Schüßler, D., Lee, P. C., & Stadtmann, R. (2018). Analyzing land use change to identify migration corridors of African elephants (Loxodonta africana) in the Kenyan-Tanzanian borderlands. Landscape Ecology,33(12), 2121-2136. doi:10.1007/s10980-018-0728-7
The purpose of the research was to analyze the land cover changes in the Kenyan-Tanzanian borderlands of the greater Amboseli ecosystem and used African elephants as an indicator species to evaluate landscape connectivity. Standing at the perspective of modern conservation planner, the researchers concerned about the impacts of recent-year agricultural expansion on the seasonal migrations of large herbivores. In the article, researchers argued the landscape connectivity of elephant population had been disrupted by the land use changes.
The study site is located in the intersection of southern Kenya and northern Tanzania, with a greater Amboseli ecosystem about 10, 000 square kilometers. The research was decided into two main parts. The first part based on a GIS method by using multiple -temporal Landsat imagery from USGS and a supervised maximum likelihood classification, to monitor the land cover changes over a 43-year period from 1975 to 2017. Seven different land cover classes including water, open vegetation, semi-open vegetation, closed shrubs, forest, agriculture, and clouds were selected, according to previous studies in Amboseli. The second part contained a literature review of overall 72 articles to measure 8 main paths of elephant migrations. Then, based on the classification result and the measured migration paths, the landscape connectivity was evaluated.
The result showed that the land cover changed considerably during these years. The woodland and bushland declined and replaced by open grasslands and agriculture lands. The increase of small-scale cultivation and the loss of vegetation density resulted in a landscape fragmentation. Only one of the eight corridors was formally protected. Therefore, the researchers concluded that wildlife habitats and migration corridors were significantly disrupted, which successfully proofed their argument.
In general, the research provided relatively convinced land cover change maps. First, it used in total 14 Satellite imageries to conduct classification. The multiple imagery references displayed smooth changes in land cover, increasing the credibility. In addition, the accuracy quality of supervised classification was examined and fixed through three different ways: visually compared map with the satellite images, using literature review as a reference and calculated the overall accuracy for each time stage. However, the credibility of the elephant migration corridors was insufficient. The corridors were totally identified by literature reviews and the most references were from the same author. The predicted corridors in the research were only straight and rough lines. Actually, the credit could be increased by using GIS to predict the possible migration corridors. Through producing a cost surface, the corridors can be displayed in a more accurate and detailed way. The literature review can still be used as references for accuracy assessment.
Overall, the research successfully provided the land cover changes in southern Kenya, but the accuracy of landscape connectivity may be impacted by the measurement uncertainty of migration corridors. Hence, I would like to give the paper a 7/10 score.