The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1–4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives include the development of methods to interpret citizen science data and of efficient, flexible computational algorithms for model fitting. Statistical ecology has come of age: it now provides a general and mathematically rigorous framework linking ecological theory and empirical data.
citizen science; hidden Markov model; hierarchical model; movement ecology; software package; spatially explicit capture–recapture; species distribution modelling; state–space model
Theoretical models predict weakening of negative biotic interactions and strengthening of positive interactions with increasing abiotic stress. However, most empirical tests have been restricted to plant–plant interactions. No empirical study has examined theoretical predictions of interactions between plants and below-ground micro-organisms, although soil biota strongly regulates plant community composition and dynamics. We examined variability in soil biota effects on tree regeneration across an abiotic gradient. Our candidate tree species was European beech (Fagus sylvatica L.), whose regeneration is extremely responsive to soil biota activity. In a greenhouse experiment, we measured tree survival in sterilized and non-sterilized soils collected across an elevation gradient in the French Alps. Negative effects of soil biota on tree survival decreased with elevation, similar to shifts observed in plant–plant interactions. Hence, soil biota effects must be included in theoretical models of plant biotic interactions to accurately represent and predict the effects of abiotic gradient on plant communities.
elevation gradient; forest regeneration; stress gradient hypothesis
The 2011 meeting of the European Ecological Federation took place in Ávila, Spain, from 26th September to 29th September. The French Ecological Society (SFE) and the Foundation for Research on Biodiversity (FRB) sponsored a session entitled ‘Evolutionary history, ecosystem function and conservation biology: new perspectives’. We report on the main insights obtained from this symposium.
conservation; phylogenies diversity; biodiversity; macroevolution
Habitat suitability models, which relate species occurrences to environmental variables, are assumed to predict suitable conditions for a given species. If these models are reliable, they should relate to change in plant growth and function. In this paper, we ask the question whether habitat suitability models are able to predict variation in plant functional traits, often assumed to be a good surrogate for a species' overall health and vigour. Using a thorough sampling design, we show a tight link between variation in plant functional traits and habitat suitability for some species, but not for others. Our contrasting results pave the way towards a better understanding of how species cope with varying habitat conditions and demonstrate that habitat suitability models can provide meaningful descriptions of the functional niche in some cases, but not in others.
ecological niche; mixed models; information theory; intraspecific variability
We modelled the present and future sub-Saharan winter distributions of 64 trans-Saharan migrant passerines to predict the potential impacts of climate change. These predictions used the recent ensemble modelling developments and the latest IPCC climatic simulations to account for possible methodological uncertainties. Results suggest that 37 species would face a range reduction by 2100 (16 of these by more than 50%); however, the median range size variation is −13 per cent (from −97 to +980%) under a full dispersal hypothesis. Range centroids were predicted to shift by 500±373 km. Predicted changes in range size and location were spatially structured, with species that winter in southern and eastern Africa facing larger range contractions and shifts. Predicted changes in regional species richness for these long-distance migrants are increases just south of the Sahara and on the Arabian Peninsula and major decreases in southern and eastern Africa.
Africa; birds; climate change; ensemble forecast; climate suitability model; species' range shift
Predictions of future species' ranges under climate change are needed for conservation planning, for which species distribution models (SDMs) are widely used. However, global climate model-based (GCM) output grids can bias the area identified as suitable when these are used as SDM predictor variables, because GCM outputs, typically at least 50×50 km, are biologically coarse. We tested the assumption that species ranges can be equally well portrayed in SDMs operating on base data of different grid sizes by comparing SDM performance statistics and area selected by four SDMs run at seven grid sizes, for nine species of contrasting range size. Area selected was disproportionately larger for SDMs run on larger grid sizes, indicating a cut-off point above which model results were less reliable. Up to 2.89 times more species range area was selected by SDMs operating on grids above 50×50 km, compared to SDMs operating at 1 km2. Spatial congruence between areas selected as range also diverged as grid size increased, particularly for species with ranges between 20 000 and 90 000 km2. These results indicate the need for caution when using such data to plan future protected areas, because an overly large predicted range could lead to inappropriate reserve location selection.
global climate models; grid size sensitivity analysis; species range
We present niche-based modelling to project the distribution of 845 European plant species for Germany using three different models and three scenarios of climate and land use changes up to 2080. Projected changes suggested large effects over the coming decades, with consequences for the German flora. Even under a moderate scenario (approx. +2.2°C), 15–19% (across models) of the species we studied could be lost locally—averaged from 2995 grid cells in Germany. Models projected strong spatially varying impacts on the species composition. In particular, the eastern and southwestern parts of Germany were affected by species loss. Scenarios were characterized by an increased number of species occupying small ranges, as evidenced by changes in range-size rarity scores. It is anticipated that species with small ranges will be especially vulnerable to future climate change and other ecological stresses.
climate change; predictive modelling; plant ranges; Germany
The direct effects of CO2 level changes on plant water availability are usually ignored in plant habitat models. We compare traditional proxies for water availability with changes in soil water (fAWC) predicted by a process-based ecosystem model, which simulates changes in vegetation structure and functioning, including CO2 physiological effects. We modelled current and future habitats of 108 European tree species using ensemble forecasting, comprising six habitat models, two model evaluation methods and two climate change scenarios. The fAWC models' projections are generally more conservative. Potential habitats shrink significantly less for boreo-alpine and alpine species. Changes in vegetation functioning and CO2 on plant water availability should therefore be taken into account in plant habitat change projections.
soil water content; BIOMOD; habitat models; CO2 effect; climate change; ensemble forecasting
Species responses to climate change may be influenced by changes in available habitat, as well as population processes, species interactions and interactions between demographic and landscape dynamics. Current methods for assessing these responses fail to provide an integrated view of these influences because they deal with habitat change or population dynamics, but rarely both. In this study, we linked a time series of habitat suitability models with spatially explicit stochastic population models to explore factors that influence the viability of plant species populations under stable and changing climate scenarios in South African fynbos, a global biodiversity hot spot. Results indicate that complex interactions between life history, disturbance regime and distribution pattern mediate species extinction risks under climate change. Our novel mechanistic approach allows more complete and direct appraisal of future biotic responses than do static bioclimatic habitat modelling approaches, and will ultimately support development of more effective conservation strategies to mitigate biodiversity losses due to climate change.
population viability analysis; bioclimatic envelope; niche model; uncertainty; fynbos; fire