Plant response to habitat amount and configuration in Swedish forests

Impacts of landscape patterns on plant species diversity at a global scale

Landscape patterns are important drivers of biodiversity. Owing to differences in vegetation types, sampling methods, diversity measures, spatial scales, and landscape levels, the impact of landscape patterns on biodiversity remains widely debated. Using a global standardized plant community database and land use and land cover maps at 30-m resolution, for the period 1990-2017, we calculated plant species α- and β-diversity, and landscape metrics at patch- and landscape-levels, and discerned the direct and indirect impacts of landscape patterns on plant species diversity based on environmental factors, namely climate, spatial features, and human disturbance. We found that landscape patterns exhibited the main indirect effects, whereas climate factors exhibited dominant direct effects on plant α-diversity via the direct effects of patch patterns and functional traits. With respect to β-diversity, landscape-level patterns exerted more direct than indirect effects. These effects are strongly dependent on scale. Landscape- and patch-level patterns had opposite effects on plant diversity, depending on their composition and spatial structure, demonstrating that their effects could be mediated by one another. The adaptation of plants to landscape patterns is mainly through variations in leaf area, plant height, specific leaf area, stem density, seed biomass, and other seed-dispersal traits, which vary across vegetation types. Our findings highlight the importance of functional traits and diversity in understanding the mechanism by which landscape patterns influence plant species diversity; accordingly, we recommend balancing the spatial structure of patch- and landscape-level patterns to enhance variation in functional traits, and, ultimately, to maintain global plant diversity.

Spatial correlation reverses the compound effect of multiple stressors on rocky shore biofilm

Understanding how multifactorial fluctuating environments affect species and communities remains one of the major challenges in ecology. The spatial configuration of the environment is known to generate complex patterns of correlation among multiple stressors. However, to what extent the spatial correlation between simultaneously fluctuating variables affects ecological assemblages in real-world conditions remains poorly understood. Here, we use field experiments and simulations to assess the influence of spatial correlation of two relevant climate variables - warming and sediment deposition following heavy precipitation - on the biomass and photosynthetic activity of rocky intertidal biofilm. First, we used a response-surface design experiment to establish the relation between biofilm, warming, and sediment deposition in the field. Second, we used the response surface to generate predictions of biofilm performance under different scenarios of warming and sediment correlation. Finally, we tested the predicted outcomes by manipulating the degree of correlation between the two climate variables in a second field experiment. Simulations stemming from the experimentally derived response surface showed how the degree and direction (positive or negative) of spatial correlation between warming and sediment deposition ultimately determined the nonlinear response of biofilm biomass (but not photosynthetic activity) to fluctuating levels of the two climate variables. Experimental results corroborated these predictions, probing the buffering effect of negative spatial correlation against extreme levels of warming and sediment deposition. Together, these results indicate that consideration of nonlinear response functions and local-scale patterns of correlation between climate drivers can improve our understanding and ability to predict ecological responses to multiple processes in heterogeneous environments.