Biodiversity varies predictably with environmental energy around the globe, but the underlaying mechanisms remain incompletely understood. The evolutionary speed hypothesis predicts that environmental kinetic energy shapes variation in speciation rates through temperature- or life history-dependent rates of evolution. To test whether variation in evolutionary speed can explain the relationship between energy and biodiversity in birds, mammals, amphibians, and reptiles, we simulated diversification over 65 myr of geological and climatic change with a spatially explicit eco-evolutionary simulation model. We modeled four distinct evolutionary scenarios in which speciation-completion rates were dependent on temperature (M1), life history (M2), temperature and life history (M3), or were independent of temperature and life-history (M0). To assess the agreement between simulated and empirical data, we performed model selection by fitting supervised machine learning models to multidimensional biodiversity patterns. We show that a model with temperature-dependent rates of speciation (M1) consistently had the strongest support. In contrast to statistical inferences, which showed no general relationships between temperature and speciation rates in tetrapods, we demonstrate how process-based modeling can disentangle the causes behind empirical biodiversity patterns. Our study highlights how environmental energy has played a fundamental role in the evolution of biodiversity over deep time. [Biogeography; diversification; machine learning; macroevolution; molecular evolution; simulation.].
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http://dx.doi.org/10.1093/sysbio/syac048 | DOI Listing |
Anal Chim Acta
March 2025
School of Automation, Central South University, 410083, Changsha, China. Electronic address:
In spectral analysis, selecting the right spectral variables is crucial for effective modeling. It reduces data dimensionality, removes irrelevant wavelength points, and improves both the generalization ability and computational efficiency of the model. However, the number of available samples often falls short of the total possible combinations of wavelengths, making variable selection a non-deterministic polynomial-time (NP) hard optimization problem.
View Article and Find Full Text PDFiScience
January 2025
Museum of Comparative Zoology, Harvard University, Cambridge, MA 02138, USA.
Tunas are high-performance pelagic fishes of considerable economic importance and have a suite of biological adaptations for high-speed locomotion. In contrast to our understanding of tuna body and muscle function, mechanosensory systems of tuna are poorly understood. Here we present the discovery of a remarkable sensory lateral line canal within the bilateral tuna keels with tubules that extend to the upper and lower keel surfaces.
View Article and Find Full Text PDFElife
January 2025
Department of Evolutionary and Environmental Biology and Institute of Evolution, University of Haifa, Haifa, Israel.
Optimal foraging theory posits that foragers adjust their movements based on prey abundance to optimize food intake. While extensively studied in terrestrial and marine environments, aerial foraging has remained relatively unexplored due to technological limitations. This study, uniquely combining BirdScan-MR1 radar and the Advanced Tracking and Localization of Animals in Real-Life Systems biotelemetry system, investigates the foraging dynamics of Little Swifts () in response to insect movements over Israel's Hula Valley.
View Article and Find Full Text PDFGenetics
January 2025
Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, Arizona 85721, USA.
Haldane's Dilemma refers to the concern that the need for many "selective deaths" to complete a substitution (i.e. selective sweep) creates a speed limit to adaptation.
View Article and Find Full Text PDFBMC Biol
January 2025
Department of Biology, Section of Zoophysiology, Aarhus University, Aarhus, 8000, Denmark.
Background: Echolocating bats face an intense arms race with insect prey that can detect bat calls and initiate evasive maneuvers. Their high closing speeds and short biosonar ranges leave bats with only a few 100 ms between detection and capture, suggesting a reactive sensory-motor operation that might preclude tracking of escaping prey. Here we test this hypothesis using greater mouse-eared bats (Myotis myotis) as a model species.
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