New concepts and methods to describe model and
quantify ecosystem services on different and multiple
spatial and temporal scales (Part 1)
Roberta Aretano
robertaaretano@alice.it
Ecosystem services are the conditions and processes through which natural ecosystems,
and the species that make them up, sustain and fulfill human life (Daily 1997).
Ecosystems like forests, grasslands, mangroves, and urban areas provide different goods
and services that are of value to people. These include provisioning services such as food
and water; regulating services such as flood and disease control; cultural services such as
spiritual, recreational, and cultural benefits; and supporting services, such as nutrient
cycling, that maintain the conditions for life on Earth (MEA, 2003). Ecosystem services
affect human well-being and all its components, including basic material needs such as
food and shelter, individual health, security, good social relations, and freedom of choice
and action (MEA, 2005).
Ecosystem services are provided at various spatial and temporal scales. Scale refers to
the physical dimension, in space or time, of phenomena or observations (O’Neill and King,
1998) and is expressed in physical units, such as meters or years. Some ecosystem
services are local (provision of pollinators), others are regional (flood control or water
purification), and still others are global (climate regulation). Traditionally, ecologists have
estimated ecological variables without much regard for location and to date, there has
been relatively little elaboration of the various spatial and temporal scales at which
ecosystem services are supplied (MEA 2003, Turner et al. 2003). Hence, there is a need
to examine the various scales at which ecosystem services are generated and used.
The ecosystem services listed in Costanza et al. (1997) can be collected into five
categories according to their spatial characteristics (Costanza, 2008):
1) Global non-proximal (they do not depend on proximity): Climate regulation, Carbon
sequestration (NEP), Carbon storage, Cultural/existence value;
2) Local proximal (depends on proximity): Disturbance regulation/ storm protection, Waste
treatment, Pollination, Biological control, Habitat/refugia;
3) Directional flow related: flow from point of production to point of use: Water
regulation/flood protection, Water supply, Sediment regulation/erosion control, Nutrient
regulation;
4) In situ (point of use): Soil formation, Food production/non-timber forest products, Raw
materials;
5) User movement related: flow of people to unique natural features: Genetic resources,
Recreation potential, Cultural/aesthetic.
The ecosystem services, as the ecosystems they are provided by, can be also classified
according to their temporal characteristics: Cycling with high/low frequency; Predictability;
Trend vs. Constant provision/use; Way of change (continuous/threshold) (Levin, 2006).
In assessing ecosystem services, scale matters for many reasons. First, ecological and
social systems and processes operate at a wide variety of scales—from very small and
short to very large and long—and between scales they can change in their nature and
sensitivity to various driving forces. It cannot be assumed that results obtained at one
scale are automatically valid at another (Kremen et al. 2000). The application of the same
approach at different spatial scales can be seen in the context of “scale transformation”
that has been criticized both for technical and for conceptual reasons (Milne and Cohen,
1999). Scale transformation is problematic because the spatial structure and the
corresponding geostatistical properties of a scene change with scale (Openshaw, 1984).
Model calibrations developed at one scale are not readily applied at others (O’Neill and
Rust, 1979; O’Neill et al., 1996); they may be further complicated if many variables are of
interest (Levin, 1992; Pierce and Running, 1995).
Second, cross-scale interactions exert a crucial influence on outcomes at a given scale
and focusing solely on a single scale can miss these interactions. In addition real-space
models are needed to represent the relationships between sources and sinks that affect
fluxes of ecosystem services, as identified by Milne and Cohen (1999) for fluxes of
nutrients. Moreover, analyzing scales is important in order to reveal the interests of
different stakeholders in ecosystem management.
Starting in the late 1960s, there has been a growing interest in the analysis and valuation
of the multiple benefits provided by ecosystems. This interest was triggered by an
increasing awareness that the benefits provided by natural and semi-natural ecosystems
were often underestimated in decision making (Odum and Odum, 1972). Since then,
economic valuation of ecosystems has received much attention in scientific literature and
several studies have provided frameworks for the valuation of ecosystem services
(Costanza et al., 1997; Turner et al., 2000; De Groot et al., 2002; MEA, 2005).
While much attention has focused on the economic theory and practice of environmental
value transfer itself, the spatial and temporal dimension to economic valuation has barely
been investigated (Eade and Moran, 1996). Ecosystem services are supplied to the
economic system at a range of spatial and temporal scales, varying from the short-term,
site level (e.g., amenity services) to the long-term, global level (e.g., carbon sequestration)
(Turner et al., 2000; Limburg et al., 2002;). Time changes the value of things therefore the
supply of ecosystem services will often be variable over time, and, where relevant, both
actual and potential future supplies of services have to be included in the valuation
(Barbier, 2000).
Landscape Science can contribute to develop ES valuation in terms of incorporating scale
and evaluating spatial temporal variability.
Ecosystem services are generated at different, sometimes overlapping, ecological scales
and furthermore exploited at multiple social scales, with possible scale-mismatching and
cross-scale interactions (Petrosillo et al. 2008). Recognizing that ESs are characterized by
spatial cross-scale interactions, the moving window algorithm can be used to measure
composition (amount) and spatial configuration (contagion) of ecosystem services along a
continuum of scales (Petrosillo et al., 2008 (Salzau). This is a way to approach landscape
complexity from the perspective of ‘‘content and context’’, giving the same importance to
the amount and spatial configuration of ecosystem services, with the aim to investigate
causes, processes and possible consequences of driving forces, i.e. land use, and
decision making at various scales (Zurlini et al., 2007). The use of a multiscale approach
that simultaneously uses larger- and smaller-scale assessments can help identify
important dynamics of the system that might otherwise be overlooked. Trends that occur at
much larger scales, although expressed locally, may go unnoticed in purely local-scale
assessments.
Geographic information system (GIS) is probably the most effective instrument for
introducing a spatial dimension into the economic valuation, through the use of “spatial
economic valuation” methodology and production of economic value maps. The adoption
of a spatial approach to economic valuation is desirable in terms of producing more
accurate economic valuation figures, for use as a repository for benefits estimates,
examining spatial sustainability, and facilitating the introduction of natural capital concepts
into environmental decision-making processes. The use of GIS to map and model natural
capital adds a new dimension to environmental economics and is worthy of further
investigation.
The multi scale integrated model of ecosystem services (MIMES) stretches the edge of
technical achievement in GIS data and display, in modeling environments, and in interface
development. MIMES is a project useful to assess the value of ecosystem services in a
sophisticated and transferable system to allow ecosystem managers to quickly understand
the dynamics of ecosystem services, how their services are linked to human welfare, how
their function and value might change under various management scenarios (Nadrowski et
al., 2008 (Salzau). It will facilitate understanding ofthe context of spatial patterns of land
use, they dynamics of value, and the scale at which information is available for estimating
ecosystem services at various scales (e.g. watershed, national and global). MIMES will
provide economic arguments for land use managers to approach conservation of
ecosystems as a form of economic development.
The remote sensing is also a useful technology to assess spatial and temporal variability in
the condition of landscapes. For example the use of satellite imagery to provide remotely
sensed indicators that account for continuous variation in vegetation structure may be
more appropriate to measure ecosystem condition and their ability to provide services
(Price et al., 2008 (Salzau). The index NDVI (Normalized Difference Vegetation Index)
provides a spatially continuous measure of vegetation structure and photosynthetic activity
that represents a supporting services, from which all the other services depend on. It can
act as an alternative to metrics derived from the discrete patch model of landscape
structure. NDVI can be easily derived from readily available Landsat imagery at a variety
of spatial extents and temporal resolutions. MODIS monthly NDVI dynamics show that
Ecosystem Services values for certain services may fluctuate during “small” intervals, too
(Zaccarelli et al., 2008 (Salzau).
To promote researches at multiple scales, new techniques are certainly needed. The scale
issue, in its different perspectives, has to be reported and addressed to frame results,
promote reported comparisons (Atkinson and Tate 2000) and make decision-making more
informed at different institutional levels.
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Part 2