3 Works

Data from: Global warming will affect the maximum potential abundance of boreal plant species

Sara Villén-Pérez, Juha Heikkinen, Maija Salemaa & Raisa Mäkipää
Forecasting the impact of future global warming on biodiversity requires understanding how temperature limits the distribution of species. Here we rely on Liebig’s Law of Minimum to estimate the effect of temperature on the maximum potential abundance that a species can attain at a certain location. We develop 95%-quantile regressions to model the influence of effective temperature sum on the maximum potential abundance of 25 common understory plant species of Finland, along 868 nationwide plots...

Individual quality and extra-pair paternity in the blue tit: sexy males bear the costs

Elisa P Badás, Amaia Autor, Javier Martínez, Juan Rivero-De Aguilar & Santiago Merino
Adaptive explanations for the evolution of extra-pair paternity (EPP) suggest that females seek extra-pair copulations with high quality males. Still, the link between ornamentation, individual quality and paternity remains unclear. Moreover, honest signaling is essential when explaining EPP because it is needed for sexual selection to occur; yet, it is understudied in multiple ornaments. Because blue tits (Cyanistes caeruleus) show variable color expression in several plumage patches, we tested: (i) over two seasons, whether males...

Data from: Corrigendum to: Deep learning improves taphonomic resolution: high accuracy in differentiating tooth marks made by lions and jaguars

Blanca Jiménez-García
Corrigendum to "Deep learning improves taphonomic resolution: high accuracy in differentiating tooth marks made by lions and jaguars". In a previous paper, we presented some convolutional neural network (CNN) models to classify images of tooth scores made by lions and jaguars through deep learning computer vision. In that work, we reached an accuracy of 82% of the testing set correctly classified. However, such an accuracy is biased, since the original sample was highly unbalanced. Therefor,...

Registration Year

  • 2020
    3

Resource Types

  • Dataset
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Affiliations

  • University of Alcalá
    3
  • Natural Resources Institute Finland
    1
  • Museo Nacional de Ciencias Naturales
    1
  • University of Chile
    1