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.     

Landscape Zonation, benefit functions and target-based planning: Unifying reserve selection strategies

The most widespread reserve selection strategy is target-based planning, as specified under the framework of systematic conservation planning. Targets are given for the representation levels of biodiversity features, and site selection algorithms are employed to either meet the targets with least cost (the minimum set formulation) or to maximize the number of targets met with a given resource (maximum coverage). Benefit functions are another recent approach to reserve selection. In the benefit function framework the objective is to maximize the value of the reserve network, however value is defined. In one benefit function formulation value is a sum over species-specific values, and species-specific value is an increasing function of representation. This benefit function approach is computationally convenient, but because it allows free tradeoffs between species, it essentially makes the assumption that species are acting as surrogates, or samples from a larger regional species pool. The Zonation algorithm is a recent computational method that produces a hierarchy of conservation priority through the landscape. This hierarchy is produced via iterative removal of selection units (cells) using the criterion of least marginal loss of conservation value to decide which cell to remove next. The first variant of Zonation, here called core-area Zonation, has a characteristic of emphasizing core-areas of all species. Here I separate the Zonation meta-algorithm from the cell removal rule, the definition of marginal loss of conservation value utilized inside the algorithm. I show how additive benefit functions and target-based planning can be implemented into the Zonation framework via the use of particular kinds of cell removal rules. The core-area, additive benefit function and targeting benefit function variants of Zonation have interesting conceptual differences in how they treat and trade off between species in the planning process.     

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.     

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.     

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.     

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 connectivity into reserve selection procedures

Methods for selecting sites to be included in reserve networks generally neglect the spatial location of sites, often resulting in highly fragmented networks. This restricts the possibility of dispersal between sites, which for many species may be essential for long-term persistence. Here I describe iterative reserve selection algorithms which incorporate considerations of reserve connectivity and evaluate their performance using a data set for macroinvertebrates in ponds. Methods where spatial criteria were only invoked when ties between sites occurred did not perform significantly better than a simple greedy algorithm in terms of reserve connectivity. An algorithm based on a composite measure of species added and changes in reserve connectivity produced a reserve network with higher connectivity, but needed more sites to represent all species. A trade-off between connectivity and efficiency may be inevitable, but the costs in terms of efficiency may be justified if long-term persistence of species is more likely.     

Two paths to a suboptimal solution - once more about optimality in reserve selection

Several studies have compared the performances of exact algorithms (integer programming) and heuristic methods in the solution of conservation resource allocation problems, with the conclusion that exact methods are always preferable. Here, I summarize a potentially major deficiency in how the relationship between exact and heuristic methods has been presented: the above comparisons have all been done using relatively simple (linear) maximum coverage or minimum set models that are by definition solvable using integer programming. In contrast, heuristic or meta-heuristic algorithms can be applied to less simplified nonlinear and/or stochastic problems. The focus of this study is two kinds of suboptimality, first-stage suboptimality caused by model simplification and second-stage suboptimality caused by inexact solution. Evidence from comparisons between integer programming and heuristic solution methods suggests a suboptimality level of around 3%-10% for well-chosen heuristics, much depending on the problem and data. There is also largely anecdotal evidence from a few studies that have evaluated results from simplified conservation resource allocation problems using more complicated (nonlinear) models. These studies have found that dropping components such as habitat loss rates or connectivity effects from the model can lead to suboptimality from 5% to 50%. Consequently, I suggest that more attention should be given to two topics, first, how the performance of a conservation plan should be evaluated, and second, what are the consequences of simplifying the ideal conservation resource allocation model? Factors that may lead to relatively complicated problem formulations include connectivity and evaluation of long-term persistence, stochastic habitat loss and availability, species interactions, and distributions that shift due to climate change.     

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.     

Connectivity of reef fish between mangroves and coral reefs: Algorithms for the design of marine reserves at seascape scales

Many species of coral reef fish undertake ontogenetic migrations between seagrass beds, mangroves, and coral reefs. A recent study from the Caribbean found that the availability of mangrove nursery habitat had a striking impact on the community structure and biomass of reef fish in their adult, coral reef habitat. The biomass of several species more than doubled when the reefs were connected to rich mangrove resources (defined as having at least 70 km of fringing Rhizophora mangle within a region of 200 km²). Here, the results of this large-scale empirical study are translated into a series of algorithms for use in natural resource management planning. Four algorithms are described that identify (i) the relative importance of mangrove nursery sites, (ii) the connectivity of individual reefs to mangrove nurseries, (iii) areas of nursery habitat that have an unusually large importance to specific reefs, and (iv) priority sites for mangrove reforestation projects. The algorithms generate a connectivity matrix among mangroves and coral reefs that facilitates the identification of connected corridors of habitats within a dynamic planning environment (e.g., reserve selection algorithms).     

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.     

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.     

Temporary conservation for urban biodiversity

Urban habitats, particularly wastelands and brownfields, maintain rich biodiversity and offer habitat for many species, even rare and endangered taxa. However, such habitats are also under socio-economic pressures due to redevelopment for housing and industrial uses. In order to maintain urban biodiversity, it is currently unknown how much open area must be preserved and whether conservation is possible without complete exclusion from economic development. In this study, we applied a simulation model based on species distribution models for plants, grasshoppers, and leafhoppers to investigate planning options for urban conservation with special focus on business areas. Altogether, we modelled the occurrence of 81 species of the urban species pool and analysed settings of different proportions of open sites, different habitat turnover times, and different lot sizes. Our simulations demonstrated that dynamic land use supports urban biodiversity in terms of species richness and rarity. Setting aside brownfields before redevelopment for a period of on average 15 years supported the highest conservation value. Consequently, we recommend integrating the concept of ‘temporary conservation’ into urban planning for industrial and business areas. This concept requires habitat to be destroyed by redeveloping brownfield sites to built-up sites, but simultaneously creating new open spaces due to abandonment of urban land uses at other locations. This maintains a spatio-temporal mosaic of different successional stages ranging from pioneer to pre-forest communities.     

Optimizing reserve expansion for disjunct populations of San Joaquin kit fox

Expanding habitat protection is a common strategy for species conservation. We present a model to optimize the expansion of reserves for disjunct populations of an endangered species. The objective is to maximize the expected number of surviving populations subject to budget and habitat constraints. The model accounts for benefits of reserve expansion in terms of likelihood of persistence of each population and monetary cost. Solving the model with incrementally higher budgets helps prioritize sites for expansion and produces a cost curve showing funds required for incremental increases in the objective. We applied the model to the problem of allocating funds among eight reserves for the endangered San Joaquin kit fox (Vulpes macrotis mutica) in California, USA. The priorities for reserve expansion were related to land cost and amount of already-protected habitat at each site. Western Kern and Ciervo-Panoche sites received highest priority because land costs were low and moderate amounts of already-protected habitat resulted in large reductions in extinction risk for small increments of habitat protection. The sensitivity analysis focused on the impacts of kit fox reproductive success and home range in non-native grassland sites. If grassland habitat is lower quality than brushland habitat resulting in higher annual variation in reproductive success or larger home ranges, then protecting habitat at the best grassland site (Ciervo-Panoche) is not cost-efficient relative to shrubland sites (Western Kern, Antelope Plain, Carrizo Plain). Finally, results suggested that lowest priority should be given to three relatively high-cost grassland sites (Camp Roberts, Contra Costa, and Western Madera) because protecting habitat at those sites would be expensive and have little effect on the expected number of surviving kit fox populations.     

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.     

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.     

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.     

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.     

Pre-emptive conservation versus “fire-fighting”: A decision theoretic approach

How can conservation planners optimally and effectively allocate limited resources between imminently threatened and presently secure areas? Such choices must be made at multiple spatial scales involving a variety of conservation targets. Allocation strategies range from a “fire-fighting” approach, which gives priority to heavily developed areas at high risk of further habitat loss, to a “pre-emptive” approach giving priority to intact habitat tracts before they become threatened. We determined optimal dynamic reserve selection strategies when selections are made in imminently threatened and presently secure areas that will become threatened at uncertain times in the future. The objective was to maximize the expected number of endemic species conserved, predicted with species-area curves. The model was solved for three forms of species-area curve proposed in theoretical studies of habitat loss. Alternative scenarios were considered on the relationship between land prices and development risk. For the most commonly proposed form of the species-area relationship, the fire-fighting approach is optimal even if land prices rise substantially when presently secure areas become threatened. This reflects the assumption that species decline accelerates only after a large proportion of original habitat has been lost. The possibility of large species losses at lower levels of habitat loss justifies at least some pre-emptive conservation, even if land prices are not correlated with threat. If species decline is proportional with habitat loss, the optimal conservation strategy depends strongly on land price dynamics.