Greenhouse Gas Emission Scenarios Research Articles

Study of the Future Evolution of the Urban Climate of Paris by Statistical–Dynamical Downscaling of the EURO-CORDEX Ensemble

Abstract High-resolution urban climate projections are needed for local decision-making on climate change adaptation. Regional climate models have resolutions that are too coarse to simulate the urban climate at such resolutions. A novel statistical–dynamical downscaling (SDD) approach is used here to downscale the EURO-CORDEX ensemble to a resolution of 1 km while adding the effect of the city of Paris (France) on air temperature. The downscaled atmospheric fields are then used to drive the Town Energy Balance urban canopy model to produce high-resolution temperature maps over the period 1970–2099, while maintaining the city’s land cover in its present state. The different steps of the SDD are evaluated for the summer season. The regional climate models simulate minimum (maximum) temperatures (TN/TX) that are too high (low). After correction and downscaling, the urban simulations inherit some of these biases but give satisfactory results for summer urban heat islands (UHIs), with average biases of −0.6 K at night and +0.3 K during the day. Changes in future summer temperatures are then studied for two greenhouse gas emission scenarios, RCP4.5 and RCP8.5. Outside the city, the simulations project average increases of 4.1 and 4.8 K for TN and TX for RCP8.5, respectively. In the city, warming is lower, resulting in a decrease in UHIs of −0.19 K at night (from 2.1 to 1.9 K) and −0.16 K during the day. The changes in UHIs are explained by higher rates of warming in rural temperatures due to lower summer precipitation and soil water content and are partially offset by increased ground heat storage in the city.

Groundwater stress in Europe—assessing uncertainties in future groundwater discharge alterations due to water abstractions and climate change

Groundwater sustains human well-being and ecosystems functioning. Many regions in Europe have experienced declining groundwater levels caused by decreasing groundwater recharge (GWR) or increasing groundwater abstractions (GWAs). These changes can lead to groundwater-related stress, threatening ecosystems and water supplies. Existing groundwater stress indicators estimate stress during a given period but do not address how stress changes or show the uncertainty of future stress. We propose a novel indicator of future groundwater stress (GWSI) due to changes in GWR and GWA and, thus, the alteration of long-term mean annual groundwater discharge (GWD). Groundwater stress is defined as any alteration in GWD since ecosystems are adapted to an equilibrium state. Focusing on decreasing GWD, which is generally more harmful than increasing GWD, we quantified the future GWSI in Europe by integrating scenarios of GWR and GWA in 2070–2099. GWR was evaluated using an ISIMIP2b multi-model ensemble of eight global hydrological models driven by the output of four global climate models under two greenhouse gas emission scenarios. GWA scenarios for irrigation, domestic and manufacturing sectors were combined with the GWR projections to generate an ensemble of GWSIs, simplified into three groundwater stress scenarios (high, intermediate, low). Projected GWSIs vary significantly among the scenarios. For the high-stress scenario, 58% of Europe’s land area is projected to experience a GWD decrease of at least 25% under RCP8.5 compared to 38% under RCP2.6, while the respective values are 26 and 1% for the intermediate-stress scenario. Groundwater demand management alone might not prevent GWD declines under the high-stress and intermediate scenarios, particularly under RCP8.5. Therefore, climate change mitigation might imperative for reducing the decline of GWD, especially in Eastern and Southeastern Europe, where changes in GWR are projected to be the primary cause of declining GWD (in the high abstraction scenario under RCP8.5). Under RCP2.6, reductions in GWAs by 25–75% might balance a GWD decline in parts of Spain and Italy where GWAs are high, even in the high-stress scenario. In line with the precautionary principle, we recommend adapting to the high-stress scenario to minimize harm to the beneficiaries of groundwater.

Phytoclimatological study in the high plains of Sétif: application of the bioclimatic classification system (Algeria)

The Global Bioclimatic Classification System (WBCS) by Rivas-Martínez is an effective approach to reflect and study the role of climate in determining the potential distribution of natural vegetation at various temporal and spatial scales. In particular, the diversity of physical characteristics in the Setifian high plains leads to the complexity of large-scale phytogeographic belts. Isobioclimates, unique combinations of bioclimatic indices (continentality, ombrotype, and thermotype), have been created for the study area based on Rivas-Martínez's global bioclimatic classification system for current and future climate scenarios, using the parallel climate model from CMIP5 (Coupled Model Intercomparison Project) under the intermediate greenhouse gas emission scenario (RCP4.5). Precipitation and temperature data from the "WorldClim" dataset were used as the data source. These climatic variables were reduced to a spatial resolution of 1 km. The objective is to understand how the climate is evolving in this region, what the consequences are, and what the future holds for these natural ecosystems. A phytosociological study complemented by satellite image analysis reveals a high diversity of pre-forestry formations. The digitally mapped results were used to 1) assess the relative redistribution of isobioclimates and the magnitude of change, 2) identify and locate the new projected isobioclimates, and 3) explore the compositional changes in vegetation types among analogous isobioclimatic zones. The ordination of the relationships between vegetation and bioclimates shows a strong correlation between Rivas-Martinez indices and the distribution and composition of vegetation. Changes in ombrotype, thermotype, bioclimate, ombrotype, and isobioclimate differed between the current and future series. The resulting map presents 9 isobioclimatic units, which are advantageous for confirming the diagnosis of bioclimatic characteristics and describing the relationships between climatic variables and the corresponding distributions of natural vegetation. We identified eight different isobioclimates for the current period (1979-2013) and seven for the future period (2050), three thermotype horizons for both the current and future periods, and finally, four ombrotype horizons for the period (1979-2013), while two ombrohorizons represent the period (2050). This approach is useful for explaining territorial diversity in environmental applications related to ecological adaptation assessment, nature conservation, landscape regionalization, and planning.

Substantial reduction in population exposure to sea level changes along the Chinese mainland coast through emission mitigation

Abstract Rising sea level increases the exposure to flooding and related damage in coastal areas with high population density and substantial economic activity. As global temperatures continue to rise due to climate change, sea levels have been consistently increasing and are projected to continue this upward trend. This study assesses the future exposure at provincial and city levels populations coastal mainland China coast to local sea level changes under five greenhouse gas (GHG) emission scenarios from IPCC-AR6, as well as two low-confidence scenarios accounting for the potential impact of uncertain ice sheet processes with low- and high-GHG emissions. We incorporate spatial heterogeneity into regional sea level projections and population projections from 2020 to 2100, extreme sea levels (ESLs) of 10-, 50-, and 100 year return periods (RP), and local coastal protection standards. Our findings indicate that the inundated areas expand continuously within the century with heightened exposure under higher emission scenarios. Although the coastal population is projected to decline, the fraction of the coastal population exposed to flooding increases across all scenarios, with accelerated growth under higher GHG emissions and higher ESLs. Zhejiang and Jiangsu emerge as the provinces most exposed to sea-level rise, whereas Taizhou, Nantong, Wuxi, Panjin, and Huzhou are identified as the top five cities with the highest population exposure to local sea level rise (SLR). Transitioning towards a sustainable scenario (i.e. SSP1-2.6) rather than a fossil fuel-intensive one (i.e. SSP5-8.5) can reduce the local SLR and substantially mitigate these exposures. Compared to the median projections under SSP5-8.5, aligning GHG emissions with SSP1-2.6 could reduce population exposure substantially in all coastal provinces, especially in Jiangsu, where population exposure to 100 year RP coastal floods would be reduced by ∼1.6 M in 2050 and by ∼5.4 M in 2100.

Fit for 2030? Possible scenarios of road transport demand, energy consumption and greenhouse gas emissions for Italy

Decarbonizing the transportation sector is one of the key challenges to reduce greenhouse gas (GHG) emissions and meet EU Green deal 2030 targets. Road transport decarbonization requires a holistic approach encompassing various strategies and interventions aimed at fostering the sustainable transition of this sector. This challenge is crucial given that road is responsible for over 90% of the overall transport GHG emissions.Within this framework, this study aims, for the Italian case, to: a) estimate the national passenger and freight road travel demand with respect to three different time periods: 2005 (reference year for EU “fit for 55” target); 2019 (last consolidated pre-covid year); 2022 (base-line year); b) define possible road transport scenarios to 2030 following the Avoid-Shift-Improve (ASI) approach; c) estimate the GHG and energy consumption inventory related to national road transport for the 2005, 2019; 2022 and 2030 scenarios. Due to the current “deep uncertainty” regarding key economic and social variables in this period, two forecasting scenarios – named “moderate decarbo” and “high decarbo” – were designed and based on different and somewhat opposite hypotheses on exogenous variables (e.g., GDP) and penetration rates of measures and policies promoting sustainable transportation (e.g., subsidies for electric vehicles) already in place. Although the current European legislation refers only to Tank-to-Wheel (TtW) objectives, this study included also the Well-to-Wheel (WtW) evaluation, which is more accurate in assessing the GHG impact of different policies, energy carriers, and technologies. As for the past, results suggest that GHG reductions over the period 2005–2022 are mostly due to crises and stagnation of the Italian economy. “Moderate decarbo” forecasts for 2030 lead to a 12% reduction of TtW (and 15% for WtW) GHG emissions compared to 2005 levels, with ASI policies compensating for the assumed economic growth. In any case these values are far from the EU “Fit for 55” goal setting a 43.7% reduction of TtW emissions. Even under very favourable hypotheses (“high decarbo” scenario), GHG emissions might be reduced by only 28% for TtW and 33% for WtW, still well below EU objectives. Furthermore, passengers and freight show very different behaviour, with the latter contributing to emissions more than proportionally, and “shift-to-rail” policies, although very useful in some market segments, contribute moderately at the overall national level. The main conclusion of this study is that the pathway towards road transport decarbonization in Italy (and possibly in other EU Countries) is very uncertain, and the ambitious 2030 target is unlikely to be met with currently planned policies alone. The transportation system needs to be constantly monitored, and new policies have to be implemented to reach higher emissions reduction goals.

Hurricane surge and inundation in the Bahamas, part 2: Flood risk assessment

AbstractA hurricane surge and inundation risk assessment has been carried out for Grand Bahama and Eleuthera in The Bahamas. 10,000 years of synthetic hurricane tracks were generated based on a statistical analysis of historical hurricanes from 1979 to 2020 inclusive. The surge and inundation were modelled using a hydrodynamic TELEMAC‐2D model covering sea around The Bahamas and the land of the two islands. Predictions of flood extents and depths were mapped for return periods of up to 1000 years for present day conditions and three climate change scenarios to 2100. The flooding experienced over Grand Bahama during Hurricane Dorian in 2019, was estimated to have a return period of up to approximately 450 years. Under the climate change scenarios the likelihood of flooding similar to Hurricane Dorian was estimated to be approximately 1.7 times more likely in 2050 and up to 3.4 times as likely in 2100 under a high greenhouse gas emissions scenario. The storm surge maps can be used by the Bahamas Department of Meteorology and other government agencies for emergency management, planning of infrastructure and building resilience in response to climate change.

Potential distribution of rice thrips (Stenchaetothrips biformis) in India under changing climate

Sudden outbreaks of agricultural pests are increasing in India due to the growing prominence of environmental issues like global warming, the occurrence of weather extremes, and hydrological extremes. Climate change impacts the developmental rates and population dynamics of agricultural pests. As rice is a staple food widely used in India, it often suffers intensive damage by various pests, leading to a considerable decrease in crop yield. One of the most common pests in rice fields in India and neighboring countries is the rice thrips (Stenchaetothrips biformis). However, the degree of pest infestation of rice crops under climate change scenarios is poorly known. Therefore, this study aimed to understand the potential geographical distribution of the rice thrips in India for future scenarios using the MaxEnt modeling framework. Future projections from global climate models (GCMs), such as HadGEM3-GC31 and MPI-ESMI-2, are used to predict the most affected regions in 2050 under three greenhouse gas emission scenarios: SSP1-2.6, SSP3-4.5, and SSP5-8.5. The results from the MaxEnt indicate that the southern and northeastern parts of India will be highly affected by rice thrips in 2050. The affected number of districts are found to be 256, 330 and 313 under SSP1-2.6, SSP3-4.5, and SSP5-8.5 scenarios, respectively. It has been observed that the maximum temperature is the most influential climatic parameter for the geographical distribution of rice thrips, followed by the annual mean and minimum temperatures. It can be concluded from these results that the elevated temperature enhances the growth and distribution of rice thrips.

Abrupt increase in Arctic-Subarctic wildfires caused by future permafrost thaw

Unabated 21st-century climate change will accelerate Arctic-Subarctic permafrost thaw which can intensify microbial degradation of carbon-rich soils, methane emissions, and global warming. The impact of permafrost thaw on future Arctic-Subarctic wildfires and the associated release of greenhouse gases and aerosols is less well understood. Here we present a comprehensive analysis of the effect of future permafrost thaw on land surface processes in the Arctic-Subarctic region using the CESM2 large ensemble forced by the SSP3-7.0 greenhouse gas emission scenario. Analyzing 50 greenhouse warming simulations, which capture the coupling between permafrost, hydrology, and atmosphere, we find that projected rapid permafrost thaw leads to massive soil drying, surface warming, and reduction of relative humidity over the Arctic-Subarctic region. These combined processes lead to nonlinear late-21st-century regime shifts in the coupled soil-hydrology system and rapid intensification of wildfires in western Siberia and Canada.

Projections of Extreme Temperature–Related Deaths in the US

ImportanceExtreme heat in the US is increasing due to climate change, while extreme cold is projected to decline. Understanding how extreme temperature along with demographic changes will affect population health is important for devising policies to mitigate the health outcome of climate change.ObjectiveTo assess the burden of extreme temperature–related deaths in the contiguous US currently (2008-2019) and estimate the burden in the mid–21st century (2036-2065).Design, Setting, and ParticipantsThis cross-sectional study used historical (1979-2000) daily mean temperatures to calculate monthly extreme heat (>97.5th percentile value) and extreme cold days (<2.5th percentile value) for all contiguous US counties for 2008 to 2019 (current period). Temperature projections from 20 climate models and county population projections were used to estimate extreme temperature–related deaths for 2036 to 2065 (mid–21st century period). Data were analyzed from November 2023 to July 2024.ExposureCurrent monthly frequency of extreme heat days and projected mid–21st century frequency using 2 greenhouse gas emissions scenarios: Shared Socioeconomic Pathway (SSP)2-4.5, representing socioeconomic development with a lower emissions increase, and SSP5-8.5, representing higher emissions increase.Main Outcomes and MeasuresMean annual estimated number of extreme temperature–related excess deaths. Poisson regression model with county, month, and year fixed effects was used to estimate the association between extreme temperature and monthly all-cause mortality for older adults (aged ≥65 years) and younger adults (aged 18-64 years).ResultsAcross the contiguous US, extreme temperature days were associated with 8248.6 (95% CI, 4242.6-12 254.6) deaths annually in the current period and with 19 348.7 (95% CI, 11 388.7-27 308.6) projected deaths in the SSP2-4.5 scenario and 26 574.0 (95% CI, 15 408.0-37 740.1) in the SSP5-8.5 scenario. The mortality data included 30 924 133 decedents, of whom 15 573 699 were males (50.4%), with 6.3% of Hispanic ethnicity, 11.5% of non-Hispanic Black race, and 79.3% of non-Hispanic White race. Non-Hispanic Black adults (278.2%; 95% CI, 158.9%-397.5%) and Hispanic adults (537.5%; 95% CI, 261.6%-813.4%) were projected to have greater increases in extreme temperature–related deaths from the current period to the mid–21st century period compared with non-Hispanic White adults (70.8%; 95% CI, −5.8% to 147.3%).Conclusions and RelevanceThis cross-sectional study found that extreme temperature–related deaths in the contiguous US were projected to increase substantially by mid–21st century, with certain populations, such as non-Hispanic Black and Hispanic adults, projected to disproportionately experience this increase. The results point to the need to mitigate the adverse outcome of extreme temperatures for population health.

High radiative forcing climate scenario relevance analyzed with a ten-million-member ensemble

Developing future climate projections begins with choosing future emissions scenarios. While scenarios are often based on storylines, here instead we produce a probabilistic multi-million-member ensemble of radiative forcing trajectories to assess the relevance of future forcing thresholds. We coupled a probabilistic database of future greenhouse gas emission scenarios with a probabilistically calibrated reduced complexity climate model. In 2100, we project median forcings of 5.1 watt per square meters (5th to 95th percentiles of 3.3 to 7.1), with roughly 0.5% probability of exceeding 8.5 watt per square meters, and a 1% probability of being lower than 2.6 watt per square meters. Although the probability of 8.5 watt per square meters scenarios is low, our results support their continued utility for calibrating damage functions, characterizing climate in the 22nd century (the probability of exceeding 8.5 watt per square meters increases to about 7% by 2150), and assessing low-probability/high-impact futures.

Mediterranean octocoral populations exposed to marine heatwaves are less resilient to disturbances.

The effects of climate change are now more pervasive than ever. Marine ecosystems have been particularly impacted by climate change, with marine heatwaves (MHWs) being a strong driver of mass mortality events. Even in the most optimistic greenhouse gas emission scenarios, MHWs will continue to increase in frequency, intensity and duration. For this reason, understanding the resilience of marine species to the increase of MHWs is crucial to predicting their viability under future climatic conditions. In this study, we explored the consequences of MHWs on the resilience (the ability of a population to resist and recover after a disturbance) of a Mediterranean key octocoral species, Paramuricea clavata, to further disturbances to their population structure. To quantify P. clavata's capacity to resist and recover from future disturbances, we used demographic information collected from 1999 to 2022, from two different sites in the NW Mediterranean Sea to calculate the transient dynamics of their populations. Our results showed that the differences in the dynamics of populations exposed and those not exposed to MHWs were driven mostly by differences in mean survivorship and growth. We also showed that after MHWs P. clavata populations had lower resistance and slower rates of recovery than those not exposed to MHWs. Populations exposed to MHWs had lower resistance elasticity to most demographic processes compared to unexposed populations. In contrast, the only demographic process showing some differences when comparing the speed of recovery elasticity values between populations exposed and unexposed to MHWs was stasis. Finally, under scenarios of increasing frequency of MHWs, the extinction of P. clavata populations will accelerate and their capacity to resist and recover after further disturbances will be hampered. Overall, these findings confirm that future climatic conditions will make octocoral populations even more vulnerable to further disturbances. These results highlight the importance of limiting local impacts on marine ecosystems to dampen the consequences of climate change.

Analyzing the impacts of climate change on ecosystem services provided by apple orchards in Southeast France using a process-based model

We know that fruit production, especially in the Mediterranean, will need to adapt to climate change to ensure the sustainability of fruit tree-based agroecosystems. However, there is a lack of evidence on the long-term effects of this change on sustainability indicators. To fill this gap, we used a fruit tree model, QualiTree, to analyze the impacts ofclimate change on the ecosystem services provided by apple orchards in south-eastern France. To do this, a blooming model was parameterized to simulate blooming date on the basis of climate data, and QualiTree was supplemented with a model of nitrogen processes in the tree and a soil module describing resource input (irrigation, mineral and organic fertilization), transfer in the soil (water and nitrogen) and metabolic transformation-immobilization (mineralization, (de)nitrification). This type of extension makes it possible to simulate a wide array of ecosystem services, including C sequestration, nitrate leaching and nitrous oxide emissions. The model was compared with data from an apple orchard in southeastern France. The predicted daily mean and variability over time of fruit growth, composition and soil water content were consistent with observed data. QualiTree was then used to assess the potential impacts of climate change on the ecosystem services supplied by apple orchards. For this purpose, weather variables from 2020 to 2100 were generated for three contrasted greenhouse gas emission scenarios, and simulations were performed under two irrigation schemes (no restriction and restricted use of water). Model outputs indicated that, on average, marketable apple yields would increase until 2050 and then subsequently decrease. The fruit refractometric index, an indicator of fruit quality, was projected to sharply decrease with the intensity of climate change. Ecosystem services such as C sequestration by the orchard will decrease with climate change severity, mainly due to a higher mineralization of soil humus, whereas N2O emissions will increase with larger denitrification rates. Soil water availability, fertility, drainage and leaching were predicted to depend more on the irrigation strategy than on climate change severity. The new functions performed in QualiTree broadened its predictive capabilities and allowed for a better understanding of ecosystem service delivery in fruit orchards under varying climate conditions.

Distribution patterns and potential suitable habitat prediction of Ceracris kiangsu (Orthoptera: Arcypteridae) under climate change- a case study of China and Southeast Asia

Ceracris kiangsu (Orthoptera: Arcypteridae), is greatly affected by climatic factors and exhibits strong adaptability, posing a serious threat to the ecological environment. Therefore, predicting its potential suitable habitat distribution provides a proactive theoretical basis for pest control. This study using the Biomod2 package of R simulated and predicted the current and future potential distribution, area changes, changes in the center points of suitable habitats, and niche shifts of C. kiangsu under two different greenhouse gas emission scenarios, SSP1-26 and SSP5-85. The results show that: (1) Currently, the high suitability areas for C. kiangsu are mainly distributed in Yunnan, Jiangxi, Hunan provinces in southern China and phongsaly province in northern Laos. In the future, the center of the suitable habitat distribution pattern of C. kiangsu will remain unchanged, primarily expanding outward from medium and high suitability areas. Additionally, significant suitable habitats for C. kiangsu were discovered in Southeast Asian countries without previous pest records. (2) Compared to the present, the overall suitable habitat area for C. kiangsu is expected to expand, particularly under the SSP5-85 climate change scenario. (3) In the SSP1-26 and SSP5-85 climate scenarios, the geometric center of the suitable habitat generally shows a trend of gradually shifting northeast. (4) Under different climate scenarios, the suitable habitat of C. kiangsu has highly overlapping, indicating that the suitable habitat of C. kiangsu in the invaded areas is broader than in its native regions. In conclusion, the research findings represent a breakthrough in identifying the potential distribution areas of C. kiangsu, which is of great practical significance for the monitoring and control of C. kiangsu pest infestation in China and Southeast Asian countries.

Климатические изменения температуры воздуха западной части российской Арк­тики в 1940—2099 гг. по данным ERA5 и моделям CMIP6

The study deals with the climatic changes in surface air temperature (SAT) in the western part of the Russian Arctic (60—80° N, 30—90° E). To analyze the changes in SAT that occurred over the period 1940—2023, we use data from the ERA5 reanalysis and the results of the Historical model experiment CMIP6. Future changes in SAT until the end of the 21st century we consider based on the results of SSP experiments of CMIP6 models. An increase in the average SAT of the studied region by 2—4°C is shown from approximately the mid-1970s to 2023. Moreover, this increase in SAT is most noticeable in the White and Kara Seas, as well as in the north and east of the Barents Sea. CMIP6 models based on different greenhouse gas emission scenarios produce markedly different forecasts for the increase in SAT for the region under study until the end of the 21st century. Thus, depending on the scenario, the average increase in SAT in the region under study by the end of the 21st century can range from 2—4°C to 6—10°, with stronger growth of SAT in the north of the region under study. At the same time, with little dependence on the future scenario, CMIP6 models predict that in the next 30 years the average SAT of the western part of the Russian Arctic will increase by approximately 2—3°C, and in the north of the region under study its increase may be more than 3°C, and in south — about 2°C. Thus, the difference in average SAT between the north and south of the region under study will decrease throughout the 21st century under any of the SSP scenarios considered.

Attributable deaths in Austria due to ozone under different climate scenarios.

Tropospheric ozone is an air pollutant that poses a public health problem in Europe. Climate change could increase the formation of ozone. Applying past and predicted annual total (all-cause) mortality data and modeled daily ozone concentrations, we performed a nationwide health impact assessment estimating annual ozone-related (attributable) deaths in Austria. Different approaches were compared. Estimates were based on maximal 1-h averages of ozone. Until the decade from 2045 till 2055, more people will die in Austria because of the demographic trends. Therefore, more deaths will also be attributable to ozone. Higher greenhouse gas emission scenarios (e.g. Representative Concentration Pathway RCP8.5 compared to RCP2.6) will lead to more ozone-related deaths, mostly due to the national emission of ozone precursors (a difference of 250-340 cases per year, depending on the model), but to a lesser extent because of global climate change. Increases in attributable deaths will be affected mostly by national, not global mitigation measures. National emission reduction will certainly have a strong and beneficial effect on local atmospheric chemistry, air quality, and public health.

Infectious disease responses to human climate change adaptations.

Many recent studies have examined the impact of predicted changes in temperature and precipitation patterns on infectious diseases under different greenhouse gas emissions scenarios. But these emissions scenarios symbolize more than altered temperature and precipitation regimes; they also represent differing levels of change in energy, transportation, and food production at a global scale to reduce the effects of climate change. The ways humans respond to climate change, either through adaptation or mitigation, have underappreciated, yet hugely impactful effects on infectious disease transmission, often in complex and sometimes nonintuitive ways. Thus, in addition to investigating the direct effects of climate changes on infectious diseases, it is critical to consider how human preventative measures and adaptations to climate change will alter the environments and hosts that support pathogens. Here, we consider the ways that human responses to climate change will likely impact disease risk in both positive and negative ways. We evaluate the evidence for these impacts based on the available data, and identify research directions needed to address climate change while minimizing externalities associated with infectious disease, especially for vulnerable communities. We identify several different human adaptations to climate change that are likely to affect infectious disease risk independently of the effects of climate change itself. We categorize these changes into adaptation strategies to secure access to water, food, and shelter, and mitigation strategies to decrease greenhouse gas emissions. We recognize that adaptation strategies are more likely to have infectious disease consequences for under-resourced communities, and call attention to the need for socio-ecological studies to connect human behavioral responses to climate change and their impacts on infectious disease. Understanding these effects is crucial as climate change intensifies and the global community builds momentum to slow these changes and reduce their impacts on human health, economic productivity, and political stability.

Observation-inferred resilience loss of the Amazon rainforest possibly due to internal climate variability

Abstract. Recent observation-based studies suggest that the Amazon rainforest has lost substantial resilience since 1990, indicating that the forest might undergo a critical transition in the near future due to global warming and deforestation. The idea is to use trends in a lag-1 auto-correlation of leaf density as an early-warning signal of an imminent critical threshold for rainforest dieback. Here we test whether the observed change in auto-correlations could arise from internal variability using historical and control simulations of nine sixth-generation Earth system model ensembles (Phase 6 of the Coupled Model Intercomparison Project, CMIP6). We quantify trends in the leaf area index auto-correlation from both models and satellite-observed vegetation optical depth from 1990 to 2017. Four models reproduce the observed trend with at least one historical realization whereby the observations lie at the upper limit of model variability. Three out of these four models exhibit similar behavior in control runs, suggesting that historical forcing is not necessary for simulating the observed trends. Furthermore, we do not observe a critical transition in any future runs under the strongest greenhouse gas emission scenario (SSP5-8.5) until 2100 in the four models that best reproduce the past observed trends. Hence, the currently observed trends could be caused simply by internal variability and, unless the data records are extended, have limited applicability as an early-warning signal. Our results suggest that the current rapid decline in the Amazon rainforest coverage is not foremost caused by global warming.

Future climate doubles the risk of hydraulic failure in a wet tropical forest.

Future climate presents conflicting implications for forest biomass. We evaluate how plant hydraulic traits, elevated CO2 levels, warming, and changes in precipitation affect forest primary productivity, evapotranspiration, and the risk of hydraulic failure. We used a dynamic vegetation model with plant hydrodynamics (FATES-HYDRO) to simulate the stand-level responses to future climate changes in a wet tropical forest in Barro Colorado Island, Panama. We calibrated the model by selecting plant trait assemblages that performed well against observations. These assemblages were run with temperature and precipitation changes for two greenhouse gas emission scenarios (2086-2100: SSP2-45, SSP5-85) and two CO2 levels (contemporary, anticipated). The risk of hydraulic failure is projected to increase from a contemporary rate of 5.7% to 10.1-11.3% under future climate scenarios, and, crucially, elevated CO2 provided only slight amelioration. By contrast, elevated CO2 mitigated GPP reductions. We attribute a greater variation in hydraulic failure risk to trait assemblages than to either CO2 or climate. Our results project forests with both faster growth (through productivity increases) and higher mortality rates (through increasing rates of hydraulic failure) in the neo-tropics accompanied by certain trait plant assemblages becoming nonviable.

Predicting the Future Distribution and Habitat Suitability of Ilex latifolia Thunb. in China under Climate Change Scenarios

Ilex latifolia Thunb., a plant of significant economic and medicinal value, is both edible and medicinal. Assessing the climate suitability for I. latifolia has profound implications for advancing medical progress and enhancing the quality of human life. This study comprehensively utilized data on the field distribution of I. Latifolia, as well as corresponding climatic, topographical, and soil data at these distribution points, with the aid of future climate data predicted by global climate models, and employed the MaxEnt model to predict and analyze the climate suitability areas of I. latifolia under three greenhouse gas emission scenarios (SSP126, SSP245, and SSP585). The research covers the spatiotemporal distribution characteristics, suitable growth range, and influencing factors from the present to the end of the 21st century (2041–2100). The predictive results of the MaxEnt model indicate that, under current climatic conditions, the main suitable growth areas for I. latifolia are concentrated in the southeastern part of China, especially in the provinces of Fujian and Zhejiang. However, facing the challenges of future climate change, it is expected that the moderately high suitable growth areas for I. latifolia will show a trend of gradual reduction. The primary climatic factors crucial for I. latifolia’s growth are annual precipitation (1469.05 to 4499.50 mm), the lowest temperature in the coldest month (−18.72 to 3.88 °C), seasonal precipitation changes (11.94 to 64.69 mm), and topographic slope (0.37 to 3.00 °), with annual precipitation being the most influential. The findings of this study provide a scientific basis for the introduction of I. latifolia and offer important reference information for the artificial cultivation, resource development, and achievement of sustainable industrial development of this species.

Estimate of Temperature Rise in the 21st Century for Various Scenarios

The International Panel on Climate Change (IPCC) published a lengthy report on climate change in early 2023. This report hypothesizes five potential scenarios of greenhouse gas emissions from 2015 to the end of the century (2100) and estimates the global average temperature gain in the year 2100 from the mid-1800s for each scenario. The method of calculation in the IPCC report is obscure. The results are merely stated. The present paper provides a clear method for estimating the temperature gain each year from 2015 until 2100, along with yearly estimates of ppm of CO2. To facilitate the calculations, a set of scenarios of future emissions was chosen that is analogous to the scenarios used by the IPCC but is more amenable to computation. The basic assumption in this paper is that most of the temperature gain from the mid-1800s to 2015 (1.15 C – as reported by the IPCC) was due to rising CO2 concentration in the atmosphere and a relationship is thereby derived between warming and gigatons of CO2 emitted for the period: 1800s to 2015. If it is assumed that the amount of warming per gigaton CO2 from the past persists into the 21st century, then future warming in the 21st century can be estimated for any assumed future scenario of CO2 emissions. This paper provides a simple and clear estimate of yearly CO2 ppm and temperature rise from 2015 to 2100 since the 1800s for a set of scenarios that cover the likely range of future emissions.