Stephanie A. Spera

Recent cropping frequency, expansion, and abandonment in Mato Grosso, Brazil had selective land characteristics

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?<?0.001). While land similar to agriculture and double cropping in 2001 was much more likely to be developed for agriculture than all other land, new cropland shifted to hotter, drier, lower locations that were more isolated from agricultural infrastructure (p?<?0.001). The scarcity of high quality remaining agricultural land available for agricultural expansion in Mato Grosso could be contributing to the slowdown in agricultural expansion observed there over 2006 to 2011. Land use policy analyses should control for land scarcity constraints on agricultural expansion.

Socioeconomic development and agricultural intensification in Mato Grosso

The Brazilian agro-industrial frontier in Mato Grosso rapidly expanded in total area of mechanized production and in total value of production in the last decade. This article shows the spatial pattern of that expansion from 2000 to 2010, based on novel analyses of satellite imagery. It then explores quantitatively and qualitatively the antecedents and correlates of intensification, the expansion of the area under two crops per year. Double cropping is most likely in areas with access to transportation networks, previous profitable agricultural production, and strong existing ties to national and international commodity markets. The article concludes with an exploration of the relationship between double cropping and socioeconomic development, showing that double cropping is strongly correlated with incomes of all residents of a community and with investments in education. We conclude that double cropping in Mato Grosso is very closely tied to multiple indicators of socioeconomic development.

The phosphorus cost of agricultural intensification in the tropics

Agricultural intensification in the tropics is one way to meet rising global food demand in coming decades1,2. Although this strategy can potentially spare land from conversion to agriculture3, it relies on large material inputs. Here we quantify one such material cost, the phosphorus fertilizer required to intensify global crop production atop phosphorus-fixing soils and achieve yields similar to productive temperate agriculture. Phosphorus-fixing soils occur mainly in the tropics, and render added phosphorus less available to crops4,5. We estimate that intensification of the 8–12% of global croplands overlying phosphorus-fixing soils in 2005 would require 1–4 Tg P yr–1 to overcome phosphorus fixation, equivalent to 8–25% of global inorganic phosphorus fertilizer consumption that year. This imposed phosphorus ‘tax’ is in addition to phosphorus added to soils and subsequently harvested in crops, and doubles (2–7 Tg P yr–1) for scenarios of cropland extent in 20506. Our estimates are informed by local-, state- and national-scale investigations in Brazil, where, more than any other tropical country, low-yielding agriculture has been replaced by intensive production. In the 11 major Brazilian agricultural states, the surplus of added inorganic fertilizer phosphorus retained by soils post harvest is strongly correlated with the fraction of cropland overlying phosphorus-fixing soils (r2 = 0.84, p < 0.001). Our interviews with 49 farmers in the Brazilian state of Mato Grosso, which produces 8% of the worlds soybeans mostly on phosphorus-fixing soils, suggest this phosphorus surplus is required even after three decades of high phosphorus inputs. Our findings in Brazil highlight the need for better understanding of long-term soil phosphorus fixation elsewhere in the tropics. Strategies beyond liming, which is currently widespread in Brazil, are needed to reduce phosphorus retention by phosphorus-fixing soils to better manage the Earths finite phosphate rock supplies and move towards more sustainable agricultural production.

Soybean Development: The Impact of a Decade of Agricultural Change on Urban and Economic Growth in Mato Grosso, Brazil

In this research we consider the impact of export-driven, soybean agriculture in Mato Grosso on regional economic growth. Here we argue that the soybean sector has served as a motor to the state’s economy by increasing the demand for services, housing, and goods, and by providing a source of investment capital to the non-agricultural sector. Specifically, we show that each square kilometer of soybean production supports 2.5 formal sector jobs outside of agriculture, and the equivalent of approximately 150,000US in annual, non-agricultural GDP. We also show that annual gains in non-agricultural employment and GDP are closely tied to soybean profitability, and thus vary from year to year. However, while this article highlights the potential of the agricultural sector as a driver of regional economic growth, it also acknowledges that this growth has been sustained by profits determined by externally set prices and the rate of exchange, and that future growth trajectories will be susceptible to potential currency of market shocks. We also show that while Mato Grosso’s economic growth has come at a significant cost to the environment, value added by the agriculture sector, directly and indirectly, has surpassed the value of the CO2-e emitted through land clearings.

Precipitation Drivers of Cropping Frequency in the Brazilian Cerrado: Evidence and Implications for Decision-Making

AbstractThe Amazon basin has been subjected to unprecedented rates of land-use change over the past several decades, primarily as a result of the expansion of agriculture. Enhanced rain forest conservation efforts toward the end of the twentieth century slowed deforestation of the Amazon but, in turn, increased demand for land repurposing in the adjacent Cerrado (savanna) region, where conservation regulations are less strict. To maintain or increase yields while minimizing the need for additional land, agricultural producers adopted a form of intensification in which two rain-fed crops are planted within a single growing season (double cropping). Using 10 years (August 2002 to July 2012) of MODIS and TRMM data, it is demonstrated that there exists a threshold growing season rainfall amount (1759 mm) for double cropping. But more nuanced is the relationship between observable precipitation information available to farmers at the time of planting decision and the choice to “double crop” in a given year. An...

Evaluation of Agricultural Land Cover Representations on Regional Climate Model Simulations in the Brazilian Cerrado

Examining interactions between large-scale land cover and land use change and regional climate in areas undergoing dynamic land transformations, like the Brazilian Cerrado, is crucial for understanding tradeoffs between human needs and ecosystem services. Yet regional climate models often do not include accurate land cover data of these complex landscapes. We use National Center for Atmospheric Research’s Weather Research and Forecasting (WRF) model coupled to the NoahMultiparameterization (Noah-MP) land surface model to run 10-year climate simulations across Brazil to assess (1) whether an accurate, regionally validated land cover data set with two, new agricultural land cover classifications improves model simulation results; (2) the ability of Noah-MP’s dynamic vegetation option to model vegetation growth; and (3) the sensitivity of the model output to scale. The results of the simulations with the updated land surface perform better over intensive agricultural areas for precipitation, evapotranspiration, and temperature, especially during the wet-to-dry season transition months. Evapotranspiration is overestimated during the start of the rainy season across all model simulations, which is likely due to the soil moisture model. We also find that using the Noah-MP dynamic vegetation significantly degrades agricultural leaf area index phenology simulations in Brazilian agricultural regions. Lastly, improving the model’s resolution did not improve model output when compared to observational data. Incorporating more accurate representations of the landscape into regional climate models is essential for quantifying potential changes in climatological seasonality in dynamic, human-modified regions and making informed land use decisions. Plain Language Summary Humans are the largest drive of landscape change globally. One region that exemplifies this change is Brazil’s Cerrado—over half of it has been cleared for agriculture. Farmers in the region depend on a stable rainy season to cultivate crops like soy and corn, but, clearing Cerrado for agriculture may disturb regional climate and affect precipitation. The first step to assessing these impacts is determining whether a more accurate land surface improves simulation results and where the model still needs to be improved. We use the Weather Research and Forecasting (WRF) model to run 10-year-long climate simulations across Brazil with both the default U.S. Geological Survey land cover map and an updated land cover map with two new agricultural categories. Our results show that using an updated map improves model results over regions of intensive agriculture, especially in the dry-to-wet-season transition months. All simulation results show an overestimation in evapotranspiration rates and a cold bias during the rainy season. These biases seem to be the result of WRF’s soil-moisture model. Understanding both these interactions and how we can use climate models to better study them is essential for making informed land use decisions.