Simulating the effects of using different types of species distribution data in reserve selection

In a perfect world, systematic conservation planning would use complete information on the distribution of biodiversity. However, information on most species is grossly incomplete. Two main types of distribution data are frequently used in conservation planning: observed and predicted distribution data. A fundamental question that planners face is - which kind of data is better under what circumstances? We used simulation procedures to analyse the effects of using different types of distribution data on the performance of reserve selection algorithms in scenarios using different reserve selection problems, amounts of species distribution known, conservation targets and costs. To compare these scenarios we used occurrence data from 25 amphibian and 41 reptile species of the Iberian Peninsula and assumed the available data represented the whole truth. We then sampled fractions of these data and either used them as they were, or converted them to modelled predicted distributions. This enabled us to build three other types of species distribution data sets commonly used in conservation planning: “predicted”, “transformed predicted” and “mixed”. Our results suggest that reserve selection performance is sensitive to the type of species distribution data used and that the most cost-efficient decision depends most on the reserve selection problem and on how much we have of the species distribution data. Choosing the most appropriate type of distribution data should start by evaluating the scenario circumstances. While there is no one best approach for every scenario, we discovered that using a mixed approach usually provides an acceptable compromise between species representation and cost.     

Accounting for habitat loss rates in sequential reserve selection: Simple methods for large problems

We develop reserve selection methods for maximizing either species retention in the landscape or species representation in reserve areas. These methods are developed in the context of sequential reserve selection, where site acquisition is done over a number of years, yearly budgets are limited and habitat loss may cause some sites to become unavailable during the planning period. The main methodological development of this study is what we call a site-ordering algorithm, which maximizes representation within selected sites at the end of the planning period, while accounting for habitat loss rates in optimization. Like stochastic dynamic programming, which is an approach that guarantees a globally optimal solution, the ordering algorithm generates a sequence in which sites are ideally acquired. As a distinction from stochastic dynamic programming, the ordering is generated via a relatively fast approximate process, which involves hierarchic application of the principle of maximization of marginal gain. In our comparisons, the ordering algorithm emerges a clear winner, it does well in terms of retention and is superior to simple heuristics in terms of representation within reserves. Unlike stochastic dynamic programming, the ordering algorithm is applicable to relatively large problem sizes, with reasonable computation times expected for problems involving thousands of sites.     

Sensitivity of conservation planning to different approaches to using predicted species distribution data

The main role of conservation planning is to design reserve networks to protect biodiversity in situ. Research within the field of conservation planning has focused on the development of theories and tools to design reserve networks that protect biodiversity in an efficient and representative manner. Whilst much progress has been made in this regard, there has been limited assessment of the sensitivity of conservation planning outcomes to uncertainty associated with the datasets used for conservation planning. Predicted species distribution data are commonly used for conservation planning because the alternatives (e.g. survey data) are incomplete or biased spatially. However, there may be considerable uncertainty associated with the use of predicted species distribution data, particularly given the variety of approaches available to generate a dataset from such predictions for use in conservation planning. These approaches range from using the probabilistic data directly to using a threshold identified a priori or a posteriori to convert the probabilistic data to presence/absence data. We assess the sensitivity of conservation planning outcomes to different uses of predicted species distribution data. The resulting reserve networks differed, and had different expected species representation. The choice of approach will depend on how much risk a conservation planner is willing to tolerate and how much efficiency can be sacrificed.     

Administrative regions in conservation: Balancing local priorities with regional to global preferences in spatial planning

Site selection, reserve selection, and spatial conservation prioritization are terms that have been used for various algorithms and methods for the spatial allocation of conservation resources. Many of these methods start from the setting of targets or weights for different conservation features. Almost always there is only one set of targets or weights, thus implicitly assuming that priorities stay the same through the entire planning region. However, priorities for biodiversity governance could vary between regions. For example, priorities inside countries could be different from global priorities. Inside a country, different stakeholders could hold different priorities. Thus, priorities could vary between sub-regions while ecological processes, such as connectivity, cross borders without regard to administrative boundaries. Here we describe how it is possible to account for conservation priorities that vary between administrative sub-regions in conservation prioritization. We illustrate how assumptions about selection methods and feature weights can significantly influence the outcome mapping of conservation priority. We also show how placing high emphasis on local considerations reduces the cost-efficiency of the global conservation outcome. Analyses proposed here will be made publicly available in software (Zonation) capable for large-scale high-resolution conservation prioritization.     

Assessing the performance of the existing and proposed network of marine protected areas to conserve marine biodiversity in Chile

The growing concern about the profound influence of human activities on marine ecosystems has been the driving force behind the creation of marine reserves in the last few decades. With almost 4200 km of coastline, Chile has not been the exception to this trend. A set of conservation priority sites has recently been proposed by the Chilean government to expand the current marine reserve network. In this study, we used the most comprehensive information currently available on the distribution of 2513 marine species in Chile to assess the efficiency of the existing system of marine protected areas (MPA) and the conservation priority sites identified by the government. Additionally, we evaluated the vulnerability of the reserve network selected with respect to threatening human activities. Our results show that both the existing protected areas and the proposed priority sites are relatively effective at protecting Chilean marine biodiversity. However, the majority of the species that are not represented within the existing or projected MPA network have very restricted distributions and are, therefore, of high conservation concern. To cover all species requires a network of 35 MPAs (46% of the total number of planning units). Many of the sites identified as irreplaceable present conflict with one or more human activities, particularly in the central region of the country. This study emphasizes the need for a systematic conservation planning approach to maximize the representation of species and prioritize those areas where conflicts between marine biodiversity conservation and human activities may occur.     

Methodological considerations in reserve system selection: A case study of Malagasy lemurs

Although data quality and weighting decisions impact the outputs of reserve selection algorithms, these factors have not been closely studied. We examine these methodological issues in the use of reserve selection algorithms by comparing: (1) quality of input data and (2) use of different weighting methods for prioritizing among species. In 2003, the government of Madagascar, a global biodiversity hotspot, committed to tripling the size of its protected area network to protect 10% of the country’s total land area. We apply the Zonation reserve selection algorithm to distribution data for 52 lemur species to identify priority areas for the expansion of Madagascar’s reserve network. We assess the similarity of the areas selected, as well as the proportions of lemur ranges protected in the resulting areas when different forms of input data were used: extent of occurrence versus refined extent of occurrence. Low overlap between the areas selected suggests that refined extent of occurrence data are highly desirable, and to best protect lemur species, we recommend refining extent of occurrence ranges using habitat and altitude limitations. Reserve areas were also selected for protection based on three different species weighting schemes, resulting in marked variation in proportional representation of species among the IUCN Red List of Threatened Species extinction risk categories. This result demonstrates that assignment of species weights influences whether a reserve network prioritizes maximizing overall species protection or maximizing protection of the most threatened species.     

Conservation assessment and prioritization of areas in Northeast India: Priorities for amphibians and reptiles

This study combines niche modeling and systematic area prioritization using distribution data for 131 species of amphibians and reptiles from Northeast India and Burma, with two objectives: (i) to evaluate the performance of the current conservation area network in Northeast India with respect to the representation of amphibians and reptiles, and (ii) to identify potential areas for expanding the current conservation area network. In a two-step protocol, maximum entropy niche modeling was used to project species’ potential geographic occurrences, and the resulting probabilistic distribution data were used to prioritize areas with algorithms that maximize the representation of all species in minimal total area. The results provided a critical assessment of conservation priorities in this data-deficient region, and indicate the utility of combining niche modeling with systematic area prioritization in such situations. Many areas that had been overlooked in previous assessments were identified. Although the existing protected areas were found to be inadequate for representation of amphibian and reptile diversity, the prioritization results show that by targeting a minimal representation of 5% of the current total area suitable for each species, the gaps can be filled with a relatively modest (0.41%) increase in the current total area covered by the network. Extended analyses were also performed to assess the effects of putatively rare species on reserve selection, which showed that the inclusion of these taxa can change the prioritization solutions significantly. The prioritization results also highlight areas of Northeast India that warrant attention from future surveys.     

Prioritisation of conservation areas in the Western Ghats, India

Areas of high conservation value were identified in the Western Ghats using a systematic conservation planning approach. Surrogates were chosen and assessed for effectiveness on the basis of spatial congruence using Pearson’s correlations and Mantel’s tests. The surrogates were, threatened and endemic plant and vertebrate species, unfragmented forest areas, dry forests, sub-regionally rare vegetation types, and a remotely sensed surrogate for unique evergreen ecosystems. At the scale of this analysis, amphibian richness was most highly correlated with overall threatened and endemic species richness, whereas mammals, especially wide-ranging species, were better at capturing overall animal and habitat diversity. There was a significant relationship between a remote sensing based habitat surrogate and endemic tree diversity and composition. None of the taxa or habitats served as a complete surrogate for the others. Sites were prioritised on the basis of their irreplaceability value using all five surrogates. Two alternative reserve networks are presented, one with minimal representation of surrogates, and the second with 3 occurrences of each species and 25% of each habitat type. These networks cover 8% and 29% of the region respectively. Seventy percent of the completely irreplaceable sites are outside the current protected area network. While the existing protected area network meets the minimal representation target for 88% of the species chosen in this study and all of the habitat surrogates, it is not representative with regard to amphibians, endemic tree species and small mammals. Much of the prioritised unprotected area is under reserve forests and can thus be incorporated into a wider network of conservation areas.     

Methods for reserve selection: Interior point search

Spatial reserve design concerns the planning of biological reserves for conservation. Typical reserve selection formulations operate on a large set of landscape elements, which could be grid cells or irregular sites, and selection algorithms aim to select the set of sites that achieves biodiversity target levels with minimum cost. This study presents a completely different optimization approach to reserve design. The reserve selection problem can be considerably simplified given the reasonable assumptions that: (i) maximum reserve cost is known; (ii) the approximate number of new reserves to be established is known; (iii) individual reserves need to be spatially contiguous. Further assuming the ability to construct a set of reserves in an efficient and close to optimal manner around designated reserve locations, the reserve selection problem can be turned into a search for a single interior point and area for each reserve. The utility of the proposed method is demonstrated for a data set of seven indicator species living in an conservation priority area in Southern Australia consisting of ca 73,000 selection units, with up to 10,000 cells chosen for inclusion in a reserve network. Requirements (ii) and (iii) above make interior point search computationally very efficient, allowing use with landscapes in the order of millions of elements. The method could also be used with non-linear species distribution models.     

Incorporating ontogenetic dispersal, ecological processes and conservation zoning into reserve design

Computational methods for marine reserve design are frequently used as decision-support tools for the identification of conservation areas. Most reserve-selection algorithms minimise the cost of the reserve system whilst aiming to meet specified biodiversity objectives. Here, we extend a widely-used selection algorithm, Marxan, to incorporate several important considerations related to biodiversity processes and management. First we relax the scorched earth assumption to allow conservation features in non-reserve zones to contribute explicitly to conservation objectives. To achieve this, we generate conservation targets at landscape scales rather than focusing purely on the representation of features within reserves. Second, we develop the notion of spatial dependencies further to incorporate spatial heterogeneity in the value of individual conservation features such as habitat types. We use the example of ontogenetic migrations of fish from mangroves to coral reefs because it nicely demonstrates how spatial ecological processes generate predictable heterogeneity in habitat value that should be considered in the reserve design process. Lastly, we show how habitat value can be disaggregated into ecosystem processes and services. Using a case study for the Belize Barrier Reef we compare reserve networks generated using our new approach with the results of traditional analyses. Consideration of the contribution of different protection zones, connectivity among habitats and more complex management goals resulted in up to a 52% increase in the mean biomass of commercially and ecologically-important fish species represented in the landscape. Our approach strengthens the ecological basis of reserve-design algorithms and might facilitate the uptake of ecosystem-based management into reserve design.     

Locating and protecting critical reserve sites to minimize expected and worst-case losses

There has been much recent interest in the development of systematic reserve selection methods that are capable of incorporating uncertainty associated with site destruction. This paper makes a contribution to this line of research by presenting two different optimization models for minimizing species losses within a planning region. Given limited acquisition budgets, the first minimizes expected species losses over all possible site loss patterns outside the reserve network while the second minimizes maximum species losses following the worst-case loss of a restricted subset of nonreserve sites. By incorporating the uncertainty of site destruction directly into the decision planning process, these models allow a conservation planner to take a less defensive and more strategic view of reserve selection that seeks to minimize species losses through the targeted acquisition of high-value/high-risk sites. We compare both of these methods to a more standard approach, which simply maximizes within reserve representation without regard for the varied level of threat faced by different sites and species. Results on a realistic dataset show that significant reductions in species losses can be achieved using either of these more intelligent modeling frameworks.     

Replacement cost: A practical measure of site value for cost-effective reserve planning

Conservation needs are often in direct competition with other forms of land-use, and therefore protection of biodiversity must be cost-efficient. While common reserve selection algorithms address this problem, quantitative planning tools often suggest an optimal set of sites that is not necessarily convenient for practical conservation. Besides cost-effective solutions we require flexibility if land-use conflicts are to be effectively resolved. We introduce a novel concept for site value in quantitative reserve planning. Replacement cost refers to the loss in solution value given that the optimal cost-efficient solution cannot be protected and alternative solutions, with particular sites forcibly included or excluded, are needed. This cost can be defined either in terms of loss of biological value or in terms of extra economic cost, and it has clear mathematical definitions in the context of benefit-function-based reserve planning. A main difference with the much-used concept of irreplaceability is that the latter tells about the likelihood of needing a site for achieving a particular conservation target. Instead, replacement cost tells us at what cost (biological or economic) can we exclude (or include) a site from the reserve network. Here, we illustrate the concept with hypothetical examples and show that replacement-cost analysis should prove useful in an interactive planning process, improving our understanding of the importance of a site for cost-efficient conservation.     

Population viability, ecological processes and biodiversity: Valuing sites for reserve selection

No-take reserves constitute one tool to improve conservation of marine ecosystems, yet criteria for their placement, size, and arrangement remain uncertain. Representation of biodiversity is necessary in reserve planning, but will ultimately fail for conservation unless factors affecting species’ persistence are also incorporated. This study presents an empirical example of the divergent relationships among multiple metrics used to quantify a site’s conservation value, including those that address representation (habitat type, species richness, species diversity), and others that address ecological processes and viability (density and reproductive capacity of a keystone species, in this case, the black chiton, Katharina tunicata). We characterized 10 rocky intertidal sites across two habitats in Barkley Sound, British Columbia, Canada, according to these site metrics. High-richness and high-production sites for K. tunicata were present in both habitat types, but high richness and high-production sites did not overlap. Across sites, species richness ranged from 29 to 46, and adult K. tunicata varied from 6 to 22 individuals m⁻². Adult density was negatively correlated with species richness, a pattern that likely occurs due to post-recruitment growth and survival because no correlation was evident with non-reproductive juveniles. Sites with high adult density also contributed disproportionately greater potential reproductive output (PRO), defined by total gonad mass. PRO varied by a factor of five across sites and was also negatively correlated with species richness. Compromise or relative weighting would be necessary to select valuable sites for conservation because of inherent contradictions among some reserve selection criteria. We suspect that this inconsistency among site metrics will occur more generally in other ecosystems and emphasize the importance of population viability of strongly interacting species.     

Conservation planning with dynamic threats: The role of spatial design and priority setting for species’ persistence

Conservation actions frequently need to be scheduled because both funding and implementation capacity are limited. Two approaches to scheduling are possible. Maximizing gain (MaxGain) which attempts to maximize representation with protected areas, or minimizing loss (MinLoss) which attempts to minimize total loss both inside and outside protected areas. Conservation planners also choose between setting priorities based solely on biodiversity pattern and considering surrogates for biodiversity processes such as connectivity. We address both biodiversity processes and habitat loss in a scheduling framework by comparing four different prioritization strategies defined by MaxGain and MinLoss applied to biodiversity patterns and processes to solve the dynamic area selection problem with variable area cost. We compared each strategy by estimating predicted species’ occurrences within a landscape after 20 years of incremental reservation and loss of habitat. By incorporating species-specific responses to fragmentation, we found that you could improve the performance of conservation strategies. MinLoss was the best approach for conserving both biodiversity pattern and process. However, due to the spatial autocorrelation of habitat loss, reserves selected with this approach tended to become more isolated through time; losing up to 40% of occurrences of edge-sensitive species. Additionally, because of the positive correlation between threats and land cost, reserve networks designed with this approach contained smaller and fewer reserves compared with networks designed with a MaxGain approach. We suggest a possible way to account for the negative effect of fragmentation by considering both local and neighbourhood vulnerability to habitat loss.     

The importance of in situ site loss in nature reserve selection: Balancing notions of complementarity and robustness

Because the threat of habitat destruction can never be entirely eliminated, there is a legitimate concern that some reserve networks, especially highly complementary ones with minimal species overlap, may be predisposed to severe losses in species representation if one or more core reserve sites are destroyed. In order to address this problem in a systematic way, we propose the use of two different optimization models for designing complementary reserve networks that are also highly robust to possible site losses. Given limited budgets, the first maximizes expected species representation over all possible site loss patterns while the second maximizes a combination of representation given all sites and remaining representation following the worst-case loss of a restricted subset of reserve sites. By incorporating reserve loss in fundamentally different ways, these two models provide a range of options in terms of information requirements, assumptions about risk aversion, and structural complexity. We compare both of these methods to a more standard approach, which completely ignores the inherent risk posed by reserve site loss. Results confirm that significantly more robust solutions can be obtained for a marginal decrease in initial species representation within the reserve system.     

Setting conservation targets under budgetary constraints

Target-based spatial prioritization is the default approach in conservation resource allocation. Here, we clarify a poorly known feature of target-based spatial prioritization that may lead to an unbalanced allocation of resources between species or other biodiversity features. Highest per-species resources will be allocated to species occurring in costly and otherwise species-poor locations, whereas smallest per-species resources will be allocated to species that occur in species-rich locations at low-cost areas. Uncertainty in information about processes determining distributions of biodiversity features may lead to uncertainty in target setting. This can be a problem if unnecessarily high targets emerge to consume excessive resources thus detracting from other conservation action. Difficulties might be encountered in particular when there are many features, targets are given simultaneously to multiple different types of biodiversity features, or components of features, or when there are interactions or correlations between features. Consequently, we recommend that the costs of targets for individual features could be evaluated to screen for such targets that consume a disproportionate fraction of available resources. Costs of targets can be evaluated by a variant of the replacement cost technique. We also find that commonly used reserve selection methods, minimum set coverage, maximum coverage, and utility maximization differ significantly in how they treat targets and their costs.     

Systematic reserve design as a dynamic process: F-TRAC and the Florida Forever program

Systematic conservation planning has become an important tool for increasing the efficiency of conservation decisions, but many planning efforts result in static plans that may lose relevance over time. We developed a process whereby planning is integrated into the decision-making process and updated every six months in response to conservation actions. The Florida Forever program is a 10-year, $3 billion land acquisition program expected to acquire approximately 1.25 million acres (607,000 ha) for conservation in Florida through the year 2010. With limited funding and duration, the program needs to be able to efficiently protect the most natural resources for a fixed cost, a situation well suited to a systematic reserve design approach. To inform this program, we conducted an assessment of natural resource conservation needs and developed the Florida Forever Tool for Efficient Resource Acquisition and Conservation (F-TRAC), a systematic reserve design analysis based on a simulated annealing site selection algorithm using Marxan software. The analysis considered conservation needs for a variety of natural resources including species, natural communities, high quality watersheds, wetlands, and sustainable forestry. Each 6-month analysis identifies an efficient portfolio of sites for resource protection, given the amount of land area likely remaining to be acquired by the Florida Forever program. The Spring 2004 model portfolio had a cost threshold of 206,308 ha, met conservation targets for 18 of 32 resource conservation features, and identified approximately 116,000 ha outside of current land acquisition projects. This study also demonstrates the use of reserve design results to evaluate existing and proposed land acquisition projects and inform decision makers; and the evaluation of acquisition trends and program success based on potential achievements as indicated by reserve design analyses.     

Integration of species persistence, costs and conflicts: An evaluation of tree conservation strategies in Cambodia

Cambodia forms part of the Indo-Burma hotspot. Its extent of biodiversity, however, is subject to considerable uncertainty, as there has been little systematic collection of flora and fauna. During the Khmer Rouge regime institutions were banned, academics were prosecuted and written documentation systematically destroyed. Compared with neighbouring countries Cambodia has a low population density and relatively large natural areas that are still intact. However, deforestation is expanding rapidly and a significant but un-estimated area of forest has been degraded by development of agro-industries, encroachment, illegal logging, over-harvesting and forest fire as well as the use of chemicals during war. The purpose of the paper is to: (i) apply reserve selection methods to design more robust conservation networks when knowledge of species occurrence is incomplete and habitat is threatened, and (ii) evaluate the usefulness of systematic conservation planning in a developing country where data are limited and institutions for implementation are weak. This study investigates the performance of four non-probabilistic strategies: (i) a so-called ‘rule of thumb’, (ii) hotspot, (iii) minimum cost representation, and (iv) maximum coverage; and one probabilistic design strategy, i.e. maximum expected coverage. The maximum expected coverage approach is between 15% and 24% more efficient than the non-probabilistic strategies. Finally, the relevance of such tools to real-world conservation planning in Cambodia is investigated. By incorporating experts in the generation of data, running the models and setting up premises, they acknowledge that it is possible to contribute to more systematic conservation planning in developing countries.     

Cost-effectiveness of conservation strategies implemented in boreal forests: The area selection process

To protect land from commercial exploitation is a common conservation practice. However, this requires large financial resources and it is therefore important to evaluate the cost-effectiveness of different strategies used in the selection of these conservation areas. In this study we compare four strategies and relate the differences in cost-effectiveness to differences in the selection process. We measure conservation benefits both as the amount of three tree structures and as the number of species in three species groups. We also estimate both the information cost associated with selecting conservation areas and the opportunity cost. We found the key habitat strategy to be the over-all most cost-effective. In this strategy, the areas have a flexible size and are selected by the authorities in a national field survey. The least cost-effective strategy was one where the selection was based only on forest classes in a satellite map. Intermediate were the retention group strategy, where small areas are left by the forest owner at harvesting, and the nature reserve strategy, where large areas are selected by the authorities. We emphasize that the differences we found are associated with the selection process and that other aspects, such as long-term survival of species, may rank the strategies differently. We conclude that the cost-effectiveness of a selection strategy depends on the size of the planning area for selection of conservation areas, the size of the conservation areas, the objective of the agent making the selection, and the amount and type of information on which the selection is based.     

Spatial structure of multispecies distributions in southern California, USA

Analysis of the spatial distribution of all species of conservation importance within a region is necessary to augment reserve selection strategies and habitat management in biodiversity conservation. In this study, we analyzed the spatial aggregation, spatial association, and vegetation types of point occurrence data collected from museum and herbaria records for rare, special concern, threatened, and endangered species of plants, reptiles, mammals, and birds in western Riverside County in southern California, USA. All taxa showed clumped distributions, with aggregation evident below 14 km for plants, 12 km for reptiles, 2 km for mammals, and 10 km for birds. In addition, all combinations of the different species groups showed high positive spatial association. The Santa Rosa Plateau exhibited the highest number of rare, special concern, threatened, and endangered species, and shrubland (coastal sage and chaparral) was the vegetation type inhabited by the most species. Local land use planning, zoning and reserve design should consider the spatial aggregation within and between species to determine the appropriate scale for conservation planning. The higher spatial association between species groups in this study may indicate interdependence between different species groups or shared habitat requirements. It is important to maintain diverse communities due to potential interdependence. The results of the study indicate that concentrating preservation efforts on areas with the highest number of species of concern and the restoration of native shrublands are the most appropriate actions for multiple species habitat conservation in this area.