{"refrec":{"BRefID":307813,"RR":"<b>Zabihi, K.; Paige, G.B.; Hild, A.L.; Miller, S.N.; Wuenschel, A.; Holloran, M.J.</b> (2017). A fuzzy logic approach to analyse the suitability of nesting habitat for greater sage-grouse in western Wyoming. <i>Journal of Spatial Science 62(2)</i>: 215-234. <a href=\"https://dx.doi.org/10.1080/14498596.2017.1292965\" target=\"_blank\">https://dx.doi.org/10.1080/14498596.2017.1292965</a>","BEntID":300139,"PublicFlag":1,"CheckedFlag":0,"wosflag":1,"vabbflag":1,"RefStringPartII":". <i>Journal of Spatial Science 62(2)</i>: 215-234. <a href=\"https://dx.doi.org/10.1080/14498596.2017.1292965\" target=\"_blank\">https://dx.doi.org/10.1080/14498596.2017.1292965</a>","DocTypID":8,"DocType":"Journal article","MarineFlag":0,"FreshFlag":0,"BrackishFlag":0,"TerrestrialFlag":0,"Authorstring":"Zabihi, K.; Paige, G.B.; Hild, A.L.; Miller, S.N.; Wuenschel, A.; Holloran, M.J.","OrigTitleTranslFlag":0,"Authorstringtrunc":"Zabihi, K. <i>et al.</i>","Englishabstract":"Habitat suitability analysis is complex and requires integration of multiple attributes at a range of spatial scales. We use fine- and broad-scale variables within a spatial modelling framework to determine the suitability of greater sage-grouse nesting habitat using fuzzy logic. Fuzzy theory allows for a landscape component to have full, partial, or no membership in a particular management target. We used seven biophysical and anthropogenic variables correlated with nest site locations to build the fuzzy model. Using field and remotely sensed data and expert opinion, we developed fuzzy functions to define numerical membership values describing relationships between landscape characteristics and nesting habitat suitability. We used a fuzzy gamma overlay function to define five suitability classes in the resulting habitat map. 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