AnalysisPolicies for the management of weeds in natural ecosystems: the case of scotch broom (Cytisus scoparius, L.) in an Australian national park
Introduction
Over the past few years there has been a growing awareness of the ecological implications of invasions by introduced organisms; they pose a threat to native biodiversity (Panetta et al., 2000) and cause unacceptable damage in both ecological and economic terms (Shogren, 2000). There are many studies on the ecology of alien invasive plants in natural ecosystems. Higgins and Richardson (1996) reviewed models of alien plant-spread. The assumptions, predictive potential, knowledge and data requirements of various modelling tools were discussed in the context of selecting the most appropriate plant-spread model for a given case. Examples of applications include Higgins et al. (1996), who modelled invasive plant-spread, to determine the effects of plant and environmental attributes on predicted rates and patterns of spread of alien pine trees in South African fynbos (a mediterranean-type shrubland); Le Maitre et al. (1996) modelled the consequences of a lack of management of invasive plants and water resources in the Western Cape Province, South Africa; Higgins and Richardson (1998) studied Pine invasions in the Southern Hemisphere, with emphasis on interactions between organism, environment and disturbance; and Parker (2000) used a matrix model approach to describe the demographic patterns on the invasion dynamics of Scotch broom in North America.
The importance of biological invasions is evidenced by the formation of the Global Invasive Species Program (GISP), which coordinates research around the world. The GISP mission is to conserve biodiversity and sustain human livelihoods by minimising the spread and impact of invasive alien species. GISP operates through a partnership network comprising scientific and technical experts working on issues of invasive species around the world1.
The economics of management strategies for Scotch Broom (Cytisus scoparius, L.), hereafter referred to as broom, is the focus of this paper. The ecology of broom is well understood in both its native (Memmott et al., 1993, Paynter et al., 1998, Paynter et al., 2000) and introduced ranges (Williams, 1981, Smith and Harlen, 1991, Smith, 1994, Downey and Smith, 2000, Parker, 2000, Sheppard et al., 2000); but the ecology and management are yet to be analysed together.
Several studies have used a similar approach to this paper in determining the optimal management strategies for different research problems in natural ecosystems. For example, Doherty et al. (1999) linked a population simulation model to a dynamic programming model to determine the optimal choice a manager should make to minimise revenue foregone by not harvesting timber while maintaining a given population of birds. Higgins et al. (1997) used a dynamic ecological economic model to value the services that the fynbos ecosystem provides under different management regimes. Other contributions to this kind of approach include White and Wadsworth, 1994, Bulte and van Kooten, 1999. This paper follows a similar approach but it is further extended to include a combination of decision variables and a budget constraint.
The aim of this paper is to answer some of the policy questions of relevance to the management of environmental weeds in general and the broom problem in Barrington Tops National Park in particular. In addressing this problem, the paper starts with a description of the problem and the study area, followed by a review of policy issues surrounding the management of broom in natural ecosystems. A dynamic optimisation model for broom management, which combines population dynamics and dynamic programming, is then developed. Results for the model in the absence of a budget constraint are then presented, followed by optimisation results subject to a budget constraint. The paper ends with a discussion of the implications of the results for the management of weeds in natural ecosystems.
Section snippets
Scotch broom and the Barrington Tops National Park
Broom is an exotic leguminous shrub, native to Europe, which invades pastoral and woodland ecosystems and adjoining river systems in cool, high rainfall regions of southeastern Australia (Hosking et al., 1998, Sheppard and Hosking, 2000). Broom has invaded 10,000 hectares of eucalypt woodland at Barrington Tops National Park in New South Wales (Waterhouse, 1988). The Park is approximately 100 km north west of Newcastle, which is the major city in the industrialised Hunter Region of New South
Policy issues surrounding the management of broom in natural ecosystems
The NSW National Parks and Wildlife Service is responsible for managing Barrington Tops National Park. The main functions of the Service include the protection and preservation of the scenic and natural features, the conservation of wildlife, the maintenance of natural processes as far as possible, the conservation of cultural resources and the provision of appropriate recreational opportunities. The Service is also charged with encouraging scientific and educational enquires into environmental
A dynamic model for broom management
Following current land-use patterns on Barrington Tops, it is assumed that a tract of land of 80,000 ha is presently used for biodiversity protection, recreation and livestock production (Odom et al., 2001). We have omitted watershed protection as one of the uses because no data on the quantity and quality of flow are available. From the aspect of broom management the land can be defined in terms of four state variables: the fraction of sites occupied by broom; the fraction of sites that are
Economic optimisation
The objective of the analysis is to choose the sequence of control strategies (ut) that maximises the present value of a stream of annual net benefits, given an initial state (w0, s0). The optimisation problem for a planning horizon of T years is:
Subject to:where δ is the discount factor (1+r)−1 for the given discount rate r. The recursive Eq. (7) shows that current net benefits (Bt) are affected by both weed
The optimal state transition
Since the problem is autonomous (the state transition equation does not depend on the time period), it is possible to solve the DP model until it converges and obtain an optimal decision rule, ut*(wt, st). The optimal decision rule provides a ‘package’ of control measures that can be used to tackle the problem each year depending on the current weed density and seed bank (wt, st).
Application of the optimal decision rule results in an optimal state transition—the relationship between the state
Discussion
The framework for broom management described here integrates a model of the dynamics of the plant's population growth and an economic model to choose management measures to optimise net benefits. The results depend on the way these two models represent reality, and the values of the parameters used in them.
In this paper, we have not presented a sensitivity analysis on model parameters, but Rees and Paynter (1997) showed that, because of the large number of seed produced by broom, the system
Summary and conclusions
This paper has presented an application of a deterministic dynamic programming model for broom management in a natural ecosystem. The model has been able to answer four out of the five policy questions raised in Section 3 of this paper. The first question was not answered because our model is not spatially-explicit, this is discussed in more detail later.
Regarding question (2), we found that the value of a known budget for coming years is considerable; with a budget of $50,000, the marginal
Acknowledgements
This project was funded by the CRC for Australian Weed Management. We thank John Hosking, Jeremy Smith, Andrew Leys and Chris Howard for helpful discussions during the initial stages of this project; Andy Sheppard, Mellesa Schroder, Cathy Ball and Dionne Coburn for data and information for modelling; and Randall Jones and Tom Nordblom for ideas on integrating weed control measures. Thanks to all seminar participants at CSIRO. We acknowledge the assistance of Richard Groves and Andy Sheppard for
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