Mar Cabeza

Climate change threatens European conservation areas

Europe has the worlds most extensive network of conservation areas. Conservation areas are selected without taking into account the effects of climate change. How effectively would such areas conserve biodiversity under climate change? We assess the effectiveness of protected areas and the Natura 2000 network in conserving a large proportion of European plant and terrestrial vertebrate species under climate change. We found that by 2080, 58 ± 2.6% of the species would lose suitable climate in protected areas, whereas losses affected 63 ± 2.1% of the species of European concern occurring in Natura 2000 areas. Protected areas are expected to retain climatic suitability for species better than unprotected areas (P<0.001), but Natura 2000 areas retain climate suitability for species no better and sometimes less effectively than unprotected areas. The risk is high that ongoing efforts to conserve Europes biodiversity are jeopardized by climate change. New policies are required to avert this risk.

Design of reserve networks and the persistence of biodiversity

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

Multiple Dimensions of Climate Change and Their Implications for Biodiversity

Background Changes in Earth’s climate over time can be measured in many ways. The different metrics available represent alternative dimensions of climate change, each with distinct implications for biodiversity conservation and other sectors. However, this diversity is rarely recognized. At any given locality, average temperature or precipitation can increase or decrease, extreme values can become more intense or frequent, and the timing of specific climatic events can shift. At the same time, climatic conditions are redistributed at broader spatial extents. Across sets of localities, particular climatic conditions can become more or less available and can shift closer or farther in position at different velocities. Metrics quantifying these and other dimensions of change are commonly used in basic and applied sciences. In ecological contexts, individual metrics have helped to explain the role of past climate changes in driving species diversity or extinctions and to forecast the exposure of biodiversity to future climate changes. Yet, a comparison of the many alternative metrics in use is lacking to gain understanding of their properties and guide their use in biodiversity assessments. The diversity of metrics of climate change. Climate parameters, such as temperature or precipitation, can change at individual localities over time (left), whereas shifts in the distribution of climatic conditions across sets of localities can also occur (right). Local metrics can quantify changes in the magnitude of average or extreme values, as well as shifts in the timing of climatic events. Regional metrics describe how specific climatic conditions may increase or decrease in area, become more dissimilar to past climatic conditions, or move in space. These and other commonly used metrics of climate change describe different dimensions of change and are expected to relate to distinct challenges for biodiversity. Different metrics thus provide complementary information when describing future climates and their potential effects. Examining metrics in combination can show how they interact to exacerbate or lessen species’ exposure to climate change. Advances Our review demonstrates that six commonly used metrics of climate change show contrasting patterns under 21st-century climate forecasts across the world. For example, whereas polar climates are projected to warm and shrink in area, the tropics see the emergence of novel climatic conditions and undergo local changes in average climates beyond past variability. To help interpret metrics of climate change, our review critically assesses the ecological implications of different metrics. Supported by examples of empirical links between observed changes in biological systems and different dimensions of climate change, we outline a conceptual framework for classification of climate change metrics according to the types of threat and opportunity they are likely to impose on biodiversity. Climate changes at the locality level are often associated with demographic threats and opportunities at the population level, whereas changes across localities can have positive or negative implications for the size and the position of species’ ranges. Outlook Forecasting the long-term impacts of future climate changes on biodiversity is challenging, not least because the responses of organisms are contingent on demographic, physiological, and evolutionary mechanisms, as well as on the interaction with other human-induced stressors such as habitat fragmentation. Lack of data for the majority of species on Earth further hampers the use of available bioclimatic modeling methods. By contrast, the use of simple metrics of climate change is more easily scalable to wholesale biodiversity. When appropriately implemented, such examination can provide a first-order assessment of the challenges that species are potentially exposed to, and in many circumstances, it might be the only option available. Interpreting Climate Change Metrics While forecasts of climate change effects on biodiversity rely mostly on bioclimatic modeling approaches of varying complexity, an alternative to existing models is to use simple metrics to quantify the exposure of regions to climate changes over time and relate them to different threats and opportunities for biodiversity. It remains poorly understood how existing metrics differ in the information they provide, specifically in the context of biodiversity. Garcia et al. (p. 10.1126/science.1247579) review the variety of metrics commonly used to describe climate change in biodiversity-impact assessments covering local changes in climate averages and extremes, regional changes in the availability and position of climates, and the velocity of climate change. While metrics are often arbitrarily chosen in studies of ecology and evolution, and interchangeably used as synonyms of climate change, they capture different dimensions of change and reveal contrasting spatial patterns across the world. Defining the links between climate change dimensions and the challenges they represent to species leads to a framework for interpreting climate change metrics. The 21st century is projected to witness unprecedented climatic changes, with greater warming often reported for high latitudes. Yet, climate change can be measured in a variety of ways, reflecting distinct dimensions of change with unequal spatial patterns across the world. Polar climates are projected to not only warm, but also to shrink in area. By contrast, today’s hot and arid climates are expected to expand worldwide and to reach climate states with no current analog. Although rarely appreciated in combination, these multiple dimensions of change convey complementary information. We review existing climate change metrics and discuss how they relate to threats and opportunities for biodiversity. Interpreting climate change metrics is particularly useful for unknown or poorly described species, which represent most of Earth’s biodiversity.

SINGLE‐SPECIES DYNAMIC SITE SELECTION

Methods for designing regional reserve networks mostly concentrate on pro- viding maximal representation of species occurring in the region. Representation-based methods, however, typically consider a static snapshot of species incidences, and the spatial dynamics of the species are ignored. It has been empirically demonstrated that reserves designed using representation do not guarantee another important goal of reserve design: long-term persistence. The question studied here is the following: Which subset of sites do you select to maximize the long-term persistence of a species living in a metapopulation, given that each site has a cost and the amount of resource (e.g., money) available is limited? We present an optimization method, which uses a combination of evolutionary optimization (a genetic algorithm) and local search to find the optimal selection of sites. The quality of each candidate solution is evaluated using a spatially realistic metapopulation model, the incidence function model. The proposed method is applied to a metapopulation of the false heath fritillary butterfly, an endangered species in Finland. With this data set, the proposed estimation method produces intuitively acceptable and consistent results within minutes of computation time. Sites favored by the algorithm are located in three patch clusters, and they tend to be inexpensive and initially occupied. Expensive and/or very isolated patches are rarely selected into the optimal site selection.

Exploring consensus in 21st century projections of climatically suitable areas for African vertebrates

Africa is predicted to be highly vulnerable to 21st century climatic changes. Assessing the impacts of these changes on Africas biodiversity is, however, plagued by uncertainties, and markedly different results can be obtained from alternative bioclimatic envelope models or future climate projections. Using an ensemble forecasting framework, we examine projections of future shifts in climatic suitability, and their methodological uncertainties, for over 2500 species of mammals, birds, amphibians and snakes in sub-Saharan Africa. To summarize a priori the variability in the ensemble of 17 general circulation models, we introduce a consensus methodology that combines co-varying models. Thus, we quantify and map the relative contribution to uncertainty of seven bioclimatic envelope models, three multi-model climate projections and three emissions scenarios, and explore the resulting variability in species turnover estimates. We show that bioclimatic envelope models contribute most to variability, particularly in projected novel climatic conditions over Sahelian and southern Saharan Africa. To summarize agreements among projections from the bioclimatic envelope models we compare five consensus methodologies, which generally increase or retain projection accuracy and provide consistent estimates of species turnover. Variability from emissions scenarios increases towards late-century and affects southern regions of high species turnover centred in arid Namibia. Twofold differences in median species turnover across the study area emerge among alternative climate projections and emissions scenarios. Our ensemble of projections underscores the potential bias when using a single algorithm or climate projection for Africa, and provides a cautious first approximation of the potential exposure of sub-Saharan African vertebrates to climatic changes. The future use and further development of bioclimatic envelope modelling will hinge on the interpretation of results in the light of methodological as well as biological uncertainties. Here, we provide a framework to address methodological uncertainties and contextualize results.

Conservation planning with uncertain climate change projections.

Climate change is affecting biodiversity worldwide, but conservation responses are constrained by considerable uncertainty regarding the magnitude, rate and ecological consequences of expected climate change. Here we propose a framework to account for several sources of uncertainty in conservation prioritization. Within this framework we account for uncertainties arising from (i) species distributions that shift following climate change, (ii) basic connectivity requirements of species, (iii) alternative climate change scenarios and their impacts, (iv) in the modelling of species distributions, and (v) different levels of confidence about present and future. When future impacts of climate change are uncertain, robustness of decision-making can be improved by quantifying the risks and trade-offs associated with climate scenarios. Sensible prioritization that accounts simultaneously for the present and potential future distributions of species is achievable without overly jeopardising present-day conservation values. Doing so requires systematic treatment of uncertainties and testing of the sensitivity of results to assumptions about climate. We illustrate the proposed framework by identifying priority areas for amphibians and reptiles in Europe.

Connectivity, probabilities and persistence: comparing reserve selection strategies

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.

Governance factors in the identification of global conservation priorities for mammals

Global conservation priorities have often been identified based on the combination of species richness and threat information. With the development of the field of systematic conservation planning, more attention has been given to conservation costs. This leads to prioritizing developing countries, where costs are generally low and biodiversity is high. But many of these countries have poor governance, which may result in ineffective conservation or in larger costs than initially expected. We explore how the consideration of governance affects the selection of global conservation priorities for the worlds mammals in a complementarity-based conservation prioritization. We use data on Control of Corruption (Worldwide Governance Indicators project) as an indicator of governance effectiveness, and gross domestic product per capita as an indicator of cost. We show that, while core areas with high levels of endemism are always selected as important regardless of governance and cost values, there are clear regional differences in selected sites when biodiversity, cost or governance are taken into account separately. Overall, the analysis supports the concentration of conservation efforts in most of the regions generally considered of high priority, but stresses the need for different conservation approaches in different continents owing to spatial patterns of governance and economic development.

Linking like with like: optimising connectivity between environmentally-similar habitats

Habitat fragmentation is one of the greatest threats to biodiversity. To minimise the effect of fragmentation on biodiversity, connectivity between otherwise isolated habitats should be promoted. However, the identification of linkages favouring connectivity is not trivial. Firstly, they compete with other land uses, so they need to be cost-efficient. Secondly, linkages for one species might be barriers for others, so they should effectively account for distinct mobility requirements. Thirdly, detailed information on the auto-ecology of most of the species is lacking, so linkages need being defined based on surrogates. In order to address these challenges we develop a framework that (a) identifies environmentally-similar habitats; (b) identifies environmental barriers (i.e., regions with a very distinct environment from the areas to be linked), and; (c) determines cost-efficient linkages between environmentally-similar habitats, free from environmental barriers. The assumption is that species with similar ecological requirements occupy the same environments, so environmental similarity provides a rationale for the identification of the areas that need to be linked. A variant of the classical minimum Steiner tree problem in graphs is used to address c). We present a heuristic for this problem that is capable of handling large datasets. To illustrate the framework we identify linkages between environmentally-similar protected areas in the Iberian Peninsula. The Natura 2000 network is used as a positive ‘attractor’ of links while the human footprint is used as ‘repellent’ of links. We compare the outcomes of our approach with cost-efficient networks linking protected areas that disregard the effect of environmental barriers. As expected, the latter achieved a smaller area covered with linkages, but with barriers that can significantly reduce the permeability of the landscape for the dispersal of some species.

Costs of Integrating Economics and Conservation Planning

Recent literature on systematic conservation planning has focused strongly on economics. It is a necessary component of efficient conservation planning because the question is about effective resource allocation. Nevertheless, there is an increasing tendency toward economic factors overriding biological considerations. Focusing too narrowly on economic cost may lead us back toward solutions resembling those obtained by opportunistic choice of areas, the avoidance of which was the motivation for development of systematic approaches. Moreover, there are many overlooked difficulties in incorporating economic considerations reliably into conservation planning because available economic data and the free market are complex. For instance, economies based on free markets tend to be shortsighted, whereas biodiversity conservation aims far into the future. Although economic data are necessary, they should not be relied on too heavily or considered separately from other sociopolitical factors. We suggest focusing on development of more-comprehensive ecological-economic modeling, while not forgetting the importance of purely biological analyses that are needed as a point of reference for evaluating conservation outcomes.