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Potential impacts of climate change on agriculture and fisheries production in 72 tropical coastal communities
2022, Cinner, Joshua E, Caldwell, Iain R, Thiault, Lauric, Ben, John, Blanchard, Julia L, Coll, Marta, Diedrich, Amy, Eddy, Tyler D, Everett, Jason D, Folberth, Christian, Gascuel, Didier, Guiet, Jerome, Gurney, Georgina G, Heneghan, Ryan F, Jägermeyr, Jonas, Jiddawi, Narriman, Lahari, Rachael, Kuange, John, Liu, Wenfeng, Maury, Olivier, Müller, Christoph, Novaglio, Camilla, Palacios-Abrantes, Juliano, Petrik, Colleen M, Rabearisoa, Ando, Tittensor, Derek P, Wamukota, Andrew, Pollnac, Richard
Climate change is expected to profoundly affect key food production sectors, including fisheries and agriculture. However, the potential impacts of climate change on these sectors are rarely considered jointly, especially below national scales, which can mask substantial variability in how communities will be affected. Here, we combine socioeconomic surveys of 3,008 households and intersectoral multi-model simulation outputs to conduct a sub-national analysis of the potential impacts of climate change on fisheries and agriculture in 72 coastal communities across five Indo-Pacific countries (Indonesia, Madagascar, Papua New Guinea, Philippines, and Tanzania). Our study reveals three key findings: First, overall potential losses to fisheries are higher than potential losses to agriculture. Second, while most locations (> 2/3) will experience potential losses to both fisheries and agriculture simultaneously, climate change mitigation could reduce the proportion of places facing that double burden. Third, potential impacts are more likely in communities with lower socioeconomic status.
Exploring uncertainties in global crop yield projections in a large ensemble of crop models and CMIP5 and CMIP6 climate scenarios
2021, Mueller, Christoph, Franke, James, Jaegermeyr, Jonas, Ruane, Alex C., Elliott, Joshua, Moyer, Elisabeth, Heinke, Jens, Falloon, Pete D., Folberth, Christian, Francois, Louis
Concerns over climate change are motivated in large part because of their impact on human society. Assessing the effect of that uncertainty on specific potential impacts is demanding, since it requires a systematic survey over both climate and impacts models. We provide a comprehensive evaluation of uncertainty in projected crop yields for maize, spring and winter wheat, rice, and soybean, using a suite of nine crop models and up to 45 CMIP5 and 34 CMIP6 climate projections for three different forcing scenarios. To make this task computationally tractable, we use a new set of statistical crop model emulators. We find that climate and crop models contribute about equally to overall uncertainty. While the ranges of yield uncertainties under CMIP5 and CMIP6 projections are similar, median impact in aggregate total caloric production is typically more negative for the CMIP6 projections (+1% to −19%) than for CMIP5 (+5% to −13%). In the first half of the 21st century and for individual crops is the spread across crop models typically wider than that across climate models, but we find distinct differences between crops: globally, wheat and maize uncertainties are dominated by the crop models, but soybean and rice are more sensitive to the climate projections. Climate models with very similar global mean warming can lead to very different aggregate impacts so that climate model uncertainties remain a significant contributor to agricultural impacts uncertainty. These results show the utility of large-ensemble methods that allow comprehensively evaluating factors affecting crop yields or other impacts under climate change. The crop model ensemble used here is unbalanced and pulls the assumption that all projections are equally plausible into question. Better methods for consistent model testing, also at the level of individual processes, will have to be developed and applied by the crop modeling community.