Peer review report 2 On “Quantifying biosphere-atmosphere exchange of CO2 using eddy covariance, wavelet denoising, neural networks, and multiple regression models”
Peer review report 2 On “Quantifying biosphere-atmosphere exchange of CO2 using eddy covariance, wavelet denoising, neural networks, and multiple regression models”
Agricultural and Forest Meteorology 201S (2015) 568
Contents lists available at ScienceDirect
Agricultural and Forest Meteorology journal homepage: ...
Agricultural and Forest Meteorology 201S (2015) 568
Contents lists available at ScienceDirect
Agricultural and Forest Meteorology journal homepage: www.elsevier.com/locate/agrformet
Peer review report
Peer review report 2 On “Quantifying biosphere-atmosphere exchange of CO2 using eddy covariance, wavelet denoising, neural networks, and multiple regression models”
Original Submission Recommendation: Minor Revision 1. Comments to Author: I have carefully reviewed this manuscript and find that it is a well-executed study. The intent of finding quantitative measurements to better understand a dynamically-changing environment is well laid out and justified equally well. I, therefore, recommend it for publication.
I do have one suggestion. Several sentences in the manuscript, in my opinion, are long. To improve readability, the author should consider shorter sentences. As an example: Lines 3-8: Long-term estimates of net ecosystem exchange of CO2 (NEE) and their partitioning into both flux and temporal components are essential to a better quantification and understanding of spatio-temporal dynamics of carbon (C) sources and sinks under human-induced disturbances. Such quantitative estimates are better suited as preventive and mitigative measures in a changing global environment and climate (Wali et al., 1999; Baldocchi, 2008; Evrendilek et al., 2011). Anonymous Available online 6 August 2015
DOI of original article: http://dx.doi.org/10.1016/j.agrformet.2012.11.002. 0168-1923/$ – see front matter http://dx.doi.org/10.1016/j.agrformet.2015.07.146