Optimising ecosystem services provided by grassland systems 4/Session IV - Estuary... · The value...
Transcript of Optimising ecosystem services provided by grassland systems 4/Session IV - Estuary... · The value...
Federal Department of Economic Affairs,
Education and Research EAER
Agroscope
www.agroscope.ch I good food, healthy environment
June 20th 2018, EGF 2018, Cork, Ireland
Optimising ecosystem services provided by grassland systems
Huguenin-Elie O., Delaby L., Le Clec’h S., Moreno G.M., Teixeira R.F.M. and Schneider M.K.
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Acknowledgments
Luc Delaby, INRA, France
Solen Le Clec’h, ETHZ, Switzerland
Gerardo M. Moreno, Uni of Extremadura, Spain
Ricardo F.M. Teixeira, Uni de Lisboa, Portugal
Manuel K. Schneider, Agroscope, Switzerland
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Ecosystem services (ESS): a broadly used concept
Two milestones followed by
an explosion:
1997:
Costanza et al. The value of the world’s
ecosystem services and natural
capital. Nature
Daily, G.C. (Ed.) Nature's services. Societal
dependence on natural
ecosystems
2005: Millennium ecosystem
assessment (MEA)
Castro & Arnauld de Sartre, 2014
Nu
mb
er
of
pu
blic
atio
ns
Production of scientific articles related to
ecosystem services (as of 25.03.2013)
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Carbon storage in soil Regulation of nutrient cycles
Agricultural yield Biodiversity conservation
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Overview of the presentation
Optimising ecosystem services (ESS) at the field scale
Management intensity as a main driver
Improvement measures based on plant traits and the
structure of the vegetation
Considering the farm and the landscape scale
Within agriculturally used grasslands
Not cropping grassland systems
Not abandoned managed systems
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Contribution of the ecosystems to human well-being
CICES V4.3 (Haines-Young & Potschin, 2013)
«Ecosystem services retain a
connection to the underlying
ecosystem functions, processes
and structures that generate them.»
«Ecosystem goods and benefits
are things that people create or
derive from final ecosystem
services»
► co-production involving the
ecosystem + agricultural inputs (Palomo et al., 2016)
Crude protein yield of grass-
clover mixtures (kg N ha-1)
Data from Nyfeler et al., 2011
Total
From the
ecosystem
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1. Optimising ESS at the field scale
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1.2 Management intensity as main driver
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Management intensity modifies the plant community and increases biomass yield
Huguenin-Elie et al., 2017; Data from surveys and experiments
0 4 8 12 16
0
2
4
6
8
10
12
14
16
0 50 100 150
0
2
4
6
8
10
12
14
16
1 2 3 4
Grass Clover Mixture
N Fertilisation
1-2 Cuts 5-6
Walter Dietl
Annual yield (t DM ha-1)
Walter Dietl
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Management intensity decreases the value of grassland for biodiversity conservation
Number of mechanical operations
0 5 10 15 20 25 30
Num
ber
of
pla
nt
specie
s
10
20
30
40
50
60
70
BioBio FP7, Case study Switzerland
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Yet another optimal management intensity for carbon storage in soil
Management intensity at the field scale
Go
od
s a
nd
se
rvic
es
Agricultural yield
C storage in soil
Biodiversity conservation
Keynote presentation on C sequestration by K. Klumpp & D.A. Fornara
Soussana and Lemaire, 2014; Ward et al., 2016; Dumont et al., 2016
Still large uncertainties on the size of the effect
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1.3 Improvement measures based on plant traits and vegetation structure
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Complementarities among species enhance yield at all levels of intensity
Data from Weigelt et al., 2009 Data from Nyfeler et al., 2009
12 4 8 16
0
2
4
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10
12
14
16
0 50 100 150
0
2
4
6
8
10
12
14
16
1 2 4
Grass
Clover
Grass-CloverAnnu
al yie
ld (
t D
M h
a-1
)
2 N Fertilisation
1-2 Cuts 5-6 Number of plant species
Low intensity High intensity
1
2
1 2
Effect of management
intensity
Effect of plant species richness
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Complementarities among species promote high yield at high digestibility
In many cases, an increase in
biomass yield is at the
expense of forage digestibility (e.g. Pontes et al., 2007).
This is not the case when the
yield is improved by optimizing
the legume proportion.
Suter et al., in preparation;
Sturludóttir et al., 2014
Yield
Legume proportion (%)
Digestibility
% m
axim
al yie
ld r
esp.
dig
estibili
ty
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Diversifying vegetation structure for biodiversity conservation
Uncut refuges on 10–20% of the meadow
area (for low management intensities)
Meadows with refuge compared to
Control meadows
Plant- and leafhoppers (Hemiptera) 0
Wild bees and bumblebees +
Orthopterans +
Mole- and Volehills 0
Butterflies +
Moths 0
Spiders 0
Parasitoid wasps 0
Hoverflies (Diptera: Syrphidae) +
Ground beetles +
Rove beetles (Staphylinidae) 0 Humbert et al., 2012; Buri et al., 2016;
Bruppacher et al., 2016; Meyer et al., 2017
J.-Y. Humbert, Uni Bern
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Diversifying vegetation structure for biodiversity conservation
Presence of trees
Moreno et al., 2016
Number of species
(estimated total on 40 field)
Open
pastures
Wood
Pastures
Plants 253 ±6 289 ±8
Bees 25 ±3 26 ±3
Spiders 65 ±6 75 ±8
Earthworms 8 ±1 11 ±1
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Wooded pastures and C storage in soil
2 m 5 m 15 m
a
ab
b
A A A
So
il ca
rbo
n c
on
ten
t (g
C k
g-1
)
Soil depth
(cm) Howlett et al., 2011
Fornara et al., 2017, Temperate climate: Not more total SOC, but more in
resilient C pools with trees.
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Combining rooting depths to improve nutrient capture
Shallow roots
(SR)
Deep roots
(DR)
Non N-Fixing
(NNF)
Lolium perenne
(Lp)
Cichorium intybus
(Ci)
N-Fixing
(NF)
Trifolium repens
(Tr)
Trifolium pratense
(Tp)
Mixture effect between shallow and
deep rooting species on N capture
Husse et al., 2017
p < 0.001
+ 12 % for NF species
+ 17 % for NNF species
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Summary for the field scale
Antagonisms among ESS along the management intensity gradient.
Various improvement measures using plant traits exists at the field
scale. Some promote several ESS.
Specific improvement
measures
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Summary for the field scale
Antagonisms among ESS along the management intensity gradient.
Various improvement measures using plant traits exists at the
field scale. Some promote several ESS.
None of them seems to alleviate the antagonisms among ESS
that exists along the management intensity gradient.
Specific improvement
measures for:
Forage production
Biodiversity
C storage
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2. Considering the farm and landscape scale
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Considering the diversity in grassland types for biodiversity conservation
Bottom Slopes
Intensive 31 ±0.9 40 ±2.1
Extensive 40 ±2.5 46 ±1.7
Plant species richness at the field scale
Plant species richness at the farm scale
100%
intensive bottom
100%
extensive slopes
25% of each
grassland type
Model farms
with 20 fields
110 ±8.6 175 ±5.3 169 ±9.3
Bottom Slopes
Int. Ext.
Int. Ext.
MultiSward FP7
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Looking for trade-offs between production and biodiversity at the farm scale
Gradient of
management
intensity
Same dry
matter yield
100% intermediate intensity
100% mediocre forage
(5.2 MJ NEL/kg DM in cut
forage*)
75% intensive & 25% extensive
90% good forage (5.8 NEL or
more*) for the dairy cows
10% poor forage (4.5 NEL*) for
the rearing calf** and dry cows.
Can be efficiently used by farms
with on-farm dairy replacement
(and 25% yearly replacement
rate)
Farm
*Swiss Feed Database **Sejrsen and Purup, 1997
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Mapping ESS
Le Clec’h et al., 2017 Biodiversity (index)
Remote sensing data
Maps of ESS
Vegetation C stock (Mg ha-1)
Sampling points
• Measurements of ESS indicators
• Remote sensing data
Identification of main
drivers
Classes of land cover
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Casal et al. Under review at JAS
• Catchment dominated
by intensive mix farming
• 12 years simulation,
mean 3 last years
Effect of the location of unfertilized cut grasslands on nutrient capture (nitrates)
BMP 1) Sources Interception
Cut 0N grassland (% area) 0 15 15
N inputs (kg ha-1) 192 164 172
N excess (kg ha-1) 84 59 61
N-NO3 concentration (mg l-1) 13.3 12.7 11.1
1) BMP: Best Management Practices
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The relationship between two ESS depends on the location
Li et al., 2017
ESS1: Primary production
ESS2: Soil conservation
Synergy**
Synergy*
Synergy
No relationship
Antagonism
Antagonism*
Antagonism**
Relationship ESS1–ESS2
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Summary for the farm and landscape scale
The farm scale offers possibilities to alleviate the antagonisms
among ESS that exists along the management intensity gradient
at the field scale.
Accurately mapping ESS is crucial for developing approaches to
optimise multiple ESS. But this is challenging because it would
need to account for:
► the effects of the diversity in grassland types
► the location of the grassland in the landscape
► the relationships among ESS
► the effect of the location on the relationships among ESS
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Vision
To optimise multiple ESS, we could (or should):
combine specific measures at the field scale with farm or
landscape approaches,
further develop approaches based on plant traits, as well as
tools allowing considering the landscape scale,
promote a variety of grassland types and optimise their spatial
location considering the surrounding nonfarm habitats.
Intensity at the farm scale
Goods a
nd s
erv
ices
High Nature Value
nonfarm habitats
Str
ea
m
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Thank you for your attention
Olivier Huguenin-Elie [email protected]
Agroscope good food, healthy environment
www.agroscope.admin.ch
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Combining rooting depths to improve nutrient capture
Shallow
roots (SR)
Deep
roots (DR)
Non N-
Fixing
(NNF)
Lolium
perenne
(Lp)
Cichorium
intybus
(Ci)
N-
Fixing
(NF)
Trifolium
repens
(Tr)
Trifolium
pratense
(Tp)
Mixture effect between
shallow and deep rooting
species (SR x DR)
Husse et al., 2017
p < 0.001
+ 17 % for NNF species
+ 12 % for NF species
Shift in vertical niche
Community type
Sp. SR DR SR+DR p
Lp 43 33 <0.01
Tr 45 33 <0.05
Ci 45 57 =0.05
Tp 53 65 =0.07
15N 30cm / (3+30cm) in %
SR x DR effect on annual N yield
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Synergies with appropriate restoration of degraded grasslands
SBP:
Sown Biodiverse
Pastures
DG:
Degraded
Grasslands
Teixeira, 2010; Teixeira et al., 2011
Effects of sowing biodiverse
pastures rich in legumes:
Yield
SBP > DG
C sequestration
SBP > DG
Insects
• Species richness: SBP = DG
• Abundance: SBP > DG