Valuing the diversity of biodiversity.
Mike Christie*, Nick Hanley**, John Warren*, Kevin Murphy***, Robert Wright** and Tony
Hyde****
*:
Institute of Rural Sciences, University of Wales Aberystwyth, SY23 3AL
**:
Economics Department, University of Stirling, FK9 4LA
***:
Department of Environmental and Evolutionary Biology, Glasgow University, G12 8QQ
****: Socio-Economic Research Services, Aberystwyth, SY23 3AH
Corresponding author:
Mike Christie, Institute of Rural Sciences, University of Wales Aberystwyth, Aberystwyth,
Wales, SY23 3AL, mec@aber.ac.uk, Tel: 01970 622217, Fax: 01970 611264
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Valuing the diversity of biodiversity
Abstract
Policy makers have responded to concerns over declining levels of biodiversity by introducing a
range of policy measures including agri-environment and wildlife management schemes. Costs
for such measures are relatively easy to establish, but benefits are less easily estimated.
Economics can help guide the design of biodiversity policy by eliciting public preferences on
different attributes of biodiversity. However, this is complicated by the generally low level of
awareness and understanding of what biodiversity means on the part of the general public. In this
paper we report research that applied the choice experiment and contingent valuation methods to
value the diversity of biological diversity. Focus groups were used to identify ecological concepts
of biodiversity that were important and relevant to the public, and to discover how best to
describe these concepts in a meaningful and understandable manner. A choice experiment
examined a range of biodiversity attributes including familiarity of species, species rarity, habitat,
and ecosystem processes, while a contingent valuation study examined public willingness to pay
for biodiversity enhancements associated with agri-environmental and habitat re-creation policy.
The key conclusions drawn from the valuation studies were that the public have positive
valuation preferences for most, but not all, aspects of biodiversity, but that they appeared to be
largely indifferent to how biodiversity protection was achieved. Finally, we also investigate the
extent to which valuation workshop approaches to data collection can overcome some of the
possible information problems associated with the valuation of complex goods. The key
conclusion was that the additional opportunities for information exchange and group discussion in
the workshops helped to reduce the variability of value estimates.
Keywords: biodiversity; agri-environmental policy; choice experiments; contingent valuation,
valuation workshops.
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1.
Introduction
Society needs to make difficult decisions regarding its use of biological resources. For example in
terms of habitat conservation, or changing how we manage farmland through agri-environmental
policy (Hanley and Shogren, 2001). Environmental valuation techniques can provide useful
evidence to support such policies by quantifying the economic value associated with the
protection of biological resources. Pearce (2001) argues that the measurement of the economic
value of biodiversity is a fundamental step in conserving this resource since ‘the pressures to
reduce biodiversity are so large that the chances that we will introduce incentives [for the
protection of biodiversity] without demonstrating the economic value of biodiversity are much
less than if we do engage in valuation’. OECD (2001) also recognises the importance of
measuring the economic value of biodiversity and identifies a wide range of uses for such values,
including demonstrating the value of biodiversity, in targeting biodiversity protection within
scarce budgets, and in determining damages for loss of biodiversity in liability regimes.
More generally, the role of environmental valuation methodologies in policy formulation is
increasingly being recognised by policy makers. For example, the Convention of Biological
Diversity’s Conference of the Parties decision IV/10 acknowledges that ‘economic valuation of
biodiversity and biological resources is an important tool for well-targeted and calibrated
economic incentive measures’ and encourages Parties, Governments and relevant organisations to
‘take into account economic, social, cultural and ethical valuation in the development of relevant
incentive measures’.
1.1.
Valuing biodiversity: the challenge
However, what concerns us here is not whether one should attempt to place economic values on
changes in biodiversity, but rather in what the particular difficulties are in doing so. These include
incommensurate values or lexicographic preference issues (Spash and Hanley, 1995; Rekola,
2003) and - the issue we focus on here - people’s limited understanding of complex
environmental goods (Hanley, et al., 1996; Christie, 2001; Limburg et al., 2002).
Stated preference valuation methods require survey respondents to make well-informed value
judgements on the environmental good under investigation. This requires information on
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unfamiliar goods to be presented to respondents in a meaningful and understandable format.
Herein lies the problem: many studies have found that members of the general public have a low
awareness and poor understanding of the term biodiversity, and that communicating relevant
information within a stated preference study to be difficult. Furthermore, if one is unaware of the
characteristics of a good, then it is unlikely that one has well-developed preferences for it which
can be uncovered in a stated preference survey.
Various surveys have examined the publics’ understanding of the term ‘biodiversity’. A recent
UK survey found that only 26% of respondents had heard of the term ‘biodiversity’ (DEFRA,
2002). Similar findings are also reported in Spash and Hanley (1995). The lack of public
understanding of the term biodiversity will make the valuation exercise difficult; however, people
can learn during a survey, and may have preferences for what biodiversity actually means, even if
they are unaware of the term itself: the DEFRA (2002) survey also found that 52% considered the
protection of wildlife to be ‘very important’, even though they did not know what biodiversity
itself meant.
A related complication is that biodiversity itself is not uniquely defined by conservation
biologists. Scientists are in general agreement that the number of species per unit of area provides
a useful starting point (Harper and Hawksworth, 1995; Whittaker, 1977). Although such a
measure appears to be relatively straightforward, issues such as what constitutes a species (Harper
and Hawksworth, 1995; Claridge and Boddy, 1990); and what size of area to count species over
complicate this measure (Whittaker, 1977). Even if these questions were resolved, ecologists
recognise that some species, such as keystone species, may be more important and/or make a
greater contribution to biodiversity than others (Wilson, 2003; Noss, 1990). A further
complicating factor relates to the extent to which the public are capable of understanding these
ecological concepts. Ecologists also recognise that biodiversity may be described and measured
in terms of species diversity within a community or habitat (Arts et al., 1990) and in terms of the
diversity of ecological functions (Steneck and Dethier, 1994; Herrera et al., 1997). Finally, the
public may have preferences for certain species that display charismatic features such as beauty
or speed, or be locally significance, even though these features may not be considered
ecologically important (May, 1995).
The issues highlighted above indicate that research that attempts to value changes in biodiversity
using a direct elicitation of public preferences will be challenging, since it requires us to identify
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appropriate language in which complex biodiversity concepts can be meaningfully conveyed to
members of the public in ways which are consistent with underlying ecological ideas on what
biodiversity is.
This paper aims to identify problems surrounding the economic valuation of ‘biodiversity’. In
particular, we report the results from a series of stated preference studies on changes in
biodiversity on UK farmland. The studies include a contingent valuation study on three
biodiversity enhancing policies (agri-environment scheme, habitat re-creation and protection of
biodiversity loss associated with housing development) and a choice experiment that examines
the value of biodiversity attributes(familiar species of wildlife, rare unfamiliar species of wildlife,
habitats and ecosystem services). We also examine through a series of valuation workshops the
impact of information deficit which typifies the knowledge level of most members of the general
public regarding biodiversity.
The paper is organised as follows. Section 2 presents a brief review of the current literature on
valuing biodiversity and identifies gaps in this literature. Our study design is explained in Section
3, with results presented in Section 4. A discussion concludes the paper.
2.
Previous Literature
A general comment on much of the existing biodiversity valuation literature is that it mostly does
not value diversity itself, but rather focuses on individual species and habitats (Pearce, 2001). In
this section, we review a number of key studies that have attempted to measure the economic
value of different elements of biodiversity. In particular, we distinguish between studies that have
valued a biological resource (e.g. a particular species, habitat area, or ecosystem function) and
those which have valued the biological diversity of those resources (e.g. ecological concepts of
biodiversity such as the rarity of a species).
2.1.
Studies that value biological resources.
There have been a large number of studies that have valued particular species. Most of these
studies have been undertaken in the US and utilise stated preference techniques, thus enabling
both use and passive-use values to be assessed. Nunes and van den Bergh (2001) provide an
extensive review of valuation studies that have addressed both single and multiple species.
Valuations for single species range from $5 to $126 per household per year, and for multiple
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species range form $18 to $194. In the UK, there have been a limited number of studies that have
valued both single and multiple species. For example, Macmillan et al. (2002) estimated the value
of wild geese conservation in Scotland, while White et al. (1997 and 2001) examine the value
associated with the conservation of four UK mammals: otters, water voles, red squirrels, and
brown hare. Macmillan et al. (2001) also takes a slightly different perspective by valuing the
reintroduction of two species (the beaver and wolf) into native forests in Scotland.
Biological resources may also be considered in terms of the diversity within natural habitats.
Studies have addressed the valuation of habitats from two perspectives. One approach is to link
the value of biodiversity to the value of protecting natural areas that have high levels of outdoor
recreation or tourist demand. A second approach to the valuation of natural areas involves the use
of stated preference methods. UK examples of contingent valuation (CV) studies that have valued
habitats include: Garrod and Willis, (1994) who examined the willingness to pay of members of
the Northumberland Wildlife Trust for a range of UK habitat types; Hanley and Craig (1991) who
valued upland heaths in Scotland’s flow country; and Macmillan and Duff (1998) who examine
the publics’ willingness to pay (WTP) to restore native pinewood forests in Scotland.
Ecosystem functions and services describe a wide range of life support systems including waste
assimilation, flood control, soil and wind erosion prevention, and water quality maintenance.
Many of these functions and services are complex and it is likely that members of the public will
possess a poor understanding of these issues. The consequence of this is that attempts to value
ecosystem functions and services will be difficult, particular in methods (such as the stated
preference methods) where respondents are required to make a value judgement based on the
description of the good in question. Analysts often use other techniques including averting
behaviour, replacement costs, and production functions to measure the indirect values of
ecosystem functions.
2.2.
Studies that value the diversity of biological resources
Studies that have quantified genetic diversity have predominantly measured direct use benefits of
biological resources in terms of inputs to the production of market goods such as new
pharmaceutical and agricultural products. The majority of studies have based valuations on
market contracts and agreements for bioprospecting by pharmaceutical industries (Simpson et al.
1996; Rausser and Small, 2000). Ten Kate and Laird (1999) provide an extensive review of such
bioprospecting agreements. Franks (1999) provides a useful contribution on the value of plant
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genetic resources for food and agriculture in the UK and also the contribution of the UK's agrienvironmental schemes to the conservation of these genetic resources.
A number of valuation studies have attempted to value biodiversity by explicitly stating to
respondents that the implementation of a conservation policy will result in a change in the
biodiversity of an area. For example, Garrod and Willis (1997) estimated passive-use values for
biodiversity improvements that increased the proportion of broad-leaved trees planted and the
area of open spaces in the forest in remote upland coniferous forests in the UK. Willis et al.
(2003) extend this work to examine public values for biodiversity across a range of UK woodland
types. Other studies have assessed public WTP to prevent a decline in biodiversity. For example,
Macmillan et al. (1996) measures public WTP to prevent biodiversity loss associated with acid
rain; whilst Pouta et al. (2000) estimate the value of increasing biodiversity protection in Finland
through implementing the Natura 2000 programme.
White et al. (1997 and 2001) examine the influence of species characteristics on WTP. They
conclude that charismatic and flagship species such as the otter attract significantly higher WTP
values than less charismatic species such as the brown hare. They further suggest that species
with a high charisma status are likely to command higher WTP values than less charismatic
species that may be under a relatively greater threat or of more biological significance in the
ecosystem. In a meta-analysis of WTP for a range of species, Loomis and White (1996) also find
that more charismatic species, such as marine mammals and birds, attract higher WTP values than
other species.
The above review has demonstrated that from those studies that have claimed to value
biodiversity, only a handful have actually examined the diversity that exists within biological
resources; most studies have alternatively tended to simply value a particular biological resource
such as a species, habitat or ecosystem service. Furthermore, studies that have attempted to value
the diversity of biological resources currently only provided limited information on the value of
the components of biological diversity. Research effort has yet to provide a comprehensive
assessment of the value attached to the components of biological diversity such as
anthropocentric measures (e.g. cuteness, charisma, and rarity) and ecological measures (e.g.
keystone species and flagship species). It is this issue of the valuing the ecological and
anthropocentric diversity of biological resources that the current research aims to address.
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3.
Study Design
3.1.
Developmental focus groups
The policy setting for this research is the development of policy on biodiversity conservation and
enhancement on farmland in England. The principal challenges in study design were to identify
which ecological and anthropocentric concepts of biodiversity needed to be communicated to the
general public, and thus form the focus of the valuation exercise. We also needed to design
effective ways of conveying the complex information on biodiversity.
In a review of ecological literature (Christie et al., 2004), we identified eleven different concepts
that ecologists commonly use to describe and measure biodiversity. Clearly, it would be
extremely difficult to attempt to value all of these concepts within a single economic valuation
study. In an attempt to simplify, a conceptual framework was drawn up to provide a framework in
which public understanding of biodiversity could be tested (Figure 1). This framework is split
into sections according to which perspective we take on the importance and meaning of
biodiversity: ecological or anthropocentric. Within each of these headings, we identify different
aspects of biodiversity that need to be considered for inclusion. The final row of the Figure shows
the biodiversity attributes that were eventually selected for the experimental design of the choice
experiment. We now explain how these were chosen.
A series of focus groups comprising members of the general public were arranged. Discussions
aimed to identify the level of understanding that the public had for each of the elements of the
framework in Figure 1, and also to identify their views on the importance of each element. The
key issues identified in the developmental focus groups included:

Over half of the participants could not remember having come across the term
‘biodiversity’ before. Some of those who had indicated a familiarity with the term
‘biodiversity’ were unable to provide a clear or accurate definition of the concept.

Participants indicated that they were familiar with related terms including ‘species’,
‘habitat’ and ‘ecosystem’.

Participants indicated that they were not familiar with the majority of scientific concepts
of biodiversity in Figure 1 such as keystone species and flagship species. On a more
positive note, it was also found that most participants of the focus groups appeared to be
capable of quickly picking up a basic understanding of most biodiversity concepts if
these were explained in layman’s terms.
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The conclusion from this is that the survey would need to employ alternative, non-scientific
terminology to meaningfully describe the ecological concepts associated with biodiversity. Based
on this focus group evidence, four attributes were identified as being appropriate to describe the
diversity of biodiversity concepts to the public:

Familiar species of wildlife. This attribute includes charismatic, familiar (recognisable)
and locally symbolic species, and may be considered in terms of both common and rare
familiar species.

Rare, unfamiliar species of wildlife. This attribute focuses on those species that are
currently rare or in decline which are unlikely to be familiar to members of the public.

Habitat. The protection of habitats and in particular the mix of species that reside within
them was considered to be an important component of biodiversity conservation. Of note
in this category was the fact that focus group participants were more concerned about
achieving a biodiversity outcome (i.e. protecting the range of species within a habitat),
rather than a focus on how this might be achieved (e.g. by targeting policy towards the
protection of ecologically significant species such as keystone or umbrella species).

Ecosystem processes. The public were also concerned with preserving the ‘health’ of
ecosystem processes. It was also considered useful to distinguish between ecosystem
processes which have a direct impact on humans and those which do not.
Another question that needed to be addressed relates to which methodology is likely to be the
most suited to the valuation of biodiversity change. In this study, we aim, if possible, to capture
all components of the total economic value associated with biodiversity change. Stated preference
methods (including contingent valuation and choice experiments) appear to be the most flexible
valuation approach since they are capable of capturing both use and passive-use values. A key
objective of this research was to measure the economic value of the component attributes of
biological diversity. It was concluded that choice experiments would be the most appropriate
method to value of these attributes (Bennett and Blamey, 2001). In addition, we also wanted to
estimate values for three types of biodiversity changes that were considered to be of particular
relevance to policy makers, namely: biodiversity enhancement associated with agrienvironmental schemes, biodiversity enhancements associated with the re-creation of wildlife
habitats, and biodiversity loss from farmland associated with development activities (e.g. house
building). Contingent valuation scenarios could be designed to directly elicit the values of the
three proposed policy programmes, and thus seems a neater, more direct approach with regard to
this second research objective. Thus, this research involved the use of both the choice experiment
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and contingent valuation methods to value biodiversity. In-person household interviews were
undertaken with a random sample of the population in two case study areas. Cambridgeshire was
chosen as a predominantly intensively arable area that supports low levels of biodiversity, while
Northumberland was chosen to represent an area with high levels of biodiversity and a lower
intensity of land use.
3.2.
Design Specifics
A key factor affecting the validity of stated preference studies relates to the success to which the
good under investigation can be meaningfully, accurately, and consistently presented to survey
respondents. Although this can be a challenge in many valuation studies, the very fact that only a
small proportion of the public have knowingly heard of the term biodiversity before presents a
significant challenge to this research. In this study, the survey instrument was required to present
a lot of information on biodiversity which is likely to be complex and new to respondents. The
majority of valuation studies tend to describe the environmental good under investigation using
verbal descriptions, perhaps supported by some written script and / or pictorial images. Although
such an approach to presenting the good can be successful with goods that are familiar to survey
respondents, evidence gathered in the developmental focus groups indicated that such a standard
approach was unlikely to be suitable for presenting biodiversity which was found to be unfamiliar
and considered complex. Feedback from the focus groups also indicated that the large volume of
new information required to be presented on biodiversity was found to lead to both confusion and
respondent fatigue. The adoption of a more visual and interactive approach was therefore
considered to be more suitable.
For these reasons, a PowerPoint ‘slideshow’ was used to convey information to respondents. This
has a number of advantages in terms of using a range of formats (pictures, audio tracks and text),
which helps minimise respondent fatigue, reduces variation in the information presented, and
maximise the effectiveness with which information is conveyed. The PowerPoint presentation
introduced survey respondents to a simple definition of biodiversity; ‘biodiversity … is the
scientific term used to describe the variety of wildlife in the countryside’. Slides 3 to 8 then
introduced the four attributes of biodiversity that had been identified in the developmental focus
groups: familiar species of wildlife, rare (unfamiliar) species of wildlife, habitat, and ecosystem
processes. Each attribute was defined, and alternative levels of biodiversity enhancements
associated with these attributes were introduced. Within these descriptions, named examples of
relevant species, habitats and ecosystem processes within the study areas were provided and
10
images presented. These were included to help respondents attain a clearer understanding of the
various aspects of biodiversity being discussed. Following the presentation of this information,
respondents were provided with an opportunity to discuss and clarify with the interviewer any
issues of outstanding confusion. In slides 9 – 12, the case study area (Cambridgeshire or
Northumberland) was then introduced. Details presented included a description of the
predominant land uses found within the case study area, and the current levels of biodiversity that
exist in that area. Respondents were then informed that human activities, such as farming and
development, are currently threatening overall levels of biodiversity in the area and the
consequences of this on the four biodiversity attributes were outlined. Slides 13 – 18 informed
respondents that the government could introduce policies to help protect and enhance biodiversity
in the respective case study areas. Policies described included agri-environmental schemes and
habitat re-creation schemes. Slides 14 – 17 then outlined how such policies could be introduced to
specifically enhance the four aspects of biodiversity identified earlier. In each case, the potential
improvements were described in terms of the attribute levels used in the choice experiment.
Respondents were then asked to think about which aspects of biodiversity they would like to see
being protected and enhanced. Finally, at the end of the presentation respondents were given a
further opportunity to clarify any issues of confusion / uncertainty regarding any aspect of the
presentation.
Feedback from respondents of a pilot survey indicated that the majority of respondents
understood the concepts presented. Respondents also indicated that the presentation of more
information (to try to increase understanding) would lead to respondent fatigue. The inclusion of
opportunities for respondents to clarify and discuss issues of confusion with the interviewer was
seen as a valuable option. The impact of information provision was an issue that was further
explored in a series of valuation workshops, as explained below.
3.2.1.
The choice experiment
Following the PowerPoint presentation, respondents of both the household survey and valuation
workshops were asked a complete a choice experiment exercise. The choice experiment was
introduced as follows:
"In the presentation you were provided with information on
different aspects of biodiversity. You were also informed that
biodiversity within Cambridgeshire (Northumberland) is under
threat. We as a society have some options over how we respond
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to the threats to biodiversity. We are therefore interested in your
opinions on what action you would most like to see taken.
We are now going to show you five alternative sets of policy
designs that could be used to enhance Cambridgeshire’s
(Northumberland’s) biodiversity. In each set, you will be asked
to choose the design which you prefer."
An example of a choice task was then presented to respondents and the choice task was
explained. Once the respondents had undertaken all five choice tasks, they were asked to indicate
the main reason that they had for making the choices that they did. This was to allow protest
responses to be identified.
We have already explained how biodiversity attributes were selected for inclusion in the choice
experiment (above). Each of these attributes was then defined according to three levels of
provision, including the status quo (i.e. ‘do nothing’ which would lead to a continued decline in
biodiversity in the study area) and two levels of improvement/enhancement. Table 1 provides a
summary of the four biodiversity attributes used in the choice experiment, along with the three
levels of provision of each attribute.
The payment vehicle used in the choice experiment was an annual increase in taxation over the
next five years. The reasons for using this payment vehicle include the fact that biodiversity
enhancement programmes are generally paid for through taxation and that participants of the
focus groups indicated that taxation was their preferred payment option. Five payment levels of
taxation were used in the choice experiment. SPSS ‘Orthoplan’ was used to generate a (3 4 x 51)
fractional factorial experimental design, which created 25 choice options. A blocking procedure
was then used to assign the options to 10 bundles of five choice sets. Thus each choice
experiment respondent was presented with a bundle of five choice tasks.
3.2.2.
The Contingent Valuation
Three biodiversity conservation policy scenarios were presented in the contingent valuation
study. These were:

WTP for an agri-environmental scheme that incorporated conservation headlands, and
reduced use of pesticides and fertilisers (Cambridgeshire only)
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
WTP for habitat creation: involving seasonal flood plains, reed beds and more natural river
flows (Cambridgeshire) and the creation of wet grassland (Northumberland)

WTP to protect farmland currently under agri-environmental schemes from development in
the form of new houses (Cambridgeshire and Northumberland)
In both case study areas, respondents of the household survey would receive only received one of
these three scenarios. In all of the above cases, the levels of biodiversity change were described in
terms of the biodiversity attributes used in the choice experiment. Annual increases in taxation
over the next five years were again the chosen payment vehicle in the CV study, and these were
presented to respondents using the payment card elicitation method.
3.2.3.
The Valuation Workshops
Six valuation workshops (Macmillan et al., 2002) were undertaken in Northumberland. The
workshops used the same survey instrument as the household study, but the structure of the
workshops allowed much greater time for reflection on the information provided, whilst
participants were encouraged to discuss the issues involved with each other. Opportunities for
questions to the moderator also existed. Following these discussions, participants were asked to
complete a further series of five choice experiment tasks. The aim of this was to explore the
impact of further information provision and discussion on value judgements.
4.
Results
In the main household survey, 741 respondents (343 in Cambridgeshire and 398 in
Northumberland) each undertook five choice experiment tasks and a single contingent valuation
scenario. In the valuation workshops, 53 respondents (Northumberland only) undertook five
choice experiment tasks before the discussion and five choice tasks after the discussion.
4.1.
Choice experiment results
The data from the choice experiment method were analysed using a conditional logit model (see
Louviere et al. 2000 for a detailed description of this method of analysis). Welfare estimates in
the form of implicit prices (IP) were derived from the conditional logit model using the following
formula
IP  
 Attribute
.
M
(3)
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where  Attribute is the coefficient on the attribute of interest and  M is the negative of the
coefficient of the monetary variable, namely the annual tax increase.
Table 2 shows results from the choice experiment data for both Cambridgeshire and
Northumberland. The pseudo-R2 value is higher for the latter sample, and is very close to the 20%
level suggested by Louviere et al. (2000) as indicating a very good fit in this kind of data. The
Cambridgeshire model shows significant estimates for all the biodiversity attributes. In almost all
cases, parameter signs are in accordance with a priori expectations and a scale effect is present in
most cases. Improving familiar species from continued decline to either ‘protecting rare familiar
species only’ or ‘protecting both rare and common familiar species’ increases utility by £35.65
and £93.49 annually for the next 5 years respectively. Moving the habitat attribute from
continued decline to ‘habitat restoration’ (£34.40) or habitat re-creation (£61.36) is also positively
valued. Moving ecosystem services from continued decline to a ‘recovery of directly-relevant
services alone’ (£53.62) unexpectedly creates higher utility than ‘all ecosystem services’
(£42.21). Another unexpected result comes from the rare, unfamiliar species attribute. Here,
although a move from continued decline to stopping decline and ‘ensuring recovery’ substantially
increases well-being (£115.15), a move to ‘slowing down decline’ is negatively valued (-£46.68).
For Northumberland, the same pattern is repeated, except that the ‘all ecosystem services’ and
‘slow down decline of rare unfamiliar species’ attributes are not significant. This means that any
improvement in ‘habitat restoration’, ‘habitat re-creation’, ‘protection of rare familiar species
only’ and the ‘protection of both rare and common familiar species’ are positively and
significantly valued, as is an improvement in ‘directly-relevant ecosystem services’ - although not
an improvement in ‘all ecosystem services’. This implies that the Northumberland group only
cared about ecosystem services that seemed to directly impact on their well-being. The
Northumberland group also had a negative value for ‘slowing down the decline of rare unfamiliar
species’, but this estimate is insignificant. The statistical equivalence of the parameter estimates
of the two models can be compared using a Likelihood Ratio test. The probability value for this
test is < 0.01, indicating that the models are different. In other words, the valuation of
biodiversity attributes varies significantly between the two case study areas.
4.2.
Comparison of household study and valuation workshop
In Table 3, models are presented for the choice exercises undertaken during the valuation
workshops. Participants made two sets of choices, one near the outset, after receiving the same
14
information as the household survey participants (referred to as ‘Before’), and one near the end,
having had a chance to discuss and reflect on the issues further (referred to as ‘After’). Neither
model fits very well due to the small sample size, but we can note that the number of significant
variables increases from three to seven between the two treatments, whilst the overall fit also
improves. In other words, a learning effect seems to be present. Looking at the ‘After’ model, we
see that it compares quite well with the household survey CE results for Northumberland (Table ),
with only the ‘slow down decline of rare unfamiliar species’ having a negative sign, and with ‘all
ecosystem services’ still being insignificant. The workshop choices also show habitat restoration
to have an insignificant effect on utility. Implicit prices are also very similar to the main survey,
with a complete recovery of rare, unfamiliar species having the highest welfare gain. Finally, we
note that a formal LR test shows that the parameters of the main survey CE model for
Northumberland are not significantly different for either the ‘Before’ or ‘After’ models from the
valuation workshops. Thus, it would appear that although the extra discussions in the workshops
improved participant’s understanding of biodiversity concepts and thus allow them to state their
WTP more precisely, this extra level of knowledge did not significantly influence their WTP for
the biodiversity attributes. In this sense, the valuation workshops provide support for the main
survey choice experiment results.
5.2 Contingent Valuation
Table 4 gives summary measures for the WTP bids for the various biodiversity conservation
scenarios in Cambridgeshire and Northumberland, along with a value for the ‘pooled’ scenarios
for each area. With respect to the ‘pooled’ results, about one-third of respondents had a WTP of
zero, in other words, did not value these increases in biodiversity. Furthermore, mean WTP is
higher for Cambridgeshire respondents (£58.87) than for those from Northumberland (£42.47):
this difference is statistically significant at the 95% level. Median WTP is considerably less than
mean WTP in all cases, illustrating a common finding in CV studies.
In Cambridgeshire, WTP is highest for agri-environmental schemes (£74.27), and lowest for
preventing development loss (£45.30). Habitat re-creation is valued at £54.97. This is of general
interest, since the theory of loss aversion (Kahneman et al. 1991) suggests that losses are often
valued more than gains. However, these changes are not symmetrical in our case. What is more,
these mean values are not statistically different from each other at 95% (p= 0.11). In
Northumberland, WTP is higher for the habitat re-creation scenario (£47.19) than the
development loss scenario (£36.84), but again this difference is not significant (p=0.18).
15
The conclusions drawn from the CV data are that people place positive values on increases in
biodiversity. This value is higher in the Cambridgeshire sample than in the Northumberland
sample. However, in no cases does WTP differ across policy scenarios to a significant degree. It
thus appears that in this sample, people care about increasing biodiversity, but not how this is
achieved.
5.
5.1.
Discussion
Do the public value biodiversity enhancements?
Two key questions which can be asked of these data: is there evidence that the general public are
willing to pay additional taxes to support biodiversity conservation, and if so, then why?
With respect to the CE data, we are first interested in whether respondents chose a biodiversity
enhancement policy option (Option A or B) as opposed to the ‘do nothing’ option. Some eighty
five percent of the choices made by CE respondents were for choice options A or B,
demonstrating that the majority of respondents were willing to pay for biodiversity
enhancements. Indeed, over half of the respondents (52.6%) stated that they considered that the
biodiversity improvements outlined in policy options A or B were ‘good value of my money’.
Those respondents who consistently choose the status quo were recorded as genuine zero bids and
they accounted for eight percent of responses: three percent stating that the biodiversity
improvements were not good use of their money, while five percent stated that they already
contribute to environmental causes. Protest votes included ‘I do not think that increases in
taxation should be used to fund biodiversity improvements’ (6.5%) and ‘The costs of biodiversity
improvement should be paid for by those who degrade biodiversity’ (14.2%). Eighteen percent of
the respondents stated other reasons for their choices.
Equivalent analysis of the CV data indicates that around two-thirds of respondents were WTP
towards the biodiversity enhancing projects. Of the one-third respondents stating that they were
not willing to pay towards a biodiversity enhancing policy, 43.3% were genuine zero bids and
38.4% were protest votes. Thus, it would appear that the general public are willing to pay
additional taxes to protect and enhance biodiversity.
16
5.2.
What aspects of biodiversity do the public value most?
Another question our research enables us to address is "what aspects of biodiversity protection
policy do the public value most?" Examining the implicit prices from the choice experiment
(Table 2) provides some answers. Familiar species attained positive and significant implicit
prices. In Cambridgeshire, scale effects were evident in that the implicit price for the protection
of both rare and common familiar species (£93.49) was significantly higher than the protection of
only the rare familiar species (£35.65). This was not, however, the case in the Northumberland
sample, where the two levels of protection had similar implicit prices (£90.59 and £97.71
respectively for the protection of rare only and rare and common familiar species). In conclusion,
evidence from the choice experiment suggests that the public do support policies that target rare
familiar species of wildlife, but the evidence is less clear for common familiar species.
The second attribute addressed in the choice experiment related to rare unfamiliar species of
wildlife. Two levels of provision were addressed. The first aimed to ‘slow down the rate of the
decline’. The second level aimed to ‘stop decline and ensure recovery’. The findings for the
‘slow down’ attribute level were interesting since it was found to be negative in the
Cambridgeshire sample (indicating that negative utility would be gained from a slow down in the
decline of the population of rare unfamiliar species – which was not predicted), while the attribute
level was not significant in the Northumberland CE model. The implications of this finding was
that it appears that the public are unwilling to support policies that simply delay the time it takes
for such species to become locally extinct. This conclusion was further emphasised by the fact
that highest implicit prices were attained from the ‘stop decline and ensure recovery’ attribute
level. Thus, the policy implication of these findings is that the public appear to only support
policies that aim to achieve recovery of the populations of rare unfamiliar species, rather than
those that simply attempt to slow down decline in population numbers. A further implication of
these findings relates to the fact that survey respondents were told that they were unlikely to ever
see these rare, unfamiliar species. Thus, these values can be considered to represent passive-use
values. Finally, these results provide support for policies, such as species Biodiversity Action
Plans, which specifically target rare, unfamiliar species.
The habitat attribute was included to assess whether the public valued ‘the restoration of existing
habitats’ or ‘the re-creation of new habitats’ on farmland. Both attribute levels were found to be
positive and significant in the two case study locations. In Cambridgeshire, the value for habitat
restoration (£35.65) was half that for habitat re-creation (£61.36), while similar values were
17
attained for both levels in Northumberland (£71.15 and £74.01 respectively). Although the reason
for this difference is unclear, it is suggested that the Cambridgeshire sample may have considered
that there were very few existing habitats within Cambridgeshire which would benefit from
restoration. However, there was evidence that the public would support policies that aimed to
protect and enhance habitats, although the value of the implicit prices were found to be slightly
lower than those found for the two species attributes.
Finally, the ecosystem services attribute was included to assess whether the public valued
ecosystems that ‘only had a direct impact on humans’ and ‘all ecosystem services include those
which did not directly affect humans’. The ecosystems services that had direct impacts on humans
were found to be positively and significantly valued. However, the ‘all ecosystems’ attribute level
was not significant in the Northumberland model and was lower than the ‘human impacts only’
attribute level in the Cambridge sample. It would thus appear that survey respondents ‘cared’
about ecosystem functions that affect humans, but were less interested in the other ecosystem
services.
Based on the above analysis, it would appear that the public do value most, but not all, of the
biodiversity attributes included in our experimental design. Although there is some evidence that
the public appear to be able to distinguish between alternative attributes, it should be noted that
the differences in the values are generally not statistically different. Unfortunately, the reason for
the lack of statistical significance is unclear; however we postulate the following possibilities.
First, it may be that respondents simply have similar WTP values for the different biodiversity
attributes. Alternatively, it may be that respondents were indifferent to what aspects of
biodiversity are protected, but rather, as one respondent put it ‘all I’m concerned about is that we
protect our wildlife … I’m not really concerned how this is achieved and to tell the truth I don’t
really know how this might best be achieved … Surely it is best to let the scientists decide what to
do’. Differentiating between these two explanations has important policy implications. The first
explanation suggests that the public do have identifiable preferences for biodiversity attributes
(all be it similar preferences) and therefore from a consumer sovereignty perspective, these
preferences should be taken into account in policy formulation (Hanley and Shogren, 2001). In
the case of the second explanation, it would appear that the public do not have specific and
identifiable preferences of biodiversity attributes, and therefore policy decisions on biodiversity
protection could now be made without further reference to public opinion. A final explanation for
the lack of significant differences between the value of biodiversity attributes may be that
18
respondent’s limited knowledge of the individual biodiversity attributes may lead to a high level
of variability in their choices; indeed, the findings from the workshop indicate that the
opportunity to further discuss the biodiversity attributes reduced the standard errors.
Unfortunately, insufficient data was collected in this research to clearly distinguish between these
explanations and we suggest that further research be undertaken.
6.
Conclusions
This study also stands out in that it is one of the few studies that attempt to value the diversity of
biodiversity. Thus, rather than simply estimating the value of a biological resource such as a
particular species or habitat, this research explores in detail values for the ecological and
anthropocentric concepts that can be used to define and describe the diversity that exists within
biological resources.
Policy makers may benefit from information on the economic value of different actions aimed at
biodiversity protection, but also on which aspects of biodiversity are most valued by taxpayers.
Stated preference methods can provide both types of value estimates, but implementing these
methods is difficult in this particular case since the general public have a rather low level of
understanding of what biodiversity is and why it matters. In this study we make use of a novel
way of conveying information to respondents, information which is consistent with ecological
understanding of what aspects of biodiversity might be considered. We then use choice
experiments to estimate the relative values people place on these attributes, and contingent
valuation to look at the value of specific policy programmes. The conclusions drawn from this are
that the public have positive values for biodiversity, but may be indifferent as to how biodiversity
is actually protected.
How policy makers might choose to use such information is something we have not addressed
here. One option is to use economics to set overall budgets for biodiversity, but ask ecologists to
determine how this money is targeted. Another option is to use the kind of evidence presented
above to use more economic information in this targeting. But economists would argue that, in a
world of scarce resources and conflicting demands, some information on public preferences for
biodiversity conservation is better than no information if society wishes to make sensible and
politically-inclusive choices.
Acknowledgements: We thank the Department of the Environment, Food and Rural Affairs for funding
this
research,
and
members
of
the
steering
committee
for
many
useful
comments.
19
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22
Table 1: Summary of biodiversity attributes and levels used in the choice experiment
POLICY
POLICY
DO NOTHING
LEVEL
LEVEL
(Biodiversity
1
2
degradation will
continue)
Familiar species
Protect rare familiar
Protect both rare and Continued decline in
of wildlife
species from further
common familiar
the populations of
decline.
species from further
familiar species.
decline.
Rare, unfamiliar
species of wildlife
Slow down the rate of Stop the decline and
decline of rare,
Continued decline in
ensure the recovery of the populations of rare,
unfamiliar species. rare unfamiliar species. unfamiliar species.
Habitat quality
Habitat restoration, e.g. Habitat re-creation,
Wildlife habitats will
by better management e.g. by creating new
continue to be
of existing habitats.
Ecosystem process
habitat areas.
Only ecosystem
degraded and lost.
All ecosystem services Continued decline in
services that have a
are restored.
direct impact on
the functioning of
ecosystem processes.
humans, e.g. flood
defence are restored.
Annual tax increase
10
25
100
260
520
No increase in your
tax bill
23
Table 2: Conditional logit models and implicit prices for household survey choice experiment
Table 3a:Cambridgeshire
Attribute
Parameter
t-value
estimate
Implicit Price
SE
(£ per annum)
95%lower
95%upper
(£)
(£)
*
35.65
17.19
1.95
69.34
FAMRARE
0.126
2.1
FAMBOTH
0.331
5.2*
93.49
18.03
58.15
128.82
-0.165
-3.0
*
-46.68
15.88
-77.80
-15.55
RARERECOVER
0.408
5.7
*
115.13
21.22
73.53
156.72
HABRESTORE
0.122
2.3*
34.40
15.32
4.37
64.42
HABCREATE
0.217
3.5*
61.36
17.52
27.02
95.69
*
53.62
16.97
20.35
86.88
42.21
19.23
4.51
79.90
SE
95%lower
95%upper
(£)
(£)
RARESLOW
ECOHUMAN
0.19
3.2
ECOALL
0.15
2.2*
-0.004
-15.2*
PRICE
Pseudo R2
14%
N (Individuals)
343
Table 3b: Northumberland
Attribute
Parameter
t-value
estimate
Implicit Price
(£ per annum)
0.309
5.1*
90.59
19.24
52.87
128.30
FAMBOTH
0.334
5.2
*
97.71
18.47
61.50
133.91
RARESLOW
-0.08
-1.5
n/a
n/a
n/a
n/a
RARERECOVER
0.645
8.1*
189.05
25.28
139.50
238.59
0.243
4.7
*
71.15
16.29
39.22
103.07
*
74.00
17.51
39.68
108.31
105.22
17.7
70.52
139.91
n/a
n/a
n/a
n/a
FAMRARE
HABRESTORE
HABCREATE
0.253
4.3
ECOHUMAN
0.359
5.9*
ECOALL
0.064
1.0
PRICE
-0.003
Pseudo R2
19%
N (Individuals)
398
-15.3
*
24
Table 3: Conditional logit models for valuation workshop choice experiment, Northumberland
‘Before’ discussion
‘After’ discussion
ATTRIBUTE
Parameter
t-statistic
Parameter
t-statistic
FAMRARE
0.172
1.1
0.327
2.0*
FAMBOTH
0.257
1.6
0.343
2.0*
RARESLOW
-0.028
-0.2
-0.316
-2.1*
RARERECOVER
0.166
0.8
0.654
3.0*
HABRESTORE
0.093
0.7
0.149
1.1
HABCREATE
0.323
*
2.0
0.332
2.0*
ECOHUMAN
0.386*
2.4
0.319
2.0*
ECOALL
0.116
0.6
0.211
1.2
-6.2
-0.004
-5.8*
-0.004
TAX
*
A_OPTA
0.823
2.3
-0.295
-0.8
A_OPTB
0.894
2.4
-0.081
-0.2
-2*lnL
417.4
440.7
<0.01
<0.01
16.7%
18.7%
53
53
p-value
Pseudo R
2
N (Individuals)
25
Table 4: WTP values for CV biodiversity scenarios in Cambridgeshire and Northumberland.
Table 5a: Cambridgeshire
CV scenario
N
Mean
Standard
95%
95%
Error
Confidence
Trimmed
Interval
Mean
Median
% with
WTP = 0
Agri-environment schemes
124
£74.27
£13.26
£48.03↔£100.51
£53.28
£24.00
29.8%
Habitat creation Scheme
107
£54.97
£6.56
£41.96↔£67.98
£48.42
£24.00
29.9%
Development loss
110
£45.30
£7.82
£29.80↔£60.79
£31.26
£16.00
37.3%
All scenarios ("pooled")
341
£58.87
£5.84
£47.38↔£70.36
£42.84
£20.00
32.3%
Median
% with
Notes: F-test for difference in means: F=2.2 and p=0.11
Table 5B: Northumberland
CV Scenario
N
Mean
Standard
95%
95%
Error
Confidence
Trimmed
Interval
Mean
WTP = 0
Habitat creation Scheme
209
£47.49
£5.98
£35.70↔£59.27
£34.35
£12.00
27.8%
Development loss
186
£36.84
£5.07
£26.82↔£46.85
£25.29
£3.00
46.8%
All scenarios ‘pooled’
395
£42.47
£3.97
£34.67↔£50.27
£30.09
£10.00
35.9%
Notes: F-test for difference in means: F=1.4 and p=0.18
26
Figure 1: Conceptual framework used in the experimental design
BIODIVERSITY CONCEPTS
ECOLOGICAL CONCEPTS
ANTHROPOCENTRIC CONCEPTS
Keystone
Umbrella
Flagship
Ecosystem
Ecosystem
Rare
Endangered
Charismatic
species
species
species
function
Health
species
species
species
Habitat quality
Ecosystem processes
Rare, unfamiliar
species of wildlife
Cuteness
Familiar
species
Locally
important
species
Familiar species of wildlife
27