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Insurance represents an integral part of local government risk management strategy. As climate change progresses, increased loss and risk related to extreme weather events such as tropical cyclones, could motivate insurers to withdraw from certain markets. In some regions, such a withdrawal represents an emergent risk that, when coupled with increasing populations and other climate change impacts, could leave local governments and ratepayers particularly vulnerable. This paper investigates such a scenario and its ramifications in the context of a region particularly vulnerable to climate change, through an exploration of the degree that consideration of emergent risks, such as loss of insurance, and the potential application of insurance alternatives influence Queensland local government risk management. The study finds little appreciation amongst government officials of emergent risk implicit in extreme weather events such as cyclones, little understanding of the nuances of risk transfer mechanisms beyond familiar traditional insurance and disaster funding mechanisms, and by default, a lack of appreciation of the relationship between the two. A lack of resource and leadership with respect to emergent risk, and an absence of dialogue between insurance brokers and local government concerning climate change risk arise as the main reasons for this result. This research is significant because it challenges current local government risk management practice through an exploration of the risks inherent in the process itself. This has potential social, economic and ecological ramifications in drawing attention to aspects of possible “uninsurability” and prospects of alleviation thereto. Further research is recommended to consider the insurance industry’s part in this study’s findings in order to inform current industry practice and thinking and further enlighten the causes of local government disengagement in this critical area.

The Paris Agreement commits state parties to a global adaptation goal and the inclusion of adaptation into their National Communications. This requires national level planning, monitoring and reporting and methods for effective global-scale adaptation tracking. However, unlike mitigation, where clear targets and goals have been agreed, adaptation is a process with varied and changing goals and risk context. Assessing adaptation plans and strategies can provide valuable insights into ongoing adaptation policy, because the plans give good indications of priorities and institutional thinking. To assess how adaptation planning aligns to the Paris Agreement, this paper used Article 7 of the agreement to develop criteria and applied these to assess national adaptation plans and strategies available in English from 36 least developed, 8 developing and 10 developed countries. The results suggest that adaptation planning aligned to the Paris Agreement can help bring a different focus to development pathways that promotes synergies rather than trade-offs between environmental, social and economic goals. Importantly, tracking adaptation planning can help ensure the continued mobilisation of the parties, guide adaptation planning nationally and locally, and support global-scale consistency in planning and action.

Real-world experience underscores the complexity of interactions among multiple drivers of climate change risk and of how multiple risks compound or cascade. However, a holistic framework for assessing such complex climate change risks has not yet been achieved. Clarity is needed regarding the interactions that generate risk, including the role of adaptation and mitigation responses. In this perspective, we present a framework for three categories of increasingly complex climate change risk that focus on interactions among the multiple drivers of risk, as well as among multiple risks. A significant innovation is recognizing that risks can arise both from potential impacts due to climate change and from responses to climate change. This approach encourages thinking that traverses sectoral and regional boundaries and links physical and socio-economic drivers of risk. Advancing climate change risk assessment in these ways is essential for more informed decision making that reduces negative climate change impacts. © 2021 The Authors

Urban food systems are connected with several pressing issues, including urban population growth, resource scarcity, and climate change. To cope within these issues, urban food systems need to become more sustainable in their practices, as well as resilient in the face of extreme weather events. While scholars have started to investigate this topic, no comprehensive analysis has yet addressed what entails sustainable and resilient urban food systems. Through a systematic review of the literature, this paper aims to improve our understanding of the key components of sustainable and resilient urban food systems. This study reviewed 53 publications and identified components related to the health, social, economy, environment, and governance domains. Only 5 of the works included in the review discussed sustainability and resilience to the impacts of climate change in urban food systems simultaneously, so there is an opportunity for original research and analysis. The most frequently identified components of urban food systems relate to: access to healthy food; connectivity between urban and rural areas; having a strong local food economy and food production; reducing food waste; and, having active participation of all actors in decision making. There is some level of consensus on linking sustainability and resilience, but diversity in food sources and the development of social capabilities need to be emphasised for climate change adaptation.

This study presents a meta-analysis of the economic values of global forest ecosystem services. The meta-analysis is conducted based on data from primary studies published between 1990 and 2018. The value-estimates from those studies are standardized into international currency units i.e. US dollar/ha/year using the purchasing power parity of countries at 2017 price levels. This standardization results in a database of 261 eligible primary studies and 758 value-estimates or observations. The study reveals large variations in the reported economic values of forests and the ecosystem services that they provide. Results from the meta-regression indicate a range of drivers that influence these economic values, including GDP per-capita, proportion of forest cover, continental location, type of forest, ecological zone, forest area, ecosystem services being valued and the valuation method employed. The meta-regression results also indicate the importance of valuing multiple ecosystem services together, rather than valuing specific services separately. The danger with the latter approach is that valuation studies can inadvertently suggest industrial plantation forests, with harvesting for timber or bio-mass energy, have the greatest economic value. However, such studies do not properly consider trade-offs inherent in the management of these types of forests; namely the loss of multiple ecosystem services that are provided by more natural forests. These findings contribute to the literature evaluating the economic values of global forest ecosystem services by conveying relevant information regarding the divergence of the economic values associated with different forest features, thus helping to inform forest management.

Formal protected areas are a critical conservation measure so long as their tenure is defined and secure and they are well managed. Protected areas in developed countries are assumed to meet these criteria and therefore have not attracted the level of attention given to the adequacy of protected areas in developing countries. We investigate this assumption using as a case study the southern temperate rainforests of Tasmania, Australia. We examine the extent to which these rainforests are protected from potential exposure to mining, commercial logging and climate change. We analyse the tenure of Tasmania's rainforests and identify the protected area categories that prohibit or allow mining or logging. We also model the potential distribution of Nothofagus cunninghamii, a dominant rainforest canopy tree species, to future climate and compare this with modelled current and future forest fire danger index. Results showed that 90% of the total area of Tasmanian rainforest (715,773 ha− 1) is in a reserve. However, the area of rainforest in reserves secured from mining and/or commercial logging is only 47% (335,863 ha− 1) as 43% (308,897 ha− 1) is in a reserve category where these land uses are permitted. The protected area category with the highest level of protection, prohibiting all mining and logging, is the Tasmanian Wilderness World Heritage Area which encompasses 325,920 ha− 1 of temperate rainforest. During a recent legislative review, 66,012 ha− 1 of rainforest in protected areas was downgraded to a reserve category that permits logging or mining. A key conservation instrument therefore is the Management Plan for the World Heritage Area as it overrides land use activities otherwise permitted including the 21,257 ha− 1 which is on a State-defined land tenure that allows for logging or mining. Climate change impacts, as modelled, suggest the main conservation challenges are in maintaining the integrity of the remaining intact rainforest blocks and better managing ignitions from lightning strikes and arsonists in the coniferous and alpine rainforests. Allowing structural degradation and fragmentation to intact rainforest blocks will reduce their capacity to buffer meso-climatic variability and resist fire events thereby undermining their ecosystem integrity. Noting that Aichi Target 11 includes the requirement that reserves are effectively managed, our case study highlights that assessing the effectiveness of a reserve system is not necessarily a straightforward matter as governance systems and regulatory frameworks involve a mix of international obligations, national and subnational policies and statutes, along with other agreements, administrative arrangements and plans of management, which can provide for a range of land use activities and be subject to modification over time.

The long-term goal of containing average warming below the 2 °C limit requires deep cuts in emissions from all sectors. The fast growing global aviation industry has committed to reduce carbon emissions. Carbon offsetting is an integral element of the sector's strategy. Already, airlines offer voluntary carbon offsetting to those customers who wish to mitigate the impact of their travel. To ensure carbon offsetting can make a meaningful and credible contribution, this paper first discusses the science behind ‘carbon offsetting’, followed by the associated policy perspective. Then, against the context of different aviation emissions pathways, the paper provides empirical evidence of current airline practices in relation to offsetting mechanisms and communication. Building on these insights, the challenges of reducing aviation emissions and using carbon credits to compensate for ongoing growth are discussed. The paper concludes by proposing five principles of best practice for carbon offsetting that airlines can use as a basis to develop credible emissions strategies, and that could inform the sectoral framework currently being developed by leading aviation organisations.

Vegetated coastal wetlands, including seagrass, saltmarsh and mangroves, are threatened globally, yet the need to avert these losses is poorly recognized in international policy, such as in the Convention on Biological Diversity and the United Nations (UN) Sustainable Development Goals. Identifying the impact of overlooking coastal wetlands in ecosystem assessment frameworks could help prioritize research efforts to fill these gaps. Here, we examine gaps in the recognition of coastal wetlands in globally applicable ecosystem assessments. We address both shortfalls in assessment frameworks when it comes to assessing wetlands, and gaps in data that limit widespread application of assessments. We examine five assessment frameworks that track fisheries, greenhouse gas emissions, ecosystem threats, and ecosystem services. We found that these assessments inform management decisions, but that the functions provided by coastal wetlands are incompletely represented. Most frameworks had sufficient complexity to measure wetland status, but limitations in data meant they were incompletely informed about wetland functions and services. Incomplete representation of coastal wetlands may lead to them being overlooked by research and management. Improving the coverage of coastal wetlands in ecosystem assessments requires improving global scale mapping of wetland trends, developing global-scale indicators of wetland function and synthesis to quantitatively link animal population dynamics to wetland trends. Filling these gaps will help ensure coastal wetland conservation is properly informed to manage them for the outstanding benefits they bring humanity.

Advances in computing power and infrastructure, increases in the number and size of ecological and environmental datasets, and the number and type of data collection methods, are revolutionizing the field of Ecology. To integrate these advances, virtual laboratories offer a unique tool to facilitate, expedite, and accelerate research into the impacts of climate change on biodiversity. We introduce the uniquely cloud-based Biodiversity and Climate Change Virtual Laboratory (BCCVL), which provides access to numerous species distribution modelling tools; a large and growing collection of biological, climate, and other environmental datasets; and a variety of experiment types to conduct research into the impact of climate change on biodiversity.Users can upload and share datasets, potentially increasing collaboration, cross-fertilisation of ideas, and innovation among the user community. Feedback confirms that the BCCVL's goals of lowering the technical requirements for species distribution modelling, and reducing time spent on such research, are being met. BCCVL facilitates and expedites modelling of climate change's impact on biodiversity.BCCVL integrates numerous species distribution modelling tools and myriad datasets.BCCVL negates the need for advanced programming and modelling expertise.BCCVL allows for increases in productivity and complexity of experimental design.BCCVL facilitates the sharing of data promoting transparency in the research process.

Rural communities in Pacific small island states, which rely directly and acutely on the benefits from ecosystem services, face a range of interlinking threats to their management of natural resources, exacerbated by climate change-related risks, all against the backdrop of rapid social and economic transition. Appropriate and sufficient community adaptation responses are required to maintain habitats and sustain livelihoods. Adaptation responses are mediated through often competing subjective discourses. We used Q-method to reveal discourses within a subsistence community in Vanuatu and amongst associated stakeholders. We revealed three discourses, which we called Strong Kastom, Kastom + Health and Tentative Modernity. When we compared stakeholder socio-demographic attributes we found a statistically significant gender difference between membership of Strong Kastom, which was skewed towards men and Tentative Modernity, which was skewed towards women. We also found that external practitioners were weighted away from Tentative Modernity. Our results suggest ecosystem-based adaptations to climate change will likely resonate with the community if they support customary natural resource knowledge and management, and provide opportunities for generating income, and promoting gender equity in decision-making. Our results also suggest external practitioners may not consider income generation to be sufficiently important to community resilience.

Planning and decision-making vastly benefit from a holistic and systematic understanding of the long-term impacts of climate change and other non-climatic stressors on the health and resilience of coral reef ecosystems, and the efficacy of adaptation strategies and management interventions on mitigating these impacts and maintaining ecosystem condition and associated ecosystem service. This study reports on an approach to modelling coral reef stressors and possible adaptation interventions using the coral reef ecosystem of Port Resolution on Tanna Island, Vanuatu as the case study serving as a microcosm of endangered Pacific Small Island Developing States (SIDS). A novel participatory modelling framework was developed and followed in a stepwise manner to integrate local and long-term climate change pressures by coupling structural analysis and the Bayesian Network (BN) techniques. The BN model was quantified through an advanced consolidated data-induced, evidence-based, and expert-driven approach that incorporated: (1) projections of future climate conditions and changing human activities; (2) the influences of multiple stressors including physical environmental and sociological factors; and (3) spatial variability in the key processes and variables. The first and second phases conceptualised the whole system by providing a graphical presentation of system variables within the Driver-Pressure-State-Impact (DPSI) framework using the structural analysis technique. In the third phase, the BN technique was used to integrate the outcomes of multidisciplinary assessments and analysis with experts’ opinion. The BN modelling phase was completed based on evidence extracted from literature which reported the results of regional and downscaled climate models, GIS-based analysis, parametrised data obtained from the region, and tacit knowledge elicited from experts. The validated model was employed to anticipate the future health and resilience condition of coral reefs under different sets of climatic trajectories and adaptive responses scenarios. The results predict the risks to the health and resilience of the Port Resolution coral reef system from the adverse impacts of climate change and harmful human activities and the possible success of adaptations strategies. A sobering conclusion was that despite the current satisfactory condition of coral reefs in the case study zone, their health and resilience would be severely threatened by 2070 in the absence of implementing adaptation strategies and associated sustainable management interventions.

In pursuit of a more robust provenance in the field of species distribution modelling, an extensive literature search was undertaken to find the typical default values, and the range of values, for configuration settings of a large number of the most commonly used statistical algorithms available for constructing species distribution models (SDM), as implemented in the R script packages (such as Dismo and Biomod2) or other species distribution modelling programs like MaxEnt. We found that documentation of SDM algorithm configuration option settings in the SDM literature is, overall, very uncommon, and the justifications for these settings were minimal, when present. Such settings were often the R default values, or were the result of trial and error. This is potentially concerning since: (i) it detracts from the robustness of the provenance for such SDM studies; (ii) a lack of documentation of configuration option settings in a paper prevents the replication of an experiment, which contravenes one of the main tenets of the scientific method; (iii) inappropriate or uninformed configuration option settings are particularly concerning if they represent a poorly understood ecological variable or process, and if the algorithm is sensitive to such settings, this could result in erroneous and/or unrealistic SDMs. Therefore, this study sets out to comprehensively test the sensitivity of eight widely used SDM algorithms to variation in configuration options settings: MaxEnt, Artificial Neural Network (ANN), Generalized Linear Model (GLM), Generalized Additive Model (GAM), Multivariate Adaptive Regression Splines (MARS), Flexible Discriminant Analysis (FDA), Surface Range Envelope (SRE) and Classification tree analysis (CTA). A process of expert elicitation was used to derive a range of appropriate values with which to test the sensitivity of our algorithms. We chose to use species occurrence records for two species - Koala (Phascolartos cinereus) and Thorny Devil (Moloch horridus) - in order to investigate how algorithm sensitivity depends on the species being modelled. Results were assessed by comparing the modelled distribution of the control SDM (default settings) to the modelled distribution from each sensitivity test SDM (i.e. non-default configuration settings). This was done using the visual and statistical measures of predictive performance available in the Biodiversity and Climate Change Virtual Laboratory (BCCVL), including the area under the (receiver operating characteristic) curve. The aim of our study was to be able to draw conclusions as to how the sensitivity of SDM algorithms to their configuration option settings may detract from the reliability of SDM results, given the often unjustified and unscrutinized use of the default settings, and generally infrequent and largely perfunctory attendance to this issue in most of the published SDM literature. Our results indicate that all of the algorithms tested showed sensitivity to alternative (non-default) values for some of their configuration settings and that often this sensitivity is species-dependent. Therefore we can conclude that the choice of configuration settings in these widely used SDM algorithms can have a large impact on the resulting projected distribution. This has important ramifications for decision-making and policy outcomes wherever SDMs are used to inform species and biodiversity management plans and policy settings. This study demonstrates that assigning suitable values for these settings is a very important consideration and as such should always be published along with the model. Documenting all configuration settings is necessary to increase the scientific robustness, transparency and reproducibility of species distribution modelling studies.

A small series of recent monitoring studies has reported major declines for many native mammal species in localised regions in northern Australia. However, the broader spatial context of these studies is uncertain. This study aims to assess the extent and timing of change in mammal status across a broad area of northern Australia (the monsoonal tropics of the Northern Territory). Indigenous information about terrestrial native mammal fauna (excluding bats) was compiled from a large series of interviews conducted across Indigenous communities. A collection of mammal skins was used to help facilitate discussions and verify identifications. The resulting information was analysed with non-parametric statistics to test for changes in mammal status across different time periods, between different regions, and between different groups of mammal species. Declines were reported as extending from the earliest memory of Indigenous participants, but the rate of decline has increased recently. These changes were reported across all five regions within the broad study area and were greater for “critical weight range” species than for other species. Indigenous participants suggested several factors were associated with the changing status of species. The study’s results reveal a pattern of widespread decline in the mammal fauna of the monsoonal tropics of northern Australia, thereby corroborating the conclusions of recent more local wildlife monitoring studies. The study also demonstrates the value and capability of Indigenous ecological knowledge to complement and corroborate more intensive and local scientific studies. The results reinforce concern for the conservation status of the mammal fauna of northern Australia.

In the hue and cry about the ‘green economy’ leading up to Rio + 20 a number of simple points have been neglected. First, the purposes of the economy have been too narrowly conceived. Second, the role of demand management is vastly underplayed. Third, the assumptions about the nature of reality are inconsistent with contemporary science. Fourth, it is mired in a complex discourse about measurement, which fails to even recognize that all economies are dependent on living within Earth's biogeochemical constraints. Fifth, it uses a conceptual framework laid down in the 18th century and tries to apply it to the Anthropocene. The simple, but to many unthinkable, fact is that you cannot get to a flourishing or even sustainable Earth if you start with the assumptions of neo-classical economics. This is not to say that some of the neo-classical tools are not useful, but that they must be deployed in a framework that it does not and cannot supply.

Gross primary productivity (GPP) is a critical response variable for many environmental problems, including terrestrial carbon accounting and the calculation of catchment water balances. Various approaches for modelling GPP have been developed and applied at continental and landscapes scales, but little attention has been given to the sensitivity of GPP to the spatial scale of its driving variables. A key driving variable is surface radiation (Rs) which is influenced by both meso-scale factors (latitude, time of year, cloudiness) and the topographic variables of slope, aspect and horizon shading. We compared the sensitivity of modelled GPP to two different sources of surface radiation (Rs): (1) the ANUCLIM method which only captures the meso-scaled factors; and (2) the SRAD method which incorporates the topographic effects GPP was calculated using the radiation use efficiency (RUE) model (Roderick et al., 2001) to discern general patterns of vegetation productivity at a sub-catchment (i.e. sub-water shed) scale. The radiation use efficiency approach uses the normalized difference vegetation index (NDVI) derived from satellite data (MODIS TERRA), along with estimates of solar radiation at the top of the atmosphere (Ro) and canopy (Rs). In this approach, Ro and Rs capture the influence of diffuse irradiance in canopy photosynthesis and vegetation productivity respectively. This research showed that Rs calculated using the SRAD program provides important discrimination of GPP regimes at a sub-catchment scale, as the result of minimum and maximum daily radiation varying between shaded and exposed surfaces. However, mean daily radiation at a whole-of-catchment scale did not differ between the two sources as the differences in the minimum and maximum daily values tend to cancel each other out. Applications of GPP models therefore need to consider whether topographic factors are important and select the appropriate source of Rs values. GPP models should also reflect understanding of radiation use efficiency. However, further research is required especially with respect to the influence of water stress on plant response.

The paper demonstrates the need to integrate across information types (i.e. weather, climate, socio-economic, policy and ecology) to better inform those involved in decision-making for ecosystem management. The provision of climate information and an understanding of ecosystem responses to climate change and variability urgently need to underpin any planning for the future. Integrating climatic information into risk assessment frameworks and adaptation planning is essential as it will enable better informed decision making in planning to ensure the adequate provision of ecosystem services (water, food, air quality, shelter etc) and appropriate adaptation and mitigation strategies for the well being of both people and nature. A substantial mindset shift to fully recognize the fundamental role of ecosystems as life-supporting systems is urgently needed. The value given to ecosystems and the magnitude of effort to manage them has to be based on this mere fact and indeed, it should be an integral part of any climate change agreement.

There is considerable discussion about the relative importance of conserving high quality wilderness areas (i.e. large and intact landscapes) versus conserving areas with high biodiversity values. Places that are needed to achieve one aspect of biodiversity conservation are not necessarily optimal for another which can lead to conflict in assigning conservation priorities. However, both are important for biodiversity conservation, and carry social, economic, and ecological values. Investment in both (a) representation of elements of biodiversity (e.g. species, habitats) and (b) wilderness conservation is not only complementary but important for the long-term persistence of biodiversity. We develop two approaches to identify areas important for the conservation of biodiversity in terms of both wilderness quality and biodiversity representation, using Australia as a case study. We defined intact areas as sub-catchments with at least 70% or more vegetation that has not been subjected to extensive habitat loss and fragmentation as the result of land clearing. The first approach aims to achieve biodiversity representation goals in areas with intact native vegetation. The results of this approach would be extremely expensive to implement as they require a large portion of land. The second approach aims to achieve biodiversity representation goals anywhere across the landscape while placing a strong emphasis on identifying spatially compact intact areas. The results of this approach show the trade-offs between the economic costs of conservation and the size of conservation areas containing intact native vegetation. This manuscript provides a novel framework for identifying cost-effective biodiversity conservation priorities inclusive of wilderness quality.

We apply a method for forecasting carbon sequestration at the landscape-level, accounting for spatial and temporal scaling issues and develop formulae to incorporate spatial variability in growth and senescence functions. The effect of environmental variability was modelled by: (a) using a relationship between stand height at age 50 years and environmental characteristics; (b) adjusting the apparent age for different environments to reflect effects on growth rate; (c) adjusting age-dependent volume to reflect effects on potential biomass. Carbon sequestration for the next 250 years was forecast for a Eucalyptus regnans—dominated water catchment reserve in Australia; stand ages ranged from 20 to 450 years. In the absence of fire or succession after 2003, the total carbon sequestered in the E. regnans stands increased by 130(±65) t-C/ha (10.3%) to a peak of 1275(±130) t-C/ha in the year 2130(±50), followed by a net efflux of carbon. However, with fire or species succession, the mixture of young and old stands maintains a long term, stable amount of sequestered carbon. A gauge of the magnitude of the bias in the landscape-level carbon accounts arising from spatial averaging of the model’s input data was obtained. Comparison of results using different parameter settings for characteristics such as senescence and understorey biomass, revealed where more field data would allow both the timing and size of the maximal carbon sequestration, and the size of the ensuing net efflux of carbon, to be determined more accurately.

A study was undertaken to explore the relationship between backscattering coefficients from a Japanese Earth Resources Satellite synthetic aperture radar (JERS-1 SAR) image and aboveground biomass sampled at 12 field plots located in Murramarang National Park, New South Wales, Australia. This is the first such investigation in Australian Eucalyptus forests. From the field survey we obtained tree and coarse woody debris (CWD) measurements for eight forested, two paddock tree and two grass (effectively zero biomass) plots. Total aboveground and component biomass were estimated for all plots using allometric equations. Live aboveground woody biomass ranged from 0 to 610 t ha−1. The mean JERS-1 SAR backscattering coefficients for the field plot areas ranged from −12.4 to −7.0 dB. The results show positive linear trends between backscattering coefficients and the biomass components of dry Eucalyptus forest. The strongest trend was produced with small branch (2 cm) biomass estimates (r2=0.84). The biomass saturation level for the JERS-1 SAR data may be higher than estimated by other studies (possibly up to 600 t ha−1), although this trend was not statistically confirmed due to the small sample size (n=8). The results suggest that estimation of forest biomass for biomass inventories in Australia might be possible using satellite radar data when landscape characteristics such as topography, surface water, and forest structure are taken into account.

The terrestrial and aquatic attributes of 70 farm dams and five semi-natural waterbodies in the upper Shoalhaven catchment, south-eastern Australia, were examined. Relationships between habitat attributes, frog species richness and the presence of individual species were explored using mixed and logistic models. A positive relationship was found between the extent of native canopy cover in the surrounding landscape and frog species richness, and the occurrence of Litoria peronii and Uperoleia laevigata at farm dams. Annual mean temperature was negatively associated with the occurrence of L. peronii and L. verreauxii, but positively associated with Crinia parinsignifera. Extent of bare ground in the riparian zone and extent of emergent vegetation cover at the water's edge were also useful habitat predictors for several species. Results demonstrate that consideration must be given to both the aquatic and terrestrial environment to develop an understanding of factors influencing frog populations in modified environments and that these factors may vary from species to species. A comparison of species richness and individual models demonstrates that there are limitations associated with reliance upon species richness data to achieve conservation outcomes. Important habitat attributes of the environment may be masked at the species richness level as a result of contrasting responses between individual species.

It is generally recognized that plants are genetically adapted to prevailing climate. However, there are very few genecological studies that quantify these relationships. Planting stock is often moved across environmental gradients with little knowledge of the ecological risks. For long-lived species (e.g. forest trees) this introduces risks of increased mortality, lowered potential growth rates, and increased susceptibility to insects and diseases. Seedwhere is a computer-based tool to support decisions on moving plant material across environmental gradients. The Gower similarity metric has been invoked as an Avenue extension in the ARCVIEW Geographic Information System. The program can be used to map the similarity of potential seed collection sites across large regions. Considerable effort has gone into developing the required GIS database for the Great Lakes region of North America. Such data are becoming increasingly available in many parts of the world. Some example applications of Seedwhere are provided for the Great Lakes region. While no panacea for this complex and large problem, the seedwhere tool provides a quantitative approach to visualizing the issue that should help resource managers.

Multi-aged stands are not a common structural type of mountain-ash forest in the Central Highlands of Victoria, southeastern Australia, but they are nevertheless important, particularly as habitat for wildlife. Extensive field data and information generated from spatial models of climate, topography and radiation regimes were examined to identify factors which related to the occurrence of stands of multi-aged mountain-ash forest. The probability of occurrence of multi-aged stands increased significantly (p

New algorithms are described that provide a maximum likelihood function fit, assuming only that the function is monotonic. Methods are given for both one and two independent variables. In the case of one independent variable, the function can be piecewise monotonic. A trend line or trend contour can be constructed, based on the median of the values. Percentile lines provide the equivalent of confidence bands about the trend. The value of the maximum likelihood can be used to compare alternative models. Some advantages of these algorithms for ecological analyses in vegetation science are discussed.

An assessment is made of the representativeness of the Wet Tropics World Heritage property of north-east Queensland, Australia. The relevance of this feature to the World Heritage criteria is discussed. Computer-based spatial data sets are used to provide a sample of the distribution of key environmental factors at both continental and regional scales. Numerical classification techniques are applied to generate environmental groups from pattens in the distribution of these environmental factors. An evaluation is presented of the representation of these groups within the World Heritage property, in the context of present and potential tropical forest cover.