Mencuccini M. (0) Dwarf trees, super-sized shrubs and scaling: Why is plant stature so important?. Plant, Cell and Environment. 38: 1-3.LinkDoi: 10.1111/pce.12442
[No abstract available]
Mimendia A., Gutierrez J.M., Alcaniz J.M., del Valle M. (0) Discrimination of Soils and Assessment of Soil Fertility Using Information from an Ion Selective Electrodes Array and Artificial Neural Networks. Clean - Soil, Air, Water. 42: 1808-1815.LinkDoi: 10.1002/clen.201300923
Multichannel sensor measurements combined with advanced treatment is the departure point for a new concept in sensorics, the electronic tongue. Our setup worked with an array of 20 ion selective electrodes plus an artificial neural network used as a pattern recognition method applied to soil analysis. With this design, we got a versatile tool which was able to perform qualitative and quantitative determinations. As first application, the qualitative discrimination between six distinct soil types based on their extractable components was attempted. The procedure was simplified to a single extraction step before measurements. Water, a BaCl2 saline solution and an acetic acid extract were evaluated as extracting agents. The best performance was reached with the acetic acid extraction method with a correct classification rate and sensitivity both of 94%, and a specificity of 100%. In addition, a quantitative determination of several physicochemical properties of agricultural interest, such as organic carbon content and selected cations (like K+ or Mg2+) and anions (like NO3 - or Cl-) was also demonstrated, showing satisfactory agreement with the reference methods. An electronic tongue system - the new approach in chemical analysis consisting of multidimensional sensor signals plus computer processing tools - showed the ability in distinguishing six distinct soil types in a first qualitative application example. A quantitative model demonstrated the correct estimation of selected cations (K+, Mg2+), anions (NO3 -, Cl-) plus the organic carbon content.
Tan J., Piao S., Chen A., Zeng Z., Ciais P., Janssens I.A., Mao J., Myneni R.B., Peng S., Penuelas J., Shi X., Vicca S. (0) Seasonally different response of photosynthetic activity to daytime and night-time warming in the Northern Hemisphere. Global Change Biology. 21: 377-387.LinkDoi: 10.1111/gcb.12724
Over the last century the Northern Hemisphere has experienced rapid climate warming, but this warming has not been evenly distributed seasonally, as well as diurnally. The implications of such seasonal and diurnal heterogeneous warming on regional and global vegetation photosynthetic activity, however, are still poorly understood. Here, we investigated for different seasons how photosynthetic activity of vegetation correlates with changes in seasonal daytime and night-time temperature across the Northern Hemisphere (>30°N), using Normalized Difference Vegetation Index (NDVI) data from 1982 to 2011 obtained from the Advanced Very High Resolution Radiometer (AVHRR). Our analysis revealed some striking seasonal differences in the response of NDVI to changes in day- vs. night-time temperatures. For instance, while higher daytime temperature (Tmax) is generally associated with higher NDVI values across the boreal zone, the area exhibiting a statistically significant positive correlation between Tmax and NDVI is much larger in spring (41% of area in boreal zone - total area 12.6 × 106 km2) than in summer and autumn (14% and 9%, respectively). In contrast to the predominantly positive response of boreal ecosystems to changes in Tmax, increases in Tmax tended to negatively influence vegetation growth in temperate dry regions, particularly during summer. Changes in night-time temperature (Tmin) correlated negatively with autumnal NDVI in most of the Northern Hemisphere, but had a positive effect on spring and summer NDVI in most temperate regions (e.g., Central North America and Central Asia). Such divergent covariance between the photosynthetic activity of Northern Hemispheric vegetation and day- and night-time temperature changes among different seasons and climate zones suggests a changing dominance of ecophysiological processes across time and space. Understanding the seasonally different responses of vegetation photosynthetic activity to diurnal temperature changes, which have not been captured by current land surface models, is important for improving the performance of next generation regional and global coupled vegetation-climate models.
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