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Leveraging community science data for population assessments during a pandemic.
Howell, Paige E; Devers, Patrick K; Robinson, Orin J; Royle, J Andrew.
  • Howell PE; U.S. Geological Survey, Eastern Ecological Science Center, Laurel, Maryland, USA.
  • Devers PK; U.S. Fish and Wildlife Service, Population and Habitat Assessment Branch, Laurel, Maryland, USA.
  • Robinson OJ; Cornell Laboratory of Ornithology, Cornell University, Ithaca, New York, USA.
  • Royle JA; U.S. Geological Survey, Eastern Ecological Science Center, Laurel, Maryland, USA.
Ecol Appl ; 32(3): e2529, 2022 04.
Article in English | MEDLINE | ID: covidwho-1620116
ABSTRACT
The COVID-19 pandemic has disrupted field research programs, making conservation and management decision-making more challenging. However, it may be possible to conduct population assessments using integrated models that combine community science data with existing data from structured surveys. We developed a space-time integrated model to characterize spatial and temporal variability in population distribution. We fit our integrated model to 10 years of eBird (2010-2020) and 9 years of aerial survey (2010-2019) Mottled Duck count data to forecast 2020 population size along the western Gulf Coast of Texas and Louisiana. Estimates of Mottled Duck abundance were similar in magnitude to estimates calculated using previous methods but were more precise and showed evidence of a declining population. The spatial distribution for Mottled Ducks each year was characterized by several concentrations of relatively high abundance, although the location of these abundance "hotspots" varied over time. Expected abundance was higher for areas with a higher proportion of area covered by marsh habitat. By leveraging large-scale community science data, we were able to conduct a population assessment despite the disruption in structured surveys caused by the pandemic. As participation in community science platforms continues to increase, we anticipate modeling frameworks, like the integrated model we developed here, will become increasingly useful for informing conservation and management decision-making.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Observational study / Qualitative research Limits: Animals / Humans Language: English Journal: Ecol Appl Year: 2022 Document Type: Article Affiliation country: Eap.2529

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Observational study / Qualitative research Limits: Animals / Humans Language: English Journal: Ecol Appl Year: 2022 Document Type: Article Affiliation country: Eap.2529