Influence of Predator Harvest, Biological Factors, and Landscape on Elk Calf Survival in Idaho

Abstract

We evaluated survival of elk (Cervus elaphus) calves on 2 contrasting study areas in north‐central Idaho, USA, from 1997 to 2004. Recruitment was modest (>30 calves:100 F [calves of either sex: F elk 1 yr old]) and stable on the South Fork study area and low (<20 calves:100 F) and declining on the Lochsa study area. The primary proximate cause of calf mortality on both study areas was predation by black bears (Ursus americanus) and mountain lions (Puma concolor). We experimentally manipulated populations of black bears and mountain lions on a portion of each study area. Black bear harvest (harvest density/600km2) initially doubled on the Lochsa treatment after manipulating season bag limits. Mountain lion harvest also increased by 60% but varied widely during the manipulation period. Harvest seasons were closed for black bears and mountain lions on the treatment portion of the South Fork study area. Using the Andersen—Gill formulation (A‐G) of the Cox proportional hazards model, we examined effects of landscape structure, predator harvest levels, and biological factors on summer calf survival. We used Akaike's Information Criterion (AICc) and multimodel inference to assess some potentially useful predictive factors relative to calf survival. We generated risk ratios for both the best models and for model‐averaged coefficients. Our models predicted that calf survival was influenced by biological factors, landscape surrounding calf locations, and predator harvest levels. The model that best explained mortality risk to calves on the Lochsa included black bear harvest (harvest density/600 km2), estimated birth mass of calves, and percentage of shrub cover surrounding calf locations. Incorporating a shrub X time interaction allowed us to correct for nonproportionality and detect that effect of shrub cover was only influential during the first 14 days of a calf's life. Model‐averaging indicated that estimated birth mass of calves and black bear harvest were twice as important as the next variables, but age of calves at capture was also influential in calf survival. The model that best explained mortality risk to calves on the South Fork included black bear harvest, age of calves at capture, and gender of calves. Model‐averaging indicated that age at capture and black bear harvest were twice as important as the next variable, forest with 33–66% canopy cover (Canopy 33–66). Risk to calves decreased when calves occupied areas with more of this forest cover type. Model‐averaging also indicated that increased mountain lion harvest lowered calf mortality risk 4% for every 1‐unit increase in lion harvest (harvest density/600 km2) but was lower (<25%) in importance compared to age at capture and black bear harvest. Our results suggest that levels of predator harvest, and presumably predator density, resource limitations expressed through calf birth mass, and habitat structure had substantial effects on calf survival. Our results can be generalized to other areas where managers are dealing with low calf elk recruitmen...

Effects of black bear relocation on elk calf recruitment at Great Smoky Mountains National Park

“…In contrast, we detected a strong relationship between calf recruitment and the number of bears relocated annually, which would be unaffected by such biases. Our findings are consistent with other manipulative studies on elk calf predation by black bears in the western United States (Schlegel 1986, White et al 2010), though our study lacked randomization and a control necessary to demonstrate a strict causal relationship.…”

“…Raithel et al (2007) used life‐stage simulation analysis to show that annual variation in calf survival may be the dominant influence on short‐term variation in elk population growth. Bears are efficient predators of neonatal ungulates, particularly when hiding cover is limited (Gunther and Renkin 1990, Mattson 1997, Vreeland et al 2004, Onorato et al 2006, White et al 2010). The elk releases and most known birth sites (24 of 32 births) from 2001 to 2005 occurred in Cataloochee Valley, North Carolina, USA, in the southeastern section of GSMNP (Murrow 2007).…”

“…Alternatively, temporary predator relocation has been suggested as a means of increasing populations of reintroduced species (McKinney et al 2006) and bear relocations have proven successful in reducing predation rates on livestock (Armistead et al 1994, Linnell et al 1997). White et al (2010) found that bear population reductions through sport hunting were effective at increasing elk calf survival, especially the first 14 days postpartum when calves were most vulnerable.…”

The late-denning activities of the American black bear in Utah

“…Researchers have also found evidence that black bears may negatively affect recruitment of calves in a reintroduced population of elk in the eastern U.S. (Yarkovich et al 2011), but research has also suggested that predation appears to have a larger affect at lower ungulate densities (Zagar and Beechum 2006). In Idaho, elk calf survival seemed to be influenced by birth weight, habitat structure, and black bear and cougar harvest (presumably in relation to their respective densities); calf mortality through predation by black bears was described as additive (i.e., in addition to, rather than replacing, other sources), and the authors suggested that a spring bear season may be effective for improving calf survival (White et al 2010). The actual significance of predation of ungulates by black bears is likely dependent on a complex relationship involving bear densities, ungulate densities, presence and densities of other predators, weather conditions, and alternate food availability (e.g., Beechum 2006, Griffin et al 2011).…”

Effects of Maternal Nutrition, Resource Use and Multi-Predator Risk on Neonatal White-Tailed Deer Survival

“…Neonatal mortality in ungulates is sensitive to variation in numerous biological and environmental factors [6], but especially body condition at birth [2], [3], [7], limiting resources (e.g., hiding vegetation; [8], [9]), and predation [10]. These factors are often interrelated and affect survival directly through predation or indirectly through resource use and maternal nutritional effects, which can influence neonate body growth and consequently survival [11], [12], [13].…”