Future Climate Change Research Articles

Warming decreased plant litter decomposition by modulating soil fauna interactions in a Tibetan alpine meadow

Litter decomposition is a vital process for maintaining ecosystem carbon cycling. It is affected by soil fauna which are predators and decomposers of litter. However, how the interactions of soil fauna communities affect litter decomposition remains unclear under warming. Here, we conducted a five-year in-situ manipulative warming experiment by Open-Top Chamber (OTC) in an alpine meadow on the Tibetan Plateau to reveal how warming affects litter decomposition. The results demonstrated that warming decreased the litter decomposition rate by 29 %, the soil collembola abundance by 25 %, and the nematode abundance by 27 %. Nematode ecological indices remain stable but a shift in the decomposition of litter to the fungivores pathway under warming. The piecewise structural equation modelling result revealed that the combined reduction in soil collembola and nematodes synergistically leads to a massive decline in litter decomposition rate under warming. Our results highlight that the interactions of soil fauna can regulate litter decomposition under warming, and collembola abundance as the “speed-limiter” of litter decomposition. Therefore, the response of changes in soil fauna relationships to warming should be completely considered in future climate change modelling of the grassland carbon cycle.

Reconstructing the rapid transitions of ecosystems during the mid-late Holocene: A pollen record from Haixing wetland in Bohai Bay, North China

Vegetation in coastal regions is sensitive to climate and sea-level changes. However, currently there is still a lack of understanding about the stability of the Holocene coastal ecosystem and the rapid conversion processes of different coastal wetland ecosystems. In this study, the high-resolution vegetation succession history of the southwest coast of Bohai Bay during the mid-late Holocene was revealed, based on pollen analysis and REVEALS model, and the rate of vegetation change was estimated. Furthermore, the characteristics and mechanisms of different ecosystem changes were explored. The results indicate that there was a prolonged transition from shallow sea to lagoon before the formation of the Haixing wetland during the interval of 7500–4100 cal yr BP. The rate of watershed vegetation change increase significantly under the common influence of the 4.2 ka event and human activities, causing a regime shift in the mountain forest ecosystems and a decrease in landscape resilience. It was characterized by a substantial reduction in broad-leaved forests (from>30% to<5%), especially for Quercus (∼3%), which have not recovered to pre-event levels since the end of the 4.2 ka event. Since 3500 cal yr BP, the Haixing area was completely detached from the influence of the Bohai Sea, forming freshwater wetlands. The local vegetation rapidly shifted from alkali-tolerant communities that followed the sea retreat to freshwater marsh plant communities. During 2000–1100 cal yr BP, under the strong impact of human activities, the succession of forest and grassland communities in the basin became more frequent. The area of coastal salt marshes expanded, with salt-tolerant plant communities taking the absolute advantage. The wetland vegetation landscape became closer to the modern appearance. Overall, our study provides new evidence for understanding the rapid evolution of coastal ecosystems in East Asia influenced by a combination of climate, hydrology and humans. It will help guide the coastal regions in facing the challenges of future global climate changes.

Sediment load assessments under climate change scenarios and a lack of integration between climatologists and environmental modelers

Increasing precipitation accelerates soil erosion and boosts sediment loads, especially in mountain catchments. Therefore, there is significant pressure to deliver plausible assessments of these phenomena on a local scale under future climate change scenarios. Such assessments are primarily drawn from a combination of climate change projections and environmental model simulations, usually performed by climatologists and environmental modelers independently. Our example shows that without communication from both groups the final results are ambiguous. Here, we estimate sediment loads delivered from a Carpathian catchment to a reservoir to illustrate how the choice of meteorological data, reference period, and model ensemble can affect final results. Differences in future loads could reach up to even 6000 tons of sediment per year. We suggest there must be a better integration between climatologists and environmental modelers, focusing on introducing multi-model ensembles targeting specific impacts to facilitate an informed choice on climate information.

Wildfire Burnt Area and Associated Greenhouse Gas Emissions under Future Climate Change Scenarios in the Mediterranean: Developing a Robust Estimation Approach

Wildfires burn annually over 400,000 ha in Mediterranean countries. By the end of the 21st century, wildfire Burnt Area (BA) and associated Green House Gas (GHG) emissions may double to triple due to climate change. Regional projections of future BA are urgently required to update wildfire policies. We present a robust methodology for estimating regional wildfire BA and GHG emissions under future climate change scenarios in the Mediterranean. The Fire Weather Index, selected drought indices, and meteorological variables were correlated against BA/GHG emissions data to create area-specific statistical projection models. State-of-the-art regional climate models (horizontal resolution: 12 km), developed within the EURO-CORDEX initiative, simulated data under three climate change scenarios (RCP2.6, RCP4.5, and RCP8.5) up to 2070. These data drove the statistical models to estimate future wildfire BA and GHG emissions in three pilot areas in Greece, Montenegro, and France. Wildfire BA is projected to increase by 20% to 130% up to 2070, depending on the study area and climate scenario. The future expansion of fire-prone areas into the north Mediterranean and mountain environments is particularly alarming, given the large biomass present here. Fire-smart landscape management may, however, greatly reduce the projected future wildfire BA and GHG increases.

Estimating future climate change impacts on human mortality and crop yields via air pollution

Future climate change may bring local benefits or penalties to surface air pollution, resulting from changing temperature, precipitation, and transport patterns, as well as changes in climate-sensitive natural precursor emissions. Here, we estimate the climate penalties and benefits at the end of this century with regard to surface ozone and fine particulate matter (PM[Formula: see text]; excluding dust and smoke) using a one-way offline coupling between a general circulation model and a global 3-D chemical-transport model. We archive meteorology for the present day (2005 to 2014) and end of this century (2090 to 2099) for seven future scenarios developed for Phase 6 of the Coupled Model Intercomparison Project. The model isolates the impact of forecasted anthropogenic precursor emission changes versus that of climate-only driven changes on surface ozone and PM[Formula: see text] for scenarios ranging from extreme mitigation to extreme warming. We then relate these changes to impacts on human mortality and crop production. We find ozone penalties over nearly all land areas with increasing warming. We find net benefits due to climate-driven changes in PM[Formula: see text] in the Northern Extratropics, but net penalties in the Tropics and Southern Hemisphere, where most population growth is forecast for the coming century.

How water, temperature, and seismicity control the preconditioning of massive rock slope failure (Hochvogel)

Abstract. The anticipation of massive rock slope failures is a key mitigation strategy in a changing climate and environment requiring a precise understanding of pre-failure process dynamics. Here we exploit &gt;4 years of multi-method high-resolution monitoring data from a large rock slope instability close to failure. To quantify and understand the effect of possible drivers (water from rain and snowmelt, internal rock fracturing, and earthquakes), we correlate slope displacements with environmental data, local seismic recordings, and earthquake catalogues. During the snowmelt phase, displacements are controlled by meltwater infiltration with high correlation and a time lag of 4–9 d. During the snow-free summer, rainfall induces accelerations with a time lag of 1–16 h for up to several days without a minimum activation rain sum threshold. Rock fracturing, linked to temperature and freeze–thaw cycles, is predominantly near the surface and unrelated to displacement rates. A classic Newmark analysis of recent and historic earthquakes indicates a low potential for immediate triggering of a major failure at the case site, unless it is already very close to failure. Seismic topographic amplification of the peak ground velocity (PGV) at the summit ranges from a factor of 2–11 and is spatially heterogeneous, indicating a high criticality of the slope. The presented in-depth monitoring data analysis enables a comprehensive rockfall driver evaluation and indicates where future climatic changes, e.g. in precipitation intensity and frequency, may alter the preconditioning of major rock slope failures.

Assessing the impact of turnip yellows virus infection and drought on canola performance: implications under a climate change scenario

IntroductionCanola (Brassica napus L.) is one of the most important crops worldwide. Turnip yellows virus (TuYV), transmitted by aphids, is one of the most damaging viruses affecting canola crops and is challenging to control. With the prediction of more intense and prolonged drought events due to future climate change, an additional factor may extensively impact the epidemiology of plant diseases. This study aimed to understand the impact of drought on canola plants infected with TuYV and to explore the relationship between virus infection and drought.MethodsTwo glasshouse experiments were conducted: 1. Competition: Four plants (two infected, two non-infected) were grown in the same pot. 2. No Competition: One plant was grown per pot. In both experiments, infected and non-infected canola plants were exposed to well-watered conditions, water stress (simulated drought), and terminal drought. Various plant traits were recorded, including biomass, leaf area, height, number of leaves, chlorophyll content, water use efficiency, and virus symptom expression.ResultsBoth virus infection and water stress reduced dry biomass, leaf area, and height. Virus infection alone reduced canola biomass by up to 49% compared to non-infected, well-watered controls. Under water stress or terminal drought, the biomass of TuYV-infected plants was further reduced by up to 71% and 65%, respectively. Virus infection also reduced the number of leaves, although water treatment alone did not. Chlorophyll content was higher in water-stressed and terminal drought plants compared to well-watered ones, while virus infection reduced chlorophyll content. The impact of drought and virus infection was more pronounced when plants were under competition.DiscussionGiven the expected increase in prolonged and frequent droughts in many canola-growing regions due to climate change, a significant detrimental effect on canola production due to the combined influence of drought and TuYV is anticipated. This study underscores the need for developing mitigation strategies to protect canola production in a changing climate.

Integrating a multi-variable scenario with Attention-LSTM model to forecast long-term coastal beach erosion

Beach erosion is an adverse impact of climate change and human development activities. Effective beach management necessitates integrating natural and anthropogenic factors to address future erosion trends, while most current prediction models focus only on natural factors, which may provide an incomplete and potentially inaccurate representation of erosion dynamics. This study enhances prediction methods by integrating both natural and anthropogenic factors, thereby enhancing the accuracy and reliability of erosion projections. By extracting historical shorelines through CoastSat model from 1986 to 2020, we develop multivariable scenarios with Attention-LSTM model to predict the regional impacts of natural and anthropogenic factors on erosion to sandy beaches along the typical shoreline of Shenzhen in China. Results reveal that Shenzhen's beaches experienced erosion up to 12 m over the past 35 years. Here we project a decrease in the mean erosion rate of the beaches, identifying population growth (21.0 %) as the main controlling factor before the mid-century in a range of scenarios. We find that Attention-LSTM multi-model ensemble approach can provide overall improved accuracy and reliability over a wide range of beach erosion compared to scenario prediction model of Attention-LSTM and statistical model of Digital Shoreline Analysis System (DSAS), yielding an average uncertainty of 10.99 compared to 13.29. These insights reveal policies to safeguard beaches because of the rising demand for beaches due to human factors, coupled with decreased impervious surfaces through ecological conservation, lead to mitigation for beach erosion. Accurate forecasts empower policymakers to implement effective coastal management strategies, safeguard resources, and mitigate erosion's adverse effects. Our study offers finely-tuned predictions of coastal erosion, providing crucial insights for future coastal conservation efforts and climate change adaptation along the shoreline, and serving as a foundation for further research aimed at understanding the evolving environmental impacts of beach erosion in Shenzhen.

Modeling of surface water allocation under current and future climate change in Keleta Catchment, Awash River Basin, Ethiopia

Modeling of surface water allocation under current and future climate change in Keleta Catchment, Awash River Basin, Ethiopia

The focus on addressing vegetation risks in China should shift from the western past to the eastern future

Actively addressing the negative effects of global climate change on vegetation has always been a hot topic of academic concern. How to accurately and comprehensively assess the vegetation risk due to climate change has been rarely reported. By comprehensively considering three dimensions—species structure (species richness), carbon sequestration function (Net Primary Production, NPP), and physiological processes (transpiration)—and based on the prediction of the future distribution characteristics of 3,370 plant species in China, this study quantified the vegetation risk and its driving mechanisms under different Shared Socioeconomic Pathways. The composite index of vegetation risk decreased to the west of the Hu Huanyong Line (NT and QTP regions) but increased to the east (NE and ST regions), with the magnitude of increase growing with the intensification of emission scenarios. In the 2070 s, the proportion of high risk and extremely high-risk areas in the east increased from 14.5 % under SSP126 to 50.0 % under SSP585. NPP and transpiration generally show an increasing trend, and species richness changes similarly to vegetation risk. In the 2070 s under SSP585, 39.2 % of QTP areas see a species richness increase over 50 %, while 33.0 % of ST areas experience a decrease over 30 %. The increase in vegetation risk in the NE region is driven by increased soil moisture, while in the ST region, it is mainly due to decreased runoff and SPEI. Therefore, China should actively respond to the risk of vegetation degradation in the east due to future climate change.

Global economic impact of weather variability on the rich and the poor

AbstractTemperature and precipitation variability and extremes impact production globally. These production disruptions will change with future warming, impacting consumers locally as well as remotely through supply chains. Due to a potentially nonlinear economic response, trade impacts are difficult to quantify; empirical assessments rather focus on the direct inequality impacts of weather extremes. Here, simulating global economic interactions of profit-maximizing firms and utility-optimizing consumers, we assess risks to consumption resulting from weather-induced production disruptions along supply chains. Across countries, risks are highest for middle-income countries due to unfavourable trade dependence and seasonal climate exposure. We also find that risks increase in most countries under future climate change. Global warming increases consumer risks locally and through supply chains. However, high-income consumers face the greatest risk increase. Overall, risks are heterogeneous regarding income within and between countries, such that targeted local and global resilience building may reduce them.

Synthetic libraries of urban landslide simulations to identify slope failure hotspots and drivers across spatial scales and landscapes

AbstractRainfall-triggered landslides are most deadly in developing countries, and future urban sprawl and climate change could intensify existing risks. In these regions, enhancing efforts in urban landslide risk mitigation and climate change adaptation is crucial. Current landslide probability assessment methodologies struggle to support effective mitigation because they fail to represent local anthropogenic factors (e.g. informal housing) across space and time scales. To meet this challenge, we demonstrated in previous work that hillslope-scale mechanistic models representing such localised changes can be used to create synthetic libraries of urban landslides that account for both data and future scenario uncertainty. Here, we show how these libraries can become an explorative tool for researchers and stakeholders, allowing them to investigate slope stability variations across spatial scales and landscapes. Results highlight, for example, how the main slope instability drivers change according to the location (e.g., upper vs lower catchment), the landcover (e.g. forest vs urban) and the spatial scale analysed (e.g. at hillslope scale slope stability was mostly controlled by water table height, whereas at regional scale by slope geometry). Ultimately, we demonstrate that stochastic analyses can lead to a greater understanding of the system interactions and they can support the identification of mitigation strategies that perform well across spatial scales and uncertain scenarios. These strategies should be prioritised even if future conditions are unknown. This reasoning is shown on a data-scarce region with expanding informal housing. However, the same methodology can be applied to any urban context and with any mechanistic-based model.

Projecting Response of Ecological Vulnerability to Future Climate Change and Human Policies in the Yellow River Basin, China

Projecting Response of Ecological Vulnerability to Future Climate Change and Human Policies in the Yellow River Basin, China

Predominant biogenic contribution of dissolved inorganic carbon in karst rivers, Southwest China

Dissolved inorganic carbon (DIC) holds significant importance within river systems, particularly in karst regions. The concentration of DIC is intricately linked to both biological processes, such as the respiration of organic matter, and geological processes, notably the strength of carbonate weathering. This dual influence exerts a profound impact on regional and global carbon cycles. However, the precise biological and geological origins of DIC in karst rivers remain a subject of debate. In this study, we delineate the sources of DIC in a typical karst catchment (Houzhai catchment) through isotopic analysis coupled with water chemistry examination. The results showed that δ13CDIC and Δ14CDIC variations range from −14.0 ‰ to −7.3 ‰ and − 426 ‰ to −31 ‰, respectively, with average values of −10.5 ‰ and − 180 ‰. Results derived from the isotopic mixing model suggest that approximately 83 % of DIC emanates from the soil CO2, while 17 % originates from carbonate sources. This indicates that biological processes exert a greater influence on DIC within the study area compared to geological processes. Seasonal variation, exemplified by higher DOC concentrations and Δ14CDIC values, alongside with lower DIC concentrations and δ13CDIC values during the wet season indicate increased input from biogenic sources, closely related to temperature and moisture conditions. Our study underscores an unbalanced contribution from biogenic and geogenic sources in karst rivers, highlighting potential inaccuracies in past carbon sink flux calculations. The roles of biogenic and geogenic sources in the carbon cycling of karst rivers, as well as their responses to future climate change, warrant a reevaluation.

Future climate change implications in Bhutan from a downscaled and bias‐adjusted CMIP6 multimodel ensemble

Future climate change implications in Bhutan from a downscaled and bias‐adjusted <scp>CMIP6</scp> multimodel ensemble

Downscaling, projection, and analysis of expected future climate change in a watershed of Omo-Gibe basin of Ethiopia

Downscaling, projection, and analysis of expected future climate change in a watershed of Omo-Gibe basin of Ethiopia

Alterations in Suitable Cultivation Area for Scutellaria baicalensis under Future Climatic Scenarios in China: Geodetector-Based Prediction

The dried roots of Scutellaria baicalensis (S. baicalensis) have been widely used as a traditional medicine. Recently, climate change and human activities have caused the degeneration of its wildlife habitat. However, there is rare knowledge on the effect and interactive effect of different variables on the spatial heterogeneity of S. baicalensis and how the pattern of suitable cultivation area in China would shift in response to climate change. Based on the Geodetector and Habitat Suitability Index (HSI) method, we proposed an assessment model to identify the critical environmental variable(s) affecting the distribution of suitable cultivation area for S. baicalensis in China and to project its shift under climate change. The results showed that soil and mean annual temperature are two determining variables in its spatial heterogeneity in China. Compared to 1981–2010, future climate change may result in a decrease in its suitable area, and yet may result in an increase in the extremely suitable area (about 1.00–1.35 million km2). S. baicalensis in the southern and northwestern part of its current distribution and the southwestern part and small area of northern China may experience expansion during the 21st century, while S. baicalensis in southern China, the Huang-Huai-Hai plain, and the midwest of northwestern China may experience contractions. Meanwhile, climate warming is expected to shift its distribution northwest through an expansion at the northern (at least 84 km) and western (at least 62 km) boundary and contraction at the southern (at least 529 km) boundary, respectively. These results could provide valuable information to policy-makers for the conservation and scientific introduction of S. baicalensis.

Impact of climate change on the geographical distribution of ticks of public health significance in Colombia: Amblyomma ovale (Ixodida: Ixodidae), the Amblyomma maculatum (Ixodida: Ixodidae) complex and the Amblyomma cajennense (Ixodida: Ixodidae) complex

Abstract Ticks of the Amblyomma maculatum (Ixodida Ixodidae) complex, the Amblyomma cajennense (Ixodida Ixodidae) complex and Amblyomma ovale (Ixodida Ixodidae) are known to transmit various Rickettsia species in Colombia, but their exact distribution is unknown. We built several models based on current climate and projected future climate changes using a maximum entropy approach. A total of 314 records of the A. cajennense complex (65.9%; n = 207), A. ovale (22.9%; n = 72), and the A. maculatum complex (11.1%; n = 35) were obtained. Amblyomma ovale has a current distribution in the Pacific, Caribbean and Andean regions and could be potentially found in the Amazon. Amblyomma maculatum has a current distribution in the Andean and could potentially be found in the Caribbean and Orinoco regions. Amblyomma mixtum can be found near the Caribbean Sea and in the Pacific region, and A. patinoi is likely to be found in the Andean region and the Caribbean. In 2070, it will be possible to find an expansion of A. ovale and A. maculatum and a decrease of A. mixtum and A. patinoi. The variables that best predict the distribution of these species are isothermality (small fluctuations in temperature) and annual precipitation. Amblyomma cajennense s.l and A. ovale, A. cajennese s.l and A. patinoi, as well as A. maculatum and A. patinoi, have an important environmental sympatry. Epidemiological and acarological surveillance is crucial to investigate rickettsiosis caused by R. parkeri in A. ovale regions, by R. rickettsii in A. patinoi and A. mixtum areas, and by R. parkeri s.s in A. maculatum regions.

The survival and growth of adult and juvenile hard clam Meretrix meretrix exposed to variable estuarine salinities in aquarium settings

Salinity fluctuations in estuaries can significantly impact marine organisms, leading to economic losses through mass mortalities of commercially important species. The effects of varying estuarine salinities on the survival, daily mortality, and growth of adult and juvenile hard clam Meretrix meretrix under controlled aquarium conditions were investigated. Adults (shell length ~45 mm) and juveniles (shell length ~30 mm) were collected from an 18 ppt estuarine habitat in Chowfaldondi, southeast Bangladesh, and exposed to six salinity levels (10, 15, 20, 25, 30, and 35 ppt) with three replications at ambient temperature. Adults were monitored for 51 days and juveniles for 23 days. Survival was significantly higher (≥80%) at 15–30 ppt for adults and 10–20 ppt for juveniles, with the lowest survival at 35 ppt. Analysis of co-variance showed that salinity had a greater effect on survival than the combined salinity*size model (p&lt;0.05). While adult clams exhibited no mortality in first 15 days, juvenile mortality (~10%) began on day two across all salinities with a dose-dependent mortality exceeding 50–80% in 25–35 ppt. Adults were more tolerant to high salinities while juveniles to low salinities. Shell length and width did not vary significantly across salinities, likely due to insufficient plankton in the supplied seawater. This study has implications for potential site selection for coastal clam aquaculture along the Bay of Bengal. The sudden changes and combined effects of multi-stressors on bivalves can be assessed for better understanding how near future climate change can impact bivalve fishery and blue economy. Res. Agric. Livest. Fish. Vol. 11, No. 2, August 2024: 239-254

Adjusting Sowing Date and Seeding Rate for Cultivated Lentil to Contrasting Rainfall Conditions in a Semi-arid Region

Adjusting the sowing date and seeding rate of lentils are important practices, which largely affect plant performance and need greater focus under semi-arid conditions. Our study aimed to optimize the sowing window and plant density specific to dry and wet conditions. A two-year field experiment was carried out under dry and wet cropping seasons (2016/2017 and 2017/2018). Two commercial lentil varieties (Syrie229 and Idleb2) were sown at early (late October/early November), normal (December), and late (January) sowing dates and with low (90 seeds/m2), medium (120 seeds/m2) and high (150 seeds/m2) seeding rate. Several traits were recorded namely plant height at first filled pod (HFFP), plant height (PH), days to flowering (DTF), days to maturity (DTM), stem diameter (SD), weight of 100 seeds (100-SW) and seed yield (SY). Our results revealed that the dry year considerably reduced all trait values except the weight of 100 seeds compared to the wet year. Sowing date had a significant effect on most traits, with the highest values being found for early sowing date compared to normal and late dates, including seed yield (1.83 vs. 1.36 and 0.94 ton/ha, respectively). It is worth noting that the difference among sowing dates was detected only under wet years for most traits. The seeding rate affected only HFFP and stem diameter under a wet year, where a high seeding rate increased HFFP while a low seeding rate increased stem diameter. To conclude, cropping season was the main driver of growth and yield, and then the effect of sowing date was dependent on climatic conditions. Our results highlight the importance of adjusting the sowing window and seeding rate to cope with the future climatic change effects.