Change Scenarios Research Articles

Power Quality Improvement Using a Novel Simplified Adaptive Control of Solar PV Integrated Shunt Active Power Filter

ABSTRACTPower quality improvement in grid‐tied solar photovoltaic (PV) system is one of the emergent current research trends. To address the power quality concern, shunt active power filters (SAPF) are widely deployed and researched in grid‐tied PV systems. This paper presents a simplified adaptive transversal (SAT)‐filter control scheme for the two‐stage PV‐SAPF system. The proposed control has the ability to improve different power quality indices. Also, it features faster operation under steady‐state and under dynamic conditions, better dc‐offset rejection ability due to estimation of the accurate fundamental component of the load current. To justify the effectiveness of the proposed control scheme, a thorough comparison is carried out with different conventional and adaptive control schemes. Simulations and extensive experimental analysis are carried out under severe transient conditions such as balanced‐unbalanced supply, sudden load, and irradiation change scenario.

Depth-dependent effects of forest diversification on soil functionality and microbial community characteristics in subtropical forests

Soil microbes are critical to the maintenance of forest ecosystem function and stability. Forest diversification, such as monocultures versus mixed forests stands, can strongly influence microbial community patterns and processes, as well as their role in soil ecosystem multifunctionality, such as in subtropical forest ecosystems. However, less is known about these patterns and processes vary with soil depth. Here, we investigated the results of an eight-year forest diversification field experiment comparing the soil ecosystem multifunctionality, bacterial and fungal community assembly, and network patterns in mixed versus monoculture plantations along vertical profiles (0–80 cm depth) in a subtropical region. We found that the introduction of broadleaf trees in coniferous monocultures led to enhanced synergies between multiple functions, thus improving soil multifunctionality. The effects of mixed plantations on the functional potential in top soils were greater than in deep soils, especially for carbon degradation genes (apu, xylA, cex, and glx). Microbial community assembly in the top layer, particularly in mixed plantations, was dominated by stochastic processes, whereas deterministic were more important in the deep layer. Soil microbial network complexity and stability were higher in the top layer of mixed plantations, but in the deep layer was monoculture. Interestingly, the changes in microbial communities and multifunctionality in the top layer were mainly related to variation in nutrients, whereas those in the deep were more influenced by soil moisture. Overall, we reveal positive effects of mixed forest stands on soil microbial characteristics and functionality compared to that of monocultures. Our findings highlighted the importance of enhancing functional diversity through the promotion of tree species diversity, and managers can better develop forest management strategies to promote soil health under global change scenarios.

Case Study on the Adaptive Assessment of Floods Caused by Climate Change in Coastal Areas of the Republic of Korea

This study aims to assess the adaptability of coastal areas in the Republic of Korea to future climate change-induced flooding. Coastal areas can be susceptible to complex external factors, including rainfall, tide levels, storm surge wave overtopping, etc. The study employs an integrated approach to address this, connecting hydrological and marine engineering technologies. The models utilized in this study encompass XP-SWMM, ADCIRC, SWAN, and FLOW-3D. This study analyzed floods in 2050 and 2100, considering expected rainfall patterns, sea level rising, and an increase in typhoon intensity based on climate change scenarios for six coastal areas in the Republic of Korea. We reviewed the adaptability of flooding to climate change in each region.

The Effect of Climate Change on Indicator Wetland Insects: Predicting the Current and Future Distribution of Two Giant Water Bugs (Hemiptera: Belostomatidae) in South Korea.

Giant water bugs (Hemiptera: Belostomatidae) are top predators in wetland ecosystems, serving as biological indicators of the health of lentic ecosystems and as effective biological control agents for freshwater snails and mosquitoes. This study aimed to predict the current and future distribution of two Korean giant water bugs, Appasus japonicus and Diplonychus esakii, under three climate change scenarios, contributing to the sustainable management of wetland ecosystems in South Korea. Using MaxEnt models, we employed seven climatic and three non-climatic variables to investigate the habitat preferences and distribution patterns of the species. The results revealed that A. japonicus is likely to experience a northward range contraction due to climate change, while D. esakii is predicted to expand its distribution northward without losing its current range. These responses may lead to occupancy turnover between the two species, potentially driving reassembly in aquatic organism community. Elevation was the primary factor influencing the distribution of A. japonicus, whereas annual mean temperature was the most informative variable for D. esakii, both factors derived under the current climate conditions. These findings suggest that both species are highly sensitive to climate change, with potential range shifts toward higher latitudes and elevations. This study provides insights into how climate change could impact two giant water bugs, thereby supporting future efforts to manage and conserve wetland ecosystems in this country.

Modelling the Effects of Forest use Change on Brownification of Finnish Rivers under Atmospheric Pressure.

Browning of surface waters due to increased terrestrial loading of dissolved organic matter (DOM) is observed across the Northern Hemisphere. The effects influence several ecosystem services from freshwater productivity to water purification. Brownification is often explained by changes in large-scale anthropogenic pressures and ecosystem functioning (acidification, climate change, and land cover changes). This study examined the effect of forest use changes on water browning in Finland, considering the effects of global pressures. Our goal was to find the ecosystems and geographic areas that are most sensitive to environmental pressures that increase the loading of DOM. We were also looking for land use strategies that decrease browning. We combined mathematical watershed modelling to scenarios of climate change, atmospheric deposition, and forest use change. Changes included scenarios of forest harvest and protection on forest, that were derived from European Union's regulation. The study area covered 20 watersheds from south to north of Finland. In northern Finland brownification continue. In southern Finland global influence (atmospheric deposition, climate change) seem to weaken, giving more space for local forest use change having an influence on brownification. Forest use change was more influential in river basins dominated by organic soils than in mineral soils. Extending forest protection decreased brownification especially in areas where the influence of atmospheric pressure is decreasing. When forest protection is planned to provide a carbon storage and sequestration potential and to favor biodiversity, it has favorable effect on surface water quality as well.

Adapting East and Southern Africa’s livestock to climate change: a decision making under deep uncertainty-based approach for effective actions

ABSTRACT Livestock farmers are increasingly challenged to adapt to the impacts of climate change, necessitating the selection of adaptation strategies to effectively mitigate risks and protect livelihoods. This paper introduces a framework designed specifically for guiding the selection of context-specific adaptation options in the Eastern and Southern Africa region. The framework builds on a decision tree that incorporates changes within a management system or switching to another one, enabling a nuanced evaluation of adaptation options. Driven repetitively under different scenarios of climate changes and/or climate models, the frequencies of selecting different adaptation measures vary across livestock value chains, climate zones, and systems. Responding to the evolution of the climate system, these frequencies evolve over time, affecting the selection. For instance, agroforestry emerges as an increasingly suitable option for cattle and, to a lesser extent, for goats due to the projected rise in moderate heat stress periods, particularly in tropical climates. Conversely, this frequency decreases for sheep, more susceptible to heat stress, beyond the effect of agroforestry. This framework resolves the need for more context – and time-specific decisions on adaptation. This decision tree-based framework serves as a robust decision-making tool to steer the livestock sector toward effective climate change adaptation.

Global change drives potential niche contraction and range shift of globally threatened African vulture

Human-induced global change poses an increasingly severe threat to biodiversity, with species having limited population sizes being particularly vulnerable. Mapping and modeling the distribution ranges of such species, along with detecting potential range shifts and contractions at both local and regional scales, are essential for developing effective conservation plans. Ruppell's vulture Gyps rueppelli, an ecologically important bird species native to Africa, is experiencing a rapid decline in its range. The purpose of this study is to map and model potential regional spatio-temporal distribution of Ruppell's vulture in Africa, alongside detecting the possibility of the species' range shifts and contractions. A total of 804 rarefied localities were identified where the Ruppell's vulture was the dominant bird species. This study employed the Maximum Entropy (MaxEnt) algorithm to perform species distribution modeling for the Ruppell's vulture. The modeling considered current climate conditions (1970s-2000s) as a baseline, along with two future climate change scenarios (Shared Socioeconomic Pathways: SSPs 245 and 585) for two future time periods (2050s and 2070s). The model's performance was evaluated by optimizing settings and examining the Area under the Receiver Operating Characteristic Curve (AUC-ROC). Among the 13 bioclimatic and anthropogenic variables included in the model, four (isothermality, cropland expansion, anthropogenic biomes, and urban expansion (in order of importance)) emerged as the most influential drivers of Ruppell's vulture regional distribution. All considered Species distribution models (SDMs) achieved high predictive performance, with AUC-ROC values exceeding 0.9.The model predicted a total of approximately 19,453 ha of suitable habitat for Ruppell's vultures in Africa, with East Africa identified as the most prominent region under the current climate scenario. Isothermality (38.8%) was the primary factor influencing Ruppell's vulture distribution, followed by agricultural expansion (29.9%) and anthropogenic biomes (7.2%) in the face of global change. The results reveal considerable future habitat loss (up to 61%) for Ruppell's vultures in the study area, alongside an eastward range shift (longitudinal axis) by the 2050s under projected climate change scenarios. These imply that Ruppell's vultures face imminent population decline and range shift due to significant habitat loss and climate change. Hence, prioritizing the development and implementation of a coordinated conservation program that incorporates captive breeding and assisted migration is critical to save this vulture species in its native African range.

Salinity influence on Mytilus galloprovincialis exposed to antineoplastic agents: a transcriptomic, biochemical, and histopathological approach

Nowadays, aquatic species face a variety of environmental risks associated with pharmaceutical consumption. More specifically, the increased number of cancer patients has been accompanied by an increased consumption of antineoplastic drugs, such as ifosfamide (IF) and cyclophosphamide (CP). These drugs have been found in aquatic ecosystems, raising concerns about their impact, especially on estuarine species, as marine waters are the final recipients of continental effluents. Simultaneously, predicted climatic changes, such as salinity shifts, may threaten organisms. Considering this, the present research aims to investigate the combined effects of IF and CP, and salinity shifts. For this, a transcriptomic, biochemical, and histopathological assessment was made using the bivalve species Mytilus galloprovincialis exposed for 28 days to IF and CP (500 ng/L), individually, at different salinity levels (20, 30, and 40). IF and CP up-regulated metabolism-related gene cyp3a1, with CP also affecting abcc gene, showing minimal salinity impact and highlighting the importance of these metabolic routes in mussels. Salinity shifts affected the transcription of genes related to apoptosis and cell cycle growth, such as p53, as well as the aerobic metabolism, the antioxidant and biotransformation mechanisms. These findings indicate mussels' high metabolic adaptability to osmotic stress. Under CP exposure and low salinity, mussels exhibited increased cellular damage and histopathological effects in digestive gland tubules, revealing detrimental effects towards M. galloprovincialis, and suggesting that a metabolic slowdown and activation of antioxidant mechanisms helped prevent oxidative damage at the control and high salinities. Overall, results reinforce the need for antineoplastics ecotoxicological risk assessment, especially under foreseen climate change scenarios.

The Germination Performance After Dormancy Breaking of Leucaena diversifolia (Schltdl.) Benth. Seeds in a Thermal Gradient and Its Distribution Under Climate Change Scenarios.

Climate change models predict temperature increases, which may affect germination, an important stage in the recruitment of individuals in agroecosystems. Therefore, it is crucial to conduct research on how temperature will impact the germination of multipurpose native species. Leucaena diversifolia (Schltdl.) Benth. is native to America and is commonly cultivated around the world due to having a high protein content in seeds, and their trees are used in agrosilvopastoral systems because they fix nitrogen and provide shade and cattle feed. However, climate change affects the critical phases of its life cycle and influences its growth, reproduction, phenology, and distribution. To assess the germination performance of Leucaena diversifolia under different temperatures throughout thermal times, we estimated germination variables and determined cardinal temperatures and thermal time; we also analysed germination and potential distribution under two climate change scenarios. We found significant variations in seed germination (78-98%) and differences in cardinal temperatures (Tb = 5.17 and 7.6 °C, To = 29.42 and 29.54 °C, and Tc = 39.45 and 39.76 °C). On the other hand, the sub-optimal and supra-optimal temperature values showed little differences: 51.34 and 55.57 °Cd. The models used showed variations in germination time for the analysed scenarios and the potential distribution. We confirm that the populations and distribution of L. diversifolia will be altered due to climate changes, but the species retains the ability to germinate under warmer conditions.

Divergent future trends in global land greening and carbon sequestration under climate change scenarios

Abstract Over the past four decades, global land greening has promoted carbon (C) storage in terrestrial ecosystems. However, whether the future trajectory of this positive greening effect on ecosystem C sequestration is sustainable under various climate scenarios remains uncertain. Here, using projections from ten Earth system models, we found divergent trends in the relationship between global land greening and C storage among three distinct shared socioeconomic pathways (SSPs). We identified global transition times for their positive relationships, which will occur in 2034, 2038, and 2048 for SSP1-2.6, SSP2-4.5, and SSP5-8.5, respectively. We found a widespread decoupling trend of vegetation greening and ecosystem C storage under medium to high emission scenarios, particularly in the tundra, boreal forest, and grassland regions, by delving deeper into six transition modes. These findings underscore the highly uncertain role of vegetation greening in land C sequestration under prospective climate change scenarios.

Ascophyllum nodosum Extract Improves Olive Performance Under Water Deficit Through the Modulation of Molecular and Physiological Processes.

The olive tree is well adapted to the Mediterranean climate, but how orchards based on intensive practices will respond to increasing drought is unknown. This study aimed to determine if the application of a commercial biostimulant improves olive tolerance to drought. Potted plants (cultivars Arbequina and Galega) were pre-treated with an extract of Ascophyllum nodosum (four applications, 200 mL of 0.50 g/L extract per plant), and were then well irrigated (100% field capacity) or exposed to water deficit (50% field capacity) for 69 days. Plant height, photosynthesis, water status, pigments, lipophilic compounds, and the expression of stress protective genes (OeDHN1-protective proteins' dehydrin; OePIP1.1-aquaporin; and OeHSP18.3-heat shock proteins) were analyzed. Water deficit negatively affected olive physiology, but the biostimulant mitigated these damages through the modulation of molecular and physiological processes according to the cultivar and irrigation. A. nodosum benefits were more expressive under water deficit, particularly in Galega, promoting height (increase of 15%) and photosynthesis (increase of 34%), modulating the stomatal aperture through the regulation of OePIP1.1 expression, and keeping OeDHN1 and OeHSP18.3 upregulated to strengthen stress protection. In both cultivars, biostimulant promoted carbohydrate accumulation and intrinsic water-use efficiency (iWUE). Under good irrigation, biostimulant increased energy availability and iWUE in Galega. These data highlight the potential of this biostimulant to improve olive performance, providing higher tolerance to overcome climate change scenarios. The use of this biostimulant can improve the establishment of younger olive trees in the field, strengthen the plant's capacity to withstand field stresses, and lead to higher growth and crop productivity.

Modeling climate-related global risk maps of rice bacterial blight caused by Xanthomonas oryzae (Ishiyama 1922) using geographical information system (GIS).

Rice is a critical staple crop that feeds more than half of the world's population. Still, its production confronts various biotic risks, notably the severe bacterial blight disease produced by Xanthomonas oryzae. Understanding the possible effects of climate change on the geographic distribution of this virus is critical to ensuring food security. This work used ecological niche modeling and the Maxent algorithm to create future risk maps for the range of X. oryzae under several climate change scenarios between 2050 and 2070. The model was trained using 93 occurrence records of X. oryzae and five critical bioclimatic variables. It has an excellent predictive performance, with an AUC of 0.889. The results show that X. oryzae's potential geographic range and habitat suitability are expected to increase significantly under low (RCP2.6) and high (RCP8.5) emission scenarios. Key climatic drivers allowing this development include increased yearly precipitation, precipitation during the wettest quarter, and the wettest quarter's mean temperature. These findings are consistent with broader research revealing that climate change is allowing many plant diseases and other dangerous microbes to spread across the globe. Integrating these spatial predictions with data on host susceptibility, agricultural practices, and socioeconomic vulnerabilities can help to improve targeted surveillance, preventative, and management methods for reducing the growing threat of bacterial blight to rice production. Proactive, multidisciplinary efforts to manage the changing disease dynamics caused by climate change will be critical to assuring global food security in the future decades.

Single and combined effects of metal-based fungicides on Eisenia andrei in different scenarios of climatic change.

This study evaluated the ecotoxicity of metal-based fungicides under the current scenarios of global climatic change (20°C and 25°C) and moisture content (30% and 50%) in single and binary mixtures of copper oxychloride (CuOx) [200, 500 and 1000mg/kg] and mancozeb (MnZn) [44, 850 and 1250mg/kg]. Endpoints assessed included mortality, changes in biomass, avoidance behaviour, and reproduction utilising standardised protocols (ISO and OECD). The changes in biomass and mortality tests lasted 28days, followed by a 28-day reproduction test and a two-day avoidance test. In all temperature-moisture combinations, the mortality rate in the exposure groups exceeded 10% only in the CuOx1000 and CuOx1000 + MnZn1250 mg/kg groups. However, at 20°C and 30% moisture, the mortality rate exceeded 10% only in the CuOx500 + MnZn850 mg/kg treatment. Relative growth rates in the CuOx and MnZn treatment groups decreased with increasing concentrations. In CuOx MnZn and the binary mixture treatments at 20°C 30% and 25°C 50% conditions, avoidance response behaviour was greater than 80% throughout the exposure, except in CuOx200 mg/kg, MnZn44 mg/kg and CuOx200 + MnZn44 mg/kg. The reproduction of exposed earthworms in all treatment groups was concentration-dependent and influenced by varying temperatures and soil moisture conditions. No juveniles or cocoons were produced in the CuOx1000 mg/kg treatment at 25°C 30%, indicating that copper oxychloride may be more toxic than mancozeb, especially in drought conditions. This study found that different temperatures and soil moisture levels altered the ecotoxicity of CuOx and MnZn. It can be concluded that climate change is likely to significantly impact the outcomes of metals to earthworms and their ecological activities.

Seagrass Biodiversity Under the Latest‐Generation Scenarios of Projected Climate Change

ABSTRACTAimThe potentially cascading consequences of climate changes on redistribution of habitat‐forming species, like seagrasses, remain a major research gap. Empirical demonstrations of local population changes are increasingly reported without a globally integrated predictive framework as a leading testable hypothesis. Therefore, here, we aimed to estimate changes in species richness, community composition, and areas of climatic refugia under future climate scenarios.LocationGlobal scale.Time PeriodPresent‐day conditions (from 2010 to 2020) and for three Shared Socioeconomic Pathway (SSP) scenarios of future climate change (from 2090 to 2100).Major Taxa StudiesSeagrasses (plantae).MethodsWe coupled seagrass occurrences with environmental predictors (temperature, salinity, nitrate, wave energy, and ice) in stacked species distribution modelling.ResultsModels estimated a present global extent of 917,169 km2 with high species richness in Temperate Australasia, Indo‐Pacific, and Temperate North Pacific. Future projections predicted widespread spatial redistribution, with Arctic expansions, losses in lower latitudes, and deeper vertical ranges, while globally maintaining the area extent occupied worldwide by seagrass species (only 5% of change). Species richness increased poleward under more drastic scenarios (SSP3‐7.0 and SSP5‐8.5), with losses in tropical zones (30oN to 30oS). Local climatic refugia are retained in all scenarios but decrease under higher emissions. Additionally, even where seagrass species remain, widespread community composition changes were predicted.Main ConclusionsOur findings serve as baselines to inform, anticipate, and mitigate cascading consequences of shifts in seagrass ecosystems that provide essential services for humanity.

Projection of climate change impact on main climate variables and assessment of the future of Köppen–Geiger climate classification in Iran

AbstractHuman society and the environment are facing significant challenges due to climate change. Climate change is projected to impact main climate variables, such as temperature and precipitation. Changes in main climate variables affect climate classification and alter climate zone maps. In this research, first, the projection of temperature and precipitation in 30 main stations of Iran under the Shared Socioeconomic Pathways scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) from Coupled Model Intercomparison Project Phase Six (CMIP6) for the end of the twenty-first century (2071–2099) was carried out. Then, the future of climate zone maps was assessed in Iran by Köppen-Geiger climate classification. The evaluation of the model data based on observation data for the period of 1991–2020 showed an acceptable correlation, with R-square and RMSE values in the ranges of 0.67–0.96 and 2.44–8.38, respectively. Results showed that the temperature in the future period (2071–2099) will increase by 1–4.7 °C under all scenarios compared to the historical study period (1991–2020), while the precipitation will either increase or decrease depending on the season and the specific climate change scenario. Assessment of future climate classifications revealed that the BW (arid desert) and BS (semi-arid steppe) categories will increase, as classified by Köppen-Geiger, will increase. At the same time, Ds and Cs (dry summer) classifications will decrease in during the study period over Iran. These findings provide policymakers with some insights into how to deal with the impacts of climate change in the future and implement some measures now.

Effectiveness of Options for the Adaptation of Crop Farming to Climate Change in a Country of the European South

This study quantitatively evaluates the effectiveness of three main options for the adaptation of crop farming to climate change (i.e., shift of planting dates, increase/addition of irrigation, and resilient hybrids/cultivars) in Greece, a country in southern Europe. The potential effect of each option on the yields of several crops in all Greek regions is estimated for 2021–2040 and 2041–2060 and compared with those under the historical local climate of 1986–2005, by using agronomic and statistical regression models, and data from different climatic simulations and climate change scenarios. Our results reveal that all the adaptation options examined have the potential to significantly reduce crop yield losses occurring under no adaptation, particularly during 2021–2040 when for many regions and crops more than half of the losses can be compensated for. Notably, in some cases during this period, the measures examined resulted in crop yields that are higher than those under the historical climate. However, the effectiveness of the measures diminished significantly in 2041–2060 under very adverse climate change conditions, highlighting the dynamic nature of adaptation. Assessing the effectiveness of combined adaptation options and evaluating additional criteria (e.g., feasibility) represent essential areas for future research.

Imaging magnetic transition of magnetite to megabar pressures using quantum sensors in diamond anvil cell

High-pressure diamond anvil cells have been widely used to create novel states of matter. Nevertheless, the lack of universal in-situ magnetic measurement techniques at megabar pressures makes it difficult to understand the underlying physics of materials’ behavior at extreme conditions, such as high-temperature superconductivity of hydrides and the formation or destruction of the local magnetic moments in magnetic systems. Here, we break through the limitations of pressure on quantum sensors by modulating the uniaxial stress along the nitrogen-vacancy axis and develop the in-situ magnetic detection technique at megabar pressures with high sensitivity (~1μT/Hz\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\sim 1{{{\\rm{\\mu }}}}{{{\\rm{T}}}}/\\sqrt{{{{\\rm{Hz}}}}}$$\\end{document}) and sub-microscale spatial resolution. By directly imaging the magnetic field and the evolution of magnetic domains, we observe the macroscopic magnetic transition of Fe3O4 in the megabar pressure range from ferrimagnetic (α-Fe3O4) to weak ferromagnetic (β-Fe3O4) and finally to paramagnetic (γ-Fe3O4). The scenarios for magnetic changes in Fe3O4 characterized here shed light on the direct magnetic microstructure observation in bulk materials at high pressure and contribute to understanding magnetism evolution in the presence of numerous complex factors such as spin crossover, altered magnetic interactions and structural phase transitions.

Seasonal Distribution of Key Small-Sized Fish in the South Inshore of Zhejiang, China

Small-sized fish are a vital food source for large predatory commercial fish and play a key role in marine food webs, bridging lower and higher trophic levels. They are indispensable in maintaining the energy flow and material cycling within aquatic ecosystems. This study utilized bottom-trawl survey data from 2017 to 2020 along the south inshore of Zhejiang, China, complemented by concurrent environmental data, to examine the influence of environmental factors on the resource density and seasonal distribution patterns of four dominant small-sized fish species. The research findings indicated that SSH (sea surface height) and Chl (chlorophyll-a concentration) emerged as the key environmental factors influencing resource densities, with all four species exhibiting similar preferences toward these variables. However, significant disparities were observed in their preferences for SST (sea surface temperature), SSS (sea surface salinity), and DO (dissolved oxygen). The various species’ resource density and distribution patterns underwent significant seasonal variations. Additionally, the seasons and regions with the highest resource densities consistently aligned, occurring predominantly in autumn within the northern waters of the study area. This research further elucidated the environmental predilections and seasonal spatial distribution traits of small-sized fish in the south inshore of Zhejiang, an important feeding ground for economic fish species in the East China Sea. This provides scientific backing for forecasting alterations in coastal fishery resources under environmental and climate change scenarios and supports ecosystem-based fisheries management strategies.

Flash flood prediction modeling in the hilly regions of Southeastern Bangladesh: A machine learning attempt on present and future climate scenarios

Flash floods are highly destructive, and their frequency and intensity are expected to escalate due to climatic changes. This study thus investigated flash flood susceptibility (FFS) by applying machine learning algorithms and climate projection to predict both present and future hazard scenarios in the southeastern hilly regions of Bangladesh. To predict FFS, we evaluated twelve flood-influencing variables: elevation (EL), slope (SL), aspect (AS), drainage density (DD), distance to stream (DS), topography roughness index (TRI), stream power index (SPI), topographic wetness index (TWI), soil permeability (SP), precipitation (PR), land use and land cover (LULC) and normalized difference vegetation index (NDVI). Earth observation data, field surveys, and past flood records were used to create a detailed flood inventory. Among the machine learning models tested, the random forest (RF) algorithm outperformed others, including support vector machine (SVC), logistic regression (LR), and extreme gradient boosting (XGBoost), and was subsequently used for flood susceptibility mapping based on future precipitation projections under two Sixth Coupled model intercomparison project (CMIP6) climate change scenarios: SSP1-2.6 and SSP5-8.5. Our findings indicated that the areas at high to very high risk of flooding are projected to increase significantly under both the SSP1-2.6 and SSP5-8.5 scenarios. Initially, around 38 % of the studied region had high to very high flood susceptibility, but this is expected to rise to 40–42 % over the projected time periods. These spatial delineations of flood-prone areas can provide guidance for developing effective mitigation and adaptation strategies to address the adverse impacts of flash flooding in the hilly river basins of Bangladesh.

Climate change favors expansion of three Eucalyptus species in China.

Eucalyptus has become one of the most widely planted species in tropical and subtropical regions in China, with important economic, ecological, and social values. However, it is currently unclear how climate change will affect different Eucalyptus species. Therefore, it is urgent to investigate the potential distribution and dynamics of Eucalyptus under current and future climate scenarios. In this study, we analyzed the potential distribution patterns of the three main Eucalyptus species (Eucalyptus grandis, Eucalyptus urophylla, and Eucalyptus tereticornis) under current and future climatic conditions (2041-2060 and 2061-2080) using the optimized MaxEnt model, which integrates a variety of environmental data including climate, topography, soil, and human influence. We also identified the main factors affecting the potential distributions of the three main Eucalyptus species. The model indicated that E. grandis exhibited heightened sensitivity to the mean temperature of the coldest quarter (7.0-20.0 °C) and annual mean temperature (11.9-24.2 °C), whereas E. urophylla displayed heightened sensitivity to precipitation of the warmest quarter (272-1694mm) and annual precipitation (812-2624mm). Conversely, E. tereticornis demonstrated heightened sensitivity to annual mean temperature (12.7-24.5°C) and temperature seasonality (63.8-598.9). Under the current climate, E. tereticornis had the widest suitable distribution area (124.91 × 104 km²), followed by E. grandis (124.89 × 104 km²) and E. urophylla (119.81 × 104 km²). Under future climate change scenarios, the suitable ranges of E. grandis, E. urophylla and E. tereticornis will continue to expand. This study highlights the importance of climate change in Eucalyptus distribution and provides quantified potential distribution maps for three Eucalyptus species under current and future climate conditions in China. This research offers valuable scientific insights pertinent to the management and rational site selection for Eucalyptus plantations.