Collaborative Research:Shifting Seasonality of Northern Forest Response to Arctic Environmental Change

合作研究：北方森林季节性变化对北极环境变化的响应

• 批准号: 0902051
• 负责人: Rosanne D'Arrigo
• 金额: $ 38.12万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-06-15 至 2013-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0902051&HistoricalAwards=false
• 关键词: Collaborative; Research; Shifting; Seasonality; Northern

AbstractThis award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).This is an investigation of the response of northern boreal forests to changes in arctic seasonality using an existing circumpolar network of centennial to millennial-length tree-ring width and density records that will be integrated with targeted field observations, satellite data and modeling efforts. The sensitivity of northern forests to arctic warming and related seasonality effects is likely to be highly complex, involving shifts in the timing and dynamics of multiple factors that can significantly impact tree growth. Researchers will assess network-based as well as limited new tree-ring data from sites along a latitudinal gradient in northeastern Alaska, one of the regions of greatest warming on the globe today. Sites will be sampled along a south to north gradient spanning from areas of: 1. interior boreal forest to 2. continuous treeline forest and 3. just north of main treeline. These data will be used to identify the nature of forest response to seasonal environmental changes across a temperature range that defines the northern limit of growth for white spruce, a dominant arctic treeline species. They will also determine if recent climate and forest growth changes appear unique (possibly anthropogenic) relative to past natural variability. Correlation, Kalman filter, spectral analyses and other techniques will allow identification of any thresholds, time-dependent changes or nonlinear shifts in growth linked to recent warming and changing climate seasonality. Ultra-high resolution, inter- and intraseasonal tree growth data (ring width, maximum latewood density as well as minimum density, early and latewood width, quantifiable wood anatomical measurements) will be compared to monthly temperature, precipitation, drought, soil moisture and radiation observations, and, where available, weekly and daily records suitable for computing the length of growing season and other seasonal parameters. A cambial growth model will permit identification of those parameters that are having the greatest impact on northern forest growth. Intraseasonal growth information will be applied to parameterize the model and hindcast controls on growth variations into the past using the tree-ring data. They will also compare the ?in situ? tree-ring data with high-resolution satellite-derived vegetation observations that have indicated growing season ?greening? and ?browning? in different regions of the circumpolar arctic forest biome. This project will thus provide a means to test the ability to coordinate remote sensing and ground-based ?in situ? observations of boreal forest growth activity in the Arctic.

摘要这一奖项是根据2009年的《美国回收与重新投资法》（公法111-5）资助的。这是对北部北方森林对北部北方森林对北极季节性变化的反应，使用百百年赛对千年长度的树木环宽度和密度记录的现有圆周网络将与目标进行现场的现场观测，并将其与目标进行现场观测，并将其集成。北部森林对北极变暖和相关季节性影响的敏感性可能非常复杂，涉及多种因素的时机和动态的转变，这些因素可能会显着影响树木的生长。研究人员将评估基于网络的基于网络的新树环数据，从阿拉斯加东北部的纬度梯度沿线的地点是当今全球最大变暖的地区之一。地点将沿着：1。内部北方森林到2。连续的绿色森林和3。位于主绿林以北的区域的南部梯度进行采样。这些数据将用于确定森林对季节性环境变化的响应的性质，该温度范围定义了白云杉的北部生长极限，白云杉是一种主要的北极绿色物种。他们还将确定相对于过去的自然变异性，最近的气候和森林增长是否显得独特（可能是人为）。相关性，卡尔曼过滤器，光谱分析和其他技术将允许识别与最近变暖和气候变化季节性相关的任何阈值，依赖时间变化或非线性变化。将将超高分辨率，季节性和季节性树木生长数据（环宽，最大林木密度以及最小密度，最小密度，早期和直木宽度，可量化的木材解剖学测量值）与每月温度，降水量，干旱，土壤水分和辐射观测以及适用于每周，每周和每日记录的每周，适合于生长季节的季节和其他季节的季节和其他季节的季节和日常记录。邮政增长模型将允许识别那些对北部森林生长最大影响的参数。季节内生长信息将用于参数化模型，并使用树环数据对过去的增长变化进行后播控件。他们还将比较“原位”吗？带有高分辨率卫星衍生植被观测的树环数据表明生长季节？绿色？还有？勃朗宁？在近极北极森林生物群落的不同区域。因此，该项目将提供一种测试协调遥感和基于地面的能力的手段？北极北方森林生长活动的观察。