Abstract
Communities in northern Morocco are vulnerable to increasing water scarcity and food insecurity. Context specific adaptation options thus need to be identified to sustain livelihoods and agroecosystems in this region, and increase the resilience of vulnerable smallholders, and their farming systems, to undesired effects of social-ecological change. This study took a knowledge-based systems approach to explore whether and how tree-based (i.e., agroforestry) options could contribute to meeting these adaptation needs. We analysed local agroecological knowledge of smallholders from the Mèknes–Tafilalet region, to (i) characterise existing farming systems at local landscape scale; (ii) identify possible niches for farm-trees within these systems; and (iii) explore locally perceived barriers to tree-based diversification. An iterative cycle of qualitative interviews, with a purposefully selected sample of 32 farmers, revealed that socio-economic constraints and agroecological conditions in the area differed markedly along a relatively short altitudinal gradient. Agroforestry practices were already integral to all farming systems. Yet, many were at risk of degradation, as water scarcity, low profitability of production systems and uncontrolled grazing constituted critical barriers to the maintenance and diversification of farm-trees. We demonstrate the discriminatory power of local knowledge, to characterise farming conditions at the local landscape scale; and unveil adoption barriers and options for tree-based diversification in northern Morocco.
Highlights
Climate change will likely exacerbate existing pressures on the Mediterranean drylands, and strain livelihood systems that depend on the provision of ecosystem services from these ecosystems
We demonstrate the discriminatory power of local knowledge, to characterise farming conditions at the local landscape scale; and unveil adoption barriers and options for tree-based diversification in northern Morocco
The contribution of this study is twofold: First, we demonstrate the utility of local agroecological knowledge for assessments of fine scale variation in adaptation contexts, and for the adoption of agroforestry practices, at local landscape scale
Summary
Climate change will likely exacerbate existing pressures on the Mediterranean drylands, and strain livelihood systems that depend on the provision of ecosystem services from these ecosystems. Throughout the world, dryland smallholders operate in fragile production environments, which are naturally water scarce, drought prone and afflicted by socio-economic barriers—including limited access to markets and technology, challenging institutional and policy environments, underdeveloped infrastructure, poverty and population growth [1,2,3]. In Morocco, people are vulnerable to future food-insecurity, as the country’s population continues to grow and food demand increases, but agricultural production fluctuates and is likely to diminish as a result of climate change [4]. Current model predictions suggest that Morocco will experience the greatest climate change induced precipitation decrease among the Middle East and North African countries; with increasing mean temperatures in all seasons, declining rainfall, and greater vegetation reference evapotranspiration—leading to decreased runoff, less groundwater recharge and enhanced water stress [5,6]. The country is at great risk of external shocks such as food price inflation, due to its strong import dependence and exposure to international markets [8]
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.