|Title||How will predicted land-use change affect waterfowl spring stopover ecology? Inferences from an individual-based model|
|Publication Type||Journal Article|
|Year of Publication||2016|
|Authors||Beatty, William S., Kesler Dylan C., Webb Elisabeth B., Naylor Luke W., Raedeke Andrew H., Humburg Dale D., Coluccy John, and Soulliere Gregory J.|
|Secondary Authors||Alves, José|
|Journal||Journal of Applied Ecology|
|Pagination||926 - 934|
|Keywords||agent‐based model, Anas platyrhynchos, asynchrony, climate change, Dabbling duck, land cover change, land‐use change, mallard migration, stopover area, stopover duration|
Wildlife populations face numerous conservation challenges, including habitat loss and climate change (Primack 2014). As a result, conservation planners have designed protected area networks to account for landscape composition, structure and function in wildlife conservation efforts (Margules & Pressey 2000). However, protected area networks are ecologically linked to surrounding landscapes, and changing land‐use practices proximate to protected areas may impede conservation effectiveness (Hansen & DeFries 2007). Thus, conservation planners need information on how future land‐use changes may affect the ability of protected area networks to conserve wildlife populations (Hamilton et al. 2013).
One tool that conservation planners may use to evaluate the implications of future land‐use changes on protected area networks is scenario planning (Peterson, Cumming & Carpenter 2003). Generally, scenario planning allows decision‐makers to consider the effects of multiple factors on complex systems characterized by high levels of uncertainty. In ecology and conservation, scenario planning may involve individual‐based models (IBMs) that include adaptive animal behaviours and stochastic processes (Frederick, Clark & Klaas 1987; Grimm & Railsback 2005; McLane et al. 2011). Thus, IBMs provide conservation planners with a means to examine the potential effects of future scenarios, altered resource distributions and other novel landscape‐level changes on wildlife populations (Peterson, Cumming & Carpenter 2003; McLane et al. 2011).
|Short Title||J Appl Ecol|