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Drivers of phytoplankton and zooplankton dynamics vary spatially and temporally in estuaries due to variation in hydrodynamic exchange and residence time, complicating efforts to understand controls on food web productivity. We conducted approximately monthly (2012–2019; n = 74) longitudinal sampling at 10 fixed stations along a freshwater tidal terminal channel in the San Francisco Estuary, California, characterized by seaward to landward gradients in water residence time, turbidity, nutrient concentrations, and plankton community composition. We used multivariate autoregressive state space (MARSS) models to quantify environmental (abiotic) and biotic controls on phytoplankton and mesozooplankton biomass. The importance of specific abiotic drivers (e.g., water temperature, turbidity, nutrients) and trophic interactions differed significantly among hydrodynamic exchange zones with different mean residence times. Abiotic drivers explained more variation in phytoplankton and zooplankton dynamics than a model including only trophic interactions, but individual phytoplankton–zooplankton interactions explained more variation than individual abiotic drivers. Interactions between zooplankton and phytoplankton were strongest in landward reaches with the longest residence times and the highest zooplankton biomass. Interactions between cryptophytes and both copepods and cladocerans were stronger than interactions between bacillariophytes (diatoms) and zooplankton taxa, despite contributing less biovolume in all but the most landward reaches. Our results demonstrate that trophic interactions and their relative strengths vary in a hydrodynamic context, contributing to food web heterogeneity within estuaries at spatial scales smaller than the freshwater to marine transition. [ABSTRACT FROM AUTHOR]

The impacts of wildfire smoke on lake habitats remains unclear. We determined the metabolic response to smoke in the epi‐pelagic and two littoral habitats in Castle Lake, California. We compared light regime, gross primary production, ecosystem respiration, and net ecosystem production in years with and without smoke. During the smoke period incident ultraviolet‐B (UV‐B) radiation and photosynthetically active radiation (PAR) decreased by 53% and 28%, respectively, while the water column extinction coefficient of UV‐B and PAR increased by 20% and 18% respectively. Epi‐pelagic productivity increased during smoke cover because of decreased solar inputs. PAR values remained sufficient to saturate productivity, suggesting observed differences were primarily the result of changes in UV‐B. Littoral‐benthic productivity did not change, possibly reflecting adaptation to high‐intensity UV‐B light in these habitats. Our results highlight the importance of understanding how prolonged wildfire smoke alters the amount of energy produced from specific habitats in lakes. Plain Language Summary: Large wildfires are increasing worldwide, but the impacts of wildfire smoke on lakes are unknown. We determined how photosynthetic activity and organism's respiration respond to smoke in the offshore and nearshore habitats in a mountain lake. Smoke limited the damage to algae caused by ultraviolet‐B radiation, resulting in increased offshore photosynthesis. Photosynthesis in the nearshore habitat did not change during smoke cover, possibly because organisms in shallow habitats have adapted to the higher intensity of damaging ultraviolet‐B radiation. Our results highlight the importance of understanding how prolonged smoke conditions can alter lakes' energy flows and food webs. Key Points: Wildfire smoke reduced ultraviolet‐B and photosynthetically active radiationLake habitats respond differently to changes in light from smoke, pelagic primary production increased with no change to littoral metabolismSmoke alters energy flows with implications for food web structure in lakes [ABSTRACT FROM AUTHOR]

Mountain lakes experience extreme interannual climate variation as well as rapidly warming air temperatures, making them ideal systems to understand lake‐climate responses. Snowpack and water temperature are highly correlated in mountain lakes, but we lack a complete understanding of underlying mechanisms. Motivated by predicted declines in snowfall with future temperature increases, we investigated how surface heat fluxes and lake warming responded to variation in snowpack, ice‐off, and summer weather patterns in a high elevation lake in the Sierra Nevada, California. Ice‐off timing determined the phenology of lake exposure to solar radiation, and was the dominant mechanism linking snowpack to lake temperature. The relative importance of heat loss fluxes (longwave radiation, latent and sensible heat exchange) varied among wet and dry years. Declines in snowpack and ice cover in mountain systems will reduce variability in lake thermal responses and increase the responsiveness of lake warming to atmospheric forcing. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Lakes are connected to surrounding terrestrial habitats by reciprocal flows of energy and nutrients. We synthesize data from California's mountain lake catchments to investigate how these reciprocal subsidies change along an elevational gradient and with the introduction of a top aquatic predator. At lower elevations, well-developed terrestrial vegetation provides relatively large inputs of organic material to lakes, whereas at higher elevations, the paucity of terrestrial vegetation provides minimal organic input but allows for higher inputs of inorganic nitrogen. There are also pronounced elevational patterns in amphibians and aquatic insects, which represent important vectors for resource flows from lakes back to land. The introduction of trout can reduce this lake-to-land resource transfer, as trout consume amphibians and aquatic insects. We propose a conceptual model in which within-lake processes influence terrestrial consumers at higher elevations, while terrestrial inputs govern within-lake processes at lower elevations. This model contributes to a more general understanding of the connections between aquatic and terrestrial habitats in complex landscapes. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Fisheries & Aquatic Sciences is the property of Canadian Science Publishing and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To examine the influence of landscape characteristics and landscape position on aquatic biogeochemistry, we sampled a total of 76 lakes within 14 different lake-chains spanning the latitudinal extent of the high-elevation Sierra Nevada (California). We measured water chemistry, dissolved organic matter (DOM), nutrients, and biotic variables in study catchments that encompassed representative ranges of area (3-22 km), elevation (2,200-3,700 m.a.s.l), elevation change (50-700 m), and average slope (13°-26°). Hierarchical models were used to account for variability in biogeochemistry because they explicitly maintain the framework of lakes within individual lake-chains while accounting for variation among lake-chains. Unconditional means models, where lake-chain was a random effect, revealed significant differences among lake-chains for nearly all biogeochemical variables. Models explained 42-95% of this variability, with the majority of the variation (70%) explained by the among lake-chain component. To explore the amount of additional variation explained by lake landscape position, we added lake network number (LNN) to models. LNN explained a significant amount of additional variation (7% average) in 8 of 23 biogeochemical parameters. However, it explained more variability within individual lake-chains (75%), where among lake-chain differences did not obscure patterns. Patterns of increase with LNN were found for dissolved organic carbon and nitrogen, fluorescence of DOM, alkalinity, and bacterioplankton abundance, whereas nitrate and nitrogen to phosphorus nutrient ratios decreased. LNN explained variation because it served as a proxy for underlying catchment characteristics that changed consistently along downstream flow paths. To characterize the amount of variation explained by catchment characteristics alone, we fit a third model that included lake-chain as a random effect and landscape or lake morphometry attributes as fixed effects. Catchment characteristics explained about as much additional variation (6%) as LNN, but for substantially more biogeochemical parameters (18 out of 23). The catchment characteristics most predictive of biogeochemistry were land-cover factors delineating alpine and subalpine zones (elevation, slope, or proportions of rock or shrub cover). In general, catchment characteristics were stronger predictors of biogeochemistry than characteristics of lake morphometry, emphasizing the relative importance of landscape processes in snowmelt-dominated lake ecosystems. [ABSTRACT FROM AUTHOR]

Abstract: We used LiDAR topographic data, AVIRIS hyperspectral data, and locally measured tidal fluctuations to characterize patterns of plant distribution within a southern California salt marsh (Carpinteria Salt Marsh (CSM)). LiDAR data required ground truthing and correction before they were suitable for use. Twenty to forty percent of the uncertainty associated with LiDAR was due to variance in the elevation of the target surface, the balance was attributed to error inherent in the LiDAR system. The incidence of LiDAR penetration of plant canopy cover (i.e., registration of ground elevation) was only three percent. The depth of LiDAR penetration into the plant canopy varied according to plant species composition; plant species-specific corrections significantly improved LiDAR accuracy (58% reduction in overall uncertainty) and with the use of ground-based surveys, reduced overall RMSE to an average of 6.3 cm in vegetated areas. A supervised classification of AVIRIS data was used to generate a vegetation map with six classification types; overall classification accuracy averaged 59% with a kappa coefficient of 0.40. The vegetation classification map was overlaid with a LiDAR-based digital elevation model (DEM) to compute elevation distributions and frequencies of tidal inundation. The average elevations of the dominant plant classifications found in CSM (e.g., Salicornia virginica, Jaumea carnosa, and salt-grass mix, a mixture of multiple marsh plant species) occurred within a 17 cm range, a vertical change that resulted in a 7% difference in the period of tidal inundation. [Copyright &y& Elsevier]

We examined bacterioplankton community composition (BCC; using polymerase chain reaction-based phylogenetic fingerprinting) and the composition of dissolved organic matter (DOM; using scanning fluorometry) within lake chains in high-elevation catchments of the Sierra Nevada, California. We compared temporal BCC dynamics in two connected cirque lakes and their inlets and found that lake : inlet community similarity of both lakes declined with increasing residence time because of seasonal snowpack melting. However, for over 3 yr the headwater lake remained distinct from its inlet even during peak snowmelt (residence time <5 d), whereas the downstream lake was consistently similar to both its inlet and the upstream lake. We subsequently sampled 17 lake chains (4-8 lakes each) throughout the Sierra Nevada longitudinally to examine how landscape position and catchment characteristics influenced the similarity in BCC and DOM among lakes and their connecting streams. Headwater lakes were significantly less similar to their inlet streams than were downstream lakes. BCC was heterogeneous throughout each catchment, but headwater inlet BCC was consistently distinct from all downstream samples. In contrast, DOM exhibited a trend of increasing homogeneity as water moved downstream: upstream and downstream waters were distinct but without clear headwater outliers. The similarity in BCC and DOM between any two lakes within a chain declined with geographic distance. Our results illustrate the contrasting roles of environmental selection and dispersal in structuring bacterioplankton communities, supporting both strong within-lake environmental selection for communities distinct from terrigenous inputs and a weaker effect of geographic dispersal differentiating communities among lakes linked by advective flow. [ABSTRACT FROM AUTHOR]