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Extreme Event Monitoring, Impact Assessment, Risk Early Warning on Ecosystem...
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Extreme Event Monitoring, Impact Assessment, Risk Early Warning on Ecosystem and Plants

A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Response to Abiotic Stress and Climate Change".

Deadline for manuscript submissions: closed (10 October 2023) | Viewed by 1676

Special Issue Editors

Dr. Tianjie Lei

E-Mail Website
Guest Editor
China Institute of Water Resources and Hydropower Research, Beijing, China
Interests: drought; flood; agrometeorological disasters; grassland; ecosystems
Prof. Dr. Changliang Shao

E-Mail Website
Guest Editor
Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China
Interests: ecosystem carbon/water/energy fluxes; grassland restoration
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Zhitao Wu

E-Mail Website
Guest Editor
Institute of Loess Plateau, Shanxi University, Taiyuan, China
Interests: drought; heat wave; carbon cycle; forest ecosystem; grassland ecosystem; remote sensing; dynamic global vegetation model; machine learning

Special Issue Information

Dear Colleagues,

This Special Issue aims to gather high-quality, original research articles, reviews, and technical notes on extreme event monitoring, impact assessment, and risk early warning on ecosystems and plants, with a particular emphasis on extreme events' effect on plants. Extreme events such as droughts, heatwaves, extreme precipitations, snowstorms, and so on have profoundly affected ecosystems, plants and even human lives over the past few decades. The extreme events’ frequency, intensity and duration are increasingly attributed to changes in global temperatures during the 21st century. Nonetheless, there are still many challenges in extreme event monitoring, impact assessment, and risk early warning on ecosystems and plants. We encourage a variety of approaches by combining field experiments, transect surveys, modeling and remote sensing to assess the characteristics and processes of extreme events.

Potential topics include, but are not limited to the following:

  • Effects of extreme events on plants
  • Biophysiochemical effects of extreme events
  • Short-term and long-term effects of extreme events
  • Extreme events effects of carbon, water, energy cycles and plant health
  • Statistics and climatology of extreme events, including droughts, floods, wet and dry spells, as well as heatwaves, cold spells and plant response
  • Variability of precipitation, temperature and the occurrence of extremes at different temporal and spatial scales
  • Diagnose and predict extreme events using remote sensing data
  • Early warning systems and climate-driven risk management
  • Risks early warning, uncertainties, and impacts: assessment, mitigation, and adaptation strategies

Dr. Tianjie Lei
Prof. Dr. Changliang Shao
Prof. Dr. Zhitao Wu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Plants is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  •  extreme climatic events
  •  biotic stress
  •  abiotic stress
  •  mass and energy fluxes
  •  biodiversity
  •  model prediction
  •  remote sensing
  •  machine learning

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Published Papers (1 paper)

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Research

17 pages, 4513 KiB  
Article
Monitoring and Mapping Winter Wheat Spring Frost Damage with MODIS Data and Statistical Data
by Di Chen, Buchun Liu, Tianjie Lei, Xiaojuan Yang, Yuan Liu, Wei Bai, Rui Han, Huiqing Bai and Naijie Chang
Plants 2023, 12(23), 3954; https://doi.org/10.3390/plants12233954 - 24 Nov 2023
Cited by 2 | Viewed by 1233
Abstract
Spring frost is an extreme temperature event that poses a significant threat to winter wheat production and consequently jeopardizes food security. In the context of climate change, the accelerated phenology of winter wheat due to global warming advances the frost-sensitive stage, thereby escalating [...] Read more.
Spring frost is an extreme temperature event that poses a significant threat to winter wheat production and consequently jeopardizes food security. In the context of climate change, the accelerated phenology of winter wheat due to global warming advances the frost-sensitive stage, thereby escalating the risk of spring frost damage. Present techniques for monitoring and assessing frost damage heavily rely on meteorological data, controlled field experiments and crop model simulations, which cannot accurately depict the actual disaster situation for winter wheat. In this study, we propose a novel method that utilizes remote sensing index and statistical data to ascertain the spatial distribution of spring frost damage to winter wheat and evaluate the extent of damage. This method was employed to monitor and assess the spring frost damage event that occurred in Shandong province from 3 to 7 April 2018. The result shows that beginning on 3 April, the daily minimum temperature in western Shandong Province dropped significantly (decreased by 17.93 °C), accompanied by precipitation. The daily minimum temperature reached the lowest on 7 April (−1.48 °C). The growth of winter wheat began to be inhibited on 3 April 2018, and this process persisted until 13 April. Subsequently, the impact of spring frost damage on winter wheat ceased and growth gradually resumed. The affected area of winter wheat spanned 545,000 mu with an accuracy rate of 89.72%. Severely afflicted areas are mainly located in the cities of Jining, Zaozhuang, Dezhou, Heze, Liaocheng, Jinan and Tai’an in western Shandong province, and the yield reduction rates were 5.27~12.02%. Our monitoring results were consistent with the distribution of county-level winter wheat yield in 2018 in Shandong province, the daily minimum temperature distribution during spring frost and severely afflicted areas reported by the news. This method proves effective in delineating the spatial distribution of agricultural disasters and monitoring the extent of disaster damage. Furthermore, it can provide reliable information of disaster area and geospatial location for the agricultural department, thereby aiding in disaster damage assessment and post-disaster replanting. Full article
(This article belongs to the Special Issue Extreme Event Monitoring, Impact Assessment, Risk Early Warning on Ecosystem and Plants)
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