Seasonal and annual fluctuations of deer populations estimated by a Bayesian state-space model.

Deer overabundance is a contributing factor in the degradation of plant communities and ecosystems worldwide. The management and conservation of the deer-affected ecosystems requires us to urgently grasp deer population trends and to identify the factors that affect them. In this study, we developed a Bayesian state-space model to estimate the population dynamics of sika deer (Cervus nippon) in a cool-temperate forest in Japan, where wolves (Canis lupus hodophilax) are extinct. The model was based on field data collected from block count surveys, road count surveys by vehicles, mortality surveys during the winter, and nuisance control for 12 years (2007-2018). We clarified the seasonal and annual fluctuation of the deer population. We found a peak of deer abundance (2010) over 12 years. In 2011 the estimated deer abundance decreased drastically and has remained at a low level then. The deer abundance gradually increased from April to December during 2013-2018. The seasonal fluctuation we detected could reflect the seasonal migration pattern of deer and the population recruitment through fawn births in early summer. In our model, snowfall accumulation, which can be a lethal factor for deer, may have slightly affected their mortality during the winter. Although we could not detect a direct effect of snow on population dynamics, snowfall decrease due to global warming may decelerate the winter migration of deer; subsequently, deer staying on-site may intensively forage evergreen perennial plants during the winter season. The nuisance control affected population dynamics. Even in wildlife protection areas and national parks where hunting is regulated, nuisance control could be effective in buffering the effect of deer browsing on forest ecosystems.

Planar chiral cyclic ether: asymmetric resolution and chirality transformation.

Remarkably stable planar chirality was found in a nine-membered diallylic cyclic ether. Enantiomerically enriched ether was prepared by a kinetic resolution of a racemic one, which is valuable as a novel type of chiral building block.

Classifying aerial stems of woody plants by developmental stages using relative growth rate.

• Here we propose a new method for classifying aerial stems of woody plants by developmental stage, using the logarithmic reciprocal of relative growth rate (LRR) as an indicator of developmental stage. • Stem analyses were conducted on naturally dead aerial stems of Lindera umbellata to clarify the changes in LRR over a lifetime. LRR, number of current-year shoots, and the recruitment and mortality rates of shoots of living stems were investigated. • LRR was at a minimum value at age 1 yr and at a maximum just before each stem died. There was little difference between the ranges of stem LRR. The recruitment and mortality rates of shoots depended on LRR. • LRR satisfied the necessary and sufficient condition for a variable as an indicator of stage better than either age or size. The LRR-structured model accurately demonstrates the real demographic processes in shoot populations over a lifetime of aerial stems. This result supports the utility of LRR as an indicator of stage. The method using LRR can be applied to analyses for other growth processes.