By examining the area of the Sarobetsu Mire in northern Japan using ALOS/PALSAR data, we have clarified the backscattering behavior and characteristics of the L-band microwaves when used in the study of peatlands. We classified the vegetation into six categories and noted the differences in scattering intensity and incident-angle dependencies among these. The scattering intensity for HH and HV polarizations was greatest with sasa (dwarf bamboo) and reeds, and least with sphagnum. The incidentangle dependency with the HH polarization was higher for sasa and reed than for other vegetation types. Analysis of the polarization revealed that such differences among vegetation classes were reflected most clearly in the volume scattering characteristic. Applying simple and multiple regression analysis for the environmental factors of soil, hydrology, vegetation, and roughness against the backscatter coefficient, we also found stronger interrelations with soil factors such as bulk density, nitrogen and carbon content, and C/N ratio, and against the backscatter coefficient, than with either the roughness or vegetation. Based on such results, we clarified the unique scattering characteristics of peatlands in which scattering from the surface soil is more marked than that from other elements. We consequently estimated the spatial distribution of surface soil characteristics in peatland using the combined data available from L-band satellite SAR, aircraft laser (airborne LiDAR), and optical sensors.
In forested streams, surrounding riparian forests provide essential supplies of organic matter to aquatic ecosystems. We focused on two pathways of particulate organic matter inputs: direct input from upper riparian forests and indirect lateral input from bank slopes, for which there are limited quantitative data. We investigated the inputs of coarse particulate organic matter (CPOM) and carbon and nitrogen in the CPOM into the uppermost reaches of a headwater stream with steep bank slopes in Hokkaido, Japan. CPOM collected by litter traps was divided into categories (e.g., leaves, twigs) and weighed. Monthly nitrogen and carbon inputs were also estimated. The annual direct input of CPOM (ash-free dry mass) was 472 g m -2 , a common value for temperate riparian forests. The annual lateral CPOM input was 353 g m -1 and 941 g m -2 when they were converted to area base. This value surpassed the direct input. Organic matter that we could not separate from inorganic sediments contributed to the total lateral input from the bank slopes (124 g m -1 ); this organic matter contained relatively high amounts of nitrogen and carbon. At uppermost stream reaches, the bank slope would be a key factor to understanding the carbon and nitrogen pathways from the surrounding terrestrial ecosystem to the aquatic ecosystem.
Abstract:A windthrow refers to the uprooting and overthrowing of trees by the wind. Typhoons are a major cause of windthrows in Japan and are predicted to intensify under global warming. This study aimed to estimate the impact of climate change on windthrows and evaluate possible adaptation measures for sustainable forest management. We incorporated Typhoon Songda (2004) simulation experiments under current and pseudo-global warming (2075-2099, RCP 8.5 scenario) conditions with windthrow modelling in four natural and four artificial (Abies sachalinensis, Pinaceae) forests of Hokkaido. Unexpectedly, pseudo-global warming conditions decreased windthrow probabilities compared with current conditions for both forest types, presumably because wind speeds of the simulated typhoon weakened in Japan's high-latitude regions. Our results indicate that reconversion of artificial forests into natural forests largely decreased windthrow probability, providing a potential adaptation measure for improved forest management. To fully understand the range of climate-change effects on windthrow in Japan, future studies should use different climate scenarios and data from other typhoons, geographical regions, and forest types.
The risk of extreme events due to weather and climate change, such as winds of unprecedented magnitude, is predicted to increase throughout this century. Artificial ecosystems, such as coniferous plantation forests, can suffer irreversible deterioration due to even a slight change in environmental conditions. However, few studies have examined the effects of converting natural forests to plantations on their vulnerability to catastrophic winds. By modelling the 2004 windthrow event of Typhoon Songda in northern Japan using the random forest machine learning method, we answered two questions: do Abies plantation forests and natural mixed forests differ in their vulnerability to strong winds and how do winds, topography and forest structure affect their vulnerability. Our results show that Abies plantation forests are more vulnerable to catastrophic wind than natural mixed forests under most conditions. However, the windthrow process was common to both types of forests, and the behaviour of wind inside the forests may determine the windthrow probability. Future management options for adapting to climate change were proposed based on these findings, including modifications of plantation forest structure to reduce windthrow risk and reconversion of plantations to natural forests.
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