A Classification of Quaking Aspen in the Central Rocky Mountains Based on Growth and Stand Characteristics

1990 ◽  
Vol 5 (3) ◽  
pp. 69-75 ◽  
Author(s):  
Wayne D. Shepperd
Keyword(s):  
Rocky Mountains ◽  
Quaking Aspen ◽  
Independent Data ◽  
Growth Data ◽  
Data Set ◽  
Stand Growth ◽  
Analysis Techniques ◽  
Central Rocky Mountains ◽  
Stand Characteristics

Abstract A classification procedure using stand growth data from 140 aspen stands throughout Colorado and southern Wyoming was developed using multivariate clustering and discriminant analysis techniques. Stands were grouped into seven logical stand classses that differed in age, stocking, productivity, or other characteristics. A method of assigning other stands to these classes is presented and applied to an independent data set. West. J. Appl. For. 5(3):69-75, July 1990.

EFFECTS OF CONIFERS AND ELK BROWSING ON QUAKING ASPEN FORESTS IN THE CENTRAL ROCKY MOUNTAINS, USA

2005 ◽  
Vol 15 (4) ◽  
pp. 1284-1295 ◽  
Author(s):  
Margot W. Kaye ◽  
Dan Binkley ◽  
Thomas J. Stohlgren
Keyword(s):  
Rocky Mountains ◽  
Quaking Aspen ◽  
Central Rocky Mountains

scholarly journals Climate variability and fire effects on quaking aspen in the central Rocky Mountains, USA

2017 ◽  
Vol 44 (6) ◽  
pp. 1280-1293 ◽  
Author(s):  
Vachel A. Carter ◽  
Andrea Brunelle ◽  
Thomas A. Minckley ◽  
John D. Shaw ◽  
R. Justin DeRose ◽  
...  
Keyword(s):  
Climate Variability ◽  
Rocky Mountains ◽  
Fire Effects ◽  
Quaking Aspen ◽  
Central Rocky Mountains

A functional classification of the drift: traits that influence invertebrate availability to salmonids

1997 ◽  
Vol 54 (6) ◽  
pp. 1211-1234 ◽  
Author(s):  
Russell B Rader
Keyword(s):  
Rocky Mountains ◽  
Aquatic Invertebrates ◽  
Food Resource ◽  
Trophic Levels ◽  
Functional Classification ◽  
Invertebrate Community ◽  
Important Food ◽  
Stream Invertebrates ◽  
Central Rocky Mountains

Twelve categories/traits were used to classify and rank aquatic invertebrates based on their propensity to drift and importance as a food resource for salmonids. Invertebrate availability was based on their (i) propensity to intentionally drift, (ii) likelihood of being accidentally dislodged by the current, (iii) drift distance, (iv) adult drift, (v) benthic exposure, (vi) body size, and (vii) abundance. This study represents the first attempt to characterize the intentional drift propensity of stream invertebrates. A ranking procedure separated invertebrates into Baetis and three groups decreasing in availability. Predicted ranks were significantly correlated with the actual rank of invertebrates in trout guts taken in three separate studies conducted in the central Rocky Mountains, suggesting that this procedure can effectively rank invertebrates based on their availability as a food resource for salmonids. A cluster analysis separated the 95 taxa into four drift guilds and six availability groups. This study provides criteria for determining when alterations in invertebrate community composition will affect food resources for higher trophic levels by causing a decline in the most available taxa. This research also supports previous findings that floods are important in maintaining invertebrates that represent an important food resource for salmonids.

Aboriginal plant use in the central Rocky Mountains: Macrobotanical records from three prehistoric sites in Birch Creek Valley, eastern Idaho

2020 ◽  
Vol 42 (1) ◽  
pp. 66-108
Author(s):  
Brooke S Arkush ◽  
Denise Arkush
Keyword(s):  
Rocky Mountains ◽  
Intermountain West ◽  
Moderate Amount ◽  
Data Set ◽  
Macrobotanical Remains ◽  
Local Site ◽  
Prickly Pear Cactus ◽  
Site Function ◽  
Central Rocky Mountains ◽  
Pear Cactus

Recent excavations at three prehistoric sites in eastern Idaho recovered a moderate amount of culturally-introduced macrobotanical remains, including mountain ball and prickly pear cactus, goosefoot, sunflower, and tobacco, all of which came from contexts dating between 1500 B.C. and A.D. 1000. Within the greater region, cactus, goosefoot, and sunflower were first used by people between ca. 11,000 and 8500 B.C., whereas the archaeobotanical record for tobacco dates back to 10,300 B.C. The Birch Creek Valley data set allows us to explore aspects of local site function and settlement practices, as well as the temporal range and ubiquity of the above-listed taxa within the northern Intermountain West and adjacent portions of the central Rocky Mountains.

scholarly journals Comparison of selected Nordic stand growth models for Norway spruce, Scots pine and birch

2011 ◽  
Vol 55 (1) ◽  
pp. 46-59 ◽  
Author(s):  
Kjell Andreassen ◽  
Bernt-Håvard Øyen
Keyword(s):  
Norway Spruce ◽  
Scots Pine ◽  
Test Data ◽  
Growth Models ◽  
Management Practice ◽  
Tree Size ◽  
Site Quality ◽  
Data Set ◽  
Stand Growth ◽  
Stand Characteristics

Abstract Thirteen Nordic stand growth models have been validated by use of a test data set from long-term research plots in Norway. The evaluated data was from time-series of even-aged, pure stands of Norway spruce, Scots pine and birch (silver birch and downy birch). In selected models from Finland, Norway and Sweden measures of site productivity, mean tree size and various stand characteristics are represented. Different models display both strengths and weaknesses in their predicting ability. Several measures of precision and bias have been calculated and the models are ranked due to their performance. We observed site quality, stand density and average tree size as the three main components in the models. Basal area increment model for spruce from Sweden had the lowest standard deviation with 23%. The mean R2 between residuals and stand characteristics from this model was also low (1.3%), which indicates that independent variables are well included. For Scots pine and birch, Finnish volume increment models showed the best fit to the Norwegian test data, with a R2 between residuals and stand characteristics of 2.8 and 6.7%, respectively. Several of the models from Sweden and Finland predicted the growth as well as stand models frequently in use in Norway. The results indicated that similar forest conditions and traditional even-aged forest management practice in the Nordic countries could be seen as a suitable basis for developing a joint family of growth models. By careful recalibration of existing models, a reasonable accuracy could be achieved and the prediction bias could be reduced.

Machine Learning Verdict of EEG Signals in Brain Computer Interface

2018 ◽  
pp. 429-441
Author(s):  
M. Jeyanthi ◽  
C. Velayutham
Keyword(s):  
Nearest Neighbor ◽  
Technology Development ◽  
Vital Role ◽  
Svm Classifier ◽  
K Nearest Neighbor ◽  
Data Mining Technique ◽  
Data Set ◽  
Eeg Data ◽  
Irrelevant Attributes

In Science and Technology Development BCI plays a vital role in the field of Research. Classification is a data mining technique used to predict group membership for data instances. Analyses of BCI data are challenging because feature extraction and classification of these data are more difficult as compared with those applied to raw data. In this paper, We extracted features using statistical Haralick features from the raw EEG data . Then the features are Normalized, Binning is used to improve the accuracy of the predictive models by reducing noise and eliminate some irrelevant attributes and then the classification is performed using different classification techniques such as Naïve Bayes, k-nearest neighbor classifier, SVM classifier using BCI dataset. Finally we propose the SVM classification algorithm for the BCI data set.

Exploring the Vegetation of the Central Rocky Mountains

IAVS Bulletin ◽  
2018 ◽  
Vol 2018 (3) ◽  
pp. 16-50
Author(s):  
Orsolya Valkó ◽  
◽  
Balázs Deák
Keyword(s):  
Rocky Mountains ◽  
Central Rocky Mountains

scholarly journals Classification of jujube defects in small data sets based on transfer learning

2021 ◽  
Author(s):  
Jianping Ju ◽  
Hong Zheng ◽  
Xiaohang Xu ◽  
Zhongyuan Guo ◽  
Zhaohui Zheng ◽  
...  
Keyword(s):  
Transfer Learning ◽  
Loss Function ◽  
Training Model ◽  
Parameter Distribution ◽  
Test Accuracy ◽  
Small Data ◽  
Data Sets ◽  
Data Set ◽  
Small Data Sets

AbstractAlthough convolutional neural networks have achieved success in the field of image classification, there are still challenges in the field of agricultural product quality sorting such as machine vision-based jujube defects detection. The performance of jujube defect detection mainly depends on the feature extraction and the classifier used. Due to the diversity of the jujube materials and the variability of the testing environment, the traditional method of manually extracting the features often fails to meet the requirements of practical application. In this paper, a jujube sorting model in small data sets based on convolutional neural network and transfer learning is proposed to meet the actual demand of jujube defects detection. Firstly, the original images collected from the actual jujube sorting production line were pre-processed, and the data were augmented to establish a data set of five categories of jujube defects. The original CNN model is then improved by embedding the SE module and using the triplet loss function and the center loss function to replace the softmax loss function. Finally, the depth pre-training model on the ImageNet image data set was used to conduct training on the jujube defects data set, so that the parameters of the pre-training model could fit the parameter distribution of the jujube defects image, and the parameter distribution was transferred to the jujube defects data set to complete the transfer of the model and realize the detection and classification of the jujube defects. The classification results are visualized by heatmap through the analysis of classification accuracy and confusion matrix compared with the comparison models. The experimental results show that the SE-ResNet50-CL model optimizes the fine-grained classification problem of jujube defect recognition, and the test accuracy reaches 94.15%. The model has good stability and high recognition accuracy in complex environments.

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