Background:
Two invasive beachgrasses were introduced to Pacific Northwest coastal dunes in the last two centuries. In 2012, the research group I am part of at OSU discovered that the two beachgrasses have bred, forming a hybrid. The two parent beachgrasses have different characteristics that affect the amount of sand they capture, and thus the shape of dunes they form. The hybrid beachgrass displays greater stem height and, in some cases, greater stem density than its parents, two traits positively correlated with sand capture.
- The research question that you asked (provide one question for each exercise).
Exercise 1: How does sand accretion along a transect within hybrid beachgrass patches compare to sand accretion outside of hybrid patches?
Exercise 2: How is species richness correlated with elevation every 2 m along a transect, using cross-correlation analysis?
Exercise 3: How does species richness vary with change in elevation every 2 m along a transect, using geographically weighted regression?
- A description of the dataset you examined, with spatial and temporal resolution and extent.
In this dataset, I have 26 GPS transects were ran in the shore-perpendicular direction that stretch from the waterline along the beach into the back of the dune. These intersect the hybrid patches at various points along the transect, although most hybrid patches have been found at the toe and face of the dune. I also have species richness data every 2 m along a transect. They were all collected over the course of 3 months in Summer 2021, are accurate to within 1 cm, and extend from Pacific City, OR in the south to Ocean Shores, WA in the north.
Fig. 1 (left): The cross-shore visualization of elevation along a GPS transect that intersects a hybrid beachgrass patch (points within the patch are shown by black points) near Fort Stevens, Oregon. Fig. 2 (right): The intersection of the GPS transect with the hybrid beachgrass patch, which is not depicted to scale.
- Hypotheses: predictions of patterns and processes you looked for.
For the first exercise, I predicted that sand accretion would be greater within the hybrid patches than outside, because of the hybrid’s taller and denser stems compared to its parents.
For the second and third exercises, I predicted that there would be lower elevation and less species richness at the area of the dune nearest the ocean, and greater elevation and more species richness in the area more inland. Thus, I expected to see high correlation values and coefficients at the start and ends of the transects, but not necessarily in the middle, with intermediate elevations and intermediate species diversity.
- Approaches: analysis approaches you used.
Exercise 1: For this first exercise, I conducted an informal slope analysis among all points in the dataset & visualized it in a plot. While this is not necessarily a formal/established approach, this step represented an initial stage of the analysis.
Exercise 2: I used the cross-correlation function (ccf() from the stats package) in R. However, prior to using this tool, I was required to do many pre-processing steps for the two datasets I was using: 1) my ecological species occurrence data at 2 m intervals along the transect, and 2) elevation data shown above, collected with a real-time kinematic GPS backpack.
Exercise 3: I used geographically weighted regression in R to look at how the regression coefficients vary along the transect.
- Results: what did you produce — maps? statistical relationships? other? Present the key, important results you created.
Exercise 1: The box and whisker plots of the slopes along the 26 transects display a wide variety of patterns. One transect from Ocean Shores, WA is shown below (Fig. 3). Not surprisingly, the points outside the patch have a much greater range and variation than those within the patch. The slope of many of these points is likely influenced by much more prominent factors than grass species, including wave energy, sand supply, and the pre-existing topography of the beach and dunes in the area.
Fig. 3: Box and whisker plots of the slope between all points along a transect, grouped by the x-axis into inside and outside of hybrid beachgrass patches.
Exercise 2: For exercise two, I produced a cross-correlation plot for each of my transects (Fig. 4). Overall, it seems that the majority of transects display a higher autocorrelation when lag values are low. However, as lag (or elevation) moves further away from 0, autocorrelation between species richness and elevation generally decreases. Many of these positive ACF values also range as high as 0.6 or 0.8 at a maximum.
Fig. 4: Cross-correlation function plot outputs from transects in Ocean Shores, WA.
Exercise 3: I produced plots for my dune transects and their coefficient values from the geographically weighted regression analysis, which illustrate the relationship between species richness and change in elevation. Many of the transects have coefficients that vary along a transect, although most transects show an increase in magnitude of coefficients steadily (Fig. 5).
Figure 5: Points (as latitude and longitude) along five dune transects, colored according to coefficient value size.
- What did you learn from each of the analyses you conducted (i.e., from each exercise)?
Exercise 1: I learned new techniques in MATLAB, and also how difficult it was to answer my Exercise 1 question as it was currently written. I realized that I need to think more deeply about my question, and how I would answer it using my current knowledge of my data and statistical techniques.
Exercise 2: I was able to do useful pre-processing and cleaning of my data and carry out new techniques I hadn’t tried before in cross-correlation. One of the main things I learned was that species richness and elevation along these coastal dune transects are generally positively correlated, although the strength of their correlation decreases as the magnitude of the lag increases.
Exercise 3: It was useful to learn that, for most transects, there is a steady increase in coefficient values that represent the relationship between species richness and change in elevation. Additionally, I learned that these geographically weighted regression results were complimentary, but not always consistent, with my cross-correlation results on a transect by transect basis.
- Significance. How are these results important to science? to resource managers?
These results begin to address questions of how the hybrid beachgrass will impact dune ecosystem services, including sand accretion and dune shape. Dune shape, in turn, may affect how well the hybrid protects against storms and sea level rise. Although these results aren’t able to answer that question directly, they nonetheless represent progress toward answering them. Managers may be able to use these results to decide how to interact with the hybrid: whether to encourage its spread, or control and even remove it.
- Software learning. Your learning: what did you learn about software (a) Arc-Info, (b) GIS programming in Python, (c) programming in R, (d) Modelbuilder in Arc,or (e) other?
I learned how to do several new techniques with new packages, including geographically weighted regression and cross-correlation analysis, in R. In addition, I improved my MATLAB skills and was able to successfully code several nested for loops. I also learned new data management techniques, such as how to more effectively annotate my code
- Statistics learning. What did you learn about statistics, including (a) hotspot, (b) spatial autocorrelation (including correlogram, wavelet, Fourier transform/spectral analysis), (c) cross-correlation/regression (cross-correlation, geographically weighted regression [GWR], regression trees, boosted regression trees), (d) multivariate methods (e.g., PCA, multiple component analysis), (e) other techniques (change detection/confusion matrices, other)?
By far, I made the most advances in learning for c). Specifically, I was able to conduct cross-correlation analysis and geographically weighted regression in R. Geographically weighted regression proved most difficult to conduct and visualize, especially considering the multiple steps and reformatting of my data I was required to do.
- Evolving question. How did the results of each analysis lead you to change/refine your question? Write out the original question you stated at the beginning of the class, and restate the question(s) you now plan to address.
My initial question overarching question that I attempted to answer for exercise 1 was: Does the hybrid capture more sand than its parents?
What I found, from the difficult of the first exercise, and after pivoting my question in the second exercise, is that it would be very difficult to answer this question with the data I have. With my current data, I am able to qualitatively characterize things like slope or volume inside and outside the hybrid patches. Additionally, I think it will be important to focus on sand accretion for patches closest to the beach (at the toe/crest of the dune), which receive the most sand deposition.
My new, tentative question that will likely evolve by Friday, and well beyond it, is: Do areas within the hybrid patch along a transect display greater changes in volume after a year, than at the same distance along a nearby, paired transect not within the hybrid patch? I can address this question using data from an upcoming field season, although I will need to think about this much more deeply before carrying out these collection methods.
- Future techniques. What techniques would you like to explore to answer your research questions in the future?
I need to continue to refine my methods of data collection and the data I will collect this upcoming field season, before I can answer my questions. However, I’d be interested in exploring other techniques with different data that I’m planning collecting on factors other than sand accretion. For instance, I’d be interested in undertaking hotspot analysis with point data of the occurrences of the hybrid and its parents on the dunes, which I will collect this upcoming field season. Additionally, I’d like to do a comparison of species richness within and outside of the hybrid patches, such as through a neighborhood or another hotspot analysis.
