In Lesson 3, we created several custom datasets for our study area wetlands within the Ottawa National Wildlife Refuge. These data contain information about plant species, vegetation groups, and invasive species for five snapshots in time between 1939 and 2005. In Lesson 4, we will use these datasets to understand how vegetation changes in response to water level fluctuations. In particular, we are interested in how emergent vegetation changes, since this group of plants provides the highest quality habitat in the wetland. We are also interested in how invasive species spread over time. Comparing multiple datasets over many time periods can get a bit complicated. In this lesson, we will explore several tools to make it easier to identify trends over time between multiple datasets.
Lesson 4 is a continuation of the scenario from Lesson 3 - "You are part of a research team tasked with creating a restoration plan for a degraded wetland complex. You need to understand how the vegetation within the wetland has historically responded to changes in water levels. This information will enable you to predict the health of the wetland in future scenarios, including anticipated hydrological changes due to climate change. You begin by searching for publicly available sources of data for your analysis. You find that there is not a dataset that has sufficient detail about vegetation for your study area. Furthermore, you are unable to find a dataset that shows wetland vegetation at multiple points in time. Your team hires a remote sensing specialist to acquire and interpret historical imagery and digitize polygons representing vegetation over time. Your job is to figure out how to use the vegetation data and GIS software to understand the relationship between fluctuating water levels and changes in vegetation."
At the successful completion of Lesson 4, you will have:
If you have questions now or at any point during this lesson, please post them to the Lesson 4 Discussion.
This lesson is worth 100 points and is one week in length. Please refer to the Course Calendar for specific time frames and due dates. To finish this lesson, you must complete the activities listed below. You may find it useful to print this page out first so that you can follow along with the directions. Simply click the arrow to navigate through the lesson and complete the activities in the order that they are displayed.
SDG image retrieved from the United Nations [1]
Last week, we talked about why wetlands are important, threats to wetlands such as human activities and invasive species, and wetland protection and restoration programs. This week, we will discuss how wetlands function. Hydraulic conditions are very important in wetland ecosystems because they influence their physical and chemical properties. Water depth is particularly important because it influences which types of vegetation are present, their abundance, and where they grow. Certain types of vegetation provide much better habitat than others. For example, aquatic and emergent vegetation provide cover that fish need to hide from predators and raise their young. Plants can be grouped into a few main categories based on the depth of water they prefer (listed from deepest water to dry land): submersed aquatic, floating aquatic, emergent, and terrestrial (e.g., shrubs and trees). These groups should look familiar to you (Hint: look in the Veg_Group shapefiles we created last week).
Wetlands are very dynamic; the physical and chemical properties of a given wetland can vary depending on current hydraulic conditions within a watershed. Some wetlands fluctuate more than others, especially those that are hydraulically connected to larger bodies of water such as drowned river-mouth wetlands along the Great Lakes or tidal salt marshes along the nation’s coasts. In these types of wetlands, the water elevation of the wetland rises and falls in response to water elevation changes in the main body of water. Water levels can fluctuate at different time scales, such as centuries, decades, annually, seasonally, daily, and even hourly. For example, the graph below shows the water levels of Lake Erie between 1850 and the present. You can see that water levels can fluctuate by more than 3 ft in a period of one or two years.
As water levels rise and fall, the water depths at any given location within a wetland will vary based on its bathymetry. For example, in an area with gentle slopes, an increase in water elevation will be spread over a larger area, so the water depth will not increase as much as in an area with steep slopes. This constant change in water depths naturally regulates plant communities. During periods of lower water levels, species that require deep water don’t survive. At the same time, underlying soils are exposed, allowing seeds from a variety of plants to germinate and mature. The opposite is also true. During periods of high water, species that require shallow water are drowned and eliminated. When the hydraulic properties of a wetland are modified, the natural cycle of vegetation regulation and regeneration is disturbed. Without low water levels to control their growth, some species are able to thrive season after season while others are never given the opportunity to grow.
The drowned-river mouth wetlands within our study are part of the Ottawa National Wildlife Refuge, which was created in 1961 to preserve vital habitat for migratory birds. The refuge contains approximately 4,500 acres of wetlands, the majority of which have been diked to control their water levels for over 60 years. Refuge managers use the dikes to maintain a series of ponds with different water depths at different times of the year. This allows them to create habitat for a variety of species, though management techniques favor migratory birds. By mimicking the natural rise and fall of water levels within the diked wetlands, emergent vegetation, which is habitat for many species, is able to thrive. Without the dikes, much of the habitat would not exist. However, the dikes hydraulically disconnect the pools from Crane Creek and Lake Erie, so that only a subset of wetland species can utilize the habitat. For example, fish, clams, and other small organisms cannot travel over the dikes.
Only a small portion of the wetlands in the refuge are not diked (e.g., wetlands within the study site); however, they are severely degraded. These wetlands have the potential to provide critical habitat since they are still connected to Lake Erie. The frequent high water levels of Lake Erie since the 1970s have contributed to the lack of natural regeneration of emergent vegetation in the undiked wetlands. Without human intervention, it is unlikely that water levels will lower enough to re-establish the vegetation that fish use for spawning and protection of their young. Wetland managers are also struggling to control the spread of several invasive plants, that threaten the native flora and fauna, including giant reed-grass (Phragmites australis), reed-canary grass (Phalaris arundinacea), narrow-leaved cattail (Typha augustifolia), purple loosestrife (Lythrum salicaria), and flowering rush (Butomus umbellatus).
GIS is a powerful tool to help wetland managers. We know that wetlands fluctuate over time in response to changes in local and regional hydrological conditions. Historical aerial photos can help us understand these changes over time. For example, they can show how vegetation in a particular wetland has responded in the past to changes in water levels. Digitizing the vegetation into a GIS database is much more useful than just looking at the images. Once the data are in a GIS format, wetland managers can easily calculate statistics, identify trends, and create models that allow them to predict the types and abundance of vegetation they can expect at different water levels. For example, they could model future vegetation changes in response to water level fluctuations caused by climate change. They can also use the data to create baseline vegetation maps to evaluate restoration efforts, such as attempts to regenerate emergent vegetation, map the spread of invasive species over time, and evaluate control methods.
Last week, we used several publicly available datasets to familiarize ourselves with our study area wetlands. We also created several new datasets related to wetland vegetation, including species, vegetation groups, and invasive species. In Lesson 4, we are going to use this data to explore a real-world example of how GIS can be used to assist wetland managers in restoration efforts. We will also explore several methods in ArcGIS to interpret and compare multiple time-series datasets.
There are two types of required readings for Lesson 4, USGS information and Esri Help Topics, and a couple of websites that I would like you to explore. The first reading is a fact sheet that provides more information about the invasive species in our study area. The second link sends you to a Virginia Institute for Marine Science (VIMS)/Center for Coastal Resource Management (CCRM) page that outlines GIS methods that are used when producing a shoreline and tidal marsh inventory. The third is a link to the Virginia Coastal Resource Tools Portal and within that page is a link to the Virginia Comprehensive Map Viewer. The Comprehensive Map Viewer displays a specific example of the shoreline and tidal marsh inventory produced by the CCRM. Feel free to explore additional VIMS/CCRM pages, there are many additional links that provide tidal marsh inventory examples. There are also a handful of Esri help topics related to operations we will use in ArcGIS during the Step-by-Step Activity.
Find the help articles listed below on ArcGIS Pro Resource Center [7] website.
This section provides links to download the Lesson 4 data and reference information about each dataset (metadata). Briefly review the information below so you have a general idea of the data we will use in this lesson.
Note: You should not complete this activity until you have read through all of the pages in Lesson 4. See the Lesson 4 Checklist for further information.
Create a new folder in your GEOG487 folder called "L4." Download a zip file of the Lesson 4 Data [13]and save it in your "L4" folder. Extract the zip file and view the contents. Information about all datasets used in the lesson is provided below.
In Lesson 4, we will use many of the same datasets from Lesson 3, including the custom data sets we created in Part II of the Step-by-Step Activity. I have provided clean copies of these datasets in the zip file above. Please use these during Lesson 4, just in case you made an error during Lesson 3. You may want to compare the data you created in Lesson 3 to the provided datasets and see if there are any differences.
In Part I, we will explore tools to visually explore and compare multiple datasets, such as animations and layouts with multiple map frames. In Part II, we will explore tools to statistically compare multiple datasets, including calculating percent area and creating graphs. We will use both techniques to interpret our data and explore how vegetation within our study area changes over time as it responds to changes in water levels.
Note: You should not complete this step until you have read through all of the pages in Lesson 4. See the Lesson 4 Checklist for further information.
Part I, we will explore several tools and technique to make it easier to visually interpret patterns in your data using ArcGIS. These can be especially helpful when you have multiple datasets to compare.
Year | water Level (m) | High, Med, Low |
---|---|---|
1962 | 173.9 | |
1973 | 174.9 | |
2005 | 174.2 |
Based on the Lake Erie Hydrograph, how do the water levels for 1962, 1973, and 2005 compare to the long term averages for Lake Erie? Which years had the highest and lowest water levels between 1920 and the present?
One of the challenges of looking at time-series data of the same location is that all of the datasets overlap each other. It is very difficult to see all of the datasets at the same time if you have them all on the same map, especially if they are polygon files.
In this lesson, we arranged the layers within each group chronologically. You could also arrange them in a different order, such as by their water level (low, medium, high) to visualize how the vegetation changes correlate with water level changes.
Make sure you have the correct answer before moving on to the next step.
When you preview your animation, you should see one layer turned on at a time beginning with the VegGrp_60s and ending with the VegGrp_00s.
If your data is not close to the example, go back and redo the previous step. You’ll need to clear the animation first by going to the View tab, Animation group, select Remove.
If you want to be able to view your animation outside of ArcGIS, you can export your animation to a video file. You can also make your animations more sophisticated by exploring the available animation tools and options within ArcGIS. For example, you can add looping, string multiple animations together, add time-series labels, and add graphs that update over time along with your animation. You can find more information, such as help articles, sample animations, and tips in the Esri help topics.
Animations are great for emailing to a client or adding to a presentation. However, if you want to print your maps, you need to create a layout. We are going to create a layout with multiple map frames to make it easier to compare our data over time. When working with multiple map frames that show similar information, it is easier to set the symbology, extent, and scale in one map, then make copies of the map, instead of setting up each map separately.
The final map layout should include all of the following elements:
In ArcGIS Pro, if two or more map frames reference the same map, any manipulation to the layers in the map (such as turning any layer on or off or zooming in or out) affects both map frames because the layout is referencing the same Map. To bypass this, a separate Map must be referenced for each Map Frame in a Layout. Go to the Insert tab, Project group, and select New Map. Insert six New Maps to your project (each should default to a different name Map, Map1, Map2, Map3...).
Switch back to your original Map. Switch off the Open Street Map Basemap for now, as it will increase the loading time while you are setting up your layout. Adjust your scale and extent, right-click on “Study_Site” in the Contents pane > Zoom to Layer. Turn on the 60sVegGrp layer.
Hold down the control key and highlight the "Study_Site", "OttawaNWR", "Vegetation Group" and "OpenStreetMap" layers in the Contents pane. Right-click and select Copy.
Go to Map1, right-click on the map name in the Contents pane > Paste. Turn the Study_Site, OttawaNWR, and 70sVegGrp layers on. Do the same in Map2 but turn Study_Site, OttawaNWR, and 00sVegGrp layers on.
Switch back to your original Map. Adjust your scale and extent, right-click on “Study_Site” in the Contents pane > Zoom to Layer.
Hold down the control key and highlight the "Study_Site", "OttawaNWR", "Invasive Group" and "OpenStreetMap" layers in the Contents pane. Right-click and select Copy.
Go to Map3, right-click on the Map name in the Contents pane > Paste. Turn the Study_Site, OttawaNWR, and 60s_Invasive layers on. Do the same in Map4 but turn Study_Site, OttawaNWR, and 70s_Invasive the layers on. And, then in Map5 turn on Study_Site, OttawaNWR, and 00s_Invasive the layers on.
Go to Map6, right-click on the Map name in the Contents pane > Paste. Turn the Study_Site, and OttawaNWR layers on.
Adding neatlines to your map layouts helps to visually group elements together. This is helpful when your map has a lot of information. Go to the Insert tab, Graphics and Text group, and then click on Rectangle. After you place the rectangle in the layout, you can select it and right-click to format and adjust the symbology settings of the neatline.
Visually exploring your data is a good way to start interpreting your results. However, it is difficult to determine the magnitude of change just by looking at a map. Calculating statistics allows you to have actual numbers to work with, allowing you to say that “variable x increased by 12%” instead of “variable x increased.”
While calculating statistics, it is very easy to make mistakes such as typos, choosing incorrect input layers, or using incorrect order of operations. To avoid possible errors, you should first visually explore your data so you have an idea of the trends that exist in the data. After calculating statistics, you can compare your results to your visual interpretation to make sure your statistical results seem reasonable.
Study Year | Water Level (High, Med, Low) | Area Open Water (sq m) | Area Emergent Vegetation (sq m) | Area Invasive Species (sq m) | Area Controlled Invasive Species (sq m) |
---|---|---|---|---|---|
1962 | |||||
1973 | |||||
2005 |
Which year has the most emergent vegetation? Which year has the most open water? Did you find it difficult to compare such complex numbers (lots of digits and decimal places)?
Study Year | Water Level (High, Med, Low) | % Tot. Area Open Water | % Tot. Area Emergent Vegetation | % Total Area Invasive | % Tot. Area Controlled Invasive |
---|---|---|---|---|---|
1962 | |||||
1973 | |||||
2005 |
Which year has the most invasive species? Which year has the least open water? How does this correlate with water levels? Which files have the most missing data? After comparing several datasets using calculated areas and percent total areas, which technique do you find is easier to detect trends between multiple datasets?
After experimenting with both visual and statistical techniques to determine trends in your data, can you think of any scenarios in which one is preferable over the other?
That’s it for the required portion of the Lesson 4 Step-by-Step Activity. Please consult the Lesson Checklist for instructions on what to do next.
Advanced Activities are designed to make you apply the skills you learned in this lesson to solve an environmental problem and/or explore additional resources related to lesson topics.
Use the tools and techniques covered in the lesson and data within your L4 folder to answer questions related to the 1930s and 1950s data. You may want to read the related questions within the Lesson 4 Quiz before completing the activity so you know what information to look out for.
In Lesson 4, we explored several techniques to interpret data and compare multiple datasets over time. Lesson 4 concludes the two-part lesson in which we completed the typical required steps in a GIS workflow (acquire or create new data, understand data content and limitations, customize data for your project, design & run analysis, interpret results, present results). In Lessons 5-8, we will demonstrate how to use several tools in ArcGIS, AGO, and Spatial Analyst to address a variety of specific environmental questions.
Lesson 4 is worth a total of 100 points.
Map Layout | The layout is posted and includes the required elements (6 map frames and an overview map, legend, scale bar, north arrow, titles, water levels, data sources, and author). (20pts) | The layout is present but is missing one or two required elements. (15pts) | The layout is present but map is missing several elements or is poorly designed. (10pts) | Map is missing. (0pts) | 20pts |
---|---|---|---|---|---|
Reflection | Discussion is present and includes ~500 words addressing ways in which maps are effective, challenges to communicating this data, and other presentation options. (15pts) | Discussion is present but is missing a required topic. (10pts) | Discussion is present but is missing several required topics. (5pts) | Discussion is missing. (0pts) | 15pts |
Prose Quality | Is free or almost free of errors (complete sentences, student's own words, grammar, spelling, etc.). (5pts) | Has errors, but they don't represent a major distraction. (2pts) | Has errors that obscure meaning of content or add confusion. (0pts) | 5pts | |
TOTAL | 40pts |
If you have anything you'd like to comment on, or add to the lesson materials, feel free to post your thoughts in the Lesson 4 Discussion. For example, what did you have the most trouble with in this lesson? Was there anything useful here that you'd like to try in your own workplace?
This page includes links to resources such as additional readings, websites, and videos related to the lesson concepts. Feel free to explore these on your own. If you'd like to suggest other resources for this list, please post them in the Lesson 4 Discussion.
Links
[1] https://www.un.org/sustainabledevelopment/news/communications-material/#FAQ
[2] https://www.glerl.noaa.gov/data/wlevels/#observations
[3] https://www.e-education.psu.edu/geog487/sites/www.e-education.psu.edu.geog487/files/activities/lesson05/2009-3_phragmites.pdf
[4] https://www.vims.edu/newsandevents/topstories/2019/ccrmp.php
[5] https://cmap22.vims.edu/VACoastalResourcesTool/
[6] https://cmap22.vims.edu/VACoastalResourcesTool/?page=CoastalViewerPage
[7] https://www.esri.com/en-us/arcgis/products/arcgis-pro/resources
[8] https://pro.arcgis.com/en/pro-app/help/mapping/layer-properties/import-symbology-from-another-layer.htm
[9] https://pro.arcgis.com/en/pro-app/help/mapping/animation/overview-of-animation.htm
[10] https://pro.arcgis.com/en/pro-app/help/mapping/animation/author-a-new-animation.htm
[11] https://pro.arcgis.com/en/pro-app/help/mapping/animation/view-the-animation-s-keyframes.htm
[12] https://pro.arcgis.com/en/pro-app/help/analysis/geoprocessing/charts/charts-quick-tour.htm
[13] https://www.e-education.psu.edu/geog487/sites/www.e-education.psu.edu.geog487/files/activities/lesson04/L4Data.zip
[14] https://www.glerl.noaa.gov/data/dashboard/GLD_HTML5.html
[15] https://www.fws.gov/refuge/ottawa
[16] https://www.friendsofottawanwr.org/refuge-challenges.html
[17] http://sws.org/
[18] http://www.epa.gov/owow/wetlands/
[19] https://www.invasivespeciesinfo.gov/
[20] http://glc.org
[21] https://ohiodnr.gov/static/documents/wildlife/fish-management/Ohio%20AIS%20State%20Management%20Plan.pdf
[22] https://www.epa.gov/wetlands/classification-and-types-wetlands#undefined
[23] http://www.fws.gov/midwest/endangered/clams/zebra.html