Beyond bioproductivity: Engaging local perspectives in land degradation monitoring and assessment
MetadataShow full item record
PublisherACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
CitationHerrmann, S., Diouf, A. A., & Sall, I. (2020). Beyond bioproductivity: Engaging local perspectives in land degradation monitoring and assessment. Journal of Arid Environments, 173, 104002.
JournalJOURNAL OF ARID ENVIRONMENTS
Rights© 2019 Elsevier Ltd. All rights reserved.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at email@example.com.
AbstractLand degradation monitoring and assessment in the Sahel zone has relied 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. In this short communication, while acknowledging the contributions of remote sensing-based indices and global-scale datasets to dismantling an outdated desertification narrative, we argue that local land users have much to contribute to our understanding of land degradation, and particularly to ensuring that scientific assessments of degradation capture variables relevant to them. We used the participatory photo elicitation method in three sites in the Senegalese Ferlo 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' knowledge and interest in the issue could potentially be harnessed more systematically, and at larger scales, in order to build a spatially explicit field-based knowledge base of land degradation complementary to remote sensing-based maps of trends in bioproductivity. Such a dataset could serve as a standalone product or as a reference dataset for development and validation of remote sensing-based indicators.
Note24 month embargo; published online: 20 July 2019
VersionFinal accepted manuscript
SponsorsOffice of Research and Development at the University of Arizona