Enhancing Agricultural Research and Precision Management for Subsistence Farming by Integrating System Models with Experiments - Группа авторов

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to drought and high temperatures. Climate change is expected to result in an increasing frequency of drought and high temperatures in this region. Because of the pressure of increasing population and intensification of agricultural activities, there is a concern of increased soil degradation and decreasing production. Chapter 8 (Jaradat & Timlin, 2022) shows how simulation models and statistical modeling are used to identify the effects of climate change on yield gaps in this area. Under the three climate change scenarios used in the study, Jaradat and Timlin (2022) found annualized crop rotation and rainfed yields were expected to decrease by 34 and 65%, respectively, compared with current conditions. In spite of using crop rotations, soil carbon is also expected to decrease due to limited rainfall and increasing temperatures. This underscores the need to develop new cropping rotations that conserve soil carbon.

      Jaradat and Timlin (2022) also look at yield gaps, which is the difference between best potential yield for the area and actual yields measured on farms. They find that three‐way relationships between potential yield (Yp), and yield gaps (Yg) under RCP4.5 and RCP8.5 for the major crops separated the seven countries of the FC into three groups: Jordan and Iraq are expected to sustain the largest yield gaps; Turkey, Lebanon and Iran, the lowest; and Syria and Israel intermediate yield gaps. They conclude that closing these yield gaps demands immediate local adaptive research and will inevitably involve the adoption of management practices and inputs that have been developed and used elsewhere in the world during the 1900s.

      The simulation studies in this book cover a wide variety of applications. They range from assessment of fertilizer and planting date on wheat and maize yields to studies of climate change impacts on surface and subsurface water resources and erosion. Models are applied to provide insight into geospatial distributions of crop response to different environmental and management variables. We also saw examples of socio‐economic analysis tied with model results. Many of the studies investigate the effects of climate change on crop yields using estimated climate data generated by climate change models (Representative Concentration Pathways RCP2.6, RCP4.5, and RCP8.5; and CMIP5 [Coupled Model Intercomparison Project, https://www.wcrp‐climate.org/wgcm‐cmip/wgcm‐cmip5]). The effects on subsistence and low‐input agriculture are expected to be severe due to lack of research on alternative management practices and limited resources for farmers. However, most studies show that increased diversification through crop rotations and use of alternative crops can decrease the variability caused by climate change and result in decreased impact of heat and water stress.

      1 Ali, S., Islam, A., & Ojasvi, P. R. (2022). Modeling water dynamics for assessing and managing ecosystem services in India. In D. Timlin (Ed.), Enhancing agricultural research and precision management for subsistence farming by integrating system models with experiments (pp. 69–103). ASA, CSSA, and SSSA. DOI

      2 Araya, A., Prasad, P. V. V., Ciampitti, I. A., Rice, C. W., & Gowda, P. H. (2022). Using crop simulation models as tools to quantify effects of crop management practices and climate change scenarios on wheat yields in northern Ethiopia. In D. Timlin (Ed.), Enhancing agricultural research and precision management for subsistence farming by integrating system models with experiments (pp. 29–47). ASA, CSSA, and SSSA. DOI

      3 Beah, A., Kamara, A. Y., Jibrin, J. M., Akinseye, F. M., Tofa, A. I., & Adam, A. M. (2021). Simulating the response of drought–tolerant maize varieties to nitrogen application in contrasting environments in the Nigeria Savannas using the APSIM model. Agronomy, 11, 76. https://doi.org/10.3390/agronomy11010076

      4  Birnholz, C., Paul, B., Sommer, R., & Nijbroek, R. (2022). Modeling soil erosion impacts and trade‐offs of sustainable land management practices in the Upper Tana Region of the Central Highlands in Kenya. In D. Timlin (Ed.), Enhancing agricultural research and precision management for subsistence farming by integrating system models with experiments (pp. 6–28). ASA, CSSA, and SSSA. doi 10.1002/9780891183891

      5 Falconnier, G. N., Corbeels, M., Boote, K. J., Affholder, F., Adam, M., MacCarthy, D. S., Ruane, A. C., Nendel, C., Whitbread, A. M., Justes, É., Ahuja, L. R., Akinseye, F. M., Alou, I. N., Amouzou, K. A., Anapalli, S. S., Baron, C., Basso, B., Baudron, F., Bertuzzi, P., … Webber, H. (2020). Modelling climate change impacts on maize yields under low nitrogen input conditions in sub‐Saharan Africa. Global Change Biology, 26, 5942–5964. https://doi.org/10.1111/gcb.15261

      6 Gao, X., Huo, Z., Qu, Z., & Tang, P. (2022). Modeling agricultural hydrology and water productivity to enhance water management in the Arid Irrigation District of China. In D. Timlin (Ed.), Enhancing agricultural research and precision management for subsistence farming by integrating system models with experiments (pp. 104–133). ASA, CSSA, and SSSA. doi 10.1002/9780891183891

      7 Jaradat, A. A., & Timlin, D. (2022). Constraints to productivity of subsistence dryland agroecosystems in the Fertile Crescent: Simulation and statistical modeling. In D. Timlin (Ed.), Enhancing agricultural research and precision management for subsistence farming by integrating system models with experiments (pp. 155–189). ASA, CSSA, and SSSA. doi 10.1002/9780891183891

      8 Ko, J., Jeong, S., Kim, H.‐Y., & Lee, B. (2022). Use of data and models in simulating regional and geospatial variations in climate change impacts on rice and barley in the Republic of Korea. In D. Timlin (Ed.), Enhancing agricultural research and precision management for subsistence farming by integrating system models with experiments (pp. 134–154). ASA, CSSA, and SSSA. doi 10.1002/9780891183891

      9 MacCarthy, D. S., Adiku, S. G. K., Kamara, A. Y., Freduah, B. S., & Kugbe, J. (2022). The role of crop simulation modeling in managing fertilizer use in maize production systems in northern Ghana. In D. Timlin (Ed.), Enhancing agricultural research and precision management for subsistence farming by integrating system models with experiments (pp. 48–68). ASA, CSSA, and SSSA. doi 10.1002/9780891183891

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