CAJ | 학술논문

采用Li-cor-8150土壤呼吸测定系统,对北京大兴杨树人工林(欧美107,Populus×euramericana cv."74/76")土壤CO_2释放通量、土壤温度和水分进行了为期1年(2007)的定位连续观测,系统研究土壤温度(T_S)和土壤含水量(w)对土壤呼吸速率(R_s)的影响.结果表明:(1)土壤呼吸速率日变化呈单峰曲线,具有明显的白天高,夜间低的规律.非生长季土壤呼吸速率较低,自5月份土壤呼吸速率上升,8月份达到最大值.(2)土壤温度是影响土壤呼吸速率的主要因素,用指数模型解释全年过程中土壤温度对土壤呼吸速率变化的能力为69%.在低温段(<0℃)土壤呼吸速率随土壤温度升高而下降,而在土壤温度>0℃条件下土壤呼吸速率与土壤温度表现为正相关.土壤呼吸速率随土壤含水量上升表现出先升高后降低的趋势,三次方程模拟表明土壤水分的贡献率为33%,而当土壤含水量低于9.5%时,土壤水分的贡献率上升到51%.(3)土壤温、湿度共同作用于土壤呼吸,在不同含水量区间土壤呼吸对土壤温度的响应程度不同:在4%～10%土壤含水量范围内.土壤温度与土壤呼吸的指数模型的R~2达到0.86,而在土壤水分较高或较低时,其相关系数仅为0.6.土壤温度是影响土壤呼吸速率变化的主导因素,当土壤含水量过低或过高时,土壤温度的主导作用相对减弱,土壤含水量的影响作用相对加强.土壤呼吸的温度敏感性受土壤温度区间和水分区间的综合影响,用指数模型模拟土壤温湿度对土壤呼吸的影响不能很好的模拟土壤湿度的作用,所以单一模型并不是描述土壤温湿度对土壤呼吸的共同影响的最优模型,而多种模型复合的数学模型有待进一步研究.
채용Li-cor-8150토양호흡측정계통,대북경대흥양수인공림(구미107,Populus×euramericana cv."74/76")토양CO_2석방통량、토양온도화수분진행료위기1년(2007)적정위련속관측,계통연구토양온도(T_S)화토양함수량(w)대토양호흡속솔(R_s)적영향.결과표명:(1)토양호흡속솔일변화정단봉곡선,구유명현적백천고,야간저적규률.비생장계토양호흡속솔교저,자5월빈토양호흡속솔상승,8월빈체도최대치.(2)토양온도시영향토양호흡속솔적주요인소,용지수모형해석전년과정중토양온도대토양호흡속솔변화적능력위69%.재저온단(<0℃)토양호흡속솔수토양온도승고이하강,이재토양온도>0℃조건하토양호흡속솔여토양온도표현위정상관.토양호흡속솔수토양함수량상승표현출선승고후강저적추세,삼차방정모의표명토양수분적공헌솔위33%,이당토양함수량저우9.5%시,토양수분적공헌솔상승도51%.(3)토양온、습도공동작용우토양호흡,재불동함수량구간토양호흡대토양온도적향응정도불동:재4%～10%토양함수량범위내.토양온도여토양호흡적지수모형적R~2체도0.86,이재토양수분교고혹교저시,기상관계수부위0.6.토양온도시영향토양호흡속솔변화적주도인소,당토양함수량과저혹과고시,토양온도적주도작용상대감약,토양함수량적영향작용상대가강.토양호흡적온도민감성수토양온도구간화수분구간적종합영향,용지수모형모의토양온습도대토양호흡적영향불능흔호적모의토양습도적작용,소이단일모형병불시묘술토양온습도대토양호흡적공동영향적최우모형,이다충모형복합적수학모형유대진일보연구.
Continuous half-hourly measurements of soil CO_2 efflux with Li-Cor-8150 in a polar plantation in Daxing District of Beijing between January and December 2007 were made to investigate the seasonal and diurnal dependence of soil respiration(R_s) on soil temperature(T_s) and water content(w). The results showed:(1) The diurnal variation of R_s was described as a single-peak curve, high during daytime and low during night. R_s was low during the non-growing season, but it increased from May and reached the maximum in August.(2) T_s was the main factor that influences R_s. An exponential model explained 69% of the annual R_s variation. In a low temperature environment(<0℃), R_s decreased with the increase in T_s. There was a positive correlatation between R_s and T_s when Ts >0 ℃. R_s increased ed at first and then decreased with the increase of w. A cubic model indicated that w contributed 33% of the variation of Rs. The contribution increased to 51% when wwaslower than 9.5%. T_s was also an important factor to R_s.(3) The influences of w and T_s a on R_s acted together. R_s responded to T_s differently under different w conditions. The R~2 of the exponential model between R_s and T_s reached 0.86 with w was the range of 4%-10%,; when w was too high or too low, the influence of T_s was relatively weakened, while the effect of w was relatively strengthened. We conclude that the sensitivity of R_s was affected by w and T_s in a non-linear fashion and could not be described by a exponential function. This study suggest multiple functions are needed to describe the complex relationship between Rs and environmental factors.