Thousands of reptile species threatened by under-regulated global trade

Wildlife trade is a key driver of the biodiversity crisis. Unregulated, or under-regulated wildlife trade can lead to unsustainable exploitation of wild populations. International efforts to regulate wildlife mostly miss ‘lower-value’ species, such as those imported as pets, resulting in limited knowledge of trade in groups like reptiles. Here we generate a dataset on web-based private commercial trade of reptiles to highlight the scope of the global reptile trade. We find that over 35% of reptile species are traded online. Three quarters of this trade is in species that are not covered by international trade regulation. These species include numerous endangered or range-restricted species, especially hotspots within Asia. Approximately 90% of traded reptile species and half of traded individuals are captured from the wild. Exploitation can occur immediately after scientific description, leaving new endemic species especially vulnerable. Pronounced gaps in regulation imply trade is having unknown impacts on numerous threatened species. Gaps in monitoring demand a reconsideration of international reptile trade regulations. We suggest reversing the status-quo, requiring proof of sustainability before trade is permitted.

In this study, the authors have sought to characterize the legal wildlife trade in reptiles at a global scale. This is a worthy research goal, and the results are likely to be of broad interest to the conservation community. While the literature already contains various large-scale, primarily descriptive wildlife trade papers, I believe this manuscript distinguishes itself in a number of ways: 1) The authors have made a substantial effort to quantify the online trade in reptiles. This is a relatively novel, but critical, data source to consider, and the methods used for this portion of the study should be relevant to conservationists seeking to quantify the online wildlife trade across disparate taxa.
2) The authors have made the effort to integrate their novel online trade data with other notable existing wildlife trade data sources, namely the CITES Trade Database and the US-centric LEMIS dataset. 3) This manuscript addresses the short timeframe over which newly described reptile species may be impacted by the global wildlife trade. I think the authors are right to emphasize the importance of this particular result; this is a specific consequence of the wildlife trade that is rarely addressed in other studies, and the implications for rapid overexploitation of newly described species are alarming.
For the reasons above, I think this manuscript is deserving of eventual publication. At the moment, however, there are a number of outstanding issues that I believe are in need of improvement. Primarily, these are related to communication and interpretation of the study results. I have organized my specific feedback into major and minor comments (see below). I do not think any of my suggestions should require substantial data re-analysis, but addressing these issues will make for a more easily interpretable paper. Finally, I would note that there were relatively minor but somewhat pervasive grammatical issues (i.e., simple typos, problems with This study evaluated the scope of the global reptile trade using online databases and trade inventories.
As the authors claimed in their results, the reptiles are arguably one of the most neglected taxa threatened by global trade. Through automated online data collection, the authors are able to document reptilian trade preferences, and regulation and monitoring gaps as currently observed. This is an important study and a much needed one for the reptilian conservation community and regulatory bodies. There are many valuable outcomes from this study that could really help us to protect the global reptiles threatened by trade. In fact, I do not have too many issues with the general approach, analyses, and the not-so-surprising findings.
However, the research questions and findings are not entirely novel, though the methodology may be considering the number of languages used and temporal extent of online data used. One of the main issues is that the authors omitted some key references in wildlife trade highly relevant to this study. It Other minor issues included grammatical errors scattered throughout the manuscript. For example, see paragraph from line 29. Fig. 4C. There is no reason to color the bars using a series of colors when they don't mean much.
Reviewer #3: Remarks to the Author: The major claims of the paper are that over 36% of reptile species are exploited, and over three quarters of those are not covered by international trade regulation. This is useful information as it gives an idea (and some quantitative information) of the proportion of reptile species in trade that are covered by international regulation (ie CITES) and therefore helps provide wider context for other trade analyses, but of course this is only for reptiles, and is still likely to be an under-estimate. Another major finding is that nearly 4000 reptile species were found to be traded.
The paper also demonstrates that endangered or range-restricted species, with hotspots in Asia are traded, and that exploitation can occur soon after description, as has been shown for other species in trade such as orchids. These particularly threatened species should be highlighted for conservation action. The other major claim is that wild collection is widespread, potentially impacting 91% of species -but this is from the LEMIS and CITES data and the proportions of wild versus captive individuals in trade are not provided -just that a certain species has been traded from wild origin -so these data should be interpreted carefully. The concluding statement of the abstract suggests that a reversal of the status quo is needed, requiring proof of sustainability before trade is permitted -this should influence thinking/stimulate discussion in this field, particularly in how such a move could be operationalised.
I do have some comments which I have outlined below.
A major comment relates to the lack of methodology regarding analysis of the CITES and LEMIS data.
There is now a lot of literature surrounding use and misuse of the CITES database in particular, but the same should apply for the LEMIS database.
In Methods line 368 you link to the CITES Trade Dashboards for retrieval of data which I think is incorrect? (I am presuming you downloaded data from the actual CITES Trade Database, rather than the summary figures from the dashboards?) It seems that you have mostly extracted species counts from these data rather than numbers, but in order for a researcher to reproduce this work, a note on these methodology need to be added.
For example what was the time frame for the data downloaded, how were they downloaded (gross reports/comparative reports etc), if comparative, did you use importer-reported or exporter-reported data sets?
In line 105-110 it appears some further analyses of the CITES data inform these results but there is no methodology on this. For example: Line 106-107 -'Critically endangered species are primarily used commercially (94-96%)…' how did you arrive at these percentages? (are these all sources, purposes, terms, units of trade etc?) 'Crocodylus siamensis represents 50% of trade events' how did you arrive at 'trade events' is this I also believe it should be made very clear that the online analyses is restricted to those species traded live for pets. Therefore the finding that over 36% of reptile species are (internationally) traded is even more likely to be an underestimate as other species may be traded online for food and products, and these species may not be captured by the online search, CITES or the LEMIS database. This information informs interpretation of the overlap between different data sources.
There are some areas of text which suffer from over-cutting of text and additional words are needed for clarity.

Reviewer #1 (Remarks to the Author):
Please see attached my major and minor comments to the authors. In this study, the authors have sought to characterize the legal wildlife trade in reptiles at a global scale. This is a worthy research goal, and the results are likely to be of broad interest to the conservation community. While the literature already contains various large-scale, primarily descriptive wildlife trade papers, I believe this manuscript distinguishes itself in a number of ways: 1) The authors have made a substantial effort to quantify the online trade in reptiles. This is a relatively novel, but critical, data source to consider, and the methods used for this portion of the study should be relevant to conservationists seeking to quantify the online wildlife trade across disparate taxa.
2) The authors have made the effort to integrate their novel online trade data with other notable existing wildlife trade data sources, namely the CITES Trade Database and the US-centric LEMIS dataset.
3) This manuscript addresses the short timeframe over which newly described reptile species may be impacted by the global wildlife trade. I think the authors are right to emphasize the importance of this particular result; this is a specific consequence of the wildlife trade that is rarely addressed in other studies, and the implications for rapid overexploitation of newly described species are alarming.
For the reasons above, I think this manuscript is deserving of eventual publication. At the moment, however, there are a number of outstanding issues that I believe are in need of improvement. Primarily, these are related to communication and interpretation of the study results. I have organized my specific feedback into major and minor comments (see below). I do not think any of my suggestions should require substantial data re-analysis, but addressing these issues will make for a more easily interpretable paper. Finally, I would note that there were relatively minor but somewhat pervasive grammatical issues (i.e., simple typos, problems with sentence construction, etc.) that should be addressed prior to publication. Some of these I've highlighted in my minor comments, but that is not a comprehensive list.
Response: Thank you, we hope this analysis can be used to inform better measures to inform conservation and ensure that trade is more sustainable, we feel that gaps in current approaches urgently need highlighting and hope that this research will better enable that. We have now gone through the text to make it easier to interpret and to fix issues stated to make it as useful as possible. Reviewer: Page 2, Figure 1: There seems to be something unusual happening with the presentation of data within this figure? Typically, the different portions of the Venn diagram represent distinct portions of the dataset, but that doesn't seem to be the case here. For example, the text and figure would seem to indicate that the authors detected 2,754 reptile species in the online trade. However, detailed inspection of the figure seems to suggest that the shared online trade-LEMIS species (1,898), the shared online trade-CITES species (683), and the species present in all three datasets (622) is actually MORE (3,203) species than the online trade pool as a whole. This is the case in the data presentation for all three datasets. Perhaps the numbers reported as the shared portion across multiple datasets are not actually mutually exclusive data subsets (as I think they should be)? Response: We originally plotted the venn diagram with non-mutually exclusive divisions. We see how this could be misleading, so have revised which numbers are displayed in the sections. Now each species is only counted within one section of the venn diagram, and noted it in the legend to ensure this is clear.

Major Comments
Reviewer: Page 2, Figure 1: The CITES listings given for the online traded species (80 + 523 + 48) don't add up to the total declared CITES listed species (650) for that dataset. Response: Corrected. We have double-checked the code, and this appears to be a typo.
Reviewer: Page 2, Figure 1: You have the unenviable task of dealing with taxonomic issues across three different datasets here. Not trying to make your work more difficult, but I think it would be worth reviewing the unique reptile species names you're using from LEMIS to make sure they are all in fact unique species. There could very easily be minor misspellings or synonymies present, which would mean that you are currently overestimating the unique reptile species present in that trade dataset. At the very least, I would give a qualifying statement about this, explaining the fact that these names, in their raw form, are not taxonomically standardized. Response: We used the same process for all datasets, online trade, CITES trade database and LEMIS, where we attempted to match them to the Reptile Database species list. In the case of LEMIS species names, only species that could be matched to a synonym present in Reptile Database were included in counts. We describe the impact of the synonymisation process on raw species counts in the supplementary text, but have added text to the methods to make it clear how undertook this process on LEMIS data and the impacts of genus-only listings. Reviewer: Page 3, text and Figure 2C: I'm rather confused about Figure 2C. First, it's showing the number of unique species that were never observed in another year? I think this requires a little more explanation in the figure caption, and I would change the y-axis label to reflect the fact that these are supposed to be unique species. Second, the average number of unique species per year values given in text seem suspicious given what the figure shows. It appears that the number of unique "all names" is substantially larger than the number of unique species name in each year, and the number of unique "all names" seems > 50 in at least 9 of the years shown. Yet the text states that the average unique "all names" per year is only 36.6 compared to 35.7 unique species names per year. Maybe I'm missing something, but the figure would suggest more drastic differences. Third, why is the CITES data plotted here, and is it also supposed to be the number of unique species by the same definition? It wouldn't seem there are on the order of 75 unique reptile species added to CITES each year, especially 75 species that do not appear in the CITES Trade Database at any point thereafter. So I'm unclear what this CITES data represents and why exactly it's relevant (doesn't seem to be referenced specifically anywhere in text?).

Response:
We have changed the way the data is displayed in 2C. The area plot was misrepresenting the data, stacking the all name and sci. name counts, the new line plot avoids this issue. We double-checked our calculation of the mean, and it appears the discrepancy was entirely in data display of stacked counts. Further we have added a second y axis to clarify CITES data line is displaying a count of CITES protected species traded, not connected to the unique species. We have updated and expanded the figure caption to reflect this. We have also added a reference in the text to this trend. Reviewer: Page 4, "Data from LEMIS shows that for 92% of species have wild-caught individuals imported, and only 44% of species had captive bred individuals imported.": Why not also report the number of LEMIS reptile trade records that are wild-caught versus captive-bred? It's fine to include this particular metric, but it seems more unintuitive to report just the number of species for which there are any wild-caught or captive-bred transactions as opposed to the actual number of reptile trade records (or individuals) that are wild-caught versus captive-bred.

Response:
We have expanded on this section, using LEMIS data to provide more details on the extent of wild-capture.

Response:
We have moved D to B, (and B to C, C to D) as suggested. We feel that giving both percent and numbers helps understand the impacts more clearly. Showing percentage everywhere makes depauperate species look highly exploited, whereas that percentage is most significant when it remains high when there are a large number of species, but we have changed the order as recommended and added a supplemental figure as suggested here ( Figure S5) which includes percentage collected even in depauperate areas so that readers can understand the impact on both diverse and more species poor regions.
Reviewer: Page 6, Figure 4: This is already very strong, but it might be worth verifying that the LEMIS species detections you're reporting are in fact commercial trade. My thought was that some of the early species detections could be scientific trade that was documented by LEMIS (and hence maybe not as much of a conservation concern). I spot-checked one species (Uroplatus giganteus), which indeed seems to be involved in the commercial trade soon after its description. I think it would just make the figure all that more convincing if it was explicitly recording appearance in the commercial trade (all online trade is commercial, I assume). Response: Thank you for highlighting this aspect, it's an important point to make. We have added details on the balance between commercial versus noncommercial trade in relation to the overall numbers reported. For the description to trade figure we filtered out the non-commercial species revising down numbers and updated figure 4 accordingly. In the case of the lag between description and trade, this filtering of non-commercial species modified the number of species we could detect in a particular year; therefore, the mean and SE of the lag time slightly. Reviewer: Page 9, "We ceased cycling through search pages when a URL returned a 404 error, or when 100 pages had been cycled through. 100 pages were surveyed to prevent endless cycling back onto initial pages, or deriving errors from misinterpreting the number of search pages returned, whilst still exceeding the number of pages on most sites.": I can see the need for this limit, but could it have led to any bias in your search results towards species that appear earlier in the alphabet (i.e., 100 pages was not enough to characterize the complete stock list of a given site)? Is there any way to verify to yourself and your readers that you in fact pulled the complete species list for every site?
Response: It is extremely difficult to verify we have collected the entire stock list for every website. The diversity of web site set-ups made comprehensive searches difficult, hence the hierarchy of search methods we needed to employ. However, the point of systematic bias remains important to address, we have reviewed a random subsample of the "cycle" searched web pages to check the ordering of species. In 4/10 sites we could not determine how species lists had been ordered, in 6 they were ordered by date, and in 1 it was ordered by popularity. We believe the combination and inconsistency of ordering would not lead to a systematic bias towards species near the beginning of the alphabet, but recognise that ordering may have led to greater variation between websites. We have added details to the methods to help clarify this variation: "We performed a post-hoc review of ten sites searched using a "cycle" search method to check whether species ordering could have led systematic biases for names near the beginning of the alphabet or price. For four websites we could not determine how species were ordered, for six websites species listings were ordered by date, and for one website species were ordered by popularity, thus even for sites with more pages we feel the results will not be impacted by biases given the inconsistency of approach for order of entries on different sites." Reviewer: Page 11, "For examination of CITES coverage over time (species detected from Internet Archive pages) we used the more stringent single name matching because of the added complexity of a changing list of CITES species and the assumption that new CITES listings would use the most recently accepted name.": Where is the corresponding analysis in-text? The only obvious temporally-based CITES analysis is in Figure 1C, which doesn't seem to have to do with the proportion of species in the online trade in a given year that were covered by CITES… Response: We have now added a statement alongside the in-text description of 2C detailing what the CITES per year findings, along with a mean CITES species per year. This change is paired with changes to Fig.2C to make what is being displayed clearer. See response to comments on Page 3, text and Fig. 2C above concerning how 2C displays the count of species that are covered by CITES appendices.
Reviewer: Page 11, "For LEMIS species counts we included those only listed to genus level, for example Anolis spp. would be counted as a species alongside Anolis carolinensis and Anolis smaragdinus etc.": I think it would be very important to mention how many of the distinct LEMIS reptile "species" you're reporting are in fact these generic species declarations. You're artificially inflating your number of traded species by including these in the count (even if we think LEMIS or any other legal wildlife trade database is actually a limited window onto the full scope of the wildlife trade). Response: We use the same name synonymisation technique on all datasets, converting the raw names provided by the databases to the Reptile Database standard, so a generic name would not be counted as specific species after cleaning of data, only in a stage of analysis. Values supplied in the supplementary text show how the overall number of species names change due to this before and after. But we have added numbers to better describe the impact of only sp. listings in LEMIS in the methods, providing an estimate of their prevalence in the overall species count. See response to comment Page 2, Figure 1. The fact that species can be imported under a generic name is also an indicator of the need from systemic change to enable exact quantitative monitoring.
Reviewer: Page12, "Website names/URLs have been redacted to preserve their anonymity.": I'm not sure the justification for anonymization here? Certainly, I understand potential privacy issues, but all of the websites you scraped are presumably openly accessible to the public already. And having the complete website information seems relevant for any reader who wants to follow up on and vet the results of your study. Response: We leave it to the journal to decide based on their policy, we feel there may be legal implications and it may contravene some of the data sharing and privacy guidelines, so will follow the journals recommendation on how to proceed and if such data should be included. As many websites are for classified advertisements and frequently update, exact reproduction of our dataset may be difficult. We have supplied all code we used to generate the dataset in the hope that, despite frequent changes to reptile selling websites, others can corroborate the broad patterns we show (namely the scope of species traded) even without the identical search engine results and reptile selling websites. We have also supplied materials to aid future running of the code: a template of the input website data to aid the web scraping on updated or new websites (Data S1), and the compiled keyword list (Data S2).

Minor Comments
Reviewer: Page1: "…unsustainability exploitation…" should be "…unsustainable exploitation…" Response: Corrected Reviewer: Page1, "Although awareness of the scale of biodiversity loss is growing; assessments…": I think you need a comma rather than a semi-colon.

Response: Corrected
Reviewer: Page1, "…potentially leaving thousands of traded species largely unmonitored…": It doesn't potentially leave them largely unmonitored. Reviewer: Page12, "…where ignored for this analysis.": "where ignored" should be "were ignored" Response: Corrected Reviewer: Page20, Figure S3: Reviewer: Pages 21-22, Figure S4: I wonder if this would be more useful to readers simply as a table or series of tables? It's not as exciting as a visualization, but if people want the information that's represented in the countryspecific bars/pie charts, that's currently very difficult to judge accurately from the visualization. Response: Some patterns, like the disparity between African and Asian country regional patterns would be hard to discern from a table, so we find visuals more intuitive, but we have added a Data S6 as a complement which provides a full table of all data used.
Reviewer: Reporting Summary, Research sample section: As stated early, it may not be completely accurate to say that the subset of LEMIS data you analyzed represents legal trade (if some of the data are in fact from seized shipments). Reporting Summary, Timing and spatial scale section, "The resulting sample covered web pages from 2012 to 2019.": I believe you mean 2002 to 2019? Reporting Summary, Timing and spatial scale section, "LEMIS data covered a period from 2000 to 2019 and represents trade into the USA.": The LEMIS data you report using only contains data from 2000-2014.

Response:
We could not find where in text where exactly this refers to but have been through the draft to check all years referenced in text are now correct.
Reviewer #2 (Remarks to the Author): This study evaluated the scope of the global reptile trade using online databases and trade inventories. As the authors claimed in their results, the reptiles are arguably one of the most neglected taxa threatened by global trade. Through automated online data collection, the authors are able to document reptilian trade preferences, and regulation and monitoring gaps as currently observed. This is an important study and a much needed one for the reptilian conservation community and regulatory bodies. There are many valuable outcomes from this study that could really help us to protect the global reptiles threatened by trade. In fact, I do not have too many issues with the general approach, analyses, and the not-so-surprising findings.
However, the research questions and findings are not entirely novel, though the methodology may be considering the number of languages used and temporal extent of online data used. One of the main issues is that the authors omitted some key references in wildlife trade highly relevant to this study. It is hard to know why prominent references like Scheffers et al. 2019 and Frank and Wilcove 2019, both recently published in Science, were ignored. This is troubling since both studies are widely considered as groundbreaking work in the recent wildlife trade literature. In particular, Frank and Wilcove's work highlighted the similar issues facing threatened species. That is, there existed a lag time between trade and protection for the published commentary and between discovery and trade appearance for the new submission. If either of these papers is discussed, the reader would be less convinced about the novelty of this study.

Response:
Thankfully the editors and other reviewers recognise the novelty and importance in our analyses, but we thank you for providing an additional reference.
The Frank and Wilcove paper is a useful and relevant addition to the paper and has now been added (added the following to the discussion "Studies have demonstrated that CITES is consistently behind the IUCN in species assessment and inclusion (28). Until population impacts are known and assessments complete, trade-bans from specific regions, where exports include threatened species, should also be considered. ". However, due to former discussions with colleagues working for the IUCN, TRAFFIC and other NGOs, Scheffers' paper is widely thought to be a misinterpretation of CITES data, see https://news.mongabay.com/2019/10/misuse-of-wildlife-trade-data-jeopardizes-efforts-to-protect-speciesand-combat-trafficking-commentary/. Thus we felt no need to reference it in this paper, because of concerns that the measures of "what is traded" are mixed with "what is measured". The desire to discover which species are traded outside the knowledge of large bodies like the IUCN and CITES was partly the motivation for our online trade searches. This is especially important for reptiles that face greater gaps in assessments than some other vertebrate groups.
Reviewer: Other minor issues included grammatical errors scattered throughout the manuscript. For example, see paragraph from line 29. Fig. 4C. There is no reason to color the bars using a series of colors when they don't mean much.

Response:
We have now edited and proofed the draft, and removed the colour from Figure 4Cthanks for comments.

Reviewer #3 (Remarks to the Author):
The major claims of the paper are that over 36% of reptile species are exploited, and over three quarters of those are not covered by international trade regulation. This is useful information as it gives an idea (and some quantitative information) of the proportion of reptile species in trade that are covered by international regulation (ie CITES) and therefore helps provide wider context for other trade analyses, but of course this is only for reptiles, and is still likely to be an under-estimate. Another major finding is that nearly 4000 reptile species were found to be traded. The paper also demonstrates that endangered or range-restricted species, with hotspots in Asia are traded, and that exploitation can occur soon after description, as has been shown for other species in trade such as orchids. These particularly threatened species should be highlighted for conservation action. The other major claim is that wild collection is widespread, potentially impacting 91% of species -but this is from the LEMIS and CITES data and the proportions of wild versus captive individuals in trade are not provided -just that a certain species has been traded from wild originso these data should be interpreted carefully. The concluding statement of the abstract suggests that a reversal of the status quo is needed, requiring proof of sustainability before trade is permitted -this should influence thinking/stimulate discussion in this field, particularly in how such a move could be operationalised.
I do have some comments which I have outlined below.
Reviewer: A major comment relates to the lack of methodology regarding analysis of the CITES and LEMIS data. There is now a lot of literature surrounding use and misuse of the CITES database in particular, but the same should apply for the LEMIS database.
Response: Thanks, we agree (especially with regards to CITES) some "high impact" publications have done this in the past and the results were very misleading. Here we have tried to use best practice throughout, and avoided quantifying the different units within several of our datasets because of both issues with reporting reliably and consistency and because of the different units used. Thanks for highlighting the issues here, we have addressed each point, and made amendments in text to better explain approaches used. We have added more detail on the CITES and LEMIS analysis complete in the methods. Further the code supplied alongside the manuscript provides a supplementary description of the exact ways LEMIS data was summarised.
Reviewer:In Methods line 368 you link to the CITES Trade Dashboards for retrieval of data which I think is incorrect? (I am presuming you downloaded data from the actual CITES Trade Database, rather than the summary figures from the dashboards?) Response: Thanks, this has been correctedhttps://trade.cites.org Reviewer:It seems that you have mostly extracted species counts from these data rather than numbers, but in order for a researcher to reproduce this work, a note on these methodology need to be added.

Response:
We retrieved counts of text keyword hits from websites, but we did not use counts in the analysis for a number of reasons (mainly because they do not reflect the number of individuals): species may be readvertised by the same seller, and sellers may advertise multiple individuals with one advertisement. We felt that they were not accurate enough to really indicate abundance of each species, this has now been detailed in methods. We have added the following text. The supplied code provides a supplementary description of how we summarised the keyword search data. Similarly the temporal trend issue brought up in the Robinson & Sinovaa 2018 paper is important, but we do not base our conclusions on examinations of temporal trends. Temporal assessments are largely restricted to the online trade and LEMIS data, while also flawed, we could better correct for sampling biases (page count regression). We also did not use CITES data in our assessments of lag from description to trade.
The ambiguity regarding purpose codes is also worth addressing as we do report those. In this case, the conflation between "commercial" (covering both industry uses and commercial pet trade) and "personal" (more likely to be largely pet trade) would impact the exact values we'd report. We do not see a way of correcting for this, but feel that the main purpose of the manuscript is not undermined -highlighting the worrying extent of species traded with little oversight. We also feel the statement that CITES is more commercially focused than the other sources would change, as evidenced by findings that side-step reported purposes (e.g. "The commercial focus of CITES is further reflected in the regulation of fashion targeted species: 100% of crocodiles and 52% of Testudines, compared with 9% of lizards and 4% of snakes have CITES appendix listings").
We appreciate having these sources brought to our attention, and hope that given our avoidance of using quantities in CITES which they highlight as a major issue that this will not impact on our results, though are glad that these issues are being highlighted more broadly as they have real implications for our understanding of quantity of trade, rather than as we have explored number of species.
I also believe it should be made very clear that the online analyses is restricted to those species traded live for pets. Therefore the finding that over 36% of reptile species are (internationally) traded is even more likely to be an underestimate as other species may be traded online for food and products, and these species may not be captured by the online search, CITES or the LEMIS database. This information informs interpretation of the overlap between different data sources. Response: We added "largely for pets" as the other databases also include a small number for fashion, even if most are for the pet trade. We mention in text that others are used for food or medicine, but they are likely to be impossible to fully assess, we also highlight this on our supplemental section on caveats. We also added further information in the discussion as follows

"CITES aims to ensure that wildlife trade is sustainable, yet it largely focuses on only the most economically valuable species traded in large volumes, leaving species which may have niche markets, are lesser-known, or range-limited, unprotected and vulnerable to trade. Key differences exist between CITES listed species being traded under CITES monitoring, and those for sale online or in LEMIS. For CITES data, the majority comprises a small number of species, traded in high volumes for the fashion trade; whereas those online were almost exclusively for the pet trade (though there is also a huge medicinal market including over 284 reptile species which was not explored here (16))"
Reviewer: Line 185-189 -I think you need to acknowledge that wild trade is not necessarily bad for species and conservation in all cases -especially when part of regulated and monitored projects where local counterparts are receiving benefits from the trade and incentives are generated for conservation. Consider work by Dilys Roe and Rosie Cooney amongst others and the following paper which discusses the possible implications of wild versus ranched/captive reptiles in trade. I don't believe this needs a lot of focus but acknowledgment of complexities through addition of a sentence will allow it to come across more balanced. Response: Thanks, we have added the suggested reference and the additional text "Thus though studies have found that captive breeding and ranching can provide alternative livelihoods and thus enable conservation, for this to be achieved mechanisms to prevent laundering are needed, and the cost of rearing animals cannot substantially exceed that for collecting from the wild"

Robinson
Reviewers' Comments: Reviewer #3: Remarks to the Author: While some aspects of the paper have been improved, based on the clarifications received I have major concerns regarding the methodology, analysis and interpretation of the CITES data.
Firstly my comment regarding adequate methodology for the CITES data has not been adequately addressed I can see the correct download url/link to the database has now been added for the CITES data, but no other information provided. For example, there is no mention of the report type used (comparative, gross/net trade report), and what was requested in the download (dates/all reptiles?).
I strongly recommend the authors look at other papers which have analysed data from the CITES Trade Database and include a section on this in the methods.
Secondly, the authors have clarified in the methods and elsewhere that they have used "number of listings rather than absolute quantities because of inaccuracies in reporting in different units". This is very unclear but I think they mean that they have summarized the data based on the number of rows which appear in the data -which they previously referred to as 'trade events', and they have now changed the wording to 'number of listings'. This is a fundamental problem.
The individual rows in the CITES data do not refer to trade events -they are data amalgamated for the year which match on import and export country, and all sources, purposes, terms and units. So for example all Python regius from Ghana to the US, traded live, from wild source, for one year (say 2015) will be summarized on that line. The references explaining this were provided in the previous review.
(This is the presuming the authors downloaded comparative tabulations -which is what is presumed but is also not clear as they have not reported this. It also assumes the authors have not downloaded the newly available shipment level database -but again -not clear) So when the authors report xx% of listings were from commercial/wild source etc, these data are not meaningful. The line I just described may contain 1200 individuals, whereas the next line reporting captive bred python regius from the US to Germany may contain 4 individuals for that year. The next line may be referring to 10,000 watch straps made from a monitor species.
The methods referring to the online analysis are very comprehensive and the results based on the online searches are sound and interesting. I get the impression the CITES and LEMIS data may have been a later addition to this paper. As a result the methodology, analyses and interpretation of the CITES data are inadequate. The same may issues may apply to the LEMIS data but I have less experience with this data set.
I recommend that the authors either make a thorough analysis of these data to the same level of attention that has been applied to the online data, or they remove all quantification of these data and ONLY use the species lists/identification of species in trade, from these data sources. This would involve the removal of some paragraphs in the results but not a fundamental restructure in my opinion.
I also still find some sections of the results and writing clunky and unclear. I have outlined a few extra comments below.
Main text, 2nd para, 2nd sentence -This now reads as if CITES only protects large charismatic mammals which is clearly not true.
Main text, 2nd para, last sentence -"Piecemeal assessments…" This sentence sounds a bit derogatory as there are several comprehensive global and/or regional assessments of reptile trade.
Results, scale of trade, third para -This paragraph is clunky -It seems obvious that the CITES data will contains a high number of CITES listed species! Also what do you mean in the first line of this paragraph that 'overlap between online trade results and species reported by LEMIS corroborate online search results'? Not clear Results, the threat from trade, second para -this paragraph is problematic for reasons explained above. What you mean here, based on my understanding, is that '50% of the rows in amalgamated data referred to Crocodylus siamensis', and so on, which is not meaningful information. Results, origin of traded species, 1st para -this whole paragraph is not meaningful for reasons described above.The addition of the word 'substantial'in this paragraph is misplaced. 2.5% and 8.8% does not represent 'substantial?' Results, origin of traded species, 2nd para -I do not think these data are meaningful and they could be misunderstood. For example, "92% of species have wild caught individuals imported". But without any quantification of these data many of these species may have had an isolated scientific specimen, or single blood sample, traded from wild where nearly 99% is from captive source.
Results, origin of traded species, 3rd para first sentence - Fig 3A seems to refer to the number of traded species not species diversity. While some aspects of the paper have been improved, based on the clarifications received I have major concerns regarding the methodology, analysis and interpretation of the CITES data.
Firstly my comment regarding adequate methodology for the CITES data has not been adequately addressed I can see the correct download url/link to the database has now been added for the CITES data, but no other information provided. For example, there is no mention of the report type used (comparative, gross/net trade report), and what was requested in the download (dates/all reptiles?).
Response: We have updated the methods section, it now reads: CITES data was retrieved from https://trade.cites.org/# on 2020-05-13) using the comparative tabulations for all "reptilia" and the appropriate years (the snapshot of 2019, and 2004-2019) to download all reptile species exported over this time.
I strongly recommend the authors look at other papers which have analysed data from the CITES Trade Database and include a section on this in the methods.

Response: Most papers on CITES data focus on the volumes exported whereas we largely focus on what is being traded and the implications. Though we cite some papers that focus on the CITES data (i.e. Frank & Wilcove 2019), but have now added more details to methods, and provided a much more in depth breakdown of the CITES data.
"Though the research focused on the percentages of species vulnerable to trade based on various forms of IUCN and CITES category we made some efforts to quantify the proportions of items with different statuses within CITES and LEMIS. Quantifications were made using a number of different approaches. Online assessments were not directly quantified due to the possibility of listing the same individuals multiple times, or having mixed batches of specimens with variable numbers. For CITES we used the summary statistics tool in ARCMAP to quantify the means and totals for the numbers exported and imported, and the range for each species or endangerment status is provided in text (or a single number if they were the same). Redlist status was associated with the data by joining the scientific name field between the two databases. Sums were made for various sources, purposes and endangerment statuses for CITES data using this same approach, based on the 2004-2019 data from the CITES trade portal. "Terms" (i.e. skins) were also explored, recategorising the standard terms (57 were used for reptiles) into nine (i.e. fashion), then summing the total item number imported and exported and determining the percentage.
Response: While it is true that the import could be a single scientific specimen, we highlighted earlier in the paper that only 2.18% of species in LEMIS are for non-commercial purposes meaning that wild collection is still impacting the vast majority of species, and that given the lack of regulation the true scope of this is difficult to assess. We further support the scale of wild collection with the number of traded individuals (44%). Granted, trade is likely targeting some species over others leading to a skew in the 92% and 44%, but without a priori assessments of trade impacts on populations the best trade data would be insufficient in determining what's damaging to a particular species. Therefore, we feel reporting broad statistics is meaningful in the sense of highlighting how much work is required to comprehensively understand the trade's impact on wild populations, and the number of species subjected to at least some collection of trade from the wild.
Results, origin of traded species, 3rd para first sentence - Fig 3A seems to refer to the number of traded species not species diversity. This is my second review of the present manuscript. I still believe this paper contains important data (particularly the analysis of the online reptile trade), and there has been improvement in some areas, such as the Figure presentation. However, I also still have significant concerns about the clarity and accuracy of the data reported throughout, which prevent me from endorsing publication. The issues I have with the manuscript are very similar to those expressed by Reviewer #3, and while the authors have attempted to respond to our comments through two rounds of review, some of the core problems remain.
My read of the tension is this: the authors are caught between a high-level, species-level analysis and a more detailed characterization of the reptile trade. I think the authors are well-justified in limiting their description of the online reptile trade to just the species that occur in that trade; quantification of the online reptile trade may be too difficult or inaccurate given the methods employed. The analysis of the online reptile trade is, to me, the most novel part of the study and could stand by itself. However, the authors have attempted to bolster their work with the inclusion of both CITES and LEMIS trade data (an understandable aim), and this is where the problems enter in. If the paper is built around the synthesis of three disparate data sources, then it will only be successful to the degree that all three data sources are accurately analyzed and well-integrated. The CITES and LEMIS data could be used exclusively to document additional reptile species in the global reptile trade, which would be analogous to the type of information provided by the online analysis. But when the authors want to make claims about the sources of animals/products in the reptile trade, for example, this will require much more detailed scrutiny and description of the CITES and LEMIS data. It's not very meaningful to highlight that X% of species have any individuals being wild-caught (as multiple reviewers have pointed out). Rather, you must clearly summarize the data at an animal-or item-level to make a convincing case. I'm concerned that these sorts of analyses are still lacking in the present manuscript. For example, the LEMIS data appear to be summarized using rows of reptile data (rather than an analysis of counts of animals or items). Wildlife trade databases are extremely difficult to understand: when you say "item" we need to be sure you actually do mean numbers of items and which types of wildlife items you're referring to. Other elements of the manuscript and response to reviewers sow further confusion: in their second response to comments, the authors state that, "only 2.18% of species in LEMIS are for non-commercial purposes meaning that wild collection is still impacting the vast majority of species." Yet this statement conflates wildlife trade's potential purposes (i.e., non-commercial trade) and sources (i.e., wild vs. captive breeding).
At this point, I would ask the authors to carefully consider whether detailed descriptions of CITES and LEMIS data are vital to their message. I understand there may be frustration since these CITES and LEMIS analysis elements are unlikely to change the overall picture that many reptile species are present in a largely unregulated global trade. But if these analyses are included, I think they have to be accurate and communicated effectively. Alternatively, it could be that the paper is better served by cutting down some of the CITES and LEMIS material and focusing on the broader, species-level overview (as Reviewer #3 recommended in the last round of comments).
Page 1, "The regulations primarily protect commercially traded, "charismatic" animal species; only recently covering lesser-known species (e.g. pangolins-2016)." I know this sentence has been subject to previous comment, but it still reads as inaccurate. It now seems as if you mean to suggest CITES only protects charismatic animal species, which is clearly untrue given that the majority of listed species are plants.
Page 2, Figure 1 I previously commented that it would be worth reviewing the unique reptile species names you're using from LEMIS. There could very easily be minor misspellings or synonymies present. Your previous response partially addressed this issue by clarifying that taxonomies from all datasets were referenced against the Reptile Database species list. This addresses the concern that you could be double (or more) counting synonymous nomenclature for a single species. But it doesn't entirely resolve the concern. If you haven't thoroughly reviewed the unique LEMIS species names you're analyzing, it's possible that misspellings are resulting in undercounting (i.e., a species name in the database is a clear misspelling of a valid species name that doesn't get matched against the Reptile Database and is therefore left out of your analysis). At the very least, I would give a qualifying statement about this, explaining the fact that these names, in their raw form, are not taxonomically standardized. Ideally, you review the LEMIS taxonomy to verify why any names are not matching the Reptile Database and resolve ambiguities. But at the very least, your readers should be clearly told this is an outstanding issue in the analysis.

Page 4, Figure 2C
I still find this figure panel unnecessarily confusing. Why not simply separate the unique species observed in online trade over time and the CITES species present in online trade over time? These are completely distinct metrics with very different interpretations (one represents species that are not documented in any other year, the other does not). For this reason, I think the two sets of information would work better as two separate panels. At the very least, the y-axis labels should be more informative. Something like "Number of unique species in the online trade" and "CITES species present in the online trade", respectively.

Page 4, Figure 2C
How could it be the case that a count of all names is ever less than strictly scientific names (as in the year 2007 here)? I think the distinction between these two categories deserves better explanation either here or in the Methods on page 13.
Page 5, "In terms of traded items, LEMIS lists 63.0% (63.2% excluding seized shipments) as wild-sourced (456,722/724,655), nearly twice that listed as originating from captive, ranching, and commercial breeding (35.6% 258,021/724,655)." If I understand correctly, you've just filtered the LEMIS data for class Reptilia, leaving 724,655 rows of data, which you treat as "items." To me this is a major issue, and one that is directly analogous to Reviewer #3's concerns about how you've treated CITES trade data in various iterations of the manuscript. Those rows of data you're analyzing are not items. Rather they could be representative of multiple reptile-derived products. This distinction matters in the sense that it affects every trade metric you report for LEMIS or CITES data that does not rely on a gross, species-level analysis. To do these calculations accurately, they should actually be on the level of items, which will require more filtering of the data or a concentration on particular wildlife product descriptions (in the LEMIS data) or Terms (in the CITES data). For example, you might report the wild versus captive sourcing of only live animals or some specific reptile product like leather.
Page 8, Figure 4 I believe in the caption it should read, "The period 2000-2001 is only covered by LEMIS data." I would also very, very explicitly mention that the LEMIS data has been filtered for commercial trade here (if indeed it has?). It's not enough to bury this important information in the Methods.
Page 9, "...this totaled to over 63% of all imports." What exactly are you summarizing here? Wildlife product shipments? A sum of wildlife product items?
Page 10, "For lower-value species banning trade from key-regions may not drive trade "underground" as can happen with higher value species (11). Conservationists actively hindered trade ban implementation for birds on such grounds (29), but when eventually applied within Europe global bird trade decreased by 90% (30)." This would seem to be a very generous read of the Reino et al. paper. First, that paper documents a decrease in bird trade when the EU implemented a trade ban, but it also notes that global trade flows were reshaped by the ban. Second, you claim that reptiles are "lower-value" species, yet your paper mentions small-ranged, endemic species and the Courchamp et al. paper you also cite explicitly lays out how rarity might be inversely related to value. So I'm not sure it's obvious that rare reptiles would be low value in a trade ban scenario. Finally, and most importantly, you're relying on the perceived effectiveness of trade bans as suggested by the Reino et al. paper, yet that manuscript uses CITES trade data, which you claim throughout this manuscript is a rather limited perspective on wildlife trade. And it doesn't address the potential for redirection to illegal trade channels, which is one of the main concerns with trade bans. All this is to say, I think you need a more nuanced discussion of potential policy solutions for global reptile trade that doesn't exclusively push for potentially ineffective or harmful trade bans.
Page 11, "We ceased cycling through search pages when a URL returned a 404 error, or when 100 pages had been cycled through. 100 pages were surveyed to prevent endless cycling back onto initial pages, or deriving errors from misinterpreting the number of search pages returned, whilst still exceeding the number of pages on most sites." Through your revisions you've convinced me that stopping at 100 pages has not led to any alphabetical bias in your coverage of online reptile trade (since sites list reptiles in different schema). But you still haven't assuaged the concern that you've not completely characterized the stock list of every site. This doesn't need to be redone necessarily, but I would explicitly state in the methods that your online data scraping strategy may result in undercounts of species in online trade given that there are reptile trade sites you may have incompletely assessed. This is my second review of the present manuscript. I still believe this paper contains important data (particularly the analysis of the online reptile trade), and there has been improvement in some areas, such as the Figure presentation. However, I also still have significant concerns about the clarity and accuracy of the data reported throughout, which prevent me from endorsing publication. The issues I have with the manuscript are very similar to those expressed by Reviewer #3, and while the authors have attempted to respond to our comments through two rounds of review, some of the core problems remain. My read of the tension is this: the authors are caught between a high-level, species-level analysis and a more detailed characterization of the reptile trade. I think the authors are well-justified in limiting their description of the online reptile trade to just the species that occur in that trade; quantification of the online reptile trade may be too difficult or inaccurate given the methods employed. The analysis of the online reptile trade is, to me, the most novel part of the study and could stand by itself. However, the authors have attempted to bolster their work with the inclusion of both CITES and LEMIS trade data (an understandable aim), and this is where the problems enter in. If the paper is built around the synthesis of three disparate data sources, then it will only be successful to the degree that all three data sources are accurately analyzed and well integrated. The CITES and LEMIS data could be used exclusively to document additional reptile species in the global reptile trade, which would be analogous to the type of information provided by the online analysis. But when the authors want to make claims about the sources of animals/products in the reptile trade, for example, this will require much more detailed scrutiny and description of the CITES and LEMIS data. It's not very meaningful to highlight that X% of species have any individuals being wild-caught (as multiple reviewers have pointed out). Rather, you must clearly summarize the data at an animal-or item-level to make a convincing case. I'm concerned that these sorts of analyses are still lacking in the present manuscript. For example, the LEMIS data appear to be summarized using rows of reptile data (rather than an analysis of counts of animals or items). Wildlife trade databases are extremely difficult to understand: when you say "item" we need to be sure you actually do mean numbers of items and which types of wildlife items you're referring to. Other elements of the manuscript and response to reviewers sow further confusion: in their second response to comments, the authors state that, "only 2.18% of species in LEMIS are for non-commercial purposes meaning that wild collection is still impacting the vast majority of species." Yet this statement conflates wildlife trade's potential purposes (i.e., non-commercial trade) and sources (i.e., wild vs. captive breeding). At this point, I would ask the authors to carefully consider whether detailed descriptions of CITES and LEMIS data are vital to their message. I understand there may be frustration since these CITES and LEMIS analysis elements are unlikely to change the overall picture that many reptile species are present in a largely unregulated global trade. But if these analyses are included, I think they have to be accurate and communicated effectively. Alternatively, it could be that the paper is better served by cutting down some of the CITES and LEMIS material and focusing on the broader, species-level overview (as Reviewer #3 recommended in the last round of comments). Response: Thank you for this, we are willing to take out most quantitative estimates; however, we feel highlighting that many species are wild sourced is also useful as it shows the conservation importance of better monitoring standards. We have tried to reduce the content on quantitative elements to just keypoints to enable a full understanding of what is being traded and the significance. We have now carefully gone through the LEMIS data as you prescribe here, ensuring that we are quantifying individuals so we can be sure in statements and providing a breakdown for the different taxa ( Figure S4) to highlight possible impacts on wild populations. We feel that by highlighting the number of species in trade (having ensured these are representative of individuals), and the origins it provides a unique and important insight into global trade dynamics and their impacts. We provide a fully detailed method and our entire analysis pipeline so that our drawn conclusions can be validated by other researchers, and that the results are an accurate representation of trade.
Please see my specific major and minor comments below. Evan A. Eskew

Major Comments
Page 1, "The regulations primarily protect commercially traded, "charismatic" animal species; only recently covering lesser-known species (e.g. pangolins-2016)." I know this sentence has been subject to previous comment, but it still reads as inaccurate. It now seems as if you mean to suggest CITES only protects charismatic animal species, which is clearly untrue given that the majority of listed species are plants. Response: We agree how the statement could have been misleading and have changed this to narrow toward animals because within the animal species particularly chordates there is a bias towards "charismatic" fauna. "Within animals the CITES regulations primarily regulate trade of commercially traded or "charismatic"…." Page 2, Figure 1 I previously commented that it would be worth reviewing the unique reptile species names you're using from LEMIS. There could very easily be minor misspellings or synonymies present. Your previous response partially addressed this issue by clarifying that taxonomies from all datasets were referenced against the Reptile Database species list. This addresses the concern that you could be double (or more) counting synonymous nomenclature for a single species. But it doesn't entirely resolve the concern. If you haven't thoroughly reviewed the unique LEMIS species names you're analyzing, it's possible that misspellings are resulting in undercounting (i.e., a species name in the database is a clear misspelling of a valid species name that doesn't get matched against the Reptile Database and is therefore left out of your analysis). At the very least, I would give a qualifying statement about this, explaining the fact that these names, in their raw form, are not taxonomically standardized. Ideally, you review the LEMIS taxonomy to verify why any names are not matching the Reptile Database and resolve ambiguities. But at the very least, your readers should be clearly told this is an outstanding issue in the analysis. Response: We have reviewed the failed matches, comparing the failed-to-match names against the species detected by other sources. We used the similiars R package to find species names with fewer than 5 characters different. Of the failed matches only 27 "species" in LEMIS were not already reported in other data sources. We have added details on the overlap of the non-matched names to the methods.
We have added details on this quantification of mismatching in the methods: "Outside of generic level listings, 83 names could not be matched. We compared the 83 names to the traded list from other sources, looking for names with fewer than 5 different characters (using the similiars v.0.1.0 package [70]); 56 species were found to be present in other sources by this metric." Page 4, Figure 2C I still find this figure panel unnecessarily confusing. Why not simply separate the unique species observed in online trade over time and the CITES species present in online trade over time? These are completely distinct metrics with very different interpretations (one represents species that are not documented in any other year, the other does not). For this reason, I think the two sets of information would work better as two separate panels. At the very least, the y-axis labels should be more informative. Something like "Number of unique species in the online trade" and "CITES species present in the online trade", respectively. Response: We agree and have split the two elements of 2C into 2C and 2D. 2C is exclusively the unique species per year, and 2D the count of CITES species each year.

Page 4, Figure 2C
How could it be the case that a count of all names is ever less than strictly scientific names (as in the year 2007 here)? I think the distinction between these two categories deserves better explanation either here or in the Methods on page 13. Response: There can be instances where the scientific only names produce more unique species for a given year. For example, let's say we only detected Xenodermus javanicus in 2007 and 2008, but the 2007 instance was via Xenodermus javanicus and the 2008 was via dragonsnake. In this case the number of species unique to 2007 would decrease when using all names because Xenodermus javanicus would have also been detected in 2008 via a common name. Essentially, using more keywords can lead to a decrease in the number of unique species in a given year because of the increased chances of detecting species in other years. We have added some additional detail to the methods justifying why the two counts were included: "To show the sensitivity to the keywords used, we counted the number of unique species in two ways: 1) counting all species detected using either scientific or common name keywords, 2) counting species only detected using scientific name keywords. The two keyword groups produce slightly different yearly species lists; therefore, changing the number of unique species per year and yearly residuals" Page 5, "In terms of traded items, LEMIS lists 63.0% (63.2% excluding seized shipments) as wild-sourced (456,722/724,655), nearly twice that listed as originating from captive, ranching, and commercial breeding (35.6% 258,021/724,655)." If I understand correctly, you've just filtered the LEMIS data for class Reptilia, leaving 724,655 rows of data, which you treat as "items." To me this is a major issue, and one that is directly analogous to Reviewer #3's concerns about how you've treated CITES trade data in various iterations of the manuscript. Those rows of data you're analyzing are not items. Rather they could be representative of multiple reptile-derived products. This distinction matters in the sense that it affects every trade metric you report for LEMIS or CITES data that does not rely on a gross, species-level analysis. To do these calculations accurately, they should actually be on the level of items, which will require more filtering of the data or a concentration on particular wildlife product descriptions (in the LEMIS data) or Terms (in the CITES data). For example, you might report the wild versus captive sourcing of only live animals or some specific reptile product like leather. Response: Thanks for highlighting this. We have updated all LEMIS quantitative values focusing the analysis on items that represent individual animals (removing "parts" and retaining only whole dead bodies, live eggs, dead specimens, live individuals, full specimens, substantially whole skins, and full animal trophies). We have removed the row-based summaries. We have also added the numbers pertaining only to live individual imports, thus the results now provide a much more accurate and comprehensive analysis of minimum numbers of individuals included. We have added details in the methods that specify the LEMIS categories we included: "To investigate the extent of wild capture in LEMIS data, we restricted our summaries to items that represent full animals (whole dead bodies, live eggs, dead specimens, live individuals, full specimens, substantially whole skins, and full animal trophies). Our quantification of non-commercial trade was calculated by the number of full animal items listed as Scientific, Reintroduction, or Biomedical research; our quantification of captive sourced trade was calculated by the number of full animal items listed as being bred/born in captivity, commercially bred, or from ranching operations. We excluded all instances of NA in either purpose or source filters. We summarised the quantity of traded items by genus, and further simplified the genus-summary to clade using Reptile Database genera and family information. For genera missing from Reptile Database (e.g., where genus information was family such as Varanidae), we manually assigned the clade. " Page 8, Figure 4 I believe in the caption it should read, "The period 2000-2001 is only covered by LEMIS data." I would also very, very explicitly mention that the LEMIS data has been filtered for commercial trade here (if indeed it has?). It's not enough to bury this important information in the Methods. Response: Thanks-LEMIS data was filtered to commercial trade only for time lag investigations. We have corrected the figure legend to make this clear.
Page 9, "…this totaled to over 63% of all imports." What exactly are you summarizing here? Wildlife product shipments? A sum of wildlife product items? Response: Items representing whole individuals; this has now been added in text and detailed Page 10, "For lower-value species banning trade from key-regions may not drive trade "underground" as can happen with higher value species (11). Conservationists actively hindered trade ban implementation for birds on such grounds (29), but when eventually applied within Europe global bird trade decreased by 90% (30)." This would seem to be a very generous read of the Reino et al. paper. First, that paper documents a decrease in bird trade when the EU implemented a trade ban, but it also notes that global trade flows were reshaped by the ban. Second, you claim that reptiles are "lower-value" species, yet your paper mentions small-ranged, endemic species and the Courchamp et al. paper you also cite explicitly lays out how rarity might be inversely related to value. So I'm not sure it's obvious that rare reptiles would be low value in a trade ban scenario. Finally, and most importantly, you're relying on the perceived effectiveness of trade bans as suggested by the Reino et al. paper, yet that manuscript uses CITES trade data, which you claim throughout this manuscript is a rather limited perspective on wildlife trade. And it doesn't address the potential for redirection to illegal trade channels, which is one of the main concerns with trade bans. All this is to say, I think you need a more nuanced discussion of potential policy solutions for global reptile trade that doesn't exclusively push for potentially ineffective or harmful trade bans.
Response: Thanks, we have tried to provide a more nuanced and detailed discussion of this and include a number of other references to try to ensure we are representative and provide wider perspectives on the complexity of the issue. We note the reviewers perspectives on trade-bans and understand their perspectives based on their recent paper on the topic (https://www.thelancet.com/journals/lanplh/article/PIIS2542-5196(20)30123-6/fulltext) Whilst we agree trade bans are a blunt instrument, banning the international trade of unassessed and endangered species without CITES appendix quotas seems a sensible alternative to a total ban, whilst enabling regulated trade of species that are unlikely to be severely impacted and can have their identity validated. Furthermore, trade requires monitoring, and monitoring and regulating wild-animal trade is something that from both a disease and conservation perspective should be a global standard, as it already is in the US (and Australia). We realise that increasing rarity can stimulate demand, but newly described species already have that issue as we demonstrate, yet these species lack even basic protection. Given that captive breeding should be a viable option within many of the major importing regions it is likely that international trade from the wild would not be required to meet demand for the majority of species. Furthermore, though as the reviewer points out CITES only gives a limited reflection on trade due to the subset of species monitored coupled with bans in major importing countries we feel that the Reino paper is a useful comparison, though we now more clearly highlight the challenges with inconsistently applied (regional) regulation.
We have rephrased the text as follows: "Studies have demonstrated that CITES is consistently behind the IUCN in species assessment and inclusion (30). Until population impacts are known and assessments complete, trade-bans from specific regions, where exports include threatened species, should also be considered. For low-value species banning trade from key-regions may not drive trade "underground" as can happen with high-value species (11), especially when such actions are used to stimulate regulated markets based on captive breeding as was found effective with crocodiles (31). Conservationists actively hindered trade ban implementation for birds on such grounds (32), but when eventually applied within Europe global bird trade decreased by 90% (33), in part because of the availability of non-wild sourced alternatives for captive breeding (34). With just under 4000 reptile species found to be traded within this study there is ample stock already in captivity to justify the development of certified and monitored captive breeding within free-trade zones and prevent the need for commercial import. Such actions have already been used in the case of other taxa, for example "The Wild Bird Act" and "EU Wild bird ban" have prevented the importation of exotic birds into the US since 1992, and Europe since 2005 (https://www.fws.gov/le/USStatutes/WBCA.pdf). In both the cases of the US and Europe, disease risk and impact on native birds was the stated case for regional bans (35), and these same justifications exist in the case of reptiles (36,37). Yet though undoubtedly effective in reducing global trade, unintended consequences, shifting routes and markets (34) also demonstrate a more holistic approach is needed such as a requirement for CITES listing for the export of reptiles, though species listed as Least Concern could be traded more widely if mechanisms for verification of species identity existed prior to export. From a standpoint of both disease and understanding trade systems like LEMIS should also become global standards for the export of live animals, and especially for wildlife export. Whilst many conservationists and organisations may challenge such an approach, as occurred in the case of birds (32), our data highlights thousands of species impacted by wild capture, including many which are new to science. By regulating what can rather than what cannot be traded internationally, we can considerably reduce the pressures on wild reptile populations. "