- Email: [email protected]
Peer review report 1 on “Seasonal, interannual changes in vegetation activity of tropical forests in Southeast Asia”
Agricultural and Forest Meteorology 217 (2016) 176
Contents lists available at ScienceDirect
Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet
Peer Review Report
Peer review report 1 on “Seasonal, interannual changes in vegetation activity of tropical forests in Southeast Asia”
Original submission Recommendation Major Revision Comments to Author General comments: The authors investigated factors that control seasonal and interannual variability in vegetation photosynthetic activity by combining three NDVI products, one SIF product and climate data. The manuscript is very well written, and the topic falls on the scope of AFM. Key findings in this manuscript include: 1) NDVI decreased during dry season, 2) SIF and NDVI showed different seasonality, and 3) NDVI in dry season was positively correlated to precipitation on interannual scales. I think the 1 st finding is well supported by the NDVI products. The 2 nd finding is very interesting, but the authors did not provide convincing reason for the discrepancy between SIF and NDVI (see my specific comments). The 3 rd finding is not supported by the data. Table 1 shows that significant positive correlation between NDVI and precipitation during dry season only appeared in 7% (84-07) or 15% (01-07) in entire area (p<0.05). In my view, Table 1 and 2 reveal interannual variability in NDVI was not mainly controlled by climate variables, which is somewhat surprising to me. Several major comments follow: I am curious why climate variables did not explain well the interannual variability in NDVI. I think non-climate variables such as land use change and fire should be discussed. The authors used a single land cover map, which is applied over a 23 year period. Given intensive land cover changes in this region, use of constant land cover map over a long-term could lead incorrect interpretations on the results. Reduction of NDVI during dry season should be better discussed. In-situ data (in particular, flux tower data or photosynthetic parameters such as Vcmax, Amax) in this region will be instrumental to better understand NDVI pattern in dry season. I recall Dr Hirano has been running one flux tower in Indonesia.
DOI of published article: http://dx.doi.org/10.1016/j.agrformet.2016.04.009. http://dx.doi.org/10.1016/j.agrformet.2016.11.114 0168-1923/
Data quality in NDVI and SIF should be provided. As the authors introduced the debates on Amazon green-up during dry season, I am pretty sure similar debates could rise in South Asian tropical forests which experience frequent, thick clouds and intensive fires. Report the acquisition rate in best quality data (thus the proportion in gap-filled data) for each period in different data sets. In Fig 3 and 4, show correlation coefficients (not p-values) of the pixels that are statistically significant (p<0.05). By reporting pvalue maps with including statistically non-significant pixels, it is very hard to interpret the patterns. The large discrepancy between SIF and NDVI seasonality looks interesting (in particular, north EF), but discussion on this matter is not interesting. Thorough intercomparison is needed. First, the data quality should be checked (see above comment). Second, compare spatial patterns between SIF and NDVI. Report where they agree and disagree and explain why. Current contents simply reported the discrepancy without further insightful discussion. Specific comments: L27: The authors stated “consistent correlations between NDVI and climate factors at seasonal and interannual time scales”, which is not supported by Table 1 and 2 if one pays attention to the percentage in p<0.05. L156: The link does not work. Also report the year of land cover map. L183: I feel 50% threshold seems too low. I am curious whether the seasonal pattern of SIF in Fig 2 is consistent whether you use higher threshold like 75%. L266: There are no Table S1 and S2. Fig 3 and 4: Show pixels (p<0.05). It is not necessary to show all pixels that are statistically not significant. The figure captions said “correlation coefficients” maps, which were actually p-values maps. L367-369: SIF also depends on leaf area and leaf reflectance. Further, SIF is tightly correlated to APAR as VIs are. See Xi’s recent paper. Yang, X., Tang, J., Mustard, J.F., Lee, J.-E., Rossini, M., Joiner, J., Munger, J.W., Kornfeld, A., Richardson, A.D. (2015) Solar-induced chlorophyll fluorescence that correlates with canopy photosynthesis on diurnal and seasonal scales in a temperate deciduous forest. Geophysical Research Letters 42, 2977-2987. Anonymous Available online 30 November 2016
Contents lists available at ScienceDirect
Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet
Peer Review Report
Peer review report 1 on “Seasonal, interannual changes in vegetation activity of tropical forests in Southeast Asia”
Original submission Recommendation Major Revision Comments to Author General comments: The authors investigated factors that control seasonal and interannual variability in vegetation photosynthetic activity by combining three NDVI products, one SIF product and climate data. The manuscript is very well written, and the topic falls on the scope of AFM. Key findings in this manuscript include: 1) NDVI decreased during dry season, 2) SIF and NDVI showed different seasonality, and 3) NDVI in dry season was positively correlated to precipitation on interannual scales. I think the 1 st finding is well supported by the NDVI products. The 2 nd finding is very interesting, but the authors did not provide convincing reason for the discrepancy between SIF and NDVI (see my specific comments). The 3 rd finding is not supported by the data. Table 1 shows that significant positive correlation between NDVI and precipitation during dry season only appeared in 7% (84-07) or 15% (01-07) in entire area (p<0.05). In my view, Table 1 and 2 reveal interannual variability in NDVI was not mainly controlled by climate variables, which is somewhat surprising to me. Several major comments follow: I am curious why climate variables did not explain well the interannual variability in NDVI. I think non-climate variables such as land use change and fire should be discussed. The authors used a single land cover map, which is applied over a 23 year period. Given intensive land cover changes in this region, use of constant land cover map over a long-term could lead incorrect interpretations on the results. Reduction of NDVI during dry season should be better discussed. In-situ data (in particular, flux tower data or photosynthetic parameters such as Vcmax, Amax) in this region will be instrumental to better understand NDVI pattern in dry season. I recall Dr Hirano has been running one flux tower in Indonesia.
DOI of published article: http://dx.doi.org/10.1016/j.agrformet.2016.04.009. http://dx.doi.org/10.1016/j.agrformet.2016.11.114 0168-1923/
Data quality in NDVI and SIF should be provided. As the authors introduced the debates on Amazon green-up during dry season, I am pretty sure similar debates could rise in South Asian tropical forests which experience frequent, thick clouds and intensive fires. Report the acquisition rate in best quality data (thus the proportion in gap-filled data) for each period in different data sets. In Fig 3 and 4, show correlation coefficients (not p-values) of the pixels that are statistically significant (p<0.05). By reporting pvalue maps with including statistically non-significant pixels, it is very hard to interpret the patterns. The large discrepancy between SIF and NDVI seasonality looks interesting (in particular, north EF), but discussion on this matter is not interesting. Thorough intercomparison is needed. First, the data quality should be checked (see above comment). Second, compare spatial patterns between SIF and NDVI. Report where they agree and disagree and explain why. Current contents simply reported the discrepancy without further insightful discussion. Specific comments: L27: The authors stated “consistent correlations between NDVI and climate factors at seasonal and interannual time scales”, which is not supported by Table 1 and 2 if one pays attention to the percentage in p<0.05. L156: The link does not work. Also report the year of land cover map. L183: I feel 50% threshold seems too low. I am curious whether the seasonal pattern of SIF in Fig 2 is consistent whether you use higher threshold like 75%. L266: There are no Table S1 and S2. Fig 3 and 4: Show pixels (p<0.05). It is not necessary to show all pixels that are statistically not significant. The figure captions said “correlation coefficients” maps, which were actually p-values maps. L367-369: SIF also depends on leaf area and leaf reflectance. Further, SIF is tightly correlated to APAR as VIs are. See Xi’s recent paper. Yang, X., Tang, J., Mustard, J.F., Lee, J.-E., Rossini, M., Joiner, J., Munger, J.W., Kornfeld, A., Richardson, A.D. (2015) Solar-induced chlorophyll fluorescence that correlates with canopy photosynthesis on diurnal and seasonal scales in a temperate deciduous forest. Geophysical Research Letters 42, 2977-2987. Anonymous Available online 30 November 2016