Coral reefs have exceptional biodiversity, support the livelihoods of millions of people, and are threatened by multiple human activities on land (e.g. farming) and in the sea (e.g. overfishing). Most conservation efforts occur at local scales and, when effective, can increase the resilience of coral reefs to global threats such as climate change (e.g. warming water and ocean acidification). Limited resources for conservation require that we efficiently prioritize where and how to best sustain coral reef ecosystems.
Here we develop the first prioritization approach that can guide regional-scale conservation investments in land- and sea-based conservation actions that cost-effectively mitigate threats to coral reefs, and apply it to the Coral Triangle, an area of significant global attention and funding. Using information on threats to marine ecosystems, effectiveness of management actions at abating threats, and the management and opportunity costs of actions, we calculate the rate of return on investment in two conservation actions in sixteen ecoregions. We discover that marine conservation almost always trumps terrestrial conservation within any ecoregion, but terrestrial conservation in one ecoregion can be a better investment than marine conservation in another. We show how these results could be used to allocate a limited budget for conservation and compare them to priorities based on individual criteria.
Previous prioritization approaches do not consider both land and sea-based threats or the socioeconomic costs of conserving coral reefs. A simple and transparent approach like ours is essential to support effective coral reef conservation decisions in a large and diverse region like the Coral Triangle, but can be applied at any scale and to other marine ecosystems.
Citation: Klein CJ, Ban NC, Halpern BS, Beger M, Game ET, Grantham HS, et al. (2010) Prioritizing Land and Sea Conservation Investments to Protect Coral Reefs. PLoS ONE5(8): e12431. https://doi.org/10.1371/journal.pone.0012431
Editor: Simon Thrush, NIWA, New Zealand
Received: May 17, 2010; Accepted: July 17, 2010; Published: August 30, 2010
Copyright: © 2010 Klein et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: Funding was provided by the Centre for Applied Environmental Decision Analysis, the Australian Research Council, and a University of Queensland Graduate School Research Travel Grant. EAT was supported by the World Wildlife Fund Fuller Postdoctoral Fellowship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Coral reefs are the world's most diverse marine ecosystem and are vital to hundreds of millions of people as a source of nutrition, economic opportunity, and storm protection . Due to climate change and local impacts, the state of coral reefs is grim and their protection is urgent , , . As with all conservation, limited resources for coral reef protection require that we prioritize where and how to act to efficiently sustain coral reef ecosystems .
Local-scale threats to coral reefs originate from both land- and sea-based human activities (e.g. over-fishing, nutrient runoff from farming) . Where both exist, conservation strategies should consider each of them , . The allocation of conservation resources to coral reefs should depend on which strategies most efficiently reduce their threats . Sophisticated approaches for identifying marine conservation priorities exist , , , but fail to explicitly address threats originating on land and the associated costs of mitigating these threats through conservation action. Effective conservation prioritization should provide guidance on how to distribute funds between land- and sea-based conservation actions to protect coral reefs.
We address this deficiency by developing the first explicit method for prioritizing conservation actions and locations to cost-effectively mitigate land- and sea-based threats to marine ecosystems and apply it to the Coral Triangle, one of the world's highest conservation priorities , . The multi-lateral Coral Triangle Initiative on Coral Reefs, Fisheries and Food Security (formalized in May 2009) is the focus of significant global conservation attention with financial commitments of at least US $400 million (http://www.cti-secretariat.net). This amount is likely to be insufficient to achieve the Initiative's goals, thus investments must be prioritized.
Standard advice from business and economics is to invest in projects where the rates of return on investment are the highest . This approach has been applied to the conservation of terrestrial biodiversity , , , but it has yet to be applied to marine conservation. Any application of the return on investment approach requires an explicit statement of overall objective. The objective in previous studies has been species focused (e.g. maximize the number of species conserved). Here, our objective is to maximize threat reduction to coral reefs across the Coral Triangle's ecoregions through investment in land- and sea-based conservation actions.
Achieving the objective relies upon a rigorous problem formulation and information on threats to marine ecosystems, effectiveness of management actions at abating threats, and the economic costs of actions. We considered 8 threats to coral reefs (Table 1), each associated either with agricultural run-off or fishing, and two actions that reduce their impact on coral reefs: effective management of coastal watersheds and coral reefs. We refer to the places where these actions are implemented as protected areas, but acknowledge that effective management is rare and involves more than just dedicating protected areas, especially in the Coral Triangle , , . As a result, protected areas require funding for management and the restriction of profitable activities. Thus, we estimated the management costs and value of foregone usage to farmers and fishers (i.e. opportunity cost) of protected areas.
Using this information, we calculated the rate of return on investment of each action in each ecoregion (denoted “ecoactions”) , where the rate is calculated as the reduction of threats (return) per dollar spent on their reduction (investment). We ranked each ecoaction (e.g. effective management of coral reefs in the Bird's Head ecoregion) in terms of how cost-effective it is at mitigating threats to coral reefs for two scenarios. Scenario 1 reflects investment of management costs alone, whereas scenario 2 also considers opportunity costs. We demonstrate how these rankings can be used to allocate a limited budget for conservation and we compare our results to those based on individual criteria (e.g. cost, species richness).
Materials and Methods
Our method for prioritizing land and sea conservation investments to protect marine ecosystems involves five general steps (Figure 1), described below.
Step 1: Define conservation objective
The first step in formulating any conservation resource allocation problem is to define a quantifiable objective. Our objective was to maximize threat reduction to coral reefs across the Coral Triangle's ecoregions through investment in land and sea-based conservation actions. We used 16 marine ecoregions that were defined on the basis of coral diversity and endemism, each of which contains 503–553 zooxanthellate coral species .
Step 2: Identify threats to ecosystem
The second step is to determine the threats to, and their relative impact on, the marine ecosystem. We considered the threats that could be mitigated with local-scale conservation action and their relative impact on coral reefs (Table 1). We used data from Halpern et al.  that depicts the impact of anthropogenic drivers of change (henceforth referred to as threats), to each 1 km2 section of coral reefs , .
Step 3: Identify conservation actions to abate threats
The third step is to identify conservation actions and their effectiveness at abating the threats identified in step two. We determined the area available (i.e. not cleared or effectively managed in each ecoregion) for implementing two actions (Table S1): 1) effective management of coastal watersheds; 2) effective management of coral reefs . We assume that each threat reduces linearly with protection of the ecoregion.
A surrogate must be used to represent where and how much of the land and sea is effectively managed at present, as this information does not exist across the Coral Triangle. In theory, protected areas are effectively managed; however, in practice, only a subset of protected areas is effectively managed for biodiversity conservation , . Therefore, we estimated which coral reefs and terrestrial protected areas are effectively managed based on a few simple guidelines, described below.
We only considered sub-catchments that reach the ocean and consider them as part of an ecoregion if their coastal pour-point emptied into the marine portion of that region. We used sub-catchment boundaries and coastal pour-point data from Halpern et al. . We assume that the protected areas are effectively managed in areas containing native vegetation. In this analysis, we used terrestrial protected areas with an IUCN designation from the World Database on Protected Areas from the World Commission on Protected Areas from December 2007. Using SPOT vegetation satellite data, we determined the amount of protected areas containing native vegetation from 2000 . For each ecoregion, we calculated the proportion of land protected under two scenarios: 1) Pessimistic scenario, where vegetated areas in only the more stringently protected areas (i.e. IUCN 1-4) are effective and 2) Optimistic scenario, where vegetated areas in all types of protected areas recognized by the IUCN (IUCN 1-6) are effective.
We used the global coral reef atlas , compiled by the World Conservation Monitoring Centre at the United Nations Environment Programme, to determine the location of coral reefs with each ecoregion. Data indicate the presence/absence of coral reefs for each 1 km2 cell. Mora et al.  provided an assessment on the extent and effectiveness of coral reef protected areas. Each protected area was classified by its regulations on extraction (no-take, take, or multi-purpose) and risk of poaching (low, medium, high). For each ecoregion, we calculated the proportion of coral reef protected under two scenarios: 1) Pessimistic scenario, where only areas with no extraction (no-take, low poaching) are effective at protecting the reefs and 2) Optimistic scenario, where areas with limited extraction (no-take or multipurpose for any level of poaching) are effective at protecting the reefs.
We show results that use the amount protected under the pessimistic scenario for terrestrial and marine conservation. However, the ranking results were insensitive to the information used as there is little difference between the amounts protected under each scenario.
Step 4: Calculate costs of implementing actions
We predicted the annual management and opportunity costs associated with land and marine protected areas (Table S1). When applying the method with opportunity costs, we assume that the ecoaction excludes extractive activities and causes economic losses that cannot be recovered in another place or industry. However, in reality, conservation can deliver benefits (e.g. improved fishing yields) that may compensate for some economic losses .
We used a model developed by Moore et al.  to predict the management costs of terrestrial protected areas in each ecoregion, as done in Kark et al  and Bode et al . The model states that the cost of managing a protected area is a nonlinear function of the size of the proposed protected area, the Purchasing Power Parity (PPP) of the nation, and the Gross National Income (GNI) of the nation:
where all logarithms are of base ten. We modeled the area of protected areas in each ecoregion by the median size of the existing vegetated protected areas (IUCN 1-6) in that ecoregion.
We used a model developed by Balmford et al.  to predict the management costs of marine protected areas in each ecoregion. The model states that the cost of managing a marine protected area is a nonlinear function of the size of the proposed protected area, distance of area from land, and the PPP of the nation:
where all logarithms are of base ten. We modeled the area of protected areas in each ecoregion by the median size of the existing no-take or multipurpose coral reef protected areas in that ecoregion. We modeled the distance of coral reef protected areas in each ecoregion by the median distance of coral reefs from land.
The economic data we used to inform the models described below were obtained from the 2006 International Monetary Fund's Financial Statistics http://www.imfstatistics.org/imf/. To calculate the PPP, we divided the PPP conversion rate (local $/international $) reported by the Monetary Fund by the exchange rate (local $/US $). We substituted missing GNI information with the Gross Domestic Product.
As some ecoregions span multiple countries, the management costs are therefore likely to vary substantially. Our analyses treat each region as a homogeneous entity, where the cost is calculated using the Balmford-Moore models , , with parameter values that are the area-weighted average of the constituent nations' exclusive economic zone. The area-weighting method is applied to the other predictor variables as done in Bode et al .
Opportunity costs, land.
We estimated the opportunity costs of agricultural production from implementation of a protected area that excludes cultivation. The agriculture opportunity cost represents the potential foregone economic returns from agricultural production (cropping and grazing) on areas containing native vegetation . The potential economic returns from agricultural production are estimated at a 5′ resolution by the maximum of the potential crop and livestock yields based on land capability, multiplied by the producer price . For each ecoregion, we calculated the maximum potential agricultural profits per unit area of native vegetation.
Opportunity costs, marine.
Spatially explicit information on catch rates for small-scale fisheries was determined for each 1 km2 of coral reef by Halpern et al.  from the FAO and Sea Around Us Project (SAUP). Although this is the best available data for artisanal fishing, it is modeled and based on many crude assumptions. Development of a new artisanal fishing model for the Coral Triangle that considers the spatial distribution of catch, population size of species across the region, historical fishing, and fishing method is an area of further research. We summed the catch rates across all coral reefs within each ecoregion. The value (US$, year 2000) of reef fish in each country are provided by the SAUP for reported landings from 1950–2004 . We used the maximum value reported per country to prevent underestimating the value over time. Like management costs, opportunity costs in some ecoregions vary substantially because they span multiple countries. Our analyses treat each region as one entity using the area-weighted average of the constituent nation's exclusive economic zone.
Step 5: Invest where the rate of return on investment is highest
The final step is to mathematically formulate the resource allocation problem and determine the rate of return (i.e. reduction of threats) on investment (i.e. cost of reducing threats) of each ecoaction. The overall impact, Ii, that a set of threats (k = 1,…,8) have on a 1 km2 section of coral reef (i = 1,…,N) was defined by Halpern et al.  as a weighted sum of land- and sea-based threatswhere Lik and Cik are threat values originating from the land and sea, respectively, and is a weighting reflecting the relative impact of threat k on coral reefs (Table 1).
In step 3, we made the assumption that threat, k, in any 1 km2 section of reef, i, is reduced linearly with protection of the ecoregion, j: and , where lj and cj are the proportion of terrestrial and coral reef protected area, respectively. Therefore, the average threat impacting coral reefs in each ecoregion (j = 1,…,16) can be written as a function of how much of the land and sea that we protect in an ecoregion,where Nj is the number of reef pixels (i) in ecoregion j and Sj is the set of indices that determine if pixel i is in region j. In doing this, we assume that the benefit of protection is evenly spread across the ecoregion. This relationship could be modified if more discrete regions were targeted.
The proportion of the ecoregion protected is the sum of the portion currently protected (loj and coj) and the portion protected by additional investment. To account for the cost of additional protection, the proportion protected after additional investment made can be expressed as the proportion of additional investment made (xj and yj) relative to the total cost of land and ocean available for protection (aj and bj), respectively:
The rate of return (threat reduction) on investment of each ecoaction can then be calculated for each land and sea-based conservation action, respectively:
The greater the rate of return on investment per ecoaction, the higher priority it is for investment. In order to achieve the conservation objective, investments should be made in high priority ecoactions unless there are ecoregional or action-specific constraints (e.g. budget or area targets). We show how a budget and area constraint influences the distribution of an arbitrary budget of US $1 B, $400 M, and $100 M. The area constraint ensures that a priority ecoaction receives funding for no more than a designated percentage of its available area, which we arbitrarily selected to be 30%.
We applied our prioritization approach to rank ecoactions using different costs and found a high concordance in the rankings (Spearman's rank correlation of 0.88, p<0.001). We present our ranking results for both scenarios at two scales (Fig. 2): across the entire Coral Triangle and within each ecoregion. At the Coral Triangle scale, we found that terrestrial conservation in one ecoregion is sometimes a higher priority than marine conservation in another ecoregion, especially in scenario 1 (management costs only). For example, the highest ranking terrestrial action (E, North Arafura ecoregion) has a larger return on investment than marine conservation in half of the ecoregions.
Scenario 1 (a) reflects investment of management costs whereas scenario 2 (b) also considers opportunity costs. Letters labeling ecoregions follow the ranking order for marine conservation (i.e. Ecoregion A ranks highest for marine conservation) and correspond to letters in Figure 3.
Funding is distributed to all available reef and land habitat (a) and restricted to 30% of available habitat (b) under scenario 1 (management costs). Shades of green and blue represent funding to land- and sea-based conservation, respectively. Letters correspond to ecoregion labels in Figure 2a.
Within any particular ecoregion, marine conservation is almost always a higher priority than terrestrial conservation. The one exception is in the North Philippines (Scenario 1), where the marine management cost is substantially larger than on the land (Table S1).
We demonstrate two ways these rankings can be used to allocate limited conservation resources under scenario 1 (management costs) (Fig. 3). First, for three different budgets (US $ 1 B, 400 M, and 100 M), we allocate money to the highest ranking ecoactions until it is spent (Fig. 3a). This assumes that within an ecoregion, all available (i.e. not currently protected or developed) coral reefs and land can be effectively managed, which is likely to be unrealistic. Thus, we show how a budget would be distributed to the highest ranking ecoactions if we cap the allocation at protection of thirty percent of the available reef or land affecting the reef (Fig. 3b).
To explore the sensitivity of our results to the threat weighting values (Table 1), we performed the analysis with the range of weighting values provided by experts (n = 24) and found that the rankings were robust to these variations (Spearman's rank correlations >0.99, p<0.001). Regardless of weighting values used, rankings for the top seven ecoactions were always the same. The remainder of ecoactions typically did not change rank and never changed by more than four places (Table S2). Depending on the budget, how these subtle discrepancies could impact the distribution of funding are important considerations.
We compare our ecoregional rankings to those based on individual criteria (Table 2). Since other approaches do not consider marine and terrestrial conservation actions simultaneously, we compare our ecoregional rankings for marine actions only. We found a lack of concordance between approaches (Spearman's rank correlations from -0.22 to 0.3), indicating that they would recommend different investment priorities. Using estimated management costs, we show how a budget of US $400 M for management of land- and sea-based threats would be distributed following each ranking scheme (Table 2). For example, we found that prioritization on cumulative threats alone would only provide enough funding for effective management of 6% of one ecoregion, whereas our approach would ensure that 30% of seven ecoregions were managed.
The purpose of this paper is to illustrate a novel approach for delivering cost-effective outcomes for marine conservation that can explicitly trade-off resource allocation decisions among land- and sea-based conservation actions to protect marine ecosystems. Our approach is useful in guiding managers and policy makers in making decisions on where and in which actions to invest. Although it is useful for supporting broad scale resource allocation decisions, the results are not necessarily applicable to all places within an ecoregion as the conservation context may vary between communities . However, the method can also be applied at a local-scale (e.g. provincial or catchment level), using more conservation actions (e.g., run-off management, improved agricultural practices, fishing gear-based management). In addition, more specific data on social and economic costs would need to be estimated for a local-scale application as the data we used may be too coarse, especially for management costs. The effectiveness of any local conservation plan in this region is reliant upon community involvement and the consideration of indigenous knowledge, management practices, and property rights , , .
One of the key results - terrestrial conservation in one ecoregion is sometimes a higher priority than marine conservation in another ecoregion - is contrary to current conservation strategies, which typically do not trade-off marine and terrestrial conservation actions to protect marine ecosystems, and suggests that more cost-effective conservation outcomes could be achieved using our method. Although another key result – within any particular ecoregion, marine conservation is almost always a higher priority than terrestrial conservation within an ecoregion - generally supports current management practice in any given place, greater conservation outcomes could be achieved when the entire region is considered.
Incorporating different socioeconomic costs did not significantly affect outcomes. However, decisions following each scenario are likely to have different social and economic implications. For example, investments including opportunity costs (Scenario 2) are more likely to minimize impact on fishers and farmers as they were explicitly considered in the analysis , , . However, scenario 2 assumes that people would be compensated for displacement due to conservation and that conservation actions preclude subsistence farming and fishing, both of which are unlikely.
We assume that each threat reduces linearly with protection of the ecoregion (Step 3, materials and methods). This represents the most parsimonious relationship between threat and protection but could easily be modified if more detailed information were available for each ecoaction. This type of information is difficult to obtain as effective monitoring and good quality data relevant to this is lacking . However, in a region with little protection and a limited budget for conservation, the use of a non-linear function that demonstrates diminishing returns may not substantially impact the results. Testing this on a specific region where this type of information could be obtained would be informative. Assessing the benefits of conservation actions, including the relationship between reducing threats and biodiversity, is a significant challenge and research priority in conservation.
Other applications of the return on investment framework to inform the allocation of resources to protect terrestrial biodiversity use a non-linear benefit function based on the species-area relationship where the total number of species (S) present in area (A) is a power–law function of that area , : . This relationship is an appropriate estimation of the benefits of protection when the objective is to conserve species, as in these studies; however, it is not applicable to our objective (i.e. threat reduction to coral reefs). Although we aimed to solve one objective, application of the return on investment thinking can be used to solve a range of conservation objectives to conserve marine ecosystems .
Priorities and investment plans following our approach versus that based on individual criteria (Table 2) would be substantially different. In addition, prioritization on species information alone, for example, will not be able to inform how funding should be divided between management actions on the land and in the sea. Similar confusion can arise if we prioritize only on cost or threat.
Our method could be adapted to provide more specific guidelines on how much and when (i.e. timing of investments) to invest in ecoactions . Such analyses may require information on budget (size and constraints), benefits of conservation (e.g. payments for ecosystem services), more specific conservation actions, social adaptive capacity indicating the likelihood of a project succeeding (e.g. willingness of people to forego resources) , distribution of species, more opportunity costs (e.g. aquaculture and forestry), a better understanding of the effectiveness of management actions, coral reef resilience , and other relevant threats (e.g. sedimentation from deforestation). At any scale, neglecting to properly address social costs to resource users will most likely lead to unsuccessful conservation plans , . These are areas of further research.
Although we apply our prioritization approach to the Coral Triangle Initiative, we acknowledge that our analysis is focused on a small aspect of the conservation problem in the Coral Triangle. In addition to identifying priority areas for effective management (Goal 1 in the Regional Plan of Action), the Coral Triangle Initiative aims to achieve outcomes relevant to fisheries management, climate change adaptation, and threatened species . However, it is important to note that effective management of coral reefs at a local scale can increase their resilience to global threats such as climate change .
A simple, transparent, and economically grounded approach like ours is essential to making any conservation decisions in a large and diverse region like the Coral Triangle, where the budget is primarily financed from international aid. Effective conservation of marine resources must consider land- and sea-based human activities and their management costs . The lack of a defensible resource allocation plan could lead to costly and contentious conservation strategies that do not protect biodiversity, impeding additional global funding to one of the world's most biodiverse and threatened regions.
Cost and protected area data for coastal catchments and coral reefs in each ecoregion.
(0.04 MB DOC)
Ranking results from scenario 1 compared to results from the impact weighting value sensitivity analysis. We perform the analysis with the maximum and minimum impact weighting values provided by experts for the land- and sea-based threats.
(0.05 MB DOC)
We thank Jorge Alvarez-Romeo, Colin Ebert, Takuya Iwamura, and Oscar Venter for their contributions to this manuscript.
Conceived and designed the experiments: CJK NB MB EG HSG AG TJK SK Et KAW HP. Performed the experiments: CJK BSH HP. Analyzed the data: CJK HP. Contributed reagents/materials/analysis tools: CJK NB BSH SK. Wrote the paper: CJK BSH EG HP.
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