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Evaluation 2 of "Banning wildlife trade can boost demand for unregulated threatened species" (anonymous reviewer)

Evaluation 2 of "Banning wildlife trade can boost demand for unregulated threatened species" (anonymous reviewer)

Published onMay 24, 2023
Evaluation 2 of "Banning wildlife trade can boost demand for unregulated threatened species" (anonymous reviewer)
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Banning wildlife trade can boost demand for unregulated threatened species
Banning wildlife trade can boost demand for unregulated threatened species

Regulation of natural resource use might have unintended spillover impacts beyond the policy targets. Overexploitation is a major cause of species extinction and banning wildlife trade is a common and immediate measure to tackle it. However, few rigorous studies have investigated consequences of wildlife trade bans, and those few studies have focused only on the policy target species. This means governments and researchers may have overlooked side effects of trade bans on unregulated threatened species. This study explores whether trade ban regulations on three threatened species (i.e., giant water bugs Kirkaldyia deyrolli, Tokyo salamanders Hynobius tokyoensis and golden venus chub Hemigrammocypris neglectus) have spillover impacts on the demand for non-banned species considered as substitutes. We draw on a 10-year online auction dataset and the recently developed causal inference approach—synthetic difference-in-differences—to analyze the trade ban regulation implemented in February 2020 in Japan, one of the largest wildlife trade markets. The results show that bans on the giant water bugs and Tokyo salamanders led to an increase in the trade of non-banned species, whereas there was no such evidence concerning the golden venus chub. The findings suggest that policy evaluations ignoring spillover effects might overstate the benefits of trade bans. Our findings raise concerns about the unintended consequences caused by trade bans and restate the importance of further efforts around consumer research, monitoring and enforcement beyond the species targeted by policies, while minimizing the costs by applying modern technologies and enhancing international cooperation.

This is an evaluation of Kubo et al (2022).

Summary measures

Overall assessment

Answer: 75/100

Confidence (from 0 - 5): none given

Quality scale rating

“On a ‘scale of journals’, what ‘quality of journal’ should this be published in?: Note: 0= lowest/none, 5= highest/best”

Answer: 3

Confidence (from 0 - 5): 4

See HERE for a more detailed breakdown of the evaluators’ ratings and predictions.

Written report

Note from The Unjournal: We made some very minimal corrections to spelling, punctuation, and grammar below.

A generally well-written/reasonably well argued paper addressing an important implication of the wildlife trade - the indirect, and often incidental effect of trade bans on the sale of species that may be sought in markets by buyers as alternatives. The paper argues that bans on the trade of species of conservation concern has spillover effects into the trade of closely related species to meet market demand - the premise is straightforward and often talked about but there have not been that many studies to my knowledge that explicitly tests such as hypothesis. Well done to the authors for putting this together.

The paper provides a timely case study of the nature and broader consequences of trade bans in the context of the wildlife trade, and why these consequences need to be more closely looked at after their implementation. Data presentation and analytical framework based on the application of SDID appears sound - and the authors have also gone on to conduct sensitivity analyses.

I would recommend the publication of this paper with some minor revisions, including tightening the language at many parts of the paper for clarity and coherence, and also more caveats for the (public) dataset used.

Principal claim - trade bans have spillover effects into the sale of species not specifically targeted by the ban per se. The paper tests this hypothesis and found what I would consider to be reasonable evidence/support (although the volume of the species sold are relatively small in my view). That said, I haven’t seen many studies that have investigated the causality of policy changes on trade of specific species, so I find it interesting to see this being demonstrated here.

My confidence on the claims made - 70-75%.

Analytical approach is sound and novel (this is the first time I have seen the use of SDID to this sort of analyses), but I would recommend more explicit recognition of the limitations that would come with such a dataset (do you think there is leakage, sale of the banned species through alternative markets). Blanket bans can drive several types of outcomes in the trade of wildlife, and in many parts of the world where governance is weak, there is bought to be leakage into the black market (so what is reported formally may not fully capture the scale of trade) - this would need to be made clever.

Ideally, it would be good to explore such patterns for a large suite of species (and species that are traded in high volumes) but I appreciate that this may not always be realistically possible.

Specific comments:

P2: More background to the online wildlife trade should be given in the intro - for context setting. Suggest to provide examples of species and species groups popular in the online trade. I find that the intro currently reads very generically, and not particularly informative at this stage.

P6: Interested to see how you derived these numbers for the alternative taxa to be traded. Please provide citations. Also hard to define what is ‘substitutable’ - in the eyes of buyers, although one reasonable position is to provide lists of closely related species.

P8: Sounds more like you are providing policy and management recommendations, than ‘implications’. Lots of recommended steps provided here - do make sure they are well substantiated- and backed by sources

P8: Has there been any examples where a species has been substituted in a formal/management-driven way?

P8: How do you recommend that the monitoring be done, and how many taxa can you effectively monitor, to determine the nature and direction of these market shifts?

P8: Can cut away the usual discussion about how biodiversity conservation is afflicted by the lack of funds. Its well known, and does not add a lot to your discussion.

P9: Do you have a good reasoning to want to pursue collaboration beyond CITES? Could CITES provide the umbrella for these collaborations? I find the last bits of the discussion to be rather general, and not much of a value-add.

P11: What steps did you take to manually check and confirm the species names?

Minor comments

P1: ‘Regulations on the harvest and use of natural resources

P1: ‘knee-jerk’ probably captures what you mean more clearly.

P1: ‘heterogenous’

P1: What kind of modern technologies? Vague.

P2: Not clear what you mean by ‘distribution’ - of the species afflicted? Please re-word

P6: I think ‘show’ is a better word.

P6: Side or incidental effects

P6: ‘has important policy implications’

Figure 5: left panel vs right panel

P7: be specific - harms conservation by driving up demand (for the alternatives) - and increased wild harvest

P7: accentuate threats to biodiversity - the trade bans can also effectively undermine the conservation of species and species groups

P8: accelerate declines of species

P10: demand

P10: increased volumes of harvest for the trade

P10: What is the reasoning why these three species were chosen?

P11: each taxon banned

Evaluator details

  1. How long have you been in this field?

    • I have worked in the field of biodiversity conservation for about 10 years.

  2. How many proposals and papers have you evaluated?

    • I review about 20-30 papers each year, and on average, 5-8 project proposals.

Sihwa Park:

Hello, I am not a reviewer of this pub. Please check the contributor’s profile.