The Brazilian Cerrado
motely-sensed data allows us to monitor natural and anthropogenic environmental changes across the globe. Check out these amazing timelapse series created using 30 m resolution Landsat satellite data.
The Brazilian Cerrado is a biodiversity hotspot comprised of dry forests, woodland savannas, and grasslands. It is also Brazil's agricultural heartland where the average farm is bigger than 200 ha (2 km2). Because the farms are so big, we can use moderate resolution data to map agricultural land cover. Working with colleagues at the Univeristy of Vermont and Woodwell Climate Institute, we use remote sensing data, specifically MODIS vegetation index data, to parse this dynamic landscape.
In the animation, the Brazilian states of Mato Grosso, Goias, Maranhao, Bahia, Piaui and Toncantins are highlighted. Large-scale single-cropped agriculture (planting one commercial crop during the wet season) is mapped in black, while double-cropped agriculture (planting two commercial crops during the wet season) is mapped in pink, sugarcropped fields are mapped in green, and irrigated agriculture is mapped in blue. Between 2001 and 2016, we see both an expansion of total agricultural area, and an intensification of that agriculture, as single-cropped land is converted to double-cropped land.
To download our annual crop-type data across a majority of the Brazil Cerrado, click here.
The Brazilian Cerrado is a biodiversity hotspot comprised of dry forests, woodland savannas, and grasslands. It is also Brazil's agricultural heartland where the average farm is bigger than 200 ha (2 km2). Because the farms are so big, we can use moderate resolution data to map agricultural land cover. Working with colleagues at the Univeristy of Vermont and Woodwell Climate Institute, we use remote sensing data, specifically MODIS vegetation index data, to parse this dynamic landscape.
In the animation, the Brazilian states of Mato Grosso, Goias, Maranhao, Bahia, Piaui and Toncantins are highlighted. Large-scale single-cropped agriculture (planting one commercial crop during the wet season) is mapped in black, while double-cropped agriculture (planting two commercial crops during the wet season) is mapped in pink, sugarcropped fields are mapped in green, and irrigated agriculture is mapped in blue. Between 2001 and 2016, we see both an expansion of total agricultural area, and an intensification of that agriculture, as single-cropped land is converted to double-cropped land.
To download our annual crop-type data across a majority of the Brazil Cerrado, click here.
SOCIO-ENVIRONMENTAL WORK
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During the first half of the 2000s, Mato Grosso was home to agricultural expansion and high deforestation rates. However, during the the latter half of the decade, deforestation rates decreased while intensification of agriculture – the planting of two crops, often a soy/corn rotation, during one growing season increased nearly 6-fold. Some attribute this coupled deforestation decrease-intensification increase to the 2006 soy moratorium, but I posit that it may also be related to land scarcity within Mato Grosso (image on the left shows agricultural areas in green, the most suitable land for agriculture in white, and the least suitable land in black). Click here to read more about this work.
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Between 2003 and 2013, Goias State (below) went from Brazil's seventh largest producer of sugarcane to its third. Now it is second only to the state of Sao Paulo. During this time, sugarcane areaexpanded over six-fold, to 847,000 ha in 2013. By integrating remote sensing, GIS, and spatial statistical analyses, we determined that pasture was seven times more likely to be converted to sugarcane than soy; capital, infrastructure and institutions constrain sugarcane production; and areas were soy is currently cultivated may be converted to sugarcane in the future given the planned expansion of transportation and sugarcane infrastructure. We conclude by suggesting sugarcane be cultivated on on degraded pastures and increasing pasture stocking rates to ensure continued protection of both natural vegetation and food production while supporting sugarcane expansion in the state. Click here to read more about this work.
OBSERVED EFFECTS OF LAND USE CHANGE ON THE WATER CYCLE
Vegetation plays an important role in modulating weather and climate. Trees are great at recycling water back into the atmosphere, where some of it gets rained back out onto the trees. But, if you cut down those trees, you have less water put back into the atmosphere (and later rained out over the region) and more leaving the system through runoff and streamflow.
Matopiba, comprised of pieces Maranhao (MA), Tocantins (TO), Piaui (PI) and Bahia (BA), is the Cerrado's newest - and potentially last - agricultural frontier. Between 2003 and 2013, agriculture expanded by over 1 million ha, and 75% was sourced in intact Cerrado vegetation. These land-use changes are changing the regional water balance, and may end up affecting precipitation throughout the Cerrado and Amazon biomes. Read more about this work here.
Matopiba, comprised of pieces Maranhao (MA), Tocantins (TO), Piaui (PI) and Bahia (BA), is the Cerrado's newest - and potentially last - agricultural frontier. Between 2003 and 2013, agriculture expanded by over 1 million ha, and 75% was sourced in intact Cerrado vegetation. These land-use changes are changing the regional water balance, and may end up affecting precipitation throughout the Cerrado and Amazon biomes. Read more about this work here.
REGIONAL CLIMATE MODELLING
Modelling Regional Climate across the Cerrado
We can use the satellite data to monitor and analyze changes in environmental factors, such as forest cover or evapotranspiration, but observations alone cannot be used to discern the physical mechanisms and causal relationships that result in environmental changes. Land-cover-climate feedbacks can be better investigated by integrating spatial datasets and analyses with models. I used NCAR's regional climate model, the Weather Research and Forecasting (WRF) model, to investigate the physical relationships between land-cover change and regional climate in the Cerrado, and determine how best to maximize agricultural production and minimize negative climatic environmental consequences, specifically, limiting deforestation and land-cover-change-induced modifications in precipitation and temperature.
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. I use WRF 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. Click here to read more about this work.
Land-Use Change, Climate, and Crop Yields
Building off our regional climate modelling work described below, we used the Weather Research and Forecasting model to run 15-year climate simulations across Brazil with with six land-cover scenarios: 1) before extensive land clearing; 2) observed in 2016; 3) Cerrado replaced with single-cropped (soy) agriculture; 4) Cerrado replaced with double-cropped (soy-maize) agriculture; 5) eastern Amazon replaced with single-cropped agriculture; and 6) eastern Amazon replaced with double-cropped agriculture. All land-clearing scenarios (2-6) contain significantly more growing season days with temperatures that exceed critical temperature thresholds for maize. Evaporative fraction significantly decreases across all land-clearing scenarios. Altered weather reduces maize yields between 6–8%, when compared to the before extensive land clearing scenario; however, soy yields were not significantly affected. Our finding provide evidence that land clearing has degraded weather in the Brazilian Cerrado, undermining one of the main reasons for land clearing: rainfed crop production. You can read more about that work here.
We can use the satellite data to monitor and analyze changes in environmental factors, such as forest cover or evapotranspiration, but observations alone cannot be used to discern the physical mechanisms and causal relationships that result in environmental changes. Land-cover-climate feedbacks can be better investigated by integrating spatial datasets and analyses with models. I used NCAR's regional climate model, the Weather Research and Forecasting (WRF) model, to investigate the physical relationships between land-cover change and regional climate in the Cerrado, and determine how best to maximize agricultural production and minimize negative climatic environmental consequences, specifically, limiting deforestation and land-cover-change-induced modifications in precipitation and temperature.
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. I use WRF 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. Click here to read more about this work.
Land-Use Change, Climate, and Crop Yields
Building off our regional climate modelling work described below, we used the Weather Research and Forecasting model to run 15-year climate simulations across Brazil with with six land-cover scenarios: 1) before extensive land clearing; 2) observed in 2016; 3) Cerrado replaced with single-cropped (soy) agriculture; 4) Cerrado replaced with double-cropped (soy-maize) agriculture; 5) eastern Amazon replaced with single-cropped agriculture; and 6) eastern Amazon replaced with double-cropped agriculture. All land-clearing scenarios (2-6) contain significantly more growing season days with temperatures that exceed critical temperature thresholds for maize. Evaporative fraction significantly decreases across all land-clearing scenarios. Altered weather reduces maize yields between 6–8%, when compared to the before extensive land clearing scenario; however, soy yields were not significantly affected. Our finding provide evidence that land clearing has degraded weather in the Brazilian Cerrado, undermining one of the main reasons for land clearing: rainfed crop production. You can read more about that work here.