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2019-01-29Zeitschriftenartikel DOI: 10.3389/fevo.2019.00009
Improving Models of Species Ecological Niches: A Remote Sensing Overview
dc.contributor.authorLeitão, Pedro J.
dc.contributor.authorSantos, Maria J.
dc.date.accessioned2019-10-31T12:54:41Z
dc.date.available2019-10-31T12:54:41Z
dc.date.issued2019-01-29none
dc.date.updated2019-08-11T15:44:56Z
dc.identifier.urihttp://edoc.hu-berlin.de/18452/21401
dc.description.abstractEffective conservation capable of mitigating global biodiversity declines require thorough knowledge on species distributions and their drivers. A species ecological niche determines its geographic distribution, and species distribution models (SDMs) can be used to predict them. For various reasons, e.g., the lack of spatial data on relevant environmental factors, SDMs fail to characterize important ecological relationships. We argue that SDMs do not yet include relevant environmental information, which can be measured with remote sensing (RS). RS may benefit SDMs because it provides information on e.g., ecosystem function, health and structure, complete spatial assessment, and reasonable temporal repeat for the processes that determine geographical distributions. However, RS data is still seldom included in such studies with the exception of climate data. Here we provide a guide for researchers aiming to improve their SDM studies, describing how they might include RS data in their specific study. We propose how to improve models of species ecological niches, by including measures of habitat quality (e.g., productivity), nutritional values, and seasonal or life-cycle events. To date, several studies have shown that using ecologically-relevant environmental predictors derived from RS improve model performance and transferability, and better approximate a species ecological niche. These data, however, are not a panacea for SDMs, as there are cases in which RS predictors are not appropriate, too costly, or exhibit low predictive power. The integration of multiple environmental predictors derived from RS in SDMs can thus improve our knowledge on processes driving biodiversity change and improve our capacity for biodiversity conservation.eng
dc.language.isoengnone
dc.publisherHumboldt-Universität zu Berlin
dc.rights(CC BY 4.0) Attribution 4.0 Internationalger
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectecological nicheeng
dc.subjectspecies conservationeng
dc.subjectremote sensingeng
dc.subjectspecies distribution (niche) modeleng
dc.subjectecological theoryeng
dc.subject.ddc570 Biologienone
dc.subject.ddc333.7 Natürliche Resourcen, Energie und Umweltnone
dc.titleImproving Models of Species Ecological Niches: A Remote Sensing Overviewnone
dc.typearticle
dc.identifier.urnurn:nbn:de:kobv:11-110-18452/21401-3
dc.identifier.doi10.3389/fevo.2019.00009none
dc.identifier.doihttp://dx.doi.org/10.18452/20673
dc.type.versionpublishedVersionnone
local.edoc.container-titleFrontiers in Ecology and Evolutionnone
local.edoc.pages7none
local.edoc.type-nameZeitschriftenartikel
local.edoc.institutionMathematisch-Naturwissenschaftliche Fakultätnone
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-publisher-nameFrontiers Media S.A.none
local.edoc.container-publisher-placeLausannenone
local.edoc.container-volume7none
dc.description.versionPeer Reviewednone
local.edoc.container-articlenumber9none
dc.identifier.eissn2296-701X

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