Livelihood landscapes – disentangling occupational diversity for natural resource management

A special contribution from Josh Cinner, from the ARC Centre of Excellence for Coral Reef Studies (see previous posts on his work here and here) and Örjan Bodin from the Stockholm Resilience Centre on their recent paper, Livelihood diversification in tropical coastal communities: a network-based approach to analyzing ‘livelihood landscapes’, which appeared in the August 11, 2010 issue of PLoS ONE, and is available free online.  They write:

In many developing countries, an individual household will often engage in a range of economic sectors, such as fishing, farming, and tourism. These diverse ‘livelihood portfolios’ are thought to help to spread risk and make households more resilient to shocks in a particular sector. Whether and how local people engage in multiple occupations has important implications for how people use and manage natural resources and is of particular relevance to people involved in managing natural resources. But for scientists, donors, and policy makers, unraveling the complexity of livelihoods in developing countries has been extremely challenging.

In our recent paper in PLoS ONE, we developed a novel method for exploring complex household livelihood portfolios.  We used a network-based approach to examine how the role of natural resource-based occupations changes along spectra of socioeconomic development and population density in 27 communities across 5 western Indian Ocean countries (see Fig. 1).

Figure 1. Kenyan livelihood landscape maps at various scales of social organization: a) Shela, Kenya; b) an aggregation of peri-urban sites in Kenya; c) an aggregation of rural sites in Kenya; d) all sites in Kenya.

In Figure 1 the links between occupations are indicated by arrows. The size of a node indicates the relative involvement in that occupational sector (larger node means more people are involved). The direction of the arrows indicates the priority of ranking. Thus an arrow into an occupation indicates that the occupation was ranked lower than the occupation the arrow came from. The thickness of the arrows corresponds to the proportion of households being engaged in the, by themselves, higher ranked occupation that are also engaged in the lower ranked occupation. The proportion of the node that is shaded represents the proportion of people that ranked that occupation as a primary occupation.

We found:

  • an increase in household-level specialization with development for most (but not all) occupational sectors, including fishing and farming, but that at the community-level, economies remained diversified.
  • We also found that households in less developed communities often share a common occupation, whereas that patterns is less pronounced in more developed communities. This may have important implications for how people both perceive and solve conflicts over natural resources.

Finally, our network-based approach to exploring livelihood portfolios can be utilized for many more types of analyses conducted at varying scales, ranging from small villages to states and regions.

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