Increasing yield gap of Brazilian pasturelands and implications for intensification
Abstract
Brazil has 213 M cattle heads (AUs) and 152 M ha of pasturelands, most with very low yields (average stocking rate in 2013 was 1.39 AU/ha). We merged Landsat imagery with municipal level agricultural census data for the period 1974-2013, to produce 30 arc-second resolution (1 km x 1 km) yearly datasets of pasturelands and cattle stocking rate (see Dias et al poster in this same session). Our analysis of this dataset indicates that, in the period 1993-2013, the total pastureland area in the country has decreased at a rate of 1.4 M ha/yr, while average stocking rate is increasing at the rate of 0.025 AU/(ha.yr). Moreover, we calculated the stocking rate of the top 5% and top 10% hectares, and the yield gap, or the difference between these top rates and the average. The yield gap is the productivity difference between what is largely possible with current technology and climate (top 5% or top 10%) and the typical cattle raiser, represented by the average. Closing the yield gap is often considered as a standard form of increasing agricultural output in general. Our results indicate that, in the same period, the top 10% are increasing at the rate of 0.040 AU/(ha.yr), while the top 5% are increasing at the rate of 0.048 AU/(ha.yr), twice as high as the average. The yield gap is widening and the rate of separation is increasing in recent years. These data suggest that top yield cattle raisers in Brazil are investing in technology significantly more than the average. Regional analysis indicates that this is happening mainly in southern and northern Brazil, while in Central, Southeast and Northeast Brazil, high productivities are not increasing as fast. Since top yields are far from stabilizing, there is a very large potential for intensification, increasing cattle size and total cattle output in Brazil.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2015
- Bibcode:
- 2015AGUFMGC13E1202C
- Keywords:
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- 1622 Earth system modeling;
- GLOBAL CHANGE;
- 1630 Impacts of global change;
- GLOBAL CHANGE;
- 1632 Land cover change;
- GLOBAL CHANGE