PREDICTING PLANT NUTRIENT CONCENTRATIONS FROM TEMPERATURE AND SIGMA-T IN THE UPPER KILOMETER OF THE WORLD OCEAN
PREDICTING PLANT NUTRIENT CONCENTRATIONS FROM TEMPERATURE AND SIGMA-T IN THE UPPER KILOMETER OF THE WORLD OCEAN
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DOI：
10.1016/0198-0149(86)90109-3
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发表时间：
1986-01-01
期刊：
影响因子：
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通讯作者：
ZENTARA, SJ
中科院分区：
文献类型：
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作者：
KAMYKOWSKI, D;ZENTARA, SJ
国家海洋数据中心的数据集由代表世界海洋所有区域的230,202个海洋站组成，统计分析了水柱上部千米处的温度和sigma-t(？t)与硝酸盐、磷酸盐或硅酸浓度的关系。每10度计算6次回归。包含足够数据的经纬度的平方。世界地图显示了在选定的主观和客观标准范围内，允许根据温度或σt预测植物营养浓度的位置。地理覆盖率沿序列改善：硝酸盐、磷酸盐和硅酸，并且对σt比对温度更好。对低于所选量的植物养分出现的温度或σt的百分比分析提供了一种检查初期营养限制的方法。等高线地图显示了硝酸盐、磷酸盐或硅酸在世界海洋中通常接近经典植物营养分析所确定的无法测量的浓度的近似温度。这些结果总结了从遥感温度或σt预测植物营养物质浓度的全球潜力，并强调了基于温度、σt和现代和过去海洋的植物营养物质在纬向和经向变化的浮游植物生长环境。
A National Oceanographic Data Center data set comprised of 230,202 oceanographic stations representing all regions of the world ocean was analyzed statistically for temperature and sigma-t (.sigma.t) relationships with nitrate, phosphate or silicic acid concentrations in the upper kilometer of the water column. Six cubic regressions were computed for each 10.degree. square of latitude and longitude containing adequate data. World maps display the locations that allow the prediction of plant nutrient concentrations from temperature or .sigma.t within the limits of selected subjective and objective criteria. Geographic coverage improves along the sequence: nitrate, phosphate and silicic acid, and is better for .sigma.t than for temperature. A percentage analysis of the temperature or .sigma.t at which less than a selected amount of plant nutrient occurs provided a method to examine incipient nutrient limitation. Contour maps display the approximate temperatures above or .sigma.t values below which nitrate, phosphate or silicic acid routinely approach unmeasurable concentrations in the world ocean as determined by classical plant nutrient analyses. The results summarize the global potential to predict plant nutrient concentrations from remotely sensed temperature or .sigma.t and emphasize the latitudinally and longitudinally changing phytoplankton growth environment based on temperature, .sigma.t and plant nutrients in present and past oceans.