Abstract Over the last decade, an increase of gastrointestinal illness due to Vibrio parahaemolyticus in the consumption of raw shellfish has been reported in multiple regions around the United States. Studies mainly attribute this increase to rising sea surface temperatures and prolonged warm seasons in the mid-latitudes. Historically, temperature has been the main environmental determinant used to predict V. parahaemolyticus concentrations in shellfish and surface water. However, studies using in situ sampling campaigns have shown that additional water quality parameters can be useful in predicting the bacterium. While the time and cost of obtaining in situ samples throughout the Chesapeake Bay at regular time intervals can exceed available resources, satellite remote sensing has the potential to provide predictions at higher temporal and spatial resolutions. This study uses satellite ocean color remote sensing and sea surface temperature (SST) from the Moderate Resolution Imaging Spectroradiometer (MODIS) to investigate the utility of remotely sensed information for Vibrio parahaemolyticus predictions in the Chesapeake Bay and whether additional remotely sensed information can improve predictions over conventional SST-based models. We find that the addition of remotely sensed salinity, total suspended solids, and chlorophyll-a generally improves presence and abundance predictions compared to SST-only models. Models using remote sensing reflectances and SST also show potential for V. parahaemolyticus predictions, which could bypass the intermediary step of deriving water quality products from reflectances. Remotely sensed ocean color products and SST from one week prior to in situ V. parahaemolyticus measurements are evaluated and shown to be useful in bacterium predictions, which could provide lead-time for management decisions. The forecast models using ocean color products in addition to SST showed improvement over SST-only forecast models. The results of this study suggest that remote sensing can be a valuable tool to aid in higher resolution V. parahaemolyticus predictions and forecasts in the Chesapeake Bay, particularly when multiple environmental predictors are employed. However, the complexities of using remotely sensed data for ecological modeling applications and evaluating model performance also highlight the need for more research in this area.

中文翻译：

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切萨皮克湾副溶血性弧菌遥感预测和预报模型评价

摘要 在过去的十年中，美国多个地区报道了食用生贝类中副溶血性弧菌引起的胃肠道疾病增加。研究主要将这种增加归因于中纬度地区海面温度上升和暖季延长。从历史上看，温度一直是用于预测贝类和地表水中副溶血性弧菌浓度的主要环境决定因素。然而，使用原位采样活动的研究表明，额外的水质参数可用于预测细菌。虽然在整个切萨皮克湾定期获取原位样本的时间和成本可能超过可用资源，卫星遥感有可能以更高的时间和空间分辨率提供预测。本研究使用中分辨率成像光谱仪 (MODIS) 的卫星海洋颜色遥感和海面温度 (SST) 来研究遥感信息对切萨皮克湾副溶血性弧菌预测的效用，以及额外的遥感信息是否可以改善预测传统的基于 SST 的模型。我们发现，与仅使用 SST 的模型相比，添加遥感盐度、总悬浮固体和叶绿素 a 通常可以改善存在和丰度预测。使用遥感反射率和 SST 的模型也显示了副溶血性弧菌预测的潜力，这可以绕过从反射率导出水质产品的中间步骤。对原位副溶血性弧菌测量前一周的遥感海洋颜色产品和 SST 进行评估，并证明其可用于细菌预测，这可以为管理决策提供提前期。除 SST 外，使用海洋颜色产品的预测模型比仅使用 SST 的预测模型有所改进。这项研究的结果表明，遥感可以成为一种有价值的工具，有助于在切萨皮克湾进行更高分辨率的副溶血性弧菌预测和预报，尤其是在使用多个环境预测因子时。然而，