Modelling pre-clearing vegetation distribution using GIS-integrated statistical, ecological and data models: A case study from the wet tropics of Northeastern Australia

Traditional vegetation mapping methods use high cost, labour-intensive aerial photography interpretation. This approach can be subjective and is limited by factors such as the extent of remnant vegetation, and the differing scale and quality of aerial photography over time. An alternative approach is proposed which integrates a data model, a statistical model and an ecological model using sophisticated Geographic Information Systems (GIS) techniques and rule-based systems to support fine-scale vegetation community modelling. This approach is based on a more realistic representation of vegetation patterns with transitional gradients from one vegetation community to another. Arbitrary, though often unrealistic, sharp boundaries can be imposed on the model by the application of statistical methods. This GIS-integrated multivariate approach is applied to the problem of vegetation mapping in the complex vegetation communities of the Innisfail Lowlands in the Wet Tropics bioregion of Northeastern Australia. The paper presents the full cycle of this vegetation modelling approach including sampling sites, variable selection, model selection, model implementation, internal model assessment, model prediction assessments, models integration of discrete vegetation community models to generate a composite pre-clearing vegetation map, independent data set model validation and model prediction's scale assessments. An accurate pre-clearing vegetation map of the Innisfail Lowlands was generated (0.83r(2)) through GIS integration of 28 separate statistical models. This modelling approach has good potential for wider application, including provision of. vital information for conservation planning and management; a scientific basis for rehabilitation of disturbed and cleared areas; a viable method for the production of adequate vegetation maps for conservation and forestry planning of poorly-studied areas. (c) 2006 Elsevier B.V. All rights reserved.

Modelling the population dynamics of the Queensland fruit fly, Bactrocera (Dacus) tryoni: a cohort-based approach incorporating the effects of weather

Queensland fruit fly, Bactrocera (Dacus) tryoni (QFF) is arguably the most costly horticultural insect pest in Australia. Despite this, no model is available to describe its population dynamics and aid in its management. This paper describes a cohort-based model of the population dynamics of the Queensland fruit fly. The model is primarily driven by weather variables, and so can be used at any location where appropriate meteorological data are available. In the model, the life cycle is divided into a number of discreet stages to allow physiological processes to be defined as accurately as possible. Eggs develop and hatch into larvae, which develop into pupae, which emerge as either teneral females or males. Both females and males can enter reproductive and over-wintering life stages, and there is a trapped male life stage to allow model predictions to be compared with trap catch data. All development rates are temperature-dependent. Daily mortality rates are temperature-dependent, but may also be influenced by moisture, density of larvae in fruit, fruit suitability, and age. Eggs, larvae and pupae all have constant establishment mortalities, causing a defined proportion of individuals to die upon entering that life stage. Transfer from one immature stage to the next is based on physiological age. In the adult life stages, transfer between stages may require additional and/or alternative functions. Maximum fecundity is 1400 eggs per female per day, and maximum daily oviposition rate is 80 eggs/female per day. The actual number of eggs laid by a female on any given day is restricted by temperature, density of larva in fruit, suitability of fruit for oviposition, and female activity. Activity of reproductive females and males, which affects reproduction and trapping, decreases with rainfall. Trapping of reproductive males is determined by activity, temperature and the proportion of males in the active population. Limitations of the model are discussed. Despite these, the model provides a useful agreement with trap catch data, and allows key areas for future research to be identified. These critical gaps in the current state of knowledge exist despite over 50 years of research on this key pest. By explicitly attempting to model the population dynamics of this pest we have clearly identified the research areas that must be addressed before progress can be made in developing the model into an operational tool for the management of Queensland fruit fly. (C) 2003 Published by Elsevier B.V.

Prospective study of individual, social, and environmental predictors of physical activity: women's leisure running

Background: Understanding and influencing the determinants of physical activity is an important public health challenge. We used prospective data to examine the influence of individual, social, and environmental factors on physical activity behaviour, using regular running as the behavioural model. Methods: Over 500 middle-aged women completed two consecutive questionnaires in 2000 and 2002. Logistic regression analyses were used to examine factors predicting adoption of and regression from regular leisure-time running during the follow-up. Results: Women who frequently used behavioural change skills were more likely to adopt regular running (OR=4.0, CI=1.7-9.5). There was an interaction between the enjoyment of running and family support: those who rated enjoyment of running high and reported high family support were less likely to adopt running (OR= 0.2, CI = 0.1-0.5). Women who reported infrequent use of motives were more likely (OR = 3.3, CI = 1.6-6.9) to regress from regular running. There was an interaction between perceived health and the neighbourhood environment: those who perceived themselves to be in poor health and had an unattractive neighbourhood were more likely (OR = 2.7, CI = 0.9-8.3) to regress from regular running. Conclusions: Behavioural skills and enjoyment may be of particular importance for the adoption of regular activity; social support and an aesthetically attractive neighbourhood are likely to have a key role in encouraging maintenance. (c) 2004 Elsevier Ltd. All rights reserved.

Variation in mortality rates in Australia: correlation with Indigenous status, remoteness and socio-economic deprivation

Background The aim of this study was to study ecological correlations between age-adjusted all-cause mortality rates in Australian statistical divisions and (1) the proportion of residents that self-identify as Indigenous, (2) remoteness, and (3) socio-economic deprivation. Methods All-cause mortality rates for 57 statistical divisions were calculated and directly standardized to the 1997 Australian population in 5-year age groups using Australian Bureau of Statistics (ABS) data. The proportion of residents who self-identified as Indigenous was obtained from the 1996 Census. Remoteness was measured using ARIA (Accessibility and Remoteness Index for Australia) values. Socioeconomic deprivation was measured using SEIFA (Socio-Economic index for Australia) values from the ABS. Results Age-standardized all-cause mortality varies twofold from 5.7 to 11.3 per 1000 across Australian statistical divisions. Strongest correlation was between Indigenous status and mortality (r = 0.69, p < 0.001). correlation between remoteness and mortality was modest (r = 0.39, p = 0.002) as was correlation between socio-economic deprivation and mortality (r = -0.42, p = 0.001). Excluding the three divisions with the highest mortality, a multiple regression model using the logarithm of the adjusted mortality rate as the dependent variable showed that the partial correlation (and hence proportion of the variance explained) for Indigenous status was 0.03 (9 per cent; p = 0.03), for SEIFA score was -0.17 (3 per cent; p = 0.22); and for remoteness was -0.22 (5 per cent; p = 0.13). Collectively, the three variables studied explain 13 per cent of the variability in mortality. Conclusions Ecological correlation exists between all-cause mortality, Indigenous status, remoteness and disadvantage across Australia. The strongest correlation is with indigenous status, and correlation with all three characteristics is weak when the three statistical divisions with the highest mortality rates are excluded. intervention targeted at these three statistical divisions could reduce much of the variability in mortality in Australia.

An internet GIS and spatial model to benchmark local government socio-economic performance

This paper develops an Internet geographical information system (GIS) and spatial model application that provides socio-economic information and exploratory spatial data analysis for local government authorities (LGAs) in Queensland, Australia. The application aims to improve the means by which large quantities of data may be analysed, manipulated and displayed in order to highlight trends and patterns as well as provide performance benchmarking that is readily understandable and easily accessible for decision-makers. Measures of attribute similarity and spatial proximity are combined in a clustering model with a spatial autocorrelation index for exploratory spatial data analysis to support the identification of spatial patterns of change. Analysis of socio-economic changes in Queensland is presented. The results demonstrate the usefulness and potential appeal of the Internet GIS applications as a tool to inform the process of regional analysis, planning and policy.

Subantarctic Macquarie Island - a model ecosystem for studying animal-derived nitrogen sources using N-15 natural abundance

Plants collected from diverse sites on subantarctic Macquarie Island varied by up to 30 parts per thousand in their leaf delta(15)N values. N-15 natural abundance of plants, soils, animal excrement and atmospheric ammonia suggest that the majority of nitrogen utilised by plants growing in the vicinity of animal colonies or burrows is animal-derived. Plants growing near scavengers and animal higher in the food chain had highly enriched delta(15)N values (mean = 12.9 parts per thousand), reflecting the highly enriched signature of these animals' excrement, while plants growing near nesting penguins and albatross, which have an intermediate food chain position, had less enriched delta(15)N values (> 6 parts per thousand). Vegetation in areas affected by rabbits had lower delta(15)N values (mean = 1.2 parts per thousand), while the highly depleted delta(15)N values (below -5 parts per thousand) of plants at upland plateau sites inland of penguin colonies, suggested that a portion of their nitrogen is derived from ammonia (mean N-15 = -10 parts per thousand) lost during the degradation of penguin guano. Vegetation in a remote area had delta(15)N values near -2 parts per thousand. These results contrast with arctic and subarctic studies that attribute large variations in plant N-15 values to nitrogen partitioning in nitrogen-limited environments. Here, plant N-15 reflects the N-15 Of the likely nitrogen sources utilised by plants.

Swapping space for time and unfair tests of ecological models

Testing ecological models for management is an increasingly important part of the maturation of ecology as an applied science. Consequently, we need to work at applying fair tests of models with adequate data. We demonstrate that a recent test of a discrete time, stochastic model was biased towards falsifying the predictions. If the model was a perfect description of reality, the test falsified the predictions 84% of the time. We introduce an alternative testing procedure for stochastic models, and show that it falsifies the predictions only 5% of the time when the model is a perfect description of reality. The example is used as a point of departure to discuss some of the philosophical aspects of model testing.

Field test of a model of migration of moths (Lepidoptera : Noctuidae) in inland Australia

A migration of Helicoverpa punctigera (Wallengren), Heliothis punctifera (Walker) and Agrotis munda Walker was tracked from Cameron Corner (29degrees00'S, 141degrees00'E) in inland Australia to the Wilcannia region, approximately 400 km to the south-east. A relatively isolated source population was located using a distribution model to predict winter breeding, and confirmed by surveys using sweep netting for larvae. When a synoptic weather pattern likely to produce suitable conditions for migration developed, moths were trapped in the source region. The next morning a simulation model of migration using wind-field data generated by a numerical weather-prediction model was run. Surveys using sweep netting for larvae, trapping and flush counts were then conducted in and around the predicted moth fallout area, approximately 400 km to the south-east. Pollen carried on the probosces of moths caught in this area was compared with that on moths caught in the source area. The survey data and pollen comparisons provided evidence that migration had occurred, and that the migration model gave accurate estimation of the fallout region. The ecological and economic implications of such migrations are discussed.

An overview of APSIM, a model designed for farming systems simulation

The Agricultural Production Systems Simulator (APSIM) is a modular modelling framework that has been developed by the Agricultural Production Systems Research Unit in Australia. APSIM was developed to simulate biophysical process in farming systems, in particular where there is interest in the economic and ecological outcomes of management practice in the face of climatic risk. The paper outlines APSIM's structure and provides details of the concepts behind the different plant, soil and management modules. These modules include a diverse range of crops, pastures and trees, soil processes including water balance, N and P transformations, soil pH, erosion and a full range of management controls. Reports of APSIM testing in a diverse range of systems and environments are summarised. An example of model performance in a long-term cropping systems trial is provided. APSIM has been used in a broad range of applications, including support for on-farm decision making, farming systems design for production or resource management objectives, assessment of the value of seasonal climate forecasting, analysis of supply chain issues in agribusiness activities, development of waste management guidelines, risk assessment for government policy making and as a guide to research and education activity. An extensive citation list for these model testing and application studies is provided. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.

Is maximizing resilience compatible with established ecological goal functions?

Cropp and Gabric [Ecosystem adaptation: do ecosystems maximise resilience? Ecology. In press] used a simple phytoplanktonzooplankton-nutrient model and a genetic algorithm to determine the parameter values that would maximize the value of certain goal functions. These goal functions were to maximize biomass, maximize flux, maximize flux to biomass ratio, and maximize resilience. It was found that maximizing goal functions maximized resilience. The objective of this study was to investigate whether the Cropp and Gabric [Ecosystem adaptation: do ecosystems maximise resilience? Ecology. In press] result was indicative of a general ecosystem principle, or peculiar to the model and parameter ranges used. This study successfully replicated the Cropp and Gabric [Ecosystem adaptation: do ecosystems maximise resilience? Ecology. In press] experiment for a number of different model types, however, a different interpretation of the results is made. A new metric, concordance, was devised to describe the agreement between goal functions. It was found that resilience has the highest concordance of all goal functions trialled. for most model types. This implies that resilience offers a compromise between the established ecological goal functions. The parameter value range used is found to affect the parameter versus goal function relationships. Local maxima and minima affected the relationship between parameters and goal functions, and between goal functions. (C) 2003 Elsevier B.V. All rights reserved.

Investigation of factors related to employment outcome following traumatic brain injury: a critical review and conceptual model

Purpose : The purpose of this article is to critically review the literature to examine factors that are most consistently related to employment outcome following traumatic brain injury (TBI), with a particular focus on metacognitive skills. It also aims to develop a conceptual model of factors related to employment outcome. Method : The first stage of the review considered 85 studies published between 1980 and December 2003 which investigated factors associated with employment outcome following TBI. English-language studies were identified through searches of Medline and PsycINFO, as well as manual searches of journals and reference lists. The studies were evaluated and rated by two independent raters (Kappa = 0.835) according to the quality of their methodology based upon nine criteria. Fifty studies met the criteria for inclusion in the second stage of the review, which examined the relationship between a broad range of variables and employment outcome. Results : The factors most consistently associated with employment outcome included pre-injury occupational status, functional status at discharge, global cognitive functioning, perceptual ability, executive functioning, involvement in vocational rehabilitation services and emotional status. Conclusions : A conceptual model is presented which emphasises the importance of metacognitive, emotional and social environment factors for improving employment outcome.

An investigation into effects of long-distance seed dispersal on organelle population genetic structure and colonization rate: a model analysis

A simulation-based modelling approach is used to examine the effects of stratified seed dispersal (representing the distribution of the majority of dispersal around the maternal parent and also rare long-distance dispersal) on the genetic structure of maternally inherited genomes and the colonization rate of expanding plant populations. The model is parameterized to approximate postglacial oak colonization in the UK, but is relevant to plant populations that exhibit stratified seed dispersal. The modelling approach considers the colonization of individual plants over a large area (three 500 km x 10 km rolled transects are used to approximate a 500 km x 300 km area). Our approach shows how the interaction of plant population dynamics with stratified dispersal can result in a spatially patchy haplotype structure. We show that while both colonization speeds and the resulting genetic structure are influenced by the characteristics of the dispersal kernel, they are robust to changes in the periodicity of long-distance events, provided the average number of long-distance dispersal events remains constant. We also consider the effects of additional physical and environmental mechanisms on plant colonization. Results show significant changes in genetic structure when the initial colonization of different haplotypes is staggered over time and when a barrier to colonization is introduced. Environmental influences on survivorship and fecundity affect both the genetic structure and the speed of colonization. The importance of these mechanisms in relation to the postglacial spread and genetic structure of oak in the UK is discussed.