Publications

A key component for biologists managing mobile species is understanding where and when a species occurs at different locations and scaling management to fit the spatial and temporal patterns of movement. We established an automated radio-telemetry tracking network to document multi-year movement in 2016–2018 of 3 endangered waterbirds among wetlands on Oʻahu, Hawaiʻi, USA: ʻalae ʻula or...

Over the past century, piñon and juniper trees have encroached into sagebrush steppe lands of the interior United States, and managers have for many years removed trees to stimulate the favored understory. While consistent understory response to tree removal in these semiarid lands suggests that trees outcompete other plants for water, no studies have linked increased soil water to...

The U.S. Fish and Wildlife Service developed national guidelines to track species recovery of the endangered rusty patched bumble bee [Bombus affinis Cresson (Hymenoptera: Apidae)] and to investigate changes in species occupancy across space and time. As with other native bee monitoring efforts, managers have specifically acknowledged the need to address species detection uncertainty and...

Effective species management and conservation require knowledge of species distribution and status. We used point-transect distance sampling surveys of the endangered palila (Loxioides bailleui), a honeycreeper currently found only on the Island of Hawai'i, USA, to generate robust estimates of total abundance and simultaneously model the distribution, abundance, and spatial correlation...

We used automatic sound recorders to study spontaneous vocalizations of wild wolves during the pup-rearing season around rendezvous sites from 24 wolf packs in six study areas across North America, Asia, and Europe. Between 2018 and 2021, for a total of 1225 pack-days, we recorded 605 spontaneous wolf chorus howls and 224 solo-howl series. Howling occurrence varied across areas, from 12...

The Hawaiian Islands have been identified as a global biodiversity hotspot. We examine the Normalized Difference Vegetation Index (NDVI) using Climate Data Records products (0.05 × 0.05°) to identify significant differences in NDVI between neutral El Niño-Southern Oscillation years (1984, 2019) and significant long-term changes over the entire time series (1982–2019) for the Hawaiian...

Climatic conditions affect animals but range-wide impacts at the population level remain largely unknown, especially in migratory species. However, studying climate–population relationships is still challenging in small migrants due to a lack of efficient and cost-effective geographic tracking method.Spatial distribution patterns of environmental stable isotopes (so called ‘isoscapes’)...

Extensive drainage of peatlands in the southeastern United States coastal plain for the purposes of agriculture and timber harvesting has led to large releases of soil carbon as carbon dioxide (CO2) due to enhanced peat decomposition. Growth in mechanisms that provide financial incentives for reducing emissions from land use and land-use change could increase funding for hydrological...

Biological nitrogen fixation represents the largest natural flux of new nitrogen (N) into terrestrial ecosystems, providing a critical N source to support net primary productivity of both natural and agricultural systems. When they are common, symbiotic associations between plants and bacteria can add more than 100 kg N ha−1 y−1 to ecosystems. Yet, these associations are uncommon in many

To help better interpret computational models in predicting drift of carp eggs in rivers, we present a series of model assessments for the longitudinal egg dispersion. Two three-dimensional Lagrangian particle tracking models, SDrift and FluEgg, are evaluated in a series of channels with increasing complexity. The model evaluation demonstrates that both models are able to accommodate...

No abstract available.

Biologists routinely fit novel and complex statistical models to push the limits of our understanding. Examples include, but are not limited to, flexible Bayesian approaches (e.g. BUGS, stan), frequentist and likelihood-based approaches (e.g. packages lme4) and machine learning methods.These software and programs afford the user greater control and flexibility in tailoring complex...