亜熱帯野草地におけるリターの分解について

摘要

本実験では生態システムの中のリターの分解について亜熱帯野草地での数種イネ科牧草と野草の分解速度の季節的変化を調べるために行った.前年度に採取したセンダングサ，ススキ，パンゴラグラス，バヒアグラスの立ち枯れを地上部リターとし，センダンダサ，ススキ，パンゴラグラスの3草種については葉身部と茎部の部位別リターとして分解試験に供試した.%This experiment was carried out to examine the seasonal change of several kinds forage grass and wild grass of litter decomposition rate in subtropical native pasture on the grassland ecosystem. The litter of the above-ground used for the experiments is standing dead plants of Bidens pilosa, silver grass, pangolagrass, bahiagrass collected in the previous year. A standing dead plant as litter materials was divided lamina part and stem part, and used three grass species Bidens pilosa, silver grass, pangolagrass. Litters that range from 4 to 7 grams of each grass put in the litter bag were set in grassland. Setting litter bags in grassland were picked up every other month. There was a significant difference on the average litter decomposition rate of three grasses which are Bidens pilosa, silver grass and pangolagrass though it showed the similar tendency in seasonal changes of the litter decomposition rate of the above-ground. It was quicker decomposition rate than litter decomposition rate of the above-ground of each grass species than that of the stem, though there was one exception in pangola grass species which lamina parts were low value than stem parts from July through September. Litter decomposition rate of the lamina parts of Bidens pilosa and silvergrass were significantly faster than that of stem parts, but was not significant litter decomposition rate between lamina and stem parts of pangolagrass. There was positively correlated with difference of litter decomposition rate between lamina part and the stem parts of which were Bidens pilosa, silvergrass and pangolagrass. There was positively correlated with difference of litter decomposition rate between digestability of used grasses. It is necessary to sufficiently consider for the decomposition rate of the litter, when it constructs the simulation model by carrying out systems analysis, since it significant change in the every season.