Archive by Author | Sarah Cameron

Wisconsin Turkey

Snapshot Saturdays are a weekly feature on the Wisconsin Department of Natural Resource’s Facebook page. Give them a Like to keep up with recent DNR news and to view the weekly Snapshot Saturdays. 

Restoration of the wild turkey population remains one of the greatest wildlife management success stories in Wisconsin. In fact, turkey are the fourth most common animal captured on Snapshot Wisconsin cameras accounting for 4% of the wildlife photos behind deer, squirrel and raccoon.

Check out this tom displaying in front of a Marathon County Snapshot Wisconsin camera!

To learn more about turkey management in Wisconsin, visit “Ecology of Wild Turkey in Wisconsin”. Interested in hosting your own Snapshot Wisconsin camera? Visit our webpage to find out how to get involved: https://dnr.wi.gov/topic/research/projects/snapshot/.

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Snapshot Saturday: June 29th, 2019

Did you know that black bear have short, curved claws that make them exceptional tree climbers? Climbing trees allows a bear to take refuge from predators, gather food and even take a break. Keep an eye out (or up) for bears this summer!

Check out this bear cub captured on a Polk County Snapshot Wisconsin camera learning the ropes.

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Interested in hosting your own Snapshot Wisconsin camera? Visit our webpage to find out how to get involved: https://dnr.wi.gov/topic/research/projects/snapshot/.

Snapshot Saturday: June 22nd, 2019

There are many telltale signs of summer, but our favorite here at Snapshot Wisconsin is the appearance of fawns on camera. Fawns are born with reddish brown coats and a collection of white spots; this coloration helps them blend in with the forest until they begin molting into their winter coats.

Have you “spotted” any fawns on your cameras yet?

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Did you know you can view and classify photos collected from Snapshot Wisconsin cameras across the state at www.SnapshotWisconsin.org? It’s a fun activity for the whole family!

Snapshot Saturday: June 15th, 2019

Think of the iconic, raspy scream you hear from a raptor during a television show or movie. Did you know that it often belongs to the red-tailed hawk? No matter the species on screen, the call is often voiced-over by this hawk’s mighty and distinctive screech.

Check out this red-tailed hawk captured on a Dodge County Snapshot Wisconsin camera (you’ll have to imagine the sound yourself!)

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Interested in hosting your own Snapshot Wisconsin camera? Visit our webpage to find out how to get involved: https://dnr.wi.gov/topic/research/projects/snapshot/.

Snapshot Wisconsin and the WWOA

WWOAAre you interested in seeing more wildlife on your Snapshot Wisconsin camera? The Wisconsin Woodland Owners Association (WWOA) is a nonprofit organization whose mission is to foster and encourage sustainable management of Wisconsin’s private woodlands.

Improving the habitat on your lands is not only beneficial for you, but for the wildlife in your woods as well! Members of WWOA receive their quarterly publication of Wisconsin Woodlands filled with ways to improve your woodlands and be stay informed about workshops, conferences and educational field-days conducted by forestry professionals.

For more information, visit www.WisconsinWoodlands.org. To learn about other woodland owner organizations, visit this DNR webpage.

Snapshot Saturday: June 8th, 2019

True to their name, all bobcats share their distinctive, bobbed tails, but no two bobcats are made the same. Bobcat coats can vary so greatly that they can even be used to identify specific individuals during research projects. Check out this Clark County bobcat captured on a Snapshot Wisconsin trail camera!

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Did you know you can view and classify photos collected from Snapshot Wisconsin cameras across the state at www.SnapshotWisconsin.org? It’s a fun activity for the whole family!

June Volunteer of the Month

June’s Volunteer of the Month is
Ralph from Sauk County!

June’s Volunteer of the Month is Ralph from Sauk County! Ralph has been a Snapshot Wisconsin trail camera host for over two years. Growing up on a farm Ralph enjoyed rambling around the fields and forests, and although he spent his career as a machinist, his love for the forest endured. His motivation for joining Snapshot Wisconsin and hosting a trail camera was to examine several questions he had about his woods, including what predator-prey relationships existed and how many deer were on the landscape.

Volunteer of the Month

In addition to volunteering with Snapshot Wisconsin, Ralph is also the chair of the Chippewa Valley Chapter of the Wisconsin Woodland Owners Association (WWOA). As an active member of WWOA, Ralph enjoys helping other woodland owners learn how to sustainably manage and preserve their woodlands for present and future generations.

Thank you, Ralph! Thank you to all of our trail camera hosts and Zooniverse volunteers for helping us discover our wildlife together.

Snapshot Saturday: June 1st, 2019

We don’t know exactly how this scene ended on this Snapshot Wisconsin camera, but we are guessing it wasn’t pretty. What interesting combinations of species have you captured on your trail camera?

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Interested in hosting your own Snapshot Wisconsin camera? Visit our webpage to find out how to get involved: https://dnr.wi.gov/topic/research/projects/snapshot/.

May Science Update: Maintaining Quality in “Big Data”

Snapshot Wisconsin relies on different sources to help classify our growing dataset of more than 27 million photos, including our trail camera hosts, Zooniverse volunteers and experts at Wisconsin DNR. With all these different sources, we need ways to assess the quality and accuracy of the data before it’s put into the hands of decision makers.

A recent publication in Ecological Applications by Clare et. al (2019) looked at the issue of maintaining quality in “big data” by examining Snapshot Wisconsin images. The information from the study was used to develop a model that will help us predict which photos are most likely to contain classification errors. Because Snapshot-specific data were used in this study, we can now use these findings to decide which data to accept as final and which images would be best to go through expert review.

Perhaps most importantly, this framework allows us to be transparent with data users by providing specific metrics on the accuracy of our dataset. These confidence measures can be considered when using the data as input for models, when choosing research questions, and when interpreting the data for use in management decision making.

False-positive, false-negative

The study examined nearly 20,000 images classified on the crowdsourcing platform, Zooniverse. Classifications for each specie were analyzed to identify the false-negative error probability (the likelihood that a species is indicated as not present when it is) and the false-positive error probability (the likelihood that a species is indicated as present when it is not).

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Figure 2 from Clare et al. 2019 – false-negative and false-positive probabilities by species, estimated from expert classification of the dataset. Whiskers represent 95% confidence intervals and the gray shading in the right panel represents the approximate probability required to produce a dataset with less than 5% error.

The authors found that classifications were 93% correct overall, but the rate of accuracy varied widely by species. This has major implications for wildlife management, where data are analyzed and decisions are made on a species-by-species basis. The graphs below show how variable the false-positive and false-negative probabilities were for each species, with the whiskers representing 95% confidence intervals.

Errors by species

We can conclude from these graphs that each species has a different set of considerations regarding these two errors. For example, deer and turkeys both have low false-negative and false-positive error rates, meaning that classifiers are good at correctly identifying these species and few are missed. Elk photos do not exhibit the same trends.

When a classifier identifies an elk in a photo, it is almost always an elk, but there are a fair number of photos of elk that are classified as some other species. For blank photos, the errors go in the opposite direction: if a photo is classified as blank, there is a ~25% probability that there is an animal in the photo, but there are very few blank photos that are incorrectly classified as having an animal in them.

Assessing species classifications with these two types of errors in mind helps us understand what we need to consider when determining final classifications of the data and its use for wildlife decision support.

Model success

When tested, the model was successful in identifying 97% of misclassified images. Factors considered in the development of the model included: differences in camera placement between sites; the way in which Zooniverse users interacted with the images; and more.

In general, the higher the proportion of users that agreed on the identity of the animal in the image, the greater the likelihood it was correct. Even seasonality was useful in evaluating accuracy for some species – snowshoe hares were found to be easily confused with cottontail rabbits in the summertime, when they both sport brown pelage.

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Not only does the information derived from this study have major implications for Snapshot Wisconsin, the framework for determining and remediating data quality presented in this article can benefit a broad range of big-data projects.

Snapshot Saturday: May 25th, 2019

In addition to making excellent back-scratchers, trees also offer a tool for black bear to communicate with one another. These so called “rub trees” assist bears in shedding their winter coats while leaving behind their scent, making their presence known to passersby.

Check out this black back and their rub tree captured on a Marinette County Snapshot Wisconsin camera!

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Did you know you can view and classify photos collected from Snapshot Wisconsin cameras across the state at www.SnapshotWisconsin.org? It’s a fun activity for the whole family!