Subnational distribution of average farm size and smallholder contributions to global food production

By Leah H. Samberg, James Gerber, Navin Ramankutty, Mario Herrero, Paul C. West. 2016

393 citations recorded by the source corpus.

Smallholder farming is the most prevalent form of agriculture in the world, supports many of the planet’s most vulnerable populations, and coexists with some of its most diverse and threatened landscapes. However, there is little information about the location of small farms, making it difficult both to estimate their numbers and to implement effective agricultural, development, and land use policies. Here, we present a map of mean agricultural area, classified by the amount of land per farming household, at subnational resolutions across three key global regions using a novel integration of household microdata and agricultural landscape data. This approach provides a subnational estimate of the number, average size, and contribution of farms across much of the developing world. By our estimates, 918 subnational units in 83 countries in Latin America, sub-Saharan Africa, and South and East Asia average less than five hectares of agricultural land per farming household. These smallholder-dominated systems are home to more than 380 million farming households, make up roughly 30% of the agricultural land and produce more than 70% of the food calories produced in these regions, and are responsible for more than half of the food calories produced globally, as well as more than half of global production of several major food crops. Smallholder systems in these three regions direct a greater percentage of calories produced toward direct human consumption, with 70% of calories produced in these units consumed as food, compared to 55% globally. Our approach provides the ability to disaggregate farming populations from non-farming populations, providing a more accurate picture of farming households on the landscape than has previously been available. These data meet a critical need, as improved understanding of the prevalence and distribution of smallholder farming is essential for effective policy development for food security, poverty reduction, and conservation agendas.

Subfields: General Agricultural and Biological Sciences, Global and Planetary Change, Plant Science

View Paper: https://www.semanticscholar.org/paper/01f6e40697a50274d39fc8c6ad632616f233ab19

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Citations in the corpus

Trade-offs between environment and livelihoods: Bridging the global land use and food security discussions (2017, neutral): “…a central role in current agricultural production, with 70% of the food calories in Latin America, sub-Saharan Africa, and South and East Asia produced in likely smallholderdominated areas (with an average farm size of 5 ha or less), which encompass ~383 million households (Samberg et al. 2016).”
Cropland Abandonment in South African Smallholder Communal Lands: Land Cover Change (1950–2010) and Farmer Perceptions of Contributing Factors (2018, background): “Considering the importance of smallholder farming to food production and rural livelihoods, large-scale, but fine resolution assessments of cropland abandonment are required to understand the extent of cropland farming decline (see an excellent example of disaggregated global farming data for smallh”
A global, spatially-explicit assessment of irrigated croplands influenced by urban wastewater flows (2017, background): “irrigating directly from sewers) [8, 50, 51] and can make substantial contributions to the production of food calories [52].”
The Global Food‐Energy‐Water Nexus (2018, background): “, De Schutter, 2011) The transition to large-scale farming, however, might be unnecessary: small-scale farms, which account for most of the global calorie and nutrient production (Herrero, et al., 2017; Samberg et al., 2016), can be very productive.”
Typology and distribution of small farms in Europe: Towards a better picture (2018, background): “This may be due to lack of detailed data, but also due to the lack of adequate and tailored analytical approaches to grasp the diversity of small farms and the factors impacting on their distribution (Samberg et al., 2016).”
A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform (2018, neutral): “Average crop ﬁ eld size in China is less than a hectare (Samberg et al., 2016); ﬁ ne resolution satellite data is required to map such crop ﬁ elds.”