bird
; breeding
; breeding population
; climate change
; modeling
; population distribution
; population dynamics
; range expansion
; Louisiana
; United States
; Aves
; Motacilla
; Seiurus motacilla
英文摘要:
There is intense interest in basic and applied ecology about the effect of global change on current and future species distributions. Projections based on widely used static modeling methods implicitly assume that species are in equilibrium with the environment and that detection during surveys is perfect. We used multiseason correlated detection occupancy models, which avoid these assumptions, to relate climate data to distributional shifts of Louisiana Waterthrush in the North American Breeding Bird Survey (BBS) data. We summarized these shifts with indices of range size and position and compared them to the same indices obtained using more basic modeling approaches. Detection rates during point counts in BBS surveys were low, and models that ignored imperfect detection severely underestimated the proportion of area occupied and slightly overestimated mean latitude. Static models indicated Louisiana Waterthrush distribution was most closely associated with moderate temperatures, while dynamic occupancy models indicated that initial occupancy was associated with diurnal temperature ranges and colonization of sites was associated with moderate precipitation. Overall, the proportion of area occupied and mean latitude changed little during the 1997–2013 study period. Near-term forecasts of species distribution generated by dynamic models were more similar to subsequently observed distributions than forecasts from static models. Occupancy models incorporating a finite mixture model on detection – a new extension to correlated detection occupancy models – were better supported and may reduce bias associated with detection heterogeneity. We argue that replacing phenomenological static models with more mechanistic dynamic models can improve projections of future species distributions. In turn, better projections can improve biodiversity forecasts, management decisions, and understanding of global change biology. Published 2016. This article is a U.S. Government work and is in the public domain in the USA
资助项目:
Clement, M.J.
; United States Geological Survey, Patuxent Wildlife Research CenterUnited States
; 电子邮件: mclement@gmail.com
United States Geological Survey, Patuxent Wildlife Research Center, Laurel, MD, United States
Recommended Citation:
Clement M.J.,Hines J.E.,Nichols J.D.,et al. Estimating indices of range shifts in birds using dynamic models when detection is imperfect[J]. Global Change Biology,2016-01-01,22(10)