1.  A description of the research question that you are exploring.

I am interested in how the spatial pattern of invasion by the recently introduced annual grass, ventenata, is influenced by the spatial pattern of suitable habitat patches (scablands) via the susceptibility of these habitat patches to invasion and ventenata’s invasion potential.  Habitat invisibility is determined by the environmental characteristics, community composition, and spatial arrangement of suitable habitat patches and the invasibility of ventenata is influenced by its dispersal ability and fecundity.

I am also interested in understanding how spatial autocorrelation influences relationships between ventenata, plant community composition, and environmental variables within and across my sample units.

2. A description of the dataset you will be analyzing, including the spatial and temporal resolution and extent.

I collected spatial data (coordinates and environmental variables) and plant species abundance data (including ventenata) data for 110 plots within and surrounding seven burn perimeters across the Blue Mountain Ecoregion of eastern Oregon (Fig. 1). Target areas were located to capture a range of ventenata cover from 0% ventenata cover to over 90% cover across a range of plant community types and environmental variables including aspect, slope, and canopy cover within and just outside recently burned areas. Once a target area was identified, plot centers were randomly located using a random azimuth and random number of paces between 5 and 100 from the target areas. Sample plots were restricted to public lands within 1600m of the nearest road to aid plot access. Environmental data for sample plots includes canopy cover, soil variables (depth, pH, carbon content, texture, color, and phosphorus content), rock cover, average yearly precipitation, elevation, slope, aspect, litter cover, and percent bare ground cover. I am planning to identify and calculate spatial pattern of habitat patches using Simpson Potential Vegetation Type raster data (Simpson 2013) to 30m resolution in Arc GIS which was developed to identify potential vegetation types across the Blue Mountain Ecoregion.

3. Hypotheses: predict the kinds of patterns you expect to see in your data, and the processes that produce or respond to these patterns.

Ventenata appears to readily invade unforested, rocky scabland patches, but is less prominent in surrounding forested areas. These areas may act as “hotspots” of invasion from which ventenata can spread into surrounding, less ideal habitat types. The “biodviersty-invasion hypothesis” (Elton 1958) posits that more biodiverse areas will be less susceptible to invasion, but propagule pressure hypotheses suggests that areas close to areas that are heavily invaded will be more likely to be invaded (Colautti et al. 2005). If environmental factors such as biodiversity influence invasion success, I would expect diverse habitats to have a higher resistance to the ventenata invasion and be less invaded, but if propagule pressure is a stronger driver of the ventenata invasion, diversity may be trumped by proximity to invaded patches which may increase these patches risk of invasion despite species composition.

4. Approaches: describe the kinds of analyses you ideally would like to undertake and learn about this term, using your data.

I would like to develop an overall understanding of the spatial pattern of invasion by performing Moran’s I to test for spatial autocorrelation. Additionally, I would like to identify hotspots of invasion using hotspot analysis. From these hotspots, I am interested in predicting spread using kernel density functions that estimate ventenata distribution. Finally I would like to relate the spatial pattern of vententata to environmental characteristics of habitat patches (including species composition) through the use of cross-correlation and geographically weighted regression.

5. Expected outcome: what do you want to produce — maps? statistical relationships? other?

I would like to produce figures that represent multivariate statistical relationships between ventenata, patch size, location, and environmental/ community variables. I am also interested in creating a map depicting areas at highest risk of invasion based on spatial and environmental data if appropriate considering the statistical relationships that result from the analysis.

6. How is your spatial problem important to science? to resource managers?

Ventenata is rapidly invading natural and agricultural areas throughout the inland Northwest where associated ecological and economic losses are readily becoming evident. However, possibly the most concerning aspect of the invasion is ventenata’s potential to increase fire intensity and frequency in invaded scabland patches, that prior to invasion supported light fuel loads and acted as natural fire breaks for the surrounding forest.  Such shifts to the fire regime could dramatically alter landscape-scale biodiversity and cause additional socioeconomic losses. Despite these concerns, little is known of the drivers influencing ventenata’s invasion potential and few management options exist. Understanding how the spatial arrangement and size of scabland patch influences susceptibility to invasion by ventenata could help managers target areas at the highest risk for invasion and mitigate losses.

7. Your level of preparation: how much experience do you have with (a) Arc-Info, (b) Modelbuilder and/or GIS programming in Python, (c) R, (d) image processing, (e) other relevant software

I have a working knowledge of programming in R and manipulating spatial data/ map making in ArcGIS. I have taken introductory level classes in R and ArcGIS, and used these tools for work and for my research. I have no experience in modelbuilder, GIS programming in python, and image processing. I am eager to learn how to use these tools and apply them to help answer ecological research questions.

References:

Colautti, R. I., Grigorovich, I. A., & MacIsaac, H. J. (2006). Propagule pressure: a null model for biological invasions. Biological Invasions, 8(5), 1023-1037.

Elton, C.S. (1958). The ecology of invasions by animals andplants. T. Methuen and Co., London.

Simpson, M. 2013. Developer of the forest vegetation zone map. Ecologist, Central Oregon Area Ecology and Forest Health Program. USDA Forest Service, Pacific Northwest Region, Bend, Oregon, USA