Explore the vast range of titles available.

Globalization and economic growth are widely recognized as important drivers of biological invasions. Consequently, there is an increasing need for governments to address the role of international trade in their strategies to prevent species introductions. However, many of the most problematic alien species are not recent arrivals but were introduced several decades ago. Hence, current patterns of alien-species richness may better reflect historical rather than contemporary human activities, a phenomenon which might be called “invasion debt.” Here, we show that across 10 taxonomic groups (vascular plants, bryophytes, fungi, birds, mammals, reptiles, amphibians, fish, terrestrial insects, and aquatic invertebrates) in 28 European countries, current numbers of alien species established in the wild are indeed more closely related to indicators of socioeconomic activity from the year 1900 than to those from 2000, although the majority of species introductions occurred during the second half of the 20th century. The strength of the historical signal varies among taxonomic groups, with those possessing good capabilities for dispersal (birds, insects) more strongly associated with recent socioeconomic drivers. Nevertheless, our results suggest a considerable historical legacy for the majority of the taxa analyzed. The consequences of the current high levels of socioeconomic activity on the extent of biological invasions will thus probably not be completely realized until several decades into the future.

The documentation of biological invasions is often incomplete with records lagging behind the species’ actual spread to a spatio-temporally heterogeneous extent. Such imperfect observation bears the risk of underestimating the already realised distribution of the invading species, misguiding management efforts and misjudging potential future impacts. In this paper, we develop a hierarchical modelling framework which disentangles the determinants of the invasion and observation processes, models spatio-temporal heterogeneity in detection patterns, and infers the actual, yet partly undocumented distribution of the species at any particular time. We illustrate the model with a case study application to the invasion of common ragweed Ambrosia artemisiifolia in Austria. The invasion part of the model reconstructs the historical spread of this species across a grid of ~6 × 6 km2 cells as driven by spatio-temporal variation in physical site conditions, propagule production, dispersal, and ‘background’ introductions from unknown sources. The observation part models the detection of the species’ occurrences based on heterogeneous sampling efforts, human population density, and estimated local invasion level. We fitted the hierarchical model using a Bayesian inference approach with parameters estimated by Markov chain Monte Carlo (MCMC). The actual spread of A. artemisiifolia concentrated on the climatically well-suited lowlands and was mainly driven by spatio-temporal propagule pressure from source cells with long-distance dispersal occurring rather frequently. Annual detection probabilities were estimated to vary between about 1 and up to 28%, depending mainly on sampling intensity. The model suggested that by 2005 about half of the actual distribution of the species was not yet documented. Our hierarchical model offers a flexible means to account for imperfect observation and spatio-temporal variability in detection efficiency. Inferences can be used to disentangle aspects of the invasion dynamics itself from patterns of data collection, develop improved future surveying schemes, and design more efficient invasion management strategies.

International audience

Wetlands in general and mires in particular belong to the most important terrestrial carbon stocks globally. Mires (i.e. bogs, transition bogs and fens) are assumed to be especially vulnerable to climate change because they depend on specific, namely cool and humid, climatic conditions. In this paper, we use distribution data of the nine mire types to be found in Austria and habitat distribution models for four IPCC scenarios to evaluate climate change induced risks for mire ecosystems within the 21st century. We found that climatic factors substantially contribute to explain the current distribution of all nine Austrian mire ecosystem types. Summer temperature proved to be the most important predictor for the majority of mire ecosystems. Precipitation—mostly spring and summer precipitation sums—was influential for some mire ecosystem types which depend partly or entirely on ground water supply (e.g. fens). We found severe climate change induced risks for all mire ecosystems, with rain-fed bog ecosystems being most threatened. Differences between scenarios are moderate for the mid-21st century, but become more pronounced towards the end of the 21st century, with near total loss of climate space projected for some ecosystem types (bogs, quagmires) under severe climate change. Our results imply that even under minimum expected, i.e. inevitable climate change, climatic risks for mires in Austria will be considerable. Nevertheless, the pronounced differences in projected habitat loss between moderate and severe climate change scenarios indicate that limiting future warming will likely contribute to enhance long-term survival of mire ecosystems, and to reduce future greenhouse gas emissions from decomposing peat. Effectively stopping and reversing the deterioration of mire ecosystems caused by conventional threats can be regarded as a contribution to climate change mitigation. Because hydrologically intact mires are more resilient to climatic changes, this would also maintain the nature conservation value of mires, and help to reduce the severe climatic risks to which most Austrian mire ecosystems may be exposed in the 2nd half of the 21st century according to IPCC scenarios.

Forecasting the spatial spread of invasive species is important to inform management planning. Niche-based species distribution models offer a well-developed framework for assessing the potential range of species. However, these models assume equilibrium between the species' distribution and its ecological requirements. During range expansion, invasive species are not in such equilibrium due to both dispersal limitation and frequent casual occurrence in sites unsuitable to persistent populations. In this article we use the example of the invasive annual plant Ambrosia artemisiifolia in Austria to evaluate if model accuracy can be enhanced in such non-equilibrium situations by taking account of propagule pressure and by restricting model calibration to naturalized populations. Moreover, we test if model accuracy increases during invasion history using distribution data from 1984 to 2005. The results suggest that models calibrated with naturalized populations are much more accurate than those based on the total set of records. Proxies of propagule pressure slightly but significantly improve goodness of fit, accuracy, and Type I and II error rates of models calibrated with all available records but have less consistent effects on models of naturalized populations. Model accuracy did not increase during the recent invasion history, probably because the species is still far from an equilibrium distribution. We conclude that even a coarse assessment of population status with records of invasive species delivers important information for predictive modelling and that proxies of propagule pressure should be included into such models at least during early to intermediate stages of the invasion history.

Aim: We develop a novel modelling framework for analysing the spatio-temporal spread of biological invasions. The framework integrates different invasion drivers and disentangles their roles in determining observed invasion patterns by fitting models to historical distribution data. As a case study application, we analyse the spread of common ragweed (Ambrosia artemisiifolia). Location: Central Europe. Methods: A lattice system represents actual landscapes with environmental heterogeneity. Modelling covers the spatio-temporal invasion sequence in this grid and integrates the effects of environmental conditions on local invasion suitability, the role of invaded cells and spatially implicit \"background\" introductions as propagule sources, within-cell invasion level bulk-up and multiple dispersal means. A modular framework design facilitates flexible numerical representation of the modelled invasion processes and customization of the model complexity. We used the framework to build and contrast increasingly complex models, and fitted them using a Bayesian inference approach with parameters estimated by Markov chain Monte Carlo (MCMC). Results: All modelled invasion drivers codetermined the A. artemisiifolia invasion pattern. Inferences about individual drivers depended on which processes were modelled concurrently, and hence changed both quantitatively and qualitatively between models. Among others, the roles of environmental variables were assessed substantially differently subject to whether models included explicit source-recipient cell relationships, spatio-temporal variability in source cell strength and human-mediated dispersal means. The largest fit improvements were found by integrating filtering effects of the environment and spatio-temporal availability of propagule sources. Main conclusions: Our modelling framework provides a straightforward means to build integrated invasion models and address hypotheses about the roles and mutual relationships of different putative invasion drivers. Its statistical nature and generic design make it suitable for studying many observed invasions. For efficient invasion modelling, it is important to represent changes in spatio-temporal propagule supply by populations. explicitly tracking the species' colonization sequence and establishment of new populations.

Globalization and economic growth are widely recognized as important drivers of biological invasions. Consequently, there is an increasing need for governments to address the role of international trade in their strategies to prevent species introductions. However, many of the most problematic alien species are not recent arrivals but were introduced several decades ago. Hence, current patterns of alien-species richness may better reflect historical rather than contemporary human activities, a phenomenon which might be called “invasion debt.” Here, we show that across 10 taxonomic groups (vascular plants, bryophytes, fungi, birds, mammals, reptiles, amphibians, fish, terrestrial insects, and aquatic invertebrates) in 28 European countries, current numbers of alien species established in the wild are indeed more closely related to indicators of socioeconomic activity from the year 1900 than to those from 2000, although the majority of species introductions occurred during the second half of the 20th century. The strength of the historical signal varies among taxonomic groups, with those possessing good capabilities for dispersal (birds, insects) more strongly associated with recent socioeconomic drivers. Nevertheless, our results suggest a considerable historical legacy for the majority of the taxa analyzed. The consequences of the current high levels of socioeconomic activity on the extent of biological invasions will thus probably not be completely realized until several decades into the future.

Question: Are there effects of long-term deposition of airborne nitrogen and sulphur on the forest floor vegetation from permanent plots collected in 1993 compared to 2005. Location: Northern limestone Alps in Austria. Methods: Single species responses were analysed by correlating trends in cover-abundance values, as derived from marginal models, with Ellenberg indicator values. Changes in the species composition of plots were analysed by correlating changes in mean Ellenberg indicator values with the displacement of plots within a multidimensional scaling ordination. Results: Trends in single species abundance were positively correlated with indicator values of soil pH but were independent of nutrient availability. A general trend towards the homogenisation of vegetation, due to convergent time vectors of the relevés, became obvious. Oligotrophic sites previously situated at the distal ends of ordination axes shifted towards the centre since they were enriched by species preferring mesotrophic conditions. The bulk of plots with intermediate site conditions hardly showed any trends. A concomitant analysis demonstrated that temporal changes in species composition exceed the variation in cover abundance estimates among different field botanists. Conclusions: N deposition can lead to a homogenisation of forest floor vegetation. Larger limestone areas with diverse soil conditions, such as the Northern limestone Alps in Austria, as a whole are thus negatively affected by airborne N deposition. Nevertheless, the vegetation was at least as strongly affected by an increase of basiphilous species as a result of decreasing S deposition. Nomenclature: Adler et al. (1994).