Ostonen I.,University of Tartu |
Rosenvald K.,University of Tartu |
Helmisaari H.-S.,University of Helsinki |
Godbold D.,Institute of Forest Ecology |
And 3 more authors.
Frontiers in Plant Science | Year: 2013
Morphological plasticity of ectomycorrhizal (EcM) short roots (known also as first and second order roots with primary development) allows trees to adjust their water and nutrient uptake to local environmental conditions. The morphological traits (MTs) of short-living EcM roots, such as specific root length (SRL) and area, root tip frequency per mass unit (RTF), root tissue density, as well as mean diameter, length, and mass of the root tips, are good indicators of acclimation. We investigated the role of EcM root morphological plasticity across the climate gradient (48-68°N) in Norway spruce (Picea abies (L.) Karst) and (53-66°N) birch (Betula pendula Roth., B. pubescens Ehrh.) forests, as well as in primary and secondary successional birch forests assuming higher plasticity of a respective root trait to reflect higher relevance of that characteristic in acclimation process. We hypothesized that although the morphological plasticity of EcM roots is subject to the abiotic and biotic environmental conditions in the changing climate; the tools to achieve the appropriate morphological acclimation are tree species-specific. Long-term (1994-2010) measurements of EcM roots morphology strongly imply that tree species have different acclimation-indicative root traits in response to changing environments. Birch EcM roots acclimated along latitude by changing mostly SRL [plasticity index (PI) = 0.60], while spruce EcM roots became adjusted by modifying RTF (PI = 0.68). Silver birch as a pioneer species must have a broader tolerance to environmental conditions across various environments; however, the mean PI of all MTs did not differ between early-successional birch and late-successional spruce. The differences between species in SRL, and RTF, diameter, and length decreased southward, toward temperate forests with more favorable growth conditions. EcM root traits reflected root-rhizosphere succession across forest succession stages. © 2013 Ostonen, Rosenvald, Helmisaari, Godbold, Parts, Uriand Lõhmus.
Zhao Z.,Institute of Forest Ecology |
Zhao Z.,Southwest University |
Huang L.,Institute of Forestry |
Zhang X.,Institute of Forestry |
And 4 more authors.
Shengtai Xuebao/ Acta Ecologica Sinica | Year: 2010
The driving forces analysis is frequently used in conventional multivariate analysis such as multiple linear regression, canonical correlation analysis, principal component analysis and logistic model. These methods, however, assume that the input data are spatially independent regardless of the facts showing otherwise in landscape analysis. To overcome the shortfalls of the conventional methods to address the spatial autocorrelations, we proposed a new model (AutoLogistic) by incorporating the spatial autocorrelations into the conventional logistic model. AutoLogistic model was then applied at the Nverzhai watershed of Zhangjiajie to identify the driving forces for the cover changes. We included spatial variables (slope, altitude, aspect), distance to the nearest road, stream and residential areas in our new model. Model predictions were validated based on the Relative Operating Characteristics (ROC) method. We found that: (1) the vegetation cover changes and the driving factors appeared positive autocorrelation in space that decreases with distance across the watershed; (2) the AutoLogistic model showed higher accuracy than that of the logistic model, with remarkable reduction in the number of independent variables; (3) the magnitudes of influences from the natural driving forces seemed significantly different from those of the anthropogenic driving forces. Slope was the single most important variable on changes in farmlands, orchards, evergreen broad-leaved stands, and the coniferous stands, while aspect showed its importance for changes of farmlands, orchards, evergreen broad-leaved stands, and the shrub stands. Elevation appeared an unimportant factor driving the cover changes. Interestingly, the changes in deciduous broad-leaves stands seemed to be more influences by anthropogenic activities.
Zhu L.,Northeast Forestry University |
Zhang Y.,Institute of Forest Ecology |
Li Z.,CAS Research Center for Eco Environmental Sciences |
Guo B.,Northeast Forestry University |
Wang X.,Northeast Forestry University
Climate of the Past | Year: 2016
We present a reconstruction of July-August mean maximum temperature variability based on a chronology of tree-ring widths over the period ADĝ€-1646-2013 in the northern part of the northwestern Sichuan Plateau (NWSP), China. A regression model explains 37.1ĝ€-% of the variance of July-August mean maximum temperature during the calibration period from 1954 to 2012. Compared with nearby temperature reconstructions and gridded land surface temperature data, our temperature reconstruction had high spatial representativeness. Seven major cold periods were identified (1708-1711, 1765-1769, 1818-1821, 1824-1828, 1832-1836, 1839-1842, and 1869-1877), and three major warm periods occurred in 1655-1668, 1719-1730, and 1858-1859 from this reconstruction. The typical Little Ice Age climate can also be well represented in our reconstruction and clearly ended with climatic amelioration at the late of the 19th century. The 17th and 19th centuries were cold with more extreme cold years, while the 18th and 20th centuries were warm with less extreme cold years. Moreover, the 20th century rapid warming was not obvious in the NWSP mean maximum temperature reconstruction, which implied that mean maximum temperature might play an important and different role in global change as unique temperature indicators. Multi-Taper method (MTM) spectral analysis revealed significant periodicities of 170-, 49-114-, 25-32-, 5.7-, 4.6-4.7-, 3.0-3.1-, 2.5-, and 2.1-2.3-year quasi-cycles at a 95ĝ€-% confidence level in our reconstruction. Overall, the mean maximum temperature variability in the NWSP may be associated with global land-sea atmospheric circulation (e.g., ENSO, PDO, or AMO) as well as solar and volcanic forcing.