Comparative water fluxes through leaf litter of tropical plantation trees and the invasive grass...

Journal of Hydrology 383 (2010) 167–178

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Journal of Hydrology

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Comparative water fluxes through leaf litter of tropical plantation treesand the invasive grass Saccharum spontaneum in the Republic of Panama

Andrew Park a,*, Patrick Friesen b, Aneth Aracelly Sarmiento Serrud c

a Department of Biology/Centre for Forest Interdisciplinary Research (CFIR), University of Winnipeg, 515 Portage Avenue, Winnipeg, Manitoba, Canada R3B 2E9b Biology Department, University of Winnipeg, 515 Portage Avenue, Winnipeg, Manitoba, Canada R3B 2E9c Departamento de Biología, Universidad de Panamá – Campus Dr Octavio Méndez Pereira, El Cangrejo, Panama Estafeta Universitaria, Ciudad de Panama, Panama

a r t i c l e i n f o s u m m a r y

Article history:Received 15 May 2009Received in revised form 27 November 2009Accepted 21 December 2009

This manuscript was handled by L. Charlet,Editor-in-Chief, with the assistance ofGeorgia Destouni, Associate Editor

Keywords:Litter layerWater holding capacityLitter drainageEvaporationTropical broadleaved treesSaccharum spontaneum L.

0022-1694/$ - see front matter � 2009 Elsevier B.V. Adoi:10.1016/j.jhydrol.2009.12.033

* Corresponding author. Tel.: +1 204 786 9407.E-mail address: [email protected] (A. Park).

The hydrological properties of leaf litter layers remain relatively unexplored, especially in tropical vege-tation communities. In this paper we explore the hydrological dynamics of litter samples from reforesta-tion plots of tropical hardwoods and the invasive sugar cane Saccharum spontaneum, which these treeswere planted to replace. Water holding capacity (WHC) and drying rates were compared under controlledconditions, and throughfall interception, drainage and calculated evaporation were measured in two fieldexperiments (A and B) conducted with different sets of samples. The WHC of samples varied from 3.4 to6.5 mm in experiment A, and from 1.6 to 7.1 mm in experiment B. Drainage through the litter samplesaveraged 78.3 ± 34.4% and 61.2 ± 34.70% TF in experiments A and B, respectively. Daily water storagewas 70.8 ± 14.25% of total WHC in experiment A and 78.6 ± 25.35% of total WHC in experiment B. Esti-mated evaporation averaged 34.8 ± 12.52% of WHC in experiment A and 34.3 ± 14.91% of WHC in exper-iment B. Although significant interspecific differences in WHC, interception of TF and evaporation wererecorded, species rankings tended to be different in experiments A and B. The exception was litter fromthe leguminous tree Gliricidia sepium, which maintained the lowest WHC and water storage in the field inboth experiments, but which evaporated water more rapidly than other species. The depth of throughfalldraining through litter samples in the field was similar among all species in both experiments. Compar-isons of regression slopes also showed that drainage depth increased with increasing throughfall at sim-ilar rates among species. On the other hand, both slopes and slope elevations differed among specieswhen drainage was expressed in l kg�1. Patterns of water storage and drainage in our samples were inbroad agreement with those of other studies, although WHC and litter necromass in our young tree plan-tations fell into the lower end of the range reported for mature Amazonian forest.

� 2009 Elsevier B.V. All rights reserved.

Introduction

Forest plantations and agroforestry are increasingly seen as via-ble land use alternatives on deforested and degraded lands in thetropics (Cusack and Mantagnini, 2004; Evans, 1999; Lamb, 1998).Their establishment over large areas is likely to change watershed-and landscape-scale hydrology because the vegetation canopy istypically transformed from pasture grasses or low shrubs tocontinuous tree cover. Changes in species composition affect thebalance between rainfall interception and evapotranspiration(Bonell, 1999; Brandt, 1987; Bruijnzeel, 2004; Crockford andRichardson, 2000; Douglas, 1999) through changes in canopyarchitecture, percent cover, and tree age in broadleaved andconiferous forests (e.g. Huber and Iroumé, 2001; Pypker et al.,2005), and in agroforestry systems (Schroth et al., 1999). Where

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a pronounced dry season occurs in the tropics, reforestation ofwhole watersheds is generally thought to reduce dry season waterflows (Jackson et al., 2005; Scott et al., 2005; Sun et al., 2006).

When trees are planted to replace grasses or cropland, there arelimited data to suggest that rainfall interception is increased(Ataroff and Rada, 2000; Waterloo, 1994). Simultaneously, theaccumulation of tree leaf litter improves the infiltration of waterinto the soil, and limits subsequent evaporation (Wallace et al.,2005). Continuous litter cover reduces raindrop erosivity by di-rectly intercepting raindrops that fall directly through the tree can-opy, or which drip from leaves and branches (Brandt, 1987; Mapa,1995; Putuhena and Cordery, 1996; Wiersum, 1985).

Litter layers also store a certain amount of water. Compared tothe large volume of research on rainfall interception by tree cano-pies, however, only a handful of studies have investigated theinterception of thoughfall (TF) by forest litter. Following a seriesof studies in the eastern United States during the 1950s (reviewedin Levia et al. (2004)), litter hydrology has been relatively

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168 A. Park et al. / Journal of Hydrology 383 (2010) 167–178

neglected. For most ecosystems, we therefore have little informa-tion about the magnitude and variability of a potentially importantwater storage reservoir that may control infiltration rates andcontribute to evapotranspiration. For example, water storage inthe litter of mature lowland rainforest can reach 163,000 l ha�1

(Marin et al., 2000), and litter layers account for 47% of the totalwater storage capacity of subtropical Eucalyptus forest and Pinusradiata d. Don plantations in Australia (Putuhena and Cordery,1996).

Research objectives

To date, there have been no investigations of the quantitativeeffects of establishing plantations of tropical hardwoods on litterhydrodynamics. In fact, we are aware of only one study that com-pares litter water storage in pasture grassland and plantations of atree species, in this case Pinus caribaea (Morelet) (Waterloo, 1994).There is an obvious need to study all the hydrological conse-quences of establishing tropical tree plantations on former pastureand farmland, including the potentially important role to be playedby leaf litter layers. Our knowledge deficits are particularlypronounced in the case of reforestation with native broadleavedtrees, which is a relatively recent phenomenon in the Neotropics(reviewed in Park and Cameron (2008)).

Our primary objective in this study was to compare dynamicwater fluxes through minimally disturbed samples of leaf litterfrom Neotropical tree plantations and the invasive wild sugar caneSaccharum spontaneum L. We investigated water fluxes in twoways: (1) by calculating water holding capacity (sensu Goldingand Stanton, 1972) and preparing drying curves of pre-saturatedlitter samples, and (2) by measuring drainage from, and changesin water storage in the litter samples under field conditions. Thefield measurements were also used in combination with the dryingcurve data to estimate the proportion of the water holding capacity

Fig. 1. Location of study site in Central Panama. Figure

that remained unsatisfied in the field (U), as well as evaporationrates from the litter samples.

Because litter decomposition in the humid tropics can be rela-tively rapid (see, for example Scherer-Lorenzen et al., 2007), weperformed two separate short-term experiments on separate setsof litter samples. These will be designated experiments A and B.

Methods

Site descriptions

Our study was conducted in a large species selection trial lo-cated in Soberania National Park (SNP) in the Republic of Panama(9�100N, 79�350W) (Fig. 1). The natural vegetation in SNP is lowlandtropical moist forest. Annual rainfall, averaged over the period1966–2003, was 2127 mm yr�1 with a four-month dry season inwhich less than 100 mm of rain fell in each month (Autoridad Nac-ional del Ambiente, unpublished data). Most rain events are shortbut intense storms, with occasional longer events of moderateintensity. The topography of the planted area consists of rollinghills with slopes of up to 48% interspersed with occasional moistswales.

The selection trial was established by the Project for Reforesta-tion Using Native Species (PRORENA), a joint project of the Smith-sonian Tropical Research Institute (STRI) and Yale TropicalResources Institute (TRI). The tree plantation consisted of a largenumber of 5-year-old monoculture tree plots (10 trees per plotat 6 � 8.5 m spacing) interspersed with large areas dominated bymature S. spontaneum L. S. spontaneum (also called canal grass orpaja blanca) is an invasive wild sugar cane from southeast Asia,and was first introduced to Panama in 1928 as part of the CanalZone Experiment Gardens (Craven et al., in press). S. spontaneumspreads rapidly by windblown seed, persists through vegetativereproduction from underground rhizomes, and can achieve a

prepared by Brad Russell, University of Winnipeg.

Table 1Mensurational characteristics of tree species and Saccharum spontaneum.

Species Stem density100 m2

BA 100 m�2 Height (m) Live crownlength (m)

Overstory LAI Understory LAI

Acacma 6 0.225 17.3 14.0 2.17 3.25Erythfu 6 0.487 10.8 10.1 3.14 1.17Glirse 6 0.229 12.1 7.5 1.82 1.15Ingapu 6 0.202 8.8 4.8 3.23 0.56Saccsp 8300 1.076 4.9 na 4.21 naSponmo 6 0.137 10.9 4.9 2.31 2.20Tectgr 6 0.101 14.1 13.4 3.28 0.48

Species codes: Acacma – Acacia mangium, Erytfu – Erythrina fuscum, Glirse – Gliricidia sepium, Ingapu – Inga punctata, Saccsp – Saccharum spontaneum, Sponmo – Spondiaasmombin, and Tectgr – Tectona grandis.

A. Park et al. / Journal of Hydrology 383 (2010) 167–178 169

biomass of 0.4 metric tons per ha in 45 days (this number extrap-olated from plot data in Kim et al., 2008). These characteristics of S.spontaneum produce an arrested succession in which reforestationby seed dispersal from the adjacent mature forest will not occur.

Species selection

Tree species chosen for litter sampling were also the subjects ofa simultaneous comparison of throughfall and interception ofplantation trees and S. spontaneum (Friesen et al., in preparation).They were selected on the basis of obvious differences in crownarchitecture, leaf size and arrangement, and stem morphology(Table 1). Additionally, the crowns of neighboring trees had to bein contact, or nearly so, and only plots that had attained an averagecrown closure of 60% or greater were chosen for study (see Section‘‘Methods”).

The tree species chosen were Acacia mangium Willd., Erythrinafusca Lour, Gliricidia sepium Jacq., Inga punctata Willd, SpondiasMombin L, and Tectona grandis Lf. All of these trees have commer-cial or traditional multipurpose value, and are increasingly beingplanted across Central America by forestry companies and farmers.Large plantations of A. mangium, an old-world exotic, have alsobeen established in reclamation projects and for commercial pur-poses in parts of its native range in Southeast Asia (Kuusipaloet al., 1995).

Tree and grass characteristics

Litter water fluxes were measured in one plot each of six treespecies and in five of seven rainfall interception transects of S.spontaneum. The transects in S. spontaneum were between 5 and6 m long, and were placed perpendicular to the boundary betweenthe grassland and a fire break. Transect locations were selectedsubjectively to span the full range of grass densities and heights.Each transect was carefully cut stem by stem at ground level usingpruning shears to minimize disturbance to the grass canopy.

We measured the height and live crown length of the centralindividual in each tree plot. Basal diameters of all stems in theplot were estimated using a diameter tape. Stem density ofS. spontaneum was estimated from four 22.5 � 51 cm (0.1147 m2)quadrats in each transect. Basal diameter was taken from 10 grassstems per transect using digital calipers, and height was estimatedon three stems per transect using an extendable ruler. Litter depthwas measured at 20 random points in each tree plot and at 5 ran-dom points in each S. spontaneum transect.

Leaf area index (LAI) in tree plots and S. spontaneum transectswas measured with an Accupar PAR-80 ceptometer (Decagon,Inc, Pullman, Ill) matched to an external quantum sensor (Li-CORInc., Lincoln, NE) for simultaneous above- and below-canopy read-ings. Canopy openness was calculated from digital photographswith a Nikon Coolpix 4500 camera equipped with a Nikon FC-E8

fisheye attachment. In tree plots, the canopy was photographedat eight random locations, above and below the height of theunderstory, where present. For S. spontaneum, LAI readings andcanopy photographs were taken from three positions in each tran-sect. Photographs were analyzed using Gap Light Analyzer (GLA)software (Frazer et al., 1999) using 36 azimuth and 20 zenith re-gions. Further details of LAI and canopy cover measurements canbe found in (Park and Cameron, 2008).

Litter measurements

Litter sample collectionFor each experiment, we collected five litter samples per plot

for tree species and a single sample in each of five S. spontaneumtransects. A sharp machete was first used to cut a rectangularboundary around each potential sample. A thin, flexible plasticsheet was then carefully inserted at the boundary between litterand mineral soil. In this way, we collected both superficial undecomposed litter and the more compacted semi-decomposedlayer beneath. This procedure yielded a coherent sample whosecorners could be lifted to check for the inclusion of mineral soil.If substantial quantities of mineral soil were present, the samplewas abandoned and a new one collected.

After collection, each sample was carefully trimmed to fit thedimensions of the litter storage/interception sampling frame. Eachsampling frame consisted of a rectangle of 1 cm diameter PVC pipewith a 5 cm deep box shaped net of plastic screen door mesh(�1.5 mm hole diameter) attached to it. Litter samples were care-fully slid from the plastic sheet into the frame. For trees with smallor medium sized leaves (intact leaf area of about 50 cm2 or less)and S. spontaneum, frames with an area of 576 cm2 were used.For T. grandis, whose leaves can reach 500 cm2 or more in size,we used a frame with an area of 1090 cm2. In practice, very largeleaves were not included in our samples, since T. grandis leaves ap-pear to break apart relatively rapidly after falling (A. Park, personalobservation).

Water holding capacity and drying curvesTo compare maximum water storage from experiments A and B,

we report the depth of water in the litter using the oven-dryweight of each sample as a reference. Following the terminologyused by Golding and Stanton (1972), we therefore use the term‘‘water holding capacity” (WHC) rather than water storage to ex-press the maximum amount of water that can be held in the litter.

Litter drying curves were prepared at the beginning of experi-ment A. Samples were first soaked for 24 h by stacking them (in-side their frames) in large plastic containers, which were thenslowly filled with water. After 24 h of complete immersion, sam-ples were allowed to drain for 30 s. Each sampling frame was thenplaced on top of a drainage collector (plastic basins, minimumdepth = 10 cm) to measure residual drainage from the litter


samples. After 30 min samples were weighed on a digital balance(Ohaus Scout Pro SP 2001) with a resolution for 0.1 g. This weightwas used as the benchmark from which subsequent water lossduring drying was calculated and as an estimate of water storagecapacity.

Samples were then placed beneath the roof of a large open-walled storage area that was open to ambient atmospheric condi-tions but protected from direct sunlight and rain by a roof. Theywere weighed every two hours for the first day of drying, and ona daily basis thereafter until no further weight reductions were re-corded. At the end of experiment A, the samples were soaked, andair dried once again to measure any changes in the storage capacityand air dry litter mass that occurred during the course of theexperiment.

The use of net sampling frames for measuring litter water stor-age has been criticized on the grounds that the mesh has a storagecapacity, which must be satisfied before drainage occurs (Helveyand Patrick, 1965). Anticipating this difficulty, we weighed eachframe dry and after 1 h of complete immersion in water. We de-ducted the saturated weight of the frame from the measuredweight of the litter plus the frame to calculate water storage duringthe first 12 h of drying. On subsequent days, we deducted the aver-age of the wet and dry weights of the frame from the litter weight,on the assumption that the storage capacity of the mesh would notbe completely satisfied as drying proceeded. Water holding capac-ity was estimated for experiment B in the same way, but limita-tions on time and labour did not allow a second set of dryingcurves to be prepared.

Field measurements of drainage and interceptionLitter frames and their drainage basins were placed in random

locations in tree plots and S. spontaneum transects. Those placedin tree plots were moved on a daily basis to sample the full rangeof canopy conditions. In the S. spontaneum transects, however,sample positions remained fixed due to the difficulty of positioningthe containers within the extremely dense stands of grass. Eachsampling frame was enclosed in a baffle (�8 cm width) that wasinclined approximately 15� from vertical. The baffle preventedwater from falling directly on the PVC tube of the sampling frame.Had this occurred, the effective area over which rainfall was col-lected would have been greater than the area of the litter sample,and would therefore have caused us to overestimate drainage. Lit-ter samples were weighed daily in the field, and the drainage watercollected using measuring cylinders of 25, 50, 100, 250, 500 or1000 ml capacity, depending on the volume of water to bemeasured.

Measurement of throughfall and rainfallThroughfall was measured using improvised rain gauges made

from 1 US gallon capacity bleach bottles and plastic funnels withvertical side walls (diameter = 21.2 cm, area = 353 cm2). Eighteenfunnels were distributed along three belt transects in each treeplot. Transects were oriented radially from the trunk of the centraltree in each plot, and the direction of each transect was determinedfrom a random compass bearing. The number of collectors in each1/3rd of the transect’s length was made proportional to the areaencompassed by imaginary concentric rings subtending each tran-sect segment (1 in the inner 1/3rd, 2 in the second and 3 in thethird). Collectors were allocated within each transect segmentusing random numbers to determine their placement along thetransect axis and perpendicular to it. They were moved at randomwithin their transect segments after every 5 or 6 rain events to re-duce overall variability of TF (Holwerda et al., 2006), and to ensurethat points of throughfall concentration, especially from the verylarge leaves of T. grandis, did not exercise undue influence on

throughfall measurements. Three additional roving collectors wereplaced randomly within each plot, and moved on a daily basis.

To collect throughfall from S. spontaneum, it was essential toplace collectors in undisturbed parts of the extremely dense stand.Collectors were placed in three positions approximately 1.5 m be-yond the end of each S. spontaneum transect by attaching 2 m PVCtubes to the funnel spouts, and draining these into the collectionbottles, which were placed in holes dug the soil. In this way, itwas never necessary to disturb the funnels, but the collectionbottles were easily accessible.

Rainfall in the open was measured using a tipping-bucket raingauge attached to a weather station (Spectrum Technologies,Plainsfield, Illinois) with a bucket capacity of 0.3 mm, which re-corded rainfall in five minute intervals. Open area rainfall was alsoestimated from the rain collected in four of our throughfall collec-tors. Rainfall from these open area funnels was used to test the rel-ative accuracy of funnel collected rain against that collected by therain gauge.

Throughfall, open area rainfall, litter wet weight, and the vol-ume of water draining into the drainage vessels below the litternets were measured each morning. A discrete rain event was heldto be one that occurred with at least seven daylight hours betweenindividual storms. Direct observation confirmed that this amountof time was sufficient to evaporate residual water from treecrowns. Litter measurements were taken between July 24th andAugust 23rd 2008 for experiment A and between September 3rdand October 1st 2008 for experiment B. At the end of each exper-iment, samples were oven dried for 48 h at a temperature of105 �C.

Data preparation and analysis

Calculation of litter water fluxesWe anticipated that litter samples would lose a measurable pro-

portion of their mass over the course of the experiments. For eachsample in experiment A, we therefore calculated a decay constantusing its air dry weight at the beginning and end of the two dryingperiods. The daily decay constant k was estimated as:

K ¼ lnL0=L50

T

� �ð1Þ

where L0 and L50 are the litter air dry weights at the beginning andend of the experiment, and T is the duration of the experiment indays. Based on the assumption that oven-dry weight would be pro-portional to air dry weight, we used the ks calculated from Eq. (1) toestimate the oven-dry weight of the samples throughout theexperiment:

Ldt ¼ Ldekt ð2Þ

where Ld is the oven-dry mass measured at the end of the experi-ment, and Ldt is the estimated oven-dry mass of a litter sample attime t. The mass of water stored in each sample after each rainevent was then calculated as follows:

Hs ¼ Hg � Fa � Ldt ð3Þ

where Hs is mass of water stored, Hg is the gross mass of the littersample plus the sample frame, and Fa is the average of the dryand saturated sample frame.

A second set of exponential constants was calculated from ini-tial and final water holding capacities to accommodate expectedchanges in maximum water content through time. These revisedwater holding capacities were used to calculate the proportion ofthe capacity that remained unsatisfied (due to incomplete wettingof leaf surfaces) after each rain event:

Us ¼ Sdt � Hs ð4Þ

Litter Layer

Drainage

Tree canopy

Unsatisfiedstorage (Us)

Storage (Hs)

Water Holding Capacity

(WHC)

Throughfall interceptionEvaporation

Throughfall (TF)

Rainfall Interception

Fig. 2. Schematic of water flows and storage parameters of litter samples.


where Us is unsatisfied WHC, Sdt is the WHC at time t, allowing forlitter decay, and Hs is water content after each event, as before (seeFig. 2).

Evaporation was estimated using the drying curve equationsfrom the first set of drying curves, following the general strategyoutlined by Waterloo (1994). A time equivalent (in hours) was cal-culated for each sample and each event, based on the proportion ofthe storage capacity present at the time of measurement. This timeequivalent could then be plugged into the drying curve equation toestimate (i) the volume of water evaporated from the time of mea-surement until the end of the next rain event, and (ii) the volumeof water evaporated since the end of the previous rain event. Thesetwo quantities were then summed to yield a single estimate ofevaporation.

Air dry weights were not available for litter samples in experi-ment B. We therefore used the ratio of oven to air dry weights, cou-pled with species averaged decay constants from experiment A toestimate the expected oven-dry weight of litter samples at differ-ent times during experiment B.

Statistical analysisThe rate of litter drying over time was tested against logarith-

mic, power and exponential relationships. The strength of theresulting models was evaluated by visual inspection of regressioncurves, and by comparing the R-squared values. In the field exper-iments, drainage, storage, evaporation and unsatisfied storagewere expressed as depths (in mm) and volumes of water perkg�1 for each rain event. Water holding capacity at the beginningand end of experiment A was compared using repeated measuresanalysis of variance (rANOVA), and one-way ANOVA with Sidakcorrected post hoc comparisons of means.

We expected that the volume of water draining through the lit-ter layer would be strongly dependant on rain event depth. Therelationship between species-specific litter drainage and through-fall was therefore tested using analysis of covariance (ANCOVA),and, where necessary, individual regression analyses with slopecomparisons. Analyses of variance were also performed on theaverage daily water stored, average daily unsatisfied WHC, totaldrainage and total estimated evaporation in each experiment. Allanalyses were conducted in SPSS for Windows (Release 14.0,2005. Chicago: SPSS Inc.).

Results

Species characteristics

Tree heights varied between 8.8 m for the multi-stemmed,spreading crowned legume I. punctata to 17.1 m for the monopo-dial A. mangium (Table 1). Mean height of S. spontaneum was4.9 m, and stem density and basal area for the grass averaged9512 (±3621) stems 100 m�2 and 1.08 (±0.406) m2 100 m�2

respectively. S. spontaneum had the highest LAI (4.21), althoughthe addition of understory LAI to the LAI of tree canopies wouldhave given several tree plots higher cumulative leaf areas.

Litter characteristics and water holding capacity

Leaf litter layers beneath the canopies of five out of six tree spe-cies were relatively homogenous, and composed primarily of leavesfrom the canopy species (see electronic Supplement S1 ons were thesparse, uneven litter cover of G. sepium (S1c) and S. mombin (S1f),whose litter was augmented by leaf residues from its understory(primarily composed of S. spontaneum). A. mangium and I punctata(S1a, d) had seed pods admixed with their leaf litter. Small twigsand herbaceous leaf litter were also present, but they appeared tobe relatively minor components of the overall litter biomass.

Significant changes were recorded in air dry litter mass andWHC between the beginning and end of Experiment A (Table 2a).Air dry litter mass declined by 0.356 kg m�2 between the begin-ning and end of the experiment (F1,27 = 75.8, P 6 0.001), with thesmallest decline being observed in G. sepium (0.19 kg m�2) andthe greatest in E. fuscum (0.56 kg m�2). Estimated WHC also de-clined between the two drying periods of experiment A, with meandeclines of 1.29 mm (F1,27 = 241.8, P 6 0.001) and 0.86 l kg�1

(F1,27 = 259.2, P 6 0.001) being recorded.Although species experienced equal rates of decline in air dry

mass (species by time interaction, P > 0.05), and there were nointerspecific differences in oven-dry mass, significant time by spe-cies interactions in WHC were recorded (F6,28 = 5.26, P = 0.001 fordepth in mm and F6,28 = 2.25, P = 0.004 for volume capacity inl kg�1). Inspection of interaction plots indicated that WHC depthdeclined more rapidly in S. spontaneum than in other species, andthat volume capacity in l kg�1 declined more rapidly in S. spontane-um, E. fusca and T. grandis.

Table 2Litter dry weights and water holding capacity (WHC) in (a) experiment A, (b) experiment B and (c) comparison of litter sample depths. Different letters within columns indicatesignificant interspecific differences (Sidak post hoc test, P 6 0.05).

Species Air dry wt. 1(kg m�2)

Air dry wt. 2a

(kg m�2)Oven dry wt.(kg m�2)

H20 holding A(mm)

H20 holding B(mm)

H20 holding A(l kg�1)

H20 holding B(l kg�1)

Residual H20b

(l kg�1)

(a)Acacma 2.14 (0.326)a 1.90 (0.253)ab 1.36 (0.214)a 5.16 (0.829)ac 4.32 (0.723) 3.21 (0.088)ac 2.64 (0.165)a 0.40 (0.082)abErytfu 2.42 (0.657)a 1.86 (0.463)ab 1.28 (0.291)a 6.48 (1.081)a 4.71 (0.748)a 3.84 (0.519)ac 2.82 (0.501)a 0.43 (0.166)abGlirse 1.33 (0.393)a 1.14 (0.311)ab 0.82 (0.247)a 3.41 (0.812)b 2.59 (0.316)b 3.49 (0.433)ac 2.72 (0.430)a 0.22 (0.047)bIngapu 2.57 (0.715)a 1.99 (0.475)a 1.45 (0.340)a 5.81 (0.701)a 4.57 (0.792)a 3.10 (0.671)ac 2.42 (0.449)a 0.37 (0.125)abSaccsp 1.92 (0.633)a 1.42 (0.258)b 1.00 (0.253)a 5.16 (1.305)a 4.15 (0.884)ac 4.71 (0.795)b 3.18 (0.475)a 0.32 (0.133)abSponmo 2.47 (1.317)a 2.04 (0.967)a 1.42 (0.735)a 5.37 (1.105)ac 4.69 (0.990)ac 3.29 (0.628)c 2.85 (0.588)a 0.44 (0.155)aTectgr 1.44 (0.236)a 1.23 (0.189)a 0.96 (0.153)a 4.04 (0.548)bc 2.92 (0.359)bc 3.62 (0.385)abc 2.61 (0.268)a 0.22 (0.030)b

Species Oven dry wt. (kg m�2) H20 holding (mm) H20 holding (l kg�1) Litter depth A (cm) Litter depth B(cm)

(b) (c)Acacma 3.68 (1.178)a 6.02 (1.507)a 2.93 (0.827)ac Acacma 4.74 (1.737)ac 4.66 (1.438)adErytfu 3.30 (0.432)ab 4.45 (1.408)abd 2.30 (0.502)ab Erytfu 3.69 (0.655)ab 3.14 (0.647)abGlirse 2.08 (0.858)bc 1.57 (0.246)bd 1.42 (0.362)b Glirse 2.39 (0.441)b 2.14 (0.555)bIngapu 3.33 (0.399)ab 7.71 (2.343)c 4.02 (1.226)c Ingapu 3.24 (0.203)ab 3.22 (0.409)abSaccsp 1.41 (0.138)c 1.62 (0.437)d 1.97 (0.414)ab Saccsp 1.85 (0.245)b 1.86 (0.799)cSponmo 2.19 (0.340)bc 3.10 (0.731)ad 2.45 (0.461)ab Sponmo 2.44 (0.222)b 2.42 (0.466)bcTectgr 3.10 (0.774)bc 5.90 (1.597)ac 1.72 (0.361)ab Tectgr 5.73 (1.209)c 5.18 (1.264)d

a ‘‘1” and ‘‘2” refer to the air dry weights at the beginning and end of the experiment A (t = 58 days).b Residual water storage calculated as the difference between the air dry and oven-dry weight of each sample.

Table 3Regression parameters of litter drying curves at the beginning of experiment A. Allcurves were exponential models of the form Smm = a � ekt, where Smm is depth of wateron the basis of oven-dry weight, a, and k are the intercept and slope coefficient,respectively, and t is time. Different letters within standard error columns indicatesignificant differences between slopes or slope elevations.

Species Intercept (std. error) Slope (std. error) F1,55 R2

Acacma 4.14 (0.226)a �0.014 (0.001)a 420.6 *** 0.88Erytfu 5.82 (0.352)a �0.014 (0.001)a 384.1 *** 0.87Glirse 2.78 (0.254)bc �0.020 (0.001)b 261.4 *** 0.83Ingapu 5.03 (0.288)ab �0.014 (0.001)a 459.3 *** 0.89Saccsp 5.31 (0.444)a �0.016 (0.001)ab 282.7 *** 0.83Sponmo 4.93 (0.329)a �0.015 (0.001)a 343.2 *** 0.86Tectgr 3.25 (0.157)c �0.016 (0.001)ab 814.9 *** 0.94


At the end of experiment A, G. sepium and S. spontaneum hadsignificantly lighter air dry weights than I. punctata, S. mombinand T. grandis (Sidak adjusted P 6 0.05). Since there were no inter-specific differences in oven-dry weight in experiment A, these dif-ferences must have arisen due to a divergence in the residual watercontents of the litter samples after they were air dried. Residualwater content varied from 11% to 22% of the water content of theair dried leaves (Table 2a). Similarly G. sepium (2.08 kg m�2) andS. spontaneum (1.41 kg m�2) had the lowest oven-dry weights inexperiment B (Table 2b).

Water holding capacity varied from 3.41 to 6.48 mm at thebeginning of experiment A, while WHC depth in samples fromexperiment B ranged from 1.57 to 7.1 mm. Water holding capacityin mm was generally lower in G. sepium and T. grandis than in theother five species in experiment A. In experiment B, WHC in mmwas lower in G. sepium and S. spontaneum than in 5 other species,but I. punctata (WHC = 7.1 mm) stored a greater depth of waterthan any other species. Calculating storage in terms of volumekg�1 of litter oven-dry weight tended to diminish observed inter-specific differences, and changed relative rankings of WHC some-what. In spite of having a relative low dry weight, S. spontaneumstored significantly more water (4.71 l kg�1) than any species ex-cept T. grandis at the beginning of experiment A. However, S. spon-taneum had the second lowest holding capacity in experiment B(1.97 l kg�1), although this volume was only significantly lowerthan that of I. punctata (4.02 l kg�1).

Litter drying curves

Exponential regression models provided the best fits to the dry-ing curve data. All models were highly significant (P 6 0.001), andreturned R-squared values between 0.83 and 0.94 (Table 3). Slopecoefficients varied little among species, ranging from �0.014 to�0.020 mm h�1 with standard errors of the estimates of 0.001 inevery case. In a comparison of the regression slopes (Zar, 1996),G. sepium was concluded to evaporate stored water at a faster ratethan A. mangium, E. fusca, I. punctata, and S. mombin (Dunn-Sidakcorrected P 6 0.1 on 21 comparisons).

Gross rainfall (Pg) and throughfall (TF)

Litter wet weights and drainage volumes were measured from26 rain events during experiment A, and 21 events during experi-

ment B. From these events, we took 21 discrete measurements oflitter weight and drainage during experiment A, and 14 measure-ments during experiment B. Where rest days intervened betweenmeasurements, therefore, two or more events contributed to themeasured drainage volumes.

Most rain events were relatively small (610 mm), but wereinterspersed by much larger storms of up to 62.6 mm in depth(Fig. 3). The mean and median rainfall depths for period 1 were14.8 mm day�1 and 7.1 mm day�1, respectively, and those forperiod 2 were 10.1 mm day�1 and 1.3 mm day�1. In spite of theseapparent differences, ranked distributions of experiment A and Brain events could not be distinguished statistically (Mann WhitneyU test, Z = �1.401, P = 0.161). Daily TF averaged 88.0 ± 21.80%of Pg. Total TF varied by species and experiment, and varied from75.1% of Pg for S. spontaneum in experiment A to 103.8% of Pg forT. grandis in experiment B (Tables 4 and 5). Coefficients of variationamong collectors for individual events averaged 38 ± 12.3%, andwere inversely proportional to the depth of the storm (CV =�6.86 TF + 48.99, R2 = 0.62).

Drainage, interception of TF, and evaporation

Overall daily patternsDrainage through the litter samples averaged 78.3 ± 34.4% of TF

and 70.6 ± 36.38% of Pg in experiment A, and was 61.2 ± 34.70%and 49.1 ± 30.87% of TF and Pg, respectively, in experiment B. Vol-umes of water drained varied by two orders of magnitude duringthe experiments, but the depth of water stored and evaporatedtended to vary within relatively narrow bounds from day to day

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204 209 213 220 224 228 231 247 251 255 259 264 271Julian day

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Table 4Water storage parameters for experiment A. Figures are mean period totals for each parameter expressed in mm depth and in liters kg�1 of litter. Different letters within columnsindicate significant interspecific differences (Sidak post hoc test, P 6 0.05).

Species Pg (mm) TF (mm) Total drainage (mm) Average storage (mm) Average unsatisfied storage (mm) Total evaporation (mm)

Acacma 385.5 373.1 329.7 (47.94)a 3.42 (0.256)ab 1.43 (0.238)abc 28.02 (3.210)acErytfu 377.8 374.6 (62.76)a 4.28 (0.521)a 1.58 (0.192)ac 39.23 (2.119)bGlirse 358.1 328.6 (69.19)a 2.49 (0.273)b 0.64 (0.194)bc 30.52 (2.584)aIngapu 393.9 322.5 (40.21)a 3.69 (0.431)ab 1.66 (0.115)a 31.76 (2.365)aSaccsp 289.4 283.0 (48.77)a 4.06 (0.521)a 1.40 (0.157)ac 40.11 (0.570)bSponmo 284.6 319.6 (49.65)a 4.14 (0.546)a 0.96 (0.170)ac 38.85 (1.676)bTectgr 371.7 326.0 (80.84)a 2.85 (0.347)ab 0.84 (0.127)c 25.06 (1.692)c

Total drainage (l kg�1a) Average storage (l kg�1) Average unsatisfied storage (l kg�1) Total evaporation (l kg�1)

Acacma 166.6 (31.374)ab 2.15 (0.170)b 0.86 (0.153)a 18.00 (4.700)aErytfu 182.6 (74.105)ab 2.55 (0.273)ab 0.95 (0.238)a 23.90 (6.025)abGlirse 284.7 (117.121)b 2.64 (0.350)ab 0.61 (0.206)a 33.31 (11.242)bIngapu 143.3 (36.293)a 1.95 (0.196)b 0.92 (0.186)a 17.13 (4.131)aSaccsp 144.7 (27.191)ab 3.10 (0.371)a 1.06 (0.347)a 32.42 (9.652)abSponmo 145.3 (58.047)ab 2.56 (0.339)ab 0.58 (0.200)a 25.42 (8.503)abTectgr 230.1 (88.673)ab 2.54 (0.211)ab 0.74 (0.226)a 23.20 (4.616)ab

Pg – Gross rainfall in mm during the measurement period.Figures in parentheses are standard deviations for total drainage and evaporation, and standard errors of the mean for storage and unsatisfied storage.

a Based on the oven-dry weight.

Table 5Water storage parameters for experiment B. Interpretation of data is as described in Table 4, except that storage and unsatisfied storage are based on oven-dry weights.

Species Pg (mm) TF (mm) Total drainage (mm) Average storage (mm) Average unsatisfied storage (mm) Total evaporation (mm)

Acacma 243.5 192.9 151.67 (24.13)a 4.06 (0.700)ac 2.61 (0.375)a 17.22 (5.540)acErytfu 205.5 187.00 (38.85)a 3.78 (0.516)ac 0.92 (0.283)ab 18.78 (3.750)acGlirse 210.8 174.98 (13.86)a 0.69 (0.165)b 0.97 (0.133)ab 6.66 (2.058)bIngapu 229.4 185.79 (9.18)a 6.28 (0.821)c 2.14 (0.728)ac 26.09 (5.979)aSaccsp 175.9 155.37 (10.59)ab 1.69 (0.780)ab 0.07 (0.070)b 12.75 (3.549)bcSponmo 214.3 179.49 (16.57)a 2.61 (0.243)ab 0.24 (0.140)bc 14.88 (2.448)bcTectgr 252.9 119.58 (31.91)b 4.76 (0.577)ac 0.92 (0.367)ab 21.88 (4.967)c

Total drainage (l kg�1) Average storage (l kg�1) Average unsatisfied storage (l kg�1) Total evaporation (l kg�1)

Acacma 36.8 (9.31)a 0.92 (0.077)ac 0.65 (0.139)a 3.97 (0.477)adErytfu 46.5 (10.52)a 0.92 (0.084)a 0.21 (0.210)ab 4.61 (0.545)abGlirse 78.8 (25.97)b 0.27 (0.049)b 0.46 (0.115)ab 2.82 (0.618)aIngapu 45.9 (7.60)ac 1.51 (0.162)c 0.55 (0.190)ab 6.33 (1.102)bcSaccsp 90.0 (12.89)b 0.94 (0.038)a 0.01 (0.038)b 7.27 (1.535)cSponmo 69.3 (10.55)bc 0.99 (0.060)ac 0.28 (0.040)ab 5.69 (0.659)bcdTectgr 37.9 (12.35)a 1.45 (0.091)ac 0.28 (0.118)ab 6.74 (0.687)c


(see examples in Fig. 4 and Supplementary material S2). Averagestorage was 70.8 ± 14.25% of the total WHC for experiment A and78.6 ± 25.35% of total WHC in experiment B. The estimated depth

of evaporation between consecutive measurements was 34.8 ±12.52% of WHC in experiment A and 34.3 ± 14.91% of WHC inexperiment B.

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Fig. 4. Joint graphs of daily evaporation (line chart), water storage (hatched bars) and drainage (grey bars) (in mm) for A. mangium (Acacma), E. fusca (Erytfu) and S.spontaneum (Saccsp) during experiments A and B. Error bars represent standard deviations of the mean.


Table 7Regression parameters for log (throughfall + 1) versus log (litter drainage + 1) forexperiment B, expressed in (a) mm depth and (b) l kg�1 of litter. Different letterswithin standard error columns indicate significant differences between slopes orslope elevations.


(a)Acacma �0.280 (0.097)ab 1.116 (0.091)a 149.2 *** 0.93Erytfu �0.295 (0.080)ab 1.172 (0.075)a 244.2 *** 0.95Glirse �0.332 (0.096)ab 1.168 (0.089)a 173.1 *** 0.94Ingapu �0.278 (0.094)a 1.117 (0.085)a 174.5 *** 0.94


There were obvious differences in variability among drainage,daily storage and evaporation within experiments, and whencomparing each variable between experiments A and B (Fig. 4and S2). Coefficients of variation (CVs) for daily drainage, storageand evaporation were, respectively, 46.2 ± 28.31, 19.1 ± 7.25 and10.1 ± 5.35% for all species pooled together in experiment A. Theequivalent CVs for experiment B were 50.4 ± 45.23, 41.7 ± 39.90and 25.3 ± 10.70. There were also apparent differences withinand among species in the variability of sample sets used in exper-iments A and B (Fig. 4 and S2).

Saccsp �0.097 (0.055)b 1.029 (0.054)a 384.0 *** 0.97Sponmo �0.346 (0.087)ab 1.179 (0.079)a 220.5 *** 0.95Tectgr �0.172 (0.087)ab 0.902 (0.077)a 137.8 *** 0.92

(b)Acacma �0.215 (0.063)ab 0.681 (0.060)ab 129.2 *** 0.92Erytfu �0.237 (0.062)ab 0.745 (0.058)ab 163.8 *** 0.93Glirse �0.292 (0.077)ab 0.914 (0.071)ab 165.9 *** 0.93Ingapu �0.233 (0.062)a 0.715 (0.056)ab 164.5 *** 0.93Saccsp �0.127 (0.048)b 0.886 (0.048)b 347.8 *** 0.97Sponmo �0.291 (0.069)ab 0.876 (0.064)b 189.8 *** 0.94Tectgr �0.168 (0.064)ab 0.607 (0.057)a 114.1 *** 0.91

DrainageAnalyses of covariance with log (TF in mm + 1) for each rain

event as the covariate returned significant species by throughfallinteractions for event-specific drainage depths and volumes inboth experiments (P 6 0.001 in every case). Nevertheless, no sig-nificant differences were found in the slopes of species-specificregressions between log transformed throughfall depth and logdrainage (mm + 1) for experiment A or B (Dunn-Sidak correctedP > 0.1 on 21 comparisons, see Tables 6 and 7). When slope eleva-tions were compared (Zar, 1996), I. punctata (a = �0.278) had alower drainage depth intercept than S. spontaneum (a = �0.097)in experiment B. This result implied that I. punctata litter inter-cepted more rain than S. spontaneum before field storage capacitywas exceeded, and that at any given rain event depth, I. punctatawould intercept more rainfall than S. spontaneum.

Several slopes and intercepts were significantly different inregressions of throughfall versus drainage volumes in l kg�1 of lit-ter. G. sepium (b = 1.081) had a significantly steeper slope coeffi-cient than I. punctata (b = 0.897) in experiment A (Table 6), andT. grandis had a significantly shallower slope (b = 0.607) than G.sepium (b = 0.914), S. spontaneum (b = 0.886) and S. mombin(b = 0.876) in experiment B (Table 6b). T. grandis had a less negativeintercept (a = �0.154) than either I. punctata (a = �0.253) or S.spontaneum (�0.233) in experiment A, and the intercept for I. punc-tata (a = �0.233) was more negative than that of S. spontaneum(�0.127) in experiment B.

When back-transformed, these results suggested that minimumrainfall depths to produce drainage varied from 0.39 to 0.94 mmfor drainage depth and 0.41–1.1 mm for drainage volume in l kg�1.All regressions were highly significant (P 6 0.001) and had closerelationships between throughfall and drainage, as shown by R-squared values between 0.91 and 0.99.

Table 6Regression parameters for log (throughfall + 1) versus log (litter drainage + 1) forexperiment A, expressed in (a) mm depth and (b) l kg�1 of litter. Different letterswithin standard error columns indicate significant differences between slopes orslope elevations.


(a)Acacma �0.229 (0.035)a 1.126 (0.030)a 1365.0 *** 0.99Erytfu �0.142 (0.048)a 1.078 (0.042)a 658.9 *** 0.97Glirse �0.192 (0.041)a 1.100 (0.036)a 909.9 *** 0.98Ingapu �0.205 (0.055)a 1.097 (0.047)a 54.6 *** 0.97Saccsp �0.191 (0.045)a 1.118 (0.043)a 673.3 *** 0.98Sponmo �0.209 (0.039)a 1.193 (0.038)a 992.9 *** 0.98Tectgr �0.155 (0.067)a 1.064 (0.058)a 339.5 *** 0.95

(b)Acacma �0.28 (0.038)ab 0.963 (0.033)ab 873.8 *** 0.98Erytfu �0.215 (0.056)ab 0.919 (0.047)ab 376.2 *** 0.96Glirse �0.225 (0.047)ab 1.081 (0.041)b 709.9 *** 0.98Ingapu �0.253 (0.049)b 0.897 (0.041)a 479.0 *** 0.97Saccsp �0.223 (0.038)b 0.966 (0.037)ab 713.1 *** 0.98Sponmo �0.243 (0.031)ab 1.020 (0.029)ab 1195.0 *** 0.99Tectgr �0.154 (0.056)a 0.974 (0.047)ab 422.3 *** 0.96

Total drainage varied from 283.0 mm/144.7 l kg�1 to 374.6 mm/284.7 l kg�1 in experiment A (Table 4) and 119.6 mm/36.8 l kg�1

and 187.0 mm/90.0 l kg�1 in experiment B (Table 5). There wereno significant differences in the total depth of water drained inexperiment A, but G. sepium drained a significantly greater totalvolume than I. punctata. In experiment B, the T. grandis drained ashallower depth of water than every species except S. spontaneum,and total volumes drained were highest in S. spontaneum, I. punctataand S. mombin.

Interception and evaporationUnlike drainage, daily water storage, daily unsatisfied WHC

and evaporation had no strong relationship with event-wisethroughfall (R2

6 0.06, P P 0.05, and see Fig. 4). Mean storagevaried from 2.49 to 4.28 mm/1.95 to 3.10 l kg�1 in experiment A(Table 4) and 0.69–4.76 mm/0.27–1.51 l kg�1 in experiment B(Table 5). Total evaporation throughout the two experiments was25.06–40.11 mm/17.13–33.31 l kg�1 and 6.66–26.09 mm/2.82–6.33 l kg�1 in experiments A and B, respectively.

Although significant interspecific differences in total storage,unsatisfied WHC and evaporation were recorded in both experi-ments (one-way ANOVA, F6,28 > 2.9, P 6 0.05), few species storedstatistically less or more water than others. Relative rankings ofmeans and totals were also inconsistent between experiments.One consistent result was that G. sepium stored relatively littlewater in both experiments relative to several other species. Simi-larly, I. punctata and E. fuscum generally stored relatively largequantities of water and had high rates of evaporation, althoughmean differences were not always statistically significant. In afew species relative ranking depended on whether water depthor volume kg�1 was the unit of measurement. For example, I. punc-tata had the third deepest water storage in experiment A, but wasranked seventh in water volume kg�1.

Discussion and conclusions

Summary of findings

Litter samples from a variety of species differed in WHC, waterstorage in the field, the fraction of WHC that remained unsatisfied,and in estimated evaporation. With the exception of G. sepium,however, we could not firmly conclude that species rankings ofwater storage variables would persist in repeated experiments(Tables 4 and 5). The litter of G. sepium was also exceptional in hav-


ing a larger drying curve slope coefficient (indicating faster evapo-ration from drying samples) than A. mangium, E. fusca, I. punctata,and S. mombin (Table 3). The low level of interspecific variationin water storage may have been due, in part, to the relativelyhomogenous litter necromass across species (Table 2). The hetero-geneity of storage rankings between experiments A and B also sug-gests that a larger number of samples might be required todistinguish subtle differences of storage parameters betweenspecies.

Although our experiments were relatively short-term, and didnot encompass a complete cycle of rainy and dry seasons, we col-lected field data from rainfall events with depths ranging from 0.9to 62.6 mm (Fig. 3). In spite of this variability, daily water storage,and to a lesser degree, estimated evaporation, were remarkablyconsistent throughout our field measurements (Fig. 4 and S2).We may tentatively conclude, therefore, that the range of condi-tions that prevail during the Panamanian rainy season were fairlysampled, and that the litter layer would store between approxi-mately 50% and 79% of its WHC during that period.

The total depth of water drained did not vary significantlyamong species in either experiment. If the spatial variability inTF within a species exceeded the variability of TF between species,then this finding might reflect our daily movement of litter sam-ples to capture the range of canopy conditions. Under these cir-cumstances, drainage could be thought of as a random normalvariable from a common population, which would be the pooledspecies samples. On the other hand, drainage also had the highestCV of any variable measured, perhaps indicating that more samplesper species would be required to detect significant interspecific dif-ferences in this variable.

Slope coefficients of drainage depth in response to TF weregreater than 1, indicating that litter drainage increased faster thanTF in all species (Tables 6 and 7). These findings are consistent withthe rapid filling of litter ‘‘field capacity” (the amount of water thatlitter can absorb before drainage occurs) at the beginning of mostrain events. This quantity is clearly different from WHC and thestorage capacity of air dry litter because some parts of the complexinterlocking litter volume may channel water rapidly to the soilwhile others remain dry throughout a rain event (Putuhena andCordery, 2000; Sato et al., 2004).

Comparison with other studies

Water holding capacity and drainageFew studies of litter water storage have been carried out over

the last five decades, and the majority of these took place in east-ern hardwood communities of the USA or coniferous plantations(see summary in Helvey and Patrick (1965)). The only comprehen-sive study of hydrological dynamics in tropical leaf litter that weare aware of is presented by Marin et al. (2000), who analyzed lit-ter storage capacity and drainage in four distinct Amazonian forestecotypes. Our figures for WHC (Table 2) occupy the lower end ofthe water storage range (4.57–16.29 mm) reported by theseauthors. This result can be understood in terms of the much greaternecromass of the litter 3.27–9.81 kg m�2) in the Amazonian forestplots relative to our 5-year old forest plantations (0.96–3.68 kg m�2) and S. spontaneum (1.00 and 1.41 kg m�2 in experi-ments A and B, respectively). Litter samples measured by Marinet al. (2000) also included a network of superficial roots that devel-ops at the interface of the decomposing leaf litter and the mineralsoil. These roots would have added an additional physical compo-nent to the water storage ‘‘infrastructure” of the forest floor. Therelatively constant values of daily storage combined with variabledrainage observed on our data (Fig. 4) are also seen in the data ofMarin et al. (2000), where long periods of relatively constant stor-age were interspersed with periods of drying with little rain.

We should also note that, despite our much smaller samplesizes (n = 5 per species per experiment), coefficients of variation(CV) of dry weight and WHC were generally lower than those ofMarin et al. (2000, n = 17–31). In our study, the CVs of oven-dryweight varied from 9.8% to 51.5% (mean values of 26.5% and21.2% in experiments A and B, respectively). In mature Amazonianforests, the average CV of dry weight was 39.8%. Coefficients of var-iation of WHC ranged from 12.4% to 31.5% in our samples versusCVs of 40.7–56.3 in Marin et al. (2000). Our conclusion from thiscomparison is that litter layers in tree plantations and S. spontane-um dominated pasture were far more homogeneous than those ofmature Amazonian forest. This observation can be easily under-stood when one considers that our litter samples were monospe-cific, or nearly so, whereas litter layers in mature rainforest willcomprise mixtures of a wide variety of species growing in intimateassociation with each other.

Drainage from litter was also comparable to the figures re-ported by Marin et al. (2000). The average percentage of TF drainedin the Amazon ranged from 25% to 93%, although rain events yield-ing 6 5 mm usually failed to yield drainage. In our study, averagepercent drainage values were 78.2 ± 31.48% and 61.9 ± 34.36% inexperiments A and B, respectively (range = 2.8–156.3%, with 17%of 228 species/rain event combinations having drainage depths lar-ger than TF). Once again, this result probably reflects spatial heter-ogeneity of canopy density (and therefore TF) that was notcaptured for every individual event.

Ataroff and Rada reported that cloud forest litter, measuredusing a similar container system to ours, intercepted only 6% ofTF, which was, in turn, only 49% of Pg (Ataroff and Rada, 2000).In comparison, interception of throughfall in our study averaged6.8 ± 10.04% in experiment A and 21.0 ± 14.10% of TF in experimentB. Waterloo (1994) estimated that interception by mission grass(Pennisetum polystachyon, (L.) Schult) litter in Fiji to be 7% of Pg,compared to 26.6% and 34.4% of total Pg in experiments A and Bfor S. spontaneum in our study. The much higher throughfall inter-ception by S. spontaneum may derive from its greater biomass (overan order of magnitude greater than the 0.82 kg m�2 reported byWaterloo) or its higher LAI (4.2 in S. spontaneum versus 0.2–2 inP. polystachyon). Alternatively, we observed that after very heavyrains, large patches of S. spontaneum canopy were beaten downto a horizontal ‘‘lodged” condition. After a series of heavy storms,lodging became permanent, which may have reduced TF, and theterminal velocity of raindrops, or changed the pathway followedby rain to the ground (TF versus SF).

Drying curves and evaporationEven fewer field data are available on rates of litter drying than for

litter water storage. Helvey included line plots of litter drying from acove forest at Coweeta, North Carolina, but did not report the expo-nent (k) (Helvey, 1964) Calculations using the beginning and endpoints of litter water content on Helvey’s (1964) plot implied a k va-lue of 0.0068, which was somewhat smaller than our average k valueof 0.0156. Waterloo (1994) reported a k value of 0.014 in severalCaribbean pine (P. caribaea) forests in Fiji, which is a close matchto our results (Table 3). Waterloo did not measure evaporation andhe assumed that evaporation rates from P. polystachyon grassland lit-ter would be similar to those from litter of P. caribaea, and therefore,no meaningful comparison can be made with evaporation from S.spontaneum in our study. More measurements of evaporation fromlitter layers in a variety of forest types are clearly needed before moregeneral conclusions about the contribution of litter to evapotranspi-ration in the humid tropics can be made.

Litter characteristicsLaboratory studies have found the depth of water stored by lit-

ter layers to be closely related to litter mass. Water storage


capacities in minimally disturbed litter samples from P. radiataplantations and schlerophyll Eucalyptus forest depend strongly onlitter density (Putuhena and Cordery, 1996). Similarly, Sato et al.(2004)found that water storage in coniferous (Cryptomeria japon-ica) and broadleaf (Lithocarpus edulis) litter depended strongly onthe air dry mass of samples. In our pooled samples, WHC was mod-erately dependent on the natural logarithm of oven-dry weight(R2 = 0.36, P 6 0.05). In our multi-species population, other vari-ables, such as average leaf fragment area, the volume of air spaces,the area to volume ratio of leaf fragments, and species-specificabsorptive capacity of the litter necromass will also affect WHC.However, these variables have not, to our knowledge, been mea-sured in any leaf litter study.

Concluding remarks

This study adds to the sparse literature on the litter moisturedynamics of tropical forests by comparing water holding capacity,drainage and evaporation among broadleaved tropical trees grownin plantation and the wild sugar cane S. spontaneum. Water holdingcapacity and the proportions of TF and Pg diverted to daily storageand drainage in our study were broadly similar to values measuredin a range of other temperate and tropical environments. However,litter samples from 5-year old tree plantations held relatively littlewater than all but one of the mature Amazonian forest ecotypesstudied by Marin et al. (2000). These differences could be attrib-uted to the lower necromass of litter in plantations and S. sponta-neum grassland, and the absence of superficial roots in oursamples. In support of this contention, WHC was roughly propor-tional to litter necromass in our study, as it was in several otherlaboratory experiments.

Interspecific statistical comparisons demonstrated that G. sepi-um had lower necromass and WHC, and evaporated les water thanother tree species and S. spontaneum. Other interspecific differ-ences tended to be specific to experiments A or B. We could notconclude, therefore, that planting fast-growing trees would pro-duce litter with different WHC, drainage or evaporation than litterfrom a ubiquitous, albeit unproductive cover of S. spontaneum.Clearly, more studies of leaf litter hydrology in a range of naturaland planted ecosystems are required to improve our overallknowledge base on this important aspect of tropical forestdynamics.

Acknowledgements

We thank the researchers, staff and students of PRORENA, ajoint program between the School of Forestry and EnvironmentalStudies, Yale University, and the Smithsonian Tropical ResearchInstitute’s Centre for Tropical Forest Science, for designing and set-ting up the selection trials. We are particularly grateful to JeffersonHall, Jeanette Egger, Marla Diaz, and Adriana Sautu for ongoingsupport and friendship during field work. Funding for PRORENAis provided by The Frank Levinson Family Foundation, the Gran-tham Foundation and the School of Forestry and EnvironmentalStudies at Yale University. Andrew Park’s research is funded byan NSERC Discovery Grant. M.J. Waterloo and an anonymous re-viewer provided helpful comments on the first draft of this article.

Appendix A. Supplementary material

Supplementary data associated with this article can be found, inthe online version, at doi:10.1016/j.jhydrol.2009.12.033.

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http://dx.doi.org/10.1016/j.jhydrol.2009.12.033


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