Optimized Maxent Model Predictions of Climate Change Impacts on the Suitable Distribution of Cunninghamia lanceolata in China
Round 1
Reviewer 1 Report
Overview and general recommendation:
This article predicted potential suitable distribution of Cunninghamia lanceolata in China in the present day, in the 2050s, and in the 2070s under different climate change scenarios using optimized Maxent models. The objective of the article fits well with the aim and scope of the journal Forests. Niche models have been widely used in predicting changes of the species distributions, especially at large scale (i.e. landscape or global). Even such models are also been criticized a lot, the authors are aware of their limitations and have tried to overcome it to make the simulation results useful. The intention is very good, the works are very impressive, and the results are somewhat similar to what it could be expected. However, the paper’s current structure needs quite an amount of re-organization, and the authors also need to compare their results with other global studies of the same species. The reviewer would suggest the author to make the adjustments and submit the paper again.
Major comments:
The abstract and introduction are straightforward and clear. The methodology part offered quite amount information about how the simulation processes were set but lacked of the key description about the Maxent model itself. Some descriptions were written in the introduction and discussion, but the model´s theory, its main structures, and the original inventors were not mentioned as a whole in the methodology. The results are acceptable but mixed with some discussions in between. Figures 5 and 6 need major modifications to make them readable. The discussion focuses on the model performances but lack of the comparisons of the simulation results in the global scale neither the explanations in the physiological aspect of why the distributions changed. All these issues make the paper a local computer simulation research and limit its use for the general global readers.
Minor comments:
Line 120 and line 151 are not consistent.
Table 1. Why chose these specific climatic variables? Are there any references or selection criteria?
Line 187 Wouldn’t it better be written as “two feature types and five FCs ” instead of “Seven feature type and FCs”?
Line 189-191 “The grid search approach” needs more explanations.
Line 336-338 This part belongs to discussion.
Figure 5 doesn’t show in the pdf file.
Figure 6’s symbols need to be marked better. Their current form is confusing. It is difficult to tell it uses the shape or the color or the combinations to represent different conditions. The legend also needs better explanations to make the reader easier to understand the results.
Author Response
Response Letter
March 3, 2020
Prof. Dr. Timothy A. Martin
Editor-in-chief
Forests
Manuscript ID: forests-729007
Title: Optimized Maxent Model Predictions of Climate Change Impacts on the Suitable Distribution of Cunninghamia lanceolata in China
Dear Editor and Reviewer,
On behalf of our co-authors, I would like to extend our gratitude and appreciation to you and the reviewers. Thank you very much for your thorough evaluation of our manuscript and for your insightful and constructive comments and suggestions, which enabled us to improve the quality of our manuscript.
Revisions in the manuscript are shown in blue font. In this letter, the original comments of the editor/reviewer are shown in orange, and our corresponding responses are in black with blue citation from our manuscript. The itemized response to each comment is provided below.
Additionally, we have reviewed the manuscript to ensure its compliance with the formatting style or Forests.
I hope that the revised version of the manuscript meets your standards and be reconsidered for publication in Forests.
Thank you for your consideration. I look forward to hearing from you.
Sincerely,
Yingchang Li
Author List:
Name: Yingchang Li
Email: [email protected]
Address: College of Forestry, Nanjing Forestry University, No. 159, Longpan Road, Nanjing City, Jiangsu Province, 210037, China.
Corresponding author:
Name: Mingyang Li
Work phone: 86-025-8542-7327
Email: [email protected]
Address: College of Forestry, Nanjing Forestry University, No. 159, Longpan Road, Nanjing City, Jiangsu Province, 210037, China.
Name: Chao Li
Email: [email protected]
Address: College of Forestry, Nanjing Forestry University, No. 159, Longpan Road, Nanjing City, Jiangsu Province, 210037, China.
Name: Zhenzhen Liu
Email: [email protected]
Address: College of Forestry, Shanxi Agricultural University, No. 1, Mingxian South Road, Taigu County, Jingzhong City, Shanxi Province, 030801, China.
Response to Reviewer 1’s Comments
Point 1: Major comments: The abstract and introduction are straightforward and clear. The methodology part offered quite amount information about how the simulation processes were set but (1.1) lacked of the key description about the Maxent model itself. Some descriptions were written in the introduction and discussion, but the model´s theory, its main structures, and the original inventors were not mentioned as a whole in the methodology. (1.2) The results are acceptable but mixed with some discussions in between. (1.3) Figures 5 and 6 need major modifications to make them readable. The discussion focuses on the model performances but (1.4) lack of the comparisons of the simulation results in the global scale (1.5) neither the explanations in the physiological aspect of why the distributions changed. All these issues make the paper a local computer simulation research and limit its use for the general global readers.
Response 1: Thank you for your assessment. We have divided the responses in accordance with the numbers in the reviewer’s comments:
(1.1) lacked of the key description about the Maxent model itself. Some descriptions were written in the introduction and discussion, but the model´s theory, its main structures, and the original inventors were not mentioned as a whole in the methodology.
Response 1.1: We added a new section to the manuscript to briefly introduce the Maxent model (Lines 160-168):
2.2. Model
The Maxent model is a niche modelling based on the maximum entropy theory [27]. Maximum entropy theory, proposed by Jaynes in 1957, holds that anything with the maximum entropy is closest to its real state under known conditions [58]. Maxent model is used to estimate the target probability distribution by finding the probability distribution of maximum entropy (i.e., that is most spread out, or closest to uniform) subject to a set of constraints that represent our incomplete information regarding the target distribution [27]. In a study of species’ distribution, the constraints are climate, soil, terrain, or other environmental variables influencing the species’ occurrence points. Maxent software was developed by Phillips et al. in 2004 [26].
- Phillips, S.J.; Dudík, M.; Schapire, R.E. A maximum entropy approach to species distribution modeling. In Proceedings of the Twenty-first international conference on Machine learning - ICML ’04; ACM Press: New York, New York, USA, 2004; Vol. 9, pp. 655–662.
- Phillips, S.J.; Anderson, R.P.; Schapire, R.E. Maximum entropy modeling of species geographic distributions. Ecol. Modell. 2006, 190, 231–259.
- Jaynes, E.T. Information Theory and Statistical Mechanics. Phys. Rev. 1957, 106, 620–630.
(1.2) The results are acceptable but mixed with some discussions in between.
Response 1.2: Please see the Response 6 in this letter.
(1.3) Figures 5 and 6 need major modifications to make them readable.
Response 1.3: Please see the Response 7 and 8 in this letter.
(1.4) lack of the comparisons of the simulation results in the global scale
Response 1.4: Cunninghamia lanceolata is a fast-growing and high-yielding tree native to the subtropical region of Southern China, therefore, the study area of C. lanceolata was primarily in China. We compared our results with those of previous studies in China, which was added to the Discussion section of the manuscript. (Lines 559-572)
Liu et al. used the data from the counties in the subtropical area in China as distribution sample sites and the WorldClim data with 2.5´ (approximately 16 km2) spatial resolution in combination with BIOCLIM model to predict the potential distribution area under the present and future climate conditions for C. lanceolata. The results indicated that the suitable distribution area would shrunk along with distinct fragmentation when the greenhouse gas emission was doubled [105]. While Lu et al. used the process-based growth model and the WorldClim data with 2.5´ spatial resolution as well as the digital version of Vegetation Map of China (1:1000,000) to map the distribution and productivity of C. lanceolata. The results showed that species is likely to experience a northward shift with minor changes in the south, and the central region of China are likely to become more suitable for C. lanceolata under future climate conditions [106]. By contrast, with the optimized Maxent model, we not only obtain the potential distribution results with high accuracy and high spatial resolution, but also improve the transfer ability of the Maxent to predict the potential distribution of C. lanceolate in the future climate scenarios.
- Liu, J.; Kang, F. Potential Impact of Climate Change on Distribution of Cunninghamia lanceolata. J. Southwest For. Univ. 2010, 30, 22–32. (in Chinese)
- Lu, Y.; Coops, N.; Wang, T.; Wang, G. A Process-Based Approach to Estimate Chinese Fir (Cunninghamia lanceolata) Distribution and Productivity in Southern China under Climate Change. Forests 2015, 6, 360–379.
(1.5) neither the explanations in the physiological aspect of why the distributions changed.
Response 1.5: We added a new paragraph to explain the influence of the climate change to the Discussion section of the manuscript. (Lines 521-536)
Climate change, especially global warming, not only causes temperature changes in different regions, but also changes the distribution pattern of precipitation. When the change of these climatic factors is close to or beyond the adaptive threshold of current plant growth, it will lead to the migration of their distribution [7]. Water availability has a significant impact on plant height, leaf area, branch number, photosynthesis and growth [96], thus, precipitation can constrain species distribution and influence distribution in various ways [97]. The increase of precipitation during the driest month results in a longer growth season and helps species migrate to more suitable habitats within their distribution [98]. In addition, extreme high and low temperatures also have a significant influence on plant growth. The decrease of the minimum temperature of the coldest month results in premature freezing injuries to plants, and long-term low temperatures will lead to the death of plants at the distribution limit [97]; while the increase of the maximum temperature of the warmest month will destroy the water balance of plants, promote the coagulation of proteins and the internal mechanism of harmful metabolites, thus hindering plants’ growth [99]. Climate extremes have been shown to have important impacts on species’ distribution and diversity, and adding extreme climate variables in niche modelling can improve the predicted accuracy and limit of species distributions under future climate change scenarios [100–104].
- Parmesan, C.; Yohe, G. A globally coherent fingerprint of climate change impacts across natural systems. Nature 2003, 421, 37–42.
- Zhang, K.; Yao, L.; Meng, J.; Tao, J. Maxent modeling for predicting the potential geographical distribution of two peony species under climate change. Sci. Total Environ. 2018, 634, 1326–1334.
- Harsch, M.A.; HilleRisLambers, J. Climate Warming and Seasonal Precipitation Change Interact to Limit Species Distribution Shifts across Western North America. PLoS One 2016, 11, e0159184.
- Vaganov, E.A.; Hughes, M.K.; Kirdyanov, A. V.; Schweingruber, F.H.; Silkin, P.P. Influence of snowfall and melt timing on tree growth in subarctic Eurasia. Nature 1999, 400, 149–151.
- Lemmens, C.M.H.M.; Boeck, H.J. De; Gielen, B.; Bossuyt, H.; Malchair, S.; Carnol, M.; Merckx, R.; Nijs, I.; Ceulemans, R. End-of-season effects of elevated temperature on ecophysiological processes of grassland species at different species richness levels. Environ. Exp. Bot. 2006, 56, 245–254.
- Easterling, D.R. Climate Extremes: Observations, Modeling, and Impacts. Science (80-. ). 2000, 289, 2068–2074.
- Parmesan, C.; Root, T.L.; Willig, M.R. Impacts of Extreme Weather and Climate on Terrestrial Biota. Bull. Am. Meteorol. Soc. 2000, 81, 443–450.
- Zimmermann, N.E.; Yoccoz, N.G.; Edwards, T.C.; Meier, E.S.; Thuiller, W.; Guisan, A.; Schmatz, D.R.; Pearman, P.B. Climatic extremes improve predictions of spatial patterns of tree species. Proc. Natl. Acad. Sci. 2009, 106, 19723–19728.
- Carrer, M.; Motta, R.; Nola, P. Significant Mean and Extreme Climate Sensitivity of Norway Spruce and Silver Fir at Mid-Elevation Mesic Sites in the Alps. PLoS One 2012, 7, e50755.
- Smale, D.A.; Wernberg, T. Extreme climatic event drives range contraction of a habitat-forming species. Proc. R. Soc. B Biol. Sci. 2013, 280, 20122829.
Point 2: Line 120 and line 151 are not consistent.
Response 2: Thank you for your comment. The spatial resolution of the climate data was 30” (approximately 1 km2), therefore, the sentence of Line 121 has been revised to “We selected only one point closest to the center in the 30” grid plots (approximately 1 km2), which was matched with climate data layers, to reduce spatial autocorrelation [50]. ” (Lines 121-122)
Point 3: Table 1. Why chose these specific climatic variables? Are there any references or selection criteria?
Response 3: Thank you for your question. “Environmental variables were selected according to their relevance to plant survival and growth, thus precipitation and temperature are the primary environmental factors affecting plant distribution since the formation of plant distribution pattern is closely associated with the precipitation and temperature [51].” (Lines 125-128) “The data included 19 climate variables, which were derived from the monthly temperature and precipitation values to generate more biologically meaningful data reflecting a range of temperature and precipitation summaries (e.g., trends, seasonality, and extremes) [57].” (Lines 149-152)
- Zhong, L.; Ma, Y.; Salama, M.S.; Su, Z. Assessment of vegetation dynamics and their response to variations in precipitation and temperature in the Tibetan Plateau. Clim. Change 2010, 103, 519–535.
- WorldClim-Global Climate Data, Free climate data for ecological modeling and GIS Available online: http://www.worldclim.org/ (accessed on Jun 1, 2016).
- Fick, S.E.; Hijmans, R.J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 2017, 37, 4302–4315.
Point 4: Line 187 Wouldn’t it better be written as “two feature types and five FCs” instead of “Seven feature type and FCs”?
Response 4: Thank you for your question. The sentence has been revised to “Two feature types and five FCs (i.e., L, H, LQ, LQH, LQP, LQHP, and LQHPT) were used in this study.” (Lines 202-203)
Point 5: Line 189-191 “The grid search approach” needs more explanations.
Response 5: Thank you for your comments. The sentence has been revised to “The grid search approach (i.e., an exhaustive search method for setting parameter values) was used to find the best combination of RM and feature type …” (Lines 204-205)
Point 6: Line 336-338 This part belongs to discussion.
Response 6: Thank you for your suggestion. The text has been relocated to the Discussion. (Lines 533-536)
Point 7: Figure 5 doesn’t show in the pdf file.
Response 7: Thank you for your suggestion and we apologize for this. All figures in the manuscript were used with full resolution, thus, Figure 5 may have been lost during the manuscript conversion to a new file for peer review. We have therefore uploaded all figure as an independent zip file for your convenience.
Point 8: Figure 6’s symbols need to be marked better. Their current form is confusing. It is difficult to tell it uses the shape or the color or the combinations to represent different conditions. The legend also needs better explanations to make the reader easier to understand the results.
Response 8: Thank you for your comment and suggestion and we apologize for the lack of clarity. Since each point represents three different information sets, it is not effective to produce multiple graphs. Therefore, we continued using the original symbols, but add a legend caption in the text. “Cimate scenarios are distinguished by a given symbol; for time periods, present day is displayed by a star, and 2050s and 2070s are distinguished by the center of symbols; suitability grades are distinguished by the color.” (Lines 433-436)
Reviewer 2 Report
Although the concept is not very novel, the study and the paper are well-designed, well-performed and well-presented
minor remarks:
* phenology is the study of periodic plant and animal life cycle events, so it cannot be other than biological – omit that word
* climate change leads not only to species extinction
* L41-42 that's unclear, rephrase it or split into shorter sentences
* fig. 1 – can’t catch the idea of lower panels, for me they are pointless as it's just zooming, however the zoomed area is not indicated on the large-scale maps
* table 1 – would be good to provide the range (min-max), mean and SD or CV (variability measure) for each parameter
* fig.5 – I wish I could say anything about it, but I see only blank page
* fig 6 – what are the red dots in the large-scale map in the upper-right corner - are these the same points that are presented in close-up - perhaps you should colour the accordingly to retain the coherence between these maps
Author Response
Response Letter
March 3, 2020
Prof. Dr. Timothy A. Martin
Editor-in-chief
Forests
Manuscript ID: forests-729007
Title: Optimized Maxent Model Predictions of Climate Change Impacts on the Suitable Distribution of Cunninghamia lanceolata in China
Dear Editor and Reviewer,
On behalf of our co-authors, I would like to extend our gratitude and appreciation to you and the reviewers. Thank you very much for your thorough evaluation of our manuscript and for your insightful and constructive comments and suggestions, which enabled us to improve the quality of our manuscript.
Revisions in the manuscript are shown in blue font. In this letter, the original comments of the editor/reviewer are shown in orange, and our corresponding responses are in black with blue citation from our manuscript. The itemized response to each comment is provided below.
Additionally, we have reviewed the manuscript to ensure its compliance with the formatting style or Forests.
I hope that the revised version of the manuscript meets your standards and be reconsidered for publication in Forests.
Thank you for your consideration. I look forward to hearing from you.
Sincerely,
Mingyang Li
Author List:
Name: Yingchang Li
Email: [email protected]
Address: College of Forestry, Nanjing Forestry University, No. 159, Longpan Road, Nanjing City, Jiangsu Province, 210037, China.
Corresponding author:
Name: Mingyang Li
Work phone: 86-025-8542-7327
Email: [email protected]
Address: College of Forestry, Nanjing Forestry University, No. 159, Longpan Road, Nanjing City, Jiangsu Province, 210037, China.
Name: Chao Li
Email: [email protected]
Address: College of Forestry, Nanjing Forestry University, No. 159, Longpan Road, Nanjing City, Jiangsu Province, 210037, China.
Name: Zhenzhen Liu
Email: [email protected]
Address: College of Forestry, Shanxi Agricultural University, No. 1, Mingxian South Road, Taigu County, Jingzhong City, Shanxi Province, 030801, China.
Response to Reviewer 2’s Comments
Point 1: phenology is the study of periodic plant and animal life cycle events, so it cannot be other than biological – omit that word
Point 2: climate change leads not only to species extinction
Response 1 and 2: Thank you for your comment. We have revised the text as follows. “Climate change significantly influences changes in ecological phenomena and processes, such as species distribution and phenology, thus accelerating the rate of species extinction or prosperity.” (Lines 13-15) “Several observational studies have shown that climate change has caused or is causing significant changes to ecological processes, including distribution ranges, morphological characteristics, and phenology, that are accelerating species extinction or prosperity [7–9]” (Lines 45-48)
Point 3: L41-42 that's unclear, rephrase it or split into shorter sentences.
Response 3: Thank you for your comment. We have revised the text as follows “The Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) indicates that the annual mean temperature of the Earth's surface has increased by 0.85 °C over the past 130 years (1880–2012). While the mean temperature of the past 60 years (1951–2012) increasing by 0.72 °C.” (Lines 40-43)
Point 4: fig. 1 – can’t catch the idea of lower panels, for me they are pointless as it's just zooming, however the zoomed area is not indicated on the large-scale maps
Response 4: Thank you for your comment. We have revised Figure 1. The lower-right panel was used to display the points in which province, and the predicted suitable distribution area was situated in said provinces. (Lines 396-397, and 418-420)
Point 5: table 1 – would be good to provide the range (min-max), mean and SD or CV (variability measure) for each parameter
Response 5: Thank you for your suggestion. As have added “The description and statistics of these climate variables are presented in Table 1 and Table A1, respectively.” (Lines 152-153)
Point 6: fig.5 – I wish I could say anything about it, but I see only blank page
Response 6: Thank you for your comment, and we apologize for this. All figures in the manuscript were used with full resolution, thus, Figure 5 may have been lost during manuscript conversion to a new file for peer review. We have therefore uploaded all figure as an independent zip file for your convenience.
Point 7: fig 6 – what are the red dots in the large-scale map in the upper-right corner - are these the same points that are presented in close-up - perhaps you should color the accordingly to retain the coherence between these maps
Response 7: Thank you for your comment. The red dots in the upper-right corner of the map were same points in the large-scale map to display their rough location in China. We revised the figure accordingly.
Author Response File: 
Author Response.docx
Round 2
Reviewer 1 Report
The authors have made all the changes/modifications according to the reviewer's suggestions. The reviewer doesn't have any further suggestions.
