Elsevier

Ecological Economics

Volume 62, Issue 1, 1 April 2007, Pages 102-114
Ecological Economics

ANALYSIS
Sustainable management of extensively managed savanna rangelands

https://doi.org/10.1016/j.ecolecon.2006.05.019Get rights and content

Abstract

Classic rangeland theory advocates stocking rangelands at relatively low and constant levels. This theory has been labelled inappropriate for savanna rangelands, because savannas are strongly influenced by stochastic processes. Opportunistic strategies that force animal numbers to track available forage have been proposed as an alternative management paradigm. However, no studies have examined whether these opportunistic strategies are sustainable or optimal. We developed a simulation model of a savanna rangeland to identify optimal, sustainable strategies for the management of extensive rangelands. We optimised the utility of agents who are motivated by economic, production or ecological factors under both deterministic and stochastic conditions. In all cases we found that it was optimal to manage the system conservatively and not opportunistically. Moreover, it was optimal to manage more conservatively under stochastic conditions. Key elements of the conservative strategy were to stock at low levels and to use fire to control tree abundance and thereby maintain the system in a grass dominated state. We conclude that opportunistic strategies of range management although intuitively appealing are not optimal.

Introduction

Savannas are defined as tropical ecosystems where grasses and trees co-dominate (Huntley and Walker, 1982). They cover large proportions of the tropical continents, that is 65% of Africa, 60% of Australia and 40% of South America (Huntley and Walker, 1982). The large area covered by savannas means that their sustainable management is of regional and global concern. One of the main land-use activities practised in savannas is livestock production, yet consensus on what might constitute sustainable livestock production systems remains elusive (Vetter, 2005).

Defining sustainable land-use systems requires careful consideration of what one means by sustainability. Following the Brundtland Report (WECD, 1987), sustainable development aims to guarantee inter- and intragenerational fairness concerning the use of natural resources. Hence a thorough evaluation of sustainable development requires the consideration of economic, ecological and ethical factors in an integrated framework. Economic sustainability typically means that resources should be managed in such a way that the utility does not decline over time (Perman et al., 2003). Ecological sustainability may mean preserving ecological resilience over time or ensuring that the flow of some ecological service does not decline over time (Daily, 1997). For instance, in a grazing system maintaining ecological resilience might involve preserving the soil layer or preventing the system from moving into a tree dominated state; while sustaining ecological services may involve maintaining large trees that act as keystone species. The interpretation of sustainability also varies among actors, because different actors have different risk aversions, discount rates and constraints. For instance, a farmer might maximise utility by maximising profit while discounting future earnings strongly; whereas a section of society might maximise utility by maximising the stability of production.

The focus of this study is the sustainable management of extensive rangeland systems in savanna regions. That is, we consider systems in which supplementary feeding of livestock is not economically viable and where grass and livestock production are primarily limited by rainfall. Rainfall in savanna regions varies with season; most rain falls in the summer months, very little rain falls in the winter months. Rainfall also varies stochastically between years. As a consequence, livestock farmers in savanna regions must develop strategies for dealing with variability and uncertainty in resource supply. Theory based on the harvesting of a stock that has density dependent and deterministic growth has strongly influenced the management of savanna rangelands (Mentis, 1984). However, more recent studies (Ellis and Swift, 1988, Behnke and Scoones, 1993) have argued that the stochastic nature of rainfall, which is the primary driver of resource supply in savannas, make such theories inappropriate for savannas.

This tension between “classic” and “new” rangeland theories (Cowling, 2000) has often been cast as a conflict between equilibrium and non-equilibrium paradigms, or between stochastic and deterministic paradigms. However, such polarisation is counter productive, because in any dynamical system both non-equilibrium or transient dynamics and equilibrium dynamics are important. Similarly, many dynamical systems are influenced by a mixture of both stochastic and deterministic processes. In savannas, the equilibrium–non-equilibrium dichotomy is particularly inappropriate because even when a savanna is not at equilibrium, its trajectory in state space is determined by the system's equilibrium points. The stochastic–deterministic dichotomy is also inappropriate in savannas because while the stochastic effects are apparent (e.g. rainfall on grass production), deterministic linkages are equally undeniable (e.g. grass consumption on animal production).

The broad aim of this study is to propose a model of savanna rangelands that combines a mix of the deterministic and stochastic, equilibrium and non-equilibrium processes that form the keystones of the “classic” and “new” rangeland paradigms. We use this model to explore guidelines for the sustainable management of livestock production systems in savannas. Our intent is to explore the extent to which different aspects of sustainability are compatible with one another. Specifically, we aim to define strategies that optimise the sustainability from the perspective of agents that are motivated by economic, ecological and production factors under deterministic and stochastic environmental conditions.

Section snippets

Ecological sub-model

We create a discrete time model, inspired by the models of Perrings and Walker (1997) and Janssen et al. (2004). The most important difference between our model and previous models is that we model, for both grasses and trees, two biomass compartments, roots and shoots. This allows us to simulate the fact that herbivores and fire cannot consume roots, and allows a separation of below ground and above ground competition (Fig. 1). The model of Perrings and Walker (1997) does not separate above

Utility

Given the different definitions of sustainability outlined in the introduction the agent may either aim to increase income, increase production or increase the value of some ecological indicator. A farmer may be interested in the economic definition, the state may be interested in the production definition and the ecological definition. In the paragraphs that follow we propose functions for the utility of these different agents.

The economic utility is determined by income and costs, which are a

Optimisation

The model is non-linear, stochastic and has multiple domains of attraction; these attributes make it poorly suited to classic optimisation methods (e.g. optimal control or dynamic programming). As an alternative, we use a simulation–optimisation approach, that is we combine our process orientated simulation model with a numerical optimisation algorithm. Simulation–optimisation methods have been successfully used to optimise hydrological (Aly and Peralta, 1999, Koutsoyiannis and Economou, 2003),

Model behaviour

The system has three attractors that are of ecological interest, grass dominated, tree dominated and savanna (mixed tree–grass) states. Scheiter and Higgins (submitted) provide a more formal discussion of the mathematical conditions necessary for the savanna state. These analyses show that the savanna state is possible when either fire is present or when grass–tree competitive interactions are weak. The weight of empirical evidence for savannas, however, supports the notion that competition

Discussion

The new rangeland ecology criticises classic rangeland ecology's recommendation of constant stocking on the basis that this represents a lost opportunity to rangeland farmers, preventing them from taking advantage of bumper grass production years (Behnke and Scoones, 1993). One alternative to constant stocking is to attempt to force animal numbers to track variation in grass production. Although intuitively appealing, the feasibility of the tracking strategies suggested by the new rangeland

Conclusions

In this paper we analyse a dynamic model that enables us to analyse a rangeland system under stochastic conditions. The model illustrates how both deterministic and stochastic processes influence rangeland dynamics. The results of our model analysis are that under stochastic conditions livestock farmers should be more conservative than under deterministic conditions. This result is perhaps surprising for those (e.g. Ellis and Swift, 1988, Westoby et al., 1989, Behnke and Scoones, 1993, Sullivan

Acknowledgements

We thank the Robert Bosch Foundation for financial support and the reviewers for valuable comments.

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