The Influence of Environmental Heterogeneity on Fertilization-Driven Patterns of Distribution and Yield in Medicinal Plants

  • Peiyao Yang
  • , Ruixue Wang
  • , Jie Liu
  • , Xu Xu
  • , Qingfeng Xu
  • , Shanshan Liu
  • , Menghui Dong
  • , Qirong Shen
  • , Zongzhuan Shen
  • , Rong Li*
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Medicinal plant production is essential for global health, yet how temperature, precipitation, and soil properties influence yield responses to fertilization remains poorly understood. Here, we conducted a meta-analysis of 668 observations from 79 studies, focusing on a wide range of plant species, to evaluate how nutrient inputs and environmental factors interact to shape medicinal plant productivity. We found that latitude, MAT, and MAP jointly determine global medicinal plant yield patterns. Yield increased with latitude and MAT but declined under prolonged fertilization and higher MAP. Optimal cultivation regions were identified between 15° and 35° absolute latitude, where temperature and precipitation conditions were most favorable. Compared with the arid environment of desertic climates, other regions, especially those with higher MAP in tropical areas, show a higher increase in yield. Our findings highlight that shifting precipitation-temperature regimes under climate change will affect fertilization outcomes on medicinal plant yield, emphasizing the need for spatiotemporally adaptive nutrient management strategies to ensure the sustainable yield of medicinal plants.

Original languageEnglish
Article number2142
Number of pages13
JournalAgronomy
Volume15
Issue number9
DOIs
Publication statusPublished - Sept 2025

Bibliographical note

Publisher Copyright:
© 2025 by the authors.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • deep learning model
  • global scale
  • MaxEnt model
  • mean annual precipitation
  • meta-analysis

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