Abstract
Abstract Rapid growth of the world's human population has increased pressure on landscapes to deliver high levels of multiple ecosystem services, including food and fibre production, carbon storage, biodiversity conservation, and recreation. However, we currently lack general principles describing how to achieve this landscape multifunctionality. We combine theoretical simulations and empirical data on 14 ecosystem services measured across 150 grasslands in three German regions. In doing so, we investigate the circumstances under which spatial heterogeneity in a driver of ecosystem functioning (an “ecosystem‐driver,” e.g., the presence of keystone species, land‐use intensification, or habitat types) increases landscape‐level ecosystem multifunctionality. Simulations based on theoretical data demonstrated that relationships between heterogeneity and landscape multifunctionality are highly variable and can range from nonsignificant to strongly positive. Despite this variability, we could identify criteria under which heterogeneity‐landscape multifunctionality relationships were most strongly positive: this happened when multiple ecosystem services responded contrastingly (both positively and negatively) to an ecosystem‐driver. These findings were confirmed using empirical data, which showed that heterogeneity in land‐use intensity (LUI) promoted landscape multifunctionality in cases where functions with both positive (e.g., plant biomass) and negative (e.g., flower cover) responses to land use intensification were included. For example, the simultaneous provisioning of ecosystem functions related to forage production (generally profiting from land‐use intensification), biodiversity conservation and recreation (generally decreasing with land‐use intensification) was highest in landscapes consisting of sites varying in LUI. Synthesis and applications. Our findings show that there are general principles governing landscape multifunctionality. A knowledge of these principles may support land management decisions. For example, knowledge of relationships between ecosystem services and their drivers, such as land use type, can help estimate the consequences of increasing or decreasing heterogeneity for landscape‐level ecosystem service supply, although interactions between landscape units (e.g., the movement of pollinators) must also be considered.
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