Download
ecog.05577.pdf 1,53MB
WeightNameValue
1000 Titel
  • Occupancy‐based diversity profiles: capturing biodiversity complexities while accounting for imperfect detection
1000 Autor/in
  1. Abrams, Jesse |
  2. Sollmann, Rahel |
  3. Mitchell, Simon |
  4. struebig, matthew |
  5. Wilting, Andreas |
1000 Erscheinungsjahr 2021
1000 LeibnizOpen
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2021-03-30
1000 Erschienen in
1000 Quellenangabe
  • Early View
1000 FRL-Sammlung
1000 Copyrightjahr
  • 2021
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1111/ecog.05577 |
1000 Ergänzendes Material
  • https://onlinelibrary.wiley.com/doi/10.1111/ecog.05577#support-information-section |
1000 Interne Referenz
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • Measuring the multidimensional diversity properties of a community is of great importance for ecologists, conservationists and stakeholders. Diversity profiles, a plotted series of Hill numbers, simultaneously capture the common diversity indices. However, diversity metrics require information on species abundance, often relying on raw count data without accounting for imperfect and varying detection. Hierarchical occupancy models account for variation in detectability, and Hill numbers have been expanded to allow estimation based on occupancy probability. But the ability of occupancy‐based diversity profiles to reproduce patterns in abundance‐based diversity has not been investigated. Here, we fit community occupancy models to simulated animal communities to explore how well occupancy‐based diversity profiles reflect patterns in true abundance‐based diversity. Because we expect occupancy‐based diversity to be overestimated, we further tested a occupancy thresholding approach to reduce potential biases in the estimated diversity profiles. Finally, we use empirical bird community data to present how the framework can be extended to consider species similarity. The simulation study showed that occupancy‐based diversity profiles produced among‐community patterns in diversity similar to true abundance diversity profiles, although within‐community diversity was generally overestimated. Applying an occupancy threshold reduced positive bias, but resulted in negative bias in richness estimates and slightly reduced the ability to reproduce true differences among the simulated communities; thus, we do not recommend application of this threshold. Application of our approach to a large bird dataset indicated differential species diversity patterns in communities of different habitat types. Accounting for phylogenetic and ecological similarities between species reduced variability in diversity among habitats. Our framework allows investigating the complexity of diversity from species detection data, while accounting for imperfect and varying detection probabilities, as well as species similarities. Visualizing results in the form of diversity profiles facilitates comparison of diversity between sites or across time. The approach offers opportunities for further development, for example by using local abundances estimated using the Royle–Nichols or N‐mixture models and further exploration of thresholding methods. In spite of some challenges, occupancy‐based diversity profiles are useful for studying and monitoring patterns in biodiversity.
1000 Sacherschließung
lokal diversity profile
lokal presence
lokal threshold
lokal biodiversity
lokal diversity index
lokal species distribution modeling
lokal occupancy
lokal specificity
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0003-0411-8519|https://orcid.org/0000-0002-1607-2039|https://orcid.org/0000-0001-8826-4868|https://orcid.org/0000-0003-2058-8502|https://orcid.org/0000-0001-5073-9186
1000 Label
1000 Förderer
  1. Bundesministerium für Bildung und Forschung |
  2. Leibniz-Institut für Zoo- und Wildtierforschung |
  3. Natural Environment Research Council |
  4. University of Kent |
  5. Projekt DEAL |
1000 Fördernummer
  1. 01LN1301A; 01LC1703A
  2. -
  3. NE/K016407/1
  4. -
  5. -
1000 Förderprogramm
  1. -
  2. -
  3. -
  4. -
  5. Open access funding
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Bundesministerium für Bildung und Forschung |
    1000 Förderprogramm -
    1000 Fördernummer 01LN1301A; 01LC1703A
  2. 1000 joinedFunding-child
    1000 Förderer Leibniz-Institut für Zoo- und Wildtierforschung |
    1000 Förderprogramm -
    1000 Fördernummer -
  3. 1000 joinedFunding-child
    1000 Förderer Natural Environment Research Council |
    1000 Förderprogramm -
    1000 Fördernummer NE/K016407/1
  4. 1000 joinedFunding-child
    1000 Förderer University of Kent |
    1000 Förderprogramm -
    1000 Fördernummer -
  5. 1000 joinedFunding-child
    1000 Förderer Projekt DEAL |
    1000 Förderprogramm Open access funding
    1000 Fördernummer -
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6427337.rdf
1000 Erstellt am 2021-05-07T13:12:14.635+0200
1000 Erstellt von 25
1000 beschreibt frl:6427337
1000 Bearbeitet von 25
1000 Zuletzt bearbeitet Fri May 07 14:12:15 CEST 2021
1000 Objekt bearb. Fri May 07 14:12:15 CEST 2021
1000 Vgl. frl:6427337
1000 Oai Id
  1. oai:frl.publisso.de:frl:6427337 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

View source