DOI: 10.3886/e106761v1
title: Intensive beef farming in the Brazilian Amazon

description: *** The files here are part of the Supplementary Information to the article authored by:<br>Petterson Vale, Holly Gibbs, Ricardo Vale, Matthew Christie, Eduardo Florence,Jacob Munger, Derquiane Sabaini<br><br>To assess the impact of confinement
operations on the productivity of livestock, we first created a baseline
estimate of the full life cycle of the cows, from birth to death, based on the
parameters in "Database S1. Productivity simulations.xlsx". The scenario where cows are finished in a
confinement was then compared to the baseline to assess productivity gains
(using the net beef production, kg/ha/day). Our simulations reflect the typical
situations in the Brazilian Amazon: we included specific zootechnical
parameters for male as well as female bovids; and for the breeding, stocking,
and fattening phases (cows have markedly different needs at each stage). All
simulations were based on a standard plot of one hectare and can be reproduced
in the simulation spreadsheet provided. Detailed equations are provided in the Supplementary Information to the paper.<br><br>Contents<br><br>Database S1.

The
file “Database S1. Productivity simulations.xlsx” contains all the parameters
and formulas for the productivity simulations. It contains two
sets of simulations, one for the full life cycle of beef cattle, from breeding
to stocking to fattening, and another set that simulates the fattening
production system in more detail. The parameters, simulations, and results are
provided in separate sheets. The outcomes of alternative parameters can be
simulated by inputting new parameters in the parameters sheet and visualizing
the outcomes in the results sheets.<br><br>Data scripts.

Scripts
are provided to implement simulations of fattening production systems using parameter
ranges. All scripts require Stata 15.<br>The
master script “simulation.do” contains all the code and information necessary
to simulate productivity rates of three types of fattening systems
(confinements, semi-confinements, and intensified pasture-based) based on
ranges of agronomic, managerial, and zootechnical parameters. The ranges are
provided in Database S1, sheet “1.Parameters”, “Fattening simulations”. To run
the simulations, follow these steps:
<br><br>1.
Store all files provided within a single folder<br>- the master
simulation.do file<br>- three auxiliary .do
files:<br>  .
simulation_commands.do<br>  . simulation_commands_inte_semi.do<br>  .
simulation_commands_past.do<br>- the Stata 15 file
simulations.dta<br><br>2.
Run the full code in the master script<br>3.
Check the file simulation_results.dta<br><br>The
parameters and variables in the simulations are described below.<br><br>Definition
of parameters:<br>* pastarea: grazing area (in the case of
confinements, confinement area)<br>* density: heads of cattle per hectare of
pastarea<br>* wgain: weight gain in kg/head/day<br>* silcons: consumption of corn silage in
kg/head/day<br>* corncons: consumption of corn in
kg/head/day<br>* soycons: consumption of soy in kg/head/day<br>* silprod: yield of corn silage per hectare
of cropping area<br>* cornprod: yield of corn per hectare of
cropping area<br>* soyprod: yield of soy per hectare of
cropping area<br>* cycle: desired weight gain in a production
cycle, in kg/cycle<br><br>Definition
of variables:<br>* silconsarea: comsumption of corn silage in
kg/ha/day<br>* cornconsarea: comsumption of corn in
kg/ha/day<br>* soyconsarea: comsumption of soy in
kg/ha/day<br>* meatgross: gross meat production in
kg/ha/day, disregarding the area used for cropping<br>* days: duration of cycle: total days for a
cow to gain the expected weight<br>*
croparea: area in hectares needed to produce the amount of corn silage, corn,
and soy necessary for a full grazing cycle<br>* tarea: area required by the production
system, including for the crops<br>* meat: net meat production in kg/ha/day,
accounting for the area used to produce the crops<br>
description: Response Rates: In
the baseline, 80% of the beef cows are finished in a traditional-, and 20% in
an intensified pasture-based system. These shares were derived as follows.
Using municipality stocking densities by Lapig (2017)
we found that, in 2015, 85% of the municipalities in the study area had a
stocking density lower than 1.71 AU/ha (our upper threshold for traditional
systems as explained below), while only 4.4% had a stocking density above 4.44
AU/ha (our lower threshold for intensified systems). Assuming that the
distribution of cattle densities across municipalities is a good proxy for the
within-municipality distribution we could conclude, conservatively, that 80% of
the properties used traditional pasture-based systems.<br><br>For
each system, we started by identifying a maximum carrying capacity. This was derived
from the fattening phase and assumed constant across the life cycle. For
example, in our traditional pasture-based system, two heads of cattle are
fattened in one hectare, one male and one female. The male weighs 445 kg and
the female 315 kg, so the carrying capacity is 1.71 Animal Units (1 AU=450 kg).
This maximum carrying capacity was used for the breeding, stocking and
fattening phases. However, the choice of 2 heads/ha for pasture-based fattening
is an intentional overestimate (see, for example, Barbosa et al., 2015, p. 61).
As a result, the carrying capacity and productivity gain of confinements were potentially
underestimated. Using the same procedures, intensified pasture-based systems were
found to support up to 4.44 AUs.<br><br>Having
calculated the carrying capacity, the stocking densities could be derived for
each phase using average weights. In the stocking phase, the carrying capacity
of pasture-based systems is converted to 3.7 heads of female animals (each
weighing 208 kg) or 2.8 heads of male animals (each weighing 273 kg). For the
breeding phase, one cow (0.9 AU) is added to each calf, so the density is 1.5
cow-calf pairs/ha. The cattle densities were obtained similarly for all systems
and phases.<br><br>Next,
we calculated the amount of feed and the corresponding agricultural area
required (Tables 2 and S2-S3 provide feed consumption parameters). The cropping
area was added to the one-hectare grazing area to obtain the total area. We
assumed that the cropping area was used only once to produce cattle feed for
the whole duration of the cycle, with no additional agricultural output. This
assumption is the most realistic for confinements as the cycle lasts about 100
days, so in one year there can be up to three agricultural production cycles.
The assumption is less realistic for a pasture-based fattening system that can
last 650 days, as it implies that a crop-producing area would yield a single
harvest in more than one year; this in turn causes the productivity estimate to
be somewhat underestimated for non-confinement fattening systems.<br><br>Finally,
to compare across systems and phases, we calculated the net beef production
(NBP) as follows (units of measurement within brackets):<br><br>(1) NPB (kg/ha/day)= stocking density (heads/ha) * daily weight gain (kg/ha/day) * W,
<br><br>where
the denominator of the stocking density is the total area (grazing + feed
production), TP is traditional pasture, and W is a weight calculated as:<br><br>(2) W = weight gain per cycle TP / weight gain per cycle<br><br>The
aim of W is to allow for the NBP
estimates to be comparable across systems that yield different weight gains.
For example, male calves gain 150 kg in traditional pasture breeding and 165 kg
in intensified pasture breeding, so the NPB of the latter is multiplied by
.909. This avoids the NBP of a given system being inflated (deflated) when
compared to other systems.<br><br>In
a second step, we restricted the analysis to systems in the fattening phase.
Confinements were compared with traditional pasture, intensive pasture, and
semi-confinements. Here the parameters were not deterministic but value ranges,
producing a richer set of scenarios. The simulations for
males and females were replaced for a single simulation where the average
parameters between males and females were employed, except for confinements
where the average was weighted according to the average share of males in
confinements (87.7%). The other procedures were the same as in step one.<br>