Global patterns of crop yield stability under additional nutrient and water inputs

Müller, C., Elliott, J., Pugh, T.A.M., Ruane, A.C., Ciais, P., Balkovic, J. ORCID: https://orcid.org/0000-0003-2955-4931, Deryng, D., Folberth, C. ORCID: https://orcid.org/0000-0002-6738-5238, Izaurralde, R.C., Jones, C.D., Khabarov, N. ORCID: https://orcid.org/0000-0001-5372-4668, Lawrence, P., Liu, W., Reddy, A.D., Schmid, E., & Wang, X. (2018). Global patterns of crop yield stability under additional nutrient and water inputs. PLoS ONE 13 (6) e0198748. 10.1371/journal.pone.0198748.

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Abstract

Agricultural production must increase to feed a growing and wealthier population, as well as to satisfy increasing demands for biomaterials and biomass-based energy. At the same time, deforestation and land-use change need to be minimized in order to preserve biodiversity and maintain carbon stores in vegetation and soils. Consequently, agricultural land use needs to be intensified in order to increase food production per unit area of land. Here we use simulations of AgMIP's Global Gridded Crop Model Intercomparison (GGCMI) phase 1 to assess implications of input-driven intensification (water, nutrients) on crop yield and yield stability, which is an important aspect in food security. We find region- and crop-specific responses for the simulated period 1980-2009 with broadly increasing yield variability under additional nitrogen inputs and stabilizing yields under additional water inputs (irrigation), reflecting current patterns of water and nutrient limitation. The different models of the GGCMI ensemble show similar response patterns, but model differences warrant further research on management assumptions, such as variety selection and soil management, and inputs as well as on model implementation of different soil and plant processes, such as on heat stress, and parameters. Higher variability in crop productivity under higher fertilizer input will require adequate buffer mechanisms in trade and distribution/storage networks to avoid food price volatility.

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