Quantifying ecosystem service flows from agricultural landscapes to people: a serviceshed approach

Background/Question/Methods

Agricultural landscapes contribute significantly to human well-being through a range of ecological and socio-economic processes. Quantifying to what extent different beneficiary communities depend on different parts of the landscape for their agricultural activities can inform more sustainable land-use decisions and agricultural support. The processes that support the production of such landscape-based benefits are known as ecosystem service flows. These flows are determined by the physical condition of service supplying areas, the sociological conditions of the benefitting populations, and social-ecological conditions of areas that connect supplying and benefiting areas. Quantifying how landscape features connect to agriculture (and thus human well-being) requires reconciling various conditions such as access to managed vs wild bee colonies and how labor contributes to agriculture production. Using publicly available data on ecosystem conditions and socio-economic activities, we first define “servicesheds” for each ecosystem services that link specific supplying areas to benefitting communities in the Canadian central prairies and the primary agricultural region of Quebec, Canada. Second, we spatially and quantitatively attribute the proportional contribution of natural and human inputs to the flow of an ecosystem service. Finally, we investigate the importance of natural and human inputs on agricultural production on varying landscape configurations.

Results/Conclusions

Servicesheds generated for agriculture-related services in our two study areas show where landscape specific farming communities benefit from agricultural activities and the attributes of supplying and benefitting areas including the stock of and the accessibility to natural and human inputs. We develop models that use these attributes to estimate and map farming communities’ actual dependence on different landscape features such as soil fertility and pollinator habitat, while taking into account agricultural landscape configurations. These results provide landscape-specific parameters for linking ecosystem conditions, human activities, and actual human use/dependence, to address the need and challenges in more sustainable spatial planning.