The goal of this work was to quantify the effects of eucalypt woodland blocks on the productivity of native pastures. This research was conducted on the Southern Tablelands of New South Wales. Tree planting or retention is seen by many as an important tool in addressing the problems of soil degradation resulting from clearing and pasture improvement that threaten the sustainability of pasture systems. In particular these are dry land salinity and erosion, both of which affect large areas of agricultural lands in the south east of Australia. Whilst native tree cover remains over substantial portions of Australian pasture lands, mainly on steeper slopes and poorer soils, little has been done to measure the effects of trees on pasture productivity and soil fertility on the Southern Tablelands. Previous studies in other areas have shown a range of effects�from facilitation to inhibition�of pasture growth in the presence of trees. Soil fertility beneath trees has been shown by a number of workers to be elevated in comparison with situations in the open. Given that the range of effects may be highly site dependent, application of results from one area to another may not be valid. Thus it is necessary to measure tree effects on a regional scale if results are to be reliable. Pasture productivity was assessed over a two year period on four sites in the vicinity of Bungendore, New South Wales. A pair of plots was selected on each site, one plot in a block of eucalypt woodland, and the other nearby in an exposed, open situation. Plots were chosen to be as similar to each other as possible with the exception of tree cover. Treed plots had a tree basal area of between 10 and 20 m2 ha-1 and plots had an area of 900 m2. Two of the sites were on granitic soils and had a tree cover consisting predominantly of Eucalyptus pauciflora. The remaining two sites were on soil derived from sedimentary rocks with tree cover consisting mainly of E. mannifera, E. dives and E. melliodora. Perennial native pasture species present were similar across all sites, although their relative contributions to standing biomass varied between sites. As the plots were grazed during the period of measurement, productivity and offtake were measured seasonally using exclosure cages on each plot. Pasture standing biomass was assessed using the comparative yield technique. Microclimate was monitored in each plot by automatic weather stations. Soil moisture to a depth of 45 cm was measured by time domain reflectometry using permanent probes in each plot. Ten additional survey plots on each site, covering the range of tree basal area from 0 - 30 m2 ha-1, were assessed each season in the second year for standing biomass, soil fertility and pasture quality; expressed by nitrogen content and dry matter digestibility. Pasture floristics were measured using the dry-weight-rank method. These additional plots were chosen to be as representative of the paddocks as possible. Over the two years that productivity was measured, it was found to be higher under trees than in the open. This was predominantly due to higher winter and spring growth within treed plots. Grazing offtake was also found to be higher under trees, partly accounting for lower standing biomass found in the treed plots. Wind run, evapotranspiration and photosynthetically active radiation were all reduced by the presence of trees. Beneficial effects of shelter from winds may largely explain the higher productivity observed in the treed plots, and could outweigh negative effects of below ground competition and radiation interception by tree canopies at low to moderate tree densities. Soil moisture was not affected by the presence of trees. Soil fertility also did not differ between treed and open plots nor was there any difference in pasture nitrogen content or dry matter digestibility. On the sites where soils were derived from sedimentary rocks, pasture floristics were found to be related to tree basal area. Themeda ausfralis biomass was negatively related to tree basal area, and was partially replaced by large tussock species such as Poa sieberiana and Chionochloa pallida. A reduction of pasture quality resulted, particularly as the latter species is not grazed to any significant extent. Given the desirability of having deep rooted perennial components in grazing lands, the results of this study indicate that it may be possible to utilise trees to assist in preventing or reducing a range of adverse environmental consequences arising from agricultural activities, without unduly compromising pasture productivity. Additionally, the wide range of environmental conditions provided by a mix of treed and open pasture promotes a higher degree of heterogeneity of the herbaceous layer. This may assist in maintaining productivity over a greater range of climatic conditions than would be the case with a more homogeneous pasture.

The vegetation of the Sydney Basin, Australia, is highly flammable and subject to a wide range of fire regimes. Sclerophyllous shrubs and sedges are common and in some vegetation types up to 70 % of fuel consumed during a fire can be live. Research into fire behaviour and fuel dynamics has been minimal. To address this issue this thesis investigated the principal factor affecting the ease of ignition and rate of combustion of individual fuel particles and fuel beds in bushfires: dead fine fuel moisture (FFM). Two common Sydney Basin vegetation types, eucalypt woodland and heathland, each with a history of problematic fire management, were measured in the field for diurnal fluctuations in FFM following rain, under conditions similar to when prescribed burns are conducted. The FFM components of current operational fire behaviour models were found to be inadequate for predictions of FFM and fire behaviour under these conditions. The equilibrium moisture content (EMC) of five fuel types from the field site was investigated in a laboratory study. An existing function describing EMC as a function of temperature and relative humidity was evaluated and found to be very accurate for these fuels. Two FFM predictive models incorporating this function were evaluated on the field data and the laboratory results were shown to be applicable to the estimation of FFM in the field. One model gave very accurate predictions of FFM below fibre saturation point, but its accuracy was reduced when screen level conditions were used instead of those measured at fuel level. A recent process-based model that accounts for rainfall showed promise for predicting when fuel is < 25 % FFM. Systematic problems with the radiation budget of this model reduced the accuracy of predictions and further refinement is required. Live fine fuel moisture content (LFMC) of common heathland shrubs and sedge was investigated over two years and found to be both seasonal and influenced by phenology. LFMC minima occurred in late winter and spring (August to October), and maxima were in summer (December to February) when new growth was recorded. The dominant near-surface fuel in mature heath was sedge. It was found to have little seasonal variation in its??? percentage dead but the percentage dead maxima occured at the same time as the LFMC minima of shrubs and sedge in both years. Simple instantaneous models for duff moisture content in woodland and heathland and LFMC and the percentage dead sedge in heathland were developed. The information gained by this study will form the basis for future development of fuel moisture models for prescribed burning guidelines and fire spread models specific to the vegetation communities of the Sydney Basin.

The vegetation of the Sydney Basin, Australia, is highly flammable and subject to a wide range of fire regimes. Sclerophyllous shrubs and sedges are common and in some vegetation types up to 70 % of fuel consumed during a fire can be live. Research into fire behaviour and fuel dynamics has been minimal. To address this issue this thesis investigated the principal factor affecting the ease of ignition and rate of combustion of individual fuel particles and fuel beds in bushfires: dead fine fuel moisture (FFM). Two common Sydney Basin vegetation types, eucalypt woodland and heathland, each with a history of problematic fire management, were measured in the field for diurnal fluctuations in FFM following rain, under conditions similar to when prescribed burns are conducted. The FFM components of current operational fire behaviour models were found to be inadequate for predictions of FFM and fire behaviour under these conditions. The equilibrium moisture content (EMC) of five fuel types from the field site was investigated in a laboratory study. An existing function describing EMC as a function of temperature and relative humidity was evaluated and found to be very accurate for these fuels. Two FFM predictive models incorporating this function were evaluated on the field data and the laboratory results were shown to be applicable to the estimation of FFM in the field. One model gave very accurate predictions of FFM below fibre saturation point, but its accuracy was reduced when screen level conditions were used instead of those measured at fuel level. A recent process-based model that accounts for rainfall showed promise for predicting when fuel is < 25 % FFM. Systematic problems with the radiation budget of this model reduced the accuracy of predictions and further refinement is required. Live fine fuel moisture content (LFMC) of common heathland shrubs and sedge was investigated over two years and found to be both seasonal and influenced by phenology. LFMC minima occurred in late winter and spring (August to October), and maxima were in summer (December to February) when new growth was recorded. The dominant near-surface fuel in mature heath was sedge. It was found to have little seasonal variation in its??? percentage dead but the percentage dead maxima occured at the same time as the LFMC minima of shrubs and sedge in both years. Simple instantaneous models for duff moisture content in woodland and heathland and LFMC and the percentage dead sedge in heathland were developed. The information gained by this study will form the basis for future development of fuel moisture models for prescribed burning guidelines and fire spread models specific to the vegetation communities of the Sydney Basin.

In this thesis I present and test a methodology for developing a stand scale index of structural complexity. If properly designed such an index can act as a summary variable for a larger set of stand structural attributes, providing a means of ranking stands in terms of their structural complexity, and by association, their biodiversity and vegetation condition. This type of index can also facilitate the use of alternative policy instruments for biodiversity conservation, such as mitigation banking, auctions and offsets, that rely on a common currency – the index value – that can be compared or traded between sites. My intention was to establish a clear and documentable methodology for developing a stand scale index of structural complexity, and to test this methodology using data from real stands.¶ As a starting point, I reviewed the literature concerning forest and woodland structure and found there was no clear definition of stand structural complexity, or definitive suite of structural attributes for characterising it. To address this issue, I defined stand structural complexity as a combined measure of the number of different structural attributes present in a stand, and the relative abundance of each of these attributes. This was analogous to approaches that have quantified diversity in terms of the abundance and richness of elements. It was also concluded from the review, that stand structural complexity should be viewed as a relative, rather than absolute concept, because the potential levels of different structural attributes are bound within certain limits determined by the inherent characteristics of the site in question, and the biota of the particular community will have evolved to reflect this range of variation. This implied that vegetation communities with naturally simple structures should have the potential to achieve high scores on an index of structural complexity.¶ I proposed the following five-stage methodology for developing an index of stand structural complexity: 1. Establish a comprehensive suite of stand structural attributes as a starting point for developing the index, by reviewing studies in which there is an established relationship between elements of biodiversity and structural attributes. 2. Develop a measurement system for quantifying the different attributes included in the comprehensive suite. 3. Use this measurement system to collect data from a representative set of stands across the range of vegetation condition (highly modified to unmodified) and developmental stages (regrowth to oldgrowth) occurring in the vegetation communities in which the index is intended to operate. 4. Identify a core set of structural attributes from an analysis of these data. 5. Combine the core attributes in a simple additive index, in which attributes are scored relative to their observed levels in each vegetation community.¶ Stage one of this methodology was addressed by reviewing a representative sample of the literature concerning fauna habitat relationships in temperate Australian forests and woodlands. This review identified fifty-five studies in south-east and south-west Australia, in which the presence or abundance of different fauna were significantly (p&lt0.05) associated with vegetation structural attributes. The majority of these studies concerned bird, arboreal mammal, and ground mammal habitat requirements, with relatively fewer studies addressing the habitat requirements of reptiles, invertebrates, bats or amphibians. Thirty four key structural attributes were identified from these fifty-five studies, by grouping similar attributes, and then representing each group with a single generic attribute. This set, in combination with structural attributes identified in the earlier review, provided the basis for developing an operational set of stand level attributes for the collection of data from study sites.¶ To address stages two and three of the methodology, data were collected from one woodland community –Yellow Box-Red Gum (E. melliodora-E. Blakelyi ) – and two dry sclerophyll forest communities – Broadleaved Peppermint-Brittle Gum (E. dives-E. mannifera ), Scribbly Gum-Red Stringybark (E. rossii E. macrorhyncha ) – in a 15,000 km2 study area in the South eastern Highlands Bioregion of Australia. A representative set of 48 sites was established within this study area, by identifying 24 strata, on the basis of the three vegetation communities, two catchments, two levels of rainfall and two levels of condition, and then locating two sites (replicates) within each stratum. At each site, three plots were systematically established, to provide an unbiased estimate of stand level means for 75 different structural attributes.¶ I applied a three-stage analysis to identify a core set of attributes from these data. The first stage – a preliminary analysis – indicated that the 48 study sites represented a broad range of condition, and that the two dry sclerophyll communities could be treated as a single community, which was structurally distinct from the woodland community. In the second stage of the analysis, thirteen core attributes were dentified using the criteria that a core attribute should:¶ 1. Be either, evenly or approximately normally distributed amongst study sites; 2. Distinguish between woodland and dry sclerophyll communities; 3. Function as a surrogate for other attributes; 4. Be efficient to measure in the field. The core attributes were: Vegetation cover &lt0.5m Vegetation cover 0.5-6.0m; Perennial species richness; Lifeform richness; Stand basal area of live trees; Quadratic mean diameter of live stems; ln(number of regenerating stems per ha+1); ln(number of hollow bearing trees per ha+1);ln(number of dead trees per ha+1);sqrt(number of live stems per ha &gt40cm dbh); sqrt(total log length per ha); sqrt(total largelog length per ha); Litter dry weight per ha. This analysis also demonstrated that the thirteen core attributes could be modelled as continuous variables, and that these variables were indicative of the scale at which the different attributes operated.¶ In the third and final stage of the analysis, Principal Components Analysis was used to test for redundancy amongst the core attributes. Although this analysis highlighted six groupings, within which attributes were correlated to some degree, these relationships were not considered sufficiently robust to justify reducing the number of core attributes.¶ The thirteen core attributes were combined in a simple additive index, in which, each attribute accounted for 10 points in a total index value of 130. Attributes were rescaled as a score from 0-10, using equations that modelled attribute score as a function of the raw attribute data. This maintained a high correlation (r > 0.97, p< 0.0001) between attribute scores and the original attribute data. Sensitivity analysis indicated that the index was not sensitive to attribute weightings, and on this basis attributes carried equal weight. In this form my index was straightforward to apply, and approximately normally distributed amongst study sites.¶ I demonstrated the practical application of the index in a user-friendly spreadsheet, designed to allow landowners and managers to assess the condition of their vegetation, and to identify management options. This spreadsheet calculated an index score from field data, and then used this score to rank the site relative to a set of reference sites. This added a regional context to the operation of the index, and is a potentially useful tool for identifying sites of high conservation value, or for identifying sites where management actions have maintained vegetation quality. The spreadsheet also incorporated the option of calculating an index score using a subset of attributes, and provided a measure of the uncertainty associated with this score.¶ I compared the proposed index with five prominent indices used to quantify vegetation condition or habitat value in temperate Australian ecosystems. These were: Newsome and Catling’s (1979) Habitat Complexity Score, Watson et al.’s (2001) Habitat Complexity Score, the Site Condition Score component of the Habitat Hectares Index of Parkes et al. (2003), the Vegetation Condition Score component of the Biodiversity Benefits Index of Oliver and Parkes (2003), and the Vegetation Condition Score component of the BioMetric Assessment Tool of Gibbons et al. (2004). I found that my index differentiated between study sites better than each of these indices. However, resource and time constraints precluded the use of a new and independent data set for this testing, so that the superior performance of my index must be interpreted cautiously.¶ As a group, the five indices I tested contained attributes describing compositional diversity, coarse woody debris, regeneration, large trees and hollow trees – these were attributes that I also identified as core ones. However, unlike these indices, I quantified weeds indirectly through their effect on indigenous plant diversity, I included the contribution of non-indigenous species to vegetation cover and did not apply a discount to this contribution, I limited the direct assessment of regeneration to long-lived overstorey species, I used stand basal area as a surrogate for canopy cover, I quantified litter in terms of biomass (dry weight) rather than cover, and I included the additional attributes of quadratic mean diameter and the number of dead trees.¶ I also concluded that Parkes et al. (2003), Oliver and Parkes (2003), and Gibbons et al. (2004), misapplied the concept of benchmarking, by characterising attributes in terms of a benchmark range or average level. This ignored processes that underpin variation at the stand level, such as the increased development of some attributes at particular successional stages, and the fact that attributes can respond differently to disturbance agents. It also produced indices that were not particularly sensitive to the differences in attribute levels occurring between stands. I suggested that a more appropriate application of benchmarking would be at the overarching level of stand structural complexity, using a metric such as the index developed in this thesis. These benchmarks could reflect observed levels of structural complexity in unmodified natural stands at different successional stages, or thresholds for structural complexity at which a wide range of biota are present, and would define useful goals for guiding on-ground management.