Literature DB >> 27541951

Using ecological production functions to link ecological processes to ecosystem services.

Randall Jf Bruins1, Timothy J Canfield2, Clifford Duke3, Larry Kapustka4, Amanda M Nahlik5,6, Ralf B Schäfer7.   

Abstract

Ecological production functions (EPFs) link ecosystems, stressors, and management actions to ecosystem services (ES) production. Although EPFs are acknowledged as being essential to improve environmental management, their use in ecological risk assessment has received relatively little attention. Ecological production functions may be defined as usable expressions (i.e., models) of the processes by which ecosystems produce ES, often including external influences on those processes. We identify key attributes of EPFs and discuss both actual and idealized examples of their use to inform decision making. Whenever possible, EPFs should estimate final, rather than intermediate, ES. Although various types of EPFs have been developed, we suggest that EPFs are more useful for decision making if they quantify ES outcomes, respond to ecosystem condition, respond to stressor levels or management scenarios, reflect ecological complexity, rely on data with broad coverage, have performed well previously, are practical to use, and are open and transparent. In an example using pesticides, we illustrate how EPFs with these attributes could enable the inclusion of ES in ecological risk assessment. The biggest challenges to ES inclusion are limited data sets that are easily adapted for use in modeling EPFs and generally poor understanding of linkages among ecological components and the processes that ultimately deliver the ES. We conclude by advocating for the incorporation into EPFs of added ecological complexity and greater ability to represent the trade-offs among ES. Integr Environ Assess Manag 2017;13:52-61.
© 2016 SETAC. © 2016 SETAC.

Entities:  

Keywords:  Decision making; Ecological model; Final ecosystem services; Pesticides; Stressors

Mesh:

Year:  2016        PMID: 27541951      PMCID: PMC6089041          DOI: 10.1002/ieam.1842

Source DB:  PubMed          Journal:  Integr Environ Assess Manag        ISSN: 1551-3777            Impact factor:   2.992


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