Assignment 1: Review of Use of Spatial Pattern Analysis to Assess Forest Cover Changes in the Mediterranean Region of Turkey
Purpose
Looking at Başkonuş Forest Enterprise, which is in the Mediterranean city of Kahramanmaraş in Turkey, the authors aimed to determine and map the main forest types from 1992-2012, evaluate the amount and rates of forest cover changes (FCC) in this time period, and investigate the factors of FCC (Bozali, Sivrikaya & Akay, 2015, p. 366).
Main Argument
The authors focused their investigations on the idea that the main factors of FCC were afforestation, forest conservation, and rehabilitation processes of the General Directorate of Forestry (GDF), which manages 99% of Turkey’s forests (Bozali, Sivrikaya & Akay, 2015, p. 366).
Key Points
Knowledge of FCC is greatly important for those making decisions in regards to Turkey’s forests (Bozali, Sivrikaya & Akay, 2015, p. 365). Human activities can fragment the landscape via urbanization, agriculture, livestock grazing, tree removal, and more (Bozali, Sivrikaya & Akay, 2015, p. 365). This may result in major changes like biodiversity loss and habitat isolation (Bozali, Sivrikaya & Akay, 2015, p. 366). This is why it is extremely important to determine the effects of policies for managing forests, like the GDF’s 2006 Forest Rehabilitation Action Plan and Forest Conversion Action Plan (Bozali, Sivrikaya & Akay, 2015, p. 366).
Methods and Analyses
Maps used in forest management from 1992 and 2012 were digitized by being scanned and saved as TIFF files (Bozali, Sivrikaya & Akay, 2015, p. 367). The attribute data included land use and cover, crown closure, and stage of development (Bozali, Sivrikaya & Akay, 2015, p. 366). The two maps were overlaid in order to determine spatial and temporal changes (Bozali, Sivrikaya & Akay, 2015, p. 367).
FRAGSTATS analyses were performed (Bozali, Sivrikaya & Akay, 2015, p. 368) and a transition matrix was created (Bozali, Sivrikaya & Akay, 2015, p. 371). The authors used landscape metrics like class % of landscape (PL), class area (CA: sum of areas of all patches belonging to a certain class), number of patches (NP), largest patch index (LPI: % of the landscape in the largest patch), mean patch size (MPS: the average patch size in a certain class), patch density (PD: number of patches per 100 ha), patch size coefficient of variation (PSCV), and area-weighted mean shape index (AWMSI: the average perimeter:area ratio for a class, weighted by the size of its patches) (Bozali, Sivrikaya & Akay, 2015, p. 368).
Alternatives
The methods and procedures used to conduct the study do appear to be appropriate for the research questions. Field surveys of plots in Başkonuş Forest could have been performed to enhance the data at hand. However, given that this method would have been extremely time-consuming and resource-consuming, the authors may have been justified in only using GIS and maps.
Supporting Evidence
Forested areas gained 376 ha from 1992 to 2012 due to GDF afforestation activities, GDF forest protective measures, and population migration from rural to urban areas (Bozali, Sivrikaya & Akay, 2015, pp. 368-370). As well, GDF rehabilitation activities led to a 1974.5 ha increase in productive forest areas, a 1598.5 ha decrease in degraded forest areas, a 684.6 ha decrease in non-forest areas, and a 1490.7 ha increase in conifer forests (Bozali, Sivrikaya & Akay, 2015, p. 370).
Argument Validity
The authors implied that the 2006 Forest Rehabilitation Action Plan and Forest Conversion Action Plan were the cause of the changed landscape of Başkonuş Forest. However, they did not explore other possible factors like climate change or interventions by non-state actors like citizens.
Rating
The authors did not specify who owns the other 1% of Turkey’s forests (Bozali, Sivrikaya & Akay, 2015, p. 366) and how this would factor into the study topic. The authors also did not mention how the people living in the region were affected by, or any responses they had to, the 2006 forest management strategies. Thus, I give the authors a score of 8/10.
Work Cited
Bozali, N., Sivrikaya, F., & Akay, A. E. (2015). Use of spatial pattern analysis to assess forest cover changes in the Mediterranean region of Turkey. Journal of Forest Research, 20(4), 365-374. doi:10.1007/s10310-015- 0493-2
Assignment 2: Review of Use of Spatial Pattern Analysis to Assess Forest Cover Changes in the Mediterranean Region of Turkey
Purpose
Focusing on endemic areas of the Qom province in central Iran, the authors evaluated the risk of cutaneous leishmaniasis (CL) and epidemiological characteristics of the disease from 2009 until 2013 (Abedi-Astaneh et al., 2016, p. 1).
Main Argument
The authors aimed to resolve the uncertainty around CL transmission by analyzing epidemiological patterns of CL infection (Abedi-Astaneh et al., 2016, p. 3). The authors focused on the idea that the epidemiology of CL had changed (Abedi-Astaneh et al., 2016, p. 9).
Key Points
CL is present in Iran in two forms: Anthroponotic (ACL) and Zoonotic (ZCL) (Abedi-Astaneh et al., 2016, p. 2). Two species of the Phlebotomus sand fly are known to be the main vectors of ACL and ZCL (Abedi-Astaneh et al., 2016, p. 2). Reservoir hosts of ZCL include different genera of gerbils (Abedi-Astaneh et al., 2016, p. 2). Reservoir hosts of ACL on the other hand, include humans and dogs (Abedi-Astaneh et al., 2016, p. 2). The long incubation period of CL leads to difficulties in determining the spatial location of disease transmission (Abedi-Astaneh et al., 2016, p. 2).
Methods and Analyses
Data on infected patients from 2009 to 2013 were retrieved from the Qom Province Health Center (Abedi-Astaneh et al., 2016, p. 3). To determine correlation between CL infection and parameters like age, gender, residential area and infection year and month, the data were analyzed with SPSS and Poisson regression and chi-squared tests with a 95% confidence level (Abedi-Astaneh et al., 2016, p. 3). 9 of 212 samples that tested positive for Leishmania spp. were used for molecular detection and identified as L. major by PCR-RLFP (Abedi-Astaneh et al., 2016, p. 1). ArcGIS 10.3 was used to store the data of patient cases of CL (Abedi-Astaneh et al., 2016, p. 5).
CL incidence rates were generated through inverse distance weighting (IDW) interpolation (Abedi-Astaneh et al., 2016, p. 5). The authors used Moran’s I index statistics to perform cluster analysis of CL cases (Abedi-Astaneh et al., 2016, p. 5). As well, Getis-Ord Gi* statistic was used for hot spot analysis (Abedi-Astaneh et al., 2016, p. 5).
Alternatives
The methods used and analyses conducted were appropriate for the study. Interviews or further surveys regarding patient lifestyle and family medical history could have been done to gather other possible variables for CL infection. However, as this would have been much more time-consuming and resource-consuming, the authors were likely justified in using the methods and analyses detailed in their paper.
Supporting Evidence
Hot spot clusters in Qom City, the capital of the province, showed disease hot spots in the northeast and southwest of the city (Abedi-Astaneh et al., 2016, p. 7). The northeastern areas of Qom City are near agricultural fields, while the southwest is the location of a newly built housing project (Abedi-Astaneh et al., 2016, p. 7). The z-scores of Moran’s I index verify the disease clustering trends, with under 5% likelihood that this could occur by chance (Abedi-Astaneh et al., 2016, p. 8). The authors linked the CL hot spot patterns with the presence of L. major in patient lesions, the fact that rats and gerbils are found in agricultural fields and the fact that Phlebotomus sand flies are known vectors of ACL and ZCL (Abedi-Astaneh et al., 2016, p. 9). They concluded that the epidemiology of CL had changed (Abedi-Astaneh et al., 2016, p. 9).
Argument Validity
Since the 9 CL patients that tested positive for L. major did not travel to specific parts of Qom City (Abedi-Astaneh et al., 2016, p. 13), it is plausible that the authors contention that the epidemiology of the disease had changed (Abedi-Astaneh et al., 2016, p. 9) is correct. However, it is also possible that other vectors or variables could have led to the patient infections. Further research in the subject should be done to confirm uncertainty around CL transmission.
Rating
The authors were specific and mentioned that they received permission from Ethical Committee, Research Deputy, Tehran University of Medical Sciences to conduct their study (Abedi-Astaneh et al., 2016, p. 5). However, the colour and symbol choice of Figure 6, showing CL incidence, is difficult to decipher (Abedi-Astaneh et al., 2016, p. 10). As well, the legend of Figure 8, showing hot spot clusters in Qom City could be more descriptive (Abedi-Astaneh et al., 2016, p. 12). Thus, I give this paper a rating of 8/10.
Work Cited
Abedi-Astaneh, F., Hajjaran, H., Yaghoobi-Ershadi, M., Hanafi-Bojd, A., Mohebali, M., Shirzadi, M., . . . Mahmoudi, B. (2016). Risk mapping and situational analysis of cutaneous leishmaniasis in an endemic area of central Iran: A GIS-based survey. PLoS ONE, 11(8), e0161317. doi:10.1371/journal.pone.0161317
Assignment 3: Review of The Effects of ‘Alley-Gating’ in an English Town
Purpose
The authors evaluated the effectiveness of “alley-gating” as a preventative measure against burglary in Oldham, northwest England (Haywood, Kautt & Whitaker, 2009, p. 361).
Main Argument
Since industrial towns in Britain commonly have rows of back-to-back terraced homes, the alleyways at the rear are vulnerable points of entry for burglars (Haywood, Kautt & Whitaker, 2009, p. 361). One method of crime reduction is installing gates across these alleyways, or “alley-gating”, with only residents holding keys to the gates (Haywood, Kautt & Whitaker, 2009, p. 362).
Key Points
Criminal activity may be controlled by manipulating the environment (Haywood, Kautt & Whitaker, 2009, p. 362). For example, alleyways may be prone to crime due to easy access to buildings while at the same time obscuring the offender (Haywood, Kautt & Whitaker, 2009, p. 361). Perpetrators lower the risk of arrest by choosing to commit crimes in the cover of vegetation or in darkness (Haywood, Kautt & Whitaker, 2009, p. 362). Thus, alley-gating may discourage criminal activity and decrease the risk of burglary (Haywood, Kautt & Whitaker, 2009, p. 362).
A single burglary is estimated to cost about £2626, meaning that burglary costs England and Wales around £1.8 billion each year (Haywood, Kautt & Whitaker, 2009, p. 363). Alley-gating is a fast and tangible method for burglary reduction and demonstrates that government funds are being well spent (Haywood, Kautt & Whitaker, 2009, p. 363).
Methods and Analyses
The authors looked at two years of burglary data (from August 31, 2005 to August 31, 2007) gained from the Greater Manchester Police (Haywood, Kautt & Whitaker, 2009, p. 364). The data contained information on domestic and non-domestic (including garden sheds and detached garages) burglaries (Haywood, Kautt & Whitaker, 2009, p. 365). Data about 766 gates were obtained from the Oldham Crime and Disorder Reduction Partnership (Haywood, Kautt & Whitaker, 2009, p. 365).
Using GIS, the authors mapped crime and gate locations in order to perform analyses (Haywood, Kautt & Whitaker, 2009, p. 370). Ten buffers of 200 m were mapped at the gate locations and the weighted displacement quotients (WDQs) were calculated (Haywood, Kautt & Whitaker, 2009, p. 370). As well, interviews with residents of the gated homes were conducted (Haywood, Kautt & Whitaker, 2009, p. 372).
Alternatives
The methods and analyses used were appropriate for the purpose of the study. Further information about neighbourhood ethnic makeup, income levels, education levels, population or more could have been explored to look at other possible factors regarding gates and burglary. As this would have been extremely resource-consuming and time-consuming, the authors were likely justified in using those methods and procedures.
Supporting Evidence
Looking at 120 crimes, 74% occurred before gate installation and 26% occurred after (Haywood, Kautt & Whitaker, 2009, p. 367). Using a chi-squared test, the authors found the gates significantly decreased the chance of burglary to the homes they were built for (Haywood, Kautt & Whitaker, 2009, p. 368). WDQ values show that the gates have positive impacts on the surrounding areas (Haywood, Kautt & Whitaker, 2009, p. 372). The interviewed residents spoke of greater pride and community cohesion and favourable outlooks about the gates due to decreased crime (Haywood, Kautt & Whitaker, 2009, p. 372).
Argument Validity
Looking at 6193 burglary cases, the authors noted that the crime hot spots did not match the areas of gate installation (Haywood, Kautt & Whitaker, 2009, p. 365). So, the positive results of the gates may or may not hold true for the areas most affected by burglary. In fact, some areas with no burglaries prior to gate installation were found to have burglaries after installation (Haywood, Kautt & Whitaker, 2009, p. 372). As well, the study did not consider other possible factors that might influence crime, such as CCTV or security lighting (Haywood, Kautt & Whitaker, 2009, p. 378).
Rating
The authors helpfully suggested other solutions to lower crime, such as taller gates, self-locking spring-shut gates or increased patrols being used in conjunction with gates to prevent the climbing or bypassing of gates (Haywood, Kautt & Whitaker, 2009, p. 377). Figure 1, the only map in the article, showed the concentric gate buffers and could have been easier to interpret if it were not black and white (Haywood, Kautt & Whitaker, 2009, p. 370). For example, each 200 m of buffer could have been a different colour. Other maps could have been created, for example, showing the study area in relation to the whole country or showing burglary hot spots compared to gate locations. In conclusion, I give this paper a rating of 7/10.
Work Cited
Haywood, J., Kautt, P., & Whitaker, A. (2009). The effects of ‘alley-gating’ in an English town. European Journal of Criminology, 6(4), 361-381. doi:10.1177/1477370809104687