Pumas, culpeo foxes, bad and good dogs. Assessing strategies to mitigate predation

Pumas, culpeo foxes, bad and good dogs. 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Assessing strategies to mitigate predation Pablo G. Gáspero, Gerardo De la Vega, Joshua P. Taylor, Valeria Fernández-Arhex, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7234506/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Predation is a key ecological process but reconciling it with the socio-economic role of livestock in rural regions remains a challenge. Human-dominated landscapes exhibit profound disruptions in the functionality of ecological processes, influencing performances of predation mitigation measures. The aim of this study was to investigate sheep mortality patterns under extensive management conditions in Patagonia, to determine the impact of pumas ( Puma concolor ) and culpeo foxes ( Lycalopex culpaeus ) and assess the influence of socio-environmental and management factors (state-subsidized lethal control and Livestock Guarding Dogs -LGD-) on the probability of sheep deaths. We monitored sheep mortality across six commercial ranches (covering 1,500 km² and 61,000 sheep), and socio-environmental and management covariates. We used hierarchical Bayesian models to evaluate covariates operating on sheep deaths occurrence probability. We performed 139 necropsies, where pumas, culpeo foxes, and domestic dogs ( Canis lupus familiaris ) were responsible for 25.9%, 22.3%, and 21.6% of recorded deaths, respectively. Statistical analyses revealed that (i) LGD significantly reduced the probability of puma predation on sheep, and (ii) the likelihood of sheep predation by culpeo foxes was directly influenced by fox relative abundance and inversely by prey biomass availability. We recommend moving beyond reductionist policies, allocating resources to promote responsible LGD implementation. Biological sciences/Ecology Earth and environmental sciences/Ecology Biological sciences/Zoology Landscapes of coexistence Human-Carnivore conflicts Livestock Guarding Dogs Lethal Control Human-dominated landscapes Human-induced trophic cascades Fear ecology Figures Figure 1 Figure 2 Figure 3 Introduction Managing predation in livestock landscapes is an environmental and socio-economic challenge 1 , 2 . Historically, lethal control has been one of the main strategies implemented globally to mitigate real or perceived livestock losses. However, retaliatory killing, together with other disturbances, configure worldwide extended human-induced trophic cascades. It has disrupted intraguild interactions among carnivores, ultimately affecting the provision of predation-related ecosystem services 3 – 5 . Worldwide large carnivores population viability depends on the consolidation of coexistence landscapes outside protected areas 1 , 6 . The performance of predation mitigation strategies is conditioned by the socio-environmental context in which they are applied 7 . Stakeholders and policymakers worldwide tend to oversimplify livestock-carnivore interactions 8 , leading to linear governance models in predation management 9 – 11 . In many regions, policies that promote lethal control continue to be implemented 9 , 12 , 13 , with inconsistent impacts on livestock losses 14 , 15 . By contrast, well-implemented non-lethal predation mitigation strategies have demonstrated success in different socio-environmental contexts 14 , 16 . However, in the Global South, and particularly in South America, empirical studies that confirm direct attacks and monitor socio-environmental covariables remain scarce 7 , 17 . Given the context dependence of mitigation effectiveness, evaluating these strategies under local conditions is essential for providing science-based management recommendations 18 . The northern Patagonian steppe in Argentina provides a compelling setting to evaluate the performance of lethal and non-lethal predation mitigation strategies, considering its history of human-induced cascades 19 – 21 . Since the late 1950s, widespread carnivore persecution led to the local extinction of pumas ( Puma concolor ), the apex predator, and the ecological extinction of large native herbivores, including guanacos ( Lama guanicoe ) and lesser rheas ( Rhea pennata ) 20 . Meanwhile, the culpeo fox ( Lycalopex culpaeus ), the dominant mesopredator in the assemblage, experienced a population release 19 . In the 1990s, a collapse in the local sheep industry led to the abandonment of many ranches and smallholdings 22 , 23 , facilitating a slow landscape recolonization by pumas 19 , 20 . In 1995, several provincial governments reinstated subsidized lethal control policies targeting pumas and culpeo foxes. Additionally, the illegal use of toxic baits for predator control is threatening Andean condor ( Vultur gryphus ) populations 24 . Recently, government agencies and NGOs have begun promoting the implementation of Livestock Guarding Dogs (LGD) to mitigate predation, without assessments of their performance in extensive Patagonian ranching systems. In this study we (a) determine the incidence of predation by native carnivores relative to other causes of sheep mortality, and (b) assess the effects of socio-environmental and management drivers on the probability of sheep mortality events. Results Sheep Mortality Patterns and Predation Incidence A total of 139 necropsies were performed over the course of the study. The causes of mortality varied by age category (Table 2 ). After the perinatal period—during which the Starvation-Hypothermia Complex (SHC) was the primary mortality factor—predation emerged as the primary source of mortality. Table 2 Incidence of sheep mortality factors by age category. Recorded across six ranches in Northern Patagonia from October 2015 to February 2018. The table presents the number of sheep carcasses found (n) and the relative incidence of mortality factors (%) for each age category and the total sample. Perinatal Lamb Yearling Adult Total n % n % n % n % n % SHC* 11 52,4 1 4,2 2 4,0 14 10,1 Dystocia 1 4,8 1 0,7 Congenital malformation 1 4,8 1 0,7 Drowning by immersion 1 2,0 1 0,7 Predation Pumas 5 11,4 31 62,0 36 25,9 Cupeo foxes 27 61,4 2 8,3 2 4,0 31 22,3 Feral dogs 1 4,8 5 11,4 14 58,3 10 20,0 30 21,6 Scavenger birds 1 4,8 1 2,0 2 1,4 Undetermined 6 28,6 7 15,9 7 29,2 3 6,0 23 16,5 *Starvation-Hypotermia Complex Native carnivore predation accounted for 48.2% of recorded deaths and, when the condition of the carcass could be assessed, most were classified as primary predation (Table 3 ). Among sheep killed by pumas, 86.1% were adults, while the remainder were lambs. Culpeo foxes primarily preyed on lambs (87.1%), with the rest of the predation events evenly distributed between yearlings (6.4%) and adults (6.4%). Predation by feral and stray dogs was also a significant cause of mortality, accounting for 21.6% of recorded deaths. These predators were responsible for the largest surplus killing events, with up to eight sheep killed in a single incident (Table 3 ). Deaths caused by feral dogs were more evenly distributed across age categories: 43.3% were yearlings, 33.3% were adults, and 23.3% were lambs. Table 3 Number and percentage of carcasses corresponding to each type of predation, classified by the species involved, along with the average number of sheep killed per event. Pumas Culpeo foxes Feral dogs Scavenger birds Primary predation 33 (91,7%) 17 (54,8%) 16 (53,3%) Secondary predation 1 (2,8%) 1 (3,2%) 9 (30,0%) 2 (100,0%) Undetermined predation 2 (5,5%) 13 (41,9%) 5 (16,7%) Independent kill events 18 22 11 2 Sheep killed per event 2,0 ± 1,6 1,4 ± 0,7 2,7 ± 2,3 1,0 Effects of socio-environmental and management covariates The 2016–2017 season data subset consisted of 45 independent mortality events, totalling 79 sheep deaths. Two models were top-ranked with Δ ELPD < -2 points. The best model explaining the occurrence of independent sheep mortality events was diag ~ LGD + hpress_puma + (1|event) + (1|ranch) (Supporting Information A4). Under this model, LGD use had a significant inverse effect on the probability of puma predation events (95% CI: -54.7 to -1.9; Fig. 2 ). Similarly, hpress_puma showed a significant inverse effect on the probability of SHC deaths (95% CI: -33.5 to -2.2), however the relationship is unlikely to be causal. The second-best model was diag ~ culpeo_rai + wh_biomass + (1|event) + (1|ranch) (Fig. 3 ). Under this model, wh_biomass and culpeo_rai had significant inverse effects on the probability of culpeo (95% CI: -0.1 to -0.01) and puma predation (95% CI: -15.9 to -0.6), respectively. Additionally, culpeo_rai had a significant direct effect on culpeo predation (95% CI: 0.1 to 1.5) and SHC deaths (95% CI: 0.04 to 1.3). Both models met normality and homoscedasticity assumptions (KS and Levene p-tests > 0.05) but exhibited underdispersion (non-parametric dispersion test p < 0.05), suggesting limited representation of residuals at the extremes of the fitted distribution. Discussion In this study, 48.2% of recorded sheep deaths were to predation by native carnivores. Although data on sheep mortality patterns under extensive livestock systems are limited and often outdated, our findings are consistent with previous research in Patagonia 25 and other regions such as North America and Europe 26 – 29 . For example, brown bear ( Ursus arctos ) predation in Norway and coyote ( Canis latrans ) predation in Utah accounted for 73.5% 27 and 87.0% 28 of sheep deaths, respectively. Our study recorded an increase in puma predation compared to previous studies from the 1979–1986 period in our study area, when the culpeo fox was the main sheep predator at that time 25 . Similar patterns were observed in Utah, where coyotes were responsible for almost all predation during the 1972–1975 period, but puma-related sheep killings increased by approximately 30% in the same area during 2006–2007, likely due to puma recolonization 28 . In the southern cone, the recolonization of top predators to semi-natural rangelands could explain the increase in puma predation in livestock landscapes like Patagonia 20 , 30 . During the perinatal period, the leading cause of mortality was the Starvation–Hypothermia Complex (SHC). However, we recommend caution in interpreting the recorded sheep mortality patterns. The incidence of perinatal deaths in these extensive systems may be underreported, as scavengers often consume newborn lambs before they can be detected, unlike older age classes. After the perinatal period, predation became the primary cause of sheep mortality. Similar patterns have been recorded in the Northern Hemisphere, either due to husbandry practices (e.g., lambing is conducted in confinement or in small, monitored plots until lambs surpass the critical first 72 hours of life; 31 , 32 or the biology of wild carnivores (e.g., increased energetic demands of reproductively active carnivores associated with raising litters; 33 . In our study, 60% of lambs over one week old died due to culpeo fox predation and, where it could be confirmed, almost all lambs were in good nutritional and health condition. The best model linked to culpeo predation suggests that these foxes respond simultaneously to bottom-up (e.g., anthropogenic energetic subsidies 34 ) and top-down regulations (e.g. mesopredator release 35 ). On one hand, sheep predation by culpeos was significantly inversely affected by prey availability, dominated by the European hare. This aligns with previous findings linking reduced hare availability to increased sheep consumption 36 and similar functional responses in coyotes 33 , 37 and jackals ( Canis mesomelas 38 ). On the other hand, culpeo relative abundance has been inversely related to the probability of sheep predation by pumas. This, combined with a moderate inverse correlation between the relative abundances of pumas and culpeos (r = -0.55), suggests an avoidance response by the mesopredator to sites intensively used by the top predator. While the adaptability of culpeo foxes and other mesopredators to human-induced trophic cascades in bottom-up/top-down pressures is well documented 19 , 39 , few studies have assessed the consequences of these processes on livestock predation 35 . In Patagonia, pumas have evolved as apex predators with no other large carnivores contesting their dominance over landscapes, prey, or kills 40 . In well-preserved puma-guanaco systems, pumas tend to select open habitats containing large guanaco aggregations 41 . However, in human-dominated landscapes, pumas have been displaced to sites that, due to their altitude, topography, or cover, offer refuge to avoid encounters with people, similar to other apex predators 4 , 42 – 45 . Consequently, puma distribution is not uniform in the study area and sheep grazing in these refuges may face increased predation risk. Therefore, the occurrence of predation events depends mainly on the spatio-temporal availability of sheep 46 . Even when territorially displaced, surplus killing events and the vulnerability of sheep to predation ( 47 , 48 can cause a few individuals to disproportionately increase puma predation as a sheep mortality factor. This is consistent with findings from Chilean Patagonia, where pumas tend to preyed on sheep more frequently than expected based on their availability 46 . Despite this complex context, our findings show that the incorporation of Livestock Guarding Dogs (LGD) significantly reduce puma predation on sheep. Our best explanatory model of sheep mortality patterns retained LGD presence and puma hunting pressures, but only LGD effectively reduced the probability of puma predation events. Extensive literature shows that preventive and retaliatory killing of predators has erratic performance in mitigating damage (see Treves et al., 2016). Hunting operates indirectly by affecting predator abundance and inducing fear landscapes 3 , 4 , but it does not address livestock vulnerability when domestic ungulates coincide spatiotemporally with carnivores 16 . Moreover, non-selective lethal control can increase predation damage when predator populations respond with source-sink dynamics and compensatory recruitment in attractive sinks 15 , 49 . In contrast, LGD work by both passively defending herds (through scent marking, territorial signals, and creating fear landscapes) and actively protecting them (by interfering and displaying agonistic behaviours during encounters with predators) 50 – 52 . While we need to deepen our understanding of LGD in Patagonia, our findings align with exhaustive assessments conducted in extensive livestock systems in North America 53 . Although LGD breeds originated in Eurasian small pastoralist systems, they have become a key tool for predation mitigation worldwide 2 , 52 . Beyond native carnivore predation, the incidence of sheep predation by feral and stray dogs recorded in our study is concerning (21.6% of sheep deaths). This finding underscores a critical policy inconsistency: while the state subsidises native carnivores eradication, there are no comparable measures to regulate or reduce dog populations through euthanasia and responsible ownership policies 54 . We urge relevant authorities in Argentina to implement effective management measures for feral and stray dogs, including control strategies aligned with animal welfare and ecosystem health priorities 54 . While the sample size and number of mortality events recorded necessitate caution in extrapolating conclusions, our findings offer important insights that challenge current predation management policies. Even when focusing solely on safeguarding the sheep industry, reliance on lethal control has proven ineffective 9 or even to exacerbate losses 14 , 15 , particularly in the current context of rural landscape depopulation and top predator recolonization in Patagonia 20 . Furthermore, when subsidies for lethal control are financed through taxes, it can create inequities, effectively forcing those who adopt preventive mitigation measures to subsidize others who are indifferent or resistant to improving their livestock management practices 12 . Therefore, we recommend that stakeholders avoid reductionist approaches to predation management and focus on minimizing sheep vulnerability rather than focusing solely on native predators removal 1 , 2 . LGD are incompatible with toxic baiting practices, we advocate for broader institutional support and promotion of LGD as a cornerstone of sustainable predation management in Patagonian livestock systems. Alone LGD incorporation in ranches extensively managed would be insufficient and should be complemented with selective removal of problematic individuals and the provision of alternative wild prey 2 , 46 . Replicating our study in better conserved puma-native prey-livestock systems would allow integrally assess LGD performance, and promote coexistence landscapes in Patagonia and worldwide 2 , 17 . Finally, we encourage ecologists, particularly in South America 17 , to increase their efforts and interest in predation dynamics within rural landscapes to contribute to sustainable rural development processes. Methods Study area. This study was conducted in Pilcaniyeu County (PC; -41.123140 / -70.721893; Fig. 1 ), located in Río Negro Province, Argentina. The terrain is predominantly hilly, with the Andean foothills to the west and mountains and plateaus to the east. Proximity to the Andes generates a strong west-to-east precipitation gradient, with annual rainfall decreasing from approximately 650 mm in the westernmost areas to less than 300 mm in the easternmost regions 55 . The steppe vegetation reflects this gradient, transitioning from grass-dominated communities ( Festuca pallescens, Pappostipa spp., Poa ligularis , and Festuca argentina ) to mixed grass-shrub communities and, further east, to shrub-dominated steppes characterized by Mulinum spinosum, Acaena splendens , and Senecio spp. In the valleys, precipitation drainage allows for the development of wet meadows dominated by Juncus balticus 55 , 56 . The main economic activity in the region is Merino sheep ranching, primarily for the international wool market and sustained by grazing on natural grasslands 55 . In Río Negro, Law 763/1972 ( "Fight against populations of species circumstantially dangerous to livestock" ) provides state-funded incentives for the lethal control of pumas and culpeo foxes 12 , 13 . The prey base is severely degraded, with the European hare ( Lepus europaeus ) dominating the available wild herbivore biomass, representing 89% of the total (Gáspero unpubl. data). Sampling units were selected based on a convenience criterion, considering landowners' willingness to participate and the availability of internal roads accessing sheep grazing areas. Fieldwork began during the 2015 lambing season (mid-October) on three ranches (A, B, and C), all of which exclusively employed lethal control of predators. In late winter 2016, ranch C incorporated four adult Livestock Guarding Dogs (LGD). Consequently, from the 2016 lambing season onward, the survey was expanded to include three additional ranches. From the 2016 lambing season to February 2018, ranches A, B, and F continued using only lethal control, while ranches C, D, and E adopted LGD as a predation mitigation strategy (Fig. 1 ). The total area covered by the six ranches encompassed 1,584 km². Sheep Mortality Monitoring. Vehicular transects were conducted seasonally along internal ranch roads at speeds of 5–15 km/h, beginning 30 minutes after sunrise. During each transect, sheep carcasses were recorded, and necropsies were performed to determine the cause of death 57 , 58 . In total, 284 survey days were completed (A: 79; B: 67; C: 56; D: 31; E: 26; F: 25). Sheep were classified into four age categories according to tooth eruption patterns and seasonal timing: (i) Perinatal - stillborn fetuses and lambs up to seven days old; (ii) Lamb - individuals older than one week up to weaning; (iii) Yearling - from weaning to 18–20 months of age; and (iv) Adult, individuals older than 20 months. Based on the nutritional and health assessments, predation events were classified into three categories: (i) Primary predation - sheep in good health and nutritional condition killed by predators; (ii) Secondary predation - predation on non-viable individuals that had died due to primary non-predation factors, such as malnutrition or disease; and (iii) Undetermined predation - cases where the pre-mortem condition could not be established (e.g., due to the consumption of vital organs by predators or scavengers). Non-viable individuals were defined as those exhibiting (a) poor nutritional condition or severe starvation and/or (b) visible signs of acute illness 57 . Socio-environmental and management covariates. We estimated a set of covariates potentially associated with the occurrence of sheep mortality events based on carcass location data (e.g. distance to nearest urban centre or village as proxy for domestic dog predation; Table 1 ). Field methods and general data processing are detailed in Supporting Information-A1. Table 1 Details of explanatory covariates and their operational hierarchical level in model structure, used to assess their contribution to sheep mortality event probability and to explore the performance of lethal and non-lethal predation management strategies. Covariable ID Metodology Hierarchical level. Description Socio-environmental Elevation ele GPS Individual carcass. Altitude of carcass location. Distance to urban center dist_centurb GIS Individual carcass. Carcass distance to nearest city or village borders. Normalized Difference Vegetation Index ndvi GIS Ranch. Mean NDVI of ranches during 2016–2017 season. Puma kill site ruggedness pumaks_tri GIS Individual carcass. Mean Terrain Ruggedness Index (TRI; Riley et al., 1999) in a 4461 m diameter buffer around carcass location. Culpeo kill site ruggedness culpeoks_tri GIS Individual carcass. Mean TRI (Riley et al., 1999) in a 3337 m diameter buffer around carcass location. Puma relative abundance puma_rai Photo-trapping & GIS Individual carcass. Puma relative abundance index (RAI) corresponding to nearest camera trap station to carcass location. Culpeo relative abundance culpeo_rai Photo-trapping & GIS Individual carcass. Culpeo fox RAI corresponding to nearest camera trap station to carcass location. European hare relative abundance lepus_rai Photo-trapping & GIS Individual carcass. European hare RAI corresponding to nearest camera trap station to carcass location. Wild herbivore availability wh_biomass CRM & Distance Sampling Ranch. Estimated annual prey items density multiplied by item body mass. Predation management Puma hunting pressure hpress_puma Questionnaires Ranch. (Number of pumas annually hunted in the ranch/ranch surface)*100 km 2 . Culpeo fox hunting pressure hpress_culpeo Questionnaires Ranch. (Number of cupeo foxes annually hunted in the ranch/ranch surface)*100 km 2 . Livestock Guarding Dogs LGD Questionnaires Ranch. (Number of LGD/ranch surface)*100 km 2 . Regarding predation management, data were obtained through a brief questionnaire administered to ranch managers. All interviewees were informed about the survey objectives, and the questionnaire was conducted only after they orally provided infomed consent, in accordance with the Ethics Code for Ethnobiological Investigation in Latin America (SOLAE, 2016). Besides interview proceedings the study was assessed and approved by Comahue National University doctoral committee (Act N° 358/2021). The questionnaire gathered information on sheep stock, the number of pumas and culpeo foxes killed annually, and the number of LGDs working on each ranch. Statistical Analyses. All data analyses were performed in R (version 4.3.1) 60 . We built hierarchical Bayesian linear models to determine the main factors influencing sheep mortality events according to their diagnosis (i.e., diag). Models were created using the Stan computational framework ( http://mc-stan.org/ ) accessed via the brms package (version 2.19.0 61 ). The subset included 76 sheep deaths corresponding to 43 mortality events recorded during the 2016–2017 season. Prior to modelling, we assessed correlations between covariates and excluded highly correlated ones (i.e., when |r| ≥ 0.6). To account for non-independence of deaths within the same mortality event (i.e., surplus killing), we included a (1|event) term in the models. Similarly, a (1|ranch) term was added to account for fixed effects related to predation management practices (i.e., LGD use and hunting pressure) and other uncontrolled variables such as ranch location with respect to rainfall gradient, primary productivity, and general livestock management. We proposed a set of models incorporating different covariates to explain the probability of mortality events due to puma, culpeo fox, and domestic dog predation, the Starvation-Hypothermia Complex (SHC), which also includes immersion and dystocia, and undetermined diagnoses. We included socio-environmental covariates operating at the individual carcass level and predation management practices at the ranch level (Table 1 ). Model comparisons included Zero-Inflated Poisson (ZIP) and Poisson models with nested and non-nested factors. Models were run for 4,000 iterations with a warm-up of 500 iterations. We set adapt Δ to 0.95 to avoid divergent transitions. Models were fitted with non-informative priors, and chain convergence was assessed using the Rhat statistic (all Rhat < 1.1). Homoscedasticity and normality assumptions of the posterior distribution were analyzed using the Dharma package (version 0.4.6; Hartig, 2019) through QQ-plot residual inspection, residual vs. predicted KS test, and within-group deviation analysis. A nonparametric dispersion test was conducted using the “testDispersion” function from the Dharma package. The best-fit model was selected based on wAIC. Models were evaluated using Bayesian Expected Logarithmic Predictive Density differences (Δ ELPD), with models having Δ ELPD < -2 points relative to the highest-ranked model being considered. Socio-environmental and management covariate effects were deemed significant if their 95% Credibility Interval (CI) did not include zero under the best-fit models. Declarations Author contributions P. G. led all stages of the research; G. de la V. contributed significantly to data curation, statistical analysis and results interpretation; J. T., V. F-A. and J. P. were consistently involved during experimental design, sampling, and manuscript writing. All authors reviewed the manuscript. Acknowledgements We thank the ranch owners and workers for their collaboration, as well as A. di Virgilio, I. Barberá, J.A. Kusanovich, J.M. Garramuño and F. Bidinost. We also acknowledge institutional support from the Ministry for the Environment and Spatial Planning of the Regional Government of Andalusia (Consejería de Medio Ambiente y Ordenación del Territorio de la Junta de Andalucía). Funding declaration P.G. discloses support for the research of this work from Instituto Nacional de Tecnología Agropecuaria [INTA-PE I037 and INTA-PD I096] and IdeaWild Foundation [GASPARGE0715-00]. The authors declare no competing interests. Data availability statement: All data generated or analysed during this study are included in this published article as Supplementary Information files [SuppInf_A2.xlsx and SuppInf_A3.xlsx]. References Carter, N. H. & Linnell, J. D. C. C. Co-Adaptation Is Key to Coexisting with Large Carnivores. Trends Ecol Evol 31 , 575–578 (2016). Miller, J. R. B. & Schmitz, O. J. Landscape of fear and human-predator coexistence: Applying spatial predator-prey interaction theory to understand and reduce carnivore-livestock conflict. Biol Conserv 236 , 464–473 (2019). Dorresteijn, I. et al. Incorporating anthropogenic effects into trophic ecology: Predator - Prey interactions in a human-dominated landscape. Proceedings of the Royal Society B: Biological Sciences 282 , (2015). Ordiz, A., Bischof, R. & Swenson, J. E. Saving large carnivores, but losing the apex predator? Biol Conserv 168 , 128–133 (2013). Ripple, W. J. et al. Status and ecological effects of the world’s largest carnivores. Science (1979) 343 , (2014). Minin, E. Di et al. Global priorities for national carnivore conservation under land use change. Sci Rep 6 , 1–9 (2016). Van Eeden, L. M. et al. Managing conflict between large carnivores and livestock. Conservation Biology 32 , 26–34 (2018). Dickman, A. J. Complexities of conflict: The importance of considering social factors for effectively resolving human-wildlife conflict. Anim Conserv 13 , 458–466 (2010). Berger, K. M. Carnivore-livestock conflicts: Effects of subsidized predator control and economic correlates on the sheep industry. Conservation Biology 20 , 751–761 (2006). Redpath, S. M. et al. Don’t forget to look down – collaborative approaches to predator conservation. Biological Reviews 92 , 2157–2163 (2017). Marchini, S. et al. Planning for human-wildlife coexistence: conceptual framework, workshop process and a model for transdisciplinary collaboration. Frontiers in Conservation Science 2 , 11 (2021). Gáspero, P. G. et al. Human-carnivore interaction in a context of socio-productive crisis: Assessing smallholder strategies for reducing predation in North-west Patagonia, Argentina. J Arid Environ 150 , 92–98 (2018). Taylor, J., Núñez, P., Gáspero, P., Pooley, S. & Fernandez-Arhex, V. Comparing narratives on carnivore management in a dryland ecosystem: a case study of state-backed lethal control. Rangeland Journal 45 , 45–52 (2023). Treves, A., Krofel, M. & Mcmanus, J. Predator control should not be a shot in the dark. Front Ecol Environ 14 , 380–388 (2016). Peebles, K. A., Wielgus, R. B., Maletzke, B. T. & Swanson, M. E. Effects of remedial sport hunting on cougar complaints and livestock depredations. PLoS One 8 , 1–8 (2013). Rigg, R. et al. Mitigating carnivore-livestock conflict in Europe: Lessons from Slovakia. Oryx 45 , 272–280 (2011). Ohrens, O., Lagos, N., Yovovich, V. & Elbroch, M. A Call for Research on Reducing Livestock-Mountain Lion Conflict. Canadian Wildlife Biology and Management 13 , 111–119 (2024). Eklund, A., Johansson, M., Flykt, A., Andrén, H. & Frank, J. Drivers of intervention use to protect domestic animals from large carnivore attacks. Human Dimensions of Wildlife 25 , 339–354 (2020). Díaz-Ruiz, F. et al. Inferring species interactions from long-term monitoring programs: Carnivores in a protected area from southern Patagonia. Diversity (Basel) 12 , 1–17 (2020). Walker, S. R. & Novaro, A. J. The World’s Southernmost Pumas in Patagonia and the Southern Andes. in Cougar: Ecology and Conservation (eds. Hornocker, M. G. & Negri, S.) 91–100 (The University of Chicago Press, Chicago, US, 2010). Palacios, R., Walker, R. S. & Novaro, A. J. Differences in diet and trophic interactions of Patagonian carnivores between areas with mostly native or exotic prey. Mammalian Biology 77 , 183–189 (2012). Easdale, M. H., Sacchero, D., Vigna, M. & Willems, P. Assessing the magnitude of impact of volcanic ash deposits on Merino wool production and fibre traits in the context of a drought in North-west Patagonia, Argentina. Rangeland Journal 36 , 143–149 (2014). Wilson, T. et al. Short- and long-term evacuation of people and livestock during a volcanic crisis: Lessons from the 1991 eruption of Volcán Hudson, Chile. Journal of Applied Volcanology 1 , (2012). Pauli, J. N., Donadio, E. & Lambertucci, S. A. The corrupted carnivore: how humans are rearranging the return of the carnivore-scavenger relationship. Ecology 99 , 2122–2124 (2018). Bellati, J. & Von Thungen, J. LAMB PREDATION IN PATAGONIAN RANCHES. in Proceedings of the 14th Vertebrate Pest Conference 3–9 (1990). Klebenow, D. A. & McAdoo, K. Predation on Domestic Sheep in Northeastern Nevada. Journal of Range Management 29 , 96 (1976). Mysterud, Ivar. & Warren, J. T. Brown Bear Predation on Domestic Sheep Registered with Mortality Transmitters. in Ninth International Conference on Bear Research and Management vol. 9 107–111 (1992). Palmer, B. C., Conover, M. R. & Frey, S. N. Replication of a 1970s study on domestic sheep losses to predators on Utah’s summer rangelands. Rangel Ecol Manag 63 , 689–695 (2010). Warren, J. T., Mysterud, I. & Lynnebakken, T. Mortality of lambs in free-ranging domestic sheep (Ovis aries) in northern Norway. J Zool 254 , 195–202 (2001). Ohrens, O., Treves, A. & Bonacic, C. Relationship between rural depopulation and puma-human conflict in the high Andes of Chile. Environ Conserv 43 , 24–33 (2016). Moberly, R. L., White, P. C. L. L., Webbon, C. C., Baker, P. J. & Harris, S. Modelling the costs of fox predation and preventive measures on sheep farms in Britain. J Environ Manage 70 , 129–143 (2004). Tallian, A. et al. Large carnivore conservation and traditional pastoralism: A case study on bear–reindeer predation mitigation measures. Ecosphere 14 , (2023). Sacks, B. N., Jaeger, M. M., Neale, J. C. C. & Mccullough, D. R. TERRITORIALITY AND BREEDING STATUS OF COYOTES RELATIVE TO SHEEP PREDATION. 63 , 593–605 (2007). Elmhagen, B. & Rushton, S. Trophic control of mesopredators in terrestrial ecosystems: top-down or bottom-up? Volume 10 Issue 3 Page 197 . Ecol Lett 10 , 197 (2007). Prugh, L. R. et al. The rise of the mesopredator. Bioscience 59 , 779–791 (2009). Novaro, A. J., Funes, M. C. & Jiménez, J. E. Patagonian foxes: Selection for introduced prey and conservation of culpeo and chilla foxes in Patagonia. in Biology and conservation of wild canids (eds. Macdonald, D. W. & Sillero-Zubiri, C.) 243–254 (Oxford University Press, New York, US, 2004). doi:10.1007/s13398-014-0173-7.2. Stoddart, L. C., Griffiths, R. E. & Knowlton, F. F. Coyote responses to changing jackrabbit abundance affect sheep predation. Journal of Range Management 54 , 15–20 (2001). Kamler, J. F., Klare, U. & Macdonald, D. W. Seasonal diet and prey selection of black-backed jackals on a small-livestock farm in South Africa. Afr J Ecol 50 , 299–307 (2012). Elmhagen, B. & Rushton, S. P. Trophic control of mesopredators in terrestrial ecosystems: Top-down or bottom-up? Ecol Lett 10 , 197–206 (2007). Elbroch, L. M. & Kusler, A. Are pumas subordinate carnivores, and does it matter? PeerJ 6 , e4293 (2018). Elbroch, L. M. & Wittmer, H. U. Puma spatial ecology in open habitats with aggregate prey. Mammalian Biology 77 , 377–384 (2012). Ordiz, A. et al. Do bears know they are being hunted? Biol Conserv 152 , 21–28 (2012). Pia, M. V., Renison, D., Mangeaud, A., De Angelo, C. & Haro, J. G. Occurrence of top carnivores in relation to land protection status, human settlements and rock outcrops in the high mountains of central Argentina. J Arid Environ 91 , 31–37 (2013). Støen, O. G. et al. Physiological evidence for a human-induced landscape of fear in brown bears (Ursus arctos). Physiol Behav 152 , 244–248 (2015). Barceló, G., Donadio, E., Alldredge, M. W. & Pauli, J. N. Human disturbance alters the foraging and spatiotemporal activity of a large carnivore. Oecologia 207 , 112 (2025). Elbroch, L. M. & Wittmer, H. U. The effects of puma prey selection and specialization on less abundant prey in Patagonia. J Mammal 94 , 259–268 (2013). Lucherini, M., Guerisoli, M. de las M. & Luengos Vidal, E. M. Surplus killing by pumas Puma concolor: rumours and facts. Mamm Rev 48 , 277–283 (2018). Swan, G. J. F., Redpath, S. M., Bearhop, S. & McDonald, R. A. Ecology of Problem Individuals and the Efficacy of Selective Wildlife Management. Trends Ecol Evol 32 , 518–530 (2017). Robinson, H. S., Wielgus, R. B., Cooley, H. S. & Cooley, S. W. Population SINK POPULATIONS IN CARNIVORE MANAGEMENT : COUGAR. 18 , 1028–1037 (2013). Van Bommel, L. & Johnson, L. Olfactory communication to protect livestock : dingo response to urine marks of livestock guardian dogs. 219–226 (2017). Van Bommel, L. & Johnson, C. N. Livestock guardian dogs as surrogate top predators? How Maremma sheepdogs affect a wildlife community. Ecol Evol 6 , 6702–6711 (2016). Gehring, T. M., VerCauteren, K. C. & Landry, J.-M. Livestock Protection Dogs in the 21st Century: Is an Ancient Tool Relevant to Modern Conservation Challenges? Bioscience 60 , 299–308 (2010). Kinka, D. & Young, J. K. Evaluating Domestic Sheep Survival with Different Breeds of Livestock Guardian Dogs. Rangel Ecol Manag (2019) doi:10.1016/j.rama.2019.07.002. Lambertucci, S. A., Zamora-Nasca, L. B., Segpunta, A., de la Reta, M. & Plaza, P. Evidence-based legislation, strong institutions and consensus needed to mitigate the negative impacts of free-ranging dogs. Ambio 53 , 299–308 (2024). Gaitán, J. J., Bran, D. E. & Oliva, G. E. Patagonian Desert. in Reference Module in Earth Systems and Environmental Sciences 1–18 (Elsevier, 2019). doi:10.1016/B978-0-12-409548-9.11929-3. Gaitán, J. J. et al. Aridity and Overgrazing Have Convergent Effects on Ecosystem Structure and Functioning in Patagonian Rangelands. Land Degrad Dev 29 , 210–218 (2018). McFarlane, D. Perinatal lamb losses. An autopsy method for the investigation of perinatal losses. New Zeland Veterinary Journal 13 , 116–135 (1965). Acorn, R. & Dorrance, M. METHODS OF INVESTIGATING PREDATION OF LIVESTOCK . (Alberta Agriculture and Rural Development, Edmonton, Canada, 2014). SOLAE. Código de Ética para la investigación, la investigación-acción y la colaboración etnocientífica en América Latina. Etnobiología 1 , 1–34 (2016). R Core Team. R: A language and environment for statistical computing. Preprint at https://www.r-project.org/ (2020). Bürkner, P. C. brms: An R package for Bayesian multilevel models using Stan. J Stat Softw 80 , (2017). Additional Declarations No competing interests reported. Supplementary Files SuppInfA1.docx SuppInfA2.xlsx SuppInfA3.xlsx SuppInfA4.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7234506","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":505542500,"identity":"6461e882-482b-4ec4-98bf-d3e58fa3450a","order_by":0,"name":"Pablo G. Gáspero","email":"data:image/png;base64,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","orcid":"","institution":"Instituto Nacional de Tecnología Agropecuaria-Estación Experimental Agropecuaria Bariloche (INTA-EEA Bariloche)","correspondingAuthor":true,"prefix":"","firstName":"Pablo","middleName":"G.","lastName":"Gáspero","suffix":""},{"id":505542502,"identity":"ce381e8f-526b-4b9d-ae1b-92e5334754ae","order_by":1,"name":"Gerardo De la Vega","email":"","orcid":"","institution":"Consejo Nacional de Investigaciones Científicas y Técnicas-Instituto de Investigaciones Forestales y Agropecuarias Bariloche (CONICET-IFAB)","correspondingAuthor":false,"prefix":"","firstName":"Gerardo","middleName":"De la","lastName":"Vega","suffix":""},{"id":505542503,"identity":"524c8e34-cf50-4bf9-a8bb-ce08a933fee4","order_by":2,"name":"Joshua P. Taylor","email":"","orcid":"","institution":"Consejo Nacional de Investigaciones Científicas y Técnicas-Instituto de Investigaciones Forestales y Agropecuarias Bariloche (CONICET-IFAB)","correspondingAuthor":false,"prefix":"","firstName":"Joshua","middleName":"P.","lastName":"Taylor","suffix":""},{"id":505542504,"identity":"fec20203-01c9-49fd-92b0-c7d6e1b0dd14","order_by":3,"name":"Valeria Fernández-Arhex","email":"","orcid":"","institution":"Consejo Nacional de Investigaciones Científicas y Técnicas-Instituto de Investigaciones Forestales y Agropecuarias Bariloche (CONICET-IFAB)","correspondingAuthor":false,"prefix":"","firstName":"Valeria","middleName":"","lastName":"Fernández-Arhex","suffix":""},{"id":505542505,"identity":"22277ae4-eb4d-4d18-a1e6-40601a15c03f","order_by":4,"name":"Javier A. Pereira","email":"","orcid":"","institution":"Consejo Nacional de Investigaciones Científicas y Técnicas-Museo Argentino de Ciencias Naturales Bernardino Rivadavia (CONICET-MACNBR)","correspondingAuthor":false,"prefix":"","firstName":"Javier","middleName":"A.","lastName":"Pereira","suffix":""}],"badges":[],"createdAt":"2025-07-28 13:38:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7234506/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7234506/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":90468423,"identity":"6eeda95d-0cf0-4abc-b4d9-f64b21421d13","added_by":"auto","created_at":"2025-09-03 06:06:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":553828,"visible":true,"origin":"","legend":"\u003cp\u003eStudy area and location of sampling units (ranches). The main map illustrates the spatial arrangement of camera traps, internal ranch roads used to record sheep mortality events, and the establishment of Distance Sampling transects.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7234506/v1/c6a9f1e16bc862e119254973.png"},{"id":90468428,"identity":"de10eb0d-0795-4b03-8fc4-78d5f8ee2b55","added_by":"auto","created_at":"2025-09-03 06:06:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":55750,"visible":true,"origin":"","legend":"\u003cp\u003e95 % Credible Interval graphical representation of covariate effects on the probability of sheep mortality diagnoses under the model \u003cem\u003ediag ~ LGD + hpress_puma + (1|event) + (1|ranch)\u003c/em\u003e. Reference: \u003cem\u003eSHC\u003c/em\u003e (Starvation Hypothermia Complex), \u003cem\u003epumapred\u003c/em\u003e (puma predation), \u003cem\u003edogpred\u003c/em\u003e (feral and stray dog predation), \u003cem\u003eculpeopred\u003c/em\u003e (culpeo fox predation) and \u003cem\u003e‘by’\u003c/em\u003e (connector to link diagnose with effect of specific covariable retained in the model).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7234506/v1/298604adcd04464ad9c80292.png"},{"id":90470433,"identity":"7d9b0d3f-cc05-4682-a629-e31a82d9a5a4","added_by":"auto","created_at":"2025-09-03 06:14:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":59885,"visible":true,"origin":"","legend":"\u003cp\u003e95 % Credible Interval graphical representation of covariate effects on the probability of sheep mortality diagnoses under the model \u003cem\u003ediag ~ culpeo_rai + wh_biomass + (1|event) + (1|ranch)\u003c/em\u003e. Reference: \u003cem\u003eSHC\u003c/em\u003e (Starvation Hypothermia Complex), \u003cem\u003epumapred\u003c/em\u003e (puma predation), \u003cem\u003edogpred\u003c/em\u003e (feral and stray dog predation), \u003cem\u003eculpeopred\u003c/em\u003e (culpeo fox predation) and \u003cem\u003e‘by’\u003c/em\u003e (connector to link diagnose with effect of specific covariable retained in the model).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7234506/v1/b5dc6df89f12e94ac3a6ec83.png"},{"id":92502640,"identity":"61d497c8-ec6d-4ce8-ae0f-ddae5a6c7025","added_by":"auto","created_at":"2025-09-30 11:46:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1365481,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7234506/v1/87028c91-2783-40e2-8c54-5604c48f6236.pdf"},{"id":90468431,"identity":"553a3400-ae89-4c59-8dc2-ea623ed9fcba","added_by":"auto","created_at":"2025-09-03 06:06:40","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":64521,"visible":true,"origin":"","legend":"","description":"","filename":"SuppInfA1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7234506/v1/04733d1bfdc512ba5e7d09f5.docx"},{"id":90468445,"identity":"f77ac92e-50ed-4604-b4f6-4d0fdb0083f7","added_by":"auto","created_at":"2025-09-03 06:06:41","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":20259,"visible":true,"origin":"","legend":"","description":"","filename":"SuppInfA2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7234506/v1/23d7c961d0d03e249b540e91.xlsx"},{"id":90468442,"identity":"a71aae1a-f00d-418a-9042-40576d1d3731","added_by":"auto","created_at":"2025-09-03 06:06:41","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":22817,"visible":true,"origin":"","legend":"","description":"","filename":"SuppInfA3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7234506/v1/73763fa26c8d5d9ccf257bb9.xlsx"},{"id":90468439,"identity":"221ea9e3-79e2-4190-ab65-7d9ba46cb372","added_by":"auto","created_at":"2025-09-03 06:06:41","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":17717,"visible":true,"origin":"","legend":"","description":"","filename":"SuppInfA4.docx","url":"https://assets-eu.researchsquare.com/files/rs-7234506/v1/aad220146e39d69c6bb212a0.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Pumas, culpeo foxes, bad and good dogs. Assessing strategies to mitigate predation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eManaging predation in livestock landscapes is an environmental and socio-economic challenge \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Historically, lethal control has been one of the main strategies implemented globally to mitigate real or perceived livestock losses. However, retaliatory killing, together with other disturbances, configure worldwide extended human-induced trophic cascades. It has disrupted intraguild interactions among carnivores, ultimately affecting the provision of predation-related ecosystem services \u003csup\u003e\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Worldwide large carnivores population viability depends on the consolidation of coexistence landscapes outside protected areas \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe performance of predation mitigation strategies is conditioned by the socio-environmental context in which they are applied \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Stakeholders and policymakers worldwide tend to oversimplify livestock-carnivore interactions \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, leading to linear governance models in predation management \u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. In many regions, policies that promote lethal control continue to be implemented \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, with inconsistent impacts on livestock losses \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. By contrast, well-implemented non-lethal predation mitigation strategies have demonstrated success in different socio-environmental contexts \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. However, in the Global South, and particularly in South America, empirical studies that confirm direct attacks and monitor socio-environmental covariables remain scarce \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Given the context dependence of mitigation effectiveness, evaluating these strategies under local conditions is essential for providing science-based management recommendations\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe northern Patagonian steppe in Argentina provides a compelling setting to evaluate the performance of lethal and non-lethal predation mitigation strategies, considering its history of human-induced cascades \u003csup\u003e\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Since the late 1950s, widespread carnivore persecution led to the local extinction of pumas (\u003cem\u003ePuma concolor\u003c/em\u003e), the apex predator, and the ecological extinction of large native herbivores, including guanacos (\u003cem\u003eLama guanicoe\u003c/em\u003e) and lesser rheas (\u003cem\u003eRhea pennata\u003c/em\u003e) \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Meanwhile, the culpeo fox (\u003cem\u003eLycalopex culpaeus\u003c/em\u003e), the dominant mesopredator in the assemblage, experienced a population release \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. In the 1990s, a collapse in the local sheep industry led to the abandonment of many ranches and smallholdings \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, facilitating a slow landscape recolonization by pumas \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. In 1995, several provincial governments reinstated subsidized lethal control policies targeting pumas and culpeo foxes. Additionally, the illegal use of toxic baits for predator control is threatening Andean condor (\u003cem\u003eVultur gryphus\u003c/em\u003e) populations \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Recently, government agencies and NGOs have begun promoting the implementation of Livestock Guarding Dogs (LGD) to mitigate predation, without assessments of their performance in extensive Patagonian ranching systems. In this study we (a) determine the incidence of predation by native carnivores relative to other causes of sheep mortality, and (b) assess the effects of socio-environmental and management drivers on the probability of sheep mortality events.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cem\u003eSheep Mortality Patterns and Predation Incidence\u003c/em\u003e\u003c/p\u003e\u003cp\u003eA total of 139 necropsies were performed over the course of the study. The causes of mortality varied by age category (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). After the perinatal period—during which the Starvation-Hypothermia Complex (SHC) was the primary mortality factor—predation emerged as the primary source of mortality.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eIncidence of sheep mortality factors by age category. Recorded across six ranches in Northern Patagonia from October 2015 to February 2018. The table presents the number of sheep carcasses found (n) and the relative incidence of mortality factors (%) for each age category and the total sample.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"11\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003ePerinatal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eLamb\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eYearling\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eAdult\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSHC*\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52,4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e4,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4,0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e10,1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDystocia\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4,8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0,7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCongenital malformation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4,8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0,7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrowning by immersion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2,0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e0,7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003ePredation\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePumas\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11,4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e62,0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e25,9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCupeo foxes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e61,4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e8,3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e4,0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e22,3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFeral dogs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4,8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11,4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e58,3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e20,0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e21,6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eScavenger birds\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4,8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e2,0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e1,4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUndetermined\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28,6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15,9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e29,2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003e6,0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c10\"\u003e\u003cp\u003e23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c11\"\u003e\u003cp\u003e16,5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"11\"\u003e*Starvation-Hypotermia Complex\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eNative carnivore predation accounted for 48.2% of recorded deaths and, when the condition of the carcass could be assessed, most were classified as primary predation (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among sheep killed by pumas, 86.1% were adults, while the remainder were lambs. Culpeo foxes primarily preyed on lambs (87.1%), with the rest of the predation events evenly distributed between yearlings (6.4%) and adults (6.4%). Predation by feral and stray dogs was also a significant cause of mortality, accounting for 21.6% of recorded deaths. These predators were responsible for the largest surplus killing events, with up to eight sheep killed in a single incident (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Deaths caused by feral dogs were more evenly distributed across age categories: 43.3% were yearlings, 33.3% were adults, and 23.3% were lambs.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNumber and percentage of carcasses corresponding to each type of predation, classified by the species involved, along with the average number of sheep killed per event.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePumas\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCulpeo foxes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eFeral dogs\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eScavenger birds\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary predation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33 (91,7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17 (54,8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16 (53,3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary predation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (2,8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (3,2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9 (30,0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2 (100,0%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUndetermined predation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (5,5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 (41,9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (16,7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndependent kill events\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSheep killed per event\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2,0 ± 1,6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1,4 ± 0,7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2,7 ± 2,3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1,0\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003eEffects of socio-environmental and management covariates\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe 2016–2017 season data subset consisted of 45 independent mortality events, totalling 79 sheep deaths. Two models were top-ranked with Δ ELPD \u0026lt; -2 points. The best model explaining the occurrence of independent sheep mortality events was \u003cem\u003ediag ~ LGD + hpress_puma + (1|event) + (1|ranch)\u003c/em\u003e (Supporting Information A4). Under this model, \u003cem\u003eLGD\u003c/em\u003e use had a significant inverse effect on the probability of puma predation events (95% CI: -54.7 to -1.9; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Similarly, \u003cem\u003ehpress_puma\u003c/em\u003e showed a significant inverse effect on the probability of SHC deaths (95% CI: -33.5 to -2.2), however the relationship is unlikely to be causal.\u003c/p\u003e\u003cp\u003eThe second-best model was \u003cem\u003ediag ~ culpeo_rai + wh_biomass + (1|event) + (1|ranch)\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Under this model, \u003cem\u003ewh_biomass\u003c/em\u003e and \u003cem\u003eculpeo_rai\u003c/em\u003e had significant inverse effects on the probability of culpeo (95% CI: -0.1 to -0.01) and puma predation (95% CI: -15.9 to -0.6), respectively. Additionally, \u003cem\u003eculpeo_rai\u003c/em\u003e had a significant direct effect on culpeo predation (95% CI: 0.1 to 1.5) and SHC deaths (95% CI: 0.04 to 1.3). Both models met normality and homoscedasticity assumptions (KS and Levene p-tests \u0026gt; 0.05) but exhibited underdispersion (non-parametric dispersion test p \u0026lt; 0.05), suggesting limited representation of residuals at the extremes of the fitted distribution.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, 48.2% of recorded sheep deaths were to predation by native carnivores. Although data on sheep mortality patterns under extensive livestock systems are limited and often outdated, our findings are consistent with previous research in Patagonia \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e and other regions such as North America and Europe \u003csup\u003e\u003cspan additionalcitationids=\"CR27 CR28\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e–\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. For example, brown bear (\u003cem\u003eUrsus arctos\u003c/em\u003e) predation in Norway and coyote (\u003cem\u003eCanis latrans\u003c/em\u003e) predation in Utah accounted for 73.5% \u003csup\u003e27\u003c/sup\u003e and 87.0% \u003csup\u003e28\u003c/sup\u003e of sheep deaths, respectively. Our study recorded an increase in puma predation compared to previous studies from the 1979–1986 period in our study area, when the culpeo fox was the main sheep predator at that time \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Similar patterns were observed in Utah, where coyotes were responsible for almost all predation during the 1972–1975 period, but puma-related sheep killings increased by approximately 30% in the same area during 2006–2007, likely due to puma recolonization \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. In the southern cone, the recolonization of top predators to semi-natural rangelands could explain the increase in puma predation in livestock landscapes like Patagonia \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDuring the perinatal period, the leading cause of mortality was the Starvation–Hypothermia Complex (SHC). However, we recommend caution in interpreting the recorded sheep mortality patterns. The incidence of perinatal deaths in these extensive systems may be underreported, as scavengers often consume newborn lambs before they can be detected, unlike older age classes. After the perinatal period, predation became the primary cause of sheep mortality. Similar patterns have been recorded in the Northern Hemisphere, either due to husbandry practices (e.g., lambing is conducted in confinement or in small, monitored plots until lambs surpass the critical first 72 hours of life; \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e or the biology of wild carnivores (e.g., increased energetic demands of reproductively active carnivores associated with raising litters; \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. In our study, 60% of lambs over one week old died due to culpeo fox predation and, where it could be confirmed, almost all lambs were in good nutritional and health condition.\u003c/p\u003e\u003cp\u003eThe best model linked to culpeo predation suggests that these foxes respond simultaneously to bottom-up (e.g., anthropogenic energetic subsidies \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e) and top-down regulations (e.g. mesopredator release \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e). On one hand, sheep predation by culpeos was significantly inversely affected by prey availability, dominated by the European hare. This aligns with previous findings linking reduced hare availability to increased sheep consumption\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e and similar functional responses in coyotes \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e and jackals (\u003cem\u003eCanis mesomelas\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e). On the other hand, culpeo relative abundance has been inversely related to the probability of sheep predation by pumas. This, combined with a moderate inverse correlation between the relative abundances of pumas and culpeos (r = -0.55), suggests an avoidance response by the mesopredator to sites intensively used by the top predator. While the adaptability of culpeo foxes and other mesopredators to human-induced trophic cascades in bottom-up/top-down pressures is well documented \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e, few studies have assessed the consequences of these processes on livestock predation \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn Patagonia, pumas have evolved as apex predators with no other large carnivores contesting their dominance over landscapes, prey, or kills \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. In well-preserved puma-guanaco systems, pumas tend to select open habitats containing large guanaco aggregations \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. However, in human-dominated landscapes, pumas have been displaced to sites that, due to their altitude, topography, or cover, offer refuge to avoid encounters with people, similar to other apex predators \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan additionalcitationids=\"CR43 CR44\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e–\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e. Consequently, puma distribution is not uniform in the study area and sheep grazing in these refuges may face increased predation risk. Therefore, the occurrence of predation events depends mainly on the spatio-temporal availability of sheep \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Even when territorially displaced, surplus killing events and the vulnerability of sheep to predation (\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e can cause a few individuals to disproportionately increase puma predation as a sheep mortality factor. This is consistent with findings from Chilean Patagonia, where pumas tend to preyed on sheep more frequently than expected based on their availability \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eDespite this complex context, our findings show that the incorporation of Livestock Guarding Dogs (LGD) significantly reduce puma predation on sheep. Our best explanatory model of sheep mortality patterns retained LGD presence and puma hunting pressures, but only LGD effectively reduced the probability of puma predation events. Extensive literature shows that preventive and retaliatory killing of predators has erratic performance in mitigating damage (see Treves et al., 2016). Hunting operates indirectly by affecting predator abundance and inducing fear landscapes \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, but it does not address livestock vulnerability when domestic ungulates coincide spatiotemporally with carnivores \u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Moreover, non-selective lethal control can increase predation damage when predator populations respond with source-sink dynamics and compensatory recruitment in attractive sinks \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. In contrast, LGD work by both passively defending herds (through scent marking, territorial signals, and creating fear landscapes) and actively protecting them (by interfering and displaying agonistic behaviours during encounters with predators)\u003csup\u003e\u003cspan additionalcitationids=\"CR51\" citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e–\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. While we need to deepen our understanding of LGD in Patagonia, our findings align with exhaustive assessments conducted in extensive livestock systems in North America\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Although LGD breeds originated in Eurasian small pastoralist systems, they have become a key tool for predation mitigation worldwide \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eBeyond native carnivore predation, the incidence of sheep predation by feral and stray dogs recorded in our study is concerning (21.6% of sheep deaths). This finding underscores a critical policy inconsistency: while the state subsidises native carnivores eradication, there are no comparable measures to regulate or reduce dog populations through euthanasia and responsible ownership policies \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. We urge relevant authorities in Argentina to implement effective management measures for feral and stray dogs, including control strategies aligned with animal welfare and ecosystem health priorities \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWhile the sample size and number of mortality events recorded necessitate caution in extrapolating conclusions, our findings offer important insights that challenge current predation management policies. Even when focusing solely on safeguarding the sheep industry, reliance on lethal control has proven ineffective \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e or even to exacerbate losses \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e, particularly in the current context of rural landscape depopulation and top predator recolonization in Patagonia \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Furthermore, when subsidies for lethal control are financed through taxes, it can create inequities, effectively forcing those who adopt preventive mitigation measures to subsidize others who are indifferent or resistant to improving their livestock management practices \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Therefore, we recommend that stakeholders avoid reductionist approaches to predation management and focus on minimizing sheep vulnerability rather than focusing solely on native predators removal \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. LGD are incompatible with toxic baiting practices, we advocate for broader institutional support and promotion of LGD as a cornerstone of sustainable predation management in Patagonian livestock systems.\u003c/p\u003e\u003cp\u003eAlone LGD incorporation in ranches extensively managed would be insufficient and should be complemented with selective removal of problematic individuals and the provision of alternative wild prey \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Replicating our study in better conserved puma-native prey-livestock systems would allow integrally assess LGD performance, and promote coexistence landscapes in Patagonia and worldwide \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. Finally, we encourage ecologists, particularly in South America \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, to increase their efforts and interest in predation dynamics within rural landscapes to contribute to sustainable rural development processes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cem\u003eStudy area.\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThis study was conducted in Pilcaniyeu County (PC; -41.123140 / -70.721893; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), located in Río Negro Province, Argentina. The terrain is predominantly hilly, with the Andean foothills to the west and mountains and plateaus to the east. Proximity to the Andes generates a strong west-to-east precipitation gradient, with annual rainfall decreasing from approximately 650 mm in the westernmost areas to less than 300 mm in the easternmost regions \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. The steppe vegetation reflects this gradient, transitioning from grass-dominated communities (\u003cem\u003eFestuca pallescens, Pappostipa spp., Poa ligularis\u003c/em\u003e, and \u003cem\u003eFestuca argentina\u003c/em\u003e) to mixed grass-shrub communities and, further east, to shrub-dominated steppes characterized by \u003cem\u003eMulinum spinosum, Acaena splendens\u003c/em\u003e, and \u003cem\u003eSenecio\u003c/em\u003e spp. In the valleys, precipitation drainage allows for the development of wet meadows dominated by \u003cem\u003eJuncus balticus\u003c/em\u003e \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e,\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe main economic activity in the region is Merino sheep ranching, primarily for the international wool market and sustained by grazing on natural grasslands \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. In Río Negro, Law 763/1972 (\u003cem\u003e\"Fight against populations of species circumstantially dangerous to livestock\"\u003c/em\u003e) provides state-funded incentives for the lethal control of pumas and culpeo foxes \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. The prey base is severely degraded, with the European hare (\u003cem\u003eLepus europaeus\u003c/em\u003e) dominating the available wild herbivore biomass, representing 89% of the total (Gáspero unpubl. data).\u003c/p\u003e\u003cp\u003eSampling units were selected based on a convenience criterion, considering landowners' willingness to participate and the availability of internal roads accessing sheep grazing areas. Fieldwork began during the 2015 lambing season (mid-October) on three ranches (A, B, and C), all of which exclusively employed lethal control of predators. In late winter 2016, ranch C incorporated four adult Livestock Guarding Dogs (LGD). Consequently, from the 2016 lambing season onward, the survey was expanded to include three additional ranches. From the 2016 lambing season to February 2018, ranches A, B, and F continued using only lethal control, while ranches C, D, and E adopted LGD as a predation mitigation strategy (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The total area covered by the six ranches encompassed 1,584 km².\u003c/p\u003e\u003cp\u003e\u003cem\u003eSheep Mortality Monitoring.\u003c/em\u003e\u003c/p\u003e\u003cp\u003eVehicular transects were conducted seasonally along internal ranch roads at speeds of 5–15 km/h, beginning 30 minutes after sunrise. During each transect, sheep carcasses were recorded, and necropsies were performed to determine the cause of death \u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e,\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. In total, 284 survey days were completed (A: 79; B: 67; C: 56; D: 31; E: 26; F: 25). Sheep were classified into four age categories according to tooth eruption patterns and seasonal timing: (i) Perinatal - stillborn fetuses and lambs up to seven days old; (ii) Lamb - individuals older than one week up to weaning; (iii) Yearling - from weaning to 18–20 months of age; and (iv) Adult, individuals older than 20 months.\u003c/p\u003e\u003cp\u003eBased on the nutritional and health assessments, predation events were classified into three categories: (i) Primary predation - sheep in good health and nutritional condition killed by predators; (ii) Secondary predation - predation on non-viable individuals that had died due to primary non-predation factors, such as malnutrition or disease; and (iii) Undetermined predation - cases where the pre-mortem condition could not be established (e.g., due to the consumption of vital organs by predators or scavengers). Non-viable individuals were defined as those exhibiting (a) poor nutritional condition or severe starvation and/or (b) visible signs of acute illness \u003csup\u003e\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cem\u003eSocio-environmental and management covariates.\u003c/em\u003e\u003c/p\u003e\u003cp\u003eWe estimated a set of covariates potentially associated with the occurrence of sheep mortality events based on carcass location data (e.g. distance to nearest urban centre or village as proxy for domestic dog predation; Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Field methods and general data processing are detailed in Supporting Information-A1.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDetails of explanatory covariates and their operational hierarchical level in model structure, used to assess their contribution to sheep mortality event probability and to explore the performance of lethal and non-lethal predation management strategies.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCovariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eID\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMetodology\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cem\u003eHierarchical level.\u003c/em\u003e Description\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSocio-environmental\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eElevation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eele\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGPS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cem\u003eIndividual carcass.\u003c/em\u003e Altitude of carcass location.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDistance to urban center\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003edist_centurb\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGIS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cem\u003eIndividual carcass.\u003c/em\u003e Carcass distance to nearest city or village borders.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNormalized Difference Vegetation Index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003endvi\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGIS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cem\u003eRanch.\u003c/em\u003e Mean NDVI of ranches during 2016–2017 season.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePuma kill site ruggedness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003epumaks_tri\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGIS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cem\u003eIndividual carcass.\u003c/em\u003e Mean Terrain Ruggedness Index (TRI; Riley et al., 1999) in a 4461 m diameter buffer around carcass location.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCulpeo kill site ruggedness\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eculpeoks_tri\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGIS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cem\u003eIndividual carcass.\u003c/em\u003e Mean TRI (Riley et al., 1999) in a 3337 m diameter buffer around carcass location.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePuma relative abundance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003epuma_rai\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePhoto-trapping \u0026amp; GIS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cem\u003eIndividual carcass.\u003c/em\u003e Puma relative abundance index (RAI) corresponding to nearest camera trap station to carcass location.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCulpeo relative abundance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eculpeo_rai\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePhoto-trapping \u0026amp; GIS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cem\u003eIndividual carcass.\u003c/em\u003e Culpeo fox RAI corresponding to nearest camera trap station to carcass location.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEuropean hare relative abundance\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003elepus_rai\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePhoto-trapping \u0026amp; GIS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cem\u003eIndividual carcass.\u003c/em\u003e European hare RAI corresponding to nearest camera trap station to carcass location.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWild herbivore availability\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ewh_biomass\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCRM \u0026amp; Distance Sampling\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cem\u003eRanch.\u003c/em\u003e Estimated annual prey items density multiplied by item body mass.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePredation management\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"1\" nameend=\"c5\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePuma hunting pressure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ehpress_puma\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eQuestionnaires\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cem\u003eRanch.\u003c/em\u003e (Number of pumas annually hunted in the ranch/ranch surface)*100 km\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCulpeo fox hunting pressure\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003ehpress_culpeo\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eQuestionnaires\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cem\u003eRanch.\u003c/em\u003e (Number of cupeo foxes annually hunted in the ranch/ranch surface)*100 km\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLivestock Guarding Dogs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u003cem\u003eLGD\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eQuestionnaires\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003e\u003cem\u003eRanch.\u003c/em\u003e (Number of LGD/ranch surface)*100 km\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eRegarding predation management, data were obtained through a brief questionnaire administered to ranch managers. All interviewees were informed about the survey objectives, and the questionnaire was conducted only after they orally provided infomed consent, in accordance with the Ethics Code for Ethnobiological Investigation in Latin America (SOLAE, 2016). Besides interview proceedings the study was assessed and approved by Comahue National University doctoral committee (Act N° 358/2021). The questionnaire gathered information on sheep stock, the number of pumas and culpeo foxes killed annually, and the number of LGDs working on each ranch.\u003c/p\u003e\u003cp\u003e\u003cem\u003eStatistical Analyses.\u003c/em\u003e\u003c/p\u003e\u003cp\u003eAll data analyses were performed in R (version 4.3.1)\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e. We built hierarchical Bayesian linear models to determine the main factors influencing sheep mortality events according to their diagnosis (i.e., diag). Models were created using the Stan computational framework (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://mc-stan.org/\u003c/span\u003e\u003cspan address=\"http://mc-stan.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) accessed via the \u003cem\u003ebrms\u003c/em\u003e package (version 2.19.0 \u003csup\u003e61\u003c/sup\u003e). The subset included 76 sheep deaths corresponding to 43 mortality events recorded during the 2016–2017 season. Prior to modelling, we assessed correlations between covariates and excluded highly correlated ones (i.e., when |r| ≥ 0.6). To account for non-independence of deaths within the same mortality event (i.e., surplus killing), we included a \u003cem\u003e(1|event)\u003c/em\u003e term in the models. Similarly, a \u003cem\u003e(1|ranch)\u003c/em\u003e term was added to account for fixed effects related to predation management practices (i.e., LGD use and hunting pressure) and other uncontrolled variables such as ranch location with respect to rainfall gradient, primary productivity, and general livestock management.\u003c/p\u003e\u003cp\u003eWe proposed a set of models incorporating different covariates to explain the probability of mortality events due to puma, culpeo fox, and domestic dog predation, the Starvation-Hypothermia Complex (SHC), which also includes immersion and dystocia, and undetermined diagnoses. We included socio-environmental covariates operating at the individual carcass level and predation management practices at the ranch level (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Model comparisons included Zero-Inflated Poisson (ZIP) and Poisson models with nested and non-nested factors. Models were run for 4,000 iterations with a warm-up of 500 iterations. We set adapt Δ to 0.95 to avoid divergent transitions. Models were fitted with non-informative priors, and chain convergence was assessed using the Rhat statistic (all Rhat \u0026lt; 1.1). Homoscedasticity and normality assumptions of the posterior distribution were analyzed using the Dharma package (version 0.4.6; Hartig, 2019) through QQ-plot residual inspection, residual vs. predicted KS test, and within-group deviation analysis. A nonparametric dispersion test was conducted using the “testDispersion” function from the Dharma package. The best-fit model was selected based on wAIC. Models were evaluated using Bayesian Expected Logarithmic Predictive Density differences (Δ ELPD), with models having Δ ELPD \u0026lt; -2 points relative to the highest-ranked model being considered. Socio-environmental and management covariate effects were deemed significant if their 95% Credibility Interval (CI) did not include zero under the best-fit models.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eP. G. led all stages of the research; G. de la V. contributed significantly to data curation, statistical analysis and results interpretation; J. T., V. F-A. and J. P. were consistently involved during experimental design, sampling, and manuscript writing. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the ranch owners and workers for their collaboration, as well as A. di Virgilio, I. Barber\u0026aacute;, J.A. Kusanovich, J.M. Garramu\u0026ntilde;o and F. Bidinost. We also acknowledge institutional support from the \u0026nbsp; Ministry for the Environment and Spatial Planning of the Regional Government of Andalusia (Consejer\u0026iacute;a de Medio Ambiente y Ordenaci\u0026oacute;n del Territorio de la Junta de Andaluc\u0026iacute;a).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eP.G. discloses support for the research of this work from Instituto Nacional de Tecnolog\u0026iacute;a Agropecuaria [INTA-PE I037 and INTA-PD I096] and IdeaWild Foundation [GASPARGE0715-00].\u0026nbsp;\u003cbr\u003e\u0026nbsp;The authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement:\u003c/strong\u003e All data generated or analysed during this study are included in this published article as Supplementary Information files [SuppInf_A2.xlsx and SuppInf_A3.xlsx].\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eCarter, N. H. \u0026amp; Linnell, J. D. C. C. Co-Adaptation Is Key to Coexisting with Large Carnivores. \u003cem\u003eTrends Ecol Evol\u003c/em\u003e \u003cstrong\u003e31\u003c/strong\u003e, 575\u0026ndash;578 (2016).\u003c/li\u003e\n\u003cli\u003eMiller, J. R. B. \u0026amp; Schmitz, O. J. Landscape of fear and human-predator coexistence: Applying spatial predator-prey interaction theory to understand and reduce carnivore-livestock conflict. \u003cem\u003eBiol Conserv\u003c/em\u003e \u003cstrong\u003e236\u003c/strong\u003e, 464\u0026ndash;473 (2019).\u003c/li\u003e\n\u003cli\u003eDorresteijn, I. \u003cem\u003eet al.\u003c/em\u003e Incorporating anthropogenic effects into trophic ecology: Predator - Prey interactions in a human-dominated landscape. \u003cem\u003eProceedings of the Royal Society B: Biological Sciences\u003c/em\u003e \u003cstrong\u003e282\u003c/strong\u003e, (2015).\u003c/li\u003e\n\u003cli\u003eOrdiz, A., Bischof, R. \u0026amp; Swenson, J. E. Saving large carnivores, but losing the apex predator? \u003cem\u003eBiol Conserv\u003c/em\u003e \u003cstrong\u003e168\u003c/strong\u003e, 128\u0026ndash;133 (2013).\u003c/li\u003e\n\u003cli\u003eRipple, W. J. \u003cem\u003eet al.\u003c/em\u003e Status and ecological effects of the world\u0026rsquo;s largest carnivores. \u003cem\u003eScience (1979)\u003c/em\u003e \u003cstrong\u003e343\u003c/strong\u003e, (2014).\u003c/li\u003e\n\u003cli\u003eMinin, E. Di \u003cem\u003eet al.\u003c/em\u003e Global priorities for national carnivore conservation under land use change. \u003cem\u003eSci Rep\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 1\u0026ndash;9 (2016).\u003c/li\u003e\n\u003cli\u003eVan Eeden, L. M. \u003cem\u003eet al.\u003c/em\u003e Managing conflict between large carnivores and livestock. \u003cem\u003eConservation Biology\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 26\u0026ndash;34 (2018).\u003c/li\u003e\n\u003cli\u003eDickman, A. J. Complexities of conflict: The importance of considering social factors for effectively resolving human-wildlife conflict. \u003cem\u003eAnim Conserv\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 458\u0026ndash;466 (2010).\u003c/li\u003e\n\u003cli\u003eBerger, K. M. Carnivore-livestock conflicts: Effects of subsidized predator control and economic correlates on the sheep industry. \u003cem\u003eConservation Biology\u003c/em\u003e \u003cstrong\u003e20\u003c/strong\u003e, 751\u0026ndash;761 (2006).\u003c/li\u003e\n\u003cli\u003eRedpath, S. M. \u003cem\u003eet al.\u003c/em\u003e Don\u0026rsquo;t forget to look down \u0026ndash; collaborative approaches to predator conservation. \u003cem\u003eBiological Reviews\u003c/em\u003e \u003cstrong\u003e92\u003c/strong\u003e, 2157\u0026ndash;2163 (2017).\u003c/li\u003e\n\u003cli\u003eMarchini, S. \u003cem\u003eet al.\u003c/em\u003e Planning for human-wildlife coexistence: conceptual framework, workshop process and a model for transdisciplinary collaboration. \u003cem\u003eFrontiers in Conservation Science\u003c/em\u003e \u003cstrong\u003e2\u003c/strong\u003e, 11 (2021).\u003c/li\u003e\n\u003cli\u003eG\u0026aacute;spero, P. G. \u003cem\u003eet al.\u003c/em\u003e Human-carnivore interaction in a context of socio-productive crisis: Assessing smallholder strategies for reducing predation in North-west Patagonia, Argentina. \u003cem\u003eJ Arid Environ\u003c/em\u003e \u003cstrong\u003e150\u003c/strong\u003e, 92\u0026ndash;98 (2018).\u003c/li\u003e\n\u003cli\u003eTaylor, J., N\u0026uacute;\u0026ntilde;ez, P., G\u0026aacute;spero, P., Pooley, S. \u0026amp; Fernandez-Arhex, V. Comparing narratives on carnivore management in a dryland ecosystem: a case study of state-backed lethal control. \u003cem\u003eRangeland Journal\u003c/em\u003e \u003cstrong\u003e45\u003c/strong\u003e, 45\u0026ndash;52 (2023).\u003c/li\u003e\n\u003cli\u003eTreves, A., Krofel, M. \u0026amp; Mcmanus, J. Predator control should not be a shot in the dark. \u003cem\u003eFront Ecol Environ\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 380\u0026ndash;388 (2016).\u003c/li\u003e\n\u003cli\u003ePeebles, K. A., Wielgus, R. B., Maletzke, B. T. \u0026amp; Swanson, M. E. Effects of remedial sport hunting on cougar complaints and livestock depredations. \u003cem\u003ePLoS One\u003c/em\u003e \u003cstrong\u003e8\u003c/strong\u003e, 1\u0026ndash;8 (2013).\u003c/li\u003e\n\u003cli\u003eRigg, R. \u003cem\u003eet al.\u003c/em\u003e Mitigating carnivore-livestock conflict in Europe: Lessons from Slovakia. \u003cem\u003eOryx\u003c/em\u003e \u003cstrong\u003e45\u003c/strong\u003e, 272\u0026ndash;280 (2011).\u003c/li\u003e\n\u003cli\u003eOhrens, O., Lagos, N., Yovovich, V. \u0026amp; Elbroch, M. A Call for Research on Reducing Livestock-Mountain Lion Conflict. \u003cem\u003eCanadian Wildlife Biology and Management\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 111\u0026ndash;119 (2024).\u003c/li\u003e\n\u003cli\u003eEklund, A., Johansson, M., Flykt, A., Andr\u0026eacute;n, H. \u0026amp; Frank, J. Drivers of intervention use to protect domestic animals from large carnivore attacks. \u003cem\u003eHuman Dimensions of Wildlife\u003c/em\u003e \u003cstrong\u003e25\u003c/strong\u003e, 339\u0026ndash;354 (2020).\u003c/li\u003e\n\u003cli\u003eD\u0026iacute;az-Ruiz, F. \u003cem\u003eet al.\u003c/em\u003e Inferring species interactions from long-term monitoring programs: Carnivores in a protected area from southern Patagonia. \u003cem\u003eDiversity (Basel)\u003c/em\u003e \u003cstrong\u003e12\u003c/strong\u003e, 1\u0026ndash;17 (2020).\u003c/li\u003e\n\u003cli\u003eWalker, S. R. \u0026amp; Novaro, A. J. The World\u0026rsquo;s Southernmost Pumas in Patagonia and the Southern Andes. in \u003cem\u003eCougar: Ecology and Conservation\u003c/em\u003e (eds. Hornocker, M. G. \u0026amp; Negri, S.) 91\u0026ndash;100 (The University of Chicago Press, Chicago, US, 2010).\u003c/li\u003e\n\u003cli\u003ePalacios, R., Walker, R. S. \u0026amp; Novaro, A. J. Differences in diet and trophic interactions of Patagonian carnivores between areas with mostly native or exotic prey. \u003cem\u003eMammalian Biology\u003c/em\u003e \u003cstrong\u003e77\u003c/strong\u003e, 183\u0026ndash;189 (2012).\u003c/li\u003e\n\u003cli\u003eEasdale, M. H., Sacchero, D., Vigna, M. \u0026amp; Willems, P. Assessing the magnitude of impact of volcanic ash deposits on Merino wool production and fibre traits in the context of a drought in North-west Patagonia, Argentina. \u003cem\u003eRangeland Journal\u003c/em\u003e \u003cstrong\u003e36\u003c/strong\u003e, 143\u0026ndash;149 (2014).\u003c/li\u003e\n\u003cli\u003eWilson, T. \u003cem\u003eet al.\u003c/em\u003e Short- and long-term evacuation of people and livestock during a volcanic crisis: Lessons from the 1991 eruption of Volc\u0026aacute;n Hudson, Chile. \u003cem\u003eJournal of Applied Volcanology\u003c/em\u003e \u003cstrong\u003e1\u003c/strong\u003e, (2012).\u003c/li\u003e\n\u003cli\u003ePauli, J. N., Donadio, E. \u0026amp; Lambertucci, S. A. The corrupted carnivore: how humans are rearranging the return of the carnivore-scavenger relationship. \u003cem\u003eEcology\u003c/em\u003e \u003cstrong\u003e99\u003c/strong\u003e, 2122\u0026ndash;2124 (2018).\u003c/li\u003e\n\u003cli\u003eBellati, J. \u0026amp; Von Thungen, J. LAMB PREDATION IN PATAGONIAN RANCHES. in \u003cem\u003eProceedings of the 14th Vertebrate Pest Conference\u003c/em\u003e 3\u0026ndash;9 (1990).\u003c/li\u003e\n\u003cli\u003eKlebenow, D. A. \u0026amp; McAdoo, K. Predation on Domestic Sheep in Northeastern Nevada. \u003cem\u003eJournal of Range Management\u003c/em\u003e \u003cstrong\u003e29\u003c/strong\u003e, 96 (1976).\u003c/li\u003e\n\u003cli\u003eMysterud, Ivar. \u0026amp; Warren, J. T. Brown Bear Predation on Domestic Sheep Registered with Mortality Transmitters. in \u003cem\u003eNinth International Conference on Bear Research and Management\u003c/em\u003e vol. 9 107\u0026ndash;111 (1992).\u003c/li\u003e\n\u003cli\u003ePalmer, B. C., Conover, M. R. \u0026amp; Frey, S. N. Replication of a 1970s study on domestic sheep losses to predators on Utah\u0026rsquo;s summer rangelands. \u003cem\u003eRangel Ecol Manag\u003c/em\u003e \u003cstrong\u003e63\u003c/strong\u003e, 689\u0026ndash;695 (2010).\u003c/li\u003e\n\u003cli\u003eWarren, J. T., Mysterud, I. \u0026amp; Lynnebakken, T. Mortality of lambs in free-ranging domestic sheep (Ovis aries) in northern Norway. \u003cem\u003eJ Zool\u003c/em\u003e \u003cstrong\u003e254\u003c/strong\u003e, 195\u0026ndash;202 (2001).\u003c/li\u003e\n\u003cli\u003eOhrens, O., Treves, A. \u0026amp; Bonacic, C. Relationship between rural depopulation and puma-human conflict in the high Andes of Chile. \u003cem\u003eEnviron Conserv\u003c/em\u003e \u003cstrong\u003e43\u003c/strong\u003e, 24\u0026ndash;33 (2016).\u003c/li\u003e\n\u003cli\u003eMoberly, R. L., White, P. C. L. L., Webbon, C. C., Baker, P. J. \u0026amp; Harris, S. Modelling the costs of fox predation and preventive measures on sheep farms in Britain. \u003cem\u003eJ Environ Manage\u003c/em\u003e \u003cstrong\u003e70\u003c/strong\u003e, 129\u0026ndash;143 (2004).\u003c/li\u003e\n\u003cli\u003eTallian, A. \u003cem\u003eet al.\u003c/em\u003e Large carnivore conservation and traditional pastoralism: A case study on bear\u0026ndash;reindeer predation mitigation measures. \u003cem\u003eEcosphere\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, (2023).\u003c/li\u003e\n\u003cli\u003eSacks, B. N., Jaeger, M. M., Neale, J. C. C. \u0026amp; Mccullough, D. R. TERRITORIALITY AND BREEDING STATUS OF COYOTES RELATIVE TO SHEEP PREDATION. \u003cstrong\u003e63\u003c/strong\u003e, 593\u0026ndash;605 (2007).\u003c/li\u003e\n\u003cli\u003eElmhagen, B. \u0026amp; Rushton, S. Trophic control of mesopredators in terrestrial ecosystems: top-down or bottom-up? Volume 10 Issue 3 Page 197 . \u003cem\u003eEcol Lett\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 197 (2007).\u003c/li\u003e\n\u003cli\u003ePrugh, L. R. \u003cem\u003eet al.\u003c/em\u003e The rise of the mesopredator. \u003cem\u003eBioscience\u003c/em\u003e \u003cstrong\u003e59\u003c/strong\u003e, 779\u0026ndash;791 (2009).\u003c/li\u003e\n\u003cli\u003eNovaro, A. J., Funes, M. C. \u0026amp; Jim\u0026eacute;nez, J. E. Patagonian foxes: Selection for introduced prey and conservation of culpeo and chilla foxes in Patagonia. in \u003cem\u003eBiology and conservation of wild canids\u003c/em\u003e (eds. Macdonald, D. W. \u0026amp; Sillero-Zubiri, C.) 243\u0026ndash;254 (Oxford University Press, New York, US, 2004). doi:10.1007/s13398-014-0173-7.2.\u003c/li\u003e\n\u003cli\u003eStoddart, L. C., Griffiths, R. E. \u0026amp; Knowlton, F. F. Coyote responses to changing jackrabbit abundance affect sheep predation. \u003cem\u003eJournal of Range Management\u003c/em\u003e \u003cstrong\u003e54\u003c/strong\u003e, 15\u0026ndash;20 (2001).\u003c/li\u003e\n\u003cli\u003eKamler, J. F., Klare, U. \u0026amp; Macdonald, D. W. Seasonal diet and prey selection of black-backed jackals on a small-livestock farm in South Africa. \u003cem\u003eAfr J Ecol\u003c/em\u003e \u003cstrong\u003e50\u003c/strong\u003e, 299\u0026ndash;307 (2012).\u003c/li\u003e\n\u003cli\u003eElmhagen, B. \u0026amp; Rushton, S. P. Trophic control of mesopredators in terrestrial ecosystems: Top-down or bottom-up? \u003cem\u003eEcol Lett\u003c/em\u003e \u003cstrong\u003e10\u003c/strong\u003e, 197\u0026ndash;206 (2007).\u003c/li\u003e\n\u003cli\u003eElbroch, L. M. \u0026amp; Kusler, A. Are pumas subordinate carnivores, and does it matter? \u003cem\u003ePeerJ\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, e4293 (2018).\u003c/li\u003e\n\u003cli\u003eElbroch, L. M. \u0026amp; Wittmer, H. U. Puma spatial ecology in open habitats with aggregate prey. \u003cem\u003eMammalian Biology\u003c/em\u003e \u003cstrong\u003e77\u003c/strong\u003e, 377\u0026ndash;384 (2012).\u003c/li\u003e\n\u003cli\u003eOrdiz, A. \u003cem\u003eet al.\u003c/em\u003e Do bears know they are being hunted? \u003cem\u003eBiol Conserv\u003c/em\u003e \u003cstrong\u003e152\u003c/strong\u003e, 21\u0026ndash;28 (2012).\u003c/li\u003e\n\u003cli\u003ePia, M. V., Renison, D., Mangeaud, A., De Angelo, C. \u0026amp; Haro, J. G. Occurrence of top carnivores in relation to land protection status, human settlements and rock outcrops in the high mountains of central Argentina. \u003cem\u003eJ Arid Environ\u003c/em\u003e \u003cstrong\u003e91\u003c/strong\u003e, 31\u0026ndash;37 (2013).\u003c/li\u003e\n\u003cli\u003eSt\u0026oslash;en, O. G. \u003cem\u003eet al.\u003c/em\u003e Physiological evidence for a human-induced landscape of fear in brown bears (Ursus arctos). \u003cem\u003ePhysiol Behav\u003c/em\u003e \u003cstrong\u003e152\u003c/strong\u003e, 244\u0026ndash;248 (2015).\u003c/li\u003e\n\u003cli\u003eBarcel\u0026oacute;, G., Donadio, E., Alldredge, M. W. \u0026amp; Pauli, J. N. Human disturbance alters the foraging and spatiotemporal activity of a large carnivore. \u003cem\u003eOecologia\u003c/em\u003e \u003cstrong\u003e207\u003c/strong\u003e, 112 (2025).\u003c/li\u003e\n\u003cli\u003eElbroch, L. M. \u0026amp; Wittmer, H. U. The effects of puma prey selection and specialization on less abundant prey in Patagonia. \u003cem\u003eJ Mammal\u003c/em\u003e \u003cstrong\u003e94\u003c/strong\u003e, 259\u0026ndash;268 (2013).\u003c/li\u003e\n\u003cli\u003eLucherini, M., Guerisoli, M. de las M. \u0026amp; Luengos Vidal, E. M. Surplus killing by pumas Puma concolor: rumours and facts. \u003cem\u003eMamm Rev\u003c/em\u003e \u003cstrong\u003e48\u003c/strong\u003e, 277\u0026ndash;283 (2018).\u003c/li\u003e\n\u003cli\u003eSwan, G. J. F., Redpath, S. M., Bearhop, S. \u0026amp; McDonald, R. A. Ecology of Problem Individuals and the Efficacy of Selective Wildlife Management. \u003cem\u003eTrends Ecol Evol\u003c/em\u003e \u003cstrong\u003e32\u003c/strong\u003e, 518\u0026ndash;530 (2017).\u003c/li\u003e\n\u003cli\u003eRobinson, H. S., Wielgus, R. B., Cooley, H. S. \u0026amp; Cooley, S. W. Population SINK POPULATIONS IN CARNIVORE MANAGEMENT : COUGAR. \u003cstrong\u003e18\u003c/strong\u003e, 1028\u0026ndash;1037 (2013).\u003c/li\u003e\n\u003cli\u003eVan Bommel, L. \u0026amp; Johnson, L. Olfactory communication to protect livestock : dingo response to urine marks of livestock guardian dogs. 219\u0026ndash;226 (2017).\u003c/li\u003e\n\u003cli\u003eVan Bommel, L. \u0026amp; Johnson, C. N. Livestock guardian dogs as surrogate top predators? How Maremma sheepdogs affect a wildlife community. \u003cem\u003eEcol Evol\u003c/em\u003e \u003cstrong\u003e6\u003c/strong\u003e, 6702\u0026ndash;6711 (2016).\u003c/li\u003e\n\u003cli\u003eGehring, T. M., VerCauteren, K. C. \u0026amp; Landry, J.-M. Livestock Protection Dogs in the 21st Century: Is an Ancient Tool Relevant to Modern Conservation Challenges? \u003cem\u003eBioscience\u003c/em\u003e \u003cstrong\u003e60\u003c/strong\u003e, 299\u0026ndash;308 (2010).\u003c/li\u003e\n\u003cli\u003eKinka, D. \u0026amp; Young, J. K. Evaluating Domestic Sheep Survival with Different Breeds of Livestock Guardian Dogs. \u003cem\u003eRangel Ecol Manag\u003c/em\u003e (2019) doi:10.1016/j.rama.2019.07.002.\u003c/li\u003e\n\u003cli\u003eLambertucci, S. A., Zamora-Nasca, L. B., Segpunta, A., de la Reta, M. \u0026amp; Plaza, P. Evidence-based legislation, strong institutions and consensus needed to mitigate the negative impacts of free-ranging dogs. \u003cem\u003eAmbio\u003c/em\u003e \u003cstrong\u003e53\u003c/strong\u003e, 299\u0026ndash;308 (2024).\u003c/li\u003e\n\u003cli\u003eGait\u0026aacute;n, J. J., Bran, D. E. \u0026amp; Oliva, G. E. Patagonian Desert. in \u003cem\u003eReference Module in Earth Systems and Environmental Sciences\u003c/em\u003e 1\u0026ndash;18 (Elsevier, 2019). doi:10.1016/B978-0-12-409548-9.11929-3.\u003c/li\u003e\n\u003cli\u003eGait\u0026aacute;n, J. J. \u003cem\u003eet al.\u003c/em\u003e Aridity and Overgrazing Have Convergent Effects on Ecosystem Structure and Functioning in Patagonian Rangelands. \u003cem\u003eLand Degrad Dev\u003c/em\u003e \u003cstrong\u003e29\u003c/strong\u003e, 210\u0026ndash;218 (2018).\u003c/li\u003e\n\u003cli\u003eMcFarlane, D. Perinatal lamb losses. An autopsy method for the investigation of perinatal losses. \u003cem\u003eNew Zeland Veterinary Journal\u003c/em\u003e \u003cstrong\u003e13\u003c/strong\u003e, 116\u0026ndash;135 (1965).\u003c/li\u003e\n\u003cli\u003eAcorn, R. \u0026amp; Dorrance, M. \u003cem\u003eMETHODS OF INVESTIGATING PREDATION OF LIVESTOCK\u003c/em\u003e. (Alberta Agriculture and Rural Development, Edmonton, Canada, 2014).\u003c/li\u003e\n\u003cli\u003eSOLAE. C\u0026oacute;digo de \u0026Eacute;tica para la investigaci\u0026oacute;n, la investigaci\u0026oacute;n-acci\u0026oacute;n y la colaboraci\u0026oacute;n etnocient\u0026iacute;fica en Am\u0026eacute;rica Latina. \u003cem\u003eEtnobiolog\u0026iacute;a\u003c/em\u003e \u003cstrong\u003e1\u003c/strong\u003e, 1\u0026ndash;34 (2016).\u003c/li\u003e\n\u003cli\u003eR Core Team. R: A language and environment for statistical computing. Preprint at https://www.r-project.org/ (2020).\u003c/li\u003e\n\u003cli\u003eB\u0026uuml;rkner, P. C. brms: An R package for Bayesian multilevel models using Stan. \u003cem\u003eJ Stat Softw\u003c/em\u003e \u003cstrong\u003e80\u003c/strong\u003e, (2017).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Landscapes of coexistence, Human-Carnivore conflicts, Livestock Guarding Dogs, Lethal Control, Human-dominated landscapes, Human-induced trophic cascades, Fear ecology","lastPublishedDoi":"10.21203/rs.3.rs-7234506/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7234506/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003ePredation is a key ecological process but reconciling it with the socio-economic role of livestock in rural regions remains a challenge. Human-dominated landscapes exhibit profound disruptions in the functionality of ecological processes, influencing performances of predation mitigation measures. The aim of this study was to investigate sheep mortality patterns under extensive management conditions in Patagonia, to determine the impact of pumas (\u003cem\u003ePuma concolor\u003c/em\u003e) and culpeo foxes (\u003cem\u003eLycalopex culpaeus\u003c/em\u003e) and assess the influence of socio-environmental and management factors (state-subsidized lethal control and Livestock Guarding Dogs -LGD-) on the probability of sheep deaths. We monitored sheep mortality across six commercial ranches (covering 1,500 km\u0026sup2; and 61,000 sheep), and socio-environmental and management covariates. We used hierarchical Bayesian models to evaluate covariates operating on sheep deaths occurrence probability. We performed 139 necropsies, where pumas, culpeo foxes, and domestic dogs (\u003cem\u003eCanis lupus familiaris\u003c/em\u003e) were responsible for 25.9%, 22.3%, and 21.6% of recorded deaths, respectively. Statistical analyses revealed that (i) LGD significantly reduced the probability of puma predation on sheep, and (ii) the likelihood of sheep predation by culpeo foxes was directly influenced by fox relative abundance and inversely by prey biomass availability. We recommend moving beyond reductionist policies, allocating resources to promote responsible LGD implementation.\u003c/p\u003e","manuscriptTitle":"Pumas, culpeo foxes, bad and good dogs. Assessing strategies to mitigate predation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-03 06:06:27","doi":"10.21203/rs.3.rs-7234506/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9298222c-3c15-407f-8098-8260906dbd44","owner":[],"postedDate":"September 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":53693126,"name":"Biological sciences/Ecology"},{"id":53693127,"name":"Earth and environmental sciences/Ecology"},{"id":53693128,"name":"Biological sciences/Zoology"}],"tags":[],"updatedAt":"2025-09-30T11:38:45+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-03 06:06:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7234506","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7234506","identity":"rs-7234506","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}