Modeling the spatial distribution of a species is a fundamental problem in ecology. A number of modeling methods have been developed, an extremely popular one being MAXENT, a maximum entropy modeling approach. In this article, we show that MAXENT is equivalent to a Poisson regression model and hence is related to a Poisson point process model, differing only in the intercept term, which is scale-dependent in MAXENT. We illustrate a number of improvements to MAXENT that follow from these relations. In particular, a point process model approach facilitates methods for choosing the appropriate spatial resolution, assessing model adequacy, and choosing the LASSO penalty parameter, all currently unavailable to MAXENT. The equivalence result represents a significant step in the unification of the species distribution modeling literature.
%0 Journal Article
%1 renner_equivalence_2013
%A Renner, Ian W.
%A Warton, David I.
%D 2013
%J Biometrics
%K distribution maxent, modelling point processes, species
%N 1
%P 274--281
%R 10.1111/j.1541-0420.2012.01824.x
%T Equivalence of MAXENT and Poisson Point Process Models for Species Distribution Modeling in Ecology
%U http://onlinelibrary.wiley.com/doi/10.1111/j.1541-0420.2012.01824.x/abstract
%V 69
%X Modeling the spatial distribution of a species is a fundamental problem in ecology. A number of modeling methods have been developed, an extremely popular one being MAXENT, a maximum entropy modeling approach. In this article, we show that MAXENT is equivalent to a Poisson regression model and hence is related to a Poisson point process model, differing only in the intercept term, which is scale-dependent in MAXENT. We illustrate a number of improvements to MAXENT that follow from these relations. In particular, a point process model approach facilitates methods for choosing the appropriate spatial resolution, assessing model adequacy, and choosing the LASSO penalty parameter, all currently unavailable to MAXENT. The equivalence result represents a significant step in the unification of the species distribution modeling literature.
@article{renner_equivalence_2013,
abstract = {Modeling the spatial distribution of a species is a fundamental problem in ecology. A number of modeling methods have been developed, an extremely popular one being MAXENT, a maximum entropy modeling approach. In this article, we show that MAXENT is equivalent to a Poisson regression model and hence is related to a Poisson point process model, differing only in the intercept term, which is scale-dependent in MAXENT. We illustrate a number of improvements to MAXENT that follow from these relations. In particular, a point process model approach facilitates methods for choosing the appropriate spatial resolution, assessing model adequacy, and choosing the LASSO penalty parameter, all currently unavailable to MAXENT. The equivalence result represents a significant step in the unification of the species distribution modeling literature.},
added-at = {2017-01-09T13:57:26.000+0100},
author = {Renner, Ian W. and Warton, David I.},
biburl = {https://www.bibsonomy.org/bibtex/23c1bd7a4dd86f06a996c6ba103c9ec14/yourwelcome},
doi = {10.1111/j.1541-0420.2012.01824.x},
interhash = {9df15d80e4ef9235a28ccf892dade78d},
intrahash = {3c1bd7a4dd86f06a996c6ba103c9ec14},
issn = {1541-0420},
journal = {Biometrics},
keywords = {distribution maxent, modelling point processes, species},
language = {en},
month = mar,
number = 1,
pages = {274--281},
timestamp = {2017-01-09T14:01:11.000+0100},
title = {Equivalence of {MAXENT} and {Poisson} {Point} {Process} {Models} for {Species} {Distribution} {Modeling} in {Ecology}},
url = {http://onlinelibrary.wiley.com/doi/10.1111/j.1541-0420.2012.01824.x/abstract},
urldate = {2017-01-06},
volume = 69,
year = 2013
}