Stochastic Models of Plant Diversity: Application to White Sands Missile Range

Abstract

Diversity is an average property of a community and is identified as the species variety and abundance. The study of biodiversity is important because it is one of the central themes in ecology; the diversity of a system is often seen as an indicator of the well-being of the system. In this study, we selected and defined theoretical statistical measures of plant diversity and developed theoretical dynamics models for plant communities. This project provides a new approach to measuring plant diversity through time. The stochastic dynamics modeled in this project contain two main components: deterministic processes and stochastic processes. Stochastic dynamics models make it possible to simulate plant diversity changes through time even without long-term observed data. Because both the time and space dimensions are included in these stochastic dynamics models, they have more extensive uses in assessing and monitoring plant communities. The potential applications of these models include (1) providing standard diversity measures, (2) monitoring the development of plant communities in terms of species diversity and structure diversity, (3) testing the significance of the influence of human activities on plant communities, and (4) estimating the rehabilitation time of a disturbed plant community.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 2000
Accession Number
ADA374140

Entities

People

  • Alan B. Anderson
  • Bruce A. Macallister
  • George Z. Gertner
  • Xiangchi Cao

Organizations

  • Construction Engineering Research Laboratory

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Computational Science
  • Data Science
  • Differential Equations
  • Ecology
  • Environmental Protection
  • Habitats
  • Literature Surveys
  • Markov Processes
  • New York
  • Probability
  • Random Variables
  • Standards
  • Stochastic Processes
  • Surveys
  • United States
  • Wildlife
  • Wildlife Management

Fields of Study

  • Environmental science

Readers

  • Aquatic Ecology
  • Statistical inference.
  • Theoretical Analysis.

Technology Areas

  • Space