Leveraging community science data for population assessments during a pandemic

Area of Science:

• Wildlife ecology
• Conservation science
• Ecological modeling

Background:

• COVID-19 pandemic disrupted crucial field research for wildlife population assessments.
• Traditional survey methods face challenges, necessitating alternative data integration approaches.
• Community science platforms offer vast, accessible datasets for ecological monitoring.

Purpose of the Study:

• To develop and apply a space-time integrated model for Mottled Duck population assessment.
• To characterize spatial and temporal variability in Mottled Duck distribution.
• To forecast Mottled Duck population size despite pandemic-related field research limitations.

Main Methods:

• Developed a space-time integrated model combining community science (eBird) and aerial survey data.
• Fit the model to 10 years of eBird and 9 years of aerial survey data (2010-2020).
• Forecasted 2020 Mottled Duck population size and distribution along the Texas and Louisiana Gulf Coast.

Main Results:

• Mottled Duck abundance estimates were precise and indicated a declining population trend.
• Identified dynamic spatial distribution hotspots for Mottled Ducks, varying annually.
• Higher expected abundance correlated with increased marsh habitat proportion.

Conclusions:

• Integrated modeling, leveraging community science data, enables robust population assessments during research disruptions.
• This framework provides precise, timely data for conservation and management decisions.
• The utility of integrated models is expected to grow with increasing community science participation.