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Observed patterns of species richness at landscape scale (gamma diversity) cannot always be attributed to a specific set of explanatory variables, but rather different alternative explanatory statistical models of similar quality may exist. Therefore predictions of the effects of environmental change (such as in climate or land cover) on biodiversity may differ considerably, depending on the chosen set of explanatory variables. Here we use multimodel prediction to evaluate effects of climate, land-use intensity and landscape structure on species richness in each of seven groups of organisms (plants, birds, spiders, wild bees, ground beetles, true bugs and hoverflies) in temperate Europe. We contrast this approach with traditional best-model predictions, which we show, using cross-validation, to have inferior prediction accuracy. Multimodel inference changed the importance of some environmental variables in comparison with the best model, and accordingly gave deviating predictions for environmental change effects. Overall, prediction uncertainty for the multimodel approach was only slightly higher than that of the best model, and absolute changes in predicted species richness were also comparable. Richness predictions varied generally more for the impact of climate change than for land-use change at the coarse scale of our study. Overall, our study indicates that the uncertainty introduced to environmental change predictions through uncertainty in model selection both qualitatively and quantitatively affects species richness projections.

The intensity of agricultural production was assessed in 25 landscape test sites across temperate Europe using a standardised farmer questionnaire. The intensity indicators, nitrogen input (to arable crops and to permanent grassland), density of livestock units and number of pesticide applications (herbicides, insecticides, fungicides and retardants), were recorded and integrated into an overall intensity index. All three components were needed to appropriately characterise the intensity of agricultural management. Four hypotheses were tested. (i) A low diversity of crops is related to higher intensity. The contrary was observed, namely because diverse crop rotations contained a higher share of crops which are more demanding in terms of nitrogen and of plant protection. (ii) Intensity decreases when there is more permanent grassland. This was confirmed by our study. (iii) Large farms are managed more intensively. There was no relation between farm size and intensity. (iv) Large fields are managed more intensively. There was a tendency towards higher nitrogen input and livestock density in landscapes with larger fields but only a few of the results were statistically significant. The aggregated overall intensity index was of limited usefulness mainly because of limitations in interpretability.