Exploring spatial and temporal patterns of invasive aquatic species

Note:

This example case study presents an approach to using ArcGIS to see if there is a spatial and temporal pattern in the incidence of invasive aquatic mussels. While the data is real, the results shown here should be viewed only for demonstration rather than for conclusive analysis. The example illustrates the use of spatial analysis to reveal patterns in data to improve understanding of a particular issue.

The mussel invasion

Two exotic aquatic invaders, the zebra mussel (Dreissena polymorpha) and the quagga mussel (Dreissena rostriformis bugensis), have the potential to inhabit most of the fresh waters of the United States and could have negative impacts on a variety of native aquatic species and eventually entire ecosystems.

The zebra mussel was originally native to the streams of southern Russia, while the quagga mussel is indigenous to Ukraine. Both these Dreissena mussels are now considered an invasive species in the United States. Ecologically, both mussel species can interfere with feeding, growth, movement, respiration, and reproduction of native mussels. Economically, their impact is felt as they can attach themselves to pipelines and impact water movement through hydroelectric turbines as well as intake structures for drinking water and irrigation systems. In the United States, researchers estimated that zebra mussels cost the power industry $3.1 billion in the 1993-1999 period, with their impact on industries, businesses, and communities exceeding $5 billion.

The distribution of mussels across the USA

Since an established population of zebra mussels was first found in Lake St. Clair, located between Lake Huron and Lake Erie, they have spread throughout the country and have been found in 30 states. Quagga mussels have been reported in 16 states. Zebra mussels were first reported in 1988 and quagga mussels was first sighted in late 1989. The spatial distribution varies by species with only quagga mussels being seen in western states, however, it is not clear if this distribution simply reflects the timing and location of introduction.

Data showing reported locations of both zebra mussels and quagga mussels from 1998 to 2013, collected by the USGS, was downloaded from the National Atlas of the United States. Data is also available in a number of different formats from the USGS (http://nas.er.usgs.gov).

The locations of mussels across the U.S.

Do both zebra and quagga mussels pose the same risk?

Understanding the current geographic distribution, behavior and biology of these invasive species can lead to a better understanding of how they spread and may help limit their future impact. Exploring reported locations of invasive mussels can show differences in the distributions between the two species and demonstrate how the incidence of mussels varies during the year in different watersheds. This information could help inform future eradication programs.

Although both these Dreissena mussels have some similarities and have been confused in the past, they do have a number of differences that may impact how they spread across the country. The life-span of these two Dreissena mussels varies, although most live 3-9 years (USGS 2008). Zebra mussels can inhabit warm waters, however, quagga mussels are unable to survive water temperatures higher than 30 degrees Celsius. Zebra mussels are found in warm shallow nutrient rich waters whereas quagga mussels inhabit both shallow warm and deep cold waters that are nutrient poor. In time, quagga mussels may become the dominant species in some areas, such as the Great Lakes (MacIsaac, 1994).

In southern Lake Michigan, quagga mussels were reported to spawn earlier in the season and at greater depths then zebra mussels (Nalepa et al. 2010). Although quagga mussels spawn fewer eggs than zebra mussels over a season, their ability to inhabit colder deeper waters may allow them to build larger populations over time. Adult zebra mussels start to reproduce in the spring, when water temperatures rise to about 12 degrees Celsius, but it is thought that they may reproduce continuously in habitats where the water stays warm year-round.

Using the 16 years of data it is possible to investigate whether the number of mussels, by specie type, changes by month across different regions of the USA. Do quagga mussels always spawn earlier in the season than zebra mussels? Do zebra mussels reproduce continuously in regions where water temperatures tend to remain warmer year-round?

Each reported location of the zebra mussels or quagga mussels also has an associated date and can be mapped by month, for example. In this case, the pattern by year is not clear on a static map, but including animation can help to show the spread of mussels from Lake St. Clair to California. This information, however, is still difficult to express clearly without a more detailed mapping method.

The locations of mussels by species.

Explore the map in ArcGIS Online.

Exploring spatial and temporal details

To evaluate overall patterns, individual mussel reports need to be aggregated to areas. USGS hydrologic units that divide the United States into 21 major geographic areas, or regions provide reasonable boundaries for this task. These geographic areas contain either the drainage area of a major river, such as the Missouri region, or the combined drainage areas of a series of rivers, such as those that drain into the Gulf of Mexico.

In order to evaluate changes in mussel numbers over a season, which will be linked to spawning patterns, the total number, by species type, can be aggregated by month. A coxcomb chart allows you to visualize the monthly totals by region. In a Coxcomb chart (also known as a rose diagram), each category is represented by a segment, each of which has the same angle. The area of a segment represents the value of the corresponding category. They are, essentially, multivariate proportional symbols. Coxcomb charts are best used to demonstrate patterns rather than for subtle differences shown by exact numbers as these can be difficult to see.

Coxcomb features showing mussel numbers by hydrologic unit

Aggregating the data by hydrologic unit and month, shows that the numbers are significantly higher in some months, but this pattern varies geographically. The largest numbers are seen in the Great Lakes region, where it is thought that they were first introduced to the country. The coxcombs clearly show geographical differences between the two species, with the quagga mussels being found in higher numbers in the west of the country, namely the California and Colorado regions, while zebra mussels are almost nonexistent in these regions.

Across the different regions, the monthly patterns change suggesting that water temperatures do indeed affect the population sizes. In the Great Lakes region mussel numbers gradually increase from February, reaching a peak in August, and then gradually decline again until October. Interestingly, however, although November, January, and February show the lowest numbers, December shows a large number of reports for both species, which might warrant further study. Overall both species show broadly similar monthly patterns. The Mid-Atlantic regions also show a distinct August peak. This summer peak is less obvious in the Ohio region and Upper Mississippi region and not seen at all in the Lower Mississippi, Tennessee, Arkansas-White-Red, and Missouri regions. In the lower Colorado region, the quagga mussels reported the highest numbers in November, while the California regions showed no distinct monthly pattern. Explore the web map to see the mussel numbers by hydrologic region.

A better understanding gained from spatial analysis of 16 years of mussel reports can help inform how to tackle the mussel invasion problem to limit their future impact. Using analysis and visualizing the results as coxcomb features illustrates the spatial and temporal patterns of both species in a single graphic. By mapping the results of your analysis in this way, the information can easily be read. It helps to think about how your results are going to be mapped as part of your analysis. Here, the map type clearly show the differences in the results in a way that may not have been as clear if multiple maps had been used.

Workflow using ArcGIS Desktop

Finding the number of mussels by type and watershed

1. Intially you need to find the hydrologic unit each mussel has been reported in. To do this you should join the hydrologic units to the mussel reports using Spatial Join.

   

2. You can now summarize the number of mussels to the hydrologic unit (HUC2) in which they were located, by species, name, and month using Summary Statistics. Your data is now a table with a row for each unique hydrologic unit, species and month.

   

Creating the coxcomb features

1. Using the table of data, created by following the above steps, add a new text field to store month names. A text field must be used because these will eventually become field names.
2. In this new month field you should calculate the relevant month name based on the known month number so, for example Month 1 becomes January. This can be done by selecting the months by number (using Select by Attributes) and doing a field calculation, which honors the selected features. In some cases, the month was unknown and was entered as month = 0. We cannot use these data so for some records the new text field will be blank.

   

   • A short Python script can be used to automate these two processes (monthNames.py). A prefix should be added to the month names to ensure they are in alphabetical order when pivoted. This means that the coxcomb features are displayed clockwise from January to December.

     

     Note:

     Use the Field alias to show other labels if required.

3. You now want to divide the data by species. Use Select By Attribute on the table to select where the species is polymorpha and only select those rows where the month is known species = 'polymorpha' AND month > 0.
4. Export the selected features to a new table showing the number of polymorpha (zebra) mussels by hydrologic unit and month.

   

5. Repeat steps 3 and 4 above but this time select the rostriformis species (species = 'rostriformis' AND month > 0). This exported table shows the number of rostriformis (quagga) mussels by hydrologic unit and month.
6. Next, you must pivot the data so that the total number of mussel species is stored by watershed and month using Pivot Table. Repeat this for both the polymorpha and the rostriformis data tables.

   

7. The final process is to link our pivoted data tables to a location in the hydrologic unit. The coxcombs are displayed at a point location and you can use Feature To Point to obtain the hydrologic unit centroids. Use the Inside option.

   

8. In both pivoted data tables we have a field showing the hydrologic unit (HUC2) which can be used in Join Data to join the table to the point features you have just created. This step should be done twice, firstly with the polymorpha table and secondly, with the rostriformis table. Export each joined dataset to a new point feature class.

   

   
9. You can now run the Coxcomb Features tool with each point feature class. A coxcomb will be created for each unique location, identified by the hydrologic unit (HUC2). A segment is created for each field that is input in the List Fields box so only month fields should be selected.

   

   • The Coxcomb scale value allows you to change the scale of the coxcomb features. All coxcombs are rescaled proportionally, ensuring the largest coxcomb radius is this input. The Measure tool can be used to find a suitable value.

     

Automation using ArcGIS Desktop

1. The model below combines all the steps above to ensure that the original mussel data is in a format ready to use in the Coxcomb Features tool.

   

2. The output from this model is a point feature class of hydrologic unit centroids with the number of mussels by species and month. Use Select by Attributes by species and export the data into two point feature classes with one for species polymorpha and one for species rostriformis.
3. The two point features classes, created in steps one and two above, can then be used in the Coxcomb construction tool. The coxcomb features are created using the monthly fields that contain the total number of invasive mussels by hydrologic unit.

   

4. Step three should be done for each species (polymorpha and rostriformis).
5. The same scale should be used for both coxcomb feature classes, as they are displayed together. The coxcomb scale value for the second analysis (species rostriformis) uses the segment radius from the first coxcomb features (species polymorpha) with the same value as the largest in the second aggregated dataset (rostriformis).

   

References

Nalepa TF, Fanslow DL, Pothoven SA. 2010. Recent changes in density, biomass, recruitment, size structure, and nutritional state of Dreissena populations in southern Lake Michigan. J. Great Lakes Res. 36: 5-19.

MacIsaac, HG. 1994. Comparative growth and survival of Dreissena polymorpha and Dreissena bugensis, exotic mollusks introduced to the Great Lakes. J. Great Lakes Res. 20(4):783-790

Ram JL, Karim AS, Banno F, Kashian DR. 2011. Invading the invaders: reproductive and other mechanisms mediating the displacement of zebra mussels by quagga mussels. Invertebrate Reproduction & Development 56(1): 1-32.