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Developing population models: A systematic approach for pesticide risk assessment using herbaceous plants as an example

Author:
Schmolke, Amelie, Kapo, Katherine E., Rueda-Cediel, Pamela, Thorbek, Pernille, Brain, Richard, Forbes, Valery
Source:
The Science of the total environment 2017 v.599-600 pp. 1929-1938
ISSN:
0048-9697
Subject:
Asclepias, Endangered Species Act of 1973, habitats, herbaceous plants, models, pesticides, risk assessment, United States
Abstract:
Population models are used as tools in species management and conservation and are increasingly recognized as important tools in pesticide risk assessments. A wide variety of population model applications and resources on modeling techniques, evaluation and documentation can be found in the literature. In this paper, we add to these resources by introducing a systematic, transparent approach to developing population models. The decision guide that we propose is intended to help model developers systematically address data availability for their purpose and the steps that need to be taken in any model development. The resulting conceptual model includes the necessary complexity to address the model purpose on the basis of current understanding and available data.We provide specific guidance for the development of population models for herbaceous plant species in pesticide risk assessment and demonstrate the approach with an example of a conceptual model developed following the decision guide for herbicide risk assessment of Mead's milkweed (Asclepias meadii), a species listed as threatened under the US Endangered Species Act. The decision guide specific to herbaceous plants demonstrates the details, but the general approach can be adapted for other species groups and management objectives.Population models provide a tool to link population-level dynamics, species and habitat characteristics as well as information about stressors in a single approach. Developing such models in a systematic, transparent way will increase their applicability and credibility, reduce development efforts, and result in models that are readily available for use in species management and risk assessments.
Agid:
5690516