Marine phytoplankton account for about 50% of all global net primary productivity (NPP). Active fluorometry, mainly Fast Repetition Rate fluorometry (FRRf), has been advocated as means of providing high resolution estimates of NPP. However, not measuring CO2-fixation directly, FRRf instead provides photosynthetic quantum efficiency estimates from which electron transfer rates (ETR) and ultimately CO2-fixation rates can be derived. Consequently, conversions of ETRs to CO2-fixation requires knowledge of the electron requirement for carbon fixation (Φe,C, ETR/CO2 uptake rate) and its dependence on environmental gradients. Such knowledge is critical for large scale implementation of active fluorescence to better characterise CO2-uptake. Here we examine the variability of experimentally determined Φe,C values in relation to key environmental variables with the aim of developing new working algorithms for the calculation of Φe,C from environmental variables. Coincident FRRf and 14C-uptake and environmental data from 14 studies covering 12 marine regions were analysed via a meta-analytical, non-parametric, multivariate approach. Combining all studies, Φe,C varied between 1.15 and 54.2 mol e− (mol C)−1 with a mean of 10.9±6.91 mol e− mol C)−1. Although variability of Φe,C was related to environmental gradients at global scales, region-specific analyses provided far improved predictive capability. However, use of regional Φ e,C algorithms requires objective means of defining regions of interest, which remains challenging. Considering individual studies and specific small-scale regions, temperature, nutrient and light availability were correlated with Φ e,C albeit to varying degrees and depending on the study/region and the composition of the extant phytoplankton community. At the level of large biogeographic regions and distinct water masses, Φ e,C was related to nutrient availability, chlorophyll, as well as temperature and/or salinity in most regions, while light availability was also important in Baltic Sea and shelf waters. The novel Φ e,C algorithms provide a major step forward for widespread fluorometry-based NPP estimates and highlight the need for further studying the natural variability of Φe,C to verify and develop algorithms with improved accuracy.

Lake Victoria's ecosystem has shown fundamental changes over its past recorded history in terms of nutrient loadings, productivity, faunal composition and fisheries. As yet, however, no attempt has been made to link the driving processes of eutrophication and fisheries to understand the feedback observed in fish stocks, food webs, exploitation patterns and trade. Single-and multi-species stock assessments, based on steady-state models with effort (and/or predation) as the only driver-still used in the region to advise on management-uniformly indicate overfished stocks of Nile perch that are in danger of collapse. These current views of overfishing are not validated by empirical observations. This chapter presents a holistic integrated ecosystem approach which combines a phenomenological analysis of key processes with a comprehensive set of simple indicators, covering physical, biological and human development, where directionality in time is made explicit to understand ongoing processes in the changing ecosystem. This new approach results in: (i) no signs of overfishing in any of the verifiable indicators; and (ii) biological production increasing over time together with effort and yield as a function of increased eutrophication. The results indicate that continued eutrophication presents a much graver risk to the resource base and thus livelihoods of Lake Victoria's coastal populations than fishing pressure. Lake Victoria can serve as an interesting case study for the inherent risk of using traditional fish stock assessment in changing ecosystems, and for the development of holistic monitoring systems for ecosystem-based management.

The Carbon, Absorption, and Fluorescence Euphotic‐resolving (CAFE) net primary production model is an adaptable framework for advancing global ocean productivity assessments by exploiting state‐of‐the‐art satellite ocean color analyses and addressing key physiological and ecological attributes of phytoplankton. Here we present the first implementation of the CAFE model that incorporates inherent optical properties derived from ocean color measurements into a mechanistic and accurate model of phytoplankton growth rates (μ) and net phytoplankton production (NPP). The CAFE model calculates NPP as the product of energy absorption (QPAR), and the efficiency (ϕμ) by which absorbed energy is converted into carbon biomass (CPhyto), while μ is calculated as NPP normalized to CPhyto. The CAFE model performance is evaluated alongside 21 other NPP models against a spatially robust and globally representative set of direct NPP measurements. This analysis demonstrates that the CAFE model explains the greatest amount of variance and has the lowest model bias relative to other NPP models analyzed with this data set. Global oceanic NPP from the CAFE model (52 Pg C m−2 yr−1) and mean division rates (0.34 day−1) are derived from climatological satellite data (2002–2014). This manuscript discusses and validates individual CAFE model parameters (e.g., QPAR and ϕμ), provides detailed sensitivity analyses, and compares the CAFE model results and parameterization to other widely cited models.

Diurnal measurements of Secchi depth, light attenuation, thermal structure, photosynthetic irradiance (PE) parameters, and chlorophyll a (Chl a) were performed at weekly intervals in three inshore bays in Lake Victoria, Uganda. The only statistically significant diurnal patterns observed were a decline in PE parameters normalized to Chl a and a decline in gross integral phytoplankton production. On a weekly timescale, Chl a was positively correlated to changes in the mean water-column temperature (T WC ) in each bay. Meteorologic data in one of these bays suggest that the synchronous increases and decreases in Chl a and T WC are related to the extent of advective exchange with deeper areas of the lake. Analysis of all data from this study, as well as available historic data, reveals that the optical properties of Lake Victoria covary with the concentration of Chl a. On weekly timescales, the PE parameters a B and P BM covary, and both parameters generally decline as Chl a increases, a pattern consistent with historic data from Lake Victoria. Empirical relations are developed that relate optical properties and PE parameters to Chl a. These relations provide a mathematical representation of the limnologic changes that Lake Victoria has experienced through eutrophication and can be used to predict these parameters over larger spatial and temporal scales and facilitate estimates of whole-lake primary production.

This study presents a methods evaluation and intercalibration of active fluorescence-based measurements of the quantum yield (/ 0 PSII ) and absorption coefficient (a PSII ) of photosystem II (PSII) photochemistry. Measurements of / 0 PSII , a PSII , and irradiance (E) can be scaled to derive photosynthetic electron transport rates (P e ), the process that fuels phytoplankton carbon fixation and growth. Bio-optical estimates of / 0 PSII and a PSII were evaluated using 10 phytoplankton cultures across different pigment groups with varying bio-optical absorption characteristics on six different fast-repetition rate fluorometers that span two different manufacturers and four different models. Culture measurements of / 0 PSII and the effective absorption cross section of PSII photochemistry (r PSII , a constituent of a PSII ) showed a high degree of correspondence across instruments, although some instrument-specific biases are identified. A range of approaches have been used in the literature to estimate a PSII ðkÞ and are evaluated here. With the exception of ex situ a PSII ðkÞ estimates from paired r PSII and PSII reaction center concentration (½RCII) measurements, the accuracy and precision of in situ a PSII ðkÞ methodologies are largely determined by the variance of method-specific coefficients. The accuracy and precision of these coefficients are evaluated, compared to literature data, and discussed within a framework of autonomous P e measurements. This study supports the application of an instrument-specific calibration coefficient (K R ) that scales minimum fluorescence in the dark (F 0 ) to a PSII as both the most accurate in situ measurement of a PSII , and the methodology best suited for highly resolved autonomous P e measurements.V C 2014 Association for the Sciences of Limnology and Oceanography Improved monitoring of phytoplankton productivity (PP) is a core goal across the aquatic sciences and underpins long term management plans for coastal seas and the global ocean (European Marine Board 2013). Following the success of global ocean observatory systems such as the free-drifting Argo profilers (http://www.argo.ucsd.edu/), scientists are now looking to integrate instruments that are capable of autonomous biological rate and flux measurements into environmental sensor networks (Claustre et al. 2010). Unlike traditional in vitro photosynthetic assays, active fluorescence-based photosynthetic measurements are well suited for environmental sensor networks as many of these optical instruments can operate autonomously providing high resolution in situ photosynthesis measurements. Bio-optical models scale active fluorescence measurements to generate estimates of electron transport rates by photosystem II (P e ), whose reductant yield fuels carbon fixation and growth. The derivation of P e is shown in Eq. 1 as the product of photon irradiance (EðkÞ), the absorption coefficient of photosystem II (PSII) light-harvesting pigments (a LHII ðkÞ), and E-dependent measurements of the quantum yield of PSII pho...

Measures of the quantum efficiency of photosynthesis (f PSII ) across an irradiance (E) gradient are an increasingly common physiological assay and alternative to traditional photosynthetic-irradiance (PE) assays. Routinely, the analysis and interpretation of these data are analogous to PE measurements. Relative electron transport rates (rETR = E ¥ f PSII ) are computed and fit to a PE curve to retrieve physiologically meaningful PE parameters. This widespread approach is statistically flawed as the response variable (rETR) is explicitly dependent on the predictor variable (E). Alternatively the E-dependency of f PSII can be modeled directly while retaining the desired PE parameters by normalizing a given PE model to E. This manuscript presents a robust analysis in support of this alternative procedure. First, we demonstrate that scaling f PSII to rETR unnecessarily amplifies the measurement error of f PSII and using a Monte-Carlo analysis on synthetic data induces significantly higher uncertainty in computed PE parameters relative to modeling the E-dependency of f PSII directly. Next a large dataset is simultaneously fitted to four PE models implemented in their original and E-normalized forms. Four statistical criteria used to evaluate the efficacy of nonlinear models demonstrate improved model fits and more precise PE parameters when data are modeled as E-dependent changes in f PSII . The analysis presented in this manuscript clearly demonstrates that modeling the E-dependency of f PSII directly should be the norm for interpreting active fluorescence measures.

ABSTRACT. East Africa's Lake Victoria provides resources and services to millions of people on the lake's shores and abroad. In particular, the lake's fisheries are an important source of protein, employment, and international economic connections for the whole region. Nonetheless, stock dynamics are poorly understood and currently unpredictable. Furthermore, fishery dynamics are intricately connected to other supporting services of the lake as well as to lakeshore societies and economies. Much research has been carried out piecemeal on different aspects of Lake Victoria's system; e.g., societies, biodiversity, fisheries, and eutrophication. However, to disentangle drivers and dynamics of change in this complex system, we need to put these pieces together and analyze the system as a whole. We did so by first building a qualitative model of the lake's social-ecological system. We then investigated the model system through a qualitative loop analysis, and finally examined effects of changes on the system state and structure. The model and its contextual analysis allowed us to investigate system-wide chain reactions resulting from disturbances. Importantly, we built a tool that can be used to analyze the cascading effects of management options and establish the requirements for their success. We found that high connectedness of the system at the exploitation level, through fisheries having multiple target stocks, can increase the stocks' vulnerability to exploitation but reduce society's vulnerability to variability in individual stocks. We describe how there are multiple pathways to any change in the system, which makes it difficult to identify the root cause of changes but also broadens the management toolkit. Also, we illustrate how nutrient enrichment is not a self-regulating process, and that explicit management is necessary to halt or reverse eutrophication. This model is simple and usable to assess system-wide effects of management policies, and can serve as a paving stone for future quantitative analyses of system dynamics at local scales.

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