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EXOTIC WOODY WEEDS Use of simulation models to predict future ...

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The model incorporates size-dependent intraspecific competition (Thomas and Weiner 1989) using a<br />

function adapted from (Aikman and Watkinson 1980). This mechanism incorporates the concepts <strong>of</strong><br />

the zone <strong>of</strong> influence (Mitchell 1969) and ecological field theory (Walker and Dowling 1991).<br />

The surface roots <strong>of</strong> trees in the uplands frequently extend well beyond the canopy perimeters (pers.<br />

obs.). Upland adult trees are widely spaced with respect <strong>to</strong> their canopies, though seedling and juvenile<br />

densities can be quite high. It was assumed that plants compete exclusively for space well outside their<br />

canopies during dry periods, but can <strong>to</strong>lerate higher densities during wetter periods, and at moist sites<br />

(eg alongside bore drains and at coastal sites).<br />

The lifecycles include mechanisms for germination, seed decay, plant desiccation, growth, maturation,<br />

density-dependent effects on growth and mortality, reproduction (including selective abortion),<br />

herbivory, interspecific competition with pasture species, and differential seed dispersal due <strong>to</strong> s<strong>to</strong>cking<br />

patterns.<br />

The model is driven by weekly averages <strong>of</strong> daily maximum and minimum temperature, and weekly<br />

<strong>to</strong>tals <strong>of</strong> rainfall and evaporation (Queensland Centre for Climate Applications, 1998). It incorporates<br />

the effects <strong>of</strong> climate change through mechanisms affecting the growth rates <strong>of</strong> plants, and their wateruse<br />

efficiency. The atmospheric CO 2 concentration, climate sensitivity (increase in global temperature<br />

at 2 x CO 2 ), and rainfall can each be adjusted <strong>to</strong> simulate <strong>future</strong> climate scenarios. The mechanisms<br />

accounting for effects <strong>of</strong> alterations in CO 2 were derived from a literature review <strong>of</strong> the effects <strong>of</strong> CO 2<br />

alone, and in concert with temperature, nutrient and moisture availability on plant fac<strong>to</strong>rs<br />

(pho<strong>to</strong>synthesis, growth rates, water use efficiency, and competitiveness).<br />

Where possible, driving functions and parameters were derived from published empirical relations and<br />

manipulative experiments (eg seedling drought <strong>to</strong>lerance), inferred from the plant's geographical<br />

distribution, or derived from analyses <strong>of</strong> field observations. Remaining parameters were derived<br />

through ad hoc iterative parameter-fitting techniques (Starfield and Bleloch 1991). The model was<br />

verified with data from the field ecology research program (Radford et al. 1999).<br />

In one experiment, seedlings were grown in pots under controlled environmental conditions designed <strong>to</strong><br />

mimic field conditions as closely as possible. After two weeks growth, the seedlings were subjected <strong>to</strong> a<br />

soil dry-down regime that eventually resulted in death. Plant size, soil moisture level and time <strong>to</strong> death<br />

were noted.<br />

2.3.3 The effects <strong>of</strong> climate change on prickly acacia population dynamics<br />

To assess the effect <strong>of</strong> climate change on the paddock populations <strong>of</strong> prickly acacia, the population<br />

dynamics model was run with a series <strong>of</strong> standard scenarios using meteorological data for a range <strong>of</strong><br />

selected sites that represent a broad range <strong>of</strong> suitability under current climate. This method<br />

standardised fac<strong>to</strong>rs that would be affected by management decisions. The decision <strong>to</strong> utilise this<br />

approach was taken after consideration <strong>of</strong> such fac<strong>to</strong>rs as the longevity <strong>of</strong> prickly acacia, the limited<br />

availability <strong>of</strong> his<strong>to</strong>rical meteorological data, and the time taken <strong>to</strong> run the model for moderate lengths<br />

<strong>of</strong> time (40 years). The long-lived nature <strong>of</strong> prickly acacia (35 years) means that the model is sensitive<br />

<strong>to</strong> initialisation conditions ie the model state at the end <strong>of</strong> a 40 year run can be highly dependent upon<br />

the number and size <strong>of</strong> plants at the beginning <strong>of</strong> the run. The model is also highly sensitive <strong>to</strong> the<br />

lives<strong>to</strong>ck species (cattle or sheep). When comparing effects between sites, the model was run with<br />

100% cattle. The paddock configuration used for all runs was 1000 ha <strong>of</strong> uplands and 1 ha <strong>of</strong> high<br />

quality habitat surrounding watering points. The rationale for this was that there is a bore-capping<br />

program in place in Queensland at present, and bore drains are only present in Queensland. Thus, the<br />

most relevant scenario <strong>to</strong> use is one in which there is a limited number <strong>of</strong> watering points in the paddock<br />

that provide moist habitat for prickly acacia. All model runs were initialised with the same number <strong>of</strong><br />

adult plants. The chosen initial adult plant densities simulate a moderately invaded paddock in the<br />

10

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