Article collected data to compare plant traits

 Article 1. Plant
Functional Trait Variation in Relation to Riparian Geomorphology: The
importance of disturbances INTRODUCTIONThis research study was conducted
by Garreth Kyle and Michelle R. Leishman, from the Department of Biological
Sciences at Macquarie University in Sydney, Australia. Their research focuses
in the riparian zone of the Upper Hunter River, located in New South Wales,
Australia. They collected data along a 5.5 km (3.4-miles) segment of the river,
identifying functional traits relating to plant growth, reproduction, and
geomorphology of vegetation within the riparian zone (Kyle and Leishman, 2009).
Statistical analysis was completed on the collected data to compare plant
traits and determine if there was any variation amongst plant communities.METHODSThey used a one-way ANOVA (analysis
of variance) and principal component analysis to compare the traits among plant
species associated to each of the three geomorphic units (point bars, benches,
and banks). Then they used Pearson’s correlation coefficients to compare trait
variation of the plant species with respect to environmental factors (Kyle and
Leishman, 2009). The 12 plant traits that were selected for comparison that
have been shown to influence colonization, growth and reproduction among plant
species. Information on plant species were collected using university and
online databases, and field observation and the field collection of leaves from
each species was conducted for further analysis on the biological features of
each plant species. These plant traits were compared to 11 environmental
factors that are shown to influence plant growth and reproduction. Multiple soil
sample were collected from each study site for further analysis. Once all the
data was collected for all 23 variables being compared in this study and
analyses were performed on the entire dataset. The ordination plot shown in figure-3
shows how trait variation is associated with the three geomorphic units, with an
overlay of Pearson’s correlation coefficients of environmental variables. Table-5
shows the comparison of principal components with environmental factors using
Pearson’s correlation coefficients.  RESULTSThey found differences among
the traits of plant species associated with the three geomorphic units (point
bars, benches, and bars) (Kyle and Leishman, 2009). Variation showed a strong
correlation to disturbance frequency and a slight correlation to soil mechanics
and composition within the riparian zone. Pearson’s correlation coefficient
shows that 9 of the 11 environmental factors that were being compared to the principal
components showed significant correlation (figure-3).  Article 2. Braided
River Flow and Invasive Vegetation Dynamics in the Southern Alps, New Zealand INTRODUCTIONThis research study was conducted
by Brian Caruso, Laura Edmondson, and Callum Pithie, from the department of
Civil and Natural Resources Engineering at the University of Canterbury,
Christchurch, New Zealand. Their research focuses on flow regime dynamics and the
invasive plant species of the Ahuriri River, a braided alpine river located in
New Zealand’s South Island (Caruso, et al., 2013).  METHODSThe flow regime metrics of thirty-three
indicators of hydrologic alteration (IHA) and thirty-four environmental flow
component (EHC) were analyzed. Flow regime refers to the variability of discharge
over a period of time. The IHA software package calculates statistical data
derived from daily hydrologic data, such as monthly flow averages, and the
magnitude, frequency, duration, and the tie of monthly maximum and minimum
flows. The EHC portion of the IHC software calculates characteristics of
monthly flows and five flow components, such as extreme low flows, low flows,
high flow pulses, small floods, and large floods (Caruso, et al., 2013). A
correlation analysis between IHA and EFC metrics was conducted using Pearson’s
correlation coefficient for each floodplain classification. A second Pearson’s
correlation coefficient was measured for each flow metric and vegetation
classification. Five sets of aerial photographs, along with data showing the
correlation between flow metrics and cover changes were evaluated over a
twenty-year period between 1991 and 2011. RESULTSThe Ahuriri River has substantial
variation with regards to hydrological characteristics of mountain braided
rivers, with differences in floods and flow regime metrics. The inconsistency
of the flow discharge of the Ahuriri River has changeable effects on the
invasive plant species and creates dynamic groupings of vegetation within the
floodplain zone, demonstrating shifting vegetation patterns and succession of
the biological and geomorphological features within this zone. Analysis has
shown that approximately 25% of the vegetation cover was removed by the largest
flood event classified and recorded during this study period. During this flood
event, there was a greater removal of herbaceous flowering plant species over
the woody plant species that grow in this region (Caruso, et al., 2013).  CONCLUSION OF REVIEW I am
interested in the dynamics of vegetation growth and reproduction within
riparian zones and learning how the vegetation transforms the morphology of the
river floodplain. The research studies I selected, focus on riparian vegetation
and feature the comparison of the relationship between two variables using Pearson’s
correlation coefficients. They are similar in that they both use two variants
with multiple variables for analysis. The two variables used in the first research
study are plant trait variation and environmental factors that are related
to soil mechanics or composition. Of these two variables, there are 12 plant
traits and 11 environmental factors compared to find correlation. The two
variables used in the second research study relate to flow regime (discharge amount) and characteristics related to invasive plant species. Of these
variables, there are 67 flow regime variables being compared to 7 vegetation
classes. The research studies are different in how they present their comparative
results. Correlation analysis was not used as the primary function of data
analysis in these studies, but rather used in addition to other forms of
analysis for further comparison of the variables. From
conducting this article review, I learned how two main variables, such as river
discharge and vegetation characteristics can be analyzed to show comparisons.
These comparisons can give a detailed assessment of how the flow regime
(discharge rates) can affect vegetation growth and reproduction rates
throughout the year. I think it would be interested to do further analysis by
comparing these findings with atmospheric data to compare vegetation growth in
association with changes in atmospheric activities. For example, I would look
at how variation in winter weather (i.e. high precipitation cold, vs. high
precipitation warm vs. low precipitation cold vs. low precipitation warm) over
multiple years can affect vegetation growth during summer months in alpine
rivers. First I would want to create a dataset comparing precipitation to the
rate of discharge, then compare that data to vegetation growth.           WORKS CITEDCaldwell, Sally. Statistics
Unplugged. 3rd ed. Belmont, CA: Wadsworth Cengage Learning, 2010.Caruso, Brian S., Laura Edmondson, and Callum Pithie.
“Braided River Flow and Invasive Vegetation Dynamics in the Southern Alps,
New Zealand.” Environmental Management
52, no. 1 (2013): 1-18. doi:10.1007/s00267-013-0070-4.Kyle, Garreth, and Michelle R. Leishman. “Plant
functional trait variation in relation to riparian geomorphology: The
importance of disturbance.” Austral
Ecology 34, no. 7 (2009): 793-804. doi:10.1111/j.1442-9993.2009.01988.x.

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