperature. Journal of Geophisical Research: Atmospheres, 2533
120(9): 3745-3757. https://doi.org/10.1002/2015JD023126 2534
Yordanova, R. Y., Christov, K. N., Popova, L. P. (2004). Antioxidative enzymes in barley plants 2535
subjected to soil flooding. Environmental and Experimental Botany, 51(2): 93–101. 2536
https://doi.org/10.1016/S0098-8472(03)00063-7 2537
Wang, H., Boutton, T.W., Xu, W., Hu, G., Jiang, P., Bai, E. (2015). Quality of fresh organic matter 2538
affects priming of soil organic matter and substrate utilization patterns of microbes. Scientific 2539
Reports, 5: 10102. https://doi.org/10.1038/srep10102 2540
Wu, L., Xu, H., Xiao, Q., Huang, Y., Suleman, M.M., Zhu, P., Kuzyakov, Y., Xu, X., Xu, M., 2541
Zhang, W. (2020). Soil carbon balance by priming differs with single versus repeated addition 2542
of glucose and soil fertility level. Soil Biology and Biochemistry, 148: 107913. 2543
https://doi.org/10.1016/j.soilbio.2020.107913 2544
Zak, D., Holmes, W.E., MacDonald, N.W., Pregitzer, K.S. (1999). Soil temperature, matric 2545
potential, and the kinetics of microbial respiration and nitrogen mineralization. Soil Science of 2546
American Journal, 663: 575-584. https://doi.org/10.2136/sssaj1999.03615995006300030021x 2547
114
Zhang, W., Liang, C., Kao-Kniffin, J. He, H., Xie, H., Zhang, X. (2017). Effects of drying and 2548
wetting cycles on the transformations of extraneous inorganic N to soil microbial residues. 2549
Scientific Report, 7: 9477. https://doi.org/10.1038/s41598-017-09944-1 2550
Zeng, Q., Dong, Y., An, S. (2016). Bacterial Community Responses to Soils along a Latitudinal 2551
and Vegetation Gradient on the Loess Plateau, China. PLOS ONE 11(4): e0152894. 2552
https://doi.org/10.1371/journal.pone.0152894 2553
Zunino, H., Borie, F., Aguilera, S., Martin, J.P., Haider, K. (1982). Decomposition of 14C-2554
labeled glucose, plant and microbial products and phenols in volcanic ash–derived soils of 2555
chile. Soil Biology and Biochemistry, 14: 37–43. https://doi.org/10.1016/0038-0717(82)90074-2556
8 2557
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