ナイジェリア・オスン州におけるカカオ生産への気候変動の経済的影響評価
Assessing the Economic Impact of Climate Change on Cocoa Production in Osun State, Nigeria (原題)
Femi S. Omotayo, Funke Florence Akinola, M. O. Lasisi
🤖 gxceed AI 要約
日本語
ナイジェリア・オスン州のカカオ生産を対象に、6つのGCMダウンスケーリング出力とRCP4.5シナリオを用いて気候変動の経済影響を推計した研究。重回帰分析で気候変動数と収量の関係を特定し、2050年までに年約13,700トン、2100年までに年約20,000トンの収量減を予測する。想定価格1トン4,450ドルでは年間損失は2050年約6,100万ドル、2100年約8,900万ドルに達する。適応策と病害防除資材の供給を提言する。
English
Uses six downscaled GCM outputs under RCP 4.5 and multiple linear regression to project climate impacts on cocoa yields in Osun State, Nigeria. Ensemble projections show annual yield losses of ~13,696 t by 2050 and ~20,004 t by 2100, valued at ~US$61M and ~US$89M at US$4,450/t. Recommends farmer adaptation and input supply for black pod control.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
日本企業のGX文脈では、食品・商社のカカオ調達サプライチェーンにおける気候リスク評価の一事例として参照価値がある。Scope 3上流の農業由来リスクを定量化する手法の参考になる。
In the global GX context
Adds to the growing body of physical climate-risk quantification for agricultural supply chains, relevant to Scope 3 upstream risk and adaptation finance discussions under TCFD/ISSB. The crop-model-plus-valuation approach is transferable to other commodity exposure assessments.
👥 読者別の含意
🔬研究者:GCMアンサンブルと収量回帰を組み合わせた農業気候影響の経済評価手法の実例として参考になる。
🏢実務担当者:カカオ等農産物調達を持つ企業が上流気候リスクを定量化する際の手法・規模感の参考になる。
🏛政策担当者:農業適応政策・病害防除支援の投資根拠として損失推計を活用できる。
📄 Abstract（原文）
Nigeria ranked among the world's four leading cocoa producers in 2021, with estimated output of between 250,000 and 300,000 metric tonnes, which contributed significantly to the country's non-oil export earnings. The southern states of Ondo, Cross River, Osun, Ekiti, Edo and Oyo are the main production areas. However, the sector has faced challenges such as low productivity, ageing trees and declining yields relative to those of regional peers. Among the effects of climate change experienced by Nigerian cocoa farmers are irregular rainfall, prolonged dry periods and greater pest and disease pressure on cocoa trees. These pressures have contributed to lower yields and deterioration in bean quality. Multiple linear regression was employed to identify climatic variables showing significant associations with cocoa yield. To investigate climate-related changes in cocoa production in the study area, downscaled outputs from six global circulation models (GCMs) were used. Climate and crop-yield simulations covered three periods: 1976–2005 (historical), 2021–2050 (mid-term) and 2071–2100 (long-term), under the RCP 4.5 emissions scenario. Fig. 5 illustrates the projected future changes in cocoa yield under RCP 4.5. For the study area, the GCM ensemble indicated annual yield reductions of 13,696 tonnes/year by 2050 and 20,004 tonnes/year by 2100. If these ensemble projections materialise, the resulting losses are estimated at approximately US$60,947,200 in 2050 and US$89,017,800 in 2100, respectively, on the assumption of a cocoa price of US$4,450 per tonne. Farmers should implement effective adaptation measures to limit the effects of future climate change on cocoa yield, with necessary inputs, including fungicides and pesticides, supplied to control cocoa black pod disease.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.9734/jaeri/2026/v27i6826first seen 2026-11-02 04:40:29 · last seen 2026-11-06 04:36:39
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