Modelling density surfaces of intraspecific classes using camera trap distance sampling

Spatially explicit densities of wildlife are important for understanding environmental drivers of populations, and density surfaces of intraspecific classes allow exploration of links between demographic ratios and environmental conditions. Although spatially explicit densities and class densities are valuable, conventional design-based estimators remain prevalent when using camera-trapping methods for unmarked populations. We developed a density surface model that utilized camera trap distance sampling data within a hierarchical generalized additive modelling framework. We estimated density surfaces of intraspecific classes of a common ungulate, white-tailed deer Odocoileus virginianus, across three large management regions in Indiana, United States. We then extended simple statistical theory to test for differences in two ratios of density. Deer density was influenced by landscape fragmentation, wetlands and anthropogenic development. We documented class-specific responses of density to availability of concealment cover, and found strong evidence that increased recruitment of young was tied to increased resource availability from anthropogenic agricultural land use. The coefficients of variation of the total density estimates within the three regions we surveyed were 0.11, 0.10 and 0.06. Synthesis and applications. Our strategy extends camera trap distance sampling and enables managers to use camera traps to better understand spatial predictors of density. Our density estimates were more precise than previous estimates from camera trap distance sampling. Population managers can use our methods to detect finer spatiotemporal changes in density or ratios of intraspecific-class densities. Such changes in density can be linked to land use, or to management regimes on habitat and harvest limits of game species.