海岸带地理特征对沉水植被丰度的影响

Effects of coastal geographical characteristics on the abundance of submerged aquatic vegetation

对北美切斯比克海湾99个河口海岸带地理特征(流域土地利用类型、河口宽度、海岸线分形维度、流域面积与河口面积比、高分辨率平均波浪高度和沉积物等)对1984—2009年间沉水植被丰度的影响进行了研究。结果表明:相同盐度分区的不同土地利用类型下,以及相同土地利用类型的不同盐度分区下,沉水植被丰度存在着明显的差异;沉水植被丰度与海岸带地理特征各单因子之间呈微弱相关性(-0.157≤r≤0.442),其中,沉水植被丰度与河口宽度(r=0.442,P<0.001)、分形维度(r=0.290,P=0.007)和平均波浪高度(r=0.306,P=0.002)相关关系相对较高,且呈极显著正相关(P<0.01);分类回归树模型分析表明,影响沉水植被丰度的海岸带地理特征因子依次为流域与河口面比、河口分形维度、盐度和平均波浪高度,共可解释沉水植被丰度空间变异的60%以上。研究表明,海岸带地理特征直接或间接的影响着区域沉水植被丰度,二者之间存在一定的相关关系;不同特征因子对沉水植被丰度的影响程度不同,但整体呈现出多因素综合的复杂影响。研究结果对切斯比克海湾沉水植被的生态恢复具有一定的指导意义。

Submerged aquatic vegetation （SAV）consists of a taxonomically diverse group of plants that lives entirely beneath the water surface. SAV provides habitat and supplies food for aquatic life, absorbs excess nutrients, and helps purify the water. Since the 1960s, SAV coverage has experienced dramatic decline worldwide due to serious deterioration of water quality in coastal ecosystems. In recent years, landscape analyses have been used to predict direct or indirect effects of geographic characteristics on aquatic organisms. In this study, we analyzed the effects of coastal geographical characteristics （ such as watershed land use types, sub-estuary mouth width, shoreline fractal dimension, ratio of watershed area/sub-estuary area, high resolution average wave height and estuary sediment, etc. ） on the spatial variation of SAV abundance based on the long-term dataset （1984--2009） from 99 sub-estuaries and their linked coastal sub-watersheds of the Chesapeake Bay in the United States. Coastal watershed land use is an important factor influencing inputs of nutrient and sediment to its associated sub-estuary,and thus indirectly affects SAV abundance. Our resuhs showed that sub-estuaries with different dominant land covers in each salinity regime had significantly different variation in SAV abundance. Abundance of different SAV species varies spatially among different salinity regimes in shallow water area. In each salinity regime, SAV abundance in sub-estuaries declined with their linked coastal dominant watershed land use type in the following order： mixed-land 〉 developed land or forested land 〉 agricultural land in fresh water （TF） regime; mixed-land or agricultural land 〉 developed land 〉 forested land in oligohaline （OH） regime; forested land or mixed-land 〉 developed land or agricultural land in mesohaline （MH） regime ; mixed-land or forested land 〉 developed land 〉 agricultural land in polyhaline （PH） regime. Sub-estuaries with different salinity regimes for each dominant land cover also had significantly different levels of SAV abundance. In each dominant watershed land use type, SAV abundance in sub-estuaries declined with salinity regime in the following order： no significant difference among four salinity regimes for developed land; OH 〉 MH 〉 TF or PH for agricultural land; OH or PH 〉 TF or MH for mixed-land; MH or PH 〉 TF or OH for forested land. Relative weaker linear correlation was found between a single geographical characteristics and SAV abundance （ - 0. 157≤ r ≤ 0. 442 ）, but SAV abundance had significantly positive correlations with a few estuary characteristics, such as sub-estuary mouth width （r = 0. 442, P 〈 0. 001 ）, shoreline fractal dimension （ r = 0. 290, P = 0. 007 ） and average wave height （ r = 0. 306, P = 0. 002 ）. A wider sub-estuary mouth could lead more sea water to diluting pollutants in shorter time and thus favors SAV growth. A higher shoreline fractal dimension value represents more complex estuary structure and small tributaries in each sub-estuary that favors SAV growth as well. Higher wave height could positively dilute pollutants or negatively erode SAV beds in a sub- estuary. The integrated impact on SAV abundance was positive. Using the classification and regression tree （CART） model, we predicted that ratio of watershed area/sub-estuary area had the greatest impact on SAV abundance that appeared at the highest level of the tree, followed by shoreline fractal dimension, salinity regime, and average wave height. The four geographical variables explained 63% of the total spatial variation in SAV abundance across the Chesapeake Bay. Our findings imply that variation in the coastal geographical characteristics can indirectly affect spatial SAV abundance. Therefore, geographical characteristics in both sub-estuaries and their associated watersheds should be considered in making strategy of SAV recovery or protection policy at the regional scale in coastal area.