Beyond bioproductivity: Engaging local perspectives in land degradation monitoring and assessment

Land degradation monitoring and assessment in the Sahel zone takes advantage of and relies substantially on temporal trends of remote sensing-based vegetation indices, which are proxies for the bioproductivity of the land. However, prior studies have shown that negative or positive trends in bioproductivity are not necessarily associated with degradation or improvement of land condition. We argue that remote sensing-based indices, while having contributed much to dismantling an outdated desertification narrative, are themselves falling short of capturing the whole picture and need to be accompanied by field observations that are relevant to local land users. We used the participatory photo elicitation method in three sites in order to elicit local pastoralists’ perspectives on land degradation and identify the indicators that they use to characterize pasture quality, while empowering them to lead the discussion. The discussion revealed indicators far beyond bioproductivity, including livestock performance as well as composition and quality of the herbaceous and woody vegetative cover, invasive species, soil quality and water availability. We found that the pastoralists’ interest, knowledge and field observations could potentially be harnessed using a crowd-sourcing approach in order to produce a geospatially explicit dataset of land degradation, which would be complementary to the remote sensing-based maps of trends in bioproductivity and could serve as a reference for the development of more targeted remote sensing-based indicators of land degradation

• Publication year

  2018

• Venue

  Journal of Arid Environments

• Publication date

  2018-05-28

• Fields of study

  Geography, Environmental Science

• Identifiers
  DOI 10.1016/J.JARIDENV.2019.104002
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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