Multiple observation processes in spatial capture-recapture models: How much do we gain?
camera trap
data integration
large carnivore
multiple observation process
noninvasive monitoring
simulation
spatial capture-recapture
Journal
Ecology
ISSN: 1939-9170
Titre abrégé: Ecology
Pays: United States
ID NLM: 0043541
Informations de publication
Date de publication:
07 2020
07 2020
Historique:
received:
12
07
2019
revised:
27
12
2019
accepted:
29
01
2020
pubmed:
1
3
2020
medline:
22
1
2021
entrez:
1
3
2020
Statut:
ppublish
Résumé
Population monitoring data may originate from multiple methods and are often sparse and fraught with incomplete information due to practical and economic constraints. Models that can integrate multiple survey methods and are able to cope with incomplete data may help investigators exploit available information more thoroughly. Here, we developed an integrated spatial capture-recapture (SCR) model to incorporate multiple data sources with imperfect individual identification. We contrast inferences drawn from this model with alternate models incorporating only subsets of the data available. Using extensive simulations and an empirical example of multi-method brown bear (Ursus arctos) monitoring data from northern Pakistan, we quantified the benefits of including multiple sources of information in SCR models in terms of parameter precision and bias. Our multiple observation processes SCR model (MOP) yielded a more complete picture of the underlying processes, reduced bias, and led to more precise parameter estimates. Our results suggest that the greatest gains from integrated SCR models can be expected in situations where detection probability is low, a large proportion of detections is not attributable to individuals, and the degree of overlap between individual home ranges is low.
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e03030Subventions
Organisme : Norges Forskningsråd
ID : 204202/F20
Pays : International
Organisme : Norges Forskningsråd
ID : 286886
Pays : International
Informations de copyright
© 2020 The Authors. Ecology published by Wiley Periodicals, Inc. on behalf of Ecological Society of America.
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