6. Multiple Threats

Submitted by Michael Rastall 9th August 2012 14:51

Threats are potentially damaging influences or disturbances on the system of analysis. A system can be potentially affected by several threats of different nature at the same time, including social changes, ecological changes, economic and technological changes. Disturbances can occur as discrete events in time, referred to as a shock or perturbation to the system, or can be gradual, which is then recognized as a stress or pressure on the system (RA 2010). A threat is generally but not always external to the system of analysis and it can be part of natural fluctuations that relate to the natural variability of the system.

In the four sites that make up the system of analysis, threats were identified by representatives of the population on a time scale that spans from the 1970s to the present. Table 5 below shows the chronological list of perceived threats and major events in two of the villages, namely MBoy II and Mang.

Table 5. Historical Trendline of Major Events and Threats

The table above shows events and threats of varied nature involving social, political, economic and ecological changes. Although this is not a comprehensive list of all the changes that may have affected the system in the past, they provide a useful overview of the multiple stresses and shocks that influence(d) it. Some of the implications of these events, as explained by village representatives, were life loss (e.g. increase in infant mortality due measles and diarrhea epidemics), increase in revenues (e.g. due to growth in the coffee market and mining activities), and decreases in production and income (e.g. due to pest invasions, drought, shift in the seasons, and water scarcity).

Some of the threats identified by the villagers relate to stresses (i.e. gradual changes) such as a shift in the seasons and scarcity of water resources, while others relate to shocks (i.e. abrupt or discrete events) such as diseases, pest invasions, and intense droughts. For the climate vulnerability analysis we selected the threats that directly depend on climate variables such as changes in mean temperature and total rainfall. Table 6 below provides a summary of the climate-related disturbances as perceived by the villagers in Mboy II, Mang and Djalobekoe.

Table 6. Description of Climate-related Disturbances

Some of the climate-related disturbances identified by the villagers have become more frequent over time. While some are isolated events that only happened once in the memory of the villagers (i.e. intense drought during 5 months and caterpillar invasion during one season), the other events (i.e. violent winds, shift in the seasons, drying water sources and diarrhea) have developed gradually and have become more notorious and frequent since the 2000s. For instance, villagers in Djalobekoe mentioned that strong winds in the past would only appear during the large dry season, but now they have become more frequent and tend to affect the village during the small rain season as well. These gradual events are probably also related to each other. For example, villagers mentioned that changes in the seasons (e.g. longer dry season, sporadic rain) decrease the availability of water sources, and the lack of water sources forces the population to use water from the rivers, which is causing diarrhea problems due to poor river water quality.

Results obtained from the surveys in the villages of Mboy II, Nampella and Djalobekoe corroborate the results obtained from the focus group discussions, particularly in relation to shifts in the seasons and extremes related to climatic variability (see Figure 6). Among the main climate-related disturbances specified by the surveyed households are: prolonged dry season (54% of the total responses for the category), prolonged wet season (46%), strong winds (46%), dry spells in wet seasons (42%), and intense rain (27%). These disturbances seem to be felt relatively equally in all surveyed villages as illustrated in the Figure 6 below.

Changes or shifts in the seasons seem to be the main climate-related disturbance affecting the villages. According to the villagers, changes in the seasons have been felt for the past 10 years. Villagers in Mboy II and Djalobekoe explain: 

“In the past, seasons were easy to differentiate: the large dry season would cover mid November to mid March, the small rain season would take place from mid March to mid June, the small dry season would then start from mid June to mid August, followed by the large rain season from mid August to mid November”.

The description of seasons above relate to observed station records collected in (a) the Ouesso station located 250 Km south-east from Yokadouma in Ouesso, Sangha, Congo, as well as (b) the Berberati station located 120 Km north-east of Yokadouma in Central African Republic. Figure 7 below shows the observed monthly rainfall totals for these two stations for the period 1979 - 2000. It is possible to see from the graphs, particularly in the Ouesso station, that there are two wet seasons, and that these correspond to the descriptions given by the villagers. The graphs also show a high inter-annual variability. In the Ouesso station, inter-annual variability is particularly high in the months of May, September and October, which seem to be peak months during the wet seasons. In the Berberati station, inter-annual variability is high in September and October, which are the end of the large rain season. 

According to the villagers, since the early 2000s it is more difficult to predict when it is going to rain and when it is going to be dry. Over the past decade, villagers have observed that (see representation in Figure 8):

  • It rains regularly during the large dry season
  • The small rain season starts earlier, in February
  • The small rain season is ‘divided’ by a period of dryness in April, after rains have started. Rain returns in May and continues until late June, prolonging the small rain season
  • The large rain season has shortened and rain is more intense during this season
  • The small dry season tends to shorten, or even disappear in some years, as it rains regularly during this season

Unfortunately, due to limited access to station data, the public perceptions cannot be compared to observed station records for the period post 2000. However, observed climate can be reproduced at the station scale with a downscaling method using a climate re-analysis circulation dataset such as NCEP (see Maraun 2010 for an updated review of statistical downscaling). The resulting downscaled time series can be used to analyze the period 1979-2009 for the Ouesso and Berberati stations. It is important to bear in mind, however, that re-analyses tend to have slightly reduced variance so the real changes might be somewhat moderated and it is more difficult to trace rainfall variability. Also, the re-analyses for both stations fail to reproduce the bi-modal seasonality, therefore these projections (and monthly data series in general) should be considered carefully when assessing seasonal shifts.

The monthly total rainfall time series of December, January and February for the NCEP re-analysis period 1979-2009 (Figure 9) show more rainfall during the dry season, as perceived by the stakeholders. Figure 10 shows rain days rather than total rainfall and focuses on rainy days in February because this seems to be the month that demonstrates most changes since 2000. The re-analysis suggests that the changes noted in the large dry season are happening rather at the end of this season. Probably this also explains why participants perceive that the small wet season is starting earlier.

A decrease in total rainfall during the month of April since 2000 could also be inferred from plotting the NCEP re-analysis data, particularly for the Berberati station from 2000 to 2007 (Figure 11). This trend goes in line with the perception of ‘dryness’ in April indicated by the participants. Plotting rainfall or rain days for the rest of the months in both stations does not give enough information to draw a reliable analysis.

The perceived changes described above have influenced the four villages in the system in several ways. The next sections will explain how these threats affect the diverse groups and activities in the villages, considering their differential exposure and their dynamic vulnerability to climate-related threats.