The management of large carnivores remains a contentious issue in many countries.
Among the most contentious management options is ‘tolerance hunting’, or the killing
of predators to increase tolerance among groups of people who do not accept the presence
of these animals [1,2]. In [3,4], we used Bayesian state space models to evaluate
the hypothesis that liberalizing culling of wolves changed wolf population dynamics
from 1995 to 2012, and concluded it slowed growth, which we inferred was owing to
increased poaching. Olson et al. [5] and Stien [6] re-visit our paper and we address
their criticisms below.
First, we disagree with Olson et al.'s [5] and Stien's [6] assertions that our paper
ignores the literature or reports it in a biased manner. We simply disagree about
the interpretation of the literature as we explain below. While they can have a different
interpretation of those papers, it does not mean that ours is incorrect and Stien's
[6, p. 1] phrasing ‘biased reporting of previously published results’ almost suggests
intent from us to mislead the reader. Both Olson et al. [5] and Stien [6] raised the
issue of density dependence analysed by Stenglein et al. [7]. In that paper, the information
on density dependence relevant to our paper is in figures 3, S2.4, S2.5 and S2.6 (we
cannot find reported numerical estimates on how recruitment changed during the relevant
period for our study in [7]). Stenglein et al. [7, p. 5] wrote that ‘The evidence
for a negative slope of the line for t > 18 was 69.0% (proportion of posterior that
was <0)’ but this concerns all years post-1998, which also include many years without
culling. For the relevant period for our paper (when culling was allowed or wolf years
2004–2012), we need to interpret the figures ourselves. On figures 3, S2.4, S2.5 and
S2.6 in [7], we find no obvious difference between the confidence intervals of annual
recruitment estimates. In fact, the only significant drop in recruitment seems to
happen much earlier, at the beginning of the t > 18 period (1998–2001 approximately)
whereas the years with culling seem to show a stable recruitment regardless of the
models used [7]. Because Stenglein et al. [7] clearly concluded that they found no
density dependence on survival, we observed then and still interpret Stenglein et
al. [7] to show no density dependence for the period relevant to our study. An additional
sentence in our discussion in [3] explaining what we just explained above might have
been welcome but seemed a digression. We also chose not to mention that Stenglein
et al. [7, p. 5] appear to trust their model because ‘48.4% of the time, the estimated
population sizes in Wisconsin from 1981 to 2011 were within the 95% posterior intervals
of μt
’ implying that more than half the time their estimates failed this relatively undemanding
test. Stenglein et al. [7] also did not, in our opinion, properly handle uncertainty
by using the midpoint between minimum and maximum population size as their population
count (while we allowed fluctuations between minimum and maximum in [3]). Both Olson
et al. [5] and Stien [6] further insist that the decline in growth rate is owing to
negative density dependence. Olson et al. [5] present a compilation of studies, but
which also includes some unrelated to negative density dependence (see our electronic
supplementary material). Neither of those papers present, in our opinion, empirical
evidence to support a mechanism for density dependence in the population and period
under discussion. Stien [6] argues that the quadratic relationship he found for area
against population size is evidence of negative density dependence. However, as we
wrote previously [8], one must first demonstrate a mechanism to assert negative density
dependence. Indeed, the United States Fish and Wildlife Service reported that the
Wisconsin wolf population grew from minima of 746 to 866 by April 2016 [9] after all
wolf-killing including tolerance hunting was barred in December 2014, or a 1-year
growth of 16%, which is larger than the annual median growth during our study period.
This accelerating growth at the relevant population size demonstrates that there is
still no evidence consistent with negative density dependence in the Wisconsin wolf
population during the period of interest for our study.
Olson et al. [5] also argue that their previous study [10] demonstrated that illegal
killing decreases with increasing availability of lethal management. However, this
study [10] was, in our opinion and that of an anonymous reviewer, not quantitatively
rigorous. One reviewer of our paper [3] indeed agreed and wrote that our ‘paper is
also important because the results are at least somewhat contradictory to a recent
paper Olson et al. [10]. That recent paper had some important shortcoming for which
this paper seems to “fix”’. We admit we might have explained the below shortcomings
in our original paper [3] but did not wish to appear confrontational. Olson et al.
[10] assumed that observed poaching correlated tightly to unobserved poaching (even
for radio-collared wolves). Embracing this assumption leads to the faulty conclusion
that observed poaching is an unbiased sample of all poaching and can be used as the
response variable for a correlation with temporal changes in policy. Treves et al.
[11] did not find support for that assumption. In a separate study in Scandinavia,
Liberg et al. [12] found that two thirds of poaching was not observed. For Wisconsin
wolves, Treves et al. [11] estimated that same observation error to be half of all
poached wolves. Olson et al. [10] also used the number of recovered radio-collared
wolves inferred to have died from poaching as their response variable, without considering
errors in inferring poaching as a cause of death. Systematic errors in attributing
poaching to Wisconsin wolf carcasses ranged from 6–37% depending on which subsample
one examined, as reported by veterinary pathologists contributing to Treves et al.
[13]. Both Olson et al. [10] and Treves et al. [11,13] agree that a high proportion
of radio-collared wolves disappeared without trace (unknown fate), which must be addressed
in some way in any analysis of poaching [11]. Most importantly, Olson et al. [10]
ignored exposure time of radio-collared wolves. We do not understand why they did
not use a survival (time to event) model with the proportion of the year with culling
as an explanatory variable. However, even using a time to event model would require
a proper treatment of unknown fates. Finally, Olson et al. [10] did not seem to consider
that marked animals (radio-collared wolves) may not suffer the same mortality pattern
as the unmarked population. This has been shown specifically in two recent studies
of wolves, which have undermined the assumption of identical mortality patterns [14,15].
Olson et al. [5] and Stien [6] raise other points which we address in detail in our
electronic supplementary material. Briefly, Stien [6] claims that there is a strong
link between probability of reproduction and proportion of the year with legal culling.
However, we believe other models in Stien [6] supplementary code do not support this
conclusion, which, if they would, would still not warrant a change of our conclusions
(see electronic supplementary material). We explain Olson et al. [5]'s assertion—that
our hypothesis is not parsimonious—is built on a misunderstanding of the cause-and-effect
relationships between cognition and behaviour. Moreover, Olson et al. [5]'s hypothesis
of density dependence is not supported by evidence (see above), so its simplicity
does not give it strength. We also argue that there is no support for the frustration
hypothesis proposed by Olson et al. [5] because previous research demonstrates that
tolerance for wolves declined, and inclination to poach rose, in the years following
culling authority. Here and elsewhere, the reasoning in Olson et al. [5] leaves the
impression of cherry-picking the literature while accusing us inaccurately of ignoring
or misrepresenting it. Olson et al. [5] insinuate that we chose to start our analysis
in 1995 because it somehow supported our hypothesis. Our choice is justified by two
of Olson et al.'s [5] co-authors writing how monitoring substantially improved after
1995 [16]. The papers they cite [7,17,18] that begin analyses earlier do not seem
to account for that change in census methods, which may affect their results. Finally,
Olson et al. [5] criticize us for calling our study ‘quasi experimental’ and write
that it is instead a ‘worst case design’ despite having published on the exact same
study system [10]. We do not follow the logic by which a system can suddenly become
the worst when other different authors write about it. Overall, the pattern emerging
from analyses in Olson et al. [5,10] is one of a stream of unrigorous assertions which
together portray a picture of the Wisconsin wolf population that is inaccurate. When
management policies are built on such weak assertions, these policies cannot have
a scientific basis, as has been shown for wolf hunting in the United States [19].
In addition, Olson et al. [5] seem, in our opinion, inclined to divert from a collegial
discussion and adopt the language and style of advocacy. While there may be many reasons
to pledge allegiance to management agencies, we believe that scholarly debates are
not compatible with ad-hominem attacks and misleading soundbites.
We appreciate the scrutiny that our analysis and our writing have sparked. Science
progresses through invalidation of hypotheses and presentation of new evidence, therefore
we welcome scrutiny of our work and collegial discussions. However, we also feel obligated
to point out that statements supporting the tolerance hunting hypothesis, either from
scientists or governments, seem to be taken for granted and evade scrutiny. A recent
illustration is a paper about wolves in Norway bluntly claiming that ‘it is not an
unreasonable expectation that allowing legal harvest might prevent some of the illegal
killing’ [20, p. 135]. In our opinion, the careful wording of nuances in the above
sentence only signals a value-based statement intended to influence policy regardless
of evidence. While our model has faced substantial and legitimate scrutiny, scientists
have remained silent about flaws or lack of evidence supporting the tolerance hunting
hypothesis. In other words, killing predators appears immune to evidence-based scrutiny,
while not killing predators must be justified by the highest level of evidence. One
possible reason is that killing predators may simply be viewed as not worthy of justification
unless one is driven by emotions [21], an attitude revealing contempt for changing
public attitudes about the value of wildlife [22] and a refusal to serve the broad
public interest [23]. Another possible reason may be that killing predators is a goal
by itself regardless of its effectiveness in reducing poaching because it provides
political services [24]. As a consequence, tolerance hunting is today a widespread
management intervention for large carnivores [2] (see our electronic supplementary
material for updated context), perhaps because it has the potential to justify large
scale killing and is extremely difficult to evaluate scientifically. We believe that
double standards in evaluating evidence are hazardous. The double standard that we
observe runs contrary to the precautionary principle and the level of scrutiny should
not be lower or plainly absent for writings supporting tolerance hunting than for
results invalidating it. We conclude by hoping that the debate our paper triggered
will encourage further research on this controversial topic.
Supplementary Material
Supplementary Material