Peer review of: Yield reduction under climate warming varies among wheat cultivars in South Africa (2020)


 
 

Reviewers' Comments: 
 
Reviewer #1: 
Remarks to the Author: 
The author(s) satisfactorily addressed my concerns. I only suggest some minor edits. Although I 
believe these edits would improve clarity and readability of the manuscript, the decision on adoption 
or rejection of them is entirely left for the author(s). 
 
1. L9. “a 12.5% yield reduction”. I think, the confidence interval needs be mentioned in Abstract. 
2. L9-10. “The yield models are then used …”. Please consider presenting your findings in Abstract, 
but not what you did. What is the estimated yield reduction for +1 to +3 degC? Their confidence 
intervals are also required. 
3. L11-13. The same suggestion is applied here. I think, a main implication of this study which is 
worth mentioning in Abstract is described around L243-245. 
4. L27. “aggregate, non-empirical”. Do you mean “biophysical” crop model? 
5. L85. “extreme weather”. “The drought event” would be more precise if the extreme weather 
indicate drought. 
6. L130. Please consider adding the confidence interval for the estimates. 
7. L212-214. I would suggest citing Fig. S3 here to show the rationale. 
8. L226. “-10 and -11 percent”. Are these relative to the multi-variety average? If so, I would ask the 
author(s) explicitly mentioning the baseline. 
9. L274. There is a variation in terminology (biophysical crop model, crop growth model etc.). Please 
use a consistent terminology. 
 
 
 
Reviewer #2: 
Remarks to the Author: 
The manuscript has now substantially improved following the authors' response to the feedback 
received from all reviewers. However, I still have some questions as some of the responses fall short 
(and there may be some new ones). 
 
- There is still a lot of talk about droughts in the introduction. The manuscript deals with warming/heat 
so it shouldn't use drought examples and papers as support. 
 
- There is a lot of similarities with Schlenker and Roberts (2009), which is great. But they focused (as 
far as I understood it) on 1C bins. As I asked previously, what would happen if you chose other bin 
sizes? Why is the threshold set at 30C and not 29C or 31C? Also, the references to support the 
threshold of 30C focus on other regions, and possibly other cultivars, and I assume this threshold 
could be different here. I'd like to see some sensitivity analysis. 
 
- precipitation data: a few things here. first, I do not see that robustness check that you mention 'at 
line ~401'. second, there are fairly good daily datasets (TAMSAT and CHIRPS) at higher resolution 
than WorldClim2. third, should you interpolate, then you need to use a method that takes into account 
elevation and other factors (like ANUSPLIN). Or you could use the weather stations to bias correct the 
gridded data over the stations. fourth, the distribution of rainfall within a season is also important, in 
addition to the seasonal sum. I was suggesting to use the seasonal CV (see Rowhani et al. 2011) but 
if you can think of another way, that would also be great. and finally, you include low rainfall to the 
highest temperature bin only. What would happen if that interaction was included with all the bins? 
 
- could all the robustness check also show a similar figure to Fig 2? just like in Schlenker and Roberts. 

 
 
- climate change impacts: the cited papers (L108) refer mainly to studies in the US, what do the 
climate models say for South Africa? It would make more sense using those numbers than relying on 
other regions (and other studies). And how do you include changes in rainfall patterns when looking at 
the impacts of climate change? 
 
- L58-60: I suppose you mean 'production' and not 'productivity'. Average yield seems to be around 4 
tonnes/ha which is quite similar to other areas that produce rainfed wheat (eg., 
https://www.frontiersin.org/articles/10.3389/fpls.2015.00990/full). Overall productivity usually has to 
do with management, seeds, soils,... and can be affected by these biotic and abiotic factors that you 
mention during an event. 
 
- Timing is always an important factor, especially with heat events. Is there a way to check the model 
output when looking at temperature profiles for specific phases of plant growth (i.e., from planting to 
flowering and flowering to harvest)? 
 
- out of curiosity, and as a result from the spatial autocorrelation analysis, how confident can one be 
with your results given the high inflation factor? also, given the differences in climate and other 
factors between the two provinces, would it make sense to run two separate models (one for each 
province) or have province as a fixed effect (or a hierarchichal fixed effect site:province - but I am 
way out of my expertise). 
 
- finally, it is a shame you do not have more info on the cultivars because that is really the main point 
of the paper and it would allow us to properly understand what is going on. While I understand that 
there is not much you can do about the data itself, I am wondering whether you can provide some 
more information in some other way. For example, in Fig 5, are there cultivars that have low heat 
impact and high yield (maybe I am thinking of all of those way above the red line in Fig5C). Could you 
look at yield trends for these? Since this is a paper on breeding as adaptation, it would be good to 
provide more info one way or another. 
 
- Table 1 needs reformatting 
 
- l25: could use some citations 
 
- references 15 and 19:remove the letter after 'GAIN'