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As atmospheric levels of CO(2) increase, reef-building corals are under greater stress from both increased sea surface temperatures and declining sea water pH. To date, most studies have focused on either coral bleaching due to warming oceans or declining calcification due to decreasing oceanic carbonate ion concentrations. Here, through the use of physiology measurements and cDNA microarrays, we show that changes in pH and ocean chemistry consistent with two scenarios put forward by the Intergovernmental Panel on Climate Change (IPCC) drive major changes in gene expression, respiration, photosynthesis and symbiosis of the coral, Acropora millepora, before affects on biomineralisation are apparent at the phenotype level. Under high CO(2) conditions corals at the phenotype level lost over half their Symbiodinium populations, and had a decrease in both photosynthesis and respiration. Changes in gene expression were consistent with metabolic suppression, an increase in oxidative stress, apoptosis and symbiont loss. Other expression patterns demonstrate upregulation of membrane transporters, as well as the regulation of genes involved in membrane cytoskeletal interactions and cytoskeletal remodeling. These widespread changes in gene expression emphasize the need to expand future studies of ocean acidification to include a wider spectrum of cellular processes, many of which may occur before impacts on calcification.

In this work we assess the pathways for environmental improvement by the coal utilization industry for power generation in Australia. In terms of resources, our findings show that coal is a long term resource of concern as coal reserves are likely to last for the next 500 years or more. However, our analysis indicates that evaporation losses of water in power generation will approach 1000 Gl (gigalitres) per year, equivalent to a consumption of half of the Australian residential population. As Australia is the second driest continent on earth, water consumption by power generators is a resource of immediate concern with regards to sustainability. We also show that coal will continue to play a major role in energy generation in Australia and, hence, there is a need to employ new technologies that can minimize environmental impacts. The major technologies to reduce impacts to air, water and soils are addressed. Of major interest, there is a major potential for developing sequestration processes in Australia, in particular by enhanced coal bed methane (ECBM) recovery at the Bowen Basin, South Sydney Basin and Gunnedah Basin. Having said that, CO2 capture technologies require further development to support any sequestration processes in order to comply with the Kyoto Protocol. Current power generation cycles are thermodynamic limited, with 35-40% efficiencies. To move to a high efficiency cycle, it is required to change technologies of which integrated gasification combined cycle plus fuel cell is the most promising, with efficiencies expected to reach 60-65%. However, risks of moving towards an unproven technology means that power generators are likely to continue to use pulverized fuel technologies, aiming at incremental efficiency improvements (business as usual). As a big picture pathway, power generators are likely to play an increasing role in regional development; in particular EcoParks and reclaiming saline water for treatment as pressures to access fresh water supplies will significantly increase.

Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve.

Vegetated coastal ecosystems, in particular mangroves, tidal marshes and seagrasses are highly efficient at sequestering and storing carbon, making them valuable assets for climate change mitigation and adaptation. The state of Queensland, in northeastern Australia, contains almost half of the total area of these blue carbon ecosystems in the country, yet there are few detailed regional or state-wide assessments of their total sedimentary organic carbon (SOC) stocks. We compiled existing SOC data and used boosted regression tree models to evaluate the influence of environmental variables in explaining the variability in SOC stocks, and to produce spatially explicit blue carbon estimates. The final models explained 75 % (for mangroves and tidal marshes) and 65 % (for seagrasses) of the variability in SOC stocks. Total SOC stocks in the state of Queensland were estimated at 569 ± 98 Tg C (173 ± 32 Tg C, 232 ± 50 Tg C, and 164 ± 16 Tg C from mangroves, tidal marshes and seagrasses, respectively). Regional predictions for each of Queensland's eleven Natural Resource Management regions revealed that 60 % of the state's SOC stocks occurred within three regions (Cape York, Torres Strait and Southern Gulf Natural Resource Management regions) due to a combination of high values of SOC stocks and large areas of coastal wetlands. Protected areas in Queensland play an important role in conserving SOC assets in Queensland's coastal wetlands. For example, ~19 Tg C within terrestrial protected areas, ~27 Tg C within marine protected areas and ~ 40 Tg C within areas of matters of State Environmental Significance. Using multi-decadal (1987-2020) mapped distributions of mangroves in Queensland; we found that mangrove area increased by approximately 30,000 ha from 1987 to 2020, which led to temporal fluctuations in mangrove plant and SOC stocks. We estimated that plant stocks decreased from ~45 Tg C in 1987 to ~34.2 Tg C in 2020, while SOC stocks remained relatively constant from ~107.9 Tg C in 1987 to 108.0 Tg C in 2020. Considering the level of current protection, emissions from mangrove deforestation are potentially very low; therefore, representing minor opportunities for mangrove blue carbon projects in the region. Our study provides much needed information on current trends in carbon stocks and their conservation in Queensland's coastal wetlands, while also contributing to guide future management actions, including blue carbon restoration projects.

AbstractClimate change is having a significant impact on ecosystem services and is likely to become increasingly important as this phenomenon intensifies. Future impacts can be difficult to assess as they often involve long timescales, dynamic systems with high uncertainties, and are typically confounded by other drivers of change. Despite a growing literature on climate change impacts on ecosystem services, no quantitative syntheses exist. Hence, we lack an overarching understanding of the impacts of climate change, how they are being assessed, and the extent to which other drivers, uncertainties, and decision making are incorporated. To address this, we systematically reviewed the peer‐reviewed literature that assesses climate change impacts on ecosystem services at subglobal scales. We found that the impact of climate change on most types of services was predominantly negative (59% negative, 24% mixed, 4% neutral, 13% positive), but varied across services, drivers, and assessment methods. Although uncertainty was usually incorporated, there were substantial gaps in the sources of uncertainty included, along with the methods used to incorporate them. We found that relatively few studies integrated decision making, and even fewer studies aimed to identify solutions that were robust to uncertainty. For management or policy to ensure the delivery of ecosystem services, integrated approaches that incorporate multiple drivers of change and account for multiple sources of uncertainty are needed. This is undoubtedly a challenging task, but ignoring these complexities can result in misleading assessments of the impacts of climate change, suboptimal management outcomes, and the inefficient allocation of resources for climate adaptation.

Coastal communities in the Coral Triangle are increasingly threatened by climate change. Sea-level rise (SLR) will result in biophysical and socioeconomic impacts that could increase the loss of livelihoods, cultural heritage and infrastructure. Effective adaptation requires a holistic approach that incorporates scientific knowledge together with local and traditional knowledge. Community-based adaptation built on local knowledge is of great value for environmental management, particularly when scientific data are lacking. This article reports a case study that integrated traditional and scientific knowledge using participatory three-dimensional modeling (P3DM) in BoeBoe village, Solomon Islands. P3DM is a process by which members of the local community build a physical terrain model and overlay it with the location of important resources such as protected areas or harvesting sites. Additionally, SLR inundation scenarios based on surveyed elevations were incorporated into a geographic information system (GIS), allowing for a real-time integration of science with local knowledge. Despite discrepancies in scales and accuracy, information from both the P3DM and GIS were complementary. The process, itself, provided a forum for discussion between many members of the village who would normally not be involved and highlighted the importance of community engagement when building capacity for adaptation to climate change.

Few studies on population-specific health effects of extreme temperature on cardiovascular diseases (CVDs) deaths have been conducted in the subtropical and tropical climates of China. We examined the association between extreme temperature and CVD across four cities in China. We performed a two-stage analysis; we generated city-specific estimates using a distributed lag non-linear model (DLNM) and estimated the overall effects by conducting a meta-analysis. Heat thresholds of 29 °C, 29 °C, 29 °C, and 30 °C and cold thresholds of 6 °C, 10 °C, 14 °C, and 15 °C were observed in Hefei, Changsha, Nanning, and Haikou, respectively. The lag periods for heat-related CVD mortality were observed only for 0–2 days, while those of cold-related CVD mortality were observed for 10–15 days. The meta-analysis showed that a 1 °C increase above the city-specific heat threshold was associated with average overall CVD mortality increases of 4.6% (3.0%–6.2%), 6.4% (3.4%–9.4%), and 0.2% (−4.8%–5.2%) for all ages, ≥65 years, and <65 years over a lag period of 0–2 days, respectively. Similarly, a 1 °C decrease below the city-specific cold threshold was associated with average overall CVD mortality increases of 4.2% (3.0%–5.4%), 4.9% (3.5%–6.3%), and 3.1% (1.7%–4.5%), for all ages, ≥65 years, and <65 years over a lag period of 0–15 days, respectively. This work will help to take appropriate measures to reduce temperature-mortality risk in different populations in the subtropical and tropical climates of China.