Characterization of uptake and loss dynamics is critical to understanding risks associated with contaminant exposure in aquatic animals. Dynamics are especially important in addressing questions such as why coexisting species in nature accumulate different levels of a contaminant. Here we manipulated copper (Cu) stable isotopic ratios (as an alternative to radioisotopes) to describe for the first time Cu dynamics in a freshwater invertebrate, the bivalve Corbicula fluminea. In the laboratory, Corbicula uptake and loss rate constants were determined from an environmentally realistic waterborne exposure to 65Cu (5.7 microg L(-1)). That is, we spiked deionized water with Cu that was 99.4% 65Cu. Net tracer uptake was detectable after 1 day and strongly evident after 4 days. Thus, short-term exposures necessary to determine uptake dynamics are feasible with stable isotopes of Cu. In Corbicula, 65Cu depuration was biphasic. An unusually low rate constant of loss (0.0038 d(-1)) characterized the slow component of efflux, explaining why Corbicula strongly accumulates copper in nature. We incorporated our estimates of rate constants for dissolved 65Cu uptake and physiological efflux into a bioaccumulation model and showed that dietary exposure to Cu is likely an important bioaccumulation pathway for Corbicula.

A presumed value of shallow-habitat enhanced pelagic productivity derives from the principle that in nutrient-rich aquatic systems phytoplankton growth rate is controlled by light availability, which varies inversely with habitat depth. We measured a set of biological indicators across the gradient of habitat depth within the Sacramento-San Joaquin River Delta (California) to test the hypothesis that plankton biomass, production, and pelagic energy flow also vary systematically with habitat depth. Results showed that phytoplankton biomass and production were only weakly related to phytoplankton growth rates whereas other processes (transport, consumption) were important controls. Distribution of the invasive clam Corbicula fluminea was patchy, and heavily colonized habitats all supported low phytoplankton biomass and production and functioned as food sinks. Surplus primary production in shallow, uncolonized habitats provided potential subsidies to neighboring recipient habitats. Zooplankton in deeper habitats, where grazing exceeded phytoplankton production, were likely supported by significant fluxes of phytoplankton biomass from connected donor habitats. Our results provide three important lessons for ecosystem science: (a) in the absence of process measurements, derived indices provide valuable information to improve our mechanistic understanding of ecosystem function and to benefit adaptive management strategies; (b) the benefits of some ecosystem functions are displaced by water movements, so the value of individual habitat types can only be revealed through a regional perspective that includes connectedness among habitats; and (c) invasive species can act as overriding controls of habitat function, adding to the uncertainty of management outcomes.

We describe a large dinoflagellate bloom, unprecedented in nearly three decades of observation, that developed in San Francisco Bay (SFB) during September 2004. SFB is highly enriched in nutrients but has low summer‐autumn algal biomass because wind stress and tidally induced bottom stress produce a well mixed and light‐limited pelagic habitat. The bloom coincided with calm winds and record high air temperatures that stratified the water column and suppressed mixing long enough for motile dinoflagellates to grow and accumulate in surface waters. This event‐scale climate pattern, produced by an upper‐atmosphere high‐pressure anomaly off the U.S. west coast, followed a summer of weak coastal upwelling and high dinoflagellate biomass in coastal waters that apparently seeded the SFB bloom. This event suggests that some red tides are responses to changes in local physical dynamics that are driven by large‐scale atmospheric processes and operate over both the event scale of biomass growth and the antecedent seasonal scale that shapes the bloom community.

Although surface water quality and its underlying processes vary over time scales ranging from seconds to decades, they have historically been studied at the lower (weekly to interannual) frequencies. The aim of this study was to investigate intradaily variability of three water quality parameters in a small freshwater tidal lagoon (Mildred Island, California). High frequency time series of specific conductivity, water temperature, and chlorophyll a at two locations within the habitat were analyzed in conjunction with supporting hydrodynamic, meteorological, biological, and spatial mapping data. All three constituents exhibited large amplitude intradaily (e.g., semidiurnal tidal and diurnal) oscillations, and periodicity varied across constituents, space, and time. Like other tidal embayments, this habitat is influenced by several processes with distinct periodicities including physical controls, such as tides, solar radiation, and wind, and biological controls, such as photosynthesis, growth, and grazing. A scaling approach was developed to estimate individual process contributions to the observed variability. Scaling results were generally consistent with observations and together with detailed examination of time series and time derivatives, revealed specific mechanisms underlying the observed periodicities, including interactions between the tidal variability, heating, wind, and biology. The implications for monitoring were illustrated through subsampling of the data set. This exercise demonstrated how quantities needed by scientists and managers (e.g., mean or extreme concentrations) may be misrepresented by low frequency data and how short-duration high frequency measurements can aid in the design and interpretation of temporally coarser sampling programs. The dispersive export of chlorophyll a from the habitat exhibited a fortnightly variability corresponding to the modulation of semidiurnal tidal currents with the diurnal cycle of phytoplankton variability, demonstrating how high frequency interactions can govern long-term trends. Process identification, as through the scaling analysis here, can help us anticipate changes in system behavior and adapt our own interactions with the system.