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Last update: 14 Dec 2007
Asian terrestrial ecosystems cover a large area characterized by a large variety in climates and ecosystem properties. No overview of the observations of ecosystem CO2 flux in this vast area, which began relatively recently, has yet been conducted. We surveyed CO2 flux observation data obtained by eddy covariance methods at 50 terrestrial sites in Asia. The measurements at most sites (44 of 50) began after 2000. The net ecosystem uptake of CO2 in boreal, temperate, and tropical Asia averaged 131, 263, and 237 g C m-2 yr-1, respectively, with large variability among sites and years; moreover, the coefficient of variation increased from boreal to tropical Asia. The spatial variability was strongly correlated with mean annual temperature: net ecosystem exchange decreased by 15 g C m-2 yr-1 for every 1 oC increase in the mean annual temperature. Our results showed that in recent years Asian terrestrial ecosystems have been a significant potential net CO2 sink and that the sink strength was largely controlled by the mean annual temperature.
To clarify the effect of global warming on marine ecosystems, we have been developing and improving a 3-D ecosystem model, COCO-NEMURO, which consists of NEMURO (North Pacific Ecosystem Model for Understanding Regional Oceanography) of PICES (North Pacific Marine Science Organization) coupled with COCO (CCSR Ocean Component Model). Hashioka and Yamanaka (2007) conducted a global warming experiment using a medium resolution version (1 x 1 degrees) of COCO-NEMURO in the western North Pacific, and they showed a significant change on seasonal variation of the lower-trophic level ecosystem. As a next step, we developed a new high-resolution version (1/4 x 1/6 degrees) of COCO-NEMURO as an offline model in collaboration with climate modelers. We are currently conducting a 20th century experiment and a global warming experiment using physical forcing from a high-resolution climate model (the CCSR/NIES/FRCGC coupled Ocean-Atmosphere GCM: K-1 model, which contributed to the IPCC-AR4 ). We will present the very early stage results of our global warming experiment.
Forest-Steppe ecotone exists along precipitation gradient in northern Mongolia. Observed at a finer scale, there exist a slope direction dependent discontinuous vegetation pattern of grassland and forest: grassland on the south slopes and Larch forest on the north slopes. This pattern has been considered to reflect the different soil wetness caused by the different conditions of solar radiations on north and south slopes. In the previous study, we modeled the dynamics of plant-soil water interactions at the slope-scale (resolution ?100m, extention:10km) and the analysis revealed the possibility of multiple, stable steady-states for a certain range of annual precipitation.
We newly incorporate the effects of livestock's grazing pressure, one of the biggest human-impacts to the vegetation in this region. The analyses show that grazing pressure generally lower and widen the precipitation range for multi-stable vegetation state. These results indicate that the area with higher grazing pressure would have higher vulnerability for climate change, such as sustained drought. A test run of the simulation model with/without heavy grazing pressure will be demonstrated based on the data from our field site.
The North Pacific is well known as one of the world’s most biologically productive regions. The quantitative assessment of phytoplankton biomass in this region is very important to estimate global primary production. Recent development of ocean color sensors such as SeaWiFS, MODIS and GLI has been accompanied by an increased effort to establish algorithms for determining ocean optical properties, phytoplankton pigments, and primary production from ocean color imagery. However, there are still some problems of in-water algorithms for ocean color sensors in the North Pacific, and bio-optical database in this region is very sparse. We carried out bio-optical measurements in the sub-arctic North Pacific from 1996 to 2004, including the sub-arctic marginal seas of the Okhotsk Sea, Bering Sea and Japan Sea. Chlorophyll a concentrations (Chl-a) and the absorption coefficients of particulate matter, phytoplankton, detritus and colored dissolved organic matter (CDOM) were also measured in seawater samples. We examined the bio-optical properties and three kinds of bio-optical algorithms,the current NASA global algorithms, OC2, OC4 and JAXA global algorithm, GLI-OC4. Our measurements show that OC2 and OC4 algorithms tend to overestimate Chl-a in the Bering Sea and underestimate Chl-a in the northwestern North Pacific. GLI-OC4 algorithm tends to overestimate Chl-a in the Bering Sea and Okhotsk Sea, and have higher accuracy in the northwestern North Pacific compared with OC2 and OC4. The overestimation of chl-a in the Bering Sea with these algorithms was considered to be caused by the higher CDOM absorption in short wavelength.
Retrospective studies of zooplankton community have revealed the lower trophic level phenology and its close relationship with water temperature anomaly in decadal scale both in the eastern and western subarctic North Pacific. Sea-saw like temperature anomaly in the eastern and western NP induced by the Aleutian Low dynamics changed peak and duration of productive season almost at the same timing but in opposite phase between the east and west. However, those studies were based on the data taken within small regions. Also, mechanisms linking climatic/environmental forcing and zooplankton phenology were unknown. In this study, we attempted to obtain basin-scale phenology pattern in the lower trophic levels using ocean color satellite remote sensing data for 1998-2006. Based on the 10 day composite of satellite Chl a data, timing and duration of spring bloom was estimated yearly for every 4 x 4 degree grid within the range of 40-60oN and 140E-120W. 3 regions were identified based on the phytoplankton seasonality (bloom timing, bloom duration, peak Chl a, and base Chl a). Interannual variation of phytoplankton phenology differed between those regions. ENSO scale variation in the timing of bloom was conspicuous in the western NP, Bering Sea and coastal Alaska. On the other hand, duration of bloom was correlated to ENSO in the eastern NP. Implication of these results on the phytoplankton phenology in the past decades will be discussed.
Currently, JAXA is operating one earth observation satellite (ALOS: DAICHI)
and two sensors (Aqua/AMSR-E and TRMM/PR).
We have studied what a satellite sensor can observe through analyses of the past and current satellite observation data (sea surface temperature, ocean color, vegetation, aerosol, cloud, precipitation .. by ADEOS-I and -II ..). From now on, we plan to contribute to the monitor and prediction of earth environment change synthetically using lineup, such as GOSAT, GCOM-W, GCOM-C, GPM, and EarthCARE.
This presentation will introduce the outline of those satellite sensors and their products, and especially some details about GCOM-C.
A global ecosystem model SEIB-DGVM was adapted to east-Siberian larch forest by incorporating empirical rules for allometry, allocation, and phenology observed at larch forests in Yakutsk, Russia Federation. Function of permafrost on soil water process was also included by simple mechanistically expressions. After calibration, the model appropriately reconstructed post fire succession pattern of forest structures and carbon cycling. It also adequately reconstructed seasonal changes of water cycling of mature larch forest. Sensibility analysis of the model showed that permafrost plays an important role for the existence of Siberian larch forest. When the model was applied to entire larch-dominated region in east Siberia, it reasonably reconstructed latitudinal gradient of LAI around Yakutsk, while it overestimated peripheral regions probably due to limitation for geographical scaling up of a model that was developed and parameterized for a specific region.
Abstract (not available)
Abstract (not available)
An internal competitive grant project of JAMSTEC, development of a greenghouse gas budget model of terrestrial ecosystems, is conducted from FY2005 to FY2007. I report the outline and current results of the project, focusing on model validation at severeal observational sites such as Takayama, Fujiyoshida, and others. Also, I discuss a strategy for scaling-up of the model to broad scales.
To improve our understanding of physical and biological impact on the carbon cycle in the Pacific Ocean in interannual to decadal time scales, the results from a numerical simulation with a physical-biogeochemical model have been diagnosed. The ecosystem processes are linked with upper ocean carbon chemistry and embedded into a three-dimensional circulation model that is forced with surface atmospheric conditions. The results for the last 55 years (1948 - 2002) in the North Pacific are focused. The modeled surface ocean at the Hawaiian Ocean Time-series (HOT) shows a shift in carbonate equilibrium to lower pH and lower saturation states of the carbonate mineral aragonite, which are consistent with the observation. Corresponding to the climate shift in the North Pacific during the mid 1970s, both natural and anthropogenic air to sea flux of CO2 increased in the Central Pacific. The responses of the upper ocean carbon cycle to this climate shift and the relation with ecosystem variability are discussed.
From this April I am working at the ESRP as a scientist of a CREST Project (co-ordinator: Drs. Yamanaka and Ishida). In my presentation, I would like to introduce my research of the last 3 or 4 years. Main topic is future projection of ecosystem change associated with global warming.
To predict effects of global warming on marine ecosystem, we developed a 3-D ecosystem model in the region around Japan, and conducted a global warming experiment. One of the key characteristics of this study is the way in which the experiment was conducted following a realistic global warming scenario IS92a of IPCC, rather than following a simple assumption limited, for example, to rising temperature. And another key characteristic is the structure of our ecosystem model. In most climate models, the marine ecosystem is represented as either a bulk formula or a simple ecosystem model to calculate the carbon cycle.
In this study, to predict the change in ecosystem structure, we used a model (NEMURO), which can explicitly represent the difference in plankton groups. In this experiment, we predicted the large changes in plankton concentrations in the subarctic-subtropical transition region in spring at the end of the 21st century. The most important thing is that, even though the increase in temperature is horizontally almost uniform in the region around Japan, as a result of interactions of the respective changes in internal physical structure, the geochemical nutrient distributions and biological plankton dynamics, the responses as the entire marine ecosystem has a larger horizontal and seasonal tendency.
Abstract (not available)
Phytoplankton make an ideal system for doing theoretical ecology. In this talk I will talk about three areas in which phytoplankton show intriguing patterns: in space, in time, and in chemical composition. In space, we focus on the vertical distribution of phytoplankton in the water column. Phytoplankton require light and nutrients to grow, but these essential resources often form contrasting gradients with depth.
We use reaction-diffusion-advection models along with game theoretical approaches to figure out how phytoplankton resolve this problem. In time, plankton communities are regularly driven away from equilibrium by the changing of the seasons. We use forced differential equation models and analytical approximations to study the dynamics of the seasonal succession of species. In chemical composition, phytoplankton nitrogen-to-phosporus (N:P) ratio varies widely depending on the conditions of growth and nutrient supply, but underlying this variability is the more conserved stoichiometry of cellular machinery within a species. We examine both these levels of variability, as well as global feedbacks that determine N:P stoichiometry of the oceans as a whole.
Phytoplankton community composition profoundly affects patterns of nutrient cycling and the dynamics of marine food webs; therefore predicting present and future phytoplankton community structure is crucial to understand how ocean ecosystems respond to physical forcing and nutrient limitations. We develop a mechanistic model of phytoplankton communities that includes multiple taxonomic groups (diatoms, coccolithophores and prasinophytes), nutrients (nitrate, ammonium, phosphate, silicate and iron), light, and a generalist zooplankton grazer. Each taxonomic group was parameterized based on an extensive literature survey. We test the model at two contrasting sites in the modern ocean, the North Atlantic (North Atlantic Bloom Experiment, NABE) and subarctic North Pacific (ocean station Papa, OSP).
The model successfully predicts general patterns of community composition and succession at both sites. Sensitivity analysis revealed that the identity of the most sensitive parameters and the range of acceptable parameter values differed between the two sites. We then use the model to predict community re-organization under different global change scenarios: a later onset and extended duration of stratification, with shallower mixed layer depths due to increased greenhouse gas concentrations; increase in deep water nitrogen; decrease in deep water phosphorus and increase or decrease in iron concentration. To estimate uncertainty in our predictions, we used a Monte Carlo sampling of the parameter space where future scenarios were run using parameter combinations that produced acceptable modern day outcomes and the robustness of the predictions was determined. Based on these scenarios, our model suggests that global environmental change will inevitably alter phytoplankton community structure and potentially impact global biogeochemical cycles.
Abstract (not available)
The boreal region is home to several processes that are unique and that are both greatly affected by climate change and are likely to have big consequences for global climate. In order to understand the consequences of climate change on such processes and their role within the complex land-atmosphere interface, it is necessary to understand process behaviour both by observations and by modelling. For Earth Observation, this requires the mapping of heterogenuous properties of the surface features from satellite data, their validation and extension to appropriate spatial and temporal scales and a close integration with biospheric models.
This presentation deals with the role of Earth Observation (EO) data in studies of land surface processes in Siberia, in the frame of the European project SIBERIA-2. A large range of EO data provided by optical, passive and active microwave sensors at various spatial and temporal resolutions has been used. Illustrations will be given on the use of a) SAR data to map forest biomass, b) moderate resolution optical data to observe the effects of climate changes on vegetation phenology, c) passive microwave data to monitor changes in snow cover and in wetlands.
The observations are analysed to estimate the trends and interannual variations in the land surface cover (vegetation, snow, wetland) since the last 20 years. The observations are also used to derive processes relevant to the carbon cycle. These include the feedback mechanisms between vegetation and snow in the tundra belt; and the correspondence between remote sensing phenology dates and the start of carbon efflux and uptake, derived from in-situ CO2 measurements and atmospheric inversion data.
Abstract (not available)