Using probability of persistence to identify important areas for biodiversity conservation

Using species distribution modeling to generate relative abundance information in socio-politically unstable territories: Conservation of Felidae in the central-western region of Mexico

The distribution range and population abundance of species provide fundamental information on the species-habitat relationship required for management and conservation. Abundance inherently provides more information about the ecology of species than do occurrence data. However, information on abundance is scarce for most species, mainly at large spatial scales. The objective of this work was, therefore, to provide information regarding the population status of six wild felids inhabiting territories in Mexico that are inaccessible or politically unstable. This was done using species distribution models derived from occurrence data. We used distribution data at a continental scale for the wild felids inhabiting Mexico: jaguar (Panthera onca), bobcat (Lynx rufus), ocelot (Leopardus pardalis), cougar (Puma concolor), margay (Leopardus wiedii), and jaguarundi (Herpailurus yagouaroundi) to predict environmental suitability (estimated by both Maxent and the distance to niche centroid, DNC). Suitability was then examined by relating to a capture rate-based index, in a well-monitored area in central western Mexico in order to assess their performance as proxies of relative abundance. Our results indicate that the environmental suitability patterns predicted by both algorithms were comparable. However, the strength of the relationship between the suitability and relative abundance of local populations differed across species and between algorithms, with the bobcat and DNC, respectively, having the best fit, although the relationship was not consistent in all the models. This paper presents the potential of implementing species distribution models in order to predict the relative abundance of wild felids in Mexico and offers guidance for the proper interpretation of the relationship between suitability and population abundance. The results obtained provide a robust information base on which to outline specific conservation actions and on which to examine the potential status of endangered species inhabiting remote or politically unstable territories in which on-field monitoring programs are not feasible.

Potential for invasion of traded birds under climate and land-cover change

Humans have moved species away from their native ranges since the Neolithic, but globalization accelerated the rate at which species are being moved. We fitted more than half million distribution models for 610 traded bird species on the CITES list to examine the separate and joint effects of global climate and land-cover change on their potential end-of-century distributions. We found that climate-induced suitability for modelled invasive species increases with latitude, because traded birds are mainly of tropical origin and much of the temperate region is 'tropicalizing.' Conversely, the tropics are becoming more arid, thus limiting the potential from cross-continental invasion by tropical species. This trend is compounded by forest loss around the tropics since most traded birds are forest dwellers. In contrast, net gains in forest area across the temperate region could compound climate change effects and increase the potential for colonization of low-latitude birds. Climate change has always led to regional redistributions of species, but the combination of human transportation, climate, and land-cover changes will likely accelerate the redistribution of species globally, increasing chances of alien species successfully invading non-native lands. Such process of biodiversity homogenization can lead to emergence of non-analogue communities with unknown environmental and socioeconomic consequences.

Roost sites of chimney swift (Chaetura pelagica) form large-scale spatial networks

Several biodiversity-centered metrics exist to quantify the importance of landscape and habitat features for conservation efforts. However, for species whose habitat use is not quantified by these metrics, such as those in urban areas, we need a method to best identify features for targeted conservation efforts. We investigated the use of social network analysis (SNA) to identify and quantify these critical habitat features. We used SNA to identify network existence in chimney swift (Chaetura pelagica) roost usage, quantify the importance of each roost site, and evaluate the impact of the loss of key sites. We identified a network consisting of ten chimney swift roosts in southern Nova Scotia, Canada, and found that 76% of swifts used more than one roost throughout the breeding season. We also isolated three key (most connected) roost sites. We evaluated the effect of loss of these key sites on the network by using a Wilcoxon-Pratt signed-rank test and by analyzing the structure of the subsequent network. We found that connections between roosts and the structure of the network were significantly affected by the loss of these key sites. Our results show that SNA is a valuable tool that can identify key sites for targeted conservation efforts for species that may not be included in conservation efforts focused purely on biodiversity.

Connecting science, policy, and implementation for landscape-scale habitat connectivity

We examined the links between the science and policy of habitat corridors to better understand how corridors can be implemented effectively. As a case study, we focused on a suite of landscape-scale connectivity plans in tropical and subtropical Asia (Malaysia, Singapore, and Bhutan). The process of corridor designation may be more efficient if the scientific determination of optimal corridor locations and arrangement is synchronized in time with political buy-in and establishment of policies to create corridors. Land tenure and the intactness of existing habitat in the region are also important to consider because optimal connectivity strategies may be very different if there are few, versus many, political jurisdictions (including commercial and traditional land tenures) and intact versus degraded habitat between patches. Novel financing mechanisms for corridors include bed taxes, payments for ecosystem services, and strategic forest certifications. Gaps in knowledge of effective corridor design include an understanding of how corridors, particularly those managed by local communities, can be protected from degradation and unsustainable hunting. There is a critical need for quantitative, data-driven models that can be used to prioritize potential corridors or multicorridor networks based on their relative contributions to long-term metacommunity persistence.

Choice of biodiversity index drives optimal fire management decisions

Preservation of biodiversity is a central goal of conservation management, yet the conditions that promote persistence may differ for the species in the community. For systems subject to stochastic disturbances such as fire, understanding which management practices promote persistence for all species in a community is complex. Before deciding on the best course of action, an objective must be specified. Yet an overarching goal of species persistence can be specified into a measureable objective many different ways. We investigated four alternative management objectives for maximizing species persistence that use common biodiversity indices: (1) attaining the minimally acceptable mix of successional vegetation states to support species' relative abundances, (2) maximizing the arithmetic mean abundance of species, (3) maximizing the geometric mean abundance of species, and (4) minimizing the average extinction risk of species. We used stochastic dynamic programming to model successional changes in vegetation in the presence of both planned and unplanned fires, and utilize an extensive data set on the occurrence of birds, reptiles, and small mammals in different successional states in semiarid Australia. We investigated the influence the choice of objective function and taxonomic focus has on the optimal fire management recommendations. We also evaluated a recent hazard reduction policy to annually burn a fixed amount of the landscape and compare results to the optimal solution. The optimal management strategy to maximize species persistence over a 100-year period is predominantly to minimize wildfires. This is because the majority of species are more likely to occur in intermediate, and late successional vegetation. However the optimal solution showed sensitivity to the objective and the species included in the analysis. These results highlight the need for careful consideration when specifying an objective to represent overarching conservation goals. Using the extinction risk objective, we show that a policy to annually burn 5% of the landscape could increase the average probability of extinction for the modelled species by 7% over the next 100 years compared to the optimal management scenario.

Core concepts of spatial prioritisation in systematic conservation planning

Systematic conservation planning (SCP) is a field of conservation biology concerned with delivering on-the-ground actions that achieve conservation goals. It describes a set of operational models that cover both design and implementation of conservation, with a strong focus on mobilising the collective action typically required to implement conservation. SCP, as it was originally described, was composed of six different stages: collection of data, identification of conservation goals, evaluation of the existing protected area network, design of expansions, implementation of conservation action, and long-term maintenance of biodiversity in the network. Since then, the operational model has been expanded into several different variants. Conservation actions applied inside SCP include establishment and expansion of reserve networks and allocation of habitat restoration and management.

Within the broader context of SCP, there is a fundamental biogeographic-economic analysis frequently called spatial conservation prioritisation or conservation assessment, which is used for identifying where important areas for biodiversity are and how conservation goals might be achieved efficiently. Here, we review the usage and meaning of the 12 biogeographic-economic core concepts of SCP: adequacy, complementarity, comprehensiveness, effectiveness, efficiency, flexibility, irreplaceability, replacement cost, representation, representativeness, threat, and vulnerability. Some of the concepts have clear definitions whereas others may have alternative and possibly conflicting definitions. With a comprehensive literature review literature, we elucidate the historical backgrounds of these concepts, the first definitions and usages, alternative later definitions, key applications, and prior reviews. This review reduces linguistic uncertainty in the application of SCP. Since SCP is a global activity with a multitude of different stakeholders involved, it is vital that those involved can speak the same language. Through these concepts, this review serves as a source of information about the historical development of SCP. It provides a comprehensive review for anyone wishing to understand the key concepts of spatial prioritisation within SCP.

Do private conservation activities match science-based conservation priorities?

Background

Private land conservation is an essential strategy for biodiversity protection in the USA, where half of the federally listed species have at least 80% of their habitat on private lands. We investigated the alignment between private land protection conducted by the world's largest land trust (The Nature Conservancy) and the science driven identification of priority areas for conservation. This represents the first quantitative assessment of the influence of defining priority areas on the land acquisitions of a conservation non-governmental organization (NGO).

Methodology/Principal Findings

The lands acquired by The Nature Conservancy (TNC) were analyzed using GIS to determine to what extent they were in areas defined as priorities for conservation. The spatial analysis of TNC lands was broken up into land known to be acquired in the last five years, five to ten years ago, prior to ten years ago, and anytime during the last sixty years (including previous sets of data plus acquisitions lacking a date). For the entire history of TNC the proportion of TNC lands within the priority areas was 74%. Prior to 10 years ago it was 80%, 5–10 years ago it was 76%, and in the last five years it was 81%. Conservation easements were found to have lower alignment with priority areas (64%) than outright fee simple acquisitions (86%).

Conclusions/Significance

Overall the location of lands acquired was found to be well aligned with the priority areas. Since there was comparable alignment in lands acquired before and after formalized conservation planning had been implemented as a standard operating procedure, this analysis did not find evidence that defining priority areas has influenced land acquisition decisions.

Utility of measuring abundance versus consistent occupancy in predicting biodiversity persistence

The primary goals of reserve selection are to represent all chosen units of biodiversity and to ensure their long-term persistence while minimizing costs. We considered two simple proxies of species persistence: a time series of point-count data to calculate abundance and a time series of presence-absence data to calculate permanence (a measure of consistent occupancy over time). Using two 10-year intervals of data from the North American Breeding Bird Survey, we compared the performance of each measure at predicting persistence 18 years later. For nonrare species, abundance and permanence predicted persistence similarly well. We performed complementarity-based reserve selections with data on species abundance and permanence (from 1970 to 1979) and then evaluated the effectiveness of the reserve networks at maintaining species populations and efficiency in land use (data from 1997 to 2006). Abundance proved a better predictor of future local persistence than permanence, which justifies the relatively larger financial and temporal costs of collecting a time series of point-count data to estimate abundance. If future extinction events were used as a measure of reserve-network effectiveness, the performance of abundance and permanence did not differ markedly. Nevertheless, when future abundance, which is a more sensitive measure of network effectiveness, was used, abundance was significantly better than permanence at selecting longer-term, high-quality, species-specific habitat but required larger reserves to do so.

Incorporating ecological and evolutionary processes into continental-scale conservation planning

Systematic conservation planning research has focused on designing systems of conservation areas that efficiently protect a comprehensive and representative set of species and habitats. Recently, there has been an emphasis on improving the adequacy of conservation area design to promote the persistence and future generation of biodiversity. Few studies have explored incorporating ecological and evolutionary processes into conservation planning assessments. Biodiversity in Australia is maintained and generated by numerous ecological and evolutionary processes at various spatial and temporal scales. We accommodated ecological and evolutionary processes in four ways: (1) using sub-catchments as planning units to facilitate the protection of the integrity and function of ecosystem processes occurring on a sub-catchment scale; (2) targeting one type of ecological refugia, drought refugia, which are critical for the persistence of many species during widespread drought; (3) targeting one type of evolutionary refugia which are important for maintaining and generating unique biota during long-term climatic changes; and (4) preferentially grouping priority areas along vegetated waterways to account for the importance of connected waterways and associated riparian areas in maintaining processes. We identified drought refugia, areas of relatively high and regular herbage production in arid and semiarid Australia, from estimates of gross primary productivity derived from satellite data. In this paper, we combined the novel incorporation of these processes with a more traditional framework of efficiently representing a comprehensive sample of biodiversity to identify spatial priorities across Australia. We explored the trade-offs between economic costs, representation targets, and connectivity. Priority areas that considered ecological and evolutionary processes were more connected along vegetated waterways and were identified for a small increase in economic cost. Priority areas for conservation investment are more likely to have long-term benefits to biodiversity if ecological and evolutionary processes are considered in their identification.

Predicting metapopulation lifetime from macroscopic network properties

This paper presents a comparatively simple approximation formula for the mean life time of a metapopulation in a habitat network where habitat patch arrangement may be irregular and patch sizes differ. It is based on previous work on the development of an analytical approximation formula by Frank and Wissel [K. Frank, C. Wissel, A formula for the mean lifetime of metapopulations in heterogeneous landscapes, Am. Nat. 159 (2002) 530] and extends it by abstracting from individual patch locations. The mean metapopulation lifetime is expressed as a function of four macroscopic network properties: the ratio of dispersal range and network size, the ratio of range of environmental correlation and network size, and the total number and (geometric mean) size of the patches. The analysis takes into account that (ceteris paribus) patches close to the boundary of the habitat network contribute less to metapopulation survival than patches close to the centre of the network. Ignoring this fact can lead to a substantial overestimation of the mean metapopulation lifetime. Due to its numerical simplicity, the formula can be used as a conservation objective function even in complex network design problems where the number of patches to be allocated is very large. Numerical tests of the formula show that it performs very well within a wide range of network structures.

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.

Optimal conservation of migratory species

BACKGROUND

Migratory animals comprise a significant portion of biodiversity worldwide with annual investment for their conservation exceeding several billion dollars. Designing effective conservation plans presents enormous challenges. Migratory species are influenced by multiple events across land and sea-regions that are often separated by thousands of kilometres and span international borders. To date, conservation strategies for migratory species fail to take into account how migratory animals are spatially connected between different periods of the annual cycle (i.e. migratory connectivity) bringing into question the utility and efficiency of current conservation efforts.

METHODOLOGY/PRINCIPAL FINDINGS

Here, we report the first framework for determining an optimal conservation strategy for a migratory species. Employing a decision theoretic approach using dynamic optimization, we address the problem of how to allocate resources for habitat conservation for a Neotropical-Nearctic migratory bird, the American redstart Setophaga ruticilla, whose winter habitat is under threat. Our first conservation strategy used the acquisition of winter habitat based on land cost, relative bird density, and the rate of habitat loss to maximize the abundance of birds on the wintering grounds. Our second strategy maximized bird abundance across the entire range of the species by adding the constraint of maintaining a minimum percentage of birds within each breeding region in North America using information on migratory connectivity as estimated from stable-hydrogen isotopes in feathers. We show that failure to take into account migratory connectivity may doom some regional populations to extinction, whereas including information on migratory connectivity results in the protection of the species across its entire range.

CONCLUSIONS/SIGNIFICANCE

We demonstrate that conservation strategies for migratory animals depend critically upon two factors: knowledge of migratory connectivity and the correct statement of the conservation problem. Our framework can be used to identify efficient conservation strategies for migratory taxa worldwide, including insects, birds, mammals, and marine organisms.

Uncertainty analysis for regional-scale reserve selection

Methods for reserve selection and conservation planning often ignore uncertainty. For example, presence-absence observations and predictions of habitat models are used as inputs but commonly assumed to be without error. We applied information-gap decision theory to develop uncertainty analysis methods for reserve selection. Our proposed method seeks a solution that is robust in achieving a given conservation target, despite uncertainty in the data. We maximized robustness in reserve selection through a novel method, "distribution discounting," in which the site- and species-specific measure of conservation value (related to species-specific occupancy probabilities) was penalized by an error measure (in our study, related to accuracy of statistical prediction). Because distribution discounting can be implemented as a modification of input files, it is a computationally efficient solution for implementing uncertainty analysis into reserve selection. Thus, the method is particularly useful for high-dimensional decision problems characteristic of regional conservation assessment. We implemented distribution discounting in the zonation reserve-selection algorithm that produces a hierarchy of conservation priorities throughout the landscape. We applied it to reserve selection for seven priority fauna in a landscape in New South Wales, Australia. The distribution discounting method can be easily adapted for use with different kinds of data (e.g., probability of occurrence or abundance) and different landscape descriptions (grid or patch based) and incorporated into other reserve-selection algorithms and software.

Tradeoffs of different types of species occurrence data for use in systematic conservation planning

Data on the occurrence of species are widely used to inform the design of reserve networks. These data contain commission errors (when a species is mistakenly thought to be present) and omission errors (when a species is mistakenly thought to be absent), and the rates of the two types of error are inversely related. Point locality data can minimize commission errors, but those obtained from museum collections are generally sparse, suffer from substantial spatial bias and contain large omission errors. Geographic ranges generate large commission errors because they assume homogenous species distributions. Predicted distribution data make explicit inferences on species occurrence and their commission and omission errors depend on model structure, on the omission of variables that determine species distribution and on data resolution. Omission errors lead to identifying networks of areas for conservation action that are smaller than required and centred on known species occurrences, thus affecting the comprehensiveness, representativeness and efficiency of selected areas. Commission errors lead to selecting areas not relevant to conservation, thus affecting the representativeness and adequacy of reserve networks. Conservation plans should include an estimation of commission and omission errors in underlying species data and explicitly use this information to influence conservation planning outcomes.

A new method for conservation planning for the persistence of multiple species

Although the aim of conservation planning is the persistence of biodiversity, current methods trade-off ecological realism at a species level in favour of including multiple species and landscape features. For conservation planning to be relevant, the impact of landscape configuration on population processes and the viability of species needs to be considered. We present a novel method for selecting reserve systems that maximize persistence across multiple species, subject to a conservation budget. We use a spatially explicit metapopulation model to estimate extinction risk, a function of the ecology of the species and the amount, quality and configuration of habitat. We compare our new method with more traditional, area-based reserve selection methods, using a ten-species case study, and find that the expected loss of species is reduced 20-fold. Unlike previous methods, we avoid designating arbitrary weightings between reserve size and configuration; rather, our method is based on population processes and is grounded in ecological theory.

Rediscovering the species in community-wide predictive modeling

Broadening the scope of conservation efforts to protect entire communities provides several advantages over the current species-specific focus, yet ecologists have been hampered by the fact that predictive modeling of multiple species is not directly amenable to traditional statistical approaches. Perhaps the greatest hurdle in community-wide modeling is that communities are composed of both co-occurring groups of species and species arranged independently along environmental gradients. Therefore, commonly used "short-cut" methods such as the modeling of so-called "assemblage types" are problematic. Our study demonstrates the utility of a multiresponse artificial neural network (MANN) to model entire community membership in an integrative yet species-specific manner. We compare MANN to two traditional approaches used to predict community composition: (1) a species-by-species approach using logistic regression analysis (LOG) and (2) a "classification-then-modeling" approach in which sites are classified into assemblage "types" (here we used two-way indicator species analysis and multiple discriminant analysis [MDA]). For freshwater fish assemblages of the North Island, New Zealand, we found that the MANN outperformed all other methods for predicting community composition based on multiscaled descriptors of the environment. The simple-matching coefficient comparing predicted and actual species composition was, on average, greatest for the MANN (91%), followed by MDA (85%), and LOG (83%). Mean Jaccard's similarity (emphasizing model performance for predicting species' presence) for the MANN (66%) exceeded both LOG (47%) and MDA (46%). The MANN also correctly predicted community composition (i.e., a significant proportion of the species membership based on a randomization procedure) for 82% of the study sites compared to 54% (MDA) and 49% (LOG), resulting in the MANN correctly predicting community composition in a total of 311 sites and an additional 117 sites (n = 379), on average, compared to LOG and MDA. The MANN also provided valuable explanatory power by simultaneously quantifying the nature of the relationships between the environment and both individual species and the entire community (composition and richness), which is not readily available from traditional approaches. We discuss how the MANN approach provides a powerful quantitative tool for conservation planning and highlight its potential for biomonitoring programs that currently depend on modeling discrete assemblage types to assess aquatic ecosystem health.

Objectives for multiple-species conservation planning

The first step in conservation planning is to identify objectives. Most stated objectives for conservation, such as to maximize biodiversity outcomes, are too vague to be useful within a decision-making framework. One way to clarify the issue is to define objectives in terms of the risk of extinction for multiple species. Although the assessment of extinction risk for single species is common, few researchers have formulated an objective function that combines the extinction risks of multiple species. We sought to translate the broad goal of maximizing the viability of species into explicit objectives for use in a decision-theoretic approach to conservation planning. We formulated several objective functions based on extinction risk across many species and illustrated the differences between these objectives with simple examples. Each objective function was the mathematical representation of an approach to conservation and emphasized different levels of threat. Our objectives included minimizing the joint probability of one or more extinctions, minimizing the expected number of extinctions, and minimizing the increase in risk of extinction from the best-case scenario. With objective functions based on joint probabilities of extinction across species, any correlations in extinction probabilities had to be known or the resultant decisions were potentially misleading. Additive objectives, such as the expected number of extinctions, did not produce the same anomalies. We demonstrated that the choice of objective function is central to the decision-making process because alternative objective functions can lead to a different ranking of management options. Therefore, decision makers need to think carefully in selecting and defining their conservation goals.

Logic for Designing Nature Reserves for Multiple Species

We examine the logic of designing nature reserves to understand better how to integrate the concepts of representativeness and persistence. Simple models of viability are used to evaluate how the expected number of species in the reserve system changes with variation in the risk of extinction among species, their rate of occurrence, and the distribution of species. The optimal size of individual reserves increased with the mean and variance of the probability of extinction among species and with the rate at which the risk of extinction declines with the cost of each reserve. In contrast, the rate of occurrence of species within reserves and their rate of accumulation with increasing reserve area had a relatively minor influence on the optimal size of reserves. Patterns of endemism were most important for the location of reserves. Including differences among species in the analysis reduced the optimal number of individual reserves (and increased the size of each) when operating under a fixed budget compared with reserve designs based on single species. A case study in the city of Melbourne, Australia, demonstrates the conservation value of small (approximately 1 ha) grassland reserves and the underrepresentation of Melbourne's volcanic plains in the region's conservation network.

Identifying areas of high herpetofauna diversity that are threatened by planned infrastructure projects in Spain

A major task related to conservation is to predict if planned infrastructure projects are likely to threaten biodiversity. In this study we investigated the potential impact of planned infrastructure in Spain on amphibian and reptile species, two highly vulnerable groups given their limited dispersal and current situation of population decline. We used distribution data of both groups to identify areas of high herpetofauna diversity, and compared the locations of these areas with the locations of the planned road, high-speed train railway and water reservoir network. Four criteria were used for this identification: species richness, rarity, vulnerability, and a combined index of the three criteria. From a total of 1441 cells of 20 x 20 km, areas of high diversity were defined as those cells whose ranked values for the different criteria included either all species or all threatened species. The combined index provided the smallest number of cells needed to retain all threatened species (1.7 and 2.6% of the cells for amphibian and reptile species, respectively). Coincidences between these high diversity areas and cells including planned infrastructures-denominated 'alert planning units'-were 35.4% for amphibians and 31.2% for reptiles. Mitigation of the potential impacts would include actions such as barriers to animal access to roads and railways and ecoducts under these constructions. Our approach provides conservation authorities information that can be used to make decisions on habitat protection. A technique that identifies threats to herpetofauna before they occur is also likely to improve the chance of herpetofauna being protected.

Designing large-scale conservation corridors for pattern and process

A major challenge for conservation assessments is to identify priority areas that incorporate biological patterns and processes. Because large-scale processes are mostly oriented along environmental gradients, we propose to accommodate them by designing regional-scale corridors to capture these gradients. Based on systematic conservation planning principles such as representation and persistence, we identified large tracts of untransformed land (i.e., conservation corridors) for conservation that would achieve biodiversity targets for pattern and process in the Subtropical Thicket Biome of South Africa. We combined least-cost path analysis with a target-driven algorithm to identify the best option for capturing key environmental gradients while considering biodiversity targets and conservation opportunities and constraints. We identified seven conservation corridors on the basis of subtropical thicket representation, habitat transformation and degradation, wildlife suitability, irreplaceability of vegetation types, protected area networks, and future land-use pressures. These conservation corridors covered 21.1% of the planning region (ranging from 600 to 5200 km2) and successfully achieved targets for biological processes and to a lesser extent for vegetation types. The corridors we identified are intended to promote the persistence of ecological processes (gradients and fixed processes) and fulfill half of the biodiversity pattern target. We compared the conservation corridors with a simplified corridor design consisting of a fixed-width buffer along major rivers. Conservation corridors outperformed river buffers in seven out of eight criteria. Our corridor design can provide a tool for quantifying trade-offs between various criteria (biodiversity pattern and process, implementation constraints and opportunities). A land-use management model was developed to facilitate implementation of conservation actions within these corridors.

Modeling opportunity costs of conservation in transitional landscapes

Conservation scientists recognize the urgency of incorporating opportunity costs into conservation planning. Despite this, applications to date have been limited, perhaps partly because of the difficulty in determining costs in regions with limited data on land prices and ownership. We present methods for estimating opportunity costs of land preservation in landscapes or ecoregions that are a changing mix of agriculture and natural habitat. Our approach derives from the literature on estimating land values as opportunity costs of alternate land uses and takes advantage of general availability of necessary data, even in relatively data-poor regions. The methods integrate probabilities of habitat conversion with region-wide estimates of economic benefits from agricultural land uses and estimate land values with a discount rate to convert annual values into net present values. We applied our method in a landscape undergoing agricultural conversion in Paraguay. Our model of opportunity costs predicted an independent data set of land values and was consistent with implicit discount rates of 15-25%. Model-generated land values were strongly correlated with actual land values even after correcting for the effect of property size and proportion of property that was forested. We used the model to produce a map of opportunity costs and to estimate the costs of conserving forest within two proposed corridors in the landscape. This method can be applied to conservation planning in situations where natural habitat is currently being converted to market-oriented land uses. Incorporating not only biological attributes but also socioeconomic data can help in the design of efficient networks of protected areas that represent biodiversity at minimum costs.

Reserve Selection Using Nonlinear Species Distribution Models

Reserve design is concerned with optimal selection of sites for new conservation areas. Spatial reserve design explicitly considers the spatial pattern of the proposed reserve network and the effects of that pattern on reserve cost and/or ability to maintain species there. The vast majority of reserve selection formulations have assumed a linear problem structure, which effectively means that the biological value of a potential reserve site does not depend on the pattern of selected cells. However, spatial population dynamics and autocorrelation cause the biological values of neighboring sites to be interdependent. Habitat degradation may have indirect negative effects on biodiversity in areas neighboring the degraded site as a result of, for example, negative edge effects or lower permeability for animal movement. In this study, I present a formulation and a spatial optimization algorithm for nonlinear reserve selection problems in grid-based landscapes that accounts for interdependent site values. The method is demonstrated using habitat maps and nonlinear habitat models for threatened birds in the Netherlands, and it is shown that near-optimal solutions are found for regions consisting of up to hundreds of thousands grid cells, a landscape size much larger than those commonly attempted even with linear reserve selection formulations.

Dynamics of extinction and the selection of nature reserves

Familiar quantitative reserve-selection techniques are tailored to simple decision problems, where the representation of species is sought at minimum cost. However, conservationists have begun to ask whether representing species in reserve networks is sufficient to avoid local extinctions within selected areas. An attractive, but previously untested idea is to model current species' probabilities of occurrence as an estimate of local persistence in the near future. Using distribution data for passerine birds in Great Britain, we show that (i) species' probabilities of occurrence are negatively related to local probabilities of extinction, at least when a particular 20-year period is considered, and (ii) local extinctions can be reduced if areas are selected to maximize current species' probabilities of occurrence We suggest that more extinctions could be avoided if even a simple treatment of persistence were to be incorporated within reserve selection methods.

Design of reserve networks and the persistence of biodiversity

Sophisticated computational methods have been developed to help us to identify sets of nature reserves that maximize the representation of regional diversity, but, until recently, the methods have not dealt explicitly and directly with the main goal of reserve networks, that of the long-term maintenance of biodiversity. Furthermore, the successful application of current methods requires reliable information about species distributions, which is not always available. Recent results show that data quality, as well as the choice of surrogates for biodiversity, could be critical for successful reserve design. Because of these problems and a lack of communication between scientists and managers, the impact of computational site-selection tools in applied conservation planning has been minimal.