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Abstract Forests support food security and nutrition worldwide, especially so for highly forest-dependent communities who collect a variety of food products from nearby forests. While the importance of forest cover to the diets of forest-dependent communities has been well-researched, little is known regarding the role of more specific forest characteristics – information that would be valuable for better identifying the landscapes that support a nutritious and diverse diet. To address this research gap, we linked child dietary data to remotely-sensed geospatial indicators of surrounding forest characteristics – using more nuance than is typically undertaken – by examining forest age, tree density, and forest fragmentation in Kenya’s East African Montane Forests. Interestingly, dietary diversity of children demonstrated no or relatively weak associations with forest characteristics. However, by parsing out individual food groups, we exposed the nuance and complexities associated with the forest-diet relationship. Vegetable/fruit consumption was positively associated with open and moderately dense forest cover, but negatively associated with fragmented forest cover. The consumption of meat and vitamin A-rich fruit was positively associated with younger forest cover, and negatively associated with dense forest cover. Older forest cover was positively associated with green leafy vegetable consumption, but negatively associated with other vegetable/fruit consumption. Our findings provide suggestive evidence that there is no single ‘ideal’ type of forest for supporting food security and nutrition – rather, different types of forests are associated with different dietary benefits. Taken together, these results indicate the need for more in-depth research that accounts for factors beyond the proximity and amount of generic forest cover. 

Abstract Understanding local patterns of rainfall variability is of great concern in East Africa, where agricultural productivity is dominantly rainfall dependent. However, East African rainfall climatology is influenced by numerous drivers operating at multiple scales, and local patterns of variability are not adequately understood. Here, we show evidence of substantial variability of local rainfall patterns between 1981 and 2021 at the national and county level in Kenya, East Africa. Results show anomalous patterns of both wetting and drying in both the long and short rainy seasons, with evidence of increased frequency of extreme wet and dry events through time. Observations also indicate that seasonal and intraseasonal variability increased significantly after 2013, coincident with diminished coherence between ENSO (El Nino Southern Oscillation) and rainfall. Increasing frequency and magnitude of rainfall variability suggests increasing need for local-level climate change adaptation strategies.