首页> 外文期刊>Journal of Agricultural, Biological, and Environmental Statistics >Predicting Life-History Traits for Female New Zealand Sea Lions, Phocarctos hookeri: Integrating Short-Term Mark-Recapture Data and Population Modeling
【24h】

Predicting Life-History Traits for Female New Zealand Sea Lions, Phocarctos hookeri: Integrating Short-Term Mark-Recapture Data and Population Modeling

机译:预测雌性新西兰海狮的生活史特征,Phocarctos hookeri:整合短期标记捕获数据和种群建模

获取原文
获取原文并翻译 | 示例
       

摘要

The trade-off between survival and reproduction by individuals is central to understanding life-history parameters of a species. Few mammal species have life-history information from long-term research. Instead, demographic models are commonly utilized to investigate an individual's life-history strategy, species dynamics, and population trends. This research investigates age-related survival and reproductive performance of adult female New Zealand (NZ) sea lions (Phocarctos hookeri), using multi-state mark-recapture data from known-age branded individuals over five years. The mark-recapture analysis was integrated with a population model to predict the lifetime reproductive output of female NZ sea lions. The integration of an analysis of short-term datasets with population modeling allows for the prediction of life-history parameters of long lived animals when long-term information is not available. While such approaches involve some caveats, it provides a framework for investigating population dynamics and is preferential to unsubstantiated assumptions. This technique can lead to better design and implementation of conservation management for long lived species.Base code is provided in the online supplement.
机译:个人生存与繁殖之间的权衡对于理解物种的生命历史参数至关重要。很少有哺乳动物物种具有长期研究的生命历史信息。取而代之的是,人口统计学模型通常用于调查个人的生活史策略,物种动态和种群趋势。这项研究使用来自已知年龄品牌个体的五年多状态标记捕获数据,调查成年雌性新西兰(NZ)海狮(Phocarctos hookeri)与年龄相关的生存和生殖能力。标记捕获分析与种群模型集成在一起,以预测雌性新西兰海狮的终生繁殖产量。短期数据集的分析与种群模型的集成可以在没有长期信息的情况下预测长寿动物的生活史参数。尽管此类方法涉及一些警告,但它提供了调查人口动态的框架,并且优先考虑没有根据的假设。该技术可以更好地设计和实施长寿物种的保护管理。在线补充中提供了基本代码。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号