Jay D. Kerby

TL;DR: In this article, machine learning and cloud-based computing were combined with historical remote sensing and field data to provide the first moderate resolution, annual, percent cover maps of plant functional types across rangeland ecosystems to effectively and efficiently respond to pressing challenges facing conservation of biodiversity and ecosystem services.

TL;DR: In this article, the authors examine some of the major limiting factors impairing seedling establishment in North America's sagebrush steppe ecosystem and propose seed enhancement technologies that may have the potential to overcome these restoration barriers.

TL;DR: In this paper, the authors examined the relationship between fire behavior and spatial scale (i.e., patch grain) of fuel heterogeneity and created four heterogeneous landscapes modeled after those created by a fire-grazing interaction that differed in grain size of fuel patches.

TL;DR: In this article, the concept of precision restoration is introduced, which targets critical biotic and abiotic barriers to restoration success and applies specific tools or methods based on barrier distribution in space and time.