Characterizing scale-specific environmental factors affecting soil organic carbon along two landscape transects
Soil organic carbon (SOC) is one of the most important soil properties affecting many other soil and environmental properties and processes. In order to understand and manage SOC effectively, it is important to identify the scale-specific main factors affecting SOC distributions, which in this study occurred in a watershed on the Loess Plateau. Two transects were selected that passed along the upper slopes on each side of the main gully of the Liudaogou watershed. Transect 1 (3411-m length) had 27 sampling sites at 131-m intervals; transect 2 (3597 m length) had 30 sampling sites at 124-m intervals. The two transects were chosen in order to compare landscape patterns of differing complexity that were in close proximity, which reduced the effects of factors that would be caused by different locations. The landscape of transect 1 was more complex due to the greater diversity in cultivation. Multivariate empirical mode decomposition (MEMD) decomposed the total variation in SOC and five selected environmental factors into four intrinsic mode functions (IMFs) and a residual according to the scale of occurrence. Scale-specific correlation analysis was used to identify significant relationships between SOC and the environmental factors. The dominant scales were those that were the largest contributors to the total SOC variance; for transect 1, this was the IMF 1 (scale of 403 m), whereas for transect 2, it was the medium scale of the IMF 2 (scale of 688 m). For both transects, vegetation properties (vegetation cover and aboveground biomass) were the main factors affecting SOC distributions at their respective dominant scales. At each scale, the main effective factors could be identified although at the larger scales, their contributions to the overall variance were almost negligible. The distributions of SOC and the factors affecting it were found to be scale dependent. The results of this study highlighted the suitability of the MEMD method in revealing the main scale-specific factors that affect SOC distributions, which is necessary in understanding and managing this important soil property.
Multiple‐Wavelet Coherence of World's Large Rivers With Meteorological Factors and Ocean Signals
Streamflow is controlled by multiple factors concurrently. However, the multivariate relationship between global streamflow and meteorological factors/ocean signals is rarely explored at different temporal scales. Determining a suite of factors that explain most of the variations in global streamflow at multiple scales will be of great significance for water‐resource management and prediction. Temporally dependent multivariate relationships between streamflow and meteorological factors/ocean signals in 16 of the world's large rivers were identified using wavelet transform coherence and multiple‐wavelet coherence. Prior to that, the continuous wavelet transform was used to detect temporal patterns in streamflow. The continuous wavelet transform results showed that significant annual oscillations occurred in all streamflow series over the study period, either with continuous annual periodicity or with intermittent breaks. Oscillations with periodicities of around 4 to 6 months were also found in many rivers. A comparison of the results from the wavelet transform coherence and multiple‐wavelet coherence analyses indicated that streamflow variation could be best explained by one, two, or three meteorological factors. The combination of factors that best explained streamflow variations differed among the rivers, although total precipitation (PRE) or the number of rainy days (WET) either alone or in combination was a dominant factor for all rivers. The most common best predictor was PRE or/and WET combined with potential evapotranspiration. The differences in best predictor were due to differences in latitude, radiation forcing, terrain, vegetation coverage, hydrological processes, and so forth.
D'une application pratique des indices bio-météorologiques
Abstract The purpose of the author is to determine statistically in what part of Switzerland maize could be cultivated with certain chance of rentability. The author gives first the method he used for determining the biometeorological index of four species of maize which were selected by the Swiss agronomical research stations. He has considered two possibilities for the growing period: ( a ) raising-ripening (l'approche globale); ( b ) raising-flowering, flowering-ripening (l'approche fractionee). From the biometeorological index, he calculated retrospectively the ripening time of these four species in the years 1901–1965. Assuming a priori that maize should be harvested before October 15th at the latest, he calculated, for a number of meteorological stations, the relative number of years when such conditions were fulfilled. Dividing the country in regions of similar mesoclimates and sorting these stations per region, it is possible to average the maximum altitude where maize can ripen at least 7, 8, 9 and 10 times within 10 years. Finally, taking into account the exposure and ground slope, he draws maps of the theoretically possible extension area, which maps are more reliable and detailed than the ones derived from actual means.