Fragmented landscapes affect honey bee colony strength at diverse spatial scales in agroecological landscapes in Kenya

Abstract

Landscape fragmentation and habitat loss at multiple scales directly affect species abundance, diversity, and productivity. There is a paucity of information about the effect of the landscape structure and diversity on honey bee colony strength in Africa. Here, we present new insights into the relationship between landscape metrics such as patch size, shape, connectivity, composition, and configuration and honey bee (Apis mellifera) colony strength characteristics. Remote-sensing-based landscape variables were linked to honey bee colony strength variables in a typical highly fragmented smallholder agroecological region in Kenya. We examined colonies in six sites with varying degrees of land degradation during the period from 2017 to 2018. Landscape structure was first mapped using medium resolution bitemporal Sentinel-1 and Sentinel-2 satellite imagery with an optimized random forest model. The influence of the surrounding landscape matrix was then constrained to two buffer distances, i.e., 1 km representing the local foraging scale and 2.5 km representing the wider foraging scale around each investigated apiary and for each of the six sites. The results of zero-inflated negative binomial regression with mixed effects showed that lower complexity of patch geometries represented by fractal dimension and reduced proportions of croplands were most influential at local foraging scales (1 km) from the apiary. In addition, higher proportions of woody vegetation and hedges resulted in higher colony strength at longer distances from the apiary (2.5 km). Honey bees in moderately degraded landscapes demonstrated the most consistently strong colonies throughout the study period. Efforts towards improving beekeeper livelihoods, through higher hive productivity, should target moderately degraded and heterogeneous landscapes, which provide forage from diverse land covers.

Keywords: Kenya; Sentinel-1; Sentinel-2; honey bees; landscape fragmentation; zero-inflated negative binomial regression.