The Value of Biodiversity in Reserve Selection: Representation, Species Weighting, and Benefit Functions

Abstract:  The limited availability of resources for conservation has led to the development of many quantitative methods for selecting reserves that aim to maximize the biodiversity value of reserve networks. In published analyses, species are often considered equal, although some are in much greater need of protection than others. Furthermore, representation is usually treated as a threshold: a species is either represented or not, but varying levels of representation over or under a given target level are not valued differently. We propose that a higher representation level should also have higher value. We introduce a framework for reserve selection that includes species weights and benefit functions for under- and overrepresentation (number of locations for each species). We applied the method to conservation planning for herb-rich forests in southern Finland. Our use of benefit functions and weighting changed the identity of about 50% of the selected sites at different funding levels and improved the representation of rare and threatened species. We also identified a small area of additional land that would substantially enhance the existing reserve network. We suggest that benefit functions and species weighting should be considered as standard options in reserve-selection applications.     

The Boundary-Quality Penalty: a Quantitative Method for Approximating Species Responses to Fragmentation in Reserve Selection

Abstract:  Aggregation of reserve networks is generally considered desirable for biological and economic reasons: aggregation reduces negative edge effects and facilitates metapopulation dynamics, which plausibly leads to improved persistence of species. Economically, aggregated networks are less expensive to manage than fragmented ones. Therefore, many reserve-design methods use qualitative heuristics, such as distance-based criteria or boundary-length penalties to induce reserve aggregation. We devised a quantitative method that introduces aggregation into reserve networks. We call the method the boundary-quality penalty (BQP) because the biological value of a land unit (grid cell) is penalized when the unit occurs close enough to the edge of a reserve such that a fragmentation or edge effect would reduce population densities in the reserved cell. The BQP can be estimated for any habitat model that includes neighborhood (connectivity) effects, and it can be introduced into reserve selection software in a standardized manner. We used the BQP in a reserve-design case study of the Hunter Valley of southeastern Australia. The BQP resulted in a more highly aggregated reserve network structure. The degree of aggregation required was specified by observed (albeit modeled) biological responses to fragmentation. Estimating the effects of fragmentation on individual species and incorporating estimated effects in the objective function of reserve-selection algorithms is a coherent and defensible way to select aggregated reserves. We implemented the BQP in the context of the Zonation method, but it could as well be implemented into any other spatially explicit reserve-planning framework .     

Sensitivity of Systematic Reserve Selection to Decisions about Scale, Biological Data, and Targets: Case Study from Southern British Columbia

Abstract:  The identification of conservation areas based on systematic reserve-selection algorithms requires decisions related to both spatial and ecological scale. These decisions may affect the distribution and number of sites considered priorities for conservation within a region. We explored the sensitivity of systematic reserve selection by altering values of three essential variables. We used a 1:20,000–scale terrestrial ecosystem map and habitat suitability data for 29 threatened vertebrate species in the Okanagan region of British Columbia, Canada. To these data we applied a reserve-selection algorithm to select conservation sites while altering selection unit size and shape, features of biodiversity (i.e., vertebrate species), and area conservation targets for each biodiversity feature. The spatial similarity, or percentage overlap, of selected sets of conservation sites identified (1) with different selection units was ≤40%, (2) with different biodiversity features was 59%, and (3) with different conservation targets was ≥94%. Because any selected set of sites is only one of many possible sets, we also compared the conservation value (irreplaceability) of all sites in the region for each variation of the data. The correlations of irreplaceability were weak for different selection units (0.23 ≤ r ≤ 0.67), strong for different biodiversity features ( r = 0.84), and mixed for different conservation targets ( r = 0.16; 0.16; 1.00). Because of the low congruence of selected sites and weak correlations of irreplaceability for different selection units, recommendations from studies that have been applied at only one spatial scale must be considered cautiously.     

Where Should Nature Reserves Be Located in South Africa? A Snake's Perspective

The present dispersion of nature reserves in South Africa is the historical result of a series of ad hoc decisions and may not be biologically optimal We have adopted a method to identify the optimal geography of nature reserves for the conservation of South Africa's snake fauna. The method of reserve selection operated on two tiers, and the spatial unit of analysis was a quarter-degree-square cell (∼625 km²). First, two scoring indices were used to rank cells with respect to species richness or to rarity. Second, two different iterative reserve-selection algorithms selected sets of cells (reserves), where each set represented all snake species at least once. Finally, the selected cells were examined for their present level of protection and their ranked scores. Depending on the algorithm chosen, only 23 or 29 cells were required to represent all species at least once; 72–78% of these cells already contained some level of protection; 59–70% of cells fell in areas of high species richness; and 72–91% of cells fell in areas with high rarity scores. Thus we conclude that most of the snake species in South Africa may be adequately protected with only modest acquisition of new reserves, and that the iterative algorithms appear to be efficient at siting cells in areas of high richness and rarity. We recommend that the reserve placement method outlined in this report be applied to as many other taxa as possible in the formulation of a national plan for an optimal reserve system for South Africa.     

Risk-sensitive foraging in common shrews (Sorex araneus L.)

Summary Risk-sensitive foraging theory predicts that predators which face starvation if there is a temporary shortfall in their food supply should choose feeding sites on the basis of variation in as well as mean expected reward rate. For a given mean reward rate they should choose high variance feeding sites (be risk-prone) if they are running below energy requirement, but low variance sites (be risk-averse) if they are running above.Common shrews presented with a choice between constant and variable feeding stations were more likely to visit the variable station when they were running below energy requirement and more likely to visit the constant station when they were running above. However, the tendency towards risk-aversion above requirement was greater than that towards risk-proneness below.When all shrews were considered together, the probability of visiting the variable station correlated negatively and continuously with intake relative to requirement.     

Optimal design of compact and connected nature reserves for multiple species

When designing a conservation reserve system for multiple species, spatial attributes of the reserves must be taken into account at species level. The existing optimal reserve design literature considers either one spatial attribute or when multiple attributes are considered the analysis is restricted only to one species. We built a linear integer programing model that incorporates compactness and connectivity of the landscape reserved for multiple species. The model identifies multiple reserves that each serve a subset of target species with a specified coverage probability threshold to ensure the species' long‐term survival in the reserve, and each target species is covered (protected) with another probability threshold at the reserve system level. We modeled compactness by minimizing the total distance between selected sites and central sites, and we modeled connectivity of a selected site to its designated central site by selecting at least one of its adjacent sites that has a nearer distance to the central site. We considered structural distance and functional distances that incorporated site quality between sites. We tested the model using randomly generated data on 2 species, one ground species that required structural connectivity and the other an avian species that required functional connectivity. We applied the model to 10 bird species listed as endangered by the state of Illinois (U.S.A.). Spatial coherence and selection cost of the reserves differed substantially depending on the weights assigned to these 2 criteria. The model can be used to design a reserve system for multiple species, especially species whose habitats are far apart in which case multiple disjunct but compact and connected reserves are advantageous. The model can be modified to increase or decrease the distance between reserves to reduce or promote population connectivity.     

Sensitivity of Marine-Reserve Design to the Spatial Resolution of Socioeconomic Data

Abstract:  Socioeconomic considerations should have an important place in reserve design. Systematic reserve-selection tools allow simultaneous optimization for ecological objectives while minimizing costs but are seldom used to incorporate socioeconomic costs in the reserve-design process. The sensitivity of this process to biodiversity data resolution has been studied widely but the issue of socioeconomic data resolution has not previously been considered. We therefore designed marine reserves for biodiversity conservation with the constraint of minimizing commercial fishing revenue losses and investigated how economic data resolution affected the results. Incorporating coarse-resolution economic data from official statistics generated reserves that were only marginally less costly to the fishery than those designed with no attempt to minimize economic impacts. An intensive survey yielded fine-resolution data that, when incorporated in the design process, substantially reduced predicted fishery losses. Such an approach could help minimize fisher displacement because the least profitable grounds are selected for the reserve. Other work has shown that low-resolution biodiversity data can lead to underestimation of the conservation value of some sites, and a risk of overlooking the most valuable areas, and we have similarly shown that low-resolution economic data can cause underestimation of the profitability of some sites and a risk of inadvertently including these in the reserve. Detailed socioeconomic data are therefore an essential input for the design of cost-effective reserve networks.     

Conservation of Mammals in Eastern North American Wildlife Reserves: How Small Is Too Small?

Abstract: A common objective of methods of systematic reserve selection has been to maximize conservation benefits—frequently current species richness—while reducing the costs of acquiring and maintaining reserves. But the probability that a reserve will lose species in the future is frequently not known because the minimum area requirements for most species have not been estimated empirically. For reserves within the Alleghenian-Illinoian mammal province of eastern North America, we empirically estimated the minimum area requirement of terrestrial mammals such that reserves should not lose species because of insularization. We compared this estimate to the actual size of 2355 reserves and reserve assemblages within the mammal province. The estimated minimum area requirement was 5037 km² (95% CI: 2700–13,296 km²). Fourteen reserves and reserve assemblages were> 2700 km², 9 were> 5037 km², and 3 were> 13,296 km². These 14 reserves accounted for 73% of the total area of reserves and 10% of the total area of the mammal province. Few reserves appear large enough to avoid loss of some mammal species without the additional cost of active management of habitat or populations. Immigration corridors and buffer zones that combine small reserves into assemblages totaling at least 2700 km² may be the most efficient means of conserving mammals in these reserves.     

Planning for robust reserve networks using uncertainty analysis

Planning land-use for biodiversity conservation frequently involves computer-assisted reserve selection algorithms. Typically such algorithms operate on matrices of species presence–absence in sites, or on species-specific distributions of model predicted probabilities of occurrence in grid cells. There are practically always errors in input data—erroneous species presence–absence data, structural and parametric uncertainty in predictive habitat models, and lack of correspondence between temporal presence and long-run persistence. Despite these uncertainties, typical reserve selection methods proceed as if there is no uncertainty in the data or models. Having two conservation options of apparently equal biological value, one would prefer the option whose value is relatively insensitive to errors in planning inputs. In this work we show how uncertainty analysis for reserve planning can be implemented within a framework of information-gap decision theory, generating reserve designs that are robust to uncertainty. Consideration of uncertainty involves modifications to the typical objective functions used in reserve selection. Search for robust-optimal reserve structures can still be implemented via typical reserve selection optimization techniques, including stepwise heuristics, integer-programming and stochastic global search.     

Dynamic reserve site selection under contagion risk of deforestation

Recently, dynamic reserve site selection models based on stochastic dynamic programming (SDP) have been proposed. The models consider a random development pattern in which the probability that a site will be developed is independent of the development status of other sites. However, development often takes the form of a contagion process in which the sites most likely to be developed are near sites that already have been developed. To consider site selections in such cases, we propose improved algorithms that make use of a graph representation of the sites network. The first formulation is an exact, dynamic programming algorithm, with which theoretical and experimental complexities are evaluated. The exact method can be applied only to small problems (less than 10 sites), but real-world problems may have hundreds or thousands of sites, implying that heuristic selection methods must be used. We provide a general framework for describing such heuristic solution methods, and propose a new heuristic method based on a parameterised reinforcement learning algorithm. The method allows us to compute a heuristic function by performing and exploiting many simulations of the deforestation process. We show that the method can be applied to problems with hundreds of sites, and demonstrate experimentally that it outperforms previously proposed heuristic methods in terms of the average number of species conserved.     

Effects of sampling error and temporal correlations in population growth on process variance estimators

Estimates of a population’s growth rate and process variance from time-series data are often used to calculate risk metrics such as the probability of quasi-extinction, but temporal correlations in the data from sampling error, intrinsic population factors, or environmental conditions can bias process variance estimators and detrimentally affect risk predictions. It has been claimed (McNamara and Harding, Ecol Lett 7:16–20, 2004) that estimates of the long-term variance that incorporate observed temporal correlations in population growth are unaffected by sampling error; however, no estimation procedures were proposed for time-series data. We develop a suite of such long-term variance estimators, and use simulated data with temporally autocorrelated population growth and sampling error to evaluate their performance. In some cases, we get nearly unbiased long-term variance estimates despite ignoring sampling error, but the utility of these estimators is questionable because of large estimation uncertainty and difficulties in estimating correlation structure in practice. Process variance estimators that ignored temporal correlations generally gave more precise estimates of the variability in population growth and of the probability of quasi-extinction. We also found that the estimation of probability of quasi-extinction was greatly improved when quasi-extinction thresholds were set relatively close to population levels. Because of precision concerns, we recommend using simple models for risk estimates despite potential biases, and limiting inference to quantifying relative risk; e.g., changes in risk over time for a single population or comparative risk among populations.     

Avoiding Pitfalls of Using Species Distribution Models in Conservation Planning

Abstract:   Museum records have great potential to provide valuable insights into the vulnerability, historic distribution, and conservation of species, especially when coupled with species-distribution models used to predict species' ranges. Yet, the increasing dependence on species-distribution models in identifying conservation priorities calls for a more critical evaluation of model robustness. We used 11 bird species of conservation concern in Brazil's highly fragmented Atlantic Forest and data on environmental conditions in the region to predict species distributions. These predictions were repeated for five different model types for each of the 11 bird species. We then combined these species distributions for each model separately and applied a reserve-selection algorithm to identify priority sites. We compared the potential outcomes from the reserve selection among the models. Although similarity in identification of conservation reserve networks occurred among models, models differed markedly in geographic scope and flexibility of reserve networks. It is essential for planners to evaluate the conservation implications of false-positive and false-negative errors for their specific management scenario before beginning the modeling process. Reserve networks selected by models that minimized false-positive errors provided a better match with priority areas identified by specialists. Thus, we urge caution in the use of models that overestimate species' occurrences because they may misdirect conservation action. Our approach further demonstrates the great potential value of museum records to biodiversity studies and the utility of species-distribution models to conservation decision-making. Our results also demonstrate, however, that these models must be applied critically and cautiously.     

Effectiveness of Vegetation Surrogates for Parasitoid Wasps in Reserve Selection

Abstract:  Selecting suitable nature reserves is a continuing challenge in conservation, particularly for target groups that are time-consuming to survey, species rich, and extinction prone. One such group is the parasitoid Hymenoptera, which have been excluded from conservation planning. If basic characteristics of habitats or vegetation could be used as reliable surrogates of specific target taxa, this would greatly facilitate appropriate reserve selection. We identified a range of potential habitat indicators of the species richness of pimpline parasitoid communities (Hymenoptera: Ichneumonidae: Pimplinae, Diacritinae, Poemeniinae) and tested their efficiency at capturing the observed diversity in a group of small woodlands in the agricultural landscape of the Vale of York (United Kingdom). Eight of the 18 vegetation-based reserve-selection strategies were significantly better at parasitoid species inclusion than random selection of areas. The best strategy maximized richness of tree species over the entire reserve network through complementarity. This strategy omitted only 2–3 species more (out of 38 captured in the landscape as a whole) than selections derived from the parasitoid survey data. In general, strategies worked equally well at capturing species richness and rarity. Our results suggest that vegetation data as a surrogate for species richness could prove an informative tool in parasitoid conservation, but further work is needed to test how broadly applicable these indicators may be.     

Edge-Core Effects and the Effectiveness of Traditional Reserves in Conservation: Eurasian Badgers in Doñana National Park

Abstract: High rates of human-mediated mortality on animals are frequently reported inside protected areas, especially near their borders, so the overall effect of reserves on animal conservation is not usually known. To determine the effect of a traditional reserve (Doñana National Park, southwestern Spain) on the Eurasian badger (   Meles meles ), a medium sized carnivore, we studied mortality causes and rates, with the aid of radiotelemetry, in two populations inside the reserve, one closer to the border than the other. Human-related mortality ( poaching and road kills) was by far the most common cause of mortality (85% of deaths recorded). The average annual mortality rate due to poaching was high (0.48 ± 0.08) for the population close to the border of the park, whereas none of the radiomarked badgers in the core of the reserve died during the study period. A logistic model that included distance from the border of the park, sampling effort, and the local area (i.e., edge and core populations) indicated that the difference between both sites was due to the effect of distance from the border on survival probability. On a regional scale, badger density at the core of the park was 3.16 times higher than outside. Overall, the effect of the reserve was positive, but edge effects reduced reserve effectiveness by 36%. Edge effects in close proximity of the border were strong, reducing badger density even below the expected density outside the reserve. Edge effects should be considered carefully when reserves are implemented because they can greatly reduce reserve effectiveness and influence the viability of the populations inside. Enlargement of reserves and control of human activities that promote edge effects, both inside and outside the reserve, are the two management actions that can most effectively mitigate edge effects.     

Representativeness and Efficiency of Bird and Insect Conservation in Norwegian Boreal Forest Reserves

I quantified local species richness of birds in different forest types and of beetles in spruce forests at different altitudes. In both cases I quantified timber production as a measure of land acquisition cost and used the ratio between the species richness and timber production as a measure of conservation cost-efficiency. I found a positive correlation between timber production and local species richness of birds as well as beetles, indicating that the forests most valuable for forestry are also the ones most valuable for biodiversity conservation. I used different selection procedures for combining sites in a reserve network to find the minimum set of sites that included all vulnerable species. The minimum set of sites for birds was 30% spruce forest, 30% pine forest, and 40% broad-leaved forest (the three main forest types). The minimum set of sites for the beetles was uniformly distributed along the altitudinal gradient. Both minimum sets were most cost-efficient for species conservation. I suggest that equal coverage of different productivity classes is more efficient for optimizing biodiversity conservation than over-representing low productivity sites. Less than 1% of Norwegian boreal forests have been protected as nature reserves. The reserve network is fairly representative with respect to altitude, but it is seriously skewed toward low productivity sites. The current network is suboptimal with respect to forest type representativeness, species protection, and cost-efficiency. This is a result of an inefficient strategy of selecting reserve sites and an unfortunate combination of selection criteria.     

Effect of risk aversion on prioritizing conservation projects

Conservation outcomes are uncertain. Agencies making decisions about what threat mitigation actions to take to save which species frequently face the dilemma of whether to invest in actions with high probability of success and guaranteed benefits or to choose projects with a greater risk of failure that might provide higher benefits if they succeed. The answer to this dilemma lies in the decision maker's aversion to risk—their unwillingness to accept uncertain outcomes. Little guidance exists on how risk preferences affect conservation investment priorities. Using a prioritization approach based on cost effectiveness, we compared 2 approaches: a conservative probability threshold approach that excludes investment in projects with a risk of management failure greater than a fixed level, and a variance‐discounting heuristic used in economics that explicitly accounts for risk tolerance and the probabilities of management success and failure. We applied both approaches to prioritizing projects for 700 of New Zealand's threatened species across 8303 management actions. Both decision makers’ risk tolerance and our choice of approach to dealing with risk preferences drove the prioritization solution (i.e., the species selected for management). Use of a probability threshold minimized uncertainty, but more expensive projects were selected than with variance discounting, which maximized expected benefits by selecting the management of species with higher extinction risk and higher conservation value. Explicitly incorporating risk preferences within the decision making process reduced the number of species expected to be safe from extinction because lower risk tolerance resulted in more species being excluded from management, but the approach allowed decision makers to choose a level of acceptable risk that fit with their ability to accommodate failure. We argue for transparency in risk tolerance and recommend that decision makers accept risk in an adaptive management framework to maximize benefits and avoid potential extinctions due to inefficient allocation of limited resources. El Efecto de la Aversión de Riesgo sobre la Priorización de Proyectos de Conservación     

Area-Based Refinement for Selection of Reserve Sites with the Benefit-Function Approach

Abstract:  Optimization of resource use is necessary for efficient conservation planning. Many reserve-selection algorithms aim to identify representative but inexpensive networks, which may lead to selecting small sites due to their lower costs and collectively higher species richness. Nevertheless, larger sites would be preferable regarding species' long-term persistence. An area-based refinement can be used to overcome this problem. We used a reserve-planning framework in which continuous benefit functions valued representation (numbers of populations), and differential species weights were based on a species' local rarity and threatened status. We introduced a refinement based on the species-area relationship that provides relatively higher values for larger sites. We applied the proposed method to rich fen vegetation in southern Finland. The species-area refinement resulted in a network of significantly larger sites with minor trade-offs with representation (numbers of populations). Giving endangered species higher weights ensured that the trade-off occurred mostly between site size and representation of low-priority species. We recommend using a species-area refinement for practical, maximum-coverage conservation planning.     

Predicting the Probability of Outbreeding Depression

Abstract: Fragmentation of animal and plant populations typically leads to genetic erosion and increased probability of extirpation. Although these effects can usually be reversed by re‐establishing gene flow between population fragments, managers sometimes fail to do so due to fears of outbreeding depression (OD). Rapid development of OD is due primarily to adaptive differentiation from selection or fixation of chromosomal variants. Fixed chromosomal variants can be detected empirically. We used an extended form of the breeders’ equation to predict the probability of OD due to adaptive differentiation between recently isolated population fragments as a function of intensity of selection, genetic diversity, effective population sizes, and generations of isolation. Empirical data indicated that populations in similar environments had not developed OD even after thousands of generations of isolation. To predict the probability of OD, we developed a decision tree that was based on the four variables from the breeders’ equation, taxonomic status, and gene flow within the last 500 years. The predicted probability of OD in crosses between two populations is elevated when the populations have at least one of the following characteristics: are distinct species, have fixed chromosomal differences, exchanged no genes in the last 500 years, or inhabit different environments. Conversely, the predicted probability of OD in crosses between two populations of the same species is low for populations with the same karyotype, isolated for <500 years, and that occupy similar environments. In the former case, we recommend crossing be avoided or tried on a limited, experimental basis. In the latter case, crossing can be carried out with low probability of OD. We used crosses with known results to test the decision tree and found that it correctly identified cases where OD occurred. Current concerns about OD in recently fragmented populations are almost certainly excessive.     

Planning for persistence in marine reserves: a question of catastrophic importance.

Large-scale catastrophic events, although rare, lie generally beyond the control of local management and can prevent marine reserves from achieving biodiversity outcomes. We formulate a new conservation planning problem that aims to minimize the probability of missing conservation targets as a result of catastrophic events. To illustrate this approach we formulate and solve the problem of minimizing the impact of large-scale coral bleaching events on a reserve system for the Great Barrier Reef, Australia. We show that by considering the threat of catastrophic events as part of the reserve design problem it is possible to substantially improve the likely persistence of conservation features within reserve networks for a negligible increase in cost. In the case of the Great Barrier Reef, a 2% increase in overall reserve cost was enough to improve the long-run performance of our reserve network by >60%. Our results also demonstrate that simply aiming to protect the reefs at lowest risk of catastrophic bleaching does not necessarily lead to the best conservation outcomes, and enormous gains in overall persistence can be made by removing the requirement to represent all bioregions in the reserve network. We provide an explicit and well-defined method that allows the probability of catastrophic disturbances to be included in the site selection problem without creating additional conservation targets or imposing arbitrary presence/absence thresholds on existing data. This research has implications for reserve design in a changing climate.