A method for statistically comparing spatial distribution maps

<p>Abstract</p> <p>Background</p> <p>Ecological niche modeling is a method for estimation of species distributions based on certain ecological parameters. Thus far, empirical determination of significant differences between independently generated distribution maps for...

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Main Authors: Reynolds Mary G, Walsh Matthew C, Yorita Krista L, Levine Rebecca S
Format: Article
Language:English
Published: BMC 2009-01-01
Series:International Journal of Health Geographics
Online Access:http://www.ij-healthgeographics.com/content/8/1/7
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spelling doaj-02a9b4df4bde4bb7b2ca2001382437b22020-11-25T00:33:28ZengBMCInternational Journal of Health Geographics1476-072X2009-01-0181710.1186/1476-072X-8-7A method for statistically comparing spatial distribution mapsReynolds Mary GWalsh Matthew CYorita Krista LLevine Rebecca S<p>Abstract</p> <p>Background</p> <p>Ecological niche modeling is a method for estimation of species distributions based on certain ecological parameters. Thus far, empirical determination of significant differences between independently generated distribution maps for a single species (maps which are created through equivalent processes, but with different ecological input parameters), has been challenging.</p> <p>Results</p> <p>We describe a method for comparing model outcomes, which allows a statistical evaluation of whether the strength of prediction and breadth of predicted areas is measurably different between projected distributions. To create ecological niche models for statistical comparison, we utilized GARP (Genetic Algorithm for Rule-Set Production) software to generate ecological niche models of human monkeypox in Africa. We created several models, keeping constant the case location input records for each model but varying the ecological input data. In order to assess the relative importance of each ecological parameter included in the development of the individual predicted distributions, we performed pixel-to-pixel comparisons between model outcomes and calculated the mean difference in pixel scores. We used a two sample Student's t-test, (assuming as null hypothesis that both maps were identical to each other regardless of which input parameters were used) to examine whether the mean difference in corresponding pixel scores from one map to another was greater than would be expected by chance alone. We also utilized weighted kappa statistics, frequency distributions, and percent difference to look at the disparities in pixel scores. Multiple independent statistical tests indicated precipitation as the single most important independent ecological parameter in the niche model for human monkeypox disease.</p> <p>Conclusion</p> <p>In addition to improving our understanding of the natural factors influencing the distribution of human monkeypox disease, such pixel-to-pixel comparison tests afford users the ability to empirically distinguish the significance of each of the diverse environmental parameters included in the modeling process. This method will be particularly useful in situations where the outcomes (maps) appear similar upon visual inspection (as are generated with other modeling programs such as MAXENT), as it allows an investigator the capacity to explore subtle differences among ecological parameters and to demonstrate the individual importance of these factors within an overall model.</p> http://www.ij-healthgeographics.com/content/8/1/7
collection DOAJ
language English
format Article
sources DOAJ
author Reynolds Mary G
Walsh Matthew C
Yorita Krista L
Levine Rebecca S
spellingShingle Reynolds Mary G
Walsh Matthew C
Yorita Krista L
Levine Rebecca S
A method for statistically comparing spatial distribution maps
International Journal of Health Geographics
author_facet Reynolds Mary G
Walsh Matthew C
Yorita Krista L
Levine Rebecca S
author_sort Reynolds Mary G
title A method for statistically comparing spatial distribution maps
title_short A method for statistically comparing spatial distribution maps
title_full A method for statistically comparing spatial distribution maps
title_fullStr A method for statistically comparing spatial distribution maps
title_full_unstemmed A method for statistically comparing spatial distribution maps
title_sort method for statistically comparing spatial distribution maps
publisher BMC
series International Journal of Health Geographics
issn 1476-072X
publishDate 2009-01-01
description <p>Abstract</p> <p>Background</p> <p>Ecological niche modeling is a method for estimation of species distributions based on certain ecological parameters. Thus far, empirical determination of significant differences between independently generated distribution maps for a single species (maps which are created through equivalent processes, but with different ecological input parameters), has been challenging.</p> <p>Results</p> <p>We describe a method for comparing model outcomes, which allows a statistical evaluation of whether the strength of prediction and breadth of predicted areas is measurably different between projected distributions. To create ecological niche models for statistical comparison, we utilized GARP (Genetic Algorithm for Rule-Set Production) software to generate ecological niche models of human monkeypox in Africa. We created several models, keeping constant the case location input records for each model but varying the ecological input data. In order to assess the relative importance of each ecological parameter included in the development of the individual predicted distributions, we performed pixel-to-pixel comparisons between model outcomes and calculated the mean difference in pixel scores. We used a two sample Student's t-test, (assuming as null hypothesis that both maps were identical to each other regardless of which input parameters were used) to examine whether the mean difference in corresponding pixel scores from one map to another was greater than would be expected by chance alone. We also utilized weighted kappa statistics, frequency distributions, and percent difference to look at the disparities in pixel scores. Multiple independent statistical tests indicated precipitation as the single most important independent ecological parameter in the niche model for human monkeypox disease.</p> <p>Conclusion</p> <p>In addition to improving our understanding of the natural factors influencing the distribution of human monkeypox disease, such pixel-to-pixel comparison tests afford users the ability to empirically distinguish the significance of each of the diverse environmental parameters included in the modeling process. This method will be particularly useful in situations where the outcomes (maps) appear similar upon visual inspection (as are generated with other modeling programs such as MAXENT), as it allows an investigator the capacity to explore subtle differences among ecological parameters and to demonstrate the individual importance of these factors within an overall model.</p>
url http://www.ij-healthgeographics.com/content/8/1/7
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