Remote sensing and ecological models: an integrated approach to analysis of wetlands

遥感和生态模型：湿地分析的综合方法

• 批准号: 194608-2008
• 负责人: ChowFraser, Patricia
• 金额: $ 1.15万
• 依托单位: McMaster University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2010
• 资助国家: 加拿大
• 起止时间: 2010-01-01 至 2011-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=452748
• 关键词: Remote; sensing; ecological; models; integrated

Our research program has developed a series of ecological indicators to help determine quality of coastal wetlands in the Great Lakes basin because these are critical habitats for fish and migratory birds and their quality has been degraded by human activities, especially in southern Ontario. The suite of indicators include the Water Quality Index (WQI), an indicator of water quality impairment and which was found to be directly related to watershed land-use alteration. Since the WQI may be too costly and labour-intensive to be used routinely by environmental agencies, we have also developed two ecological indices, the Wetland Fish Index, and the Wetland Macrophyte Index, which are statistically related to the WQI, and which can be calculated based on presence/absence of fish or macrophyte species. We have also contributed numerous papers on the controlling effect of water level fluctuations on emergent vegetation in coastal wetlands, particularly as it pertains to degraded marshes. In 2005, we used a new approach to predict the effect of water levels, which involved the calculation of a new term called "inundated area". We have since confirmed that the marsh inundation model can be applied to many marshes in other Great Lakes areas, and that this method can also be used to assess the effects of multiple stressors (e.g. water level, human disturbance and exotic invasions) at the landscape level. We now propose to use an integrated approach involving Geographical Information Systems, remote sensing technology and field observations using SCUBA to quantify fish and bird habitat in coastal wetlands. Remote sensing is chosen to develop a cost-effective way to map aquatic vegetation (different habitat classes) at the scale of an entire Great Lake. My long term goal is to advance the use of ecological indicators and remote sensing to meaure how fish and bird habitat change through time. This research is expected to have an impact on the ability of Canadian governments to anticipate major changes in our natural heritage in response to climate change and land-use alterations in the most heavily populated region of Canada.

我们的研究项目开发了一系列生态指标，以帮助确定五大湖流域沿海湿地的质量，因为这些湿地是鱼类和候鸟的重要栖息地，它们的质量已经因人类活动而下降，尤其是在安大略省南部。这套指标包括水质指数（WQI），这是一个水质损害的指标，被发现与流域土地利用变化直接相关。由于湿地水质指数的成本太高，需要大量的人力，环保机构不可能经常使用，因此我们制定了两个生态指数，即湿地鱼类指数和湿地大型植物指数，它们在统计上与湿地水质指数有关，并可根据鱼类或大型植物物种的存在/缺失来计算。我们还撰写了许多关于水位波动对沿海湿地，特别是与退化沼泽有关的新兴植被的控制作用的论文。2005年，我们采用了一种新的方法来预测水位的影响，其中包括计算一个名为“淹没面积”的新术语。我们已经证实，沼泽淹没模型可以应用于其他五大湖地区的许多沼泽，并且该方法也可以用于在景观水平上评估多种压力因素（如水位，人为干扰和外来入侵）的影响。我们建议采用地理信息系统、遥感技术和实地观测相结合的综合方法，对沿海湿地的鱼类和鸟类栖息地进行量化。选择遥感是为了开发一种在整个大湖尺度上绘制水生植被（不同生境类别）的经济有效的方法。我的长期目标是推进生态指标和遥感的使用，以测量鱼类和鸟类栖息地如何随时间变化。这项研究预计将对加拿大政府预测自然遗产的重大变化的能力产生影响，以应对加拿大人口最稠密地区的气候变化和土地利用变化。