Weekly Wolf Wrap Up!

Miley Cyrus Speaks Out Against Cruel Wolf Killings. For those who've seen the musician's selfies with her pets and trippy animal-themed posts on Instagram, Miley Cyrus' most recent plea for animal rights will come as no surprise.

On Tuesday night, Cyrus called upon her Instagram followers to take action by signing a petition against Canada's massive wolf cull.

In a caption, Cyrus writes that changes are needed "in a world that at times needs to reevaluate its morals when dealing with kindness and compassion towards animals."

In January the British Columbia government began a controversial 5- to 10-year wolf cull, which it claims will protect endangered caribou, one of the wolves' prey.

However, the plans have fallen under criticism from wildlife conservationists who argue that killing hundreds of wolves each year isn't the answer.

In a blog post for Huffington Post Canada, Chris Genovali, executive director of the Raincoast Conservation Foundation, explained the complex origins of caribou endangerment:

"This unscientific and unethical wolf cull is a consequence of oil and gas development, and industrial logging, which have endangered woodland caribou. … Rather than address the real problem, i.e. the destruction of life sustaining caribou habitat, Alberta has chosen to scapegoat wolves … "
Cyrus also delved into the issue's complexities on her Instagram.

As of Wednesday morning, the petition, organized by Pacific Wild, had reached over 196,000 signatures.

In addition to Instagram, Cyrus has also used her music to advocate against animal cruelty. Her latest album, " Miley Cyrus and Her Dead Petz," (released for free on Soundcloud) hints at activists' campaign to #emptythetanks of SeaWorld. In a song titled "Pablo the Blowfish," she sings, "If I could do it again, I'd release you to sea, cause I can't bear to see something wild die in a tank."

The power that musicians have to influence public opinion is nothing to shake a stick at. As a recent analysis of singer Harry Styles' comments about SeaWorld revealed, when popular artists speak about issues near to their heart, people listen.

Living with WolvesConflicts between people and wildlife pose a serious challenge to conservation. Too often, the response to a conflict is to kill the wildlife, an approach that can threaten the survival and recovery of species and does nothing to keep other wildlife from moving in and repeating the behavior. Working with ranchers, Defenders has pioneered many practical solutions to help livestock and wolves coexist by using effective nonlethal deterrents like fladry, range riders, electric fencing and livestock guardian dogs to help protect livestock and build social acceptance for wolves. And, our recently updated publication “Livestock and Wolves” shares these stories and best practices. It covers nonlethal tools, methods and strategies that work, and offers real-life examples of successful solutions devised by livestock producers, agency managers and researchers working together.

California Wolf CountryOn Thursday, the first of a series of public meetings on California’s draft wolf recovery plan took place, and we were there to be a part of it. The state is fast becoming a leader when it comes to wolf recovery in the West. After OR-7 became the first known wolf in the state after nearly 90 years, California protected wolves under the state’s Endangered Species Act. And 83 percent of California voters believe that wolves should be protected and are a vital part of America’s wilderness and natural heritage. Defenders is looking forward to engaging all of the diverse participants – private landowners, representatives of the state’s wildlife department, local community members, conservationists – in productive dialogue to make wolf recovery in the Golden is a success for all.

Save The Endangered Norwegian Wolves!
For thousands of years, large numbers of wolves roamed Norway. Today, there are only about 30 left in the wild, and hunters are lining up in record numbers for licenses to kill half of them this hunting season, which is already well underway and goes through March.

More than 11,000 Norwegian hunters have registered for the chance to shoot 16 wolves. That’s roughly 763 hunters per wolf. You don’t have to be against hunting to know that this isn’t right. We, as human beings in this age of environmental stress and widespread extinction, need to be stewards of nature and take care of what wildlife remains.

Please join me in asking the Norwegian government to end these wolf hunts, so that this amazing animal, on the brink of extinction in Norway, can stand a chance.

Norway is famous for its measured policies, reasoned diplomacy and, above all, its defense of the environment. But that belies what’s going on with wolves, as well as Norwegian brown bears and wolverines. Just 1% of the country has been designated a "wolf zone", in which the animals are allowed to exist. But, even there, only three litters a year are permitted. Once three pairs of wolves have bred, all the rest can be shot.

Hunters, and the government issuing these licenses, claim that “culling” wolves is necessary to protect livestock. But the statistics totally disprove this. Every year, some 2 million sheep are released onto public land without supervision. Around 1,500 of them are killed by wolves. Far more sheep - around 100,000 - die from falling into crevasses, drowning, and disease.

After this hunting season, only 14 wolves would remain, assuming others aren’t killed by illegal hunting. That is not enough to sustain their population.This is extermination, pure and simple, and most Norwegians have already come out against it.

Please join me in asking Norway to halt the wolf hunt immediately and give them a chance to survive in the lands they have lived in for millennia.

LETTER TO
Norwegian Environmental Agency
Head of Communications of the NEA Tore Høyland
Save The Endangered Norwegian Wolves!

US Fish & Wildlife Service: Protect Wolves in Idaho and Montana.
US Fish & Wildlife Service: Protect Wolves in Idaho and Montana
Update #2 4 days ago ▾
Update#2. The collaring of the four wolves in the Frank can serve a greater purpose. This could serve for the better if the monitoring is extended for another five years. Collaring these wolves could give very important information on exactly how bad Idaho's aggressive wolf policies have been. The information could give further evidence that could warrant an emergency relisting or even lead to the wolves being placed back on the Endangered list altogether.

Update #1 5 days ago ▾
UPDATE # 1---Idaho's Fish&Game has collared Four Wolves in the Frank Church Wilderness Area They were only to collar Elk for a count study. When questioned about collaring these wolves Idaho Fish & Game stated that it was a mistake of communication with their agents in the field.. This is just another example of HOW Idaho’s Wolf Management Policy’s are out to Eliminate any wolf they can. This is yet another example of an out of control wolf management policy.

About This Petition
EXTEND THE MONITORING PROGRAM FOR ANOTHER FIVE YEARS

According to the Endangered Species Act, after a species is delisted it must be monitored for five years to ensure the population remains healthy. Unfortunately for the wolves of Idaho and Montana, their monitoring runs out in May of 2016.

Idaho and Montana wolf "management" is allowing more and more wolves to be killed. Over 2,300 wolves have been killed in these two states since the northern Rocky Mountains wolves stopped receiving protection under the Endangered Species Act in 2009.

Idaho and Montana are currently allowing heavy hunting and trapping over long seasons with very few limits. Idaho is even spending thousands in taxpayer funds to kill wolves, both aerially as well as trapping them in federally protected wilderness areas. Given their adversarial treatment of wolves, and a critical assesment of the wolf count program, wildlife advocates such as myself are highly skeptical of the wolf population numbers from these states. The federal government must oversee the population counts, and make sure they are legitimate. 

The population of wolves in these two states are at grave risk of becoming unsustainable, if it hasn't happened already. We request that the United States Fish & Wildlife Service perform their own population count and consider an emergency re-listing of the northern Rocky Mountains wolves under the Endangered Species Act.


Sponsored by: Defenders of Wildlife


This is a crucial time for wildlife. A record number of anti-Endangered Species Act (ESA) measures have been placed in the FY 2016 House and Senate bills that fund the Interior Department and other key wildlife agencies, threatening wolves and other endangered wildlife in America. These measures attempt to block or remove protections for individual species and undermine key sections of the ESA – like making it significantly more difficult for citizens to bring government agencies to court for failing to follow the law.
The ESA has saved so many species on the brink of extinction. Won't you help us protect this bedrock of environmental law so that other imperiled species can be saved?
Urge your Members of Congress to oppose the record number of anti-ESA proposals in Congress!
Demand the MNRF Protects Wolves and Coyotes in Ontario.
Demand the MNRF Protects Wolves and Coyotes in Ontario
Update #3 2 days ago ▾
Hello beautiful protectors of the wild! 

Yesterday I delivered 85000+ signatures to the MNRF from over 20 countries! Amazing! Thank you!

I received word from the ministry that the commenting period has ben extended an extra week so please keep spreading the word. I will deliver extra signatures next week. Also, if you didn't before, please comment directly to the ministry: http://wolvesontario.org/moose/

Update #2 4 days ago ▾
WOW!!!!! 75K+ signatures and counting! I am so excited to deliver these tomorrow to the Ministry. I just wanted to send along a note to Canadian and specifically Ontario signers that you can increase your impact by commenting directly. A local NGO has set up a comment form to make it easier for you: http://wolvesontario.org/moose/

Thanks again for all your support! Together we can save wolves and coyotes in Ontario!

Update #1 6 days ago ▾
Hello everyone!

WOW! Almost 20000 signatures! We will be submitting all signatures to the ministry's registry on Monday, as that's when the comment period ends. If you can, please share the link through your social media so that we can get as many signatures as possible by Monday. Time is of the essence. 

Thanks so much! 

Amelia

About This Petition
The MNR in Ontario is currently proposing new hunting regulations for coyotes and wolves. The new regulations would allow for the hunting of an unlimited amount of coyotes in the province, as well as create new boundaries for wolf hunting that don't protect the at-risk Eastern Wolf. 

By signing today you are helping to protect these keystone species. 

Background: 
In recent years, the moose population of Ontario has declined significantly. The MNRF has decided that the way to deal with this decline is to increase hunting of wolves, though the Moose Project itself has stated that unless the entire pack is killed it won't make a significant difference and increased hunting is unlikely to take down an entire pack. 

The new regulations also take away the "seal" that hunters are required to purchase to hunt wolves and coyotes. The money that is collected from these seals is used for further research into wolf and coyote populations. By taking away this income, the research into the populations of wolves and coyotes in the province will be minimal and therefore accurate management practices will be impossible. 

By signing today you are speaking up as a voice for the wolves and coyotes in the province.
To keep things simple, this Petition stated its case without referring to the source literature. That's okay if you know where to find it, but here a couple of references and summaries, in case they're helpful. If I've made any errors in the summaries, those errors are mine alone, and I'll be happy to correct them.

The article about the responses of coyotes to food availability and "exploitation" (Gese 2005) describes a seven-year study by USDA Wildlife Services in southeastern Colorado. The "exploitation" was the large-scale killing of coyotes in 1987 and 1988 (44%-75% mortality) in one of the study areas. The "response" of the coyote population to the "exploitation" was that the surviving coyotes kept their same territories, but had smaller packs, younger average age, younger reproductive age, double-size litters, and more female pups than male pups. The population recovered to its original size in about eight months. There were no livestock in the study area (the favored prey of the coyotes was rabbit), so this study didn't learn about possible effects on livestock depredation.

The article about the effects of wolf-killing programs on livestock depredation (Wielgus and Peebles 2014) describes 25 years of data in Idaho, Montana and Wyoming. As expected, in years when there were more livestock or more breeding wolf pairs, there was more depredation. However, counter to the goals of the wolf-killing programs, it turned out that (unless wolf mortality caused by man was more than 25% each year) when more wolves were killed, there was *more* livestock depredation the next year. Of course, the purpose of those programs was to *lower* depredation, not increase it. But that's not what happened; go figure. Or keep reading about the predictable effects of fractured pack structure: more breeding wolf pairs, and more livestock depredation. And the expense: "mortality rates exceeding 25% are unsustainable over the long term." Programs like that cost a lot already, and stepping them up to higher levels of destruction would cost even more--financially and ecologically. So the wolf-killing programs aren't such a great idea. The authors recommend non-lethal controls backed up by targeted removals as necessary. Non-lethal controls remove attractants and add deterrents to keep predators away from livestock. They can include fencing, fladry, lights, rotational grazing, predator-resistant groups, livestock guardian animals, electronic alarms, range riders, carcass disposal, etc.

== References ==
Gese, Eric M. 2005. "Demographic and Spatial Responses of Coyotes to Changes in Food and Exploitation." In Wildlife Damage Management Conference, 271–85. USDA, APHIS, Wildlife Services.http://digitalcommons.unl.edu/cgi/viewcontent.cgi?article=1118&context=icwdm_wdmconfproc
Wielgus, Robert B., and Kaylie A. Peebles. 2014. "Effects of Wolf Mortality on Livestock Depredations." PLoS ONE 9 (12): e113505. doi:10.1371/journal.pone.0113505.http://dx.doi.org/10.1371/journal.pone.0113505.

Abstract


Predator control and sport hunting are often used to reduce predator populations and livestock depredations, – but the efficacy of lethal control has rarely been tested. We assessed the effects of wolf mortality on reducing livestock depredations in Idaho, Montana and Wyoming from 1987–2012 using a 25 year time series. The number of livestock depredated, livestock populations, wolf population estimates, number of breeding pairs, and wolves killed were calculated for the wolf-occupied area of each state for each year. The data were then analyzed using a negative binomial generalized linear model to test for the expected negative relationship between the number of livestock depredated in the current year and the number of wolves controlled the previous year. We found that the number of livestock depredated was positively associated with the number of livestock and the number of breeding pairs. However, we also found that the number of livestock depredated the following year was positively, not negatively, associated with the number of wolves killed the previous year. The odds of livestock depredations increased 4% for sheep and 5–6% for cattle with increased wolf control - up until wolf mortality exceeded the mean intrinsic growth rate of wolves at 25%. Possible reasons for the increased livestock depredations at ≤25% mortality may be compensatory increased breeding pairs and numbers of wolves following increased mortality. After mortality exceeded 25%, the total number of breeding pairs, wolves, and livestock depredations declined. However, mortality rates exceeding 25% are unsustainable over the long term. Lethal control of individual depredating wolves may sometimes necessary to stop depredations in the near-term, but we recommend that non-lethal alternatives also be considered.

Introduction


Predator control and sport hunting are often used to reduce predator populations, livestock depredations, and increase social acceptance of large carnivores such as brown bears (Ursus arctos[1], wolves (Canis lupus[2], cougars (Puma concolor[3], jaguars (Panthera onca[4], lions (Panthera leo[5], leopards (Pantera pardus[6], and others [7].

Gray wolves (our model animal) are currently being hunted in Idaho, Wyoming and Montana, in part, to reduce livestock depredations [8]. However, to our knowledge, the long-term effectiveness of lethal wolf control to reduce livestock depredations has not yet been rigorously tested. For example, Bradley and Pletscher [9] predicted that breeding pairs are responsible for most livestock depredations because they are bound to the den site, not natural prey distribution [10]. Brainerd et al. [11] predicted that increased wolf mortality could result in fracture of pack structure and increased breeding pairs. If this is the case, increased mortality of wolves could result in increased breeding pairs and livestock depredations following lethal control. In other species, Collins et al. [12] and Treves et al. [13] found increased damages by black bears (Ursus americanus) following high remedial mortality and Peebles et al. [14] found that increased mortality of cougars resulted in increased livestock depredations because of social disruption. In this paper we test the widely accepted, but untested, hypothesis that increased lethal control decreases wolf livestock depredations in a large scale (tri-state) long-term (25 year) quasi-experimental [15]. The “remedial control” hypothesis predicts that livestock depredations will decrease following increased lethal control.

Methods


We obtained the confirmed number of cattle (Bos primigenius) and sheep (Ovis aries) depredated, wolf population estimates, number of breeding pairs, and the number of wolves killed in the wolf-occupied area of each state for each year between 1987–2012 from United States Fish and Wildlife Services Interagency Annual Wolf Reports [16] (Table S1). The number of wolves killed were wolves that were killed through control methods including wolves killed legally by livestock owners or through government control methods, these numbers do not include other sources, including natural mortality. Only the total numbers of livestock killed, not the number of confirmed livestock depredation incidents, were available from the USFW database.

Numbers of livestock were similarly obtained from United States Department of Agriculture National Agricultural Statistics Service for counties where wolves are present [17] (Table S1). Livestock numbers for individual properties were not available so livestock tallies were made across the tri-state area using counts from wolf occupied counties.

Following Peebles et al. [14], we used forward selection, negative binomial general linearized models to assess the relationship between livestock depredations and numbers of livestock, wolves, breeding pairs, and wolves killed. We used this method because depredations were over-dispersed and consisted of 0 to positive integer count data with a variance exceeding the mean [18]. The best statistical model was then selected using the lowest AIC (Akaike Information Criterion) and highest log-likelihood [19]. The rate ratio, analogous to odds-ratio, was computed from the coefficients to aid in interpreting the results [20]. For example, a rate ratio of 1.0 for any independent variable means the effect on the dependent variable is unchanged. A rate ratio of 1.5 means the odds are increased by 50%.

To establish directionality, we analyzed the effect of independent variables in year 1 on number of livestock depredated in year 2. This one year time-lag between control kills and depredations removes the directional effect of depredations causing kills. After assessing the models, we plotted and interpreted the most important independent variables against depredations to provide a visual representation of model terms. Only the independent variables that had a rate ratio larger than 1.01or smaller than 0.99, meaning the change in the mean number of livestock depredated was increased or decreased by at least 1%, were examined further. We conducted our regressions on the entire tri-state area and the 3 separate states- but only report the larger tri-state area here because the results were basically the same in all cases (Figures S1 and S2).

Results


The total number of livestock depredated between January 1987- December 2012 in the tri-state area was 5670; 1853 were cattle and 3723 were sheep. Sample size for paired depredations in year 2 and wolf and cattle numbers and wolves killed in year 1 was: 17 years for Idaho, 17 years for Wyoming, and 25 years for Montana (N total  = 59).

All of the well performing models (AIC<466) for cattle depredated included the # wolves killed, # of breeding pairs and the # of wolves killed by # breeding pairs interaction (Table 1) - and the coefficients for these terms were very similar across models. The best models were #10, #12 and #13. The 1st model was g(y)  =  exp [1.307+0.05078(wolves killed through control methods) +0.07979(# of breeding pairs) +2.116×10−8(# of cattle) – 1.343×10−3(# breeding pairs*wolves killed) – 2.980×10−8(# of cattle*wolves killed)]. The 2nd model was g(y)  =  exp [1.142+0.05293(wolves killed through control methods) +0.08791(# of breeding pairs) +2.674×10−7(# of cattle) – 0.001377(wolves killed*# of breeding pairs) – 1.701×10−8(# of cattle*# of breeding pairs)]. The 3rd model was g(y)  =  exp [1.182+0.05795(wolves killed through control methods) +0.07783(# of breeding pairs) +2.112×10−7(# of cattle) – 0.001378(wolves killed*# of breeding pairs) – 7.804×10−9(# of cattle*# of wolves killed)]

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Table 1. AIC and log-likelihood values for forward selection of main effects and interaction effects models of cattle depredations
doi:10.1371/journal.pone.0113505.t001

In both models all of the main effects and some two way interactions were found to be statistically significant (Table 2). The number of wolves killed in year one was positively related to the number of cattle depredated the following year (rate ratios  = 1.05, 1.05 and 1.06, z = 5.67 and 5.66, 4.69, P<0.001) (Figure 1). For each additional wolf killed the estimated mean number of cattle depredated the following year increased by 5 to 6%. The number of breeding pairs was also positively related to the number of cattle depredated (rate ratios  = 1.08, 1.09 and 1.08, z = 6.28, 4.87 and 6.04, P = 0.0336 and <0.001) (Figure 2). For each additional breeding pair on the landscape the estimated mean number of cattle depredated the following year increased by 8 to 9%. Breeding pairs were highly correlated with numbers of wolves (Table S2).

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Figure 1. Wolves killed vs cattle depredated.
Number of wolves killed through control methods the previous year versus the number of cattle depredated the following year. The dashed lines show the upper and lower limits of the 95% confidence interval for the best fit line.
doi:10.1371/journal.pone.0113505.g001

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Figure 2. Number of breeding pairs vs cattle depredated.
Number of breeding pairs present on the landscape the previous year versus the number of cattle depredated the following year. The dashed lines show the upper and lower limits of the 95% confidence interval for the best fit line.
doi:10.1371/journal.pone.0113505.g002

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Table 2. Summary of best model for cattle depredated.
doi:10.1371/journal.pone.0113505.t002

There was also one important 2-way negative interaction for the relationship between the increasing numbers of wolves killed and decreasing breeding pairs on livestock depredations (rate ratios  = 0.99, z = −5.39, −5.49 and −5.12, P<0.001. In our models, the main effects of wolves killed was increased depredations. But the negative interaction effect in the model shows that depredations ultimately declined with increased wolf kills as number of breeding pairs decreased. These conflicting effects on livestock depredations are represented here as proportion of wolves killed vs. cattle depredations in (Figure 3). Depredations increased with increasing wolf mortality up to about 25% mortality but then depredations declined when mortality exceeded 25%.

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Figure 3. The proportion of wolves killed vs cattle depredated.
Proportion of wolves killed the previous year versus the number of cattle depredated the following year. The dashed lines show the upper and lower limits of the 95% confidence interval for the best fit line.
doi:10.1371/journal.pone.0113505.g003

One model out of 53 (Table 3) was also selected for determining which factors may influence the number of sheep depredated the following year (Table 4). The model was g(y)  =  exp [−10.499+0.05539(minimum wolf population) +0.03883(wolves killed through control methods) +3.058×10−5(cattle) +2.077×10−4(sheep) – 5.116×10−4(wolves killed*wolf population) – 4.932×10−7(wolves killed*cattle) – 1.159×10−7(wolf population*cattle) – 3.712×10−6(wolves killed*sheep) – 6.827×10−7(wolf population*sheep) – 3.408×10−10(cattle*sheep) +6.532×10-10(wolves killed*wolf population*cattle) +4.819×10−9(wolves killed*wolf population*sheep) +3.682×10−12(wolves killed*cattle*sheep) – 4.336×10−15(wolves killed*wolf population*cattle*sheep)].

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Table 3. AIC and log-likelihood values for forward selection of main effects and interaction effects models of sheep depredations.
doi:10.1371/journal.pone.0113505.t003

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Table 4. Summary of best following year sheep depredated models.
doi:10.1371/journal.pone.0113505.t004

Both of the main effects and one interaction effect were significant in this model. Once again, the number of wolves killed was positively related to the number of sheep depredated the following year (rate ratio  = 1.04, z = 2.218, P = 0.026) (Figure 4). For each additional wolf killed the estimated mean number of sheep being depredated the following year increased by 4%. The minimum wolf population was also positively related to the number of sheep depredated the following year (rate ratio  = 1.06, z = 3.220, P = 0.001) (Figure 5). For each additional wolf on the landscape the estimated mean number of sheep being depredated the following year increased by 6%. The number of cattle and sheep were found to be positively related to the number of sheep depredated but the coefficient was negligible (rate ratios  = 1.00 and 1.00, z = 4.718 and 3.320, P = <0.001 and 0.001) which results in an increase of sheep depredated the following year by 1.00 or less than 1%. However, as with cattle, there was an important 2-way negative interaction. Sheep depredations increased with increasing wolf mortality rate up until about 25%, then depredations began to decline after mortality exceeded 25% (Figure 6).

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Figure 4. Wolves killed vs sheep depredated.
Number of wolves killed through control methods the previous year versus the number of sheep depredated the following year. The dashed lines show the upper and lower limits of the 95% confidence interval for the best fit line.
doi:10.1371/journal.pone.0113505.g004

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Figure 5. Minimum wolf population vs sheep depredated.
Minimum year end wolf population the previous year versus the number of sheep depredated the following year. The dashed lines show the upper and lower limits of the 95% confidence interval for the best fit line.
doi:10.1371/journal.pone.0113505.g005

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Figure 6. Proportion of wolves controlled versus the number of sheep depredated.
Proportions of wolves killed through control methods the previous year versus the number of sheep depredated the following year. The dashed lines show the upper and lower limits of the 95% confidence interval for the best fit line.
doi:10.1371/journal.pone.0113505.g006

Discussion


Our results do not support the “remedial control” hypothesis of predator mortality on livestock depredations the following year. However, lethal control of wolves appears to be related to increased depredations in a larger area the following year. Our results are supported by the findings of Harper et al. (2008) in Minnesota where they found that across the state (large scale) none of their correlations supported the hypothesis that killing a high number of wolves reduced the following year's depredations. Harper et al also found that trapping and not catching wolves decreased depredations more than no trapping at all, suggesting that a mere increase in human activity at depredation sites reduced further depredations by those wolves in their study area. By contrast, Bjorge and Gunson (1985) found reducing the population from 40 to 3 wolves in 2 years in Alberta (a 10 fold reduction to near extirpation) resulted in a decline of livestock depredations for two years - followed by subsequent recolonization and increased depredations thereafter. Tompa (1983) also found that lethal control prevented conflict for more than a year in some areas of British Columbia. It should be noted that these 2 studies examined wolf control and livestock depredations at a fine scale (grazing allotment or wolf pack territory or management zone). They did not examine wolf control and livestock depredations at a larger scale (wolf occupied areas) as was done by Harper et al. (2008) and us (this study). It appears that wolf control is associated with reduced depredations at the local wolf pack scale but increased depredations at the larger wolf population scale. This appears consistent with Treves et al. (2005) prediction that the removal of carnivores generally only achieves a temporary reduction in livestock depredations locally when immigrants can rapidly fill the vacancies.

There were several different factors that influenced the number of livestock depredated the following year by wolves. In order of importance, based on the values of the rate ratios, these include: the number of wolves removed through control methods, the number of breeding pairs, the minimum wolf population, and the number of livestock on the landscape. Consistent with expectations, each additional breeding pair on the landscape increased the expected mean number of cattle depredated by 8 to 9% and each additional wolf on the landscape increased the expected mean number of sheep depredated by 6%. Cattle were most affected by breeding pairs and sheep by wolves – perhaps because it takes more than one wolf (a pack) to kill a relatively larger cow and only one wolf to kill a smaller sheep. However, contrary to the “remedial control” hypothesis, each additional wolf killed increased the expected mean number of livestock depredated by 5–6% for cattle and 4% for sheep. It appears that lethal wolf control to reduce the number of livestock depredated is associated with increased, not decreased, depredations the following year, on a large scale – at least until wolf mortality exceeds 25%. Why 25%? The observed mean intrinsic growth rate of wolves in Idaho, Wyoming, and Montana is about 25% [21]. Therefore, once anthropogenic mortality exceeds 25%, the numbers of breeding pairs and wolves must decline – resulting in fewer livestock depredations.

Below 25% mortality, lethal control may increase breeding pairs and wolves through social disruption and compensatory, density dependent effects. For example, wolf control efforts occur year round and often peak during grazing season in areas with livestock depredations[22][23]. However, if control takes place during the breeding season and a member of the breeding pair is removed it may lead to pack instability and increased breeding pairs [24][10]. Furthermore, loss of a breeder in a pack during or near breeding season can result in dissolution of territorial social groups, smaller pack sizes and compensatory density dependent effects – such as increased per-capita reproduction [11][25][26]. Culling of wolves may also cause frequent breeder turnover [11] and related social disruption – which can result in reduced effective prey use (through loss of knowledge of prey sources and ability to subdue prey) which may also result in increased livestock depredations [27][28]. All of these effects could potentially result in increased livestock depredations.

We would expect to see increased depredations, wolves killed, and breeding pairs as the wolf population grows and recolonizes the area - but our data suggest that lethal control exacerbates these increases. The secondary effects of time, wolf population growth rate, wolf occupied area, and wolf population size on depredations were already subsumed in the primary main effect terms of breeding pairs (cattle) and wolves (sheep), so those secondary effects cannot account for the positive effects of wolf kills on depredations. We do not yet know the exact mechanism of how increased wolf mortality up to ≤25% results in increased livestock depredations, but we do know that increased mortality is associated with compensatory increased breeding pairs, compensatory numbers of wolves, and depredations [24][10][27],[28][11][26]. Further research is needed to determine the exact causal mechanism(s). Annual mortality in excess of 25% will reduce future depredations, but that mortality rate is unsustainable and cannot be carried out indefinitely if federal relisting of wolves is to be avoided. Furthermore, a 5% (sheep) and 5% (cattle) kill rate of wolves yields the same number of cattle and sheep depredations as a 35% (cattle) and 30% (sheep) kill rate (Figures 3 & 6), but the 30% or 35% rate is unsustainable for wolf population persistence and the 5% rate is not. The worst possible case appears to be a high mortality rate at about 20–25%, since this corresponds to a “standing wave” of the highest livestock depredations. Further research is needed to test if this high level of anthropogenic wolf mortality (25%) is associated with high levels of predation on natural prey such as deer and elk.

Further research is also needed to account for the limitations of our data set. The scale of our analysis was large (wolf occupied areas in each state in each year) and the scale of some other studies were small (wolf packs). Simultaneous, multi-scale analysis (individual wolf packs, wolf management zones, and wolf occupied areas) may yield further insights.

Although lethal control is sometimes a necessary management tool in the near-term, we suggest that managers also consider testing non-lethal methods of wolf control [29] because these methods might not be associated with increased depredations in the long-term.

Supporting Information

Figure_S1.tif
Proportion of wolves harvested vs cattle depredated. Proportion of wolves harvested the previous year in each state (Montana, Idaho and Wyoming) versus the number of cattle depredated the following year.

Figure S1.


Proportion of wolves harvested vs cattle depredated. Proportion of wolves harvested the previous year in each state (Montana, Idaho and Wyoming) versus the number of cattle depredated the following year.
doi:10.1371/journal.pone.0113505.s001

(TIF)

Figure S2.


Proportion of wolves harvested vs sheep depredated. Proportion of wolves harvested the previous year in each state (Montana, Idaho and Wyoming) versus the number of sheep depredated the following year.
doi:10.1371/journal.pone.0113505.s002

(TIF)

Table S1.


Data by state, 1987–2012. Data for all variables used in the analysis grouped by state from 1987–2012.
doi:10.1371/journal.pone.0113505.s003

(DOCX)

Table S2.


Pearson correlation matrix. Pearson correlation matrix for independent variables: cattle, sheep, minimum wolf population, wolves harvested and number of breeding pairs.
doi:10.1371/journal.pone.0113505.s004

(DOCX)

Acknowledgments


This analysis and paper benefitted from the insights and comments of Hilary Cooley (U.S. Fish and Wildlife Service), and John Pierce, Donny Martorello, Brian Kertsen, Ben Maletzke, and Stephanie Simick (Washington Department of Fish and Wildlife).

Author Contributions

Conceived and designed the experiments: RBW KAP. Performed the experiments: RBW KAP. Analyzed the data: RBW KAP. Contributed reagents/materials/analysis tools: RBW KAP. Wrote the paper: RBW KAP.

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