Campus Tree Inventory and GIS Database for St. Lawrence University Campus
Introduction
                      The purpose of this study is to collect an inventory of the trees found in the “walking” part of campus.  While this is not an exhaustive list of the trees found on St. Lawrence property, the main purpose of this study is to create a baseline GIS (Geographic Information System) of the distribution of tree species within several minutes of the science buildings.  An inventory of trees on St. Lawrence campus compiled in a GIS will provide a visual groundwork for various opportunities.                       Data includes Genus Species, DBH (diameter at breast height), and latitude/longitude coordinates for each tree in the study area.  All data is collected with either the Trimble GPS, or Cybertracker unit.  Differential correcting of the coordinates is acquired through the use of software online.  Spatial representation of all data points are provided through ESRI’s Arcview 3.3 software.                     One possible result of this project is the further development of campus vegetation.  Arboretums (a collection of woody plants representing the local suite of a vegetative community) are used across the world as an educational and aesthetic tool.  Arboretums involve not just a large diversity of tree and plant species, but are also designed to model an entire healthy ecosystem.  Trees are strategically planted to provide food, habitat, and protection for numerous organisms which live in a forest community.      Since there is a large species diversity in the area, classes studying the importance of biodiversity, ecology, and general biology could all utilize a nearby arboretum.  As this project involves finding the spatial representation of species diversity on campus, it would provide insight as to the best place an arboretum could be developed on this campus.  In addition to the pedagogical benefits of an arboretum, the aesthetic benefit of a managed forest is also significant. 
 
The cybertracker unit that I used to collect the majority of the data with, is composed of a Palm Pilot, and a GPS attachment.  The software used to communicate between the two components was written by scientists working in Africa on mammal population studies.  However, the data that needed to be collected was extremely difficult to obtain.  They found that tracking the animals, observing their routes, etc, was close to impossible without extensive training.  Bushmen who had been living in the area for generations, on the other hand, were not only able, but required to stalk animals, since they used them as a food source.  The main problem that developed was the trackers that could provide the best data weren’t literate.  The Cybertracker was developed as a way to employ the highly skilled indigenous locals.   The scientists created the databases, and then used graphical depiction of the activities they were after.  Creating scientific data through the use of an icon driven sequence allowed for extremely accurate scientific data.  Because all database items are represented as images, one can see the possibilities to involve people that do not have scientific training, but have skills that are immensely valuable.  Opportunities are present not just in other countries; involving local individuals should be a priority for the scientific community.  Science is often looking into the future for problems which may not be readily apparent at the present time, and attempting to make changes which will help decrease possible catastrophic effects.   However, since the problems are not readily apparently, and the changes that need to be made will affect local communities, misunderstanding and antagonism often result.  If communities on the other hand play an active role in the research, not only will scientists have the expert advice of someone who knows and is experienced in the location, but will also be playing a role in helping local acceptance and agreement of lifestyle changes.
Results
       Though the main purpose of this study was to provide a database which others could incorporate into their classes, or own research, there were several observations that were made.  While at first glace the species appears to be rather diverse, with a total of more than 30 different deciduous species alone.   However, over ˝ of the representative species appeared 5 or less times on campus, and a third appeared only once (Fig. 1).  Additionally, there appeared to be a significant age class discontinuity across campus (Forman, 1995).  For example, Sugar Maple trees show an opposite growth curve from what is expected for a normal forest. (Fig 2)
Conifers (Courtesy of Brad Baldwin’s Exotic Species Class
Deciduous
Figure 1. Number of trees per species on campus.
Figure 2.  DBH intervals for Sugar Maples on Campus
Poster By: Josh Earl
Literature Cited:
Niering William A.; Richard H. Goodwin. 1962. Ecological Studies in the Connecticut Arboretum Natural Area I. Introduction and a Survey of Vegetation Types. Ecology. 43:41-54
Forman, Richard T. 1995. Land Mosaics: The Ecology of landscapes and regions.  Harvard University.  
Discussion
        Most forest growth shows an initial large population of smaller trees, followed by smaller and smaller populations of larger trees.  Obviously, this is because as trees grow older, they are more susceptible to death.  This is a fine adaptation because the younger trees replace the older dying ones.  The trend of Sugar Maples on the campus however, leads one to believe that in the relatively near future, many of the tall stands of trees will be gone, and at the same time there will be very few younger trees to replace them.  Additionally, campus between ODY park street and University has some of the largest Sugar maples on campus, however it happens to have the lowest amount of younger trees.  If the university wishes to continue to have shade trees in the future, steps should be taken to make sure more young trees are available to take the place of the older ones.