Potential Distribution and Key Factors of Dasyhippus barbipes (Orthoptera: Acrididae: Gomphocerinae) in China Under Climate Change Scenarios
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsAll the comments are in the attachment.
Comments for author File: 
Comments.pdf
Author Response
Thank the reviewer for the rigorous evaluation and for pointing out the shortcomings of our manuscript. We have carefully revised the manuscript in response to all major and minor comments, providing point‑by‑point replies in red font. We once again thank you for your efforts and valuable suggestions to improve the quality of the paper. Please see the attachment for details.
Author Response File: Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsDear colleagues,
The model species, Dasyhippus barbipes, is a grasshopper widely distributed across the North China, Mongolia and South Siberia. In the dry steppes and semi-deserts, it may be very abundant. This is why we should try to understand the patterns of its distribution now and in the future. That means the significance of the obtained results is particularly relevant now and may be more significant in the future. I believe as well that your studies are original and are trying to solve an important problem related to plant protection, especially relative to monitoring and forecasting. The Discussion seems quite reasonable and is based on the results achieved. I guess your results may be interesting for many colleagues despite the regional character of your investigations. However, some parts of your manuscript should be improved and clarified.
(1) Are you sure that all points used are associated with D. barbipes? The problem of the species identification is very important and some misidentification may affect results of modelling. In many cases, only qualified specialists can distinguish between closely related species. In your case, this problem is especially significant, because the similar D. peipingensis is distributed across some parts of North China (e.g., see "Fauna Sinica. Insects, vol. 32 (2003)). In addition, the model species can be quite easily confused with some grasshoppers of the genus Aeropedellus that also inhabit the area. I suspect there may be some significant problems.
(2) The next problem is associated with a spatial resolution and some estimations of areas. Actually you used the spatial resolution of 0.5 arcminute (30 arcsecond). The use of the value of 1 km is simply a visual representation.However, at the latitude of central Inner Mongolia the actual size of a pixel is about 930 m x 650 m. I am sure that you should note a resolution in arcminutes (or arcseconds). In this context, you should explain clearly how you estimated areas (e.g., of suitable habitats) as well, because if you used some opportunities of ArcGIS, that is fine, but if you counted the number of pixels and multiplied these numbers, your estimation will be exaggerated.
(3) (Subsection 2.4) The Maxent allows to use two alternative approaches to get some statistical support, either dividing the data into training and test sets or running and averaging many replicates, e.g. by cross-validation. In you prefer to select replicates, the Maxent will generate the models only for replicates. And your results show that the modelling outputs are for replicates, because if you really used the training/test modelling, the Maxent should produced two sets of outputs, one for the training set and one for the test set. You have only one set (but with variation). In addition, you did not explain what are the differences between for levels of suitability (some figures). However, these differences are very important for understanding and estimations of your results.
(4) The next question concerns models created for future periods. If I understand correctly, you used the same set of variables for your forecast as for the modern period, but that raises the question of probable soil transformation. I admit that the nature and level of human impact may remain the same, but I have no doubt that in most cases, the soil pH will change.
Technical comments:
Title — I suggest to add some words explaining the species taxonomical position (e.g., (Orthoptera: Acrididae: Gomphocerinae) and the author name
line 25 and so on — if I understand this right, you didn't optimize the model per se, you optimized several parameters of modelling.
line 63 — drought > droughts
line 70 — you are submitting your article to an international journal with a wide audience. It will be better if you will follow the internationally recognized taxonomical system of Orthoptera (we can check the Orthoptera Species File) (Orthoptera: Acrididae: Gomphocerinae: Gomphocerini)
lines 80–88 and so on — some parts of your text look as excessive, because they reproduce widely known information
line 111 — why did you select 10-km radius? Please, explain.
Figures 1–6 — all figures should be increased, font sizes should be increased in almost all cases, some parts of legends should be deciphered. Figures 3 should be optimally divided (a+b) and (c)
line 118 — the BCC-CSM2-MR climate model — please, add the reference!
lines 120–123 and so on 125 > 1–2.5
lines 145–146 — please, add the data and references about the package used.
Figure 3b — Rondom > random
Table 2 and some parts of the text — actually, the contribution of several variables (DEM and especially HFP, bio 2 and 13) is too low to discuss. And the role of altitudes (see lines 298–303) looks overestimated.
Figure 6 — please, explain how you compare models? I mean relative to the modern situation or sequentially.
lines 310–313, 344–345 — "Under current climatic conditions, the suitable habitat for D. barbipes is mainly distributed in the central and eastern grassland regions of Inner Mongolia, with additional suitable areas in the eastern Tianshan Mountains of Xinjiang and the central Qilian Mountains of Gansu." — There are no real data concerning occurrence of the model species in Tien Shan and your model shows presences of some areas with very low suitability in the region.
Author Response
Dear Reviewer,
We sincerely thank you for acknowledging the timeliness and data quality of our manuscript, as well as for your detailed and professional comments, which have provided important guidance for further improving our study. Please see the attachment for details.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThe manuscript is timely and potentially impactful for surveillance and early warning of Dasyhippus barbipes under climate change cenarios.
The dataset size and recency are notable strengths.
But several core SDM/ENM practices need strengthening to avoid inflated performance estimates and biased inference about drivers and future range shifts.
Specify the WorldClim version precisely (v2.0 vs v2.1) and baseline period.
Justify the 10 km thinning distance relative to species dispersal and 1 km raster resolution; consider sensitivity tests (e.g., 5/10/20 km).
Provide key MaxEnt settings for reproducibility: number of background points, replicate type, random seed, clamping/extrapolation settings.
Fix several encoding/typos (e.g., “paĴern”, “hĴp”).
Improve figure readability showing correlation matrix; response curves should show presence rug/quantiles and indicate whether curves are marginal).
Author Response
Dear Reviewer,
We sincerely thank the reviewer for acknowledging the timeliness and data quality of our manuscript, as well as for the detailed professional comments, which have provided important guidance for further improving our study.Please see the attachment for details.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsAll the comments are in the attachment.
Comments for author File: Comments.pdf
Author Response
We sincerely thank you for your continued rigorous evaluation and for pointing out the remaining issues in our manuscript. We have carefully addressed each of your comments as follows. Please see the attachment for details.
Author Response File: Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsDear colleagues,
Thank you very much for serious improvements of your manuscript. However, some problems remain
The problem of training/test sampling vs replicates. The Maxent allows to use two alternative approaches to get some statistical support, either dividing the data into training and test sets or running and averaging many replicates, e.g. by cross-validation. In you prefer to select replicates, the Maxent will generate the models only for replicates (Fig. 3). If you really used the training/test modelling, the Maxent should produced two sets of outputs, one for the training set and one for the test set. The supplementary table corresponds to the variant with training and test sets, but Fig. 3c appears to have been generated differently, using the package, in the part that allows generating models with replicates. Otherwise, you should have two sets of estimates (including the ROC) for two data sets. For example, I counted s.d. for your training (0.002) and test (0.004) sets, but in the text, there is only one value (0.002). Please, explain explicitly how you used the training and test sets and how you generated the Fig. 3b.
Line 176 — bootstrapping and cross-validation are quite different approaches of the so-called resampling. They are not synonyms. You should clearly explain what a method was used (either bootstrapping or cross-validation). I won't even bother to clarify that each of them includes different options
Figure 3b — Rondom > Random
Now there are two figures 6, please, check numbering and references in the text.
Author Response
We sincerely thank you for your continued rigorous evaluation and for pointing out the remaining methodological and presentation issues in our manuscript. Please see the attachment for details.
Author Response File: Author Response.pdf
Round 3
Reviewer 1 Report
Comments and Suggestions for AuthorsAll the comments are in the attachment.
Comments for author File: Comments.pdf
Author Response
Dear Reviewer,
We sincerely thank you for your critical and constructive comments on our manuscript. Your valuable suggestions have greatly helped us improve the quality of our work. We have carefully addressed all of your comments and have provided point‑by‑point replies below. All revisions have been highlighted in red in the revised manuscript. Please see the attachment for details.
Author Response File: Author Response.pdf
