561 items found
Endangered species
Human wildlife conficts
Colorado
Brochure
Endangered species
Human wildlife conficts
Colorado
Brochure
- What to Do if You Live in Wolf Country
- Recreating in Wolf Country
- What to Do if You Encounter a Wolf
- What We Know About Wolves
- Report a Sighting
Camouflage mismatch
Climate change
Latitudinal gradient
Phenological mismatch
Phenotypic plasticity
Range edge
Snow
Snowshoe hares
Camouflage mismatch
Climate change
Latitudinal gradient
Phenological mismatch
Phenotypic plasticity
Range edge
Snow
Snowshoe hares
LocationNorth America.
Time period2010–2017.
Major taxa studiedSnowshoe hare (Lepus americanus).
MethodsWe used > 5,500 by-catch photographs of snowshoe hares from 448 remote camera trap sites at three independent study areas. To quantify moult phenology and phenotypic plasticity, we used multinomial logistic regression models that incorporated geospatial and high-resolution climate data. We estimated occurrence of camouflage mismatch between hares’ coat colour and the presence and absence of snow over 7 years of monitoring.
ResultsSpatial and temporal variation in moult phenology depended on local climate conditions more so than on latitude. First, hares in colder, snowier areas moulted earlier in the fall and later in the spring. Next, hares exhibited phenotypic plasticity in moult phenology in response to annual variation in temperature and snow duration, especially in the spring. Finally, the occurrence of camouflage mismatch varied in space and time; white hares on dark, snowless background occurred primarily during low-snow years in regions characterized by shallow, short-lasting snowpack.
Main conclusionsLong-term climate and annual variation in snow and temperature determine coat colour moult phenology in snowshoe hares. In most areas, climate change leads to shorter snow seasons, but the occurrence of camouflage mismatch varies across the species’ range. Our results underscore the population-specific susceptibility to climate change-induced stressors and the necessity to understand this variation to prioritize the populations most vulnerable under global environmental change.
[show more]White-tailed ptarmigan
<em>Lagopus leucura</em>
Colorado
White-tailed ptarmigan
<em>Lagopus leucura</em>
Colorado
CPW website species profile: LynxLynx populations in Colorado plummeted in the late 1800s and early 1900s for various reasons, including general predator poisoning and unregulated trapping. The last known lynx was illegally trapped near Vail in 1974, a year after the state listed the lynx as endangered. In 1997, Colorado Parks and Wildlife undertook what was to become one of North America’s most high-profile carnivore reintroductions to date. Four years after the last lynx was released into the state in 2006, CPW deemed the initial lynx introduction effort a success. Research has now focused towards determining and maintaining the long-term success of the reintroduction. Learn more about lynx and Colorado’s successful lynx reintroduction in our Lynx Fact Sheet. Or, learn how to identify a lynx and report a lynx sighting.
Lynx Research Projects:
[show more]Camera trap
Convolutional neural network
Deep neural networks
Image classification
Machine learning
r package
Remote sensing
Camera trap
Convolutional neural network
Deep neural networks
Image classification
Machine learning
r package
Remote sensing
- Motion-activated cameras (“camera traps”) are increasingly used in ecological and management studies for remotely observing wildlife and are amongst the most powerful tools for wildlife research. However, studies involving camera traps result in millions of images that need to be analysed, typically by visually observing each image, in order to extract data that can be used in ecological analyses.
- We trained machine learning models using convolutional neural networks with the ResNet-18 architecture and 3,367,383 images to automatically classify wildlife species from camera trap images obtained from five states across the United States. We tested our model on an independent subset of images not seen during training from the United States and on an out-of-sample (or “out-of-distribution” in the machine learning literature) dataset of ungulate images from Canada. We also tested the ability of our model to distinguish empty images from those with animals in another out-of-sample dataset from Tanzania, containing a faunal community that was novel to the model.
- The trained model classified approximately 2,000 images per minute on a laptop computer with 16 gigabytes of RAM. The trained model achieved 98% accuracy at identifying species in the United States, the highest accuracy of such a model to date. Out-of-sample validation from Canada achieved 82% accuracy and correctly identified 94% of images containing an animal in the dataset from Tanzania. We provide an r package (Machine Learning for Wildlife Image Classification) that allows the users to (a) use the trained model presented here and (b) train their own model using classified images of wildlife from their studies.
- The use of machine learning to rapidly and accurately classify wildlife in camera trap images can facilitate non-invasive sampling designs in ecological studies by reducing the burden of manually analysing images. Our r package makes these methods accessible to ecologists.
Led By
Study Area
Gunnison River and Harrison Creek
Project Status
Ongoing
Research Objectives
- To maintain wild brood stocks of whirling disease resistant rainbow trout to supplement hatchery stocks, as necessary.
- To evaluate wild stocks for continued disease resistance.
Project Description
Fishery managers stock whirling disease resistant rainbow trout (known as the Hofer strain) in waters across the state to supplement and recover populations previously lost to whirling disease.
In addition to maintaining hatchery brood stocks (fish used for spawning) of whirling disease resistant rainbow trout, two wild brood stocks have been established to supplement and replace hatchery brood stocks, as necessary. Researchers periodically evaluate that these brood stocks retain resistance to whirling disease. These evaluations allow Colorado Parks and Wildlife biologists and researchers to determine if the resistance characteristics of these populations are changing or remaining static, and ensure that eggs collected from these populations and used to supplement hatchery brood stocks will continue to produce rainbow trout that are resistant to whirling disease.
One of these wild brood stocks is located in Harrison Creek, a tributary of Lake Catamount in Steamboat Springs, Colorado. This wild brood stock is being used to rear crosses of the Hofer and Harrison Lake rainbow trout strains (known as the HxH). Known to be partially resistant to whirling disease, the Harrison Lake strain of rainbow trout originates from Harrison Lake, Montana. Recent research has shown that fish stocked in Harrison Creek return to the creek to spawn, facilitating future wild egg collections. Additionally, resistance to whirling disease is increasing in this population as more HxHs become established.
The other wild brood stock is located in the East Portal of the Gunnison River in the Black Canyon of the Gunnison National Park. Once managed for crosses of the Hofer and Colorado River Rainbow trout strains (known as the HxC), recent research shows that the HxC constituted only a small proportion of the total adult spawning rainbow trout population. Despite this, exposure experiments conducted using eggs from the East Portal showed that these fish had started to develop a resistance to whirling disease, likely a result of low infection levels and continued natural reproduction. Eggs are taken from this brood stock on an annual basis to stock other locations within the Gunnison River, and to maintain the Gunnison River Rainbow trout brood stock in Colorado hatcheries.
Associated Publications
- Fetherman, E. R., and G. J. Schisler. 2016. Sport Fish Research Studies. Federal Aid Project F-394-R15. Federal Aid in Fish and Wildlife Restoration, Job Progress Report. Colorado Parks and Wildlife, Aquatic Wildlife Research Section. Fort Collins, CO.
- Fetherman, E. R., and G. J. Schisler. 2015. Sport Fish Research Studies. Federal Aid Project F-394-R14. Federal Aid in Fish and Wildlife Restoration, Job Progress Report. Colorado Parks and Wildlife, Aquatic Wildlife Research Section. Fort Collins, CO.
- Fetherman, E. R., and G. J. Schisler. 2014. Sport Fish Research Studies. Federal Aid Project F-394-R13. Federal Aid in Fish and Wildlife Restoration, Job Progress Report. Colorado Parks and Wildlife, Aquatic Wildlife Research Section. Fort Collins, CO.
- Fetherman, E. R., and G. J. Schisler. 2013. Sport Fish Research Studies. Federal Aid Project F-394-R12. Federal Aid in Fish Restoration Job Progress Report. Colorado Parks and Wildlife. Aquatic Research Section. Fort Collins, CO.