The development of species distribution models (SDMs) has benefited biodiversity conservation through their linkage of science to policy and decision processes. These models have evolved to provide scenarios of future landscapes based on known and projected environmental parameters. Whereas there are many caveats to their use, the persuasive power of the models for conveying the consequences of environmental change to the non-science community is immense. Scientists are obliged to convey the uncertainty of the futures depicted in their models, but also to involve the stakeholders who will shape those future conditions. Stakeholders can identify the natural resources they want to sustain, voice their priorities in environmental policy, and articulate the range of solutions they are willing to accept. The creation of alternative futures is an academic exercise if not linked to real viable decisions concerning important resources. SDMs only reach their full potential when they bring together scientists, public stakeholders and policy makers, and are used as an adaptive management tool to understand complex landscapes that are undergoing short- and long-term change.

Conservation managers and policy makers require models that can rank the impacts of multiple, interacting threats on biodiversity so that actions can be prioritized. An integrated modelling framework was used to predict the viability of plant populations for five species in southern California's Mediterranean-type ecosystem. The framework integrates forecasts of land-use change from an urban growth model with projections of future climatically-suitable habitat from climate and species distribution models, which are linked to a stochastic population model. The population model incorporates the effects of disturbance regimes and management actions on population viability. This framework: (1) ranks threats by their relative and cumulative impacts on population viability, such as land-use change, climate change, altered disturbance regimes or invasive species, and (2) ranks management responses in terms of their effectiveness for land protection, assisted dispersal, fire management and invasive species control. Too-frequent fire was often the top threat for the species studied, thus fire reduction was ranked the most important management option. Projected changes in suitable habitat as a result of climate change were generally large, but varied across species and climate scenarios; urban development could exacerbate loss of suitable habitat.

As climates change, some plant species will need to migrate across landscapes fragmented by unsuitable environments and human activities to colonize new areas with suitable climates as previously habited areas become uninhabitable. Previous modelling of plant's migration potential has generally assumed that climate changes at a constant rate, but this ignores many potentially important aspects of real climate variability. In this study, a spatially explicit simulation model was used to investigate how interannual climate variability, the occurrence of extreme events and step changes in climate might interact with gradual long-term climate change to affect plant species’ capacity to migrate across fragmented landscapes and persist. The considered types of climate variability generally exacerbated the negative effects of long-term climate change, with a few poignant exceptions where persistence of long-lived trees improved. Strategic habitat restoration ameliorated negative effects of climate variability. Plant functional characteristics strongly influenced most results. Any modelling of how climate change may affect species persistence, and how actions such as restoration may help species adapt, should account for both short-term climate variability and long-term change.

Climate change is predicted to be a major threat for biodiversity and, from a conservation prospective, it is important to understand how ecosystems may respond to that change. Predicted climate change effects on the distribution of meadows in the arid and semi-arid Argentinean Patagonia by 2050 were assessed for change trends and areas of desertification vulnerability using species distribution models (SDM) and climate-change models. Four modelling techniques composed an ensemble-forecasting approach. Suitable areas for meadows will decrease by 7.85% by 2050 given predicted changes in climate. However, there were two contrasting trends: severe reduction of suitable areas for meadows in north-west Patagonia and Tierra del Fuego Island, and an expansion of suitable areas for meadows in the south and a small section in the north-west. Meadows in Patagonia will likely be impacted by climate change, probably due to changes in precipitation regimes, and consequently many species that rely on meadows in an arid environment will also be impacted. Given the low level of protection of meadows in Patagonia, such information on meadow distribution and vulnerability to climate change will be important for increasing and improving the network of conservation areas through conservation planning.

Knowledge of the factors determining species distributions is essential for developing conservation strategies. Sandgrouse Pterocles alchata and P. orientalis are threatened in Spain, the stronghold of European populations. Spatial modelling was used to: (1) assess the relative importance of abiotic, anthropogenic and geographical factors in the distribution of both sandgrouse species, (2) determine the most important anthropogenic predictors for each species occurrence, and (3) identify areas where conservation efforts should be prioritized. Abiotic and anthropogenic factors explained most of the variation in sandgrouse distributions. Both species were associated with arid flatlands, arable land cover being the most important anthropogenic variable determining their distribution. The Common Agricultural Policy (CAP) is the main driver of agricultural management in Europe, and may thus have a direct effect on sandgrouse distributions. P. orientalis exhibited broader habitat tolerance than P. alchata; the latter species tolerates warmer climates. Consequently, the network of core and marginally suitable areas identified for each species differs, and connectivity between the populations of these areas seems unlikely. Potential future changes in sandgrouse distribution will probably be directed principally by the synergistic effects of climate change and expected land-use transformations resulting from the new CAP and ongoing population growth, urbanization and infrastructure development.

Spatial simulation may be used to model the potential effects of current biodiversity approaches on future habitat modification under differing climate change scenarios. To illustrate the approach, spatial simulation models, including landscape-level forest dynamics, were developed for a semi-natural grassland of conservation concern in a southern Italian protected area, which was exposed to woody vegetation encroachment. A forest landscape dynamics simulator (LANDIS-II) under conditions of climate change, current fire and alternative management regimes was used to develop scenario maps. Landscape pattern metrics provided data on fragmentation and habitat quality degradation, and quantified the spatial spread of different tree species within grassland habitats. The models indicated that approximately one-third of the grassland area would be impacted by loss, fragmentation and degradation in the next 150 years. Differing forest management regimes appear to influence the type of encroaching species and the density of encroaching vegetation. Habitat modifications are likely to affect species distribution and interactions, as well as local ecosystem functioning, leading to changes in estimated conservation value. A site-scale conservation strategy based on feasible integrated fire and forest management options is proposed, considering the debate on the effectiveness of protected areas for the conservation of ecosystem services in a changing climate. This needs to be tested through further modelling and scenario analysis, which would benefit from the enhancement of current modelling capabilities of LANDIS-II and from combination with remote sensing technologies, to provide early signals of environmental shifts both within and outside protected areas.

Transport infrastructures are a major driver of global landscape change. In many areas, highways were built before environmental impact assessments required the implementation of wildlife crossing structures. A fundamental task in the development of ecological networks is identifying areas where dispersal pathways of vulnerable populations may be blocked or affected by high volume roads. Financial considerations may limit investment, thus it is vital to establish the relative contribution of each road defragmentation location to upholding habitat connectivity and availability. In this paper, recent methodological developments in habitat network analysis, derived from the probability of connectivity index, were refined and used to evaluate the role of each highway defragmentation location in restoring landscape connectivity. The forest protected area network in the Basque country (northern Spain) was selected as an illustrative case study. The proposed approach was able to quantify and effectively account for a combination of factors determining the contribution of each highway defragmentation location to upholding connectivity, which are rarely jointly considered in analyses oriented to support restoration decisions in landscapes affected by the barrier effect of transport infrastructures. The contribution to connectivity of each defragmentation location depended on its topological position in the landscape, on the relative decrease in the effective distance among habitat areas that results from the permeability restoration at that location, on the distance from the defragmentation location to other alternative wildlife crossing structures already existing in the landscape, on the amount of habitat in the areas connected by the linkages that run through the defragmentation location and on the dispersal abilities of the focal species.

The Tonle Sap is the largest wetland in South-east Asia and the heart of the largest inland fishery in the world. Its unique flood pulse system and annual flow reversal is a hotspot for biodiversity and productivity, as well as an essential habitat for many endangered fishes and birds. Despite predicted changes to the wetland's hydrology due to climate change and hydropower development in the Mekong, the consequent impacts on the fauna of the lake are poorly understood. A spatial modelling framework was developed to simulate the impact of potential scenarios of change using relationships between fauna and biophysical characteristics. Potential impacts on 61 animal species with documented nutritional, conservation or ecological value were examined. A large number of species rely on gallery forest to provide important habitats for their life history, yet this area is likely to be highly impacted by permanent inundation. There is a strong synchronicity between life histories and the flood pulse; consequently continued hydrological disruptions will have a significant impact on ecosystem dynamics, imposing further challenges to conservation. Protecting areas that may become suitable for gallery forests and shrublands under a modified flood regime will be crucial to management planning and the maintenance of a diverse and healthy ecosystem.

The ngwayir (western ringtail possum Pseudocheirus occidentalis) is an arboreal species endemic to south-western Australia. The range and population of this species have been significantly reduced through multiple anthropogenic impacts. Classified as vulnerable, the ngwayir is highly susceptible to extremes of temperature and reduced water intake. Ngwayir distribution was determined using three different species distribution models using ngwayir presence records related to a set of 19 bioclimatic variables derived from historical climate data, overlaid with 2050 climate change scenarios. MaxEnt was used to identify core habitat and demonstrate how this habitat may be impacted. A supplementary modelling exercise was also conducted to ascertain potential impacts on the tree species that are core habitat for ngwayir. All models predicted a reduction of up to 60% in the range of the ngwayir and its habitat, as a result of global warming towards the south-west of the project area, with a mean potential distribution of 10.3% of the total modelled area of 561 059 km2. All three tree species modelled (jarrah, marri and peppermint) were predicted to experience similar contractions in range throughout most of the predicted ngwayir range, although their distributions differed. Populations of ngwayir persisting outside core habitat may indicate potential conservation opportunities.

The availability of spatial data sourced from either field-derived or satellite-based systems has created new opportunities to estimate and/or monitor changes in carbon sequestration rates, climate change impacts or the potential habitat alterations occurring across large landscapes. However, an effort to create models is not standardized, in part, due to different needs and data sources available for the models. For example, data may have different spatial resolutions with varying degrees of complexity in regards to inputs and statistical methods. This study determines effects of 20, 15, 10, five and one km sampling resolutions on detection of changes in net primary productivity (NPP), occupancy selection criteria for areas to be included in the sample and identification of significant variables impacting NPP in Indonesia forests. Production forest designated for selective harvest was used to define the sampling areas. Variances explained by predictive models were similar across cell sizes although relative importance of variables was different. Partial dependence plots were used to search for potential thresholds or tipping points of NPP change as affected by an independent variable such as minimum daytime temperature. Applying different cell occupancy selection rules significantly changed the overall distribution of NPP values. The magnitude of those changes within a cell size varied with changes in cell size. The mean estimated NPP for production forests across Indonesia differed significantly at every sampling resolution and occupancy selection criteria. Lows ranged from 1.107 to 1.121 kg C m−2 yr−1 for the 1-km cell size for the three occupancy selection criteria with highs ranging from 1.245 to 1.189 kg C m−2 yr−1 for the 20-km cell size. The difference in NPP values between these two cell sizes for the three occupancy selection criteria extrapolates to a range in annual biomass of 132 × 106 to 66 × 106 t for the total area of production forests in Indonesia.

The fundamental goal of conservation planning is biodiversity persistence, yet most reserve selection methods prioritize sites using occurrence data. Numerous empirical studies support the notion that defining and measuring objectives in terms of species richness (where the value of a site is equal to the number of species it contains, or contributes to an existing reserve network) can be inadequate for maintaining biodiversity in the long-term. An existing site-assessment framework that implicitly maximized the persistence probability of multiple species was integrated with a dynamic optimization model. The problem of sequential reserve selection as a Markov decision process was combined with stochastic dynamic programming to find the optimal solution. The approach represents a compromise between representation-based approaches (maximizing occurrences) and more complex tools, like spatially-explicit population models. The method, the inherent problems and interesting conclusions are illustrated with a land acquisition case study on the central Platte River.

The distribution of subterranean copepods may reflect the persistence of cave assemblages in relation to the environmental health of the overlying landscape. Areas supporting groundwater fauna were established by modelling the persistence of seven copepod species using a geographical information system (GIS). Environmental drivers were found to influence subterranean copepod distribution in the caves of the Romanian Carpathians. Habitat-based modelling, using ordinary least squares regression and geographically-weighted regression to identify the significant predictors explaining copepod habitat suitability, predicted suitable areas for the selected taxa. The most constant predictor was land cover, a measure of human impact and climate change, followed by precipitation and altitude. The model performed well for the majority of analysed taxa, and the areas predicted as suitable for narrowly distributed taxa overlapped with observed distributions. GIS facilitated the prediction of suitable habitat, and also enabled spatial autocorrelation to be tested. The results of this study demonstrate the importance of sustainable management of the terrestrial surface in limestone areas in conserving copepod biodiversity.

Ants are among the worst invasive species, and can have tremendous negative impacts on native biodiversity, agriculture, estates, property and human health. Invasive ants are extremely difficult to control, and thus early detection is essential to prevent ant invasions, in particular through surveillance efforts at ports of entry. This paper assesses the potential distribution of 14 of the worst invasive ant species in France, under current and future climatic conditions. Consensus species distribution models, using five different modelling techniques, three global climate models and two CO2 emission scenarios, indicated that France presented suitable areas for 10/14 species, including five listed on the Invasive Species Specialist Group's selection of the world's 100 worst invasive species. Among these 10 species, eight were predicted to increase their potential range with climate change. Areas with the highest concentration of potential invaders were mainly located along the coastline, especially in the south-west of France, but all departments appeared to be climatically suitable for at least two invasive species. A ranking of climatic suitability per species for 17 major airports and 14 maritime ports indicated that the ports of entry with the highest suitability were located in Biarritz, Toulon and Nice, and the species with the greatest potential distribution in France were Lasius neglectus and Linepithema humile, followed by Solenopsis richteri, Pheidole megacephala and Wasmannia auropunctata.

In the face of an already changing climate, conservation practitioners and local communities face the major challenge of how to plan for a future climate. In data-sparse areas of the world, where action is often most needed, the daunting scope of the problem can lead to inaction. This paper shows that climate adaptation planning can be accomplished successfully with publicly and globally available data by linking science and stakeholders through a facilitated process. Working with local stakeholders in the western Tanzanian Greater Mahale and Greater Gombe Ecosystems, future climate projections produced using Climate Wizard and analyses of literature provided an understanding of the climate vulnerabilities of local ecosystems and human livelihoods. Facilitated workshops enabled local stakeholders to use this information to develop conceptual models and hypotheses of change for these systems, and to identify possible modifications to conservation plans. Here, climate change planning required the modification of most current conservation strategies, developing some new strategies and abandoning others. The paper indicates that climate adaptation planning is achievable even in data-sparse rural and developing areas, but requires appropriate scientific analyses, engaged stakeholders and a facilitated process.