Background: This assignment will give you the opportunity to participate in ongoing scientific research. For the past several years, I have been involved in ecological research in old-growth forests in Wisconsin. In many areas the forest floor is dominated by a grasslike species, Pennsylvania sedge (Carex pensylvanica). The sedge may exclude other ground species by interspecific competition, which may decrease the number of species in an area, which is a main component of biodiversity. The Penn sedge ‘lawns’ are probably caused by selective herbivory by an abundance of white-tailed deer. The deer do not like the sedge but consume most other ground plants. [Open Stax Concepts of Biology Chapter 19 has information on interspecific competition and herbivory, Ch. 21 on biodiversity.] Another problem in the forests is that dominant trees, such as white pine and sugar maple, do not show successful reproduction to replace the old pines and maples that die, which leads to the question – does Pennsylvania sedge decrease the establishment of tree seedlings? With support from a UMUC Faculty Research Grant to create this assignment, I collected data in the summer of 2013 that you can use to test three hypotheses- HypothesesA. Pennsylvania sedge inhibits regeneration of white pineB. Pennsylvania sedge inhibits regeneration of sugar mapleC. Pennsylvania sedge decreases biodiversityChoice of Study Site – Practice with Google Earth: Most, if not all, students are familiar with the use of GPS (Global Positioning System) to navigate. I assume that many of you are also familiar with Google Earth, an interactive aerial map of the globe. It is a very useful tool. When we lived in Okinawa, we chose a home to rent before our 2011 move to Rhode Island by investigating the property and its environs on Google Earth, and are very happy with our choice. Google Earth can be downloaded free at earth.google.com I also make use of Google Earth in choosing study sites for my research, especially when I was searching for remaining old-growth white pine forests in Upper Michigan. For practice with this relatively-new technology, I have included an exercise involving Google Earth with this assignment (under ‘Report’ below).Methods of Data Collection Data were collected during 2-4 August 2013 in a study plot within a forest dominated by trees of sugar maple, red oak, and red maple at Trout Lake Cathedral Point, Vilas County, Wisconsin (Figure 1). All ground species were identified in 2- x 2-meter quadrats that were positioned as a strip of adjacent quadrats in transects of adjacent across the plot. In ecology, a quadrat is defined as a sample area and a transect is a sample line. Figures 2 and 3 illustrate the method of transects of continuous quadrats. Within each of the sample quadrats, the percent cover of Penn sedge was estimated and all established tree seedlings (defined as > 20 cm in height and < 1 cm in diameter at breast height) were counted. This site was chosen to test the hypotheses because patches of Penn sedge covered portions of the plots but was absent in other parts. A total of 189 quadrats were sampled. Seedlings of white pine were most abundant, with a total of 124 plants in the quadrats, even though trees of white pine were rare. White pine, common in a stand adjacent to the study plot, has shown a recent burst of reproduction in the forest. There were 95 sugar maple seedlings in the quadrats. Other tree seedlings were few, so we will confine our analyses to white pine and sugar maple. [Identification notes- Species on the forest floor can be identified from field guides, or more officially, from large books such Wisconsin Flora or the 3-volume Michigan Flora. Specimens, plants that typify a species, are also deposited in an herbarium, where plants can be submitted for identification. Nowadays, sites such as Wisflora from the Wisconsin State Herbarium (http://www.botany.wisc.edu/wisflora/) are available online. Another new trick that I use is to enter the scientific names of species into ‘Google Images’ and compare it to digital photos of the plant. In the 189 Point quadrats, 20 herb species and 9 tree species as seedlings were identified. The most common herb was mayflower (Maianthemum canadense) in 89% of the quadrats. Three species, including eastern hemlock, were only in one quadrat. The hemlock seedling was quite a surprise as there are no hemlock trees in the vicinity.]Figure 1. Trout Lake study area with patch of Pennsylvania sedge on the forest floor. Fig1.JPG Figure 2. Transect line entering ‘lawn’ of Pennsylvania sedge, with scattered white pine seedlings. Fig2.JPG Figure 3. Quadrat of 2 x 2 meters created by centering two 2-meter sticks 2 meters apart on the transect tape. This quadrat on a sedge boundary contains small sugar maple and white pine seedlings. Fig3.JPG Testing the Hypotheses – Data Analysis The field data for you to use to test the hypotheses are given in an Excel spreadsheet with the file name ‘UMUCRiegeSedge.’ UMUCRiegeSedge.xls Listed for each quadrat are the percent cover of Pennsylvania sedge, the number of white pine seedlings, the number of sugar maple seedlings, and the number of species. So, you ask, where can I start to make sense of this big spreadsheet full of numbers? I would suggest one good way to begin is to tabulate the data by categories. For example, you might classify the quadrats by percent Penn sedge, such as 0-25%, 26-50%, 51-75%, 76-100%. Then you can average the number of seedlings or number of species per quadrat for each sedge category. [Hint- be sure to use average numbers per quadrat and not total numbers within each category, as the Penn sedge categories will have different numbers of quadrats.] If you look at scientific papers, you will see lots of tables and graphs, as these are excellent ways for the reader to understand the results. When graphing data, the independent variable (cause) is on the x-axis and dependent variable (effect) is on the y-axis. Our hypotheses have Penn sedge as the cause, hence percent sedge cover will be on the x-axis and the seedling/biodiversity data on the y-axis. In your report, use graphs and/or tables, as well as a written summary, to present your analytical results. [Although the data are presented in an Excel spreadsheet you are not required to use Excel for the report. You can copy the spreadsheet into another program or analyze it manually with a calculator if you wish.]REPORTYour report should be organized under the following bold headings (or a similar format).Background – Choice of Study SiteI use GPS readings of latitude and longitude for reports on my study sites, so others may be able to locate them. The Trout Lake Point study plot for this Penn sedge project was approximately centered at 46o 02′ 45.00′ N latitude and 89o 40′ 07.25′ W longitude. It extended south to north about 43.0′ to 47.0′ and east to west about 6.0′ to 8.5′. Please use Google Earth to locate the study plot (coordinates of latitude and longitude should be in the lower right corner of the Google Earth screen). The current aerial photograph on Google Earth was taken on July 26, 2015. Click on ‘View’ in the top menu, then ‘historical Imagery’ in the view menu. On the sliding bar find the photo for May 9, 2013. Note the ice on Trout Lake, as it was a late spring. Note that the deciduous trees (maples, oaks, etc.) have yet to leaf, while the pines and other conifers are green. Look over the study site and its surroundings by navigating with the GPS coordinates given above and describe (1) the forest of the peninsula in general from what you can see from the aerial perspective and (2) why you think the study plot was not extended farther south or farther north within the peninsula.HypothesesSimply restate the 3 hypotheses here.[Normally a scientific report would next have a section on methods, but you can skip this since I already stated the methods in the assignment.]ResultsHere, write a 2-3 paragraph report on your analysis of the data. Include tables and/or graphs and explain them. [Graphing reminder – best to put independent variable on x-axis and dependent variable on y-axis.] Conclusions & Discussion Summarize your analyses by concluding whether the data support or disprove Hypotheses A, B, and C. Then discuss how your conclusions might relate to the many factors that influence forest composition. For example, one factor not measured that may affect our data is the amount of shade. Although the study area had similar tree composition throughout, some areas contained thicker shade, which might decrease both sedge cover and species richness, thus obscuring any relationship between the two. Ecology is very complex, that’s why it is so much fun (but it makes it very difficult to verify causes and effects). Again, be creative in the discussion. Shade is just one example of many factors that influence plant growth. One experiment leads to another in the scientific method. In your discussion, use your conclusions to generate at least one new hypothesis that could be tested to further add to our knowledge of the effects of Pennsylvania sedge.