Geology topics

Research about Alberta, British Columbia, Montana

Source-linked reports with geographic coverage including Alberta, British Columbia, Montana.

3 recordsLinked to original sources

USGS2023

Bighorn sheep associations: Understanding tradeoffs of sociality and implications for disease transmission

Sociality directly influences mating success, survival rates, and disease, but ultimately likely evolved for its fitness benefits in a challenging environment. The tradeoffs between the costs and benefits of sociality can operate at multiple scales, resulting in different interpretations of animal behavior. We investigated the influence of intrinsic ( e.g. , relatedness, age) and extrinsic factors ( e.g. , land cover type, season) on direct contact (simultaneous GPS locations ≤ 25 m) rates of bighorn sheep ( Ovis canadensis ) at multiple scales near the Waterton-Glacier International Peace Park. During 2002–2012, male and female bighorn were equipped with GPS collars. Indirect contact (GPS locations ≤ 25 m regardless of time) networks identified two major breaks whereas direct contact networks identified an additional barrier in the population, all of which corresponded with prior disease exposure metrics. More direct contacts occurred between same-sex dyads than female-male dyads and between bighorn groups with overlapping summer home ranges. Direct contacts occurred most often during the winter-spring season when bighorn traveled at low speeds and when an adequate number of bighorn were collared in the area. Direct contact probabilities for all dyad types were inversely related to habitat quality, and differences in contact probability were driven by variables related to survival such as terrain ruggedness, distance to escape terrain, and canopy cover. We provide evidence that probabilities of association are higher when there is greater predation risk and that contact analysis provides valuable information for understanding fitness tradeoffs of sociality and disease transmission potential.

Alberta, British Columbia, Montana↗

USGS2021

Testing a generalizable machine learning workflow for aquatic invasive species on Rainbow Trout (Oncorhynchus mykiss) in northwest Montana

Biological invasions are accelerating worldwide, causing major ecological and economic impacts in aquatic ecosystems. The urgent decision-making needs of invasive species managers can be better met by the integration of biodiversity big data with large-domain models and data-driven products. Remotely sensed data products can be combined with existing invasive species occurrence data via machine learning models to provide the proactive spatial risk analysis necessary for implementing coordinated and agile management paradigms across large scales. We present a workflow that generates rapid spatial risk assessments on aquatic invasive species using occurrence data, spatially explicit environmental data, and an ensemble approach to species distribution modeling using five machine learning algorithms. For proof of concept and validation, we tested this workflow using extensive spatial and temporal hybridization and occurrence data from a well-studied, ongoing, and climate-driven species invasion in the upper Flathead River system in northwestern Montana, USA. Rainbow Trout (RBT; Oncorhynchus mykiss), an introduced species in the Flathead River basin, compete and readily hybridize with native Westslope Cutthroat Trout (WCT; O. clarkii lewisii), and the spread of RBT individuals and their alleles has been tracked for decades. We used remotely sensed and other geospatial data as key environmental predictors for projecting resultant habitat suitability to geographic space. The ensemble modeling technique yielded high accuracy predictions relative to 30-fold cross-validated datasets (87% 30-fold cross-validated accuracy score). Both top predictors and model performance relative to these predictors matched current understanding of the drivers of RBT invasion and habitat suitability, indicating that temperature is a major factor influencing the spread of invasive RBT and hybridization with native WCT. The congruence between more time-consuming modeling approaches and our rapid machine-learning approach suggest that this workflow could be applied more broadly to provide data-driven management information for early detection of potential invaders.

Alberta, British Columbia, Montana↗

USGS2021

Influence of water temperature and biotic interactions on the distribution of westslope cutthroat trout (Oncorhynchus clarkii lewisi) in a population stronghold under climate change

Climate warming is expected to have substantial impacts on native trout across the Rocky Mountains, but there is little understanding of how these changes affect future distributions of co-occurring native fishes within population strongholds. We used mixed-effects logistic regression to investigate the role of abiotic (e.g., temperature) and biotic factors (bull trout presence, Salvelinus confluentus ) on distributions of westslope cutthroat trout ( Oncorhynchus clarkii lewisi ; WCT) in the North Fork Flathead River, USA and Canada. The probability of WCT presence increased with stream temperature and decreased with channel gradient and bull trout presence, yet the effect of bull trout was reduced with increasing pool densities. Combining this model with spatially explicit stream temperature projections, we predict a 29% increase in suitable habitat under high emissions through 2075, with gains at mid-elevation sites predicted to exceed bull trout thermal tolerances and high-elevation sites expected to become more thermally suitable for WCT. Our study illustrates the importance of considering abiotic and biotic drivers to assess species response to climate change, helping to guide local-scale climate adaptation and management.

Alberta, British Columbia, Montana↗