Neutral models for testing landscape hypotheses

被引:0
|
作者
Robert H. Gardner
Dean L. Urban
机构
[1] University of Maryland Center for Environmental Science,Appalachian Laboratory
[2] Duke University,Nicholas School of the Environment and Earth Sciences
来源
Landscape Ecology | 2007年 / 22卷
关键词
Neutral landscape models; Pattern and process; Landscape hypothesis testing; Land cover analysis;
D O I
暂无
中图分类号
学科分类号
摘要
Neutral landscape models were originally developed to test the hypothesis that human-induced fragmentation produces patterns distinctly different from those associated with random processes. Other uses for neutral models have become apparent, including the development and testing of landscape metrics to characterize landscape pattern. Although metric development proved to be significant, the focus on metrics obscured the need for iterative hypothesis testing fundamental to the advancement of the discipline. We present here an example of an alternative neutral model and hypothesis designed to relate the process of landscape change to observed landscape patterns. The methods and program, QRULE, are described and options for statistical testing outlined. The results show that human fragmentation of landscapes results in a non-random association of land-cover types that can be describe by simple statistical methods. Options for additional landscape studies are discussed and access to QRULE described in the hope that these methods will be employed to advance our understanding of the processes that affect the structure and function in human dominated landscapes.
引用
收藏
页码:15 / 29
页数:14
相关论文
共 50 条
  • [1] Neutral models for testing landscape hypotheses
    Gardner, Robert H.
    Urban, Dean L.
    [J]. LANDSCAPE ECOLOGY, 2007, 22 (01) : 15 - 29
  • [2] Comparing fire spread algorithms using equivalence testing and neutral landscape models
    Brian R. Miranda
    Brian R. Sturtevant
    Jian Yang
    Eric J. Gustafson
    [J]. Landscape Ecology, 2009, 24 : 587 - 598
  • [3] Comparing fire spread algorithms using equivalence testing and neutral landscape models
    Miranda, Brian R.
    Sturtevant, Brian R.
    Yang, Jian
    Gustafson, Eric J.
    [J]. LANDSCAPE ECOLOGY, 2009, 24 (05) : 587 - 598
  • [4] Testing Hypotheses in Nonparametric Models ofProduction
    Kneip, Alois
    Simar, Leopold
    Wilson, Paul W.
    [J]. JOURNAL OF BUSINESS & ECONOMIC STATISTICS, 2016, 34 (03) : 435 - 456
  • [5] Testing Inequality Constrained Hypotheses in SEM Models
    van de Schoot, Rens
    Hoijtink, Herbert
    Dekovic, Maja
    [J]. STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL, 2010, 17 (03) : 443 - 463
  • [6] Estimation and hypotheses testing in boundary regression models
    Drees, Holger
    Neumeyer, Natalie
    Selk, Leonie
    [J]. BERNOULLI, 2019, 25 (01) : 424 - 463
  • [7] Simple robust testing of hypotheses in nonlinear models
    Bunzel, H
    Kiefer, NM
    Vogelsang, TJ
    [J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2001, 96 (455) : 1088 - 1096
  • [8] Hypotheses Testing for Error-in-Variables Models
    Patricia Gimenez
    Heleno Bolfarine
    Enrico A. Colosimo
    [J]. Annals of the Institute of Statistical Mathematics, 2000, 52 : 698 - 711
  • [9] TESTING HYPOTHESES IN MIXED LINEAR-MODELS
    SEIFERT, B
    [J]. JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 1993, 36 (2-3) : 253 - 268
  • [10] Hypotheses testing for error-in-variables models
    Gimenez, P
    Bolfarine, H
    Colosimo, EA
    [J]. ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS, 2000, 52 (04) : 698 - 711