Flawed analysis and unconvincing interpretation: a comment on Chapron and Treves 2016

Olson, Erik R.; Crimmins, Shawn M.; Beyer, Dean E.; MacNulty, Daniel R.; Patterson, Brent R.; Rudolph, Brent A.; Wydeven, Adrian P.; Deelen, Timothy R. Van

doi:10.1098/rspb.2017.0273

Cited by 9 publications

(31 citation statements)

References 11 publications

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“…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.…”

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confidence: 95%

“…Both Olson et al . [ 5 ] and Stien [ 6 ] raised the issue of density dependence analysed by Stenglein et al . [ 7 ].…”

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confidence: 99%

“…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 .…”

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confidence: 99%

“…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.…”

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Reply to comments by Olson et al . 2017 and Stien 2017

Chapron

Treves²

2017

Proc. R. Soc. B.

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confidence: 95%

“…Both Olson et al . [ 5 ] and Stien [ 6 ] raised the issue of density dependence analysed by Stenglein et al . [ 7 ].…”

mentioning

confidence: 99%

“…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 .…”

mentioning

confidence: 99%

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confidence: 99%

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Reply to comments by Olson et al . 2017 and Stien 2017

Chapron

Treves²

2017

Proc. R. Soc. B.

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“…Those studies also revealed that poaching was systematically under-estimated by traditional measures of risk and hazard or that mortality of marked animals differed from that of unmarked animals under legal, lethal management regimes (Schmidt et al, 2015;Treves et al, 2017c;Santiago-Ávila, 2019;Treves, 2019a). For a pertinent example, after wolf-killing had been legalized or made easier (liberalized), wolf population growth in two U.S. states slowed over and above the number of wolves killed (Chapron and Treves, 2016a,b), notwithstanding a lively debate (Chapron and Treves, 2017a,b;Olson et al, 2017;Pepin et al, 2017;Stien, 2017). Four separate lead authors studying different datasets about the same Wisconsin wolf control system have now inferred that poaching rates or intentions rose with liberalized wolfkilling policies (Browne-Nuñez et al, 2015;Hogberg et al, 2015;Chapron and Treves, 2017a,b).…”

Section: Does One Source Of Predator Removal Affect Other Sources Of mentioning

confidence: 99%

Predator Control Needs a Standard of Unbiased Randomized Experiments With Cross-Over Design

et al. 2019

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Rapid, global changes, such as extinction and climate change, put a premium on evidence-based, environmental policies and interventions, including predator control efforts. Lack of solid scientific evidence precludes strong inference about responses of predators, people, and prey of both, to various types of predator control. Here we formulate two opposing hypotheses with possible underlying mechanisms and propose experiments to test four pairs of opposed predictions about responses of predators, domestic animals, and people in a coupled, dynamic system. We outline the design of a platinum-standard experiment, namely randomized, controlled experiment with cross-over design and multiple steps to blind measurement, analysis, and peer review to avoid pervasive biases. The gold-standard has been proven feasible in field experiments with predators and livestock, so we call for replicating that across the world on different methods of predator control, in addition to striving for an even higher standard that can improve reproducibility and reliability of the science of predator control.

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