Wolf harvest numbers and quota numbers by FWP's trapping districts and wolf management unit (WMU) for the current hunting/trapping season in Montana. For display in the Montana Wolf Harvest Dashboard: https://www.arcgis.com/apps/dashboards/e6fb069d45b74034ad85569e5f96ae7a . Data are from the Montana Fish, Wildlife and Parks' mandatory reporting records provided by hunters and trappers, wolf regulations and FWP Commission. Harvest numbers are updated multiple times per day during the hunting/trapping season. This data is also displayed on the wolf harvest status web page: https://myfwp.mt.gov/fwpPub/speciesHuntingGuide?wmrSpeciesCd=GW. More information about wolf hunting and trapping in Montana is available at: https://fwp.mt.gov/hunt/regulations/wolf

In 2023/24, there were *** wolf packs counted in Germany. The numbers have been constantly increasing since 2013 and 2023/24, saw the highest number of packs.

Large carnivores are globally threatened due to habitat fragmentation and loss, prey depletion, and human exploitation. Human exploitation includes both legal and illegal hunting and trapping. Protected areas can create refugia from hunting and trapping, however, hunting can still threaten wide-ranging large carnivores when they leave these areas. Large carnivore reintroductions to protected areas are often motivated to restore ecological processes, including wolf reintroduction to Yellowstone National Park (YNP). Determining if harvest is compensatory or additive is essential for informed conservation strategies, as it influences the overall impact on wolf populations and their ecosystems. If the harvest was compensatory, then increasing harvest pressure outside YNP should not decrease overall survival for transboundary wolves. Alternatively, if increasing harvest was additive, then increasing harvest pressure outside YNP should decrease overall survival for transboundary wolves. We tested the effects of variable harvest pressure following delisting on the survival of YNP gray wolves (Canis lupus) from 1995 to 2022. We defined three harvest levels: no harvest, harvest with limited quotas, and unlimited harvest. We used Cox-proportional hazards models and cumulative incidence functions to estimate survival rates, factors affecting survival, and cause-specific mortality between these three harvest periods to test predictions of the additive mortality hypothesis. Most wolves that primarily lived in YNP were harvested adjacent to the park border. Cox-proportional hazards models revealed that mortality was highest during years of unlimited harvest during winter outside YNP. Cause-specific mortality analyses showed that natural mortality from other wolves and harvest were the two leading causes of death, but that harvest mortality had additive effects on wolf mortality. Wolf survival decreased with increased harvest mortality, while natural mortality remained relatively unchanged. High rates of additive harvest mortality of wolves could negatively impact wolf survival in YNP. Harvest mortality of transboundary wolves is additive possibly due to source-sink dynamics of uneven spatial susceptibility of wolves to harvest mortality across protected area borders, as well as effects of harvest on complex social dynamics of wolves in YNP. Transboundary management of large carnivores is challenging, yet cooperation between agencies is vital for wolf management in and around Yellowstone National Park. Our results support the use of small quota zones surrounding protected areas, that minimize transboundary mortality impacts on large carnivores living primarily inside protected areas.

Twenty six wolves were captured and radio collared in 1984 and 1985 on the Arctic National Wildlife Refuge. These wolves included members of 8 packs and 11 lone wolves. Average weights were 43.1 kg for males and 36.7 kg for females with the average age being 2-3 years old. Only 5 wolves were 4 years old and older. Activity areas were delinieated for all packs as some packs had insufficient data to accurately define territories. These activity areas were non-overlaping. Only 1 wolf pack had a large scale seasonal shift in areas used. Formation of new packs and long-distance movements were common. One wolf had a documented movement of 770 km, the longest recorded movement in Alaksa. Wolf densities were 1/726 km2 in 1984 and 1/686 km2 in 1985 for an area of 24,700 km2. Litter sizes averaged 3.0 and 4.2-4.75 in 1984 and 1985 respectively. Over-summer pup survival was related to pack size; more pups survived in larger packs. This was in contrast to other studies where pup survival and pack size were unrelated. After wolves had left, den sites were visited, scats were collected, and dens were mapped. Mortality (natural and human induced) was 35% of the fall population. Rabies was documented in the wolf population in the spring on 1985. It is believed that rabies in the wolf population in the arctic is more common than previously thought and may be cyclic in conjunction with outbreaks of rabies in the Arctic fox (Alopex lagopus) population.

This dataset includes information on deer-vehicle collisions, vehicle miles traveled, weather, and deer, wolf, and human populations, for counties in Wisconsin from 1981-2016.

Methods These data are described in the README.txt file. A full replication package for the paper associated with this data is available at: https://github.com/jennifer-raynor/wolvs_and_DVCs.

Wolves 2

## Overview

Wolves 2 is a dataset for object detection tasks - it contains Wolves annotations for 381 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

Rapid Evolution of Prehistoric Dogs from Wolves by Natural and Sexual Selection Emerges from an Agent-Based Model

Here, we provide the necessary .py files to recreate the results found in the above-entitled manuscript. If you desire to load the data provided, it's recommended you use pandas 2.0.3 and python 3.10.13.

Nearly all .py files will require you have evolutuion_system.py file in the base directory. This .py file enacts the ABM as described in the manuscript. All other .py files should be placed in the same base directory.

You should construct a data folder and a figures folder in the base directory. In the data folder create an efast, prcc, and a monotonicity subfolder. These exists so you do not have to re-run the efast, prcc, or monotonicity simulations. In the figures folder create subfolders for default_distributions, distributions, efast, monotonicity, prcc, validation, and verification. Any figures generated will be produced in the corresponding figures sub-folder. ...

This dataset contains gray wolf (Canis lupus) survival and cause-specific mortality data from radiocollared wolves (n=756 collared-wolf tenures) from 1968-2018 in the USGS Wolf Project study area (2,060 km2) of the Superior National Forest, USA, an area that also includes the Boundary Waters Canoe Area Wilderness. Also, included are the annual resident winter wolf counts for the study area.

1. Although local variation in territorial predator density is often correlated with habitat quality, the causal mechanism underlying this frequently observed association is poorly understood and could stem from facultative adjustment in either group size or territory size. 2. To test between these alternative hypotheses, we used a novel statistical framework to construct a winter population-level utilization distribution for wolves (Canis lupus) in northern Ontario, which we then linked to a suite of environmental variables to determine factors influencing wolf space use. Next, we compared habitat quality metrics emerging from this analysis as well as an independent measure of prey abundance, with pack size and territory size to investigate which hypothesis was most supported by the data. 3. We show that wolf space use patterns were concentrated near deciduous, mixed deciduous/coniferous and disturbed forest stands favoured by moose (Alces alces), the predominant prey species in the diet of wolves in northern Ontario, and in proximity to linear corridors, including shorelines and road networks remaining from commercial forestry activities. 4. We then demonstrate that landscape metrics of wolf habitat quality – projected wolf use, probability of moose occupancy and proportion of preferred land cover classes – were inversely related to territory size but unrelated to pack size. 5. These results suggest that wolves in boreal ecosystems alter territory size, but not pack size, in response to local variation in habitat quality. This could be an adaptive strategy to balance trade-offs between territorial defence costs and energetic gains due to resource acquisition. That pack size was not responsive to habitat quality suggests that variation in group size is influenced by other factors such as intraspecific competition between wolf packs.

Data file containing spatial variables of wolf GPS-positions and random points for step selection functions that is used in the article “Wolves at the door? Factors influencing the individual behavior of wolves in relation to anthropogenic features”. Abstract: The recovery of large carnivores in human-dominated landscapes comes with challenges. In general, large carnivores avoid humans and their activities, and human avoidance favors coexistence, but individual variation in large carnivore behavior may occur. The detection of individuals close to human settlements or roads can trigger fear in local communities and in turn demand management actions. Understanding the sources of individual variation in carnivore behavior towards human features is relevant and timely for ecology and conservation. We studied the movement behavior of 52 adult established wolves (44 wolf pairs) with GPS-collars over two decades in Scandinavia in relation to settlements, buildings, and roads. We fit fine-scale movement data to individual step selection functions to depict the movement decisions of wolves while travelling, and then used weighted linear mixed models to identify factors associated with potential individual pair deviations from the general behavioral patterns. Wolves consistently avoided human settlements and main roads, with little individual variation. Indeed, after correcting for season, time of the day, and latitude, there was little variability in habitat selection among wolf pairs, demonstrating that all wolf pairs had similar movement pattern and generally avoided human features of the landscape. Wolf avoidance of human features was lower at higher latitudes particularly in winter, likely due to seasonal prey migration. Although occasional sightings of carnivores or their tracks near human features do occur, they do not necessarily require management intervention. Communication of scientific findings on carnivore behavior to the public should suffice in most cases.

Since 1986, surveys in spring and fall each year count the number of wolves found in Denali National Park and Preserve, north of the Alaska Range.

Fecal prevalence (number of detected infections/number of samples) and apparent maximum prevalence (number of infected wolves/number of unique wolves) in northern Yellowstone wolves years 2018–2020.

Dataset for paper: Wolves in the borderland – changes in population and wolf diet in Romincka Forest, along the Polish-Russian-Lithuanian state borders

https://doi.org/10.5061/dryad.qfttdz0qn

The dataset provides data to assess the wolf numbers and diet in the Romincka Forest in northern Poland.

Description of the data and file structure

Data are grouped into three files:

Nowak_Repository_genotyping.txt. Results of genetic fingerprinting based on 13 DNA microsatellite markers for non-invasive samples found during the fieldwork in the Romincka Forest, along with reference samples from Baltic, Central European, and Carpathian wolf subpopulations. This is a TAB-separated file that contains the following columns:

(1) ID - identification number of the sample;

(2) sex - sex of the individual based on the analysis of DBX intron 6 and DBY intron 7;

Followed by columnes with numerical data for allele sizes of 13 polymorphic microsatellite loci: FH2001, FH2010, FH2017, FH2054,...

Wolves Finder

## Overview

Wolves Finder is a dataset for object detection tasks - it contains Wolves annotations for 551 images.

## Getting Started

You can download this dataset for use within your own projects, or fork it into a workspace on Roboflow to create your own model.

  ## License

  This dataset is available under the [CC BY 4.0 license](https://creativecommons.org/licenses/CC BY 4.0).

In 2023/24, there were ** wolf couples counted in Germany. This was the highest figure since 2020/21.

This map depicts IDFG wolf management zones, towns, roads, and hydrography.2013 Idaho Wolf Monitoring Progress Report

Recovering populations of carnivores suffering Allee effects risk extinction because positive population growth requires a minimum number of cooperating individuals. Conservationists seldom consider these issues in planning for carnivore recovery because of data limitations, but ignoring Allee effects could lead to overly optimistic predictions for growth and underestimates of extinction risk. We used Bayesian splines to document a demographic Allee effect in the time series of gray wolf (Canis lupus) population counts (1980–2011) in the southern Lake Superior region (SLS, Wisconsin and the upper peninsula of Michigan, USA) in each of four measures of population growth. We estimated that the population crossed the Allee threshold at roughly 20 wolves in four to five packs. Maximum per-capita population growth occurred in the mid-1990s when there were approximately 135 wolves in the SLS population. To infer mechanisms behind the demographic Allee effect, we evaluated a potential component Allee effect using an individual-based spatially explicit model for gray wolves in the SLS region. Our simulations varied the perception neighborhoods for mate-finding and the mean dispersal distances of wolves. Simulation of wolves with long-distance dispersals and reduced perception neighborhoods were most likely to go extinct or experience Allee effects. These phenomena likely restricted population growth in early years of SLS wolf population recovery.

Nonbreeding helpers can greatly improve the survival of young and reproductive fitness of breeders in many cooperatively breeding species. Breeder turnover, in turn, can have profound effects on dispersal decisions made by helpers. Despite its importance in explaining group size and predicting population demography of cooperative breeders, our current understanding of how individual traits influence animal behavior after disruptions to social structure is incomplete particularly for terrestrial mammals. We used 12 years of genetic sampling and group pedigrees of gray wolves (Canis lupus) in Idaho, USA, to ask questions about how breeder turnover affected the apparent decisions by mature helpers (>2-year-old) to stay or leave a group over a one-year time interval. We found that helpers showed plasticity in their responses to breeder turnover. Most notably, helpers varied by sex and appeared to base dispersal decisions on the sex of the breeder that was lost as well. Male and female helpers stayed in a group slightly more often when there was breeder turnover of the same sex, although males that stayed were often recent adoptees in the group. Males, however, appeared to remain in a group less often when there was breeding female turnover likely because such vacancies were typically filled by related females from the males’ natal group (i.e., inbreeding avoidance). We show that helpers exploit instability in the breeding pair to secure future breeding opportunities for themselves. The confluence of breeder turnover, helper sex, and dispersal and breeding strategies merge to influence group composition in gray wolves.

This map depicts the home ranges of documented, suspected, and terminated wolf packs located in and near Idaho. Wolf management zones, prominent cities, major roads, major lakes, national forest lands, and wilderness areas are also depicted.The lighter colored packs near the Idaho border are monitored by surrounding states.2015 Idaho Wolf Monitoring Progress Report Click here for more information about wolf management in Idaho.