Spatiotemporal interaction of tef head smudge disease (Curvularia spp.) and tef (Eragrostis tef) in the Western Amhara Region, Ethiopia, under the moderate (SSP245) and extreme (SSP285) climate change scenarios
エチオピア西部アムハラ地域におけるテフ穂かび病（Curvularia spp.）とテフ（Eragrostis tef）の緩和（SSP245）および極端（SSP285）気候変動シナリオ下での時空間相互作用 (AI 翻訳)
Melkamu Birhanie Mekonnen, Girmaye Dires Abeje, Mequannent Andualem Mekonnen
🤖 gxceed AI 要約
日本語
本研究は、エチオピア西部アムハラ地域におけるテフ穂かび病とテフの分布を、現在と将来（2050年、2070年）の気候変動シナリオ（SSP245、SSP285）下でMaxEntモデルを用いて予測した。結果、テフの生育域はシナリオに応じて変動し、病気との重複域も変化することが示された。気候変動が作物生産と病害リスクに複合的な影響を与えることを示唆している。
English
This study models the spatiotemporal dynamics of tef head smudge disease and tef in the Western Amhara Region, Ethiopia, under current and future climate scenarios (SSP245, SSP285) using MaxEnt. Results show shifts in tef suitability and disease distribution, with overlapping areas changing over time. The findings highlight compounded challenges of climate change on food security.
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
本論文はエチオピアを対象としており、日本への直接的な示唆は限定的だが、気候変動が農業病害に与える影響の解析手法は、日本の農業適応策にも応用可能である。
In the global GX context
While focused on Ethiopia, this paper demonstrates a modeling approach for climate-driven disease risk that is globally relevant for agricultural adaptation planning.
👥 読者別の含意
🔬研究者:Provides a case study of MaxEnt modeling for crop-disease interactions under climate scenarios, useful for similar analyses in other regions.
🏛政策担当者:Highlights the need for integrated climate adaptation strategies that consider both crop suitability and disease pressure.
📄 Abstract（原文）
Tef is an important food security orphan crop in the Western Amhara Region, Ethiopia. However, its production is constrained by tef head smudge disease caused by Curvularia spp. Therefore, this study aims to model the spatiotemporal dynamics of tef head smudge disease and tef, as well as their spatiotemporal interaction. Therefore, this study conducted a comprehensive analysis of the current and projected geographic distribution of tef head smudge disease and tef by 2050 and 2070 under SSP245and SSP285 climate change scenarios using the MaxEnt model. The model has achieved 89.3% - 90.5% accuracy for tef and over 93% accuracy for tef head smudge disease across the current and future climate change scenarios. Tef is predicted to cover 33% of the Western Amhara region under the current climate scenario. However, its projections indicate shifts to 23.1% under SSP245 and 40.6% under SSP285 by 2050. By 2070, tef is projected to cover around 33.7% and 19.97% of the region under SSP245 and SSP285, respectively. Tef head smudge disease is predicted to occur on about 10,951 ha of land under the current climate change scenario. However, its distribution is predicted to be 6,361 ha and 18,812 ha by 2050 under SSP245 and 285, respectively. However, tef head smudge disease and tef are predicted to overlap on 9,659 ha of land under the current climate change scenario. This overlap is expected to increase to around 15,846 hectares (SSP285) by 2050, but decrease to 3,334 hectares (SSP285) by 2070. This study highlights the compounded challenges of climate change and disease pressure on tef production. Therefore, this research provides critical insights for policymakers and researchers to enhance resilience in tef cultivation and safeguard food security in the face of climate change.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.1371/journal.pone.0343054first seen 2026-05-05 19:14:06
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