EAGER: Harnessing citizen science to disentangle the social and ecological drivers of urban biodiversity

Colorado State University, Fort Collins CO

Investigators

Abstract

The research aims to explore how wealth and other socioeconomic factors affect biodiversity in cities. Urban areas contain a significant amount of biodiversity, including 20% of the world's bird species and 5% of its plant species. However, biases in how ecological data are collected often hide the true distribution of urban wildlife. Wealthier urban neighborhoods often have more parks and green spaces, which can lead to greater diversity of plants and animals compared to lower-income areas. Yet, this pattern may be affected by biases that favor data collection in wealthier neighborhoods. Understanding urban ecology requires accurate data that capture the complex interactions between humans and nature. One way that this is done is through citizen science. Citizen science involves the public in collecting ecological data. This allows researchers to study social and ecological patterns across multiple cities. For example, the eBird project records millions of bird sightings each year. But, eBird data may be biased towards wealthier areas, potentially overestimating biodiversity compared to less affluent neighborhoods. The project will reduce these biases by analyzing data from diverse urban neighborhoods across multiple cities. The researchers will use these data to test how social and economic factors affect biodiversity patterns. By understanding these relationships, the research will address how cities affect ecological patterns and the drivers of biodiversity in urban settings. The research will also enhance citizen science's role in urban ecology by reducing bias in these datasets. The results will be important for understanding urban ecology and promoting social and environmental justice. More accurate assessments of biodiversity are essential for urban planning and conservation efforts, benefiting both wildlife and human communities. Additionally, the project will train students, including those from underserved communities. The research will expand a framework designed to mitigate sampling bias in citizen science data, focusing on understanding factors influencing the socioeconomic status (SES) and urban biodiversity relationship. The project aims to achieve three objectives: 1) Identify and quantify SES-related biases in citizen science datasets using eBird observations and a reference dataset of bird observations from underrepresented neighborhoods to fill sampling gaps; 2) Assess SES-biodiversity relationships after accounting for these biases; and 3) Evaluate how SES, built environment characteristics, and natural factors shape biodiversity across multiple cities, providing insights into urban biodiversity drivers. Our approach will apply a preferential sampling model from spatial statistics literature to jointly model species occupancy, spatial sampling intensity, and their relationships, enabling a comprehensive assessment of biodiversity patterns and sampling biases. By challenging assumptions about SES-biodiversity relationships and evaluating how socioeconomic factors interact with the built environment and natural features, this research aims to provide a clearer understanding of urban ecological dynamics, potentially reshaping theoretical frameworks and guiding future research in urban ecology and citizen science, while improving the reliability of biodiversity assessments crucial for urban planning and conservation strategies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.