Modeling Responses of Diatom Productivity and Biogenic Silica Export to Iron Enrichment in the Equatorial Pacific Ocean

Using a three-dimensional physical-biogeochemical model, we have investigated the modeled responses of diatom productivity and biogenic silica export to iron enrichment in the equatorial Pacific, and compared the model simulation with in situ (IronEx II) iron fertilization results. In the eastern equatorial Pacific, an area of 540,000 km(2) was enhanced with iron by changing the photosynthetic efficiency and silicate and nitrogen uptake kinetics of phytoplankton in the model for a period of 20 days. The vertically integrated Chl a and primary production increased by about threefold 5 days after the start of the experiment, similar to that observed in the IronEx II experiment. Diatoms contribute to the initial increase of the total phytoplankton biomass, but decrease sharply after 10 days because of mesozooplankton grazing. The modeled surface nutrients (silicate and nitrate) and TCO(2) anomaly fields, obtained from the difference between the "iron addition'' and "ambient'' (without iron) concentrations, also agreed well with the IronEx II observations. The enriched patch is tracked with an inert tracer similar to the SF6 used in the IronEx II. The modeled depth-time distribution of sinking biogenic silica (BSi) indicates that it would take more than 30 days after iron injection to detect any significant BSi export out of the euphotic zone. Sensitivity studies were performed to establish the importance of fertilized patch size, duration of fertilization, and the role of mesozooplankton grazing. A larger size of the iron patch tends to produce a broader extent and longer-lasting phytoplankton blooms. Longer duration prolongs phytoplankton growth, but higher zooplankton grazing pressure prevents significant phytoplankton biomass accumulation. With the same treatment of iron fertilization in the model, lowering mesozooplankton grazing rate generates much stronger diatom bloom, but it is terminated by Si(OH)(4) limitation after the initial rapid increase. Increasing mesozooplankton grazing rate, the diatom increase due to iron addition stays at minimum level, but small phytoplankton tend to increase. The numerical model experiments demonstrate the value of ecosystem modeling for evaluating the detailed interaction between biogeochemical cycle and iron fertilization in the equatorial Pacific.

Comparative carbon cycle dynamics of the present and last interglacial

Changes in temperature and carbon dioxide during glacial cycles recorded in Antarctic ice cores are tightly coupled. However, this relationship does not hold for interglacials. While climate cooled towards the end of both the last (Eemian) and present (Holocene) interglacials, CO₂ remained stable during the Eemian while rising in the Holocene. We identify and review twelve biogeochemical mechanisms of terrestrial (vegetation dynamics and CO₂ fertilization, land use, wild fire, accumulation of peat, changes in permafrost carbon, subaerial volcanic outgassing) and marine origin (changes in sea surface temperature, carbonate compensation to deglaciation and terrestrial biosphere regrowth, shallow-water carbonate sedimentation, changes in the soft tissue pump, and methane hydrates), which potentially may have contributed to the CO₂ dynamics during interglacials but which remain not well quantified. We use three Earth System Models (ESMs) of intermediate complexity to compare effects of selected mechanisms on the interglacial CO₂ and δ¹³ CO₂ changes, focusing on those with substantial potential impacts: namely carbonate sedimentation in shallow waters, peat growth, and (in the case of the Holocene) human land use. A set of specified carbon cycle forcings could qualitatively explain atmospheric CO₂ dynamics from 8ka BP to the pre-industrial. However, when applied to Eemian boundary conditions from 126 to 115 ka BP, the same set of forcings led to disagreement with the observed direction of CO₂ changes after 122 ka BP. This failure to simulate late-Eemian CO₂ dynamics could be a result of the imposed forcings such as prescribed CaCO₃ accumulation and/or an incorrect response of simulated terrestrial carbon to the surface cooling at the end of the interglacial. These experiments also reveal that key natural processes of interglacial CO₂ dynamics eshallow water CaCO₃ accumulation, peat and permafrost carbon dynamics are not well represented in the current ESMs. Global-scale modeling of these long-term carbon cycle components started only in the last decade, and uncertainty in parameterization of these mechanisms is a main limitation in the successful modeling of interglacial CO₂ dynamics.

Modeling the Effects of Size on Patch Dynamics of an Inert Tracer

Mesoscale iron enrichment experiments have revealed that additional iron affects the phytoplankton productivity and carbon cycle. However, the role of initial size of fertilized patch in determining the patch evolution is poorly quantified due to the limited observational capability and complex of physical processes. Using a three-dimensional ocean circulation model, we simulated different sizes of inert tracer patches that were only regulated by physical circulation and diffusion. Model results showed that during the first few days since release of inert tracer, the calculated dilution rate was found to be a linear function with time, which was sensitive to the initial patch size with steeper slope for smaller size patch. After the initial phase of rapid decay, the relationship between dilution rate and time became an exponential function, which was also size dependent. Therefore, larger initial size patches can usually last longer and ultimately affect biogeochemical processes much stronger than smaller patches.

Investigation of the seasonality of N. pachyderma in the North Atlantic Ocean during Heinrich Stadial 1 using an ecosystem modeling approach

Fossil shells of planktonic foraminifera serve as the prime source of information on past changes in surface ocean conditions. Because the population size of planktonic foraminifera species changes throughout the year, the signal preserved in fossil shells is biased towards the conditions when species production was at its maximum. The amplitude of the potential seasonal bias is a function of the magnitude of the seasonal cycle in production. Here we use a planktonic foraminifera model coupled to an ecosystem model to investigate to what degree seasonal variations in production of the species Neogloboquadrina pachyderma may affect paleoceanographic reconstructions during Heinrich Stadial 1 (~18-15 cal. ka B.P.) in the North Atlantic Ocean. The model implies that during Heinrich Stadial 1 the maximum seasonal production occurred later in the year compared to the Last Glacial Maximum (~21-19 cal. ka B.P.) and the pre-industrial era north of 30 ºN. A diagnosis of the model output indicates that this change reflects the sensitivity of the species to the seasonal cycle of sea-ice cover and food supply, which collectively lead to shifts in the modeled maximum production from the Last Glacial Maximum to Heinrich Stadial 1 by up to six months. Assuming equilibrium oxygen isotopic incorporation in the shells of N. pachyderma, the modeled changes in seasonality would result in an underestimation of the actual magnitude of the meltwater isotopic signal recorded by fossil assemblages of N. pachyderma wherever calcification is likely to take place.

Environmental variables modeling based on remote sensing data using time series analysis: forestry and agricultural applications

En la actualidad, el seguimiento de la dinámica de los procesos medio ambientales está considerado como un punto de gran interés en el campo medioambiental. La cobertura espacio temporal de los datos de teledetección proporciona información continua con una alta frecuencia temporal, permitiendo el análisis de la evolución de los ecosistemas desde diferentes escalas espacio-temporales. Aunque el valor de la teledetección ha sido ampliamente probado, en la actualidad solo existe un número reducido de metodologías que permiten su análisis de una forma cuantitativa. En la presente tesis se propone un esquema de trabajo para explotar las series temporales de datos de teledetección, basado en la combinación del análisis estadístico de series de tiempo y la fenometría. El objetivo principal es demostrar el uso de las series temporales de datos de teledetección para analizar la dinámica de variables medio ambientales de una forma cuantitativa. Los objetivos específicos son: (1) evaluar dichas variables medio ambientales y (2) desarrollar modelos empíricos para predecir su comportamiento futuro. Estos objetivos se materializan en cuatro aplicaciones cuyos objetivos específicos son: (1) evaluar y cartografiar estados fenológicos del cultivo del algodón mediante análisis espectral y fenometría, (2) evaluar y modelizar la estacionalidad de incendios forestales en dos regiones bioclimáticas mediante modelos dinámicos, (3) predecir el riesgo de incendios forestales a nivel pixel utilizando modelos dinámicos y (4) evaluar el funcionamiento de la vegetación en base a la autocorrelación temporal y la fenometría. Los resultados de esta tesis muestran la utilidad del ajuste de funciones para modelizar los índices espectrales AS1 y AS2. Los parámetros fenológicos derivados del ajuste de funciones permiten la identificación de distintos estados fenológicos del cultivo del algodón. El análisis espectral ha demostrado, de una forma cuantitativa, la presencia de un ciclo en el índice AS2 y de dos ciclos en el AS1 así como el comportamiento unimodal y bimodal de la estacionalidad de incendios en las regiones mediterránea y templada respectivamente. Modelos autorregresivos han sido utilizados para caracterizar la dinámica de la estacionalidad de incendios y para predecir de una forma muy precisa el riesgo de incendios forestales a nivel pixel. Ha sido demostrada la utilidad de la autocorrelación temporal para definir y caracterizar el funcionamiento de la vegetación a nivel pixel. Finalmente el concepto “Optical Functional Type” ha sido definido, donde se propone que los pixeles deberían ser considerados como unidades temporales y analizados en función de su dinámica temporal. ix SUMMARY A good understanding of land surface processes is considered as a key subject in environmental sciences. The spatial-temporal coverage of remote sensing data provides continuous observations with a high temporal frequency allowing the assessment of ecosystem evolution at different temporal and spatial scales. Although the value of remote sensing time series has been firmly proved, only few time series methods have been developed for analyzing this data in a quantitative and continuous manner. In the present dissertation a working framework to exploit Remote Sensing time series is proposed based on the combination of Time Series Analysis and phenometric approach. The main goal is to demonstrate the use of remote sensing time series to analyze quantitatively environmental variable dynamics. The specific objectives are (1) to assess environmental variables based on remote sensing time series and (2) to develop empirical models to forecast environmental variables. These objectives have been achieved in four applications which specific objectives are (1) assessing and mapping cotton crop phenological stages using spectral and phenometric analyses, (2) assessing and modeling fire seasonality in two different ecoregions by dynamic models, (3) forecasting forest fire risk on a pixel basis by dynamic models, and (4) assessing vegetation functioning based on temporal autocorrelation and phenometric analysis. The results of this dissertation show the usefulness of function fitting procedures to model AS1 and AS2. Phenometrics derived from function fitting procedure makes it possible to identify cotton crop phenological stages. Spectral analysis has demonstrated quantitatively the presence of one cycle in AS2 and two in AS1 and the unimodal and bimodal behaviour of fire seasonality in the Mediterranean and temperate ecoregions respectively. Autoregressive models has been used to characterize the dynamics of fire seasonality in two ecoregions and to forecasts accurately fire risk on a pixel basis. The usefulness of temporal autocorrelation to define and characterized land surface functioning has been demonstrated. And finally the “Optical Functional Types” concept has been proposed, in this approach pixels could be as temporal unities based on its temporal dynamics or functioning.

Simulation, Design and Analysis of Air-Breathing Combined-Cycle Engines for High Speed Propulsion

Desde la aparición del turborreactor, el motor aeróbico con turbomaquinaria ha demostrado unas prestaciones excepcionales en los regímenes subsónico y supersónico bajo. No obstante, la operación a velocidades superiores requiere sistemas más complejos y pesados, lo cual ha imposibilitado la ejecución de estos conceptos. Los recientes avances tecnológicos, especialmente en materiales ligeros, han restablecido el interés por los motores de ciclo combinado. La simulación numérica de estos nuevos conceptos es esencial para estimar las prestaciones de la planta propulsiva, así como para abordar las dificultades de integración entre célula y motor durante las primeras etapas de diseño. Al mismo tiempo, la evaluación de estos extraordinarios motores requiere una metodología de análisis distinta. La tesis doctoral versa sobre el diseño y el análisis de los mencionados conceptos propulsivos mediante el modelado numérico y la simulación dinámica con herramientas de vanguardia. Las distintas arquitecturas presentadas por los ciclos combinados basados en sendos turborreactor y motor cohete, así como los diversos sistemas comprendidos en cada uno de ellos, hacen necesario establecer una referencia común para su evaluación. Es más, la tendencia actual hacia aeronaves "más eléctricas" requiere una nueva métrica para juzgar la aptitud de un proceso de generación de empuje en el que coexisten diversas formas de energía. A este respecto, la combinación del Primer y Segundo Principios define, en un marco de referencia absoluto, la calidad de la trasferencia de energía entre los diferentes sistemas. Esta idea, que se ha estado empleando desde hace mucho tiempo en el análisis de plantas de potencia terrestres, ha sido extendida para relacionar la misión de la aeronave con la ineficiencia de cada proceso involucrado en la generación de empuje. La metodología se ilustra mediante el estudio del motor de ciclo combinado variable de una aeronave para el crucero a Mach 5. El diseño de un acelerador de ciclo combinado basado en el turborreactor sirve para subrayar la importancia de la integración del motor y la célula. El diseño está limitado por la trayectoria ascensional y el espacio disponible en la aeronave de crucero supersónico. Posteriormente se calculan las prestaciones instaladas de la planta propulsiva en función de la velocidad y la altitud de vuelo y los parámetros de control del motor: relación de compresión, relación aire/combustible y área de garganta. ABSTRACT Since the advent of the turbojet, the air-breathing engine with rotating machinery has demonstrated exceptional performance in the subsonic and low supersonic regimes. However, the operation at higher speeds requires further system complexity and weight, which so far has impeded the realization of these concepts. Recent technology developments, especially in lightweight materials, have restored the interest towards combined-cycle engines. The numerical simulation of these new concepts is essential at the early design stages to compute a first estimate of the engine performance in addition to addressing airframe-engine integration issues. In parallel, a different analysis methodology is required to evaluate these unconventional engines. The doctoral thesis concerns the design and analysis of the aforementioned engine concepts by means of numerical modeling and dynamic simulation with state-of-the-art tools. A common reference is needed to evaluate the different architectures of the turbine and the rocket-based combined-cycle engines as well as the various systems within each one of them. Furthermore, the actual trend towards more electric aircraft necessitates a common metric to judge the suitability of a thrust generation process where different forms of energy coexist. In line with this, the combination of the First and the Second Laws yields the quality of the energy being transferred between the systems on an absolute reference frame. This idea, which has been since long applied to the analysis of on-ground power plants, was extended here to relate the aircraft mission with the inefficiency of every process related to the thrust generation. The methodology is illustrated with the study of a variable- combined-cycle engine for a Mach 5 cruise aircraft. The design of a turbine-based combined-cycle booster serves to highlight the importance of the engine-airframe integration. The design is constrained by the ascent trajectory and the allocated space in the supersonic cruise aircraft. The installed performance of the propulsive plant is then computed as a function of the flight speed and altitude and the engine control parameters: pressure ratio, air-to-fuel ratio and throat area.

Modeling the Real-Time Use of Reserves in the Joint Energy and Reserve Hourly Scheduling of a Pumped Storage Plant

This paper studies the impact that different approaches of modeling the real-time use of the secondary regulation reserves have in the joint energy and reserve hourly scheduling of a price-taker pumped-storage hydropower plant. The unexpected imbalance costs due to the error between the forecasted real-time use of the reserves and the actual value are also studied and evaluated for the different approaches. The proposed methodology is applied to a daily-cycle and closed-loop pumped-storage hydropower plant. Preliminary results show that the deviations in the water volume at the end of the day are important when the percentage of the real-time use of reserves is unknown in advance, and also that the total income in all approaches after correcting these deviations is significantly lower than the maximum theoretical income.

Modeling the control of DNA replication in fission yeast

A central event in the eukaryotic cell cycle is the decision to commence DNA replication (S phase). Strict controls normally operate to prevent repeated rounds of DNA replication without intervening mitoses (“endoreplication”) or initiation of mitosis before DNA is fully replicated (“mitotic catastrophe”). Some of the genetic interactions involved in these controls have recently been identified in yeast. From this evidence we propose a molecular mechanism of “Start” control in Schizosaccharomyces pombe. Using established principles of biochemical kinetics, we compare the properties of this model in detail with the observed behavior of various mutant strains of fission yeast: wee1− (size control at Start), cdc13Δ and rum1OP (endoreplication), and wee1− rum1Δ (rapid division cycles of diminishing cell size). We discuss essential features of the mechanism that are responsible for characteristic properties of Start control in fission yeast, to expose our proposal to crucial experimental tests.

A theory for controlling cell cycle dynamics using a reversibly binding inhibitor

We demonstrate, by using mathematical modeling of cell division cycle (CDC) dynamics, a potential mechanism for precisely controlling the frequency of cell division and regulating the size of a dividing cell. Control of the cell cycle is achieved by artificially expressing a protein that reversibly binds and inactivates any one of the CDC proteins. In the simplest case, such as the checkpoint-free situation encountered in early amphibian embryos, the frequency of CDC oscillations can be increased or decreased by regulating the rate of synthesis, the binding rate, or the equilibrium constant of the binding protein. In a more complex model of cell division, where size-control checkpoints are included, we show that the same reversible binding reaction can alter the mean cell mass in a continuously dividing cell. Because this control scheme is general and requires only the expression of a single protein, it provides a practical means for tuning the characteristics of the cell cycle in vivo.

Modeling the dynamics of human hair cycles by a follicular automaton

The hair follicle cycle successively goes through the anagen, catagen, telogen, and latency phases, which correspond, respectively, to hair growth, arrest, shedding, and absence before a new anagen phase is initiated. Experimental observations collected over a period of 14 years in a group of 10 male volunteers, alopecic and nonalopecic, allowed us to determine the characteristics of scalp hair follicle cycles. On the basis of these observations, we propose a follicular automaton model to simulate the dynamics of human hair cycles. The automaton model is defined by a set of rules that govern the stochastic transitions of each follicle between the successive states anagen, telogen, and latency, and the subsequent return to anagen. The transitions occur independently for each follicle, after time intervals given stochastically by a distribution characterized by a mean and a variance. The follicular automaton model accounts both for the dynamical transitions observed in a single follicle and for the behavior of an ensemble of independently cycling follicles. Thus, the model successfully reproduces the evolution of the fractions of follicle populations in each of the three phases, which fluctuate around steady-state or slowly drifting values. We apply the follicular automaton model to the study of spatial patterns of follicular growth that result from a spatially heterogeneous distribution of parameters such as the mean duration of anagen phase. When considering that follicles die or miniaturize after going through a critical number of successive cycles, the model can reproduce the evolution to hair patterns similar to well known types of diffuse or androgenetic alopecia.

From patterns to processes: Phase and density dependencies in the Canadian lynx cycle

Across the boreal forest of North America, lynx populations undergo 10-year cycles. Analysis of 21 time series from 1821 to the present demonstrates that these fluctuations are generated by nonlinear processes with regulatory delays. Trophic interactions between lynx and hares cause delayed density-dependent regulation of lynx population growth. The nonlinearity, in contrast, appears to arise from phase dependencies in hunting success by lynx through the cycle. Using a combined approach of empirical, statistical, and mathematical modeling, we highlight how shifts in trophic interactions between the lynx and the hare generate the nonlinear process primarily by shifting functional response curves during the increase and the decrease phases.

Some examples of modeling in chemical engineering: thermal treatment of polymers, phase equilibrium calculations and process design

Presentation submitted to PSE Seminar, Chemical Engineering Department, Center for Advanced Process Design-making (CAPD), Carnegie Mellon University, Pittsburgh (USA), October 2012.

Logical Modeling and Dynamical Analysis of Cellular Networks

The logical (or logic) formalism is increasingly used to model regulatory and signaling networks. Complementing these applications, several groups contributed various methods and tools to support the definition and analysis of logical models. After an introduction to the logical modeling framework and to several of its variants, we review here a number of recent methodological advances to ease the analysis of large and intricate networks. In particular, we survey approaches to determine model attractors and their reachability properties, to assess the dynamical impact of variations of external signals, and to consistently reduce large models. To illustrate these developments, we further consider several published logical models for two important biological processes, namely the differentiation of T helper cells and the control of mammalian cell cycle.

Evolution of the stable carbon isotope composition of atmospheric CO₂ over the last glacial cycle

We present new δ¹³C measurements of atmospheric CO₂ covering the last glacial/interglacial cycle, complementing previous records covering Terminations I and II. Most prominent in the new record is a significant depletion in δ¹³C(atm) of 0.5‰ occurring during marine isotope stage (MIS) 4, followed by an enrichment of the same magnitude at the beginning of MIS 3. Such a significant excursion in the record is otherwise only observed at glacial terminations, suggesting that similar processes were at play, such as changing sea surface temperatures, changes in marine biological export in the Southern Ocean (SO) due to variations in aeolian iron fluxes, changes in the Atlantic meridional overturning circulation, upwelling of deep water in the SO, and long-term trends in terrestrial carbon storage. Based on previous modeling studies, we propose constraints on some of these processes during specific time intervals. The decrease in δ¹³C(atm) at the end of MIS 4 starting approximately 64 kyr B.P. was accompanied by increasing [CO₂]. This period is also marked by a decrease in aeolian iron flux to the SO, followed by an increase in SO upwelling during Heinrich event 6, indicating that it is likely that a large amount of δ¹³C-depleted carbon was transferred to the deep oceans previously, i.e., at the onset of MIS 4. Apart from the upwelling event at the end of MIS 4 (and potentially smaller events during Heinrich events in MIS 3), upwelling of deep water in the SO remained reduced until the last glacial termination, whereupon a second pulse of isotopically light carbon was released into the atmosphere.

Do open-cycle hatcheries relying on tourism conserve sea turtles? Sri Lankan developments and economic-ecological considerations

By combining economic analysis of markets with ecological parameters, this article considers the role that tourism-based sea turtle hatcheries (of an open-cycle type) can play in conserving populations of sea turtles. Background is provided on the nature and development of such hatcheries in Sri Lanka. The modeling facilitates the assessment of the impacts of turtle hatcheries on the conservation of sea turtles and enables the economic and ecological consequences of tourism, based on such hatcheries, to be better appreciated. The results demonstrate that sea turtle hatcheries serving tourists can make a positive contribution to sea turtle conservation, but that their conservation effectiveness depends on the way they are managed. Possible negative effects are also identified. Economic market models are combined with turtle population survival relationships to predict the conservation impact of turtle hatcheries and their consequence for the total economic value obtained from sea turtle populations.