Quantifying Key Environmental Determinants Shaping the Ecological Niche of Fruit Moth Carposina sasakii Matsumura, 1900 (Lepidoptera, Carposinidae)

Comments 1: [The manuscript analyzes the environmental drivers of an important fruit tree pest and uses the MaxEnt model to predict the global suitable habitat distribution and its change trends under future climate scenarios, which has certain application value and significance for biosecurity prevention and control. There are some issues in the details of data processing and analysis, and the following revisions are suggested.]

Response 1: Thank you so much. We are grateful for the feedback and will reply to this reviewer’s comments in order.

Comments 2: [In the processing of geographical distribution data, the specific parameters of spatial thinning (such as the minimum distance threshold) are not clarified. Different distance thresholds may affect the spatial independence of distribution points and the model prediction results. It is recommended to supplement the relevant parameter settings and the basis for their selection.]

Response 2: Thank you for the suggestion, we agreed with this comment and modified the manuscript accordingly.

[Since the environmental variable resolution was 5 arc-minutes, the rarefaction distance parameter was set to 5 km [15]. All adjacent redundant vertices within this threshold were removed, retaining only key nodes that significantly contributed to the geometry [14].]

References:

[14] Sun, P.; Li, H.; Hao, E.; Lu, P.; Qiao, H. Prediction and analysis of global potential distribution of Semanotus bifasciatus based on MaxEnt model. Journal of Plant Protection 2024, 51, 1506–1517. https://doi.org/10.13802/j.cnki.zwbhxb.2024.2023110.

[15] Zhang, Y.; Wan, Y.; Wang, C.; Chen, J.; Si, Q.; Ma, F. Potential distribution of three invasive agricultural pests in China under climate change. Scientific Reports 2024, 14, 13672. https://doi.org/10.1038/s41598-024-63553-3.]

Where in the revised manuscript can this change be found [Page 3, and Line 92-95.]

 Comments 3: [In the simulation of future climate scenarios, using only one climate model is likely to lead to uncertainties. It is recommended to supplement the reasons for selecting a single model, or consider adding 1-2 mainstream CMIP6 models for multi-model comparative analysis to reduce the uncertainties of the prediction results.]

Response 3: Thank you for the suggestion, we apologize for the confusion. The sentence has been revised as follows:

[The CMCC-ESM2 was selected for this study due to its accurate simulation of temperature, precipitation, and wind patterns, as well as its enhanced representation of terrestrial biogeochemistry, including expanded carbon pools, plant functional types, and nitrogen cycle dynamics [17,18]. These were closely corresponding to the climatic factors selected in this study.]

References：

[17] Lovato, T.; Peano, D.; Butenschön, M.; Materia, S.; Iovino, D.; Scoccimarro, E.; Fogli, P. G.; Cherchi, A.; Bellucci, A.; Gualdi, S.; Masina, S.; Navarra, A. CMIP6 simulations with the CMCC Earth System Model (CMCC-ESM2). Journal of Advances in Modeling Earth Systems 2022, 14, e2021MS002814. https://doi.org/10.1029/2021MS002814.

[18] Cherchi, A.; Fogli, P. G.; Lovato, T.; Peano, D.; Iovino, D.; Gualdi, S.; Masina, S.; Scoccimarro, E.; Materia, S.; Bellucci, A.; Navarra, A. Global mean climate and main patterns of variability in the CMCC-CM2 coupled model. Journal of Advances in Modeling Earth Systems 2019, 11, 185–209. https://doi.org/10.1029/2018MS001369.]

Where in the revised manuscript can this change be found [Page 3, and Line 111-115.]

 Comments 4: [In the centroid migration analysis, only the coordinates of the current distribution centroid are provided. It is recommended to supplement the centroid coordinates, migration direction and distance under each future scenario, and plot the centroid migration trajectory diagram with relevant data.]

Response 4: Thank you for the reminder, we apologize for the confusion. The sentence has been revised as follows:

[Despite the profound influence of global climate change on species distribution patterns, our analysis reveals remarkable spatial stability in the distribution centroid of C. sasakii. Geographical coordinates in the current and future scenarios did not change (73.494546 E, 36.777818 N) (Figure 13).]

Where in the revised manuscript can this change be found [Page 13, and Line 302-305.]

 Comments 5: [It is recommended to supplement the changes in area distribution of different suitability levels in each time period in the prediction results of future scenarios.]

Response 5: Thank you for the reminder, we apologize for the confusion. The sentence has been revised as follows:

[The high suitable area, medium suitable area, low suitable area, and total suitable area projections for C. sasakii habitats under current and future climate scenarios are listed in Figure 12. These patterns demonstrate climate change’s nonlinear modulation of pest habitats structures.]

Where in the revised manuscript can this change be found [Page 12, and Line 295-298.]

Comments 6: [In the discussion section, it is suggested to conduct a more in-depth analysis of the research limitations, such as the impact of potential geographical biases in the current distribution data on the prediction results; the influence mechanism of climate factor thresholds can be further analyzed in depth, such as the correlation between precipitation thresholds and pest development.]

Response 6: Thank you for the suggestion, we agreed with this comment and modified the manuscript accordingly.

[As a fruit-boring pest in East Asia, C. sasakii enters its overwintering generation in spring, a critical period for population recovery and development. Due to effective accumulated temperature requirements, development is slow and population levels are low [16]. By July when precipitation reaches 370 mm, adult emergence peaks, enhancing reproductive and dispersal abilities. Egg production and harm range expand, with increased hatching and larval survival rates. Previous studies found this to be the most active life stage, with the shortest generation time due to effective accumulated temperature [36], validating our analysis. Monitoring from spring and centralized control in July can efficiently manage populations by targeting adult activities, such as egg-laying at fruit outlets, achieving effective prevention and control.

References：

[16] Fang, S.; Qiao, X.; Su, S.; Jian, C.; Chen, M. Damage and Control Research Progress of Carposina sasakii. Shaanxi Journal of Agricultural Sciences 2022, 68, 77–82.

[36] Hua, B.; Zhang, A.; Lu, X.; Hua, L. Occurrence patterns of Carposina sasakii in apricot orchards in the Qinling Mountains. Acta Agriculturae Boreali-occidentalis Sinica 1998, 7, 39–42.]

[Although the MaxEnt model offers advantages in simplicity, minimal sample requirements, and high prediction accuracy, it shares limitations with other niche prediction models [45]: (1) Overfitting occurs when distribution points are concentrated, leading to local environmental feature dominance and reduced generalizability [46]. Sparsity techniques mitigate spatial autocorrelation but cannot fully eliminate bias. (2) Species distribution is influenced by both abiotic and biotic factors. This study primarily used bioclimatic variables, excluding biological factors like host plant distribution and interspecific competition. Human activities also significantly impact C. sasakii populations. Current predictions focus on climate-driven geographical distribution, highlighting key climate characteristics [47]. Future work should incorporate host plant data, human factors, and additional variables for context-specific predictions.

References:

[45] Wei, X.; Xu, D.; Zhuo, Z. Predicting the Impact of Climate Change on the Geographical Distribution of Leafhopper, Cicadella viridis in China through the MaxEnt Model. Insects 2023, 14, 586. https://doi.org/10.3390/insects14070586.

[46] Zhang, S.; Li, C.; Zhang, Y. Impact of environmental variables and species distribution data on prediction of potential suitable areas for Paeonia szechuanica based on MaxEnt model. Journal of Gansu Forestry Science and Technology 2024, 49, 49–55, 71.

[47] Wang, R.; Li, Q.; He, S.; Liu, Y.; Wang, M.; Jiang, G. Modeling and mapping the current and future distribution of Pseudomonas syringae pv. Actinidiae under climate change in China. PLOS ONE 2018, 13, e0192153. https://doi.org/10.1371/journal.pone.0192153.]

Where in the revised manuscript can this change be found [Page 15-17, and Line 347-356, 418-428.]

 Comments 1: [The submitted MS, entitled “Quantifying Key Environmental Determinants Shaping the Ecological Niche of fruit moth Carposina sasakii Matsumura” represents interesting and important data on SDM (species distribution modelling) of Carposina sasakii moth. Such predictions are of a real importance, taking into account that the species in question is a significant lepidopteran pest, inflicting damage agricultural fruit trees.

The MS is well-written and well organized and undoubtedly worthy for publication in “Insects” after minor revision. I have only minor comments and suggestions (see below):]

Response 1: Thank you so much. We are grateful for the feedback and will reply to this reviewer’s comments in order.

 Comments 2: [Title. It is necessary to provide not only author, but also year of the description (Matsumura, 1900) as it commonly accepted in the scientific publications. I also recommend to provide taxonomic position of the taxon in question. Please, consider the following title “Quantifying Key Environmental Determinants Shaping the Ecological Niche of fruit moth Carposina sasakii Matsumura 1900 (Lepidoptera, Carposinidae)”.]

Response 2: Thank you for the suggestion, we agreed with this comment and modified the manuscript accordingly.

[Quantifying Key Environmental Determinants Shaping the Ecological Niche of the Fruit Moth Carposina sasakii Matsumura, 1900 (Lepidoptera: Carposinidae)]

Where in the revised manuscript can this change be found [Page 1, and Line 2-4.]

 Comments 3: [Consider revising Section ”3.2 Environmental Variable Contributions”. Avoid repetition of the same information to make the text more concise and clearer. For instance,

Lines 186-187 “Precipitation variables contributed 50.7% to the model (prec7 alone contributing 38%), while temperature factors accounted for 49.3%.”

This information is already given few lines above, see lines 181-182: (Lines 181-182

“Collectively, precipitation variables accounted for 50.7% of total contributions (prec7 being dominant), while temperature variables contributed 49.3%.”)

Line 193 These results establish prec7 as the primary limiting factor

You already point it out in the Line 190: (Line 190 “with prec7 emerging as the primary limiting factor”)

Line 200 “Notably, prec7 exhibited a significantly lower normalized training gain value” and see lines 192-193: Lines 192-183 “Notably, prec7 showed the smallest 192

normalized training gain when…”]

Response 3: Thank you for the suggestion, we agreed with this comment and modified the manuscript accordingly.

[Among them, the normalized training gain value of prec7 is significantly lower than that of other variables, which further confirms our research: prec7 provides unique and crucial information for simulating the global habitat suitability of C. sasakii.]

Where in the revised manuscript can this change be found [Page 6, and Line 184-188, 196, 206-209.]

 Comments 4: [Please, check and revise legends for Figures 8, 9, 10, 11. They are identical: Predicted distribution of Carposina sasakii (years 2021–2100) under SSP126 scenarios. Is that copy+paste error? I believe, the correct is different models, SSP126, SSP245, SSP370, SSP585.]

Response 4: Thank you for the comment, we apologize for the confusion. The figure legends have been revised as follows:

[Figure 8 legend: ... under SSP126 scenario.

Figure 9 legend: ... under SSP245 scenario.

Figure 10 legend: ... under SSP370 scenario.

Figure 11 legend: ... under SSP585 scenario.]

Where in the revised manuscript can this change be found [Page 9-12, and Line 264-294.]

 Comments 5: [Italicize Latin name of the taxon in question throughout the text.]

Response 5: Thank you for the reminder, we have modified the manuscript accordingly.

Comments 6: [For other minor corrections, please see attached file.]

Response 6: We thank the reviewer for the detailed annotations in the attached file. We have carefully reviewed and incorporated all suggested minor corrections, which included typographical fixes, grammatical improvements, and clarifications of phrasing. All changes have been implemented in the revised manuscript to polish the language and accuracy of the text.