Research

Kaiser, A., & Resasco, J. (2024). The impact of impervious surface and neighborhood wealth on arthropod biodiversity and ecosystem services in community gardens. Urban Ecosystems, 1-13.

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Abstract: As the number of humans living in cities has grown, interest in the value of community gardens to provide agricultural products has increased. However, neighborhoods with different land cover patterns and socioeconomic characteristics often differ in their ecological attributes, leading to potential differences in biodiversity-mediated ecosystem services (e.g., pollination and pest control). Here we ask, how do impervious surface and socioeconomic features of the urban matrix around community gardens impact arthropod biodiversity and pollination and pest control. services? We collected arthropods (insects, arachnids, myriapods, and isopods) across community gardens in Boulder Co., CO, and used experimental jalapeño pepper plants as a sentinel crop to measure herbivory damage and pollination services. We categorized arthropods into functional guilds to see how impervious surface and neighborhood wealth in the urban matrix surrounding a site impacts the abundance of three focal groups – pollinators, herbivorous pests, and predators. We also looked at how bee Hill-Simpson diversity responded to these variables. Through structural equation modeling, we found that fruit size increased as bee biodiversity increased, and bee biodiversity and overall pollinator abundance were negatively related to neighborhood wealth. Additionally, pollinator abundance was lower in gardens surrounded by higher amounts of impervious surfaces. Neighborhood wealth and impervious surfaces were positively correlated with herbivore and predator abundances, but these abundances had no relationship with herbivory damage in our plants. This research shows that reducing the amounts of impervious surface in the urban matrix can help increase bee biodiversity and abundance and improve pollination services in urban community gardens.

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Kaiser A, Resasco J,  Dee LE. (2025). Synthetic control methods enable stronger causal inference using participatory science data in cities. Submitted for review. 

Abstract: As urban populations grow, conserving biodiversity within cities is increasingly vital and of global policy interest. However, urban environments pose unique challenges for understanding drivers of biodiversity change, as fragmented land ownership makes traditional biodiversity monitoring and randomized experiments logistically difficult. While participatory science platforms like iNaturalist offer a promising data source by providing extensive biodiversity data from urban areas, inferring causality remains challenging due to confounding factors in observational data. To leverage these data advances, we offer a framework that combines records from iNaturalist with synthetic control methods, a quasi-experimental approach. We demonstrate this approach in a case study assessing the impact of Hurricane Ida (2021) on bee biodiversity in Philadelphia, USA. The synthetic control estimated a 9.4% decline in bee abundance two years post-event. In contrast, three conventional ecological analyses—an interrupted time series regression, before-after comparison, and a before-after control impact (BACI) design—failed to detect this decline, with the before-after approach naively detecting an increase due to unaccounted temporal trends. Synthetic control methods offer a powerful tool for estimating citywide biodiversity responses to climate events and policy interventions, enhancing the utility of participatory science data for urban ecology.

Keywords: citizen science, community science, GBIF, causal analysis, urban biodiversity, driver attribution