The impact of climate change and climate extremes on sugarcane production

被引:21
|
作者
Flack-Prain, Sophie [1 ]
Shi, Liangsheng [2 ]
Zhu, Penghui [1 ,2 ]
da Rocha, Humberto R. [3 ]
Cabral, Osvaldo [4 ]
Hu, Shun [2 ]
Williams, Mathew [1 ,5 ]
机构
[1] Univ Edinburgh, Sch GeoSci, Edinburgh, Midlothian, Scotland
[2] Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan, Peoples R China
[3] Univ Sao Paulo, Inst Astron Geofis & Ciencias Atmosfer, Lab Clima & Biosfera, Sao Paulo, Brazil
[4] EMBRAPA Meio Ambiente, Jaguariuna, Brazil
[5] Univ Edinburgh, Natl Ctr Earth Observat, Edinburgh, Midlothian, Scotland
来源
GLOBAL CHANGE BIOLOGY BIOENERGY | 2021年 / 13卷 / 03期
基金
英国生物技术与生命科学研究理事会; 巴西圣保罗研究基金会; 英国自然环境研究理事会;
关键词
C-4; plant; climate sensitivity; crops; model; sugarcane; yield; WATER-USE; MODEL; YIELD; CO2; CROP; SIMULATION; FOREST; PHOTOSYNTHESIS; NITROGEN; DROUGHT;
D O I
10.1111/gcbb.12797
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
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 Sao 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 Sao Paulo, median yield and yield lows decreased under all future climates projections (x over bar = -4% and -12% respectively). At Guangxi, where moisture stress was low, radiation was the principal driver of yield variability (yield-effect x over bar = -1.2%). Conversely, high moisture stress at Sao Paulo raised yield sensitivity to temperature (yield-effect x over bar = -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.
引用
收藏
页码:408 / 424
页数:17
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