S. K. M. Ernest

This study evaluates how ecological forecasting models perform under novel biotic conditions using a long-term desert rodent experiment, showing reduced accuracy and increased uncertainty when models are transferred to new conditions.

The paper examines how changes in bird community size composition affect long-term trends in abundance, biomass, and energy use in North America.

The paper shows that compensation for species loss in a desert rodent community declined over 30 years due to reduced functional redundancy and changing community composition.

The paper develops a general deep learning model for bird detection in aerial imagery, achieving high recall and precision with minimal local training.

The paper finds empirical species abundance distributions are more uneven than their statistical baselines, but small communities limit the ability to detect deviations.

The paper examines the macroevolution of three dimensionless life history metrics across tetrapod classes, finding correlated evolution with body mass and distinct strategy subspaces.

This paper develops an automated iterative forecasting system for ecological systems, demonstrating its application to rodent abundance forecasts using monthly data from the Portal Project.

The paper examines how body size shifts affect the metabolic responses of ectotherms to increasing temperatures.

The paper observes diverse native bees visiting non-flowering shrubs for honeydew sugars without floral cues, suggesting novel sensory mechanisms or social foraging networks.