Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ ZENODOarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2017
License: CC 0
Data sources: ZENODO
DRYAD
Dataset . 2017
License: CC 0
Data sources: Datacite
versions View all 2 versions
addClaim

Data from: Genomics meets applied ecology: characterizing habitat quality for sloths in a tropical agroecosystem

Authors: Fountain, Emily D.; Kang, Jung koo; Tempel, Douglas J.; Palsbøll, Per J.; Pauli, Jonathan N.; Peery, M. Zachariah;

Data from: Genomics meets applied ecology: characterizing habitat quality for sloths in a tropical agroecosystem

Abstract

Understanding how habitat quality in heterogeneous landscapes governs the distribution and fitness of individuals is a fundamental aspect of ecology. While mean individual fitness is generally considered a key to assessing habitat quality, a comprehensive understanding of habitat quality in heterogeneous landscapes requires estimates of dispersal rates among habitat types. The increasing accessibility of genomic approaches, combined with field-based demographic methods, provides novel opportunities for incorporating dispersal estimation into assessments of habitat quality. In this study, we integrated genomic kinship approaches with field-based estimates of fitness components and Approximate Bayesian Computation (ABC) procedures to estimate habitat-specific dispersal rates and characterize habitat quality in two-toed sloths (Choloepus hoffmanni) occurring in a Costa Rican agricultural ecosystem. Field-based observations indicated that birth and survival rates were similar in a sparsely-shaded cacao farm and adjacent cattle pasture-forest mosaic. Sloth density was threefold higher in pasture compared to cacao, whereas home range size and overlap were greater in cacao compared to pasture. Dispersal rates were similar between the two habitats, as estimated using ABC procedures applied to the spatial distribution of pairs of related individuals identified using 3,431 SNP and 11 microsatellite locus genotypes. Our results indicate that crops produced under a sparse overstory can, in some cases, constitute lower quality habitat than pasture-forest mosaics for sloths, perhaps because of differences in food resources or predator communities. Finally, our study demonstrates that integrating field-based demographic approaches with genomic methods can provide a powerful means for characterizing habitat quality for animal populations occurring in heterogeneous landscapes.

SNP genotypesSNP genotypes for individuals used in the ABC model. File is formatted for the program code used.SNP_Data.csvMicrosatellite genotypesThe microsatellite genotypes for individuals used in the ABC model.Microsatellite_Data.csvEcology DataThe ecological data used in the ABC model including year captured, life stage, sex and habitat patch the individual was captured in. Time represents the years for the study period with the first year (2010) represented by a zero. Life stage is determined at the time the individual was tracked either 1 for subadult or 2 for adult. Patch represents either cacao (0) or pasture-forest mosaic (1) habitat.Ecology_Data.csv

Keywords

habitat quality, Choloepus hoffmani, agroecosystem, sloths, kinship

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    0
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
    OpenAIRE UsageCounts
    Usage byUsageCounts
    visibility views 2
  • 2
    views
    Powered byOpenAIRE UsageCounts
Powered by OpenAIRE graph
Found an issue? Give us feedback
visibility
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
0
Average
Average
Average
2