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Ripple, W. J., & Beschta, R. L. (2012). Trophic cascades in Yellowstone: The first 15 years after wolf reintroduction. Biol Conserv, 145.
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Apollonio, M., Mattioli, L., Scandura, M., Mauri, L., Gazzola, A., & Avanzinelli, E. (2004). Wolves in the Casentinesi Forests: insights for wolf conservation in Italy from a protected area with a rich wild prey community. Biol Conserv, 120.
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Dugnol, B., Fernández, C., Galiano, G., & Velasco, J. (2007). Implementation of a diffusive differential reassignment method for signal enhancement: An application to wolf population counting. Appl Math Comput, 193.
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Dugnol, B., Fernández, C., & Galiano, G. (2007). Wolf population counting by spectrogram image processing. Appl Math Comput, 186.
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Fritts, S. H., Bangs, E. E., & Gore, J. F. (1994). The relationship of wolf recovery to habitat conservation and biodiversity in the northwestern United States. Landsc Urban Plan, 28.
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Plumer, L., Talvi, T., Männil, P., & Saarma, U. (2018). Assessing the roles of wolves and dogs in livestock predation with suggestions for mitigating human-wildlife conflict and conservation of wolves. Conservat. Genet., 19(3), 665–672.
Abstract: Predation on livestock is a cause of serious and long-lasting conflict between farmers and wildlife, promoting negative public attitudes and endangering conservation of large carnivores. However, while large carnivores, especially the grey wolf (Canis lupus), are often blamed for killing sheep and other farm animals, free-ranging dogs may also act as predators. To develop appropriate measures for livestock protection, reliable methods for identifying predator species are critical. Identification of predators from visual examination of livestock wounds can be ambiguous and genetic analysis is strongly preferable for accurate species determination. To estimate the proportion of wolves and dogs implicated in sheep predation, we developed a sensitive genetic assay to distinguish between wolves and domestic dogs. A total of 183 predator saliva samples collected from killed sheep in Estonia were analysed. The assay identified the predator species in 143 cases (78%). Sheep were most often killed by wolves (81%); however, predation by dogs was substantial (15%). We compared the molecular results with field observations conducted by local environmental officials and recorded some disagreement, with the latter underestimating the role of dogs. As predator saliva samples collected from prey are often of poor quality, we suggest using mitochondrial DNA as a primary tool to maximise the number of successfully analysed samples. We also suggest adopting forensic DNA analysis more widely in livestock predation assessments as a legislative measure since misidentification that is biased against wolves can be counterproductive for conservation by enhancing conflict with society and leading to increased culling and poaching.
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Mori, E., Benatti, L., Lovari, S., & Ferretti, F. (2016). What does the wild boar mean to the wolf? European Journal of Wildlife Research, 63(1), 9.
Abstract: Generalist predators are expected to shape their diets according to the local availability of prey species. In turn, the extent of consumption of a prey would be influenced by the number of alternative prey species. We have tested this prediction by considering the wild boar and the grey wolf: two widespread species whose distribution ranges overlap largely in Southern Europe, e.g. in Italy. We have reviewed 16 studies from a total of 21 study areas, to assess whether the absolute frequency of occurrence of wild boar in the wolf diet was influenced by (i) occurrence of the other ungulate species in diet and (ii) the number of available ungulate species. Wild boar turned out to be the main prey of the wolf (49% occurrence, on average), followed by roe deer (24%) and livestock (18%). Occurrence of wild boar in the wolf diet decreased with increasing usage of roe deer, livestock, and to a lower extent, chamois and red deer. The number of prey species did not influence the occurrence of wild boar in the wolf diet. The wild boar is a gregarious, noisy and often locally abundant ungulate, thus easily detectable, to a predator. In turn, the extent of predation on this ungulate may not be influenced so much by the availability of other potential prey. Heavy artificial reductions of wild boar numbers, e.g. through numerical control, may concentrate predation by wolves on alternative prey (e.g. roe deer) and/or livestock, thus increasing conflicts with human activities.
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Iliopoulos, Y., Youlatos, D., & Sgardelis, S. (2013). Wolf pack rendezvous site selection in Greece is mainly affected by anthropogenic landscape features. Eur J Wildl Res, 60.
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Galaverni, M., Palumbo, D., Fabbri, E., Caniglia, R., Greco, C., & Randi, E. (2012). Monitoring wolves (Canis lupus) by non-invasive genetics and camera trapping: A small-scale pilot study. Eur J Wildl Res, 58.
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Gholib, G., Heistermann, M., Agil, M., Supriatna, I., Purwantara, B., Nugraha, T. P., et al. (2018). Comparison of fecal preservation and extraction methods for steroid hormone metabolite analysis in wild crested macaques. Primates, 59(3), 281–292.
Abstract: Since the non-invasive field endocrinology techniques were developed, several fecal preservation and extraction methods have been established for a variety of species. However, direct adaptation of methods from previous studies for use in crested macaques should be taken with caution. We conducted an experiment to assess the accuracy and stability of fecal estrogen metabolite (E1C) and glucocorticoid metabolite (GCM) concentrations in response to several preservation parameters: (1) time lag between sample collection and fecal preservation; (2) long-term storage of fecal samples in 80% methanol (MeOH) at ambient temperature; (3) different degrees of feces drying temperature using a conventional oven; and (4) different fecal preservation techniques (i.e., freeze-drying, oven-drying, and field-friendly extraction method) and extraction solvents (methanol, ethanol, and commercial alcohol). The study used fecal samples collected from crested macaques (Macaca nigra) living in the Tangkoko Reserve, North Sulawesi, Indonesia. Samples were assayed using validated E1C and GCM enzyme immunoassays. Concentrations of E1C and GCM in unprocessed feces stored at ambient temperature remained stable for up to 8 h of storage after which concentrations of both E1C and GCM changed significantly compared to controls extracted at time 0. Long-term storage in 80% MeOH at ambient temperature affected hormone concentrations significantly with concentrations of both E1C and GCM increasing after 6 and 4 months of storage, respectively. Drying fecal samples using a conventional oven at 50, 70, and 90 °C did not affect the E1C concentrations, but led to a significant decline for GCM concentrations in samples dried at 90 °C. Different fecal preservation techniques and extraction solvents provided similar results for both E1C and GCM concentrations. Our results confirm previous studies that prior to application of fecal hormone analysis in a new species, several preservation parameters should be evaluated for their effects on hormone metabolite stability. The results also provide several options for fecal preservation, extraction, and storage methods that can be selected depending on the condition of the field site and laboratory.
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