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This analysis says # wolves has "No Effect" on # wolf depredations!

Posted by wielgus on 12 Feb 2016 at 17:55 GMT

Re-Review of PONE-D-15-15642 “Wolf lethal control and livestock depredations: counter-evidence from respecified models” by Niraj Poudyal, Nabin Baral, and Stanley T. Asah.

My initial concerns and objections remain.

The authors claim that the major concerns expressed (strongly by reviewer #1, somewhat by reviewer #2, very strongly by reviewer #4 - myself) regarding co-linearity between their “most important” time series variable and: # of wolves, # of breeding pairs, # of wolves killed are of no real concern. I quote “The explanatory variables were somewhat correlated but not perfectly correlated, so multicollinearity is not a serious problem”.

Please see the below attached plots and R2 values of the collinearity. The R2 for wolves vs. year ranges from .91 to 0.97 – a near perfect correlation.

The same goes for breeding pairs vs. year:

And wolves killed vs. year:

In this case, as in many other ecological problems, time is auto-correlated with the biological parameters of real interest (population size, population growth rate, mortality rate, predation rate, depredation rate, etc. etc). That is why no ecologists use time as an explanatory variable for number of animals next year, harvestable surplus, or livestock depredations. Instead, ecologists use numbers of animals last year, reproductive rate, and number of deaths to explain numbers of animals or depredations this year. As I previously stated: time explains everything, but explains nothing.

Indeed, I quote the authors again “Nowhere in this rebuttal have we mentioned that time explains anything. We used the time index as a control variable”

But because time is so strongly auto-correlated with the real variables of interest – it cannot be used as a control either. For example, on Page 7, bottom paragraph, the authors state “Only the number of wolves killed remained significant in our replication: the other two explanatory variables of the original model were no longer significant. The sign of the number of wolves killed was negative in our case”.

In addition they forgot to mention – the sign of the number of breeding pairs at time t was positive. More breeding pairs actually means fewer depredations!

In other words – their model showed that number of wolves and number of breeding pairs of wolves had no effect of livestock depredations by wolves at all, or had a benefitial effect, if any (Table 1). Wow! This is a major paradigm shift! Predators have no effect (or a good effect) on the number of prey killed! It makes no difference if there are 10 wolves, 100 wolves, 1,000 wolves, or 10,000 wolves. Wolves have nothing to do with wolf depredations on livestock. Revise all the ecology textbooks and wildlife management plans. It’s a new world!

Of course, this is all absolute nonsense. The only reason these results were obtained was because the real biological variables of interest (# wolves, # breeding pairs, # wolves killed) were strongly auto-correlated with time, and time subsumed all of them. The wolf variables were simply smoothing variables added to improve the fit of the completely synthetic, non-biological time model.

Before submitting my original paper for publication in this journal, it was reviewed by wolf biologists from the Washington Department of Fish & Wildlife, Idaho Department of Fish and Game, Montana Fish, Wildlife and Parks, Wyoming Department of Fish and Game, and the US Fish and Wildlife Service. All of these biologists know that wolves and livestock depredations were auto-correlated with time, and I explained that is why I was leaving that variable out of the analyses. All understood my approach, and to my knowledge, agreed (since none suggested using time as a causative biological variable).

The authors of this paper conclude and argue that killing wolves reduced depredations next year - contradictory to my findings ….but they could have just as easily concluded and argued that number of live wolves had no effect (or a benefitial effect) – also contradictory to my findings.

The authors piled on layers and layers of statistical mumbo-jumbo and jiggery-pokery to try to explain their results, get published, and perhaps slay a well-known carnivore population specialist – but the bottom line is that this paper is biological nonsense. There are very good reasons that ecologists do not use time as an explanatory or controlling variable in their investigations – unfortunately these authors seem unaware of that practice.

Even some reviewers were swayed by their statistical jargon – so many readers would also likely be. Wolf haters and policy makers would jump on this paper as justification for widespread killing of wolves. This is a dangerous paper for wolves and ecology and I sincerely hope it is not published.

Robert Wielgus

Competing interests declared: This paper tries to refute my previous paper

RE: This analysis says # wolves has "No Effect" on # wolf depredations!

nbaral replied to wielgus on 12 Feb 2016 at 18:47 GMT

Authors’ Response: Thank you very much for plotting the variables against time. These plots look beautiful. Yes, we completely agree with your point these variables have trends as indicated by high R2 values. Your argument (based on those graphs) is the exact reason why the time index should be included in modeling the data.

You have mentioned that “there are very good reasons that ecologists do not use time as an explanatory or controlling variable in their investigations”. We would like to know what those good reasons are. In our previous response, we provided some references regarding how ecologists actually address the time variable in their investigations.

Where did you find that more breeding pairs means fewer depredations in our manuscript? If you’re making a reference to Table 1 then that is misinterpretation of the result. The positive coefficient of the number of breeding pairs should be interpreted as more breeding pairs actually means more depredations.

The number of wolves and the number of breeding pairs were highly correlated, so there was no need to include both the variables in the models. We ran models with the number of wolves too, but found that the number of breeding pairs was a better predictor so we presented this variable only in the final models. We know substantially that the number of wolves, their breeding pairs and number of livestock depredations are related, but the goal here is to test whether those relationships are reflected in the empirical data and over time—that is the fundamental impetus of time series analysis. It is not always the case that empirical findings support substantial claims. One instance of not finding empirical support for a theoretical claim would not require revising all the ecology textbooks and wildlife management plans. We hope that this addresses your major worry.

Scientific findings are always open for contest. The results gain their legitimacy based on logics and reasons not based on authority. We refuted the results based on reasons but not on feelings. We don’t have anything against you personally; our only intention is to let the truth emerge through debates and discussions. We consider you as a well-known carnivore population specialist and wish you all the best for your successful and productive career.

We are neither for nor against the killing of wolves for management purposes by concerned authorities. We strongly believe that managers on the field should decide how to manage wildlife population informed by the best available science to them. Throughout the history, science is used, abused, construed and misconstrued by people to promote their agendas. As a producer of scientific knowledge, we don’t have control over how the knowledge would be used in the real world. But the fear of misuse of knowledge should not be a barrier in the production of scientific knowledge. If our conservation policies are based on “wishy-washy” science, then we cannot expect much from such policies for the betterment of this planet. We don’t believe that the findings of this rebuttal would lead to widespread killings of wolves. Critical consumers of science would know how to interpret the results and translate those results into management actions. Plus, as human dimensions scholars, we actually understand the line between advocacy and science. We do not conduct the scientific practice with worries about what others that we label as hateful or loving of a particular animal will do. And, the opinions and/or knowledge of other human dimensions scientists do not replace methodological and analytic rigor nor is used as justification for oversights in these processes.

Competing interests declared: We refuted the findings of the authors who commented on this.