the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 17 Apr 2026
Climate-smart grassland use in dry steppes of Russia and Kazakhstan – Assessment of green-house-gas emission dynamics, agricultural potentials and trade-offs
Abstract. Livestock production systems face multiple challenges under climate change. Traditional systems have to be evaluated with respect to their production as well as their climate mitigation potentials in the future. We investigated grassland-based livestock production options in the dry steppe region in south-western Russia and northern Kazakhstan using the dynamic global vegetation model (DGVM) Lund-Potsdam-Jena-managed Land (LPJmL). The analysis explicitly includes feed-backs between grazing animals and feed quality and quantity and its effects on biogeochemical flows under different management assumptions varying the amount of applied fertilizer and livestock densities. By calculating environmental impacts for a selection of management combinations according to different objectives, we can assess livestock-related GHG emissions of methane, nitrous oxide, and carbon dioxide, as well as nitrogen pollution to the environment. Results show that environmental conditions, even within this relatively homogeneous arid steppe region, do not only affect production potentials but also trade-offs between maximizing productivity and minimizing environmental impacts per product. This leaves an option space of achieving comparatively high production under low environmental costs.
- Preprint
(2075 KB) - Metadata XML
- BibTeX
- EndNote
Status: open (until 13 Aug 2026)
- RC1: 'Comment on egusphere-2026-1529', Val Snow, 26 May 2026 reply
-
RC2: 'Comment on egusphere-2026-1529', Anonymous Referee #2, 30 Jul 2026
reply
Rolinski and others model livestock production systems in the dry steppe of Central Asia. There are some interesting results that create interesting potential recommendations, but I was left wondering at times what the major take away points of the analyses are. i.e., in the abstract, what is the 'option space of achieving
comparatively high production under low environmental costs’?The abstract could benefit from more numerical values; what was found?This seems to be an entirely modeling exercise. Are the findings constrained by any data?I was also a bit surprised by the lack of collaborators from local regions, although this could be confused by current institutional affiliations. This makes it unclear how these recommendations can potentially be used by practitioners.182: why was RCP 8.5 chosen? This has been roundly criticized as an unrealistic scenario and unfortunately has become a bit of a distraction in the scenario modeling literature. I can see its inclusion largely in the abstract for comparison.What are the representative uncertainties in the models in equation 1?2.5.3: nitrogen is complicated, were these or other fluxes validated and were modeled value like N application constrained by amounts used in practice?Why is 1970 explored in Fig. 2 and not a more contemporary period, especially when the large land use transition radically changed the landscape between then and now?What is the y axis definition and units for figure 6? Is this the number of objectives?Citation: https://doi.org/10.5194/egusphere-2026-1529-RC2
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 301 | 148 | 25 | 474 | 21 | 20 |
- HTML: 301
- PDF: 148
- XML: 25
- Total: 474
- BibTeX: 21
- EndNote: 20
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1
This is a relevant and interesting study of the potential issues with productivity, GHGs and N pollution in a major grassland area. I think the intent of the study is worthy and even topical. Unfortunately, the model and its assumptions were inadequately described, even fundamental concepts such as the calculation of CH4 emissions and the N partitioning in the animal. The authors did not show any vegetation production outputs let alone the metabolisable energy production and consumption that is a crucial intermediate point between the soil/vegetation and the livestock. This is particularly important as some rough calculations suggest unlikely production and I suspect that the imposed scenarios have constrained the pattern of outputs in unintended ways.
I understand that the authors are using a milking cow only as a means of transforming vegetation growth into production, GHGs and N excreta. They may be better of imposing simple equations partitioning harvested vegetation C and N into destinations and forgoing outputs that ‘look’ like animal production. Alternatively, a full explanation and sense checking of the animal component is essential.
Given this I was not able to fully assess the results and conclusions. The majority of my comments are attached as comments on the PDF.
I would be interested to assess a major revision but the authors would need to addressed the missing information on the model’s assumptions and show that that the model is making fundamental sense before jumping to outputs.
Please note that my manuscript rating evaluation (which was mandatory) is based on very incomplete information and does not include an assessment of the results/conclusions.