With growing concern about the climate change, potential sources of Greenhouse Gas (GHG) emissions mitigation are being identified. Lately, the livestock sector has received considerable attention in this regard as the sector reportedly contributes significantly to human-induced GHG emissions [1] - [3] .

The global demand for livestock products has grown over the years and is likely continue that growth in the future [4] . Increasing overall livestock output has implications for the environment. The sources of GHG emissions from the livestock sector can be segregated into two broad categories: 1) emissions that emanate from land use changes due to livestock production; typically when forest land is converted into pasture or cropland to accommodate increased livestock production, it results in increased GHG emissions due to land clearing and reduced long term carbon sequestration; 2) emissions which are attributed to non-land use change sources such as enteric fermentation, feed production and processing, manure handling, and processing and transportation of animal products.

Unlike the emissions estimates for non-land use sources, which have been well documented in the literature [1] [2] , the emissions induced by land use changes due to livestock production have not been adequately addressed and are a contentious issue [5] . While [3] and [6] estimate about 2.4 to 2.6 billion tons carbon dioxide equivalent (CO₂ e) emissions per year as a result of land use change due to livestock production, these reports, however, do not provide a detailed explanation of the methods used to obtain these estimates. A FAO report authored by [2] estimates approximately 7.1 billion tons of CO₂ e emissions annually from the livestock sector and attribute about 0.65 billion tons CO₂ e per year (about 9.2% of the total emissions from the sector) to the land use changes. However, this estimate fails to account fully the emissions from land use change associated with livestock production at the global level as it mainly accounts for land use changes in Latin America due to soybean production in Brazil and Argentina and pasture expansion in Brazil, Chile, Nicaragua, and Paraguay. Given that the report does not account for land use changes in all regions of the world and all crops, it is likely that it underestimates the emissions from land use change caused by livestock production at the global level. Moreover, [2] ’s emission estimates are based on the reference years 1996-2006, which need updating to account for the livestock production after 2006. A more recent estimate of GHG emissions from livestock sector by [1] does not include the emissions from land use changes. Given this gap in the literature, this work focuses on estimating GHG emissions induced by land use changes due to projected increase in livestock production between 2004 and 2022.

The objectives of this paper are threefold: 1) provide a baseline projection for regional livestock output growth between 2004 and 2022 at the global scale; 2) use the baseline projection estimates of livestock output to estimate the expected global land use changes by regions; and 3) estimate the GHG emissions associated with those changes. Considering the global scale of this work and the number of interactions among many economic sectors and regions, a Computable General Equilibrium (CGE) modeling framework is used.

A modified version of the standard GTAP (Global Trade Analysis Project) model, GTAP-BIO, is used for this analysis. The GTAP model is a multi-sector, multi-region CGE model, which is widely used for policy, trade, and environmental analysis. GTAP models consumer (private households) preference using a Constant Difference of Elasticity (CDE) function, which allows income elasticities to differ across goods. Producer/firm production functions are modeled using nested Constant Elasticity of Substitution (CES) forms. Moreover, it assumes constant returns to scale in production and perfectly competitive markets. The Armington assumption is used for traded goods i.e. the imports are differentiated by country of origin. The general equilibrium nature of the model is imposed by applying Walras Law in the model, i.e. in equilibrium all markets clear (i.e. aggregate demand equals aggregate supply in all input and output markets, imports equal exports in the international market), all firms earn zero economic profits, and all consumers operate on their budget constraints, and global investments equal global savings. The standard GTAP model is fully described and discussed with underlying assumptions and equations in the book “Global Trade Analysis” [7] , the discussion in this section is focused on the features of GTAP-BIO model that are pertinent to the objectives of this study.

The GTAP-BIO was originally developed and used to estimate the impact of increased biofuels production on global land use and associated GHG emissions [8] [9] . The GTAP-BIO explicitly models the competition among crops, livestock, and the biofuels sector in the land market. Besides modeling the land use, the model explicitly incorporates feed demand for livestock. The livestock feed demand includes not only conventional feed sources but also distillers’ grains, a by-product of corn ethanol production, primarily used as a livestock feed ingredient (for details see [10] ). Given that the GTAP-BIO model explicitly models land supply and the livestock feed demand in addition to retaining the general equilibrium features of the standard GTAP model, the model is very appropriate to estimate the growth of livestock demand and associated land use changes.

Figure 1 illustrates the land supply module in the GTAP-BIO model. This module determines the supply of land for forest, crop, and pasture production purposes in 18 Agro-Ecological Zones (AEZs) around the world. The elasticity of transformation, ETL1 determines the transformation of land for forest, crops and pasture, while ETL2 governs allocation of crop land among different crops. ETL3 is the elasticity of transformation of pasture land for meat and milk production. These elasticities are tuned according to the changes in land cover and harvested areas at the global scale [11] .

To examine the impact of increased livestock output on global land use and resulting GHG emissions, two experiments are developed and applied using the GTAP-BIO model and GTAP database version 7, which corresponds to the reference year 2004.

1) Experiment 1: This experiment is carried out by using the forecasted changes (Figure 2) in GDP, population, capital, skilled labor, and unskilled labor between the years 2004 (baseline) and 2022 as exogenous shocks to the GTAP-BIO model for all GTAP regions (Table 1). The land use changes obtained from this experiment can be attributed to changes in demand for all goods and services in the regional economies including changes in livestock production.

2) Experiment 2: Experiment 1 is repeated, while the household and intermediate demands for livestock products held constant¹. The difference in land use between this experiment and the first experiment can be attributed to the effect of the livestock demand on land use.

Two additional steps are followed. First, the resulting land use changes are introduced into the emissions factors developed by Plevin et al. [12] to calculate induced land use emissions due to changes in livestock outputs

for the time period of 2004-2022. These authors have developed a comprehensive model, “the AEZ_EF v47”, specifically designed to estimate GHG emissions associated with land use changes. The model considers various sources and sinks of GHG emission such as the above and below-ground live biomass, dead organic matter, soil organic matter, harvested wood products, non-CO₂ emissions (e.g. methane and nitrous oxide), and foregone sequestration in estimating the induced land use emissions. Moreover, the model is designed to fit well with the GTAP-BIO model such that the regions and AEZs in the AEZ_EF v47 model exactly match with the 19 regions and 18 AEZs in the GTAP model. This facilitates direct use of the land use change results from the GTAP model simulations into the AEZ_EF v47 model. Second, a series of simulations with changes in the substitution parameter of the GTAP-BIO model are tested to examine the sensitivity of the results.

The projected data for GDP, population, and capital (Figure 2) mainly come from the Centre d’Études Prospectives et d’Informations Internationales (CEPII) baseline database version 2.1 [13] . The projected changes in skilled and unskilled labor between the years 2004 to 2022 (Figure 2) are from the baseline projection database prepared by [14] for the GTAP model. Both the CEPII and [14] information are presented originally as a country level data and therefore are aggregated into the 19 GTAP regions. The percentage change in each of the five variables between 2004 and 2022 is calculated and then used as a shock to these variables in the model thereby simulating projected growth in livestock output and associated land use change.

Based on regional projections of GDP, population, capital, and skilled and unskilled labor, demand for livestock outputs are forecasted for the period between the years 2004 to 2022. Globally, the demand for non-ruminant output increases the most. Regionally, this expansion is the most evident in fast-growing economies such as CHIHKG and INDIA.

Changes in land use as a result of the growth in livestock output are estimated to be large with a loss of forest amounting to over 43.3 million hectares, a reduction in crop land of about 1 million hectares, and an increase in pasture of over 44 million hectares. Given that the forests sequester more carbon than other land uses, clearing them results in significant GHG emissions. The change in land use due to increased livestock production increases emissions by about 20 billion tons of CO₂ e between 2004 and 2022 or about an average of 1.1 billion tons annually, which is about 15.5% of the total emissions (7.1 billion tons of CO₂ e) from livestock sector as estimated by [2] and about 2.2% of the total human-induced GHG emissions (49 billion tons of CO₂ e) as estimated by the Intergovernmental Panel on Climate Change for the year 2004 [15] . When consumer’s responses to price changes are made more elastic i.e. more sensitive to price changes and willing to substitute more readily among livestock products, there is more increase in demand for livestock output especially the non-ruminant products with significant reduction in deforestation and GHG emissions.

The results from this study indicate that there is a potential for significant reduction in GHG emissions from livestock sector through policy interventions that target the consumption pattern of the private households. For this purpose, the intervention should encourage increased substitution among livestock products. In particular, the policies should encourage consumers to substitute non-ruminant for ruminant meat products.

The authors are grateful for the financial support from the University of Nebraska-Lincoln and Fort Hays State University.

Sunil P. Dhoubhadel,Farzad Taheripour,Matthew C. Stockton, (2016) Livestock Demand, Global Land Use Changes, and Induced Greenhouse Gas Emissions. Journal of Environmental Protection,07,985-995. doi: 10.4236/jep.2016.77087