Paper No. 125-3
Presentation Time: 2:10 PM
TESTING THE NICHE CENTER HYPOTHESIS ON PLEISTOCENE BIVALVES
The relationship between species’ macroevolution and abiotic environmental variables is an area of active research in modern and fossil taxa. Ecological niche models (ENMs) have been applied to modern fauna to test hypotheses of abiotic niche characteristics and distributional dynamics that result in speciation and extinction. One area of intense modern interest is the Niche Center Hypothesis (NCH), which predicts a negative relationship between species abundance and distance to the center of the species’ fundamental niche in environmental space (Brown, 1984). Modern tests of this hypothesis yield mixed results; however, this may be a product of the limitations of estimating the fundamental niche using short (ecological) time-series data (Martínez-Meyer et al., 2013; Osorio-Olvera et al., 2019; Dallas et al., 2020). To test this hypothesis, we utilize occurrence data for six marine bivalve species from the Gulf and Atlantic Coastal Plains that extend our NCH analysis over geological timescales (0–2.8 Ma). Incorporation of the significant climate variability experienced by these species across their Pleistocene fossil record should improve model estimation of abiotic niche characteristics (temperature and salinity), and better characterize species’ fundamental niches, thereby leading to improved NCH test accuracy. ENMs were applied here to generate environmental-space ellipsoids containing known occurrences of each species, within which distances from an environmental center were calculated and frequency distributions were analyzed. Preliminary results support weak, variable, or absent NCH relationships among these taxa, which suggests that (1) the structure of species distributions within their fundamental niche is potentially complex, and (2) modern data alone are likely insufficient to meaningfully characterize the relationship between species biogeography and abiotic environment, which has important implications for predicting species’ responses to modern climate change.