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Comparing process‐based and constraint‐based approaches for modeling macroecological patterns
Author(s) -
Xiao Xiao,
O'Dwyer James P.,
White Ethan P.
Publication year - 2016
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.1890/15-0962.1
Subject(s) - ecology , principle of maximum entropy , constraint (computer aided design) , theoretical ecology , ecological systems theory , range (aeronautics) , process (computing) , relative abundance distribution , abundance (ecology) , entropy (arrow of time) , computer science , relative species abundance , biology , mathematics , artificial intelligence , population , physics , materials science , geometry , demography , quantum mechanics , sociology , composite material , operating system
Ecological patterns arise from the interplay of many different processes, and yet the emergence of consistent phenomena across a diverse range of ecological systems suggests that many patterns may in part be determined by statistical or numerical constraints. Differentiating the extent to which patterns in a given system are determined statistically, and where it requires explicit ecological processes, has been difficult. We tackled this challenge by directly comparing models from a constraint‐based theory, the Maximum Entropy Theory of Ecology ( METE ) and models from a process‐based theory, the size‐structured neutral theory ( SSNT ). Models from both theories were capable of characterizing the distribution of individuals among species and the distribution of body size among individuals across 76 forest communities. However, the SSNT models consistently yielded higher overall likelihood, as well as more realistic characterizations of the relationship between species abundance and average body size of conspecific individuals. This suggests that the details of the biological processes contain additional information for understanding community structure that are not fully captured by the METE constraints in these systems. Our approach provides a first step towards differentiating between process‐ and constraint‐based models of ecological systems and a general methodology for comparing ecological models that make predictions for multiple patterns.