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Beyond subsistence: the aggregate contribution of campesinos to the supply and conservation of native maize across Mexico


Mexico is the center of domestication and a center for diversity of maize. Area planted with maize is the country’s largest agricultural land use, mostly planted by smallholder family farmers known as campesinos. They generally plant native varieties, saving and sharing seed by and among themselves, enabling the evolutionary processes that sustain and generate crop genetic diversity to continue today. Campesinos have been viewed as largely subsistence farmers generating limited maize surpluses. Here, we show that subsistence production is insufficient for explaining the quantity of maize they produce and the extent of the area they plant across Mexico. Our hypothesis is that beyond supplying their own consumption needs, campesinos collectively produce maize to respond to the demand of non-maize producing local consumers. We quantify the extent of subsistence versus surplus production among campesinos, showing that they produce more maize than would be needed to feed themselves and generate substantial surpluses. We test statistically the association between the area campesinos plant with maize across the country with socioeconomic variables that link their production to the demand by other consumers, and examine the implications of the results for the supply and conservation of native maize in the country. Our results suggest that maize trading linking campesinos to other consumers may be important and widespread, contributing to create additional incentives beyond self-consumption to plant native varieties from saved seed. We conclude that there are important opportunities for maintaining maize evolution under domestication at large scale by strengthening local maize markets.

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  1. A government program providing a subsidy per hectare of land cultivated to farmers who were originally subscribed at the onset of North American Free Trade Agreement (NAFTA). The data was originally retrieved from However, this link it is no longer active. The downloaded data used in our previous study is available at (Bellon et al., 2018b Accessed September 29, 2020.

  2. SIAP is the government body that compiles and reports on official agricultural statistics. The reported data is based on field information collected and validated at the municipality level according to SIAP’s Technical Standard for the Generation of Basic Agricultural and Fishery Statistics (SIAP 2016).

  3. It should be pointed out that there is a high correlation between the area planted reported by SIAP and calculated from the PROCAMPO beneficiaries by municipality (0.85), indicating that there is a high likelihood that inferences based on PROCAMPO data apply nationally (Supplementary Material Fig S1 and S2).

  4. There are other estimates of daily per capita maize grain consumption, e.g. 267 and 370 g (Ranum et al. 2014; Stuart, 1990 respectively) which are lower than the amount used here. While per capita consumption may vary across the country, we are not aware of data documenting this variation. CONEVAL per capita consumption is used to calculate national poverty rates, only distinguishing between rural and urban consumption.

  5. 6,627,641 + 16,794,624 = 23,422,265- 21,166,430 = 2,255,835 persons. It should be pointed out that in our earlier paper (Bellon et al. 2018a) we estimated that a population of 54 million people could potentially be fed from the production of municipalities with average yields ≤3 t ha−1. The discrepancy is that in that paper we used all the area planted and not just that of farms planting ≤5 ha and the per capita consumption was increased only by 25% instead of 100%.


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Correspondence to Mauricio R. Bellon.

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B.Supplementary Information


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A.Appendix 1. Diagnostic tests

A.Appendix 1. Diagnostic tests

Table 4 presents the value of the Moran I statistic two-sided on the residuals of an OLS regression of the model in Eq. 1. It is highly statistically significant, indicating the presence of spatial autocorrelation and thus the need to address it. Table 4b-c shows the values of different Lagrange Multiplier tests statistics for different specifications of the spatial autocorrelation: error dependence and lagged dependent variable. Since both the LMerr and LMlag are statistically significant, we compared their robust forms RLMerr and RLMlag. Results suggest that the lag model as the likely alternative (RMLag = 22.273, p value = 0.000 versus RLMerr = 0.63505, p value = 0.426).

Table 4 Diagnostic tests for spatial autocorrelation (new)

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Bellon, M.R., Mastretta-Yanes, A., Ponce-Mendoza, A. et al. Beyond subsistence: the aggregate contribution of campesinos to the supply and conservation of native maize across Mexico. Food Sec. 13, 39–53 (2021).

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  • Zea mays L.
  • Smallholder farmers
  • Local markets
  • Crop evolution
  • Spatial lag models