QUANTIFYING WITHIN-LAKE GRADIENTS OF WAVE ENERGY - INTERRELATIONSHIPS OF WAVE ENERGY, SUBSTRATE PARTICLE-SIZE AND SHORELINE PLANTS IN AXE LAKE, ONTARIO

QUANTIFYING WITHIN-LAKE GRADIENTS OF WAVE ENERGY - INTERRELATIONSHIPS OF WAVE ENERGY, SUBSTRATE PARTICLE-SIZE AND SHORELINE PLANTS IN AXE LAKE, ONTARIO
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DOI:
10.1016/0304-3770(82)90085-7
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发表时间:
1982-01-01
期刊:
影响因子:
1.8
通讯作者:
KEDDY, PA
KEDDY, PA
中科院分区:
生物学3区
文献类型:
--
作者:
KEDDY, PA

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暴露被定义为波浪对湖岸植被的总影响。波浪可能直接影响海岸线植物(例如,通过将幼苗连根拔起)或间接地(例如,通过侵蚀沉积物)。暴露可能是影响湖滨带植物分布的重要生态因子。开发了一种利用风数据和获取测量值识别暴露梯度的方法。获取量要么直接从16个罗盘方位的航空照片中测量(直接获取量),要么从32个罗盘方位计算以补偿湖盆的形状(有效获取量)。风的数据要么是平均风速乘以方向频率百分比,要么是方向风速。四个时间段5月,生长季节,无冰季节和全年,被认为是。这产生了2倍。2倍。4 = 16个暴露测量值。对加拿大安大略Axe湖600 m长的海岸线上的25个点进行了沉积物特征(粉土和粘土的比例;砂分选系数)和海岸线植物(6种选定物种所占的深度范围)采样。然后使用16种不同的计算方法计算所有25个点的暴露值。斯皮尔曼等级相关系数被用来确定计算的暴露值,沉积物特性和物种分布之间的相关性。沙选系数、谷精草、Nymphoides cordata(Ell.)弗恩和角狸藻(Utricularia cornuta Michx.)与所有暴露指标呈正相关。粉土和粘土的比例,莼菜,斑茅Dulichium arundinaceum(L.)布里特。和Pontederia cordata L.与所有暴露指标呈负相关。基于直接获取的计算产生了最强的相关性。当使用有效的获取,测量的基础上,每年或5月的方向值产生最好的结果。显然,计算出的暴露量提供了一种生物学上有意义的方法,可以沿着暴露梯度对海岸线沿着地区进行排名。
Exposure is defined as the total effect of waves on lakeshore vegetation. Waves may affect shoreline plants directly (e.g., by uprooting seedlings) or indirectly (e.g., by eroding for sediments). Exposure may be an important ecological factor affecting the within-lake distribution of shoreline plants. A method for identifying exposure gradients, using wind data and fetch measurements was developed. Fetch was either measured directly from aerial photographs for 16 compass bearings (direct fetch) or calculated from 32 compass bearings to compensate for the shape of the lake basin (effective fetch). Wind data were either mean wind velocity multiplied by directional percent frequency or exceedance by direction. Four time periods May, growing season, ice-free season and entire year, were considered. This yielded 2 .times. 2 .times. 4 = 16 measures of exposure. A total of 25 points on a 600 m section of shoreline on Axe Lake, Ontario, Canada were sampled for sediment characteristics (proportion silt and clay; sand sorting coefficient) and shoreline plants (depth ranges occupied by 6 selected species). Exposure values then were calculated for all 25 points using the 16 different methods of calculation. Spearman rank correlation coefficients were used to determine the correlation between calculated exposure values, sediment characteristics and species distributions. The sand sorting coefficient, Eriocaulon septangulare With., Nymphoides cordata (Ell.) Fern. and Utricularia cornuta Michx. were positively correlated with all measures of exposure. Proportion silt and clay, Brasenia schreberi Gmel., Dulichium arundinaceum (L.) Britt. and Pontederia cordata L. were negatively correlated with all measures of exposure. Calculations based on direct fetch yielded the strongest correlations. When effective fetch was used, measurements based on annual or May exceedance by direction values yielded the best results. Apparently, calculated measures of exposure provided a biologically meaningful way to rank areas of shoreline along an exposure gradient.