The impact of climate change and climate extremes on sugarcane production

Abstract

Sugarcane production supports the livelihoods of millions of small‐scale farmers in developing countries, and the bioenergy needs of millions of consumers. Yet, future sugarcane yields remain uncertain due to differences in climate projections, and because the sensitivity of sugarcane ecophysiology to individual climate drivers (i.e. temperature, precipitation, shortwave radiation, VPD and CO2) and their interactions is largely unresolved. Here we ask: how sensitive is sugarcane yield to future climate change, including climate extremes, and what are its key climate drivers? We combine the Soil‐Plant‐Atmosphere model with detailed time‐series measurements from experimental plots in Guangxi, China, and São Paulo State, Brazil. We first calibrated and validated modelled carbon and water cycling against field flux and biometric data. Second, we simulated sugarcane growth under the historical climate (1980–2018), and six future climate projections (2015–2100). We computed the ‘yield‐effect’ of each climate driver by generating synthetic climate forcings in which the driver time series was alternated to that of the historical median. In Guangxi, median yield and yield lows (i.e. lower decile) were relatively insensitive to forecast climate change. In São Paulo, median yield and yield lows decreased under all future climates projections (truex¯ = −4% and −12% respectively). At Guangxi, where moisture stress was low, radiation was the principal driver of yield variability (yield‐effect truex¯ = −1.2%). Conversely, high moisture stress at São Paulo raised yield sensitivity to temperature (yield‐effect truex¯ = −7.9%). In contrast, a number of other modelling studies report a positive effect of increased temperatures on sugarcane yield. We ascribe the disparity between model predictions to the representation of key phenological processes, including the link between leaf ageing and thermal time, and the role of ageing in driving leaf senescence. We highlight climate sensitivity of phenological processes as a key focus for future research efforts.

Improving the representation of sugarcane crop in the Joint UK Land Environment Simulator (JULES) model for climate impact assessment

“…Nevertheless, we found that if temperatures above 35°C become more frequent in the future, a decline in net carbon uptake is expected to affect sugarcane yields if the crop does not adapt (Figures 3a and 9). This agrees with the recent findings of Flack‐Prain et al (2021), where temperature is the main driver for sugarcane yield decline in future projections for São Paulo, Brazil. In their study, the Soil–Plant–Atmosphere model was employed which simulates photosynthesis at sub‐daily timestep.…”

Heat stress in sugarcane: physiological changes and gene expression

“…In addition to inducing quantitative and qualitative losses in production, excessive heat shortens the crop cycle's duration, reducing the leaf area accelerating metabolism, consequently causing early plant senescence. Photosynthesis is one of the physiological processes most sensitive to heat (Demirevska-Kepova et al, 2005;Flack-Prain et al, 2021) due to the sensitivity of the thylakoid membrane, the structure where chloroplasts are contained, damage caused by excess heat causes a reduction in chlorophyll production (Ristic et al, 2007;Sharma et al, 2022).…”

Genome-wide characterization of cys-tathionine-β-synthase domain-containing proteins in sugarcane reveals their role in defense responses under multiple stressors

“…Abiotic stresses such as drought, salinity, extreme temperature, and low soil fertility also affect sugarcane growth and yield worldwide ( Lakshmanan and Robinson, 2014 ; Budeguer et al, 2021 ). Drought is the most important abiotic factor and can reduce sugarcane yield by up to 50–60% ( Ferreira et al, 2017 ; Flack-Prain et al, 2021 ). Generally, plants or organs responding to water stress exhibit physiological and metabolic changes to minimize water loss under moderate-to-severe short-term stress ( Lakshmanan and Robinson, 2014 ; Ferreira et al, 2017 ).…”