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Although spatially explicit decision support tools are widely used in marine conservation planning, only a few studies have used multi-objective approaches to explicitly achieve biodiversity conservation and sustainable use objectives. Here, we use spatial analyses of a comprehensive environment-based classification (developed using Gradient Forest modelling) that summarises spatial patterns in demersal fish composition and turnover in the oceans around New Zealand, and a 20-year record of trawl locations (representing spatial use by fishers), to identify options for biodiversity protection that vary in their relative delivery of conservation outcomes and impacts on fishers. We also compare analyses carried out at a national scale with those generated by aggregating independent regional analyses. The top-ranked 20% of sites identified using fish composition data alone would on average protect 33% of the geographic range of each fish species, but would result in a 58% loss of areas currently fished. By contrast, using the trawl locations as a cost layer reduced average fish protection by 23% in relative terms, but loss of fished areas was almost eliminated. Using different weightings to vary the influence of the trawl footprint, a range of intermediate scenarios were identified that delivered greater fish protection than the fully cost-constrained scenario. However, these intermediate scenarios resulted in greater reductions in the area retained for fishers than the biodiversity optimised scenario. Aggregated regional scenarios delivered lower conservation returns and higher impacts on fisheries than comparable single national scenarios, reflecting the constraining of opportunities for biodiversity protection whilst avoiding overlaps with trawling. While stakeholder MPA design processes often occur at regional scales, our analyses demonstrate the value of considering both regional and national analyses to identify optimal reserve configurations. • Spatial estimates of demersal fish composition and turnover, and trawl fisheries were used to identify options for biodiversity protection. • The analyses were carried out at both national and regional scales. • Exploration of scenarios ranged from complete protection of economic resource use through to maximising the protection of biodiversity. • Regional scenarios delivered lower conservation returns and higher impacts on fisheries than comparable single national scenarios. [ABSTRACT FROM AUTHOR]

Abstract Many development projects, whether they are about construction of factories, mines, roads, railways, new suburbs, shopping malls, or even individual houses, have negative environmental consequences. Biodiversity offsetting is about compensating that damage, typically via habitat restoration, land management, or by establishment of new protected areas. Offsets are the fourth step of the so-called mitigation hierarchy, in which ecological damage is first avoided, minimized second, and third restored locally. Whatever residual damage remains is then offset. Offsetting has been increasingly adopted all around the world, but simultaneously serious concerns are expressed about the validity of the approach. Failure of offsetting can follow from either inappropriate definition of the size and kind of offset, or, from failure in implementation. Here we address planning of offsets, and identify fundamental operational design decisions that define the intended outcome of an offsetting project, and organize these decisions around objectives, offset actions, and the three fundamental ecological axes of ecological reality: space, time and biodiversity. We also describe how the offset ratio of a project (size of offset areas compared to impact area) can be constructed based on several partial multipliers that arise from factors such as degree of compensation required relative to no net loss, partial and delayed nature of restoration or avoided loss gains, time discounting, additionality, leakage, uncertainty, and factors associated with biodiversity measurement and offset implementation. Several of these factors are partially subjective and thus negotiable. The overall purpose of this effort is to allow systematic, well informed and transparent discussion about these critical decisions in any offset project. [ABSTRACT FROM AUTHOR]

Highlights: [•] We describe a framework for structured analysis of conservation strategies. [•] Structured analysis is a top-down logical investigation of the properties of a strategy. [•] We apply structured analysis to dynamic reserves and temporary conservation contracts. [•] This application reveals that temporary conservation is generally a risky and data-intensive strategy. [•] Structured analysis clarifies the utility and feasibility of a conservation strategy. [Copyright &y& Elsevier]

Abstract: Spatial conservation prioritization concerns the effective allocation of conservation action. Its stages include development of an ecologically based model of conservation value, data pre-processing, spatial prioritization analysis, and interpretation of results for conservation action. Here we investigate the details of each stage for analyses done using the Zonation prioritization framework. While there is much literature about analytical methods implemented in Zonation, there is only scattered information available about what happens before and after the computational analysis. Here we fill this information gap by summarizing the pre-analysis and post-analysis stages of the Zonation framework. Concerning the entire process, we summarize the full workflow and list examples of operational best-case, worst-case, and typical scenarios for each analysis stage. We discuss resources needed in different analysis stages. We also discuss benefits, disadvantages, and risks involved in the application of spatial prioritization from the perspective of different stakeholders. Concerning pre-analysis stages, we explain the development of the ecological model and discuss the setting of priority weights and connectivity responses. We also explain practical aspects of data pre-processing and the post-processing interpretation of results for different conservation objectives. This work facilitates well-informed design and application of Zonation analyses for the purpose of spatial conservation planning. It should be useful for both scientists working on conservation related research as well as for practitioners looking for useful tools for conservation resource allocation. [Copyright &y& Elsevier]

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]

Abstract: The Natura 2000 (N2k) network of protected areas is a backbone of biodiversity conservation in Europe, with likely further relevance for the development of green infrastructure. EU member states have legal responsibilities for evaluating the condition of and maintaining their national networks. While it is desirable to maintain the condition of the N2k network or even improve it by habitat restoration, it is a fact that national environmental bodies operate under budgetary constraints – money available for conservation is limited. Consequently, there may be a need to prioritize targeting of conservation effort in and around the N2k network. In this study we develop a high-resolution spatial conservation prioritization for the Finnish national N2k network, using data about the distribution and quality of 68 N2k habitats occurring in Finland. The aim of the work is to identify management landscapes, landscapes that have exceptionally high conservation value and which could be managed as one management unit. We identify top-priority areas of the N2k network. We also identify highest-priority N2k areas that do not have the status of a protected area in the Finnish legislation. The present work was commissioned by the Natural Heritage Services of Metsähallitus, a national administrator that is responsible for the maintenance of the Finnish protected area network. The primary purpose of this work is to assist targeting of habitat maintenance, management and restoration in and around the Finnish N2k network. The analysis done here could be replicated elsewhere using publicly available spatial prioritization software. [Copyright &y& Elsevier]

Abstract: The prevalent approach for reserve network design is within the framework of systematic conservation planning which includes target setting as an integral step. In target-based planning the conservation goal is translated into conservation targets for biodiversity features, such as species, habitats or ecosystem services. In effect, many targets are set for factors that can be considered as low-level components of biodiversity as a whole. This paper investigates the relations between common formulations for reserve selection, including minimum set cover, maximum coverage and maximal utility planning. We conclusively show how the use of many low-level targets can significantly reduce return on conservation investment. This finding should influence the way targets are viewed in systematic conservation planning, and it is directly relevant for globally accepted state-of-the-art conservation practices. We also describe a novel planning framework combining target- and benefit-based approaches which could be widely useful in the design of conservation area networks. [Copyright &y& Elsevier]

Abstract: Target-based planning is an integral component of systematic conservation planning. Using empirical data, we investigate a prior conceptual proposition that target-based planning may lead to lower average protection levels across biodiversity features due to its prescriptive nature where conservation outcome is measured in terms of achievement of many independently developed targets. We used spatial distribution models and externally provided targets set for 253 biodiversity features from the Maputaland–Pondoland–Albany hotspot and compared target-based planning to alternative approaches, such as maximum-utility planning, which can operate without the specification of strict targets. We found that target-based planning retained on average a significantly lower fraction of the distributions of all biodiversity features than did alternative methods. This sub-optimality fundamentally follows from the nestedness of species distributions being ignored in target setting, leading to investment in features that occur in relatively species-poor and expensive areas. Consequently, benefit-based alternatives to target-based planning will achieve higher overall conservation performance. [Copyright &y& Elsevier]

Abstract: Site selection, reserve selection, and spatial conservation prioritization are terms that have been used for various algorithms and methods for the spatial allocation of conservation resources. Many of these methods start from the setting of targets or weights for different conservation features. Almost always there is only one set of targets or weights, thus implicitly assuming that priorities stay the same through the entire planning region. However, priorities for biodiversity governance could vary between regions. For example, priorities inside countries could be different from global priorities. Inside a country, different stakeholders could hold different priorities. Thus, priorities could vary between sub-regions while ecological processes, such as connectivity, cross borders without regard to administrative boundaries. Here we describe how it is possible to account for conservation priorities that vary between administrative sub-regions in conservation prioritization. We illustrate how assumptions about selection methods and feature weights can significantly influence the outcome mapping of conservation priority. We also show how placing high emphasis on local considerations reduces the cost-efficiency of the global conservation outcome. Analyses proposed here will be made publicly available in software (Zonation) capable for large-scale high-resolution conservation prioritization. [Copyright &y& Elsevier]

Abstract: Target-based spatial prioritization is the default approach in conservation resource allocation. Here, we clarify a poorly known feature of target-based spatial prioritization that may lead to an unbalanced allocation of resources between species or other biodiversity features. Highest per-species resources will be allocated to species occurring in costly and otherwise species-poor locations, whereas smallest per-species resources will be allocated to species that occur in species-rich locations at low-cost areas. Uncertainty in information about processes determining distributions of biodiversity features may lead to uncertainty in target setting. This can be a problem if unnecessarily high targets emerge to consume excessive resources thus detracting from other conservation action. Difficulties might be encountered in particular when there are many features, targets are given simultaneously to multiple different types of biodiversity features, or components of features, or when there are interactions or correlations between features. Consequently, we recommend that the costs of targets for individual features could be evaluated to screen for such targets that consume a disproportionate fraction of available resources. Costs of targets can be evaluated by a variant of the replacement cost technique. We also find that commonly used reserve selection methods, minimum set coverage, maximum coverage, and utility maximization differ significantly in how they treat targets and their costs. [ABSTRACT FROM AUTHOR]

Abstract: We apply a recently developed conservation prioritization method (Zonation algorithm) to a national-scale conservation planning task. The Finnish Forest and Park Service (Metsähallitus) was given the mandate to expand the current protected areas in southern Finland by 10000ha. The question is which areas should be selected out of the total area of 1760000ha. The data available include a nation-wide GIS data set describing general features of forests at the resolution of 25m×25m for entire Finland and another data set about biodiversity features within the current state-managed conservation areas. Ecologically, the key information includes forest age and the volume of growing stock for 20 forest types representing different productivity classes and dominant tree species. Our analysis employs four different connectivity components to identify forest areas that are (i) locally of high quality and internally well connected, (ii) well connected to surrounding high-quality forests, (iii) well connected to existing conservation areas, and (iv) large enough to allow efficient implementation. Expert evaluation of the results suggested that the present quantitative analysis was helpful in identifying areas with high conservation value systematically across southern Finland. Our analysis also showed that the highest forest conservation potential in Finland is located on privately owned land. The present techniques can be applied to many large-scale planning and management projects. [Copyright &y& Elsevier]

Abstract: Species that persist on a shifting mosaic of successional habitat offer particular challenges to conservation, to monitoring methods, and to population dynamic modelling. The conservation of the heath fritillary butterfly (Melitaea athalia) in woodland in England, for example, depends on the creation of woodland clearings by coppicing (rotational cutting). We have developed a simulation model to assist in the conservation of such populations, called MANAGE. We have parameterised the model for the M. athalia population in the Blean Woods in Kent, and used it to answer several management questions. We find that: (1) simulations predict that the observed rates of coppicing will not be enough to meet existing conservation (Biodiversity Action Plan) targets, except when the most generous modelling assumptions are made; (2) the greatest uncertainty in the model outcome arises from uncertainty in the colonisation parameters; (3) in the worst case scenario (using the most pessimistic model assumptions), a population would require 2.3% of the Blean Woods to be coppiced each year, which is around double the currently-observed rate; (4) the four management units of the Blean where coppicing is practised are not independent metapopulations– they support each other; and (5) to sustain a population in a smaller landscape would require less coppicing overall, but more as a percentage of the landscape. This modelling approach may prove useful in the development of conservation management plans for other species that inhabit successional habitats. [Copyright &y& Elsevier]

The persistence of species in reserves depends in large part on the persistence of functional ecological interactions. Despite their importance, however, ecological interactions have not yet been explicitly incorporated into conservation prioritization methods. We develop here a general method for incorporating consumer–resource interactions into spatial reserve design. This method protects spatial consumer–resource interactions by protecting areas that maintain the connectivity between the distribution of consumers and resources. We illustrate our method with a conservation planning case study of a mammalian predator, American marten (Martes americana), and its two primary prey species, Red-backed vole (Clethrionomys rutilus) and Deer mouse (Peromyscus maniculatus). The conservation goal was to identify a reserve for marten that comprised 12% of a forest management unit in the boreal forest in Québec, Canada. We compared reserves developed using analysis variants that utilized different levels of information about predator and prey habitat distributions, species-specific connectivity requirements, and interaction connectivity requirements. The inclusion of consumer–resource interactions in reserve-selection resulted in spatially aggregated reserves that maintained local habitat quality for the species. This spatial aggregation was not induced by applying a qualitative penalty for the boundary length of the reserve, but rather was a direct consequence of modelling the spatial needs of the interacting consumer and resources. Our method for maintaining connectivity between consumers and their resources within reserves can be applied even under the most extreme cases of either complete spatial overlap or complete spatial segregation of consumer–resource distributions. The method has been made available via public software. [Copyright &y& Elsevier]

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

Robust design of Marine Protected Areas in ocean environments is often challenging due to inadequate knowledge of biodiversity patterns, reflecting difficulties in the prediction of species distributions from sampling data that are often sparse or inadequate. Models that combine species and environmental data, such as Gradient Forests (GF), provide one analytical approach to this problem, efficiently combining available information to produce spatial models of species turnover throughout an area of interest. Spatial estimates of species turnover can then be classified to estimate spatial patterns in species composition; however, the performance of GF-based classifications within a conservation planning context has not previously been evaluated. Here we assess the utility for conservation planning (using the software Zonation) of a GF-based hierarchical classification that summarises spatial patterns in demersal fish composition in the oceans around New Zealand. Progressively more complex Zonation analyses assessed the effects of (i) varying the number of classification groups, (ii) adding information describing species turnover, and (iii) adding information describing spatial variation in demersal fish species richness. The best-performing GF-based conservation ranking used layers describing the distributions of 30 classification groups, demersal fish species turnover between these groups, and species richness. Conservation outcomes from this ranking were only marginally less efficient than those from a more conventional ranking that used 217 individual species distribution layers (7% less efficient). This indicates that GF-based classifications may provide a practical alternative for marine conservation planning. Additional advantages arise from the greater ease with which a single classification layer summarising complex biodiversity patterns can facilitate decision-making in participatory stakeholder processes. [Display omitted] • Gradient Forest-based environmental classifications described spatial patterns of demersal fish composition, turnover and richness. • The efficacy of Gradient Forest-based classifications for conservation planning were compared to 'traditional' estimates of individual species' distributions. • A single Gradient Forest-based classification was only marginally less efficient in a conservation planning analysis than a more conventional approach (7% less efficient). • Gradient Forest-based classifications summarise complex biodiversity patterns and provide a practical alternative for marine conservation planning. [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]

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: The most widespread reserve selection strategy is target-based planning, as specified under the framework of systematic conservation planning. Targets are given for the representation levels of biodiversity features, and site selection algorithms are employed to either meet the targets with least cost (the minimum set formulation) or to maximize the number of targets met with a given resource (maximum coverage). Benefit functions are another recent approach to reserve selection. In the benefit function framework the objective is to maximize the value of the reserve network, however value is defined. In one benefit function formulation value is a sum over species-specific values, and species-specific value is an increasing function of representation. This benefit function approach is computationally convenient, but because it allows free tradeoffs between species, it essentially makes the assumption that species are acting as surrogates, or samples from a larger regional species pool. The Zonation algorithm is a recent computational method that produces a hierarchy of conservation priority through the landscape. This hierarchy is produced via iterative removal of selection units (cells) using the criterion of least marginal loss of conservation value to decide which cell to remove next. The first variant of Zonation, here called core-area Zonation, has a characteristic of emphasizing core-areas of all species. Here I separate the Zonation meta-algorithm from the cell removal rule, the definition of marginal loss of conservation value utilized inside the algorithm. I show how additive benefit functions and target-based planning can be implemented into the Zonation framework via the use of particular kinds of cell removal rules. The core-area, additive benefit function and targeting benefit function variants of Zonation have interesting conceptual differences in how they treat and trade off between species in the planning process. [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: Conservation needs are often in direct competition with other forms of land-use, and therefore protection of biodiversity must be cost-efficient. While common reserve selection algorithms address this problem, quantitative planning tools often suggest an optimal set of sites that is not necessarily convenient for practical conservation. Besides cost-effective solutions we require flexibility if land-use conflicts are to be effectively resolved. We introduce a novel concept for site value in quantitative reserve planning. Replacement cost refers to the loss in solution value given that the optimal cost-efficient solution cannot be protected and alternative solutions, with particular sites forcibly included or excluded, are needed. This cost can be defined either in terms of loss of biological value or in terms of extra economic cost, and it has clear mathematical definitions in the context of benefit-function-based reserve planning. A main difference with the much-used concept of irreplaceability is that the latter tells about the likelihood of needing a site for achieving a particular conservation target. Instead, replacement cost tells us at what cost (biological or economic) can we exclude (or include) a site from the reserve network. Here, we illustrate the concept with hypothetical examples and show that replacement-cost analysis should prove useful in an interactive planning process, improving our understanding of the importance of a site for cost-efficient conservation. [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]

Abstract: Spatial reserve design concerns the planning of biological reserves for conservation. Typical reserve selection formulations operate on a large set of landscape elements, which could be grid cells or irregular sites, and selection algorithms aim to select the set of sites that achieves biodiversity target levels with minimum cost. This study presents a completely different optimization approach to reserve design. The reserve selection problem can be considerably simplified given the reasonable assumptions that: (i) maximum reserve cost is known; (ii) the approximate number of new reserves to be established is known; (iii) individual reserves need to be spatially contiguous. Further assuming the ability to construct a set of reserves in an efficient and close to optimal manner around designated reserve locations, the reserve selection problem can be turned into a search for a single interior point and area for each reserve. The utility of the proposed method is demonstrated for a data set of seven indicator species living in an conservation priority area in Southern Australia consisting of ca 73,000 selection units, with up to 10,000 cells chosen for inclusion in a reserve network. Requirements (ii) and (iii) above make interior point search computationally very efficient, allowing use with landscapes in the order of millions of elements. The method could also be used with non-linear species distribution models. [Copyright &y& Elsevier]

Classical metapopulations are groups of local populations living in networks of spatially distinct habitat patches in a balance between local extinctions and recolonizations of empty habitat. Models are needed for understanding and predicting metapopulation dynamics in changing landscapes. One particularly important question is what is the effect of habitat loss to the persistence of a metapopulation. A class of metapopulation models that have been successfully used in practical applications are called stochastic patch occupancy models (SPOMs), which model the presence/absence of the species on habitat patches as a Markov chain. The presence–absence assumption makes the model relatively parameter sparse, facilitates empirical data collection, and enables rigorous parameter estimation. This study reviews theory of SPOMs and describes a computational tool, called SPOMSIM, which allows one to simulate SPOMs and estimate parameters for them. SPOMSIM offers a range of choices for submodels; alternatives are provided for the functional forms of local extinction, the dispersal kernel, computation of connectivity, the colonization function, the implementation of the rescue effect and the implementation of regional stochasticity. SPOMSIM includes also, among other things, a utility based on hierarchical clustering for the analysis of the structure of a patch network, a reserve network optimization algorithm, and a patch system editor which makes it possible to investigate the consequences of changes in landscape structure. Potential uses for SPOMSIM include scientific metapopulation studies, teaching and conservation management. [Copyright &y& Elsevier]

• We used a combination of community attributes to measure urban Biodiversity Quality. • We introduce a protocol for spatial prioritization of urban Biodiversity Quality. • Expert evaluations and pre-existing spatial data were used in the protocol. • Priority mapping helps planners and developers to avoid biodiversity loss. • The method is easy to replicate but requires spatial data and expert knowledge. Spatial prioritization can produce useful information about biodiversity values from urban areas. However, its typical focus on (endangered) species distributions assumes a rather restricted approach to urban biodiversity. In 2006, Feest suggested that five attributes of species assemblages more holistically describe the so called "Biodiversity Quality" of an area: species richness, biomass, population density, evenness, and rarity. Here we apply these attributes in spatial prioritization for urban biodiversity, across ten taxonomic groups: vascular plants, polypores, fungi (other than polypores), birds, bats, mammals (other than bats), herpetofauna, butterflies, hymenoptera, and beetles. In addition, we introduce two more attributes relevant for urban biodiversity conservation: support for specialist species and regional representativeness of the species assemblages. First, spatial data about local urban biotopes was acquired. For each taxon, the capacity of each urban biotope to support the seven introduced attributes of Biodiversity Quality was evaluated via expert elicitation. Expert opinion was then translated into a spatial analysis implemented with the Zonation software. Different anthropogenic, semi-natural, and natural habitats, such as herb-rich forests, lakeshores, open wastelands, fortifications, and botanical gardens, were identified as important for urban Biodiversity Quality. To minimize negative impact on biodiversity, future construction and development should be directed to built-up areas and agricultural fields. Our conception of urban biodiversity lies in between species- and habitat/ecosystem -based analyses and offers a more comprehensive perception of urban biodiversity than a focus on species distributions only, which facilitates the planning of ecologically sustainable cities and biodiverse urban green infrastructure. [ABSTRACT FROM AUTHOR]

Abstract: The science and practice of ecological restoration are increasingly being called upon to compensate for the loss of biodiversity values caused by development projects. Biodiversity offsetting—compensating for losses of biodiversity at an impact site by generating ecologically equivalent gains elsewhere—therefore places substantial faith in the ability of restoration to recover lost biodiversity. Furthermore, the increase in offset-led restoration multiplies the consequences of failure to restore, since the promise of effective restoration may increase the chance that damage to biodiversity is permitted. But what evidence exists that restoration science and practice can reliably, or even feasibly, achieve the goal of ‘no net loss’ of biodiversity, and under what circumstances are successes and failures more likely? Using recent reviews of the restoration ecology literature, we examine the effectiveness of restoration as an approach for offsetting biodiversity loss, and conclude that many of the expectations set by current offset policy for ecological restoration remain unsupported by evidence. We introduce a conceptual model that illustrates three factors that limit the technical success of offsets: time lags, uncertainty and measurability of the value being offset. These factors can be managed to some extent through sound offset policy design that incorporates active adaptive management, time discounting, explicit accounting for uncertainty, and biodiversity banking. Nevertheless, the domain within which restoration can deliver ‘no net loss’ offsets remains small. A narrowing of the gap between the expectations set by offset policies and the practice of offsetting is urgently required and we urge the development of stronger links between restoration ecologists and those who make policies that are reliant upon restoration science. [Copyright &y& Elsevier]

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]

Gaps in research exist for country-wide analyses to identify areas of particular importance for biodiversity and ecosystem services to help reach Aichi Target 11 in developing countries. Here we provide a spatial conservation prioritization approach that ranks landowners for maximizing the representation of biodiversity features and ecosystem services, while exploring the trade-offs with agricultural and commercial forestry production and land cost, using Uruguay as a case study. Specifically, we explored four policy scenarios, ranging from a business as usual scenario where only biodiversity and ecosystem services were included in the analysis to a potentially unsustainable scenario where expansion of alternative land uses and economic development would be given higher priority over biodiversity and ecosystem services. At the 17% land target proposed for conservation, the representation levels for biodiversity and ecosystem services were, on average, higher under the business as usual scenario. However, a small addition to the proposed target (from 17 to 20%) allowed to meet same representation levels for biodiversity and ecosystem services, while decreasing conflict with agricultural and commercial forestry production and opportunity costs to local landowners. Under the unsustainable scenario, a striking 41% addition to the conservation target (from 17 to 58%) was needed to meet same representation levels for threatened ecosystems and ecosystem services, which are crucial to sustain human well-being. Our results highlight that more realistic and potentially higher conservation targets, than politically set targets, can be achieved at the country level when sustainable development needs are also accounted for. [ABSTRACT FROM AUTHOR]

Bats are considered important bioindicators and deliver key ecosystem services to humans. However, it is not clear how the individual and combined effects of climate change and land-use change will affect their conservation in the future. We used a spatial conservation prioritization framework to determine future shifts in the priority areas for the conservation of 169 bat species under projected climate and land-use change scenarios across Africa. Specifically, we modelled species distribution models under four different climate change scenarios at the 2050 horizon. We used land-use change scenarios within the spatial conservation prioritization framework to assess habitat quality in areas where bats may shift their distributions. Overall, bats’ representation within already existing protected areas in Africa was low (∼5% of their suitable habitat in protected areas which cover ∼7% of Africa). Accounting for future land-use change resulted in the largest shift in spatial priority areas for conservation actions, and species representation within priority areas for conservation actions decreased by ∼9%. A large proportion of spatial conservation priorities will shift from forested areas with little disturbance under present conditions to agricultural areas in the future. Planning land use to reduce impacts on bats in priority areas outside protected areas where bats will be shifting their ranges in the future is crucial to enhance their conservation and maintain the important ecosystem services they provide to humans. [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]

The voluntary non-monetary approach to conservation refers to actions that citizens or organizations could voluntarily implement in their area of influence without the incentive of monetary compensations. To be effectively implemented by untrained actors, actions should be clearly defined, straightforward to implement and not require specific scientific knowledge. The costs of actions should also be sufficiently affordable to be widely applied without monetary incentives. A voluntary non-monetary approach has so far not been clearly described as a distinct group of tools for nature conservation. Here we review the scarce scientific literature on the topic. To illustrate the applicability of a voluntary non-monetary approach to conservation, we then investigate its potential for farmland conservation. We considered a list of 119 actions available from “conservation-evidence”, a source of systematically collected evidence on effectiveness of conservation actions. Among 119 actions, 95 could be scored for feasibility of implementation, costs, and existence of evidence in UK, Spain and Finland. Sixteen to seventeen actions were potentially suitable for implementation by a voluntary non-monetary approach. This implies that the voluntary non-monetary approach could be widely applicable across many countries and environments. It is our hope that this study will represent a clarion call for conservation scientists to clearly recognize the voluntary non-monetary approach, its characteristics, and its potential for addressing conservation issues on private land. Adoption of such voluntary measures may be more dependent on encouragement (‘nudging’) than on the usual coercive or financial emphasis (‘shoving’). [ABSTRACT FROM AUTHOR]

Maintaining enough green areas and ensuring fair access to them is a common planning challenge in growing and densifying cities. Evaluations of green area access typically use metrics like population around green areas (within a certain buffer), but these do not fully ensure equitable access. We propose that using systematic and complementarity-driven spatial prioritization, often used in nature conservation planning, could assist in the complex planning challenge. Here, we demonstrate the use of spatial prioritization to identify green areas with highest recreational potential based on their type and their accessibility for the residents of the Helsinki Metropolitan area, the capital district of Finland. We calculated travel times from each city district to each green area. Travel times were calculated separately to local green areas using active travel modes (walking and biking), and to large forests (attracting people from near and far) using public transport. We prioritized the green areas using these multimodal travel times from each district and weighting the prioritization with population data with Zonation, conservation prioritization software. Compared to a typical buffer analysis (population within a 500 m buffer from green areas), our approach identified areas of high recreational potential in different parts of the study area. This approach allows systematic integration of travel-time-based accessibility measures into equitable spatial prioritization of recreational green areas. It can help urban planners to identify sets of green areas that best support the recreational needs of the residents across the city. • We demonstrated spatial prioritization for fair access to green areas. • We analyzed accessibility using different travel modes covering the whole city area. • Our method provides more equitable solutions than a typical buffer method. [ABSTRACT FROM AUTHOR]