Multi-scale scenarios of spatial-temporal dynamics in the European livestock sector
Research highlights
▶ The study is a novel modeling approach for simulating spatio-temporal dynamics of livestock. ▶ Drivers operating at different spatial scales are integrated. ▶ Results indicate for most of the old European Union member states decreasing livestock numbers. ▶ In the new EU member countries numbers of beef cattle and poultry are expected to grow. ▶ Livestock densities are expected to increase in absence of environmental legislations. ▶ Environmental pressure from livestock may also remain if environmental policies are in place. ▶ New areas of environmental pressure due to livestock will more likely occur without such policies.
Introduction
Over the past 20–30 years European livestock farming and the spatial distribution of livestock across Europe has been largely shaped by far-reaching reforms of the European Common Agricultural Policy (CAP), animal diseases, increasing environmental concerns and changed consumer awareness (Hasha, 2002, Hermansen, 2003, EC, 2004, EC, 2006). These issues are still very much influencing the livestock sector and are anticipated to remain drivers of change in the near future. The European livestock sector is expected to remain dynamic in the forthcoming years (EC, 2009). In 2003 EU ministers of agriculture adopted a fundamental reform which entailed the introduction of a system of decoupled payments per farm (Single Farm Payment (SFP)), meaning that subsidy payments were no longer linked to volume of production (EC, 2009). Moreover, a cross-compliance instrument was introduced to accompany this system making the payments conditional on all statutory management requirements (SMR) in the field of environmental, animal welfare and public health requirements as well as standards of good environmental and agricultural condition (GEAC). Especially regions that are characterized by high livestock densities are anticipated to show a decrease in livestock number within the coming years. Whether this decrease will also take place in the new member countries where the SFP system has also gradually been introduced as from 2008 is uncertain (Ciaian and Swinnen, 2006). Most of these countries have shown an enormous decline in livestock numbers after the communist system collapsed. It is still to be seen whether the recovery to the pre-1990s level of livestock numbers will be stronger than the influence of the introduced SFP system.
European livestock farming, namely high density farming is, however, not only shaped by agricultural policies but also by environmental legislations, such as the Nitrates Directive. The Nitrates Directive delineates Nitrate Vulnerable Zones (NVZs) aiming to reduce water pollution from nitrogen compounds, which are largely produced by livestock. NVZs are regions with a high risk for nitrogen leaching and the Nitrates Directive sets legally binding rules to reduce nitrogen losses from agriculture to the environment (EC, 1991).
Changes in the livestock systems are associated with changes in their spatial distribution. Livestock distribution is driven by several processes operating at multiple scales, such as changes in (global) markets and trade, regional changes in land suitability, production conditions and technology as well as local environmental constraints and both agricultural and environmental policies. Because of these interacting processes European livestock distribution is very heterogeneous, being characterized by regional concentrations which potentially conflict with environmental targets such as those set under the Nitrates and Water Framework Directives. The impact of different livestock types on the environment has been explored at several scales and especially its impact on the nitrogen cycle is judged as one of the most critical issues threatening the functioning of the earth system (Rockström et al., 2009). Steinfeld et al. (2006) provide an environmental impact assessment of livestock at the global scale. The authors discuss the environmental challenges of livestock farming, evaluate its environmental burden, and discuss potential policy options for alleviating these. At the European scale, Halberg et al. (2005) discuss a number of assessment tools for determining the environmental impact of various livestock types. Oenema et al. (2007) have studied nutrient losses from manure management for Europe and have concluded large differences between European Union (EU) member countries. However, the spatial resolution of the study is limited to regions (NUTS 2; Nomenclature of Territorial Units for Statistics (NUTS)1). At the regional to local scales several authors have studied a broad range of environmental concerns related to livestock farming in Europe (Hooda et al., 2000, Nielsen and Kristensen, 2005). In addition to these environmental impact assessments, numerous studies have also been published studying the impacts of policy scenarios on ammonia emissions, nitrogen leaching and runoff from animal production systems (Berntsen et al., 2003, Oenema, 2004, Gömann et al., 2005, van Groenigen et al., 2008). These studies are, however, either very data intensive restricting their applicability to single farms or relatively small regions, or they use a simplified aggregated approach permitting a European-wide application. But since many environmental impacts depend on the location, the accuracy of such aggregated assessments is low by definition.
To explore possible environmental impacts of livestock farming across Europe but also to be able to make ex-ante assessments of environmental policies, a robust understanding of spatial dimensions of livestock farming and their spatial dynamics is required. Current EU—wide livestock density data only provide information on livestock types and numbers at administrative level (e.g., NUTS 2). To deal with the limitations of such aggregated data the Food and Agricultural Organization of the United Nations (FAO) has downscaled livestock types to a 3 arc-minute resolution using empirical analysis (FAO, 2007). The spatial patterns obtained were, however, not validated. At the European scale, Elbersen et al. (2006) and Neumann et al. (2009) have disaggregated farm types and livestock types, respectively, from NUTS 2 level to high resolution raster data (1 km). Neumann et al. (2009) showed that such downscaling was successful for cattle and sheep but especially difficult for poultry. Such downscaling approaches are only valid for the current situation and do not allow for an assessment of future changes in spatial livestock pattern in response to policies and other conditions. Only a few attempts were made to simulate spatial changes in future livestock distribution. At the global scale, Bouwman et al. (2005) have modeled spatial dynamics of both pastoral and mixed livestock systems based on FAO projections till 2030. Spatial livestock distributions are strongly linked to the presence of grassland and feed requirements while socio-economic aspects are not taken into account. Biophysical land characteristics and feed requirements were also considered by Koch et al. (2008) to assess impact of grazing on land use dynamics in the Jordan River region. For China, Verburg and Keulen (1999) linked a land cover change model with a livestock module to investigate near-future changes on the livestock distributions. Dalgaard et al. (2002) have modeled agricultural activity for different Danish (livestock) farm types to explore consequences of the Agenda 2000 reform. These authors have applied the agricultural model ESMERALDA to simulate changes in agricultural activities, such as livestock farming, for estimating changes in manure-N. While the methodology clearly illustrates the impact of the CAP, other factors influencing the spatial distribution of livestock, such as environmental legislations, demand for livestock products and changes in biophysical conditions were beyond the scope of the study. The mentioned studies illustrate the limited number of efforts made to simulate spatial-temporal dynamics of livestock farming. Their strength lies on exploring some specific aspects of changes in livestock farming, however, interactive processes at the global, international and local scale are disregarded.
In this paper we present a novel multi-scale modeling approach for simulating spatial and temporal dynamics of livestock distribution. The aim of the study was to explore changes in the European livestock sector by integrating a broad range of processes related to livestock farming while accounting for drivers at different spatial scales. Both quantity and spatial distribution of six different livestock types (dairy cattle, beef cattle, sheep, goats, pigs, and poultry) was simulated over the 2000–2030 period for the entire extent of the EU for four contrasting scenarios. Objective of this study is to provide a method for exploring changes in spatial patterns of livestock farming for large areas. Such explorations can provide a basis for environmental impact assessments of livestock farming at broad spatial scales to complement local field-based studies.
Section snippets
Multi-scale land use modeling approach
Understanding land use and land cover change processes requires an integrated approach accounting for socio-economic and biophysical driving forces (Turner et al., 1995, Lambin et al., 2001). Many case studies were conducted to gain understanding of the complex interactions between human and natural systems (Lambin et al., 2003, Mottet et al., 2006, Overmars and Verburg, 2006). An integrated approach also requires integration of different spatial scales at which land use change drivers act. Its
Development of livestock numbers
Scenario-specific livestock numbers for 2010, 2020, and 2030 were calculated with LEITAP/IMAGE. Overall, all four scenarios state similar trends in livestock numbers with often remarkable differences between old and new EU member countries. In most of the EU-15 member countries2 almost all livestock decreases with a strong decline for ruminants and a smaller decline or even an increase for
Validity of methodology
The presented model chain illustrates how different modeling approaches can be consistently linked across spatial scales to simulate the future spatial-temporal dynamics in the European livestock sector. This modeling approach is complementary for field-based studies end experimental studies assessing the environmental impact of livestock such as degrazing, nitrogen leaching and greenhouse gas emissions. While those studies are often restricted to the farm or regional scale the modeling
Conclusions
Our study presents a novel multi-scale model chain to explore detailed spatial and temporal dynamics of livestock types. The approach requires the application of a range of complex models. More simple approaches would not have sufficed because the European livestock farming sector is very dynamic. This dynamic can primarily be traced back to recent changes in the European economy, politics, and consumer behavior. Elaboration of spatial and temporal changes in livestock distribution requests a
Acknowledgement
The authors acknowledge the EURURALIS and NITROEUROPE projects and the BSIK RvK IC2 project ‘Integrated analysis of emission reduction over regions, sectors, sources and greenhouse gases’ for funding this research. We’d like to thank our colleagues from Alterra and the Land Dynamics group at Wageningen University for their critical discussions and comments on this study. Special thanks go to Bas Eickhout and Annelies Balkema for processing the livestock numbers with IMAGE.
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