Do ecological differences between taxonomic groups influence the relationship between species’ distributions and climate? A global meta-analysis using species distribution models

Understanding whether and how ecological traits affect species’ geographic distributions is a fundamental issue that bridges ecology and biogeography. While climate is thought to be the major determinant of species’ distributions, there is considerable variation in the strength of species’ climate–distribution relationships. One potential explanation is that species with relatively low dispersal ability cannot reach all geographic areas where climatic conditions are suitable. We tested the hypothesis that species from different taxonomic groups varied in their climate–distribution relationships because of differences in life history strategies, in particular dispersal ability. We conducted a meta-analysis by combining the discrimination ability (AUC values) from 4317 species distribution models (SDMs) using fit as an indication of the strength of the species’ climate–distribution relationship. We found significant differences in the strength of species’ climate–distribution relationships across taxonomic groups, however we did not find support for the dispersal hypothesis. Our results suggest that relevant ecological trait variation among broad taxonomic groups may be related to differences in species’ climate–distribution relationships, however which ecological traits are important remains unclear

Presence-absence versus presence-only modelling methods for predicting bird habitat suitability

Habitat suitability models can be generated using methods requiring information on species presence or species presence and absence. Knowledge of the predictive performance of such methods becomes a critical issue to establish their optimal scope of application for mapping current species distributions under different constraints. Here, we use breeding bird atlas data in Catalonia as a working example and attempt to analyse the relative performance of two methods: the Ecological Niche factor Analysis (ENFA) using presence data only and Generalised Linear Models (GLM) using presence/absence data. Models were run on a set of forest species with similar habitat requirements, but with varying occurrence rates (prevalence) and niche positions (marginality). Our results support the idea that GLM predictions are more accurate than those obtained with ENFA. This was particularly true when species were using available habitats proportionally to their suitability, making absence data reliable and useful to enhance model calibration. Species marginality in niche space was also correlated to predictive accuracy, i.e. species with less restricted ecological requirements were modelled less accurately than species with more restricted requirements. This pattern was irrespective of the method employed. Models for wide-ranging and tolerant species were more sensitive to absence data, suggesting that presence/absence methods may be particularly important for predicting distributions of this type of species. We conclude that modellers should consider that species ecological characteristics are critical in determining the accuracy of models and that it is difficult to predict generalist species distributions accurately and this is independent of the method used. Being based on distinct approaches regarding adjustment to data and data quality, habitat distribution modelling methods cover different application areas, making it difficult to identify one that should be universally applicable. Our results suggest however, that if absence data is available, methods using this information should be preferably used in most situations

Predicting freshwater habitat integrity using land-use surrogates

Freshwater biodiversity is globally threatened due to human disturbances, but freshwater ecosystems have been accorded lessprotection than their terrestrial and marine counterparts. Few criteria exist for assessing the habitat integrity of rivers and data used for such assessments are generally of limited geographical coverage. Here, we use a fine-scale dataset describing river integrity in north-western South Africa to explore the extent to which measures of freshwater habitat integrity can be predicted from remotely sensed data, which are readily available in many parts of the world. A spatial statistical model was built using broad land-cover variables to predict the habitat integrity (subdivided into riparian and instream integrity) of rivers.We also explored the importance of the spatial scale. Results showed that riparian and, to a lesser degree, instream habitat integrity of river systems could be predicted with reasonable accuracy. The total area under natural vegetation was the most significant predictor of riparian integrity, which is best predicted by land-use activities at catchment level, rather than more locally. Our GIS-based model thus provides a fine-scale approach to assessing river habitat integrity as a supplement to landscape-level conservation plans for river systems, and represents a significant contribution towards the monitoring componentof the River Health Programme (RHP), which reports on the state of rivers in South Africa

Global patterns of β-diversity along the phylogenetic time-scale : the role of climate and plate tectonics

Aim: We aimed to assess the relative influence of the historical and contemporary processes determining global patterns of current \u3b2-diversity. Specifically, we quantified the relative effects of contemporary climate and historical plate tectonics on \u3b2-diversity at different phylogenetic scales. Location: Global. Time Period: Contemporaneous. Major taxa studied: Mammals and birds. Methods: We analysed the current \u3b2-diversity patterns of birds and mammal assemblages at sequential depths in the phylogeny, that is, from the tips to deeper branches. This was done by slicing bird and mammal phylogenetic trees into 66 time slices of 1 Ma (from 0 to 65 Ma) and recording the branches within each slice. Using global distribution data, we defined the branches\u2019 geographical distribution as the union of the corresponding downstream species distributions. For each time slice, we (a) computed pairwise \u3b2-diversity across all the grid cells for the whole world and (b) estimated the correlation between this \u3b2-diversity matrix and contemporary climatic and geographical distances, and past geological distances, a proxy for plate tectonics. Results: Contemporary climate best explained the \u3b2-diversity of shallow branches (i.e., species). For mammals, the geographical isolation of landmasses generated by plate tectonics best explained the \u3b2-diversity of deeper branches, whereas the effect of past isolation was weaker for birds. Main conclusions: Our study shows that the relative influence of contemporary climate and plate tectonics on the \u3b2-diversity of bird and mammal assemblages varies along the phylogenetic time-scale. Our phylogenetic time-scale approach is general and flexible enough to be applied to a broad spectrum of study systems and spatial scales

How to best threshold and validate stacked species assemblages? Community optimisation might hold the answer

1. The popularity of species distribution models (SDMs) and the associated stacked species distribution models (S-SDMs), as tools for community ecologists, largely increased in recent years. However, while some consensus was reached about the best methods to threshold and evaluate individual SDMs, little agreement exists on how to best assemble individual SDMs into communities, i.e. how to build and assess S-SDM predictions. 2. Here, we used published data of insects and plants collected within the same study region to test (1) if the most established thresholding methods to optimize single species prediction are also the best choice for predicting species assemblage composition, or if community-based thresholding can be a better alternative, and (2) whether the optimal thresholding method depends on taxa, prevalence distribution and/or species richness. Based on a comparison of different evaluation approaches we provide guidelines for a robust community cross-validation framework, to use if spatial or temporal independent data are unavailable. 3. Our results showed that the selection of the “optimal” assembly strategy mostly depends on the evaluation approach rather than taxa, prevalence distribution, regional species pool or species richness. If evaluated with independent data or reliable cross-validation, community-based thresholding seems superior compared to single species optimisation. However, many published studies did not evaluate community projections with independent data, often leading to overoptimistic community evaluation metrics based on single species optimisation. 4. The fact that most of the reviewed S-SDM studies reported over-fitted community evaluation metrics highlights the importance of developing clear evaluation guidelines for community models. Here, we move a first step in this direction, providing a framework for cross-validation at the community level

Evaluating the ecological realism of plant species distribution models with ecological indicator values

Species distribution models (SDMs) are routinely applied to assess current as well as future species distributions, for example to assess impacts of future environmental change on biodiversity or to underpin conservation planning. It has been repeatedly emphasized that SDMs should be evaluated based not only on their goodness of fit to the data, but also on the realism of the modelled ecological responses. However, possibilities for the latter are hampered by limited knowledge on the true responses as well as a lack of quantitative evaluation methods. Here we compared modelled niche optima obtained from European-scale SDMs of 1,476 terrestrial vascular plant species with empirical ecological indicator values indicating the preferences of plant species for key environmental conditions. For each plant species we first fitted an ensemble SDM including three modeling techniques (GLM, GAM and BRT) and extracted niche optima for climate, soil, land use and nitrogen deposition variables with a large explanatory power for the occurrence of that species. We then compared these SDM-derived niche optima with the ecological indicator values by means of bivariate correlation analysis. We found weak to moderate correlations in the expected direction between the SDM-derived niche optima and ecological indicator values. The strongest correlation occurred between the modelled optima for growing degree days and the ecological indicator values for temperature. Correlations were weaker for SDM-derived niche optima with a more distal relationship to ecological indicator values (notably precipitation and soil moisture). Further, correlations were consistently highest for BRT, followed by GLM and GAM. Our method gives insight into the ecological realism of modelled niche optima and projected core habitats and can be used to improve SDMs by making a more informed selection of environmental variables and modeling techniques

Improving spatial predictions of taxonomic, functional and phylogenetic diversity

In this study, we compare two community modelling approaches to determine their ability to predict the taxonomic, functional and phylogenetic properties of plant assemblages along a broad elevation gradient and at a fine resolution. The first method is the standard stacking individual species distribution modelling (SSDM) approach, which applies a simple environmental filter to predict species assemblages. The second method couples the SSDM and macroecological modelling (MEMSSDM-MEM) approaches to impose a limit on the number of species co-occurring at each site. Because the detection of diversity patterns can be influenced by different levels of phylogenetic or functional trees, we also examine whether performing our analyses from broad to more exact structures in the trees influences the performance of the two modelling approaches when calculating diversity indices. We found that coupling the SSDM with the MEM improves the overall predictions for the three diversity facets compared with those of the SSDM alone. The accuracy of the SSDM predictions for the diversity indices varied greatly along the elevation gradient, and when considering broad to more exact structure in the functional and phylogenetic trees, the SSDM-MEM predictions were more stable. SSDM-MEM moderately but significantly improved the prediction of taxonomic diversity, which was mainly driven by the corrected number of predicted species. The performance of both modelling frameworks increased when predicting the functional and phylogenetic diversity indices. In particular, fair predictions of the taxonomic composition by SSDM-MEM led to increasingly accurate predictions of the functional and phylogenetic indices, suggesting that the compositional errors were associated with species that were functionally or phylogenetically close to the correct ones; however, this did not always hold for the SSDM predictions.Synthesis. In this study, we tested the use of a recently published approach that couples species distribution and macroecological models to provide the first predictions of the distribution of multiple facets of plant diversity: taxonomic, functional and phylogenetic. Moderate but significant improvements were obtained; thus, our results open promising avenues for improving our ability to predict the different facets of biodiversity in space and time across broad environmental gradients when functional and phylogenetic information is available

Vulnerability of terrestrial vertebrate food webs to anthropogenic threats in Europe

Vertebrate species worldwide are currently facing significant declines in many populations. Although we have gained substantial knowledge about the direct threats that affect individual species, these threats only represent a fraction of the broader vertebrate threat profile, which is also shaped by species interactions. For example, threats faced by prey species can jeopardize the survival of their predators due to food resource scarcity. Yet, indirect threats arising from species interactions have received limited investigation thus far. In this study, we investigate the indirect consequences of anthropogenic threats on biodiversity in the context of European vertebrate food webs. We integrated data on trophic interactions among over 800 terrestrial vertebrates, along with their associated human-induced threats. We quantified and mapped the vulnerability of various components of the food web, including species, interactions, and trophic groups to six major threats: pollution, agricultural intensification, climate change, direct exploitation, urbanization, and invasive alien species and diseases. Direct exploitation and agricultural intensification were two major threats for terrestrial vertebrate food webs: affecting 34% and 31% of species, respectively, they threaten 85% and 69% of interactions in Europe. By integrating network ecology with threat impact assessments, our study contributes to a better understanding of the magnitude of anthropogenic impacts on biodiversity.While direct threats to species are well studied, indirect threats arising from species interactions are less documented, especially on a macroecological scale. In this study, we show the importance of considering interactions to understand threats to biodiversity. By analyzing the vulnerability of European vertebrate food webs to six major anthropogenic threats, we highlight the far-reaching impact of pressures such as direct exploitation and agricultural intensification, shedding light on the broader consequences of human activities on biodiversity.imag

Using the Nature Futures Framework as a lens for developing plural land use scenarios for Europe for 2050

Ambitious international targets are being developed to protect and restore biodiversity under the Convention on Biological Diversity's post-2020 Global Biodiversity Framework and the European Union's Green Deal. Yet, the land system consequences of meeting such targets are unclear, as multiple pathways may be able to deliver on the set targets. This paper introduces a novel scenario approach assessing the plural implementations of these targets. The Nature Futures Framework (NFF) developed by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services aims to illustrate the different, positive ways in which society can value nature. It therefore offers a lens through which the spatial implementation of sustainability targets may be envisioned. We used CLUMondo, a spatially explicit model, to simulate plural land system scenarios for Europe for 2050. The model builds on current land system representations of Europe and explores how and where sustainability targets can be implemented under projected population trends and commodity demands. We created three different scenarios in which the sustainability targets are met, each representing an alternative, normative view on nature as represented by the NFF, favoring land systems providing strong climate regulation (Nature for Society), species conservation (Nature for Nature), or agricultural heritage features (Nature as Culture). Our results show that, irrespective of the NFF view, meeting sustainability targets will require European land systems to drastically change, as natural grasslands and forests are forecast to expand while productive areas are projected to undergo a dual intensification and diversification trajectory. Despite each NFF perspective showcasing a similar direction of change, 20% of Europe's land area will differ based on the adopted NFF perspective, with hotspots of disagreement identified in eastern and western Europe. These simulations go beyond existing scenario approaches by not only depicting broad societal developments for Europe, but also by quantifying the land system synergies and trade-offs associated with alternative, archetypal, interpretations and values of how nature may be managed for sustainability. This quantification exemplifies a means towards constructive dialogue, on the one hand by acknowledging areas of contention, and bringing such issues to the fore, and on the other by highlighting points of convergence in a vision for a sustainable Europe

A tool for simulating and communicating uncertainty when modelling species distributions under future climates

Tools for exploring and communicating the impact of uncertainty on spatial prediction are urgently needed, particularly when projecting species distributions to future conditions. We provide a tool for simulating uncertainty, focusing on uncertainty due to data quality. We illustrate the use of the tool using a Tasmanian endemic species as a case study. Our simulations provide probabilistic, spatially explicit illustrations of the impact of uncertainty on model projections. We also illustrate differences in model projections using six different global climate models and two contrasting emissions scenarios. Our case study results illustrate how different sources of uncertainty have different impacts on model output and how the geographic distribution of uncertainty can vary. Synthesis and applications: We provide a conceptual framework for understanding sources of uncertainty based on a review of potential sources of uncertainty in species distribution modelling; a tool for simulating uncertainty in species distribution models; and protocols for dealing with uncertainty due to climate models and emissions scenarios. Our tool provides a step forward in understanding and communicating the impacts of uncertainty on species distribution models under future climates which will be particularly helpful for informing discussions between researchers, policy makers, and conservation practitioners