Spatial and temporal contrasts in the distribution of crops and pastures across Amazonia: A new agricultural land use data set from census data since 1950

Abstract

Amazonia holds the largest continuous area of tropical forests with intense land use change dynamics inducing water, carbon, and energy feedbacks with regional and global impacts. Much of our knowledge of land use change in Amazonia comes from studies of the Brazilian Amazon, which accounts for two thirds of the region. Amazonia outside of Brazil has received less attention because of the difficulty of acquiring consistent data across countries. We present here an agricultural statistics database of the entire Amazonia region, with a harmonized description of crops and pastures in geospatial format, based on administrative boundary data at the municipality level. The spatial coverage includes countries within Amazonia and spans censuses and surveys from 1950 to 2012. Harmonized crop and pasture types are explored by grouping annual and perennial cropping systems, C3 and C4 photosynthetic pathways, planted and natural pastures, and main crops. Our analysis examined the spatial pattern of ratios between classes of the groups and their correlation with the agricultural extent of crops and pastures within administrative units of the Amazon, by country, and census/survey dates. Significant correlations were found between all ratios and the fraction of agricultural lands of each administrative unit, with the exception of planted to natural pastures ratio and pasture lands extent. Brazil and Peru in most cases have significant correlations for all ratios analyzed even for specific census and survey dates. Results suggested improvements, and potential applications of the database for carbon, water, climate, and land use change studies are discussed. The database presented here provides an Amazon-wide improved data set on agricultural dynamics with expanded temporal and spatial coverage.Key Points Agricultural census database covers Amazon basin municipalities from 1950 to 2012Harmonized database groups crops and pastures by cropping system, C3/C4, and main cropsWe explored correlations between groups and the extent of agricultural lands

Re-evaluating the 1940s CO<sub>2</sub> plateau

“…Such differences are considerable and their impact is of similar magnitude as, for instance, stopping deforestation or wood harvest completely during 1940-1950, as estimated in idealized simulations using the OSCAR model. It is notable that the model estimates based on HYDE 3.1 (Hurtt et al, 2011) show a stagnation of the previously rising land-use emission rates during the 1940s. The BLUE model shows that, globally, emissions from cropland and pasture expansion slow down during the 1940s, while CO 2 uptake in abandoned land increases steeply.…”

“…OSCAR embeds a bookkeeping module (Gitz and Ciais, 2003) capable of calculating its own CO 2 emissions from LUC, on the basis of land-cover change, wood harvest, and shifting cultivation area inputs. LUC information is aggregated in 10 different regions from the original dataset from Hurtt et al (2011).…”

“…A major uncertainty results from all model studies applying land-use reconstructions that are based on FAO data for agricultural areas, which are available only from 1961 onwards. While Houghton (2003) included additional historical sources for some regions, the HYDE 3.1 database (Klein Goldewijk et al, 2011) and thus the dataset by Hurtt et al (2011) rely on extrapolating these country-level statistics back in time using population dynamics. In HYDE 3.1, the cropland and pasture values per capita are allowed to change "slightly" prior to 1961 (Klein Goldewijk et al, 2011).…”

Sensitivity of land use change emission estimates to historical land use and land cover mapping

“…However, in the bookkeeping method, the total deforestation area could be the main reason for the uncertainty if regional PFT shares the same ecosystem carbon density in that region. Besides uncertainty in carbon density of forests affected by LULCC, if better historical regional forest area census could be combined with satellite observations [e.g., Imbach et al, 2015;Hansen et al, 2013;Kim et al, 2015], the BM3 or FM3 methods could be used to further reduce the uncertainty on E LUC in that region.…”

A Pathway to Carbon Neutral Agriculture in Denmark

“…Danish agricultural production does not import meat or milk from pastures, but pasture areas often are near lands in Latin America that produce soybeans (Imbach et al 2015). As soybeans expand, they often occupy pasture, which in turn expands into forested areas (Arima et al 2011;Barreto 2010).…”