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: 2012
• 资助国家: 加拿大
• 起止时间: 2012-01-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=497480
• 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.

我们的研究计划已经开发了一系列的生态指标，以帮助确定大湖盆地沿海湿地的质量，因为这些是鱼类和候鸟的关键栖息地，尤其是在安大略省南部的人类活动，它们的质量已降低。 指标套件包括水质指数（WQI），这是水质障碍的指标，发现与水土地使用变化直接相关。 由于WQI可能过于昂贵且劳动密集型，以至于环保机构通常使用两个生态指数，即湿地鱼指数和湿地大植物指数，这些指数与WQI统计相关，并且可以基于鱼类或植物的不存在来计算它们。 我们还为水位波动对沿海湿地的新兴植被的控制作用提供了许多论文，尤其是与退化的沼泽有关。在2005年，我们使用了一种新方法来预测水位的影响，该方法涉及一个称为“淹没区”的新术语的计算。 此后，我们已经确认，沼泽淹没模型可以应用于其他大湖地区的许多沼泽，并且该方法也可以用于评估景观水平上多种压力源（例如水位，人类干扰和外来入侵）的影响。 现在，我们建议使用涉及地理信息系统，遥感技术和现场观察的综合方法，使用水肺进行量化沿海湿地中的鱼类和鸟类栖息地。 选择遥感来开发一种具有成本效益的方式来在整个大湖泊的规模上绘制水生植被（不同的栖息地类）。 我的长期目标是提高生态指标和遥感的使用，以使鱼类和鸟类栖息地如何随着时间的流逝而变化。 预计这项研究将对加拿大政府预测我们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多的地区的气候变化和土地利用改变。