Reliability in Distribution Modeling—A Synthesis and Step-by-Step Guidelines for Improved Practice

Information about the distribution of a study object (e.g., species or habitat) is essential in face of increasing pressure from land or sea use, and climate change. Distribution models are instrumental for acquiring such information, but also encumbered by uncertainties caused by different sources...

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Autores principales:	Anders Bryn, Trine Bekkby, Eli Rinde, Hege Gundersen, Rune Halvorsen
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	assumptions bias distribution modeling equilibrium errors inaccuracies Evolution QH359-425 Ecology QH540-549.5
Acceso en línea:	https://doaj.org/article/7696e8378fc94555b9b031a4d3661112
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spelling	oai:doaj.org-article:7696e8378fc94555b9b031a4d36611122021-11-18T09:54:31ZReliability in Distribution Modeling—A Synthesis and Step-by-Step Guidelines for Improved Practice2296-701X10.3389/fevo.2021.658713https://doaj.org/article/7696e8378fc94555b9b031a4d36611122021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fevo.2021.658713/fullhttps://doaj.org/toc/2296-701XInformation about the distribution of a study object (e.g., species or habitat) is essential in face of increasing pressure from land or sea use, and climate change. Distribution models are instrumental for acquiring such information, but also encumbered by uncertainties caused by different sources of error, bias and inaccuracy that need to be dealt with. In this paper we identify the most common sources of uncertainties and link them to different phases in the modeling process. Our aim is to outline the implications of these uncertainties for the reliability of distribution models and to summarize the precautions needed to be taken. We performed a step-by-step assessment of errors, biases and inaccuracies related to the five main steps in a standard distribution modeling process: (1) ecological understanding, assumptions and problem formulation; (2) data collection and preparation; (3) choice of modeling method, model tuning and parameterization; (4) evaluation of models; and, finally, (5) implementation and use. Our synthesis highlights the need to consider the entire distribution modeling process when the reliability and applicability of the models are assessed. A key recommendation is to evaluate the model properly by use of a dataset that is collected independently of the training data. We support initiatives to establish international protocols and open geodatabases for distribution models.Anders BrynAnders BrynTrine BekkbyTrine BekkbyEli RindeHege GundersenRune HalvorsenFrontiers Media S.A.articleassumptionsbiasdistribution modelingequilibriumerrorsinaccuraciesEvolutionQH359-425EcologyQH540-549.5ENFrontiers in Ecology and Evolution, Vol 9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	assumptions bias distribution modeling equilibrium errors inaccuracies Evolution QH359-425 Ecology QH540-549.5
spellingShingle	assumptions bias distribution modeling equilibrium errors inaccuracies Evolution QH359-425 Ecology QH540-549.5 Anders Bryn Anders Bryn Trine Bekkby Trine Bekkby Eli Rinde Hege Gundersen Rune Halvorsen Reliability in Distribution Modeling—A Synthesis and Step-by-Step Guidelines for Improved Practice
description	Information about the distribution of a study object (e.g., species or habitat) is essential in face of increasing pressure from land or sea use, and climate change. Distribution models are instrumental for acquiring such information, but also encumbered by uncertainties caused by different sources of error, bias and inaccuracy that need to be dealt with. In this paper we identify the most common sources of uncertainties and link them to different phases in the modeling process. Our aim is to outline the implications of these uncertainties for the reliability of distribution models and to summarize the precautions needed to be taken. We performed a step-by-step assessment of errors, biases and inaccuracies related to the five main steps in a standard distribution modeling process: (1) ecological understanding, assumptions and problem formulation; (2) data collection and preparation; (3) choice of modeling method, model tuning and parameterization; (4) evaluation of models; and, finally, (5) implementation and use. Our synthesis highlights the need to consider the entire distribution modeling process when the reliability and applicability of the models are assessed. A key recommendation is to evaluate the model properly by use of a dataset that is collected independently of the training data. We support initiatives to establish international protocols and open geodatabases for distribution models.
format	article
author	Anders Bryn Anders Bryn Trine Bekkby Trine Bekkby Eli Rinde Hege Gundersen Rune Halvorsen
author_facet	Anders Bryn Anders Bryn Trine Bekkby Trine Bekkby Eli Rinde Hege Gundersen Rune Halvorsen
author_sort	Anders Bryn
title	Reliability in Distribution Modeling—A Synthesis and Step-by-Step Guidelines for Improved Practice
title_short	Reliability in Distribution Modeling—A Synthesis and Step-by-Step Guidelines for Improved Practice
title_full	Reliability in Distribution Modeling—A Synthesis and Step-by-Step Guidelines for Improved Practice
title_fullStr	Reliability in Distribution Modeling—A Synthesis and Step-by-Step Guidelines for Improved Practice
title_full_unstemmed	Reliability in Distribution Modeling—A Synthesis and Step-by-Step Guidelines for Improved Practice
title_sort	reliability in distribution modeling—a synthesis and step-by-step guidelines for improved practice
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/7696e8378fc94555b9b031a4d3661112
work_keys_str_mv	AT andersbryn reliabilityindistributionmodelingasynthesisandstepbystepguidelinesforimprovedpractice AT andersbryn reliabilityindistributionmodelingasynthesisandstepbystepguidelinesforimprovedpractice AT trinebekkby reliabilityindistributionmodelingasynthesisandstepbystepguidelinesforimprovedpractice AT trinebekkby reliabilityindistributionmodelingasynthesisandstepbystepguidelinesforimprovedpractice AT elirinde reliabilityindistributionmodelingasynthesisandstepbystepguidelinesforimprovedpractice AT hegegundersen reliabilityindistributionmodelingasynthesisandstepbystepguidelinesforimprovedpractice AT runehalvorsen reliabilityindistributionmodelingasynthesisandstepbystepguidelinesforimprovedpractice
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Reliability in Distribution Modeling—A Synthesis and Step-by-Step Guidelines for Improved Practice

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