Dataset Information

Vegetation response to precipitation anomalies under different climatic and biogeographical conditions in China.

ABSTRACT: Understanding precipitation-vegetation interaction is of great importance to implementing adaptation and mitigation measures for terrestrial ecosystems. Many studies have explored the spatial pattern of precipitation-vegetation correlation along the precipitation amount gradient. While the impacts of other precipitation characteristics remain poorly understood. Here, we provided a comprehensive investigation of spatiotemporal patterns of vegetation response to precipitation anomalies in China, using satellite-derived vegetation index and multi-source climate datasets for the years 1982-2015. Subsequently, we attempted to examine in detail what specific factors, climatic or biogeographic, are responsible for spatiotemporal patterns of precipitation-vegetation relationship. Results show that vegetation in Inner Mongolia Plateau is strongly affected by precipitation anomalies. Vegetation has a 1-2 month lag response to precipitation anomalies and is significantly correlated with 2-6 month cumulative precipitation anomalies. Seasonal differences of vegetation response are also remarkable. Moreover, the largest NDVI-precipitation correlation appears in areas with 150-500?mm of mean annual precipitation, 0.075-0.275 of fraction of precipitation days, and 19-23 of precipitation concentration index. More locally, the spatial distribution of NDVI-precipitation correlations is closely related to the vegetation type and elevation. The results can provide technical basis and beneficial reference to water resource and ecological management strategies in China for associated policymakers and stakeholders.

SUBMITTER: Chen Z

PROVIDER: S-EPMC6972909 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Vegetation response to precipitation anomalies under different climatic and biogeographical conditions in China.

Chen Zefeng Z Wang Weiguang W Fu Jianyu J

Scientific reports 20200121 1

Understanding precipitation-vegetation interaction is of great importance to implementing adaptation and mitigation measures for terrestrial ecosystems. Many studies have explored the spatial pattern of precipitation-vegetation correlation along the precipitation amount gradient. While the impacts of other precipitation characteristics remain poorly understood. Here, we provided a comprehensive investigation of spatiotemporal patterns of vegetation response to precipitation anomalies in China, u ...[more]

PMID: 31965046

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Project description:Early detection of pathogenic fungi in controlled environment areas can prevent major food production losses. Grey mould caused by Botrytis cinerea is often detected as an infection on lettuce. This paper explores the use of vegetation indices for early detection and monitoring of grey mould on lettuce under different lighting conditions in controlled environment chambers. The aim was focused on the potential of using vegetation indices for the early detection of grey mould and on evaluating their changes during disease development in lettuce grown under different lighting conditions. The experiment took place in controlled environment chambers, where day/night temperatures were 21 ± 2/17 ± 2 °C, a 16 h photoperiod was established, and relative humidity was 70 ± 10% under different lighting conditions: high-pressure sodium (HPS) and light-emitting diode (LED) lamps. Lettuces were inoculated by 7-day-old fungus Botrytis cinerea isolate at the BBCH 21. As a control, non-inoculated lettuces were grown under HPS and LEDs (non-inoculated). Then, the following were evaluated: Anthocyanin Reflectance Index 2 (ARI2); Carotenoid Reflectance Index 2 (CRI2); Structure Intensive Pigment Index (SIPI); Flavanol Reflectance Index (FRI); Greenness (G); Greenness 2 (G2); Redness (R); Blue (B); Blue Green Index 2 (BGI2); Browning Index 2 (BRI2); Lichtenthaler Index 1 (LIC1); Pigment Specific Simple Ratio (PSSRa and PSSRb); Gitelson and Merzlyak (GM1 and GM2); Zarco Tejada-Miller Index (ZMI); Normalized Difference Vegetation Index (NDVI); Simple Ratio (SR); Red-Eye Vegetation Stress Index (RVSI); Photochemical Reflectance Index (PRI); Photochemical Reflectance Index 515 (PRI515); Water Band Index (WBI); specific disease index for individual study (fD); Healthy Index (HI); Plant Senescence Reflectance (PSRI); Vogelmann Red Edge Index (VREI1); Red Edge Normalized Difference Vegetation Index (RENDVI); and Modified Red Edge Simple Ratio (MRESRI). Our results showed that the PSRI and fD vegetation indices significantly detected grey mould on lettuce grown under both lighting systems (HPS and LEDs) the day after inoculation. The results conclusively affirmed that NDVI, PSRI, HI, fD, WBI, RVSI, PRI, PRI515, CRI2, SIPI, chlorophyll index PSSRb, and coloration index B were identified as the best indicators for Botrytis cinerea infection on green-leaf lettuce (Lactuca sativa L. cv Little Gem) at the early stage of inoculated lettuce's antioxidative response against grey mould with a significant increase in chlorophyll indices.

Dataset Information

Vegetation response to precipitation anomalies under different climatic and biogeographical conditions in China.

Publications

Vegetation response to precipitation anomalies under different climatic and biogeographical conditions in China.

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