Global Temperature Research Articles

Does Environmental Factor Influence the Rating of Creditworthiness? A Comparative Analysis of Developed versus Developing Countries

This paper examines the influence of environmental factor in the determination of a country’s creditworthiness given the world’s agenda to contain the rise in global temperature. This paper leverages on two environmental factor proxies, CO2 emissions per capita and renewable energy per capita, to assess whether the environmental factor plays a significant role in determining the sovereign credit ratings (SCRs) issued by three leading credit rating agencies (CRAs), i.e., Moody’s, S&P and Fitch for 49 countries spanning the period of 2000 to 2021. The empirical results show that the environmental factor is being considered by the CRAs. Since the signing of the Paris Agreement in 2015, the environmental factor has turned significant for the determination of the SCRs of developing countries, but not for the developed countries. The creditworthiness of developing countries is subjected to a penalty for CO2 emissions. While the level of renewable energy adoption is higher amongst the developed countries, the evidence does not show that their level of CO2 emissions is lower. This paper recommends the CRAs to explicitly state the environmental factor criteria and update their SCR methodologies to ensure uniformity in application.

Assessing climate-driven glacial retreat, snow-cover reduction and GLOF risks: implications for water resource management amid rising global temperatures and CO2

Context The consequences of climate change, including alterations in snow and glacier patterns and rising temperatures, pose a risk of glacial lake outburst floods (GLOFs), which can have cross-border impacts, leading to the loss of life and property downstream. Aims This research focused on the assessment of changes in snow cover within Chitral district imposed by temperature increase. Methods ArcGIS and Origin programs were used in this research to study the glacier pattern of Chitral. Results Therer was a significant increase of 266.7% in urban development and an expansion of 135.9 km2 in agricultural areas within this remote mountainous region. The findings of the study show that in the year 2000, >51.6% of Chitral district’s total land was covered by snow during early winter. However, this coverage drastically declined to ~6.8% by 2008. Across the initial two 4-year periods, ~44.7% (5694.6 km2) of the glaciated area transitioned to barren rock, whereas the overall reduction in snow-covered areas accounted for ~43.3% (5514.6 km2). Conclusion Owing to the increasing stress on freshwater resources, it is essential to conduct thorough analyses and monitoring of snow patterns to ensure sustainable freshwater availability and effective environmental risk management. Implications This study emphasises the critical consequences of climate-driven glacial retreat, waning snow cover and increased risks of glacial lake outburst floods (GLOFs) for the management of water resources with the rise in global CO2 and temperatures levels. These changes threaten the timing and availability of water supply, with impacts on agriculture, ecosystem and hydropower. Effective adaptation measures and sustainable management practices are crucial to alleviate these risks and ensure water security in a warming world.

Effects of Climate Change and Greenhouse Gas Emission Relevance to Environmental Stress on Horticultural Crops

Global climate change significantly impacts the yield and quality of sustainable horticulture crops. Rising global temperatures have forced the agricultural community to modify planting and harvesting timetables, frequently calling for earlier crop production. Notably, several concerning elements are brought about by climate change, including greenhouse gas emissions (GHGs), higher temperatures, higher concentrations of carbon dioxide (CO2), nitrous oxide (N2O) and methane (CH4), ozone depletion (O3), and deforestation. All of these factors exacerbate environmental stresses on crops. Climate change is, therefore, likely to have a negative impact on livestock production and crop yields. Thus, the main goal of the review paper is to provide a thorough summary of the various aspects that affect the production of fruits, vegetables, and plantation crops in horticulture, with a focus on greenhouse gas emissions and environmental stressors like high temperatures, droughts, salinity, and CO2 emissions. This assessment will also look at how new greenhouse technologies and horticultural crop varieties can be used to lessen the adverse effects of climate change on crops.

Late-arriving 2023 summer marine heatwave in the East China Sea and implications for global warming

In 2023, the global temperature rose significantly, triggering a marine heatwave (MHW) in the East China Sea (ECS) from August 12 to October 13. Unlike the typical July onset, this event was delayed. Here we investigate the mechanisms behind the late onset and prolonged duration of the 2023 MHW in the ECS and its potential linkage to global warming. The early phase was driven by shortwave radiation and ocean dynamics, while the later phase saw reduced northerly winds, allowing warmer, more humid southerlies to dominate. This shift decreased the air-sea humidity difference, enhancing downward latent heat fluxes. Future CMIP6 projections also suggest that delayed MHWs are linked to weak heat exchanges, limiting the oceanic heat transport to the atmosphere. Our findings highlight the increasing risk of prolonged MHWs in the ECS and the urgent need for improved climate preparedness.

Research on the Mechanism of Load Transfer Structures in the Construction Process of “Internal Support—Large Block” Prefabricated Subway Stations

In the context of rising global temperatures, countries around the world are increasingly tailoring their own “carbon neutrality” plans. China has also formulated its “dual-carbon” goals, and the construction industry is gradually transitioning towards prefabrication to reduce carbon emissions. This paper uses the Sha Pu Station of Shenzhen’s Metro Line 12 as a case study by which to explore the effects and mechanisms of the load transfer structure during the assembly process of prefabricated subway stations. A three-dimensional finite element model considering soil–structure interaction was established using MIDAS GTS NX finite element software, 2018 version. The internal forces, stresses, and deformations of the station structure were compared under two scenarios—with and without the load transfer structure—using a control variable method. The research results indicate that the load transfer structure effectively reduces shear forces, bending moments, and stresses in the station structure; limits lateral displacements during the assembly process; and effectively concentrates the maximum stresses during construction at the location of the load transfer structure, thereby preventing stress concentration phenomena and enhancing the overall stability of the station structure. This study elucidates the role and effectiveness of the load transfer structure during the assembly of prefabricated components in subway stations, providing a reference for the construction of similar prefabricated metro stations.

Carbon Capture Storage dalam Pengelolaan Barang Milik Negara

Climate change has gained prominence following the 2015 Paris Agreement, which aims to limit global temperature rise to below 2 degrees Celsius, with efforts to keep it under 1.5 degrees Celsius. This agreement stresses the importance of collective action to reduce greenhouse gas emissions and build resilience against climate impacts. In June 2023, the global average surface temperature reached a record high, with subsequent months also setting heat records. Mitigating global warming's adverse effects, such as rising temperatures and extreme weather changes, requires significant reductions in greenhouse gas emissions. Efforts in the energy sector have led to a decrease in CO2 emissions from 40.6 million tons in 2018 to 127.67 million tons in 2023. These efforts include enhancing energy efficiency, transitioning to renewable energy, and implementing carbon capture and storage (CCS) technologies In Indonesia, CCS regulations are outlined in Minister of Energy and Mineral Resources Regulation No. 2 of 2023. CCS involves the capture, transport, injection, and permanent storage of carbon emissions. The management of state-owned assets related to CCS falls under the Ministry of Finance Regulation No. 140/PMK.06/2020, which addresses the transfer, utilization, and valuation of upstream oil and gas assets. This paper discusses the role of state asset management in the implementation of CCS in Indonesia, examining current regulations, challenges, and future prospects.

Earth system responses to different levels of greenhouse gas emissions mitigation

Anthropogenic carbon dioxide (CO2) emissions are the main driver of climate change, with global warming increasing almost linearly with cumulative CO2 emissions. Hence, future warming will primarily result from future emissions of CO2 with contributions from other greenhouse gases (mostly CH4 and N2O) and aerosols. Climate projections of the 21st century, such as those assessed by the IPCC, are provided from comprehensive climate models, also called Earth System models, driven by scenarios of the 21st century evolution of emissions from those climate forcers. While it seems now inevitable that the world will reach 1.5°C of warming above pre-industrial levels by the early 2030s, the extent to which we exceed this warming level and how quickly we may be able to reduce temperatures again depends strongly on global activity taken now to limit emissions. In this paper, we review the current understanding on Earth system changes under two highly contrasted possible future worlds. We first focus on high-end scenarios, where anthropogenic emissions continue to increase over the course of the 21st century, leading to large warming levels, associated impacts on all components of the Earth System, and increased risks of triggering tipping points. We then assess low-end scenarios, where anthropogenic emissions rapidly decline, reaching net zero and potentially becoming net negative before the end of the 21st century. Such “overshoot” scenarios lead to a peak in global warming followed by a slow decline in global temperature, with some degree of reversibility in the global carbon cycle and key Earth system components. We also review paleoclimatic information relevant to these two contrasting future worlds. Paleoclimate evidence for geo-biosphere interactions shows that stabilizing feedbacks operate on millennial or longer timescales, whereas destabilizing feedbacks and tipping cascades occurred also on shorter timescales.

How could 50 °C be reached in Paris: Analyzing the CMIP6 ensemble to design storylines for adaptation

Reaching a surface temperature of 50 °C in a heavily populated region, like Paris, would have devastating effects. Although such a high value seems far from the present-day record of 42.6 °C, its occurrence cannot be dismissed by the end of the 21st century, due to the continuous increase of global mean temperature. In this paper, we address two questions that were asked by the City of Paris to a group of scientists: When does this event start to be likely? What are the prevailing meteorological conditions? We base our study on the CMIP6 simulation ensemble. Many of the CMIP6 yield biases in temperature. Rather than using methods of bias correction, which are not necessarily adapted to high extremes, we propose a pragmatic approach of model selection in order to seek such high temperature events that are deemed realistic. We analyze the meteorological conditions leading to first occurrences of such hot events and their common atmospheric patterns. This paper describes a simple data mining approach (on a large ensemble of climate model simulations) which could be adapted to other regions of the world, in order to help decision makers anticipating and adapting to such devastating meteorological events.

Pengaruh Setting kawasan Tamansari terhadap Temperature Humidity Index

Title: The Effect of Environmental Setting of Tamansari on Temperature Humidity Index Geometric shape, land cover type, and density impact increasing global temperature and microclimate comfort. Tamansari was originally a park, garden, and bathhouse for the King and his family. Today, Tamansari is a heritage tourism area surrounded by dense residential areas in the middle of Yogyakarta City. This study aims to determine how the setting of the Tamansari area affects changes in temperature and relative humidity, which impact changes in the Temperature Humidity Index (THI) on the micro-scale of the Tamansari area. The method used is descriptive quantitative analysis, and calculation analysis was performed using the (THI) equation. The study results showed that the THI value in the Tamansari area was uncomfortable, with a THI value of 27.77-32.52°C. Building coverage ratio, population, and human activities affect the THI value. The THI value can also change due to weather factors that affect the physical condition of the area, especially in open areas.

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.

Ammonites as paleothermometers: Isotopically reconstructed temperatures of the Western Interior Seaway track global records

Ammonites are externally shelled cephalopods that were common in the North American Western Interior Seaway (WIS), and as they grew their aragonitic shells via accretion, they recorded aspects of their environment in the stable isotopic composition of their shells. While the mobility of ammonites may complicate efforts to reconstruct temperatures from their shells, they remain a potentially valuable target for paleothermometry. In this study, we reconstruct the spatial and temporal variability of WIS temperatures using a suite of ammonites (n = 113) spanning the last 25 million years of the Cretaceous along a North-South gradient ranging from the Canadian WIS to the Mississippi Embayment. We present a temporally high-resolution (~0.6 Ma) oxygen isotope record from these ammonites that indicates cooling temperatures in the WIS of comparable magnitude (~18 °C +/− 4°) to the temperature change seen in global studies, most notably cooling from the Cretaceous Thermal Maximum in the Turonian until the late Maastrichtian. Studies disagree regarding the development and strength of a latitudinal (pole-to-equator) temperature gradient during the Cretaceous; we do not see strong evidence for a latitudinal temperature gradient in the WIS. We do not observe any bias driven by ammonite morphology in our isotopic data, though we suggest that researchers consider the effects of taxonomy and ecological bias on their temperature records. As our ammonite δ18O record matches the direction and magnitude of global temperature reconstructions, our data imply that ammonites are viable targets for paleothermometry.

Ambrosia (Ragweed) pollen - a growing aeroallergen of concern in South Africa

BackgroundRagweed is an invasive, highly allergenic weed predicted to expand its habitat with warming global temperatures. Several Ambrosia species have been identified in South Africa for well over a century, however, its presence remained undetected by allergists and aerobiologists until the development of an extensive aerospora monitoring system across South African urban areas since 2019. This paper presents the inventory of preliminary investigation of the Ambrosia airborne pollen and the taxonomic identification of ragweed species. MethodsBurkard volumetric spore traps for collecting pollen samples are set up in nine South African cities (Johannesburg, Cape Town, Pretoria, Kimberley, Durban, Potchefstroom, Ermelo, Bloemfontein and Gqeberha). Light microscopic identification was combined with environmental DNA metabarcoding analysis to confirm the species level of airborne Ambrosia at selected monitoring stations. Ragweed sensitization was examined in Cape Town between February 2019 and February 2024, using Allergy Xplorer (ALEX2) multicomponent allergen array. ResultsAmbrosia pollen was detected in five aerobiological monitoring stations over the sampling period (Durban, Kimberley, Pretoria, Potchefstroom, Johannesburg). Periods of four consistent pollination years were observed in Kimberley (min: 1; max: 16 p.g/m3) and Durban (min: 26; max: 66 p.g/m3). In Pretoria, ragweed pollen was detected for two years (2020-2021; 2022-2023) with average total annuals (5-17 p.g/m3). A peak flowering period between March and April was observed in Potchefstroom, and several ragweed pollen peaks were present between the end of December and the beginning of May in Durban. The highest number of Ambrosia pollen grains was recorded in Potchefstroom, with 308 grains, and a maximum peak of 47 p.g/m3. eDNA metabarcoding confirmed the presence of Ambrosia artemisiifolia and A.trifida species. The overall prevalence of Ambrosia-sensitisation amongst 673 tests (age range 7-72 years) was 8.2% (55/673), with no significant difference in sensitisation patterns between age groups. ConclusionOur study confirms the need to monitor the spread of ragweed, and an increasing awareness of Ambrosia as an allergen of concern in Southern Africa. Extension of aerobiological networks and testing for Ambrosia sensitisation across urban and rural sites will be required.

Organic Matter Composition as a Driver of Soil Bacterial Responses to Pig Carcass Decomposition in a Canadian Continental Climate

AbstractOrganic by‐products are released into the surrounding soil during the terrestrial decomposition of animal remains. The affected area, known as the Cadaver Decomposition Island (CDI), can undergo biochemical changes that contribute to landscape heterogeneity. Soil bacteria are highly sensitive to labile inputs, but it is unknown how they respond to shifts in dissolved organic matter (DOM) quantity and quality resulting from animal decomposition. We aimed to evaluate the relationship between soil DOM composition and bacterial activity/function in CDIs under a Canadian temperate continental climate. This was studied in soils surrounding adult pig carcasses (n = 3) that were surface deposited within a mixed forested environment (Trois‐Rivières, Québec) in June 2019. Using fluorescence spectroscopy and dissolved organic carbon analyses, we detected a pulse of labile protein‐like DOM during the summer season (day 55). This was found to be an important driver of heightened soil bacterial respiration, cell abundance and potential carbohydrate metabolism. These bacterial disturbances persisted into the cooler autumn season (day 156) and led to the gradual transformation of labile DOM inputs into microbially sourced humic‐like compounds. By the spring (day 324), DOM quantities and bacterial measures almost recovered, but DOM quality remained distinct from surrounding vegetal humic signals. All observed effects were spatially constrained to the topsoil (A‐horizon) and within 20 cm laterally from the carcasses. These findings provide valuable insight into CDI organic matter cycling within a cold‐climate ecosystem. Repeated CDI studies will however be required to capture the changing dynamics resulting from increasing global temperatures.

C2 Product Selectivity by 2D-Nanosheet of Layered Zn-doped Cu2(OH)3(NO3)- A Pre-Catalyst for Electrochemical CO2 Reduction.

The natural carbon cycle cannot mitigate and recycle the excess CO2 in the atmosphere, leading to a continuous rise in the global temperature. Electrochemical conversion of CO2 is one of the useful methods to utilise this anthropogenic CO2 and convert it into value-added chemicals. However, this process suffers the challenges of product selectivity and good Faradaic efficiency. In our current work, we report the role of Zn-doping in the 2D-Nanosheet of Cu2(OH)3(NO3)- a pre-catalyst that undergoes the in situ transformation into metallic state along with surface reconstruction. Our studies show, in the aqueous medium, the optimum amount of Zn plays a crucial role in the production of ethanol with the Faradaic efficiency of ∼45.2% though C-C coupling. Temperature-programmed desorption studies conclude that Zn increases the product selectivity for CO adsorption on Cu2(OH)3(NO3) nanosheets, further facilitating the C-C coupling at higher negative potential. The detailed XPS studies also reveal that the in-situ conversion of Cu2+ to Cu0 and Cu+ at negative potential contributes to the production of C2 products. The post-catalytic microstructural and spectroscopic studies converge to this point thatcumulative effect of oxidation state, surface reconstruction, as well as the presence of Zn modulates overall Faradaic efficiency for ethanol formation.

Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks

Neural Bayes estimators are neural networks that approximate Bayes estimators in a fast and likelihood-free manner. Although they are appealing to use with spatial models, where estimation is often a computational bottleneck, neural Bayes estimators in spatial applications have, to date, been restricted to data collected over a regular grid. These estimators are also currently dependent on a prescribed set of spatial locations, which means that the neural network needs to be re-trained for new data sets; this renders them impractical in many applications and impedes their widespread adoption. In this work, we employ graph neural networks (GNNs) to tackle the important problem of parameter point estimation from data collected over arbitrary spatial locations. In addition to extending neural Bayes estimation to irregular spatial data, the use of GNNs leads to substantial computational benefits, since the estimator can be used with any configuration or number of locations and independent replicates, thus amortising the cost of training for a given spatial model. We also facilitate fast uncertainty quantification by training an accompanying neural Bayes estimator that approximates a set of marginal posterior quantiles. We illustrate our methodology on Gaussian and max-stable processes. Finally, we showcase our methodology on a data set of global sea-surface temperature, where we estimate the parameters of a Gaussian process model in 2161 spatial regions, each containing thousands of irregularly-spaced data points, in just a few minutes with a single graphics processing unit.

Simulation of modern and future climate by INM-CM6M

Abstract The paper considers the results of climate change modelling for 1850–2100 using the INM-CM6M climate model of the Marchuk Institute of Numerical Mathematics of the Russian Academy of Sciences. The calculations were performed according to the CMIP6 protocol for modelling the present-day climate for the period from 1850 to 2014 and the IPCC scenarios SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5 of anthropogenic forcing changes in 2015–2100. We analyse changes in such characteristics of the climate system as global mean near-surface temperature, spatial distributions of near-surface temperature, precipitation, sea level pressure, and radiative forcing characteristics in comparison with observational data and results obtained with the previous (INM-CM5) version of the model. We conclude that the new version of the model is superior to the previous one in terms of the quality of simulation of the observed climate and its changes in 1960–2022. The amplitude of global warming predicted by the INM-CM6M for moderate IPCC scenarios is close to the average value of the CMIP6 model ensemble, and for severe scenarios it is closer to the upper limit of its range. For the SSP3-7.0 and SSP5-8.5 scenarios, INM-CM6M predicts a complete loss of Arctic sea ice in summer. As the rate of global warming increases, so does the amplitude and duration of extreme weather and climate events.

Basin-scale spatio-temporal development of glacial lakes in the Hindukush-Karakoram-Himalayas

Glacial lakes are expanding exponentially in the cryospheric environment of the Hindukush-Karakoram-Himalayas (HKH). Rapid glacier melting due to an above mean global annual temperature increase in HKH is attributed as the main reason for the expansion of the glacial lakes. The rapid expansion of glacial lakes increases the risk of future Glacial Lake Outburst Floods (GLOFs) events in the HKH.In the present study, glacial lake inventories for the Indus, Ganga and Brahmaputra (IGB) river basins in the HKH were generated for 1990, 2000, 2010 and 2020 using Landsat (TM & OLI) at the sub-basin level to understand the spatio-temporal and regional patterns of glacial lakes dynamics, elevational evolution, and changes in the typology. We mapped 17,641 glacial lakes (area: 1082.57 ± 192.601 km2) in 1990, 18,206 (area: 1120.95 ± 198.49 km2) in 2000, 18,399 (area: 1147.12 ± 201.26 km2) in 2010, and 19,284 (area: 1191.81 ± 209.21 km2) in 2020. Between 1990 and 2020, IGB basins showed an increase of 9.31 % in total number and 10.09 % in total area of glacial lakes. In 2020, the Brahmaputra basin had the maximum total area (area: 763.59 ± 132.14 km2), followed by Indus basin (area: 217.47 ± 43.39 km2) and the Ganga basin (area: 210.74 ± 33.66 km2). However, between 1990 and 2020, glacial lakes in the Ganga basin (n: 22.08 %) had the highest growth rate, followed by the Indus basin (n: 14.73 %) and the Brahmaputra basin (n: 4.41 %). In 2020, 76.11 % of glacial lakes were end-moraine-dammed M(e) lakes, followed by other bedrock-dammed B(o) lakes (16.45 %), supraglacial lakes (2.79 %), lateral moraine-dammed M(l) lakes (2 %), cirque B(c) lakes (1.06 %), other moraine-dammed M(o) lakes (0.38 %), and other glacial (O) lakes (1.18 %). Given the rapid growth of glacial lakes in the region along with their likely flood volumes and damage potential in case of their failures, the present study will be of importance for disaster management authorities, an important input for detection of potentially hazardous glacial lakes and for development of mitigation strategies to minimize the impact of potential future GLOF events.

Global Mean Surface Temperature: What Can We Learn from the Trajectory over a Millions-year Span?

Global mean surface temperature serves as a crucial metric in understanding the Earth’s climate dynamics, providing insights into long-term climate trends and variability. Over the course of a million years, the trajectory of global temperatures has been shaped by a multitude of factors, including natural climatic cycles, human activities, and external influences. By examining the historical trends and drivers influencing global mean surface temperature, researchers can gain valuable insights into the past, present, and future climate scenarios. This article delves into the intricate interplay of these factors and explores the lessons we can learn from studying the temperature trajectory over a million-year span.

The fertility recovering from heat stress and interactions of heat shock protein 20 with reproduction-related proteins in Monochamus alternatus.

Due to the rise in global temperatures with climate change, insects, as ectotherms, critically depend on their heat tolerance for survival and reproduction. Heat shock proteins (HSPs) are essential for heat tolerance by averting protein denaturation; however, whether HSPs contribute to reproduction-related heat tolerance remains largely unexplored. The study investigated the reproductive heat tolerance and recovery of Monochamus alternatus, a major forestry pest, in response to heat stress. Alongside impairing the development and viability of reproductive organs and sperm, heat stress was also found to reduce fecundity, fertility, mating, and oviposition behaviors. Remarkably, all reproductive parameters of M. alternatus recovered within 4 weeks postexposure. To investigate the recovery mechanisms, we identified 10 reproduction-related proteins as candidate substrate proteins of an HSP protein in M. alternatus using immunoprecipitation coupled with mass spectrometry analysis. Heat stress inhibited the transcription of these reproduction-related genes, thereby adversely affecting reproductive parameters. However, the induction of HSP20s transcription in response to heat stress appeared to facilitate the refolding of these critical reproduction-related proteins during the recovery phase, thus preventing lasting reproductive damage. Overall, this study suggests that while M. alternatus populations might be vulnerable to climate-induced temperature increases, their fertility can recover, mediated by the interaction of HSPs with reproduction-related genes. These findings offer profound insights into insect heat tolerance and recovery, expanding our understanding of HSP20 proteins' biological functions.

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.