Search

Conservation policies and environmental impact assessments commonly target threatened species and habitats. Nevertheless, macroecological research provides reasons why also common species should be considered. We investigate the consequences of focussing solely on legally protected species and habitats in a spatial conservation planning context using a comprehensive, benthic marine data set from the northern Baltic Sea. Using spatial prioritization and surrogacy analysis, we show that the common approach in conservation planning, where legally listed threatened species and habitats are the focus of conservation efforts, could lead to poor outcomes for common species (and therefore biodiversity as a whole), allowing them to decline in the future. If conservation efforts were aimed solely at threatened species, common species would experience a loss of 62% coverage. In contrast, if conservation plans were based only on common species, threatened species would suffer a loss of 1%. Threatened species are rare and their ecological niches distinct, making them poor surrogates for biodiversity. The best results are achieved by unified planning for all species and habitats. The minimal step towards acknowledging common species in conservation planning would be the inclusion of the richness of common species, complemented by information on indicator species or species of high importance for ecosystem functioning. The trade‐off between planning for rare and common species should be evaluated, to minimize losses to biodiversity. [ABSTRACT FROM AUTHOR]

Conservation planning addresses the development and expansion of protected areas and requires data on for instance species, habitats, and biodiversity. Data on threats is often minimal, although necessary in conservation planning. In principle, threats should guide which conservation actions to take and where, and how to allocate resources. The lack of threat information may also limit the validity of areas to be conserved, if the condition of areas is degraded by threats unknown. The protocol described here outlines the methodology for a systematic review to explore how threats are theoretically and methodologically understood and used in conservation plans across freshwater, marine and terrestrial environments. Our primary research question is: how have threats informed conservation planning? Studies will be categorized according to the types of threats and conservation features used, theoretical and methodological approaches applied, geographical context, and biome. The results are expected to increase our understanding about how threats can and should be addressed in conservation planning. [ABSTRACT FROM AUTHOR]

Effective planning of a large-scale restoration project is challenging, because of the range of factors that need to be considered (e.g. restoration of multiple habitats with varying degradation levels, multiple restoration goals and limited conservation resources). Ecological restoration planning studies typically focus on biodiversity and ecosystem services, rather than employment and other co-benefits. Robust Offsetting (RobOff), a restoration planning tool, was used in a forest restoration project in Durban, South Africa, to plan forest restoration considering a mosaic of habitats with varying levels of degradation, diverse restoration actions, a limited budget and multiple (biodiversity, carbon stock and employment) goals. To achieve this, the restoration action currently being implemented (= current action) was compared to three restoration alternatives. The three restoration alternatives included (1) natural regeneration action; (2) carbon action; and (3) biodiversity action. The results supported biodiversity action as most beneficial in terms of maximizing biodiversity, carbon storage and job creation. Results showed that investing in biodiversity action is preferable to the status quo. RobOff ensured optimal allocation of limited resources to actions and habitats that have a potential to achieve higher biodiversity, carbon storage and job creation. EDITED BY Neville Crossman [ABSTRACT FROM AUTHOR]

Including threats in spatial conservation prioritization helps identify areas for conservation actions where biodiversity is at imminent risk of extinction. At the global level, an important limitation when identifying spatial priorities for conservation actions is the lack of information on the spatial distribution of threats. Here, we identify spatial conservation priorities under three prominent threats to biodiversity (residential and commercial development, agricultural expansion, and forest loss), which are primary drivers of habitat loss and threaten the persistence of the highest number of species in the International Union for the Conservation of Nature (IUCN) Red List, and for which spatial data is available. We first explore how global priority areas for the conservation of vertebrate (mammals, birds, and amphibians) species coded in the Red List as vulnerable to each threat differ spatially. We then identify spatial conservation priorities for all species vulnerable to all threats. Finally, we identify the potentially most threatened areas by overlapping the identified priority areas for conservation with maps for each threat. We repeat the same with four other well-known global conservation priority area schemes, namely Key Biodiversity Areas, Biodiversity Hotspots, the global Protected Area Network, and Wilderness Areas. We find that residential and commercial development directly threatens only about 4% of the global top 17% priority areas for species vulnerable under this threat. However, 50% of the high priority areas for species vulnerable to forest loss overlap with areas that have already experienced some forest loss. Agricultural expansion overlapped with ~20% of high priority areas. Biodiversity Hotspots had the greatest proportion of their total area under direct threat from all threats, while expansion of low intensity agriculture was found to pose an imminent threat to Wilderness Areas under future agricultural expansion. Our results identify areas where limited resources should be allocated to mitigate risks to vertebrate species from habitat loss. [ABSTRACT FROM AUTHOR]

There is high-level political support for the use of green infrastructure (GI) across Europe, to maintain viable populations and to provide ecosystem services (ES). Even though GI is inherently a spatial concept, the modern tools for spatial planning have not been recognized, such as in the recent European Environment Agency (EEA) report. We outline a toolbox of methods useful for GI design that explicitly accounts for biodiversity and ES. Data on species occurrence, habitats, and environmental variables are increasingly available via open-access internet platforms. Such data can be synthesized by statistical species distribution modeling, producing maps of biodiversity features. These, together with maps of ES, can form the basis for GI design. We argue that spatial conservation prioritization (SCP) methods are effective tools for GI design, as the overall SCP goal is cost-effective allocation of conservation efforts. Corridors are currently promoted by the EEA as the means for implementing GI design, but they typically target the needs of only a subset of the regional species pool. SCP methods would help to ensure that GI provides a balanced solution for the requirements of many biodiversity features (e.g., species, habitat types) and ES simultaneously in a cost-effective manner. Such tools are necessary to make GI into an operational concept for combating biodiversity loss and promoting ES. [ABSTRACT FROM AUTHOR]

Egoh et al. (2014) prioritized areas for ecological restoration in the European Union (EU) so that Europe could cost-efficiently meet the globally agreed 15% restoration target., We identify three major deficiencies in their analysis, one conceptual and two operational, which compromise the conclusions of the prioritization., The conceptual flaw is neglect of both the magnitude of degradation and the magnitude of improvement of the ecosystem condition expected due to restoration., The first operational flaw is inclusion of inappropriately measured restoration costs into the analyses. The second is use of spatial units that are so large (10 × 10 km) that only a fraction of each unit could realistically be restored, thereby overestimating restoration gains., Synthesis and applications. The prioritization suggested by Egoh et al. (2014) runs a risk of focusing restoration efforts towards areas where the ecological improvement of restoration is the smallest. Thus, in this article, we propose that the recommendations by Egoh et al. (2014) will not help to achieve the high-level target of the Convention on Biological Diversity and EU of halting the loss of biodiversity and the degradation of ecosystem services, but instead may actually compromise progress towards the target. More detailed analyses are needed before well-informed decisions about restoration prioritization can be made across the EU and elsewhere. [ABSTRACT FROM AUTHOR]

Protected areas are one of the main tools for halting the continuing global biodiversity crisis caused by habitat loss, fragmentation and other anthropogenic pressures. According to the Aichi Biodiversity Target 11 adopted by the Convention on Biological Diversity, the protected area network should be expanded to at least 17% of the terrestrial world by 2020 (http://www.cbd.int/sp/targets). To maximize conservation outcomes, it is crucial to identify the best expansion areas. Here we show that there is a very high potential to increase protection of ecoregions and vertebrate species by expanding the protected area network, but also identify considerable risk of ineffective outcomes due to land-use change and uncoordinated actions between countries. We use distribution data for 24,757 terrestrial vertebrates assessed under the International Union for the Conservation of Nature (IUCN) 'red list of threatened species', and terrestrial ecoregions (827), modified by land-use models for the present and 2040, and introduce techniques for global and balanced spatial conservation prioritization. First, we show that with a coordinated global protected area network expansion to 17% of terrestrial land, average protection of species ranges and ecoregions could triple. Second, if projected land-use change by 2040 (ref. 11) takes place, it becomes infeasible to reach the currently possible protection levels, and over 1,000 threatened species would lose more than 50% of their present effective ranges worldwide. Third, we demonstrate a major efficiency gap between national and global conservation priorities. Strong evidence is shown that further biodiversity loss is unavoidable unless international action is quickly taken to balance land-use and biodiversity conservation. The approach used here can serve as a framework for repeatable and quantitative assessment of efficiency, gaps and expansion of the global protected area network globally, regionally and nationally, considering current and projected land-use pressures. [ABSTRACT FROM AUTHOR]

We introduce a novel approach to building corridors in spatial conservation prioritization. The underlying working principle is the use of a penalty structure in an iterative algorithm used for producing a spatial priority ranking. The penalty term aims to prevent loss or degradation of structural connections, or, equivalently, to promote to a higher rank landscape elements that are required to keep networks connected. The proposed method shows several convenient properties: (1) it does not require a priori specification of habitat patches, end points or related thresholds, (2) it does not rely on resistance coefficients for different habitats, (3) it does not require species targets, and (4) the cost of additional connectivity via corridors can be quantified in terms of habitat quality lost across species. Corridor strength and width parameters control the trade-off between increased structural connectivity via corridors and other considerations relevant to conservation planning. Habitat suitability or dispersal suitability layers used in the analysis can be species specific, thus allowing analysis both in terms of structural and functional connectivity. The proposed method can also be used for targeting habitat restoration, by identifying areas of low habitat quality included in corridors. These methods have been implemented in the Zonation software, and can be applied to large scale and high resolution spatial prioritization, effectively integrating corridor design and spatial conservation prioritization. Since the method operates on novel principles and combines with a large number of features already operational in Zonation, we expect it to be of utility in spatial conservation planning. [ABSTRACT FROM AUTHOR]

Conservation planning often relies on the use of surrogates for representing many aspects of biodiversity. Previous tests on the effectiveness of charismatic mammals as biodiversity surrogates have suffered from the lack of fine-resolution data and produced varied and contrasting results., In this study, we used unique high-resolution data for more than 600 biodiversity features from the Maputaland- Pondoland- Albany global biodiversity hot spot to assess how the surrogacy effectiveness of the ' Big Five' charismatic mammal species could be improved., We found that combining the ' Big Five' charismatic mammal species with well-known and surveyed taxonomic groups, such as birds, amphibians and reptiles, and habitat types, which can be mapped quickly and inexpensively, increases the representation of poorly surveyed taxonomic groups, such as endemic and threatened invertebrate and plant species, as well as other mammal species. In particular, habitat types were found to be an integral component of a successful surrogate strategy. Nevertheless, a broad cross-taxon surrogate group composed of the ' Big Five', birds, amphibians and reptiles, was found to be a more effective surrogate than habitat types on their own. Meanwhile, other taxonomic groups and habitat types were not effective surrogates for the ' Big Five' charismatic species., As charismatic mammals have an important marketing value, they can be promoted to generate funding, which can then facilitate the implementation of conservation action and cover management costs, thereby indirectly benefiting other threatened biodiversity., Synthesis and applications. While some geographic areas and taxa have been extensively studied, detailed information about the distributions of species is missing for much of the world. This study provides important information that can have operational relevance to prioritize areas for conservation action in areas of the world with poor data on biodiversity. We found that other taxa are not good surrogates for charismatic mammal species. We also found that habitat types are a necessary component of surrogacy strategies that cover plants and insects. Overall, a combination of habitat types and charismatic mammals, complemented with other well-known taxa (birds, amphibians and reptiles), provided the highest surrogacy effects. [ABSTRACT FROM AUTHOR]

Highlights: [•] We analyze the dispersal of ecological communities or other collections of species. [•] Community-level dispersal is modelled as a distribution of dispersal kernels. [•] The distribution is optimally approximated by any finite number of kernels. [•] The approximation method improves our understanding on spatial modelling. [•] The method can be directly applied in conservation decision making tools. [Copyright &y& Elsevier]

Habitat restoration is increasing in importance as a conservation action, compared with more traditional establishment of conservation areas. It is applied, for example, in the context of biodiversity offsetting, in which environmental impacts of economic activity are offset by additional compensating conservation efforts., We present a publicly available decision support software tool for the comparison of ecological impacts of alternative land-use options., Methods implemented account for uncertain consequences of alternative land-use options, including conservation actions. These actions have different costs and effects on different biodiversity features, including species, guilds or habitat types, in different environments. Consequences of actions are uncertain through time, and time discounting is allowed in the investigation of temporal preferences., This tool facilitates analyses relevant for planning of habitat restoration or management, environmental impact avoidance, biodiversity offsetting and scenario development for systematic conservation planning. RobOff derives its name from Robust Offsetting. [ABSTRACT FROM AUTHOR]

We develop a high-resolution conservation prioritization analysis for New Zealand's rivers and streams that simultaneously consider both the present state (representation) of ecosystems, and the prioritization of management actions designed to mitigate ongoing human impacts on their expected future state (retention). As input we used information about the geographic distributions of river ecosystem groups and their compositional similarity, species richness, present condition as compared to their estimated pristine state, and upstream and downstream connectivity. Candidate management actions included riparian planting, establishment of wetlands on tile-drain outflows, and use of riparian buffer strips in plantation forests. The analysis, carried out at a 1-ha resolution for a study area of 22,000 km2 in Southland, New Zealand, demonstrates a credible range of options for management intervention, particularly in lowland streams under serious threat from agricultural intensification. The proposed analysis can be replicated elsewhere for terrestrial, freshwater, or marine systems using publicly available software. [ABSTRACT FROM AUTHOR]

The effectiveness of a system of reserves may be compromised under climate change as species' habitat shifts to nonreserved areas, a problem that may be compounded when well-studied vertebrate species are used as conservation umbrellas for other taxa. The Northwest Forest Plan was among the first efforts to integrate conservation of wide-ranging focal species and localized endemics into regional conservation planning. We evaluated how effectively the plan's focal species, the Northern Spotted Owl, acts as an umbrella for localized species under current and projected future climates and how the regional system of reserves can be made more resilient to climate change. We used the programmaxent to develop distribution models integrating climate data with vegetation variables for the owl and 130 localized species. We used the programzonation to identify a system of areas that efficiently captures habitat for both the owl and localized species and prioritizes refugial areas of climatic and topographic heterogeneity where current and future habitat for dispersal-limited species is in proximity. We projected future species' distributions based on an ensemble of contrasting climate models, and incorporating uncertainty between alternate climate projections into the prioritization process. Reserve solutions based on the owl overlap areas of high localized-species richness but poorly capture core areas of localized species' distribution. Congruence between priority areas across taxa increases when refugial areas are prioritized. Although core-area selection strategies can potentially increase the conservation value and resilience of regional reserve systems, they accentuate contrasts in priority areas between species and over time and should be combined with a broadened taxonomic scope and increased attention to potential effects of climate change. Our results suggest that systems of fixed reserves designed for resilience can increase the likelihood of retaining the biological diversity of forest ecosystems under climate change. [ABSTRACT FROM AUTHOR]

Biodiversity offset areas may compensate for ecological damage caused by human activity elsewhere. One way of determining the offset ratio, or the compensation area needed, is to divide the present conservation value of the development site by the predicted future conservation value of a compensation area of the same size. Matching mean expected utility in this way is deficient because it ignores uncertainty and time lags in the growth of conservation value in compensation areas. Instead, we propose an uncertainty analytic framework for calculating what we call robustly fair offset ratios, which guarantee a high enough probability of the exchange producing at least as much conservation value in the offset areas than is lost from the development site. In particular, we analyze how the fair offset ratio is influenced by uncertainty in the effectiveness of restoration action, correlation between success of different compensation areas, and time discounting. We find that very high offset ratios may be needed to guarantee a robustly fair exchange, compared to simply matching mean expected utilities. These results demonstrate that considerations of uncertainty, correlated success/failure, and time discounting should be included in the determination of the offset ratio to avoid a significant risk that the exchange is unfavorable for conservation in the long run. This is essential because the immediate loss is certain, whereas future gain is uncertain. The proposed framework is also applicable to the case when offset areas already hold conservation value and do not require restoration action, in which case uncertainty about the conservation outcome will be lower. [ABSTRACT FROM AUTHOR]

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. [Copyright &y& Elsevier]

1. Freshwater ecosystems are amongst the most threatened and poorly protected globally. They continue to be degraded through habitat loss, pollution and invading species and conservation measures are urgently needed to halt declining trends in their biodiversity and integrity. 2. During the past decade a suite of decision support tools and computational approaches have been developed for efficient and targeted conservation action in terrestrial or marine ecosystems. These methods may be poorly suited for planning in freshwater systems because connectivity in terrestrial and marine systems is typically modelled in a way unsuitable for rivers, where connectivity has a strong directional component. 3. We modify the conservation prioritization method and software,zonation, to account for connectivity in a manner better suited to freshwater ecosystems. Prioritization was performed using subcatchment/catchment-based planning units and connectivity was modified to have directional upstream and downstream components consistent with the ecology of our target species. 4. We demonstrate this modified method for rivers and streams in the southern North Island of New Zealand. Data included predicted occupancy from boosted regression tree models of species distributions for 18 fish species. The study area covered 2.1 million hectares and included 394 first- to fourth order catchment or subcatchment planning units. 5. Realistic modelling of connectivity had a major influence on the areas proposed for conservation. If connectivity was ignored, recommended conservation areas were very fragmented. By contrast, when connectivity was modelled, high priority conservation targets consisted of entire river basins or headwater subcatchments. 6. The proposed method serves as a starting point for the implementation of reserve selection methods in river ecosystems. [ABSTRACT FROM AUTHOR]

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

Abstract: 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. [Copyright &y& Elsevier]

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

Abstract: Studies of habitat selection and movements often use radio-tracking data for defining animal home ranges. Home ranges (HR) can be approximated by a utilization density distribution (UD) that instead of assuming uniform use of areas within HR boundary provides a probabilistic measure of animal space use. In reality, radio-tracking data contain periods of frequent autocorrelated observations interspersed with temporally more independent observations. Using such temporally irregular data directly may result in biased UD estimates, because areas that have been sampled intensively receive too much weight. The problem of autocorrelation has been tackled by resampling data with an appropriate time interval. However, resampling may cause a large reduction in the data set size along with a loss of information. Evidently, biased UD estimates or reduction in data may prejudice the results on animal habitat selection and movement. We introduce a new method for estimating UDs with temporally irregular data. The proposed method, called the time kernel, accounts for temporal aggregation of observations and gives less weight to temporally autocorrelated observations. A further extension of the method accounts also for spatially aggregated observations with relatively low weights given to observations that are both temporally and spatially aggregated. We test the behaviour of the time kernel method and its spatiotemporal version using simulated data. In addition, the method is applied to a data set of brown bear locations. [Copyright &y& Elsevier]

Reserve selection methods are often based on information on species' occurrence. This can be presence absence data, or probabilities of occurrence estimated with species distribution models. However, the effect of the choice of distribution model on the outcome of a reserve selection method has been ignored. Here we test a range of species distribution models with three different reserve selection methods. The distribution models had different combinations of variables related to habitat quality and connectivity (which incorporates the effect of spatial habitat configuration on species occurrence). The reserve selection methods included (i) a minimum set approach without spatial considerations; (ii) a clustering reserve selection method; and (iii) a dynamic approach where probabilities of occurrence are re-evaluated according to the spatial pattern of selected sites. The sets of selected reserves were assessed by re-computing species probability of occurrence in reserves using the best probability model and assuming loss of non-selected habitat. The results show that particular choices of distribution model and selection method may lead to reserves that overestimate the achieved target; in other words, species may seem to be represented but the reserve network may actually not be able to support them in the long-term. Instead, the use of models that incorporated connectivity as a variable resulted in the selection of aggregated reserves with higher potential for species long-term persistence. As reserve design aims at the long-term protection of species, it is important to be aware of the uncertainties related to model and method choice and their implications. [ABSTRACT FROM AUTHOR]

The article presents a study that examines the migration and survival of the butterfly Parnassius smintheus in a heterogeneous landscape consisting of 21 habitat patches imbedded in a matrix of meadow and forest habitat. The results show the need for spatial population studies to account for the effects of different habitat types on the migration of individuals among habitat patches. It also suggests management options for the conservation of endangered species in other parts of the world.

Journal of Applied Ecology (2004) 41, 252–262 [ABSTRACT FROM AUTHOR]

Site-selection algorithms are used in reserve design to select networks of sites that maximize biodiversity, given some constraints. These algorithms are based on a snapshot of species occurrence, and they typically aim to minimize the area or cost needed to represent all the species once or a few times. Most of these algorithms ignore the question of how well species are likely to persist in the set of selected sites in the long term. Furthermore, the role of the unselected habitat in biodiversity persistence has received no attention in this context. We used a theoretical approach to evaluate the long-term performance of reserve networks in preserving biodiversity by using a model of spatiotemporal population dynamics ( a metapopulation model ). We compared extinction rates of species in reserve networks in two situations: when all sites remain suitable habitat for the species and, conversely, when the habitat in the unselected sites is lost. We made this comparison to explore the significance of unselected sites for spatial population dynamics and for the continued presence of species in the reserve network. Basic site-selection algorithms are liable to perform badly in terms of biodiversity maintenance because the persistence of species may be strongly dependent on sites not included in the reserve network. Our results support recent calls for the integration of spatial population modeling into reserve network design. Advances in metapopulation theory provide tools that can be used for this purpose. [ABSTRACT FROM AUTHOR]

1. The construction of a predictive metapopulation model includes three steps: the choice of factors affecting metapopulation dynamics, the choice of model structure, and finally parameter estimation and model testing. 2. Unless the assumption is made that the metapopulation is at stochastic quasiequilibrium and unless the method of parameter estimation of model parameters uses that assumption, estimates from a limited amount of data will usually predict a trend in metapopulation size. 3. This implicit estimation of a trend occurs because extinction-colonization stochasticity, possibly amplified by regional stochasticity, leads to unequal numbers of observed extinction and colonization events during a short study period. 4. Metapopulation models, such as those based on the logistic regression model, that rely on observed population turnover events in parameter estimation are sensitive to the implicit estimation of a trend. 5. A new parameter estimation method, based on Monte Carlo inference for statistically implicit models, allows an explicit decision about whether metapopulation quasi-stability is assumed or not. 6. Our confidence in metapopulation model parameter estimates that have been produced from only a few years of data is decreased by the need to know before parameter estimation whether the metapopulation is in quasi-stable state or not. 7. The choice of whether metapopulation stability is assumed or not in parameter estimation should be done consciously. Typical data sets cover only a few years and rarely allow a statistical test of a possible trend. While making the decision about stability one should consider any information about the landscape history and species and metapopulation characteristics. [ABSTRACT FROM AUTHOR]

Abstract: We develop methods for conservation resource allocation, to help with decisions about targeting of protection, habitat management, maintenance and restoration or biodiversity offsetting. We construct a framework, where conservation actions have different responses for different biodiversity features in different environments, and in which uncertainty in responses and the time perspective are explicitly considered. Costs of actions in different environments are also accounted for. Costs can be defined as constants, functions of time or as functions of the total area in which an action is performed. We optimize the combination of actions to maximize conservation value given uncertain responses, limited resources, different robustness requirements and limits to the area in which different actions can be undertaken. Accounting for the uncertainty in responses to actions or accounting for time can change the optimal combination of actions. We can account for both negative consequences of uncertainty (robustness analysis) and positive aspects of uncertainty (opportunity analysis). To allow for the complexity of the analysis above and to significantly reduce data demands, we have omitted an explicit spatial structure from these analyses. Nevertheless, we describe approaches that account for spatial considerations, for example, by using the present methods in combination with software that is intended for the spatial analysis of static biodiversity pattern. The proposed analyses have been implemented in a software package called RobOff, which will be made freely, publicly available. Thereby it is possible for the first time to effectively find solutions to a significant set of conservation resource allocation problems. These analyses can assist conservation scientists and managers in decision making based on quantitative analysis. [Copyright &y& Elsevier]

Resource allocation to multiple alternative conservation actions is a complex task. A common trade-off occurs between protection of smaller, expensive, high-quality areas versus larger, cheaper, partially degraded areas. We investigate optimal allocation into three actions in boreal forest: current standard forest management rules, setting aside of mature stands, or setting aside of clear-cuts. We first estimated how habitat availability for focal indicator species and economic returns from timber harvesting develop through time as a function of forest type and action chosen. We then developed an optimal resource allocation by accounting for budget size and habitat availability of indicator species in different forest types. We also accounted for the perspective adopted towards sustainability, modeled via temporal preference and economic and ecological time discounting. Controversially, we found that in boreal forest set-aside followed by protection of clear-cuts can become a winning cost-effective strategy when accounting for habitat requirements of multiple species, long planning horizon, and limited budget. It is particularly effective when adopting a long-term sustainability perspective, and accounting for present revenues from timber harvesting. The present analysis assesses the cost-effective conditions to allocate resources into an inexpensive conservation strategy that nevertheless has potential to produce high ecological values in the future. [ABSTRACT FROM AUTHOR]

The Natura 2000 (N2k) is a network of protected areas, established to implement the Birds and the Habitats Directives of the European Union (EU) with the goal of conservation irrespective of national boundaries. We provide the first assessment of the whole terrestrial N2k using spatial prioritizations, and high-resolution vertebrate species distribution data. First, we quantified species' representation in the network, and compared it against outcomes of hypothetical optimal planning scenarios at the EU, member state, and biogeographical levels. Second, we examined the spatial configuration of N2k sites and same-sized hypothetical top priority sites based on the three planning scenarios. We found that N2k covered all vertebrate directive species, and the coverage was significantly better than with a random allocation of sites. We observed substantial differences in representation between taxa, followed by the fact that N2k succeeded better in covering threatened and directive species than non-directive species. The current species representation in N2k was closer to optimal allocations done at member states' or biogeographical levels than the EU-wide allocation. Furthermore, the N2k sites overlapped more with the EU-wide allocation and they were more evenly distributed across the EU compared to sites in all hypothetical optimal allocations. Finally, we found that the biogeographical scenario covered well the ranges of habitats directive species, following the biogeographical approach taken by the EU in the Habitats Directive. Our results show that despite N2k being moderately successful, there is substantial effectiveness to be gained from member state collaboration via potential expansions or complementary conservation policies. [ABSTRACT FROM AUTHOR]