Changes In Precipitation Patterns Research Articles

Altered intra-annual precipitation patterns affect the N-limitation status of soil microorganisms in a semiarid alpine grassland

The ongoing intensification of the hydrological cycle due to global climate change alters intra-annual precipitation variability. Changes in precipitation patterns lead to disparities in soil moisture; however, the responses of soil extracellular enzyme activities (EEAs) and microbial metabolism limitations to them is unclear. This study conducted an in situ field experiment in the alpine grasslands of the Kunlun Mountains to simulate the same amount of precipitation but change the distribution time of precipitation within the plant growing season. We examined the effects of variability in intra-annual precipitation patterns on the stoichiometry of topsoil (0–5 and 5–20 cm) properties, microbial biomass, and EEAs. Results showed that altered precipitation patterns significantly increased soil moisture’s disparity index (D) by 57 %–89 %. The activity of nitrogen-acquiring enzymes (L-leucine aminopeptidase) was increased by 20.82–32.08 % (P < 0.05) with increased variability of precipitation, while phosphorus-acquiring enzymes (Acid phosphatase) and carbon-acquiring enzymes (β-glucosidase) both decrease by 9.25–23.35 % and by 17.86–33.04 %, respectively (P < 0.05). We determined that soil microorganisms in the study region were metabolism-limited by nitrogen (vector angles < 45◦), and increased precipitation variability exacerbated nitrogen limitation (decrescent vector angles) and alleviated carbon limitation (shortened vector length). In addition, soil EEAs can be both interactively influenced by biotic and abiotic factors, with abiotic factors (i.e., D, soil organic carbon content, and soil total nitrogen content) having a stronger effect. Our study provides an effective strategy for regulating soil EEAs, microbial biomass, and microbial metabolism limitation and contributes to developing nutrient management and restoration strategies in semiarid alpine grassland ecosystems.

Adapting Plant Protection Strategies to Meet the Challenges Posed by Climate Change on Plant Diseases: A review

Climate change poses a significant challenge to global agriculture, with profound implications for plant disease dynamics and plant protection strategies. This review aims to synthesize current research on the impact of climate change on plant diseases, particularly focusing on how these changes affect pathogen life cycles, host resistance, and disease distribution. Emphasizing the Indian context, this paper explores the adaptation of plant protection strategies in response to these challenges, including the integration of traditional methods and advanced scientific approaches. It provides a comprehensive overview of the key aspects of climate change relevant to agriculture, including changes in temperature, precipitation patterns, and atmospheric CO2 levels. It delves into the direct and indirect impacts of these climatic changes on plant diseases, highlighting how altered environmental conditions influence pathogen virulence and the susceptibility of host plants. This section also discusses the shifted patterns in pest and disease distribution due to climate change, with a focus on the Indian agricultural scenario. Then it examines the current challenges in plant protection, assessing the limitations of traditional methods like chemical, biological, and cultural control in the context of a changing climate. It identifies critical areas such as increased disease incidence, pathogen resistance development, and the necessity for sustainable and adaptable plant protection strategies. Further it explores various adaptive strategies, including Integrated Disease Management (IDM), advances in breeding for disease resistance, biotechnological approaches, and climate-smart agricultural practices. It outlines how IDM principles and practices are being adapted to new climate scenarios, the role of genetic engineering and traditional breeding in developing disease-resistant varieties, the development of biopesticides and biocontrol agents, and the application of climate forecasts in disease management. Case studies and practical applications from different regions of India provide real-world examples of effective adaptation strategies, drawing lessons and best practices. The review concludes by identifying research gaps, advocating for multidisciplinary collaborations between plant pathology, climatology, and agronomy, and emphasizing the critical role of policy in supporting adaptive strategies. This comprehensive synthesis and analysis aim to contribute to the broader understanding of plant protection in the era of climate change and guide future research and policy-making in this vital field.

Nitraria sibirica adapts to long-term soil water deficit by reducing photosynthesis, stimulating antioxidant systems, and accumulating osmoregulators

Amid climate change and shifts in precipitation patterns, drought conditions are expanding worldwide. Drought stress severely threatens plant growth in arid and semi-arid regions, wherein shrubs play a crucial role in maintaining ecological stability. Despite its ecological significance, studies are lacking on how Nitraria sibirica adapts to long-term drought stress. Therefore, in this study, to elucidate the mechanism of drought stress adaptation in N. sibirica, we analysed morphological, physiological, and transcriptional characteristics of plants in two soil habitats: riparian (moist) and desert (arid). The results showed that in desert soils, as soil water content decreased, leaf thickness increased, while plant height and leaf area decreased. Physiologically, photosynthesis decreased; soluble sugar, starch, proline, and hydrogen peroxide content increased significantly; while soluble proteins decreased significantly. Additionally, membrane lipid peroxidation products and antioxidant enzyme activities significantly increased under drought stress. Then, Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analysis identified 313 key genes, which were considered the most significantly enriched in the photosynthesis and photosynthetic antenna protein pathways. Further, we found that the proteins encoding photosystem II (PsbP, PsbQ, PsbR, PsbY, and Psb27), photosystem I (PsaD, PsaF, PsaG, PsaH, PsaK, and PsaO), photosynthetic electron transport (PetF), and light-trapping antenna proteins were significantly downregulated under drought stress. Taken together, these results suggest that N. sibirica adapts to long-term drought conditions by suppressing photosynthesis, activating antioxidant systems, and recruiting osmoregulators. This study provides a basis for elucidating the growth mechanisms of N. sibirica under long-term drought stress conditions.

The Influences of Rainfall Intensity and Timing on the Assemblage of Dung Beetles and the Rate of Dung Removal in an Alpine Meadow.

Changes in precipitation patterns, including rainfall intensity and rainfall timing, have been extensively demonstrated to impact biological processes and associated ecosystem functions. However, less attention has been paid to the effects of rainfall intensity and rainfall timing on the assembly of detritivore communities and the decomposition rate of detritus such as animal dung. In a grazed alpine meadow on the eastern Qinghai-Tibet Plateau, we conducted a manipulative experiment involving two levels of rainfall intensity (heavy rainfall, 1000 mL/5 min; light rainfall, 100 mL/5 min) and five levels of rainfall timing (0, 2, 4, 24, and 48 h after yak dung deposition). The aim was to determine the effects of rainfall intensity, timing, and their interaction on the assemblage of dung beetles and dung removal rate during the early stage (i.e., 96 h after yak dung deposition) of dung decomposition. Light rainfall significantly increased species richness in the treatment of 48 h after dung pats were deposited. Heavy rainfall significantly decreased beetle abundance in both the 0 h and 48 h treatments while light rainfall had no effect on beetle abundance. Dung mass loss was significant lower in the 2 h treatment compared to other treatments regardless of rainfall intensity. The structural equation model further revealed that the species richness of dung beetles and dung mass loss were significantly affected by rainfall timing but not by rainfall intensity. However, no significant relationships were observed between any variables examined. These findings suggest that changes in precipitation patterns can influence both the structure of dung beetles and the rate of dung decomposition but may also decouple their relationship under a certain circumstance. Therefore, it is crucial to pay greater attention to fully understand local variability between the biological processes and ecosystem functions within a global climate change scenario.

Increased drought and extreme events over continental United States under high emissions scenario

The frequency, severity, and extent of climate extremes in future will have an impact on human well-being, ecosystems, and the effectiveness of emissions mitigation and carbon sequestration strategies. The specific objectives of this study were to downscale climate data for US weather stations and analyze future trends in meteorological drought and temperature extremes over continental United States (CONUS). We used data from 4161 weather stations across the CONUS to downscale future precipitation projections from three Earth System Models (ESMs) participating in the Coupled Model Intercomparison Project Phase Six (CMIP6), specifically for the high emission scenario SSP5 8.5. Comparing historic observations with climate model projections revealed a significant bias in total annual precipitation days and total precipitation amounts. The average number of annual precipitation days across CONUS was projected to be 205 ± 26, 184 ± 33, and 181 ± 25 days in the BCC, CanESM, and UKESM models, respectively, compared to 91 ± 24 days in the observed data. Analyzing the duration of drought periods in different ecoregions of CONUS showed an increase in the number of drought months in the future (2023–2052) compared to the historical period (1989–2018). The analysis of precipitation and temperature changes in various ecoregions of CONUS revealed an increased frequency of droughts in the future, along with longer durations of warm spells. Eastern temperate forests and the Great Plains, which encompass the majority of CONUS agricultural lands, are projected to experience higher drought counts in the future. Drought projections show an increasing trend in future drought occurrences due to rising temperatures and changes in precipitation patterns. Our high-resolution climate projections can inform policy makers about the hotspots and their anticipated future trajectories.

Impact of and solutions to effects of climate changes for Longyearbyen, Svalbard, Norway

Climate changes forces us to make significant mitigation and adaptation measures. As temperature rises and the environmental conditions changes, a variety of challenges occur. Across the whole globe, harming consequences are already being experienced. The Arctic region is particularly vulnerable to changes in Earth’s climate system, especially because of the albedo effect, and the region is already heavily impacted. Primarily through the melting of ice, both sea ice and glaciers, permafrost thawing and changing precipitation patterns. Longyearbyen, Svalbard, is one examples of a society having to change as a direct result of global warming. This paper focuses on the challenges Longyearbyen will be facing and possible adaption methods and solutions. Because of environmental changes, the risk of natural hazards will increase, infrastructure will get damaged and traditional engineering methods will be impossible to implement. This is threatening to human lives as well as the habitat and survival of mammals, birds, and plants. It will be essential to find ways to predict and limit the effects of climate challenges, by protecting people and infrastructure from them. This will require innovation, adaption and risk-taking. By investigating the climate challenges facing Longyearbyen and possible ways to address them, this paper emphasizes the urgency of tackling the effects of climate changes in the Arctic in order to protect the communities in the Arctic region.

Environmental Change Impact on Agriculture Economic Products

There are significant environmental changes in the northwest region of China. These changes are raising concerns about their effects on agricultural products. In addition, this paper synthesizes findings from various studies to find the relationship between environmental changes and agricultural products. Expect for historical challenges, like barren land and sandstorms, governance build many policies to make ecological and agricultural improvements. These policies target to solve the environmental problems. Furthermore, the study processes many influential factors like changing precipitation patterns, ecological improvements, creative farming practices, and governmental policy impacts. By using the ARIMA model to forecast the data from the China Agricultural Information Network, results evaluate how environmental changes affect prices of key agricultural products, especially for peaches and watermelons. In the rest of studies also highlights the roles of technology and policies and providing insights into their economic and ecological significance. In conclusion, this study reveals the understanding of relationship between environmental changes and agricultural products, and it offer insights for sustainable development in the northwest region of China.

Spatial distribution patterns of dated landslide events in the Northern Apennines in response to Holocene regional climatic changes

In this work we examine the spatial and temporal distribution of radiocarbon dates from landslides on the NE-facing side of the Northern Apennines during the Holocene, focusing on the region’s associated vegetation and climatic changes. We also propose a method for identifying areas and landslides that may contain very old organic materials for future research in the region. This analysis was based on a principal component analysis (PCA) on 5255 grid cells measuring 1 km2 each, overlaid on the study area. These grid cells incorporated variables derived from the terrain characteristics, including underlying lithologies and topographic features.Our findings reveal that, during the upper Holocene, the last dated events of recurrent and single-event landslides occurred first closer to the coldest and wettest territories once occupied by the glacier termina during the Last Glacial Maximum (LGMgt). Subsequently the last dated events occurred at distances greater than 30 km from the LGMgt, towards the mountain chain’s margin. Conversely, at the beginning of the Holocene, an opposite pattern emerged, with landslide events occurring towards the chain interior. These spatial patterns were consistently observed when considering also the entire dataset of 87 dates for landslide events. During the middle Holocene, we observed that the recurrent landslides were primarily concentrated within a narrow belt 8.5 km from the LGMgt. Furthermore, higher rates of landslide activity were associated with the 4.2 ka BP event and persisted until approximately 2.0 ka BP, indicating a correlation with wet and cool periods. In conclusion, these spatial patterns in landslide events can be linked to changes in precipitation patterns and dominant atmospheric circulation in the mountain belt occurred since the beginning of the Holocene.

On the identification of seasonal trends, dependency and driving forces of precipitation and vertically integrated vapour transport over Northeast India

AbstractThe vertically integrated horizontal vapour transport (IVT) accompanied by westerlies and southwesterlies mainly contributes as a distant source of moisture to the seasonal precipitation (PR). The moisture transport and PR patterns across the eastern Himalayas (Sikkim, northern Sub‐Himalayan West Bengal and Arunachal Pradesh) are strongly modulated by the orographic setup, local land‐atmospheric factors and teleconnection with climate indices of the Indian and Pacific oceans. This study elaborates on the changing patterns of PR and IVT, changes in IVT contribution to the seasonal PR under the nonstationary framework and evaluates the nonlinear dependency on local and distant drivers with piecewise regression model. Asymmetries in significant seasonal trends are conspicuous due to multi‐altitude interactions. Strong declining trend over Assam and Arunachal Pradesh is evident for PR with concurrent rising trend over the Meghalaya plateau. The IVT signals show a significant decline in post‐monsoon (October and November) and winter (December to February) across Assam Plain. The increase in mean IVT contributes significantly to seasonal PR. Significant decline in the contribution of heavy IVT to winter PR is observed over Manipur, Mizoram, Tripura and part of Assam. Surface 2 m temperature and net thermal radiation exhibit contrasting influence on seasonal PR. IVT shows mainly positive association with surface 2 m dew point temperature and latent heat flux across the eastern Himalayas. NINO3.4 index exhibits strong negative influence on post‐monsoon PR. The Pacific Decadal Oscillation is strongly associated with summer (March to May) PR. Monsoon (June to September) IVT is negatively influenced by the Pacific Decadal Oscillation over the Sub‐Himalayan West Bengal, Gangetic West Bengal, Bihar and Jharkhand. The Southern Oscillation Index is negatively linked with summer IVT. The combination of local driving forces mainly controls the seasonal PR and IVT across all seasons. Besides, distant drivers are prominent in monsoon and post‐monsoon. This study reveals insights into recent changes of PR and IVT, their contribution to seasonal water resources in the eastern Himalayas and the controlling strength of local land‐atmosphere feedback mechanism and distant land‐ocean coupling drivers under nonstationary climate.

Fine-root morphology of woody and herbaceous plants responds differently to altered precipitation: A meta-analysis

The growth of plant roots and their acquisition of resources are significantly impacted by changes in precipitation patterns. Although numerous studies have examined the impact of precipitation on fine root systems, the rooting strategies of woody and herbaceous plants under different precipitation patterns remain to be comparatively evaluated. Accordingly, in the current study, we conducted a meta-analysis of 64 peer-reviewed articles to explore the response of 17 biomass and fine-root traits of woody and herbaceous plants to precipitation changes. Our findings demonstrate that woody and herbaceous plants have developed different root strategies to cope with altered precipitation. Specifically, when precipitation increased, the fine roots of woody plants had a larger surface area and significantly increased shallow root growth. In contrast, the fine-root morphological traits of herbaceous plants showed a stronger response to increased precipitation, in which fine-root length, volume, and tissue density increased. This may result in more effective use of available water by herbaceous than woody plants. When precipitation decreased, woody plants displayed more active fine-root morphological alterations, presenting a conservative fine-root phenotype of resource acquisition, with lower specific root length and higher fine-root tissue density. Moreover, woody plants transfer absorptive fine-root structures to deep soil layers, whereas herbaceous plants are less drought-tolerant. Furthermore, woody plants may allocate biomass more optimally than herbaceous plants in precipitation-reduction scenarios. Increased precipitation may boost soil carbon sequestration and stability in woody plant-dominated forest ecosystems under future climate change scenarios, while drought may considerably reduce soil carbon storage in grassland ecosystems. In more arid environments, where woody and herbaceous plants coexist, drought may lead to the expansion of woody plants and subsequent predominance of woody plants vegetation change. our findings will fill knowledge gaps in the literature regarding the effects of precipitation changes on the fine-root dynamics of various functional plants and will improve predictions of the vegetation dynamics of forests, grasslands, and other ecosystems vegetation dynamics under changing precipitation patterns.

Differential responses of soil extracellular enzyme activity and stoichiometry to precipitation changes in a poplar plantation

Changes in precipitation patterns can significantly affect belowground processes. Although soil extracellular enzymes play a vital role in several biogeochemical processes, our knowledge of how precipitation changes affect soil extracellular enzyme activity (EEA) and stoichiometry remains insufficient. In this study, we investigated the activities of C-acquiring enzyme (β-1,4-glucosidase), N-acquiring enzymes (β-N-acetylglucosaminidase and leucine aminopeptidase), and P-acquiring enzyme (acid phosphatase) under different precipitation scenarios [ambient precipitation (CK), 30% decrease in precipitation (moderate DPT), 50% decrease in precipitation (extreme DPT), 30% increase in precipitation (moderate IPT), and 50% increase in precipitation (extreme IPT)] in a poplar plantation. We found soil EEA exhibited more pronounced increases to moderate IPT compared to moderate DPT (positive asymmetry), the opposite trend (negative asymmetry) was observed under extreme precipitation; whereas soil EEA C:N:P stoichiometry exhibited negative asymmetry at moderate precipitation changes, and exhibited positive asymmetry at extreme precipitation changes. Under moderate precipitation changes, the asymmetry of soil EEA was mainly regulated by asymmetries of respective microbial biomass and litter mass; the asymmetry of soil EEA stoichiometry was mainly regulated by asymmetries of respective soil stoichiometric ratios and litter mass. Furthermore, under extreme precipitation changes, the asymmetries of soil EEA and stoichiometry were best explained by the asymmetry of soil moisture. Our results provide the first evidence of double asymmetric responses of soil EEA and stoichiometry to precipitation changes and highlight the need to consider this asymmetry when modeling the dynamics of biogeochemical cycling in forest ecosystems.

Rainfall Variability and its Effect on Livestock Production Across Nigeria

This study aimed at investigating climate variability and its impact on livestock production across Nigeria. Observational data of monthly rainfall was obtained for a period of 42 years (1979 to 2021) from Nigerian Meteorological Agency (NiMET). The yearly animal production data was also obtained for a period of 10 years (2013 to 2022) from Federal Ministry of Agriculture and Natural resources. The data obtained was subjected to descriptive statistical analysis (mean, standard deviation and coefficient of variation) to show spread and variability; linear regression to show trend (changes with time); coefficient of correlation to show statistical relationship between the variables (rainfall and each of the animal production); revealing insights into changing precipitation patterns. Positive and negative correlations were identified, indicating how changes in rainfall influenced livestock output. And the significance of these correlations was determined through t-tests, shedding light on the strength of the relationship between rainfall and livestock production.

A hybrid simulation framework for predicting virus impacts on Chinese cabbage yields

AbstractSustainable production of Chinese cabbage (Brassica rapa L.) is essential for the economy and food security in South Korea. However, climate change poses significant threats to its growth and quality. Changes in precipitation patterns, such as drought and heavy rain, can affect the development of crop, leading to stunted growth or disease. This can lead to significant losses in crop yield. In this study, a hybrid modeling system was developed to predict the incidence of viral disease and evaluate impacts of combination of virus infection and environmental variabilities (including climate and location) on marketable cabbage yields. The crop growth model was successfully developed using a limited number (n = 7) of previous studies (root mean square error 0.25–0.33 Mg ha−1, R2 = 0.87–0.99). The developed hybrid modeling system was composed of a virus incident model and a crop growth model. According to simulated results, all study locations had around 20% incidence rates. However, based on the simulation results, the rates of viral disease incidence varied depending on the climate of each year. Among several climatic factors, precipitation had the greatest effect on virus outbreaks. Jeju Island, which had relatively high rainfall, had a higher disease incidence rate than other provinces. According to shared socioeconomic pathways (SSPs), in SSP245 (an intermediate development pathway), the yield of 1.58 Mg ha−1 was reduced to 1.26 Mg ha−1 due to a 25% viral disease outbreak. In SSP585 (a high development pathway), with an incidence of 23%, the yield was reduced by 0.2 Mg ha−1. These results will be useful for efficiently cultivating crops under various climatic conditions and seeking management methods to minimize damage from viral disease.

Plant-Derived Epi-Nutraceuticals as Potential Broad-Spectrum Anti-Viral Agents.

Although the COVID-19 pandemic appears to be diminishing, the emergence of SARS-CoV-2 variants represents a threat to humans due to their inherent transmissibility, immunological evasion, virulence, and invulnerability to existing therapies. The COVID-19 pandemic affected more than 500 million people and caused over 6 million deaths. Vaccines are essential, but in circumstances in which vaccination is not accessible or in individuals with compromised immune systems, drugs can provide additional protection. Targeting host signaling pathways is recommended due to their genomic stability and resistance barriers. Moreover, targeting host factors allows us to develop compounds that are effective against different viral variants as well as against newly emerging virus strains. In recent years, the globe has experienced climate change, which may contribute to the emergence and spread of infectious diseases through a variety of factors. Warmer temperatures and changing precipitation patterns can increase the geographic range of disease-carrying vectors, increasing the risk of diseases spreading to new areas. Climate change may also affect vector behavior, leading to a longer breeding season and more breeding sites for disease vectors. Climate change may also disrupt ecosystems, bringing humans closer to wildlife that transmits zoonotic diseases. All the above factors may accelerate the emergence of new viral epidemics. Plant-derived products, which have been used in traditional medicine for treating pathological conditions, offer structurally novel therapeutic compounds, including those with anti-viral activity. In addition, plant-derived bioactive substances might serve as the ideal basis for developing sustainable/efficient/cost-effective anti-viral alternatives. Interest in herbal antiviral products has increased. More than 50% of approved drugs originate from herbal sources. Plant-derived compounds offer diverse structures and bioactive molecules that are candidates for new drug development. Combining these therapies with conventional drugs could improve patient outcomes. Epigenetics modifications in the genome can affect gene expression without altering DNA sequences. Host cells can use epigenetic gene regulation as a mechanism to silence incoming viral DNA molecules, while viruses recruit cellular epitranscriptomic (covalent modifications of RNAs) modifiers to increase the translational efficiency and transcript stability of viral transcripts to enhance viral gene expression and replication. Moreover, viruses manipulate host cells' epigenetic machinery to ensure productive viral infections. Environmental factors, such as natural products, may influence epigenetic modifications. In this review, we explore the potential of plant-derived substances as epigenetic modifiers for broad-spectrum anti-viral activity, reviewing their modulation processes and anti-viral effects on DNA and RNA viruses, as well as addressing future research objectives in this rapidly emerging field.

Towards the selection of a longer record of quantitative precipitation forecast dataset from TIGGE ensembles for India during the monsoon season

ABSTRACT A reliable forecast of summer monsoon precipitation is crucial in India. To select a longer record of forecast data from the THORPEX Interactive Grand Global Ensemble (TIGGE) archives, we applied two criteria: the length of the dataset should be at least 10 years of continuous record, and the forecast product should have at least 20 ensemble members for a lead time of minimum 5 days. We evaluate the ensemble quantitative precipitation forecasts (QPFs) obtained from the four agencies throughout the monsoon season (June to September) from 2011 to 2020 in 22 river basins of India in forecasting normal and extreme precipitation events. The Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG) is used as observation data. The proficiency of QPFs is evaluated using six criteria from deterministic, dichotomous, and probabilistic error statistics. The error values are classified into three categories – low, moderate, and high. A Forecast Reliability Index is formulated using the given four QPFs, and three categories for each of the six error statistics to answer (a) which QPF shows better performance in which river basin and (b) whether any conclusion can be made on the overall performance of a QPF for all the River Basins of India.

Mediterranean springs: Keystone ecosystems and biodiversity refugia threatened by global change

AbstractMediterranean spring ecosystems are unique habitats at the interface between surface water and groundwater. These ecosystems support a remarkable array of biodiversity and provide important ecological functions and ecosystem services. Spring ecosystems are influenced by abiotic, biotic, and anthropogenic factors such as the lithology of their draining aquifers, their climate, and the land use of their recharge area, all of which affect the water chemistry of the aquifer and the spring discharges. One of the most relevant characteristics of spring ecosystems is the temporal stability of environmental conditions, including physicochemical features of the spring water, across seasons and years. This stability allows a wide range of species to benefit from these ecosystems (particularly during dry periods), fostering an unusually high number of endemic species. However, global change poses important threats to these freshwater ecosystems. Changes in temperature, evapotranspiration, and precipitation patterns can alter the water balance and chemistry of spring water. Eutrophication due to agricultural practices and emergent pollutants, such as pharmaceuticals, personal care products, and pesticides, is also a growing concern for the preservation of spring biodiversity. Here, we provide a synthesis of the main characteristics and functioning of Mediterranean spring ecosystems. We then describe their ecological value and biodiversity patterns and highlight the main risks these ecosystems face. Moreover, we identify existing knowledge gaps to guide future research in order to fully uncover the hidden biodiversity within these habitats and understand the main drivers that govern them. Finally, we provide a brief summary of recommended actions that should be taken to effectively manage and preserve Mediterranean spring ecosystems for future generations. Even though studies on Mediterranean spring ecosystems are still scarce, our review shows there are sufficient data to conclude that their future viability as functional ecosystems is under severe threat.

Wildfire univariate and bivariate characteristics simulation based on multiple machine learning models and applicability analysis of wildfire models

Wildfires can significantly impact regional and global climate, human health, and ecosystems, making it necessary to model their behavior and predict their outcomes. With increasing global temperatures and changing precipitation patterns due to climate change, the frequency and intensity of wildfires are expected to increase, heightening the requirement for accurate wildfire simulation models to support wildfire management and mitigation efforts. However, the interactions between the causative variables of wildfires and the wildfire bivariate characteristics have not been explored in wildfire modeling. Therefore, the copula function was applied to solve the complicated and nonlinear relationship of the dependence structure in wildfire statistics and the relationship between wildfire causative variables. Subsequently, we modeled wildfire characteristics globally using six machine learning models and compared the performances of the models. Specifically, the main conclusions were obtained as follows: (1) among the six machine learning models, long short-term memory had the best applicability in simulating wildfire characteristics; (2) when there were 4 predictors, the accuracy of wildfire characteristic simulation reached the average level; and (3) long short-term memory achieved excellent model performance within 56% of the global climate sub-regions. Overall, this analysis provides a reference to better understand wildfire and contributes to wildfire management.

Spatiotemporal patterns of soil water replenishment and their seasonal origins in a subtropical red soil critical zone

Assessing the integration of precipitation and its isotopic signals in soil water is crucial for understanding the sensitivity of soil available water to precipitation variability. Here the investigations of water stable isotopes and in-situ soil water content were conducted for determining the spatiotemporal patterns of soil water replenishment and their seasonal origins in a subtropical red soil critical zone. Variations in soil water content provide valuable information regarding the quantity and depth of soil water replenishment in response to precipitation events. Soil water replenishment often penetrated to a depth of 100 cm or more from winter to early summer (from December to the next June), but the corresponding replenishment amounts were relatively low. However, most soil water replenishment events were generally limited to the upper 40 cm soil layers between midsummer and autumn (from July to November), with relatively large amounts in summer. The temporal and vertical variations in the seasonal origin index of soil water indicated that summer precipitation constituted the largest fractions (∼66 %) of soil water storage in the entire explored soil profile (thickness = 130 cm) during the study period. Winter precipitation was overrepresented in soil water only at the depth of 0–20 cm in spring, but it may vary slightly from year to year due to changes in winter precipitation patterns (amount and frequency). The findings of the current study broadly highlight how precipitation contributes to soil water storage over space and time, which has significant implications for plant water sources.

How is climate change adaptation aid allocated? A study of climate justice in Ecuador

&#x0D; &#x0D; &#x0D; This paper analyses the allocation of climate adaptation aid in subnational and local jurisdictions in Ecuador. It examines the influence of physical and socioeconomic vulnerability and local capacity as independent variables of aid allocation. The study introduces projections of physical vulnerability to determine whether inter-generational aspects of climate justice are taken into account and uses geographically weighted regression models to study the spatial distribution of aid allocation. The findings show that physical and socioeconomic vulnerabilities influence adaptation aid allocation. However, projected changes in patterns of precipitation and temperatures are not associated with this variable. Furthermore, the spatial distribution of current climate aid is uneven, leaving clusters of vulnerable jurisdictions unattended. Finally, the study finds no association between local capacity and adaptation aid allocation. Findings suggest that the allocation of adaptation aid may not contribute to achieving adaptation scenarios where justice for current and future generations is central to decision-making.&#x0D; &#x0D; &#x0D;

Climate change and its implications on wildlife conservation

The Intergovernmental Panel on Climate Change (IPCC) Synthesis Report, released nearly a year ago, summarized five years of reports on global temperature rises, fossil fuel emissions and climate impacts and emphasised that there was “a rapidly closing window of opportunity to secure a liveable and sustainable future for all.” It demonstrated an undeniable scientific consensus about the urgency of the climate crisis, its primary causes, its current devastating impacts – especially on the most climate vulnerable regions – and the irreversible harm that will occur to both the natural world and human society if warming surpasses 1.5°C, even temporarily. For Indonesia, climate change poses a formidable challenge for its people and its rich terrestrial and marine biodiversity that encompasses such a diverse array of ecosystems ranging from lush rainforests and dry savannas to extensive swamps and coral reefs. As the world's fourth most populous nation and the biggest archipelagic country in the world, Indonesia consists of some 17,000 islands, with over 8,000 km of coastline and is therefore extremely vulnerable to the impacts of global climate change. The nation's rich biodiversity, encompassing iconic species such as the Sumatran tiger, orangutan, and Komodo dragon, is intricately linked to the health of its ecosystems. Rising temperatures, changing precipitation patterns, and the increasing frequency of extreme weather events disrupt these ecosystems, leading to shifts in species composition and distribution.