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opencc-zeroDec 2017View details →

Data from: Does wolf presence reduce moose browsing intensity in young forest plantations?

Large carnivores can be a key factor in shaping their ungulate prey's behavior, which may affect lower trophic levels. While most studies on trade-offs between food acquisition and risk avoidance by ungulate prey species have been conducted in areas with limited human impact, carnivores are now increasingly returning to highly anthropogenic landscapes. Many of these landscapes are dominated by forestry, and ungulate-forestry conflicts are an increasing issue. The aim of this study was to test if the indirect effects of a re-colonizing large predator, the wolf (Canis lupus), results in a change in browsing intensity by moose (Alces alces) in young forest plantations in a boreal forest in Sweden. We selected 24 different forest plantations, with 12 located in low-wolf and 12 in high-wolf utilization areas. In each plantation, we measured browsing intensity, tree height, tree density, distance to the closest forest edge and we counted the number of moose pellet groups. In contrast to our predictions, wolf utilization was not the main driver of moose browsing patterns. Instead, moose browsing intensity declined with tree density and height. Separate analyses on the main tree species showed that wolf utilization had an influence, but browsing intensity was in fact higher in the high-wolf utilization areas for three out of five tree species. This pattern seemed to be driven by a strong confounding relationship between wolf utilization, tree density and height, which were both lower in the high-wolf utilization areas. We argue that this confounding effect is due to wolves being pushed towards the less productive parts of the landscape away from human activity centers. Therefore, we concluded that in order to better understand carnivore driven risk- mediated effects on herbivore behavior in anthropogenic landscapes we need to better understand the complexity of human-carnivore-prey-ecosystem interactions.

opencc-zeroAug 2021View details →

Moose habitat selection under the landscape of predation risk

Landscape of fear refers to the spatial variation in prey perception of predation risk, that under certain conditions, may lead to changes in their behavior. Behavioral responses of prey in relation to large carnivore predation risk have mainly been conducted in areas with low anthropogenic impact. We used long-term data on the distribution of moose in different habitat types in a system characterized by intensive management of all three trophic levels (silviculture, harvest of wolves and moose) to study effects on moose habitat selection resulting from the return of an apex predator, the wolf. We assumed that coursing predators such as wolves will cause an increased risk for moose in some habitat types and tested the hypotheses that moose will avoid open or young forest habitats following wolf establishment. After wolf recolonization, moose reduced their use of one type of open habitat (bog) but there was neither change in the use of the other open habitat type (clear-cut), nor in their use of young forest. Wolf establishment did not influence the use of habitat close to dense habitat when being in open habitats. Thus, the effect of wolves varied among habitat types and there was no unidirectional support for a behavioral effect of wolves' establishment on moose habitat use. Human-driven habitat heterogeneity, concentration of moose forage to certain habitat types, and the effects of a multiple predator guild on moose may all contribute to the results found. We conclude that the landscape of fear is likely to have weak ecological effects on moose in this system.

Figs. 2–3 in Seasonality of Coprophagous Beetles (Coleoptera: Hydrophilidae, Geotrupidae, Scarabaeidae) Inhabiting Moose (Alces Alces Linnaeus) Dung in Kampinoski Park Narodowy, Poland

Figs. 2–3. Seasonality of coprophagous beetles in Kampinoski Park Narodowy, Poland. 2) Temporal changes in abundance (individuals/kg of moose dung) and dry weight (g/kg of moose dung) of captured beetles; 3) Temporal changes in abundance and dry weight of two dung beetle nesting guilds.

Fig. 6 in Seasonality of Coprophagous Beetles (Coleoptera: Hydrophilidae, Geotrupidae, Scarabaeidae) Inhabiting Moose (Alces Alces Linnaeus) Dung in Kampinoski Park Narodowy, Poland

Fig. 6. Seasonality with one evident population peak of the most abundant coprophagous beetle species on moose dung in Kampinoski Park Narodowy, Poland.

Fig. 5 in Seasonality of Coprophagous Beetles (Coleoptera: Hydrophilidae, Geotrupidae, Scarabaeidae) Inhabiting Moose (Alces Alces Linnaeus) Dung in Kampinoski Park Narodowy, Poland

Fig. 5. Temporal changes in Shannon-Weaver (H') and Pielou's evenness (J) indices of the coprophagous beetle fauna in Kampinoski Park Narodowy, Poland.

Fig. 4 in Seasonality of Coprophagous Beetles (Coleoptera: Hydrophilidae, Geotrupidae, Scarabaeidae) Inhabiting Moose (Alces Alces Linnaeus) Dung in Kampinoski Park Narodowy, Poland

Fig. 4. Monthly dominance structures of captured coprophagous beetles in Kampinoski Park Narodowy, Poland. Ac. de – Acrossus depressus; Ac. ru – Acrossus rufipes; Ag. ne – Agoliinus nemoralis; An. st – Anoplotrupes stercorosus; Ch. di – Chilothorax distinctus; Eu. co – Eurodalus coenosus; Ge. st – Geotrupes stercorarius; k – number of species; Li. ze – Limarus zenkeri; n – number of individuals; O – other species (may include both nesting guilds); Pl. bo – Planolinoides borealis; Pl. fa – Planolinus fasciatus; Tr. ve – Trypocopris vernalis; Grey slices – paracoprids, white slices – endocoprids.

Fig. 1 in Seasonality of Coprophagous Beetles (Coleoptera: Hydrophilidae, Geotrupidae, Scarabaeidae) Inhabiting Moose (Alces Alces Linnaeus) Dung in Kampinoski Park Narodowy, Poland

Fig. 1. Baited pitfall trap used to capture coprophagous beetles in Kampinoski Park Narodowy, Poland. Photograph by D. Marczak.

Fig. 7 in Seasonality of Coprophagous Beetles (Coleoptera: Hydrophilidae, Geotrupidae, Scarabaeidae) Inhabiting Moose (Alces Alces Linnaeus) Dung in Kampinoski Park Narodowy, Poland

Fig. 7. Seasonality with two or more apparent population peaks of the most abundant coprophagous beetle species on moose dung in Kampinoski Park Narodowy, Poland.

opencc-zeroMar 2023View details →

Data for: Landscape of fear or landscape of food? Moose hunting triggers an anti-predator response in brown bears

Hunters can affect the behavior of wildlife by inducing a landscape of fear, selecting individuals with specific traits, or by altering resource availability across the landscape. Most research investigating the influence of hunting on wildlife resource selection has focused on target species and less attention has been devoted to non-target species, such as scavengers that can be both attracted or repelled by hunting activities. We used resource selection functions to identify areas where hunters were most likely to kill moose (Alces alces) in south-central Sweden during the fall. Then, we used step-selection functions to determine whether female brown bears (Ursus arctos) selected or avoided these areas and specific resources during the moose hunting season. We found that, during both day and nighttime, female brown bears avoided areas where hunters were more likely to kill moose. We found evidence that resource selection by brown bears varied substantially during the fall and that some behavioral changes were consistent with disturbance associated with moose hunters. Brown bears were more likely to select concealed locations in young (i.e., regenerating) and coniferous forests and areas further away from roads during the moose hunting season. Our results suggest that brown bears react to both spatial and temporal variations in apparent risk during the fall: moose hunters create a landscape of fear and trigger an anti-predator response in a large carnivore even if bears are not specifically targeted during the moose hunting season. Such anti-predator responses might lead to indirect habitat loss and lower foraging efficiency and the resulting consequences should be considered when planning hunting seasons.

opennotspecifiedNov 2019View details →

Fig. 2.—Bayesian maximum clade credibility tree showing 37 mitochondrial genome haplotypes from 60 in Phylogeography of moose in western North America

Fig. 2.—Bayesian maximum clade credibility tree showing 37 mitochondrial genome haplotypes from 60 moose and an inset of sample locations according to haplotype number, sampled in western North America, 2004–2016, and including a Eurasian moose mitogenome from Kazakhstan (Hassanin et al. 2012—GenBank accession NC_020677). In the tree, each haplotype is followed by a sequence of highlighted (by subspecies) and labeled (by state or provincial abbreviation) squares signifying the location where each sample was collected. In the inset, haplotypes unique to a single individual are colored white, while the seven haplotypes found in multiple moose are colored by haplotype number.

opennotspecifiedNov 2019View details →

Fig. 1 in Phylogeography of moose in western North America

Fig. 1.—Centroid locations of 26 local populations of moose in western North America sampled for genetic material during 2004–2016 with respect to putative subspecies range boundaries. Populations 1 and 2 in Colorado and southcentral Wyoming were introduced from native lineages elsewhere in Wyoming.

opennotspecifiedNov 2019View details →

Fig. 3 in Phylogeography of moose in western North America

Fig. 3.—Locations of 26 local populations of moose, labeled by sampling location (see Fig. 1), relative to the first two components of a principal coordinates analysis of allele frequencies at 13 microsatellite loci, sampled from three subspecies in western North America, 2004–2016.