Articles | Volume 19, issue 17
© Author(s) 2022. This work is distributed underthe Creative Commons Attribution 4.0 License.
Strong influence of trees outside forest in regulating microclimate of intensively modified Afromontane landscapes
- Final revised paper (published on 08 Sep 2022)
- Preprint (discussion started on 21 Oct 2021)
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor |
: Report abuse
RC1: 'Comment on bg-2021-261', Anonymous Referee #1, 16 Nov 2021
- AC1: 'Reply on RC1', Iris Aalto, 01 Feb 2022
RC2: 'Comment on bg-2021-261', Anonymous Referee #2, 12 May 2022
- AC2: 'Reply on RC2', Iris Aalto, 30 May 2022
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (14 Jun 2022) by Christopher Still
AR by Iris Aalto on behalf of the Authors (01 Jul 2022)  Author's response Author's tracked changes Manuscript
ED: Publish as is (26 Jul 2022) by Christopher Still
MS No.: bg-2021-261
Title: Strong influence of trees outside forest in regulating microclimate of intensively modified Afromontane landscapes
Author(s): Iris Johanna Aalto, Eduardo Eiji Maeda, Janne Heiskanen, Eljas Kullervo Aalto, and Petri Kauko Emil Pellikka
MS type: Research article
Iteration: Initial submission
This paper aims to examine the effect of canopy cover on microclimate in an intensively modified Afromontane landscape in Taita Taveta, Kenya. The authors studied microclimate sensors under different canopy covers, and land surface temperature (LST) from Landsat 8 thermal infrared sensors and combined these data with high-resolution airborne laser scanning data to disentangle combined effects of topography and canopy cover on microclimate. This is an interesting comparison of temperatures across canopy cover changes, forest types, and elevational gradients to help understand thermal regulation by forests and microclimates that buffer species and local climate against warming.
A strength of the study is that it utilizes multiple temperature datasets (in situ and remote sensing) and that it includes study sites along an elevational gradient with CC changes. The study shows a strong negative relationship between canopy cover and temperature, with the strongest effect on maximum temperature. Results are well reported with good figures. The main weakness of the paper is that it does not carefully describe the different physical measurements, what they actually measure, and how they related and interact. The link between microclimate and LST is not clearly established.
Line 40-41 describes the values of Forests and TOF as “vital ecosystem services” which I think implies that they are source of many goods and services to humans (ie. That next sentence is redundant). When you say that forests and TOF are “also a source of goods for humans,” are you actually referring to uses that degrade forests, such as logs for building or firewood gathering? This should be clarified because it can conflict with the ecosystem services you have just described. The tension between what forests provide when they are left standing, and how they are used for raw materials sets the stage for the existing condition of your study area.
On lines 97 to 102 of the Methods you describe this. But I think this is important background on TOF and helps readers understand why TOF are important (e.g. carbon storage and biodiversity). I recommend moving these lines to the Introduction to complete the TOF paragraph.
For example, the De Frenne study states “…the local temperature experienced by living organisms (referred to as the (‘microclimate’)... While quite general, this definition includes the thermal regulation of forests across scales.
Lines 48-45: The authors compare understory microclimate variability to continental scale studies of spatial variability in LST measurements. LST is canopy temperature, a different physical measurement that indicates partitioning of solar radiation driven by transpirational cooling. I think you should add a sentence recognizing the differences in these physical measurements and that you are inferring a relationship between radiometric surface temperature and understory temperatures especially since the relationship between these various temperature measurements are not well understood.
Scherrer, D. M. K-F. Bader, and C. Korner. 2011. Drought-sensitivity ranking of deciduous tree
species based on thermal imaging of forest canopies. Agricultural and Forest Meteorology, 151,
Kim, Y., Still, C.J., Hanson, C.V., Kwon, H., Greer, B.T. & Law, B.E. (2016). Canopy skin temperature variations in relation to climate, soil temperature, and carbon flux at a ponderosa pine forest in central Oregon, Agricultural and Forest Meteorology, 226, 161-173.
Mildrexler, D.J., Yang, J.Z., & Cohen, W.B. 2016. A Forest Vulnerability Index Based On
Drought and High Temperatures. Remote Sensing of Environment, 173, 314-325.
Nemani, R. R., and S. W. Running 1997. Land cover characterization using multitemporal red, near-IR, and thermal-IR data from NOAA/AVHRR, Ecol. Appl., 7, 79–90.
Goward, S. N., Cruickshanks, G. D., & Hope, A. S. (1985). Observed relation between thermal emission and reflected spectral radiance of a complex vegetated landscape, Remote Sensing of Environment, 18, 137-146.
Goward, S. N., & Hope, A. S. (1989). Evapotranspiration from combined reflected solar and emitted terrestrial radiation: Preliminary FIFE results from AVHRR data., Advanced Space Research, 9, 239-249.
Methods and Results
Oyler, J. W., S. Z. Dobrowski, Z. A. Holden, and S. W. Running, 2016: Remotely sensed land skin temperature as a spatial predictor of air temperature across the conterminous United States. J. Appl. Meteor. Climatol., 55, 1441–1457
Davis, K. T., Dobrowski, S. Z., Holden, Z. A., Higuera, P. E., and Abatzoglou, J. T. (2019a). Microclimatic buffering in forests of the future: the role of local water balance. Ecography 42, 1–11. doi: 10.1111/ecog.03836
369-370: At line 356 you questioned whether LST is representative of understory conditions and provided citations. Here you state that your results showed that LST can be used as a proxy for assessing the impacts of CC on microclimate. Do your results really show this? Or do they show that an increase in canopy cover results in a commensurate decrease in LST?
Other Specific Comments:
Line 140: delete “laying” so sentence reads “as the plot was outside of the ALS coverage.”
Line 191: Reword to: CC also affected temperature variability
Line 287: In additional to sensible heat flux, could some of the cooling effect be due to transpirational cooling?
298: Change discovery to finding.
292: prevalent doesn’t make sense here. Please clarify.
295: “One likely reason…”: isn’t another likely reason that on cloudy days there is less solar insolation at the surface, which has a disproportionately large effect on warming areas with low CC on sunny days?
314: Change extent to magnitude
328: Can simplify sentence to “Soil and air temperatures impact crop productivity,…”