『Abstract
Silicate weathering and resulting transport of dissolved matter
influence the global carbon cycle in two ways. First by the uptake
of atmospheric/soil CO2 and second by providing
the oceanic ecosystems via the fluvial systems with the nutrient
dissolved silica (DSi). Previous work suggests that regions dominated
by volcanics are hyperactive or even “hot spots” concerning DSi-mobilization.
Here, we present a new approach for predicting DSi-fluxes to coastal
zones, emphasizing “first-order” controlling factors (lithology,
runoff, relief, land cover and temperature). This approach is
applied to the Japanese Archipelago, a region characterized by
a high percentage of volcanics (29.1% of surface area). The presented
DSi-flux model is based on data of 516 catchments, covering approximately
56.7% of the area of the Japanese Archipelago. The spatial distribution
of lithology - one of the most important first order controls
- is taken from a new high resolution map of Japan. Results show
that the Japanese archipelago is a hyperactive region with a DSi-yield
6.6 times higher than the world average of 3.3 t SiO2
km-2 a-1, but with large regional variations.
Approximately 10% of its area exceeds 10 times the world average
DSi-yield. Slope constitutes another important controlling factor
on DSi-fluxes besides lithology and runoff, and can exceed the
influence of runoff on DSi-yields. Even though the monitored area
on the Japanese archipelago stretches from about 31゜ to 46゜N,
temperature is not identified as a significant first-order model
variable. This may be due to the fact that slope, runoff and lithology
are correlated with temperature information is substituted to
a certain extent by these factors. Land cover data also do not
improve the prediction model. This may partly be attributed to
misinterpreted land cover information from satellite images. Implications
of results for Earth System and global carbon cycle modeling are
discussed.
Keywords: Japan; Dissolved silica; Empirical model; Chemical weathering』
Introduction
Data handling and analysis techniques
Hydrochemical data and geodata handling
DSi-flux modeling technique
Results
Regional settings
Observed DSi-fluxes
Relations between proposed first-order controls and DSi-fluxes
Predicted DSi-fluxes: the control of runoff and slope
Discussion
General discussion
Discussion of model results
Error discussion
Lithology
Runoff
Hydrothermal activity
Landcover and vegetation effects
Temperature
Anthropogenic effects
Lake effects
Implications for the global carbon cycle
Conclusion
Acknowledgments
Appendix A
Appendix B
References