Integrating Landscape Pattern into Characterising and Optimising Ecosystem Services for Regional Sustainable Development

Abstract

Humans benefit from ecosystem services (ES) and profoundly influence the ecosystem in rapid urbanisation and large-scale urban sprawl contexts, especially at the landscape level. However, the impacts of landscape pattern, the driving mechanism of sub-ES and the spatially explicit regional optimisation, have been largely ignored. In response, to the present paper explores two primary aspects: the relationship among ES, landscape pattern, urban income and agricultural output, and the regional governance of optimised ES values (ESV), using the Wuhan urban agglomeration as a case study area. The survey method is employed in obtaining the adjusted magnitude matrix of land use and ecosystem services. Spatial regression analyses are conducted on each ES, including food provision, climate regulation and soil maintenance, with socio-economic indicators and landscape pattern index as explanatory variables. Finally, geographically weighted regression and scenario analyses are conducted on each sub-ESV to generate adjusted coefficients in each county for ESV regulation. The results show that urban per capita disposable income and agricultural output significantly contribute to ESV change, with the former being negative and the latter being positive. A highly aggregated landscape also produces reduced ESV, particularly in soil maintenance and gas and climate regulation. We summarise the ESV in 2020 and in the period after adjustment in different administrative counties. Provision, regulation and culture ecosystem benefits substantially increase when attempts are made to lower the landscape aggregation pattern by 1%. In general, counties and county-level cities have the largest ESV, with food provision as the optimum ecosystem benefit. Districts in the capital city show an immense growth in provision and regulation, and county-level cities show the highest growth rate in cultural service. Integrating the landscape pattern into characterising and optimising ES, provides references for regional governance on land-use planning and socio-economic development, which is vital to sustainable regional development.