Citizen science project on urban canids provides different results from camera traps but generates interest and revenue

As urbanization increases, wildlife increasingly encounters people.
Coyotes (Canis latrans) and red foxes (Vulpes vulpes) are two canid
species that have readily adapted to urban environments. Citizen science
has emerged as a low-cost method of collecting data on urban-adapted
species that can benefit management agencies but may provide different
results than traditional methods. We analyzed data collected by citizen
scientists and via motion-triggered camera traps to see how each related
to the anthropogenic features of distance to roads, building density, and
median household income and the natural feature of distance to water. We
also investigated the potential benefits of advertising the citizen
science project on social media. We used occupancy models to analyze data
from a grid of 67 cameras across Wichita, Kansas, USA, from March 2023 to
February 2024. We used generalized linear models to evaluate data
collected simultaneously from a website we created and advertised on
social media where members of the public could report sightings of urban
canids. The camera-trap occupancy models suggested that red fox occurrence
was only related positively to building density and coyote occurrence was
related negatively to building density and positively to income. The
citizen science models suggested that sighting reports of both species
were more likely closer to roads, at intermediate building densities, and
in high income neighborhoods. Coyotes and red foxes were both most likely
to be detected by people during crepuscular periods but most likely to be
detected by cameras at night. We also found that advertisements increased
sighting reports and generated six times as much revenue for the wildlife
agency than was spent. Our study suggests that citizen science data
differs from camera-trap data by tracking human activity patterns and
distribution, but citizen science projects can provide other benefits such
as generating interest in and revenue for management agencies.