Meteorological Impacts on Rubber Tree Powdery Mildew and Projections of Its Future Spatiotemporal Pattern

Jiayan Kong, Lan Wu, Jiaxin Cao, Wei Cui, Tangzhe Nie, Yinghe An and Zhongyi Sun ()
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Jiayan Kong: Ecology and Environment College, Hainan University, Haikou 570208, China
Lan Wu: Ecology and Environment College, Hainan University, Haikou 570208, China
Jiaxin Cao: Ecology and Environment College, Hainan University, Haikou 570208, China
Wei Cui: Development Research Center, National Forestry and Grassland Administration, Beijing 100714, China
Tangzhe Nie: Key Laboratory of Effective Utilization of Agricultural Water Resources, Ministry of Agriculture and Rural Affairs, Northeast Agricultural University, Harbin 150030, China
Yinghe An: Ecology and Environment College, Hainan University, Haikou 570208, China
Zhongyi Sun: Ecology and Environment College, Hainan University, Haikou 570208, China

Agriculture, 2024, vol. 14, issue 4, 1-16

Abstract: Meteorological conditions play a crucial role in driving outbreaks of rubber tree powdery mildew (RTPM). As the climate warms and techniques improve, rubber cultivation is expanding to higher latitudes, and the changing climate increases the RTPM risk. Rubber plantations on Hainan Island, situated on the northern margin of the tropics, have been selected as a case study to explore the meteorological mechanisms behind RTPM outbreaks quantitatively using a structural equation model, and project current and future RTPM outbreak patterns under different climate change scenarios by building predictive models based on data-driven algorithms. The following results were obtained: (1) days with an average temperature above 20 °C and days with light rain were identified as key meteorological drivers of RTPM using structural equation modeling (R 2 = 0.63); (2) the Bayesian-optimized least-squares boosted trees ensemble model accurately predicted the interannual variability in the historical RTPM disease index (R 2 = 0.79); (3) currently, due to the increased area of rubber plantations in the central region of Hainan, there is a higher risk of RTPM; and (4) under future climate scenarios, RTPM shows a decreasing trend (at a moderate level), with oscillating and sporadic outbreaks primarily observed in the central and northwest regions. We attribute this to the projected warming and drying trends that are unfavorable for RTPM. Our study is expected to enhance the understanding of the impact of climate change on RTPM, provide a prediction tool, and underscore the significance of the climate-aware production and management of rubber.

Keywords: structural equation model; Bayesian-optimized least-squares boosted trees ensemble; climate change; Hainan Island (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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