Quantifying effects of compound dry-hot extremes on vegetation in Xinjiang (China) using a vine-copula conditional probability model

环境科学 归一化差异植被指数 藤蔓copula 植被(病理学) 增强植被指数 蒸散量 旱季 气候学 藤蔓 降水 生长季节 自然地理学 气候变化 多元统计 地理 生态学 气象学 统计 植被指数 数学 地图学 生物 地质学 病理 医学
作者
H.W. Li,Yongping Li,Guohe Huang,J. Sun
出处
期刊:Agricultural and Forest Meteorology [Elsevier BV]
卷期号:311: 108658-108658 被引量:48
标识
DOI:10.1016/j.agrformet.2021.108658
摘要

Extreme events (e.g., drought and heatwave) occur frequently and intensively with climate change, where the combination of dry and hot events has catastrophic impacts on terrestrial ecosystems. It is challenged to quantitatively understand the vegetation vulnerability under compound dry-hot extremes. In this study, a vine-copula conditional probability (VCCP) model is proposed to quantify the impacts of dry-hot events on vegetation dynamics, where the dependence patterns of the Normalized Difference Vegetation Index (NDVI), standardized precipitation evapotranspiration index (SPEI), and standardized temperature index (STI) are modelled through vine copula functions. The VCCP model can evaluate the conditional probability of vegetation loss under multiple dry-hot events and reveal the temporal and spatial patterns of vegetation vulnerability of different land-use types. Then, the VCCP model is applied to Xinjiang province, where the ecological environment is fragile and soil erosion is serious. The dependence patterns among NDVI, SPEI and STI in summer season (June-August) during 1983-2015 are identified. The main findings are: (i) spatial and temporal responses of vegetation to drought and hot events present distinctively; (ii) under the extreme scenario, the average probability of vegetation loss below the 50th percentile in August reach 58.2%, followed by July (with 44.0%) and June (with 33.1%); (iii) the northern and southwestern regions of Xinjiang (especially for the grassland in the mountain areas) have the worst resistance to extreme dry-hot events in summer season. The findings can provide insights into the impacts of compound extremes on vegetation conditions and help decision makers take effective and efficient ecosystem management to mitigate climatic disasters.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
Hello应助我又不乱来采纳,获得10
1秒前
370086320完成签到,获得积分10
1秒前
jicm发布了新的文献求助10
1秒前
顾矜应助西子阳采纳,获得10
3秒前
无花果应助花成花采纳,获得10
6秒前
6秒前
夏花发布了新的文献求助10
6秒前
李爱国应助MOMO采纳,获得10
7秒前
搜集达人应助健壮的诗槐采纳,获得10
7秒前
8秒前
ccc关注了科研通微信公众号
8秒前
快乐游轮完成签到 ,获得积分10
9秒前
9秒前
9秒前
隐形曼青应助练习者采纳,获得10
9秒前
VDC应助高高的不悔采纳,获得30
12秒前
13秒前
博雅雅雅雅雅完成签到,获得积分10
13秒前
13秒前
14秒前
Nicheng发布了新的文献求助10
14秒前
14秒前
15秒前
zx9290发布了新的文献求助10
15秒前
15秒前
斯文败类应助hashtag采纳,获得30
15秒前
15秒前
星辰大海应助橘子采纳,获得10
16秒前
18秒前
ccc发布了新的文献求助10
18秒前
spw关注了科研通微信公众号
18秒前
爱吃食物的女孩完成签到 ,获得积分10
18秒前
科目三应助LamChem采纳,获得10
18秒前
jingyan完成签到,获得积分10
19秒前
19秒前
19秒前
Ava应助西子阳采纳,获得10
19秒前
机灵的冰夏完成签到,获得积分10
20秒前
来了来了发布了新的文献求助10
20秒前
高分求助中
【此为提示信息,请勿应助】请按要求发布求助,避免被关 20000
All the Birds of the World 4000
Production Logging: Theoretical and Interpretive Elements 3000
Musculoskeletal Pain - Market Insight, Epidemiology And Market Forecast - 2034 2000
Am Rande der Geschichte : mein Leben in China / Ruth Weiss 1500
CENTRAL BOOKS: A BRIEF HISTORY 1939 TO 1999 by Dave Cope 1000
Munson, Young, and Okiishi’s Fundamentals of Fluid Mechanics 9 edition problem solution manual (metric) 800
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3748536
求助须知:如何正确求助?哪些是违规求助? 3291591
关于积分的说明 10073642
捐赠科研通 3007395
什么是DOI,文献DOI怎么找? 1651600
邀请新用户注册赠送积分活动 786523
科研通“疑难数据库(出版商)”最低求助积分说明 751765