Potential impact of climate and socioeconomic changes on future agricultural land use in West Africa

Ahmed, Kazi Farzan; Wang, Guiling; You, Liangzhi; Yu, Miao

doi:https://doi.org/10.5194/esd-7-151-2016

Articles | Volume 7, issue 1

https://doi.org/10.5194/esd-7-151-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue:

Climate, land use, and conflict in Africa

https://doi.org/10.5194/esd-7-151-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 7, issue 1

Research article

|

23 Feb 2016

Research article |

| 23 Feb 2016

Potential impact of climate and socioeconomic changes on future agricultural land use in West Africa

Kazi Farzan Ahmed, Guiling Wang, Liangzhi You, and Miao Yu

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Final revised paper (published on 23 Feb 2016)
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Preprint (discussion started on 16 Jul 2015)
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Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC C548: 'Review', Anonymous Referee #1, 14 Sep 2015
- AC C614: 'Response to the comments from Referee no. 1', Kazi Ahmed, 01 Oct 2015
RC C715: 'Review', Anonymous Referee #2, 20 Oct 2015
- AC C760: 'Response to the comments from referee no. 2', Kazi Ahmed, 09 Nov 2015

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Kazi Ahmed on behalf of the Authors (09 Nov 2015) Author's response Manuscript

ED: Referee Nomination & Report Request started (12 Nov 2015) by Martin Claussen

RR by Anonymous Referee #3 (01 Dec 2015)

Suggestions for revision or reasons for rejection

The manuscript provides a simple algorithm for diagnosing changes in cropland area under different socioeconomic and climate scenarios. The aim of the manuscript is important, particularly the separation of changes attributable to changes in climate and those attributable to socioeconomic changes. However, the study doesn’t provide sufficient information to assess the reliability of the results. I have two main concerns with the analysis.

Major concerns:
1. Not enough detail is provided on the performance of the DSSAT model as compared to FAO data. The process of calibration is clear, but the outcome is not. For example, a figure similar to figure S2 in Ahmed et al., 2015 showing the FAO yield data and DSSAT calibrated data for major crops in strategic countries would be immensely helpful to readers when evaluating the reliability of the model yield results.

2. The authors need to justify points 1 and 2 in the decision-making algorithm, or perform sensitivity analyses similar to those used in points 3 and 4. I appreciate that a number of sensitivity analyses have already been performed, but without a strong justification or understanding of the sensitivity of the model to this assumption, it’s not clear how much confidence we can place in the results. Particularly because this is the first step in the algorithm, and therefore affects all downstream results. The authors cite Burney et al. (2010) and Hurtt et al. (2011) when indicating that cropland conversion happens at the expense of forested area, but Hurtt et al. (2011) conduct a sensitivity analysis on choice of primary or secondary land converted, and Burney et al. (2010) assume that future cropland conversion will occur in proportion to past cropland conversion (not solely at the expense of forests, but instead following Ramankutty and Foley 1999). Both citations indicate a decline in forested area, but do not indicate that cropland expansion occurs solely in forested areas.

Specific points
- Why were MIROC and CESM chosen from the CMIP 5 archive? How do they compare to other CMIP 5 models in simulating the climate of West Africa over the observational record

-What is driving the differences in Hurt et al. (2011) and LandPro-SE? This is an important point to discuss since readers need to know the benefits and limitations of each product when weighing the plausibility of each potential outcome.

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RR by Anonymous Referee #1 (13 Dec 2015)

Suggestions for revision or reasons for rejection

The authors develop an algorithm in order to downscale country-resolved projections of crop production from equilibrium models to a 0.5° pixel resolution. Thus, the objective is to increase the resolution of land use projections. While I can see many potential benefits of high resolution land use projections, I think there is a fundamental flaw in the design of the approach.

Different approaches and assumptions are used to analyze future land use. Particularly, positive assessments describe the most likely land use development. In contrast, normative assessments determine possible/potential land use developments. Both types of assessments are useful. However, they may produce very different results. If the assessment framework includes different steps, it is important to use consistent methods throughout the analysis. It does not make sense to solve a calibrated equilibrium model (positive approach) with a coarse resolution in step 1 and then downscale the results of this model with normative assumptions. The authors do not explain the consistency of assumptions between the two levels. This is a fundamental deficiency of the approach. The authors argue that the technical objective of their algorithm is to compute high resolution land use projections. However, I think the objective should be to get consistent and reliable high resolution land use projections.

The authors also claim "to account for (the) uncertainties" of the behavioral rules through a scenario analysis. This is at best superficial. I don’t think that the approach adequately addresses uncertainty by selectively choosing a few alternative behavioral assumptions out of infinite possibilities. It is a limited sensitivity analysis and nothing more.

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RR by Anonymous Referee #2 (14 Dec 2015)

ED: Reconsider after major revisions (16 Dec 2015) by Martin Claussen

AR by Kazi Ahmed on behalf of the Authors (22 Jan 2016) Author's response Manuscript

ED: Referee Nomination & Report Request started (25 Jan 2016) by Martin Claussen

RR by Anonymous Referee #3 (01 Feb 2016)

ED: Publish as is (03 Feb 2016) by Martin Claussen

AR by Kazi Ahmed on behalf of the Authors (09 Feb 2016)

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Short summary

A prototype model LandPro was developed to study climate change impact on land use in West Africa. LandPro considers climate and socioeconomic factors in projecting anthropogenic future land use change (LULCC). The model projections reflect that relative impact of climate change on LULCC in West Africa is region dependent. Results from scenario analysis suggest that science-informed decision-making by the farmers in agricultural land use can potentially reduce crop area expansion in the region.