Modelers often need to quantify the rates at which zooplankton consume a variety of species, size classes and trophic types. Implicit in the equations used to describe the multiple resource functional response (i.e. how nutritional intake varies with resource densities) are assumptions that are not often stated, let alone tested. This is problematic because models are sensitive to the details of these formulations. Here, we enable modelers to make more informed decisions by providing them with a new framework for considering zooplankton feeding on multiple resources. We define a new classification of multiple resource responses that is based on preference, selection and switching, and we develop a set of mathematical diagnostics that elucidate model assumptions. We use these tools to evaluate the assumptions and biological dynamics inherent in published multiple resource responses. These models are shown to simulate different resource preferences, implied single resource responses, changes in intake with changing resource densities, nutritional benefits of generalism, and nutritional costs of selection. Certain formulations are further shown to exhibit anomalous dynamics such as negative switching and sub-optimal feeding. Such varied responses can have vastly different ecological consequences for both zooplankton and their resources; inappropriate choices may incorrectly quantify biologicallymediated fluxes and predict spurious dynamics. We discuss how our classes and diagnostics can help constrain parameters, interpret behaviors, and identify limitations to a formulation's applicability for both regional (e.g. HighNitrate-Low-Chlorophyll regions comprising large areas of the Pacific) and large-scale applications (e.g. global biogeochemical or climate change models). Strategies for assessing uncertainty and for using the mathematics to guide future experimental investigations are also discussed. r

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The Black Sea is a permanently anoxic basin with a well-defined redox gradient. We combine environmental 16S rRNA gene data from clone libraries, terminal restriction fragment length polymorphisms, and V6 hypervariable region pyrosequences to provide the most detailed bacterial survey to date. Furthermore, this data set is informed by comprehensive geochemical data; using this combination of information, we put forward testable hypotheses regarding possible metabolisms of uncultured bacteria from the Black Sea's suboxic zone (microaerophily, nitrate reduction, manganese cycling, and oxidation of methane, ammonium, and sulfide). Dominant bacteria in the upper suboxic zone included members of the SAR11, SAR324, and Microthrix groups and in the deep suboxic zone included members of BS-GSO-2, Marine Group A, and SUP05. A particulate fraction (30 μm filter) was used to distinguish between free-living and aggregate-attached communities in the suboxic zone. The particulate fraction contained greater diversity of V6 tag sequences than the bulk water samples. Lentisphaera, Epsilonproteobacteria, WS3, Planctomycetes, and Deltaproteobacteria were enriched in the particulate fraction, whereas SAR11 relatives dominated the free-living fraction. On the basis of the bacterial assemblages and simple modeling, we find that in suboxic waters, the interior of sinking aggregates potentially support manganese reduction, sulfate reduction, and sulfur oxidation.

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