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气候异常对油棕生产力的非线性影响。

Nonlinear impacts of climate anomalies on oil palm productivity.

作者信息

Kamil Nur Nadia, Xiao Saizi, Syed Salleh Sharifah Nabilah, Xu Hongbing, Zhuang Castiel Chen

机构信息

Economics and Industry Development Division, Malaysian Palm Oil Board, Selangor, Malaysia.

School of Economics, University of Nottingham Malaysia, Selangor, Malaysia.

出版信息

Heliyon. 2024 Aug 6;10(15):e35798. doi: 10.1016/j.heliyon.2024.e35798. eCollection 2024 Aug 15.

Abstract

Oil palm contributes to various global needs as one of the most productive oil crops, but there exist ongoing concerns regarding its yield reductions and associated environmental impacts resulting from land conversion. This is the first detailed report investigating the nonlinear threats to estate-level oil palm yields posed by El Niño Southern Oscillation (ENSO) in the equatorial Pacific Ocean, a major driver of climate variability. Using the Malaysian Palm Oil Board administrative records on monthly performances reported by oil palm estates through the e-submissions portal spanning from January 2015 to June 2023, we focused on elucidating the impacts of ENSO on fresh fruit bunch yield, oil extraction rate, and oil yield. We found that both El Niño and La Niña conditions, characterized by extreme levels of ENSO indices cumulated over lags of 0-23 months prior to harvest, were associated with statistically significant reductions in yields. Lag association patterns unveiled that production risks were linked to pre-harvest exposure to extreme ENSO indices in various time windows. Subgroup analyses further revealed that the effects were pronounced in labor-intensive estates and those lacking fertilizer investments. This study underscores the necessity for adaptation strategies in response to future climate anomalies.

摘要

油棕作为最高产的油料作物之一,满足了全球的多种需求,但人们一直担心其因土地转换导致的产量下降及相关环境影响。这是第一份详细报告,研究了赤道太平洋厄尔尼诺-南方涛动(ENSO)对种植园层面油棕产量构成的非线性威胁,ENSO是气候变率的一个主要驱动因素。利用马来西亚棕榈油委员会的行政记录,这些记录来自2015年1月至2023年6月通过电子提交门户报告的油棕种植园月度生产数据,我们着重阐明ENSO对鲜果串产量、出油率和产油量的影响。我们发现,厄尔尼诺和拉尼娜现象,其特征是收获前0 - 23个月累积的ENSO指数处于极端水平,均与产量的统计学显著下降有关。滞后关联模式表明,生产风险与收获前不同时间窗口内暴露于极端ENSO指数有关。亚组分析进一步显示,这些影响在劳动密集型种植园和缺乏肥料投入的种植园中更为明显。本研究强调了应对未来气候异常的适应策略的必要性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/802e/11337023/8addb861a51e/gr1.jpg

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