Factors recorded by both means of transects and

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Last updated: December 20, 2019

Factors affecting plant species diversity and distribution of native andnonnative species along the Wa’ahila Ridge Trail (Oahu, Hawaii) wereinvestigated in ten different elevational plots.  All plant species within each of the tenplots were recorded by both means of transects and quadrat sampling withestimates of their biomass and canopy cover. Plant species diversity was later calculated using Simpson’s indexA1 .The hypothesis that increased canopy cover would increase plant speciesdiversity was supported by the data and observations of plant distributiontrends along the ten different elevation plots.

 A decrease in canopy cover was found primarily within the lowerelevation plots and were all dominated by nonnative grass.  This relationship was concluded to beattributable to a large-scale forest fire in 2007.  The secondary succession that took placewithin these plots promoted the growth of invasive grasses such as Megathyrsus maximus and out competition with other species may have reason forthe low plant species diversity within these plots.  Nonnative species appeared to be betteradapted to these open canopy climates and are not easily displaced by nativespecies or another species found along the trail. The relationship betweenprecipitation and plant species diversity was insignificant to examinedistribution trends of but observational analysis of each plot revealed thatincreasing sample size might produce significant data for analysis.   IntroductionBy observation alone, a visual assessment of climate factors andvegetation may support a strong correlation between the two.

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  On a global scale, vegetative communities arestrongly correlated with different regions of temperature climate-moist tropicsare associated with tropical forests, dry subtropics with deserts, etc.  At the root of plant ecology lies therelationship between climate and spatial distribution among differentvegetative communities and even various physiographic factors such as canopycover, precipitation levels, and soil type.Ko?ppen’s climate classification system defined boundaries betweenclimates correspondingly to vegetative zones (Ko?ppen, 1936).  Its categories are based on annual andmonthly means of temperature and precipitation among five climaticregions-tropical moist climates, dry climates, moist mid-latitude climates withmild winters, moist mid-latitudes with cold winters, and polar climates.  Ko?ppen’s climate classification system wasone of the first quantitative establishments of defining the relationship betweenclimate and vegetation on a global scale (Ko?ppen, 1936).

  Similarly, Prentice et al. (1992) identified 13 different vegetative types in relationto five different climatic factors-the daily sum of degrees, mean temperatures,and the ratio of annual evapotranspiration to annual potentialevapotranspiration in what they called the BIOME model.  Their findings of the BIOME model allowed forextensive use in reproductions investigating the equilibrium response ofvegetative communities to changes in climate. Thephenology of alien species varies in cycle with the native Hawaiian plantspecies due to differences in the adapted climates. In response, nonnativespecies that overtake native populations remain latent during the wettestmonths, resulting in increased surface runoff and erosion.  Andropogon virginicus is an invasive species thathas impacted Hawaii’s ecosystem through such mechanisms (Smith 2007).  Rejmarek (1989) found that nonnative speciesexhibit greater coverage in proportion to native species within early mesicecosystems.  Over 30 dominant species andtheir year of maximum coverage were recorded over 20 years of vegetativesuccession in Hutcheson Memorial Forest, NJ.

 The data revealed that both proportion and number of alien species aregreatest during the initial stages of mesic succession and tended to decreasein numbers at both ends of the moisture gradient. He noted that native speciescolonized more successfully on either extreme of the moisture gradient. It wasconcluded that nonnative species within the experiment were not well adapted tothe native environment and thus could not successfully colonize among eithersides of the moisture extremes as the natives could (Rejmarek, 1989). A study conductedby Egler (1992) confirmed that locations among the Ko’olau Mountains exhibitpatterns between vegetative zones and particular species that inhabitthem.  Egler (1992) investigatedvegetative zones of the Ohia forests in the arid and semiarid lowland of Oahu,Hawaii.  Part of the study area residedalong the Ko’olau mountain range.  Mt.

Tantalus, residing along the windward range of the Ko’olau Mountains, wasidentified as one of the climatically distinct vegetative zones.  The dominant species exhibiting the highestbiomass was the observed native Metrosideros collina.  This occurrencewas attributed to the moist regions of Mt. Tantalus where precipitationexceeded 50 inches per year. Eglers study on vegetative zones confirmed thatthere are climatically distinct zones along the Ko’olau Mountains relative tothe distribution of different plant species and their ability to adapt betterto Hawaii’s native climate.  Using such findings, it may beexpected to see an immediate relationship and spatial distribution betweenvegetative communities along the various elevations of the Wa’ahila Ridge Trail(Oahu, Hawaii).  After the fire in 2007 alongthe lower elevation plots, a drier, more herbaceous vegetative community may beexpected within successional areas -as has been documented previously in theliterature.  At higher elevation plots,where precipitation was expected to be greater, larger plant growth and canopycoverage can also be expected.

  However,by limiting sun exposure, it may alter the vegetative community and we can predictA2  to see a widerrange of species inhabiting the area.   This investigation focused primarily onidentifying such distribution patterns within the ten different plots along theWa’ahila Ridge TrailA3 .  General observations were made in terms ofdifferences in species richness, vegetative coverage, and biodiversity.  Abiotic factors such as temperature, soildepth, and precipitation levels were recorded.

One hypothesis tested isthat there is no correlation between plant species diversity and precipitation.  Another hypothesis tested was that there is apositive correlation between canopy cover and species diversity.  Materials and Methods:  The vegetation and physiographicdata was recorded using transect and quadrat sampling methods.  A total of 10 plots, that were 20×20 meterseach, were covered A4 alongsidethe Wa’ahila Ridge Trail on O’ahu, HawaiI, October 2017. Each quadrat consistedof 1×1 meter dimensions and each transect was analyzed 15 meters inlength.  Data collected over the 10 plotsat various elevations was compiled and analyzed.

All plant species within eachconical quadrat station area and transect line were recorded andidentified.  Individuals that fell withina transect line were identified and recorded in meter length using a transecttape.  Physiographic features such aslight exposure (%), rainfall, and soil depth were recorded. The followingcommunity structures were also recorded: dominate species, population density,and % coverage.

    Mechanical devices were used to providereadings for most of the physiographic data. An iButton was used to record airtemperatures within the surveyed area and a rain gauge was used to measurerainfall.  Correlation analyses wereconducted on the relationship between plant species diversity and precipitationlevels, as well as between plant species diversity index and estimated % canopycover. Plant species diversity was calculated by Simpson’s index using aMicrosoft Excel spreadsheet. Results Thisinvestigation focused primarily on plant species and ecological distributionpatterns along climatically different plots along the Wa’ahila Ridge Trail onthe island of O’ahu, Hawaii. Transect sampling of plant species within tendifferent elevations along the trail revealed few statistically significantpatterns and several more observations between the various plots along thetrail.

The relationship between plant species diversity (Simpson’s index) and %canopy cover was considered statisticallysignificant A5 (Correlation:=; =2.64; df=18; and p=0.05).There was a positive relationship between plant species diversity and % canopycover along the ten plots on the trail-as canopy cover increased, plant speciesdiversity increased as well (Fig. 1). Plots at higher elevations (Plots 8-10) were observed to have greaterabsolute canopy cover and thus a greater species diversity value for eachcorresponding plot (Table 1). The highest % canopy cover was recorded at plot 9at 21.

775% and with plot 8 just following at 20.525%.  All species found within these two plots weresimilar in richness and diversity, with plot 9 containing several extra speciesnot found in plot 8 such as Citharexylumcaudatum (fiddle wood), Heteropogoncontortus (pili grass) and Pimentadioica (all spice). The highestspecies diversity index (Simpson’s index) was recorded for plot 10 at3.

19.  The lowest plant species indexvalue was recorded at plot 5 with a value of 1.23.  According to Fig. 2, there was no significantrelationship between plant species diversity and precipitation levels(Correlation; =; =3.18; df=18; p=0.327). With a P-value of greater than 0.

05, the null hypothesis that there isno correlation between plant species diversity and precipitation levels failedto be rejected.  There were no graphicaltrends that could be observed for further analyzing the relationship betweenplant species diversity and precipitation levels (Fig. 2).     Figure 1A6 : Relationship between plant speciesdiversity and % canopy coverage. Plant species diversity was measured bySimpson’s index (D). The correlation analysis for the given data is providedbelow: (Correlation; =; =2.64; df=18; p=0.

05)  Figure 2: Relationship between plant species diversityand precipitation levels. Plant species diversity was measured by Simpson’sindex (D). The correlation analysis for the given data is provided below:(Correlation; =; =3.18; df=18; p=0.327)  Figure 3: Canopy Closure along the ten elevational plots on the Wa’ahila Ridge Trailwas measures as a percent estimate within each plot and increased as the plotsprogressed in elevation.

  A transitionpoint appeared to be present after plot 7 where possible environmental orclimatic shifts may have caused a change in canopy cover.Discussion                      The firsthypothesis, which was valued as a framework for this investigation is repeatedas follows:  Plant species diversityincreases with increasing canopy coverage because a more suitable habitat isavailable for species to propagate. Compared to the dry and high sun exposureat lower elevation plots, a more humid environment with sufficient sun exposureand shade will provide the right environment for a wider range of species toinhabit.

  Plant species diversity wasalso hypothesized to increase with increasing precipitation levels, sincenative plants are better adapted to such conditions in Hawaii, it was expectedto observe or record several native species only at the higher elevationalplots. These two hypotheses have been developed to investigate distributiontrends along climatically different regions within the Wa’ahila Ridge Trail.     The analysis of plant speciesdiversity and % canopy cover authenticates the prediction that plant speciesdiversity increases within conditions of higher canopy cover. Contrary to theexpected results, nonnative plants dominated the upper elevational plots,exhibiting similar biomass coverage as the lower elevation plots.  One indigenous species, Waltheria indica (uhaloa), and one native Hawaiian species, Furcraea foetida (agave) wererecorded along the 10 plots on the trail.

Although several other native plantswere observed, these were the only two species that were represented in thepopulation. This was contrary to what was expected since these two species weresurveyed within the lower elevational plots. W.

indica was identified within plots 1-6 while F.foetida) was recorded in plots1,2,4,5, and 7. It is possible that these species are better adapted to drier climatesA7 and do not propagate well within shadier understories consistent with plotsabove plot 7.  Any native individualspreviously prevalent along the upper plots would have been outcompeted bynonnatives such as the frequent Leucaenaleucocephala or Senna surattensisassociated with the upper elevational plots with increased canopy cover.

  The distribution patterns of this specieswere demonstrated over a wide range of plots, prevalent from plot 1 all throughplot 10. The climates within both elevations seemed to be well suited for thisspecies.Megathyrsus maximus dominated both lower and upper elevational plots.  This species is considered a highlysuccessful invader in tropical and warmer climates and competes highly withnative flora.  M.

maximus is highly fire resistant and spreads quickly to invadeopen land during the initial stages of succession after a fire (Amondt 2011).  Secondary successionfollowing the forest fire of 2007 along the Wa’ahila Ridge Trail attributedgreatly to the observed distribution trends within the plots. Plant speciesdiversity decreased within the areas of succession following the fire. It wasconcluded that nonnative species such as M.maximus dominated the open land and would outcompete both native andanother nonnative species. The physiographic datacollected at each station denoted possible explanations for such trends.  Within the lower elevations (plots 1-7),there was a much lower level of canopy closure and a lower mean precipitation level.  It may be concluded from this data that thegiven conditions support a smaller range of species (primarily nonnativegrasses and shrubs such as Megathyrsusmaximus) and thus confirming reduced species diversity.

The fire that tookplace among the lower half of the plots was concluded to have a great effect onsuch trends.  According to Ainsworth(2007), primary succession following a fire may facilitate an environmentfavored by most nonnative weeds and shrubs. Megathyrsusmaximus showed to dominate the lower elevational plots, yet minimaladditional species were able to inhabit the hot and dry conditions along plots1 through 7 allowing M. maximus todominate the community.  Within thecanopies present along the upper plots (plots 7-10), the shadier and coolerenvironment may have provided an environment suitable for a greater diversityof species to grow-thus confirming the increase in recorded species along theseplots.Differences in canopyclosure may have attributed greatly in explaining the observed trend of nativeand nonnative prevalence between the various communities.  Among the lower elevation plots where canopyclosure was observed as very scattered (less than 5%), plant species diversityshowed to decrease.

It was concluded that the high prevalence of nonnativespecies within the community outcompeted much of the land available for nativeand another competing species. With fewer nonnative species to overtake thevegetation within the plant community, a greater number of individuals aregiven the opportunity to grow-possibly increasing species richness and in thiscase exhibiting reduced species diversity. Although it wouldbe expected for native species to be found in greater numbers within the higherelevation plots, the data supported otherwise. Plot 10 displayed few native species, yet was dominated by nonnative treessuch as Grevillea robusta (silk oak) andMegathyrsus maximus.  It was concluded that the arid climate thatprovided greatest sun exposure and minimal % canopy cover were favored by thenonnative species-as they were betteradapted to the physiographic properties similar to their mainlandA8 . With little to no native predators,introduced species such as the lower elevation-dominant Megathyrsusmaximus andLeucaena leucocephala had the opportunity to overtake much of thevegetation and land-as seen with their distinctly high prevalence and biomassalong the community.

   The relationshipbetween plant species diversity and precipitation levels was statisticallyinsignificant.  There was a slight negative relationship A9 between the two factorsA10 but the data collected was unsupportive to reject the null hypothesis (fig.2).  A greater sample size may have solved thisinsignificance.  Inconsistencies withdata collection at additional plots may also have affected the trend, such asidentification of various species along the trail. If one species was recordedas another within another plot (or vice versa), the plant species diversity maychange in relation to abiotic factors being testedA11 .

 A1Good A2GoodJ Predictions aresupported A3I’m a littleconfused on what your 2 hypotheses are A4Awkwardwording. Maybe you could say, A total of 10 plots that were 20x20m each on theWa’ahila Ridge Trail on O’ahu, Hawaii were used in data collection in October2017. A5good A6captionsgo below graphs and above tables A7yougave reasoning, good J A8goodexplanation/reasoning A9goodobservable trend A10(fig.x) A11Overall,I thought this was really good! The wording in some areas was awkward and hardto follow, but for the most part I understood what the point of the study wasand what conclusions you ended up with.

Also be careful with grammar! 

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