Agricultural Water Management 105 (2012) 21–31
Contents lists available at SciVerse ScienceDirect
Agricultural Water Management
journal homepage: www.elsevier.com/locate/agwat
Assessing the ecosystem services supplied by freshwater flows in Mediterranean
agroecosystems
Bárbara A. Willaarts a,∗ , Martin Volk b , Pedro A. Aguilera a
a
b
Department of Plant Biology and Ecology, Carretera de Sacramento s/n, University of Almeria, 04120 Almeria, Spain
Department of Computational Landscape Ecology, UFZ - Helmholtz Centre for Environmental Research, Permoserstr. 15, D-04318 Leipzig, Germany
a r t i c l e
i n f o
Article history:
Received 13 June 2011
Accepted 14 December 2011
Available online 5 January 2012
Keywords:
Green water
Blue water
Agroecosystems
Hydrologic ecosystem services
GIS-based Hydrologic Modeling
a b s t r a c t
Water performs essential ecological functions in agroecosystems and supplies an array of hydrologic
ecosystem services (HES). The nature and quantity of HES is intimately linked with the management
of the territory, and the capacity of the different land uses to partition rainfall into green (evapotranspiration) and blue (runoff) freshwater flows. This paper presents an innovative method to empirically
assess the underlying relationship between the use and management of Mediterranean agroecosystems,
their spatial pattern of green and blue freshwater flow generation and the provision of HES. We test
this approach in Sierra Norte de Sevilla, a characteristic Spanish agro-forestry system. To assess the
hydrological functioning we used the spatially explicit hydrologic model BalanceMED. HES’ identification and societal valuation was done through an expert panel. The hydrologic performance and the
social values ascribed to the different services were combined to identify key provisioning areas or HES
hotspots. Our results show that multifunctional agroecosystems, where agrarian and forestry activities co-exist, optimize the partition and use of freshwater flows and supply the largest bundles of HES
at a wide range of spatial scales. The often low profitability of these extensive activities is prompting
either the intensification or the abandonment of many Mediterranean agro ecosystems. We discuss the
trade-offs in HES associated with these land use trends, and we illustrate the potential options available
for implementing payments for ecosystem services (PES) schemes to pursue “win–win” management
solutions.
© 2011 Elsevier B.V. All rights reserved.
1. Introduction
Water is the most essential component for ecosystem functioning and plays a key role in sustaining human wellbeing
(Falkenmark, 2003). Across the landscape, water flows through
terrestrial and aquatic systems, taking part in multiple ecological
processes and supplying an array of hydrologic ecosystem services
(HES) (e.g. drinking water, food or climate regulation). HES are
defined as “all the benefits ecosystems supply by regulating the
hydrologic cycle” (adapted from Brauman et al., 2007).
The provisioning of HES relies upon the so-called blue and green
water flows (Falkenmark and Rockström, 2004). Green water refers
to the amount of rainfall infiltrated and stored in the soil’s root
zone supporting primary productivity of natural and agricultural
systems through evapotranspiration. Blue water is the amount of
∗ Corresponding author. Present address: CEIGRAM, Edificio Producción Vegetal: Fitotecnia, Campos de Prácticas de Agrónomos, Technical University of Madrid,
28040 Madrid, Spain. Tel.: +34 91 452 49 00x1945; Fax: +34 91 452 48 18.
E-mail address: [email protected] (B.A. Willaarts).
0378-3774/$ – see front matter © 2011 Elsevier B.V. All rights reserved.
doi:10.1016/j.agwat.2011.12.019
rainfall exceeding the soil’s storage capacity that runs downstream
to fed rivers, lakes and aquifers.
The quantity and quality of freshwater flows and HES supply
is closely related to the management of the territory. Vegetation
cover, land use and climate play a critical role in the partition of
rainfall into green and blue water flows (Zhang et al., 2001; Calder,
2005). Currently there is considerable evidence that land conversions have large impacts on the water cycle because they alter the
ratio and condition of freshwater flows in catchments (Farley et al.,
2005; Gerten et al., 2005; Scanlon et al., 2007). Indeed hydrologic
changes linked to global-land-use conversions rival or even surpass
those produced by climate change (Vörösmarty et al., 2000).
Human induced changes on land and water resources have considerable socio-economic consequences (Vörösmarty et al., 2005).
This is primarily because modifications in the regional pattern of
freshwater flows entail significant trade-offs in HES at a wide range
of spatial scales (Foley et al., 2007; Gordon et al., 2005). Variations
in the provision of blue HES ascribed to land changes are well documented (Foley et al., 2005; Schröter et al., 2005), since blue water
supplies are well known to direct market benefits (e.g. water for
irrigation, sanitation or hydropower). However, the extent to which
changes in the management of a territory alter the supply of green
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B.A. Willaarts et al. / Agricultural Water Management 105 (2012) 21–31
HES have largely remained hidden and undervalued, till the importance of green water flows for rain-fed agriculture and the supply
of other water-driven plant services have been explicitly acknowledged (Rockström et al., 1999; Falkenmark and Rockström, 2004;
Gordon et al., 2005, 2010).
Conventional approaches to water management have focused
on managing solely the blue component of the water cycle
(Falkenmark and Rockström, 2004; Jewitt, 2006). This narrow
approach to water management has often failed to secure the provision of blue HES and it has also done poorly to enhance the provision
of off-stream services. The increasing demand for blue water but
essentially the existing ‘green water blindness’ (Falkenmark, 2003)
as well as the overlooked tight relationship between land and water
have been argued as key drivers of many unsuccessful water policies (Scanlon et al., 2007; Tielbörger et al., 2010).
Accordingly, effective water management needs to move
towards the development of “Integrated Water and Land Resources
Management (IWLRM)” approaches (Falkenmark and Rockström,
2004), to better understand land–water interactions, to forecast
intended and unintended consequences of land changes on the
water cycle and to acknowledge the multiple benefits supplied by
freshwater flows (Vörösmarty et al., 2005; Rockström et al., 2010).
Hence, successful IWRLM requires site-specific assessments to provide reliable information on the local hydrology of catchments and
the array of HES provided.
A large proportion of Southern Mediterranean agroecosystems are dedicated to agro-forestry activities, especially along
the marginal mountain areas (García Mora et al., 2003). These
systems support high rates of biological diversity, and their extensive use has contributed over time to sustain and optimize the
nutrient cycles under existing poor soil conditions (Pineda and
Montalvo, 1995). The industrialization process that took place in
many Mediterranean countries after the 1950s caused important
socio-economic changes (e.g. rural migration, prices fall of typical agroecosystem products such as wood, charcoal or wool),
prompting important shifts in the management of these multifunctional systems and altering their hydrological functioning (Gallart
and Llorens, 2003; Otero et al., 2010). Because such changes alter
the flow of HES, it becomes necessary to gain insight regarding
the underlying relationship between land and water, in order to
forecast functional changes and trade-offs in HES under different
resource-use scenarios (Brauman et al., 2007).
Our study assesses the link between the use and management
of Mediterranean agroecosystems, its hydrological functioning and
the resulting flow of HES. Accordingly, this paper has three main
objectives: (1) model the generation of green and blue freshwater flows across Mediterranean agroecosystems; (2) identify
and value the main HES provided by these systems; and (3)
map priority areas for HES provision to devise suitable management options that maximize water benefits for a wide range
of beneficiaries.
2. Methodology
2.1. Study area
Sierra Norte de Sevilla (SNORTE) is a Mediterranean agroecosystem located in the Southwest of Spain (Fig. 1). It covers
an area of approximately 1700 km2 and is located in the central
part of Sierra Morena Mountain range. It includes the headwaters
of three important sub-basins of the Guadalquivir basin, namely
Viar, Huesna and Retortillo. The climate is Mediterranean subhumid, with wet and mild winters and dry and hot summers. Mean
annual precipitation is around 800 mm and annual average temperature is around 16 ◦ C, although there is a high intra-annual
Table 1
Map sources required to run BalanceMED.
Map layers
Format
Scale
Soil units
Land use and cover (year 2003)a
Digital elevation model
Monthly precipitationb
Monthly potential evapotranspirationb , c
Vector
Vector
Raster
Raster
Raster
1:10,000
1:25,000
20 m
100 m
100 m
Source: CMA (2010).
a
The 2003 land use map represented the most updated source of information at
the time this study was conducted.
b
Mean values for the time series 1971–2000. According to the World Meteorological Organization (WMO) this time series represents current mean climatic
conditions.
c
Based on the equation proposed by Thornthwaite (1948).
variability (CMA, 2003). The lithology is mainly composed of low
permeable metamorphic materials (mainly slates, schist, and
quartzite) interspersed with granites and permeable limestones
and marbles. Prevailing soils are Lytic and Eutric Leptosols, poorly
developed, acid and non-suitable for cultivation. Only in the
calcareous areas, Eutric and Chromic Cambisols can be cultivated.
Climate, terrain conditions and soil development have shaped
the landscape of SNORTE. The upper mountains in the northern
part are covered by original Mediterranean forests and woody crops
(mainly olives), whereas the peneplains of the southern part represent agro-forestry ecosystems, locally called “dehesas” (Pineda and
Montalvo, 1995). These agroecosystems result from the opening of
native Mediterranean forests (Quercus ssp.) for grazing (primarily
with Merino sheep, Iberian pigs and autochthonous Retinta cows),
forming a complex mosaic of sparse oak trees mixed with pastures,
crops and shrubs. They are ‘man-made’ ecosystems evolved from
the ingenious and dynamic adaptation of humans to the Mediterranean environment (Plieninger and Schaar, 2008). As is the case
with most of the 2.4 million ha of dehesas existing across Spain
(MARM, 2011), SNORTE has suffered important transformations
in its management in the last decades (Rescia et al., 2010). The
industrialization process after the 1950s and currently the European Common Agricultural Policy (CAP) are both promoting the loss
of its multifunctional use, disrupting its eco-cultural equilibrium
(Schröder, 2005; Willaarts, 2010).
2.2. Hydrological functioning: green and blue freshwater flow
generation
To assess the spatial partition of rainfall into green and blue
freshwater flows we used the hydrologic model BalanceMED
(Willaarts, 2010). It is a semi-deterministic model developed to
quantify the hydrological functioning of Mediterranean catchments using long time series of monthly rainfall and potential
evapotranspiration. Model formulation is written and run in Excel
2007 and the hydrological outputs mapped with ARC GIS 9.2 (ESRI,
2006).
Conceptually, BalanceMED assumes that a fraction from total
precipitation is intercepted (I) by the plant canopy and returned
to the atmosphere through evaporation without reaching the soil.
The remaining precipitation (effective rainfall) reaches the soil and
infiltrates. A significant part of the infiltrated rainfall is either consumed by the vegetation and transpired (T) or directly evaporated
from the soil surface (E) back to the atmosphere. If the infiltrated
water exceeds the soil storage capacity, the remaining flow can
either percolate and recharge aquifers (R) or drain as runoff into
the closest rivers or surface water bodies (Q). Table 1 depicts the
map sources required to run the model. Mean values for climate
variables instead of year to year values were chosen to isolate the
B.A. Willaarts et al. / Agricultural Water Management 105 (2012) 21–31
23
Fig. 1. Geographical location of SNORTE. The light shadow area represents the boundaries of the study area. Catchment limits are represent in light grey.
potential effect of climate variability in the partition of rainfall into
green and blue water flows. Fig. 2 illustrates the different pathways
of water movement simulated by BalanceMED.
To reflect hydrological differences across the territory, SNORTE
was divided into so-called “hydrological units” (HU) by overlaying
the soil and land use map. Each HU represents a defined area with
unique soil, plant and land management characteristics. Parameter
values required to simulate the water movement within each unit
were extracted from databases linked to the different map sources
(Fig. 2). With these inputs BalanceMED estimates mean monthly
values of I, T, E, R and Q. Model formulation is described next.
2.2.1. Interception (It )
It (mm) = PPt − (a × nt )
(1)
PPt is the mean precipitation each HU receives; ˛ is the leaf canopy
interception and nt is the mean number of rainy days in month t
for the time series 1971–2000. ˛ values for the different types of
vegetation covers were extracted from the literature (Breuer et al.,
2003; Díaz et al., 2005).
2.2.2. Transpiration (Tt )
Tt (mm) = min [w, (St − WP)]
Fig. 2. Potential pathways of water movement simulated with BalanceMED.
(2)
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B.A. Willaarts et al. / Agricultural Water Management 105 (2012) 21–31
w is the potential water uptake by plants within a HU (mm); St is
the soil moisture content (mm) in month t and WP is the soil wilting
point (mm). w is a parameter highly influenced by the vegetation
type and soil development within the HU, and was calculated as
(Neitsch et al., 2005):
PTt
× 1 − exp
w(mm) =
1 − exp(−ˇ)
−ˇ × dsoil
droot
(3)
where PTt is the potential water transpiration in month t (mm); ˇ is
a water-use distribution parameter; dsoil is the soil depth (mm) and
droot is the plant root depth (mm) within a HU. ˇ was set constant for
all HU at 10 (Neitsch et al., 2005). dsoil values (mm) were obtained
from the database linked to the soil map; and droot values (mm)
were obtained from the literature (Canadell et al., 1996; Breuer
et al., 2003).
PTt represents only a fraction of the potential evapotranspiration
(PETt ). This fraction is highly influenced by the development stage
of the leaf canopy (r), which is the dimensionless fraction of the
incident beam radiation that penetrates the canopy, calculated as
(Campbell and Norman, 1998):
r = exp[(Kb ) × (LAI)]
(4)
Kb is the canopy extinction coefficient with a constant value of 0.82
(Stockle, 1985) and LAI is the leaf-area index (cm3 /cm3 ). LAI values
for the different types of vegetation types were obtained from the
literature (Breuer et al., 2003). PTt was then calculated as:
PTt (mm) = (1 − r) × PETt
(5)
2.2.3. Evaporation (Et )
Et (mm) = min [PEt , (St − WP)]
(6)
PEt (mm) = r × PETt
(7)
PEt is the potential evaporation from the soil surface; St the soil
moisture in month t and WP is the soil wilting point of the HU.
2.2.4. Groundwater recharge (Rt )
To estimate Rt we incorporate the model APLIS (Andreo et al.,
2004) as a subcomponent of BalanceMED. APLIS was specifically
developed to estimate the mean rate of recharge in carbonate
aquifers in Southern Spain.
A + P + 3L + 2I + S
Rt (mm) = Dt ×
90
Rt (mm) = 0 if St ≤ FC
if St > FC
(8)
(9)
Dt represents the volume of water exceeding the maximum soil
storage capacity within each HU (mm) in month t; St is the soil
moisture (mm); FC is the soil field capacity (mm); A is the mean
altitude; P is the mean slope; I is the infiltration water capacity and
S is the soil texture. A, P, I, L and S are dimensionless, since they
have been previously converted into categorical values following
Andreo et al. (2004).
2.2.5. Surface runoff (Qt )
Qt (mm) = Dt − Rt
(10)
Translated into freshwater flows, Qt represents the surface fraction of the blue water flow (SBW), while Rt is the groundwater flow
(GBW) (Fig. 2). Tt maintains the primary productivity of forests and
agricultural systems, representing therefore a “productive” green
water flow (PGW). It and Et are two vapor fluxes not involved in
maintaining the productivity of systems, and thus both fluxes represent a “non-productive” green water flow (nPGW).
2.2.6. Model validation
To validate model results, monthly volumetric flow rates (VFR)
from the only available gauging station located in the Huesna subbasin within SNORTE (CMA, 2008) were recorded for the time
series 1971–2000. Mean-monthly values of VFR were contrasted
against Qt values provided by BalanceMED, using 4 common model
evaluation statistics (Loague and Green, 1991): (i) mean squared
error (MSE), which describes the squared average of the differences between the estimations and the observed data; (ii) model
efficiency (ME), which indicates how well the plot of observed vs.
simulated values fits the 1:1 line; (iii) coefficient of determination
(R2 ), which indicates the strength of the linear relationship between
the observed and simulated values; and (iv) the coefficient of residual mass (CRM), which indicates if the model estimation is underor overestimated.
2.3. HES identification and valuation
The main driver underpinning the maintenance of HES is instrumental; and relates to the benefits agroecosystems supply to upand downstream users in catchments. Hence, it is crucial to include
the human dimension (e.g. people’s values and preferences) when
performing an ecosystem service assessment (Cowling et al., 2008;
Menzel and Teng, 2010).
The identification and valuation of HES was performed through
an expert panel following a similar approach as Binning et al. (2001)
and Shelton et al. (2001). A questionnaire with a potential list of
HES was sent by to 25 national experts on ecosystem services,
hydrology, agronomy, forestry and local environmental authorities.
In total 18 experts (10 scientists and 8 local managers) participated.
The list of HES was elaborated using the expertise knowledge of the
study area and relevant services identified in other water-related
studies (MEA, 2003; Falkenmark and Rockström, 2004; de Groot,
2006; Brauman et al., 2007). Experts were also invited to complete
the list of HES. Once the final list of HES was agreed among all,
experts were further requested to value the importance of each service based on the benefits it supplies. Value rankings ranged from
0 (none) to 1 (low), 2 (medium), 3 (high) and 4 (very high). Likewise, experts were requested to identify which land uses supply
each identified HES; and indicate the spatial scale (local, regional,
international) at which each service delivers its benefits.
2.4. Mapping HES hotspots
If HES should be maintained in the long run it is necessary to
spatially identify key provisioning areas, also called “HES hotspot”
(Egoh et al., 2008; O’Farrell et al., 2010).
To map the importance of each HU delivering a HES, we took
into account: (1) the biophysical performance of the production
function (freshwater flow); (2) the land use type, since the same
production function can deliver different benefits depending on the
use and management of the territory (de Groot, 2006; Feld et al.,
2009); and (3) the societal value attached to each service. Consequently, the importance of one HU to provide a service (HESscore )
was quantified as:
HESscore = F(x) × Land × Value
(11)
where F(x) is the value of the freshwater flow (either green or blue)
providing the service linearly transformed into a scale from 0 to
1. This transformation implies that HUs with a high evapotranspiration or runoff rate will score close to 1, while HUs with a low
hydrological performance will score close to 0. Land is a dichotomic
variable (0, 1) expressing if the HU supplies or not the HES based on
its land use; and Value expresses the mean societal value assigned
by the experts to each HES (ranking between 0 and 4).
B.A. Willaarts et al. / Agricultural Water Management 105 (2012) 21–31
25
Table 2
Water balance of Monthly (t) values of model outputs (It , Et , Tt , Rt , Qt ) were aggregated to provide mean annual volumes (mm) of green and blue freshwater flows.
Non productive green water flow (nPGW)
Interception
mm/year
Rainfall partition (%)
65.9
9.0
12 t=1
It
Evaporation
12 t=1
Et
47.1
6.5
Individual maps of HESscores were integrated to obtain the HES
provisioning capacity map (HESindex ). To identify hotspot areas, map
values were ranked in three major classes using the quartile classification in ArcGIS® 9.2. Areas with a HESindex above third quartile
are considered HES hotspots.
3. Results
3.1. Hydrological functioning
3.1.1. Rainfall partitioning and model validation
Table 2 shows the annual summary of the monthly outputs provided by BalanceMED. The largest fraction of annual rainfall (43.4%)
is used to support primary productivity of forest and agricultural
systems and therefore represents a “productive green flow”. The
non productive fraction (15.5%) represents a smaller amount and
accounts for all the water losses occurred through canopy or soil
evaporation.
The fraction of rainfall not evapotranspired turns into a blue
water flow. The greatest blue freshwater flow becomes superficial
(almost 24.2% of annual precipitation) and feeds rivers, streams
and small water bodies. The remaining fraction (16.9%) constitutes
a groundwater flow, which percolates deep to recharge aquifers.
Productive green water
flow (PGW)
Blue ground water (GBW)
Transpiration
Aquifer recharge
12 316.4
43.4
t=1
Tt
123.4
16.9
12 t=1
Rt
Blue surface water
(SBW)
Runoff
12
t=1
Qt
176.1
24.2
Table 3
Model evaluation of BalanceMED. Four metrics were calculated to validate model
results: mean squared error (MSE) (range = −∞/+∞, optimum 0); model efficiency
(ME) (range = −∞/+∞, optimum 1); regression coefficient (R2 ) (range = 0–1, optimum 1); and coefficient of residual masses (CRM) (range = 0–1, optimum 0).
Statistics
Value
MSE
ME
R2
CRM
1
0.82
0.75
0.03
Model validation confirms the reliability of BalanceMED to
quantify the spatial pattern of green and blue water flow generation
in the study area (Table 3). The mean squared error (MSE) shows
that the average difference between observed and predicted values
(1 hm3 ) is equivalent to 25% of the average monthly blue surface
runoff (4.3 hm3 ) recorded in the gauge station of the upper Huesna
sub-basin. ME value indicates that BalanceMED performance is satisfactory according to the model performance assessment provided
by Moriasi et al. (2007). The R2 shows a good fit, implying that
75% of the variation found in the volumetric flow rates (VFR) is
accounted by the BalanceMED when modeling surface runoff (Qt )
values. CRM is slightly above zero, implying that surface runoff is
somewhat overestimated.
Fig. 3. Mean annual values (mm) of (a) non-productive green water (nPGW); (b) productive green water (PGW); (c) blue surface water (SBW); and (d) blue groundwater
(GBW).
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B.A. Willaarts et al. / Agricultural Water Management 105 (2012) 21–31
accounting for 26–30% of annual rainfall (Fig. 4). Only in woody and
abandoned crops the fraction of groundwater recharge becomes
more important (30%), mainly because these land uses extend along
the calcareous and permeable mountain areas in the north. Most
water bodies (e.g. rivers, reservoirs and ponds) store rainfall as surface runoff, although a small fraction (<15%) is normally infiltrated,
and contributes to deep water recharge.
3.2. Identification and valuation of HES
Fig. 4. Rainfall partition (%) into productive green water (PGW), non productive
green water (nGPW), surface blue water (SBW) and blue groundwater (GBW) flows
in the different land uses.
3.1.2. Influence of the use and management of the territory in the
generation of freshwater flows
The diversity of orographic, lithological and climate characteristics as well as the different land use management types are the
underlying drivers of the heterogeneous spatial pattern of green
and blue freshwater flows found in the study area (Fig. 3). The
highest rates of evaporated or non-productive green water occur
in the northern half, in calcareous HUs mainly dedicated to grow
woody crops and where vegetation cover is small (Fig. 3a). On the
contrary, the highest rates of transpired or productive green water
flows overlap with HUs spread across SNORTE presenting a high
forest cover (Fig. 3b).
The greater surface flows of blue water are generated in
the western part, in metamorphic HUs with steep slopes and
mainly covered by shrubs (Fig. 3c). In contrast, the highest rate
of groundwater recharge occurs in the northeast, overlapping with
permeable calcareous HUs with a mixture of land uses (Fig. 3d). The
predominance of surface flows is related with the high impermeability and complex orography of SNORTE, which promotes short
and fast water courses in the medium and upper stretches (CMA,
2003).
Fig. 4 quantifies the effect of vegetation and land management on the partition of rainfall into green and blue water flows.
Extensively managed HUs with a medium to high vegetation cover
(e.g. Mediterranean and riparian forests, afforestation, shrubs, and
dehesas with or without shrubs) have large soil moisture requirements to maintain their primary productivity, and therefore the
largest fraction of effective rainfall (between 52 and 57%) is invested
in producing green water flows. On the contrary, HUs subjected to
a more intensive use and with a lower vegetation cover (e.g. crops
and pastures) consume on average less green water (<50% of total
rainfall). These differences in green water consumption between
land uses are statistically significant (ANOVA test, p-value < 0.001).
Remarkable differences can be found as well when comparing
the ratio (%) of productive and non-productive green water consumption (Fig. 4). On average, crops and pastures HUs evaporate a
larger fraction of green water (19–22%), compared to forests, shrubs
and dehesas (10–15%). This implies that denser vegetated HUs are
more efficient in terms of water used to produce a unit of biomass
(Rockström et al., 1999; Falkenmark and Rockström, 2004) as they
have less water losses through evaporation.
The fraction of rainfall diverted to blue water is influenced by
the vegetation cover and management but not its allocation into
surface or groundwater flows. Since the majority of SNORTE has
a low permeability, surface flows predominate in most land uses,
According to the experts’ criteria SNORTE provides nine HES
(Table 4). Five out of these nine services are green water dependent, while the remaining four are of blue nature. Most valued
services (scores between 3 and 4) are forage, drinking water, flow
regulation, recreation, olive crops and cork production. Less valued services (scores between 1 and 2) are meso-climate regulation
and hydropower generation. The maintenance of aquatic biodiversity is a HES with intermediate importance (scores between 2 and
3).
Grouping the nine HES according to the ecosystem services categories proposed by the Millennium Ecosystem Assessment (MEA,
2003), we found that cultural and provisioning HES are on average
more valued than regulating services, but these differences are not
statistically significant (Kruskall–Wallis test; p > 0.05). Likewise, no
significant differences were found when comparing the societal
value of green and blue water dependent services (Kruskall–Wallis
test; p > 0.05). Differences found among HES’ values appear to be
more influenced by the scale of benefit delivery (Fig. 5). The majority of HES supply their benefits upstream and downstream (Fig. 5a).
However, SNORTE’s hydrological functioning also benefits stakeholders beyond its borders – at regional and European scales –
by regulating the meso-climate and preserving some important
threatened European aquatic species (for example the fire salamander (Salamandra salamandra), the lataste’s viper (Vipera latestei) and
the water vole (Arvicola sapidus)). As Fig. 5b shows, HES delivering their benefits downstream and upstream are significantly the
most valued services. HES providing their benefits at greater spatial
scales are less valuable from a societal perspective.
3.3. HES hotspots
Fig. 6a identifies key provisioning areas or HES hotspots within
SNORTE. Most hotspots are located in the northern half and in the
central part and occupy 38% of SNORTE’s area. Areas with a medium
HES index extend mainly along the central and southern part and
occupy 28% of total area. The remaining 34% of the study area shows
low capacity to deliver HES, and most of these areas are located in
the northern and eastern part.
The performance of the three main HES provisioning areas
(low, medium and hotspot) is described in Fig. 6b. Hotspot
areas supply the largest bundles of HES and exhibit the greatest biophysical capacity to supply most services. These areas are
important providers of blue-water-dependent HES, whose benefits are enjoyed downstream and at greater spatial scales (e.g.
European). HES’ hotspots are also the greatest suppliers of onsite
green water benefits through the provision of cork and forage
and to a lesser extent meso-climate regulation (Fig. 6b). Areas
with a medium capacity to provide HES supply less green water
dependent services and their mean performance to deliver benefits at different spatial scales decreases significantly. Lastly, low
HES production areas show very little capacity to provide HES, and
the most important (green) benefits are accrued locally through
the production of olive crops, forage and regionally via climate
regulation.
Differences encountered in the HES provisioning capacity are
intimately linked with the vegetation cover and management of
B.A. Willaarts et al. / Agricultural Water Management 105 (2012) 21–31
27
Table 4
Hydrologic ecosystem services (HES) supplied by SNORTE and associated freshwater flows involved their provision. Societal value refers to the mean value assigned by the
different experts to each HES (minimum value 0; maximum 4).
Typology
Hydrological asset
HES
Societal value
Cultural
Blue water (surface and groundwater)
Recreation (fishing and swimming)
Maintenance of aquatic biodiversity
3.25
2.50
Productive Green water
Forage
Olive crops
Cork
Drinking water
Hydropower
3.75
3.13
3.00
3.38
1.00
Flow regulation
Meso-climate regulation
3.38
1.63
Provisioning
Blue water (surface runoff)
Regulating
a
Green water reservoir
Green watera
Productive (transpired) and non-Productive (evaporated).
Fig. 5. Richness (a) and societal values (b) of HES supplied by SNORTE at several spatial scales. Different letters indicate significant differences in HES value across delivering
scales (Kruskal–Wallis Test; p < 0.05).
the territory (Fig. 7). Areas with a relatively high woody vegetation cover provide larger bundles of HES compared to those that
have been intensified to maximize the supply of one set of HES
(e.g. olive crops and forage) and where the land cover is low thicket
or even artificial. Likewise, areas extensively used where native
forests coexist with dehesas that are mainly used for livestock
production, supply a greater flow of HES when compared to fully
natural or even abandoned areas.
4. Discussion
Over half of the total annual rainfall that SNORTE receives turns
into green water and is largely used to support primary productivity of forest and agricultural ecosystems. This rate of green water
consumption is lower than the value estimated for the Guadalquivir
basin as a whole, where the mean annual evapotranspiration represents around 80% of the annual precipitation (GBA, 2010). The
Fig. 6. HES provisioning map (a) and bundles of HES (b) supplied by the different provisioning areas.
28
B.A. Willaarts et al. / Agricultural Water Management 105 (2012) 21–31
Fig. 7. Correspondence analysis between landscape structure and HES provisioning
areas. Landscape cover and management explains 95% of the variance shown by the
different uses found in SNORTE when supplying HES (2 -test; p < 0.05).
lower rates of green water consumption quantified in SNORTE are
to a large extend related to the fact that soils in this mountain area
are poorly developed (CMA, 2004), limiting the soil moisture content and thus the capacity of vegetation to consume larger volumes
of green water. This small soil water storage capacity is probably the
main reason why vegetation in this area is subjected to significant
water stress compared to other areas within the Guadalquivir basin,
CMA, 2011). Nevertheless, the rate of rainfall diverted to green
water is in agreement with the calculations obtained by Zhang
et al. (2001). This author found that in regions with an aridity index
(PET/PP) close to 1, evapotranspiration rates of mixed vegetation
types range between 55 and 60% of annual rainfall.
In addition to physical factors, land management also exerts
considerable influence on the partition of rainfall in the study area.
The opening of the original Mediterranean forest and its conversion
to dehesas and pastures has reduced the evapotranspiration rates
by 2% and 8%, respectively (cp. Fig. 4). Joffre and Rambal (1993),
however, found that differences in evapotranspiration rates across
land uses in SNORTE largely depend on the precipitation regime. In
a humid year differences in the evapotranspiration rates between
forest and pastures remain below 15% depending on the location,
rainfall amount and soil properties. However, in dry years when
water requirements for vegetation are not met, forests can consume up to 62% more green water than pastures, mainly because
trees have larger root systems and therefore access to deeper water.
Farley et al. (2005) also found that land cover changes have a larger
effect on the water balance of catchments in dry regions. Accordingly, the maintenance of an open mixed-agrarian landscape with
pastures and dehesas represents an effective adaptation measure
from a hydrological perspective to the frequent droughts affecting
SNORTE and surroundings.
From an ecosystem service perspective, the hydrological
changes linked to the domestication of the Mediterranean forests
have influenced the capacity of the study area to supply HES at a
wide range of scales. Nowadays, the greatest flow of water-related
benefits is of green nature despite the overall well known socioeconomic importance of blue services. Tielbörger et al. (2010) also
found that green water flow supplies some of the most important
ecosystem services in arid Mediterranean ecosystems.
Despite the flow’s color supplying the service, SNORTE supplies
the largest number of water-related benefits beyond its borders,
mainly downstream but also at larger scales. This spatial mismatch
between service production and enjoyment its benefit is a common feature within ecosystem services assessment (Hein et al.,
2006; Fisher et al., 2009). Among blue water dependent services
this is of special importance, since their benefit enjoyment is determined by the direction of the blue flows (Fisher et al., 2009); and
thus away from the production source. Green water dependent services show a higher spatial overlapping since they are produced and
enjoyed mainly in situ (except for meso-climate regulation and flow
regulation). From a management point of view, the large spatial
disconnection between service production and benefit enjoyment
implies that changes in the land management within SNORTE will
exert the largest impacts beyond its borders.
To support the continuous supply of HES by SNORTE, the HES
index map elaborated in this study provides a valuable piece of
information for decision makers. On the one hand, it illustrates
the areas with the greatest biophysical performance to provide
HES. Moreover, it incorporates social preferences for HES based
on the opinion of local and national experts. Heretofore, most of
the spatial assessments have mapped ecosystem services hotspots
by overlapping existing biophysical information but disregarding
stakeholders’ preferences (Chan et al., 2006; Egoh et al., 2008;
O’Farrell et al., 2010). But avoiding the human dimension and people’s values in ecosystem planning runs the risk of making the
whole attempt of securing services irrelevant for policy making
(Cowling et al., 2008; Menzel and Teng, 2010).
The combination of both dimensions – social and ecological –
helped to evidence a major finding in this research: the maintenance of an heterogeneous landscape mosaic where agro-forestry
land uses (dehesas) coexist with Mediterranean forests not only
enhances high rates of biological diversity in this part of the
Mediterranean basin (Pineda and Montalvo, 1995; Plieninger and
Wilbrand, 2001), but also optimizes the provision of HES at a wide
range of spatial scales.
Several studies (Schröder, 2005; Rescia et al., 2010; Willaarts,
2010) have described an ongoing trend of livestock intensification in SNORTE, which is causing an overall decrease in forest and
shrubby vegetation cover in many farms. In principle, this trend
could be beneficial for the downstream areas since it increases
blue water availability. However, as livestock densities increase so
does the probability of having water quality problems, which might
hamper the overall supply of blue water-related services. To our
knowledge no specific studies have been conducted to assess this
particular issue in SNORTE. Nevertheless, the European Nitrogen
Assessment (Sutton and van Grinsven, 2011) stresses that currently
one third of the total farm input of nitrogen to soils in Europe comes
from animal manures linked to livestock intensification; and that
the fraction of nitrogen in animal manures that is lost to the environment is typically twice the mineral nitrogen fertilizer from plant
production.
Along with the livestock intensification process, Schröder
(2005) and Rescia et al. (2010) also observed an expansion of shrubs
across dehesas, pastures and crops resulting from the abandonment
of traditional forestry practices in SNORTE. This woody expansion
has the opposite hydrological impact, as it increases the demand
for green water, reducing the generation and availability of blue
water and related services.
These observed land use trends taking place in SNORTE result
from the shift dehesas have experienced in their land management
over recent decades, away from a diverse agro-silvo-pastoral system to a much simpler modern pastoral-hunting scheme (Willaarts,
2010). According to Schröder (2005) and Rescia et al. (2010) the
major drivers of such changes are related with: (1) the low demand
for many of the main traditional dehesa products (e.g. wood-related
products), which contributes to the abandonment of forestry
practices; (2) the need to maintain farm profitability, which is causing the increase in livestock densities (number of animals/unit
of area), especially of bovine and porcine animals; and (3) the
increased demand for hunting as a recreational activity in the larger
B.A. Willaarts et al. / Agricultural Water Management 105 (2012) 21–31
farms – i.e. big landowners who pursue this activity because it is
very profitable and socially prestigious, but they have an untied
relationship with their lands and disregard most traditional activities.
In an attempt to maintain dehesas’ multifunctional landscapes,
the Regional Environmental Government of Andalusia signed in
2006 the so-called “Dehesa Agreement” (CMA, 2006). This pact
sought to join efforts among different institutions and landowners
to promote the maintenance of these agroecosystems in southern Spain and their flow of services. However, and despite the
institutional interest, the lack of economic incentives to promote
the implementation of specific sustainable forestry and agrarian
practices continues to threaten the persistence of these cultural
systems. One way to overcome the loss of these heterogeneous agricultural landscapes and maximize the supply of services could be
through the implementation of the so-called ‘Green Water Credits’ (GWC) (Grieg-Gran et al., 2006). GWC is an innovative scheme
of payments for ecosystem services (PES), where landowners are
paid for specific land and soil management activities to secure the
provision of different freshwater services at source (Grieg-Gran
et al., 2006). Such a PES scheme could be applied and enforced
by local institutions in southern Spain but also by the EU Common Agricultural Policy (CAP). Currently, the CAP is discussing
a new mechanism to subsidize famers based on the green farm
practices they apply, in an attempt at “greening the CAP” (Kaley
and Baldock, 2011). The implementation of GWCs seems feasible under this new approach to subsidize agriculture in Europe,
particularly in agroecosystems of Southern Europe where agricultural productivity is low but ecosystem and cultural values are very
important.
Nevertheless GWCs as any other PES scheme should be regarded
as an economic complement, rather than a substitute, to other
ongoing initiatives like: (1) the development of commercial
strategies promoting the consumption of ‘dehesa products’ with
denomination of origin (Schröder, 2005); or (2) the development of alternative sources of income through the ecotourism
or sustainable gaming activities (Rescia et al., 2010). Overall, the
implementation of a PES scheme could contribute to maintain and
recover landscape multifunctionality in SNORTE, enhancing the
supply of HES and associated benefits to a wide range of spatial
scales. However, the “reversibility” in ES loss (Rodríguez et al.,
2006) remains uncertain even if the ongoing landscape trends
(intensification and abandonment) could be reversed. Foremost
because ecosystems are complex and changes do not occur linearly
and in predictable ways; and thus, it is difficult to forecast intended
environmental changes (de Fries et al., 2004; Carpenter et al., 2009).
Nevertheless, to the extent that ecological knowledge can quantify
the ecosystem response to varying scales resulting from changes
in land use and management, the assessment presented in this
paper can inform decision makers about potential trade-offs that
arise under various land management scenarios and future measures for optimizing the supply of HES for up- and downstream
users.
5. Conclusions
Up-to-date quantitative studies assessing the underlying relationship between the management of ecosystems, their ecological
functioning and the associated flow of services have been scarce.
Our research represents a step forward, as we have developed a method to empirically assess the link between land use
and management of agroecosystems, its hydrological functioning and the supply of water-related services. We applied this
framework to one particular region but we expect it to be
applicable to other Mediterranean agroecosystems facing similar
trends.
29
To provide relevant information for achieving IWLRM we have
identified key HES hotspots. As opposed to most ecosystem services mappings performed so far, HES hotspots in this study were
identified by taking into account the biophysical performance of
the different land uses but also social’ preferences for the different
services. Including both the societal and biophysical dimension in
ecosystem management increases the reliability of the information
provided for decision makers and ecosystem managers (Cowling
et al., 2008; Menzel and Teng, 2010).
A major finding of our research is that maintaining a multifunctional use of Mediterranean ecosystems combining agrarian
and forestry practices optimizes the use of freshwater flows and
generates the larger bundles of HES. The importance of promoting
multifunctionality in landscapes for ecosystem service provision
has been highlighted previously (de Fries et al., 2004; Gordon
et al., 2010; O’Farrell et al., 2010). However, to our knowledge
this is the first time empirical research has been done in this
direction.
Most HES benefits are delivered away from the source of production of freshwater flows; thus, changes in the management of
mountainous agroecosystems will have important implications for
a wide range of ecosystem service beneficiaries (e.g. locals but
downstream users as well). In the Mediterranean region, ongoing processes of land abandonment reduce the efficiency of green
water use since most green-provisioning HES are lost. Moreover,
shrub encroachment and forest expansion reduces the availability
of blue water, diminishing the supply of services downstream. Likewise, land use intensification resulting from an increase in livestock
density might prevent shrub and woody vegetation expansion, and
thus it can help to reduce green water demand by vegetation. However, the impacts on water quality might alter the flow of blue water
dependent services downstream.
Overall, most of the changes in Mediterranean agroecosystems
result from the current low profitability of traditional farm practices. Bearing in mind the multiple non-market benefits these
systems provided, it seems reasonable to explore options for setting up PES schemes such as “Green Water Credits”. Such schemes
could help to achieve “win–win” solutions by incentivizing land
owners to improve land management, and at the same optimize
provision of multiple water benefits for other stakeholders.
Acknowledgements
This research was supported by the Regional Environmental Government of Andalucía through the project “Ecological and
Socio-economic Assessment of the Ecosystem Services supplied by
the Network of Protected Areas in Andalusia” (UAL-CG 400431). The
authors acknowledge the valuable comments for the manuscript
provided by two anonymous reviewers, who helped to focus and
make improvements to the paper.
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