HOGSETT WE, WEBER JE, TINGEY D, HERSTROM A, LEE EH, LAURENCE JA
US EPA, Environmental Research Laboratory-Corvallis200 SW 35thCorvallis, Oregon 97333, USA
Environ Manage. 1997 Jan;21(1):105-20. doi: 10.1007/s002679900010.
/ The risk tropospheric ozone poses to forests in the United States is dependent on the variation in ozone exposure across the distribution of the forests in question and the various environmental and climate factors predominant in the region. All these factors have a spatial nature, and consequently an approach to characterization of ozone risk is presented that places ozone exposure-response functions for species as seedlings and model-simulated tree and stand responses in a spatial context using a geographical information systems (GIS). The GIS is used to aggregate factors considered important in a risk characterization, including: (1) estimated ozone exposures over forested regions, (2) measures of ozone effects on species' and stand growth, and (3) spatially distributed environmental, genetic, and exposure influences on species' response to ozone. The GIS-based risk characterization provides an estimation of the extent and magnitude of the potential ozone impact on forests. A preliminary risk characterization demonstrating this approach considered only the eastern United States and only the limited empirical data quantifying the effect of ozone exposures on forest tree species as seedlings. The area-weighted response of the annual seedling biomass loss formed the basis for a sensitivity ranking: sensitive-aspen and black cherry (14%-33% biomass loss over 50% of their distribution); moderately sensitive-tulip popular, loblolly pine, eastern white pine, and sugar maple (5%-13% biomass loss); insensitive-Virginia pine and red maple (0%-1% loss). In the future, the GIS-based risk characterization will include process-based model simulations of the three- to 5-year growth response of individual species as large trees with relevant environmental interactions and model simulated response of mixed stands. The interactive nature of GIS provides a tool to explore consequences of the range of climate conditions across a species' distribution, forest management practices, changing ozone precursors, regulatory control strategies, and other factors influencing the spatial distribution of ozone over time as more information becomes available.KEY WORDS: Ecological risk assessment; GIS; Ozone; Risk characterization; Forests; Trees
对流层臭氧对美国森林构成的风险取决于在所讨论森林分布范围内臭氧暴露的变化以及该地区主要的各种环境和气候因素。所有这些因素都具有空间性质，因此提出了一种臭氧风险特征描述方法，该方法将物种作为幼苗时的臭氧暴露 - 响应函数以及模型模拟的树木和林分响应置于使用地理信息系统（GIS）的空间背景中。GIS用于汇总在风险特征描述中被认为重要的因素，包括：（1）森林区域的估计臭氧暴露量；（2）臭氧对物种和林分生长影响的度量；（3）对物种对臭氧响应的空间分布环境、遗传和暴露影响。基于GIS的风险特征描述提供了对臭氧对森林潜在影响的程度和大小的估计。展示这种方法的初步风险特征描述仅考虑了美国东部地区，并且仅使用了有限的实证数据来量化臭氧暴露对作为幼苗的森林树种的影响。年度幼苗生物量损失的面积加权响应构成了敏感性排名的基础：敏感的——颤杨和黑樱桃（在其分布的50%范围内生物量损失14% - 33%）；中度敏感的——北美鹅掌楸、火炬松、东部白松和糖枫（生物量损失5% - 13%）；不敏感的——弗吉尼亚松和红枫（损失0% - 1%）。未来，基于GIS的风险特征描述将包括对作为大树的单个物种三到五年生长响应的基于过程的模型模拟，以及相关环境相互作用和混合林分的模型模拟响应。随着更多信息的获取，GIS的交互性质提供了一个工具，用于探索物种分布范围内气候条件范围、森林管理实践、不断变化的臭氧前体、监管控制策略以及其他影响臭氧随时间空间分布的因素的后果。
生态风险评估；GIS；臭氧；风险特征描述；森林；树木
