Final report for GW22-230
Project Information
Negative impacts of livestock predation by large carnivores are disproportionately borne by livestock producers (hereafter, ranchers). Carnivore-livestock conflicts threaten economic interests, human safety, and reduce quality of life. Finding effective solutions requires tools that support operational flexibility and contingency in changing environmental, social, and economic climates. Unfortunately, tools aimed at reducing carnivore-livestock conflict are often designed by non-ranchers, lacking the local, experiential, and generational knowledge needed to ensure tools are applicable, versatile, and worth the investment. Range riding - the use of human presence where livestock are grazed to deter carnivores - is a tool providing spatial and temporal adaptability; range riders make decisions in direct response to the behaviors of carnivores and livestock regarding if, when, and how to move livestock, deter carnivores, and monitor the activity of both. Range riding is unique in that it can provide a myriad of operational benefits, both related and unrelated to carnivore conflict such as carcass detection, rotational grazing, and adaptive management. Yet to date, the effectiveness of range riding has not been comprehensively studied. Through partnerships with 600+ livestock producers in the western USA, we are studying the effectiveness of range riding at reducing direct losses (depredation), indirect losses (reproduction, body condition, and illness), and livestock stress to define under which operational, environmental, and economical contexts range riding can be most effective. Using interdisciplinary methods and coproduction processes with our ranching, NGO, and agency partners, we will interpret and disseminate our findings through three rancher-led peer-learning workshops, 2-3 scientific publications, a fact sheet, and at least two types of Extension resources.
Research Goals/Objectives
Improve the profitability and long-term sustainability of ranches operating in areas with large carnivores through evaluating the effectiveness of range riding, an adaptive and versatile rangelands tool.
- Evaluate the effectiveness of different intensities and styles of riding (varied rider behavior) at reducing behavioral and chemical indicators of stress in grazing livestock.
- Through interviews with ranchers, provide the context and detail necessary to understand decision making around range riding as it relates to operational management and protocols, ecosystem resiliency, and economic sustainability.
- Coproduce these findings through incorporating data collected by researchers, ranchers, and landowner groups to create a robust evaluation of range riding.
- Co-interpret and disseminate our coproduced findings on range riding with ranchers and landowner groups, wildlife management agencies, and policy makers.
- Ensure our research methods measure metrics relevant to livestock production, and our products communicate coproduced findings in a way that is relevant to livestock production.
Educational and Outreach Goals
- Through at least 3 rancher-to-rancher knowledge exchanges, expand and integrate effective range riding strategies that support an enhanced quality of life for ranchers, livestock, and wildlife.
- Coproduce a range rider fact sheet with producer partners to be shared broadly at rancher workshops and presentations.
- Provide data on range riding to NRCS that informs the development of conservation practices that incentivize broad adoption of riding by ranchers who need it.
Cooperators
- - Producer
- - Producer
- - Producer
Research
Background: The potential effectiveness of range riding depends, in part, on the goals of the rancher using a rider. Some producers use riders primarily to reduce depredation through human presence, while others focus on monitoring herd health and carnivore activity. Rancher partners participating in the Conflict Reduction Consortium hosted by Western Landowners Alliance were particularly interested in the potential of riding to reduce indirect losses.
As part of our existing Conservation on Workinglands Conservation Innovation Grant that wrapped up this last year, (CoW-CIG) we ran focus groups that met ≥1 time/month with ranchers from across the West to understand what value riding provided to them, how best to measure that value, and what methods would be useful and feasible to measure that value. Funding from that grant allowed us to examine the influence of varied rider strategies on 1) annual depredation rates, 2) historical indirect losses, and 3) chemical indicators of stress in cattle herds. However, our producer partners requested we add to this research list. Specifically, they requested 1) interviews with ranchers to contextualize important ranch-level decision-making related to using a rider and 2) cattle behavioral data (specifically landscape use and foraging behaviors) so the influence of varied rider strategies on behavioral indicators of carnivore-induced stress on cattle can be evaluated. To add these two methods, we are using the funding that the Graduate Student Western SARE provided. These additions will improve rancher profitability through reducing conflict, enhancing stewardship through an improved understanding of how a rider can reduce cattle stress that leads to indirect losses, and improving overall quality of life for ranchers and their communities by helping to empower operational decision-making.
Objectives with hypotheses:
Objective 1: Identify whether varied range riding activity alters chemical and behavioral indicators of stress in cattle;
As rider intensity increases, measured as time spent within proximity of the herd and time riding at dusk, dawn, or at night,
- seasonal cortisol and thyroid levels will improve,
- seasonal herd vigilance will decrease, and
- average time spent in high-quality foraging areas will increase (which may improve physiological markers of stress like cow body condition scores, illness rates and reproductive rates).
To examine the influence of varied rider activity on cattle behavior, we have been, and will continue to collect several data streams. These include data on rider activity, habitat features and forage quality/quantity, carnivore spatial use, and cattle behavioral activity. All operations have active wolf populations, and some have active grizzly bear populations.
Range Rider Data
In grazing seasons 2022, 2023, and 2024, participating range riders completed rider data sheets. We encouraged daily data collection but to accommodate time constraints of range riders, we also allowed for weekly data collection (Nickerson_Daily_Rider, Nickerson_Weekly_Rider). Several riders in Washington and Montana also recorded their riding tracks in a GPS unit. Range riders were trained each spring on data collection for both GPS units and data sheets that were provided at the start of the season. Range Rider GPS tracks will be used to compare rider landscape use and proximity to cattle location data (recorded by the rider) and carnivore location data when available. Rider data sheets provide data on 1) rider intensity (frequency and duration of rides, and how often a rider uses management in the field while riding such as moving cattle, fixing fence, etc.), 2) time within proximity versus away from the herd (and activity when away), 3) time of day or night riding, and 4) observations while monitoring the herd and of carnivore activity. Combined, these data comprehensively define rider intensity, use of the landscape, timing, and monitoring.
Environmental Data
Environmental data will be collected this spring through our producer partners and existing open-sourced data such as ArcGIS Pro, MODIS, Western Regional Climate Centers, and through data-sharing agreements with wildlife agencies (75% of which are near-completed or completed). Examples of needed data include seasonal drought conditions, forage quality and quantity, water sources, whether herds are receiving supplemental feed, and alternative native prey densities captured through game camera photos. These variables of interest and covariates will be used to isolate the influence of varied range rider behavior on herd behavioral stress from other potential stressors like heat, cold, illness, and distance to water.
Predator Data
Data on carnivore locations were collected using three methods: 1) range rider observations recorded via rider data sheets (see attachments), 2) data provided by wildlife agencies through data sharing agreements, and 3) game camera grids deployed on grazing allotments/pastures. On each operation, we deployed 30 cameras in two-three grids of 10-15 cameras. Grid locations were selected based on areas of high use by cattle and were moved over the course of the season to match the timing of when cattle were moved to new grazing areas. Together, all three methods will provide a more robust understanding of carnivore presence than each could provide alone.
Cattle Behavioral Data
To explore the influence of predator induced physiological, chemical, and behavioral stress on livestock, we measured the following metrics: 1) cortisol and thyroid levels, 2) reproductive rates, 3) abortion rates, 4) illness rates, 5) body condition scores, 6) cattle vigilance, and 7) cattle landscape use behavior. Funding from the Student SARE was used to look at vigilance and landscape behavior use specifically across four herds during the 2023 and 2024 grazing seasons with added VHF collars and/or ear tags deployed on cattle, and compare these metrics to the previously mentioned physiological and chemical metrics for a more robust evaluation. Vigilance is the amount of time cattle spend moving or on the lookout for predators rather than eating, ruminating, or resting, all of which contribute to weight gain, reproductive success, and reduced illness. We collected cattle vigilance data from camera trap photos of cattle captured via our existing camera trap grids (10-15 cameras per grid), and via range rider observations recorded on rider data sheets. Cattle photos from all three seasons are currently being coded, categorized as either vigilant (head up above shoulders and not chewing, running) or not vigilant (head down at or below shoulders feeding, head up above shoulders chewing, walking, or lying down/resting/ ruminating). Because cattle are often in groups, we count the total number of individuals in each photograph and the proportion of cows, our cattle of interest, that are vigilant/not vigilant. Range rider data sheets from both seasons are also being thematically analyzed for cattle behavior and given a similar scoring of vigilant or not vigilant. Thus, at the end of each season, each cattle herd will have 31 date-specific vigilance scores – a scoring for each game camera deployed, and a scoring from each recorded rider data sheet. Scores will then be averaged to a daily vigilance score.
To collect data on landscape use by livestock in 2023 and 2024, we deployed VHF collars and ear tags on four operations. VHF collars allowed range riders to more easily locate and record cattle locations on rider data sheets, which not only improved cattle location data, but also allowed for a comparison between range riders with, and without VHF assistance. We prioritized collaring lead cows on all operations, with a minimum of 20% of each herd receiving a collar or ear tag. Cattle were collared at the start of the season with help from ranchers, range riders, and other employees. Cattle location data will be used this spring to evaluate the quality and quantity of forage available in areas where herds are spending most of their time. Furthermore, this information will be compared to the varied behavior of range riders and carnivores to understand if riders reduce carnivore-induced stress in cattle, therefore improving foraging behavior that leads to improved cow and calf health.
To map high-priority grazing areas at each operation, this spring we will use ArcGIS Pro and MODIS to map out areas of high forage quality (NDVI), forage quantity (NPP), and acceptable distance to water over all utilized allotments and pastures. We will then bring these maps to our producer and range rider partners for confirmation and adjustment if needed. Where possible, priority areas will reflect seasonal changes in green-up based on the dates that livestock were present.
By modeling both herd vigilance and herd landscape use/foraging behavior as a function of varied range rider activity and varied carnivore activity, these data will allow us to answer the following research questions:
- Does varied range rider activity influence the proximity of carnivores to cattle?
- Does varied range rider activity influence vigilance in cattle?
- Does varied range rider activity influence the quality of foraging areas used by cattle?
Cattle Chemical and Physiological Data:
On seven ranches our first season (2022) and on 13 in 2023 and 2024, we collected hair samples from cow tails for cortisol and thyroid function analyses. We sampled at least 20% of the herd in both the spring and fall efforts (see below for total sample numbers). A sub-sample of hair samples from the 2022 and 2023 seasons have been analyzed by the Smithsonian, (see Results and Discussion) but the remaining samples will not be analyzed by the Smithsonian until spring 2025. At the suggestions of the Smithsonian to improve the robustness of our findings, we also tested 10% of each herd for thyroid function to compare to cortisol levels and physiological cattle data.
Herd physiological data (body scores, reproductive rates, abortion rates, and illness rates) were either collected from producers during tail hair sampling (if present) or will be collected by Ph.D. student Rae Nickerson this spring.
By incorporating cattle behavioral analysis into our range riding methods, the potential influence of a range rider on indirect losses can be more accurately determined, since it is likely that behavioral stress responses to predation risk have a larger influence on reproduction and illness than chemical responses to stress alone. The analysis of behavioral, physiological, and chemical responses are needed to accurately model herd stress, and the methods outlined above will allow us to measure whether range riders can improve cattle foraging time, resting time, and the quality of forage used by a herd.
Objective 2: As mentioned above, conflict reduction tools are often created and evaluated without the direct involvement of ranchers. This can result in tools being researched at inappropriate temporal or spatial scales, or tested within a limited scope that does not account for the diverse, complex, and sometimes limiting relationships between an operation’s social, ecological, and economic dynamics. In turn, this can result in tools or solutions that are not feasible to deploy or maintain, are cost prohibitive, or simply ineffective in certain contexts. The coproduction of our research questions and methods have ensured that our temporal and spatial scales are sufficiently diverse, but capturing qualitative data was critical to ensuring our findings are representative of diverse producer needs and circumstances.
To capture this complexity, we conducted unstructured interviews (Interview Questions CIG) with the majority of our 30+ rancher and range rider partners operating in Washington, Montana, Wyoming, Oregon, California, New Mexico, and Arizona - including all ranchers from the existing CoW-CIG, and the three additional ranchers involved in the research outlined above for Objective 1. (see Results and Discussion). All operations have active wolf populations, and operations in Washington and Montana also have active grizzly bear populations. Interview questions asked ranchers to reflect on range riding as a tool, to describe their range riding-related husbandry practices and operational protocols, identify production limitations that may influence the effectiveness of a range rider, and describe anticipated challenges to accurately analyzing range riding’s potential. Ranchers were encouraged to lead conversations in whatever direction they would like, and interviews were recorded. Because of a stop-work order from Montana State University based on their interpretation of federal orders on our remaining grant, we are currently seeking funding for two part time technicians to help Ph.D. student Rae Nickerson transcribe and code interviews this spring using inductive thematic analysis (Marshall & Rossman, 1998; Braun & Clarke, 2006). Inductive thematic analysis is a qualitative data analysis technique where themes are derived from the data themselves as opposed to being predetermined, then categorized after data collection (Braun & Clarke, 2006). We will categorize and code distinct responses until saturation of categories is met, and response frequencies achieved. Interview findings will be crucial to capturing the diverse and complex relationships driving rancher decision-making on the operation and provide the needed descriptions for the development of future technical and financial support programs like those provided by NRCS.
Objective 3. During the 2023 and 2024 grazing seasons, Rae Nickerson and her technicians continued to meet regularly with producer and rider partners to co-collect data and maintain relationships. Fieldwork started in January and ended in November, and Rae’s team spent most of that time living and working with producers and range riders in the field.
Objective 4. We continue to meet regularly with our producer and rider partners, although less formally (often on the phone), to ensure that our coproduced findings are being co-interpreted.
Objective 5. Our team maintained regular communication with our rider and producer partners during the 2023 and 2024 seasons to ensure our research methods measured metrics relevant to livestock production, and our products communicate coproduced findings in a way that is relevant to livestock production (see Products for our Range Rider Toolkit coproduced with our partners at Western Landowners Alliance).
Citations:
- Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
- Marshall, C., & Rossman, G. B. (1998). Designing qualitative research. Sage Publications.
Our research objectives were to:
- Evaluate the effectiveness of different intensities and styles of riding at reducing behavioral and chemical indicators of stress in grazing livestock.
- Through interviews with ranchers, provide the context and detail necessary to understand decision making around range riding as it relates to operational management and protocols, ecosystem resiliency, and economic sustainability.
- Coproduce these findings through incorporating data collected by researchers, ranchers, and landowner groups to create a robust evaluation of range riding.
- Co-interpret and disseminate our coproduced findings on range riding with ranchers and landowner groups, wildlife management agencies, and policy makers.
- Ensure our research methods measure metrics relevant to livestock production, and our products communicate coproduced findings in a way that is relevant to livestock production.
Objective 1: In 2022 we collected data from 210 game cameras across seven ranches, and 390 cameras on 13 different ranches in 2023 and 2024. Spring and fall cattle hair samples from 2022 (n = 256) and 2023 (1723) were analyzed by the Smithsonian winter 2024, and the remaining 2024 season samples (n = about 1500 – 2000, some still to be collected from producers) will be analyzed this spring when the Smithsonian hires a spring technician. Once we receive the results, chemical analysis and comparison to behavioral and physiological markers of stress in cattle will be completed by Rae Nickerson by summer 2026 (see Research Outcomes for a preliminary analysis).
While attempting to code our game camera photos after our first season, we realized quickly that we did not have the resources (both financial and human power) to code our images by hand. Coding would have taken us over 11,000 hours of work. To remediate this situation, we reached out to researchers at the University of Michigan working on a new AI software built to code lab videos for animal behavior called LabGym (Hu et al., 2023). Collaboratively, we have been adjusting this software to also work for photos and we hope to write a methods paper together over the next few years. The software edits and updates for our purposes were completed this winter when Rae was home from the field, and now we are coding our photos to train the software in species and behavioral recognition before running LabGym which should take about a month. We hope to have all photos coded and categorized by LabGym by May 2025, and vigilance analysis completed by summer 2026.
In (2023) we collected cattle location data by deploying 219 collars/ear tags across four ranches. We had a collar/tag failure rate of about 30% by the time units were removed in October and November of 2023. However, we found from communication with range riders that finding cows with at least 20% herd coverage was more than sufficient (continuously hearing 3-6 cows at once). For that reason, we only collared 10% of each herd in 2024 to simplify our process and stay within the number of remaining functional units. We deployed about 150 VHF collars/tags on three of the same ranches last year, adding a new producer in Washington state. We did not place collars on cattle in Oregon last year. Collars and tags were removed during the October and November months with a similar failure rate of about 40%. About 20% of remaining rider data sheets (with cattle VHF location information data) are still being mailed to us by producers and range riders.
We will co-create forage quality/quantity maps with producers this spring before the 2026 grazing season. Trying to sit producers down to look at maps during the grazing season last season was too challenging, and folks were unavailable over the holidays. With these maps, we will be able to look at whether carnivore and rider activity altered the quality of foraging areas used by cattle. We hope to have all mapping and forage quality analysis done by summer 2026.
Exploratory analyses on cattle hair samples:
To study how (1) predator activity and (2) rider activity influence chemical indicators of stress in livestock, we trimmed the tails of at least 30% of each participating herd – once in the spring immediately before livestock were turned-out onto grazing allotments, and once in the fall right after the herd returned from allotment at the end of the grazing season. Our spring season samples represent a “baseline” measure of herd stress, and we only analyzed one spring sample per herd although we trimmed each spring to clear new growth before the grazing season started. Alternatively, our fall season samples only represent grazing season-specific stress. Therefore, each herd has one baseline spring sample, and a fall/grazing season sample for each grazing season they participated in the study.
We conducted a preliminary analysis on cow hair samples collected during the 2023 season (spring and fall) from three ranches: ranch O (n = 162), A (n = 27), and I (n = 33). We examined ranches that were geographically and operationally similar because we expect several environmental and operational covariates to also influence stress markers in cattle (Heimbürge et al., 2019; Moya et al., 2013, Bristow & Holmes, 2007). We wanted to test whether there was a significant statistical difference between cortisol and thyroid levels across (1) spring and fall samples, and (2) ranches. Using a two-way ANOVA, we found a significant effect of ranch on cortisol levels (p < 0.001), and of season on cortisol levels dependent on ranch (p = 0.02), but there was no significant effect of season on cortisol levels (p = 0.94). Calculating for effect size, we found that ranch explained approximately 20% of the variance on cortisol concentration, compared to less than 1% variance explained by season.
We then ran a Tukey’s Honest Significant Difference test for ranch, season, and the interaction of ranch and season. We found that there was no significant difference between ranch I and ranch A, (p = 0.27), a significant difference between ranch O and ranch A (p < 0.001) with ranch O having higher cortisol concentrations, and a significant difference between ranch O and ranch I (p < 0.001) with ranch O again having higher concentrations. Season remained non-significant (p = 0.95). Looking at the interaction between ranch and season, we found that ranch O consistently has higher cortisol concentrations than ranch I in both autumn and spring (p < 0.001 for both seasons), and higher concentrations than ranch A only in autumn (p < 0.001).
We then ran a Kruskal-Wallis to test for the significance of ranch and season on our thyroid data. We found that season did not have a significant effect (p = 0.34, chi-squared = 6.06) but ranch had a significant effect (p = 0.05, chi-squared = 0.90). We then ran a Dunn test and found that thyroid levels were significantly different between ranch A and ranch I (p = 0.02), and ranch O and ranch I (p = 0.02), but not between ranch O and ranch A (p = 0.43).
To compare differences in cortisol concentrations across seasons for each ranch, we ran paired t-tests. On ranch O, there was no significant difference for cortisol levels between seasons (p = 0.23, t-statistic = -1.22) with a mean difference of -0.04ng/ml between spring and fall. On ranch A, the seasonal difference was significant (p < 0.01, t-statistic = 3.65) with a mean difference of 0.25ng/ml between spring and fall. On ranch I, there was no significant difference (p = 0.95, test-statistic = 0.07) with a mean difference of 0.00 between spring and fall.
Next, we ran the Wilcoxon tests for seasonality differences in thyroid levels for each ranch where “V” represents the magnitude of change in thyroid levels between spring and fall, but p-values represent whether that magnitude is significant regardless of the size of V. We found that ranch O had a significant difference in thyroid levels across seasons (p < 0.001, V = 13), as did ranch A (p < 0.001, V = 102). Ranch I did not have a significant difference (p = 0.78, V = 70).
Discussion:
The results of our preliminary analysis showed a significant effect of ranch on cortisol and thyroid levels, but a non-significant effect of season on either. Ranch O had significantly higher cortisol levels than ranch I in spring and autumn, and ranch A only in autumn. The only significant difference in cortisol concentrations between spring and autumn was on ranch A, with a mean difference of 0.25ng/ml. Thyroid levels were significantly lower on ranch I compared to ranches A and O, and ranches O and A had significantly different thyroid levels between seasons, but not ranch I.
It's important to note that these preliminary results have yet to be analyzed with the many covariates that also influence cortisol and thyroid levels. “Ranch” and “Season” contain many potential individual drivers of chemical stress markers such as forage quality/quantity, predator activity, allotment size, supplementary feeding protocols, and more. The following discussion is purely exploratory, and our future analyses will incorporate all landscape, operational, and other covariates necessary to tease out the impact of predator and rider activity.
We did not expect to see a significant difference in cortisol and thyroid levels between seasons since grazing season growth from past years (including the cortisol and thyroid concentrations from those grazing seasons) would be included in the hair of our spring baseline samples. We did expect to see differences across ranches since, as mentioned above, several landscape and operational factors can influence cortisol and thyroid levels, including our predator and rider activity variables of interest.
We did not expect cortisol concentrations to be highest on the O ranch. Although strictly speculation at this point, ranch O has historically had fewer wolf conflicts than ranches A and I, so we expected to see lower concentrations. It is possible that because ranch O operates on allotments significantly larger than ranches A and I, cattle may need to travel farther distances for quality forage and water, and cortisol concentrations also increase from increased activity via the hypothalamic-pituitary-adrenal (HPA) axis, although more analysis is needed (Gerlach, 2015). It is also possible that cattle, like other mammals, adapt to constant and acute stressors, muting their cortisol response (Caceres et al., 2023; Chen et al., 2015). This may have resulted in lower cortisol concentrations on ranch A and I with historically more wolf conflicts. Whereas rare interactions may spike stress, and caused the higher levels observed at ranch O. This is why comparing our chemical data to our behavioral (vigilance) and physiological data (body scores and reproductive rates) will be crucial, as behavioral and physiological indicators of stress would still be high on ranches with predator pressure despite an adapted, muted cortisol response (Gy et al., 2002; Pryce et al., 2001).
The one ranch with higher cortisol concentrations in the spring compared to the fall was ranch A. Ranch A has constant wolf pressure year-round compared to ranches O and I where animals only experience predation pressure during the fall/grazing season. Since the baseline sample for ranch A includes cortisol levels from year-round predator pressure, this may explain why spring cortisol concentrations were higher than fall alone.
Thyroid levels are primarily an indicator of whether sufficient nutrition is available (Gy et al., 20022), and although one might expect nutrition to improve during the grazing season, all three of these herds receive supplementary feeding and mineral during the non-grazing season. Thyroid levels were lowest on ranch I which has historically had a significant amount of wolf conflict. Since both thyroid levels and cortisol concentrations were low, it’s possible that cows from ranch I are experiencing the muted cortisol response caused by acute and constant predator-induced stress, while still showing increased vigilance (to be examined), and decreased thyroid levels.
Both ranches O and A had significant seasonal differences in thyroid levels, where ranch A had higher levels in the spring, and ranch O had higher levels in the fall. We will need to explore operational and landscape covariates like supplementary feeding and mineral protocols and forage availability to better understand these results.
Objective 2: Due to the full-time nature of our fieldwork and our commitments to our peer-to-peer range rider workshops (see Education and Outreach Results), we are behind where we would like to be on our interview analysis. Although all 25 interviews with our willing/available producer are rider partners were completed last season, our workload increased significantly after we took on seven additional producers to our study during the summer of 2023. We were able to secure additional funding for technician wages and travel, but all funds ended up being needed for technician field work. Additionally, a stop-work order from Montana State University based on their interpretation of federal orders on our remaining grant has resulted in funds we planned on having no longer being available. Thus, we are currently seeking funding for two part time technicians to help Ph.D. student Rae Nickerson transcribe and code a large number of interviews this spring using inductive thematic analysis. If awarded requested funding, we hope to get technicians hired no later than April and transcription and analysis complete by June 2026. Rae will then write up the results by early fall 2026.
Objectives 3, 4, and 5:
Rae is still waiting on some 2024 data from producers (rider data sheets, cow tail hair samples, allotment boundaries, and seasonal final numbers). Rae will continue to collect these data via phone calls, emails, and mail this spring, aiming to finish analysis by this summer, and at least one academic publication and one Extension Guide by fall/winter 2026. Rae Nickerson will also use these communications over the phone and Zoom this spring and summer to wrap up analysis, coproduce results, and disseminate findings with the agricultural community, landowner groups, wildlife management agencies, researchers, and policy makers (see Education and Outreach for details on range rider workshops).
Citations:
- Bristow, D. J., & Holmes, D. S. (2007). Cortisol levels and anxiety-related behaviors in cattle. Physiology & Behavior, 90(4), 626–628. https://doi.org/10.1016/j.physbeh.2006.12.009
- Caceres, S., Moreno, J., Crespo, B., Silvan, G., & Illera, J. C. (2023). Physiological stress responses in cattle used in the Spanish rodeo. Animals, 13(16), 2654. https://doi.org/10.3390/ani13162654
- Chen, Y., Arsenault, R., Napper, S., & Griebel, P. (2015). Models and methods to investigate acute stress responses in cattle. Animals, 5(4), 1268–1295. https://doi.org/10.3390/ani5040402
- Gerlach, B. M. (2014). The effects of exercise on beef cattle health, performance, and carcass quality; and the effects of extended aging, blade tenderization, and degree of doneness on beef aroma volatile formation (Doctoral dissertation, Kansas State University). K-REx. https://krex.k-state.edu/handle/2097/17229
- Gy, H., Kulcsár, M., & Rudas, P. (2002). Clinical endocrinology of thyroid gland function in ruminants. Veterinární Medicína, 47(7), 199–210.
- Heimbürge, S., Kanitz, E., & Otten, W. (2019). The use of hair cortisol for the assessment of stress in animals. General and Comparative Endocrinology, 270, 10–17. https://doi.org/10.1016/j.ygcen.2018.09.016
- Hu, Y., Ferrario, C. R., Maitland, A. D., Ionides, R. B., Ghimire, A., Watson, B., ... & Ye, B. (2023). LabGym: Quantification of user-defined animal behaviors using learning-based holistic assessment. Cell Reports Methods, 3(3), 100461. https://doi.org/10.1016/j.crmeth.2023.100461
- Moya, D., Schwartzkopf-Genswein, K. S., & Veira, D. M. (2013). Standardization of a noninvasive methodology to measure cortisol in hair of beef cattle. Livestock Science, 158(1–3), 138–144. https://doi.org/10.1016/j.livsci.2013.10.007
- Gillund, P., Reksen, O., Gröhn, Y. T., & Karlberg, K. (2001). Body condition related to ketosis and reproductive performance in Norwegian dairy cows. Journal of Dairy Science, 84(6), 1390–1396. https://doi.org/10.3168/jds.S0022-0302(01)70170-1
- Pryce, J. E., Coffey, M. P., & Simm, G. (2001). The relationship between body condition score and reproductive performance. Journal of Dairy Science, 84(6), 1508–1515. https://doi.org/10.3168/jds.S0022-0302(01)70184-1
Research Outcomes
Objective 1: Recommendations for sustainable agriculture production and future research from our objective 1 findings will be available as soon as we finish coding and analyzing our data. Our exploratory cortisol concentration and thyroid levels analysis of ranches O, A, and I did not incorporate sufficient covariates to feel confident making recommendations or conclusions (see updated timeline for details).
Objective 2: Although interview analysis is not complete, we are seeing trends. Common themes from interviews with range riders and ranchers across the west include: 1) Being unable to afford a range rider if the costs were not somehow subsidized as they are for many producers by an agency (e.g., Washington State Department of Agriculture grant or Defenders of Wildlife), 2) being unsure if range riders are actually reducing conflict, but wanting to use a range rider for the additional benefits a range rider provides (communication across ranches, faster depredation detection, or catching other on-range issues like injury or illness), 3) that an effective range rider needs to have cattle experience, not just wildlife experience, and 4) that they have noticed reductions in both calf weights and cow reproduction since carnivore populations increased locally. When analysis is complete, we will be able to share these perceptions to help riders and range rider programs be more effective across varied operational, environmental, and economic contexts.
At our two peer-to-peer range rider workshops, the experiential knowledge of producers and riders were collected during panel discussions, breakout groups, and inter-stakeholder group discussion. Although yet to be analyzed, preliminary findings were meaningful. Regarding what skills/traits are needed by a rider to be effective, producers stated that riders need to (1) have a great work ethic and flexible schedule, (2) be trusted by the local community, (3) listen well, be curious to learn and keen to observe, (4) know the specific terrain and livestock herd (with recognition that this takes on average 1-2 full years), (5) have livestock skills and prioritize stockmanship, not just wildlife skills, (6) have excellent wildlife track and sign skills, (7) want to come back year after year, and the most requested skill/trait (8) good communication skills and the ability to maintain and build trust with a diverse set of stakeholders.
Common concerns included (1) how do we keep range rider programs funded so that good riders want to come back each year, (2) how do we familiarize riders with more than one allotment so they can cover for one another more effectively, but not in a way that prevents each rider from learning their herd and allotment, (3) how do we better deploy riders by knowing where conflict is/will be concentrated, (4) whether producers should be allowed to ride their own herds as part of a funded range rider program, (5) how do we provide work for riders off season, and (6) how do we find riders with the diverse skillset required to be effective?
Collectively, participants at each workshop defined good range riding and range rider programming as (1) happy livestock, (2) good pregnancy rates, (3) healthy and sustainable range forage, (4) riders who know their allotment and their herd so well that they can recognize problems quickly, (5) shared wolf/predator location information, (6) improved relationships, and (7) improved carcass detection rates. Aspects that participants believed would improve riding’s effectiveness included (1) access to thermal, (2) access to wolf collar data and/or VHF telemetry (mixed – some participants see access to wolf collar data as a distraction and not that useful), and (3) better property access (especially for agency riders). Both workshops agreed that how a rider should spend their time and what an “effective rider” looks like will always be context specific to each ranch/allotment, regardless of how we try to cookie-cutter define what a “range rider” is. Flexibility is key.
When asked what metrics should be used to distribute range riders across a landscape with many producers requesting riders and only so many riders (think NRCS ranking protocols/questions), participants collectively agreed that (1) history of conflict, (2) current conflict, (3) known wolf presence, and (4) rancher acceptance/willingness should be considered (not in order of importance). How many riders were needed to effectively cover what number of head/acres was a lingering question.
Participants agreed that some kind of range rider accreditation or training program was needed at a west-wide scale. This presented a challenge in both groups, as ranchers expressed concern about being passed more responsibility/burden related to carnivore conflict to “train” riders that will not be riding their allotments, while also recognizing that the best training would have to happen on allotment with the producer due to the context-dependent nature of range riding. A combination of off-site initial training through a training program followed by on-ranch training with the producer, ranch employee, or other riders was suggested. Partnering with universities, particularly Extension, was mentioned as a possible way forward for the initial accreditation/training program.
Objective 3, 4, and 5: Although still wrapping up data collection and analyses, we believe our findings will be drastically improved by having producer and rider partners coproducing research with us every step of the way of this project. We have created ample opportunities for co-interpretation and the dissemination of our preliminary findings and will continue to prioritize such moving forward (see Education and Outreach for details on, and survey responses from our Range Rider Toolkit, webinars, workshops, and trainings).
In late 2023, our collective efforts resulted in 22 million dollars becoming available through NRCS for range riding efforts in Oregon, New Mexico, Colorado, Montana, and Arizona. Our broader CoW-CIG team has been working to make information available to landowners on how to qualify and apply for these funds (see Education and Outreach for more on our peer-to-peer range rider workshops).
Education and Outreach
Participation Summary:
Our education and outreach goals were as follows:
- Through at least 3 rancher-to-rancher knowledge exchanges, expand and integrate effective range riding strategies that support an enhanced quality of life for ranchers, livestock, and wildlife.
- Coproduce a range rider fact sheet with producer partners to be shared broadly at rancher workshops and presentations.
- Provide data on range riding to NRCS that informs the development of conservation practices that incentivize broad adoption of riding by ranchers who need it.
Ph.D. student Rae Nickerson held meetings with ranchers and riders in Trego, Missoula, and Valier, Montana, and Colville, Washington, between April and December 2022 to discuss research goals and project participation, and to hear from attendees on what they feel is most important for successful range riding programs (education and outreach goal 1). Rae also presented on the research goals at a conference for Cyber Tracker International in spring 2023, where she discussed how track and sign skills can be used by range riders and agency depredation investigators to improve their accuracy and standardize their process. Her presentation was one of the most attended by the 300 attendees.
In the early fall of 2023, Rae met with agency partners from Oregon, Washington, Montana, Idaho, California, Wyoming, and Colorado at the Western States Wolf Rendezvous in Missoula to update state wildlife agency partners on the project and provide preliminary findings from the interviews for wolf managers across the West (education and outreach goal 3).
At the end of 2023, Rae and partners at Western Landowners Alliance finalized a draft version of the Range Rider Toolkit after over a year of coproduction with producer and rider partners (education and outreach goals 2 and 3). In 2024, we hosted a webinar to present and get feedback from the broader producer and range rider community on the Toolkit (see video here: https://www.youtube.com/watch?v=ebPnYapfEAg&t=3471s).
In February 2024, our core CoW-CIG team met with project partners in Missoula to host a two-day in-person and online meeting on our project progress (education and outreach goals 1 and 2). Over 55 agency, NGO, rancher, and range rider partners attended both in person and over Zoom to provide feedback on our coproduction process, our Range Rider Toolkit (fact sheet) and continue building relationships and trust among various stakeholders. This meeting also helped inform the scope of work for the new funds awarded to Western Landowners Alliance and Heart of the Rockies (part of the 22 million awarded through the RCPP).
In summer 2024, Rae met with producer and range rider stakeholders in Northeast Washington State to learn more about their experience with the two major range riding NGOs (Northeast Washington Wolf Cattle Collective and Cattle Producers of Washington - education and outreach goal 1). Rae shared early findings from her research and invited members of both groups to attend the upcoming range rider workshops. Rae also assisted with an evaluation requested by Washington State University of the two NGO rider groups that provided additional travel funds for this research project (see Products section for final report).
Two workshops were held by partner organization Western Landowners Alliance in Arizona/New Mexico (66 participants) and Montana (105 participants) in the summer of 2024 focused on range riding and other nonlethal tools to reduce predator conflicts (education and outreach goal 1). In early 2024, we surveyed rancher and range rider partners to ask what type of workshop they were most interested in for the Student SARE funds. They requested track and sign skills to improve their ability to accurately determine carnivore species and behavior in the field, information on new technology, an opportunity to hear from producers and riders in other states, and an opportunity to discuss challenges and setbacks with local government agency staff.
In partnership with Western Landowners Alliance, Ph.D. student Rae Nickerson organized and facilitated two peer-to-peer workshops in La Grande, Oregon and Eager, Arizona during autumn 2024 (education and outreach goal 1). These workshops had around 100 attendees each. Rae brought a team of producer and rider panelists from her research to each workshop. Day one of these workshops included presentations and discussion on important range rider related content including a presentation from NRCS staff on how the new RCPP funds will be available and distributed. Day two was a wildlife track and sign certification opportunity offered to producers and range riders for free in partnership with Cyber Tracker North America. SARE surveys were collected by Western Landowners Alliance at both workshops. Our Range Rider Toolkit was shared broadly at all workshops (education and outreach goal 2).
Rae has continued participation in the Conflict Reduction Consortium (CRC) hosted by Western Landowners Alliance (WLA) – a group of landowners, practitioners, wildlife agency, researchers, and NGO folks committed to finding policy solutions and tools to reduce wildlife related conflicts. The CRC meets for two hours once a month and has committed to working through wolf-grizzly bear livestock conflict issues for the last few years as part of WLA’s participation in the CoW-CIG. In 2023 and 2024, 30-40 total participants including livestock producers met monthly to discuss carnivore livestock conflict related concerns and policy (education and outreach goals 1, 2, and 3).
In January 2025, Rae provided a training for range riders in Colorado hosted by Colorado Parks and Wildlife and Colorado Department of Agriculture. Over 100 producers and range riders attended, and a second, four-day training will be offered in April 2025. The Range Rider Toolkit was shared broadly (not funded by the Student SARE but related to education and outreach goals 1, 2, and 3).
This May, Rae Nickerson will organize and host two additional and free wildlife track and sign certification opportunities for riders and producers in northeast Washington. We expect around 30 participants total and will pass out SARE surveys at the end of each certification (funds provided by another grant – education and outreach goals 1 and 3).
SARE surveys were collected at both of our peer-to-peer range rider workshops in La Grande, Oregon and Eager, Arizona last fall. Out of n=53 total survey respondents, 100% agreed that the event improved their awareness of the topics covered. Ninety-six percent agreed that the event provided new knowledge and was current, up to date, and relevant, and 70% that the event provided new skills. Seventy-two percent of those surveyed believed that the event modified their opinions and attitudes.
Seventy-two percent of respondents strongly agreed that the instructors presented information that would help them, and between 80 and 94% of respondents strongly agreed that the instructors stimulated them to learn, related program content to real-life situations, stimulated them to think about how to use the information presented, allowed for questions and interaction with participants, demonstrated enthusiasm, answered questions clearly, and showed respect for all persons attending the program.
Overall, the events received an 81% excellent rating with a 19% good rating. Respondents together reported that they will share what they learned from the workshops with at least 852 new people. Some of the reported “best” things about the sessions included (1) getting to know the different organizations and stakeholders in person, especially hearing their diverse experience, knowledge, and ideas, (2) the culture of respect, honesty, and team work maintained at the workshop through hard conversations and different perspectives/points of view, (3) having all agencies present with a stake in the game, (4) community development, (5) the panel discussions and break-out discussions, (6) provided hope and optimism that there can be effective solutions to the current conflict, (7) learning about new NRCS and other funding options for range riding and conflict, (8) networking with fellow producers and/or range riders, and (9) the collaboration and relationship building.
Constructive feedback for future events included (1) choosing a less busy time of year for producers, (2) to include more information on when range riding doesn’t work (under what contexts), and (3) to provide more workshops like these that are longer with more time for panel discussion, mingling, and questions.
Of the producers and landowners who took the survey (n=29), 76% said they were likely to adopt one or more of the practices mentioned, 56% said doing so would improve their operations diversification of strategies, 30% reported that using the practice would reduce the need for off farm purchasing (less relevant to range riding), 79% reported some aspect of the range riding would increase networking with other producers, and 63% reported that range riding would add value into their overall operation.
Of the professionals and practitioners who took our survey (n=40), 80% reported that they would use some aspect of the training educationally or as a participant in the future, 86% said they would participate in making range riding an available resource, 74% reported they would use some aspect of the workshop as a professional development tool for their peers, and 95% reported that they would use some aspect of the workshop to improve the advice/counsel they provide to producers. When asked to describe how they are likely to use some aspect of these workshops for an educational purpose, the professional and practitioner responses included (1) at their job with the USFS, (2) with their peers and encourage participation at future events by other producers, (3) letting people know specifically about what resources are available for conflict mitigation, and (4) helping to educate non-ranchers on the intricacies of wolf-livestock conflict.