Open AccessFuzzy Models to Inform Social and Environmental Indicator Selection for Conservation Impact Monitoring
Author(s) -
Game Edward T.,
Bremer Leah L.,
Calvache Alejandro,
Moreno Pedro H.,
Vargas Amalia,
Rivera Baudelino,
Rodriguez Lina M.
Publication year - 2017
Publication title -
conservation letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.153
H-Index - 79
ISSN - 1755-263X
DOI - 10.1111/conl.12338
Subject(s) - environmental resource management , order (exchange) , selection (genetic algorithm) , business , environmental economics , risk analysis (engineering) , environmental planning , environmental impact assessment , computer science , environmental science , ecology , economics , finance , artificial intelligence , biology
Conservation projects increasingly aim to deliver both environmental and social benefits. To monitor the success of these projects, it is important to pick indicators for which there is a reasonable expectation of change as a result of the project, and which resonate with project stakeholders. Results chains are widely used in conservation to describe the hypothesized pathways of causal linkages between conservation interventions and desired outcomes. We illustrate how, with limited additional information, results chains can be turned into fuzzy models of social‐ecological systems, and how these models can be used to explore the predicted social and environmental impacts of conservation actions. These predictions can then be compared with the interests of stakeholders in order to identify good indicators of project success. We illustrate this approach by using it to select indicators for a water fund, an increasingly popular and multiobjective conservation strategy.