Human domination of the biosphere includes changes to disturbance regimes, which push many ecosystems towards early-successional states. Ecological theory predicts that early-successional ecosystems are more sensitive to perturbations than mature systems, but little evidence supports this relationship for the perturbation of climate change. Here we show that vegetation (abundance, species richness and species composition) across seven European shrublands is quite resistant to moderate experimental warming and drought, and responsiveness is associated with the dynamic state of the ecosystem, with recently disturbed sites responding to treatments. Furthermore, most of these responses are not rapid (2-5 years) but emerge over a longer term (7-14 years). These results suggest that successional state influences the sensitivity of ecosystems to climate change, and that ecosystems recovering from disturbances may be sensitive to even modest climatic changes. A research bias towards undisturbed ecosystems might thus lead to an underestimation of the impacts of climate change.

Above- and belowground carbon (C) stores of terrestrial ecosystems are vulnerable to environmental change. Ecosystem C balances in response to environmental changes have been quantified at individual sites, but the magnitudes and directions of these responses along environmental gradients remain uncertain. Here we show the responses of ecosystem C to 8–12 years of experimental drought and night-time warming across an aridity gradient spanning seven European shrublands using indices of C assimilation (aboveground net primary production: aNPP) and soil C efflux (soil respiration: Rs). The changes of aNPP and Rs in response to drought indicated that wet systems had an overall risk of increased loss of C but drier systems did not. Warming had no consistent effect on aNPP across the climate gradient, but suppressed Rs more at the drier sites. Our findings suggest that above- and belowground C fluxes can decouple, and provide no evidence of acclimation to environmental change at a decadal timescale. aNPP and Rs especially differed in their sensitivity to drought and warming, with belowground processes being more sensitive to environmental change.

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Neural networks are trained to estimate the germination percentages of Plasmopara viticola oospores, overwintered in natural conditions in two viticultural areas in northern Italy, by using climatic (temperature and rainfall) data, as well as the previous germination measurement, as input variables. The 288 available patterns consist of a set of selected independent variables associated with the corresponding germination percentage. All 12 networks investigated converge to a non-linear relationship between the selected independent variables and oospore germination. The highest correlation coefficient (equal to 0.83) between the real and estimated germination percentages is obtained by considering, as input to the network, the climatic data (both temperature and rainfall) recorded during the 40 days before sampling and the germination percentage assessed in the germination assay carried out immediately before the present sampling.

1. The capacity to forecast the effects of climate change on biodiversity largely relies on identifying traits capturing mechanistic relationships with the environment through standardized field experiments distributed across relevant spatial scales. The effects of short-term experimental manipulations on local communities may overlap with regional climate gradients that have been operating during longer time periods. However, to the best of our knowledge, there are no studies simultaneously assessing such long-term macroecological drivers with local climate manipulations.2. We analysed this issue with springtails (Class Collembola), one of the dominant soil fauna groups, in a standardized climate manipulation experiment conducted across six European countries encompassing broad climate gradients. We combined community data (near 20K specimens classified into 102 species) with 22 eco-morphological traits and reconstructed their phylogenetic relationships to track the evolution of adaptations to live at different soil depths, which is key to cope with desiccation. We then applied joint species distribution models to investigate the combined effect of the regional aridity gradient with the local experimental treatment (drought and warming) over the assembly of springtail communities and tested for significant trait-environment relationships mediating their community-level responses.