Towards Integrated Frameworks for Assessing Bird Species Richness Using Citizen Science and Geospatial Data

ORCID

Ong'ondo: https://orcid.org/0000-0002-3550-2110; Kameni: https://orcid.org/0000-0001-5450-7518

MSU Affiliation

College of Arts and Sciences; Department of Geosciences; College of Forest Resources; Department of Wildlife, Fisheries and Aquaculture; College of Agriculture and Life Sciences; Department of Animal and Dairy Sciences

Creation Date

2026-06-01

Abstract

Citizen science has become increasingly essential for assessing species population trends and guiding conservation strategies. However, integrating citizen science input and datasets with spatial analysis remains underutilized, despite its critical potential to enhance ecological understanding and inform targeted conservation efforts. This study utilized bird data from the Kenya Bird Map initiative (January 2019–December 2023), combining with satellite imagery processed through Google Earth Engine (GEE) over the same period, to investigate the environmental factors that influenced species richness in Nairobi National Park and its surrounding buffer zone. Our methodology incorporated multiple satellite-derived datasets, selecting key environmental variables based on their ecological relevance, spatial resolution, and temporal consistency. We focused on vegetation productivity and climatic factors as critical determinants of species richness, using NDVI and EVI to assess vegetation cover and evaluating the roles of precipitation, soil moisture, and temperature in shaping species distribution and habitat quality. A Generalized Linear Model (GLM) was applied to analyze the relationship between species richness and these environmental covariates. NDVI exhibited a significant positive association with species richness (0.280 ± 0.052, P < 0.001), indicating that higher vegetation productivity supports greater bird diversity. Precipitation also had a positive effect (0.165 ± 0.056, P = 0.003), whereas soil moisture negatively influenced species richness (−0.159 ± 0.052, P = 0.002), suggesting that excessively wet conditions may reduce habitat suitability. Temperature did not exhibit a significant relationship (0.016 ± 0.043, P = 0.717). Nonlinear trends were observed, with intermediate levels of NDVI and soil moisture maximizing species richness. Interaction effects revealed that vegetation, precipitation, and soil moisture collectively influenced richness, highlighting the complexity of species-habitat associations. These findings emphasize the importance of sustainable land-use practices that align with conservation priorities to safeguard biodiversity in rapidly changing environments.

Publication Date

9-24-2025

Publication Title

Rangeland Ecology and Management

Publisher

Elsevier

First Page

218

Last Page

229

Rights

© 2025 The Society for Range Management

Link to Full Text

Share

COinS
 

Digital Object Identifier (DOI)

https://doi.org/10.1016/j.rama.2025.08.013