The spatial distribution of plant populations is an important feature of population structure and it de- termines the population's ecological preferences, biological characteristics and relationships with environment...The spatial distribution of plant populations is an important feature of population structure and it de- termines the population's ecological preferences, biological characteristics and relationships with environmental factors. The point pattern analysis method was adopted to study the distribution pattern of Picea schrenkiana indi- viduals of different size classes and the correlations between two size classes as well as the impact of topog- raphical attributes on the population distribution. With increasing diameter at breast height, the plant density of the P. schrenkiana population showed a declining trend. Old trees showed a random distribution at a small spatial scale (0-12 m), whereas saplings, small trees and big trees all had an aggregated distribution at all scales. With the increase of tree age, the scales at which maximal aggregation occurred gradually increased and the aggregation strength decreased. At a small scale (0-16 m), all size classes showed a negative correlation and the larger the difference between tree size, the more significant the negative correlation. The number of medium, big and old trees had a significantly positive correlation with elevations, whereas the number of saplings and small trees was not significantly correlated with elevations. The numbers of saplings, small and medium trees showed a significant positive correlation with slope gradient, whereas the number of big trees was not significantly correlated, and the number of old trees was negatively correlated with gradient. With the exception of old trees, saplings, small, me- dium and big trees showed negative correlations with convexity index. The study provides a theoretical basis for the conservation, rehabilitation and sustainable management of forest ecosystems in the Tianshan Mountains.展开更多
Soil complexity and its multivariable nature restrict the precision of soil maps that are essential tools for soil sustainable management. Most methods developed for reducing impurities of soil map units focus on soil...Soil complexity and its multivariable nature restrict the precision of soil maps that are essential tools for soil sustainable management. Most methods developed for reducing impurities of soil map units focus on soil external properties. Taking into account the soil internal properties like geochemical weathering indices could increase the map unit's purity. However, the compatibility of these indices with Soil Taxonomic Classes has not been studied yet. This study has been performed in a hilly region with different soil types, vegetation and diverse topographic attributes to illustrate the spatial variability of soil weathering indices and their compatibility with Soil Taxonomic Classes. The grid sampling is at 100 m interval. Physico-chemical and total elemental analyses were performed on 184 and 56 soil samples respectively. Eight topographic attributes and 14 common soil development indices were determined. Principal components analysis(PCA) was done to identify the most important components. The results indicated that Morphological Index(MI) was the best index to show the degree ofsoil development in the studied region. Spatial distribution of Soil Taxonomic Classes showed relatively good compatibility with the first principal component(PC1), Vogt(V) and morphological indices. This study showed that using soil development indices with the conventional methods could be helpful tools in soil survey investigations.展开更多
基金funded by the 12th Five-year Science and Technology Support Program(2011BAD38B0505)the Forestry Industry Research Special Funds for Public Welfare Projects (200804022C)the CFERN & GENE Award Funds on Ecological Papers
文摘The spatial distribution of plant populations is an important feature of population structure and it de- termines the population's ecological preferences, biological characteristics and relationships with environmental factors. The point pattern analysis method was adopted to study the distribution pattern of Picea schrenkiana indi- viduals of different size classes and the correlations between two size classes as well as the impact of topog- raphical attributes on the population distribution. With increasing diameter at breast height, the plant density of the P. schrenkiana population showed a declining trend. Old trees showed a random distribution at a small spatial scale (0-12 m), whereas saplings, small trees and big trees all had an aggregated distribution at all scales. With the increase of tree age, the scales at which maximal aggregation occurred gradually increased and the aggregation strength decreased. At a small scale (0-16 m), all size classes showed a negative correlation and the larger the difference between tree size, the more significant the negative correlation. The number of medium, big and old trees had a significantly positive correlation with elevations, whereas the number of saplings and small trees was not significantly correlated with elevations. The numbers of saplings, small and medium trees showed a significant positive correlation with slope gradient, whereas the number of big trees was not significantly correlated, and the number of old trees was negatively correlated with gradient. With the exception of old trees, saplings, small, me- dium and big trees showed negative correlations with convexity index. The study provides a theoretical basis for the conservation, rehabilitation and sustainable management of forest ecosystems in the Tianshan Mountains.
基金Center of Excellence"Improvement Soil Quality in order to Optimize the Plant Nutrition"of Soil Science department, University of Tehran and College of Agriculture and Natural Resources, University of Tehran for financial support of the study (Grant No. 7104017/6/19)
文摘Soil complexity and its multivariable nature restrict the precision of soil maps that are essential tools for soil sustainable management. Most methods developed for reducing impurities of soil map units focus on soil external properties. Taking into account the soil internal properties like geochemical weathering indices could increase the map unit's purity. However, the compatibility of these indices with Soil Taxonomic Classes has not been studied yet. This study has been performed in a hilly region with different soil types, vegetation and diverse topographic attributes to illustrate the spatial variability of soil weathering indices and their compatibility with Soil Taxonomic Classes. The grid sampling is at 100 m interval. Physico-chemical and total elemental analyses were performed on 184 and 56 soil samples respectively. Eight topographic attributes and 14 common soil development indices were determined. Principal components analysis(PCA) was done to identify the most important components. The results indicated that Morphological Index(MI) was the best index to show the degree ofsoil development in the studied region. Spatial distribution of Soil Taxonomic Classes showed relatively good compatibility with the first principal component(PC1), Vogt(V) and morphological indices. This study showed that using soil development indices with the conventional methods could be helpful tools in soil survey investigations.