首页 | 本学科首页   官方微博 | 高级检索  
     


A scalable algorithm for dispersing population
Authors:Sathish Govindarajan  Michael C Dietze  Pankaj K Agarwal  James S Clark
Affiliation:(1) Algorithms and Complexity, Max Planck Institut für Informatik, Stuhlsatzenhausweg 85, Saarbrücken, 66123, Germany;(2) Organismic & Evolutionary Biology, Harvard University, 22 Divinity Ave, Cambridge, MA 02138, USA;(3) Department of Computer Science, Duke University, Box 90129, Durham, NC 27708, USA;(4) Department of Biology, Duke University, Box 90338, Durham, NC 27708, USA
Abstract:Models of forest ecosystems are needed to understand how climate and land-use change can impact biodiversity. In this paper we describe an ecological dispersal model developed for the specific case of predicting seed dispersal by trees on a landscape for use in a forest simulation model. We present efficient approximation algorithms for computing seed dispersal. These algorithms allow us to simulate large landscapes for long periods of time. We also present experimental results that (1) quantify the inherent uncertainty in the dispersal model and (2) describe the variation of the approximation error as a function of the approximation parameters. Based on these experiments, we provide guidelines for choosing the right approximation parameters, for a given model simulation.
Keywords:Forest ecosystem  Biodiversity  Ecological dispersal model  Forest simulation model  Approximation algorithms
本文献已被 SpringerLink 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