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In tropical regions, widespread loss of native forest and savanna vegetation is increasing extreme heat, particularly in agricultural regions. Using the case of rising extreme heat from lost forest and savanna vegetation in Brazilian Amazon and Cerrado regions, we modeled losses to soy production, the region’s principal economic activity. We assessed two types of extreme-heat regulation values: the value of avoided extreme-heat exposure of soy from the conservation of neighboring ecosystems and the value of lost revenue due to increased extreme heat exposure from increased ecosystem conversion. Our modeling combines empirical estimates of (1) the influence of ecosystem conversion on extreme heat over neighboring cropland, (2) the impacts of extreme heat on agricultural yields, and (3) native vegetation area, agricultural area, and crop prices. We examine lost soy value from land conversion over the period 1985 to 2012, potential losses from further conversion under plausible land and climate change scenarios (2020–2050), and the future value of conservation of the region’s remaining ecosystem area near soy. Soy revenue lost due to extreme heat from native vegetation loss (1985–2012) totaled 99 (2005USD) ha−1 for 2012-2013 growing season. By 2050, agricultural growth, ecosystem conversion, and climate change could boost extreme-heat regulation values by 25% to 95%. Future values were strongly sensitive to changes in agricultural density, rates of native vegetation loss, and climate. Extreme-heat regulation values were largest in the Cerrado biome and the southeastern Amazon. Relative to land values, the value of extreme heat regulation was largest relative to the carbon value of biomass in the Cerrado. By regulating the exposure of agriculture to extreme heat, ecosystem conservation can create considerable value for the soy sector.

Large-scale agriculture in the state of Mato Grosso, Brazil is a major contributor to global food supplies, but its continued productivity is vulnerable to contracting wet seasons and increased exposure to extreme temperatures. Sowing dates serve as an effective adaptation strategy to these climate perturbations. By controlling the weather experienced by crops and influencing the number of successive crops that can be grown in a year, sowing dates can impact both individual crop yields and cropping intensities. Unfortunately, the spatiotemporally resolved crop phenology data necessary to understand sowing dates and their relationship to crop yield are only available over limited years and regions. To fill this data gap, we produce a 500 m rainfed soy (Glycine max) sowing and harvest date dataset for Mato Grosso from 2004 to 2014 using a novel time series analysis method for Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery, adapted for implementation in Google Earth Engine (GEE). Our estimates reveal that soy sowing and harvest dates varied widely (about 2 months) from field to field, confirming the need for spatially resolved crop timing information. An interannual trend toward earlier sowing dates occurred independently of variations in wet season onset, and may be attributed to an improvement in logistic or economic constraints that previously hampered early sowing. As anticipated, double cropped fields in which two crops are grown in succession are planted earlier than single cropped fields. This difference shrank, however, as sowing of single cropped fields occurred closer to the wet season onset in more recent years. The analysis offers insights about sowing behavior in response to historical climate variations which could be extended to understand sowing response under climate change in Mato Grosso., Soy cultivation; Sowing date; Mato Grosso; Climate change; Remote sensing; Time series analysis.

Hundreds of millions of the world's poorest people directly depend on smallholder farming systems. These people now face a changing climate and associated societal responses. We use mapping and a literature review to juxtapose the climate fate of smallholder systems with that of other agricultural systems and population groups. Limited direct evidence contrasts climate impact risk in smallholder agricultural systems versus other farming systems, but proxy evidence suggests high smallholder vulnerability. Smallholders distinctively adapt to climate shocks and stressors. Their future adaptive capacity is uncertain and conditional upon the severity of climate change and socioeconomic changes from regional development. Smallholders present a greenhouse gas (GHG) mitigation paradox. They emit a small amount of CO2 per capita and are poor, making GHG regulation unwarranted. But they produce GHG-intensive food and emit disproportionate quantities of black carbon through traditional biomass energy. Effectively accounting for smallholders in mitigation and adaption policies is critical and will require innovative solutions to the transaction costs that enrolling smallholders often imposes. Together, our findings show smallholder farming systems to be a critical fulcrum between climate change and sustainable development.

The rate and location of cropland expansion onto cattle pastures in Brazil could affect global food security, climate change, and economic growth. We combined mapping, statistical modeling, and qualitative methods to investigate patterns and processes of pasture to crop conversion (P2C) in Mato Grosso State (MT), Brazil, a globally important center of agricultural production. P2C land constituted 49% of cropland expansion from 2000 to 2013. For a random sample of 250 m pixels in MT, we estimated a regression model skilled at predicting P2C land in the rest of the state as a function of cattle ranching suitability, cropping suitability, and P2C conversion costs. Surprisingly, just 1/7 of pasture agronomically suitable for cultivation had undergone P2C. Hedonic regressions revealed that agronomic characteristics of land were associated with less than 20% of the variation in cropland suitability. Instead, the majority of the variation stemmed from a combination of proximity to agricultural infrastructure, characteristics of neighboring lands, and time fixed effects. The weak relationship between agronomic characteristics of land and P2C location suggests a less certain future for P2C than projections made with agronomic models. Consequentially, complications may arise for greenhouse gas mitigation policies in Brazil predicated on widespread expansion of cropland on pasture vs. natural areas. Our follow-up qualitative research shows that because P2C has often involved land rentals or sales, poorly functioning land institutions may have constrained P2C. Locally poor land quality, omitted from agronomic P2C predictions, can either catalyze or constrain P2C by limiting returns to ranching, farming, or both. Interventions to control rates and locations of P2C should take these insights into account.

About 70% of agricultural output variance due to climate in Mato Grosso, Brazil was determined by changes in cropping frequency and/or changes in cropping area rather than yield (the most common climate impact indicator), a study now shows. The sensitivity of agricultural output to climate change has often been estimated by modelling crop yields under climate change scenarios or with statistical analysis of the impacts of year-to-year climatic variability on crop yields1,2. However, the area of cropland and the number of crops harvested per growing season (cropping frequency) both also affect agricultural output and both also show sensitivity to climate variability and change3,4,5,6,7,8,9. We model the change in agricultural output associated with the response of crop yield, crop frequency and crop area to year-to-year climate variability in Mato Grosso (MT), Brazil, a key agricultural region. Roughly 70% of the change in agricultural output caused by climate was determined by changes in frequency and/or changes in area. Hot and wet conditions were associated with the largest losses and cool and dry conditions with the largest gains. All frequency and area effects had the same sign as total effects, but this was not always the case for yield effects. A focus on yields alone may therefore bias assessments of the vulnerability of agriculture to climate change. Efforts to reduce climate impacts to agriculture should seek to limit production losses not only from crop yield, but also from changes in cropland area and cropping frequency.

We reviewed studies addressing the extent to which more integrated agricultural systems (IAS) have been found to be more resilient to climate variability and climate change than more specialized agricultural systems. We found limited literature directly addressing the topic, necessitating the use of proxy measures to enlarge the sample. Where necessary, we used agricultural system richness and diversity as proxies for the presence of the sort of synergistic relationships that typify IAS, interannual climate variability for climate change, and myriad agricultural indicators for resilience. We found that (1) 37 papers addressed the topic either through mathematical modeling or statistical modeling; (2) in the statistical papers, integration was overwhelmingly (n = 17/24) associated with increased climate resilience; (3) these findings stemmed mainly from comparisons of more versus less diverse or rich farming systems, while few studies investigated the influence of farm system synergies on resilience; (4) yield, revenue, profit, and yield variance were all used to demonstrate resilience; (5) modeling studies tended to investigate resilience across multiple years, while most statistical approaches tracked single-year outcomes; (6) the IAS-climate resilience links demonstrated were not generalizable across units of analysis, spatiotemporal scale, and from autonomous to directed integration; and (7) few of the articles reviewed identified and measured the mechanism by which IAS were shown to have conferred resilience. Our findings reveal suggestive, although by no means conclusive, evidence that farm system integration can enhance resilience and highlight the need for research to test whether integration policies can have similar outcomes. WIREs Clim Change 2017, 8:e461. doi: 10.1002/wcc.461 For further resources related to this article, please visit the WIREs website.

This study examines whether policies to encourage cattle ranching intensification in Brazil can abate global greenhouse gas (GHG) emissions by sparing land from deforestation. We use an economic model of global land use to investigate, from 2010 to 2030, the global agricultural outcomes, land use changes, and GHG abatement resulting from two potential Brazilian policies: a tax on cattle from conventional pasture and a subsidy for cattle from semi-intensive pasture. We find that under either policy, Brazil could achieve considerable sparing of forests and abatement of GHGs, in line with its national policy targets. The land spared, particularly under the tax, is far less than proportional to the productivity increased. However, the tax, despite prompting less adoption of semi-intensive ranching, delivers slightly more forest sparing and GHG abatement than the subsidy. This difference is explained by increased deforestation associated with increased beef consumption under the subsidy and reduced deforestation associated with reduced beef consumption under the tax. Complementary policies to directly limit deforestation could help limit these effects. GHG abatement from either the tax or subsidy appears inexpensive but, over time, the tax would become cheaper than the subsidy. A revenue-neutral combination of the policies could be an element of a sustainable development strategy for Brazil and other emerging economies seeking to balance agricultural development and forest protection.

The expansion of crop agriculture onto low productivity cattle pastures in the agricultural frontier of Brazil is a form of agricultural intensification that can help to contribute to global food and climate goals. However, the amount of pasture to crop conversion in the region lags both agronomic and economic potential. We administered a survey in combination with a lab-in-the-field experiment to 559 farmers in Mato Grosso, Brazil. We used the results to explore behavioral determinants of pasture to crop conversion. We compared farmers choices across two rounds of a risk game meant to mimic the economic risk of decisions to convert pasture to crops. We found framing the risk game to concern agriculture profoundly altered subjects’ experimental choices. These discrepancies involved the majority of experimental subjects, and were highly heterogenous in nature. They were also somewhat predictive of subjects’ behavior converting pasture to cropland. Our findings indicate that farmers may make economic decisions involving agriculture and/or agricultural land differently from other economic decisions. Our finding is of relevance for research into the propensity of farmers to intensify and for policies seeking to influence rates of agricultural intensification.

Along agricultural frontiers, non-governmental organizations are developing agricultural certification systems for use as conservation tools. In this article, we propose a typology of certification systems that we use to frame a critical examination of the efficacy of these systems and their limitations in achieving conservation goals. On the basis of these findings, we recommend improved management practices. Our analysis draws on case studies that examine the use of certification to regulate two very distinct production systems: smallholder shade coffee cooperatives in El Salvador and industrial scale soy and beef operations in the Brazilian Amazon. Despite their disparate contexts, both case studies demonstrate that agricultural certification to achieve conservation goals is difficult to design, implement, and evaluate. Certifiers must enroll consumers and firms who do not prioritize conservation goals, navigate scientific uncertainty regarding best conservation practices, and also market their brand a...

The tropics are a critical nexus of important environmental services and resources, productive lands that are critical to feeding the planet in years to come, and rural economies beset by disease and malnutrition, and in need of economic development. This special issue synthesizes a series of multidisciplinary dialogues aiming to examine the complex challenge of tropical agricultural systems. The work contained five principle themes: (a) The future of tropical agriculture is vital for developing world economies and the global environment in ways that scholars are still working to characterize. (b) The tropics are highly socioeconomically and environmentally heterogeneous. (c) We expect sociocultural and institutional factors to strongly shape the future of tropical agriculture and the environment. (d) Sustainable tropical agriculture means linking smallholders, the vast bulk of farmers, with commercial agriculture, the vast bulk of agribusiness. (d) Scholarship from the environmental sciences can help to ...

One in every five patches of tropical forest near agriculture in Brazil appears to contribute more to agricultural production by preventing crop-killing extreme heat exposure than it could produce ...

This letter uses satellite remote sensing to examine patterns of cropland expansion, cropland abandonment, and changing cropping frequency in Mato Grosso, Brazil from 2001 to 2011. During this period, Mato Grosso emerged as a globally important center of agricultural production. In 2001, 3.3 million hectares of mechanized agriculture were cultivated in Mato Grosso, of which 500 000 hectares had two commercial crops per growing season (double cropping). By 2011, Mato Grosso had 5.8 million hectares of mechanized agriculture, of which 2.9 million hectares were double cropped. We found these agricultural changes to be selective with respect to land attributes?significant differences (p?0.001) existed between the land attributes of agriculture versus non-agriculture, single cropping versus double cropping, and expansion versus abandonment. Many of the land attributes (elevation, slope, maximum temperature, minimum temperature, initial soy transport costs, and soil) that were associated with an increased likelihood of expansion were associated with a decreased likelihood of abandonment (p?