Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks

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.     

Response of tree growth to a changing climate in boreal central Canada: A comparison of empirical,process-based,and hybrid modelling approaches

The impact of 2 × CO₂ driven climate change on radial growth of boreal tree species Pinus banksiana Lamb., Populus tremuloides Michx. and Picea mariana (Mill.) BSP growing in the Duck Mountain Provincial Forest of Manitoba (DMPF), Canada, is simulated using empirical and process-based model approaches. First, empirical relationships between growth and climate are developed. Stepwise multiple-regression models are conducted between tree-ring growth increments (TRGI) and monthly drought, precipitation and temperature series. Predictive skills are tested using a calibration–verification scheme. The established relationships are then transferred to climates driven by 1× and 2 × CO₂ scenarios using outputs from the Canadian second-generation coupled global climate model. Second, empirical results are contrasted with process-based projections of net primary productivity allocated to stem development (NPP_s). At the finest scale, a leaf-level model of photosynthesis is used to simulate canopy properties per species and their interaction with the variability in radiation, temperature and vapour pressure deficit. Then, a top-down plot-level model of forest productivity is used to simulate landscape-level productivity by capturing the between-stand variability in forest cover. Results show that the predicted TRGI from the empirical models account for up to 56.3% of the variance in the observed TRGI over the period 1912–1999. Under a 2 × CO₂ scenario, the predicted impact of climate change is a radial growth decline for all three species under study. However, projections obtained from the process-based model suggest that an increasing growing season length in a changing climate could counteract and potentially overwhelm the negative influence of increased drought stress. The divergence between TRGI and NPP_s simulations likely resulted, among others, from assumptions about soil water holding capacity and from calibration of variables affecting gross primary productivity. An attempt was therefore made to bridge the gap between the two modelling approaches by using physiological variables as TRGI predictors. Results obtained in this manner are similar to those obtained using climate variables, and suggest that the positive effect of increasing growing season length would be counteracted by increasing summer temperatures. Notwithstanding uncertainties in these simulations (CO₂ fertilization effect, feedback from disturbance regimes, phenology of species, and uncertainties in future CO₂ emissions), a decrease in forest productivity with climate change should be considered as a plausible scenario in sustainable forest management planning of the DMPF.     

A comparison of four process-based models and a statistical regression model to predict growth of Eucalyptus globulus plantations

In forest management and ecological research, consideration of the impacts and risks of climate change or management optimisation is complex. Computer models have long been applied as tools for these tasks. Process-based forest growth models claim to overcome the limitations of empirical statistical models, but the capacity of different process-based models and modelling approaches have rarely been compared directly. This study evaluates stepwise multiple regression models in comparison to four process-based modelling approaches (3-PG, 3-PG+, CABALA and Forest-DNDC) for greenfield predictions of Eucalyptus globulus plantation growth from 2 to 8 years after planting throughout southern Australia.     

Assessing the past and future distribution and productivity of ponderosa pine in the Pacific Northwest using a process model, 3-PG

Climate variability at decadal scales influences not only the growth of widely distributed species such as Pinus ponderosa, but also can have an effect on the timing and severity of fire and insect outbreaks that may alter species distributions. In this paper, we present a spatial modelling technique to assess the influence of climatic variability on the annual productivity of P. ponderosa in the Pacific Northwest (PNW) of North America over the past 100 years and infer how a sustained change in climate might alter the geographic distribution of this species across defined ecotones. Field observations were used to establish criteria for P. ponderosa dominance including: (1) maximum summer leaf area index (LAI), ranges between 1.5 and 2.5; (2) 80% of available soil water is depleted during summer months; and (3) soil water will return to full capacity at least once during the year. Where these three criteria were not met, eventual replacement of P. ponderosa would be predicted. We utilized a simple physiological model, Physiological Principles for Predicting Growth (3-PG) to predict annual variation in LAI from climatic data provided by the Oregon Climate Service over the period from 1900 to 2000 and from broad scale 0.5°-spatial resolution future climate projections produced by the Hadley Climate Center, UK. From these simulations we produced a series of maps that display predicted shifts of zones where ponderosa pine might be expected to contract or expand its range if modeled climatic conditions at annual and decadal intervals were sustained. From the historical simulations, the most favorable year for pine dominance was 1958 and the least favorable, 1924. The most favorable decade was in the 1900s and the least favorable in the 1930s. The future predictions indicate a reduction in the current range of the P. ponderosa type along the western Cascade Range however, an increase along the east side and inland PNW. The model predicts that pine dominance should increase between 5 and 10% over the next century, mainly in inland Oregon, Idaho, and Washington.     

Temporal limits to simulating the future spread pattern of invasive species: Buddleja davidii in Europe and New Zealand

The spread of invasive species is a major ecological and economic problem. Dynamic spread modelling is a potentially valuable tool to assist regional and central government authorities to monitor and control invasive species. To date a lack of suitable data has meant that most broad scale dispersal models have not been validated with independent datasets, and so their predictive ability and reliability has remained unscrutinised. A dynamic, stochastic dispersal model of the widely invasive plant Buddleja davidii was calibrated on European spread data and then used to project the temporal progression of B. davidii's distribution in New Zealand, starting from several different historical distributions. To assess the model's performance, we constructed an occupancy map based on the average number of simulation realisations that have a population present. The application of Receiver Operating Characteristic (ROC) curves to occupancy maps is introduced, but with specificity substituted by the proportion of available area used in a realisation. A derivative measure, the partial area under these curves when assessed through time (pAUC), is introduced and used to assess overall performance of the spread model. The model was able to attain a high level of model sensitivity, encompassing all of the known locations within the occupancy envelope. However, attempting to simulate the spread of this invasive species beyond a decade had very low model specificity. This is due to several factors, including the exponential process of spread (the further a population spreads the more sites exist from which it can spread stochastically), and the Markovian chain property of the stochastic system whereby differences between realisations compound through time. These features are seen in many reports of spread models, without being explicitly acknowledged. Our measure of pAUC through time allows a model's temporal performance and its specificity to be simultaneously assessed. While the rapid deterioration in model performance limits the utility of this type of modelling for forecasting long-term broad-scale strategic management of biological invasions, it does not necessarily limit its attractiveness for informing smaller scale and shorter term invasion management activities such as surveillance, containment and local eradication.     

A Voronoi diagram based population model for social species of wildlife

A population model is presented that accounts for spatial structure within habitat patches. It is designed for social species of wildlife that form social group home ranges that are much smaller than patch size. The model represents social group home ranges by Voronoi regions that tessellate a patch to form a Voronoi diagram. Neighbouring social groups are linked with habitat-confined shortest paths and form a dispersal network. The model simulates population dynamics and makes use of Voronoi diagrams and dispersal networks as a spatial component. It then produces density maps as outputs. These are maps that show predicted animal densities across the patches of a landscape. A construction procedure for the particular Voronoi diagram type used by the model is described. As a test case, the model is run for the squirrel glider (Petaurus norfolcensis), a small arboreal marsupial native to Australia. A time series of density maps are produced that show squirrel glider density changing across a landscape through time.     

Simple rules for ranking and optimally managing metapopulations

We present two ‘rules of thumb’ for metapopulation management. The first identifies an explicit formula for the persistence time of the population, and thus enables the population manager to form a priority species ranking by identifying those species most at risk of extinction. The second identifies an optimal management strategy that gives direction on how to alter the colonisation rate (creation or improvement of habitat corridors) and local extinction rate (restoring habitat quality or expanding habitat) in order to maximise the persistence time under a budgetary constraint. We employ a simple stochastic version of Levins (1969) metapopulation model, which is first calibrated to a more realistic spatial model. Our rules are tested on computer-generated patch networks and a model for malleefowl (Leipoa ocellata) in the Bakara region of South Australia.     

Impacts of Livestock Grazing and Tree Clearing on Birds of Woodland and Riparian Habitats

Abstract:  We investigated the impact of pastoral management on birds in subtropical grassy eucalypt woodland in southeastern Queensland, Australia, where the patterns of land management have made it possible to disentangle the effects of livestock grazing from those of tree clearing. We recorded changes in bird species composition, density, and relative abundance across two woodland habitat types (riparian and nonriparian) and two levels of clearing (wooded and nonwooded) and three levels of livestock grazing (low, moderate, and high) replicated over space (1000 km²) and time (2001–2002). We predicted that species that depend on understory vegetation would be most negatively affected by livestock grazing. A Bayesian generalized linear model showed that the level of grazing had the greatest effect when trees were present. When trees were absent, the impact of grazing was overshadowed by the effects of a lack of trees. Over 65% of species responded to different levels of grazing, and the abundance of 42% of species varied markedly with habitat and grazing. The most common response to grazing was high species relative abundance under low levels of grazing (28% of species), species absence at high levels of grazing (20%), and an increase in abundance with increasing grazing (18%). Despite having similar bird assemblages, the effect of grazing was stronger in riparian habitat than in adjacent woodland habitat. Our results suggest that any level of commercial livestock grazing is detrimental to some woodland birds, particularly the understory-dependant species, as predicted. Nevertheless, provided trees are not cleared, a rich and abundant bird fauna can coexist with moderate levels of grazing. Habitats with high levels of grazing, on the other hand, resulted in a species-poor bird assemblage dominated by birds that are increasing in abundance nationally .     

Modelling coupled peach tree-aphid population dynamics and their control by winter pruning and nitrogen fertilization

Nitrogen fertilization and winter pruning are commonly used to control crop production in peach [Prunus persica (L.) Batsch] orchards. They are also known to affect the dynamics of Myzus persicae (Sulzer) (Homoptera: Aphididae) aphid populations via bottom-up regulation processes. Interactions between crops and pests can cause complex system behaviour in response to management practices. An integrated approach will therefore improve the understanding of the effects of these two cultural practices on aphid and peach performances.We developed a simulation model that describes the cultural control of interacting peach tree and aphid population dynamics. It uses the principles of common trophic models while gathering available knowledge and explicit assumptions on peach and aphid functioning and the effects of cultural practices.The model was able to qualitatively reproduce the system behaviour observed in the field. It accounted for actions and feedback such as stimulation of foliar growth by winter pruning, consecutive aphid population increase, subsequent damage to foliage, and partial compensatory growth of foliage. The model also reproduced low losses in fruit production due to aphid infestations. However, it called for further integration of ‘long-term’ effects. Analysis of the model showed the complexity of peach tree and aphid responses to leaf N × winter pruning interactions. Simulations indicated that fruit production losses remained low within a range of realistic values of leaf N and pruning intensity, whereas manipulating peach and aphid dynamics, their interactions and their relationships to practices could result in higher losses.The model is useful to evaluate the relevance of cultural practices for a bottom-up regulation of aphid dynamics in crop-pest management. After considering other control methods and fruit quality, it can be used to find a combination of practices that optimises trade-offs between fruit production and environmental conservation goals. A modelling approach that links crop growth and pest population dynamics and integrates management practice effects has strong potential for improving crop-pest management in an integrated crop production context.     

Predicted Climate‐Driven Bird Distribution Changes and Forecasted Conservation Conflicts in a Neotropical Savanna

Abstract: Climate‐change scenarios project significant temperature changes for most of South America. We studied the potential impacts of predicted climate‐driven change on the distribution and conservation of 26 broad‐range birds from South America Cerrado biome (a savanna that also encompass tracts of grasslands and forests). We used 12 temperature or precipitation‐related bioclimatic variables, nine niche modeling techniques, three general circulation models, and two climate scenarios (for 2030, 2065, 2099) for each species to model distribution ranges. To reach a consensus scenario, we used an ensemble‐forecasting approach to obtain an average distribution for each species at each time interval. We estimated the range extent and shift of each species. Changes in range size varied across species and according to habitat dependency; future predicted range extent was negatively correlated with current predicted range extent in all scenarios. Evolution of range size under full or null dispersal scenarios varied among species from a 5% increase to an 80% decrease. The mean expected range shifts under null and full‐dispersal scenarios were 175 and 200 km, respectively (range 15–399 km), and the shift was usually toward southeastern Brazil. We predicted larger range contractions and longer range shifts for forest‐ and grassland‐dependent species than for savanna‐dependent birds. A negative correlation between current range extent and predicted range loss revealed that geographically restricted species may face stronger threat and become even rarer. The predicted southeasterly direction of range changes is cause for concern because ranges are predicted to shift to the most developed and populated region of Brazil. Also, southeastern Brazil is the least likely region to contain significant dispersal corridors, to allow expansion of Cerrado vegetation types, or to accommodate creation of new reserves.     

Using spatial models to establish climatic limiters of plant species’ distributions

Plant species’ climatic range limiters provide clues to reconstruct past climates, restore ecosystems, and manage agricultural systems. However, precise climatic limiters are unknown for many important species, and determining them typically involves long-term autecological studies. A new method presented here automatically and quantitatively infers limiters for a plant species using its documented, digitized distribution. The method uses available and accessible elevation and climate datasets from the US Geological Survey (USGS) and NOAA, along with common off-the-shelf (COTS) geographic information software technology (GIS) to determine which variables in the plant distribution climate space are actually limiting the range by restricting its movement into surrounding territory. The method utilizes precision climate interpolation allowing for independent variables in addition to latitude and longitude, via a software package developed at Australian National University (ANUSPLIN). For this first run, elevation and slope were included as independent variables for interpolating precipitation and temperature surfaces. The model defined limits for five Sonoran Desert plant species: Carnegiea gigantea, Cercidium microphyllum, Encelia farinosa, Ferocactus acanthodes, and Larrea tridentata. Results were tested against environmental factors outlined in autecological studies. Important model-derived climatic constraints to the distribution of C. gigantea include insufficient monsoon precipitation, low winter and monsoon temperatures, and excessive monsoon and fall precipitation. The distribution of C. microphyllum is constrained by cold winter and fall temperatures, excessive spring and summer precipitation and insufficient fall precipitation. E. farinosa is restricted by frigid winter temperatures and too much summer rainfall. Key factors limiting F. acanthodes are cold winter temperatures and inadequate fall and monsoon precipitation. An inordinate amount of precipitation during the summer, monsoon, and fall constrict the range of L. tridentata, along with an abnormally cool summer or monsoon. Results indicate that the method adequately resolves plant range limiters consistent with the autecological record. Future changes to the model are offered to improve results.     

Parasite transmission in a migratory multiple host system

A transmission model was devised for trichostrongyloid nematodes of saiga antelopes and domestic sheep in Kazakhstan. The framework extends previous models by including seasonal migration of saigas, contact with separate populations of sheep, and climate-driven stochasticity in herbage biomass and in the development, survival and migration onto herbage of free-living larvae. The model was parameterised for the contrasting life histories of Marshallagia, Haemonchus and Nematodirus, three important parasites of saigas and sheep in the region, and was successful at predicting broad qualitative patterns of infection dynamics in sheep and saigas. Parasite transmission between saigas and sheep was predicted to be most important for Marshallagia (from sheep to saigas in the south in winter, and onward transmission to sheep in the north in summer) and Haemonchus (from sheep in the north in summer via saigas to sheep further south in autumn). Model predictions for winter transmission of Marshallagia infection in saigas were consistent with field data, which showed that saigas culled before they have grazed the winter range carry lower burdens of this parasite than older animals. The model provides a mechanistic explanation for its predictions, which will assist hypothesis formation, and further the epidemiological basis of efforts to control parasite transmission between wildlife and livestock in both directions. A similar modelling approach could prove useful in other situations where detailed mechanistic models of parasite transmission are inappropriate in the face of parameter uncertainty and spatio-temporal variation in climate and host density. This is likely to include the majority of wildlife-parasite systems.     

Sanitary felling of Norway spruce due to spruce bark beetles in Slovenia: A model and projections for various climate change scenarios

A model is presented to predict sanitary felling of Norway spruce (Picea abies) due to spruce bark beetles (Ips typographus, Pityogenes chalcographus) in Slovenia according to different climate change scenarios. The model incorporates 21 variables that are directly or indirectly related to the dependent variable, and that can be arranged into five groups: climate, forest, landscape, topography, and soil. The soil properties are represented by 8 variables, 4 variables define the topography, 4 describe the climate, 4 define the landscape, and one additional variable provides the quantity of Norway spruce present in the model cell. The model was developed using the M5′ model tree. The basic spatial unit of the model is 1 km², and the time resolution is 1 year. The model evaluation was performed by three different measures: (1) the correlation coefficient (51.9%), (2) the Theil's inequality coefficient (0.49) and (3) the modelling efficiency (0.32). Validation of the model was carried out by 10-fold cross-validation. The model tree consists of 28 linear models, and model was calculated for three different climate change scenarios extending over a period until 2100, in 10-year intervals. The model is valid for the entire area of Slovenia; however, climate change projections were made only for the Maribor region (596 km²). The model assumes that relationships among the incorporated factors will remain unchanged under climate change, and the influence of humans was not taken into account. The structure of the model reveals the great importance of landscape variables, which proved to be positively correlated with the dependent variable. Variables that describe the water regime in the model cell were also highly correlated with the dependent variable, with evapotranspiration and parent material being of particular importance. The results of the model support the hypothesis that bark beetles do greater damage to Norway spruce artificially planted out of its native range in Slovenia, i.e., lowlands and soils rich in N, P, and K. The model calculation for climate change scenarios in the Maribor region shows an increase in sanitary felling of Norway spruce due to spruce bark beetles, for all scenarios. The model provides a path towards better understanding of the complex ecological interactions involved in bark beetle outbreaks. Potential application of the results in forest management and planning is discussed.     

Trophic ecology of large predatory reef fishes: energy pathways, trophic level, and implications for fisheries in a changing climate

Large predatory fishes are disproportionately targeted by reef fisheries, but little is known about their trophic ecology, which inhibits understanding of community dynamics and the potential effects of climate change. In this study, stable isotope analyses were used to infer trophic ecology of a guild of large predatory fishes that are targeted by fisheries on the Great Barrier Reef, Australia. Each of four focal predators (Plectropomus leopardus, Plectropomus maculatus, Lethrinus miniatus and Lutjanus carponotatus) was found to have a distinct isotopic signature in terms of δ¹³C and δ¹⁵N. A two-source mixing model (benthic reef-based versus pelagic) indicated that P. leopardus and L. miniatus derive the majority (72 and 62 %, respectively) of their production from planktonic sources, while P. maculatus and L. carponotatus derive the majority (89 and 74 %, respectively) of their production from benthic reef-based sources. This indicates that planktonic production is important for sustaining key species in reef fisheries and highlights the need for a whole-ecosystem approach to fisheries management. Unexpectedly, there was little isotopic niche overlap between three of four focal predators, suggesting that inter-specific competition for prey may be low or absent. δ¹⁵Nitrogen indicated that the closely related P. leopardus and P. maculatus are apex predators (trophic level > 4), while δ¹³C indicated that each species has a different diet and degree of trophic specialisation. In view of these divergent trophic ecologies, each of the four focal predators (and the associated fisheries) are anticipated to be differentially affected by climate-induced disturbances. Thus, the results presented herein provide a useful starting point for precautionary management of exploited predator populations in a changing climate.     

Modelling the impact of defoliation and leaf damage on forest plantation function and production

After presenting a short review of process-based model requirements to capture the plant dynamic response to defoliation, this paper describes the development and testing of a model of crown damage and defoliation for Eucalyptus. A model that calculates light interception and photosynthetic production for canopies that vary spatially and temporally in leaf area and photosynthetic properties is linked to the forest growth model CABALA. The process of photosynthetic up-regulation following defoliation is modelled with a simple conditional switch that triggers up-regulation when foliar damage or removal causes the ratio of functional leaf area to living tissue in the tree to change.We show that the model predicts satisfactorily when validated with trees of Eucalyptus nitens and Eucalyptus globulus from a range of sites of different ages, subject to different types of stress and different types of defoliation events (R² = 0.96 across a range of sites). However, the complexity of particular situations can cause the model to fail (e.g. very heavy defoliation events where branch death occurs).It is concluded that while the model will not cope with all situations, an appropriate level of generality has been captured to represent many of the physiological processes and feedbacks that occur following defoliation or leaf damage. This makes the model useful for guiding management interventions following pest attack and allows the development of scenarios including climate change impact analyses and decision-making on the merits of post-defoliation fertilisation to expedite recovery.     

Driving mechanisms of desertification process in the Horqin Sandy Land—a case study in Zhalute Banner, Inner Mongolia of China

Both natural and human factors contributing to desertification were examined to understand the driving mechanisms of the desertification process in Zhalute Banner, Inner Mongolia of China. The coefficient of variation (CV) and climate departure index (Z) were calculated to examine the fluctuations and trends of interannual variations of temperature and precipitation; TM remote sensing data was extracted to obtain the sandy land area; linear regression analysis was used to analyze climate changes and the socio-economic evolution over the years, and it was also used to standardize the variables, which included annual temperature, annual precipitation, human population, and livestock number, in order to measure the difference in the rate of change between climate and anthropogenic factors. The results showed that there was a rise of about 1.6°C in temperature but no significant change in precipitation from 1961 to 2000, which indicated a short-term climatic trend toward aridity in this area, a condition necessary for desertification. The fraction of precipitation in spring tended to increase whilst the fraction in autumn and winter decreased. Both the human population and livestock population had tripled and the cultivated area had doubled from 1961 to 2000, suggesting that socio-economic factors might have contributed more significantly to the desertification. Between 1988 and 1997, the sandy land area increased by 12.5%, nearly 2.4 times in the farming section. It could be concluded that the driving mechanisms of the desertification processes in Zhalute banner are mainly the policy of cropland expansion and the rising populations of humans and their livestock, which has affected the land use pattern in the past decades.     

Simulating soil organic matter with CQESTR (v. 2.0): Model description and validation against long-term experiments across North America

Soil carbon (C) models are important tools for examining complex interactions between climate, crop and soil management practices, and to evaluate the long-term effects of management practices on C-storage potential in soils. CQESTR is a process-based carbon balance model that relates crop residue additions and crop and soil management to soil organic matter (SOM) accretion or loss. This model was developed for national use in U.S and calibrated initially in the Pacific Northwest. Our objectives were: (i) to revise the model, making it more applicable for wider geographic areas including potential international application, by modifying the thermal effect and incorporating soil texture and drainage effects, and (ii) to recalibrate and validate it for an extended range of soil properties and climate conditions. The current version of CQESTR (v. 2.0) is presented with the algorithms necessary to simulate SOM at field scale. Input data for SOM calculation include crop rotation, aboveground and belowground biomass additions, tillage, weather, and the nitrogen content of crop residues and any organic amendments. The model was validated with long-term data from across North America. Regression analysis of 306 pairs of predicted and measured SOM data under diverse climate, soil texture and drainage classes, and agronomic practices at 13 agricultural sites having a range of SOM (7.3–57.9 g SOM kg⁻¹), resulted in a linear relationship with an r² of 0.95 (P < 0.0001) and a 95% confidence interval of 4.3 g SOM kg⁻¹. Using the same data the version 1.0 of CQESTR had an r² of 0.71 with a 95% confidence interval of 5.5 g SOM kg⁻¹. The model can be used as a tool to predict and evaluate SOM changes from various management practices and offers the potential to estimate C accretion required for C credits.     

A process-based population dynamics model to explore target and non-target impacts of a biological control agent

The risks and benefits associated with efforts to control invasive alien species using classical biological control are being subjected to increasing scrutiny. A process-based population dynamics model was developed to explore the interactions between a folivorous biological control agent, Cleopus japonicus, and its plant host Buddleja davidii. The model revealed that climate could have a significant impact upon the interactions between B. davidii and C. japonicus. At the coolest sites, the impact of C. japonicus on B. davidii was slowed, but it was still eventually capable of controlling populations of B. davidii. At the warmer sites where both B. davidii and C. japonicus grew faster, B. davidii succumbed rapidly to weevil damage. We hypothesise that barring an encounter with a natural enemy, C. japonicus will eventually be able to provide sustained control B. davidii throughout the North Island of New Zealand. The model scenarios illustrate the potential for the C. japonicus population to attain high densities rapidly, and to defoliate patches of B. davidii, creating the potential for spill-over feeding on non-target plants. The potential magnitude of this threat will depend partly on the climate suitability for C. japonicus, the pattern by which it migrates in response to a reduction in the available leaf resource, and the suitability of non-target plants as hosts. In all migration scenarios considered, the pattern of population growth and resource consumption by C. japonicus was exponential, with a strong tendency toward complete utilisation of resource patches more quickly at the warmer compared to colder sites. In addition to providing some useful hypotheses about the effects of climate on the biological control system, and the non-target risks, it also provides some insight into the mechanisms by which climate affects the system.     

A concept model to estimate the potential distribution of the Asiatic citrus psyllid (Diaphorina citri Kuwayama) in Australia under climate change—A means for assessing biosecurity risk

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.