Academic Journal

The Time Lag Effect Improves Prediction of the Effects of Climate Change on Vegetation Growth in Southwest China

التفاصيل البيبلوغرافية
العنوان: The Time Lag Effect Improves Prediction of the Effects of Climate Change on Vegetation Growth in Southwest China
المؤلفون: Meng Wang, Zhengfeng An, Shouyan Wang
المصدر: Remote Sensing; Volume 14; Issue 21; Pages: 5580
بيانات النشر: Multidisciplinary Digital Publishing Institute
سنة النشر: 2022
المجموعة: MDPI Open Access Publishing
مصطلحات موضوعية: time lag effect, multiple time delay combination model, annual delay effects, interannual delay effects, typical climate types
جغرافية الموضوع: agris
الوصف: Climate change is known to significantly affect vegetation development in the terrestrial system. Because Southwest China (SW) is affected by westerly winds and the South and East Asian monsoon, its climates are complex and changeable, and the time lag effect of the vegetation’s response to the climate has been rarely considered, making it difficult to establish a link between the SW region’s climate variables and changes in vegetation growth rate. This study revealed the characteristics of the time lag reaction and the phased changes in the response of vegetation to climate change across the entire SW and the typical climate type core area (CA) using the moving average method and multiple linear model based on the climatic information of CRU TS v. 4.02 from 1982 to 2017 together with the annual maximum (P100), upper quarter quantile (P75), median (P50), lower quarter quantile (P25), minimum (P5), and mean (Mean) from GIMMS NDVI. Generally, under the single and combined effects of temperature and precipitation, taking the time lag effect (annual and interannual delay effect) into account significantly improved the average prediction rates of temperature and precipitation, which increased by 18.48% and 25.32%, respectively. The optimal time delay was 0–4 months when the annual delay was taken into consideration, but it differed when considering the interannual delay, and the delaying effect of precipitation was more significant than that of temperature. Additionally, the response intensity of vegetation to temperature, precipitation, and their interaction was significantly more robust when the annual delay was taken into account than when it was not (p < 0.05), with corresponding multiple correlation coefficients of 0.87 and 0.91, respectively. However, the degree of response to the combined effect of individual effects and climate factors tended to decrease regardless of whether time delay effects were taken into account. A more comprehensive analysis of the effects of climate change on vegetation development ...
نوع الوثيقة: text
وصف الملف: application/pdf
اللغة: English
Relation: Ecological Remote Sensing; https://dx.doi.org/10.3390/rs14215580
DOI: 10.3390/rs14215580
الاتاحة: https://doi.org/10.3390/rs14215580
Rights: https://creativecommons.org/licenses/by/4.0/
رقم الانضمام: edsbas.A8640535
قاعدة البيانات: BASE