INTRODUCTION
A custom project was assigned to address a geographic question of the students' choosing. The objective chosen was to track beavers and their associated ecological impacts on a property in Ogema, WI to determine whether beaver genocide is justified. Beavers have frequented this property (see Figure 1) for the past couple years and through generations have migrated northwest, reshaping the landscape along the way.
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| Figure 1: Area of Interest |
Although beavers can bring positives to the environment, their actions can often cause unwanted side-effects and diminishing value of the landscape. Many poplar, birch, and occasionally oak and maple trees are chewed down. Often times these fallen trees cause additional damage and prevent future growth to the nearby trees. Damming of ponds and digging trenches to transport wood causes directed flooding to otherwise dry property. This causes already established trees to die from being submerged in the new waterline.
In order to analyze the ecological impacts that beavers have had, proper project design is essential in producing accurate and meaningful results. Carefully designing an organized geodatabase with domains ensures proper data collection and meaningful results to help answer the objective desired.
For this objective, affected trees on the property were marked to gauge the extent of damage to the property including the tree type, diameter, height and the date and extent of chew. Beaver dams were also marked to show where these resources were going toward and how the beavers have contained water and shaped the landscape. Finally, the beaver huts and scent mounds were marked to evaluate the number of beavers and draw patterns. Together, this data can be used to get a better comprehension of the impacts beavers have had on the landscape.
METHODS
Design of a geodatabase was constructed in ArcCatolog, collection of data was gathered in ArcCollector, processing was handled in ArcMap, and design in Adobe Illustrator. The first stage in tracking beaver impacts was to design an organized geodatabase.
Designing a Geodatabase in ArcCollector
The database was first split into two feature datasets. The first,
EcologicalImpacts, contains feature classes pertaining to the environment. The second,
Beavers, pertaining to the animals themselves. Within EcologicalImpacts are feature classes
AffectedTrees and
BeaverDams.
The AffectedTreees feature class was created to show the extent of wood damaged directly by chew and to analyze spatial patterns. The BeaverDams show how the beavers have reshaped the landscape by containing water in low areas and flooding landscape to access additional areas for tree removal. This provides basic and direct impacts beavers have on the environment.
Within the Beavers feature dataset are feature classes
BeaverHuts and
ScentMounds. The beaver huts locate where the beavers have previously and currently live and to draw spatial connections to the affected landscape. The ScentMounds provide additional insight to where the beavers currently are located. Beavers dig up and carry mud and branches to form a pile and leave their scent to warn other beavers the area is inhabited.
This provides information directly relating to the beavers themselves and a way to connect the environmental impacts to the beavers.
Although for this project there is no topologies or networks, it is still good practice to organize the catalog tree in case the project expands and topologies need to be made--it is easier to locate layers in the meantime (see Figure 2).
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| Figure 2: Project geodatabase design in ArcCollector |
After the feature classes were created, domains were established to limit the possible attributes for each field within the feature class--this ensures data integrity. The AffectedTrees feature class was created with
Type, Diameter, Height, Date, and
Chew fields. A domain was created for the text field
Type limiting the possibilities to poplar, birch, apple, oak, maple, cottonwood, and alder (see Figure 3). This field was created to determine which types of trees have most suffered from beaver chewing.
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| Figure 3: Coded domain limiting type of tree to a set of options |
Range domains were then created (see Figure 4) for the long integer fields
Diameter and Height limiting the possibilities to a range of values, preventing manual errors out in the field and editing during processing.
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| Figure 4: Range domain limiting the value to a range of possibilities |
The diameter and height fields were created to determine years of growth and amount of wood that was taken from the landscape. The years of growth was calculated by multiplying the diameter by 2, which is the growth factor of aspens for a forest-grown tree with competition. The
Date field was created to determine the date of the last chew on the affected tree. This field was created to determine where most beaver activity is happening and patterns across time. The possibilities were limited by a domain into these categories:
- Old: Weathered, smooth chew marks and dark hardwood at chew with no woodchips at base of tree and vegetation growing on and over the tree
- Dated: Slightly-weathered chew marks and darkened hardwood at chew with few to no woodchips at base of tree and slight vegetation growing on and over the tree
- Recent: Rough, defined chew marks and light hardwood at chew with woodchips under the foliage at base of tree and slight to no vegetation growing on and over the tree
- Fresh: Sharp, jagged chew marks and white hardwood at chew with woodchips over the foliage at base of tree and no vegetation growing on and over the tree
Figures 5, 6, 7, and 8 show examples of each category in the field:
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| Figure 5: Smooth chew marks with dark hardwood, no woodchips, and vegetation growth over tree indicating an old chew |
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| Figure 6: Weathered chew marks with darkened hardwood and few wood chips indicating a dated chew |
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| Figure 7: Slightly-faded chew marks with light hardwood and wood chips beneath foliage indicating a recent chew |
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| Figure 8: Sharp, jagged chew marks with white hardwood and wood chips above foliage indicating a fresh beaver chew |
Finally, the chew field was limited by a domain to
Full and
Partial to indicate if the affected tree had been fully or partially chewed by a beaver. A well organized geodatabase structured through domains allows easy and accurate data collection.
Collecting Data Using ArcCollector
The layers created in the previous section were then published to an ArcGIS Online account as a service (see Figure 9).
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| Figure 9: Publishing a service in ArcMap for use of a webmap in ArcGIS Online |
Feature access allowed creating, updating, deleting, and syncing so in data collection all users were able to perform those functions. Descriptive metadata was logged for the service and then published. A map was then created in ArcGIS Online and the published service was then added as layers. The map was then saved and ready for data collection on the ArcCollector app.
To collect data, the ArcCollector application was downloaded to a phone. The app then shows all user maps through the personal ArcGIS Online account (see Figure ). The option to download the map was used; this feature allows users to access their map and collect data for all layers while offline and without data connection. Users can then sync their data later when they have access to a connection.
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| Figure 10: ArcCollector app maps with the option to download and sync in areas of no cellular connection |
Once the Ecological Impacts of Beavers map was downloaded and ready for use offline, data collection can begin. The Collect New feature directs the user to the layers created in ArcCatalog in the previous section as shown by Figure .
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| Figure 11: ArcCollector app showing layers available in the Collect New Feature icon |
When Affected Tree is selected, the ArcCollector app directs the user to the fields within the feature class. When selecting the Type field, a popup shows the set of allowed terms designed in ArcCatalog by using a domain (see Figure ).
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| Figure 12: A list of allowable terms for a field in ArcCollector |
The long integer fields such as diameter and height within the Affected Trees layer only allows a value within the established range determined in ArcCatalog (see Figure ).
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| Figure 13: A range of allowed values for a field in ArcCollector |
The yellow caution icon to the far right in the figures above indicate that the field must have a value in order to collect the data point. This was determined previously in ArcCatalog by not allowing null values for these fields.
When collecting new features in ArcCollector, the app records the data at the coordinates the user's phone shows. However, there is a function to allow the user to collect data at any point on the map (see Figure ).
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| Figure 14: The collect data from a point on the map function in ArcCollector |
This feature allows the user to collect data at a point that is otherwise inaccessible. In this project, it made collecting beaver huts possible because navigating over thin ice is not desirable.
RESULTS/DISCUSSION
Figure shows the final screenshot containing 151 points in ArcCollector after all data was gathered. The symbology for the map is listed below:
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| Figure 15: Final data collection in ArcCollector |
Although 151 affected trees were collected, there were far more observed in the field--too many to collect in one day. For the sake of time and the objective of this project, this was more than enough to observe spatial patterns and extent of direct ecological impacts. It would be safe to assume there was on average around 3 other affected trees within 5 feet of each collected point. Data was collected from the house (blue dot in Figure ) northwest to the furthest beaver hut, mostly lining the ponds and along the trails. Below is an interactive map showing all data collected.
Figure 16 shows beaver activity on affected trees. The clustering of recent and fresh trees to the northwest supports the migration pattern of the beavers moving northwest. There were a considerable number of other trees in this area with fresh and recent chews, but limited to the scope of project were not marked. The pattern of migration is also supported by the beaver huts themselves (having vegetation growth and the size). However the cluster of fresh and recent chews to the far east was a surprise. The forest just west of this area has recently been flooded allowing the beavers a new area to chew, which they've fully taken advantage. These trees most likely were chewed to reinforce the southern dams.
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| Figure 16: Beaver activity using the date of chew classification of affected trees |
Figure 17 shows the hydrologic impact of beaver dams. As a whole, the property lies on mostly low land. Along the waterline, ridges normally contain the water into swamp and a larger pond at the northern-most section. However, the beavers have formed multiple dams along this swamp area to form a chain of shallow ponds. These chambers of water flood outward into otherwise dry land where current trees exist, slowly killing submerged trees. The beavers then dig trenches for narrow pathways of water to transport the newly accessible area of trees.
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| Figure 17: Hydrologic Impact showing the dams and waterline of ponds |
Figure 18 shows the types of trees affected by beavers. Most all trees were poplar due to beaver preference and the abundance of such trees on the property. For the number of birch on the property, the percentage of trees chewed was consistent with the poplar trees. On a rare occasion a beaver had chewed an oak or maple tree. Since there are plenty of other desirable trees, it was either an honest mistake or a beaver hell-bent on frustrating the landowner.
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| Figure 18: Type of trees affected by beavers |
Figure 19 shows the age of trees affected by beavers. There were many 5-9 and 15-19 year-old trees logged. There were a few outliers that reached up to 30 years old.
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| Figure 19: Age of trees affected based on diameter multiplied by the growth factor of aspen |
The average age of affected trees logged was 14 years old. This is a substantial loss to the environment due to the setback in tree maturity for a healthy harvest. Fourteen years of tree growth lost for 150 trees requires lots of resources with no benefit to the land owner.
Figure 20 shows the height of trees affected by beavers. In total, there was 4,740 ft. of wood lost to beavers. Since only 150 data points were logged, this number is far greater and could be roughly estimated at 25,000 ft. Granted, this would not be considered board feet of lumber, but still has value at maturity.
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| Figure 20: Height of trees affected by beavers |
CONCLUSION
To conduct a project worthwhile of time, a clear objective should first be determined and the project should then be designed accordingly to specifically address this objective. This will ensure the appropriate data will be collected producing meaningful results to be analyzed.
For this project, the objective gave insights into the considerable ecological impacts the beavers have had on the property. The affected trees and beaver damage showed the extent of direct impacts the beavers have had while the beaver huts showed the actual movement and presence of the beavers themselves. With this information, it can be determined that the beavers are overpopulated causing more damage than positive impacts for the owner of this property. Many trees that have taken over 20 years to grow have been removed, causing additional damage to nearby trees. An extensive number of additional trees will die from the flooding the beaver dams have caused. Although beavers can provide positive effects to the landscape, the owner should feel justified in removing them (see Figure 21).
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| Figure 21: A justified, happy landowner successfully removing a well-fed beaver in Ogema, WI |
Designing a new project without experience in the subject matter often presents difficulties because its hard to foresee everything. It would've been helpful to meet the project objective with more detail by collecting indirect impacts of the beavers. The number of additional trees damaged could've been collected in a field within the affected trees feature class to show a more complete extent of damages. Additionally, the project could be expanded by creating a line feature class to provide the waterline of the ponds. Older aerial imagery could then be digitized to assess the previous waterline. The area between the two lines would give an assessment of the flooding incurred after damming of the ponds. The number of trees in this flooded area could then be estimated to provide a number of additional tree loss.
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