Recovering Forecast Distributions of Crop Composition: Method and Application to Kentucky Agriculture
Round 1
Reviewer 1 Report
This is a remarkable paper highlighting prospects and opportunity for incremental, empirical analysis of farmers' decisions and their economic and environmental outcomes.
My only suggestions would be
1) considering the journal, perhaps a richer argumentation of the sustainability implications of such an approach, expanding section 5.3, would be interesting to read
2) any suggestion of how such study could be complemented with inquiring directly with a sample of farmers the determinant of their decision, so can this empiric data-based approach be complemented by qualitative data on the socio-economic sphere?
Author Response
Thank you for providing insightful comments. We revised our manuscript based on the comments. Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
I recommend the manuscript without comments
Author Response
Thank you for providing insightful comments. We revised our manuscript based on the comments. Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 3 Report
This study represents an effort to estimate crop transition probabilities and forecast distributions of total acreage for five major crops in the state of Kentucky using the multinomial logit (MNL) model. But there remain some serious concerns I have about the methodology of and conclusions. The paper should only be reconsidered after substantial revision addressing the objections raised below.
Line 122 an introduction of MNL is necessary since it is a new model for reader.
Lines 163-164: Why do you want to identify changes in rotations at field level rather in each grid cells? When the land cover data was aggregated into field level, there will be aggregation error. For example there are missing data in CDL and it was assumed that same crop are
Lines 181-182: could authors provide reference to support your view.
Lines 181-186: I strongly question about the method used here. There are lots factors that farmers will take into consideration when they they are planning a crop rotation. It needs to weigh fixed and fluctuating production circumstances such as market, farm size, labor supply, climate, soil type, growing practices and so on. However authors only considered soil weather and elevation factors. Reader will concern the reliability of results.
Lines 187: I don’t think only soil textures is enough to represent soil quality. other important soil quality indicator such as Soil Organic Matter and soil nitrate need take into account.
Lines 299: please show figure or map to support the results, and show where model shows good or poor prediction, and why?
Lines 329 please show averaged observations in the figure too so that reader can know how well model prediction fit with observations.
Author Response
Thank you for providing insightful comments. We revised our manuscript based on the comments. Please see the attachment.
Author Response File: Author Response.pdf
