Abstract

We investigated the causes for the seasonal and spatial variation of soil respiration in a first rotation Sitka spruce chronosequence composed of four age classes ( 10, 15, 31, and 47 year old) in Central Ireland. The study aimed at identifying easily determinable environmental parameters that explained the variation in soil respiration rates. The variation in temperature and soil water content influenced the seasonal trend observed in the spatial variability of soil respiration. The highest coefficients of variation in soil respiration were observed during autumn drought, while lower coefficients were generally observed during periods with highest soil respiration rates. On average, the sampling strategy of 30 sampling points per stand was adequate to obtain an average rate of soil respiration within 20% of its actual value at the 95% confidence level. Significantly higher soil respiration rates were observed at locations with high accumulation of organic matter and in collars established in close vicinity to tree stems. The organic layer thickness was the only variable that yielded significant regressions for explaining spatial variation in soil respiration in all the stands. Correlation analyses between the studied variables and soil respiration suggested the relative importance of heterotrophic and autotrophic components differed in their annual contribution to total soil respiration at each forest stand. Multiple regression analyses were used to assess the relative importance of primary temporal and spatial controls over soil respiration. Soil temperature and organic layer thickness explained most of the variance of soil respiration for the different sampling periods, while soil water content had a weaker effect as well as a different influence on soil respiration depending on the time of the year. The strong linear correlation between forest floor carbon and soil carbon stock further confirmed organic layer thickness as an integrative factor encompassing the effect of soil carbon pools on soil respiration. Moreover, its inclusion in the multiple regression analyses overrode the influence of both distance and fine root biomass. Overall, a multiple linear regression model driven by easily determinable environmental variables such as soil temperature, organic thickness, soil water content, soil bulk density, and soil organic carbon concentration allowed us to explain 54% of total variance of soil respiration over the different stand ages for the entire year P 0.05). Our results show that the adoption of an adequate sampling strategy, and the determination of some key environmental variables may help to explain a large proportion of total variation of soil respiration over the entire rotation length of afforested ecosystems.