Back

Ecological niche stability of Biomphalaria intermediate hosts for Schistosoma mansoni under extreme flooding and seasonal change

Iacovidou, M. A.; Byaruhanga, A. M.; Besigye, F.; Nabatte, B.; Kabaterine, N. B.; Chami, G. F.

2025-01-08 ecology
10.1101/2025.01.07.631649 bioRxiv
Show abstract

Understanding spatiotemporal distributions and niches of vectors and intermedi-ate hosts for ecologically dependent pathogens is crucial for identifying endemic areas, assessing habitat suitability for transmission, and targeting interventions for both the environment and humans. This study focuses on Biomphalaria sudan-ica and B. stanleyi, intermediate hosts of intestinal schistosomes, with over 700 million people at risk in endemic areas. We identified how extreme flooding and seasonal changes influence habitat preferences and species interactions across 674 sites in 52 villages in rural Uganda between 2022-2024. A comprehensive analy-sis of ground truth data was conducted, covering spatiotemporal information, site characteristics, physicochemical parameters, ecological factors, and human activi-ties. Spatiotemporal models incorporating a new polygon-based method to account for space, bypassing limitations of administrative boundaries, with time as a fixed effect were developed to analyse snail abundance. B. sudanica was associated with marshy sites near lake shorelines and presence of hyacinths, while B. stanleyi was more likely found in deeper waters with Vallisneria plants. However, both species often cohabited at the same sites. The extent of habitat suitability for each species fluctuated seasonally and more starkly with extreme flooding resulting in switch-ing of dominance between species. Our study shows that climatic variations may influence local changes in habitat suitability without necessitating an expansion of environmental areas. By providing a robust, generalisable spatiotemporal mod-elling pipeline, our study enables precise tracking of dynamic ecological niches in a changing climate that, if replicated in other areas, can be used to better target environmental and human interventions.

Matching journals

The top 5 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.