Abstract
Ecosystem service‐based management requires an accurate understanding of how human modification influences ecosystem processes and these relationships are most accurate when based on functional traits. Although trait variation is typically sampled at local scales, remote sensing methods can facilitate scaling up trait variation to regional scales needed for ecosystem service management. We review concepts and methods for scaling up plant and animal functional traits from local to regional spatial scales with the goal of assessing impacts of human modification on ecosystem processes and services. We focus our objectives on considerations and approaches for (1) conducting local plot‐level sampling of trait variation and (2) scaling up trait variation to regional spatial scales using remotely sensed data. We show that sampling methods for scaling up traits need to account for the modification of trait variation due to land cover change and species introductions. Sampling intraspecific variation, stratification by land cover type or landscape context, or inference of traits from published sources may be necessary depending on the traits of interest. Passive and active remote sensing are useful for mapping plant phenological, chemical, and structural traits. Combining these methods can significantly improve their capacity for mapping plant trait variation. These methods can also be used to map landscape and vegetation structure in order to infer animal trait variation. Due to high context dependency, relationships between trait variation and remotely sensed data are not directly transferable across regions. We end our review with a brief synthesis of issues to consider and outlook for the development of these approaches. Research that relates typical functional trait metrics, such as the community‐weighted mean, with remote sensing data and that relates variation in traits that cannot be remotely sensed to other proxies is needed. Our review narrows the gap between functional trait and remote sensing methods for ecosystem service management.
Highlights
Evaluation of ecosystem service policy and management requires understanding the consequences of human modification on ecosystem processes and dependent ecosystem services at regional scales
Ecology and Evolution published by John Wiley & Sons Ltd
Statistical relationships that link local trait variation to regional environmental gradients can fail to capture these anthropogenic effects on trait variation and be of limited use in human-modified regions
Summary
Evaluation of ecosystem service policy and management requires understanding the consequences of human modification on ecosystem processes and dependent ecosystem services at regional scales (sensu Forman and Godron 1986; Chazdon 2008; Daily et al 2009). These metrics can be related to the ecosystem processes of interest based on experimental data gathered at local plot scales, and subsequently to dependent ecosystem services according to the values placed on ecosystem properties or fluxes by stakeholders (Dıaz et al 2007; Lavorel et al 2011; Finegan et al 2015) It is unclear how sampling should be conducted to capture the necessary functional trait variation in highly heterogeneous human-modified regions and whether it is even possible to model the corresponding fine-resolution trait data at the regional scale with currently available methods (Garnier et al 2007; Van Bodegom et al 2012).
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