Characterizing the Morphology of Costa Rican Stingless Bees to Parameterize the InVEST Crop Pollination Model

Autor: Christopher Sun, Rebecca Chaplin-Kramer
Rok vydání: 2022
DOI: 10.1101/2022.10.07.511273
Popis: The InVEST Crop Pollination model operates on land use and land cover (LULC) characteristics, using available nesting sites and floral resources within a specified flight range to gauge the abundance and yield of bees species. In this study, we parameterize the InVEST Crop Pollination model to validate predictions of relative pollinator abundance in Costa Rica. Flight ranges of bee species are required as model inputs, yet are not readily available in literature compared to morphological attributes such as body length. To harness the availability of morphological data, we express the flight range of any given species as a function of its morphological attributes through a series of regressions, allowing for the estimation of flight ranges of species for which this metric is unknown. After proper parameterization, the model-predicted relative pollinator abundances of three species—Tetragonisca angustula, Partamona orizabaensis, and Trigona corvina—are compared against field data. A single proto-pollinator is then constructed as a representative species for analysis at a broader level, with model predictions validated against the total pollinator abundance across the entire spatial distribution represented by the field data. The model performs with a higher accuracy on the proto-pollinator compared to the individual species, revealing that there is surprisingly minimal added value from estimating individual flight ranges for each species. Rather, generalizing the biodiverse assortment of Costa Rican bees may yield better approximations for relative pollinator abundance.
Databáze: OpenAIRE