Structural – compositional variation in three age-classes of temperate rainforests in southern coastal British Columbia

1995 ◽  
Vol 73 (1) ◽  
pp. 54-64 ◽  
Author(s):  
André Arsenault ◽  
Gary E. Bradfield
Keyword(s):  
Principal Component Analysis ◽  
British Columbia ◽  
Species Composition ◽  
Forest Structure ◽  
Canonical Correlation ◽  
Rain Forest ◽  
Principal Component ◽  
Age Classes ◽  
Temperate Rain Forest ◽  
Coastal British Columbia

Relationships between forest structure and species composition were examined in three age-classes of temperate rain forest in southern coastal British Columbia. Old forests (> 250 years) exhibited greater structural and compositional heterogeneity than young (31–60 years) and mature (61–80 years) forests. Size-class distributions of living and dead standing trees in the three age groups suggested both qualitative and quantitative differences in regeneration and mortality processes. The canonical correlation between structure and composition was high (Rc = 0.84), but a substantial amount of total variation remained unexplained by the analysis. Principal component analysis (PCA) axis 1 of species composition separated the lower elevation (warmer and drier) mature forests from the higher elevation (cooler and wetter) young and old forests. PCA axis 1 of structure separated the young and mature forests as a group from the old forests. PCAs of the separate age-classes indicated weaker compositional – structural linkages than with all age-classes combined. Study area differences explained greater proportions of variation in young and mature forests (up to 53%) than in old forests (< 10%). The results indicate a slow recovery process following impacts from human disturbance in coastal forests. Key words: canonical correlation analysis, old-growth temperate rain forest, principal component analysis, species composition, forest structure.

scholarly journals Correlation between macroalgae diversity and water quality in Southwest Maluku waters

2020 ◽  
Vol 45 (1) ◽  
pp. 25-32
Author(s):  
Marsya Jaqualine Rugebregt ◽  
Hairati Arfah ◽  
Ferdinand Pattipeilohy
Keyword(s):  
Water Quality ◽  
Principal Component Analysis ◽  
Species Composition ◽  
Diversity Index ◽  
Principal Component ◽  
Quality Parameters ◽  
Nursery Ground ◽  
Water Sampler ◽  
Phosphate Nitrate ◽  
Seawater Quality

Macroalgae play an important role in the ecosystem of the coastal area, serving as a shelter ground, nursery ground, and feeding ground. Macroalgae communities are directly influenced by water quality. This study aim was to determine the correlation between the macroalgae diversity and water quality in southwest Maluku waters. This research was conducted in September 2019 at seven research stations. Macroalgae samples were collected by transect method, while seawater quality was measured using Van Dorn Water Sampler. The macroalgae diversity, species composition, and dominance were determined. Water quality parameters analyzed were temperature, salinity, pH, phosphate, nitrate, and ammonia. Correlations between macroalgae diversity and water quality were determined using principal component analysis. This study recorded 45 species of macroalgae consisting of 15 species of red algae (Rhodophyta), 6 species of brown algae (Phaeophyta), and 24 species of green algae (Chlorophyta). Diversity Index varied ranged from low to moderate categories (0.969 - 2.345). Water quality in general is still quite good for macroalgae life. Macroalgae diversity and water quality correlate and influence each other.

Bryophyte community differences between edge and interior environments in temperate rain-forest fragments of coastal British Columbia

2005 ◽  
Vol 35 (3) ◽  
pp. 580-592 ◽  
Author(s):  
Lyn K Baldwin ◽  
Gary E Bradfield
Keyword(s):  
British Columbia ◽  
Species Richness ◽  
Functional Groups ◽  
Rain Forest ◽  
Species Abundance ◽  
Forest Edge ◽  
Forest Fragments ◽  
Old Growth ◽  
Edge Zone ◽  
Temperate Rain Forest

The species richness, community composition, and abundance of bryophytes within taxonomic and functional groups were examined in relation to habitat conditions in forest edge and interior habitats of nine old-growth temperate rain-forest patches remaining after logging in the Nimpkish River Valley of Vancouver Island, British Columbia. Bryophytes were sampled at a fine scale using 0.1 m × 0.3 m microplots to examine responses of species abundance on the forest floor, downed logs, and tree bases and at a coarser scale using 10 m × 2 m belt transects to determine changes in patterns of species richness and distribution. Edge habitats, sampled to a depth of 45 m into the forest fragments, were characterized by greater windthrow disturbance. Within the edge zone, increases in the richness of clearing-affiliated functional groups were associated primarily with the location of windthrown trees and tip-up mounds, rather than with distance from the edge per se. Interior habitats had both greater abundance of old-growth-associated functional groups and total bryophyte cover. The extension of the edge zone to at least 45 m into remnant patches carries implications for minimum patch size requirements in the context of variable-retention logging of coastal temperate rain forests.

scholarly journals 13,000 years of fire history derived from soil charcoal in a British Columbia coastal temperate rain forest

Ecosphere ◽  
2016 ◽  
Vol 7 (7) ◽  
Author(s):  
K. M. Hoffman ◽  
D. G. Gavin ◽  
K. P. Lertzman ◽  
D. J. Smith ◽  
B. M. Starzomski
Keyword(s):  
British Columbia ◽  
Rain Forest ◽  
Fire History ◽  
Soil Charcoal ◽  
Temperate Rain Forest

Linguistic Code and Cognitive Style: Interdomain Analyses

1978 ◽  
Vol 46 (3_suppl) ◽  
pp. 1159-1164 ◽  
Author(s):  
Millicent E. Poole
Keyword(s):  
Principal Component Analysis ◽  
Cognitive Style ◽  
Canonical Correlation ◽  
Principal Component ◽  
Cognitive Domains ◽  
Individual Interviews ◽  
Linguistic Code ◽  
Linguistic Coding ◽  
The Relationship ◽  
Critical Link

This study was an investigation of the relationship between linguistic coding and cognitive style. Group tests and individual interviews were administered to 96 adolescents, aged between 15 and 16 yr., to obtain measures in the linguistic and cognitive domains. Interdomain relationships were explored using principal component analysis and canonical correlation. The pattern of relationships between the two domains suggested a ‘specificity’ dimension as being the critical link.

scholarly journals A PCA–CCA network for RGB-D object recognition

2018 ◽  
Vol 15 (1) ◽  
pp. 172988141775282 ◽  
Author(s):  
Shiying Sun ◽  
Ning An ◽  
Xiaoguang Zhao ◽  
Min Tan
Keyword(s):  
Principal Component Analysis ◽  
Object Recognition ◽  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Principal Component ◽  
Component Analysis ◽  
Depth Information ◽  
Processing Unit ◽  
Data Set

Object recognition is one of the essential issues in computer vision and robotics. Recently, deep learning methods have achieved excellent performance in red-green-blue (RGB) object recognition. However, the introduction of depth information presents a new challenge: How can we exploit this RGB-D data to characterize an object more adequately? In this article, we propose a principal component analysis–canonical correlation analysis network for RGB-D object recognition. In this new method, two stages of cascaded filter layers are constructed and followed by binary hashing and block histograms. In the first layer, the network separately learns principal component analysis filters for RGB and depth. Then, in the second layer, canonical correlation analysis filters are learned jointly using the two modalities. In this way, the different characteristics of the RGB and depth modalities are considered by our network as well as the characteristics of the correlation between the two modalities. Experimental results on the most widely used RGB-D object data set show that the proposed method achieves an accuracy which is comparable to state-of-the-art methods. Moreover, our method has a simpler structure and is efficient even without graphics processing unit acceleration.

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