文献类型：期刊文献

英文题名：Developing, testing and application of rodent population dynamics and capture models based on an adjusted Leslie matrix-based population approach

作者：Fu, Liyong[1] Tang, Shouzheng[1] Liu, Yingan[2] Sharma, Ram P.[3] Zhang, Huiru[1] Lei, Yuancai[1] Wang, Hong[1] Song, Xinyu[1]

第一作者：符利勇

通信作者：Fu, LY[1]

机构：[1]Chinese Acad Forestry, Res Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China;[2]Nanjing Forest Univ, Dept Math, Nanjing 210037, Jiangsu, Peoples R China;[3]Norwegian Univ Life Sci, Dept Ecol & Nat Resource Management, N-1432 As, Norway

年份：2014

卷号：7

期号：3

外文期刊名：INTERNATIONAL JOURNAL OF BIOMATHEMATICS

收录：;Scopus(收录号：2-s2.0-84901604268);WOS:【SCI-EXPANDED(收录号:WOS:000339628000002)】；

基金：The authors thank Prof. Yemao Xia, Prof. Xiangdong Lei and other researchers at the Chinese Academy of Forestry for their insightful suggestions. We also thank two anonymous reviewers for useful comments on previous versions of the manuscript. Total expense of field investigation was borne by the Chinese National Natural Science Foundations (Nos. 31300534, 31100476) for financial support for this study.

语种：英文

外文关键词：Apodemus agrarius; capture model; Leslie matrix; optimal population density; population dynamics model; capture-mark-recapture

摘要：Small rodents in general and the multimammate rat Apodemus agrarius in particular, damage crops and cause major economic losses in China. Therefore, accurate predictions of the population size of A. agrarius and an efficient control strategy are urgently needed. We developed a population dynamics model by applying a Leslie matrix method, and a capture model based on optimal harvesting theory for A. agrarius. Our models were parametrized using demographic estimates from a capture-mark-recapture (CMR) study conducted on the Qinshui Forest Farm in Northwestern China. The population dynamics model incorporated 12 equally balanced age groups and included immigration and emigration parameters. The model was evaluated by assessing the predictions for four years based on the known starting population in 2004 from the 2004-2007 CMR data. The capture model incorporated two functional age categories (juvenile and adult) and used density-dependent and density-independent factors. The models were used to assess the effect of rodent control measures between 2004 and 2023 on population dynamics and the resulting numbers of rats. Three control measures affecting survival rates were considered. We found that the predicted population dynamics of A. agrarius between 2004 and 2007 compared favorably with the observed population dynamics. The models predicted that the population sizes of A. agrarius in the period between 2004 and 2023 under the control measure applied in August 2004 were very similar to the optimal population sizes, and no significant difference was found between the two population sizes. We recommend using the population dynamics and capture models based on CMR-estimated demographic schedules for rodent, provided these data are available. The models that we have developed have the potential to play an important role in predicting the effects of rodent management and in evaluating different control strategies.