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Increasing global temperatures as a result of climate change are widely considered inevitable for Australia. Despite this, the specific effects of climate change on Australian agriculture are little studied and the effects on agricultural pests and diseases are virtually unknown. In this paper we consider the impact of climate change on the Asiatic citrus psyllid (Diaphorina citri Kuwayama [Hemiptera: Psyllidae]); one of two known vectors of huanglongbing (citrus greening); a debilitating disease which is caused in Asia by a phloem-limited bacterium ‘Candidatus Liberibacter asiaticus’ (α-Proteobacteria). D. citri does not occur in Australia, but if introduced would pose a major threat to the viability of the Australian citrus industry and to native Citrus species. This paper presents an approach developed to understand how climate change may influence the behaviour, distribution and breeding potential of D. citri. Here we developed and describe an initial dynamic point model of D. citri biology in relation to its citrus host and applied it to a scenario of increasing temperatures, as indicators of climate change, on a continental scale. A comparison between model outputs for the three time frames considered (1990, 2030 and 2070) confirms that increasing temperatures projected under climate change will affect the timing and duration of new citrus growth (flush) necessary for psyllid development throughout Australia. Flushing will start progressively earlier as the temperature increases and be of shorter duration. There will also be a gradual southward expansion of shorter durations of the occurrence of flush. Increasing temperatures will impact on D. citri both directly through alteration of its temperature dependant development cycle and indirectly through the impact on the host flushing cycle. For the whole of Australia, a comparison between model outputs for the three scenarios considered indicates the seasonality of D. citri development will change to match changes in citrus flush initiation. Results indicate that the risk of establishment by D. citri is projected to decrease under increasing temperatures, mainly due to shortened intervals when it can feed on new leaf flushes of the host. However, the spatially heterogeneous results also suggest that regions located on the southern coastline of Australia could become more suitable for D. citri than projected under current temperatures. These results confirm the value of a linked host-pest approach as based on D. citri climatic requirements alone the model would have accounted only for shorter development periods and predicted an increased risk of potential distribution. [Copyright &y& Elsevier]

Abstract: In the management of recreational fishing, multiple biophysical and socio-economic objectives need to be considered. The identification of best management options is technically challenging because of the lack of scientific tools to inform resource managers of future responses/impacts of these different options. This paper proposes a decision support system which aims at greatly improving stakeholder dialogue and decision making. The system consists of two main components: an integrated agent-based model for simulating recreational fishing behavior and reef ecosystem dynamics; and an evaluation model based on the analytic hierarchy process (AHP) together with a technique for order preference by similarity to ideal solution (TOPSIS). The evaluation component is responsible for assessing alternative strategies based on the simulation outputs generated by the former. We apply the proposed system to the assessment of management strategies for recreational fishing in the Ningaloo Marine Park, an iconic coral reef system in Western Australia. A set of management strategies, including a “business-as-usual” strategy and six alternative site closure strategies are assessed using the proposed solution. The site closure strategies evaluated vary in length and number of popular sites closed. The evaluation results illustrate the usefulness of the proposed system in tackling complex management choices. We also perform a sensitivity analysis on the stakeholder or decision maker outcome preference weights and provide measures for assessing the sensitivity of strategy ranking outcomes to changes in these weights. [Copyright &y& Elsevier]

Abstract: Detailed and reliable information about the spatial distribution of species provides critical information for effective conservation planning. In Victoria, Australia, this responsibility is held by the Department of Sustainability and Environment, which maintains and curates a database of site records for species: the Victorian Biodiversity Atlas. But the information is provided in point form, and therefore, it does not provide an adequate view of species distributions for all management purposes. By integrating known occurrences of species with environmental GIS data layers using a machine learning algorithm, random forest, we have built species distribution models for 523 vertebrate fauna species across the whole state, providing predictive ‘maps’ that are available for use in various conservation planning activities. In this paper, we introduce and discuss the methods we developed and implemented for producing these models. Specifically, 26 explanatory variables were used for the modelling; three versions of models were built using different sets of explanatory variables; pseudo-absences were chosen by filtering random points with a profile model; model accuracy was assessed using several measures, especially lift curve-related ones; a threshold was selected for each model to transform continuous result to binary one by maximizing the sum of sensitivity and (pseudo) specificity, which was proved to be valid for presence-only data. [Copyright &y& Elsevier]

Restoration of abandoned and degraded ecosystems through enhanced management of mature remnant patches and naturally regenerating (regrowth) forests is currently being used in the recovery of ecosystems for biodiversity protection and carbon sequestration. Knowledge of long-term dynamics of these ecosystems is often very limited. Vegetation models that examine long-term forest growth and succession of uneven aged, mixed-species forest ecosystems are integral to the planning and assessment of the recovery process of biodiversity values and biomass accumulation. This paper examined the use of the Ecosystem Dynamics Simulator (EDS) in projecting growth dynamics of mature remnant brigalow forest communities and recovery process of regrowth brigalow thickets. We used data from 188 long-term monitored plots of remnant and regrowth forests measured between 1963 and 2010. In this study the model was parameterised for 34 tree and shrub species and tested with independent long-term measurements. The model closely approximated actual development trajectories of mature forests and regrowth thickets but some inaccuracies in estimating regeneration through asexual reproduction and mortality were noted as reflected in stem density projections of remnant plots that had a mean of absolute relative bias of 46.2 (±12.4)%. Changes in species composition in remnant forests were projected with a 10% error. Basal area values observed in all remnant plots ranged from 6 to 29m2 ha−1 and EDS projections between 1966 and 2005 (39 years) were 68.2 (±10.9)% of the observed basal area. Projected live aboveground biomass of remnant plots had a mean of 93.5 (±5.9)tha−1 compared to a mean of 91.3 (±8.0)tha−1 observed in the plots. In regrowth thicket, the model produced satisfactory projections of tree density (91%), basal area (89%), height (87%) and aboveground biomass (84%) compared to the observed attributes. Basal area and biomass accumulation in 45-year-old regrowth plots was approximately similar to that in remnant forests but recovery of woody understorey was very slow. The model projected that it would take 95 years for the regrowth to thin down to similar densities observed in original or remnant brigalow forests. These results indicated that EDS can produce relatively accurate projections of growth dynamics of brigalow regrowth forests necessary for informing restoration planning and projecting biomass accumulation. [Copyright &y& Elsevier]

The tropical savanna landscape of northern Australia is perhaps the most extensive and flammable ecosystem in the world. Like savannas worldwide, there still remains uncertainty as to the functioning of much of this system and the mechanisms maintaining a state between open grassland and woodland. We use the development of a process-based model to examine the processes operating on the eucalypt dominated tree component of the northern Australian savannas, focussing on the interaction of water availability and fire. A process-based, tree population dynamics model (Flames) has been developed to understand the interactive effects of fire and rainfall variability on trees in Australian savanna ecosystems where there has been limited modelling to date. This paper shows that the model is capable of simulating the range of tree populations found in northern Australia by considering soil properties (texture and depth) and rainfall distribution. The model indicates that seasonal variability and inter-annual variability in rainfall is critical in defining the structure and density of tree stands in northern Australia. We also show that fire plays an important role in defining tree structure by removing the most sensitive (the very young and old) trees and that frequent fronting fires will lead to ongoing reductions in tree populations. While fire is an important factor in northern Australia, the model indicates its effects on tree populations at a sub-continental scale are secondary to the impact of rainfall variability. [Copyright &y& Elsevier]

Bayesian decision support tools are becoming increasingly popular as a modelling framework that can analyse complex problems, resolve controversies, and support future decision-making in an adaptive management framework. This paper introduces a model designed to assist the management of an endangered Eucalypt species, the Swamp Gum (Eucalyptus camphora). This tree species is found in the Yellingbo Nature Conservation Reserve (YNCR), an isolated patch of forest in the Yarra Valley (Victoria, Australia), where E. Camphora has become increasingly threatened by dieback. In order to maintain and rehabilitate existing trees and encourage regeneration, management strategies and action plans have concentrated on restoring the hydrological regime, which has been altered due to agricultural activities within the catchment. However, research suggests that nutrient enrichment from surrounding horticulture and livestock is having a greater impact on the health of the trees. A Bayesian network model has been developed for E. Camphora and used to explore the differences between these two hypotheses. Model outputs suggest that the influencing factors of E. Camphora condition are (a) spatially specific and (b) differ according to the group conducting the study in the YNCR. Given the poor quality of data and knowledge available, further research is required to identify the causal factors of dieback. The model offers a framework to guide future integrative and iterative monitoring and research in the YNCR. [Copyright &y& Elsevier]

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 1 400 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. [Copyright &y& Elsevier]

Learning occurs in all stages of a fishery, in the entire fishing career of a fisher, and even within a single fishing trip. It is an important aspect of fleet dynamics; failure to take it into proper account biases results of population dynamics studies and results of stock assessments. In this paper, I introduce and slightly generalise three learning models and derive a new one. I use them to analyse data on the short-term learning behaviour of all fishers as a group in the fishery of the western king prawn Penaeus latisulcatus in the Gulf St Vincent, Australia, to demonstrate their utilities. The damped periodic change inferred in fishing efficiency of all fishers as a group with time (shot number) over a fishing day in the P. latisulcatus fishery had a period of 9.44±1.06 shots and could have resulted from periodic ‘forgetting’ and forcing by good catch rates. The new learning model was used to test the hypothesis that fishers in the P. latisulcatus fishery learn more from their failures in catch rate than from their successes, or more from their successes than from their failures, or as much from their successes as from their failures. Although very limited, the data suggest that fishers as a group learn 69.03±311.52% more from their successes in good catch rates than from their failures. [Copyright &y& Elsevier]

This paper describes an assessment of the Lachlan Catchment, in south-eastern Australia, undertaken to develop and apply methods for catchment planning. The GROWEST and Physiological Process for Predicting Growth (3-PG) models were used to model the spatial distribution of primary productivity for temperate pastures and forest plantations, respectively. For both models, spatial estimates of growth were obtained using long-term monthly climatic surfaces with a resolution of 0.01° of latitude and longitude. However, two different approaches were used to model temporal changes in productivity and to investigate the effects of climate variability on the reliability of production over time. Monthly climate surfaces for the period from 1950 to 1999 with a resolution of 0.25° were used to simulate growth for temperate pastures using GROWEST. Tree growth in plantations was simulated using 3-PG with 50 years of monthly climate data at 14 climate stations (sites) within the catchment.Production estimates were then used to examine the reliability of production for both systems and determine areas within the catchment that are most suited to perennial pasture production and those most suited to forest plantations for timber production. There are similarities in the spatial and temporal estimates produced from the different models, but production of temperate pastures is more constrained by low temperatures. While the majority of the catchment is capable of growing pasture, only a small area is capable of high growth rates that are required for commercial timber plantations. Forest plantations are also comparatively more reliable than temperate pastures in the more productive areas of the catchment. The study concludes that the methods for developing spatial and temporal estimates of growth are relevant for integrated catchment planning. [Copyright &y& Elsevier]

This paper describes a process-based metapopulation dynamics and phenology model of prickly acacia, Acacia nilotica, an invasive alien species in Australia. The model, SPAnDX, describes the interactions between riparian and upland sub-populations of A. nilotica within livestock paddocks, including the effects of extrinsic factors such as temperature, soil moisture availability and atmospheric concentrations of carbon dioxide. The model includes the effects of management events such as changing the livestock species or stocking rate, applying fire, and herbicide application. The predicted population behaviour of A. nilotica was sensitive to climate. Using 35 years daily weather datasets for five representative sites spanning the range of conditions that A. nilotica is found in Australia, the model predicted biomass levels that closely accord with expected values at each site. SPAnDX can be used as a decision-support tool in integrated weed management, and to explore the sensitivity of cultural management practices to climate change throughout the range of A. nilotica. The cohort-based DYMEX modelling package used to build and run SPAnDX provided several advantages over more traditional population modelling approaches (e.g. an appropriate specific formalism (discrete time, cohort-based, process-oriented), user-friendly graphical environment, extensible library of reusable components, and useful and flexible input/output support framework). [Copyright &y& Elsevier]

• A mathematical programming approach for the multi-action problem is proposed (MAMP). • A new MIP model that includes fragmentation penalty in actions (MAMP-E) is presented. • The models are applied to the Mitchell River basin in Queensland, Australia. • MIP models get shorter execution times and higher quality solutions. • The MAMP-E model obtains higher ecological benefits than the MAMP model. Planning for management actions that address threats to biodiversity is important for securing its long term persistence. However, systematic conservation planning (SCP) has traditionally overlooked this aspect and just focused on identifying priority areas without any recommendation on actions needed. This paper develops a mixed integer mathematical programming (MIP) approach for the multi-action management planning problem (MAMP), where the goal is to find an optimal combination of management actions that abate threats, in an efficient way while accounting for connectivity. An extended version of the MAMP model (MAMP-E) is also proposed that adds an expression for minimizing fragmentation between different actions. To evaluate the efficiency of the two models, they were applied to a case study corresponding to a large area of the Mitchell River in Northern Australia, where 45 species of freshwater fish are exposed to the presence of four threats. The evaluation compares our exact MIP approach with the conservation planning software Marxan and the heuristic approach developed in Cattarino et al. (2015). The results obtained show that our MIP models have three advantages over their heuristic counterparts: shorter execution times, higher solutions quality, and a solution quality guarantee. Hence, the proposed MIP methodology provides a more effective framework for addressing the multi-action conservation problem. [ABSTRACT FROM AUTHOR]