1 23

Environmental and ResourceEconomicsThe Official Journal of theEuropean Association ofEnvironmental and ResourceEconomists ISSN 0924-6460Volume 47Number 3 Environ Resource Econ (2010)47:329-347DOI 10.1007/s10640-010-9381-6

Mapping Biodiversity Indicators andAssessing Biodiversity Values in GlobalForests

1 23

Your article is protected by copyright and

all rights are held exclusively by Springer

Science+Business Media B.V.. This e-offprint

is for personal use only and shall not be self-

archived in electronic repositories. If you

wish to self-archive your work, please use the

accepted author’s version for posting to your

own website or your institution’s repository.

You may further deposit the accepted author’s

version on a funder’s repository at a funder’s

request, provided it is not made publicly

available until 12 months after publication.

Environ Resource Econ (2010) 47:329–347DOI 10.1007/s10640-010-9381-6

Mapping Biodiversity Indicators and AssessingBiodiversity Values in Global Forests

Elena Ojea · Paulo A. L. D. Nunes · Maria L. Loureiro

Accepted: 3 May 2010 / Published online: 22 May 2010© Springer Science+Business Media B.V. 2010

Abstract Biodiversity loss is a problem of global concern affecting ecosystem function-ing and services provided to humans. The Millennium Ecosystem Assessment is built on aconceptual framework that links biodiversity with the services ecosystems provide to soci-ety and human welfare. Numerous empirical studies have measured ecosystem goods andservices in terms of economic values; however, less evidence is available of the indirecteffect of biodiversity on these values. Based on this, we first compile market and non-marketforest valuation studies and, secondly, explore the potential of an econometric modellingexercise by conducting a worldwide meta-analysis. This exercise aims to highlight the roleof biodiversity indicators on valuation. In this way, we can study the underlying transmissionmechanisms that explain to what extent biodiversity is related to human welfare. Further-more, we also propose to evaluate the magnitudes of the respective distributional impacts,including the different ecosystem goods and services under consideration. Our results showthat biodiversity indicators may have an underlying effect on forest ecosystem values, whichalso depend on the type of ecosystem services. Lastly, the results are discussed and analysedwith respect to their policy implications concerning biodiversity conservation.

Keywords Biodiversity · Forest · Ecosystem services · Meta-analysis · Millenniumecosystems approach

E. Ojea (B)Basque Centre for Climate Change (BC3), Gran Vía 35-2, 48009 Bilbao, Spaine-mail: elena.ojea@bc3research.org

P. A. L. D. NunesDepartment of Economics, Cà Foscari University of Venice, Venice, Italye-mail: pnunes@unive.it; paulo.nunes@feem.it

P. A. L. D. NunesFondazione ENI Enrico Mattei, Venice, Italy

M. L. LoureiroDepartamento de Fundamentos da Análise Económica, Universidade de Santiago de Compostela (USC),Santiago de Compostela, Spaine-mail: maria.loureiro@usc.es

123

Author's personal copy

330 E. Ojea et al.

AbbreviationsEVRI Environmental valuation reference inventoryGDP Gross domestic productIMF International monetary foundIPCC Intergovernmental panel on climate changeIUCN International union for conservation of natureMA Millennium ecosystem assessmentOLS Ordinary least squares

1 Introduction

Under the conceptual framework of the Millennium Ecosystem Assessment (MA), humanwell-being is the central focus for ecosystem services assessment (Mooney et al. 2004),acknowledging the fact that biodiversity plays a crucial role in determining the ecosystems’capacity to provide goods and services (MA 2003). Changes in biodiversity affect ecosystemfunctioning and, at the same time, are reflected in welfare changes. Within this framework,direct and indirect interactions exist between biodiversity and welfare through ecosystemservices.

Ecosystem goods and services are classified into four categories: provisioning, regulating,supporting, and cultural services (MA 2003). While the value of some ecosystem services,such as provisioning, is well known and can be easily obtained from existing markets, othervalues related to cultural services can only be obtained from non-market valuation techniques,and as a consequence, are not usually considered in management and decision-making pro-cesses. Indeed, forest degradation and biodiversity losses are seen to be a consequence ofthese types of market failures (Pearce and Moran 1994). Based on this premise, this papermakes a first attempt to synthesise the work conducted on market and non-market valuationat a global level, in the case of forest ecosystem services. The MA framework is used as atool to bridge ecosystem welfare values and biodiversity through a meta-analytical approach.

Evidence suggests that biodiversity loss may accelerate in the future, particularly as aresult of climate change (Pimm and Raven 2000; Thomas et al. 2004). By the end of thetwenty-first century, climate change and its impacts are expected to be the dominant, directcause of biodiversity loss and changes in global ecosystem services (MA 2005). The grow-ing concern and knowledge regarding the decline of biodiversity has generated a number ofstudies that describe the importance of biodiversity for ecosystem functioning (Loureau et al.2001; Chavas 2009). Based on the belief that biodiversity conservation is a way to assurefuture ecosystem services and resilience to climate change, the contribution of this paper is tofurther explore how biodiversity is affecting forest economic values. Worldwide biodiversityindices are obtained from IUCN national data, where indicators denoting both the absolutenumber of listed species (biodiversity abundance) and the relative number of endangered redlist species (threatened biodiversity) are interacted with forest ecosystem services values bymeans of a meta-analysis.

This article is structured as follows: firstly, Sect. 2 underlines the importance of forestecosystems’ goods and services and the conceptual framework under which biodiversity andecosystem services can be measured in terms of human welfare. Section 3 presents the datacompilation, data treatment and methodology. Section 4 contains the main objectives to beaddressed while results are discussed in Sect. 5, and some concluding remarks are made inSect. 6.

123

Author's personal copy

Mapping Biodiversity Indicators and Assessing Biodiversity Values in Global Forests 331

2 Valuation of Forest Goods and Services

Forests worldwide are known to be critically important habitats in terms of both the bio-logical diversity they contain and in terms of the ecological functions they serve. Thereare approximately 4 billion hectares of forests in the world (FAO 2005) which amountsto 30.5% of land area. Their provision of goods and services plays an important role inthe overall health of the planet and is of fundamental importance to human economy andwelfare. The MA classifies ecosystem goods and services in: provisioning services, whichconsist of products obtained from ecosystems including food, fibre, freshwater or geneticresources; cultural services, the non-material benefits that people obtain from the ecosystem,including the aesthetic experience, recreation or spiritual enrichment; regulating services,including benefits obtained from the regulation of ecosystem processes, such as air qualityregulation, climate regulation, water regulation, erosion regulation, pollination or naturalhazard regulation; and supporting services, those which are necessary for the productionof all other ecosystem services, such as soil formation, photosynthesis, primary production,nutrient cycling and provisioning of habitat (MA 2003). All these services rely on the qual-ity and functioning of the ecosystems; it is biodiversity that feeds the system, providingthese different values. Ecosystem management, biodiversity conservation and future devel-opment alternatives depend on the tradeoffs among these services. Figure 1 summarises theconceptual framework employed in the present study, in which biodiversity and ecosystemservices are related to welfare. Under this framework, global changes caused by humanactivity, such as climate change, alteration of biochemical cycles, or land use changes, areaffecting ecosystem functions and biodiversity. As a consequence of these alterations, eco-system goods and services are also changing, producing an impact on human welfare. Thisimpact can be measured in terms of the economic values these ecosystem services provideto humans.

The primary role of an economic analysis is to present information to decision makersregarding how society might balance the tradeoffs inherent to resource allocation decisions,

Fig. 1 Conceptual framework for biodiversity and global change effects on welfare under the ecosystemservices approach. Source: adapted from MA 2005 (by Simboloxico)

123

Author's personal copy

332 E. Ojea et al.

including how the benefits might be distributed (Rolfe et al. 2000). There is concern thatalthough international demands for timber and other products can be evaluated throughexport markets, there is no corresponding mechanism to assess international demands forconservation and preservation of the cultural values. Godoy et al. (2000) illustrate this issueconducting an economic valuation of tropical forest services. They obtain a low economicvalue for the rainforest on behalf of the local community, which explains their choice toclear forests for other land uses. Although outsiders value the rain forest for its high-use andnon-use values, local people receive only a small share of the total value. In relation to this,Rolfe et al. (2000) show that, depending on the circumstances of the conservation proposal,foreigners can hold substantial non-use values for rainforest preservation in other countriesrelative to preservation options in their own country. Their results provide a tool for decisionmakers in terms of prioritising rainforest preservation options. This evidence demonstratesthe importance of non-market values, such as non-use values and recreation, in the overallassessment of preservation proposals, both for tropical forests and non-tropical forests. Basedon this evidence, both market and non-market forest values are taken into consideration inthe present analysis.

Previous studies that value ecosystem services focus on a single type of forest or on onetype of economic value. For example, Chomitz et al. (2005) value biodiversity ‘hotspot’areas in Brazil examining data from a survey of property values, relating land price to landcharacteristics. As a result, they conclude that forest land had a market value which was70 per cent lower than comparable cleared land. Portela et al. (2008) also derive non-tim-ber values from revealed preferences based on actual choices of forest owners for differentmanagement schemes. These forest goods were almost twice as great as timber revenues forprivate non-industrial forests. In another study, Lindhjem (2007) reviews stated preferenceliterature in Scandinavia in a meta-analysis over the last 20 years, concluding that non-marketforest values are insensitive to the size of the forest. Other studies have shown how ecosystemservices contribute to economic activity. Richmond et al. (2007) investigated how the pro-ductivity of ecosystems contributes to a country’s GDP, obtaining a positive relationship. Thetotal welfare contribution of ecosystem services has been estimated at $33 trillion per year(Costanza et al. 1997), although this approach has also been criticised by several economists(Toman 1998; Bockstael et al. 2000). From the MA framework, we know that these eco-system services are supported by ecosystem functioning, where biodiversity plays a crucialrole (Mooney et al. 2004). However, a scarce number of studies look specifically at the linksbetween biodiversity and the values of the ecosystem services it provides. Costanza et al.(2007) are an exception; in their study ecosystems’ net primary production is explained interms of biodiversity richness. As a result, they find that a one percent loss in biodiversityin warm eco-regions results in roughly a half percent change in the value of the ecosystemservices provided in these regions (Costanza et al. 2007). Tilman et al. (2005) show howhigher plant diversity can lead to greater carbon storage in plant mass. More recently, Chavas(2009) analyses the productive value of biodiversity on ecosystems, stating that this valuecan be expected to vary across ecosystems.

Economic impacts of biodiversity and their relationships with forest services have not yetbeen assessed in a worldwide perspective nor based on current evidence from the growingliterature. This study provides such an empirical exercise. Thus, we compile economic valuesfor forest ecosystem goods and services from both market and non-market valuation tech-niques, in an attempt to study the role of ecosystem services and biodiversity in the economicvalues these forests provide.

123

Author's personal copy

Mapping Biodiversity Indicators and Assessing Biodiversity Values in Global Forests 333

3 Methodology and Data Analysis

A database with 65 studies and 248 value estimates has been analysed with respect to thesocio-economic values derived from the services provided by these worldwide forest eco-systems (a list of the studies is presented in Table 1). Studies were collected from existingscientific sources such as the EVRI database and the IUCN database for forest studies,together with a review of published studies from ECONLIT. Original studies cover the pasttwo decades. The studies included were those in which forest economic values could beconverted to a common value per hectare per year unit. When a study presented more thanone estimate, the best estimate as presented by the authors was included in our dataset. Asystematic procedure has been developed to define the variables to be used in this analysis.

Table 1 List of studies Aakerlund (2000) Kaiser and Roumasset (2002)

Anthon and Thorsen (2002) Kniivilä (2004)

Balick and Mendelsohn (1992) Kniivilä et al. (2002)

Bann (1997) Kontoleon and Swanson (2003)

Bateman and Lovett (2000a) Kramer and Mercer (1997)

Bateman and Lovett (2000b) Kramer et al. (1995)

Bateman et al. (1996) Kramer et al. (2003)

Bellu and Cistulli (1995) Lienhoop and Macmillan (2007)

van Beukering (2002) Mahapatra and Tewari (2005)

van Beukering et al. (2003) Mallawaarachchi et al. (2001)

Bienabe and Hearne (2006) Mogas et al. (2006)

Bonnieux and Le Goffe (1997) Monela et al. (2001)

Bostedt and Mattsson (2006) Murthy et al. (2005)

Campos and Riera (1996) Naidoo and Adamowicz (2005)

Chase et al. (1998) Ninan and Sathyapalan (2005)

Christie et al. (2001) Nowak et al. (2007)

Costello and Ward (2006) Oumar et al. (2006)

Dubgaard (1998) Phillips et al. (2008)

Edwards-Jones et al. (1995) Raunikar and Buongiorna (2004)

Emerton (1999) Ricketts et al. (2004)

ERM (1996) Rosales et al. (2005)

Garber-Yonts et al. (2004) Samuel and Thomas (1996)

Garrod and Willis (1997) Sattout et al. (2007)

Godoy et al. (2000) Scarpa et al. (2000)

Gurluk (2006) Shahwahid et al. (2003)

Hanley and Ruffel (1993) Shechter et al. (1998)

Hanley et al. (1998) Siikamaki and Layton (2007)

Hanley et al. (2002) Simpson et al. (1996)

van der Heide et al. (2005) Verma (2000)

Horne et al. (2005) Walsh et al. (1984)

Horton et al. (2003) Wang et al. (2007)

Hougner et al. (2006) Zandersen et al. (2005)

Howard (1995)

123

Author's personal copy

334 E. Ojea et al.

More specifically, the MA classification has been explored for ecosystem services and a spe-cific service has been assigned to each economic value. Moreover, each forest type has beenclassified into a biome type and additional indicators of biodiversity and climatic variableshave been added to the dataset. Biodiversity indicators1 have been constructed employingthe IUCN red list database, including the number of fauna and flora species that are listed byIUCN at a national level2 (IUCN 2007). Two indices for biodiversity have been employedin our analysis. First, the IUCN Listed Species (LS) indicator, which is the absolute num-ber of species in each country listed in the IUCN catalogue.3 This index corresponds to anabundance indicator of the total number of species:

L Si = E Ni + C Ri + V Ui + L Ri + N Ti + DDi + LCi ; for each country i; (1)

Second, the IUCN Red Species (RS) indicator is used, which is a relative figure, obtained fromthe rate of threatened species (including vulnerable, endangered and critically endangered)respect to all listed species in that country (i):

RSi = E Ni + C Ri + V U

L Si(2)

These indicators have been constructed for flora and fauna species and are all included inour regressions as flora and fauna indices. These indices represent different relevant criteriafor conservation management decision making, the former favouring biodiversity richnessand the latter the conservation of endangered species. Spatially explicit biodiversity indi-ces would have been more desirable than countrywide indices for conducting this exercise.However, since we have a large and worldwide dataset of forest values and considering thatIUCN contains the only biodiversity information available at a global scale, in this way weare able to carry out a first attempt at investigating the link between biodiversity and forestvalues. Moreover, it is a common practice in meta-analyses to include variables at a nationalscale, such as GDP or population density, in the models. Finally, methodological and con-text characteristics linked to the valuation studies were introduced. From this set of studies,special attention was given to the links between forest services, biodiversity indicators andforest economic values.

With the described dataset, and following previous studies on meta-analyses for eco-system values (Brander et al. 2007; Ghermandi et al. 2008; Richardson and Loomis 2009;Woodward and Wui 2001), a benchmark OLS regression is estimated to explore the linksbetween the forest values and the different forest services, their characteristics and interac-tions with biodiversity. The dependent variable in our model is the forest service economicvaluation, measured as the estimated value per hectare per year reported by each originalstudy.4 Following a common procedure in meta-analyses (Brander et al. 2007; Horowitz and

1 Biodiversity is a very complex concept and a broad range of indicators have been developed and discussedby ecologists. Biodiversity richness is one of the most employed indicators. However, we were not able tocompute such a complex indicator at a national level for all our valuation data, and two more simplistic indi-cators for biodiversity were constructed. We acknowledge the limitations of this choice but believe that theseindicators give us relevant information at this stage.2 Indices were included at a national level basis since more accurate forest biodiversity indices were notavailable for such a worldwide analysis.3 IUCN categories include: CR Critically Endangered, EN Endangered, VU Vulnerable, LR/cd Lower Risk,NT Near Threatened, DD Data Deficient, and LC Least concern. Note that not all categories necessarily includethreatened species.4 Original reported values were converted to value per hectare per year when necessary with simple calcula-tions employing the area of the forest and/or the number of households/visitors.

123

Author's personal copy

Mapping Biodiversity Indicators and Assessing Biodiversity Values in Global Forests 335

McConnell 2002), these values have been converted and updated to e2008 using the Pur-chasing Power Parity (PPP) per capita GDP from the World Economic Outlook obtained fromthe IMF (IMF 2007). Forest values are thus explained by the forest service characteristics,biodiversity indicators and finally, context characteristics (summarised in Table 2), such that:

Y = α + β f X f + βb Xb + βc Xc + u (3)

where Y is the forest value per hectare per year, a is the constant term, the betas represent thevectors of the coefficients in the regression model to be estimated, and associated with thefollowing types of explanatory variables: forest specific (Xf), biodiversity specific (Xb) andcontext specific (Xc), while u represents a vector of residuals. A double log model is estimateddue to a better statistical fit. This functional form has proved to be the best specification interms of statistical performance, and according to the results provided by a Box-Cox test.5

Explanatory variables are summarised and described in Table 2. Forest specific variablesreflect the forest study area (lnha), the type of forest (mediterranean, boreal, tempconif,tempmix, tropicalwet and tropicalmix) and the type of ecosystem service provided (cultural,provisioning and regulating) following the MA classification. Due to the nature of the data, afourth category was constructed to include those values obtained from all types of ecosystemservices (allservices). Lastly, the variable hotspot is included which indicates whether theforests are part of these important international areas for conservation. Biodiversity indi-cators are added to the dataset in the form of the number of flora and fauna species inthe country in absolute (Listed Species) and relative (Red Species) terms (flora and fauna).Context variables are also presented in Table 2, where study variables, such as the methodemployed in assessing the economic value, the year of publication, and the country’s GDP andpopulation density are reported. The economic valuation method is classified into four cat-egories: revealed preference techniques (revealed), including travel cost and hedonic priceapproaches for forest valuation; market techniques (market), including market prices andproduction functions; stated preference techniques (stated), including contingent valuationand choice experiments; and lastly, mixed methods and others, such as benefit transfer, wereclassified as othermethod. Finally, and following previous meta-analyses, the year of study(year) as well as an indicator of the level of income in the country where the valuation tookplace (lnGDP)6 (IMF 2007; World Bank 2007) together with information about the densityof population in the country (World Bank 2007; Heston et al. 2009) are included.

4 Objectives and Hypotheses

The aim of this exercise is to study the interactions between forest ecosystem values, the eco-system services they provide and biodiversity levels. Our main objective is to test whether, bymeans of a meta-analysis, evidence can be provided on the transmission mechanism betweenbiodiversity and welfare through ecosystem services, as postulated by the MA conceptualframework. To address this empirical question, we have set up two main hypotheses. The firstone explores the role of our biodiversity indicators in economic benefits derived from forestecosystem services. Since biodiversity richness is positively related to net primary produc-tion (Costanza et al. 2007; Tilman et al. 2005), we expect our biodiversity abundance index

5 Box Cox test resulted in 406.07 which is well above the critical level at 1% of Chi2(19, 0.01) = 38.58.6 GDP per capita corresponds to the country of the study site where the economic valuation has been under-taken. However, if foreign visitors are valuing a forest, for example, then the GDP per capita has been correctedconsidering the GDP of their country of origin.

123

Author's personal copy

336 E. Ojea et al.

Table 2 Descriptive analysis of data

Mean

Forest services’ characteristics

Forest area lnha Natural logarithm of forestsize (in hectares)

11.72

Type of forest mediterranean* Mediterranean (1); rest (0) 0.12

boreal Boreal (1); rest (0) 0.05

tempconif Temperate coniferous (1); rest (0) 0.21

tempmix Temperate not-conifer(broadleaf, mixed, etc.) (1);rest (0)

0.23

tropicalwet Tropical wet (1); rest (0) 0.25

tropicalmix Tropical dry or tropicalgrasslands (1); rest (0)

0.13

Protection status hotspot If the forest is a hotspot (1); otherwise (0) 0.14

Forest ecosystem goods andservices

cultural Cultural service (1); rest (0) 0.58

regulating Regulating service (1); rest (0) 0.13

provisioning* Provisioning service (1); rest (0) 0.24

allservices Cultural and provisioning andregulating (1); rest (0)

0.05

Biodiversity indicators

IUCN listed species (LS) fauna Number of fauna specieslisted by IUCN

306.42

flora Number of flora species listedby IUCN

209.90

IUCN Red species (RS) fauna Number of endangered,critically endangered andvulnerable fauna species inIUCN red list relative to thetotal number of species

0.14

flora Number of endangered,critically endangered andvulnerable flora species inIUCN red list relative tototal number of species

0.54

Context characteristics

Forest marginal value lnval Natural logarithm of value/hectare. year (e2008)

3.76

Environmental valuation method market Market values andreplacement costs (1); rest(0)

0.25

stated* Stated preference techniques(travel cost and hedonicprices) (1); rest (0)

0.50

revealed Revealed preferencetechniques contingentvaluation and choiceexperiments (1); rest (0)

0.10

othermethod Other methods (mixedtechniques, benefit transfer)(1); rest (0)

0.15

Year of publication year Year of publication 2000.14

123

Author's personal copy

Mapping Biodiversity Indicators and Assessing Biodiversity Values in Global Forests 337

Table 2 continued

Mean

Income lnGDP Natural logarithm of percapita GDP (e2008) of thecountry of study

9.15

Population density lnpop Density of population in thecountry in logarithmic form(hab./sq. km)

131.30

* Omitted variables

to be significant in explaining forest ecosystem values. However, our sample is larger thanthat of Costanza et al. (2007) and includes many types of ecosystem services, encompass-ing cultural, regulating and provisioning. The interaction of forest values with biodiversitymay thus depend on the type of ecosystem service considered. Our second hypothesis dealswith the effect of biodiversity on forest values depending on the type of ecosystem service.Costanza et al. (2007) find a positive link between flora biodiversity richness and provisionof services. However, we have no a priori expectations of how biodiversity affects culturalor regulating services. The approach we follow to explore these links consists in introducingthe interaction effects of the corresponding variables in the regression. In this way, we com-pute the joint effect of the biodiversity indicators together with the ecosystem services andassess how these are related to the value of those services. The effects of these biodiversityindicators in ecosystem services values have not yet been considered in literature, and haveimportant implications for policy analysis, nature conservation and resource reallocation.

5 Results

5.1 Baseline Models

With the described dataset we proceed with the estimation of the meta-regression of world-wide forest ecosystem services values. We present two baseline models, differing only respectto the biodiversity indices, where the IUCN Listed Species model includes absolute biodi-versity indices of flora and fauna, while the IUCN Red Species model includes the relativebiodiversity indices of flora and fauna. By including both models we compare the marginaleffects of two biodiversity indicators in our results: the abundance of species and the relativestatus of endangerment. We employ Ordinary Least Squares (OLS) where all sets of variablesdescribed in the previous section are included.7 The models are corrected from authorshipeffects by clustering the observations from the same studies. Baseline specification modelresults are presented in Table 3. Both model specifications show an acceptable fit, obtainingan R2 of 0.58 and 0.56, respectively for the Listed Species and Red Species model. Tests forcollinearity have also been implemented by checking the correlation matrix and obtainingthe Variance Inflation Factors (VIF), resulting in no correlation problems with all coefficientsunder 0.8 in the correlation matrix and VIF values lower than 10.

As a result of the econometric analysis, these baseline models serve as a first attempt tosynthesise market and non-market forest valuation studies, where the heterogeneity in the

7 A Generalized Least Square (GLS) model with random effects was estimated following Wooldridge (2003)to explore the panel nature of the data, although this model does not improve our OLS estimates and is notpresented here (although available under request).

123

Author's personal copy

338 E. Ojea et al.

Table 3 Baseline specification models

IUCN Listed species model IUCN Red species model

Lnval Coefficient t-value Coefficient t-values.e. s.e.

Forest services’ characteristics

lnha −0.5880*** −5.74 −0.5615*** −4.62

(0.1025) 0.1215

boreal 1.4938 1.18 1.0160 0.72

(1.2703) 1.4027

tempmix 0.0609 0.05 −0.7347 −0.69

(1.2279) 1.0589

tempconif 1.6900* 1.90 1.3056 1.51

(0.8903) 0.8637

tropicalwet 2.3779* 1.70 1.2696 1.19

(1.3996) 1.0688

tropicalmix 3.3939* 2.19 1.9402 1.59

(1.5509) 1.2178

hotspot 1.1637* 1.68 0.7663 1.10

(0.6907) 0.6969

cultural 0.2784 0.22 0.2939 0.22

(1.2660) 1.3107

provisioning −0.2868 −0.34 −0.3725 −0.43

(0.8439) 0.8707

allservices 3.7015** 2.89 3.2063** 2.70

(1.2802) 1.1858

Biodiversity indicators

fauna 0.0021** 2.78 −5.3575 −1.44

(0.0008) 3.7236

flora −0.0009 −0.82 −2.2778* −1.69

(0.0010) 1.3481

Context characteristics

othermethod −0.9148 −1.27 −0.7231 −0.84

(0.7204) 0.8657

market −1.0588 −1.01 −0.7681 −0.62

(1.0499) 1.2434

revealed −1.3557* −1.89 −0.9483 −1.31

(0.7187) 0.7221

year −0.0961 −1.58 −0.1100∗ −1.68

(0.0610) 0.0656

lnGDP 0.6524* 1.64 0.4578 1.15

(0.3985) 0.3977

lnpop 0.0061** 3.07 0.0065*** 4.65

(0.0020) 0.0014

123

Author's personal copy

Mapping Biodiversity Indicators and Assessing Biodiversity Values in Global Forests 339

Table 3 continued

IUCN Listed species model IUCN Red species model

Lnval Coefficient t-value Coefficient t-values.e. s.e.

Constant 194.3649 1.63 226.5103* 1.75

(119.1522) 129.5018

N 172 172

F-test 14.08 15.94

Prob > F 0.0000 0.0000

R2 0.5773 0.5641

*** Indicates statistical significance at α = 0.001; ** Indicates statistical significance at α = 0.1; and* Indicates that the variable is statistically significant at α = 0.1

economic measures is controlled by forest characteristics, biodiversity indicators and othercontext characteristics. The final number of observations in the regression drops to 172 dueto missing values, given that information for all our variables is not always available fromthe primary studies. Before discussing the implications regarding the biodiversity indices,we will summarise the main results in terms of the variables affecting forest values. Fromthe results in Table 3, we can observe how the model including the species list indicatorperforms better, finding more statistically significant variables that influence forest values.The estimated coefficient of the forest area (lnha) is negative and shows significant marginaldecreasing utility with the provision of additional hectares. This coefficient can be inter-preted as the elasticity of the forest area, where a 1% increase in the forest area decreasesthe forest marginal value by 0.59%. This result has been found in previous meta-analysesof ecosystem values such as Ghermandi et al. (2008) or Wooldridge (2003) for wetlands, aswell as in the non-market valuation literature (Loomis et al. 1993). As expected, the type offorest also has a significant effect on forest values. Temperate conifer (tempconif) and tropicalforests (tropicalwet and tropicalmix) are in general related to higher economic values, withrespect to the omitted variable of Mediterranean forests (mediterranean). Bearing in mindthat allservices is the omitted variable, the results show that values obtained from a singleecosystem service are lower than values obtained from more than one ecosystem service. Thisresult is in line with our expectations and contradicts the possibility of an embedding effect,where valuing two goods separately yields a greater value than the sum of both (Loomiset al. 1993). In contrast, we do not obtain any significant effect linked to each specific typeof ecosystem service (cultural or provisioning). This result is rather surprising as one wouldexpect significant differences between ecosystem services. However, our analysis is basedon the MA broad categories of classification and further assessment could take more specificand detailed ecosystem services into account. In addition, the role of the MA classificationin the valuation of ecosystem services has been recently questioned in the literature; somerecent studies explore additional classifications of ecosystem services that may be more suit-able to conduct economic valuation (Boyd and Banzhaf 2007; Fisher et al. 2009; Fisher andTurner 2008; Wallace 2007). Another finding from the Listed Species baseline model is thatthe methodology used in the primary study affects the economic valuations, while studiesemploying revealed preference techniques are more likely to derive lower economic valuescompared to stated preferences methods. Moreover, in line with economic theory, per capitaincome (lnGDP) is statistically significant and positive in the first model too, where the richer

123

Author's personal copy

340 E. Ojea et al.

the country the higher the forest value. A 1% increase in the GDP per capita of a countrycorresponds to a 0.65% increase in the valuation per hectare of forests. The second model withRed Species reaffirms previous results although less significant variables are found. In con-trast, the year of the study is only statistically significant in this Red Species model presentinga negative sign and pointing out that more recent studies are associated with lower values.Finally, the variable population density (lnpop) is positive and significant in both modelsindicating that those forests located in more density populated countries are valued higher.In particular, a 1% increase in population density (lnpop) increases forest values by 0.06%.

Special attention is given to the significance of the biodiversity indicators in explainingforest values. We have chosen to model the two indicators of abundance and status separatelysince they are related to different aspects of biodiversity as a whole and since policy conserva-tion decisions can be taken based on one or the other. With respect to the first model of IUCNListed Species, we find that only fauna is statistically significant in explaining forest valua-tions. Bearing in mind the general nature of our biodiversity indicators, from this model weobtain that the fauna indicator is positive and statistically significant. The higher the numberof fauna species, the higher the value of forest services. To quantify this link, our model pre-dicts that an increase in one listed species increases ceteris paribus the forest value per hectareby 0.212%. Given that the average forest value per hectare has been computed as $3.76, thispercentage increase represents nearly one dollar per hectare. In addition, our results showthat when the number of species decreases by one unit, then the marginal price of the forestdecreases by 0.211%. This result implies that investing in fauna conservation, in terms ofincreasing species abundance, is expected to produce high marginal economic returns in for-est ecosystem services. In the case of flora species, the resulting coefficient is not significant.

The second model in Table 3 presents the biodiversity indicators in the form of Red Spe-cies indices (See Eq. 2). The main results reaffirm previous findings, where an increase in thearea of forest decreases forest valuations, and the provision of various ecosystem servicesis related to higher forest values than a single provision. Furthermore, population densitypositively affects forest values. Regarding the biodiversity indicators, in the second model ofIUCN Red Species, we can observe how flora is statistically significant and presents a neg-ative sign. This index can be understood as the relative amount of endangered flora speciesrespect to total listed species, and affects forest values negatively. Implications derived fromthis result encourage interventions to reduce the amount of endangered species, as scarcity ofbiodiversity decreases the economic returns from forest ecosystem services. However, thisvariable is significant at the margin (p-value 0.100), and as a consequence we do not wantto derive further policy implications.

Although our biodiversity indicators are different in both regressions, results confirm thatinvesting in conservation carries associated benefits from ecosystem services in terms of for-est values per hectare. These results show signs of the underlying effects of biodiversity onforest values, although these interactions should be further investigated in future research. Wenow proceed with an additional analysis to explore this relation in greater detail through theinteractions with ecosystem services. As discussed earlier, biodiversity could affect welfareestimates depending on the type of ecosystem services as well as on the distribution of forests.An investigation on these possible effects is worthwhile.

5.2 Interactions Between Biodiversity and Ecosystem Services

In order to have a deeper understanding of the previous results and in line with our objectives,the second step of this study explores whether biodiversity affects forest values depending

123

Author's personal copy

Mapping Biodiversity Indicators and Assessing Biodiversity Values in Global Forests 341

on the types of services provided and for the cases discussed in the literature. At this stage,we only consider our absolute biodiversity indices (IUCN Listed Species), since previouswork (Costanza et al. 2007) has looked into these interactions for species abundance. We alsobuild up on the Listed Species baseline model since it resulted in a better statistical fit andsignificance of explanatory variables in the previous models. We add cross effects betweenfauna and cultural services (fauna*cultural) to our baseline scenario as existence values andrecreation could be expected to be strongly related to biodiversity richness. We also includethe cross effect between flora and cultural services (flora*cultural) for the same reason, sincerecreation quality and aesthetics may also be determined by flora species diversity. Finally,

Table 4 Model with interaction effects between biodiversity indices and ecosystem services

lnval Coefficient Standard error t-value

Forest services’ characteristics

lnha −0.4711*** 0.0871 −5.41

boreal 1.6727 1.4828 1.13

tempmix −0.2831 1.2273 −0.23

tempconif 1.4262* 0.8155 1.75

tropicalwet 1.4175 1.2796 1.11

tropicalmix 1.8880 1.3396 1.41

hotspot 0.6885 0.8800 0.78

cultural 2.2252 2.0061 1.11

provisioning −1.3868 0.9006 −1.54

allservices 3.2367*** 1.1789 2.75

Biodiversity listed species indicators

fauna 0.0012* 0.0007 1.81

flora −0.0015 0.0010 −1.46

Interaction effects

fauna*cultural −0.0018 0.0028 −0.63

flora*cultural −0.0064 0.0048 −1.34

flora*provisioning 0.0022* 0.0011 2.06

Context characteristics

othermethod −0.1810 0.8901 −0.20

market −0.4674 1.2139 −0.38

revealed −1.0468 0.7010 −1.49

year −0.0887 0.0578 −1.53

lnGDP 0.2791 0.2981 0.94

lnpop 0.0057** 0.0017 3.26

constant 182.0463 113.7931 1.60

N 172

F-test 9.04

Prob > F 0.0000

R2 0.6175

*** Indicates statistical significance at α = 0.001; ** Indicates statistical significance at α = 0.01; and* Indicates that the variable is statistically significant at α = 0.1

123

Author's personal copy

342 E. Ojea et al.

the cross effect of flora and provisioning services (flora*provisioning) is included to assessto what extent the diversity of plants is related to timber, non-timber forest products andbioprospecting economic values.8

Table 4 presents the joint effects of biodiversity abundance and ecosystem services, result-ing in a similar R2 of 0.62. As far as the variables of interest are concerned, from Table 4we observe that the fauna index remains significant and positive. Interactions with culturalservices are not significant; however, we find that the interaction between flora diversityand provisioning services is positive and statistically significant. One interpretation of thisrelationship could be that a higher plant species abundance level is related to higher foresteconomic values from provisioning services. This result has implications for the conservationof species diversity and the provision of economic values. On one hand, provisioning ser-vices include timber which is traditionally related to silvicultural practices with low diversityof flora species. However, in our results this positive sign of the interaction between floraspecies and provisioning services may be explained by the relative importance of other pro-visioning services such as non-timber forest products or bioprospecting in the benefits fromforest ecosystem services.

Biodiversity, as considered in this analysis, has significant implications for the valueof forest services. We found evidence of biodiversity affecting forest values for one spe-cific interaction, while future analysis will determine whether these results are pointingto an underlying effect of biodiversity on the values provided by ecosystem services, andif different interactions with other ecosystem services can be seen. Further research on asmaller geographical scale, where biodiversity indices can be site-specific, may confirm thesefindings.

6 Concluding Remarks

The MA framework has been employed to link biodiversity and forest ecosystem values ina meta-analysis of worldwide forest valuation studies, based on the role of biodiversity asa fundamental component of ecosystems, supporting their capacity to provide services tohumans. This exercise constitutes a first attempt worldwide to link biodiversity indicatorsto the economic values provided by ecosystem services. Values were collected for manydifferent forest ecosystem types and services, both from market and non-market valuationtechniques in a collection of worldwide studies.

Results highlight the complexity of dependencies between biodiversity loss, forest eco-system services and their value to humans. The MA framework has proven to be a usefulguideline in the empirical analysis conducted in this exercise, especially at this scale. Fromthis study we obtain a first overview of how biodiversity may be valued through ecosystemservices. Results point to an underlying interaction between biodiversity and the value pro-vided by forest ecosystem services worldwide. The models show how biodiversity abundanceand scarcity can affect forest values and how this effect can vary with the set of ecosystemservices forests provide. Different policy implications can be derived from this exercise:the conservation of biodiversity in terms of species abundance is recommended as forestvalues are expected to increase and at the same time, high rates of threatened species mustbe avoided; investment in endangered species conservation is also found to be beneficialfor forest economic returns. Although a growing number of studies nowadays deal with

8 Other interactions such as fauna and provisioning services have not been included due the lack of evidencefor this effect in the literature, and in the case of regulating services, due to the small number of observationsin our sample.

123

Author's personal copy

Mapping Biodiversity Indicators and Assessing Biodiversity Values in Global Forests 343

ecosystem services and the benefits they provide to humans, many challenges still remainunsolved (see De Groot et al. 2009 for a recent review). Valuation efforts on ecosystemservices have changed the terms of discussion on nature conservation strategies: investmentsin conservation have shifted from being seen as conservation-development trade-offs to beingincreasingly seen as win-win situations, increasing social, economic and ecological benefits.The results of the present analysis contribute to this idea and support the positive interactionbetween biodiversity conservation and the benefits obtained from ecosystem services in thecase of forests.

These results are a first attempt to link biodiversity with ecosystem economic revenuesemploying the MA conceptual framework, which links biodiversity to ecosystem functioningand ecosystem services provided to humans. A big effort has been made in terms of datacollection to assess these links. Nevertheless, we acknowledge that the analysis conductedhere is constrained by data limitations and future applications at a more regional scale willcontribute to test the performance of this framework. Nevertheless, important directions forpolicy analysis relating to conservation priorities can be derived from the results here pre-sented. Another direct use of the current work may allow us to conduct a benefit-transferanalysis of forest valuation estimates, when direct valuation is too costly or implausible.Such assessments may be very useful in the context of unexpected catastrophic events suchas wildfires or drastic climate change episodes. Furthermore, the present work may allowus to have an indicator of the valuation in terms of global welfare values provided by forestecosystems.

Acknowledgements This work has been produced within the project CIRCE - Climate Change and ImpactResearch: the Mediterranean Environment; we therefore thank the European Commission, contract no.036961,for the financial support. We are grateful to two anonymous referees for thorough and detailed comments ona previous version of this paper. The authors thank Joshua Bishop of IUCN for having shared a databaseof valuation studies on forest biodiversity benefits, which was compiled by Katrina Mullan and AndreasKontoleon of Cambridge University, under a grant provided by the Government of Germany (BMU) andadministered by the European Environment Agency. The full database is available upon request from IUCN.Elena Ojea thanks Ramon Ortiz for helpful comments and Maria Loureiro wishes to thank the financial sup-port received by the Spanish Ministry of Environment via the National Parks Research Program, grant number2007/PN005.

References

Aakerlund NF (2000) Contingent ranking study of Danish preferences of forest characteristics. The RoyalVeterinary and Agricultural University (KVL)

Anthon S, Thorsen BJ (2002) Valuing afforestation, a hedonic approach. Report for the Forest and NatureAgency, Ministry of the Environment, Denmark

Balick M, Mendelsohn R (1992) Assessing the economic value of traditional medicines from tropical rainforests. Conserv Biol 6:128–130

Bann C (1997) An economic analysis of tropical forest land use options, Ratanakiri Province, Cambodia.Research Report, Economy and Environment Program for South East Asia (EEPSEA), InternationalDevelopment Research Centre, Ottawa. http://www.idrc.ca/eepsea/ev-8446-201-1-DO_TOPIC.html.Cited 23 Mar 2009

Bateman IJ, Lovett AA (2000a) Valuing and mapping woodland access potential. Q J Forest 94(3):215–222Bateman IJ, Lovett AA (2000b) Estimating and valuing the carbon sequestered in softwood and hardwood

trees, timber products and forest soils in Wales. J Environ Manage 60:301–323Bateman IJ, Lovett AA, Brainard JS (1996) Transferring benefit values: a GIS approach. In: The contingent

valuation method: academic luxury or practical tool, Posford Duvivier Environment/CSERGE seminarand workshop. Department of Economics, University College, London

Bellu LG, Cistulli V (1995) Economic valuation of forest recreation facilities in the Liguria region, Italy.CSERGE Working Paper GEC, 97–08

123

Author's personal copy

344 E. Ojea et al.

Bienabe E, Hearne RR (2006) Public preferences for biodiversity conservation and scenic beauty within aframework of environmental services payments. For Policy Econ 9(4):335–348

Bockstael NE, Freeman AM, Kopp R, Portney PR, Smith KV (2000) On measuring economic values fornature. Environ Sci Technol 34:1384–1389

Bonnieux F, Le Goffe P (1997) Valuing the benefits of landscape restoration: a case study of the Cotentin inLower-Normandy, France. J Environ Manage 50(3):321–333

Bostedt G, Mattsson L (2006) A note on benefits and costs of adjusting forestry to meet recreational demands.J For Econ 12:75–81

Boyd J, Banzhaf S (2007) What are ecosystem services? The need for standardized environmental accountingunits. Ecol Econ 63(2–3):616–626

Brander LM, Van Beukering P, Cesar HSJ (2007) The recreational value of coral reefs: a meta-analysis. EcolEcon 63:209–218

Campos P, Riera P (1996) Social benefits from forests. An applied analysis of Iberian Dehesas and Montados.Información Comercial Española

Chase LC, Lee DR, Shulze WD, Anderson DJ (1998) Ecotourism demand and differential pricing of nationalpark access in Costa Rica. Land Econ 74:466–482

Chavas J-P (2009) On the productive value of biodiversity. Environ Resour Econ 42:109–131Chomitz KM, Alger K, Thomas TS, Orlando H, Vila Nova P (2005) Opportunity costs of conservation in a

biodiversity hotspot: the case of southern Bahia. Environ Dev Econ 10(3):293–312Christie M, Crabtree B, Slee B (2001) An economic assessment of informal recreation policy in Scottish

countryside. Scott Geogr J 116(2):125–142Costanza R, Fisher B, Mulder K, Liu S, Christopher T (2007) Biodiversity and ecosystem services: A multi-

scale empirical study of the relationship between species richness and net primary production. Ecol Econ61:478–491

Costanza R, d’Arge R, deGroot R, Farber S, Grasso M, Hannon B, Limburg K, Naeem S, O’Neill RV, ParueloJ, Raskin RG, Sutton P, van der Belt M (1997) The value of world’s ecosystem services and naturalcapital. Nature 387(6630):253–260

Costello C, Ward M (2006) Search, bioprospecting and biodiversity conservation. J Environ Econ Manage52(3):615–626

De Groot RS, Alkemade R, Braat L, Hein L, Willemen L (2009) Challenges in integrating the concept ofecosystem services and values in landscape planning, management and decision making, EcologicalComplexity, (forthcoming)

Dubgaard A (1998) Economic valuation of recreational benefits from Danish forests. In: Dabbert S, Dubg-aard A, Slangen L, Whitby M (eds) The economics of landscape and wildlife conservation. Oxon:. CABInternational, UK

Edwards-Jones G, Edwards-Jones ES, Mitchell K (1995) A comparison of contingent valuation methodol-ogy and ecological assessment as techniques for incorporating ecological goods into land-use decisions.J Environ Plan Manag 38(2):215–230

Emerton L (1999) Mount Kenya: the economics of community conservation. In: IIED evaluating Eden series,Discussion Paper 4

ERM, Environmental Resources Management (1996) Valuing management for biodiversity in British forests,Report to UK Forestry Commission

FAO-Food and Agriculture Organization (2005) Global forest resources assessment 2005: Progress towardssustainable forest management, Forestry Paper 147

Fisher B, Turner KR, Morling P (2009) Defining and classifying ecosystem services for decision making. EcolEcon 68(3):643–653

Fisher B, Turner RK (2008) Ecosystem services: classification for valuation. Biol Conserv 141:1167–1169Garber-Yonts B, Kerkvliet J, Johnson R (2004) Public values for biodiversity conservation in the Oregon Coast

Range. For Sci 50(5):589–602Garrod GD, Willis KG (1997) The non-use benefits of enhancing forest biodiversity: a contingent ranking

study. Ecol Econ 21:45–61Ghermandi A, van den Bergh JCJM, Brander LM, de Groot HLF, Nunes PALD (2008) The economic value

of wetland conservation and creation: a meta-analysis, FEEM Nota di Lavoro 079/2008, SustainableDevelopment Series

Godoy R, Wilkie D, Overman H, Cubask AG, Demmer J, McSweeney K, Brokaw N (2000) Valuation ofconsumption and sale of forest goods from a Central American rain forest. Nature 406:62–63

Gurluk S (2006) The estimation of ecosystem services’ value in the region of Misi Rural Development Project:results from a contingent valuation survey. For Policy Econ 9(3):209–218

123

Author's personal copy

Mapping Biodiversity Indicators and Assessing Biodiversity Values in Global Forests 345

Hanley N, Ruffel R (1993) The contingent valuation of forest characteristics: two experiments forestry andthe environment: economic perspectives. In: Adamowicz WL, White W, Phillips WE (eds). CAB Inter-national Wallingford, pp 171–197

Hanley N, Willis K, Powe N, Anderson M (2002) Valuing the benefits of biodiversity in forests, Report to UKForestry Commission

Hanley N, Wright RE, Adamowicz WL (1998) Using choice experiments to value the environment. EnvironResour Econ 11(3–4):413–428

Heston A, Summers R, Aten B (2009) Penn world table version 6.3. Center for international comparisons ofproduction, income and prices at the University of Pennsylvania. http://pwt.econ.upenn.edu/php_site/pwt_index.php. Cited August 2009

Horne P, Boxall PC, Adamowicz WL (2005) Multiple-use management of forest recreation sites: a spatiallyexplicit choice experiment. For Ecol Manag 207:189–199

Horowitz JK, McConnell KE (2002) A review of WTA/WTP studies. J Environ Econ Manag 44:426–477Horton B, Colarullo G, Bateman IJ, Peres C (2003) Evaluating non-user willingness to pay for a large-scale

conservation program in Amazonia: a UK/Italian contingent valuation study. Environ Conserv 30:139–146

Hougner C, Colding J, Söderqvist T (2006) Economic valuation of a seed dispersal service in the StockholmNational Urban Park, Sweden. Ecol Econ 59:364–374

Howard P (1995) The economics of protected areas in Uganda: costs, benefits and policy issues. Dissertation,University of Edinburgh

IFM, International Monetary Fund (2007) World Economic Outlook database. http://www.imf.org/external/ns/cs.aspx?id=28. Cited Apr 2008

IUCN-International Union for the Conservation of Nature (2007) Table 6a, Number of extinct, threatened andother species of animals in each Red List Category in each country, and Table 6b, Number of extinct,threatened and other species of plants in each Red List Category in each country. http://www.iucnredlist.org/info/stats. Cited 17 Mar 2008

Kaiser B, Roumasset J (2002) Valuing indirect ecosystem services: the case of tropical watersheds. EnvironDev Econ 7(4):701–714

Kniivilä M (2004) Contingent valuation and cost-benefit analysis of nature conservation: a case study in NorthKarelia, Finland, Research Notes 157, Faculty of Forestry, University of Joensuu

Kniivilä M, Ovaskainen V, Saastamoinen O (2002) Costs and benefits of forest conservation: regional andlocal comparisons in eastern Finland. J For Econ 8:131–150

Kontoleon A, Swanson T (2003) The willingness to pay for property rights for the Giant Panda: can a charis-matic species be an instrument for nature conservation. Land Econ 79(4):483–499

Kramer RA, Mercer DE (1997) Valuing a global environmental good: US residents’ willingness to pay toprotect tropical rain forest. Land Econ 73(2):196–210

Kramer RA, Sharma N, Munashinghe M (1995) Valuing tropical forests. Methodology and case study ofMadagascar, World Bank Environment Paper 13, 31 Dec 1995

Kramer RA, Holmes TP, Haefele M (2003) Using contingent valuation to estimate the value of forest ecosys-tem protection. In: Ills EO, Abt KL (eds) Forests in a Market Economy. Kluwer, Dordrecht

Lienhoop N, Macmillan D (2007) Valuing wilderness in Iceland: estimation of WTA and WTP using themarket stall approach to contingent valuation. Land Use Policy 24(1):289–295

Lindhjem H (2007) 20 years of stated preference valuation of non-timber benefits from Fennoscandian forests:A meta-analysis. J For Econ 12:251–277

Loomis JB, Lockwood M, DeLacy T (1993) Some empirical evidence on embedding effects in contingentvaluation of forest protection. J Environ Econ Manag 25(1):45–55

Loureau M, Naeem S, Inchausti P, Bengtsson J, Grime JP, Hector A, Hooper DU, Huston MA, Raffaelli D,Schmid B, Tilman D, Wardle DA (2001) Biodiversity and ecosystem functioning: current knowledgeand future challenges. Science 294:804–808

Mahapatra AK, Tewari DD (2005) Importance of non-timber forest products in the economic valuation of drydeciduous forests of India. For Policy Econ 7(3):455–467

Mallawaarachchi T, Blamey RK, Morrison MD, Johnson AKL, Bennett JA (2001) Community values forenvironmental protection in a cane farming catchment in Northern Australia: a choice modelling study.J Environ Manag 62(3):301–316

MA-Millennium Ecosystem Assessment (2005) Ecosystems and human well-being: biodiversity synthesis.World Resources Institute, Washington, DC

MA-Millennium Ecosystem Assessment (2003) Ecosystem and human well-being: a framework for assess-ment. World Resources Institute, Washington, DC

Mogas J, Riera P, Bennett JA (2006) Comparison of contingent valuation and choice modelling with second-order interactions. J For Econ 12(1):5–30

123

Author's personal copy

346 E. Ojea et al.

Monela GC, Chamshama SAO, Mwaipopo R, Gamassa DM (2001) A study on the social, economic andenvironmental impacts of forest landscape restoration in Shinyanga region, Tanzania, Report to IUCN,2001

Mooney HA, Cropper A, Reid W (2004) The millennium ecosystem assessment: what is it all about?. TrendsEcol Evol 19(5):221–224

Murthy IK, Bhat PR, Ravindranath NH, Sukumar R (2005) Financial valuation of non-timber forest productflows in Uttara Kannada district, Western Ghats, Karnataka. Curr Sci India 88(10):1573–1579

Naidoo R, Adamowicz WL (2005) Biodiversity and nature based tourism at forest reserves in Uganda. EnvironDev Econ 10:159–178, Cambridge University Press

Ninan KN, Sathyapalan J (2005) The economics of biodiversity conservation: a study of a coffee growingregion in the Western Ghats of India. Ecol Econ 55(1):61–72

Nowak DJ, Wang J, Endreny T (2007) Environmental and economic benefits of preserving forests withinurban areas: air and water quality. In: de Brun CTF (ed) The economic benefits of land conservation

Oumar BC, Bishop J, Deme M, Diadhiou HD, Dieng AB, Diop O, Garzon PA, Gueye B, Kebe M, Ly OK,Ndiaye V, Ndione CM, Sene A, Thiam D, Wade IA (2006) The economic value of wild resources inSenegal: a preliminary evaluation of non-timber forest products, game and freshwater fisheries, IUCN,Gland. Switzerland and Cambridge, UK

Pearce D, Moran D (1994) The economic value of biodiversity, IUCN, the World Conservation Union. Earth-scan Publications Ldt, London

Phillips S, Silverman R, Gore A (2008) Greater than zero: toward the total economic value of Alaska’s NationalForest Wildlands. The Wilderness Society, Washington, D.C

Pimm SL, Raven P (2000) Extinction by numbers. Nature 403:843–845Portela R, Wendland KJ, Pennypacker LL (2008) The idea of market-based mechanisms for forest conserva-

tion and climate change. In: Streck C, O’Sullivan R, Janson-Smith T (eds) Forests, climate change andthe carbon market. Oxford University Press, Oxford

Raunikar R, Buongiorna J (2004) Willingness to pay for forest amenities: the case of non-industrial ownersin the south central United States. Ecol Econ 56(1):132–143

Richardson L, Loomis JB (2009) The total economic value of threatened, endangered and rare species: Anupdated meta-analysis. Ecol Econ 68(5):1535–1548

Richmond A, Kaufmann RK, Myneni RB (2007) Valuing ecosystem services: a shadow price for net primaryproduction. Ecol Econ 64:454–462

Ricketts TH, Daily GC, Ehrlich PR, Michener CD (2004) Economic value of tropical forest to coffee produc-tion. PNAS 101(34):12579–12582

Rolfe J, Bennett J, Louviere J (2000) Choice modelling and its potential application to tropical rainforestpreservation. Ecol Econ 35:289–302

Rosales RMP, Kallesoe MF, Gerrard P, Muangchanh P, Phomtavong S, Khamsomphou S (2005) Balancing thereturns to catchment management: the economic value of conserving natural forests in Sekong, Lao PDR,IUCN Water, Nature and Economics Technical Paper 5. The World Conservation Union, Ecosystemsand Livelihoods Group Asia

Samuel J, Thomas T (1996) The valuation of unpriced forest products by private woodland owners in Wales. In:Roper CS, Park A (eds) The living forest: non market benefits of forestry. Proceedings of an internationalsymposium on non-market benefits of forestry

Sattout EJ, Talhouk SN, Caligari PDS (2007) Economic value of cedar relics in Lebanon: an application ofcontingent valuation method for conservation. Ecol Econ 61(2–3):315–322

Scarpa R, Hutchinson WG, Chilton SM, Buongiorno J (2000) Importance of forest attributes in willingnessto pay for recreation: a contingent valuation study of Irish forests. For Policy Econ 1:315–329

Shahwahid HM, Suhaimi AR, Rasyikah MK, Jamaluddin AS, Huang YF, Farah MS (2003) Policies and incen-tives for rainwater harvesting in Malaysia, National Hydraulic Research Institute of Malaysia (NAHRIM)Report

Shechter M, Reiser B, Zaitsev N (1998) Measuring passive use value: pledges, donations and CV responsesin connection with an important natural resource. Environ Resour Econ 12:457–478

Siikamaki J, Layton DF (2007) Discrete choice survey experiments: a comparison using flexible methods.J Environ Econ Manag 53(1):122–139

Simpson RD, Sedjo RA, Reid JW (1996) Valuing biodiversity for use in pharmaceutical research. J Polit Econ104(1):163–185

Thomas CD, Cameron A, Green RE, Bakkenes M, Beaumont LJ, Collingham YC, Erasmus BFN, de SiqueiraMF, Grainger A, Hannah L, Hughes L, Huntley B, van Jaarsveld AS, Midgley GF, Miles L, Ortega-Huerta M, Peterson AT, Phillips OL, Williams SE (2004) Extinction risk from climate change. Nature427:145–148

123

Author's personal copy

Mapping Biodiversity Indicators and Assessing Biodiversity Values in Global Forests 347

Tilman D, Polasky S, Lehman C (2005) Diversity, productivity and temporal stability in the economies ofhumans and nature. J Environ Econ Manag 49:405–426

Toman M (1998) Why not to calculate the value of the world’s ecosystem services and natural capital. EcolEcon 25:57–60

van Beukering PJH (2002) The economic value of tropical forest and its consequences for setting up paymentschemes for environmental services: a comparison between the Leuser National Park (Indonesia) andthe Iwokrama Forest (Guyana). In: Seminar proceedings on issues in International Nature Conservation,Utrecht University

van Beukering PJH, Cesar HSJ, Janssen MA (2003) Economic valuation of the Leuser National Park in Suma-tra, Indonesia. Ecol Econ 44(1):43–62

van der Heide CM, van den Bergh JCJM, van Ierland EC, Nunes PALD (2005) Measuring the economic valueof two habitat defragmentation policy scenarios for Veluwe, the Netherlands, Fondanzione Enrico MatteiNota Di Lavoro 42

Verma M (2000) Economic valuation of forests of Himachal Pradesh. Report to IIED Himachal Pradesh,Forestry Review. Indian Institute of Forest Management, Bhopal, India

Wallace KJ (2007) Classification of ecosystem services: problems and solutions. Biol Conserv 139(3-4):235–246

Walsh RG, Loomis JB, Gillman RA (1984) Valuing option, existence, and bequest demands for wilderness.Land Econ 60(1):14–29

Wang X, Bennett J, Xie C, Zhang Z, Liang D (2007) Estimating non-market environmental benefits of the con-version to cropland to forest and grassland program: a choice modeling approach. Ecol Econ 63(1):114–125

Woodward RT, Wui Y (2001) The economic value of wetland services: a meta-analysis. Ecol Econ 37:257–270Wooldridge JM (2003) Introductory econometrics: a modern approach. Thomson-South-Western College Pub-

lishing, MansonWorld Bank the (2007) The little green data book. International Bank for Reconstruction and Development/The

World Bank, WashingtonZandersen M, Termansen M, Jensen FS (2005) Benefit transfer over time of ecosystem values: the case of

forest recreation, Working Paper no. FNU-61, Danish Centre For Forest, Landscape and Planning

123

Author's personal copy