Neural net modeling of estuarine indicators: Hindcasting phytoplankton biomass and net ecosystem production in the Neuse (North Carolina) and Trout (Florida) Rivers, USA

Phytoplankton biomass, as chlorophyll (Chl) a, and net ecosystem production (NEP), were modeled using artificial neural networks (ANNs). Chl a varied seasonally and along a saline gradient throughout the Neuse River (North Carolina). NEP was extremely dynamic in the Trout River (Florida), with phototrophic or heterotrophic conditions occurring over short-term intervals. Physical and chemical variables, arising from meteorological and hydrological conditions, created spatial and/or temporal gradients in both systems and served as interacting predictors for the trends/patterns of Chl a and NEP. ANNs outperformed comparable linear regression models and reliably modeled Chl a concentrations less than 20 μg L-1 and NEP values, denoting the apparent non-linear interactions among abiotic and indicator variables. ANNs underestimated Chl a concentrations greater than 20 μg L-1, likely due to the periodicity of data acquisition not being sufficient to generalize system variability, the designated 'lag' effect for variables not being adequate to portray estuarine flow dynamics, the exclusion of (one or more) variables that would have improved prediction, and/or an unrealistic expectation of network performance. Variables indicative of meteorological and hydrological forcing and/or proxy measurements of phytoplankton had the greatest relative impact on prediction of Chl a and NEP. Except for their predictive capability, ANNs might appear to be of limited value for ecological applications and problem solving; interpreting the absolute impact of and/or interacting relationships among network variables is intrinsically difficult. Statistical methods or 'rule extraction' algorithms that convey comprehensible network interpretation are needed prior to the routine use of ANNs in programs assessing and/or forecasting the response of biotic indicators to perturbation or for a means to discern estuarine function

Response of a Lake Michigan coastal lake to anthropogenic catchment disturbance

A paleolimnological investigation of post-European sediments in a Lake Michigan coastal lake was used to examine the response of Lower Herring Lake to anthropogenic impacts and its role as a processor of watershed inputs. We also compare the timing of this response with that of Lake Michigan to examine the role of marginal lakes as ‘early warning’ indicators of potential changes in the larger connected system and their role in buffering Lake Michigan against anthropogenic changes through biotic interactions and material trapping. Sediment geochemistry, siliceous microfossils and nutrient-related morphological changes in diatoms, identified three major trophic periods in the recent history of the lake. During deforestation and early settlement (pre-1845–1920), lake response to catchment disturbances results in localized increases in diatom abundances with minor changes in existing communities. In this early phase of disturbance, Lower Herring Lake acts as a sediment sink and a biological processor of nutrient inputs. During low-lake levels of the 1930s, the lake goes through a transitional period characterized by increased primary productivity and a major shift in diatom communities. Post-World War II (late 1940s–1989) anthropogenic disturbances push Lower Herring Lake to a new state and a permanent change in diatom community structure dominated by Cyclotella comensis . The dominance of planktonic summer diatom species associated with the deep chlorophyll maximum (DCM) is attributed to epilimnetic nutrient depletion. Declining Si:P ratios are inferred from increased sediment storage of biogenic silica and morphological changes in the silica content of Aulacoseira ambigua and Stephanodiscus niagarae . Beginning in the late 1940s, Lower Herring Lake functions as a biogeochemical processor of catchment inputs and a carbon, nutrient and silica sink. Microfossil response to increased nutrients and increased storage of biogenic silica in Lower Herring Lake and other regional embayments occur approximately 20–25 years earlier than in a nearby Lake Michigan site. Results from this study provide evidence for the role of marginal lakes and bays as nutrient buffering systems, delaying the impact of anthropogenic activities on the larger Lake Michigan system.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43091/1/10933_2004_Article_1688.pd

Primary Production in the Gulf of Mexico Coastal Waters Using Remotely Sensed Trophic Category Approach

Attempts to derive ocean-color based estimates of pigment and primary production in coastal waters have been complicated by the contributions of signals from non-pigment materials to the water leaving radiance. An ocean-color model to estimate primary production was evaluated for coastal waters of the northern Gulf of Mexico. The model utilizes C-sat, (mg m(-3)) (a variable that accounts for the pigment sensed by the satellite sensor), photosynthetically available radiation (PAR, J m(-2) day(-1)) and a parameter. psi* m(2) (g Chl)(-1), the water column chlorophyll specific cross-section for photosynthesis. C-sat and PAR were treated as variables while psi*; was a site-specific parameter in the model. The model uses the approach outlined in Morel and Berthon (1989) Limnology and Oceanography, 34, 1545-1562, but with site-specific statistical relationships to estimate the integrated pigment in the water column from C-sat and site-specific trophic categories (oligotrophic to eutrophic) based on pigment concentration in the water column. The statistical relationships perform extremely well within the ranges of C-sat and integral chlorophyll normally encountered in the coastal waters of the northern Gulf of Mexico. psi* varies between 0.054 and 0.063 m(2) (g Chi)(-1) and are comparable to values observed in other regions. The ability of the model to predict production using psi* within each of the trophic categories was demonstrated. The overall performance of the model has been encouraging for two reasons: (a) the possibility of estimating production from future ocean-color sensors, and (b) the fact that the model performs well in a dynamic coastal area

Spring Isothermal Mixing In the Great Lakes: Evidence of Nutrient Limitation and Nutrient-Light Interactions in a Suboptimal Light Environment

During the spring isothermal mixing period (April-May) in 1993-1995, photosynthesis-irradiance and growth-irradiance experiments were conducted in Lakes Erie, Huron, Michigan, and Ontario to assess light limitation. Additionally, nutrient enrichment experiments were conducted in Lake Ontario. Results from the photosynthesis-irradiance experiments suggested that phytoplankton communities in all the lakes can be either light limited or light saturated, as the threshold parameter (I-k) was similar to mean water column irradiances (mean (I) over bar(wc), ratio = 1.0). Growth-irradiance experiments also suggested the potential for light saturation; mean daily irradiance exceeded the threshold growth irradiance (I-k,I-g) in 95% of cases. Growth rates became light saturated at lower irradiances than photosynthetic rates. Evidence for a nutrient-light interaction in controlling in situ growth rates was also found in the nutrient enrichment experiments at incubation irradiances greater than or equal to (I) over bar(wc). Our results suggest that an interaction between nutrients and light is often controlling phytoplankton growth during spring mixing in the Great Lakes. The role of these nutrient-light interactions has increased in the past decade due to increased light availability in the lower lakes caused by phosphorus load reductions and the filtering activities of nonindigenous mussels