Improving marine ecosystem models: Use of data assimilation and mesocosm experiments

Our inability to accurately model marine food webs severely limits the prognostic capabilities of current generation marine biogeochemistry models. To address this problem we examine the use of data assimilation and mesocosm experiments to facilitate the development of food web models. The components of the data assimilation demonstrated include the construction of measurement models, the adjoint technique to obtain gradient information on the objective function, the use of parameter constraints, incorporation of discrete measurements and assessing parameter observability. We also examine the effectiveness of classic and contemporary optimization routines used in data assimilation. A standard compartment-type food web model is employed with an emphasis on organic matter production and consumption. Mesocosm experiments designed to examine the interaction of inorganic nitrogen with organic matter provide the data used to constrain the model. Although we are able to obtain reasonable fits between the mesocosm data and food web model, the model lacks the robustness to be applicable across trophic gradients, such as those occurring in coastal environments. The robustness problem is due to inherent structural problems that render the model extremely sensitive to parameter values. Furthermore, parameters governing actual ecosystems are not constants, but rather vary as a function of environmental conditions and species abundance, which increases the sensitivity problem. We conclude by briefly discussing possible improvements in food web models and the need for rigorous comparisons between models and data (a modeling workbench) so that performance of competing models can be assessed. Such a workbench should facilitate systematic improvements in prognostic marine food web models

Phytoplankton temporal strategies increase entropy production in a marine food web model

We develop a trait-based model founded on the hypothesis that biological systems evolve and organize to maximize entropy production by dissipating chemical and electromagnetic potentials over longer time scales than abiotic processes by implementing temporal strategies. A marine food web consisting of phytoplankton, bacteria and consumer functional groups is used to explore how temporal strategies, or the lack there of, change entropy production in a shallow pond that receives a continuous flow of reduced organic carbon plus inorganic nitrogen and illumination from solar radiation with diel and seasonal dynamics. Results show that a temporal strategy that employs an explicit circadian clock produces more entropy than a passive strategy that uses internal carbon storage or a balanced growth strategy that requires phytoplankton to grow with fixed stoichiometry. When the community is forced to operate at high specific growth rates near 2 d-1, the optimization-guided model selects for phytoplankton ecotypes that exhibit complementary for winter versus summer environmental conditions to increase entropy production. We also present a new type of trait-based modeling where trait values are determined by maximizing entropy production rather than by random selection.Comment: 39 pp. including Supplementary Material, 6 Figure

Differences and implications in biogeochemistry from maximizing entropy production locally versus globally

In this manuscript we investigate the use of the maximum entropy production (MEP) principle for modeling biogeochemical processes that are catalyzed by living systems. Because of novelties introduced by the MEP approach, many questions need to be answered and techniques developed in the application of MEP to describe biological systems that are responsible for energy and mass transformations on a planetary scale. In previous work we introduce the importance of integrating entropy production over time to distinguish abiotic from biotic processes under transient conditions. Here we investigate the ramifications of modeling biological systems involving one or more spatial dimensions. When modeling systems over space, entropy production can be maximized either locally at each point in space asynchronously or globally over the system domain synchronously. We use a simple two-box model inspired by two-layer ocean models to illustrate the differences in local versus global entropy maximization. Synthesis and oxidation of biological structure is modeled using two autocatalytic reactions that account for changes in community kinetics using a single parameter each. Our results show that entropy production can be increased if maximized over the system domain rather than locally, which has important implications regarding how biological systems organize and supports the hypothesis for multiple levels of selection and cooperation in biology for the dissipation of free energy

Microbial Communities Are Well Adapted to Disturbances in Energy Input

Within the broader ecological context, biological communities are often viewed as stable and as only experiencing succession or replacement when subject to external perturbations, such as changes in food availability or the introduction of exotic species. Our findings indicate that microbial communities can exhibit strong internal dynamics that may be more important in shaping community succession than external drivers. Dynamic “unstable” communities may be important for ecosystem functional stability, with rare organisms playing an important role in community restructuring. Understanding the mechanisms responsible for internal community dynamics will certainly be required for understanding and manipulating microbiomes in both host-associated and natural ecosystems. Although microbial systems are well suited for studying concepts in ecological theory, little is known about how microbial communities respond to long-term periodic perturbations beyond diel oscillations. Taking advantage of an ongoing microcosm experiment, we studied how methanotrophic microbial communities adapted to disturbances in energy input over a 20-day cycle period. Sequencing of bacterial 16S rRNA genes together with quantification of microbial abundance and ecosystem function were used to explore the long-term dynamics (510 days) of methanotrophic communities under continuous versus cyclic chemical energy supply. We observed that microbial communities appeared inherently well adapted to disturbances in energy input and that changes in community structure in both treatments were more dependent on internal dynamics than on external forcing. The results also showed that the rare biosphere was critical to seeding the internal community dynamics, perhaps due to cross-feeding or other strategies. We conclude that in our experimental system, internal feedbacks were more important than external drivers in shaping the community dynamics over time, suggesting that ecosystems can maintain their function despite inherently unstable community dynamics. IMPORTANCE Within the broader ecological context, biological communities are often viewed as stable and as only experiencing succession or replacement when subject to external perturbations, such as changes in food availability or the introduction of exotic species. Our findings indicate that microbial communities can exhibit strong internal dynamics that may be more important in shaping community succession than external drivers. Dynamic “unstable” communities may be important for ecosystem functional stability, with rare organisms playing an important role in community restructuring. Understanding the mechanisms responsible for internal community dynamics will certainly be required for understanding and manipulating microbiomes in both host-associated and natural ecosystems.We are grateful for support from the National Science Foundation (grants EF-0928742 to J.J.V. and J.A.H. and OCE-1238212 to J.J.V.).S

The Road We’ve Traveled: 12 Years of Undergraduate Software Engineering at the Rochester Institute of Technology

In 1996, the Rochester Institute of Technology launched the first undergraduate software engineering program in North America. This paper briefly reviews the development of the program, and describes the program’s evolution up to the present. We illuminate both the constant aspects of the program – what we believe we got right – as well as the changes made in light of pedagogical, technological and disciplinary advances. We conclude by considering the current and future challenges for undergraduate software engineering education both at RIT and elsewhere

Diel light cycles affect phytoplankton competition in the global ocean

© The Author(s), 2022. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Tsakalakis, I., Follows, M. J., Dutkiewicz, S., Follett, C. L., & Vallino, J. J. Diel light cycles affect phytoplankton competition in the global ocean. Global Ecology and Biogeography, 31(9), (2022): 1838-1849, https://doi.org/10.1111/geb.13562.Aim Light, essential for photosynthesis, is present in two periodic cycles in nature: seasonal and diel. Although seasonality of light is typically resolved in ocean biogeochemical–ecosystem models because of its significance for seasonal succession and biogeography of phytoplankton, the diel light cycle is generally not resolved. The goal of this study is to demonstrate the impact of diel light cycles on phytoplankton competition and biogeography in the global ocean. Location Global ocean. Major taxa studied Phytoplankton. Methods We use a three-dimensional global ocean model and compare simulations of high temporal resolution with and without diel light cycles. The model simulates 15 phytoplankton types with different cell sizes, encompassing two broad ecological strategies: small cells with high nutrient affinity (gleaners) and larger cells with high maximal growth rate (opportunists). Both are grazed by zooplankton and limited by nitrogen, phosphorus and iron. Results Simulations show that diel cycles of light induce diel cycles in limiting nutrients in the global ocean. Diel nutrient cycles are associated with higher concentrations of limiting nutrients, by 100% at low latitudes (−40° to 40°), a process that increases the relative abundance of opportunists over gleaners. Size classes with the highest maximal growth rates from both gleaner and opportunist groups are favoured by diel light cycles. This mechanism weakens as latitude increases, because the effects of the seasonal cycle dominate over those of the diel cycle. Main conclusions Understanding the mechanisms that govern phytoplankton biogeography is crucial for predicting ocean ecosystem functioning and biogeochemical cycles. We show that the diel light cycle has a significant impact on phytoplankton competition and biogeography, indicating the need for understanding the role of diel processes in shaping macroecological patterns in the global ocean.Simons Collaboration on Computational Biogeochemical Modeling of Marine Ecosystems supported M.J.F. and S.D. on CBIOMES grant #549931; C.L.F. on CBIOMES grants #827829 and #553242; and J.J.V. and I.T. on CBIOMES grant #549941. The National Science Foundation supported I.T. and J.J.V. on award #1558710 and J.J.V. on awards #1637630, #1655552 and #1841599

Velopharyngeal Status of Stop Consonants and Vowels Produced by Young Children With and Without Repaired Cleft Palate at 12, 14, and 18 Months of Age: A Preliminary Analysis

The objective was to determine velopharyngeal (VP) status of stop consonants and vowels produced by young children with repaired cleft palate (CP) and typically developing (TD) children from 12 to 18 months of age

Using Maximum Entropy Production to Describe Microbial Biogeochemistry Over Time and Space in a Meromictic Pond

Determining how microbial communities organize and function at the ecosystem level is essential to understanding and predicting how they will respond to environmental change. Mathematical models can be used to describe these communities, but properly representing all the biological interactions in extremely diverse natural microbial ecosystems in a mathematical model is challenging. We examine a complementary approach based on the maximum entropy production (MEP) principle, which proposes that systems with many degrees of freedom will likely organize to maximize the rate of free energy dissipation. In this study, we develop an MEP model to describe biogeochemistry observed in Siders Pond, a phosphate limited meromictic system located in Falmouth, MA that exhibits steep chemical gradients due to density-driven stratification that supports anaerobic photosynthesis as well as microbial communities that catalyze redox cycles involving O, N, S, Fe, and Mn. The MEP model uses a metabolic network to represent microbial redox reactions, where biomass allocation and reaction rates are determined by solving an optimization problem that maximizes entropy production over time, and a 1D vertical profile constrained by an advection-dispersion-reaction model. We introduce a new approach for modeling phototrophy and explicitly represent oxygenic photoautotrophs, photoheterotrophs and anoxygenic photoautotrophs. The metabolic network also includes reactions for aerobic organoheterotrophic bacteria, sulfate reducing bacteria, sulfide oxidizing bacteria and aerobic and anaerobic grazers. Model results were compared to observations of biogeochemical constituents collected over a 24 h period at 8 depths at a single 15 m deep station in Siders Pond. Maximizing entropy production over long (3 day) intervals produced results more similar to field observations than short (0.25 day) interval optimizations, which support the importance of temporal strategies for maximizing entropy production over time. Furthermore, we found that entropy production must be maximized locally instead of globally where energy potentials are degraded quickly by abiotic processes, such as light absorption by water. This combination of field observations and modeling results indicate that natural microbial systems can be modeled by using the maximum entropy production principle applied over time and space using many fewer parameters than conventional models

(127, k, d) Reed-Solomon code with erasures: simulation and field programmable gate arrays (FPGA) design

Telecommunication applications require transmitting data with different format such as sound, video, email, measures, signalling and help contents . This leads to a growing complexity of transmitting systems and to higher and higher data rates . On reception, the system must be able to quickly detect and correct errors due to the transmission channel noise (decreasing error rate) . Error detecting-correcting codes suited to applications reduce the error rate (cyclic codes, convolutional code . . .) . This paper presents an overview of the implementation of a (127, k, d) Reed-Solomon error-correcting code with erasures . The technology used to mark on symbols is described in details here . The coding algorithm computes the codewords and marks the symbols . The decoding algorithm detects and corrects either the errors t' = t, or the erasures e' = 2* t, or a combination of the two (e' + 2 * t' < d-1). The error detection is possible for a number of erasures exceeding 2 * t . The number of rectifiable errors is t . This work is the result of the collaboration between the LICM laboratory and TDF-C2R company . Many Hamming distances of a (127, k, d) Reed-Solomon error-correcting code with erasure have been tested with measure files, simulating different real environments . Results obtained from computer simulations using diversified environment models are in good agreement with analytical results . Moreover, the core of the «(127, 121, 7) Reed-Solomon code with erasures» coder/decoder has been implemented on an ALTERA/FLEX1 OK family FPGA from a VHDL specification . This core can be used to design applications with continuous data streams .Les applications actuelles de télécommunications nécessitent la transmission de données aussi diverses que le son, la vidéo, la messagerie et les données de mesures, de signalisations et d'assistance. Cela entraîne une complexité croissante des systèmes de transmission et un débit de plus en plus élevé. A la réception, le système doit pouvoir détecter et corriger rapidement les éventuelles erreurs dues au bruit de canal (diminution du taux d'erreurs). Une des techniques pour diminuer ce taux est d'utiliser un code détecteur correcteur d'erreurs adapté à l'application (codes cycliques, code convolutif, .,). Plus spécifiquement, cet article concerne un code détecteur correcteur d'erreurs Reed-Solomon (127, k, d) avec la description complète d'une technique de marquage des symboles pour la mise en oeuvre des effacements. L'algorithme de codage calcule les mots de code et marque les symboles. L'algorithme de décodage opère soit sur les erreurs t' = t, soit sur les effacements e' = 2 * t, soit sur un panachage des deux (e' + 2 * t' ≤ d-1), t étant le nombre maximum d'erreurs corrigibles. En plus la détection des erreurs est possible pour un nombre d'effacements supérieur à 2 * t. Dans le cadre d'une étude menée conjointement entre le laboratoire LICM et TDF-C2R, plusieurs distances Hamming du code Reed-Solomon (127, k, d) ont été simulées (entre autres à partir de mesures réelles). Les résultats de simulation permettent de quantifier la valeur ajoutée concernant les effacements. De plus, la conception sur FPGA d'un code de Reed-Solomon (127, 121, 7) est étudiée afin d'implanter une fonction « codeur/décodeur avec effacements », pouvant être réutilisée lors de la synthèse d'autres applications traitant des flots de données en continu