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G. Kent Webb San Jose State Information Systems [email protected] u Deer Map Data harvested from social media: Flickr, Youtube ly warning predictor of EHD outbreak rce: Googe Trends, searches on eer dying” Deer Management Research Using the Internet: Analysis of Deer- Vehicle Collisions and a Survey of Current Deer Management Issues

G. Kent Webb San Jose State Information Systems [email protected] Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

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Page 1: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

G. Kent WebbSan Jose State

Information [email protected]

Deer MapData harvested from social media:

Flickr, Youtube

Early warning predictor of EHD outbreakSource: Googe Trends, searches on “deer dying”

Deer Management ResearchUsing the Internet: Analysis of Deer-Vehicle Collisionsand a Survey of Current Deer Management Issues

Page 2: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Deer Location and Density is Aggregated,Often at the County Level

Yearly Deer Traffic Deaths, at least: 1.5 million. 2011 Reported Hunt: 6.44 million

The Data Analysis Problem: Deer-Vehicle Collisions Depend on the Conditions at Specific Locations Deer density data is often aggregated at county or regional level MulticollinearitySchwabe et al (2002) findPositive correlation at p < .01 withnumber of collisions andnumber of bucks, butNegative correlation at p < .01 withnumber of collisions andnumber of does(more does, fewer collisions)

Mr. T, Victim of Hit andRun, 2010. Back in the Rut, 2012

Page 3: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Deer Icons in Google Map

Links to photo or video of deer from social media site

Page 4: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Predict High-Risk Deer-Collision Freeway Segments by Using Google Maps to See Where These Deer May Have Access to the Freeway

Kolowksi and Nielson (2008) examined the similarity between bobcat habitat and road habitat to create a technique for mapping wild-life vehicle collision risk. The authors conclude: “Unlike other modeling techniques used to identify risk of road mortality, our method requires little field data collection and relies on readily available digital spatial data.”

Page 5: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Freeway Risk and Collisions

Overlay Risk Map and Data From California Roadkill

Observation System

U.C. Davis Web Site Allowing Users to Post Observations of Wildlife

Collisions

Blue Balloons Mark Collisions

Page 6: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

H1: Deer collisions per mile of freeway are higher in the high risk segments

Table 2, Freeway Deer-Vehicle Collisions in Study Area

Freeway Risk Category

Deer-Vehicle

Collision per Mile

Number of Deer-Vehicle

Collisions

Miles of Freeway

Percent of Deer-

Vehicle Collisions

Proportion of Freeway

Miles

High 0.41818 23 55 79.3 % 10.4 %Low 0.01265 6 474 20.7 % 89.6 %Total 0.05482 29 529 100.0% 100.0 %

Webb, G.K. "Predicting Risk of Deer-Vehicle Collisions Using a Social Media-Based Geographic Information System" (2012) Issues in Information Systems Volume 13, Issue 2. pp. 170-181

Page 7: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Statistical analysis shows the strong correlation between the two sources of data

High Risk Freeway

Low Risk Freeway

Mean Deer-Vehicle Collisions per Mile

0.418182 0.012658

Variance 0.470034 0.012524Observations, Miles of Freeway 55 474

Maximum 3 1Minimum 0 0Null Hypothesis: No difference in the number of deer-vehicle collisions per mile in the high risk and the low risk freeway segmentsDegrees of freedom 54t-stat 4.379884

P(T < t) one tail 0.0000275 *t-Critical value for α = .05 1.673565

* The null hypothesis is rejected at well above the 0.001 confidence level

Page 8: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Analyze Specific Road Conditions UsingGoogle Maps

High risk segment of I-280

Deer habitat on both sides of freeway.

Blue balloonsmarkdeer-vehiclecollisions.

Page 9: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Analyze Using Street View

- Deer spotted in nearby open space- No collisions were reported along this high risk segment of I-280- Little vegetation to block vision or attract deer

Page 10: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Analyze Using Street View

High collision segment on U.S.1 Thick vegetation growing along the road Few deer sighted in the areaVerified with physical inspection of the area

Page 11: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Combined DataCreatesBay Area Deer Map

- Analyze Bias and Information- Independent Data, Many Sources

Google Maps:- Lots of Information- Difficult Analytical Platform- Experimental: Fusion Tables

Page 12: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Internet Project, DeerFriendly.com: Decision Support Site, Environmental Scanning, Knowledge Warehouse, Model Development

58,911 Unique Visitors in 2012

Page 13: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Deer disease a major concern October 27, 2012 Michigan, Royal Oak Daily Tribune... epizootic hemorrhagic disease (EHD) ... “There’s a lot we don’t know about how weather affects the disease. Last year’s mild winter and dry weather this year have affected the abundance of the little insects that transmit the disease... If you believe in global warming, we may see more cases in the future ..." DNR wildlife veterinarian Dan O’Brien

July 2012 Oct 2012

- South Dakota Reduces Tags during 2012 Season Because of EHD- Other States May Reduce Tags This Year- An important issue for a long-term deer model

2012 Searches on EHD

Page 14: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Chronic Wasting Disease (CWD)(Mad Cow for Deer – Prions)

States with First Case of CWD Discovered in 2012

- Pennsylvania, Deer Farm – Some deer escaped, but eventually found and killed- Iowa, Deer Farm (10,000 farms in U.S.)- Texas, Low deer density area along the border with New Mexico near other cases

Wisconsin Legislative Audit Bureau determines culling deer in CWD areas is not effective. Not density – Ecosphere, 2013Deer culls continue to be the main treatment response in other states.

Some recent articles report development of tests for CWD, low accuracy, but do not require killing deer

January, 2013

Page 15: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

A conservation model crafted specifically for Texas November 14, 2012 Austin American-StatesmanThe state has provided super strong private landowner protections for management and access, and it's invented the concepts of modern deer management to control herd numbers [balanced sex and age], enhanced habitat manipulation, supplemental feeding and management of buck harvests to improve the genetic makeup of a population. Those concepts remain somewhat controversial ...“We’re not discounting the North American Model,” says Macy Ledbetter, a private consulting biologist who helped write the document. “It was a wonderful document when it was produced in the late 1800s...

Rank State 2011 Harvest

1 Texas 583,854 (down from 662, 769)

2 Michigan 422,014

3 Mississippi 381,326

32 Oregon 43,223

42 California 10,368 (down from 14,817)

43 Arizona About 10,000, not reported

44 New Mexico About 8,000, not reported

45 Nevada 5,831 (reduced tags)

California deer harvest is51 percent two pointbuckWashington: 24 percentNevada: 30 percent

California Buck to doeratio reported in 15 to100 range

Little public support fortrophy hunting

Page 16: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Review of Wisconsin Deer Program- Led by Texas Deer Biologist, Dr. James Kroll, so concern about imposing the Texas model – didn’t happen

Recommendations - criticized inaccurate deer population models - called for more passive approach to CWD, the approach of killing deer has failed - called for more public input in making decisions (Wisconsin routinely issues press releases for public meetings, not found in California – Nevada hunters calling for more transparency)

Governor's office takes on direct role in hunt management October 12, 2012 South Dakota, AberdeenNews.comWildlife management is at issue, specifically regarding mountain lions, elk, deer and antelope... an outside consultant will be contracted ... to review and advise the state Wildlife Division ... wildlife belong to the people in South Dakota

Page 17: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Nevada – Deer Wars... “We’re overharvesting,” insists Scott Raine, the wildlife commission’s former chairman ... Raine insists the modeling used to estimate Nevada’s mule deer population is based on false assumptions or conjecture and that the numbers are far lower than cited. “They’re just wild guesses,” [Nevada Model on the internet]Hunters, wildlife officials lock horns over whether Nevada mule deer are over-harvested October 27, 2012 RGJ.com

Nevada Hunter: “There are no deer! ... I have lived in Nevada since 1953 and hunted deer since 1962 ...Someone in NDOW needs to start telling the truth about the deer herds in our state...Nevada's deer herds misrepresented November 13, 2012 Elko Daily Free Press, Gene Perry

Page 18: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Studies Reported to Press during 2012 in States with Declining Deer Populations: Only Oregon Related to Deer Hunt ManagementState Suspected Cause State Suspected Cause

New Brunswick Habitat loss, coyote North Dakota Oil Development, Weather

Maine Habitat, coyote Colorado Oil and Gas Development

West Virginia Coyote, deer main diet, 50% decline 10yr

Wyoming Oil and Gas Development

Virginia Habitat, coyote Montana Wolves, mountain lions, bears

North Carolina Coyote Utah Coyotes

South Carolina Coyote Washington Mountain lion, killing 10 to 35% has no impact

Georgia Coyote Oregon Habitat, disease. Population model

Florida - Cypress Water level, pythons Nevada * Not specifically identified

Michigan, Upper Peninsula

Coyotes California Habitat, mountain lion?, NOT coyote (or management)

81 pound coyote or wolf hybrid shot in Missouri in November, previous record is 74 poundsCoyotes, may need to kill 70 percent. * Stewart: No impact of predator control. 2011

Page 19: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

What the public sees when it Googles“Deer Population California”: dfg.ca.gov

Page 20: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Overlay of Estimates for 1962 and 2012Bottom Graph from California Department of Fish and Wildlife Web Site

Too ManyDeer?

Page 21: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

19901992

19941996

19982000

20022004

20062008

20102012

0

100000

200000

300000

400000

500000

600000

700000

800000

900000

0

5000

10000

15000

20000

25000

California Estimated Deer Population (1990 to 2012) and Reported Harvest (Kill)

PopulationHarvest

Year

Population

Harvest

Population data from Sac Bee report sourcing CDFW. Har-vest from CDFW

CDFW attributes 2011 harvest decline to increasein poaching and new internet reporting system. Not seen in other states.

Estimated population assuming hunters havetaken the historical average 3.5 percent: 294 K

Page 22: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

2011ReportedKill

California Reported Deer Kill 1910 into 1990s

Almost to Where Hunting Was Suspended in the PastDebate on Historic Reporting Variation – Hunter Efficiency Has Improved

Tags Issued is a Variable We Can Control

http://www.dfg.ca.gov/wildlife/hunting/deer/docs/habitatassessment/part2.pdf

Page 23: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Similar Pattern of Harvest Data on The Utah Division of Wildlife WebsiteBut Without the Qualifications Seen on The California Site

A Deer Relocation By Helicopter Currently Underway in Utah

2011DeerHarvest

Page 24: G. Kent Webb San Jose State Information Systems g.webb@sjsu.edu Deer Map Data harvested from social media: Flickr, Youtube Early warning predictor of EHD

Wildlife in the U.S. and Deer in California are FallingOut of the Public’s Interest

- Public Outreach, a CurrentTheme in Wildlife Management

Search Volume on “Wildlife”, 2004 to 2012

Search Volume on “Deer” Darker, More Volume