Predicting the distribution and abundance of bustards, storks, and harriers in Kenya using citizen science data DOI Creative Commons
Frank Juma Ong’ondo,

Rosie Trevelyan,

Anthony Kuria

et al.

Frontiers in Ecology and Evolution, Journal Year: 2025, Volume and Issue: 13

Published: April 14, 2025

Citizen science has the potential to advance scientific knowledge by producing large datasets from diverse landscapes. The Kenya Bird Map (KBM) collected a data set on Kenyan birds, yet it is largely untapped for research. This study utilized KBM records (hereafter data) address specific questions regarding distribution and abundance of grassland specialist birds (bustards) opportunist species (storks harriers) within Laikipia County, Nairobi National Park Masai Mara, Kenya. Our objectives were predict these bird species’ spatial using identify key landscape elements influencing their occurrence. extracted portal 2013 - 2023, only full protocol card records. Data bustards, harriers, harrier-hawks, storks filtered, focusing pentads with over four submissions. We applied Sentinel-2B median imagery December accessible through Google Earth Engine, alongside geographic information systems remote sensing techniques classify characterize land cover types as explanatory variables. A linear mixed-effect model was used birds’ response. regression result showed that bustards responded positively patch density but negatively shrubland woodland. Storks positive responses woodland, while harriers negative had highest number records, least. Mara 16 reported across three regions, For first time, our recognized importance ongoing efforts incorporate complementary ecological deepen understanding communities environmental changes. findings suggest substantial identifying monitoring temporal

Language: Английский

Predicting the distribution and abundance of bustards, storks, and harriers in Kenya using citizen science data DOI Creative Commons
Frank Juma Ong’ondo,

Rosie Trevelyan,

Anthony Kuria

et al.

Frontiers in Ecology and Evolution, Journal Year: 2025, Volume and Issue: 13

Published: April 14, 2025

Citizen science has the potential to advance scientific knowledge by producing large datasets from diverse landscapes. The Kenya Bird Map (KBM) collected a data set on Kenyan birds, yet it is largely untapped for research. This study utilized KBM records (hereafter data) address specific questions regarding distribution and abundance of grassland specialist birds (bustards) opportunist species (storks harriers) within Laikipia County, Nairobi National Park Masai Mara, Kenya. Our objectives were predict these bird species’ spatial using identify key landscape elements influencing their occurrence. extracted portal 2013 - 2023, only full protocol card records. Data bustards, harriers, harrier-hawks, storks filtered, focusing pentads with over four submissions. We applied Sentinel-2B median imagery December accessible through Google Earth Engine, alongside geographic information systems remote sensing techniques classify characterize land cover types as explanatory variables. A linear mixed-effect model was used birds’ response. regression result showed that bustards responded positively patch density but negatively shrubland woodland. Storks positive responses woodland, while harriers negative had highest number records, least. Mara 16 reported across three regions, For first time, our recognized importance ongoing efforts incorporate complementary ecological deepen understanding communities environmental changes. findings suggest substantial identifying monitoring temporal

Language: Английский

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