Climate and land-use change are key drivers of environmental degradation in the Anthropocene, but too little is known about their interactive effects on biodiversity and ecosystem services. Long-term data on biodiversity trends are currently lacking. Furthermore, previous ecological studies have rarely considered climate and land use in a joint design, did not achieve variable independence or lost statistical power by not covering the full range of environmental gradients. Here, we introduce a multi-scale space-for-time study design to disentangle effects of climate and land use on biodiversity and ecosystem services. The site selection approach coupled extensive GIS-based exploration (i.e. using a Geographic information system) and correlation heatmaps with a crossed and nested design covering regional, landscape and local scales. Its implementation in Bavaria (Germany) resulted in a set of study plots that maximise the potential range and independence of environmental variables at different spatial scales. Stratifying the state of Bavaria into five climate zones (reference period 1981–2010) and three prevailing land-use types, that is, near-natural, agriculture and urban, resulted in 60 study regions (5.8 × 5.8 km quadrants) covering a mean annual temperature gradient of 5.6–9.8°C and a spatial extent of ~310 × 310 km. Within these regions, we nested 180 study plots located in contrasting local land-use types, that is, forests, grasslands, arable land or settlement (local climate gradient 4.5–10°C). This approach achieved low correlations between climate and land use (proportional cover) at the regional and landscape scale with |r ≤ 0.33| and |r ≤ 0.29| respectively. Furthermore, using correlation heatmaps for local plot selection reduced potentially confounding relationships between landscape composition and configuration for plots located in forests, arable land and settlements. The suggested design expands upon previous research in covering a significant range of environmental gradients and including a diversity of dominant land-use types at different scales within different climatic contexts. It allows independent assessment of the relative contribution of multi-scale climate and land use on biodiversity and ecosystem services. Understanding potential interdependencies among global change drivers is essential to develop effective restoration and mitigation strategies against biodiversity decline, especially in expectation of future climatic changes. Importantly, this study also provides a baseline for long-term ecological monitoring programs.

Caterpillars of the butterfly Maculinea rebeli develop as parasites inside ant colonies. In intensively studied French populations, about 25% of caterpillars mature within 1 year (fast-developing larvae [FDL]) and the others after 2 years (slow-developing larvae [SDL]); all available evidence indicates that this ratio is under the control of egg-laying females. We present an analytical model to predict the evolutionarily stable fraction of FDL (pESS). The model accounts for added winter mortality of SDL, general and kin competition among caterpillars, a competitive advantage of SDL over newly entering FDL (priority effect), and the avoidance of renewed infection of ant nests by butterflies in the coming season (segregation). We come to the following conclusions: (1) all factors listed above can promote the evolution of delayed development; (2) kin competition and segregation stabilize pESS near 0.5; and (3) a priority effect is the only mechanism potentially selecting for. However, given the empirical data, pESS is predicted to fall closer to 0.5 than to the 0.25 that has been observed. In this particular system, bet hedging cannot explain why more than 50% of larvae postpone growth. Presumably, other fitness benefits for SDL, for example, higher fertility or longevity, also contribute to the evolution of delayed development. The model presented here may be of general applicability for systems where maturing individuals compete in small subgroups.

Theory predicts that males and females should often join the mating pool at different times (sexual dimorphism in timing of emergence [SDT]) as the degree of SDT affects female mating success. We utilize an analytical model to explore (1) how important SDT is for female mating success, (2) how mating success might change if either sex's mortality (abruptly) increases, and (3) to what degree evolutionary responses in SDT may be able to mitigate the consequences of such mortality increase. Increasing male pre‐mating mortality has a non‐linear effect on the fraction of females mated: The effect is initially weak, but at some critical level a further increase in male mortality has a stronger effect than a similar increase in female mortality. Such a change is expected to impose selection for reduced SDT. Increasing mortality during the mating season has always a stronger effect on female mating success if the mortality affects the sex that emerges first. This bias results from the fact that enhancing mortality of the earlier emerging sex reduces female–male encounter rates. However, an evolutionary response in SDT may effectively mitigate such consequences. Further, if considered independently for females and males, the predicted evolutionary response in SDT could be quite dissimilar. The difference between female and male evolutionary response in SDT leads to marked differences in the fraction of fertilized females under certain conditions. Our model may provide general guidelines for improving harvesting of populations, conservation management of rare species under altered environmental conditions, or maintaining long‐term efficiency of pest‐control measures.

Background: Patterns that arise from an ecological process can be driven as much from the landscape over which the process is run as it is by some intrinsic properties of the process itself. The disentanglement of these effects is aided if it possible to run models of the process over artificial landscapes with controllable spatial properties. A number of different methods for the generation of so-called ‘neutral landscapes’ have been developed to provide just such a tool. Of these methods, a particular class that simulate fractional Brownian motion have shown particular promise. The existing methods of simulating fractional Brownian motion suffer from a number of problems however: they are often not easily generalisable to an arbitrary number of dimensions and produce outputs that can exhibit some undesirable artefacts. Methodology: We describe here an updated algorithm for the generation of neutral landscapes by fractional Brownian motion that do not display such undesirable properties. Using Monte Carlo simulation we assess the anisotropic properties of landscapes generated using the new algorithm described in this paper and compare it against a popular benchmark algorithm. Conclusion/Significance: The results show that the existing algorithm creates landscapes with values strongly correlated in the diagonal direction and that the new algorithm presented here corrects this artefact. A number of extensions of the algorithm described here are also highlighted: we describe how the algorithm can be employed to generate landscapes that display different properties in different dimensions and how they can be combined with an environmental gradient to produce landscapes that combine environmental variation at the local and macro scales.

Based on a marginal value approach, we derive a nonlinear expression for evolutionarily stable (ES) dispersal rates in a metapopulation with global dispersal. For the general case of density-dependent population growth, our analysis shows that individual dispersal rates should decrease with patch capacity and-beyond a certain threshold-increase with population density. We performed a number of spatially explicit, individual-based simulation experiments to test these predictions and to explore further the relevance of variation in the rate of population increase, density dependence, environmental fluctuations and dispersal mortality on the evolution of dispersal rates. They confirm the predictions of our analytical approach. In addition, they show that dispersal rates in metapopulations mostly depend on dispersal mortality and inter-patch variation in population density. The latter is dominantly driven by environmental fluctuations and the rate of population increase. These conclusions are not altered by the introduction of neighbourhood dispersal. With patch capacities in the order of 100 individuals, kin competition seems to be of negligible importance for ES dispersal rates except when overall dispersal rates are low.