Barren ground caribou (Rangifer tarandus granti) are distributed in herds that seasonally use specific geographic regions within an annual range, with varying levels of fidelity during different ...periods (e.g., calving, insect relief, wintering). As a result, caribou management is generally tailored to individual herds that often range across administrative boundaries. Herd ranges can shift over time, seasonal ranges of adjacent herds often overlap, herds merge, and there is often little genetic differentiation among adjacent herds. If substantial herd interchange occurs, it would have important management implications by influencing estimates of herd size, herd composition, and harvest rates. We compiled satellite telemetry data from 2003–2015 for 4 large arctic caribou herds to quantify herd interchange rates. We calculated a metric of herd interchange based on the relationship of caribou locations to typical weekly herd ranges (all yrs combined) and the distance to other radio-collared caribou from each of the 4 herds (yr specific). Although herd membership cannot always be clearly defined based on location, this metric provides an objective measure of the strength of evidence of herd membership that can be used to make comparisons among herds and time periods. We also calculated herd overlap and quantified how it varied throughout the year. Herd interchange was rare in the 2 larger herds, generally occurring when caribou overwintered with an adjacent herd, whereas herd interchange from the 2 smaller herds was more frequent and could last longer than a year. Although sample sizes were limited, there were no clear patterns in herd interchange with year or annual herd size. The 2 smaller herds had large seasonal overlap with adjacent herds, suggesting that herd interchange may be related to spatiotemporal herd overlap and relative herd size. Our results can help managers understand herd interchange and overlap to make management decisions, interpret research results, and develop more accurate population models.
Wolf (Canis lupus) kill rates are fundamental to understanding predation, but are not well known at low moose (Alces alces) densities. We investigated kill rates of 6 wolf packs (2–10 wolves/pack) ...during 2 winters on the Yukon Flats, a region of eastern Interior Alaska where moose were the sole ungulate prey of wolves occurring at densities <0.2 moose/km2. Our objectives were to compare kill rates with those from areas of greater moose densities, and to determine potential trends in kill rates across the winter. We located moose killed by wolves in February–March 2009, and November 2009–March 2010 using aerial tracking techniques and global positioning system (GPS) location clusters. Wolves killed more moose in early than late winter (βMONTH = −0.02 moose/pack/day, 95% CI = −0.01 to −0.04), and kill rate estimates (mean, 95% CI) were greatest in November (0.033 moose/wolf/day, 0.011–0.055) and least in February (0.011, 0.002–0.02). Kill rates were similar between February and March 2009 (0.019 moose/wolf/day, 0.01–0.03) and 2010 (0.018, 0.01–0.03). Prey composition was primarily adult females (39%) and young-of-the-year (35%). We attribute an elevated kill rate in early winter to predation on more vulnerable young-of-the-year. Kill rates in our study were similar to those from other studies where moose occurred at greater densities. We suggest that very few, if any, wolf–moose systems in Alaska and the Yukon experience a density-dependent phase in the functional response, and instead wolves respond numerically to changes in moose density or availability in the absence of alternative prey. Through a numerical response, wolf predation rates may approximate the annual growth potential of the moose population, contributing to persistent low densities of moose and wolves on the Yukon Flats. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.
We investigated the winter density and territory size of wolves (Canis lupus) on the Yukon Flats, Alaska, where moose (Alces alces) was the sole ungulate prey, occurring at a low density and ...representing a biomass of ungulate food lower than previously studied in North America. Using locations (GPS coordinates) from collars deployed on seven wolves, we estimated territory sizes with adaptive kernel and minimum convex polygon methods. We then estimated wolf density from a population area defined by these territory sizes and counts of wolves in five marked packs. From November 2009 to April 2010, we obtained 6263 GPS locations. Pack size ranged from two to 10 wolves, with average size of 5.0 in November 2009 and 4.8 in March 2010. Average winter territory size for the five packs was 1433 km2 with the 95% adaptive kernel method and 1608 km2 with the minimum convex polygon method. Density (wolves/1000 km2) was 3.6 in November and 3.4 in March with the 95% adaptive kernel method and 3.4 in November and 3.3 in March with the minimum convex polygon method. Territories were large and estimates produced by the two methods differed by 11%. Densities were low, and the two analysis methods yielded densities that differed from each other by 3% to 6%. Low wolf density corresponded with low biomass of ungulate food, suggesting that moose availability on the Yukon Flats likely limited wolf density. Nous avons étudié la densité hivernale et la taille du territoire du loup (Canis lupus) aux Yukon Flats, en Alaska, où l'orignal (Alces alces) était la seule proie ongulée. Il s'y trouvait en faible densité et représentait une biomasse de nourriture ongulée inférieure à celle étudiée ailleurs en Amérique du Nord. Grâce aux positions (coordonnées de GPS) prélevées à partir de colliers posés sur sept loups, nous avons estimé la taille des territoires au moyen de la méthode d'estimation adaptative à noyaux et de la méthode du polygone convexe minimal. Ensuite, nous avons estimé la densité du loup à partir d'une zone de population définie par la taille de ces territoires et par les dénombrements de loups de cinq meutes marquées. De novembre 2009 à avril 2010, nous avons obtenu 6 263 positions GPS. La taille des meutes variait de deux à dix loups, pour une taille moyenne de 5,0 loups en novembre 2009 et de 4,8 en mars 2010. La taille moyenne du territoire hivernal de cinq meutes était de 1 433 km2 dans le cas de la méthode adaptative à noyaux de 95 % et de 1 608 km2 dans le cas de la méthode du polygone convexe minimal. La densité (loups/1000 km2) était de 3,6 en novembre et de 3,4 en mars avec la méthode adaptative à noyaux de 95 %, puis de 3,4 en novembre et de 3,3 en mars avec la méthode du polygone convexe minimal. Les territoires étaient vastes et les estimations obtenues à l'aide des deux méthodes différaient de 11 %. Les densités étaient faibles, et les deux méthodes d'analyse ont donné des densités qui différaient l'une de l'autre dans une mesure 3 % à 6 %. La faible densité des loups correspondait à la faible biomasse de nourriture ongulée, ce qui laisse supposer que la disponibilité de l'orignal aux Yukon Flats limitait vraisemblablement la densité du loup.
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