Of these 14 species, 57.2% are classified as savanna species (appendix A), 21.4% are native to Wisconsin but not species commonly found in Oak Savannas and 21.4% are species considered exotic in Wisconsin (Figure 7A). When analyzing their frequencies, 90.6% of the species found in the area of study are considered savanna species, 3.4% Wisconsin natives, 5.1% were not identified and 0.9% exotic (Figure 7B). Figure 7. A. Species classification for the 14 different species found in the area of study. B. Percentage based on the relative frequencies of each class in the area of study. These 14 species are distributed differently across the area of study, with some species dominating specific areas while others are distributed scattered around the site (Figure 8). …show more content…
Species distribution across the area of study. One hundred and fifty two of the trees surveyed were dead (7.1%), with 81 of those (53.29%) situated in the Green Prairie management unit (Figure 9). Sixty seven out of this 152 trees (44%) were unable to identified and classified as Unknown. Of the percentage that could be identified, Black/Red Oak and Black Cherry presented the bigger frequencies (50 and 16, respectively). Figure 9. Dead trees found in the area of study. 4.2 Percentage of canopy density Sixty five measurements were made for the Southwestern Grady Oak Savanna area and part of the Green Prairie, by sampling 7 of the transects based on the UW Arboretum grid. The first two transects were sampled every 10 meters but the 5 remainings were sampled every 50 meters, due to time concerns (Figure 10). Figure 10. Points sampled for percentage of canopy cover. Based on the data obtained and using the Kriging tool in ArcGIS I created a percentage of canopy density map for the area (Figure 11). This map shows the different percentage of canopy density for the units, diving it into 6 classes ranging from 25.6% to
On September 17th, 2015 our group went on the Orange Trail of the State Botanical Garden of Georgia in Athens, Georgia to collect data for our lab. The biome of this area that we explored fit a temperate deciduous forest type. We walked along the trail and picked random spots to start measuring our transects. We measured DBH size and canopy coverage at 10, 20, 30, and 40 meters respectively along each transect for a total of six transects. We used a densitometer to measure the percent of canopy coverage of the tree closest to the center of the sampling points along each of the transects. We used a measuring tape to measure out 10, 20, 30, and 40 meters respectively along each of the six
Habitat: Commonly found in terrestrial. Forest light gaps, slips, margins, disturbed sites, open habitats, riverbeds, cliffs, inshore and offshore islands, fernland, herbfield,
Introduction: Almost every place on Earth, from the surface of your skin to the bottom of the ocean, is teeming with living things. To keep track of the vast diversity of life, biologists historically named and classified organisms according to their appearance. The system of categorizing organisms is
diversity is low because only one area was sampled so this could account for the species being the same. If
The Southwest Savanna is characterized by the hilltops, rivers and valleys and steep wooded slopes within the area. The average growing season in this part of southern Wisconsin is 153 days, making it the fourth longest growing season of the different landscapes within the state (Wisconsin Department of Natural Resources 2015). Of all the land in this section of Wisconsin, about 3.5% belongs to state, county, or municipal governments; this includes the state parks, natural areas, and wildlife areas. (Wisconsin Department of Natural Resources 2015). In the past, a majority of the forests in the Southern Savanna burned frequently. These forests depended on the fires to help maintain the area and return nutrients to the soil. In the mid-1800s,
The reduction of vegetative cover during and after fire can have a severe negative impact on several different factors including: water quality, soil erosion, wildlife and threatened or endangered species, introduction or spread of invasive and exotic species, and economic or social impacts to the surrounding communities. We will implement a vegetation monitoring protocol that will help guide us in restoration and recovery efforts of the High Park fire scar and the surrounding areas and watershed. A collaboration with the US Forest Service will be aggressively pursued in the hopes that a combined use of the Forest Inventory and Analysis (FIA) program and our separate vegetation monitoring protocol can be utilized. We will use the burn severity field data collection points and cross-reference them with the FIA data points to see if there is any overlap between them. If there is then the FIA data points will be given preference as those points can possibly provide more information than solely High Park Fire data collection points. If there is not the ability to utilize the FIA data collection points, due to privacy, cost, or unforeseen reasons, then the High Park Fire data collection points will be
The experiment was conducted in Sheboygan County at three locations of varying distance from Lake Michigan, where they were surveyed for the occurrence of the invasive tree species black locust. The first location, Kettle Moraine State Park, is located 20 miles inland west of Lake Michigan. As its name suggests, this location has a combination of kettles and moraines. Kettles are steep side impressions in a landscape while moraines are linear deposits that accumulated at the edge of an ice sheet. This creates a rolling hill landscape that can create quite the diversity of vegetation. This site was dominated by mostly sugar maple with the occasional red oak and birch. There was very little ground coverage, due to the dense shade cast by the
Little Bluestem is one of the most abundant grasses in Kansas, and its roots which grow 5-8 feet long, enable it to resist moderate drought conditions (SITE). Plots 5 and 6 contain co-dominant species; Yellow Indian Grass (20%), Big Bluestem (30%), and Prairie Dropseed (35%) are all dominant. In Plot 7, the dominant species is Prairie Dropseed (40%). The dominant species in Plot 8 is Big Bluestem (25%). In Plot 9 and 10, Little Bluestem becomes dominant again, and Switchgrass is observed to be the co-dominant. Species richness is shown in the Figure 5; there is a higher species richness in Plot 1 through
The sparrow had a total of one species with a relative abundance of 0.0526. The earthworm had a total of six species with a relative abundance of 0.3158. The red-headed woodpecker had a total of one species with a relative abundance of 0.0526. The bigger brown spider had a total of one species with a relative abundance of 0.0526 (see Figure 1). The total number of species in the wooded area was nineteen with the species evenness of 0.7823. It also had a Shannon diversity index of 1.6266 and species richness of eight (see Table 1). The twelve different species at the water’s edge site are turtle, buzzard, deer, frog, beaver, tiny brown spider, small black bird, small yellow and brown stripes spider, dark with brown stripes spider, water spider, tibellus spider, and dog. The turtle had a total of five species with a relative abundance of 0.1515. The buzzard had a total of three species with a relative abundance of 0.0909. The deer had a total of one species with a relative abundance of 0.0303. The frog had a total of one species with a relative abundance of 0.0303. The beaver had a total of two species with a relative abundance of 0.0606. The tiny brown spider had a total of one species with a relative
The Bartlett Experimental Forest: 2,600 acres established in 1931 with a general focus on silviculture, wildlife, and forest production.
maximus and S. surattensis at varying elevations. Percent cover is often used to determine the coverage of a particular species; in this case it is used to determine the cover of Guinea grass and Kolomano on the different plots. Based on observations from several ridge hikes, a hypothesis had been drawn up, and stated that: As elevation increases, so does percent cover of M. maximus and S. surrattensis. M. maximus is a good species to test because of it’s high abundance, particularly on the ridge. Kolomano is also a readily available on the ridge and is easily visible due to its flowers. By collecting measurements of percent cover at each of the 11 plots, the hypothesis could be supported or refuted.
In the North Carolinian piedmont, there are several different forest communities. The main types are, loblolly/ slash pine forest, mesic forest, oak forest, and floodplain forest (NC Wildlife 2015). Soil types, elevation, climate, and nutrient availability are important components of determining forest types. There are also certain species, considered indicators that help predict the type of forest community. The change in environmental factors and species distribution allow for different forest types (Cortes, Islebe 2005). Measuring the environmental factors of a plot and identifying the different species present can predict Forest types and is commonly done by land and forest managers (Fortunel etc. Al 2014). This experiment tests different locations of the NC piedmont, to help determine forest types in this area.
The following figure will be useful for locating mentioned species throughout the paper, it documents the 4 AFPs and AFGP and what species they are found in.
HA: There is significant difference in abundance among the four species calculated from the transect sampling.
Species are the most important unit of association in natural balance in terms of gladly assessable pasture entities as units of organismal evolution. Species diversity refers to the different types of living organisms on the Earth. This includes the many types of birds, insects, plants, bacteria, fungi, mammals and more. Many differing species often live to gather in communities depending on each other to provide their needs. The study of species diversity is of necessity based primarily on comparative and correlative research. The spatial area required to classify ecological community for many organisms of interest (eg. tree plants, birds and most mammals) is merely too large (and too difficult to define precisely)