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Spatial patterns of population regulation in sage grouse ( Centrocercus spp.) population viability analysis
Author(s) -
LaMontagne Jalene M.,
Irvine Robyn L.,
Crone Elizabeth E.
Publication year - 2002
Publication title -
journal of animal ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.134
H-Index - 157
eISSN - 1365-2656
pISSN - 0021-8790
DOI - 10.1046/j.1365-2656.2002.00629.x
Subject(s) - population viability analysis , population , spatial heterogeneity , lek mating , biology , population density , density dependence , ecology , extinction (optical mineralogy) , grouse , allee effect , spatial ecology , population model , galliformes , population size , habitat , demography , endangered species , paleontology , sociology , mate choice , mating
Summary1 Population viability analyses (PVAs) are commonly used to identify species of concern. Many PVA techniques assume that all populations are regulated by a single mechanism. 2 We compared population viability predictions for three subspecies of sage grouse ( Centrocercus spp.) based on the assumptions that: (i) population regulation was density‐independent vs. dependent on more complex feedback mechanisms; (ii) the mechanism of population regulation was homogeneous within a region vs. heterogeneous among leks; (iii) environmental variation was spatially correlated within regions vs. uncorrelated among leks. 3 We used sage grouse as a model species for this analysis because counts of lekking male grouse are available in some areas since the 1950s, these counts are known to fluctuate widely, and sage grouse appear to be declining throughout their range. 4 We fit population regulation models to data including density‐independence, density‐dependence, delayed density‐dependence and a simplified version of Turchin & Taylor's (1992) response surface model. 5 We show that the best‐fit models typically include spatial heterogeneity in mechanisms of population regulation. Inclusion of spatial heterogeneity increased expected time for population persistence, and changed the rank order of risk of extinction for different regions. 6 We suggest that it is important to consider multiple models of population regulation when applying population viability analysis techniques because viability projections are influenced strongly by model structure.