Guide for the Sustainable Intensification Assessment Framework

Musumba, Mark; Grabowski, Philip; Palm, Cheryl; Snapp, Sieglinde S.

doi:10.2139/ssrn.3906994

Cited by 31 publications

(19 citation statements)

References 33 publications

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“…The consideration of farmers' social networks allows us to partly capture the social domain of sustainable intensification as described in Musumba et al . (2017). Agroecology was considered to capture the heterogeneity in preferences among the sample farmers along the two agroecological zones in Sikasso region, described in the section above on the study area.…”

Section: Study Area and Methodologymentioning

confidence: 99%

“…The consideration of the subsamples in our analysis was to explore heterogeneity in preferences and trade-offs with respect to two policyrelevant variables for intensification: social network and agroecology. The consideration of farmers' social networks allows us to partly capture the social domain of sustainable intensification as described in Musumba et al (2017). Agroecology was considered to capture the heterogeneity in preferences among the sample farmers along the two agroecological zones in Sikasso region, described in the section above on the study area.…”

Section: Discrete Choice Model Estimationmentioning

confidence: 99%

“…To assess the impacts of agricultural development interventions on smallholder farmers, multidimensional approaches are necessary. In this regard, Musumba et al (2017) have developed a sustainable intensification assessment framework (SIAF) incorporating five domains to define and assess sustainable intensification: productivity, economic, environment, human and social domains. The SIAF applies metrics at field, farm, household and landscape levels.…”

Section: Introductionmentioning

confidence: 99%

“…In this study in southern Mali, we used a discrete choice experiment (DCE), a method which involves asking individuals to state their preference over hypothetical alternative scenarios, goods or services (Train, 2009), to evaluate farmers' preferred sorghum production technologies from a sustainability perspective. This study aimed to assess multidimensional evaluation criteria (as developed by Musumba et al ., 2017) for designing and testing technologies for sustainable sorghum production among smallholder farmers in southern Mali, as well as in similar sociocultural and agroecological settings, to support the incorporation of sustainable intensification in agricultural research (Lynam and Herdt, 1989) and its effective prioritization in research and development (R&D) (Cassman and Grassini, 2020). This study also contributes to the growing application of DCE for understanding farmers' preferences for agricultural technologies in the developing country context.…”

Section: Introductionmentioning

confidence: 99%

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Farmers' preferences for sustainable intensification attributes in sorghum-based cropping systems: evidence from Mali

Badolo

Kotu²,

Oyinbo

et al. 2022

Renew. Agric. Food Syst.

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Sorghum plays a crucial role in the rural economy and nutrition of rural households in Mali. Yet the productivity of this crop is constrained by limited adoption of agricultural intensification technologies, which could be partly because technology development does not properly consider farmers' preferences. This study with smallholder farmers in southern Mali aimed to assess farmers' preferences for different attributes of sorghum technologies through the lens of sustainable intensification. The study used a discrete choice experiment, a method which involves asking individuals to state their preference over hypothetical alternative scenarios, goods or services. We considered six attributes corresponding to different domains of sustainable intensification: grain yield, risk of yield loss, soil fertility, nutrition, labor requirement and fodder yield. We analyzed the data using the mixed logit model, while considering the multinomial logit model as a robustness check. The findings revealed that smallholder farmers are strongly interested in transitioning from their existing sorghum-based cropping systems to those that closely align with these domains of sustainable intensification. However, there were diverse preferences among all the smallholder farmers studied, and between distinct sub-groups of smallholder farmers characterized by their social networks and agroecological zones, which yield relevant policy implications. Overall, these results support the growing research and development prioritization and policy interests toward scaling sustainable intensification among farmers, with a particular focus on human nutrition.

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Section: Study Area and Methodologymentioning

confidence: 99%

Section: Discrete Choice Model Estimationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Farmers' preferences for sustainable intensification attributes in sorghum-based cropping systems: evidence from Mali

Badolo

Kotu²,

Oyinbo

et al. 2022

Renew. Agric. Food Syst.

View full text Add to dashboard Cite

show abstract

“…Allowing agricultural production to be increased without exceeding the earth's local and regional carrying capacity is one of the greatest challenges for SAI (Garnett et al, 2013;Firbank et al, 2018). In addition, another complication is the lack of consensus on the meaning and wider uptake of SAI (Pywell et al, 2015;Musumba et al, 2017;Xie et al, 2019). This is coupled with insufficient attention to the drivers influencing water use in agricultural systems and practices in the landscape along the food chain (including producers, manufacturers, distributors and consumers) (Godfray and Garnett, 2014;Hallstrom et al, 2015;Macfadyen et al, 2015).…”

Section: Challenges and Critiques Of Sustainable Agricultural Intensi...mentioning

confidence: 99%

Gap analysis and methodological framework to assess and develop water centric sustainable agricultural intensification pathways in Sub-Saharan Africa

Haileslassie

Mekuria²,

Uhlenbrook³

et al. 2022

Front. Water

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The sustainable agricultural intensification (SAI) debate, partly rooted in discussions over the Green Revolution, was developed in the 1990s in the context of smallholder agriculture in Africa. In many Sub-Saharan African (SSA) countries, production is still largely rainfed, with the prevalence of significant yield gaps and rapid environmental degradation. Projections indicate that climate and demographic changes will further intensify the competition for freshwater resources. Currently, SAI is centered around predominantly rain-fed agricultural systems, often at a farm and plot scales. There has been increased attention to the improved role of agricultural water management (AWM) to address the daunting challenges of climate change, land degradation and food and nutritional insecurity in SSA. Nonetheless, the supporting frameworks and tools remain limited and do not connect the sustainability assessment and the development of intensification pathways (SIP) along multiple scales of the rainfed irrigation continuum. This paper reviews the gaps in concepts and practices of SAI and suggests a methodological framework to design context-specific and water-centered SIP for the SSA region. Accordingly, the proposed methodological framework demonstrates: (a) how to couple sustainability assessment methods to participatory SIPs design and adaptive management approach; (b) how contextualized sustainability domains and indicators can help in AWM centered SIP development; (c) the approaches to handle multiple scales and water-related indicators, the heterogeneity of biophysical and social settings when tailoring technology options to local contexts; and (d) the principles which enable the SIP designs to enable synergies and complementarities of SAI measures to reinforce the rainfed-irrigation continuum. This methodological framework allows researchers to integrate the sustainability assessment and SIP design, and guides policymakers and practitioners in planning, implementing and monitoring SAI initiatives (e.g., Framework for Irrigation Development and Agricultural Water Management in Africa) across multiple scales.

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The Landscape Data Commons: A system for standardizing, accessing, and applying large environmental datasets for agroecosystem research and management

McCord,

Webb,

Bestelmeyer

et al. 2023

Agricultural & Env Letters

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Understanding where, when, and why agroecosystems are changing requires quality information about ecosystems that span land tenure, ecological processes, and spatial scales. Over the past two decades, land management agencies and research groups have adopted a suite of standardized methods for monitoring rangelands, which have been implemented at over 85,000 monitoring locations globally. However, the ability to use these data to understand agroecosystem dynamics and change across scales and across land ownership has been limited because, until now, these data have not been available in a harmonized, accessible format for analyses, modeling, and decision‐support tools. We present the Landscape Data Commons, a cyberinfrastructure platform that harmonizes and aggregates standardized agroecosystem data, enables linkages to models, and facilitates analysis and interpretation of data within decision‐support tools. The Landscape Data Commons provides a community platform for users to contribute data and develop next‐generation tools to support agroecosystem management through the 21st century.

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Guide for the Sustainable Intensification Assessment Framework

Cited by 31 publications

References 33 publications

Farmers' preferences for sustainable intensification attributes in sorghum-based cropping systems: evidence from Mali

Farmers' preferences for sustainable intensification attributes in sorghum-based cropping systems: evidence from Mali

Gap analysis and methodological framework to assess and develop water centric sustainable agricultural intensification pathways in Sub-Saharan Africa

The Landscape Data Commons: A system for standardizing, accessing, and applying large environmental datasets for agroecosystem research and management

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