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Satellite observations identify the Mongolian steppes as a hotspot of global biomass reduction, the extent of which is comparable with tropical rainforest deforestation. To conserve or restore these grasslands, the relative contributions of climate and human activities to degradation need to be understood. Here we use a recently developed 21-year (1988–2008) record of satellite based vegetation optical depth (VOD, a proxy for vegetation water content and aboveground biomass), to show that nearly all steppe grasslands in Mongolia experienced significant decreases in VOD. Approximately 60% of the VOD declines can be directly explained by variations in rainfall and surface temperature. After removing these climate induced influences, a significant decreasing trend still persists in the VOD residuals across regions of Mongolia. Correlations in spatial patterns and temporal trends suggest that a marked increase in goat density with associated grazing pressures and wild fires are the most likely non-climatic factors behind grassland degradation. [ABSTRACT FROM AUTHOR]

We analyzed measurements of net ecosystem exchange of CO2 (NEE) over 15 European forests (the EuroFlux data set) to investigate which climate and forest characteristics explain temporal and intersite variations in NEE and its components, gross primary production (GPP) and respiration (R). Informed stepwise regression was used to derive a parameter-efficient, empirical model that was consistent with process knowledge. The resulting model required seven site-specific parameters to describe flux behavior at different temporal scales as a function of radiation, temperature, and air humidity. The interpretation appeared robust despite method and data uncertainties, although the data set was probably biased toward well-watered boreal and temperate European forests. Radiation, temperature, and leaf area (through forest assimilation capacity) appear to be the main drivers of the observed temporal and intersite variation in gross primary production, ecosystem respiration, and net ecosystem exchange. [ABSTRACT FROM AUTHOR]

The net ecosystem exchange (NEE) of forests represents the balance of gross primary productivity (GPP) and respiration (R). Methods to estimate these two components from eddy covariance flux measurements are usually based on a functional relationship between respiration and temperature that is calibrated for night-time (respiration) fluxes and subsequently extrapolated using daytime temperature measurements. However, respiration fluxes originate from different parts of the ecosystem, each of which experiences its own course of temperature. Moreover, if the temperature-respiration function is fitted to combined data from different stages of biological development or seasons, a spurious temperature effect may be included that will lead to overestimation of the direct effect of temperature and therefore to overestimates of daytime respiration. We used the EUROFLUX eddy covariance data set for 15 European forests and pooled data per site, month and for conditions of low and sufficient soil moisture, respectively. We found that using air temperature (measured above the canopy) rather than soil temperature (measured 5 cm below the surface) yielded the most reliable and consistent exponential (Q10) temperature-respiration relationship. A fundamental difference in air temperature-based Q10 values for different sites, times of year or soil moisture conditions could not be established; all were in the range 1.6–2.5. However, base respiration (R0, i.e. respiration rate scaled to 0 °C) did vary significantly among sites and over the course of the year, with increased base respiration rates during the growing season. We used the overall mean Q10 of 2.0 to estimate annual GPP and R. Testing suggested that the uncertainty in total GPP and R associated with the method of separation was generally well within 15%. For the sites investigated, we found a positive relationship between GPP and R, indicating that there is a latitudinal trend in NEE because the absolute decrease in GPP towards the pole is greater than in R. [ABSTRACT FROM AUTHOR]