Community science enhances modelled bee distributions in a tropical Asian city

Bees and the ecosystem services they provide are vital to urban
ecosystems, but little is understood about their distributions,
particularly in the Asian tropics. This is largely due to taxonomic
impediments and limited inventorying, monitoring, and digitization of
occurrence records. While expert collections (EC) are demonstrably
insufficient by themselves as a data source to model and understand bee
distributions, the boom of community science (CS) in urban areas provides
an untapped opportunity to learn about bee distributions within our
cities. We used CS observations in combination with EC observations to
model the distribution of bees in Singapore, a small tropical city-state
in Southeast Asia. To address the restricted spatial context, we performed
multiple bias corrections and show that species distribution models
performed well when estimating the distribution of habitat specialists
with distinct range limits detectable within Singapore. We successfully
modelled 37 bee species, where model statistics improved for 23 species
upon the incorporation of CS observations. Nine species had insufficient
EC observations to obtain acceptable models, but could be modelled with
the incorporation of CS observations. This is the first study to combine
both EC and CS observations to map and model the occurrences of tropical
Asian bee species for a highly urbanised region at such fine resolution.
Our results suggest that urban landscapes with impervious surfaces and
higher temperatures are less suitable for bee species, and such findings
can be used to advise the management of urban landscapes to optimise the
diversity of bee pollinators and other organisms.