9th International Deer Biology Congress

AUTHORS: Hayato Iijima, Forestry and Forest Products Research Institute

ABSTRACT: Estimation of deer abundance and its spatio-temporal dynamics are essential for population of management of deer species. There are many methods to estimate wildlife abundance. However, it is difficult to obtain sufficient data to estimate wildlife abundance by classical estimation ways because of budget limitations. It is necessary to develop a model that can integrate various but fragmented data to estimate spatio-temporal deer abundance dynamics. The objective of this study is to develop a model to estimate spatio-temporal abundance dynamics of sika deer (Cervus nippon). I used monitoring data of sika deer that were obtained in Yamanashi Prefecture, central Japan. The monitoring data included three type of deer abundance indices, the number of hunted and culled deer, and landscape characteristics. The three indices were seen deer per unit effort (SPUE) obtained from hunters’ reports, pellet group density, and block count survey. As the landscape characteristics, the percentages of evergreen forests, deciduous forests, and artificial grasslands were obtained. The number of hunted and culled deer was available from 2005 to 2015. The period and sampling area of three deer abundance indices differed. I constructed a Bayesian integrated population model for these data. In the model, I assumed that the latent spatio-temporal deer abundance correlated with three deer abundance indices, deer abundance decreased by hunting and culling but increase by population growth rate of each location that was affected by the difference of carrying capacity of each location. The carrying capacity of each location was assumed to be determined from landscape characteristics. The developed model could estimate deer abundance by 5 km square unit from 2005 to 2015. The carrying capacity of each location was enhanced by the higher percentages of deciduous forests and artificial grasslands. The result indicated that the increase of food availability provided suitable habitat for sika deer. The increase of deer abundance was regulated by hunting, culling, and density-dependence that was determined from the relationship between deer abundance and carrying capacity.

Compared to other estimation ways, a Bayesian integrated population model had advantages as: 1) the model could incorporate various but not-systematically obtained monitoring data, 2) the model could consider the latent and unobservable population dynamics of target species, and 3) the model could discriminate the stochastic error and observation error. If other type of data about vital rate of sika deer from capture-recapture, GPS tracking, or camera-trapping are obtained, the model can be easily expanded to estimate such vital rate by incorporating these data. Furthermore, the information about spatio-temporal abundance dynamics will contribute the development of hunting and culling program of target species.