Forcing Of Climate Change Research Articles

Defects detection of pier and abutments foundations: an overview of a recent experience in Basilicata (Southern Italy)

Piers and abutments are bridge supports temporarily or permanently immersed into the water, that may suffer erosion and scour phenomena. As known, the latter involves different processes at different spatial scales not easy to investigate in a combined approach, such as: contraction scour, local scour, gradation of the soil bed, river channel dynamic, climate change and hydrological forces. To this, it should be added that piers/abutments are highly exposed to environmental actions, such as earthquake, landslides and floods that may seriously compromise their stability and, consequently, lead the bridge or an its portion to an out-of-service, or else to a failure. Therefore, it is important to properly identify and assess defects extent and severity on piers and abutments, in order to evaluate their conservation status, and to formulate a judgment for ranking priorities within a multi-level and multi-criteria framework, such as the recent guidelines issued by the Italian Ministry of Infrastructures and Transport. To this regard, in this work an overview of some significant defects related to piers and abutments, with particular emphasis to the ones due to the interaction with the water flow, are illustrated and commented. They are collected in an on-going campaign of inspections performed in the Basilicata region (South of Italy), concerning bridges falling within State Roads networks. Comments are made from a structural and hydraulic point view, in order to highlight the inspected defects importance within the Classes of Attention, according to Italian Guidelines for bridges.

Prediction of the Climate Change and Radiative Forcing Scenarios on Monthly Runoff Urban Basin in Kerman, Iran

Prediction of the Climate Change and Radiative Forcing Scenarios on Monthly Runoff Urban Basin in Kerman, Iran

Astronomically forced late Paleocene-early Eocene climate variability in the Subei Basin, East China

The latest Paleocene to early Eocene was an interval of globally warm climate. However, the driving mechanisms regulating climate across this interval remain unclear due to the paucity of well-dated and stratigraphically continuous records from terrestrial basins. In this study, we present a continuous ∼430-m lacustrine core record from the QY-1 borehole spanning the late Paleocene-Early Eocene in the Subei Basin, East China. This unique record can be used to better elucidate the response of terrestrial sedimentation to astronomically forced climate change. A 4.54 Myr long astronomical time scale spanning 57.1 to 52.56 Ma is constructed for the second member of the Funing Formation (Ef2) based on magnetostratigraphy and cyclostratigraphy. Low-latitude summer insolation via eccentricity modulation of precession controlled paleolake evolution in the basin during the studied interval. At the same time, we show that the climate system during this greenhouse state was sensitive enough to respond to the small changes in insolation associated with 200-kyr eccentricity cycles. Evidence from gamma ray data suggests that the climate in the Subei Basin changed from warm and humid to arid at ∼54.1 Ma.

Chemical Investigation on the Mechanism and Kinetics of the Atmospheric Degradation Reaction of Trichlorofluoroethene by OH⋅ and Its Subsequent Fate in the Presence of O2 /NOx.

The M06-2X/6-311++G(d,p) level of theory was used to examine the degradation of Trichlorofluoroethene (TCFE) initiated by OH⋅ radicals. Additionally, the coupled-cluster single-double with triple perturbative [CCSD(T)] method was employed to refine the single-point energies using the complete basis set extrapolation approach. The results indicated that OH-addition is the dominant pathway. OH⋅ adds to both the C1 and C2 carbons, resulting in the formation of the C(OH)Cl2 -⋅CClF and ⋅CCl2 -C(OH)ClF species. The associated barrier heights were determined to be 1.11 and -0.99 kcal mol-1 , respectively. Furthermore, the energetic and thermodynamic parameters show that pathway 1 exhibits greater exothermicity and exergonicity compared to pathway 2, with differences of 8.11 and 8.21 kcal mol-1 , correspondingly. The primary pathway involves OH addition to the C2 position, with a rate constant of 6.2×10-13 cm3 molecule-1 sec-1 at 298 K. This analysis served to estimate the atmospheric lifetime, along with the photochemical ozone creation potential (POCP) and ozone depletion potential (ODP). It yielded an atmospheric lifetime of 8.49 days, an ODP of 4.8×10-4 , and a POCP value of 2.99, respectively. Radiative forcing efficiencies were also estimated at the M06-2X/6-311++G(d,p) level. Global warming potentials (GWPs) were calculated for 20, 100, and 500 years, resulting in values of 9.61, 2.61, and 0.74, respectively. TCFE is not expected to make a significant contribution to the radiative forcing of climate change. The results obtained from the time-dependent density functional theory (TDDFT) indicated that TCFE and its energized adducts are unable to photolysis under sunlight in the UV and visible spectrum. Secondary reactions involve the [TCFE-OH-O2 ]⋅ peroxy radical, leading subsequently to the [TCFE-OH-O]⋅ alkoxy radical. It was found that the alkoxy radical resulting from the peroxy radical can lead to the formation of phosgene (COCl2 ) and carbonyl chloride fluoride (CClFO), with phosgene being the primary product.

Assessing the Impact of Stratospheric Aerosol Injection on US Convective Weather Environments

AbstractContinued climate warming, together with the overall evaluation and implementation of a range of climate mitigation and adaptation approaches, has prompted increasing research into proposed solar climate intervention methods, such as stratospheric aerosol injection (SAI). SAI would use aerosols to reflect a small amount of incoming solar radiation away from Earth to stabilize or reduce future warming due to increasing greenhouse gas concentrations. Research into the possible risks and benefits of SAI relative to the risks from climate change is emerging. There is not yet, however, an adequate understanding of how SAI might impact human and natural systems. For instance, little to no research to date has examined how SAI might impact environmental conditions critical to the formation of severe convective weather over the United States (US). This study uses ensembles of Earth system model simulations of future climate change, with and without hypothetical SAI deployment, to examine possible future changes in thermodynamic and kinematic parameters critical to the formation of severe weather during convectively active seasons over the US Results show that simulated forced changes in thermodynamic parameters are significantly reduced under SAI relative to a climate change (SSP2‐4.5) world, while simulated changes in kinematic parameters are more difficult to distinguish. Also, unforced internal climate variability is likely to significantly modulate the projected forced climate changes over large regions of the US.

Climate change adaptation and mitigation at individual level: knowledge and attitudes among school teachers in Kalutara district

Purpose Climate change is the biggest global health threat of the 21st century. Its impacts scatter through every stratum of society placing the marginalized clusters at the highest vulnerability and calling for action at all levels. Adaptation enhances resilience, whereas mitigation minimizes the anthropogenic forces of climate change; these are crucial initiatives for climate-resilient sustainable development. The aim of this study was to determine the knowledge and attitudes on climate change adaptation and mitigation at individual level and assess related factors. Design/methodology/approach A descriptive study is done to assess the knowledge and attitudes of school teachers in three educational zones of the Kalutara district using random cluster sampling. A self-administered questionnaire including 25 equally weighted questions to assess knowledge and 10 statements to assess attitudes was used. Findings The response rate was 98.8% [n = 618] and 23% of the study population had poor knowledge of climate change adaptation and mitigation at the individual level. Favorable attitudes were observed among more than 65% of participants for all the statements on climate change adaptation and mitigation. Average family income, working duration, involvement in school environmental societies and highest education qualification showed a significant positive association, whereas age and current grade had a significant negative association with good knowledge. The level of knowledge had no significant variation among male and female teachers. Originality/value Overall knowledge was poor among more than 20% of the teachers highlighting the need for school and community-based awareness programs to be implemented to address the issue.

Impact of Climate Change on Flowering Phenology and Abundance on Mertensia spp.

This research article delves into the intricate dance between climate change and two enchanting flower species, Mertensia fusiformis and M. ciliata. These blossoms, with their nodding blue petals and elegant foliage, grace the Great Basin and alpine meadows. However, their delicate beauty conceals a resilient spirit, tested by the relentless forces of climate change. We explore the physiology of these flowers, uncovering the influence of rising temperatures on their flowering patterns. M. fusiformis tends to bloom earlier, adapting to shifting climatic cues. In contrast, M. ciliata shows variations in flower size and coloration. The consequences of climate change ripple through these species' distribution and habitat suitability. Warmer temperatures propel M. fusiformis to higher elevations, where it faces new challenges and competition. M. ciliata experiences habitat loss as alpine treelines ascend, pushing it into crevices and microclimates. These flowers' pollination mechanisms also adapt to changing conditions, with shifts in pollinator behavior and abundance disrupting their age-old partnerships. Conclusively, climate change orchestrates a captivating yet disquieting symphony in the lives of Mertensia fusiformis and M. ciliata. They stand as messengers, urging us to acknowledge the fragility of our ecosystems and take action to preserve the beauty of our planet's flora.

Why Has the Summertime Central U.S. Warming Hole Not Disappeared?

Abstract A cooling trend in summer (May–August) daytime temperatures since the mid-twentieth century over the central United States contrasts with strong warming of the western and eastern United States. Prior studies based on data through 1999 suggested that this so-called warming hole arose mainly from internal climate variability and thus would likely disappear. Yet it has prevailed for two more decades, despite accelerating global warming, compelling reexamination of causes that in addition to natural variability could include anthropogenic aerosol–induced cooling, hydrologic cycle intensification by greenhouse gas increases, and land use change impacts. Here we present evidence for the critical importance of hydrologic cycle change resulting from ocean–atmosphere drivers. Observational analysis reveals that the warming hole’s persistence is consistent with unusually high summertime rainfall over the region during the first decades of the twenty-first century. Comparative analysis of large ensembles from four different climate models demonstrates that rainfall trends since the mid-twentieth century as large as observed can arise (although with low probability) via internal atmospheric variability alone, which induce warming-hole-like patterns over the central United States. In addition, atmosphere-only model experiments reveal that observed sea surface temperature changes since the mid-twentieth century have also favored central U.S cool/wet conditions during the early twenty-first century. We argue that this latter effect is symptomatic of external radiative forcing influences, which, via constraints on ocean warming patterns, have likewise contributed to persistence of the U.S. warming hole in roughly equal proportion to contributions by internal variability. These results have important ramifications for attribution of extreme events and predicting risks of record-breaking heat waves in the region. Significance Statement Our paper makes a significant contribution to analysis of a cooling trend in summer (May–August) daytime temperatures since the mid-twentieth century over the central United States, contrasting with strong warming over the remainder of the United States and having important ramifications for assigning cause to and predicting record-breaking heat waves in the region. Observations and model simulations reveal the critical importance of hydrologic cycle change resulting from ocean–atmosphere impacts. Precipitation has increased substantially over the region as a result of atmospheric circulation trends consisting of generally lower pressure and cooler air advection into the region. The persistence of this pattern of increased rainfall/lower temperatures is likely due to near-equal contributions of external forcing (climate change) and internal climate variability.

Natural disasters and energy innovation: unveiling the linkage from an environmental sustainability perspective

Natural disasters, characterized by their escalating frequency and intensification, fueled relentlessly by the inexorable forces of climate change, unambiguously underscore the urgent need to reassess our built environments and meticulously revise infrastructure design to withstand the unforgiving onslaught of these extreme events, thereby demanding concerted attention and unwavering dedication from policymakers and academic researchers to navigate this formidable predicament. The current study delves into the exploration of how natural disaster impact the course of energy technology evolution. To achieve this, This investigation uses panel data from 1990–2020 and sophisticated econometric analyses to model the effect of calamities on energy technology advancement across BRICS countries. Rigorous empirical methodologies lend credibility regarding the observed detrimental impact of disasters on innovation. The preliminary findings of the investigation suggest that natural disasters potentially exert a markedly detrimental effect on energy technology innovation. This influence is not merely confined to the year of the disaster occurrence but persistently lingers for the subsequent 4-year period. Moreover, the adverse impacts of such environmental upheavals on energy evolution seem to be mitigated by various factors. These include robust economic growth, government stability, interpersonal globalization, financial openness, trade openness, and the expansion of social globalisation. Adding further dimension to this research is the understanding that epidemics have the most pronounced negative implications on energy innovation. Concluding on a nuanced note, the study underscores a significant inverse relationship between natural disasters and low-carbon energy innovation. Interestingly, however, there is no discernible correlation when it comes to non-low carbon energy innovation. In a nutshell, this research presents a potential reference guide for policymakers, illuminating pathways to enhance the degree of energy innovation while tackling natural disasters and ensuring environmental sustainability.

Tropical Volcanic Eruptions and Low Frequency Indo‐Pacific Variability Drive Extreme Indian Ocean Dipole Events

AbstractVolcanic eruptions can have significant climate impacts and serve as useful natural experiments for better understanding the effects of abrupt, externally forced climate change. Here, we investigate the Indian Ocean Dipole's (IOD) response to the largest tropical volcanic eruptions of the last millennium. Post‐eruption composites show a strong negative IOD developing in the eruption year, and a positive IOD the following year. The IOD and El Niño‐Southern Oscillation (ENSO) show a long‐term damped oscillatory response that can take up to 8 years to return to pre‐eruptive baselines. Moreover, the Interdecadal Pacific Oscillation (IPO) phase at the time of eruption controls the IOD response to intense eruptions, with negative (positive) IPO phasing favoring more negative (positive) IOD values via modulation of the background state of the eastern Indian Ocean thermocline depth. These results have important implications for climate risk in low‐likelihood, high‐impact scenarios, particularly in vulnerable communities unprepared for IOD and ENSO extremes.

Developing machine learning models for accurate prediction of radiative efficiency of greenhouse gases

BackgroundGreenhouse gases (GHGs), particularly halocarbons, contribute significantly to the radiative forcing of climate change due to their long lifetime. Accurate prediction of GHG radiative efficiency (RE) is required to assess the relative impacts of GHGs on climate change. MethodsAn RE dataset consisting of around 82 K molecules was generated using a narrow band model (NBM) and density functional theory (DFT) computed infrared spectra. This dataset, along with 568 experimentally available RE data, was utilized to develop machine learning (ML) models through a transfer learning approach. Significant findingsThe accuracy of REs calculated with NBM and DFT was evaluated against experimental data. A moderate level of agreement was observed, with a tendency to overestimate the results. ML models were then trained using DFT data, and their performance was compared using various model architectures. The directed message-passing neural network (DMPNN) model outperformed other models, and when combined with quantum mechanical features (ml-QM-DMPNN), a slight improvement was observed. The DMPNN and ml-QM-DMPNN models were refined by the transfer learning technique using the experimental dataset, which resulted in predicting experimental REs with root mean square errors (RMSEs) of 0.0582 and 0.0564 Wm−2ppb−1, respectively. This study offers critical insights into developing ML models that can predict REs of molecules, thereby facilitating the design of environmentally-friendly chemicals and materials.

The emergence of a climate change signal in long-term Irish meteorological observations

Detecting the emergence of a forced anthropogenic climate change signal from observations is critical for informing adaptation responses. By regressing local variations in climate onto annual Global Mean Surface Temperature (GMST), we track the emergence of an anthropogenic signal in long-term quality assured observations of temperature and precipitation for the island of Ireland, a sentinel location on the western European Atlantic seaboard. Analysis of station based observations, together with island scale composite series is undertaken for annual and seasonal means, together with 16 indices of extremes, with the derived signal-to-noise ratio classified as normal, unusual or unfamiliar relative to early industrial climate. More than half of indices show the emergence of at least unusual conditions relative to early industrial climate. The increase in annual mean temperature has led to the emergence of unfamiliar climate at six of eleven stations. Warming at the island scale is estimated at 0.88 °C per degree warming in GMST. While many stations show the emergence of unusual climate for spring, summer and autumn mean temperature, no forced signal of change is found for winter mean temperature. Changes in cool/warm days and nights are unfamiliar relative to early industrial climate. However, no anthropogenic signal is found for the hottest day annually or in summer – an extreme often associated with climate change in public consciousness. Increases in annual precipitation totals have emerged as unusual for western stations with large increases in winter totals per degree warming in GMST (e.g., 25.2% and 19.7% at Malin Head and Markree, respectively), indicating heightened flood risk with continued warming. By contrast, summer precipitation shows no significant relationship with GMST. Increases in rainfall intensity have emerged as unusual for 30% of stations, with increases consistent with the Clausius-Clapeyron relationship. Our analysis shows that an emerging climate change signal is discernible for Ireland, a location strongly influenced by climate variability.

The Shanxi Formation responses to astronomically forced climate changes during the Upper Paleozoic in the Eastern Ordos Basin, NW China

A clearly defined geochronology and stratigraphic interpretation will enhance our understanding of the evolution of paleo water depth and transitional facies, contributing to hydrocarbon exploration. Transitional deposition is extensively observed in the upper Paleozoic of the Ordos Basin. Nevertheless, the correlation between the variations of paleo water depth and global sea-level changes remains uncertain. In this study, we employed gamma-ray logging (GR) data to analyze the cyclostratigraphy of the upper Paleozoic Shanxi Formation in the Ordos Basin. We characterized the elemental geochemistry of the Shanxi Formation using X-ray fluorescence. We reconstructed changes in Paleo Water Depth in the Ordos Basin during the upper Paleozoic by employing sedimentary noise modeling of the tuned GR logging data. Time series analysis showed evidence of the existence of 405 kyr long eccentricity, 125 kyr short eccentricity, and 35.5 kyr obliquity in sedimentary records, which was supported by a sediment accumulation rate model. Using the tuned GR data, we constructed a ∼3.07 Myr astronomical time scale in the Shanxi Formation of the sampling well. Moreover, we used the volcanic ash age (298.18 ± 0.32) Ma at the boundary of the Shanxi Formation and Taiyuan Formation as the anchor point to provide an absolute astronomical time scale from 295.11 Ma to 298.18 Ma for the study area. The variation of Paleo Water Depth in the upper Paleozoic transitional facies was confirmed by both the sedimentary noise model and the X-ray fluorescence (XRF) data, thus supporting each other. Additionally, we discovered a long-period obliquity of approximately 1.2 million years in this model, which is consistent with the global sea-level fluctuations observed during the same period. These results reveal a novel approach for evaluating the Paleo Water Depth variations in transitional facies. Furthermore, our study offers a detailed explanation of the relationship between the evolution of the sedimentary environment and the climate change resulting from astronomical orbit during the glacial period.

The KNMI Large Ensemble Time Slice (KNMI–LENTIS)

Abstract. Large-ensemble modelling has become an increasingly popular approach to studying the mean climate and the climate system’s internal variability in response to external forcing. Here we present the Royal Netherlands Meteorological Institute (KNMI) Large Ensemble Time Slice (KNMI–LENTIS): a new large ensemble produced with the re-tuned version of the global climate model EC-Earth3. The ensemble consists of two distinct time slices of 10 years each: a present-day time slice and a +2 K warmer future time slice relative to the present day. The initial conditions for the ensemble members are generated with a combination of micro- and macro-perturbations. The 10-year length of a single time slice is assumed to be too short to show a significant forced climate change signal, and the ensemble size of 1600 years (160 × 10 years) is assumed to be sufficient to sample the full distribution of climate variability. The time slice approach makes it possible to study extreme events on sub-daily timescales as well as events that span multiple years such as multi-year droughts and preconditioned compound events. KNMI–LENTIS is therefore uniquely suited to study internal variability and extreme events both at a given climate state and resulting from forced changes due to external radiative forcing. A unique feature of this ensemble is the high temporal output frequency of the surface water balance and surface energy balance variables, which are stored in 3-hourly intervals, allowing for detailed studies into extreme events. The large ensemble is particularly geared towards research in the land–atmosphere domain. EC-Earth3 has a considerable warm bias in the Southern Ocean and over Antarctica. Hence, users of KNMI–LENTIS are advised to make in-depth comparisons with observational or reanalysis data, especially if their studies focus on ocean processes, on locations in the Southern Hemisphere, or on teleconnections involving both hemispheres. In this paper, we will give some examples to demonstrate the added value of KNMI–LENTIS for extreme- and compound-event research and for climate-impact modelling.

Climate change adaptation activities planning and implementation in large cities: results of research carried out in Poland and selected European cities

Continuous climate change forces cities to take actions to prevent risks and adapt urban spaces to new conditions. The experience of many European cities in recent years shows that actions adapting urban space to climate change have become an important part of local policy. The subject of the article is the adaptation activities planned and implemented for climate change in urban spaces. The purpose of this article is to classify and identify adaptation activities carried out in large cities. The authors analyzed data from 44 Polish cities and placed them in the context of leading adaptation activities carried out in selected European cities. The purpose of the detailed research is to compare the number and type of activities planned and implemented on the scale of individual Polish cities, indicating dominant and minority activities. The authors conclude that with the passage of time, climate change adaptation activities will have an increasing impact on shaping the landscape of European cities, including those of Poland. Their number will gradually increase, as will the awareness of the city authorities and the activity of local communities. The types of activity will also change and, with them the quality of urban spaces and the quality of life of residents. The authors also conclude that further research will need to conduct quantitative and qualitative studies in the context of the effectiveness of the adaptation process in urban spaces, resulting from the evaluation and monitoring of both systematically updated planning and strategic documents and implemented spatial programs and interventions.

Changes in How Climate Forces the Vegetation of Southern Africa

Global climatic changes are altering ecosystem structure and functioning, yet detecting and forecasting such change is difficult. In this study, we use the concept of a phytoclime—a region where climate favours the growth of similar combinations of plant types—to examine how changes in climate forcing may impact on regional vegetation. We use species distribution data to estimate the parameters of a physiological plant growth model for 5006 vascular plant species common to southern Africa. Plant type suitability surfaces are calculated as the average climatic suitability of locations for all species belonging to a plant type. We calculated plant type suitability surfaces for ten different plant types. The resulting surfaces were used to produce a spatial classification of phytoclimes, which we interpret as regions that can climatically support particular plant type combinations. We use the phytoclime definitions and climatologies from five global circulation models (GCMs) simulating three shared economic pathways (SSPs) to forecast how the climatic forcing underlying the phytoclimes will change. Our analyses forecast that change in phytoclime state will be widespread throughout the region. There were, however, substantial differences in the timing of when changes would occur. The central interior of the region was forecast to change earlier than the arid west and southern coast. These differences in timing were driven by differences in the responses of trees, succulents, C3 and C4 grasses to the GCMs forecast aridification of the region’s central interior. Phytoclime modelling provides an indication of the potential of a region’s climate to support different plant types; it thereby provides forecasts of the potential impacts of climate change on regional vegetation structure and functioning.

Heterogenous influence of productive capacities pillars and natural resources on ecological sustainability in developing Belt and Road host countries

Global climate change and environmental pollution force humanity to create new sustainable growth models. Growth policy relies heavily on the pillars of sectoral productivity: resource efficiency and sustainable resource management. This research adds to the determination of the impact of the numerous productive capacity indices (PCI) and natural resources on the ecological sustainability of emerging Belt and Road host nations from 2000 to 2018. The study utilized the system generalized method of moments (Sys-GMM) and the Feasible generalized least squares (FGLS) estimators to analyze the association among the variables. The empirical findings suggest that cumulative PCI and technological innovation have a promising impact on emissions reduction, while natural resources positively derive emissions. Manifestly, sub-indicators of PCI offer heterogeneous outcomes. Productive capacities in human capital, ICT, energy, and governance encourage ecological sustainability, while transport, private sector development, and structural change increase emissions. Augmented Mean Group estimator also validates similar findings. This research suggests improving operational efficiencies and productive capacities leads to better ecological outcomes.

Spatial-Temporal Characteristics and Driving Forces of Aboveground Biomass in Desert Steppes of Inner Mongolia, China in the Past 20 Years

The desert steppe serves as a transitional zone between grasslands and deserts, and long-term monitoring of aboveground biomass (AGB) in the desert steppe is essential for understanding grassland changes. While AGB observation techniques based on multisource remote-sensing data and machine-learning algorithms have been widely applied, research on monitoring methods specifically for the desert steppe remains limited. In this study, we focused on the desert steppe of Inner Mongolia, China, as the study area and used field sampling data, MODIS data, MODIS-based vegetation indices (VI), and environmental factors (topography, climate, and soil) to compare the performance of four commonly used machine-learning algorithms: multiple linear regression (MLR), partial least-squares regression (PLS), random forest (RF), and support vector machine (SVM) in AGB estimation. Based on the optimal model, the spatial–temporal characteristics of AGB from 2000 to 2020 were calculated, and the driving forces of climate change and human activities on AGB changes were quantitatively analyzed using the random forest algorithm. The results are as follows: (1) RF demonstrated outstanding performance in terms of prediction accuracy and model robustness, making it suitable for AGB estimation in the desert steppe of Inner Mongolia; (2) VI contributed the most to the model, and no significant difference was found between soil-adjusted VIs and traditional VIs. Elevation, slope, precipitation, and temperature all had positive effects on the model; (3) from 2000 to 2020, the multiyear average AGB in the study area was 58.34 g/m2, exhibiting a gradually increasing distribution pattern from the inner region to the outer region (from north to south); (4) from 2000 to 2020, the proportions of grassland with AGB slightly and significantly increasing trend in the study area were 87.08% and 5.13%, respectively, while the proportions of grassland with AGB slightly and significantly decreasing trend were 7.76% and 0.05%, respectively; and (5) over the past 20 years, climate change, particularly precipitation, has been the primary driving force behind AGB changes of the study area. This research holds reference value for improving desert steppe monitoring capabilities and the rational planning of grassland resources.

Steep-slope viticulture: The effectiveness of micro-water storage in improving the resilience to weather extremes

Steep-slope vineyards are widely distributed in the Mediterranean region and have a pivotal role in wine production, economic development, and cultural heritage. Nevertheless, they are threatened by climate change in terms of opposite weather extremes, such as heavy rainfalls and long-lasting droughts. In response, rainwater harvesting systems have emerged as valuable solutions for managing water resources and controlling related problems. Of primary importance is the identification of suitable sites for installation. However, a systematic selection procedure still needs to be explored; it is necessary for morphologically complex vineyards that include historical features of significant cultural value (such as terraced systems). To fill this gap, this study employed a high-resolution overflow simulation model that combines a set of criteria to identify the optimal network of water harvesting structures (also drawing on traditional knowledge) and quantify the potential for water storage during rainfall of varying intensities. The study area considered is located within the “Soave Traditional Vineyards” (north of Italy) site, a Globally Important Agricultural Heritage System (GIAHS) recognized by FAO. The surface overflow was simulated considering two key rainstorms that occurred in the last few years at different time intervals. 53 potential sites for water harvesting were selected according to field survey, runoff simulation, and topographic analysis. The results indicate that the water potentially collected from designed sites could have a double function: (1) mitigate the surface overflow that can potentially cause downslope terrace collapse or even flooding villages; (2) provide irrigation water for vineyards during water scarcity scenarios. The spatial distribution of the water collected could undoubtedly guide sustainable decisions in steep-slope viticultural systems under climate change forcing.

Impacts of climate change on dragonflies and damselflies in West and Central Asia

AbstractAimTo project the impact of climate change on dragonfly and damselfly diversity in West and Central Asia.LocationWest and Central Asia.Time period1900–2020 data used to predict distributions in 2070 and 2100.Taxon studiedOdonata.MethodsBased on 149,001 records, distribution models were created for 159 species using MaxEnt. Environmental variables consisted of climate variables taken from BIOCLIM, river data and soil data. The future climate data were obtained from CHELSA from CMIP6 climate models. The same variables were collected for three scenarios (SSP1‐2.6, SSP3‐7.0 and SSP5‐8.5) of shared socioeconomic pathways for the years 2050–2070 and 2080–2100. For each scenario and period, diversity maps were prepared for six species groups: all species, Lentic, Lotic, Oriental, Afrotropical and Palaearctic species.ResultsStrong declines in diversity are expected in western Turkey, the Levant and Azerbaijan, and to a lesser extent in parts of Iran and southern Central Asia. An increase is expected in eastern Turkey and at higher elevations in Central Asia with a limited increase throughout the Arabian Peninsula. In contrast to expectations, a decrease in areas with <15 species was found. Faunal composition is predicted to show strong shifts, with Palaearctic species declining and Oriental and Afrotropical species increasing. No clear difference between the trend of lentic and lotic species is found, although there are clear spatial differences in trend between these groups.Main ConclusionsClimate change will result in strong changes in diversity and distribution of dragonflies and damselflies in West and Central Asia with regional declines and increases. None of the species are predicted to go extinct based on the impact of climate change only, however, the combined impact of climate change and anthropogenic forces is likely to push some of the species to near extinction by 2100.