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Studies examining the underlying causes of the distributions of species and their future trajectories under climate change have benefitted from the accumulation of measurements of thermal tolerance across the tree of life. However, gaps in the global coverage of heat-tolerance data for ectotherms persist on four critical fronts. First, most large-scale analyses treat heat tolerance as a fixed species trait despite that population-level variation can equal or exceed cross-species variation. Second, terrestrial non-arthropod invertebrates and aquatic ectotherms other than bony fish have been poorly sampled, particularly in boreal and tropical regions, the Indian Ocean and the mesopelagic-deep ocean. Third, the study of climate impacts on the heat tolerance of terrestrial ectotherms has often neglected the interaction of environmental temperatures with water availability. And fourth, the mechanisms driving the dependence of heat tolerance on oxygen supply-demand remain largely unknown. We contend that filling those data and knowledge gaps requires novel strategies for the ecophysiological sampling of the range of understudied populations and species that occupy the length of climatic gradients globally. Such developments are essential for comprehensively predicting species responses to climate change across aquatic and terrestrial biomes. [ABSTRACT FROM AUTHOR]

• We reviewed the literature of the last decade on food web ecology. • The diversity of approaches, scales and study objectives prevent synthesis. • Progress requires theory refinement and standards for data and methods. • Geographically distributed empirical and experimental studies are also required. Food webs represent the energy fluxes and the nutrient cycling between interacting species that underpin several ecosystem functions. Whether and how interactions vary across environmental gradients is still largely unknown. We reviewed the literature searching for systematic relationships between structural food-web properties and environmental gradients. Temperature and biotic factors are amongst the most frequently addressed drivers of food-web structure. We also assessed the degree to which food-web ecology has accomplished a mechanistic understanding of ecosystem functioning. We found that most studies are one-off descriptions of local food webs making it difficult to achieve an understanding of the response to human or environmental gradients. The lack of a consistent theory predicting how food webs change across environmental gradients, the diversity of objectives in food-web studies, and the absence of a standardized methodology for analysing them severely limit progress in the field. Moving forward requires the establishment of a core set of testable predictions, agreed standards for data collection and analysis, and the development of geographically distributed experimental studies of food-web dynamics. [ABSTRACT FROM AUTHOR]

Quantifying intraspecific variation in heat tolerance is critical to understand how species respond to climate change. In a previous study, we recorded variability in critical thermal maxima (CT max) by 3 °C among populations of small Iberian lizard species, which could substantially influence predictions of climate-driven activity restriction. Here, we undertake experiments to examine whether we could reproduce similar levels of heat-tolerance variability in response to water deficit. We hypothesized that deprivation of drinking water should increase variability in CT max between populations more than deprivation of food under the theoretical expectation that the variation of the more limiting resource must trigger stronger variation in physiological performance. We measured CT max after manipulating availability of live prey and drinking water in two populations of an arid and a mesic lizard species from the Iberian Peninsula. We quantified a mean CT max across all studied lizards of 44.2 °C ± 0.2 SE for the arid species and 41.7 °C ± 0.3 SE for the mesic species. Using multimodel inference, we found that water deprivation (combined with food supply) caused population differences in CT max by 3 to 4 °C which were two to three times wider than population differences due to food deprivation (combined with water supply) or to food and water provision. To highlight the need for more thermo-hydroregulatory research, we examined bias in research effort towards thermal versus hydric environmental effects on heat tolerance through a systematic literature review. We show that environmental temperature has been used five times more frequently than precipitation in ecological studies of heat tolerance of terrestrial species. Studies linking thermal tolerance of ectotherms to the interplay of air temperature and water availability are needed in the face of projected increases in aridity and drought in the 21st century, because the balance of body temperature and water resources are functionally interlinked. [ABSTRACT FROM AUTHOR]

Highlights • A framework to guide forest management to deal more effectively with plant invasions. • Models based on age/size classes represent a significant improvement. • Height classes are influenced by distinct factors operating at different scales. • Step forward for establishing management actions at appropriate spatial scales. • Way to enhance the efficiency of control actions on major forest invaders. Abstract Identifying the key factors driving invasion processes is crucial for designing and implementing appropriate management strategies. In fact, the importance of (model-based) prevention and early detection was highlighted in the recent European Union regulation on Invasive Alien Species. Models based on abundance estimates for different age/size classes would represent a significant improvement relative to the more usual models based only on species' occurrence data. Here, we evaluate the relative contribution of different environmental drivers to the spatial patterns of abundance of several height classes (or life-stages) of invasive tree populations at the regional scale, using a data-driven hierarchical modelling approach. A framework for modelling life-stages to obtain spatial projections of their potential occurrence or abundance has not been formalized before. We used Acacia dealbata (Silver-wattle) as a test species in northwest of Portugal, a heavily invaded region, and applied a multimodel inference to test the importance of various environmental drivers in explaining the abundance patterns of five plant height classes in local landscape mosaics. The ensemble of height classes is considered here as a proxy for population dynamics, life-stages and age of adult trees. In this test with A. dealbata , we used detailed field data on population height structure and calibrated an independent model for each height class. We found evidence to support our hypothesis that the distribution of height classes is mostly influenced by distinct factors operating at different scales. The spatial projections which resulted from several height class models provide an overview of population structure and invasion dynamics considering various life-stages, that is widely used in biodiversity and invasion research. The approach proposed here provides a framework to guide forest management to deal more effectively with plant invasions. It allows to test the effects of key invasion factors (depending on the focal species and on data availability) and supports the spatial identification of suitable areas for invasive species' occurrence while also accounting for the structural complexity of invasive species populations, thereby anticipating future invasion dynamics. The approach thus constitutes a step forward for establishing management actions at appropriate spatial scales and for focusing on earlier stages of invasion and their respective driving factors (regeneration niche), thereby enhancing the efficiency of control actions on major forest invaders. [ABSTRACT FROM AUTHOR]

• Flood susceptibility is used as a spatial indicator and a proxy for flood risk. • Incorporating flood susceptibility into SDMs explains its effects on biodiversity. • Remotely Sensed SAR images contribute to understanding flood effects on biodiversity. • Flood is a limiting factor in shaping amphibians, mammals, and reptiles' distributions. As significant ecosystem disturbances flooding events are expected to increase in both frequency and severity due to climate change, underscoring the critical need to understand their impact on biodiversity. In this study, we employ advanced remote sensing and machine learning methodologies to investigate the effects of flooding on biodiversity, from individual species to broader ecological communities. Specifically, we utilized Sentinel-1 synthetic aperture radar (SAR) images and an ensemble of machine-learning algorithms to derive a flood susceptibility indicator. Our primary objective is to investigate the potential benefits of incorporating flood susceptibility, as a proxy for flood risk, into species distribution models (SDMs). By doing so, we aim to improve the performance of SDMs and gain deeper insights into the consequences of floods to biodiversity. Within the biodiverse landscape of the Zagros Mountains, a crucial Irano-Anatolian biodiversity hotspots, we examined the sensitivity of mammals, amphibians, and reptiles' distributions to flooding. Our analysis compared the performance of models that combined flood susceptibility with climate variables against models relying solely on climate variables. The results indicate that the inclusion of flood susceptibility significantly improves the capacity of models to explain and map species distributions for 67% of the species in our study region. Notably, amphibians and mammals are more profoundly affected by flooding compared to reptiles. The study highlights the importance of incorporating flood susceptibility as a predictor variable in species distribution models to improve the baseline characterization of potential species distributions. The importance of this variable will obviously depend on the regional context and the species studied but its relevance is likely to increase with climate change. In summary, our research demonstrates the integration of remote sensing and machine learning as a potent approach to advance biodiversity data science, monitoring, and conservation in the face of climate-induced flooding. [ABSTRACT FROM AUTHOR]

Abstract: Gap analysis is a widely used method for assessing the representation of species in protected area (PA) networks. However, representation does not imply persistence. Here, we investigated whether gap analysis may result in misleading conservation guidelines by comparing the representation to two indicators of persistence. We ran a gap analysis with Finnish breeding birds and identified conservation priorities based on current distribution patterns. We tested the sensitivity of these results by using two target setting schemes and several thresholds defining the amount of protected area, and found the levels of representation identified by gap analysis to be robust. We then compared the gap analysis results with recent population trends and projected changes in potential suitable climate under different climate change scenarios for the year 2050. We show that although high latitude species are well represented in PAs, they are currently declining and are projected to lose climatic suitability in the near future. In contrast, low latitude species with poor representation in PAs have increasing population trends and are generally expected to expand their ranges into protected areas in the near future. This study demonstrates with empirical data a mismatch between representation in PAs and population trends, resulting in misleading understanding of current PA effectiveness. The mismatch is linked to the latitude of species distributions and corresponds to expected future changes, indicating that the patterns are potentially driven by climate change. We therefore urge practitioners and researchers to include better indicators of persistence in gap-analysis frameworks even for short term assessments. [Copyright &y& Elsevier]

Abstract: Biodiversity surrogates are needed because detailed data on the distributions of species and communities is very limited. Among alternative surrogate strategies there is an environmental diversity (ED) framework, which uses the p-median model to sample environmental space as evenly as possible. The underlying idea is that such a sample would represent underlying species diversity well. However, tests of the effectiveness of ED as a surrogate for species diversity have been inconclusive, and there is a debate concerning the usefulness of different implementations of ED. In particular, it has been argued that tests of the ED framework are flawed because they used discrete algorithms (calculating the p-median from an observed environmental space), while continuous versions of ED should be preferred (i.e. calculating the p-median from a theoretical, continuously spaced, environmental space). Unfortunately, progress has been hampered by lack of independent testing of the two ED approaches. Here, we provide the first empirical test of the effectiveness of both continuous and discrete ED using European distributions of amphibians and reptiles. Analyses were implemented considering two different extents: (1) western Europe and (2) the Iberian Peninsula. In both cases, implementations of ED represented species at a lower rate than expected by chance (P <0.05). Unlike suggested by some authors, the continuous ED was not consistently superior to the discrete form: continuous implementations of ED performed slightly better when fewer areas were selected and discrete ED performed better when the whole of the western European region was considered. Our results support findings that ED has only limited value as a surrogate for biodiversity and invite the interpretation that failure of ED is more likely to be related with oversimplification of assumptions underlying the model than to the particular p-median algorithm used. [Copyright &y& Elsevier]

Comparison of the two flagship species of British bumblebee conservation (Bombus distinguendus and B. sylvarum) with a widespread, common, and more stable species (B. pascuorum) shows (1) that the two rarer and range-declining species in Britain had narrower (more specialized) climatic niches in western Europe even before their most severe declines, and (2) that the areas where they persist in Britain from 2000 onwards are closer climatically to the centres of their pre-decline west-European climatic niches than the areas from which they have been lost. Although data are available for few bumblebee species at present and further tests are needed, the first result supports earlier suggestions that it is bumblebee species with narrower climatic niches that are most vulnerable to decline. The second result supports the suggestion that it is in areas nearer the edges of their climatic niches where these species are most vulnerable to decline, although this can be ameliorated locally by higher food-resource levels. This is not to say that all patterns of bumblebee decline have been influenced by climatic niche, particularly in North America. Nonetheless, in Britain we find that even without climatic change, an interaction between climatic niche and food-plant reductions from land-use change retains the potential to explain at least some of the broader patterns of which species have declined, where they have declined, and how they have declined. [Copyright &y& Elsevier]

Concern over implications of climate change for biodiversity has led to the use of bioclimatic models to forecast the range shifts of species under future climate-change scenarios. Recent studies have demonstrated that projections by alternative models can be so variable as to compromise their usefulness for guiding policy decisions. Here, we advocate the use of multiple models within an ensemble forecasting framework and describe alternative approaches to the analysis of bioclimatic ensembles, including bounding box, consensus and probabilistic techniques. We argue that, although improved accuracy can be delivered through the traditional tasks of trying to build better models with improved data, more robust forecasts can also be achieved if ensemble forecasts are produced and analysed appropriately. [Copyright &y& Elsevier]

I address the problem of the mismatch between the spatial resolution of data for species and reserves. Such mismatch may help to recognise variability in species recording in reserves. Using distribution data from 10 × 10 km grid cells for angiosperms, bryophytes, pteridophytes in Portugal, I investigate how mapping rules used to assign reserve coverages to grid cells would affect estimates of species representation in reserves. It was found that the estimated representation of species would be greatly affected by variation in the mapping rules used. The range of expected representation of species in reserves would vary from a minimum of 30% for bryophytes to a maximum of 63% for angiosperms. Current reserve networks would always represent fewer angiosperms than expected by chance; depending on the rules, more or fewer bryophytes than expected by chance; and slightly more, or just as many, pteridophytes as expected by chance. These results call for the need to assess sensitivity of reserve selection and evaluation procedures to data and decision-rules, without which it may be difficult to assess the effectiveness of reserves to represent biodiversity. [Copyright &y& Elsevier]

Understanding the biological correlates of range sizes in plant species is important to predict the response of species to climate change. We used climate envelope models to estimate species’ potential range size and range filling for 48 European tree species. We hypothesized that potential range size relates to the climatic tolerances of plant species, and that the degree of range filling is influenced by species dispersal. We tested these hypotheses using, for each species, estimates for tolerance to cold and drought, type of dispersal, fruit size and seed size. Consistent with previous observations, we found that both the size of potential ranges and range filling increase from south to north. Species tolerance to temperature and water stress, as well as their dispersal-related traits also showed marked spatial patterns. There was, moreover, a significant positive partial correlation between cold tolerance and potential range size, when drought tolerance was partialed out, and a non-significant partial correlation between drought tolerance and potential range size, with cold tolerance partialed out. Range filling was not significantly larger in species dispersed by wind than in those dispersed by animals. There was a negative correlation between seed mass and range filling, but its statistical significance varied across different subsets of species and climate envelope algorithms; the correlation between fruit length and range filling was not significant. We conclude that climatic tolerances and dispersal traits influence species range size and range filling, and thus affect the range dynamics of species in response to global change. Using traits will therefore help to predict future distribution of species under climate change. [ABSTRACT FROM AUTHOR]

Abstract: Given the rate of projected environmental change for the 21st century, urgent adaptation and mitigation measures are required to slow down the on-going erosion of biodiversity. Even though increasing evidence shows that recent human-induced environmental changes have already triggered species’ range shifts, changes in phenology and species’ extinctions, accurate projections of species’ responses to future environmental changes are more difficult to ascertain. This is problematic, since there is a growing awareness of the need to adopt proactive conservation planning measures using forecasts of species’ responses to future environmental changes. There is a substantial body of literature describing and assessing the impacts of various scenarios of climate and land-use change on species’ distributions. Model predictions include a wide range of assumptions and limitations that are widely acknowledged but compromise their use for developing reliable adaptation and mitigation strategies for biodiversity. Indeed, amongst the most used models, few, if any, explicitly deal with migration processes, the dynamics of population at the “trailing edge” of shifting populations, species’ interactions and the interaction between the effects of climate and land-use. In this review, we propose two main avenues to progress the understanding and prediction of the different processes occurring on the leading and trailing edge of the species’ distribution in response to any global change phenomena. Deliberately focusing on plant species, we first explore the different ways to incorporate species’ migration in the existing modelling approaches, given data and knowledge limitations and the dual effects of climate and land-use factors. Secondly, we explore the mechanisms and processes happening at the trailing edge of a shifting species’ distribution and how to implement them into a modelling approach. We finally conclude this review with clear guidelines on how such modelling improvements will benefit conservation strategies in a changing world. [Copyright &y& Elsevier]

The multiple uses of land-cover models have led to validation with choice metrics or an ad hoc choice of the validation metrics available. To address this, we have identified the major dimensions of land-cover maps that ought to be evaluated and devised a Similarity Validation (SimiVal) tool. SimiVal uses a linear regression to test a modelled projection against benchmark cases of, perfect, observed and systematic-bias, calculated by rescaling the metrics from a random case relative to the observed, perfect case. The most informative regression coefficients, p-value and slope, are plot on a ternary graph of ‘similarity space’ whose extremes are the three benchmark cases. SimiVal is tested on projections of two deliberately contrasting land-cover models to show the similarity between intra- and inter-model parameterisations. We find metrics of landscape structure are important in distinguishing between different projections of the same model. Predictive and exploratory models can benefit from the tool. [ABSTRACT FROM AUTHOR]

Inferring biotic interactions from functional, phylogenetic and geographical proxies remains one great challenge in ecology. We propose a conceptual framework to infer the backbone of biotic interaction networks within regional species pools. First, interacting groups are identified to order links and remove forbidden interactions between species. Second, additional links are removed by examination of the geographical context in which species co-occur. Third, hypotheses are proposed to establish interaction probabilities between species. We illustrate the framework using published food-webs in terrestrial and marine systems. We conclude that preliminary descriptions of the web of life can be made by careful integration of data with theory. [ABSTRACT FROM AUTHOR]

Highlights: [•] We analyze the potential impacts of future climatic, land use and vegetation changes on Iberian birds. [•] Bird species that are highly and negatively exposed to global change are currently less threatened. [•] Moreover those bird species also possess biological characteristics that render them more resilient to changes. [•] Thus, it is important to consider not only the exposure to changes but the ability of species to persist under such changes. [•] Alternative conservation actions might be required depending on the source of risk. [ABSTRACT FROM AUTHOR]

Abstract: The establishment of linkages between habitats is of great importance to avert the detrimental impacts of land fragmentation and climate change on biodiversity. Linkages need to be cost-efficient, and should account for specific dispersal requirements of species. Since cost-efficient linkages defined independently for each individual species are more costly than linkages optimised for multiple species, there is need for methods specifically designed to retrieve efficient linkages for multiple species. MulTyLink (Multiple Type Linkages) is a C++ open source program that defines cost-efficient linkages free of barriers for the species considered, and that allows species-specific dispersal requirements to be considered. Here we present, discuss and illustrate the algorithms used by MulTyLink to identify cost-efficient linkages for multiple species. [Copyright &y& Elsevier]