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Iliopoulos, Y., Sgardelis, S., Koutis, V., & Savaris, D. (2009). Wolf depredation on livestock in central Greece. Mamm. Reas., 54(1), 11–22.
Abstract: We studied wolfCanis lupus Linnaeus, 1758 -- livestock conflict in central Greece by investigating patterns of 267 verified wolf attacks on livestock for 21 months. Wolves attacked adult goats 43% and cattle 218% more than expected, whereas sheep 41% less than expected from their availability. Wolves killed less than four sheep or goats in 79%, and one cow or calf in 74% of depredation events, respectively. We recorded higher attack rates during wolf post-weaning season. Wolf attacks on strayed, or kept inside non predator-proof enclosures, sheep and goats, were on average two to four times respectively more destructive than those when livestock was guarded by a shepherd. Sheepdog use reduced losses per attack. Optimal sheepdog number ranged from 3 to 9 animals depending on flock size. Losses per attack were positively related to the number of wolves involved. Total losses per farm were positively correlated with the size of livestock unit but percentage losses per capita increased with decreasing flock size. Management implications to mitigate livestock depredation are discussed.
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Genov, P. W., & Kostava, V. (1993). Untersuchungen zur zahlenmäßigen Stärke des Wolfes und seiner Einwirkung auf die Haustierbestände in Bulgarien. Zeitschrift für Jagdwissenschaft, 39(4), 217–223.
Abstract: Die Untersuchung wurde in der Zeitspanne von 1984 bis 1988 durchgeführt. Es wurden die Protokolle des Staatlichen Versicherungsinstituts benutzt, die Angaben für Raubüberfälle von Wölfen auf Haustiere beinhalten (Tabelle 1). Außerdem wurden Angaben über die während dieser Zeitspanne erlegten Wölfe zusammengefaßt. Die Abschußzahlen lauten: 1984 – 163, 1985 – 147, 1986 – 179, 1987 – 211 und 1988 – 220 Tiere. Die Anzahl der in den einzelnen Gebirgen lebenden Wölfe wurde nach einer Umfrage festgestellt. Für die in Betracht kommenden Gebirge werden folgende Bestandszahlen angenommen: Rhodopen -- 60-80 Individuen, 189 bis 264 km2 pro Tier, Rila- und Piringebirge -- 60-80 Tiere, 109 bis 145 km2 pro Tier, Ossogowo-Belassiza Gebirgssystem -- 40-50 Individuen, 57-70 km2 pro Tier, West- und Mittelbalkan -- 35-38 Wölfe, 200 km2 pro Tier. Dazu kommen noch 10-15 Wölfe im Flußbecken von Beli Lom und etwa 20 Exemplare in Strandscha- und Sakargebirge. Insgesamt lebten in Bulgarien im Jahre 1988 etwa 260-330 Wölfe (Abb. 1).
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Kruska, D. (1988). Mammalian domestication and its effect on brain structure and behavior. In H. J. Jerison, & I. Jerison (Eds.), Intelligence and Evolutionary Biology. New York: Springer-Verlag.
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Ruid, D. B., Paul, W. J., Roell, B. J., Wydeven, A. P., Willging, R. C., Jurewicz, R. L., et al. (2009). Wolf-Human Conflicts and Management in Minnesota, Wisconsin, and Michigan. In A. P. Wydeven, T. R. Van Deelen, & E. J. Heske (Eds.), Recovery of Gray Wolves in the Great Lakes Region of the United States: An Endangered Species Success Story (pp. 279–295). New York, NY: Springer New York.
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Irving-Pease, E. K., Ryan, H., Jamieson, A., Dimopoulos, E. A., Larson, G., & Frantz, L. A. F. (2019). Paleogenomics of Animal Domestication. In C. Lindqvist, & O. P. Rajora (Eds.), Paleogenomics: Genome-Scale Analysis of Ancient DNA (pp. 225–272). Cham: Springer International Publishing.
Abstract: Starting with dogs, over 15,000 years ago, the domestication of animals has been central in the development of modern societies. Because of its importance for a range of disciplines – including archaeology, biology and the humanities – domestication has been studied extensively. This chapter reviews how the field of paleogenomics has revolutionised, and will continue to revolutionise, our understanding of animal domestication. We discuss how the recovery of ancient DNA from archaeological remains is allowing researchers to overcome inherent shortcomings arising from the analysis of modern DNA alone. In particular, we show how DNA, extracted from ancient substrates, has proven to be a crucial source of information to reconstruct the geographic and temporal origin of domestic species. We also discuss how ancient DNA is being used by geneticists and archaeologists to directly observe evolutionary changes linked to artificial and natural selection to generate a richer understanding of this fascinating process.
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Aldezabal, A., & Garin, I. (2000). Browsing preference of feral goats (Capra hircus L.) in a Mediterranean mountain scrubland. J Arid Env, 44.
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McComb, K., Moss, C., Sayialel, S., & Baker, L. (2000). Unusually extensive networks of vocal recognition in African elephants. Anim Behav, 59.
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Van Horik, J., & Emery, N. (2011). Evolution of cognition. Wiley Interdiscip Rev Cogn Sci, 2.
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Boyce, P. N., & McLoughlin, P. D. (2021). Ecological Interactions Involving Feral Horses and Predators: Review with Implications for Biodiversity Conservation. Jour. Wild. Mgmt., n/a(n/a).
Abstract: ABSTRACT For many ecosystems, feral horses are increasingly becoming an important if not dominant component of ungulate biomass and hence influence on community dynamics. Yet we still know little of how horses contribute to key ecological interactions including predator-prey and indirect competitive relationships at a community level. Notably, feral species like horses can exhibit life-history traits that differ from that of native (mainly artiodactyl) herbivore competitors. Artificial selection for traits like increased, early, or extended reproduction that have yet to be reversed by natural selection, coupled with naturally selected differences in anatomy and behavior, in addition to unique management objectives for horses compared to other species, means that the dynamics of feral horse populations are not likely to align with what might be expected of other large herbivores. Unexpected population dynamics and inherent biological asymmetries between native ungulates and feral horses may therefore influence the former via direct competition for shared resources and through enemy-mediated interactions like apparent competition. In several localities feral horses now co-exist with multiple native prey species, some of which are in decline or are species at risk. Compounding risks to native species from direct or indirect competitive exclusion by horses is the unique nature and socio-political context of feral horse management, which tends towards allowing horse populations to be limited largely by natural, density-dependent factors. We summarize the inherent asymmetries between feral horse biology and that of other ungulate prey species with consequences for conservation, focusing on predator-prey and emerging indirect interactions in multi-prey systems, and highlight future directions to address key knowledge gaps in our understanding of how feral horses may now be contributing to the (re)structuring of food webs. Observations of patterns of rapid growth and decline, and associated skews in sex ratios of feral horse populations, indicate a heightened potential for indirect interactions among large ungulate prey species, where there is a prevalence of feral horses as preferred prey, particularly where native prey are declining. In places like western North America, we expect predator-prey interactions involving feral horses to become an increasingly important factor in the conservation of wildlife. This applies not only to economically or culturally important game species but also at-risk species, both predators (e.g., wolves [Canis lupus], grizzly bears [Ursus arctos]) and prey (e.g., woodland caribou [Rangifer tarandus caribou]), necessitating an ecological understanding of the role of horses in natural environments that goes beyond that of population control. ? 2021 The Wildlife Society.
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Hofmeester, T. R., Cromsigt, J. P. G. M., Odden, J., Andrén, H., Kindberg, J., & Linnell, J. D. C. (2019). Framing pictures: A conceptual framework to identify and correct for biases in detection probability of camera traps enabling multi-species comparison. Ecol Evol, .
Abstract: Abstract Obtaining reliable species observations is of great importance in animal ecology and wildlife conservation. An increasing number of studies use camera traps (CTs) to study wildlife communities, and an increasing effort is made to make better use and reuse of the large amounts of data that are produced. It is in these circumstances that it becomes paramount to correct for the species- and study-specific variation in imperfect detection within CTs. We reviewed the literature and used our own experience to compile a list of factors that affect CT detection of animals. We did this within a conceptual framework of six distinct scales separating out the influences of (a) animal characteristics, (b) CT specifications, (c) CT set-up protocols, and (d) environmental variables. We identified 40 factors that can potentially influence the detection of animals by CTs at these six scales. Many of these factors were related to only a few overarching parameters. Most of the animal characteristics scale with body mass and diet type, and most environmental characteristics differ with season or latitude such that remote sensing products like NDVI could be used as a proxy index to capture this variation. Factors that influence detection at the microsite and camera scales are probably the most important in determining CT detection of animals. The type of study and specific research question will determine which factors should be corrected. Corrections can be done by directly adjusting the CT metric of interest or by using covariates in a statistical framework. Our conceptual framework can be used to design better CT studies and help when analyzing CT data. Furthermore, it provides an overview of which factors should be reported in CT studies to make them repeatable, comparable, and their data reusable. This should greatly improve the possibilities for global scale analyses of (reused) CT data.
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