Representative Concentration Pathways Research Articles

Changes in high-latitude surface energy balance driven by snowpack and vegetation dynamics under warmer climate

Abstract With rapid climate warming, expected changes in snowpack and vegetation will alter the seasonal surface albedo of high-latitude ecosystems. The extent to which these albedo changes may affect surface energy balances and thus soil temperatures is uncertain, but represents a potentially important component of ecosystem feedbacks to climate change. Here, we apply a well-tested process-rich ecosystem model, ecosys, to examine changes in seasonal surface albedo and soil temperature driven by climate-induced snowpack and vegetation changes across Alaska under a warmer twenty-first century climate. Under the Representative Concentration Pathway 8.5 climate change scenario, the modeled changes in surface albedo exhibited large seasonal and spatial variations. We found spring albedo decreases driven by increases in snow-free periods (>20 d) and an extended growing season length that resulted in greater gains in leaf area index (LAI) in most parts of Alaska. In contrast, we modeled increases in summer and winter albedo (despite modeled increases in LAI) across much of the boreal forest due to an increased proportion of aspen, which has a higher leaf albedo than the currently dominant black spruce. Modeled latent heat fluxes generally increase across the twenty-first century, particularly during the spring and summer. Overall, climate warming and changes in surface energy fluxes resulted in a 3.5 ± 0.50 °C increase in spatial- and annual-averaged top 10 cm surface soil temperatures across Alaskan ecosystems by the year 2100, with larger increases in tundra than boreal forest regions. We conclude that under warmer climates, seasonal variations in albedo and surface energy fluxes are particularly pronounced during the spring and summer, driven by changes in snowpack and vegetation dynamics.

Nonunidirectional Habitat Changes Associated With Global Climate Change: The Example of the Indo‐Pacific King Mackerel (Scomberomorus guttatus) in the Taiwan Strait

ABSTRACTClimate change poses a significant threat to marine ecosystems, potentially altering the distribution of marine organisms and causing many species to migrate towards the poles. The habitat changes of species targeted for fishing are likely to affect fishing activities and the livelihoods of coastal communities. Hence, the present study analyzed the distribution of Indo‐Pacific king mackerel (IKM) in the Taiwan Strait (TS) by using ensemble modeling and considering two representative concentration pathway (RCP) scenarios (2.6 and 8.5) to assess the implications of predicted climate change. Four species distribution models incorporating sea surface height, chlorophyll, salinity, and temperature were used as inputs to create an ensemble model that replicated IKM distribution under current ocean conditions. The ensemble habitat model does not show monotonic decrease of IKM habitat but reveals more complex change in the 21st century with a hump around 2050. By end of the century, IKM is predicted to decline under RCP 8.5 scenario more seriously than under RCP 2.6. The study highlights the need for adaptation measures in managing IKM fisheries in the TS, emphasizing the importance of considering non‐unidirectional habitat changes in the global oceans as well.

Projected Changes in Dry and Wet Spells over West Africa during Monsoon Season Using Markov Chain Approach

This study examines projected changes in dry and wet spell probabilities in West Africa during the July–August–September monsoon season using a Markov chain approach. Four simulations of regional climate models from the CORDEX-Africa program were used to analyze projected changes in intraseasonal variability. The results show an increase in the probability of having a dry day, a dry day preceding a wet day, and a dry day preceding a dry day, and a decrease in the probability of wet days in the Sahel region under anthropogenic forcing scenarios RCP4.5 and RCP8.5. The decrease in wet days is stronger in the far future and under the RCP8.5 scenario (up to −30%). The study also finds that the probability of consecutive dry days (lasting at least 7 days and 10 days) is expected to increase in western Sahel, central Sahel, and the Sudanian Area under both scenarios, with stronger increases in the RCP8.5 scenario. In contrast, a decrease is expected over the Guinea Coast, with the changes being more important under the RCP4.5. Dry spell probabilities increasing in the Sahel areas and in the northern Sudanian Area is linked to the increase in the very wet days (R95P) in the daily rainfall intensity index (SDII). These changes in dry and wet spell probabilities are important for water management decisions and risk reduction in the energy and agricultural sectors. This study also highlights the need for decision-makers to implement mitigation and adaptation policies to minimize the adverse effects of climate change.

The implications of climate change for New Zealand’s freshwater fish

Climate change is poised to reshape ecological communities globally by driving species into new environments and altering interactions between species. Conservation efforts should not only address current pressures but also plan for future pressures, such as sensitive species moving into degraded environments or arising problematic trophic interactions. This study sought to assess how climate change may affect the end-of-century distributions of New Zealand’s native and non-native freshwater fish, including consequences for the overlap between trout (a non-native sports fish) and native species vulnerable to trout predation. Random forest modelling was used to predict end-of-century distributions for New Zealand’s freshwater fish based on six hydrologically downscaled global climate models across four representative concentration pathways. Severe climate change impacts could drive nine native fish species to extinction or near-extinction and cause substantial declines in another eight native species. Seven non-natives are also predicted to decline substantially, including a 30-40% reduction in the extent of trout. To avert these potential extinctions, it is crucial to mitigate climate change severity and improve land use impacting freshwater ecosystems.

Building high-resolution projections of temperature potential changes using statistical downscaling for the future period 2026-2100 in the Highland region of Yemen – A supportive approach for empowering environmental planning and decision-making

Environmental resources and ecological systems are significantly affected by the steady rise of the global temperature. However, the degree of temperature change at the regional and local levels is uncertain. The uncertainty arises from various factors, but mostly due to the short length of ground data and dependency of local studies on the large-scale and spatially coarse output of Global Climate Models (GCMs). Therefore, the output of GCM cannot be directly used in impact assessment studies at a regional and local level. In this study, the Statistical Down-Scaling Model (SDSM) is employed to investigate the magnitude of temperature changes (Minimum and Maximum Temperature) for the future period 2026-2100. The SDSM builds relationships between large-scale predictors and local climate variables, allowing for finer-resolution projections at a regional level. The study utilized the Climate Hazard Infra-Red Temperature with Station (CHIRTS-daily) to complete daily missing records in more than 90 ground stations. Additionally, predictors of the National Center for Environmental Prediction (NCEP) for the historical period (1961-2010) and the Canadian Earth System Model (CanESM2) for the future period (2026-2100) are employed to calibrate SDSM and to build finer-resolution scenarios under two representative concentration pathways; RCP2.6 and RCP8.5. The methodology additionally involved validating the SDSM performance using observed historical data before applying it to future projections. The findings indicate that both minimum and maximum temperatures (T-min and T-max) will increase, with a more pronounced rise in minimum temperature (T-min). Over the future period (2026-2100), the projected average temperature rise is 1.10°C (T-max) and 1.43°C (T-min) under RCP2.6. For RCP8.5, the projected average increases are 1.56°C and 2.3°C for T-max and T-min, respectively. Overall, the most significant increase is projected to occur in the 2090s (2076-2100) under RCP8.5, particularly in the lowlands and wadis of Al Mahwit and Raymah governorate. In these areas, the minimum temperature (T-min) exhibited an increased absolute value of up to 3.2°C. This high rise in temperatures is expected to result in increased evapotranspiration, prolonged droughts, and possibly breakouts of some plant diseases and pests. This would require effective adaptation measures such as harvesting rainwater and growing short-time and heat-resistance crops. Engaging in field visits and social discussions added depth to the study by introducing various traditional methods and indigenous practices. Valuable resources for future efforts to mitigate the potential impacts of climate change are offered by these insights.

The Analysis and the Impact of Surface Temperature Anomalies on the Health of Residents in the River Niger Basin Development Authority Area, West Africa.

This study investigates the impact of surface temperature anomalies on the health of residents within the River Niger Basin Development Authority (RIBDA) enclave, which covers Nigeria, Niger, and Mali in West Africa, with a focus on the regional implications for public health. Historical climate data from 1985 to 2014, sourced from the Climatic Research Unit Time-Series, Version 3.22 (CRU TS 3.22), was analyzed to comprehend past climate patterns and establish a baseline for future comparisons. Predictions for future climate conditions (2015-2044) were derived by adjusting the CRU data using temperature projections from the Community Climate System Model 4 under the Representative Concentration Pathway 8.5 scenario. To assess the potential impacts of these climate changes, particularly during the boreal summer season of July-August-September (JAS), the study utilized the Hydrology, Entomology, and Malaria Transmission Simulator (HYDREMATS). Findings indicate that surface temperature can intricately influence disease transmission, with varied effects on parameters such as Ro, EIR, prevalence, and immunity index. Observations revealed fluctuations in temperature anomalies over the years, with negative anomalies in 1991-1995 and positive anomalies in subsequent years. Although precise predictions for 2016-2044 are challenging based solely on data trends from 1985 to 2015, continued temperature rises could potentially lead to increased disease prevalence and decreased immunity index. Moreover, the analysis identified a notable temporal increase in mean annual temperature and mean annual maximum temperature from 1999 to 2020, suggesting a faster warming trend in maximum temperatures compared to minimum temperatures. This increase in temperature variability may alter the onset and cessation dates of the rainy season, affecting water availability, accessibility, and consumption, consequently fostering conditions conducive to health-related diseases. By incorporating predicted long-term temperature changes due to greenhouse gas emissions while maintaining current inter-annual climate patterns, this approach allows researchers to anticipate potential future health implications in the studied regions.

Mapping and assessing the future provision of lake ecosystem services in Lithuania

Lakes supply multiple ecosystem services (ES), key to supporting socio-ecologic systems and human well-being. In the context of future land use and climate changes, it is imperative to anticipate potential impacts on lake ES supply. Hence, studies that deal with future lake ES, such as mapping, are lacking. In this work, we mapped and assessed the future supply of three ES: (1) maintenance of nursery conditions (nursery ES), (2) maintenance of chemical conditions of freshwaters (nutrient regulation ES), and (3) direct and indirect cultural outputs (recreation ES) in Lithuania. Four future scenarios were utilised, integrating land use and climate changes: A0 - business as usual; A1-urbanisation; A2: land abandonment and afforestation; and A3 - agricultural intensification. The projected year was 2050, following the intermediate Representative Concentration Pathway (RCP 4.5). The future scenarios were simulated using the open-source software Dinamica EGO based on a 6-step modelling framework. Statistical differences among the scenarios and ES were analysed by applying a Kruskal-Wallis ANOVA test. Spatial analysis was done by performing a Moran's I and Getis-Ord (Gi∗) hotspot analysis. The results showed significant differences in nursery and nutrient regulation ES. The highest supply in nursery ES was observed for the A0 scenario. For nutrient regulation ES, the lowest ES supply was identified for the A1 scenario and for recreation ES, the highest was found in the A2 scenario. The eastern and northeastern regions of Lithuania showed a high ES supply. Hot spots were only identified in the eastern region. These regions are associated with a high area covered by forests and protected areas. The central region shows a low ES supply, identified as a cold spot where the agricultural landscape dominates. The results of the PCA analysis revealed an association between nursery and recreation ES. Nutrient regulation was not associated with the other two ES. Mapping and assessing the impact of future scenarios is vital to anticipating the potential dynamics of lake ES, especially in the context of climate change. This information is essential in the context of environmental management, helping decision-makers to ensure a sustainable ES supply and contributing to human wellbeing.

Projection of Climate Extreme Indices Based on Representative Concentration Pathways (RCP) in Aceh Province

Projection of Climate Extreme Indices Based on Representative Concentration Pathways (RCP) in Aceh Province

Adapted RCP 4.5 and 8.5 climate change scenarios for invasive Sus scrofa in Mexico

Climate change is a common factor that contributes to the growth or decline of animal populations. The present study, conducted using the Species Distribution Model, highlights the fact that despite the recognized negative impact of wild boar (Sus scrofa) on semi-natural areas and agricultural systems worldwide, the species remains poorly studied. According to projections for Representative Concentration Pathways (RCP) 4.5 and 8.5, increased clusters of wild boar abundance are expected to emerge around fragmented species assemblages by 2070. Sus scrofa is an extremely destructive and rapidly spreading invasive species whose movement appears to be facilitated by humans. As a consequence, many endemic plants are threatened with extinction. Biological corridors between fragments with poor conservation status should be linked to priority areas for adequate protection. The creation of preserved landscapes in territories separated from semi-natural ecosystems is recommended. Additionally, these measures can help mitigate the negative impact of S. scrofa on local biodiversity. Continuous monitoring and adaptive management strategies will be crucial for long-term conservation of the affected areas. Environmental protection efforts must prioritize the restoration of natural habitats and the implementation of strict regulations to control the spread of this invasive species. Collaborations between conservation organizations, governments, farmers, and local communities are essential to ensure effective wild boar management and the preservation of arable land and forests. Moreover, public awareness campaigns about the environmental impact of wild boar and the importance of conservation efforts are critical for garnering broader support.

Changes in Distribution Ranges of Abies Species Dominating in the Forests of Northeast Asia Since the Last Glacial Maximum

ABSTRACTAimClimate variations within the stadial–interstadial cycles drive shifts in the distribution of forest dominants. This study examines how climate dynamic alters the distribution ranges of two boreal and one cold‐temperate Abies species dominating in Northeast Asia.LocationNortheast Asia: China, Japan, Korea and Russia.TaxonAbies nephrolepis, A. sachalinensis (sect. Balsamea) and A. holophylla (sect. Pseudopicea).MethodsWe developed climate envelope species distribution models (SDMs) using warmth and coldness indices, the continentality index, and proxies of rain and snow precipitation indices. We interpolated SDMs on reconstructed climates for the Last Glacial Maximum (LGM) and the Holocene Climatic Optimum (HCO) and to predicted climates for 2070 under global warming scenarios RCP2.6 and RCP8.5.ResultsDuring the LGM, the climatic optimum for all species covered extensive areas on the shelves of the Japanese and Yellow Seas, facilitated by the global sea level drop. The interglacial climatic optimum supports the expansion of A. nephrolepis and A. sachalinensis compared to the LGM, whereas the range of A. holophylla climatic niche range experiences a reduction.Main ConclusionsOur findings highlight the significant impact of climatic oscillations on the spatial distribution and ecological dynamics of Abies species in Northeast Asia. The contrasting responses of boreal and temperate fir species to glacial and interglacial periods underscore the complex interplay between climate change and the distribution of forest dominants. Projections under future warming scenarios suggest that Abies species will face further range shifts, emphasising the need for adaptive forest management and conservation strategies, especially in the southern part of their distribution.

Impact of climate change on the distribution of the invasive water hyacinth in Ethiopia

The introduction of exotic species poses one of the greatest threats to biodiversity globally. Water hyacinth is a dangerous invasive species that has harmed Ethiopia’s wetland ecology and economy. This research aims to evaluate the current distribution of water hyacinth and the impact of environmental variables on its spread, while also mapping future habitat suitability under climate change scenarios and assessing how these changes may influence the species' potential expansion. To estimate the risks of climate change to the species, a predictive model was developed from six modeling methodologies to investigate the climatic suitability of target species for the years 2050 and 2070 under two Representative Concentration Pathway (RCP) scenarios (RCP4.5 and RCP 8.5). Under the current climatic scenario, only 69.78% (789 503.8 km2) and 16.02% (181 262.8 km2) of the country is moderately and highly suitable for species dispersion and invasion respectively. The remaining 14.2% (160 620.9 km2) is unsuitable for the distribution and invasion of the species. In 2050, under the RCP4.5 and RCP 8.5, the ‘highly suitable’ range of water hyacinth is anticipated to expand by 16.35% and 15.39%, whereas the ‘moderately suitable’ area is predicted to increase by 70.81% and 71.52%, respectively. Under the RCP8.5 scenarios, compared to the current climatic conditions, in 2070 the ‘highly suitable’ region for the species is expected to increase by 11.48%. Its continuing growth would exacerbate the issue of ecological and economic crisis, cause significant economic and environmental harm and endanger the community’s way of life. In order to avert or reduce these effects, a thorough examination of water hyacinth along the two RCPs by water resource scientists and mamangers, that takes into account how climate change is affecting water hyacinth growing locations in Ethiopia, and provides a proper solution, is mandatory.

Wave climate projections off coastal French Guiana based on high-resolution modelling over the Atlantic Ocean

Global warming is altering the atmosphere and ocean dynamics worldwide, including patterns in the generation and propagation of ocean waves, which are important drivers of coastal evolution, flood risk, and renewable energy. In French Guiana (northern South America), where most of the population is concentrated in coastal areas, understanding future wave climate change is critical for regional development, planning and adaptation purposes. The most energetic waves typically occur in boreal winter, in the form of long-distance swell originating from the mid-latitude North Atlantic Ocean. However, existing high-resolution wave climate projections that cover the French Guiana region focus on the hurricane season only (summer-fall). In this study, we used a state-of-the-art basin-scale spectral wave model and wind fields from a high-resolution atmospheric global climate model to simulate present and future winter (November to April) wave climate offshore of French Guiana. The model performance was evaluated against wave data from ERA5 reanalysis, satellite altimetry and coastal buoys between 1984 and 2013. For the future greenhouse gas emission scenario (Representative Concentration Pathway) RCP-8.5, we found a statistically significant overall projected decrease (∼5 %) in wintertime average significant wave height and mean wave period, with a ∼1° clockwise rotation of mean wave direction. The results suggest that these decreasing trends are primarily driven by changes in large-scale patterns across the Atlantic that counteract an expected increase in local wind speed. We discuss the implications of such projections for mud-bank dynamics along coastal French Guiana, although further local studies are required to address future coastal evolution and hazards. Finally, we identify a need for more in situ wave data near French Guiana to improve quantitative assessments of model performance and allow a correction of possible model biases.

Increasing warm-season evaporation rates across European lakes under climate change

Lakes represent a vital source of freshwater, accounting for 87% of the Earth’s accessible surface freshwater resources and providing a range of ecosystem services, including water for human consumption. As climate change continues to unfold, understanding the potential evaporative water losses from lakes becomes crucial for effective water management strategies. Here we investigate the impacts of climate change on the evaporation rates of 23 European lakes and reservoirs of varying size during the warm season (July–September). To assess the evaporation trends, we employ a 12-member ensemble of model projections, utilizing three one-dimensional process-based lake models. These lake models were driven by bias-corrected climate simulations from four General Circulation Models (GCMs), considering both a historical (1970–2005) and future (2006–2099) period. Our findings reveal a consistent projection of increased warm-season evaporation across all lakes this century, though the magnitude varies depending on specific factors. By the end of this century (2070–2099), we estimate a 21%, 30% and 42% average increase in evaporation rates in the studied European lakes under RCP (Representative Concentration Pathway) 2.6, 6.0 and 8.5, respectively. Moreover, future projections of the relationship between precipitation (P) and evaporation (E) in the studied lakes, suggest that P-E will decrease this century, likely leading to a deficit in the availability of surface water. The projected increases in evaporation rates underscore the significance of adapting strategic management approaches for European lakes to cope with the far-reaching consequences of climate change.

Quantifying food security and mitigation risks consequential to climate change impacts on crop yields

Abstract Climate change is expected to impact crop yields globally, with some regions benefiting from favorable conditions and CO2 fertilization, while others face adverse effects from altered precipitation and higher temperatures. Changes in crop yields can destabilize the global food system and pose challenges to food security. Moreover, crop production is crucial, as biofuels are becoming increasingly important contributors to climate change mitigation measures aimed at limiting global warming. This study uses the IMAGE integrated assessment model framework to analyze different indicators related to food security and climate change mitigation under varying climate change impacts on crop yields. Twelve spatially explicit crop productivity projections were taken from the full archive of the Global Gridded Crop Model Intercomparison (GGCMI) of 120 climate-crop model combinations, forced by CMIP6-based climate scenarios. The selection includes two average-performing climate-crop model combinations, two pessimistic combinations that perform one standard deviation below the mean, and two optimistic model combinations that perform one standard deviation above the mean. To single out the effect of climate change on productivity changes, we drew samples from two representative concentration pathways (RCP2.6 and RCP8.5). These productivity projections were applied within an otherwise uniform scenario (SSP2) and analyzed for their effect on total calorie demand, crop prices, and number of people at risk of undernourishment to quantify food security. Risks to climate change mitigation targets were explored by modeling the total bioenergy supply, emissions, and global mean temperature. The results revealed significant differences in the risk of food security and mitigation potential between different regions and climate change scenarios. Across scenarios, the crop area extent can vary up to 2 million km2 due to changing crop yields. The projected change in global hunger ranges from 60 to 160 million undernourished people, indicating uncertainty between climate and crop model combinations. Low-income regions are especially impacted because of their high sensitivity to changes in food prices. Global climate change mitigation ambitions can also deviate by the latter part of the 21st century, as changes in yields will impact biofuel production as well as Agriculture, Forestry and Other Land Use (AFOLU) emissions. The quantitative insights generated by this study highlight the need for global policy efforts to make the agricultural system more adaptive to climate change to handle potential negative impacts.

Mapping tree canopy thermal refugia for birds using biophysical models and LiDAR.

Accurately predicting exposure of animals to climate change requires evaluating the effects of warming on the microclimates they occupy. Birds, like many other taxa, make extensive use of cool microsites in vegetation during hot weather. Taking advantage of recent advances in modelling tree canopy microclimates, we combined LiDAR-based individual tree canopy mapping and biophysical modelling to evaluate the current and future availability of cool microsites in a subtropical African savanna landscape. We constructed biophysical models for two common bird species, an ~ 40-g bulbul and an ~ 200-g hornbill, and modelled exposure to conditions under which the body temperature (Tb) of individuals resting in canopies exceeds 42°C, equivalent to ~ 2°C above resting thermoneutral Tb. At present, 34.5% of trees taller than 2m in our 139-ha study site provide microclimates in which resting Tb remained below 42°C for both species during our study period. Under a Representative Concentration Pathway 8.5 climate change scenario and assuming no change in vegetation structure, by the end of the Century the availability of microsites characterized by Tb < 42°C will decrease to just 0.4% and 3.8% for bulbuls and hornbills, respectively. The proportion of trees in whose canopies bulbuls' and hornbills' exposure to Tb > 42°C is limited to < 10 d summer- 1 will decrease from 98 to 99% currently to 3.0% and 24.3% by end-century, respectively. These findings reveal the magnitude of changes for birds in a savanna thermal landscape under a business-as-usual emissions scenario.

Projections of Climate Change Impact on Stream Temperature: A National-Scale Assessment for Poland

This national-scale assessment explores the anticipated impact of climate change on stream temperature in Poland. Utilizing an ensemble of six EURO-CORDEX projections (2006 to 2100) under Representative Concentration Pathways (RCPs) 4.5 and 8.5, the study employs the Soil and Water Assessment Tool (SWAT) to simulate stream temperature regimes. Validation against observed stream temperatures at 369 monitoring points demonstrates the reliability and accuracy of the SWAT model performance. Projected changes in air temperature reveal distinct seasonal variations and emission scenario dependencies. The validated stream temperature model indicates a uniform warming tendency across Poland, emphasizing the widespread nature of climate change impacts on aquatic ecosystems. Results show an increase in country-averaged stream temperature from the baseline (16.1 °C), with a rise of 0.5 °C in the near future (NF) and a further increase by 1 °C in the far future (FF) under RCP4.5. Under RCP8.5, the increase is more pronounced, reaching 1 °C in the NF and a substantial 2.6 °C in the FF. These findings offer essential insights for environmental management, emphasizing the need for adaptive strategies to mitigate adverse effects on freshwater ecosystems. However, as a preliminary study, this work uses a simplified temperature model that does not account for detailed hydrological processes and spatial variability, making it a good starting point for more detailed future research.

Estimation of Future Climate Change in Low Folded Zone, Iraq with the LARS-WG and Five GMS Models under CMIP5 Scenarios

This study investigates the trends of climate change in the Low Folded Zone region of Iraq and provides future projections for daily maximum and minimum temperatures, as well as precipitation. Using the LARS-WG model and five General Circulation Models (GCMs) under three Representative Concentration Pathways (RCP) scenarios, the research aims to provide valuable insights into the anticipated changes in climate variables. The calibration and validation of the model demonstrate its capability to simulate future climatic data, with statistical indices indicating a strong correlation between observed and generated data. The projected future temperatures showed a consistent increase across all selected stations, with average annual maximum temperatures expected to rise by 1.06 to 5.48°C by the end of the twenty-first century. The highest increase in temperatures was predicted under the high-emission scenario RCP8.5. The results also indicated spatial and temporal variations in precipitation patterns, with the annual percentage increase in precipitation ranging from 7.07% to 10.75% for RCP 2.6, 0% to 2.2% for RCP4.5, and 3.7% to 6.8% for RCP8.5. The findings reveal a projected increase in annual temperatures and variable precipitation patterns, highlighting the urgency of proactive measures to address the challenges posed by climate change in the region. The results of this study are crucial for informing decision-makers and planners in developing strategies for climate change adaptation and resource management, particularly in water resource management and agricultural planning.

Climate Change Effects on Land Use and Land Cover Suitability in the Southern Brazilian Semiarid Region

Climate change is expected to alter the environmental suitability of land use and land cover (LULC) classes globally. In this study, we investigated the potential impacts of climate change on the environmental suitability of the most representative LULC classes in the southern Brazilian semiarid region. We employed the Random Forest algorithm trained with climatic, soil, and topographic data to project future LULC suitability under the Representative Concentration Pathway RCP 2.6 (optimistic) and 8.5 (pessimistic) scenarios. The climate data included the mean annual air temperature and precipitation from the WorldClim2 platform for historical (1970–2000) and future (2061–2080) scenarios. Soil data were obtained from the SoilGrids 2.1 digital soil mapping platform, while topographic data were produced by NASA’s Shuttle Radar Topography Mission (SRTM). Our model achieved an overall accuracy of 60%. Under the worst-case scenario (RCP 8.5), croplands may lose approximately 8% of their suitable area, while pastures are expected to expand by up to 30%. Areas suitable for savannas are expected to increase under both RCP scenarios, potentially expanding into lands historically occupied by forests, grasslands, and eucalyptus plantations. These projected changes may lead to biodiversity loss and socioeconomic disruptions in the study area.

Role of the Warm Arctic Cold Eurasian-like pattern on the near future warming rate of East Asian surface temperature

Abstract Internal climate variability (ICV) plays an important role in either accelerating or slowing down the rate of surface temperature warming in East Asia in the near future. To examine the influence of ICV on East Asian surface temperature in the near future, we mainly analyzed the data sets obtained from Max Planck Institute Grand Ensemble model simulations under the Representative Concentration Pathway 8.5 scenario. It is found that the ICV associated with the so-called Warm Arctic-Cold Eurasian (WACE)-like pattern contributes to the near-future warming rate of East Asian surface temperature. Similar results are also obtained from large ensemble model simulations participating in the Coupled Model Intercomparison Project Phase 6 under the Shared Socioeconomic Pathways 5–8.5 scenario. This implies that the near-term warming rate in East Asia could vary depending on how the climate model simulates the WACE-like pattern, indicating that the ability to accurately simulate ICV in climate models is crucial for future climate mitigation and adaptation policies.

Mapping the Future: Climate-Induced Changes in Aboveground Live-Biomass Carbon Density Across Mexico’s Coniferous Forests

Climate variations in temperature and precipitation significantly impact forest productivity. Precipitation influences the physiology and growth of species, while temperature regulates photosynthesis, respiration, and transpiration. This study developed bioclimatic models to assess how climate change will affect the carbon density of aboveground biomass (cdAGB) in Mexico’s coniferous forests for 2050 and 2070. We used cdAGB data from the National Forest and Soils Inventory (INFyS) of Mexico and 19 bioclimatic variables from WorldClim ver. 2.0. The best predictors of cdAGB were obtained using machine learning techniques with the “caret” library in R. The model was trained with 80% of the data and validated with the remaining 20% using Generalized Linear Models (GLMs). Current cdAGB prediction maps were generated using the best predictors. Future cdAGB was calculated with the average of three general circulation models (GCMs) of future climate projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5), under four Representative Concentration Pathways (RCPs): 2.6, 4.5, 6.0, and 8.5 W/m2. The results indicate cdAGB losses in all climate scenarios, reaching up to 15 Mg C ha−1, and could occur under the RCP 8.5 scenario by 2070 in the central region of the country. Temperature-related variables are more important than precipitation variables. Bioclimatic variables can explain up to 20% of the total variance in cdAGB. The temperature in the study area is expected to increase by 2.66 °C by 2050 and 3.36 °C by 2070, while precipitation is expected to fluctuate by ±10% relative to the current values, which could geographically redistribute the cdAGB of the country’s coniferous forests. These findings underscore the need for forest management to focus not only on biodiversity conservation but also on the carbon storage capacity of these ecosystems.