Reva GillmanGeog 566 Exercise 2

Part 1.

1. Research question: What are the geographic distributions of some of the ‘riskier’ species that arrived on Japanese Tsunami Marine Debris (JTMD)? What do their native and non-native ranges look like, and how do they compare with each other?

First of all, I had to choose 4 species with clear invasion history out of the 104 JTMD species, to focus on. Out of the 31 with invasion history, I chose Asterias amurensis (seastar) and Hemigrapsus sanguineus (Japanese shore crab) since they are known to be an issue in other regions. I then chose two species with large non-native spread: Crassostrea gigas (Japanese oyster), an economically important aquaculture species, and Teredo navalis, the shipworm with an almost global distribution that has burrowed in wooden ships all over the globe for 100’s of years.

Within my spatial problem, I am asking the following research question type: What is the variability of property y? Property y is the geographic distribution of the riskier species. I am also able to ask: How are values of property y related to values of property x in space? For this problem, y is the native geographic distribution, and x is the non-native geographic distribution.

2. Spatial statistics notation: Property y, at location i, with neighbors at locations i+h and i-h. Although this doesn’t directly apply to my problem, I suppose y is the native geographic distribution, and x is the non-native geographic distribution, and could be represented as follows: yi = f(xi-h, i+h)

3. Spatial processes that my problem involves: attraction and repulsion, dispersal, diffusion, and advection. The currents largely control the dispersal of species via rafting, the reason some debris items landed in certain locations, and not in others. Also competition, as some of these species have out-competed species and become invasive in regions outside of their native range.

4. I will use inductive reasoning for my spatial problem. By looking at the visual representation of the geographic distribution of JTMD species, I can develop a theory based on that information, which entails moving from specific to general. By looking at the geographic distribution of the riskier JTMD species, I can use observations to develop a theory of their more prevalent native versus non-native regions, and compare those regions with each other.

5. I will be using descriptive statistics for my question: describing a pattern, and drawing

interpretations visually on the geographic distribution of the JTMD species.

6. My spatial problem will not subsume space and time, or consider it irrelevant. I will be looking at explicit concepts of space to analyze the problem. The spatial dimensions (geographic regions) are measured in objective units, but the evaluation of the regions that JTMD species are native to is fundamental to the study. Although looking at this explicit concept of space cannot demonstrate causation, I can get a flexible interpretation of causes because the geographic regions use location, distance, and arrangement, which allows for multiple interpretations of the cause of the dispersal of these particular species.

Part 2.

Marine Ecoregions of the World (MEOW)

Reva GillmanTutorial 2 Manipulating Layer Properties in ArcGIS ArcMap 10.4.1

1. Question that I asked:

What are the geographic distributions of some of the ‘riskier’ species that arrived on Japanese Tsunami Marine Debris (JTMD)? What do their native and non-native ranges look like, and how do they compare with each other?

First of all, I had to choose 4 species with clear invasion history out of the 104 JTMD species, to focus on. Out of the 31 with invasion history, I chose Asterias amurensis (seastar) and Hemigrapsus sanguineus (Japanese shore crab) since they are known to be an issue in other regions. I then chose two species with large non-native spread: Crassostrea gigas (Japanese oyster), an economically important aquaculture species, and Teredo navalis, the shipworm with an almost global distribution that has burrowed in wooden ships all over the globe for 100’s of years.

2. Name of the tool or approach that I used:

Manipulating Layer Properties in ArcGIS ArcMap 10.4.1 in order to manipulate the polygons in the shape file, to make them appear different colors according to which realms were documented as native or non-native regions for each species.

3. Brief description of steps I followed to complete the analysis:

First I made an excel spreadsheet of the species data, by going through each ‘risky’ species distribution, converting regions to realms, and typing that up in the spreadsheet. Then, I did a join with Realm_Code which matched up with the attribute table from the shape file. However, I ran into issues with mapping this data, as it would only map the region that was native, or non-native, without the other regions represented at all, so I had to figure out another method.

My second attempt was to directly select regions of the shape file, and change the symbology by going into selection, and clicking on use with this symbol. This may have eventually worked, but was very hard to figure out which regions to select for each species, and there was not an intuitive way to save the selections as a new layer.

Finally, I found out how to go into Layer Properties, and manipulate the shape file from there:

A. First you left-click on the layer you want to manipulate, and select Properties from the bottom of the options.

B. Go into SymbologyC. Underneath the Categories options on the left, select unique valuesD. From the value field, select the field that you are interested in, in my case that

was Realm_CodeE. Select the Add all values button on the bottom, which will put all of the

selected field options in the screen. F. From there, you can select a field, and remove it, or add values as needed, which

I did for each species

G. By double clicking on each field, you can select the appropriate color that you want to represent each category, you can change the outline of the symbol, the fill color, and texture. I did this to make the color of invasive realms one color,

and native realms another color, and regions where the species was both native and non-native another color/texture.

H. Then, you can copy and paste the layer, to manipulate again for the species, so you don’t have to start from scratch.

4. Brief description of results you obtained.

Below, there are the 4 maps of each species distribution, to see the extent of their ranges.

Crassostrea gigas Geographic Distribution

Hemigrapsus sanguineus geographic distribution

Teredo navalis geographic distribution

Non-nativeBoth (native and not)Native

Non-nativeBoth (native and not)

5. Critique of the method - what was useful, what was not?The final graphs are informative, and intuitive, and I think have a nice result. This method can be tedious if you want to look at many different layers of maps. For me, it worked out because I chose to look at four different layers of species geographic distributions, but if this method was less tedious I might have looked at more. By going through and manually selecting each polygon, or realm, that I wanted to highlight, I had a lot of control over what the final map looked like, and I liked the level of detail you can find with symbology, outlines of polygons, fill color, and texture of fill. The final maps are straightforward, and easy to save each layer, copy, and paste the next layer so you don’t have to start from scratch each time.