The Effects of Environmental Variables on Montane Longleaf Pine Ecosystems, Oak

Mountain State Park, Alabama

By:

Kevin Willson

Dr. Scot Duncan and Dr. Malia Fincher, REU Mentors

Samford University

August 2014

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Introduction

Longleaf pine (Pinus palustris) woodlands used to dominate the southeast portion of

the United States. Stretching from eastern Texas to Florida and north to Virginia,

dominant and mixed longleaf pine ecosystems harbored an array of biodiversity and

covered over 37 million hectares of land (Frost 1993, Walker 1984). The longleaf pine

tree grows to the top of the canopy, can live up to 500 years old, and produces a strong,

long-lasting wood that does not decay readily due to the resin found within the tree

(Brockway 1997). The tree is native to regions controlled by fire, which would naturally

sweep through swaths of land every one to three years and clear out the understory of the

woodland (Loudermilk 2011). In the Birmingham area, fires would return every 6-8

years (Bale 2009). Fire creates favorable conditions for longleaf seeds to germinate by

thinning out less fire-resistant plants and trees and exposing seeds to bare mineral soil,

freeing nutrients for immediate consumption, and burning away litter on the forest floor

(Brockway 1997). These mineral soils are exposed by fires burning through most of

these flammable organic soil horizon, burning away the little O and A horizons built up

within the soil (Varner 2005). Other than the ability to resist fire in most life stages,

longleaf does not compete well against other large growing deciduous and pine trees,

especially with anthropogenic changes that have occurred over the past several thousand

years (Landers 1995).

Before European settlers arrived, both nature and Native Americans helped encourage

longleaf pine ecosystems. Lightning would induce fires during the spring and summer,

while Natives introduced additional burnings in the fall and winter to herd larger game

animals for hunting (Frost 2006). European settlers slowly took over the Southeastern

US starting in the 1600s and made large changes to the landscape. People collected the

pine’s resin because it could be converted into turpentine, tar, and pitch, while the wood

was in high demand to construct buildings and lay railroad tracks (Jose 2006). The

tremendous value people placed on longleaf as a resource, coupled with the tree’s

abundance throughout the Southeast, led to immense destruction of the habitats while

supplying an ever growing United States during the 18th, 19th, and 20th centuries. By the

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end of the 1940s, most longleaf stands had been completely logged with little restoration

attempts to regrow the trees (Jose 2006). Starting in the early 1900s, the United States

began implementing a stringent fire suppression regime to try to protect forests, which

unknowingly continued hurting longleaf pine forests. The overharvesting of longleaf

pines paired with intensive fire suppression throughout the South have hurt the species in

its ability to recapture lost land, leading to drastic losses in endemic species needing the

pine and ecosystem to prosper. The lack of fire has allowed the other trees including

loblolly pine and more deciduous trees to outgrow and out-compete the longleaf pine in

most areas throughout the Southeast (Van Lear 2005).

The longleaf pine plays a critical role in maintaining habitats throughout the

Southeast. As a keystone species, the lack of abundant longleaf pine exhibits the

ecosystem’s inability to become properly re-established, indicating the overall loss of

pristine fire climax habitats (Brockway 1997, Landers 1995). The tree’s loss has led to

the demise of a number of plant and animal species, with over 29 plant and animal

species labelled as threatened or endangered because of, or partially due to, the loss of the

longleaf pine ecosystem (Van Lear 2005, Brockway 1997). Montane systems, though

smaller in area, are just as important as its coastal companion in helping restore longleaf

pine. Montane longleaf habitats support different ecosystems than the coastal plains and

could potentially harbor species that are not found elsewhere within the South.

As scientists attempt to restore longleaf pine ecosystems after an era of fire

suppression, researchers, including Van Lear (2005), Varner (2003 & 2005), Brockway

(1997), Lavoie (2010) and Fowler (2007), have studied how this pine species and its

ecosystem have been affected over the past century. The soils of regularly burned

ecosystems feature fluctuating leaf litter and organic soil horizons, which significantly

differs from unburned forest floors that have deeper leaf litter and organic soil horizons

(Lavoie 2010). Montane systems may be unique to other longleaf pine regions because

of differences in slope and soil depth, yet little is known about possible differences

because of the lack of research within mountainous regions of this habitat. Oak

Mountain State Park (OMSP), the research site for the study, is one of the few montane

ecosystems that still contain longleaf pine. Within the field study sites at OMSP, thick

layers of leaf litter are noticeable and have added to soil depth, likely accumulating from

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the lack of consistent fire our research plots have not had over in the recent past. This

soil accumulation affects all ecosystems within the longleaf pine range.

While scientists are collecting large amounts of data on coastal longleaf pine

ecosystems (Drewa 2002, Gitzenstein 2001, Jose 2010, Noel 1998, Outcalt 2010, Peet

1993, etc.), relatively few scientific studies have looked into understanding montane

longleaf ecosystems (Bale 2009, Maceina 2000, Varner 2003). The effects of increased

organic matter in the soil change soil moisture retention, nutrient availability, and soil

bulk density, which may have profound effects on the species richness and abundance

found in the area (Brockway 1997). Though part of the study will look to see how soils

may relate to the number and basal area of adult longleaf pine, we are also interested in

seeing how canopy cover could impact juvenile survival.

Few studies in the past have looked into the effects of canopy cover on longleaf pine

ecosystems. Peacot (2005) found a negative the relationship between the quality of light

coming through canopy and overstory tree stocking, while McGuire (2001) found an

increase in juvenile longleaf pine growth when gaps were created in the canopy from tree

removal. Unfortunately, both of these studies were focused on coastal ecosystems. Our

study will look at the impacts of canopy cover in montane ecosystems in regards to how

light availability affects the growth of juvenile longleaf pine trees.

In this study, we not only attempted to add to the science of montane longleaf

ecosystems, but tried to appreciate how environmental variations within mountainous

areas may change longleaf pine growth. In comparing two different regions of Oak

Mountain State Park, a foothills and a mountain slope zone, we attempted to add

literature of how variations between the smaller foothills and a larger mountain change

the biodiversity and abundance of longleaf pine juveniles and adults. A number of

differences exist between characteristics of foothill and ridge regions in Oak Mountain

State Park including the steepness of the slopes, soil depth, and bedrock variations

between shale (in the foothills) and sandstone (in the ridge). By seeing the change of

habitats between a steeper ridge and rolling foothills, we may better understand the

differences between coastal plain ecosystems, generally flatter than the foothills at

OMSP, and montane ecosystems. We need more data on montane longleaf pine

ecosystems to better understand how the community there interacts with the abiotic

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features of the land and to improve restoration efforts. To learn more about these system,

this study looked into finding patterns that may predict juvenile longleaf pine abundance

and basal area of adult longleaf pine.

Hypotheses: This study looked into two important measures of longleaf pine health,

juvenile longleaf pine abundance and total basal area of adult longleaf pine, and how

several variables may affect and predict these factors. These two measures were studied

because they represent two important factors that help examine both longleaf recruitment

and adult growing capabilities. I hypothesized that variables that decreased soil depth,

increased slope, increased tree species richness, and increased non-longleaf pine basal

area had negative relationships with juvenile longleaf pine frequency and basal area of

adult longleaf pine trees because the less stress and more species of tree filling space and

niches, the fewer number of longleaf will be able to compete within the ecosystem.

I was also interested in determining if a relationship exists between canopy openness

and total number of juvenile longleaf pine in the understory. As a young, small tree,

collecting enough light is one of the most critical components to surviving; the more

light, the more likely a juvenile tree is to survive. Because canopy cover (the opposite of

canopy openness) would affect light availability on the forest floor, I expected canopy

openness and the abundance of juvenile longleaf pine to be mathematically related to one

another and have a positive relationship.

Environmental Variables: Environmental variables measured for this study included

canopy openness, slope steepness and soil depth. Canopy openness, the percentage of

overhead sunlight able to reach the ground, was determined using a hemispherical lens

and camera to take a 180° picture approximately one meter above the ground in the

center of the subplot. The photo was processed using GLA (V. 2) software used to

determine the amount of tree cover within the subplot (Frazer 1999). Slope was recorded

from the lowest to highest points of the perimeter of each subplot and measured with a

clinometer (Suunto PM5/360 PC, Finland). Soil depth was tested at the center of the

subplot as well as at points two meters away from the center of the subplot in the four

cardinal directions. Soil depth was measured by inserting a four foot steel soil probe (3/8

inch diameter made by Forestry Suppliers, Inc in Jackson, MS) into the ground until it

could not go any further or until bedrock was struck and the depth was recorded. The soil

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depth data used for the statistical analyses in this study were the average recordings of the

five measurements in each subplot. Soil depth may affect the total basal area of longleaf

pine in foothill and ridge regions in the park for several reasons. In this region, more

complete organic horizons indicate fewer fires sweeping through the area, which

negatively affects longleaf pines’ ability to compete in the ecosystem. Also, deeper soils

generally have more nutrients and water retention, which allows a larger diversity of trees

and more competition due to less stress in attaining and retaining water and nutrients.

Indicator variables: Indicator variables included total tree species richness, juvenile

longleaf pine abundance, and longleaf pine and non-longleaf pine basal area. Total tree

species per subplot – the species richness - was the unit of measuring biodiversity in this

study. Juvenile longleaf pines shorter than 1.3 meters was measured for basal diameter,

height, and abundance. Only five or six of the ten subplots was measured in each plot (1,

4, 5, 8, 9) and one randomly chosen subplot (2, 3, 6, 7, or 10) if the researcher had

enough time to examine one more subplot. Finally, we looked at tree biodiversity and

basal area measured in these plots by Dr. Scot Duncan ten years ago to try finding

possible variables that affect tree biodiversity – measured by recording total number of

tree species in each subplot – and total basal area of longleaf pines, which was calculated

by taking the area of the tree at breast height. Though some comparisons used in the

research were taken from data collected ten years apart, the slope and soil depth data that

we collected in 2014 would not likely change much from 2004.

The statistical analyses were performed using SPSS (Version 19, IBM). The Mann-

Whitney U non-parametric test provided the statistical evidence of differences between

the ridge and foothills as well as differences between subplots with and without longleaf

pine adults/juveniles. Multiple linear regressions were used to determine how predictive

the independent measured variables were on the dependent variables (juvenile longleaf

pine frequency and adult longleaf pine basal area per plot). All of the data was tested

using multiple linear regressions and then subplots with no longleaf pine were taken out

of the analysis for the purposes of seeing: when longleaf pine did grow, what were factors

that may influence growth. If the p value was under 0.200, the variable was kept to look

in the next multiple linear regression test to see if it became significant.

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Methods

Study Site: Oak Mountain State Park is located in Pelham, Alabama and contains

9,940 acres of land (Alabama State Parks Website). Numerous ecosystems are found in

the park, from the ridgeline woodland at the top of Double Oak Mountain to the foothill

forests and stream habitats that are scattered around the mountain. Double Oak Mountain

is a twin ridged, ridge and valley system that is runs in a Northeast to Southwest

direction. The mountain influences many aspects of the natural ecology in the park from

water runoff to plant species diversity found in various areas within OMSP. The park

features two different topographic regions due to the mountain, including the ridge (the

mountain face) and the foothills, the rolling hills around the mountain. The ridge is

higher in altitude, topping out at 1,260 feet above sea level and is made mostly of shale in

the mountain’s valley and sandstone in the twin peaks. The foothills fluctuate in

topography greatly, having numerous high points as compared to the ridge which only

has several ridgeline high points and long slopes. The foothills are also mostly made of

shale with traces of sandstone. In the past, most of this land likely contained a large

amount of longleaf pine judging by the number of longleaf pine stumps still found on the

ridge and in the foothills, though other trees have overtaken many parts of the park.

Average rainfall in the area is approximately 135 centimeters of rain per year (Maceina

2000) and average high temperatures range from 54 °F in January to 91 °F in July

(Birmingham). Frost and freezing temperatures occur between one to three times per

year (Maceina 2000).

Study Design: The research plots used as the study sites at Oak Mountain State Park

were created approximately 11 years ago by Dr. Scot Duncan. Ten foothill plots were

randomly placed on the top of forested hills within the foothills region of the park. Ten

ridge plots were selected at random on the southeast slopes of Double Oak Mountain.

These plots were 50x20 meters and divided into ten 10x10 meter subplots. Each subplot

was individually measured for the study’s variables.

Results

Juvenile longleaf pine were not found very frequently throughout the subplots as

compared to adult longleaf pine, only found in 34% of the 108 subplots sampled versus

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adult longleaf found in 64.5% of 200 subplots. Within the foothill region, four plots had

juvenile longleaf for a grand total of five subplots (9.09% of sampled subplots). In the

ridge, all 10 plots had longleaf pine juveniles for a total of 32 (60.3%) of the 53 subplots

sampled. The ridge subplots that had juvenile longleaf averaged 12.2 juveniles per

subplot, whereas the foothills plots averaged 2.8 per subplot.

Longleaf pine tree basal area found within the plots significantly varied between and

within the foothills and ridge. Within the foothills plots, there was an average of 31

longleaf pine trees per plot, making up approximately 18% of the numbers of trees

recorded, while the ridge plots contained an average of 14.9 longleaf pine per plot (19%

of the number of trees). Total longleaf basal area in subplots had less variability than in

the foothills, while the ridge longleaf pines averaged a larger basal area overall (Table 1).

The total basal area of other trees in the foothill subplots totaled about 15.64 m2, while

ridge plots totaled about 7.93 m2. Tree species totals found that foothill subplots

harbored roughly 1.5 more species overall per subplot than as compared to the ridge

subplots (Table 1).

Canopy openness was relatively similar between the foothill and ridge plots, though

the foothill plots kept a relative uniform average while the ridge plots saw more variation

(Table 1). Slope had significant differences between the two regions and was greater on

ridge subplots. The soil depth average was almost two times deeper in the foothill plots

than as compared to the ridge plots. Significant portions of the subplots in the ridge

lacked canopy cover due to very shallow or absent soils, which never occurred in the

foothills.

Four independent variables (slope, soil depth, species richness, and non-longleaf pine

basal area) were used in a comparison of subplots with and without adult longleaf pine in

ridge plots. In these tests, the only significant variable differing between the two sets of

plots was non-longleaf pine total basal area, which doubled in subplots without longleaf

pine (Table 4). In the foothill plots, the only two significantly different variables between

subplots with and without longleaf pine were the species richness and non-longleaf tree

total basal area variables.

In a similar comparison between subplots with and without juvenile longleaf pine,

four different variables (canopy openness, slope, soil depth, and tree species richness)

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were significantly different between subplots. In the foothills, slope was much shallower

and soil depth was much deeper than in the ridge, as seen in Table 3. The ridge subplot

comparison found that canopy openness and soil depth were the two variables

significantly different in subplots with and without the juveniles (Table 4).

Multiple Regression Models:

In the first regression model, juvenile longleaf pine frequency was the dependent

variable and canopy openness, soil depth, tree species richness, slope, and non-longleaf

pine basal area. The data was separated by foothills and ridge. Running a multiple linear

regression test for foothill plots found that the three variables tested (slope, soil depth,

and species richness, excluding non-longleaf pine basal area and canopy openness due to

lack of statistical strength) were all significant in predicting juvenile frequency within the

five subplots the juveniles were found in (Table 2). Analysis of the ridge plots found that

soil depth, non-longleaf pine basal area, and slope did not play a significant role in

predicting juvenile frequency, but canopy openness and species richness did positively

correlate to the is variable significantly.

The next question looked for a connection between the dependent variables of

biodiversity and longleaf pine basal area and the independent variables of soil depth,

slope, tree species richness, and non-longleaf pine basal area. Subplots that did not

contain longleaf pine were removed and the regression was run again with the same

dependent and independent variables. In the ridge plots, the significant variables in a

multiple linear regression included soil depth, slope, and “other” tree total basal area. In

a multiple linear regression only including these three variables, the test found a strong

correlation to predicting longleaf pine basal area (R2 = 0.363, p < 0.001). Individually,

slope was negatively predicted basal area, the soil depth positively predicted basal area,

and the non-longleaf pine total basal area negatively predicted longleaf pine basal area

(Table 2).

Discussion

Overall, we found that the biggest factors we tested affecting longleaf pine growth in

Oak Mountain State Park were stress and competition. Stress was best measured through

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two environmental stressors, slope and soil depth, competition was measured with a

comparison of total basal areas of trees, and stress and competition were measured

together by tree species richness. Our findings suggest that the longleaf pine have had to

deal with significantly different environmental conditions within the two subsets of a

montane ecosystem. The ridge is a more difficult and stressful environment for plants to

grow as compared to the foothills. Also, succession due to fire suppression is more

advanced in the foothills than in the ridge because invading tree species have an easier

time getting a foothold there due to less stress.

The ridge and foothill regions of Oak Mountain State Park appear to be very different

environmentally, with significantly different slopes, soil depths, tree species richness and

non-longleaf pine basal area. All of these factors seemed to have played a role in

affecting the growth of juvenile and adult longleaf pine.

Juvenile longleaf pine, if present, would indicate that the longleaf pines in the forest

are mature enough to reproduce and the there are enough beneficial factors to allow the

seeds to germinate into the juvenile stage. The differences in the variables measured

must have affected regeneration of longleaf pine, seeing as regeneration nearly halted in

the foothills, yet recruitment of seedlings continued on the ridge. Due to the lack of

juvenile longleaf pine in the foothill subplots, the results given have to be taken as

provincial findings due to small sample sizes, though this lack of juveniles in the foothills

also provides evidence that juvenile longleaf pine are more likely to survive in more

stressful environments due to lack of competition for space and resources. This disparity

exists despite the fact that adult longleaf basal area was higher in the foothills.

Adult longleaf pine basal area was used as an indirect measure of total LLP space and

indicates the total space and resources taken up by this one species in a subplot. There

was significantly more longleaf pine basal area in the foothill plots, meaning there was

more successful growth of longleaf pine overall in the foothill plots than in the ridge

plots.

Environmental variables seem to directly impact growth of the longleaf pine

community both on individual and collective levels. Slope was steeper in the ridge than

in the foothills. Differences in slope are due to the geology of the mountain and foothills,

where ridge plots are above a thick layer of sandstone, which is not as easily eroded as

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the shale in the rest of the park. Sandstone prevents groundwater penetration for long

term storage, hurting trees during drier periods, while steeper slopes quicken water runoff

and groundwater flow. Juvenile longleaf pine were not significantly affected by the

indirect effects of slope in the ridge, nor were there any differences in ridge subplots with

and without juvenile longleaf pine. In the foothills, slope was negatively related to

juvenile longleaf pine frequency, with significantly less slope when juvenile longleaf was

present in the foothills. For adults, steeper slopes on the ridge had a negative relationship

for longleaf pine basal area, though no pattern was found in the foothill plots between the

two variables. Subplots with adult longleaf pine and subplots without longleaf pine did

not differ for slope in either the foothills or on the ridge. Combined, these two results

indicate shallower slopes generally increased longleaf pine growth, but was not the

variable that allowed or prevented the establishment of the adult tree. Overall, when

slope causes enough stress, it affects the tree to continue to grow, with tree growth

improving on shallower slope. The data show that steeper slopes may hinder all species

of tree growth, but could benefit juvenile longleaf pine due to less competition. The data

also indicates that if slope was steep enough, then it could indirectly affect tree growth

and therefore may affect the longleaf pine community.

Soil depth was deeper in the foothills than in the ridge and may be a pivotal variable in

affecting longleaf pine recruitment and growth. In foothills, juvenile longleaf pine numbers

had a significant negative relationship to soil depth, but no such relationship existed in the

ridge. In the foothills, soil depth was almost a perfect predictor of juvenile longleaf pine

frequency and count, showing strong trends that stress in the habitat may be beneficial for

longleaf pine to become established. Adult longleaf pine basal area in the ridge was

marginally non-significant, but positively related to soil depth, with deeper soils indicating

greater basal area, while there was no significant trend found in the foothills. There was also

no significant difference in subplots where adult longleaf pine was present or absent in either

the foothills or the ridge. The lack of change between subplots with and without adult

longleaf pine indicates that soil depth was not the variable that allowed or prevented the

establishment of the adult tree. When compiling all of this data, soil depth provides evidence

that it causes stress that affects longleaf pines’ continued growth when shallow enough and

that the deeper the soil, the easier for the tree to grow. Like with slope, if soil depth was not

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extreme enough, then it would not play a direct factor in the longleaf pine community.

Finally, longleaf pine generally grows better in deeper soils, but the juvenile longleaf pine

have more success in shallower soils due to less competition. The shallower soil may be a

limiting factor in survival for other plants, but not for juvenile longleaf pine; this opens up

space and resources for more juvenile longleaf pine to germinate and grow.

Non-longleaf pine basal area, being greater in the foothills than the in the ridge, seemed

to have a negative impact on the ability for adult longleaf pine to grow. Non-longleaf pine

basal area was used as a way to measure the amount of space non-longleaf pine trees took in

the two regions of the park, giving an idea of the total area of trees are found in each subplot.

There was significantly more tree area in the foothills than as compared to the ridge,

supporting that the notion that higher amounts of stress lead to lower amounts of total tree

growth. Overall, the only significant regression result for both juvenile and adult growth was

for adult longleaf pine basal area in the ridge, which has a negative relationship. There was

also a significant drop in non-longleaf pine basal area when longleaf pine were in the area.

This supports the idea that other trees generally compete against and are bad for the LLP

community. With more stress, there will be both lower non-longleaf pine basal area and

higher longleaf pine take up space per subplot. Combined with tree species richness results,

the data may provide evidence that that non-longleaf pine trees and the longleaf pine

community have an antagonistic relationship.

Tree species richness was also greater in the foothills than in the ridge. Tree species

richness was used as an indicator of the state of the ecosystem, with increased richness

meaning greater competition for longleaf pine trees. This variable also pointed to possible

stress variations between ridge and foothills. In the ridge, tree species richness was

negatively related to longleaf pine basal area, meaning increased diversity related to the

declining health of longleaf pine community, while decrease in diversity would be beneficial

to longleaf pine trees. Tree species richness was greater in foothill subplots without adult

longleaf pine, supporting the idea that as species richness increases, the more competition

and the worse it is for the longleaf pine community. The ridge plots were not significantly

affected by species richness, which due to the lesser amounts competition from increased

stress. For juvenile longleaf pine, tree species richness was positively related in the ridge,

but negatively related in the foothills. The mixed results support the idea that lower levels of

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stress in a high stress environment create higher chances of germination and growth into the

juvenile stages. In the foothills, more stress is needed to weed out competition for juvenile

longleaf pine to grow, so more stress means less competition. The findings suggest that

longleaf pine compete with other tree species for resources: the more resources the longleaf

pine obtain, the more area they are able to take. Juvenile longleaf also have to compete with

other species when there is little stress, but when stress is elevated to affect the amount of

species, juvenile longleaf pine only need to worry about stressors like soil depth and slope.

We were very surprised to find that canopy openness lacked any significant trends

with any of the tests performed. Young longleaf trees need many hours of direct sunlight

to survive and grow each day. Canopy openness is directly related to light availability at

the forest floor. When more light allowed to reach the forest floor, undergrowth receive

more energy to photosynthesize and produce sugars to store, making it an important

factor in small plant growth. There was one marginally non-significant result when

comparing canopy openness with juvenile longleaf pine in the ridge, with a positive

relationship between the two. The number of insignificant results provide evidence that

canopy openness did not play a major role in longleaf pine recruitment or growth. This

lack of difference may exist because both areas may be at or close to full closure, which

is especially true in the foothills with an increased invasion of broadleaf trees.

Conclusion:

Stress is helpful for LLP as steeper slopes and shallower soils introduce stress that has

been waning with fire suppression. The lack of stress has allowed increased competition

against the longleaf pine, with elevated tree species richness and growth of non-longleaf pine

negatively and unevenly impacting this community the foothills region of the park. These

have seemed to increased stress in the longleaf pine community to have a greater negative

impact than slope and soil depth do. Both of these could be key factors in successful

germination, with soil depth being significantly lower and slope being significantly greater

when comparing plots with and without juvenile LLP. Using these initial findings, we can

start looking into how these variables predict and/or affect the ability for this tree to establish

itself from the juvenile stage into an adult and how it continues to grow throughout its

lifetime.

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In future research, other factors that should be looked into include temperature, slope

aspect, and the average distance away from the parent tree. All of these could also be

factors that cause changes in the abundance of juvenile longleaf pine and size of adult

LLP in each of the subplots. For example, ridge slopes face southeast, meaning the

summer sun is more intense on the slope than others facing different directions, drying

the soils more quickly than on the north facing slopes. How does this change with

different slope aspects? Chance also may play a large factor of deciding whether a

juvenile or adult longleaf pine will grow from a seed into a juveniles or juveniles into an

adult, respectively.

Using these initial findings, we can start looking into how these variables predict

and/or affect the ability for this tree to germinate and grow from seeds into the juvenile

stage and into an adult. There is generally poor recruitment of longleaf pine in the park

overall, so how can that be improved upon by the trees? With this poor recruitment

means a potential drop in adult longleaf pine in the future. With this initial research, we

will need to look for more a detailed understanding of what other environmental factors

play a role in the growth of longleaf pine to help them maintain and re-extend their

community in the future.

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Tables and Graphs

Table 1. Results of a Mann-Whitney U test seeing if there were differences between the ridge and foothill regions in Oak Mountain State Park in Pelham, AL. A p value of less than .05 indicates a significant difference.

Foothill RidgeVariable Mean (SD) Range Mean (SD) Range P valueCanopy Openness (%) 12.7 (1.7) 7.9 – 17.5 14.5 (5.5) 9.5 – 36.7 0.176Slope (⁰) 12.0 (5.8) 1.0 – 28.0 21.0 (6.0) 5.0 – 41.0 <0.001Avg Soil Depth (cm) 34.2 (13.9) 4.9– 65.2 18.3 (13.9) 0.0 – 53.0 <0.001Juvenile LLP Count 2.8 (1.8) 1.0 – 5.0 12.2 (16.3) 1.0 – 53.0 <0.001LLP Basal Area (m2) 0.18 (.15) 0.0024 - 0.84 0.11 (0.09) 0.0005 -0.47 0.004Tree Species Richness 5.6 (2.0) 2.0 – 11.0 4.1 (1.5) 1.0 - 9.0 <0.001Non-LLP Basal Area (m2) 0.13 (.09) 0.016 - .51 0.065 (.06) 0.0009 - 0.33 <0.001

Table 2. Results of multiple linear regressions of the number of juvenile longleaf pine or adult longleaf pine basal area (dependent variables) against Canopy Openness (and/or Species richness), Slope, basal area of Non-longleaf trees, and Soil Depth (independent variables) in two different topographic regions of Oak Mountain State Park in Pelham, AL. P values less than .05 represent significant R2 values.

Region Model’s Dependentvariable

R2 P Independentvariables

Beta P

Foothills Juvenile Frequency 1.000 0.011 Slope -0.442 0.020Soil Depth -0.953 0.006Species Richness -0.232 0.038

Adult Basal Area 0.204 0.030 Canopy Openness 0.224 0.124Slope 0.144 0.281Soil Depth -0.105 0.438Species Richness -0.214 0.139Non-LLP Basal Area -0.132 0.393

Ridge Juvenile Frequency 0.355 0.001 Canopy Openness 0.313 0.067Slope -0.274 0.145Soil Depth 0.065 0.845Species Richness 0.537 <0.001Non-LLP Basal Area -0.105 0.431

Adult Basal Area 0.387 <0.001 Canopy Openness -0.176 0.115Slope -0.386 0.001Soil Depth 0.208 0.068Species Richness -0.024 0.824Non-LLP Basal Area -0.280 0.014

Table 3. Comparison of subplots with and without juvenile longleaf pine in Oak Mountain State Park in Pelham, AL. P values less than .05 represent a significant difference between the subplots using a Mann-Whitney U test.

With Juvenile LLP Without Juvenile LLPRegion Variables Mean (SD) Range Mean (SD) Range P ValueFoothills Canopy Openness (%) 12.5 (1.7) 10.2 – 14.0 13.9 (5.0) 9.6 – 32.8 0.447

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Slope (⁰) 12.6 (5.8) 7.0 – 28.0 19.9 (5.7) 7.0 – 32.0 0.002Avg Soil Depth (cm) 32.52 (14.0) 15.7 – 54.2 23.9 (13.3) 0.0 – 48.1 0.002Species Richness 4.8 (2.0) 2.0 – 7.0 5.8 (1.9) 3.0 – 11.0 0.437

Ridge Canopy Openness (%) 14.4 (5.5) 9.8 – 36.7 13.9 (5.0) 9.6 – 32.8 0.466Slope (⁰) 21.5 (6.0) 9.0 - 38.0 19.9 (5.7) 7.0 – 31.5 0.357Avg Soil Depth (cm) 16.8 (13.7) 0.0 – 48.4 23.9 (13.3) 0.0 – 48.1 0.103Species Richness 3.7 (1.3) 2.0 – 6.0 4.3 (1.4) 1.0 – 9.0 0.155

Table 4. Comparison of subplots with and without adult longleaf pine in Oak Mountain State Park in Pelham, AL. P values less than .05 represent a significant difference between the subplots using a Mann-Whitney U test.

With adult LLP Without adult LLPRegion Variables Mean (SD) Range Mean (SD) Range P ValueFoothills Slope (⁰) 12.5 (5.7) 2.0 – 28.0 11.4 (5.8) 1.0 – 26.0 0.423

Avg Soil Depth (cm) 34.1 (13.8) 4.9 – 64.4 34.2 (14.4) 12.3 – 65.2 0.908Species Richness 5.6 (1.9) 2.0 – 11.0 5.73 (1.9) 3.0 – 11.0 <0.001Non-LLP Basal Area (m2) 0.13 (0.09) 0.016 – 0.51 .20 (0.09) 0.070 - 0.44 <0.001

Ridge Slope (⁰) 21.0 (6.0) 5.0 – 41.0 21.1 (5.8) 8.0 – 32.0 0.886Avg Soil Depth (cm) 17.8 (13.8) 0.0 – 48.4 19.5 (13.3) 0.0 – 48.1 0.564Species Richness 4.14 (1.4) 1.0 – 9.0 3.1 (1.26) 2.0 – 5.0 0.966Non-LLP Basal Area (m2) 0.065 (0.063) 0.0 – 0.22 0.11 (0.064) 0.017 - 0.33 <0.001

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