首页 | 本学科首页   官方微博 | 高级检索  
     


Important population viability analysis parameters for giant pandas (Aliuropoda melanoleuca)
Authors:Gong Ming-Hao  Song Yan-Ling  Yang Zhi-Song  Lin Chen
Affiliation:Wildlife Monitoring Centre, Academy of Forest Inventory and Planning, State Forestry Administration, Beijing 100714, China. gongmh2005@hotmail.com.
Abstract:Population viability analysis (PVA) is a tool to evaluate the risk of extinction for endangered species and aid conservation decision-making. The quality of PVA output is dependent on parameters related to population dynamics and life-history; however, it has been difficult to collect this information for the giant panda (Aliuropoda melanoleuca), a rare and endangered mammal native to China, confined to some 30 fragmented habitat patches. Since giant pandas are long-lived, mature late, have lower reproductive rates, and show little sexual dimorphism, obtaining data to perform adequate PVA has been difficult. Here, we develop a parameter sensitivity index by modeling the dynamics of six giant panda populations in the Minshan Mountains, in order to determine the parameters most influential to giant panda populations. Our data shows that the giant panda populations are most sensitive to changes in four female parameters: initial breeding age, reproductive rate, mortality rate between age 0 and 1, and mortality rate of adults. The parameter sensitivity index strongly correlated with initial population size, as smaller populations were more sensitive to changes in these four variables. This model suggests that demographic parameters of females have more influence on the results of PVA, indicating that females may play a more important role in giant panda population dynamics than males. Consequently, reintroduction of female individuals to a small giant panda population should be a high priority for conservation efforts. Our findings form a technical basis for the coming program of giant panda reintroduction, and inform which parameters are crucial to successfully and feasibly monitoring wild giant panda populations.
Keywords:
本文献已被 CNKI PubMed 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号