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281.
The rivers of the world are undergoing accelerated change in the Anthropocene, and need to be managed at much broader spatial and temporal scales than before. Fluvial remote sensing now offers a technical and methodological framework that can be deployed to monitor the processes at work and to assess the trajectories of rivers in the Anthropocene. In this paper, we review research investigating past, present and future fluvial corridor conditions and processes using remote sensing and we consider emerging challenges facing fluvial and riparian research. We introduce a suite of remote sensing methods designed to diagnose river changes at reach to regional scales. We then focus on identification of channel patterns and acting processes from satellite, airborne or ground acquisitions. These techniques range from grain scales to landform scales, and from real time scales to inter-annual scales. We discuss how remote sensing data can now be coupled to catchment scale models that simulate sediment transfer within connected river networks. We also consider future opportunities in terms of datasets and other resources which are likely to impact river management and monitoring at the global scale. We conclude with a summary of challenges and prospects for remotely sensed rivers in the Anthropocene. © 2019 John Wiley & Sons, Ltd.  相似文献   
282.
A bio-energetic model, based on the DEB theory exists for the Pacific oyster Crassostrea gigas. Pouvreau et al. [Pouvreau, S., Bourles, Y., Lefebvre, S., Gangnery, A., Alunno-Bruscia, M., 2006. Application of a dynamic energy budget model to the Pacific oyster, C. gigas, reared under various environmental conditions. J. Sea Res. 56, 156–167.] successfully applied this model to oysters reared in three environments with no tide and low turbidity, using chlorophyll a concentration as food quantifier. However, the robustness of the oyster-DEB model needs to be validated in varying environments where different food quantifiers reflect the food available for oysters, as is the case in estuaries and most coastal ecosystems. We therefore tested the oyster-DEB model on C. gigas reared in an Atlantic coastal pond from January 2006 to January 2007. The model relies on two forcing variables: seawater temperature and food density monitored through various food quantifiers. Based on the high temperature range measured in this oyster pond (3–30 °C), new boundary values of the temperature tolerance range were estimated both for ingestion and respiration rates. Several food quantifiers were then tested to select the most suitable for explaining the observed growth and reproduction of C. gigas reared in an oyster pond. These were: particulate organic matter and carbon, chlorophyll a concentration and phytoplankton enumeration (expressed in cell number per litre or in cumulative cell biovolume). We conclude that when phytoplankton enumeration was used as food quantifier, the new version of oyster-DEB model presented here reproduced the growth and reproduction of C. gigas very accurately. The next step will be to validate the model under contrasting coastal environmental conditions so as to confirm the accuracy of phytoplankton enumeration as a way of representing the available food that sustains oyster growth.  相似文献   
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