In a survey conducted in 2024 about the Australian public's view on climate change, 79 percent of respondents claimed that they were concerned about more droughts and flooding affecting crop production and food supply. Additionally, 78 percent of respondents stated that they were concerned about more bushfires in the country. Consequences of global warming in Australia The consequences of climate change have already affected many regions on a global scale, but Australia is experiencing especially adverse impacts. As the driest inhabited continent on earth, climate change increases the risk of extremely high temperatures, droughts, and bushfires every year. The highest temperatures recorded in Australia as of 2022 exceeded 50 degrees Celsius in many locations in the country. This leads to significant impacts on not only wildlife and flora but also on livelihoods in Australia. The estimated change in GDP from unmitigated climate change was forecast to have negative economic ramifications for Australia. Public view on climate change Due to the tangible impacts of global climate change, it is not surprising that the majority of the public perceives global warming in Australia as a pressing and serious problem, which has to be addressed sooner rather than later. Around 50 percent of Australians stated that the Australian government’s actions on climate change are not sufficient against the impact global warming has on the country. Still highly dependent on fossil fuels, the energy sector is the biggest greenhouse gas emitter in Australia. Almost half of the Australian public claimed that climate adaptation funding should be paid by fossil fuel producers. This would also lessen the burden for taxpayers on the funding of climate change adaptation.

In general, the younger U.S. generation is more concerned about climate change than the older generations. Between 2015 and 2018, 51 percent of those between 18 and 34 years of age agreed that global warming would pose a serious threat within their lifetime, while only 29 percent of those aged 55 years and older agreed with the statement. This likely reflects the different time periods that are experienced by each age group, where older generations will have less time in their lives for the effects to be realized. A larger percentage of the younger generation also believed that climate change was a very serious issue in comparison to the older generations. About 58 percent of the younger respondents believed there was a scientific consensus regarding climate change as of January 2018. The differences in the perception of climate change may also be due to the exposure and education of younger people in climate change discussions as well as the relationship between age and political ideology.

Climate and political ideology
Overall, about 53 percent of U.S. adults believe that global warming is mainly caused by human activity. However, there is a great disparity between political beliefs where 83 percent of people who identified as Liberal Democrats believe in anthropogenic climate change, in comparison to that 18 percent of identified Conservative Republicans were in agreement. This discrepancy can also be seen in politicians and their opinions on acting on climate change.

This work involves 1) synthesizing information from the literature and 2) modeling impacts of climate change on specific aspects of salmon life history and viability. Annual literature reviews summarize information from peer-reviewed journals and major technical reports relevant to managing Pacific salmon, with an emphasis on information that is most relevant for salmon in the Pacific Northwest and the Columbia River Basin. Original research involves modeling exploration of changes in climate on spawner to smolt productivity, juvenile survival, upstream migration survival and timing, prespawn mortality, and whole life cycle population viability. Collection of data collected by numerous other sources (e.g., tribes, states) managed and made public by NWFSC.

1. The climate on our planet is changing and the range distributions of organisms are shifting in response. In aquatic environments, species might not be able to redistribute poleward or into deeper water when temperatures rise because of barriers, reduced light availability, altered water chemistry, or any combination of these. How species respond to climate change may depend on physiological adaptability, but also on the population dynamics of the species.

2. Density dependence is a ubiquitous force that governs population dynamics and regulates population growth, yet its connections to the impacts of climate change remain little known, especially in marine studies. Reductions in density below an environmental carrying capacity may cause compensatory increases in demographic parameters and population growth rate, hence masking the impacts of climate change on populations. On the other hand, climate-driven deterioration of conditions may reduce environmental carrying capacities, making compensation less likely and populations more susceptible to the effects of stochastic processes.

3. Here we investigate the effects of climate change on Baltic blue mussels using a 17-year data set on population density. Using a Bayesian modelling framework, we investigate the impacts of climate change, assess the magnitude and effects of density dependence, and project the likelihood of population decline by the year 2030.

4. Our findings show negative impacts of warmer and less saline waters, both outcomes of climate change. We also show that density-dependence increases the likelihood of population decline by subjecting the population to the detrimental effects of stochastic processes (i.e., low densities where random bad years can cause local extinction, negating the possibility for random good years to offset bad years).

5. We highlight the importance of understanding, and accounting for both density dependence and climate variation when predicting the impact of climate change on keystone species, such as the Baltic blue mussel. 08-Oct-2020

Approximately 25% of mammals are currently threatened with extinction, a risk that is amplified under climate change. Species persistence under climate change is determined by the combined effects of climatic factors on multiple demographic rates (survival, development, reproduction), and hence, population dynamics. Thus, to quantify which species and regions on Earth are most vulnerable to climate-driven extinction, a global understanding of how different demographic rates respond to climate is urgently needed. Here, we perform a systematic review of literature on demographic responses to climate, focusing on terrestrial mammals, for which extensive demographic data are available. To assess the full spectrum of responses, we synthesize information from studies that quantitatively link climate to multiple demographic rates. We find only 106 such studies, corresponding to 87 mammal species. These 87 species constitute < 1% of all terrestrial mammals. Our synthesis reveals a strong mismatch between the locations of demographic studies and the regions and taxa currently recognized as most vulnerable to climate change. Surprisingly, for most mammals and regions sensitive to climate change, holistic demographic responses to climate remain unknown. At the same time, we reveal that filling this knowledge gap is critical as the effects of climate change will operate via complex demographic mechanisms: a vast majority of mammal populations display projected increases in some demographic rates but declines in others, often depending on the specific environmental context, complicating simple projections of population fates. Assessments of population viability under climate change are in critical need to gather data that account for multiple demographic responses, and coordinated actions to assess demography holistically should be prioritized for mammals and other taxa.

1. Recent studies unravelled the effect of climate changes on populations through their impact on functional traits and demographic rates in terrestrial and freshwater ecosystems, but such understanding in marine ecosystems remains incomplete. 2. Here, we evaluate the impact of the combined effects of climate and functional traits on population dynamics of a long-lived migratory seabird breeding in the southern ocean: the black-browed albatross (Thalassarche melanophris, BBA). We address the following prospective question: ''Of all the changes in the climate and functional traits, which would produce the biggest impact on the BBA population growth rate?'' 3. We develop a structured matrix population model that includes the effect of climate and functional traits on the complete BBA life cycle. A detailed sensitivity analysis is conducted to understand the main pathway by which climate and functional trait changes affect the population growth rate. 4. The population growth rate of BBA is driven by the combined effects of climate over various seasons and multiple functional traits with carry-over effects across seasons on demographic processes. Changes in Sea Surface Temperature (SST) during late winter cause the biggest changes in the population growth rate, through their effect on juvenile survival. Adults appeared to respond to changes in winter climate conditions by adapting their migratory schedule rather than by modifying their at-sea foraging activity. However, the sensitivity of the population growth rate to SST affecting BBA migratory schedule is small. BBA foraging activity during the pre-breeding period has the biggest impact on population growth rate among functional traits. Finally, changes in SST during the breeding season have little effect on the population growth rate. 5. These results highlight the importance of early life histories and carry-over effects of climate and functional traits on demographic rates across multiple seasons in population response to climate change. Robust conclusions about the roles of various phases of the life cycle and functional traits in population response to climate change rely on an understanding of the relationships of traits to demographic rates across the complete life cycle.

The impacts of climate change on forest community composition are still not well known. Although directional trends in climate change and community composition change were reported in recent years, further quantitative analyses are urgently needed. Previous studies focused on measuring population growth rates in a single time period, neglecting the development of the populations. Here we aimed to compose a method for calculating the community composition change, and to testify the impacts of climate change on community composition change within a relatively short period (several decades) based on long-term monitoring data from two plots—Dinghushan Biosphere Reserve, China (DBR) and Barro Colorado Island, Panama (BCI)—that are located in tropical and subtropical regions. We proposed a relatively more concise index, Slnλ, which refers to an overall population growth rate based on the dominant species in a community. The results indicated that the population growth rate of a majority of populations has decreased over the past few decades. This decrease was mainly caused by population development. The increasing temperature had a positive effect on population growth rates and community change rates. Our results promote understanding and explaining variations in population growth rates and community composition rates, and are helpful to predict population dynamics and population responses to climate change.

This repository contains the data and results from the paper Estimating future heat-related and cold-related mortality under climate change, demographic and adaptation scenarios in 854 European cities published in Nature Medicine (https://doi.org/10.1038/s41591-024-03452-2).

It provides projections of excess death rates and burden for the period 2015-2099 for five age groups in 854 cities across 30 countries, under three Shared Socioeconomic Pathway (SSP) scenarios, and four adaptation scenarios. The results include point estimates for five-year periods and four global warming levels, along with 95% empirical confidence intervals.

The fully reproducible analysis code using the data and producing the results included in this repository is provided in GitHub. The results can be visualised and explored in a dedicated Shiny app.

Content

This repository contains three zip files, each with an internal codebook:

• data.zip: contains the input data necessary to run the analysis. It includes historical and projected daily temperature at the city level, age-group specific projections of population and survival rates at the country level, and exposure-response functions extracted from another Zenodo repository (https://doi.org/10.5281/zenodo.10288665). This file also include a script showing how each dataset was extracted for the purpose of this projection study.
• results_csv.zip: contains the full results from the health impact projections. It includes one file for each combination of geographical level (city, country, region or European wide) and scale of reporting (five year periods or global warming levels).
• results_parquet.zip: contains the same information as the results_csv.zip but in a parquet format. This allows for more efficient storage and data reading.

It is recommended to only download results_csv.zip for a quick exploration of the results, or only results_parquet.zip when the results are to be loaded into a software for deeper analysis.

Population trend data for over 1000 species across the terrestrial, freshwater and marine realm. Data contains trend info, trait data, climatic niche as well as temperature data at the study sites of the population data collection.

The first version of the Canadian Global Coupled Model, CGCM1, and its control climate are described by Flato et al. (1999). The atmospheric component of the model is essentially GCMII described by McFarlane et al. (1992). It is a spectral model with triangular truncation at wave number 32 (yielding a surface grid resolution of roughly 3.7 degrees x3.7 degrees) and 10 vertical levels. The ocean component is based on the GFDL MOM1.1 code and has a resolution of approximately 1.8 degrees x1.8 degrees and 29 vertical levels. The model uses heat and water flux adjustments obtained from uncoupled ocean and atmosphere model runs (of 10 years and 4000 years duration respectively), followed by an `adaption' procedure in which the flux adjustment fields are modified by a 14 year integration of the coupled model. A multi-century control simulation with the coupled model has been performed using the present-day CO2 concentration to evaluate the stability of the coupled model's climate, and to compare the modelled climate and its variability to that observed. An ensemble of four transient climate change simulations has been performed and is described in Boer et al. (1999a; b). Three of these simulations use an effective greenhouse gas forcing change corresponding to that observed from 1850 to the present, and a forcing change corresponding to an increase of CO2 at a rate of 1% per year (compounded) thereafter until year 2100. The direct forcing effect of sulphate aerosols is also included by increasing the surface albedo (as in Reader and Boer, 1999) based on loadings from the sulphur cycle model of Langner and Rodhe (1991). The fourth simulation considers the effect of greenhouse gas forcing only. The change in climate predicted by a model clearly depends directly on this specification of greenhouse gas (and aerosol) forcing, and of course these are not well known. The prescription described above is similar to the IPCC "business as usual" scenario, and using a standard scenario allows the results of this model to be compared to those of other modelling groups around the world. Some initial results from these simulations are presented below. The climate sensitivity of CGCM1 is about 3.5 degrees C. For the A2 emissions scenario the main emphasis is on a strengthening of regional and local culture, with a return to family values in many regions. The A2 world consolidates into a series of roughly continental economic regions, emphasizing local cultural roots. In some regions, increased religious participation leads many to reject a materialist path and to focus attention on contributing to the local community. Elsewhere, the trend is towards ncreased investment in education and science and growth in economic productivity. Social and political structures diversify with some regions moving towards stronger welfare systems and reduced income inequality, while others move towards "lean" government. Environmental concerns are relatively weak, although some attention is paid to bringing local pollution under control and maintaining local environmental amenities. The A2 world sees more international tensions and less cooperation than in A1 or B1. People, ideas and capital are less mobile so that technology diffuses slowly. International disparities in productivity, and hence income per capita, are maintained or increased. With the emphasis on family and community life, fertility rates decline only slowly, although they vary among regions. Hence, this scenario family has high population growth (to 15 billion by2100) with comparatively low incomes per capita relative to the A1 andB1 worlds, at US$7,200 in 2050 and US$16,000 in 2100.Technological change is rapid in some regions and slow in others as industry adjusts to local resource endowments, culture, and education levels. Regions with abundant energy and mineral resources evolve more resource intensive economies, while those poor in resources place very high priority on minimizing import dependence through technological innovation to improve resource efficiency and make use of substitute inputs. The fuel mix in different regions is determined primarily by resource availability. And divisions among regions persist in terms of their mix of technologies, with high-income but resource-poor regions shifting toward advance... Visit https://dataone.org/datasets/doi%3A10.5063%2FAA%2Fdpennington.40.5 for complete metadata about this dataset.

1. Climate change is expected to alter not only year-to-year variation in climate but also aspects of within-year variation, such as the length of the intervals between rainfall events and the duration of heat waves. Yet we still have a poor understanding of how intra-annual climate variability and individual weather events alter key vital rates (e.g. individual growth, reproduction and survival) that in part determine population dynamics.
2. Traditionally, ecologists have accounted for this variability across long time periods by attempting to correlate annual vital rates with measures of within-year variability (e.g., the coefficient of variation) to match the scale at which demographic data are collected. An alternative to this aggregate approach is to use within-season yet still relatively infrequent censuses in a probabilistic framework to determine the most likely way that vital rates respond to shorter-term variation in the environment, and how these short-term changes cumulatively lead to the observed yearly vital rates.
3. Here, I present an approach for inferring daily responses of vital rates to short-term weather variability, and apply it to understand how five species of summer annual plants in the Chihuahuan Desert will respond to climate change.
4. Vital rate models reveal that species differ in their responses to above- and below-average conditions, but generally fall into two life histories: 1) species that have fast growth on favorable days, but also experience higher mortality on less favorable days, and 2) species that have slower growth in the same conditions but lower mortality. Results show that the expected rainfall changes in the Chihuahuan desert (more late, cool season rainfall and less frequent, more intense rainfall events) could reduce growth and increase mortality of all summer annual plants.
5. Synthesis. My study shows that vital rates can change in response to short-term variability even when the total amount of rainfall and average temperature, common covariates in demographic models, remain constant. Accounting for changes in short-term environmental variation in climate change predictions will likely be important in systems with considerable environmental variation between censuses. The approach I present here can be widely applied to understand how short-term variability and individual weather events will alter organism responses to climate change.

According to an April 2024 survey on climate change conducted in the United States, some 70 percent of the respondents claimed they believed that global warming was happening. A much smaller share, 13 percent, believed global warming was not happening.

Details about DNA extraction, library preparation, bioinformatics can be found in the methods of our manuscript. The data file is the fasta alignment of the 121 mitochondrial genomes of narwhals, which was used for the analyses.

This layer maps economic damage due to climate change by county level across the United States. Projections for three time periods and two emissions scenarios are included for agricultural production, human mortality, and energy expenditures.The default symbology and pop-up display change in energy expenditures for an intermediate emission scenario (RCP 4.5) for the period 2040-2059 relative to 2012.AttributesEnergy - Percent change in residential and commercial sector energy expenditure relative to 2012. Estimates are based on modeling from Rhodium Group’s version of the National Energy Modeling System RHG-NEMS.Mortality - Net change in deaths per 100,000 population due to heat and cold. Changes are reported relative to 2012 statistics from the Centers for Disease Control and Prevention.Agriculture - Percent change in total agricultural yields, area-weighted average, for maize, wheat, soybeans, and cotton due to climate change including effects of CO2 fertilization. Changes are reported relative to statistics from the US Department of Agriculture in the year 2012. Counties with null values did not have production of these crops in 2012.High Risk Labor - Percent change in labor productivity in high risk sectors. High risk sectors consist of agriculture, forestry, fishing, hunting, mining quarrying, oil extraction, gas extraction, utilities, construction, manufacturing, transportation and warehousing. Total Labor - Percent change in labor supply of full-time-equivalent workers for all jobs. Values are based on total productivity losses assuming there is no growth in the labor force and account for changes in labor supply. Changes are reported relative to statistics from the Bureau of Labor Statistics in the year 2012.Emissions Scenarios Representative Concentration Pathwaysintermediate (RCP 4.5) and high (RCP 8.5)Time PeriodsTwo-Decade periods2020-20392040-20592080-2099For more information about how the data used in this layer were created see:Climate Impact LabHsiang, S., Kopp, R.E., Jina, A., Rising, J., Delgado M., Mohan, S., Rasmussen, D.J., Muir-Wood, R., Wilson, P., Oppenheimer, M., Larsen, K., and Houser, T. (2017). Estimating economic damage from climate change in the United States. Science. doi:10.1126/science.aal4369

This data set defines boundaries of oil and gas project areas, greater sage-grouse (Centrocercus urophasianus) core areas, and non-core and non-project areas within the Wyoming Landscape Conservation Initiative (WLCI; southwestern Wyoming). Specifically, the data represents results from the manuscript “Combined influences of future oil and gas development and climate on potential Sage-grouse declines and redistribution” for high oil and gas development, low population size, and with effects of climate change under an RCP 8.5 scenario (2050) . The oil and gas development scenario were based on an energy footprint model that simulates well, pad, and road patterns for oil and gas recovery options that vary in well types (vertical and directional) and number of wells per pad and use simulation results to quantify physical and wildlife-habitat impacts. I applied the model to assess tradeoffs among 10 conventional and directional-drilling scenarios in a natural gas field in southwestern Wyoming (see Garman 2017). The effects climate change on sagebrush were developed using the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM, version 4) climate model and representative concentration pathway 8.5 scenario (emissions continue to rise throughout the 21st century). The projected climate scenario was used to estimate the change in percent cover of sagebrush (see Homer et al. 2015). The percent changes in sage-grouse population sizes represented in these data are modeled using an individual-based population model that simulates dynamics of populations by tracking movements of individuals in dynamically changing landscapes, as well as the fates of individuals as influenced by spatially heterogeneous demography. We developed a case study to assess how spatially explicit individual based modeling could be used to evaluate future population outcomes of gradual landscape change from multiple stressors. For Greater sage-grouse in southwest Wyoming, we projected oil and gas development footprints and climate-induced vegetation changes fifty years into the future. Using a time-series of planned oil and gas development and predicted climate-induced changes in vegetation, we re-calculated habitat selection maps to dynamically modify future habitat quantity, quality, and configuration. We simulated long-term sage-grouse responses to habitat change by allowing individuals to adjust to shifts in habitat availability and quality. The use of spatially explicit individual-based modeling offered an important means of evaluating delayed indirect impacts of landscape change on wildlife population outcomes. This process and the outcomes on sage-grouse population changes are reflected in this data set.

R code and demographic data related the the research article "Microclimate and forest density drive plant population dynamics under climate change" Macroclimatic changes are impacting ecosystems worldwide. The majority of terrestrial species, however, lives in the shade of trees where impacts of macroclimate change are buffered. Yet, how microclimate buffering can impact future below-canopy biodiversity redistributions at the continental scale is unknown. Here we assess the effects of changes in microclimate and forest density on plant population dynamics under macroclimate change. We built 25-m resolution mechanistic demographic distribution models at European extent based on plant demography responses to changes in the environment in a unique cross-continental climate change transplant experiment. We show that changes in microclimate and light due to canopy opening amplify macroclimate change impacts on forest biodiversity, while shady forest floors due to dense tree canopies mitigate severe warming impacts. The microclimate and forest density thus emerge as powerful tools for forest managers and policy makers to shelter forest biodiversity from climate change.

1. Climate change is reported to have caused widespread changes to species’ populations and ecological communities. Warming has been associated with population declines in long-distance migrants and habitat specialists, and increases in southerly distributed species. However, the specific climatic drivers behind these changes remain undescribed. 2. We analysed annual fluctuations in the abundance of 59 breeding bird species in England over 45 years to test the effect of monthly temperature and precipitation means upon population trends. 3. Strong positive correlations between population growth and both winter and breeding season temperature were identified for resident and short-distance migrants. Lagged correlations between population growth and summer temperature and precipitation identified for the first time a widespread negative impact of hot, dry summer weather. Resident populations appeared to increase following wet autumns. Populations of long-distance migrants were negatively affected by May temperature, consistent with a potential negative effect of phenological mismatch upon breeding success. There was evidence for some nonlinear relationships between monthly weather variables and population growth. 4. Habitat specialists and cold-associated species showed consistently more negative effects of higher temperatures than habitat generalists and southerly distributed species associated with warm temperatures. Results suggest that previously reported changes in community composition represent the accumulated effects of spring and summer warming. 5. Long-term population trends were more significantly correlated with species’ sensitivity to temperature than precipitation, suggesting that warming has had a greater impact on population trends than changes in precipitation. Months where there had been the greatest warming were the most influential drivers of long-term change. There was also evidence that species with the greatest sensitivity to extremes of precipitation have tended to decline. 6. Our results provide novel insights about the impact of climate change on bird communities. Significant lagged effects highlight the potential for altered species’ interactions to drive observed climate change impacts, although some community changes may have been driven by more immediate responses to warming. In England, resident and short-distance migrant populations have increased in response to climate change, but potentially at the expense of long-distance migrants, habitat specialists and cold-associated species.

Climate and land-use change are major components of global environmental change with feedbacks between these components. The consequences of these interactions show that land use may exacerbate or alleviate climate change effects. Based on these findings it is important to use land-use scenarios that are consistent with the specific assumptions underlying climate-change scenarios. The Integrated Climate and Land-Use Scenarios (ICLUS) project developed land-use outputs that are based on a downscaled version of the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) social, economic, and demographic storylines. ICLUS outputs are derived from a pair of models. A demographic model generates county-level population estimates that are distributed by a spatial allocation model (SERGoM v3) as housing density across the landscape. Land-use outputs were developed for the four main SRES storylines and a baseline ("base case"). The model is run for the conterminous USA and output is available for each scenario by decade to 2100. In addition to housing density at a 1 hectare spatial resolution, this project also generated estimates of impervious surface at a resolution of 1 square kilometer. This shapefile holds population data for all counties of the conterminous USA for all decades (2010-2100) and SRES population growth scenarios (A1, A2, B1, B2), as well as a 'base case' (BC) scenario, for use in the Integrated Climate and Land Use Scenarios (ICLUS) project.

Climate change adaptation is vital for Pacific SIDS. Long-term effects, including the increasing frequency and severity of extreme events such as high rainfall, droughts, tropical cyclones, and storm surges are affecting the people in this region. Coupled with non-climate drivers, such as inappropriate land use, overexploitation of resources, increasing urbanization and population increase, development in the region is increasingly undermined. For the low lying atolls, the likely economic disruption from climate change pressures could be catastrophic and potentially lead to population relocation and therefore social and cultural disruption and disproportion. Failure to reduce vulnerability may result in loss of future risk management opportunities when impacts may be greater and options fewer.Available onlineCall Number: [EL]Physical Description: 136 p.

File List Climate_data.txt (MD5: 2177e250ad42ca1c88c283d1f20c7265) Population_dynamics_data.txt (MD5: f392760fde47de38f641648dcd8ffe76) Georeference_location_data.kmz (MD5: 0e74aff74928cdc4558da7758e8bc7c3)

Description Long-term data sets of population dynamics of plants are scarce, yet provide valuable information for addressing critical ecological and evolutionary questions. Such data can be used to determine how climate change affects demographic viability and evolutionary stable demographic strategies. Here we provide a long-term data set with longitudinal (1997–2012) individual records for 3835 plants of the chamaephyte Cryptantha flava L. (A. Nelson) Payson (Boraginaceae) near Redfleet State Park in Uintah County, Utah, USA (40° 35' 42.63" N, 109°25' 55.92" W, 1790 m a.s.l.). We used permanent plots to track the individual responses (survival, changes in size, reproduction, and recruitment) to artificial manipulations of precipitation via rainout shelters in 1998 and 1999 in subsets of those plots. These data provide unique opportunities to examine the effect of ambient climatic variation and interpret longer-term climate change effects on native plant species’ population dynamics in interaction with the surrounding plant communities. We provide the following data and data formats: (1) monthly background precipitation and temperature at the closest permanent weather station, (2) individual-level population dynamics from 1997 to 2012 with point location (x, y coordinates) of the individuals of C. flava within the permanent plots as well as microhabitat conditions, and (3) geo-referenced location of each permanent plot.

      Key words: climate change; Colorado Plateau desert; Cryptantha flava; long-term demography; plant population dynamics; rainout shelter.