Incorporating citizen science data in spatially explicit integrated population models
Related Experiment Video
Updated: Jan 23, 2026

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations
Published on: October 29, 2016
Catherine C Sun1, J Andrew Royle2, Angela K Fuller3
1New York Cooperative Fish and Wildlife Research Unit, Department of Natural Resources, Cornell University, 226 Mann Drive, Ithaca, New York, 14853, USA.
Abstract:
Information about population abundance, distribution, and demographic rates is critical for understanding a species' ecology and for effective conservation and management. To collect data over large spatial and temporal extents for such inferences, especially for species with low densities or wide distributions, citizen science can be an efficient approach. Integrated models have also emerged as an important methodology to estimate population parameters by combining multiple types of data, including citizen science data. We developed a spatially explicit integrated model that combines opportunistically collected presence-absence (PA) data, commonly collected in citizen science efforts, with systematically collected spatial capture-recapture (SCR) data, which are often limited to small spatial and temporal extents. We conducted single and multi-season simulations with parameters informed by North American black bear (Ursus americanus) populations, to evaluate the influence of varying amounts of opportunistic PA data collected at larger spatial and temporal extents on the estimation of population-level parameters. Integrating opportunistic PA data increased the precision and accuracy of posterior estimates of abundance, and survival and recruitment rates. In some cases, adding PA locations improved abundance estimates more than increasing PA detection probability. Posterior estimates were as precise and unbiased as when higher quality, but sparse, SCR data were available. We also applied the integrated model to SCR and citizen science PA data collected on black bears in New York, with results consistent with our simulations. Our findings indicate that citizen science in integrated models can be a cost-efficient way to improve estimates of population parameters and increase the spatiotemporal extent of inference. Continued developments with integrated models and citizen science data will offer additional ways to improve our understanding of population structure and demographics.
Related Concept Videos
Explicit Memories
Episodic memory contains information about personally experienced events and is reported as a story. An example of episodic memory is recalling a birthday celebration. This type of memory includes the what, where, and when of an event, as...
Analysis of Population Pharmacokinetic Data
Psychology as a Science
The scientific method in psychology involves six critical steps: making observations, formulating hypotheses, conducting tests, analyzing...
Conservation of Small Populations
What is Population Genetics?
Population Growth

