A Model for Spatially Explicit Landscape Configuration and Ecosystem Service Performance, ESMAX: Model Description and Explanation

Author:

Morris Richard1,Davis Shannon2,Grelet Gwen-Aëlle3ORCID,Doscher Crile2,Gregorini Pablo1

Affiliation:

1. Department of Agricultural Science, Faculty of Agriculture and Life Sciences, Lincoln University, P.O. Box 85005, Lincoln 7674, New Zealand

2. School of Landscape Architecture, Faculty of Environment, Society and Design, Lincoln University, Lincoln 7674, New Zealand

3. Manaaki Whenua—Landcare Research, 54 Gerald Street, Lincoln 7640, New Zealand

Abstract

It is critical that we move our understanding of the ecosystem services (ESs) produced by landscapes from the present abundance of analysis to a fundamental basis of design. This involves enhancing the ability to understand and model the interconnected, coevolving system of humans and the rest of nature, thus contributing to the design of sustainable landscapes. In this paper, we hypothesise that the spatial configuration of landscape components (the size and arrangement of tree clumps, paddocks, crops, water features, etc.) impacts the production of regulating ESs, which in turn have a leveraging effect on provisioning and cultural ESs. Drawing on the precepts of Ecological Field Theory, we present the development and implications of a conceptual Geographic Information System (GIS)-based model, ESMAX, that utilises the idiosyncratic distance-decay characteristics of regulating ESs. These ‘ES fields’ are visualised as radiating into the landscape from their source components, addressing a gap in biophysical reality that has been identified as a shortcoming of existing ES modelling based on landcover proxies. Hypothetical landscape arrangements of simplified landscape components are tested with ESMAX across three regulating ESs: cooling effect, nitrogen retention, and habitat provision. The model calculates the overall ES performance of each landscape arrangement by tabulating the ES fields produced and, critically, the nonlinear response where fields overlap. The results indicate a primary sensitivity to the size of components and a secondary sensitivity to the arrangement of components. Consequently, ESMAX can be used to design landscape configurations that (1) maximise the production of specific regulating ESs and (2) improve the utilisation of natural ES-producing resources.

Publisher

MDPI AG

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