Effects of Wolf Presence on Daily Travel Distance of Range Cattle

Clark, Patrick E.; Johnson, Douglas E.; Larson, Larry L.; Louhaichi, Mounir; Roland, Tyanne; Williams, John

doi:10.1016/j.rama.2017.06.010

Cited by 8 publications

(6 citation statements)

References 57 publications

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“…When experiencing predation, ungulates may aggregate into larger groups which reduces the probability of being preyed upon (Hebblewhite and Pletscher, 2002; Figure 2). Clark et al (2017) found livestock that grazed mountainous areas and were exposed to wolf presence traveled less each day than cattle that were not exposed to wolves. Livestock fidelity to safe habitats could restrict daily movements and impact livestock diets (Lima and Dill, 1990;Clark et al, 2017).…”

Section: Freedom From Fear and Distressmentioning

confidence: 94%

“…Clark et al (2017) found livestock that grazed mountainous areas and were exposed to wolf presence traveled less each day than cattle that were not exposed to wolves. Livestock fidelity to safe habitats could restrict daily movements and impact livestock diets (Lima and Dill, 1990;Clark et al, 2017). Cows whose calves were preyed upon by wolves were more vigilant and spent less time grazing than cows whose calves were not harmed (Kluever et al, 2008).…”

Section: Freedom From Fear and Distressmentioning

confidence: 94%

“…Congregation of livestock and reduction in daily distances traveled could be used to alert managers to implement strategies to minimize the impacts of predation (e.g., Breck et al, 2011;Breck et al, 2012). Example of the aggregation of ungulates into larger groups (Hebblewhite and Pletscher, 2002) and reduction in grazing sites (Lima and Dill, 1990;Clark et al, 2017) which could be identified by livestock managers via real-time global positioning system (GPS) dashboards. The identification of predator presence could prompt livestock managers to change grazing location or increase anti-predator management to improve the welfare of livestock.…”

Section: Freedom From Fear and Distressmentioning

confidence: 99%

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Opportunities to monitor animal welfare using the five freedoms with precision livestock management on rangelands

et al. 2022

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Advances in technology have led to precision livestock management, a developing research field. Precision livestock management has potential to improve sustainable meat production through continuous, real-time tracking which can help livestock managers remotely monitor and enhance animal welfare in extensive rangeland systems. The combination of global positioning systems (GPS) and accessible data transmission gives livestock managers the ability to locate animals in arduous weather, track animal patterns throughout the grazing season, and improve handling practices. Accelerometers fitted to ear tags or collars have the potential to identify behavioral changes through variation in the intensity of movement that can occur during grazing, the onset of disease, parturition or responses to other environmental and management stressors. The ability to remotely detect disease, parturition, or effects of stress, combined with appropriate algorithms and data analysis, can be used to notify livestock managers and expedite response times to bolster animal welfare and productivity. The “Five Freedoms” were developed to help guide the evaluation and impact of management practices on animal welfare. These freedoms and welfare concerns differ between intensive (i.e., feed lot) and extensive (i.e., rangeland) systems. The provisions of the Five Freedoms can be used as a conceptual framework to demonstrate how precision livestock management can be used to improve the welfare of livestock grazing on extensive rangeland systems.

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Section: Freedom From Fear and Distressmentioning

confidence: 94%

Section: Freedom From Fear and Distressmentioning

confidence: 94%

Section: Freedom From Fear and Distressmentioning

confidence: 99%

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Opportunities to monitor animal welfare using the five freedoms with precision livestock management on rangelands

et al. 2022

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“…These study areas (A, B, C, D) were selected to represent the broad range in environmental and livestock management variability typical of extensive, public-land grazing areas in the northern Rocky Mountains. Study area landscapes generally graded upward from low-elevation, steep-walled canyon lands vegetated by native bunchgrass, to dissected plateaus with pine savanna and open woodlands, topping out on relatively high-elevation mountain slopes vegetated by mixed conifer forest (Clark et al 2017).…”

Section: Methodsmentioning

confidence: 99%

“…Wolf presence was monitored on the study areas using a combination of telemetry tracking (radio and GPS), scat surveys, camera traps, den/rendezvous site surveys, direct observation, and depredation reporting. Presence was generally at moderate levels for all study areas although there was variability among months within years (Clark et al 2017). Wolf resource selection during the rendezvous period (15 June to 15 August; Schullery 2003) was mapped using an existing logistic regression model developed and validated by Ausband et al (2010) throughout central and western Idaho.…”

Section: Methodsmentioning

confidence: 99%

Predicting Spatial Risk of Wolf-Cattle Encounters on Rugged and Extensive Grazing Lands

Clark¹,

Chigbrow²,

Johnson³

et al. 2018

vertebrate_pest_conference

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Cattle grazing lands in the mountainous western United States are rugged, complex, and extensive. Terrain, vegetation, and other landscape features vary greatly across space. Risk of wolf-cattle encounters and potential for depredation loss certainly differ spatially as consequence of this variability. Yet, our understanding of this spatial risk is quite poor and this knowledge gap severely hampers our abilities to manage wolf-livestock interactions and mitigate conflicts. During 2009-2011, a research study was conducted at four study areas (USFS cattle grazing allotments) in western Idaho to evaluate and predict risk of wolf-cattle encounters. Each year, a random sample of 10 lactating beef cows from each study area was instrumented with GPS collars that logged positions at 5-minute intervals throughout the summer grazing season. Cattle resource selection was modeled using these GPS data and negative-binomial regression. An existing model was used to classify habitats within the study areas in terms of probability of use by wolves as rendezvous sites. Efficacy of this model was confirmed using scat, telemetry, and rendezvous site data. Spatial overlaps in the predicted selectivity of wolves and cattle were assessed and study area landscapes were then classified into five encounter-risk classes (very low to very high). Concurrent wolf and cattle GPS tracking data were used to document wolf-cattle encounters and thus evaluate the accuracy of this classification. About 94% of observed wolf-cattle encounters occurred within either the high or highest encounter-risk classes. Areas classified to the highest risk class were located on smooth, relatively flat slopes in concave terrain (e.g., stream terrace meadows) but not all were associated with surface water. Having this predictive understanding of where wolf-cattle encounters are most likely to occur will allow livestock producers and wildlife managers to more effectively apply resources, husbandry practices, and mitigation techniques to reduce conflict.

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