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Demand for models in biodiversity assessments is rising, but which models are adequate for the task? We propose a set of best-practice standards and detailed guidelines enabling scoring of studies based on species distribution models for use in biodiversity assessments. We reviewed and scored 400 modeling studies over the past 20 years using the proposed standards and guidelines. We detected low model adequacy overall, but with a marked tendency of improvement over time in model building and, to a lesser degree, in biological data and model evaluation. We argue that implementation of agreed-upon standards for models in biodiversity assessments would promote transparency and repeatability, eventually leading to higher quality of the models and the inferences used in assessments. We encourage broad community participation toward the expansion and ongoing development of the proposed standards and guidelines.

– Swiss forests experience strong impacts under the CH2011 scenarios, partly even for the low greenhouse gas scenario RCP3PD. Negative impacts prevail in low-elevation forests, whereas mostly positive impacts are expected in high-elevation forests. – Major changes in the distribution of the two most important tree species, Norway spruce and European beech, are expected. Growth conditions for spruce improve in a broad range of scenarios at presently cool high-elevation sites with plentiful precipitation, but in the case of strong warming (A1B and A2) spruce and beech are at risk in large parts of the Swiss Plateau. – High elevation forests that are temperature-limited will show little change in species composition but an increase in biomass. In contrast, forests at low elevations in warm-dry inner-Alpine valleys are sensitive to even moderate warming and may no longer sustain current biomass and species. – Timber production potential, carbon storage, and protection from avalanches and rockfall react differently to climate change, with an overall tendency to deteriorate at low elevations, and improve at high elevations. – Climate change will affect forests also indirectly, e.g., by increasing the risk of infestation by spruce bark beetles, which will profit from an extended flight period and will produce more generations per year.

The opportunity to reflect broadly on the accomplishments, prospects, and reach of a field may present itself relatively infrequently. Each biennial meeting of the International Biogeography Society showcases ideas solicited and developed largely during the preceding year, by individuals or teams from across the breadth of the discipline. Here, we highlight challenges, developments, and opportunities in biogeography from that biennial synthesis. We note the realized and potential impact of rapid data accumulation in several fields, a renaissance for inter-disciplinary research, the importance of recognizing the evolution-ecology continuum across spatial and temporal scales and at different taxonomic, phylogenetic and functional levels, and re-exploration of classical assumptions and hypotheses using new tools. However, advances are taxonomically and geographically biased, and key theoretical frameworks await tools to handle, or strategies to simplify, the biological complexity seen in empirical systems. Current threats to biodiversity require unprecedented integration of knowledge and development of predictive capacity that may enable biogeography to unite its descriptive and hypothetico-deductive branches and establish a greater role within and outside academia.

1. Aim - Concerns over how global change will influence species distributions, in conjunction with increased emphasis on understanding niche dynamics in evolutionary and community contexts, highlight the growing need for robust methods to quantify niche differences between or within taxa. We propose a statistical framework to describe and compare environmental niches from occurrence and spatial environmental data.¦2. Location - Europe, North America, South America¦3. Methods - The framework applies kernel smoothers to densities of species occurrence in gridded environmental space to calculate metrics of niche overlap and test hypotheses regarding niche conservatism. We use this framework and simulated species with predefined distributions and amounts of niche overlap to evaluate several ordination and species distribution modeling techniques for quantifying niche overlap. We illustrate the approach with data on two well-studied invasive species.¦4. Results - We show that niche overlap can be accurately detected with the framework when variables driving the distributions are known. The method is robust to known and previously undocumented biases related to the dependence of species occurrences on the frequency of environmental conditions that occur across geographic space. The use of a kernel smoother makes the process of moving from geographical space to multivariate environmental space independent of both sampling effort and arbitrary choice of resolution in environmental space. However, the use of ordination and species distribution model techniques for selecting, combining and weighting variables on which niche overlap is calculated provide contrasting results.¦5. Main conclusions - The framework meets the increasing need for robust methods to quantify niche differences. It is appropriate to study niche differences between species, subspecies or intraspecific lineages that differ in their geographical distributions. Alternatively, it can be used to measure the degree to which the environmental niche of a species or intraspecific lineage has changed over time.

International audience; Understanding the nature of competitive interactions among trees is critical to understand forest community structure and dynamics, and to predict their responses to global change. However, predicting the outcome of competitive interaction between numerous pairs of tree species and across large gradients of abiotic conditions remains challenging. A classical hypothesis -the competition-relatedness hypothesis- assumes that because of niche and trait conservatism, closely related species tend to be ecologically more similar and thus compete more severely than distantly related species. However, this hypothesis has remained largely untested with direct measurements of competition. Rather, it was only evaluated from simple patterns of species co-occurrence in the past. Recent publications have challenged this hypothesis on the ground that coexistence requires more complex explanations than simply niche differentiation. Coexistence is also driven by differences in species' competitive ability, and this could have effects opposed to the competition- relatedness hypothesis. For instance, pairs of species sharing similar values of trait responsible for a high competitive ability should compete less strongly than species with more distinct trait values. Using data on individual tree radial growth from more than 17000 forest plots in the French Alps, we explore the relative role of these two contrasting views of competitive interactions for 130 pairs of species. We developed a Bayesian neighbourhood growth competition model to estimate the intensity of competition between pairs of species. We then tested the relation between strength of competition between pairs of species and i)their phylogenetic distance or ii)their functional similarity for several key functional traits.

Recruitment algorithms in forest gap models are examined with particular regard to their suitability for simulating forest ecosystem responses to a changing climate. The traditional formulation of recruitment is found limiting in three areas. First, the aggregation of different regeneration stages (seed production, dispersal, storage, germination and seedling establishment) is likely to result in less accurate predictions of responses as compared to treating each stage separately. Second, the relatedassumptions that seeds of all species are uniformly available and that environmental conditions are homogeneous, are likely to cause overestimates of future species diversity and forest migration rates. Third, interactions between herbivores (ungulates and insect pests) and forest vegetation are a big unknown with potentially serious impacts in many regions. Possible strategies for developing better gap model representations for the climate-sensitive aspects of each of these key areas are discussed. A working example of a relatively new model that addresses some of these limitations is also presented for each case. We conclude that better models of regeneration processes are desirable for predicting effects of climate change, but that it is presently impossible to determine what improvements can be expected without carrying out rigorous tests for each new formulation.