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RICHARDS, SHANE A.; HUGH POSSINGHAM,; JAMES TIZARD,. "OPTIMAL FIRE MANAGEMENT FOR MAINTAINING COMMUNITY DIVERSITY." Ecological Applications. Ecological Society of America. 1999. HighBeam Research. 26 Apr. 2018 <https://www.highbeam.com>.
RICHARDS, SHANE A.; HUGH POSSINGHAM,; JAMES TIZARD,. "OPTIMAL FIRE MANAGEMENT FOR MAINTAINING COMMUNITY DIVERSITY." Ecological Applications. 1999. HighBeam Research. (April 26, 2018). https://www.highbeam.com/doc/1G1-60949634.html
RICHARDS, SHANE A.; HUGH POSSINGHAM,; JAMES TIZARD,. "OPTIMAL FIRE MANAGEMENT FOR MAINTAINING COMMUNITY DIVERSITY." Ecological Applications. Ecological Society of America. 1999. Retrieved April 26, 2018 from HighBeam Research: https://www.highbeam.com/doc/1G1-60949634.html
Abstract. Disturbance events strongly influence the dynamics of plant and animal populations within nature reserves. Although many models predict the patterns of succession following a disturbance event, it is often unclear how these models can be used to help make management decisions about disturbances. In this paper we consider the problem of managing fire in Ngarkat Conservation Park (CP), South Australia, Australia. We present a mathematical model of community succession following a fire disturbance event. Ngarkat CP is a key habitat for several nationally rare and threatened species of birds, and because these species prefer different successional communities, we assume that the primary management objective is to maintain community diversity within the park. More specifically, the aim of management is to keep at least a certain fraction of the park, (e.g., 20%), in each of three successional stages. We assume that each year a manager may do one of the following: let wildfires burn unhindered, fight wildfires, or perform controlled burns. We apply stochastic dynamic programming to identify which of these three strategies is optimal, i.e., the one most likely to promote community diversity. Model results indicate that the optimal management strategy depends on the current state of the park, the cost associated with each strategy, and the time frame over which the manager has set his/her goal.
Key words: Australia; biodiversity conservation; community succession; decision theory; disturbance events, stochastic; fire; management model; managing wildfire to promote biodiversity; Markov model; modeling disturbance events; stochastic dynamic programming; succession.
INTRODUCTION
The spatial and temporal dynamics of communities are often strongly influenced by one or more types of disturbance event (Sousa 1984, Pickett and White 1985). A disturbance is an event that may, directly or indirectly, disrupt a community and change resource availability (Pickett and White 1985). The event may be abiotic (e.g., fire, frost, flood, severe wave action) or biological (e.g., predation, disease). The pattern of succession following a disturbance is dependent on the disturbance regime. Common descriptors of a disturbance regime include the characteristic size, shape, intensity, season, and frequency of the disturbance (Gill 1981, Sousa 1984, Pickett and White 1985). The pattern of succession is also dependent on other factors, such as the state of the community before the disturbance event, the life-history properties of species at or near the site prior to disturbance, and post-disturbance environmental conditions. Disturbances that occur frequently may favor early-successional species while an absence of disturbance may favor late-successional species. Also, disturbances of larger areal extent may favor early-successional over late-successional species (Miller 1982).
For any area there will be a disturbance regime that minimizes biodiversity losses. Managers of nature reserves have some degree of control or influence over disturbances (e.g., managers may suppress fires or initiate prescribed burns); hence, it is important that management decisions that influence disturbances are well planned (Frankel et al. 1995) and their potential impacts on the population dynamics of threatened species are identified.
If managers of nature reserves are to make effective and efficient management decisions then there must be well-defined management objectives. These objectives may be either short or long term. One objective may be to provide conditions that maximize the chance of long-term persistence of rare or locally threatened species (Good 1981). When different species prefer different successional communities we need to ensure that at any time the reserve is community diverse, i.e., it contains a mosaic of successional states each of sufficient area to support the successional-specific species. Often a manager must choose among a variety of management strategies, each associated with different costs and resource requirements, and each having a different short- and long-term likelihood of success. Ecological theories may identify which strategies may be useful at achieving an objective, but a manager is still faced with the problem of deciding which is the best strategy, given the constraints of time and money. To assist managers we need to merge ecological theory into a decision-making framework so that managers can make the best strategic decision, given the latest knowledge on the state of the system of interest (Maguire et al. 1987, Possingham and Tuck 1996, Possingham 1997). It is important to note that a single strategy may not always be the best for achieving a management objective; the best strategy may change as the state of the system changes.
In this paper we show how a mathematical model of succession and disturbance can be incorporated into a decision-making framework. To achieve this, the management objective must be explicitly defined and expressed in the context of the model. It is also important to define a list of management strategies available to the manager, along with their effects on the disturbance regime and their relative costs. To illustrate the approach, we consider the problem of managing fire within Ngarkat Conservation Park (CP), South Australia, Australia.
Ngarkat CP is an example of a nature reserve where the fire regime plays an important role in governing community diversity (Specht et al. 1958, Symon 1982, Forward 1996). The park is located 200 km southeast of Adelaide, South Australia, and covers ~270 x [10.sup.3] ha. At the broad level, two vegetation associations dominate the park: eucalypt open scrub (mallee), and open heath of sclerophyllous shrubs. The Department of Environment and Natural Resources and the Department of Housing and Urban Development have documented the fire history of Ngarkat CP since the 1940s. Almost every part of the park has been burnt by wildfire in the last 55 yr and some areas have been burnt 5 times during this period (Forward 1996). Many of the wildfires were [is less than] 20 ha in size but a few were estimated to be [is greater than] 50 x [10.sup.3] ha (20% of the park). The result of these fires has been a continually changing mosaic of vegetation successional states within the park.
In this paper we investigate the problem of deciding when wildfires within Ngarkat CP should be fought and when prescribed burns should be implemented, given that the management objective is to promote community diversity within the park. We assume that habitat can be classified as being in one of three successional states, which we call "early, middle, and late successional." Maintaining a range of successional states in the park is important because Ngarkat CP contains key habitat for several nationally rare and threatened bird species (Garnett 1993). Four species of particular conservation concern are the Slender-billed Thornbill (Acanthiza iredalei hedleyi), the Mallee Emu-Wren (Stipiturus mallee), the Red-lored Whistler (Pachycephala rufogularis), and the Malleefowl (Leipoa ocellata). The Slender-billed Thornbill and Mallee Emu-Wren appear to favor vegetation that is recovering from fire; however as the vegetation becomes taller and denser (10-30 yr after fire) their abundance decreases, whereas the abundance of Red-lored Whistlers generally increases (Garnett 1993, Woinarski and Recher 1997). The Malleefowl prefers older vegetation ([is greater than] 30 yr), where mallees are tall and the understory is relatively open (Garnett 1993); hence, any management decision about fire should consider the successional preferences of all four species.
"Wildfires," defined as "fires that are not prescribed," may be modeled as a stochastic event. Often, a reserve manager cannot predict with high certainty when or where wildfires will occur, or their subsequent size. However, managers can reduce the chance of wildfires (e.g., placing fire bans), and managers can suppress the spread of wildfires by creating firebreaks and active fire fighting. Fire is an effective management tool to manipulate vegetation (Gill 1977). Low-intensity prescribed burning is often used to reduce fuel buildup in an attempt to reduce the intensity and size of subsequent wildfires. Such burning is controversial (Gill 1977, Good 1.981) because it can dramatically alter the community structure of a reserve (Frankel et al. 1995). The purpose of this paper is to show how a mathematical model can be used to help managers determine if the current fire regime is sufficient for promoting community diversity within a reserve, and, if it is not, what management strategies will alter the fire regime so that community diversity is most likely to be achieved. …
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