Modeling the temperature-nitrate relationship in the coastal upwelling domain of the California Current
Modeling the temperature-nitrate relationship in the coastal upwelling domain of the California Current
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DOI：
10.1002/jgrc.20216
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发表时间：
2013-07
影响因子：
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通讯作者：
D. Palacios;E. Hazen;I. Schroeder;S. Bograd
中科院分区：
文献类型：
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作者：
D. Palacios;E. Hazen;I. Schroeder;S. Bograd
[1]鉴于硝酸盐在维持东部边界流生态系统的高初级生产力和渔业产量方面的重要性，有必要了解通过上升流过程到达真光区的这种营养物的数量。由于这样的测量不是常规可用的，我们开发了基于温度的水柱(0-200米)硝酸盐预测模型，该模型基于距离海岸50公里内的加州海流系统(30-47°N)区域的温度。预测是使用广义相加模型进行的，该模型基于1959-2004年期间收集的37,607个观测值的汇编，并用2005-2011年期间的另一组6430个观测值进行了验证。只考虑温度的模型具有相对较高的解释能力(解释偏差，D2=71.6%)，但包含重要的深度、纬度和季节偏差。将盐度和温度(D2=91.2%)结合在一起的模型修正了纬度和深度偏差，但没有季节性偏差。最好的模型包括氧气、温度和盐度(D2=96.6%)，并充分预测了硝酸盐在两个相距较远的位置(44°39.1‘N和32°54.6’N)的时间行为，略有偏差或没有偏差[均方根误差(RMSE)分别为2.39和0.40微米]。对于只有温度可用的情况，包括深度、月份和纬度作为代理协变量的模型纠正了一些偏差，但其预测技能较低(均方根误差分别为2.50和5.22μM)。这项研究的结果在上升流地区初级生产者(浮游植物、大型藻类)硝酸盐有效性的代理推导以及生物地球化学和生态系统模拟研究中具有应用价值。
[1] Given the importance of nitrate in sustaining high primary production and fishery yields in eastern boundary current ecosystems, it is desirable to know the amounts of this nutrient reaching the euphotic zone through the upwelling process. Because such measurements are not routinely available, we developed predictive models of water-column (0–200 m) nitrate based on temperature for a region of the California Current System (30–47°N) within 50 km from the coast. Prediction was done using generalized additive models based on a compilation of 37,607 observations collected over the period 1959–2004 and validated with a separate set of 6430 observations for the period 2005–2011. A temperature-only model had relatively high explanatory power (explained deviance, D2 = 71.6%) but contained important depth, latitudinal, and seasonal biases. A model incorporating salinity in addition to temperature (D2 = 91.2%) corrected for the latitudinal and depth biases but not the seasonal bias. The best model included oxygen, temperature, and salinity (D2 = 96.6%) and adequately predicted nitrate temporal behavior at two widely separated locations (44°39.1′N and 32°54.6′N) with slight or no bias [root-mean-square error (RMSE) = 2.39 and 0.40 µM, respectively). For situations when only temperature is available, a model including depth, month, and latitude as proxy covariates corrects some of the biases, but it had lower predictive skill (RMSE = 2.50 and 5.22 μM, respectively). The results of this study have applications for the proxy derivation of nitrate availability for primary producers (phytoplankton, macroalgae) in upwelling regions and for biogeochemical and ecosystem modeling studies.