Showing papers by "Yasuhiro Yamanaka published in 2010"

Ocean ecosystem responses to future global change scenarios: A way forward

Abstract: The overall aim of GLOBEC was ‘To advance our understanding of the structure and functioning of the global ocean ecosystem, its major subsystems, and its response to physical forcing so that a capability can be developed to forecast the responses of the marine ecosystem to global change’. GLOBEC specifi ed four objectives, and objective 3 was ‘To determine the impacts of global change on stock dynamics using coupled physical, biological, and chemical models linked to appropriate observation systems and to develop the capability to project future impacts’. During the GLOBEC era, earth observational networks were developed such as the Global Climate Observing System (GCOS), which includes the Global Ocean Observing System (GOOS). Although imperfect, this global observational network is providing an unprecedented view of climate change in the earth system, and has increased our understanding tremendously over the past several decades. An increasing number of independent observations of the atmosphere, land, cryosphere, and ocean are providing a consistent picture of a warming world. Such multiple lines of evidence, the physical consistency among them, and the consistency of fi ndings among multiple, independent analyses, form the basis for the iconic phrase of the observations chapter in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR4, IPCC 2007a ) that the ‘warming of the climate system is unequivocal’. Moreover, the evidence is strong that, especially in recent decades, human activities have contributed to the global warming. The IPCC-AR4 additionally cautioned that further warming and changes in the global climate system will very likely emerge over the next century. The climate changes anticipated during the twenty-fi rst century have the potential to greatly affect marine ecosystems. A major challenge facing the scientifi c community is to develop modelling and data analysis approaches for determining how climate change will affect the structure and functioning of marine ecosystems. During the GLOBEC era, our understanding of ecosystem structure and dynamics has improved greatly (deYoung et al ., Chapter 5 ; Moloney et al. , Chapter 7 , both this volume), and new ecosystem modelling approaches have been developed and existing methods improved (see deYoung et al ., Chapter 5 , this volume). As we look forward, the next step is to use the knowledge gained from GLOBEC as a foundation, as we continue to develop data collection and modelling tools that can make suffi ciently confi dent projections of marine ecosystem responses to future global climate change. In this chapter, we summarize the available evidence for recent changes in climate effects in the oceans, and the status of our ability to project ecosystem responses to likely future global change.

Observational needs of dynamic green ocean models

Abstract: The numerical modelling community is an important user group of ocean observations requiring data of global coverage for model parameterisation and evaluation. Dynamic Green Ocean Models (DGOMs) are a class of ocean biogeochemistry models that represent various types of plankton with distinct functions in food webs and biogeochemical cycles. DGOMs are used to study the feedbacks between climate and ocean biogeochemistry, particularly those mediated by ecosystem dynamics that influence CO2, DMS, and N2O fluxes to and from the atmosphere. DGOMs require experimental data for the parameterization of plankton growth and loss rates and of ecological interactions, and a range of observations for their evaluation. The most urgent data needs are: (1) decadal trends in surface ocean pCO2 and subsurface O2, (2) biomass (in carbon concentration) and (3) growth rates as a function of temperature for the important plankton types, and (4) sinking flux of particulate organic carbon. A global coverage is essential to evaluate the model mean state. Repeated measurements for all seasons are most useful to evaluate the model response to environmental change. These data can be obtained by a combination of platforms, including remote sensing, repeat sections and gliders, and oceanic and atmospheric time-series stations.

Physiological acclimation by phytoplankton explains observed changes in Si and N uptake rates during the SERIES iron-enrichment experiment

Abstract: During the SERIES iron-enrichment experiment in the eastern subarctic Pacific, after addition of iron and its subsequent depletion, the Si:N drawdown ratio increased at approximately the time that diatoms became iron limited Laboratory studies have reported that this results from a decrease in the rate of N uptake together with a more moderate decrease in the rate of Si uptake for iron-limited cultures compared to iron-replete cultures However, for SERIES Boyd et al (Limnol Oceanogr 50 (2005)) reported an unexplained increase in the rate of Si uptake at the onset of iron limitation and suggested that studies of nutrient uptake kinetics should be undertaken in search of an explanation We compare the classic Michealis–Menten (MM) kinetics to the recently developed optimal uptake (OU) kinetics (the SPONGE: Smith and Yamanaka Limnol Oceanogr 52 (2007)) within a variable-composition model, which employs cell quotas for each relevant nutrient, applied to the multi-element (C, N, Si, Fe) dynamics during SERIES Using the Monte Carlo Markov Chain, we fit two versions of the model (differing only in the equations for nutrient uptake) to the available data for nutrient concentrations, chlorophyll, biogenic silica and particulate organic carbon and specific growth rates With either uptake kinetics, the model reproduces observed concentrations well for nutrients and somewhat less well for chlorophyll The different uptake kinetics yield greater differences in modeled elemental composition of phytoplankton and biomass of phytoplankton and zooplankton, which are not directly constrained by data MM kinetics cannot reproduce the observed increase in Si uptake rate as a function of the decreasing trend in concentration of silicic acid, and it predicts Si limitation throughout nearly all of the experiment after iron-fertilization In contrast, OU kinetics reproduces the increase in Si uptake rate and matches the observation-based estimate for the timing of the return to iron limitation The key assumption of the SPONGE, that uptake rates of all nutrients depend on physiological acclimation by phytoplankton as a function of the ambient concentration of the growth-limiting nutrient, was originally formulated for modeling chemostat experiments We show that it also agrees with the observations from this field experiment and provides an explanation for the increases in Si uptake rate and Si:N drawdown ratio

Effects of physical changes in the ocean on the atmospheric pCO2: glacial-interglacial cycles

Abstract: Based on LGM experiments with an atmosphere–ocean general circulation model, we systematically investigated the effects of physical changes in the ocean and induced biological effects as well on the low atmospheric CO2 concentration (pCO2) at the last glacial maximum (LGM). Numerical experiments with an oceanic carbon-cycle model showed that pCO2 was lowered by ~30 ppm in the LGM ocean. Most of the pCO2 reduction was explained by the change in CO2 solubility in the ocean due to lower sea surface temperature (SST) during the LGM. Moreover, we found that SST changes in the high-latitude Northern Atlantic could explain more than one-third of the overall change in pCO2 induced by global SST change, suggesting an important feedback between the Laurentide ice sheet and pCO2.

Relationship between Sinking Organic Matter and Minerals in the Shallow Zone of the Western Subarctic Pacific

Abstract: We used time-series sediment trap data for four major components, organic matter and ballast minerals (CaCO3, opal, and lithogenic matter) from 150, 540, and 1000 m in the western subarctic Pacific (WSAP), where opal is the predominant mineral in sinking particles, to develop four simple models for settling particles, including the “ballast model”. The ballast model is based on the concept that most of the organic matter “rain” in the deep sea is carried by the minerals. These four models are designed to simultaneously reproduce the flux of each major component of settling particles at 540 and 1000 m by using the data for each component at 150 m as initial values. Among the four models, the ballast model, which considers the sinking velocity increase with depth, was identified as the best using the Akaike information criterion as a measure of the model fit to data. This model successfully reproduced the flux of organic matter at 540 and 1000 m, indicating that the ballast model concept works well in the shallow zone of the WSAP on a seasonal timescale. This also suggests that ballast minerals not only physically protect the organic matter from degradation during the settling process but also enhance the sinking velocity and reduce the degree of decomposition.