Data from: Hierarchical multi-grain models improve descriptions of species’ environmental associations, distribution, and abundance

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datacite.RelatedIdentifierhttps://doi.org/10.1002/eap.2117
datacite.RelatedIdentifier.relatedIdentifierTypeDOI
datacite.RelatedIdentifier.relationTypeIsSupplementTo
dc.contributor.authorMertes, Katherine
dc.contributor.authorJetz, Walter
dc.contributor.authorWikelski, Martin
dc.date.accessioned2020-03-18T11:34:38Z
dc.date.available2020-03-18T11:34:38Z
dc.date.issued2020-03-18
dc.date.submitted2020
dc.description.abstractThe characterization of species’ environmental niches and spatial distribution predictions based on them are now central to much of ecology and conservation, but implicitly requires decisions about the appropriate spatial scale (i.e. grain) of analysis. Ecological theory and empirical evidence suggest that range‐resident species respond to their environment at two characteristic, hierarchical spatial grains: (i) response grain, the (relatively fine) grain at which an individual uses environmental resources, and (ii) occupancy grain, the (relatively coarse) grain equivalent to a typical home range. We use a multi‐grain (MG) occupancy model, aided by fine‐grain remotely sensed imagery, to simultaneously estimate species‐environment associations at both grains, conduct grain optimization to measure response grain, and apply this analysis framework to an example species: a medium‐sized bird (Tockus deckeni) in a heterogeneous East African landscape. Based on home range analysis of movement data, we calculate an occupancy grain of 1km for T. deckeni. Using a grain optimization procedure across 32 grains from 10m to 500m, we identify 60m as the most strongly supported response grain for a suite of environmental variables, slightly coarser than opportunistic behavioral observations would have suggested. Validation confirms that the accuracy of the optimized MG occupancy model substantially exceeds that of equivalent single‐grain (SG) occupancy models. We further use a simulation approach to assess the potential impacts of accounting for the multi‐scale structure of species’ environmental requirements on estimates of population size. We find that the more strongly supported MG approach consistently predicts a minimum population sizes in the study landscape that is much lower than that provided by the SG model. This suggests that SG approaches commonly used in conservation applications could lead to overly optimistic abundance and population estimates and that the MG approach may be more appropriate for supporting species conservation goals. More generally, we conclude that multi‐grain approaches of the sort presented, and increasingly enabled by growing high‐resolution remotely sensed data, hold great promise for offering a more mechanistic framework for assessing the appropriate grain(s) for population monitoring and management and enable more reliable estimates of abundances and species’ distributions.
dc.identifier.doidoi:10.5441/001/1.cp97k9j1
dc.identifier.urihttps://datarepository.movebank.org/handle/10255/move.1052
dc.language.isoeng
dc.relationEcological Applications
dc.relation.haspartdoi:10.5441/001/1.cp97k9j1/1
dc.relation.haspartdoi:10.5441/001/1.cp97k9j1/2
dc.relation.isreferencedbydoi:10.1002/eap.2117
dc.rightsCC0 1.0 Universalen
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/
dc.subjectTockus deckeni
dc.subjectanimal movement
dc.subjectanimal tracking
dc.subjectGPS logger
dc.subjectspecies distributions
dc.subjectspecies-environment relationships
dc.subjectTockus deckeni
dc.subjectVon der Decken's hornbill
dc.titleData from: Hierarchical multi-grain models improve descriptions of species’ environmental associations, distribution, and abundance
dc.typeArticle
dspace.entity.typeData package
dwc.ScientificNameTockus deckeni
mdr.animal.count18
mdr.citation.BibTex
@misc{001/1_cp97k9j1,
  title = {Data from: Hierarchical multi-grain models improve descriptions of species’ environmental associations, distribution, and abundance},
  author = {Mertes, K and Jetz, W and Wikelski, M},
  year = {2020},
  URL = {http://dx.doi.org/10.5441/001/1.cp97k9j1},
  doi = {doi:10.5441/001/1.cp97k9j1},
  publisher = {Movebank data repository}
}
mdr.citation.CSE
Mertes K, Jetz W, Wikelski M. 2020. Data from: Hierarchical multi-grain models improve descriptions of species’ environmental associations, distribution, and abundance. Movebank Data Repository. https://doi.org/10.5441/001/1.cp97k9j1
mdr.citation.RIS
TY  - DATA
ID  - doi:10.5441/001/1.cp97k9j1
T1  - Data from: Hierarchical multi-grain models improve descriptions of species’ environmental associations, distribution, and abundance
AU  - Mertes, Katherine
AU  - Jetz, Walter
AU  - Wikelski, Martin
Y1  - 2020/03/18
KW  - Tockus deckeni
KW  - Africa
KW  - animal movement
KW  - animal tracking
KW  - GPS logger
KW  - species distributions
KW  - species-environment relationships
KW  - Tockus deckeni
KW  - Von der Decken's hornbill
KW  - Tockus deckeni
PB  - Movebank data repository
UR  - http://dx.doi.org/10.5441/001/1.cp97k9j1
DO  - doi:10.5441/001/1.cp97k9j1
ER  -
mdr.journal.titleEcological Applications
mdr.location.count189700
mdr.study.id1087068449
relation.isAuthorOfDatapackagec53d97c2-22c2-401f-b255-a470c9b21fba
relation.isAuthorOfDatapackageac96b0f1-eef0-4ec3-a3be-9b8deda57efc
relation.isAuthorOfDatapackagee428d6f8-12ff-4b7c-a303-e85efc5fdbe8
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sensor.nameGPS
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