Ecosystems and agro-biodiversity �across small and large-scale maize production systems

TEEBAgFood - CONABIO

RESEARCH OBJECTIVES

1. To compare the dependencies and impacts of different maize production systems on ecosystem services.

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II. Formulate policy options and recommendations towards improving the sustainability of production practices and enabling an agricultural transition that better balances economic costs and benefits for maize systems.

1. Maize has become one of the most important crops for humanity, mostly because of its great environmental adaptability and high productivity.

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• Maize production has increased twice as much as its harvested area since the year 1990.

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• There is no crop with such a wide variety of uses as maize.

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• The vast majority of maize in the world is produced as a raw material for the livestock, sweetener and oil industries, as well as for the production of ethanol and other non-edible products.

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• The agricultural policy of the United States of America has played a critical role in global maize production, trade and supply.

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• Despite the global expansion of modern maize varieties, landraces are still grown in several regions of the world.

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• Smallholders provide most of the world´s direct food-maize and are the stewards of the genetic, agricultural and landscape diversity of this crop.

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• Agrobiodiversity that is managed in small-scale maize production systems has a strategic value for feeding both the societies that produce and those that consume this cereal.

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SOME PRELIMINARY FACTS ON MAIZE

Section 2

Typology of maize production systems

Note: To map the potential distribution of maize production systems we used yield as a proxy of input intensity. Smallholders (< 2 ton/ha), Intermediate (2-6 ton/ha) and Intensive (>6 ton/ha).

Source: own elaboration using data from You et al. 2014: Spatial Production Allocation Model (SPAM) 2005 v2.0. October 21, 2016. Available from http://mapspam.info

Section 3

Smallholder maize systems

Defined as subsistence or semi-subsistence oriented production units in which either part or all of the agricultural production is consumed directly by the household, as food or in other uses (e.g. feed, construction).

Defining characteristics

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• Medium to high intraspecific and interspecific diversity
• High genetic diversity of crops
• Rely on family labor and on culturally acquired knowledge to manage ecosystem services underlying farm productivity
• Rely on seed saving and seed exchange

Geo-climatic context

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• Mean annual temperature (M=21.9, 11-30 °C)
• Annual precipitation (M= 1319, 16-2945 mm)
• Evapotranspiration rates (M=1337, 588-2096 mm)
• Altitude (M=415, -223-2003 m)
• Slope index (M=87, 3.2-100)
• Dominant soils: Ferrosols (13.86%),
• Acrisols (11.6%), Leptosols (11.14%), Cambisols (9.86%) and Arenosols (9.24%)

Section 3.1

Intensive maize systems: Rainfed

Defined as fully commercially-oriented production units whose main focus lies in maximizing profit.

Defining characteristics

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• Low to very low inter and intraspecific diversity
• Poor genetic variability of crops
• Depend on commercial seed supply
• Fully mechanized units
• Control of production factors: genetic makeup of seeds, nutrient input, control of weeds, pests, diseases and water
• Farms with large to very large area

Geo-climatic context

• Mean annual temperature (M=11, -2.8-28.4°C)
• Annual precipitation (M=892, 29-1866 mm)
• Evapotranspiration rates (M=894, 496-1689 mm)
• Altitude (M=231, -239-776 m)
• Slope index (M=93, 77-100)
• Dominant soils: Phaeozems (24%), Luvisols (22%), Cambisols (11%), Acrisols (9%)

Section 3.2

Defined as fully commercially-oriented production units which main focus lies in maximizing profit.

Defining characteristics

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• Diversity, input use and level of mechanization is in principle the same as in intensive rainfed systems
• Intensive irrigated systems can to a certain extent “escape” the geographical and seasonal limitation imposed by rainfall regimes

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Intensive maize systems: Irrigated

Geo-climatic context

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• Mean annual temperature (M= 14, -1.4-28°C)
• Annual precipitation (M= 516, 0-1732mm)
• Evapotranspiration rates (M= 1148, 363-2007 mm)
• Altitude (M= 91, 50-100 m)
• Slope index (M= 91, 50-100 )
• Dominant soils: Luvisols (13.6%), Cambisols
• (12.1%), Calcisols (9.8%), and Kastanozems (11.6%)

Section 3.2

Defined as agricultural schemes that prohibit the use of genetically modified seeds, chemical fertilizers, pesticides and insecticides.

Defining characteristics

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• Reliance of organic systems on a well-defined set of recommended management practices recognized through a certification process
• Commercially oriented
• Produce maize mainly for the organic meat/milk/poultry food industry
• Rely on the use of crop rotation with forage legumes, cover crops and green manures, intercrops and organic fertilizers to manage soil fertility.
• Management of pests and diseases through colonization prevention, population regulation and curative practices.
• Management of weeds trough crop rotation, use of cover crops and flaming, mechanical weeding methods, etc.

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Organic maize systems

• In 2013, 43.1 million ha of agricultural land worldwide were either under certified organic management or in the process of conversion
• The area destined for the production of cereals was 3,309,788 ha, with maize accounting for 10% of this area, after wheat (36%), oats (14%) and barley (11%)
• Main producers of organic maize are China and the U.S., which together account for 54.7% of the entire area of organic maize production

Section 3.3

Externalities of maize systems: non-monetary valuations

Externalities of maize systems: monetary valuations

Dependency of global systems on maize genetic diversity

Section 5.1

• Maize was domesticated in Mexico around 9,000 years ago (1), 5,000 years later it spread to the rest of the American Continent, and subsequently to the rest of the world (2) where it has become one of the three most used cereals, thanks to its productivity, plasticity and adaptability.

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• All maize production systems depend on the availability of genetic diversity.

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• Intensive maize production systems rely on genetically stable hybrid commercial seeds that seek predominantly to enhance yield.

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• Although breeding has focused in producing “pure” lines, breeding programs have continuously introduced exotic materials for their ability to provide beneficial genetic response, especially for new or unusual sources of stress but also for yield.

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• Small traditional production (often conducted in multiple climatic contexts and in marginal settings) depends on a wide range of existing and future sources of genetic variability to confront biotic and abiotic stresses.

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• Smallholders, by producing in those settings, maintain maize genetic diversity using management practices that involve recurrent selection, experimentation and gene flow with wild relatives

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1) Matsuoka et al., 2002; van Heerwaarden et al., 2011, 2) Vigouroux et al., 2011

Figure 4.4: Schematic representation of the “life cycle” of maize seeds in intensive vs traditional smallholder production systems, where the former has a starting and a finishing point while the latter is cyclic, retaining part of the production to start a new cycle (WR are “wild relatives”).

Qualitative assessment

Genetic externalities of maize production in intensive and smallholders systems

Section 5.2

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Externalities of genetic uniformity

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1. Promoting genetic uniformity allows for mechanization and better harvesting timing, but also makes crops susceptible to the rapid spread of pests and diseases.

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• The problem of not breeding new base material is that it implies leaving out a wide range of potentially useful diversity that was discarded early or never used at all.

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• The first consequence of this is that the diversity not present in the breeding panels could be responsible for traits that were not relevant at the time of selection, but that can be so now or for other parts of the world.
• The second consequence is that eventually this lack of initial variation is translated into a lack of divergence for inbred parental lines.

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• Rare alleles (low frequency) are a crucial source of adaptation to new conditions and pests (1) as well as for agricultural traits associated with quantitative trait loci (2). Recurrent rounds of selection of modern breeding have caused genetic bottlenecks that have tended to eliminate rare alleles (3).

Southern Leaf Corn Blight

Photo credit: taken from https://en.wikipedia.org/wiki/Southern_corn_leaf_blight

1) Vigouroux et al,. 2011, 2) Jiao et al., 2012, 3) Romay et al., 2013

Qualitative assessment

Section 5.2

Externalities of genetic diversity

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1. On-farm cultivation of maize landraces allows for the generation of new diversity and promotes local adaptation.

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• In Mexico 4.6 Million ha were grown in 2010 with 59 native landraces (figure 5.3) in a wide range of environments covering 11 biogeographic regions and environmental conditions (1).

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• Considering around 30,000 plants/ha are grown, that is 1.38 x 10¹¹ individual plants being grown each year.

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2. The selection of these seeds is commonly done by choosing around 290 ears of the harvested material, each with 400 kernels (2). Because seeds from the same ear have the same mother this reduces the population to 290 effective families that would pass to the next generation.

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• 290 maize families per ha in 4.6 Million ha means 1.33 x 10⁹ plants contributing to the next generation with their background genetic diversity along with rare alleles

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• Selection of these ears is performed independently by around 3 million smallholders, in different environments and in a process in which both men and women make the decisions based on their own criteria.

Figure 5.3. Mexican native landraces (57 of 59) and teocintles growing in Mexico. Top part shows maize landraces cobs and one teocintle (center). Made with data from the Global Maize Project (CONABIO, 2011) and pictures from: Guillermo Aguilar Castillo, Luis Alonso Borunda Paquot, José Alfredo Carrera Valtierra, Eliud Castaño Suárez, Roger Iván Díaz Gallardo, Noel Orlando Gómez Montiel, José Cruz Jiménez Galindo, María del Carmen Loyola Blanco, Cecilio Mota Cruz, Alejandro Ortega Corona, Rafael Ortega Paczka, Oscar Palacios Velarde, Hugo Perales Rivera, Beatriz Rendón Aguilar, Froylán Rincón Sánchez, José Ron Parra, José de Jesús Sánchez González, Miguel Ángel Sicilia Manzo, Víctor Antonio Vidal Martínez. CONABIO Images Bank. Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias (INIFAP). Information on Mexican maize landraces can be consulted at CONABIO’s website on maize landraces and CONABIO’s poster on maize landraces.

1) Perales and Golicher, 2014, 2) van Heerwaarden et al., 2012

Qualitative assessment

Impacts of maize production practices on ecosystem services: agro-ecological, organic and conventional agricultural management

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• The aim of this section is to make visible the trade-offs and synergies in the provision of ES by maize production systems under conservation agriculture and organic systems compared with conventional practices.

• Compared to conventional agriculture, conservation agriculture reduces soil erosion (25-70%), improves soil fertility (60%), enhances water regulation by increasing the amount of percolated water (50%-200%), and results in higher maize yields (26%-190%).

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• By reducing runoff and water soil erosion, CA decreased the amount of transported pesticides, nutrients and sediments to water bodies, in detriment of water quality.

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• Evidence on positive outcomes of organic maize systems (OS) relative to conventional systems is conclusive for three ecosystems services: soil structure and fertility enhancement, biodiversity, and water flow regulation.

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• OS do result in lower maize yields (approximately 11% and up to 28% lower during the transitioning period). However, given their premium price, the value of provisioning ES (maize for food and raw materials) in OS is higher than conventional maize, in spite of their lower yields.

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• OS perform better than conventional maize production: percolated water in OS was 15-20% higher; they retained 200-300% more SOC, and N in the soil was 34% more.

Section 5.3

Photo credit: Iván Montes de Oca Cacheux

Qualitative assessment

Photo credit: Adalberto Ríos Szalay

The cultural value of maize diversity

Section 5.4

The presence of native maize landraces is conspicuous in smallholder farms in both Mexico and Ecuador.

• There are 35 indigenous groups in Ecuador, 14 of which live up in the mountains and depend on maize cultivation.

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• Most producers (54%) plant from two to seven maize varieties along other associated crops, mainly beans (50%), and 98% of the production is for their own consumption.

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• In the 1960s, 29 maize landraces and several complexes were identified in the country (Timothy et al, 1963), and in the last two decades (Yánez et al., 2003) additional landraces have been found.

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• According to Tapia (2015) the practice of subsistence agriculture and the great variety of uses given to maize landraces has made their conservation possible.

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• The diversity of uses for maize among rural communities is manifested in the many dishes prepared with this staple in everyday life as well as religious festivals and entertainment events in both urban and rural settings.

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Ecuador

Local festivities related to maize (Photo credit: Edison Sylva)

Maize at the entrance of Sangolquí and Pallatanga, Ecuador (Photo credit: Edison Sylva)

Qualitative assessment

Section 5.4

• Maize can be considered a “cultural keystone species” in Mexico , that is, a culturally salient species that shapes in a major way the cultural identity of a people (Garibaldi and Turner, 2004).

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• Maize’s key role in defining cultural identity for Mexicans materializes through its prevalent place in the landscape, its essential irreplaceable place in daily nourishment and cuisine, its multiplicity of use, and in narratives and ceremonial roles.

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• Although in Mexico maize is used primarily as a staple, it has multiple uses and is the species with more uses reported in the Florentine Codex, written by Francisco Hernández several decades after the Spanish conquest (Estrada, 1989).

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• Mexico’s iconic milpa system is constructed around maize. In its usual form, the milpa is the cultivation of maize, beans and squash in the same field and season.

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• Maize’s importance as a central component of Mexican cuisine is well known, the number of dishes based on maize are in the hundreds and continue to be developed.

Mexico

Painting by Diego Rivera

Qualitative assessment

Comparative importance of maize in Ecuador, Mexico and USA

Section 5.4

Garibaldi and Turner 2004: 5 [yes, very high], 4 [yes, high], 3 [yes, moderate], 2 [yes, low] 1 [yes, though very low or infrequent], 0 [no, not used]

Qualitative assessment

Comparative importance of maize in Ecuador, Mexico and USA

Section 5.4

Garibaldi and Turner 2004: 5 [yes, very high], 4 [yes, high], 3 [yes, moderate], 2 [yes, low] 1 [yes, though very low or infrequent], 0 [no, not used]

Qualitative assessment

Valuation of ecosystem services for maize production in Ecuador, Mexico and USA

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• Agricultural production depends on a number of external inputs such as labor, machinery, and agro-chemicals, as well as on internal inputs provided by natural capital and its derived ecosystem services (ES).

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• A production function is a mathematical equation that relates the various inputs involved in the production of a good with the amount of goods produced. The production function method has been used as way to uncover the value of specific attributes of the environment, or of particular ecological functions and processes (Barbier, 1994; Barbier, 2007; Kumar, 2010).

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• The aim of the present study was to identify the relation between a set of ecosystem services (provision, regulation and support services) and maize production in our three case study countries, in order to value their contribution to maize production. The variables chosen to represent proxies for ecosystem services were: annual precipitation and irrigated area as provision services for agriculture; rainfall seasonality and maximum temperature as regulation services; and sowed maize area and soil organic carbon as support services.

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• Data for the multiple regressions comprised both environmental and management variables (to control for agricultural inputs).

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• Administrative units of Mexico and USA were classified as 1) high-yield irrigated (> 2 ton/ha and > 75% of maize area under irrigation), 2) high-yield rainfed (> 2 ton/ha and > 95% of maize area rainfed), 3) mixed (>5% and <75% of maize area under irrigation), and 4) low-yield rainfed (< 2 ton/ha and > 95% of maize area rainfed). In the case of Ecuador we grouped cantons according to their region: Amazonia, Andes and coastal region. We run a linear regression model with heteroscedasticity correction for each of this systems.

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• The significant betas (i.e. elasticities) obtained for each model were used to calculate the value of the marginal product of ecosystem services.

Section 6.1

Monetary valuation

Ecuador

Section 6.1

Monetary valuation

A total of 203 cantons were used for the three production functions developed for Ecuador

a) Boxplot for altitude, slope index and soil organic carbon

b) Boxplot for rainfall seasonality, maximum temperature and annual precipitation

Value of the marginal product of ecosystems services for maize production in different maize-producing regions in Ecuador

Section 6.1

Monetary valuation

Sum of VMP of ecosystem services in different maize producing cantons in Ecuador

Mexico

Section 6.1

Monetary valuation

A total of 2,287 municipalities were included in the regression analysis for Mexico

a) Boxplot for altitude, slope index and soil organic carbon

b) Boxplot for rainfall seasonality, maximum temperature and annual precipitation

Section 6.1

Monetary valuation

Sum of VMP of ecosystem services in different maize producing municipalities in Mexico

Value of the marginal product of ecosystems services for maize production in different maize-producing municipalities in Mexico

USA

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Section 6.1

Monetary valuation

a) Boxplot for altitude, slope index and soil organic carbon

b) Boxplot for rainfall seasonality, maximum temperature and annual precipitation

A total of 2,231 counties were included in the regression analyses for USA

Value of the marginal product of ecosystems services for maize production in different maize-producing counties in USA

Section 6.1

Monetary valuation

Sum of VMP of ecosystem services in different maize producing counties in USA

Section 6.1

Monetary valuation

Conclusions

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Land was the ecosystem service that showed the highest marginal value of all ecosystem services.

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In some cases other ecosystem services like maximum temperature in the Ecuadorian Andes, rainfall seasonality in mixed municipalities in Mexico and irrigated area in high-yield irrigated counties in USA showed similar or higher contribution to maize production than sown area.

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Even though an ecosystem services might have a similar contribution to maize production in similar areas, its value is higher for the area (canton/county/municipality) that produces more, simply because its contribution is relative to the total production of maize.

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Future attempts to estimate the marginal value of ecosystem services to agricultural production will greatly benefit from longitudinal data, data at a lower level of aggregation (e.g. farm level), the use of primary instead of modelled data (e.g. data on soil and climate), and maize-specific management data (as available for Ecuador).

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The hidden value of green water provision for maize production

Section 6.2

• The supply of water is a critical ecosystem service for agriculture. It is estimated that around 70% of the water extracted from aquifers, rivers and lakes is used in agricultural production (FAO, 2011).

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• Water availability in agricultural ecosystems depends not only on infiltrated water, but also on moisture retained by the soil. In fact, it is estimated that around 80% of the water used by agricultural crops comes from this latter source (Molden, 2007).

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• Green water is defined as the rainwater consumed by a crop (Mekonnen and Hoekstra, 2011: p. 1578).

• The aim of the present valuation was to quantify the hidden value of green water provision for maize production.

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• To analyze the data according to maize systems we collected the spatially explicit data of green water (in millimeters) modeled for 1996-2005 by Mekonnen and Hoekstra (2010) available in a 5 by 5 ARC minute raster grid and spatially explicit data about maize production modelled for 2005 by You et al. (2014), also available at the same resolution.

Photo credit: Iván Montes de Oca Cacheux

Pixel classification

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Rainfed: Less than 25% of the maize area is irrigated.

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Mixed: Between 25 and 75% of the maize area is irrigated.

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Irrigated: More than 75% of the maize area is irrigated.

Monetary valuation

Section 6.2

For Ecuador we had a total of 1,819 pixels. Of these, 202 were irrigated, 101 were mixed and 1,516 were rainfed.

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Rainfed areas comprised 78.5% of the total harvested maize area, 68% of the country´s maize production, and used 79.7% of the total green water use.

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Rainfed areas used the greatest amount of green and blue water in absolute terms.

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Per hectare irrigated areas showed the greatest use of green water per ha, while mixed areas the greatest use of blue water.

Deflated cost of irrigated water in Ecuador: USD 0.165 per cubic meter (Y. Cartagena Ayala, personal communication, 2016)

Cost of maize in 2005: USD 345 per ton (FAOSTAT, 2016)

ECUADOR

Monetary valuation

Section 6.2

MEXICO

Deflated cost of irrigated water in Mexico: USD 0.184 per cubic meter (C. Cabrera Cedillo, personal communication, 2016)

Cost of maize in 2005: USD 144.9 per ton (FAOSTAT, 2016)

For Mexico a total of 9,453 pixels were used, of which 83.5% were rainfed, 8.7% mixed and 7.7% were irrigated.

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Irrigated pixels had the smallest cultivated area (9.3%) but contributed 12.9% of the entire maize production. Rainfed areas accounted for close to 76.6% of the green water use and 72.5% of the blue water consumption.

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Per hectare, mixed units used up the greatest amount of green water (581.5 m3), followed by irrigated (487.1 m3) and rainfed units (347.5 m3), whereas blue water use was greatest among irrigated (9.1 m3/ha) compared to mixed (8.5 m3/ha) and rainfed (4.5 m3/ha) areas.

Monetary valuation

Section 6.2

USA

Deflated cost of irrigated water in USA: USD 1.144 per cubic meter (Agricultural Resources and Environmental Indicators, 2006)

Cost of maize in 2005: USD 79 per ton (FAOSTAT, 2016)

In USA data from 15,843 pixels was used.

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Rainfed maize production comprised the great majority of maize producing pixels in USA (51%), they have the greatest cultivation area (78.6%), produced 78.5% of the total maize production, used up 74.5% of the total green water and 9.4% of the blue water used in maize production.

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In contrast, irrigated areas used 13.2 % of the green water and 56% of the blue water.

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Monetary valuation

Conclusions

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The potential cost of green water for all maize production systems are very significant and remain widely unaccounted for both in maize markets and policies. In Ecuador these represent 27.4 to 77.5 of the value of maize production in the country. In Mexico and USA , this value even surpass the total value of maize production.

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Areas producing maize in USA are the ones “saving” most if green water was considered an asset with economic value (figure 4.17), or seeing it the other way around, they would be the ones “losing the most” if green water suddenly became unavailable and it had to be replaced by irrigation.

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Finally, a word of caution regarding the previous estimations: we merged data from two different data sources; data from maize area and maize production came from You et al. (2014) while data from green and blue water came from Mekonnen and Hoekstra (2010). Even though both sources used as its base spatially explicit data on maize production generated by FAO (2006), You et al. (2014) added subnational data from a network of data resources from various local subnational offices. This means that data is not necessarily compatible which may result in estimations that are not entirely accurate.

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Section 6.2

Monetary valuation

The cost of grey water in maize production systems

Section 6.3

Among the most widely acknowledged impacts of agricultural production on ecosystem services is water contamination by agrochemicals and nutrient load (Conley et al. 2009). It has been estimated that 50% of the nitrogen used in agricultural systems is used by plants, 2 to 5% remains in the soil, 25% is released as N2O emissions, and 20% is leached into aquatic ecosystems (Galloway et al., 2004).

The aim of this section was to elaborate a partial estimate of the externalities of chemical nitrogen fertilizer use (NITROGEN) in maize production, that is, the cost of meeting a water quality standard.

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Grey water refers to the “volume of freshwater that is required to assimilate the load of pollutants based on existing ambient water quality standards” (Mekonnen and Hoekstra , 2011: p.1578).

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To analyze the data according to maize systems we collected the spatially explicit data of grey water (in millimeters) modeled for 1996-2005 by Mekonnen and Hoekstra (2010) available in a 5 by 5 ARC minute raster grid and spatially explicit data about maize production modelled for 2005 by You et al. (2014), also available at the same resolution.

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Grey water was monetized using irrigations costs described in section 5.3

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http://www.gulfhypoxia.net/overview/

Monetary valuation

Section 6.3

ECUADOR

The grey water footprint of Ecuador was the smallest among our study countries which is clearly reflected in the map.

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A total of 1,819 pixels were used to calculate the cost of grey water in Ecuador of which half of them (45.8%) corresponded to smallholder grids, and the rest (54.2%) to mixed production grids.

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Smallholder pixels represented 57.4% of the harvested area, 37.2% of the total production, and 42% of the total grey water footprint.

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Smallholder : <2 ton/ha

Intermediate: 2 -6 ton/ha

Intensive: > 6 ton/ha

Deflated cost of irrigated water in Ecuador: USD 0.165 per cubic meter (Y. Cartagena Ayala, personal communication, 2016)

Cost of maize in 2005: USD 345 per ton (FAOSTAT, 2016)

Monetary valuation

Section 6.3

MEXICO

For Mexico we had data for 9,376 pixels of which 3.2% were intensive grids, 47.5% were intermediate producers and 46.6% were smallholders.

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Irrigated pixels shared 5.9% of the total maize area, and produced 17% of the total maize production.

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The average grey water footprint was higher among high-yielding units, then by intermediate ones and is lowest among low-yielding units. However, given the larger maize producing areas of both intermediate and low-yield units, these end up having a greater grey water footprint and associated costs than intensive ones.

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Deflated cost of irrigated water in Mexico: USD 0.184 per cubic meter (C. Cabrera Cedillo, personal communication, 2016)

Cost of maize in 2005: USD 144.9 per ton (FAOSTAT, 2016)

Monetary valuation

Section 6.3

USA

The highest grey water footprint in USA is distributed along the Corn Belt region corresponding to the states of Iowa, Illinois, Minnesota, South Dakota, Nebraska, Kansas, Missouri, Indiana and Ohio, as well as small portions of Idaho, Washington and Texas.

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A total of 15,845 units were included in the analysis of which 0.3% were smallholder units, 19.6% were intermediate, and 80.1% were intensive ones. Intensive units held 95.6% of the total harvested area of maize and 98% of the entire maize production.

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On average intensive maize producers had a higher grey water footprint (20.6 mm) than intermediate ones (3.1 mm), in both total (18,484,160,113 vs. 709,811,663 m3) and relative terms (203.2 vs 31 m3/ha).

Deflated cost of irrigated water in USA: USD 1.144 per cubic meter (Agricultural Resources and Environmental Indicators, 2006)

Cost of maize in 2005: USD 79 per ton (FAOSTAT, 2016)

Monetary valuation

Conclusions

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The three countries generated vastly different grey water footprints. The total grey water generated by the three countries was 24,703,616,726 cubic meters per year (77.7% produced by USA, 21.6% by Mexico and 0.7% by Ecuador ) with a total estimated remediation cost of 23.1 billion USD each year.

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In USA intensive units were responsible for almost all the grey water footprint of the country, while in Mexico, smallholders and intermediate producers were responsible for it mainly because they represented the predominant maize producers in both cases.

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Using the cost of the amount of water needed to dilute nitrate levels in water to value the impact of eutrophication, represents, without doubt, only a small part of the total economic cost that should be accounted for given the negative impacts of nitrogen leaching for aquatic ecosystems and biodiversity.

Section 6.3

Monetary valuation

Section 6.4

• Centers of origin and genetic diversity have been recognized as having “crucial importance to humankind”

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• The Mexican Biosafety Law (DOF, 2005) considers that areas inside the country where centers of origin and genetic diversity of native crops are located should be officially established so they can be protected.

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• To comply with the cost-benefit obligations previously required to decree these areas for maize, an economic study was undertaken which used the methodology of shadow prices to uncover and make other values (such as characteristics related to physiochemical aspects, cropping, culture, diet and cuisine) of maize landraces visible in order to demonstrate the benefits entailed of preserving the areas where these are grown (SEMARNAT, 2011).

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• Arslan and Taylor (2009) elaborated an assessment of the cultural values underlying maize landraces production for traditional maize farmers in Mexico through shadow prices using the National Survey to Rural Households in Mexico as its basis.

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• Like Arslan and Taylor (2009) we found that the shadow price of rainfed maize for self-consumption in 2011 is around nineteen times higher than the market price for white maize grain.

Maize cultivation. Florentine code

Monetary valuation

The value of maize landraces: a shadow price analysis to support decision making related to the protection of the centers of origin and genetic diversity of maize in Mexico in 2011

1) All policies related to the production of maize should acknowledge that there are different types of production systems, each with different dependencies and impacts on ecosystem services

• Different maize production systems need different policies.
• Markets must differentiate, value and acknowledge the diverse sources and attributes of maize production systems and their resulting products.

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2) There is a need to invest more in publicly funded scientific research and specific data generation regarding maize production systems

• Reconsider agricultural research and development as a national state strategy.
• There is a need for financial investment in global maize generation of knowledge, research and development.
• All maize farmers worldwide should be able to benefit more directly from research and breeding efforts.
• Breeding and agronomical efforts should incorporate a focus on local landraces.

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Public policies recommendations

Section 7

Photo credit: Efrain Hernández Xolocotzi

Photo credit: Efrain Hernández Xolocotzi

3) There is a need to support the valuation and conservation of on-farm crop genetic resources

• We must make efforts to understand, value and strengthen the processes by which genetic diversity is continuously evolving.
• A worldwide driven decisive effort is needed to strengthen in situ conservation efforts to complement ex situ conservation in the public domain.
• Family agriculture and traditional small scale agriculture should be revalued.

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4) A transition leading to sustainable practices in the production of maize should be promoted

• All maize production systems must aim at being sustainable in their agricultural production approach.
• Financial support is necessary for the different maize production systems to aim towards sustainability.
• Subsidies need to be reconsidered.

Section 7

Photo credit: Diana Kennedy

References

Arslan A, Taylor JE (2009) Farmers’ subjective valuation of subsistence crops: the case of traditional maize in Mexico. Am J Agr Econ 91(4):956–972

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