Collaborative Research: Greening of the Arctic - Synthesis and Models to Examine the Effects of Climate, Sea-ice, and Terrain on Circumpolar Vegetation Change

合作研究：北极绿化——检验气候、海冰和地形对极地植被变化影响的综合和模型

• 批准号: 0531166
• 负责人: Howard Epstein
• 金额: $ 40.66万
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0531166&HistoricalAwards=false
• 关键词: Collaborative; Research; Greening; Arctic; Synthesis

AbstractChanges to the vegetation of the Arctic are intimately linked to changes to the sea-ice cover, land surface temperatures, and a host of terrain variables. The overarching goals of this research are to (1) explore the sea-ice/terrain/vegetation linkages by synthesizing a group of recently available long-term circumpolar databases, (2) examine how the vegetation of the circumpolar Arctic is responding to global climate change, and (3) use this information in combination with models to help predict future response of arctic vegetation. The project will address directly the question of how the terrestrial vegetation of the Arctic has responded to climate change to date and how it will respond in the future as portions of the Arctic Ocean become seasonally ice free as indicated by current understanding of trends in sea ice. An average 17% increase in greenness, as measured by the normalized difference vegetation index (NDVI), occurred in northern Alaska from 1981 to 2001, concomitant with strong ice retreat in the Beaufort Sea and rising land-surface temperatures. The trend in NDVI is consistent with observations regarding shrub cover, modeling, and experimental evidence linking temperature increases to biomass increases. The group will synthesize 23+ years of data from Earth orbiting satellites in combination with detailed circumpolar maps of climate, vegetation, terrain, and substrate variables to determine how the ocean and land have interacted during the years of record, and then use this information to improve existing models of Arctic vegetation change. They will use primarily a time series of surface temperature, sea-ice, and NDVI data from the Advanced Very High Resolution Radiometers (AVHRR) aboard the NOAA satellites. A host of other remote sensing data will complement these to extend the length of the record and to look at finer scale changes. The primary region of study is the circumpolar Arctic as defined by the presence of tundra vegetation and an Arctic climate. A larger area defined by the arctic watershed will be studied in less detail. They will create a circumpolar integrated geographic information system for this region. The NDVI patterns will be analyzed spatially and temporally with respect to mapped variables including land-surface temperatures (LSTs), sea-ice patterns, the age of the terrain, substrate, topography, elevation, and regional floras. They will use vegetation change models to determine if the greening detected thus far can be used to project future patterns of vegetation change in the Arctic. A spatial analysis using BIOME4, a global model of vegetation change, will predict changes in the patterns of arctic and boreal plant communities, and ArcVeg, a model of arctic vegetation dynamics, will link the changes detected using remote sensing to ground-based measurements of plant species composition and structure to examine the rates at which changes can be expected.

北极植被的变化与海冰覆盖、陆地表面温度和许多地形变量的变化密切相关。本研究的总体目标是（1）通过综合一组最近可用的长期环极数据库来探索海冰/地形/植被的联系，（2）研究环极北极的植被如何响应全球气候变化，以及（3）结合模型使用这些信息来帮助预测北极植被的未来响应。该项目将直接处理北极陆地植被迄今如何应对气候变化的问题，以及随着目前对海冰趋势的了解表明北冰洋部分地区季节性无冰，北极陆地植被今后将如何应对。1981年至2001年，根据归一化植被指数（NDVI）测量，北方阿拉斯加的绿色度平均增加了17%，同时，博福特海的冰强烈退缩，地表温度上升。植被指数的趋势是一致的观察灌木覆盖，建模和实验证据连接温度升高，生物量增加。该小组将综合地球轨道卫星23年以上的数据，结合详细的气候，植被，地形和基质变量的环极地图，以确定海洋和陆地在有记录的年份中如何相互作用，然后使用这些信息来改进现有的北极植被变化模型。他们将主要使用来自NOAA卫星上的高级甚高分辨率辐射计（AVHRR）的地表温度、海冰和归一化差异植被指数数据的时间序列。大量其他遥感数据将补充这些数据，以延长记录的长度，并观察更精细的尺度变化。研究的主要区域是环极北极，这是由冻原植被和北极气候的存在所定义的。由北极分水岭定义的更大的区域将被研究得不那么详细。他们将为该区域建立一个环极综合地理信息系统。将分析空间和时间的归一化植被指数模式映射变量，包括地表温度（LST），海冰模式，年龄的地形，基板，地形，海拔和区域植物区系。他们将使用植被变化模型来确定迄今为止检测到的绿化是否可以用于预测北极未来的植被变化模式。利用BIOME 4这一全球植被变化模型进行的空间分析将预测北极和北方植物群落格局的变化，而ArcVeg这一北极植被动态模型将把遥感探测到的变化与植物物种组成和结构的地面测量联系起来，以检查预计变化的速度。