Alien invasive species can affect large areas, often with wide-ranging impacts on ecosystem structure, function and services. Prunus serotina is a widespread invader of European temperate forests, where it tends to form homogeneous stands and limits recruitment of indigenous trees. We hypotesized that invasion by P. serotina would be reflected in the nutrient contents of the native species’ leaves and in the respiration of invaded plots as efficient resource uptake and changes in nutrient cycling by P. serotina probably underly its aggressive invasiveness. We combined data from 48 field plots in the forest of Compiègne, France, and data from an experiment using 96 microcosms derived from those field plots. We used general linear models to separate effects of invasion by P. serotina on heterotrophic soil and litter respiration rates and on canopy foliar nutrient content from effects of soil chemical properties, litter quantity, litter species composition and tree species composition. In invaded stands, average respiration rates were 5.6% higher for soil (without litter) and 32% higher for soil and litter combined. Compared to indigenous tree species, P. serotina exhibited higher foliar N (+24.0%), foliar P (+50.7%) and lower foliar C:N (−22.4%) and N:P (−10.1%) ratios. Prunus serotina affected foliar nutrient contents of co-occuring indigenous tree species leading to decreased foliar N (−8.7 %) and increased C:N ratio (+9.5%) in Fagus sylvatica, decreased foliar N:P ratio in Carpinus betulus (−13.5%) and F. sylvatica (−11.8%), and increased foliar P in Pinus sylvestris (+12.3%) in invaded vs. uninvaded stands. Our results suggest that P. serotina is changing nitrogen, phosphorus and carbon cycles to its own advantage, hereby increasing carbon turnover via labile litter, affecting the relative nutrient contents in the overstory leaves, and potentially altering the photosynthetic capacity of the long-lived indigenous broadleaved species. Uncontrolled invasion of European temperate forests by P. serotina may affect the climate change mitigation potential of these forests in the long term, through additive effects on local nutrient cycles.

This study evaluates the effects of the large 2007 Peloponnese (Greece) wildfires on changes in broadband surface albedo (α), daytime land surface temperature (LSTd) and night-time LST (LSTn) using a 2-year post-fire time series of Moderate Resolution Imaging Spectroradiometer satellite data. In addition, it assesses the potential of remotely sensed α and LST as indicators for fire–burn severity. Immediately after the fire event, mean α dropped up to 0.039 (standard deviation = 0.012) (P < 0.001), mean LSTd increased up to 8.4 (3.0) K (P < 0.001), and mean LSTn decreased up to –1.2 (1.5) K (P < 0.001) for high-severity plots (P < 0.001). After this initial alteration, fire-induced changes become clearly smaller and seasonality starts governing the α and LST time series. Compared with the fire-induced changes in α and LST, the post-fire NDVI drop was more persistent in time. This temporal constraint restricts the utility of remotely sensed α and LST as indicators for fire–burn severity. For the times when changes in α and LST were significant, the magnitude of changes was related to fire–burn severity, revealing the importance of vegetation as a regulator of land surface energy fluxes.

Aim: To propose a species distribution modelling framework and its companion “iSDM” R package for predicting the potential and realized distributions of invasive species within the invaded range.Location: Northern France.Methods: The non‐equilibrium distribution of invasive species with the environment within the invaded range affects the environmental representativeness of species presence–absence data collected from the field and introduces uncertainty in observed absences as these may either reflect unsuitable sites or be incidental. To address these issues, we here propose an environmental systematic sampling design to collect presence–absence data from the field and a probability index to sort and subsequently separate environmental absences (EAs: reflecting environmentally unsuitable sites) from dispersal‐limited absences (DLAs: reflecting sites out of dispersal reach). We first conducted a comprehensive test based on a virtual species to evaluate the performance of our framework. Then, we applied it on different life stages of a non‐native tree species (Prunus serotina Ehrh.) invasive in Europe.Results: Regarding the potential distribution, we found higher model performances for both the virtual species (true skill statistics (TSS) > 0.75) and P. serotina (TSS ≥ 0.68) after carefully selecting absences with a low probability to be DLAs compared with classical models that incorporate both EAs and DLAs (e.g. TSS = 0.11 for P. serotina with 80% of DLAs). On the contrary, both EAs and DLAs as well as dispersal‐related covariates were needed to capture the realized distribution of both the virtual species and P. serotina.Main Conclusions: Our framework helps overcoming the conceptual and methodological limitations of the disequilibrium in species’ distribution models inherent to invasive species and enables managers to robustly estimate both the realized and potential distributions of invasive species. Although more relevant for modelling the distribution of non‐native species, this framework can also be applied to native species.