Publications

Big sagebrush ecosystems are widespread across drylands of western North America and provide numerous services, but the abundance of these ecosystems has declined substantially and the future of these ecosystems is uncertain. As a result, characterizing potential areas for expansion of these ecosystems is important. Species distribution models of the big sagebrush suggest areas of increasing clima

Background: Wildland–urban interface (WUI) maps identify areas with wildfire risk, but they are often outdated owing to the lack of building data. Convolutional neural networks (CNNs) can extract building locations from remote sensing data, but their accuracy in WUI areas is unknown. Additionally, CNNs are computationally intensive and technically complex, making them challenging for end-users, su

Quantification of predation, herbivory, and parasitism is critical to understanding the dynamics and trophic interactions of populations in an ecosystem. Such quantification can be challenging if the availability or consumption of the taxa are difficult to assess. Sometimes the consumption of a single prey, forage, or host is used as an overall index of the predation, herbivory, or parasitism for

Translocation of animals, especially for threatened and endangered species, is a currently popular but very challenging activity. We translocated 158 adult Agassiz's desert tortoises (Gopherus agassizii), a threatened species, from the National Training Center, Fort Irwin, in the central Mojave Desert in California, USA, to 4 plots as part of a long-distance, hard-release, mitigation-driven transl

The ability to track animals with Global Positioning System (GPS) collars opened an enormous potential for studying animal movements and behaviour in their natural environment. One such endeavour is to identify clusters of GPS locations as a way to estimate predator kill rate. Clapp et al. (2021) developed an R package (GPSeqClus) to assess a location dataset based on user-defined parameters to id

Quantifying seepage losses from unlined irrigation canals is necessary to improve water use and conservation. The use of heat as a tracer is widely used in quantifying seepage rates across the sediment–water interface. In this study, field observations and two-dimensional numerical models were used to simulate seepage losses during the 2018 and 2019 irrigation season in the Truckee Canal system. N

Here we determine how traditional morphometrics (TM) compares with geometric morphometrics (GM) in discriminating among morphologies of four forms of ciscoes of the Coregonus artedi complex collected from Lake Huron. One of the forms comprised two groups of the same deepwater cisco separated by capture depth, whereas the other three forms were shallow-water ciscoes. Our three groups of shallow-wat

Conservation planning for large ecosystems has multiple benefits but is often challenging to implement because of the multiple jurisdictions, species, and habitats involved. In addition, decision making at large spatial scales can be hampered because many approaches do not explicitly incorporate potentially competing values and concerns of stakeholders. After the Deepwater Horizon oil spill, estab

Non-native species maps are important tools for understanding and managing biological invasions. We demonstrate a novel approach to extend presence modeling to map fractional cover (FC) of non-native yellow sweet clover Melilotus officinalis in the Northern Great Plains, USA. We used ensembles of MaxEnt models to map FC across landscapes from satellite imagery trained from regional aerial imagery

Information on velocity fields in rivers is critical for designing infrastructure, modeling contaminant transport, and assessing habitat. Although non-contact approaches to measuring flow velocity are well established, these methods assume a stationary imaging platform. This study eliminates this constraint by introducing a framework for moving aircraft river velocimetry (MARV). The workflow takes

A San Francisco Estuary core was analysed at high resolution to assess its component stratigraphic signatures of the Anthropocene in the form of non-native species, Hg, spheroidal carbonaceous particles, δ13Corg, δ15N, radiogenic materials, and heavy metals. Time series analysis of the core using Ti data provides a chronology to depth 167 cm into the 1960s. Below this, to depth 230 cm, the lowermo

Accurate estimation of fuels is essential for wildland fire simulations as well as decision-making related to land management. Numerous research efforts have leveraged remote sensing and machine learning for classifying land cover and mapping forest vegetation species. In most cases that focused on surface fuel mapping, the spatial scale of interest was smaller than a few hundred square kilometers