Analysis of neighborhood dynamics of forest ecosystems using likelihood methods and modeling

被引:114
作者
Canham, CD [1 ]
Uriarte, M [1 ]
机构
[1] Inst Ecosyst Studies, Millbrook, NY 12545 USA
关键词
AIC; likelihood methods; model selection; neighborhood processes; parameter estimation; seed dispersal; seedling establishment; spatially explicit models;
D O I
10.1890/04-0657
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Advances in computing power in the past 20 years have led to a proliferation of spatially explicit, individual-based models of population and ecosystem dynamics. In forest ecosystems, the individual-based models encapsulate an emerging theory of "neighborhood" dynamics, in which fine-scale spatial interactions regulate the demography of component tree species. The spatial distribution of component species, in turn, regulates spatial variation in a whole host of community and ecosystem properties, with subsequent feedbacks on component species. The development of these models has been facilitated by development of new methods of analysis of field data, in which critical demographic rates and ecosystem processes are analyzed in terms of the spatial distributions of neighboring trees and physical environmental factors. The analyses are based on likelihood methods and information theory, and they allow a tight linkage between the models and explicit parameterization of the models from field data. Maximum. likelihood methods have a long history of use for point and interval estimation in statistics. In contrast, likelihood principles have only more gradually emerged in ecology as the foundation for an alternative to traditional hypothesis testing. The alternative framework stresses the process of identifying and selecting among competing models, or in the simplest case, among competing point estimates of a parameter of a model. There are four general steps involved in a likelihood analysis: (1) model specification, (2) parameter estimation using maximum likelihood methods, (3) model comparison, and (4) model evaluation. Our goal in this paper is to review recent developments in the use of likelihood methods and modeling for the analysis of neighborhood processes in forest ecosystems. We will focus on a single class of processes, seed dispersal and seedling dispersion, because recent papers provide compelling evidence of the potential power of the approach, and illustrate some of the statistical challenges in applying the methods.
引用
收藏
页码:62 / 73
页数:12
相关论文
共 63 条
[1]  
Beissinger SR, 2002, CONDOR, V104, P208, DOI 10.1650/0010-5422(2002)104[0208:WLANSO]2.0.CO
[2]  
2
[3]   Why do tree species affect soils? The Warp and Woof of tree-soil interactions [J].
Binkley, D ;
Giardina, C .
BIOGEOCHEMISTRY, 1998, 42 (1-2) :89-106
[4]   CAUSES AND CONSEQUENCES OF RESOURCE HETEROGENEITY IN FORESTS - INTERSPECIFIC VARIATION IN LIGHT TRANSMISSION BY CANOPY TREES [J].
CANHAM, CD ;
FINZI, AC ;
PACALA, SW ;
BURBANK, DH .
CANADIAN JOURNAL OF FOREST RESEARCH, 1994, 24 (02) :337-349
[5]   Interspecific variation in susceptibility to windthrow as a function of tree size and storm severity for northern temperate tree species [J].
Canham, CD ;
Papaik, MJ ;
Latty, EF .
CANADIAN JOURNAL OF FOREST RESEARCH, 2001, 31 (01) :1-10
[6]  
Canham CD, 2004, CAN J FOREST RES, V34, P778, DOI [10.1139/x03-232, 10.1139/X03-232]
[7]  
Chamberlin TC., 1890, Science, V15, P92, DOI [10.1126/science.148.3671.754, DOI 10.1126/SCIENCE.NS-15.366.92]
[8]   Spatial and temporal variation of biomass in a tropical forest: results from a large census plot in Panama [J].
Chave, J ;
Condit, R ;
Lao, S ;
Caspersen, JP ;
Foster, RB ;
Hubbell, SP .
JOURNAL OF ECOLOGY, 2003, 91 (02) :240-252
[9]  
Clark JS, 1999, ECOLOGY, V80, P1475, DOI 10.2307/176541
[10]  
Clark JS, 2003, ECOLOGY, V84, P1370, DOI 10.1890/0012-9658(2003)084[1370:UAVIDA]2.0.CO