Meta analysis on wetland qualities and their economic values

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Wetland Quality as a Determinant of

Economic Value of Ecosystem Services: an Exploration

H Chena*, P Kumarb and T Barkera

a School of Environmental Sciences, Liverpool University, UK

b Ecosystem Services Economics Unit, UN Environment Programme

*Email: h.chen47@lancaster.ac.uk; hongyan.chen88@gmail.com

Abstract

Wetland quality is a critical factor in determining values of wetland goods and services.

However, in many studies on wetland valuation, wetland quality has been ignored.

While those studies might give useful information to the local people for decision-

making, their lack of wetland quality information may lead to the difficulty in

integrating wetland quality into a cross-studies research like meta-analysis. In a meta-

analysis, a statistical regression function needs withdrawing from those individual

studies for analysis and prediction. This research introduces the wetland quality factor,

a critical but frequently missed factor, into a meta-analysis and simultaneously

considers other influential factors, such as study method, socio-economic state and

other wetland site characteristics, as well. Thus, a more accurate and valid meta-

regression function is expected. Due to no obvious quality information in primary

studies, we extract two kinds of wetland states from the study context as relative but

globally consistent quality measurement to use in the analysis, as the first step to

explore the effect of wetland quality on values of ecosystem services.

Key words: wetland quality, ecosystem services, economic valuation, meta analysis,

sustainability

1. Introduction

Wetland ecosystems are one of the most productive ecosystems on this planet,

delivering massive goods and services to human society (Maltby 2022). However, due

to poor awareness of their values and underestimation of their contribution, many

wetlands have been converted to farmland or urban areas or influenced by pollution due

to agricultural and industrial activities (Maltby 1986). Consequentially, global wetland

ecosystems have severely declined and degraded during the past decades. In order to

restore and protect wetlands, hence ensure a sustainable supply of wetland goods and

services, it is important to recognize their values. Vital to this is the development of

valuation methods that explicitly link wetland values, the capital base of the ecosystem,

to the design of policies (Pearce and Atkinson, 1993; Dasgupta and Mäler, 2000; Arrow

et al., 2004; Maler et al., 2008; Dasgupta, 2010; Kumar and Chen, 2014).

For a typical wetland ecosystem, its values can be accounted in terms of

populations and diversity of species, and annual rates (a-1) of fish harvested, carbon

stored or recreational visits. These are generally categorised as values from wetland

provisioning, regulating or cultural services (MA, 2005). Proper and accurate

estimation of these values enables comparative analyses of intervention practices and

contributes to improvements of policy-making (Barbier, 1993; Barbier et al., 1997;

Turner et al., 2000). A critical factor in determining the values of wetlands is quality

since a healthy and functioning wetland will provide rich ecosystem services (Zedler

and Kercher, 2005; Maltby, 2009). This is a neglected aspect of studies.

The quantity of the wetland valuation practice has increased in relatively recent

years. In the review by Heimlich et al. (1998), 33 studies over the last 26 years were

listed and in Brander et al. (2009) there are more than 50 valuation studies for European

inland wetlands. Based on primary studies of wetland valuation, several meta-analyses

have been conducted to explore the commonalities through inter-study comparisons, to

find the general relationship between wetland values and influential factors and to

estimate the wetland values of non-valued areas. The examples include Brouwer et al.

(1999), Woodward and Sui (2002), Brander et al. (2006), Brander et al. (2009),

Ghermandi et al. (2010).

The wetland quality factor has been ignored in most primary studies and

subsequently in the meta-analyses based on them. As mentioned in Brander et al. (2007),

it is often the case that the provision of goods and services is indicated in a meta-

analysis merely by binary variables, and that quality is not captured at all. This

limitation may lead to generalisation errors and therefore to benefit transfer errors,

which would probably lead to errors in policy making for the wetland sustainable

development.

This paper tries to integrate a wetland quality factor into a meta-regression function,

keeping other influential factors, such as study method, socio-economic state and other

site characteristics, included as well. Due to no obvious quality information in primary

studies, we extract two kinds of wetland states from the study context as relative but

globally consistent quality measurement to use in the meta-analysis. Thus, a more

accurate and valid regression result is expected.

2. Overview of wetland quality evaluation

Wetlands differ immensely with respect to their hydrology, geochemistry, plant

communities and landscape position. In a real sense, no two wetlands are similar in

their quality or function (Wright et al., 2006). Despite this variability, some consistent

and recurring impacts can be observed and some common dynamic processes and

properties can be found in different wetlands. Wetland quality is to measure if the

wetland is healthy or not, which might be reflected in the performance of wetland

functioning. Wetland hydrological, geochemical and ecological functions and their

performance are the direct or indirect results of wetland characteristics and dynamic

processes.

Various methods have been developed for wetland quality evaluation in the past

decades. In USA, Wetland evaluation technique (WET) (Adamus et al., 1987) assigns

a qualitative probability rating of high, moderate or low to each function, according to

characterizing predictors and their relationship with wetland functions. However, it

does not provide information on the degree of functional performance. A more advance

method might be the hydrogeomorphic (HGM) approach (Smith, 1994; Brinson et al.,

1998; Cole, 2006), which provides a procedure for assessing the capacity of a wetland

to perform functions, based on interactions of the structural components of the

ecosystem with surrounding landscape features. From these methods, Maltby (2009)

developed a wetland functional assessment method to define and assess wetland quality

for European wetlands, combining the probability of occurring and the level of the

performance of wetland functions.

Quality index presents an alternative to the above methods. This method compares

wetland functional capacity under existing conditions with that under the conditions

where the highest, sustainable functional capacity occurs (Smith et al., 1995). The

quality index may measure the functional capacity either across the suite of functions

performed by a wetland (Smith and Theberge, 1987) or for a specific function from a

specific perspective. An example of the former can be found in Lodge et al. (1995),

where the indices are derived by totalling the weighted scores for each function and

dividing by the maximum possible score. The instances of the latter include the index

of biological integrity developed by Karr et al. (1986), floristic quality

assessment index by Miller and Wardrop (2006) and wetland fish index by Seilheimer

and Chow-Fraser (2006).

3. Meta analysis and wetland quality: a review

As a technique originally used in experimental medical treatment and psychotherapy

(Glass, 1976), meta-analysis statistically analyzes the findings of empirical studies,

helping to extract information from large masses of data in order to quantify a more

comprehensive assessment (Brouwer et al., 1999). It enables researchers to explain

differences in outcomes found in single studies on the basis of differences in underlying

assumptions, standards of design and/or measurement (Ledoux et al., 2001). Since the

beginning of the 1990s, meta-analysis has been playing an increasingly important role

in environmental economics research (van den Bergh et al. 1997; Smith and Kaoru,

1990). In economic valuation of ecosystem services, meta-analysis has been used to

explore the relationship between values and their influential factors. This general

functional relationship could be used to predict with local information the ecosystem

values for policy sites where conducting a primary research is unfeasible (function

transfer).

Several articles, for example, Brander et al., (2006) and Bateman and Jones,

(2003), have argued that function transfers perform better than direct transferring the

estimated values in primary studies to the policy sites in question. However, for the use

of meta-analytic functions for benefit transfer, some important underlying assumptions

(Rosenberger and Phipps, 2007) have to be borne in mind:

1) There exists a valuation function that links the values of a resource with the

characteristics of sites, studies and socio-economic circumstances;

2) The difference between sites can be captured through a price vector;

3) Values are stable over time or vary in a systematic way, and

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摘要：

WetlandQualityasaDeterminantofEconomicValueofEcosystemServices:anExplorationHChena*,PKumarbandTBarkeraaSchoolofEnvironmentalSciences,LiverpoolUniversity,UKbEcosystemServicesEconomicsUnit,UNEnvironmentProgramme*Email:h.chen47@lancaster.ac.uk;hongyan.chen88@gmail.comAbstractWetlandqualityisacriticalfa...

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