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You are here: Home » Online First » Volume 19, 2024 - Number 2 » WILDPOP: AN INTERACTIVE TOOL FOR ESTIMATING OCCUPANCY AND ABUNDANCE OF WILDLIFE POPULATIONS,  Carpathian Journal of Earth and Environmental Sciences February 2024, Vol. 19, No. 2, p. 321 – 328; DOI:10.26471/cjees/2024/019/302


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Laurentiu ROZYLOWICZ1*, Viorel D. POPESCU1,2, Marian D. MIREA1, Steluta MANOLACHE1, Iulia V. MIU1, Andreea NITA1, Lavinia PINDARU1, & Raluca I. BANCILA1,3
1University of Bucharest, Center for Environmental Research, 1 N. Balcescu, Bucharest 010041, Romania
2Columbia University, Ecology, Evolution and Environmental Biology, New York, NY 10027, USA
3Emil Racovita Institute of Speleology of Romanian Academy of Sciences, 13, Septembrie Road, 050711 Bucharest, Romania
Corresponding author: laurentiu.rozylowicz@g.unibuc.ro


WILDPOP: AN INTERACTIVE TOOL FOR ESTIMATING OCCUPANCY AND ABUNDANCE OF WILDLIFE POPULATIONS,  Carpathian Journal of Earth and Environmental Sciences February 2024, Vol. 19, No. 2, p. 321 – 328; DOI:10.26471/cjees/2024/019/302

Full text

Abstract:

Species abundance or population size is an ecological parameter of critical importance for wildlife management and conservation decisions. Widely used data collection methods, such as sign surveys and remote cameras, often count non-identifiable individuals or individuals prone to misidentification. In ecological modeling, these individuals are considered unmarked, and a state-of-the-art modeling approach for such data is occupancy-type modeling for unmarked individuals, which explicitly incorporates imperfect detection. Hierarchical modeling of this kind requires advanced statistical analyses, typically conducted using the R software platform and the “unmarked” package. However, these models can be explored only by researchers with programming skills and a thorough understanding of hierarchical analysis of wildlife population data. To help researchers and practitioners implement these models, we have developed a Shiny web-based interactive tool for wildlife population assessment, which works with data collected by scientists and wildlife managers. This app facilitates the use of occupancy-type modeling for unmarked individuals (single-season single species occupancy and N-mixture models) for non-coder users. The app performs simulations for single-season single species occupancy and N-mixture models with or without covariates, and estimates occupancy and abundance employing users provided data. The results are displayed as text, tables, and graphs, helping users understand hierarchical modeling and answering real-life wildlife management questions.



Keyword: hierarchical modeling, single-season single species occupancy, N-mixture abundance, Shiny, unmarked, Romania


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