Evaluating the effectiveness and efficiency of biodiversity conservation spending

Ecological Economics 70 (2011) 1789–1796

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Ecological Economics j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / e c o l e c o n

Analysis

Evaluating the effectiveness and efficiency of biodiversity conservation spending Helen F. Laycock a, Dominic Moran b, James C.R. Smart a, David G. Raffaelli a, Piran C.L. White a,⁎ a b

Environment Department, University of York, Heslington, York, YO10 5DD, UK Scottish Agricultural College, Kings Buildings, West Mains Road, Edinburgh, Midlothian, EH9 3JG, UK

a r t i c l e

i n f o

Article history: Received 7 October 2010 Received in revised form 24 March 2011 Accepted 4 May 2011 Available online 12 June 2011 Keywords: Conservation planning Cost-Utility Analysis Interdisciplinary Questionnaire Species Action Plans Threat Reduction Assessment

a b s t r a c t Evaluation of effectiveness and efficiency should be an integral component of biodiversity conservation strategies. We used Cost-Utility Analysis (CUA) and Threat Reduction Assessment (TRA) to evaluate the effectiveness and efficiency of individual Species Action Plans (SAPs) with regard to improving conservation status and reducing threats within the UK Biodiversity Action Plan. Spending was highly biassed towards vertebrates, in particular mammals and birds. Of 38 fully-costed SAPs, the top five most expensive SAPs accounted for almost 80% of the total money spent. Just over half of the SAPs studied had improved the conservation status of the species concerned, and one third of SAPs achieved at least a 50% reduction in threats. SAP cost was significantly positively related to improvement in conservation status but unrelated to threat reduction for that species. Effectiveness and efficiency were significantly correlated with one another in terms of threat reduction for different species, but there was no correlation between effectiveness and efficiency in terms of improving conservation status. Although conservation decisions should not be made solely on the outcome of such analyses, CUA and TRA can provide an important contribution to the evidence base to inform the development of more effective and efficient conservation strategies. © 2011 Elsevier B.V. All rights reserved.

1. Introduction Numerous conservation programmes have been established to counter declines in biodiversity (Cullen et al., 2001). Monitoring the progress made by such programmes is essential for developing more efficient and successful conservation strategies (Ferraro and Pattanayak, 2006; Hughey et al., 2003; Murdoch et al., 2007; Wilson et al., 2006). An analysis that compares an ecological measure of programme output with an economic measure of programme costs can provide information on effectiveness and efficiency which can contribute to the evidence base for policy decisions on conservation. This type of interdisciplinary evaluation, accounting for both ecological and economic factors, has increased in recent years (see Laycock et al., 2009). The approach has been criticised because of the limited commensurability in the measurement of conservation status between species and the lack of incorporation of indirect benefits (Hockley, 2009). The focus on single species as benefits is a limitation, but an objective measure of conservation status provides an important first step in the evaluation process (Moran et al., 2010). Cost-Utility Analysis and Threat Reduction Assessment are two recently-developed techniques that meet these criteria. Cost-Utility Analysis was first developed to evaluate health-care programmes by comparing the outputs of competing alternatives in terms of the

⁎ Corresponding author. Tel.: + 44 1904 324062; fax: + 44 1904 322998. E-mail address: [email protected] (P.C.L. White). 0921-8009/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.ecolecon.2011.05.002

utility that they provide, where utility refers to the improvement in health status following a treatment, measured in Quality-AdjustedLife-Years (QALY; Cullen et al., 2001; Hughey et al., 2003). Cullen et al. (1999) developed the Conservation Output Protection Year (COPY) to serve an equivalent function in conservation evaluation, but with utility now referring to the improvement in conservation status following the implementation of a conservation programme. Threat Reduction Assessment was developed by Salafsky and Margoluis (1999) as a technique for using progress in reducing threats to biodiversity as a proxy measurement of conservation success. Threat Reduction Assessment as applied by Salafsky and Margoluis (1999) was criticised by Hughey et al. (2003) for not considering the costs of threat reduction and for assuming that all threats are of equal importance. In this study, we attempt to address both of these issues. In common with many other countries, the UK has suffered substantial declines in biodiversity in recent years, losing more than 100 species during the 20th Century (Anon, 1995), and 54% of native birds and 71% of native butterflies over the last 20 years (Thomas et al., 2004). The UK Biodiversity Action Plan (BAP) consists of a series of action plans for the recovery of threatened species and habitats (Defra, 2007). The targets for individual Species Action Plans (SAPs) are not necessarily equivalent, but all were expressed initially in terms of a specific conservation outcome for the year 2010. There have been previous assessments of the UK BAP. The official reporting rounds in 1999, 2002 and 2005 (UK Biodiversity Partnership, 2006) had an ecological basis, and some previous evaluation has also been done on a cost basis (GHK Consulting Ltd., 2006; Shepherd et al.,

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2002). Combining these two elements to test the cost-effectiveness and efficiency of conservation is a top priority for UK biodiversity research (Ferris, 2007). Laycock et al. (2009) used Cost-Effectiveness Analysis to provide the first integrated ecological–economic assessment of the UK BAP. Cost-Effectiveness Analysis evaluates the success of a programme in meeting a specific target, which is an important first step in evaluation. However, Cost-Utility Analysis and Threat Reduction Assessment provide a more sophisticated approach. Cost-Utility Analysis can be used to evaluate improvement in conservation status, and Threat Reduction Assessment provides a means of assessing progress in reducing threats. These two techniques are therefore much better suited to adaptive conservation management. Here, we extend the work of Laycock et al. (2009) by applying Cost-Utility Analysis and Threat Reduction Assessment to evaluate the effectiveness (conservation gain) and efficiency (conservation gain per cost invested) of species conservation within the UK BAP, in terms of improving conservation status and reducing threats. Since a review of the UK BAP in 2006, there are now 1150 SAPs (JNCC, 2006). At the time of data collection in 2005, there were 391 SAPs, 11 of which were grouped due to similar conservation requirements of the individual species (JNCC, 2006), leaving 380 single-species SAPs on which our study focuses.

is the present value, i.e. compounded, cost per COPY; and Cit is the cost of SAPi in year t

Cost  COPY Ratio =

h i ∑Tt = 0 Cit ð1 + dÞt COPYi

:

ð2Þ

Here, compounding allows different SAP cost/benefit profiles to be compared on a consistent basis. However, as we are not valuing the benefits in economic terms, the present value Cost-COPY Ratio calculated here does not represent the net present value that would be provided by a full Cost-Benefit Analysis. In terms of improving the conservation status of the species concerned, the most effective SAPs are those that have achieved the greatest COPY and the most efficient SAPs are those that have the lowest Cost-COPY Ratio. Hereafter we will use the terms COPYeffective and COPY-efficient when referring to the effectiveness or efficiency, respectively, of SAPs in improving conservation status of the species concerned. 2.3. Threat Reduction Assessment We used the following equation to calculate the total severity of each threat:

2. Methods 2.1. Questionnaires

Sn =

For each of the 380 single-species SAPs, we sent a questionnaire to the Lead Partner responsible for coordinating the SAP (JNCC, 2006). Questionnaires followed the recommendations of White et al. (2005); a complete description and a copy of the questionnaire are provided in Appendix A. From the questionnaires, we sought to obtain the following data on each SAP: total cost; annual costs from time of implementation to time of data collection (2005); conservation status in the UK over the lifetime of the SAP and over the same time period if the SAP had never been implemented, according to IUCN categories (Extinct, Extinct in the Wild, Critically Endangered, Endangered, Vulnerable, Near Threatened and Least Concern) including a rating from a given range within each category; the known threats affecting the species (based on the ‘Current or emerging threats’ identified in the 2005 UK BAP Reporting Round) at the time the SAP was first implemented and that have emerged since then; the level of severity of each threat at the start of the SAP or when it first arose according to its scale, intensity and urgency; a percentage score awarded to each of these three criteria according to their importance in determining the overall severity of the threats; and the percentage reduction in each threat as a direct result of the implementation of the SAP.

We used the following equation to calculate the level of COPY achieved by each SAP:

T

h
 i t Sitw −Sitw=o ð1 + dÞ ;

ð1Þ

where COPYi stands for Conservation Output Protection Years achieved by SAPi; SAPi has been in effect for T years; Sitw is the conservation status of species i in year t with SAPi; Sitw/o is the conservation status of species i in year t without SAPi; and d is the discount (in this case, compounding) rate. We then calculated the efficiency of each SAP at improving conservation status using Eq. (2), where the Cost-COPY Ratio

ð3Þ

where the species is subject to N threats; Sn is the total severity of threat n; RSn, RIn and RUn are the severity ratings given to threat n under the scale, intensity and urgency criteria, respectively; and WS, WI and WU are the percentage importances of the scale, intensity and urgency criteria, respectively, to overall threat severity. We then calculated the effectiveness of each SAP at reducing threats using Eq. (4), where TRIi is the Threat Reduction Index of SAPi and Dn is the percentage by which SAPi has reduced threat n N

TRIi ð%Þ = ∑1 ½ðDn  Sn Þ = 100:

ð4Þ

Finally, we calculated the efficiency of each SAP at reducing threats using Eq. (5), where the Cost-Threat Reduction Ratio is the present value, i.e. compounded, cost per percent threat reduction; SAPi has been in effect for T years; Cit is the cost of the SAP in year t; and d is the compounding rate

Cost  Threat Reduction Ratio =

2.2. Cost-utility Analysis

COPYi = ∑t = 0

RSn RIn RUn  WS +  WI +  WU ; ∑N1 RSn ∑N1 RIn ∑N1 RUn

T t ∑0 Cit  ð1 + dÞ : TRIi

ð5Þ

In terms of reducing the threats against the species concerned, the most effective SAPs are those that have the greatest Threat Reduction Index and the most efficient SAPs are those that have the lowest CostThreat Reduction Ratio. Hereafter we use TR-effective and TR-efficient when referring to the effectiveness or efficiency, respectively, with which a SAP reduces threats facing the species concerned relative to the targets in the SAPs. 2.4. Species Utility The approach described above assumes that all species are of equal value, or utility, and so achieving a given level of COPY-effectiveness (or TR-effectiveness) in one SAP is exactly equivalent to achieving that

H.F. Laycock et al. / Ecological Economics 70 (2011) 1789–1796

same level of COPY-effectiveness (or TR-effectiveness) in another SAP. However, the level of utility provided by conserving different species to the same extent may vary. For instance, in conserving one species, it is possible that other species that use the same habitat will benefit through that habitat being protected. The extent of this ‘added value’ is related to a species' home range size (Caro and O'Doherty, 1999), so we used a combination of taxonomic and dietary groups as a proxy for home range size (Hendriks, 2007; Holling, 1992). The resulting weighting scale consisted of 13 categories, each given a weighting score evenly spaced between 1.00 and 0.08, with the higher and more carnivorous taxa receiving greater weight than the lower and more herbivorous taxa (Table 1). We then multiplied the COPY achieved by each SAP, as calculated in Eq. (1), and the Threat Reduction Index of each SAP, as calculated in Eq. (4), by this utility weight. Finally, we fed these figures into Eqs. (2) and (5) to give the Utility-Weighted CostCOPY Ratio and the Utility-Weighted Cost-Threat Reduction Ratio of each SAP. In addition to their ecological ‘added value’, some species may contribute significantly to social utility in terms of non-use values (Christie et al., 2006; Nunes and van den Bergh, 2001; White et al., 1997, 2001). Although progress is being made in developing more consistent frameworks for the valuation of biodiversity and ecosystems (TEEB, 2008), the valuation techniques used in such studies are frequently contentious, subjective and context-dependent (Laycock et al., 2009; White et al., 2001). Since many of the SAPs analysed concern little-known species, any attempt to assign monetary equivalents of social utility value to improvements in the conservation status of these species would be extremely speculative. Thus, we chose to base the utility measure used in our analysis solely on ecological rather than economic or social grounds.

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Our analysis (presented in Appendix B) showed that the compounding rate had little effect on the results, so we present the results using the 0% rate and the 3.5% compounding rate only. 2.6. Expert Feedback To assess the relative merits of Cost-Utility Analysis and Threat Reduction Assessment in terms of ease and accuracy of data collection, we asked Lead Partners to score each section of the questionnaire on a scale of 1 to 6 (from very difficult/inaccurate to very easy/accurate) to indicate how easy they had found each section to complete and how accurate they felt they had been able to be with their answers. 3. Results 3.1. Data Collection We obtained COPY data on 51 (13.2%) of the 380 single-species SAPs (see Appendix C Table 1 for details). High levels of representation were achieved for molluscs, moths and stoneworts, whilst fungi and lichens were under-represented. The average level of representation achieved across all groups was 38.6%. Cost data were only available for 38 SAPs (10%) overall, and it is impossible to calculate Cost-COPY Ratios for those SAPs that have achieved zero COPY. Hence we could only calculate this COPY-efficiency measure for 20 (5.3%) of the SAPs. We obtained Threat Reduction Index data on 37 (9.7%) SAPs, but cost data were only available for 27 (7.1%) of these. Thus we could only calculate the Cost-Threat Reduction Ratios for these 27 SAPs. 3.2. SAP Costs

2.5. Sensitivity Analysis There is considerable theoretical literature surrounding the choice of discount rate, so we conducted a sensitivity analysis altering the discount (in our case, compounding) rate. The UK Government currently advises a 3.5% (real) discount rate be used for social projects (HM Treasury, 2003), whereas 6% was previously recommended for most applications in central government (HM Treasury, 1997). We applied both the 3.5% and 6% rates, along with a 0% rate, which assumes that preferences are time invariant. Note that because the different SAPs were not all implemented at the same time, the only time point common to all SAPs is the point of data collection. Thus, this had to be taken as the reference date for discounting, which means that we actually compounded rather than discounted, taking the last year of data availability (2004/2005) as Year 0 and the first year that any SAPs were implemented (1995/1996) as Year 9.

Table 1 Weights used to account for differences in utility between species, according to the added ecological conservation value that they are likely to provide. Species categories Vertebrate homeotherms

Weight Carnivores Omnivores Herbivores

Vertebrate poikilotherms

Invertebrates

Plants/fungi/lichens

Carnivores Omnivores Herbivores Carnivores Omnivores Herbivores

Birds Mammals Birds Mammals Birds Mammals

1.00 0.92 0.85 0.77 0.69 0.62 0.54 0.46 0.38 0.31 0.23 0.15 0.08

The cost of implementing the 38 SAPs for which cost data were available across both analyses over the 10-year period in question varied from £960 to £7,000,000 (see Appendix C Table 2), with a mean cost per SAP of £519,169 ± 220,137 (SE), when d = 3.5%. The distribution of spending across SAPs was extremely skewed (median cost= £17,711, when d = 3.5%), with the most expensive SAP receiving 39.6% of the total funds spent on these 38 SAPs, and the top five most expensive SAPs receiving 78.1% of this total. Vertebrates received 85.4% of the total funds, despite only constituting 18.4% of the costed SAPs, and 71.0% of the total funds were spent on mammal and bird SAPs, which represent only 10.5% of the costed SAPs. 3.3. Cost-utility Analysis A total of 25 SAPs (49.0% of those studied) had achieved zero COPY and thus had not improved the conservation status of the species concerned at all (Table 2). The mean COPY achieved across all SAPs studied was 0.47 ± 0.12 (median = 0), when d = 3.5%, and there was a highly significant positive correlation between SAP cost and the COPY achieved (Spearman's rank correlation: r s = 0.501; d.f. = 37; p = 0.001). Hence, the most expensive SAPs also tend to be the most COPY-effective. The Cost-COPY Ratio of the SAPs studied varied from £2937 to £34,520,668, when d = 3.5% (Table 2), with a mean of £3,223,328 ± 1,901,694 (median = £112,288). There was no significant correlation between the ranking of SAPs based on their COPY-efficiency and the ranking of the same subset of SAPs based on their COPY-effectiveness (Spearman's rank correlation: rs = − 0.380; d.f. = 19; p = 0.100). Many SAPs that achieved relatively high COPY values were also relatively costly to implement, so fared worse when ranked according to COPY-efficiency rather than according to COPY-effectiveness (e.g. the Capercaillie Tetrao urogallus L.). Conversely, SAPs that achieved relatively low COPY values, but cost relatively little to implement, appear very COPY-efficient compared to other SAPs (e.g. the leaf

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Table 2 COPY, Present Value (PV) COPY, Utility-Weighted PV COPY, Cost-COPY Ratio, PV Cost-COPY Ratio and Utility-Weighted PV Cost-COPY Ratio achieved by Species Action Plans, ranked by decreasing PV COPY. Compounding rate of 3.5% applied as indicated. Species Action Plan

Bog hoverfly Eristalis cryptarum Corncrake Crex crex Deptford pink Dianthus armeria Whorl snail Vertigo geyeri Capercaillie Tetrao urogallus Ribbon-leaved water-plantain Alisma gramineum Vendace Coregonus albula Cirl Bunting Emberiza cirlus Narrow-mouthed whorl snail Vertigo angustior Natterjack toad Bufo calamita Yellow marsh saxifrage Saxifraga hirculus Large blue butterfly Maculinea arion A leaf beetle Cryptocephalus nitidulus Triangular club-rush Schoenoplectus triqueter Hazel pot beetle Cryptocephalus coryli Leaf-rolling weevil Byctiscus populi Small Cow-wheat Melampyrum sylvaticum Narrow-headed ant Formica exsecta A leaf beetle Cryptocephalus primarius Heath fritillary Mellicta athalia Otter Lutra lutra A lichen Calicium corynellum Straw belle Aspitates gilvaria gilvaria Grey Partridge Perdix perdix Ramshorn snail Anisus vorticulus Basking Shark Cetorhinus maximus Mole cricket Gryllotalpa gryllotalpa A ground beetle Bembidion argenteolum A diving beetle Agabus brunneus Pashford pot beetle Cryptocephalus exiguus 6 spotted pot beetle Cryptocephalus sexpunctatus Bast bark beetle Ernoporus tiliae A weevil Melanapion minimum A weevil Procas granulicollis Jumping weevil Rhynchaenus testaceus A rove beetle Stenus palposus Black-backed meadow ant Formica pratensis A stiletto fly Cliorismia rustica A stiletto Fly Spiriverpa lunulata Marsh moth Athetis pallustris Black-veined moth Siona lineata Freshwater pearl mussel Margaritifera margaritifera Glutinous snail Myxas glutinosa Norwegian mugwort Artemisia norvegica Newman's lady fern Athyrium flexile Fen orchid Liparis loeseliia Holly-leaved naiad Najas marina Oblong Woodsia Woodsia ilvensis Norfolk flapwort Lophozia rutheanaa Red alga Anotrichium barbatum A hoverfly Chrysotoxum octomaculatum a

COPY

PV COPY

Utility-Weighted PV COPY

Cost-COPY ratio (£)

PV Cost-COPY Ratio (£)

Utility-Weighted PV Cost-COPY Ratio (£)

d = 0%

d = 3.5%

d = 3.5%

d = 0%

d = 3.5%

d = 3.5%

3.89 2.21 2.15 1.80 1.75 1.41 1.10 0.93 0.99 0.90 0.68 0.64 0.50 0.43 0.49 0.40 0.39 0.36 0.22 0.20 0.16 0.10 0.07 0.05 0.05 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 − 0.03

4.26 2.52 2.41 2.07 1.89 1.66 1.20 1.03 1.03 0.99 0.72 0.71 0.52 0.52 0.51 0.41 0.41 0.37 0.23 0.21 0.17 0.11 0.07 0.05 0.05 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 − 0.04

0.98 2.52 0.19 0.48 1.60 0.13 0.65 0.88 0.24 0.45 0.06 0.16 0.08 0.04 0.08 0.06 0.03 0.11 0.03 0.03 0.16 0.01 0.01 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 − 0.01

3085

2937

12,771

18,140 15,883 4,000,000

18,359 16,543 4,003,461

229,227 72,054 4,709,955

198,182 1,196,559 24,242 1,181,931 88,235 1,562,500 90,909

207,512 1,233,488 28,460 1,245,234 108,464 1,650,909 95,060

385,815 1,449,097 123,146 2,707,030 1,349,282 7,183,952 633,731

40,816 25,000

42,593 25,890

283,950 174,390

10,000 1,260,000 17,500,000 50,000 107,857 32,800,000 500,000

10,408 1,413,799 19,135,516 50,920 116,112 34,520,668 540,218

69,387 9,296,215 21,042,688 609,371 781,822 42,358,426 3,601,451

For these species, only data on the progress of the Species Action Plan in England were available.

beetle Cryptocephalus nitidulus Fabricius). However, some SAPs performed equally well whether judged on COPY-effectiveness or COPY-efficiency (e.g. the bog hoverfly Eristalis cryptarum Fabricius and whorl snail Vertigo geyeri Lindholm). Vertebrate SAPs were significantly less COPY-efficient than both invertebrate (H = 6.828; d.f. = 1; p = 0.009) and plant (H = 5.400; d.f. = 1; p = 0.020) SAPs, according to the Kruskal–Wallis Test. In addition, there is a significant positive correlation between Cost-COPY Ratio and species distribution, defined as the number of 10 km squares in which the species was recorded during the 10 years preceding initial implementation of the SAP (Spearman's rank correlation: rs = 0.564; d.f. = 19; p = 0.010). Thus the conservation status of more widespread species has been improved with less COPY-

efficiency by the SAP than the conservation status of species with restricted distributions. 3.4. Threat Reduction Assessment Only one SAP (2.7% of those studied) achieved 100% Threat Reduction, whereas three SAPs (8.1%) achieved 0% Threat Reduction (Table 3). Just 12 of the SAPs (32.4%) managed to achieve at least 50% Threat Reduction, whereas 18 SAPs (48.6%) achieved less than 25% Threat Reduction (Fig. 1). The mean Threat Reduction Index achieved across all SAPs studied was 34.6 ± 5.0% (median = 33.0%), and there was no correlation between the cost of SAPs and their Threat Reduction Index (Spearman's rank correlation: rs = 0.215; d.f. = 29;

H.F. Laycock et al. / Ecological Economics 70 (2011) 1789–1796

100

Vertebrate SAPs were significantly less TR-efficient as well as COPY-efficient than both invertebrate (Kruskal–Wallis: H = 7.882; d.f. = 1; p = 0.005) and plant (Kruskal–Wallis: H = 7.500; d.f. = 1; p = 0.006) SAPs. However, there was no significant correlation between Cost-Threat Reduction Ratio and species distribution (Spearman's rank correlation: rs = 0.070; d.f. = 36; p = 0.679).

90

Percent of SAPs

80 70 60 50 40

3.5. Species Utility

30 20 10 0

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0-9

10-19 20-29 30-39 40-49 50-59 60-69 70-79 80-89

>90

Minimum TRI achieved (%) Fig. 1. Percentage of all Species Action Plans (SAPs) studied that achieved at least a given minimum Threat Reduction Index (TRI).

p = 0.254). Hence the most expensive SAPs are not necessarily the most TR-effective. The Cost-Threat Reduction Ratio of the SAPs studied varied from £42 to £655,202, when d = 3.5% (Table 3), with a mean of £53,645 ± 26,811 (median = £893). Overall, there was a significant correlation between the ranking of SAPs in terms of their TR-effectiveness and their ranking in terms of TR-efficiency (Spearman's rank correlation: rs = − 0.613; d.f. = 26; p = b 0.001).

After weighting the SAPs according to a measure of their ecological utility (Tables 2 and 3), SAPs for vertebrates tended to increase more in effectiveness relative to those for invertebrates, which in turn tended to increase more than those for plants. These changes reflect the relative utility weightings of the different groups. As a result, there were significant positive correlations of the SAP cost with both the Utility-Weighted COPY (Spearman's rank correlation: rs = 0.566; d.f. = 37; p b 0.001) and the Utility-Weighted Threat Reduction Index (Spearman's rank correlation: rs = 0.514; d.f. = 29; p = 0.004). In addition, the rank order of SAP efficiency, both in terms of improvement in conservation status (COPY) and reduction in threats (TR), changed slightly to favour vertebrates over invertebrates and invertebrates over plants (Tables 2 and 3). Indeed, there was now no significant difference in SAP COPY-efficiency across vertebrates, invertebrates and plants (Kruskal–Wallis: H = 4.979; d.f. = 2; p = 0.083). However, vertebrate SAPs were still significantly less TRefficient than both invertebrate (Mann–Whitney: U = 7.000; d.f. = 1;

Table 3 Threat Reduction Index, Utility-Weighted Threat Reduction Index, Cost-Threat Reduction Ratio, Present Value (PV) Cost-Threat Reduction Ratio and Utility-Weighted PV Cost-Threat Reduction Ratio of Species Action Plans, ranked by decreasing Threat Reduction Index. Compounding rate of 3.5% applied as indicated. Species Action Plan

Threat reduction index (%)

Utility-Weighted Threat Reduction Index (%)

Jumping weevil Rhynchaenus testaceus Yellow marsh saxifrage Saxifraga hirculus Norfolk flapwort Lophozia rutheanaa Leaf-rolling weevil Byctiscus populi Hazel pot beetle Cryptocephalus coryli A leaf beetle Cryptocephalus nitidulus Fen orchid Liparis loeseliia Red-necked Phalarope Phalaropus lobatus Glutinous snail Myxas glutinosa A stiletto fly Cliorismia rustica A stiletto Fly Spiriverpa lunulata Black-veined moth Siona lineata Capercaillie Tetrao urogallus Deptford pink Dianthus armeria A diving beetle Bidessus minutissimus Ramshorn snail Anisus vorticulus A lichen Calicium corynellum Straw belle Aspitates gilvaria gilvaria Holly-leaved naiad Najas marina Natterjack toad Bufo calamita Basking Shark Cetorhinus maximus Marsh moth Athetis pallustris Red alga Anotrichium barbatum Vendace Coregonus albula Otter Lutra lutra Grey Partridge Perdix perdix A leaf beetle Cryptocephalus primarius Whorl snail Vertigo geyeri Bast bark beetle Ernoporus tiliae Triangular club-rush Schoenoplectus triqueter A weevil Melanapion minimum Narrow-mouthed whorl snail Vertigo angustior A weevil Procas granulicollis Heath fritillary Mellicta athalia A ground beetle Bembidion argenteolum Pashford pot beetle Cryptocephalus exiguus A rove beetle Stenus palposus

100.00 87.02 86.60 80.00 80.00 80.00 73.05 57.56 56.67 50.00 50.00 50.00 49.71 43.67 42.83 40.48 38.89 34.85 32.98 24.21 18.54 12.88 11.91 11.83 10.78 10.65 10.00 10.00 8.00 6.58 5.00 2.77 2.50 0.45 0.00 0.00 0.00

15.00 6.96 6.93 12.00 12.00 12.00 5.84 57.56 8.50 11.50 11.50 7.50 42.25 3.49 13.28 6.07 3.11 5.23 2.64 11.14 8.53 1.33 1.93 6.39 9.92 9.05 1.50 2.30 1.20 0.53 0.75 0.64 0.38 0.07 0.00 0.00 0.00

a

Cost-Threat Reduction Ratio (£/%)

PV Cost-Threat Reduction Ratio (£/%)

Utility-Weighted PV Cost-Threat Reduction Ratio (£/%)

d = 0%

d = 3.5%

d = 3.5%

50 690 40 125 250 63 465

54 893 42 134 273 68 606

357 11,164 526 894 1819 455 7577

212

240

1598

140,824 893

151,891 1012

178,695 12,650

618 129 217

667 138 236

4448 1724 1570

43,988 67,407 466 180 18,432 259,708 154,004 2000 2850 1250

50,802 71,038 503 212 21,138 305,257 169,051 2183 3431 1317

110,435 154,465 3356 2649 39,136 331,842 198,866 14,556 14,915 8781

400 8673 800 563,844

429 10,542 1053 655,202

2860 45,791 7023 4,338,234

For these species, only data on the progress of the Species Action Plan in England were available.

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p = 0.003) and plant (Mann–Whitney: U = 0.000; d.f. = 1; p = 0.004) SAPs. 3.6. Expert Feedback The mean scores assigned by Lead Partners to the different sections of the questionnaire differed significantly for both ease of completion (χ 2 = 15.692; d.f. = 3; p = 0.001) and accuracy of answers (χ 2 = 10.480; d.f. = 3; p = 0.015), according to the non-parametric Friedman test. Using paired Wilcoxon signed ranks tests to identify the reasons for these significant differences, it becomes apparent that Lead Partners found the cost (Z = −2.073; p b 0.05) and threat (Z = −2.403; p b 0.05) sections of the questionnaire significantly harder to complete than the conservation status section (see Fig. 2). In addition, they felt that they had been significantly more accurate with their answers in the conservation status section than in the cost (Z = 2.963; p b 0.01) and threat (Z = 2.180; p b 0.05) sections (see Fig. 2). 4. Discussion 4.1. Effectiveness and Efficiency of Species Action Plans The mean level of COPY achieved by SAPs was 0.47 when d = 3.5%, with a range of 0 to 4.26. Cullen et al. (2001) found levels of COPY achieved by New Zealand threatened species programmes between 1987 and 1999 varied from 0 to 2.265, with a mean of 0.53, although these values were based on a compounding rate of 6%. Hence, the SAPs have not been substantially less effective than the New Zealand threatened species programmes at improving species conservation status, and a similar proportion (roughly half) had achieved zero COPY. It may be that these species are so close to extinction that improving their status is virtually impossible or that action has so far been confined to research, or maybe these SAPs are simply poorly designed and/or implemented (Cullen et al., 2001). On average, the SAPs studied only managed to reduce the threats facing the species concerned by about one third. Previous applications of the technique have found threat reduction values of between 25% and 58% over a 3year timeframe (Salafsky and Margoluis, 1999). It may also be that substantial reductions in threats require a more complete knowledge of threats facing different species than is currently available (Fairburn et al., 2004), as well as a concerted effort over longer time periods than those used in such studies to date (Brown and Shogren, 1998; UK Biodiversity Group, 2001). The Cost-COPY Ratio of the SAPs studied varied from £2937 to £34,520,668, when d = 3.5%, with a mean of £3,223,328. Cullen et al. (2001) found much more modest Cost-COPY Ratios for New Zealand 6 Ease of completion Accuracy of answers

Mean score

5 4 3

4.2. Data Reliability

2 1 0

threatened species programmes, with a maximum of £2,327,560 when d = 6%, suggesting that the New Zealand conservation programmes have been more COPY-efficient than the SAPs. In the New Zealand study, the most costly species conservation plans also tended to be the most COPY-effective, suggesting that resource allocation was relatively efficient. Similarly, in the US ESA, those plans that received greater funding showed more favourable status (Male and Bean, 2005). In the present study, although there was a significant correlation between plan cost and improvement in conservation status, there was no correlation between cost and threat reduction. This may be because for some SAPs, especially those relating to localised, rarer species, local action can be very effective in achieving an increase in conservation status without any significant reduction in the broader threats. However, the lack of a correlation between cost and threat reduction may also reflect a relative lack of efficiency in resource allocation across SAPs. Spending on the SAPs has been highly skewed towards vertebrates, especially mammals and birds, yet vertebrate SAPs have been significantly less COPY-efficient and TR-efficient than both invertebrate and plant SAPs. This vertebrate bias in funding is pervasive throughout conservation and clearly reflects a greater social utility arising from the conservation of these species. For example, the top 10 species by total spending within the US ESA consists solely of mammals and birds, and 95% of the conservation budget goes to vertebrates (Male and Bean, 2005; Metrick and Weitzman, 1996). Following weighting of the COPY and Threat Reduction Index achieved by the SAPs according to a rangebased measure of ecological utility, a positive correlation between cost and threat reduction did emerge and vertebrate SAPs were no longer significantly less efficient at improving conservation status than invertebrate and plant SAPs. However, vertebrate SAPs were still significantly less efficient at reducing threats than both invertebrate and plant SAPs. It is possible that the concentration of limited financial resources on more charismatic species may have a negative impact on the recovery of endangered species in general (Restani and Marzluff, 2002), although some Lead Partners in our survey commented that conservation efforts directed towards high profile, charismatic species can help to raise the funding profile of less charismatic species. Conservation action for more wide-ranging species may also therefore yield greater ecological added value, as well as greater social utility. SAPs of more widespread species have been less efficient at improving conservation status than SAPs of species with restricted distributions. This may relate to the trend for widespread BAP species to be declining and those with restricted range to be recovering or stable found by an evaluation of the UK BAP after five years (UK Biodiversity Group, 2001). The more widely distributed a species is, the greater the area that has to be conserved, thus reducing overall recoverability and making conservation more costly and less efficient (Miller et al., 2002). The SAP-type focus on individual species is probably best suited to conserving rarer species with restricted range, whereas for more abundant and widespread species, ecosystem-level approaches based on improvements to habitat quality and quantity may be both more effective and more efficient.

Cost

Conservation Status

Threats

Questionnaire section Fig. 2. Mean scores on a scale of 1 to 6 given to each section of the questionnaire by Lead Partners, where 1 = very difficult/inaccurate, 2 = difficult/inaccurate, 3 = quite difficult/inaccurate, 4 = quite easy/accurate, 5 = easy/accurate, 6 = very easy/accurate. Unshaded bars represent scores for ease of completion and shaded bars represent scores for accuracy of answers. Error bars indicate standard errors.

We were entirely reliant upon Lead Partners for our data and thus our results can only be as accurate as the data we were provided with. There is also potential for bias when asking Lead Partners to evaluate their own SAPs as there may be an incentive for them to understate the progress made to ensure that funding continues (Cullen et al., 2001). Alternatively, they may overstate the progress to make their SAP appear to have been a good use of scarce conservation resources and thus also ensure continued funding (Cullen et al., 2001; Guikema and Milke, 1999). Despite all these potential problems, the Lead Partners are still the best source of data regarding the progress of the SAPs. Furthermore, the alternative would be to conduct large-scale

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independent ecological surveys, which would be prohibitively expensive and time consuming. Many Lead Partners commented on the lack of basic data for their species, such as population size and distribution, as well as a general lack of monitoring. Therefore, their estimates of conservation status used in the Cost-Utility Analysis were often based on expert opinion rather than actual data. This introduces a level of uncertainty into the analysis, but also highlights the importance of monitoring and data collection for conservation evaluation (Murdoch et al., 2007).

and two anonymous referees for comments which helped to improve the manuscript. Finally, we are extremely grateful to all the SAP Lead Partners who participated in this study.

5. Conclusion

References

Cost-Utility Analysis offers a cost-effective method for using the expertise available to evaluate the progress of conservation programmes in an adaptive manner and respond accordingly (Cullen et al., 2005). In addition, it can easily be adapted for application to multiple-species programmes, as demonstrated by Cullen et al. (2005), and potentially even habitat conservation programmes. Threat Reduction Assessment is sensitive to changes over short time periods and so can identify potential improvements or deteriorations in biodiversity before they could be picked up by directly monitoring the species themselves, as in Cost-Utility Analysis (Salafsky and Margoluis, 1999). Furthermore, Threat Reduction Assessment produces a standardised index (%) that can be used to compare different conservation programmes in vastly different biological and socioeconomic contexts, and can be readily interpreted by trained professionals and the general public alike (Salafsky and Margoluis, 1999). Indeed, with very little adaptation, Threat Reduction Assessment can deal with either single-species, multiple-species, habitat or site-specific conservation programmes, since all are concerned with reducing threats to an endangered entity. It could also be readily extended for use in an ecosystem service-based context (White et al., 2010). However, for the evaluation of SAPs, our analysis of the feedback we received from Lead Partners during the questionnaire process suggests that Cost-Utility Analysis represents an easier to conduct and more accurate assessment of the effectiveness of the SAPs than Threat Reduction Assessment. Biodiversity conservation requires society to make difficult choices about the allocation of limited resources. These decisions should not be based exclusively on economic reasoning, since moral, social and cultural considerations are also inevitably involved (Bulte and van Kooten, 2000; Moran et al., 1996). However, Cost-Utility Analysis and Threat Reduction Assessment can help to inform the conservation decision-making process and they should be used to contribute to the development of more efficient conservation strategies. At present the application of both approaches is limited by the lack of reliable data on the costs of conservation. Maintaining detailed records of effectiveness, anticipated costs and actual expenditure should be a priority for conservation management. However, species-based assessments are limited inevitably to the direct benefits of conservation efforts. The development of more holistic, ecosystem-based approaches, such as extending the assessment of benefits to encompass the broader ecological benefits of individual species programmes (Christie et al., 2010), would allow these wider benefits to be incorporated into the evaluation process.

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Acknowledgements We thank the Economic and Social Research Council and the Natural Environment Research Council for funding. D.M. also acknowledges funding provided by the Scottish Government Rural and Environment Research and Analysis Directorate (RERAD). We thank R. Cullen for providing additional unpublished information on the Cost-Utility Analysis technique, and A. Maddock, A. Cooke, J. Matthews, M. Marquiss, D. Yalden, M. Marsh and E. Westmoreland for useful comments on questionnaire design. We are grateful to Paul Armsworth

Appendix A. Supplementary Data Supplementary data to this article can be found online at doi:10.1016/j.ecolecon.2011.05.002.

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