Tree Ring Indices and Statistics
نویسندگان
چکیده
منابع مشابه
Fit Indices Versus Test Statistics.
Model evaluation is one of the most important aspects of structural equation modeling (SEM). Many model fit indices have been developed. It is not an exaggeration to say that nearly every publication using the SEM methodology has reported at least one fit index. Most fit indices are defined through test statistics. Studies and interpretation of fit indices commonly assume that the test statisti...
متن کاملBivariate Drought Analysis Using Streamflow Reconstruction with Tree Ring Indices in the Sacramento Basin, California, USA
Long-term streamflow data are vital for analysis of hydrological droughts. Using an artificial neural network (ANN) model and nine tree-ring indices, this study reconstructed the annual streamflow of the Sacramento River for the period from 1560 to 1871. Using the reconstructed streamflow data, the copula method was used for bivariate drought analysis, deriving a hydrological drought return per...
متن کاملVariations in Environmental Signals in Tree-Ring Indices in Trees with Different Growth Potential.
We analysed two groups of Quercus robur trees, growing at nearby plots with different micro-location condition (W-wet and D-dry) in the floodplain Krakovo forest, Slovenia. In the study we compared the growth response of two different tree groups to environmental variables, the potential signal stored in earlywood (EW) structure and the potential difference of the information stored in carbon i...
متن کاملRobust Tree-Ring Detection
The study of tree-rings is a common task in dendrology. Usually the rings deliver information about the age of the tree, historic climate conditions and forest densities. Many different techniques exist to perform the tree-ring detection, but they commonly are semi-automatic. The main idea of this work is to propose an automatic process for the tree-ring detection and compare it with a manual d...
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ژورنال
عنوان ژورنال: Science
سال: 1968
ISSN: 0036-8075,1095-9203
DOI: 10.1126/science.160.3823.101