• Energy Research

A framework for identifying species that may become invasive under future climate conditions is presented, based on invader attributes and biogeography in combination with projections of future climate. We illustrate the framework using the CLIMEX niche model to identify future climate suitability for three species of Hawkweed that are currently present in the Australian Alps region and related species that are present in the neighbouring region. Potential source regions under future climate conditions are identified, and species from those emerging risk areas are identified. We use dynamically downscaled climate projections to complement global analyses and provide fine-scale projections of suitable climate for current and future (2070–2099) conditions at the regional scale. Changing climatic conditions may reduce the suitability for some invasive species and improve it for others. Invasive species with distributions strongly determined by climate, where the projected future climate is highly suitable, are those with the greatest potential to be future invasive species in the region. As the Alps region becomes warmer and drier, many more regions of the world become potential sources of invasive species, although only one additional species of Hawkweed is identified as an emerging risk. However, in the longer term, as the species in these areas respond to global climate change, the potential source areas contract again to match higher altitude regions. Knowledge of future climate suitability, based on species-specific climatic tolerances, is a useful step towards prioritising management responses such as targeted eradication and early intervention to prevent the spread of future invasive species.

Changes to the frequency of fire due to management decisions and climate change have the potential to affect the flammability of vegetation, with long-term effects on the vegetation structure and composition. Frequent fire in some vegetation types can lead to transformational change beyond which the vegetation type is radically altered. Such feedbacks limit our ability to project fuel loads under future climatic conditions or to consider the ecological tradeoffs associated with management burns. We present a “pathway modelling” approach to consider multiple transitional pathways that may occur under different fire frequencies. The model combines spatial layers representing current and future fire danger, biomass, flammability, and sensitivity to fire to assess potential future fire activity. The layers are derived from a dynamically downscaled regional climate model, attributes from a regional vegetation map, and information about fuel characteristics. Fire frequency is demonstrated to be an important factor influencing flammability and availability to burn and therefore an important determinant of future fire activity. Regional shifts in vegetation type occur in response to frequent fire, as the rate of change differs across vegetation type. Fire-sensitive vegetation types move towards drier, more fire-adapted vegetation quickly, as they may be irreversibly impacted by even a single fire, and require very long recovery times. Understanding the interaction between climate change and fire is important to identify appropriate management regimes to sustain fire-sensitive communities and maintain the distribution of broad vegetation types across the landscape.

The interaction of gradual climate trends and extreme weather events since the turn of the century has triggered complex and, in some cases, catastrophic ecological responses around the world. We illustrate this using Australian examples within a press–pulse framework. Despite the Australian biota being adapted to high natural climate variability, recent combinations of climatic presses and pulses have led to population collapses, loss of relictual communities and shifts into novel ecosystems. These changes have been sudden and unpredictable, and may represent permanent transitions to new ecosystem states without adaptive management interventions. The press–pulse framework helps illuminate biological responses to climate change, grounds debate about suitable management interventions and highlights possible consequences of (non-) intervention.

Observed increases in the frequency and intensity of heatwave events, together with the projected acceleration of these events worldwide, has led to a rapid expansion in research on the health impacts of extreme heat.To examine how research on heatwaves and their health-related impact is distributed globally.A systematic review was undertaken. Four online databases were searched for articles examining links between specific historical heatwave events and their impact on mortality or morbidity. The locations of these events were mapped at a global scale, and compared to other known characteristics that influence heat-related illness and death.When examining the location of heatwave and health impact research worldwide, studies were concentrated on mid-latitude, high-income countries of low- to medium-population density. Regions projected to experience the most extreme heatwaves in the future were not represented. Furthermore, the majority of studies examined mortality as a key indicator of population-wide impact, rather than the more sensitive indicator of morbidity.While global heatwave and health impact research is prolific in some regions, the global population most at risk of death and illness from extreme heat is under-represented. Heatwave and health impact research is needed in regions where this impact is expected to be most severe.

Input data aggregation affects crop model estimates at the regional level. Previous studies have focused on the impact of aggregating climate data used to compute crop yields. However, little is known about the combined data aggregation effect of climate (DAEc) and soil (DAEs) on irrigation water requirement (IWR) in cool-temperate and spatially heterogeneous environments. The aims of this study were to quantify DAEc and DAEs of model input data and their combined impacts for simulated irrigated and rainfed yield and IWR. The Agricultural Production Systems sIMulator Next Generation model was applied for the period 1998-2017 across areas suitable for potato (Solanum tuberosum L.) in Tasmania, Australia, using data at 5, 15, 25 and 40 km resolution. Spatial variances of inputs and outputs were evaluated by the relative absolute difference (rAD¯) between the aggregated grids and the 5 km grids. Climate data aggregation resulted in a rAD¯ of 0.7-12.1%, with high values especially for areas with pronounced differences in elevation. The rAD¯ of soil data was higher (5.6-26.3%) than rAD¯ of climate data and was mainly affected by aggregation of organic carbon and maximum plant available water capacity (i.e. the difference between field capacity and wilting point in the effective root zone). For yield estimates, the difference among resolutions (5 km vs. 40 km) was more pronounced for rainfed (rAD¯ = 14.5%) than irrigated conditions (rAD¯ = 3.0%). The rAD¯ of IWR was 15.7% when using input data at 40 km resolution. Therefore, reliable simulations of rainfed yield require a higher spatial resolution than simulation of irrigated yields. This needs to be considered when conducting regional modelling studies across Tasmania. This study also highlights the need to separately quantify the impact of input data aggregation on model outputs to inform about data aggregation errors and identify those variables that explain these errors.

AbstractAnthropogenic climate change is causing a rise in global temperatures, with this trend projected to increase into the future. Rising temperatures result in an increase in the frequency and severity of heatwave events, with an associated increase in poor health outcomes for vulnerable individuals. This places an increasing strain on health care services. However, methods calculating future health care costs associated with this trend are poorly understood. We calculated health care costs attributable to heatwave events in Tasmania 2009–2019, using ambulance dispatches as a case study. We also modeled the expected health and economic burden for projected heatwave frequencies between 2010 and 2089. We developed our models based on two possible approaches to describing population adaptation to heatwaves—an adapted population calculated by determining heatwave episodes using a rolling baseline, and a non‐adapted population calculated by determining heatwave episodes using a static baseline. Using a rolling baseline calculation for 2010 to 2089, we estimated additional ambulance costs averaging AUD$57,147 per year and totaling AUD$4,571,788. For the same period using a static baseline, we estimated additional ambulance costs averaging AUD$517,342 per year and totaling AUD$41,387,349. While this method is suitable for estimating the health care costs associated with heatwaves, it could be utilized for estimating health care costs related to other climate‐related extreme events. Different methods of estimating heatwaves, modeling an adapted versus non‐adapted population, provide substantial differences in projected costs. There is potential for considerable health system cost savings when a population is supported to adapt to extreme heat.