Please note: the source for this material comes from the individual papers and presentations
Landscape Ecology
For this first assignment, my partner and I chose an interesting article by Thiele et al. titled, Connectivity or area: what drives plant species richness in habitat corridors?, which attempted to relatively compare area and connectivity in terms of producing species richness in agricultural land, specifically liner landscape elements (LLE) in Northwest Germany.
Because our lecture on landscape ecology mentioned that GIS played a role in being able to obtain information about the connectivity and richness of species, we selected this article to explore how it is used in practice. In summary, this article gathered data and produced final results through the geospatial modelling environment tool in ArcGIS, field sampling, buffer creation, and the influence of area vs. connectivity was modelled in the software R. They found that connectivity was more influential in species richness and that the GIS analysis was important in discovering this result.
We gave this paper a rating of 10.
The full write up can be found here.
In terms of my classmates, I found the presentation involving Wolves influence Elk: Behaviour Shapes a Trophic Cascade quite interesting. This group effectively explained what a trophic cascade is, and explained the process of GIS use within this research paper in a manner that was easily understood. They mentioned that the researchers tagged elk using gps collars and analyzed the steps of elk and created a “step selection function” in order to establish or understand the movements and patterns of elk. They found that wolf distribution did affect elk populations, but plants were also heavily affected. Thus the presenters created a unique link between wolves and plants, by making elk a “middle man”. Overall, the chosen paper was interesting and the style of presentation was also very clear and informative.
Health Geography
In this assignment, my partner and I explored the use of GIS in health geography, which we learned from lectures is a field with expansive scope for GIS analysis. Here, we reviewed a paper by Tanser et al., titled Localied Spatial Clustering of HIV Infections in a Widely Disseminated Rural South African Epidemic.
The attempted to identify areas greatest in need of intervention, and created geographical prioritization by analyzing the varying levels of HIV infection within the study area of KwaZulu-Natal, rural South Africa. Using the spatial analytical techniques of Gaussian kernel and Kulldorff spatial scan statistic, clusters of HIV infections were discovered, revealing micro-graphical patterns of the disease spread. The Gaussian kernel analysis created a geographical spread of the HIV cases that were collected through consensual surveillance surveys, and showed that the disease varied across the study area. The Kulldorff spatial scan statistic enabled clustering analysis to occur. Together, these GIS techniques enabled the researchers to find areas of high HIV cases and relate these areas to various socio-economic variables, and note these areas for specific health intervention.
Overall, we give this paper a rating of 10 due to it’s concise and understandable use of the GIS techniques.
The full write up can be found here.
In terms of our classmates, I personally found the presentation regarding Community Mapping of Sex Work Criminalization and Violence to be particularly interesting. Though the methodology of this paper could be improved (as also stated by the students), it was interesting to see that multivariable logistic regression was used, as well as odds ratio, to find that there was an correlation between interruptions in the sex workers’ HIV treatment, and the police displacement of sex workers. This showed that as more police got involved, the health risk for these sex workers became greater, as their treatments were not able to be completed.
Crime Analysis
For this assignment, my partner and I explored the use of GIS in crime analysis, following the lecture material on how valuable GIS can be for proper and effective crime intervention by police departments. Titled Crime Mapping in Nigeria using GIS, this paper by Balogun et al. attempts to better understand the spread of crime across Benin City, Nigeria, by updating their crime management to use GIS.
In doing so, the researchers began by handing out surveys to the public and used their responses to assess the current crime situation in the city. Then, using this data, the locations of crimes and the locations of police stations were mapped, and it was found that though some police stations resided in places of high crime, the cultural fear and taboo surrounding crime reporting prevented the levels of crime from decreasing. Hence, this study provided light onto a greater social and cultural problem, which is to normalize crime reporting. Furthermore, the results showed that law enforcers needed to be better responsive to crimes so that more reporting can take place.
Overall, we gave this paper a 7 because though it was interesting to see how GIS can lead to the discovery of greater social issues, the methodology of GIS analysis could have been explained better.
The full write up can be found here.
In terms of our classmates, I found the presentation regarding Spatial Patterns of Serial Murders to be interesting. It was fascinating to see how the use of frequency distribution analysis showed that the murderers would go farther from their home or “original domain”, then come back once they realized that they may get caught. Hence, this lead to the conclusion that the spatial patterns of serial murderers were around the “home base” and would related more to familiar locations and distances. However, since there was no map or model produced in this study, I hope to see a follow-up study to this paper where a visual is created.
