Spatial distribution of benthic-pelagic coupling

沿海河口和海湾是由潮汐、风和河流流动造成的强烈环境梯度的地点。海底沉积物是这种变化的一种表现，海底栖息地(沙、泥、植物)反映了环境和动物群落发展的能量。浅层混合良好的水柱确保底部通过沉积物和有机碎屑的再悬浮以及从分解中释放营养物质来影响上覆水域。在水柱中产生的物质(浮游植物)下沉到底部，在那里为这些过程提供动力。物质在海底、水柱和沿海海洋之间循环的速度决定了河口如何处理污染、过量营养物质和各种压力。虽然对不同栖息地类型的范围有一些了解，但它们的相对重要性还不是很清楚。例如，预计富含有机物质的泥土中的分解程度将大于干净沙子中的分解程度，但用于预测沿海生态系统功能的模型很少包括这种空间分辨率水平。拟议的研究将记录沿海生境的变化，以及在这些生境中发生物理交换、分解和初级生产(植物、微藻)的速度。我将使用远程探测技术，如声学海底测绘，来定义栖息地的变化。将在多个地点测量一系列关于分解、植物生长和其他过程的详细测量，以便在环境条件及其在生态系统功能中的作用之间进行匹配。然后，这些信息将被输入到改进的生态系统模型中，以便能够更好地预测营养物质负载、资源开采、渔业、商业发展和气候变化的影响。

Coastal estuaries and bays are sites of strong environmental gradients caused by tides, winds and river flow. Bottom sediments are a manifestation of this variation, with bottom habitat (sand, mud, plants) reflecting the energy of the environment and development of animal communities. The shallow well-mixed water column insures that the bottom influences overlying waters by resuspension of sediments and organic debris, and release of nutrients from decomposition. Material produced in the water column (phytoplankton) sinks to the bottom where it fuels these processes. The rate at which material is cycled between the bottom, water column, and coastal ocean determines how estuaries deal with pollution, excess nutrients, and a variety of stresses. Although there is some understanding of the range of different habitat types, their relative importance is not well known. For example, it is expected that decomposition will be greater in organic-rich mud than in clean sand, but this level of spatial resolution is rarely included in the models that are used to make predictions about the functioning of coastal ecosystems. The proposed research will document variation in coastal habitats as well as the rate at which physical exchange, decomposition, and primary production (plants, microalgae) occur in these habitats. I will use remote detection techniques such as acoustic seabed mapping to define habitat variation. A series of detailed measurements on decomposition, plant growth, and other processes will be measured in multiple locations, allowing a match between environmental conditions and their role in ecosystem functioning. This information will then be input to improved ecosystem models to allow greater capability in prediction of effects from nutrient loading, resource extraction, fisheries, commercial development, and climate change.