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Luizza, Matthew W.; Colorado State University, Natural Resource Ecology Laboratory; mwluizza@rams.colostate.edu; Wakie, Tewodros; Colorado State University, Natural Resource Ecology Laboratory; tewodros.wakie@colostate.edu; Evangelista, Paul H.; Colorado State University, Natural Resource Ecology Laboratory; paul.evangelista@colostate.edu; Jarnevich, Catherine S.; U.S. Geological Survey, Fort Collins Science Center; jarnevichc@usgs.gov. |
The threats posed by invasive plants span ecosystems and economies worldwide. Local knowledge of biological invasions has proven beneficial for invasive species research, but to date no work has integrated this knowledge with species distribution modeling for invasion risk assessments. In this study, we integrated pastoral knowledge with Maxent modeling to assess the suitable habitat and potential impacts of invasive Cryptostegia grandiflora Robx. Ex R.Br. (rubber vine) in Ethiopia’s Afar region. We conducted focus groups with seven villages across the Amibara and Awash-Fentale districts. Pastoral knowledge revealed the growing threat of rubber vine, which to date has received limited attention in Ethiopia, and whose presence in Afar was... |
Tipo: Peer-Reviewed Reports |
Palavras-chave: Afar region; Citizen science; Cryptostegia grandiflora; Ethiopia; Invasive species; Local ecological knowledge; Maxent; Participatory mapping; Pastoral livelihoods; Risk assessment; Rubber vine; Species distribution modeling. |
Ano: 2016 |
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Miller, Brian W.; Department of the Interior North Central Climate Science Center, Natural Resource Ecology Laboratory, Colorado State University; brian.miller@colostate.edu; Morisette, Jeffrey T.; Department of the Interior North Central Climate Science Center, Natural Resource Ecology Laboratory, Colorado State University; U.S. Geological Survey; morisettej@usgs.gov. |
Developing resource management strategies in the face of climate change is complicated by the considerable uncertainty associated with projections of climate and its impacts and by the complex interactions between social and ecological variables. The broad, interconnected nature of this challenge has resulted in calls for analytical frameworks that integrate research tools and can support natural resource management decision making in the face of uncertainty and complex interactions. We respond to this call by first reviewing three methods that have proven useful for climate change research, but whose application and development have been largely isolated: species distribution modeling, scenario planning, and simulation modeling. Species distribution... |
Tipo: Peer-Reviewed Synthesis |
Palavras-chave: Agent-based modeling; Complex-adaptive systems; Natural resource management; Scenario planning; Simulations; Species distribution modeling; State-and-transition modeling. |
Ano: 2014 |
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