|Liu, C; Berg, B; Kutsch, W; Westman, CJ; Ilvesniemi, H; Shen, X; Shen, G; Chen, X: Leaf litter nitrogen concentrations as related to climate factors in Eurasian forests, Global Ecology and Biogeography, 15, 438-444 (2006)|
ABSTRACT Aim The aim of this study is to determine the patterns of nitrogen (N) concentrations in leaf litter of forest trees as functions of climatic factors, annual average temperature (Temp, °C) and annual precipitation (Precip, dm) and of forest type (coniferous vs. broadleaf, deciduous vs. evergreen, Pinus, etc.). Location The review was conducted using data from studies across the Eurasian continent. Methods Leaf litter N concentration was compiled from 204 sets of published data (81 sets from coniferous and 123 from broadleaf forests in Eurasia). We explored the relationships between leaf litter N concentration and Temp and Precip by means of regression analysis. Leaf litter data from N2-fixing species were excluded from the analysis. Results Over the Eurasian continent, leaf litter N concentration increased with increasing Temp and Precip within functional groups such as conifers, broadleaf, deciduous, evergreen and the genus Pinus. There were highly significant linear relationships between ln(N) and Temp and Precip (P < 0.001) for all available data combined, as well as for coniferous trees, broadleaf trees, deciduous trees, evergreen trees and Pinus separately. With both Temp and Precip as independent variables in multiple regression equations, the adjusted coefficient of determination ( ) was evidently higher than in simple regressions with either Temp or Precip as independent variable. Standardized regression coefficients showed that Temp had a larger impact than Precip on litter N concentration for all groups except evergreens. The impact of temperature was particularly strong for Pinus. Conclusions The relationship between leaf litter N concentration and temperature and precipitation can be well described with simple or multiple linear regression equations for forests over Eurasia. In the context of global warming, these regression equations are useful for a better understanding and modelling of the effects of geographical and climatic factors on leaf litter N at a regional and continental scale.