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Abstract:
Rapid growth of the world’s human population has increased pressure on land
-scapes 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 land
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scape multifunctionality.
2. We combine theoretical simulations and empirical data on 14 ecosystem services
measured across 150 grasslands in three German regions. In doing so, we investi
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gate 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 re
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sponded contrastingly (both positively and negatively) to an ecosystem-
driver.
4. These findings were confirmed using empirical data, which showed that heteroge
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neity 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 simul
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taneous provisioning of ecosystem functions related to forage production (gener
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ally profiting from land-
use intensification), biodiversity conservation and
recreation (generally decreasing with land-
use intensification) was highest in land
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scapes consisting of sites varying in LUI.
5.
Synthesis and applications
. Our findings show that there are general principles gov
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erning 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 eco
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system service supply, although interactions between landscape units (e.g., the
movement of pollinators) must also be considered.
