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

摘要本奖项由2009年美国复苏与再投资法案（公法111-5）资助。这是对北方北方森林对北极季节性变化的响应的调查，利用现有的百年至千年树木年轮宽度和密度记录的环极网络，将与有针对性的实地观测、卫星数据和建模工作相结合。北方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，涉及可能显著影响树木生长的多种因素的时间和动态变化。研究人员将评估阿拉斯加东北部纬度梯度沿线站点的基于网络和有限的新树木年轮数据，阿拉斯加是当今全球变暖最严重的地区之一。站点将沿着南向北的梯度从区域跨越：1。内部北方森林至2。3.连续的林木线森林；就在主要林木线的北边。这些数据将用于确定森林对季节性环境变化的响应性质，该温度范围界定了白云杉生长的北部极限，白云杉是北极主要的树线物种。它们还将确定，相对于过去的自然变率，最近的气候和森林生长变化是否显得独特（可能是人为的）。相关性、卡尔曼滤波、光谱分析和其他技术将允许识别任何阈值、随时间变化的变化或与最近变暖和气候季节性变化有关的增长非线性变化。超高分辨率、季节间和季节内的树木生长数据（年轮宽度、最大晚木密度和最小密度、早木和晚木宽度、可量化的木材解剖测量）将与每月的温度、降水、干旱、土壤湿度和辐射观测进行比较，如果有的话，还将与适合计算生长季节长度和其他季节性参数的每周和每日记录进行比较。形成层生长模型将有助于查明对北方森林生长影响最大的那些参数。季节内生长信息将用于参数化模型，并利用树木年轮数据对过去的生长变化进行后投控制。他们也会比较？原位?树木年轮数据与高分辨率卫星衍生的植被观测数据显示了生长季节？绿化？和褐变?在极地周围不同地区的北极森林生物群系。因此，这个项目将提供一种手段来测试遥感和地面卫星协调能力。原位?对北极北方森林生长活动的观察。

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.