Mali Climate Vulnerability Mapping
This technical report considers an exercise of climate vulnerability mapping in Mali, which applied a spatial vulnerability index containing 18 indicators that is grouped into three vulnerability components – climate exposure, sensitivity, and adaptive capacity. The report translates the findings via map outputs with Figure 5 as the overall vulnerability map. The purpose of the vulnerability mapping in Mali was to highlight hotspots of particularly high relative vulnerability.
Overall, the findings show that northern Mali is particularly vulnerable; however, the population in the north only totals six percent of the country’s population. The capital city of Bamako in southern Mali is estimated to have low vulnerability due to its high capacity and low sensitivity. Most of Mali’s population – 75 percent – lives in southeastern Mali where the vulnerability is on average medium to medium-high.
The report emphasizes that when using vulnerability mapping, which covers broad regions, to be cautious that context-specific reasons can affect one community differently than others. Additionally, through using a spatial vulnerability index approach, the results depend on the robustness of the underlying data as well as how varying methodologies may affect assumptions within the data. The report authors stress to those using the report for application to also review the annexes section.
Excerpt from the report:
The results need to be qualified as being broadly indicative of patterns of vulnerability. In this regard, four points are worth highlighting:
- Vulnerability maps and resulting “hotspots” are built on assumptions regarding the mechanisms that produce vulnerability and data layers of varying accuracy. While we have provided a rationale section for each indicator layer in the metadata, in which we state our underlying assumptions, ideally we would be able to test these assumptions against outcome measures (e.g., morbidity, mortality, crop losses, or economic losses) related to specific climate events (e.g., floods or droughts).
- We collated the best available sub-national data for Mali, which proved to be a remarkably information rich environment for a least developed country. Nevertheless, limitations in global, regional, and national data mean that there is uncertainty associated with the results. This means that maps should be used in conjunction with ground validation when results are to be applied in specific localities. While we sought to keep our indicator layers to a reduced set, avoiding some data sets of questionable quality, some of the indicator data layers in this analysis have unknown levels of uncertainty. We were only able to characterize uncertainty in 7 out of 18 data layers. We have sought to address known data quality issues in the limitations section of the metadata.
- While maps can appear to provide unambiguous guidance on where to focus attention, map interpretation needs to be guided by accompanying text describing underlying uncertainties, because small changes in data and methods could produce different results. We provide a preliminary sensitivity analysis in Annex III to investigate the influence of our underlying assumptions regarding the construction of vulnerability on the overall vulnerability map.
- Map development would be improved by better data as well as a better understanding of the underlying functional form of the relationship among indicators (how a unit increase in one indicator relates to a unit increase in another indicator in terms of its impact on vulnerability); fungability (the degree to which a low score on one indicator compensates for high scores in another); and threshold effects for certain indicators. We further address these issues in the conclusion (Section 4. 1).