A 3D numerical model ¡V COHERENS has been applied to construct a coupled hydrodynamic and ecological model for studying Tapeng Bay, which is a coastal lagoon situated in southwest of Taiwan. The simulations have been carried out to study the influences and their interacting mechanisms among the tidal currents, nutrients and micro planktons in the Lagoon. Model results have been compiled for calculating the nutrient fluxes and the primary productions in the Tapeng Bay. Tapeng Bay is a semi-enclosed coastal lagoon, which has only one tidal inlet for exchanging lagoon water with the coastal currents along the Kaoping coast on the narrow shelf in southwest of Taiwan. The study area is situated in the tropical climate zone where has sunshine through out the year except the rainy days concentrated in the summer season, which is influenced by the southwest monsoon. There are several drainage channels that collect the untreated domestic sewerage and wastewater discharged from the fish farms surround the lagoon. The discharges in these channels are usually low during the dry season. The solid contained in the water are mostly settled on the channel beds. During the raining season, high discharges due to the storm rainfalls re-suspend the sediments and carry into the lagoon. These sediments, which contain high concentrations of suspended solids and nutrients, cause the Bay water highly eutrophied. Therefore, the Bay is fully influenced by the seasonal variations. There are a lot of aquaculture, i.e. oyster farming and fish cage, in the Bay area since the water is calm and rich. But the balance between the nature and the anthropogenic disturbance is breaking. Besides the water level variation generated from the tidal inlet, the fresh water inflow from 3 major channels are included in the model to simulate their influences to the hydrodynamics and the density driven circulation due to changing salinities and temperatures from these inlets. Plankton, detritus, dissolved nutrients and dissolved oxygen is taking into account as the model variables for this marine eco-system. The plankton growth is mainly generated due to temperature, light intensity and nutrient level. Only the nitrogen cycle has been considered in the model by assuming there are enough supply of phosphate and silicate. Model runs have been carried out according to different seasonal situations of the boundary conditions. Furthermore, climates (heats, lights, winds, etc) are also included in the model to distinct seasonal characteristics. It is shown, from the model results, that the currents mainly dominate the distribution of nutrients in the Tapeng Bay. The nutrient level controls plankton growth. The nutrient sources are mainly coming from the coastal currents (through tidal inlet) in the wintertime, whereas the summer source was from the drainage channels due to the wash out by the high discharge rates. Beside these, dissolved oxygen concentrations in the Bay water are strongly influenced by the plankton growth rate, faster the photosynthesis higher the DO concentrations. The eutrophication levels of the Tapeng Bay water have been compiled using the plankton carbon level modeled at various situations. According to the Nixon standard (1995), Tapeng Bay has eutrophication through out the year. Mesotrophic condition can be observed during the wintertime, whereas the hypereutrophic level can be concluded during the raining season.

<p>The hypothetical assumption that chloride is conservative in the soil has been debated for the last decade. The results of the recent years of study in chlorine biogeochemistry show that chloride is non-conservative but rather participates in complex biogeochemical reactions in the soil. These interactions in nature inform the development of simplified hydrochemical model of chloride dynamics in the soil that is driven on soil routine component of HBV hydrological model. This novel attempt affords the opportunity to explore chlorine biogeochemistry further by evaluating the biological processes such as microbial biomass that predominate chlorine cycles in the same order of magnitude as earlier studied abiotic factors. Data from soil lysimeter experiment with different inputs treatments were used in the calibration and validation of both the hydrological and biogeochemical model. The results show that (1) model efficiency reduces with decreasing water residence and with increasing soil organic matter. (2) Longer water residence time (low water input), high chloride and high nitrogen input loads relatively enhance maximum biomass accumulation in a shorter time span. (3) Chloride retention time reduces with increasing chloride loads under short water residence. (4) Microbial biomass growth rate is highest under high chloride input treatments. (5) Biomass death rates shows reducing trend under short water residence (High water input). Further researches are therefore suggested for possible model expansion and to make the results of this model plausible under field conditions.</p>

The hypothetical assumption that chloride is conservative in the soil has been debated for the last decade. The results of the recent years of study in chlorine biogeochemistry show that chloride is non-conservative but rather participates in complex biogeochemical reactions in the soil. These interactions in nature inform the development of simplified hydrochemical model of chloride dynamics in the soil that is driven on soil routine component of HBV hydrological model. This novel attempt affords the opportunity to explore chlorine biogeochemistry further by evaluating the biological processes such as microbial biomass that predominate chlorine cycles in the same order of magnitude as earlier studied abiotic factors. Data from soil lysimeter experiment with different inputs treatments were used in the calibration and validation of both the hydrological and biogeochemical model. The results show that (1) model efficiency reduces with decreasing water residence and with increasing soil organic matter. (2) Longer water residence time (low water input), high chloride and high nitrogen input loads relatively enhance maximum biomass accumulation in a shorter time span. (3) Chloride retention time reduces with increasing chloride loads under short water residence. (4) Microbial biomass growth rate is highest under high chloride input treatments. (5) Biomass death rates shows reducing trend under short water residence (High water input). Further researches are therefore suggested for possible model expansion and to make the results of this model plausible under field conditions.

Numerical models are powerful and widely used tools for environmental prediction; however, any model prediction contains errors due to imperfect model parameterizations, insufficient model resolution, numerical errors, imperfect initial and boundary conditions etc. A variety of approaches is applied to quantify, correct and minimize these errors including skill assessments, bias correction and formal data assimilation. All of these require observations and benefit from comprehensive data sets. In this thesis, two aspects related to the quantification and correction of errors in biological ocean models are addressed: (i) A new bias correction method for a biological ocean model is evaluated, and (ii) a novel approach for expanding the set of typically available phytoplankton observations is assessed. The bias correction method, referred to as frequency-dependent nudging, was proposed by Thompson et al. (Ocean Modelling, 2006, 13:109-125) and is used to nudge a model only in prescribed frequencies. A desirable feature of this method is that it can preserve high frequency variability that would be dampened with conventional nudging. The method is first applied to an idealized signal consisting of a seasonal cycle and high frequency variability. In this example, frequency-dependent nudging corrected for the imposed seasonal bias without affecting the high-frequency variability. The method is then applied to a non-linear, 1 dimensional (1D) biogeochemical ocean model. Results showed that application of frequency-dependent nudging leads to better biogeochemical estimates than conventional nudging. In order to expand the set of available phytoplankton observations, light measurements from sensors attached on grey seals where assessed to determine if they provide a useful proxy of phytoplankton biomass. A controlled experiment at Bedford Basin showed that attenuation coefficient estimates from light attenuation measurements from seal tags were found to correlate significantly with chlorophyll. On the Scotian Shelf, results of the assessment indicate that seal tags can uncover spatio-temporal patterns related to phytoplankton biomass; however, more research is needed to derive absolute biomass estimates in the region.

<p>Northern peatlands (>45°N) mostly initiated during the Holocene and have been a large C sink to the atmosphere. Northern peatland formation prefers wet and cold condition where the productivity persistently exceeds decomposition and thereby C accumulates. As the northern high latitude region is likely to be warmer in the future, whether northern peatlands will continue being C sinks or switch to C sources is uncertain. To address this issue, I revise and apply a process-based model designed for describing peatland biogeochemical processes, Peatland Terrestrial Ecosystem Model (PTEM), to simulate the C dynamics at both site and regional level, from 15 ka BP-2300. For the site-level simulation, PTEM 1.0 is substantially revised into PTEM 2.0 in terms of peat accumulation process, plant functional types, productivity and decomposition, and soil thermal properties. A simulation from peat initiation to 2300 is conducted for three northern peatland sites. I found PTEM 2.0 can effectively capture the historical C accumulation progress, when compared with the observation. The future simulation indicates northern peatlands have reduced C sink capacity or switch to a C source under N insufficiency and water table deepening. </p> <p>Afterwards, a historical pan-Arctic simulation during 15ka BP-1990 is conducted. PTEM 2.0 is revised into PTEM 2.1 by adding spatially-explicit run-on and run off processes. The spatially-explicit peat initiation dataset is derived from neural network approach and a spatially-explicit peat expansion trend is established on top of it. My estimated pan-Arctic peatland C storage is 396-421 Pg C with the long-term C accumulation rate (CAR) of 22.9 g C∙m-2 yr-1. The simulated spatial distribution of peat C and the temporal pattern of CAR both agree with literature values. I analyzed northern peatlands’ response to historical climate change since 0.5 ka BP and found decreased CAR in the warmer non-permafrost and permafrost-thaw region, while the opposite was found in the colder permafrost region. The results indicate warmer southern peatlands will first switch to a C source under warming while more northern peatlands will become larger sinks. </p> <p>Based on the result of historical simulation, a future simulation is conducted for 1990-2300 with peatland expansion/shrinkage considered. PTEM 2.1 is revised into PTEM 2.2 such that the water table depth, run-on and run-off are estimated from a TOPMODEL approach. In the 21st century, northern peatlands are projected to be a C source of 1.2-13.3 Pg C under five out of six climate scenarios. During 2100-2300, northern peatlands under all scenarios are a C source under all climate scenarios. Northern peatlands switch to C sources due to deepening water table depth, insufficient N availability, and plant functional type shift. I found that northern peatlands remain as a C sink until a mean pan-Arctic peatlands annual temperature reaches -2.09 - -2.89°C. This study predicts a northern peatland sink to a source shift around 2050, earlier than previous estimates of after 2100, and emphasizes the vulnerability of northern peatlands to climate change. </p>

Devant l'intérêt croissant pour l'environnement et la conservation de la biodiversité, comprendre les principaux mécanismes des cycles biogéochimiques ayant lieu dans les écosystèmes coralliens et lagonaires est une priorité. Un modèle 3D couplé physique-biochéochimique a été mis en place sur le lagon de Nouvelle-Calédonie (NC) : un 'hot spot' de biodiversité sous l'influence de divers forçages d'origines naturelles et anthropiques.Les interactions terre-lagon ont été abordées à travers l'étude d'un événement extrême La Nina (2008) qui cause de fortes précipitations, amenant d'importants apports dans le lagon.Les résultats du modèle fournissent une vue synoptique de la réponse biogéochimique-physique du lagon, mettant en évidence que la totalité du lagon fût impacté par les apports des rivières et un hydrodynamisme plus actif, où les concentrations en chlorophylle-a ont été doublées.L'interaction complexe océan-lagon a été abordée à travers la modélisation des processus d'upwelling du Sud Ouest (SO) de la NC. Quatre étés australs ont été simulés, mettant en évidence l'importance des processus d'upwelling qui représentent un important forçage de la production primaire au SO de la NC. Une analyse lagrangienne du transport a montré que les eaux issues de l'upwelling peuvent atteindre le lagon SO sous certaines conditions, un phénomène pouvant avoir des conséquences sur le recrutement larvaire et l'enrichissement du lagon. Le modèle 3D couplé est un outil robuste pour l'étude de cet environnement très variable et complexe. Il peut représenter une aide à la décision des managers ainsi qu'un support d'analyse et de planification d'échantillonnage aux scientifiques. / In view of increasing environmental awareness and biodiversity conservation, understanding the main forcing mechanism driving biogeochemical cycles in coral reefs and lagoon coastal areas is a priority. We used a 3D coupled 'on-line' physical-biogeochemical model on the New Caledonia lagoon : a hot spot of biodiversity under several forcing from climate to human origin.Interactions between land and lagoon were investigated through the study of an extreme event La Niña (2008) that caused heavy rainfalls and large organic and inorganic inputs in the lagoon.Model results provided a synoptic view of the lagoon biogeochemical-physical response, highlighting that the whole lagoon was impacted by river inputs and stronger hydrodynamics were the chlorophyll-a concentration was almost double.The complex interaction between the ocean and the lagoon was investigated through the modeling of the South Western (SW) wind-driven upwelling. Four austral summers (2005-2008) were simulated and results were found to be in good agreement with measured data reported in previous publications, highlighting that upwelling processes represent strong drivers of the primary production in the SW of NC. A Lagrangian transport analysis showed that oceanic upwelled waters were able to reach the South West lagoon under certain conditions, representing an important issue for larvae recruitment and lagoon enrichment. The 3D coupled on-line biogeochemical-physical model was a robust tool to study such complex and highly variable environment. It could represent a support for decision makers to manage coastal areas as well as for scientists to plan sampling strategy or to analyse cruise data.

<p>Methane (CH₄) is the second most powerful greenhouse gas (GHG) behind carbon dioxide (CO₂), and is able to trap a large amount of long-wave radiation, leading to surface warming. Carbon monoxide (CO) plays an important role in controlling the oxidizing capacity of the atmosphere by reacting with OH radicals that affect atmospheric CH₄ dynamics. Terrestrial ecosystems play an important role in determining the amount of these gases into the atmosphere. However, global quantifications of CH₄ emissions from wetlands and its sinks from uplands, and CO exchanges between land and the atmosphere are still fraught with large uncertainties, presenting a big challenge to interpret complex atmospheric CH₄ dynamics in recent decades. In this dissertation, I apply modeling approaches to estimate the global CH₄ and CO exchanges between land ecosystems and the atmosphere and analyze how they respond to contemporary and future climate change.</p> <p>Firstly, I develop a process-based biogeochemistry model embedded in Terrestrial Ecosystem Model (TEM) to quantify the CO exchange between soils and the atmosphere at the global scale (Chapter 2). Parameterizations were conducted by using the CO <i>in situ</i> data for eleven representative ecosystem types. The model is then extrapolated to global terrestrial ecosystems. Globally soils act as a sink of atmospheric CO. Areas near the equator, Eastern US, Europe and eastern Asia will be the largest sink regions due to their optimum soil moisture and high temperature. The annual global soil net flux of atmospheric CO is primarily controlled by air temperature, soil temperature, SOC and atmospheric CO concentrations, while its monthly variation is mainly determined by air temperature, precipitation, soil temperature and soil moisture. </p> <p>Secondly, to better quantify the global CH₄ emissions from wetlands and their uncertainties, I revise, parameterize and verify a process-based biogeochemical model for methane for various wetland ecosystems (Chapter 3). The model is then extrapolated to the global scale to quantify the uncertainty induced from four different types of uncertainty sources including parameterization, wetland type distribution, wetland area distribution and meteorological input. Spatially, the northeast US and Amazon are two hotspots of CH₄ emissions, while consumption hotspots are in the eastern US and eastern China. The relationships between both wetland emissions and upland consumption and El Niño and La Niña events are analyzed. This study highlights the need for more in situ methane flux data, more accurate wetland type and area distribution information to better constrain the model uncertainty.</p> <p>Thirdly, to further constrain the global wetland CH₄ emissions, I develop a predictive model of CH₄ emissions using an artificial neural network (ANN) approach and available field observations of CH₄ fluxes (Chapter 4). Eleven explanatory variables including three transient climate variables (precipitation, air temperature and solar radiation) and eight static soil property variables are considered in developing the ANN models. The models are then extrapolated to the global scale to estimate monthly CH₄ emissions from 1979 to 2099. Significant interannual and seasonal variations of wetland CH₄ emissions exist in the past four decades, and the emissions in this period are most sensitive to variations in solar radiation and air temperature. This study reduced the uncertainty in global CH₄ emissions from wetlands and called for better characterizing variations of wetland areas and water table position and more long-term observations of CH₄ fluxes in tropical regions.</p> <p>Finally, in order to study a new pathway of CH₄ emissions from palm tree stem, I develop a two-dimensional diffusion model. The model is optimized using field data of methane emissions from palm tree stems (Chapter 5). The model is then extrapolated to Pastaza-Marañón foreland basin (PMFB) in Peru by using a process-based biogeochemical model. To our knowledge, this is among the first efforts to quantify regional CH₄ emissions through this pathway. The estimates can be improved by considering the effects of changes in temperature, precipitation and radiation and using long-period continuous flux observations. Regional and global estimates of CH₄ emissions through this pathway can be further constrained using more accurate palm swamp classification and spatial distribution data of palm trees at the global scale.</p>