The fragile alpine vegetation in the Tibetan Plateau (TP) is very sensitive to environmental changes, making TP one of the hotspots for studying the response of vegetation to climate change. Existing studies lack detailed description of the response of vegetation to different climatic factors using the method of multiple nested time series analysis and the method of grey correlation analysis. In this paper, based on the Normalized Difference Vegetation Index (NDVI) of TP in the growing season calculated from the MOD09A1 data product of Moderate-resolution Imaging Spectroradiometer (MODIS), the method of multiple nested time series analysis is adopted to study the variation trends of NDVI in recent 17 years, and the lag time of NDVI to climate change is analyzed using the method of Grey Relational Analysis (GRA). Finally, the characteristics of temporal and spatial differences of NDVI to different climate factors are summarized. The results indicate that: (1) the spatial distribution of NDVI values in the growing season shows a trend of decreasing from east to west, and from north to south, with a change rate of -0.13/10° E and -0.30/10° N, respectively. (2) From 2001 to 2017, the NDVI in the TP shows a slight trend of increase, with a growth rate of 0.01/10a. (3) The lag time of NDVI to air temperature is not obvious, while the NDVI response lags behind cumulative precipitation by zero to one month, relative humidity by two months, and sunshine duration by three months. (4) The effects of different climatic factors on NDVI are significantly different with the increase of the study period.
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http://dx.doi.org/10.3390/ijerph16183452 | DOI Listing |
PeerJ
January 2025
College of Agriculture, Shanxi Agricultural University, Shanxi, Jinzhong, China.
It is crucial to elucidate the impact of climate change on wheat production in China. This article provides a review of the current climate change scenario and its effects on wheat cultivation in China, along with an examination of potential future impacts and possible response strategies. Against the backdrop of climate change, several key trends emerge: increasing temperature during the wheat growing season, raising precipitation, elevated CO concentration, and diminished radiation.
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January 2025
Department of Disease Prevention and Control, Daping Hospital, State Key Laboratory of Trauma and Chemical Poisoning, Army Medical University (Third Military Medical University), Changjiang Branch St, 10#, Yuzhong, Chongqing, 400042, China.
The effects of short-term ambient ozone (O) exposure on health outcomes have received growing concerns, but its effects on psoriasis is still unclear. The purpose of our study was to investigate the effects of short-term exposure to O on psoriasis, and to find out potential modifiers. A hospital-based time-series study with outpatient visit data of psoriasis was performed in Chongqing, the largest metropolitan in Southeast China.
View Article and Find Full Text PDFNat Ecol Evol
January 2025
PLECO Plants and Ecosystems Research Group, Department of Biology, University of Antwerp, Wilrijk, Belgium.
In the temperate zone, deciduous trees exhibit clear above-ground seasonality, marked by a halt in wood growth that represents the completion of wood formation in autumn and reactivation in spring. However, the growth seasonality of below-ground woody organs, such as coarse roots, has been largely overlooked. Here we use tree monitoring data and pot experiments involving saplings to examine the late-season xylem development of stem and coarse roots with leaf phenology in four common deciduous tree species in Western Europe.
View Article and Find Full Text PDFSci Rep
January 2025
Inner Mongolia Academy of Agricultural and Animal Husbandry Sciences, Zhao Ju Road Num. 22, Yu Quan District, Hohhot, 010031, China.
One of the major problem in the cultivation of sugar beets is continuous cropping obstacle in China. In order to evaluate the effects of continuous cropping year on the photosynthetic performance, dry matter accumulation, and distribution of sugar beet, this study was conducted in the 2020-2021 crop season at the Agriculture and Forestry Sciences of Ulanqab, Inner Mongolia. A split plot system arrangement with three replications was set up to carry out the field testing.
View Article and Find Full Text PDFPlant Genome
March 2025
USDA-ARS Southeast Area, Plant Science Research, Raleigh, North Carolina, USA.
Integrating genomic, hyperspectral imaging (HSI), and environmental data enhances wheat yield predictions, with HSI providing detailed spectral insights for predicting complex grain yield (GY) traits. Incorporating HSI data with single nucleotide polymorphic markers (SNPs) resulted in a substantial improvement in predictive ability compared to the conventional genomic prediction models. Over the course of several years, the prediction ability varied due to diverse weather conditions.
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