Inferring plant ecosystem organization from species occurrences

被引:32
作者
Azaele, S. [1 ]
Muneepeerakul, R. [1 ]
Rinaldo, A. [2 ]
Rodriguez-Iturbe, I. [1 ]
机构
[1] Princeton Univ, Dept Civil & Environm Engn, Princeton, NJ 08544 USA
[2] Ecole Polytech Fed Lausanne, Fac ENAC, Lab Ecohydrol, CH-1015 Lausanne, Switzerland
关键词
Maximum entropy; Ising model; Power law; Ecological interactions; Occurrence data; Species associations; NULL MODEL ANALYSIS; MAXIMUM-ENTROPY; STATISTICAL-MECHANICS; INFORMATION THEORY; PATTERNS; FACILITATION; COMMUNITIES; BIODIVERSITY; NETWORKS;
D O I
10.1016/j.jtbi.2009.09.026
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
In this paper, we present an approach capable of extracting insights on ecosystem organization from merely occurrence (presence/absence) data. We extrapolate to the collective behavior by encapsulating some simplifying assumptions within a given set of constraints, and then examine their ecological implications. We show that by using the mean occurrence and co-occurrence of species as constraints, one is able to capture detailed statistics of a plant community distributed across a vast semiarid area of the United States. The approach allows us to quantify the species' effective couplings: Their frequencies exhibit a peak at zero and the minimal pairwise model is able to capture about 80% of the ecosystem structure. Our analysis reveals a relatively stronger impact of the species network on uncommon species and underscores the importance of species pairs experiencing positive couplings. Additionally, we study the associations among species and, interestingly, find that the frequencies of groups of different species, which the approach is able to capture. exhibit a power-law-like distribution. (C) 2009 Elsevier Ltd. All rights reserved.
引用
收藏
页码:323 / 329
页数:7
相关论文
共 35 条
[1]  
[Anonymous], 1996, WILEY, DOI DOI 10.2307/2265928
[2]  
[Anonymous], 2003, PROBABILITY THEORY
[3]   Dynamical evolution of ecosystems [J].
Azaele, Sandro ;
Pigolotti, Simone ;
Banavar, Jayanth R. ;
Maritan, Amos .
NATURE, 2006, 444 (7121) :926-928
[4]   Inclusion of facilitation into ecological theory [J].
Bruno, JF ;
Stachowicz, JJ ;
Bertness, MD .
TRENDS IN ECOLOGY & EVOLUTION, 2003, 18 (03) :119-125
[5]  
Callaway RM, 1997, ECOLOGY, V78, P1958, DOI 10.1890/0012-9658(1997)078[1958:CAFASA]2.0.CO
[6]  
2
[7]   Statistical mechanics unifies different ecological patterns [J].
Dewar, Roderick C. ;
Porte, Annabel .
JOURNAL OF THEORETICAL BIOLOGY, 2008, 251 (03) :389-403
[8]   Performance guarantees for regularized maximum entropy density estimation [J].
Dudík, M ;
Phillips, SJ ;
Schapire, RE .
LEARNING THEORY, PROCEEDINGS, 2004, 3120 :472-486
[9]  
Gotelli NJ, 2000, ECOLOGY, V81, P2606, DOI 10.1890/0012-9658(2000)081[2606:NMAOSC]2.0.CO
[10]  
2