A Model to Predict How Individual Factors Influence Secchi Depth Variations among and within Lakes

This work presents a model to predict lake Secchi depth. It has been developed as a part of a comprehensive ecosystem model, LakeWeb. The Secchi depth model is based on a modelling technique using dimensionless moderators. It gives, e.g., weekly variations and accounts for how various factors influence Secchi depth individually in spite of the fact that many of them are interrelated in a complex manner. The model has been tested over a wide range of lakes. It gives predictions that agree well with empirical reference regressions, and also expected and requested divergences when the regressions do not provide sufficient resolution. The model is driven by the following data which are easily accessed from standard monitoring programs or maps: Total phosphorus, colour, pH, mean depth and lake area reflecting the three main processes influencing variations of Secchi depth within and among lakes, allochthonous inputs, autochthonous production and resuspension.     

Primary Productivity of Phytoplankton,Environmental Covariates and Fish Growth in West Bengal Ponds under a Polyculture System

Measurements of primary production by phytoplankton in four fish ponds over a period of one year revealed a distinct spatial variation in rate. The ponds were used for polyculture, monoculture, or a traditional system of fish culture. The rates of gross photosynthesis were highly correlated with temperature, free CO₂, oxygen, inorganic nitrogen (NH₄⁺, NO₂⁻, and NO₃⁻) and PO₄-P. It was shown by step-wise multiple regression analysis that in the polyculture pond with a predominantly autotrophic metabolism, gross photosynthesis was the most significant factor correlated with fish growth. In another polyculture system in which the metabolism was mainly hetero-trophic, the influence of the photosynthesis rate was slight.     

Increased Benthic Algal Primary Production in Response to the Invasive Zebra Mussel (Dreissena polymorpha) in a Productive Ecosystem, Oneida Lake, New York

Increased water clarity associated with zebra mussel (Dreissena polymorpha) populations may favor benthic algal primary production in freshwater systems previously dominated by pelagic phytoplankton production. While zebra mussel-mediated water clarity effects on benthic primary production have been implicated in published reports, few production estimates are available. This study estimates benthic primary production in Oneida Lake, NY before and after zebra mussel invasion (1992), using measured photosynthetic parameters ( , α^B and β) from sampled benthic algal communities. In the summers of 2003 and 2004, primary production was measured as O₂ evolution from algal communities on hard (cobble) and soft (sediment) substrate from several depths. We also backcast estimates of benthic primary production from measurements of light penetration since 1975. Estimates of whole-lake epipelic and epilithic algal primary production showed a significant (4%) increase and exhibited significantly less interannual variability subsequent to the establishment of zebra mussels. We applied our model to two lakes of differing trophic status; the model significantly overestimated benthic primary production in a hypereutrophic lake, but there was no significant difference between the actual and predicted primary production values in the oligotrophic lake. The hypereutrophic lake had higher zebra mussel densities than Oneida (224 vs. 41 per sample respectively). Though total community respiration (measured in total darkness) was factored into our model predictions of production, our model may need modification when heterotrophic respiration is a large portion of total community metabolism.     

Responses of CO2 Exchange and Primary Production of the Ecosystem Components to Environmental Changes in a Mountain Peatland

The complexity of natural ecological systems presents challenges for predicting the impact of global environmental changes on ecosystem structure and function. Grouping of plants into functional types, that is, groups of species sharing traits that govern their mechanisms of response to environmental perturbations, reduce the complexity of species diversity to a few key plant types for better understanding of ecosystem responses. Chambers were used to measure CO₂ exchange in grass and moss growing together in a mountain peatland in southern Germany to assess variations in their response to environmental changes and how they influence ecosystem CO₂ exchange. Parameter fits and comparison for net ecosystem exchange (NEE) in two ecosystem components were conducted using an empirical hyperbolic light response model. Annual green biomass production was 320 and 210 g dwt m ⁻², whereas mean maximum NEE was –10.0 and –5.0 μmol m ⁻² s ⁻¹ for grass and moss, respectively. Grass exhibited higher light use efficiency (α) and maximum gross primary production [(β+γ)₂₀₀₀]. Leaf area index explained 93% of light use and 83% of overall production by the grass. Peat temperature at 10-cm depth explained more than 80% of the fluctuations in ecosystem respiration (R _eco). Compared to grass, moss NEE was more sensitive to ground water level (GWL) draw-down and hence could be more vulnerable to changes in precipitation that result in GWL decline and may be potentially replaced by grass and other vegetation that are less sensitive. Author’s Contribution  Werner Borken conceived the study. Ai Nishiwaki, Margerete Wartinger, G. Lischeid and Zaman Hussain conducted measurements. Jan Muhr helped with the methodologies and result discussion. Dennis O. Otieno designed and conducted measurements and wrote the paper.     

Linking Belowground Carbon Allocation to Anaerobic CH4 and CO2 Production in a Forested Peatland,New York State

Heterotrophic soil microorganisms rely on carbon (C) allocated belowground in plant production, but belowground C allocation (BCA) by plants is a poorly quantified part of ecosystem C cycling, especially, in peat soil. We applied a C balance approach to quantify BCA in a mixed conifer-red maple (Acer rubrum) forest on deep peat soil. Direct measurements of CH₄ and CO₂ fluxes across the soil surface (soil respiration), production of fine and small plant roots, and aboveground litterfall were used to estimate respiration by roots, by mycorrhizae and by free-living soil microorganisms. Measurements occurred in two consecutive years. Soil respiration rates averaged 1.2 bm μmol m^{? 2} s^{? 1} for CO₂ and 0.58 nmol m^{? 2} s^{? 1} for CH₄ (371 to 403 g C m^{? 2} year^{? 1}). Carbon in aboveground litter (144 g C m^{? 2} year^{? 1}) was 84% greater than C in root production (78 g C m^{? 2} year^{? 1}). Complementary in vitro assays located high rates of anaerobic microbial activity, including methanogenesis, in a dense layer of roots overlying the peat soil and in large-sized fragments within the peat matrix. Large-sized fragments were decomposing roots and aboveground leaf and twig litter, indicating that relatively fresh plant production supported most of the anaerobic microbial activity. Respiration by free-living soil microorganisms in deep peat accounted for, at most, 29 to 38 g C m^{? 2} year^{? 1}. These data emphasize the close coupling between plant production, ecosystem-level C cycling and soil microbial ecology, which BCA can help reveal.