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Diversity – Independent Factors Predict Elevated Extinction Rates, Dustin Perriguey
Diversity – Independent Factors Predict Elevated Extinction Rates, Dustin Perriguey
Earth and Planetary Sciences Faculty and Staff Publications
Multiple linear regression was used to determine the relationships between diversity-independent factors (i.e., abiotic, climatic) 2, 5, and 10 Myrs-prior to the most elevated Phanerozoic extinctions. We constructed five abiotic variables from Phanerozoic proxy records1–5 to compare to extinction rates: mean temperature, temperature instability, carbon cycle instability, continental weathering rates, and habitat instability. All three models were statistically significant (P < 0.05) and explained > 70% of the variation in Alroy’s6 three-timer generic extinction rates. However, the 2 Myr-prior model explained the most variance in extinction rates and had the most predictive power, based on adjusted and predictive R2 (~ 72% and 41%, respectively). Carbon …
Northeastern China 4.2ka Database, Louis A. Scuderi, Xiaoping Yamg, Samantha Ascoli, Hongwei Li
Northeastern China 4.2ka Database, Louis A. Scuderi, Xiaoping Yamg, Samantha Ascoli, Hongwei Li
Paleoclimate Datasets
The Hunshandake Sandy Lands of northeastern China, currently a semiarid lightly vegetated region, were characterized by perennial lakes and forest stands in the early and middle Holocene. Well-developed dark grassland-type paleosols (mollisols) at the southern edge of the Hunshandake OSL-dated to between 6.93 +0.61 and 4.27 +0.38 ka along with lacustrine sands at higher elevations that date to between 5.7 +0.3 and 5.2 +0.2 ka and thick gray lacustrine sediments suggest a wetter climate. Between 4.2 and 3.8 ka, the region experienced extreme drying that was exacerbated by lake overflow drainage and sapping that depleted the groundwater table. The region …