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.     

One- and two-objective approaches to an area-constrained habitat reserve site selection problem

We compare several ways to model a habitat reserve site selection problem in which an upper bound on the total area of the selected sites is included. The models are cast as optimization coverage models drawn from the location science literature. Classic covering problems typically include a constraint on the number of sites that can be selected. If potential reserve sites vary in terms of area, acquisition cost or land value, then sites need to be differentiated by these characteristics in the selection process. To address this within the optimization model, the constraint on the number of selected sites can either be replaced by one limiting the total area of the selected sites or area minimization can be incorporated as a second objective. We show that for our dataset and choice of optimization solver average solution time improves considerably when an area-constrained reserve site selection problem is modeled as a two objective rather than a single objective problem with a constraint limiting the total area of the selected sites. Computational experience is reported using a large dataset from Australia.     

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.     

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.     

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.     

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.     

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.     

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.     

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.     

Conservation of coral reef biodiversity: a comparison of reserve selection procedures for corals and fishes

A range of different biodiversity-based selection methods for nature reserves has been tested for terrestrial environments, including those based on diversity hotspots, endemicity hotspots and complementarity. In this study, we investigate the utility of these approaches for a coral reef embayment. We compare coral and fish species richness in a random accumulation of reserve sites with (a) hotspots analysis, (b) stratified selection of hotspots, and (c) complementarity. Cumulative species-site curves indicated that complementarity maximized the rate of accumulation of species of both corals and fishes in reserves, while the hotspot approach performed moderately well. An equivalent number of reserve sites supported a greater proportion of the coral biodiversity when compared to fishes, reflecting the broader distribution of corals. Our results indicate that when choosing an indicator group as a proxy for representing overall diversity in a reserve network, the group with the greatest heterogeneity will provide the best results. Our findings also show that although a modest number of protected sites (20%) will incorporate much of the local diversity (>75%), species-specific approaches must be incorporated to target rare species.     

Uncertainty analysis favours selection of spatially aggregated reserve networks

It has been widely argued that habitat fragmentation is bad for (meta)population persistence and that a high level of fragmentation is a similarly undesirable characteristic for a reserve network. However, modelling the effects of fragmentation for many species is very difficult due to high data demands and uncertainty concerning its effect on particular species. Hence, several reserve selection methods employ qualitative heuristics such as boundary length penalties that aggregate reserve network structures. This aggregation usually comes at a cost because low quality habitats will be included for the sake of increased connectivity. Here a biologically justified method for designing aggregated reserve networks based on a technique called distribution smoothing is investigated. As with the boundary length penalty, its use incurs an apparent biological cost. However, taking a step further, potential negative effects of fragmentation on individual species are evaluated using a decision-theoretic uncertainty analysis approach. This analysis shows that the aggregated reserve network (based on smoothed distributions) is likely to be biologically more valuable than a more fragmented one (based on habitat model predictions). The method is illustrated with a reserve design case study in the Hunter Valley of south-eastern Australia. The uncertainty analysis method, based on information-gap decision theory, provides a systematic framework for making robust decisions under severe uncertainty, making it particularly well adapted to reserve design problems.     

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.     

Reserve selection with minimum contiguous area restrictions: An application to open space protection planning in suburban Chicago

Conservation efforts often require site or parcel selection strategies that lead to spatially cohesive reserves. Although habitat contiguity is thought to be conducive to the persistence of many sensitive species, availability of funding and suitable land may restrict the extent to which this spatial attribute can be pursued in land management or conservation. Using optimization modeling, we explore the economic and spatial tradeoffs of retaining or restoring grassland habitat in contiguous patches of various sizes near the Chicago metropolitan area. The underlying mathematical construct is the first exact, generalized formulation that directly models spatial contiguity in optimal reserve selection. The construct allows conservation planners to analyze and weigh different minimum contiguous habitat size requirements that are to be used in specific land acquisition or retention projects.     

First-best, second-best, and heuristic solutions in conservation reserve site selection

Previous studies which dealt with the conservation reserve site selection problem used either optimization methods, specifically linear integer programming (IP), or heuristic algorithms. The trade-off between computational efficiency versus optimality has been discussed in some articles and conflicting messages were signaled. Although the problem of suboptimality was acknowledged, some authors argued that heuristics may be preferable to exact optimization because IP models are computationally complex and may not be solvable when too many reserve sites are involved. On the other hand, some studies reported that fairly large problems could be solved easily. This paper shows that although the computational complexity argument can be valid for large reserve selection problems, by properly guiding the solver and exploiting the problem structure, formal optimization can deliver second-best (near-optimal) solutions that dominate the greedy heuristic solutions.     

Assessing replacement cost of conservation areas: How does habitat loss influence priorities?

Replacement cost refers to the loss incurred if the ideal set of conservation areas cannot be protected due to compulsory inclusion or exclusion of some area candidates. This cost can be defined either in terms of loss of conservation value or in terms of extra acquisition cost, and it has a clear mathematical definition as a difference between the value of the unconstrained optimal solution and a constrained suboptimal solution. In this work we for the first time show how replacement cost can be calculated in the context of sequential reserve selection, where a reserve network is developed over a longer time period and ongoing habitat loss influences retention and availability of sites. In case of site exclusion, a question that can be asked is, “if a site belonging to the ideal (optimal) solution cannot be obtained, what expected loss in reserve network value does this entail by the end of the planning period given that the rest of the solution is re-organized in the most advantageous manner?” Heuristically, the proposed method achieves the ambit of combining irreplaceability and vulnerability into one score of site importance. We applied replacement cost analysis to conservation prioritization for wood-inhabiting fungi in Norway, identifying factors that influence replacement cost and urgency of site acquisition. Among other things we find that the reliability of loss rate information is important, because the optimal site acquisition order may be strongly influenced by underestimated loss rates.     

Within-site habitat configuration in reserve design: A case study with a peatland bird

This study assesses the effects of considering within-site habitat configuration when designing reserve networks. This attribute takes all its importance in situations where the long-term integrity of (within-site) habitat patches cannot be preserved without protecting their surrounding environment. We addressed this issue through the concrete problem of selecting a reserve network of natural peatlands in southern Québec, Canada. We used a reserve-selection algorithm that minimized the total number of peatlands to include within networks. The algorithm was constrained to include peatlands containing habitat patches that met specific size thresholds. Five habitat-clustering thresholds were used to set the eligibility of each site to the selection process. The resulting reserve networks were evaluated according to their representation efficiency and to the expected consequences for the Palm Warbler (Dendroica palmarum), an area and isolation-sensitive bird restricted to peatlands in southern Québec.Constraining the algorithm to include peatlands showing increasingly larger patches of habitats led to larger networks, both in terms of area and number of sites, and to networks composed of smaller sites. These effects increased with the representation target (i.e., the % of each habitat preserved). With respect to the Palm Warbler, selecting peatlands with larger patches of habitats had only an indirect effect on its site-occupancy pattern. Indeed, despite the fact that the probability of occurrence of the warbler was negatively correlated with the size of habitat patches, the habitat-clustering threshold influenced the incidence of the warbler mainly via its effect on the physical attributes of the selected networks - including the area, isolation level, and the number of selected sites. Because increasing the habitat-clustering threshold led indirectly to a greater regional availability of prime breeding habitats for the Palm Warbler, it mitigated the severe negative impact of an hypothetical alteration or destruction of non-selected peatlands. Our study thus emphasizes the importance of determining how the different factors describing within-site configuration are correlated with other intrinsic characteristics of the sites available to the selection process before opting for a site-selection strategy.     

Designing spatially-explicit reserve networks in the presence of mandatory sites

In the selection of reserve networks there are special sites whose ecologic, strategic or morphologic values dictate their inclusion. The existence of regional rare or confined-distribution species is one among other reasons that often determines the existence of such mandatory sites. Moreover, quite often these mandatory sites are located far apart. Although several methods have been proposed to accommodate structural connectivity in reserve selection, they were not devised to deal specifically with such mandatory sites. Those that encourage aggregation of sites by means of criteria incorporated in the objective function do not seem suitable to acquire consistent connectivity levels in the presence of mandatory sites. Methods that enforce “full connectivity” tend to produce long and narrow solutions, which results in efficiency deficits and biological unsuitability, as they force the selection of more sites of less quality to ensure connectivity. Hence specific methods to select ecological reserves when mandatory sites exist are needed. Here we discuss and propose a 0-1 linear programming model to deal with this issue. The model was applied in two data sets of forest breeding birds and butterflies. Its solutions and computational performances are discussed.     

Designing marine reserves for interacting species: Insights from theory

The primary goals of marine reserves include protecting biodiversity and ecosystem structure. Therefore, a multispecies approach to designing and monitoring reserve networks is necessary. To gain insight into how the interactions between species in marine communities may affect reserve design, we synthesize marine reserve community models and community models with habitat destruction and fragmentation, and we develop new extensions of existing models. This synthesis highlights the potential for species interactions to alter reserve design criteria; in particular, accounting for species interactions often leads to an increase in reserve size necessary to protect populations. Accounting for species interactions also indicates the need to base reserve design and monitoring on a variety of species, especially long-distance dispersers, inferior colonizers, and specialists. Finally, the new model extensions highlight how, given dispersal, source populations outside reserves as well as increases in fished populations after reserve establishment may negatively affect reserve populations of competitors or prey. Therefore, multispecies harvest dynamics outside reserves and before reserve establishment are critical to determining the appropriate reserve size, spacing, and expectations after establishment. These models highlight the importance of species interactions to reserve design and provide guidelines for how this complexity can begin to be incorporated into conservation planning.     

Optimal reserve selection in a dynamic world

In this paper we present a novel expansion of the problem of optimal reserve site selection over time. We explore a case where areas with valuable biodiversity cannot all be protected immediately due to budget restrictions and there is a probability of species extinction on reserved as well as non-reserved sites. Add to this the risk of land-use conversion facing all non-reserved areas. We furthermore introduce a new type of control by making the planning authorities have the option to sell reserved land on which biodiversity value has decreased. We formulate and solve this problem through stochastic dynamic integer-programming. The current study shows that, due to the dynamic and stochastic nature of biodiversity evolution, the inclusion of a swapping option may increase overall efficiency. Finally, we test a number of decision criteria (heuristics) to investigate alternatives to the cumbersome task of determining the true optimum.     

The effects of including marine ecological values in terrestrial reserve planning for a forest-nesting seabird

Theoretical advances in systematic reserve design aim to promote the efficient use of limited conservation resources and to increase the likelihood that reserve networks enhance the persistence of valued species and ecosystems. However, these methods have rarely been applied to species that rely on spatially disjunct habitats. We used the marbled murrelet, a seabird that requires old-growth forest in which to nest and high quality marine habitats in which to forage, as a case study to explore methods of incorporating multiple ecological values into single species spatial reserve design. Specifically, we used the cost function in MARXAN to include the ecological value of marine habitats while identifying spatial solutions for terrestrial nesting habitat reserves. Including marine values influenced terrestrial reserve designs most when terrestrial habitat targets were low and little or none of the target was represented in pre-existing protected areas. Our results suggest that including marine values in the planning process will influence marbled murrelet terrestrial reserve designs most where substantial terrestrial nesting habitat still exists, where new reserves are relatively unconstrained by pre-existing reserves, or when conservation resources only allow the protection of a small fraction of available habitat. This paper presents a novel framework for incorporating multiple measures of ecological value in the spatial reserve design process and should be particularly useful for species that rely on multiple habitats during their life cycle.