Impact Of Climate Change Research Articles

Low impact of Carpobrotus edulis on soil microbiome after manual removal from a climate change field experiment

Synergic effects between climate change and invasive species may alter soil microbial diversity and functioning, as well as cause major shifts in physicochemical properties. Moreover, some of these ecological impacts may manifest even after the removal of the invasive species. We have conducted a field experiment to assess such effects on soil microbial communities (fungi and bacteria) and physicochemical properties seven months after the removal of Carpobrotus edulis (L.), an invasive plant of coastal dune ecosystems. C. edulis grew on the experimental plots for 14 months under current (“invasive species treatment”) and increased warming and drought conditions (“combined treatment”). Then, all plant parts (above and belowground biomass) were removed with a non-aggressive eradication method and soil samples were collected seven months later in the experimental and control plots (no invasive species and current climatic conditions). We predicted a general compositional shift in microbial communities in response to the presence of the invasive species. Moreover, given that water is the most limiting factor in this type of ecosystem, we also predicted a more pronounced compositional shift in the treatment combining invader presence and climate change. While species richness was similar amongst treatments, we observed some taxonomic and functional variation in soil microbial communities. Notably, fungal and bacterial communities exhibited contrasting responses. The species composition of bacteria differed significantly between the “invasive species” and “control” treatments, while, in the case of fungi, the most substantial difference occurred between the “invasive species” treatment and the combined treatment of “invasive species and climate change”. Some chemical properties, such as carbon and nitrogen content or pH, strongly differed amongst treatments, with the “invasive species” showing a different response compared to the other two treatments. Overall, our study suggests smaller short-term effects on the microbial community compared to soil chemical properties. Furthermore and contrary to our initial expectations, the potential impact on the soil microbiome seemed to be weaker in the face of rising temperatures and drought conditions predicted by climate change. This outcome highlights the remarkable complexity of the impact of invasive species and climate change on belowground microbial communities.

Assessing the impact of climate change and reservoir operation on the thermal and ice regime of mountain rivers using the XGBoost model and wavelet analysis

AbstractThis study presents an analysis of the influence of climatic conditions and the operation of a dam reservoir on the occurrence of ice cover and water temperature in two rivers (natural and transformed by reservoir operations) located in the Carpathian Mountains (central Europe). The analyses are based on data obtained from four hydrological and two climatological stations. The Extreme Gradient Boosting (XGBoost) machine learning model was used to quantitatively separate the effects of climate change from the effects arising from the operation of the dam reservoir. An analysis of the effects of reservoir operation on the phase synchronization between air and river water temperatures based on a continuous wavelet transform was also conducted. The analyses showed that there has been an increase in the average air temperature of the study area in November by 1.2 °C per decade (over the period 1984–2016), accompanied by an increase in winter water temperature of 0.3 °C per decade over the same period. As water and air temperatures associated with the river not influenced by the reservoir increased, there was a simultaneous reduction in the duration of ice cover, reaching nine days per decade. The river influenced by the dam reservoir showed a 1.05 °C increase in winter water temperature from the period 1994–2007 to the period 1981–1994, for which the operation of the reservoir was 65% responsible and climatic conditions were 35% responsible. As a result of the reservoir operation, the synchronization of air and water temperatures was disrupted. Increasing water temperatures resulted in a reduction in the average annual number of days with ice cover (by 27.3 days), for which the operation of the dam reservoir was 77.5% responsible, while climatic conditions were 22.5% responsible.

Quantifying the Impact of Climate Change on Mortality Rates: A Stochastic Actuarial Approach in Uganda

Purpose: The aim of the study was to analyze the quantifying the impact of climate change on mortality rates: a stochastic actuarial approach in Uganda. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that climate change significantly increases mortality rates, particularly through the rise in extreme weather events and temperature-related illnesses. Using stochastic actuarial models, the research demonstrated a strong correlation between climate variability and higher mortality, especially among vulnerable populations such as the elderly and those with pre-existing health conditions. The findings underscore the urgent need for climate adaptation strategies in Uganda's public health planning to mitigate the adverse effects of climate change on mortality. Unique Contribution to Theory, Practice and Policy: Risk theory, ecological theory & actuarial life table theory may be used to anchor future studies on analyze the quantifying the impact of climate change on mortality rates: a stochastic actuarial approach in Uganda. Practitioners should integrate climate data into actuarial models used for mortality forecasting and risk assessment. Policymakers should develop and enforce regulatory standards that require the inclusion of climate change considerations in actuarial assessments and reporting.

Improving Cuticle Thickness and Quality Traits in Table Grape cv. ‘Italia’ Using Pre-Harvest Treatments

Table grape viticulture, due to the impact of climate change, will have to face many challenges in the coming decades, including resistance to pathogens and physiological disorders. Our attention was focused on fruit cracking due to its ubiquitous presence in several species. This study explores the effects of three different treatments on the epidermis and cuticle of table grape berries by evaluating the impact of the girdling technique on various fruit quality parameters, including cuticle thickness, sugar content, acidity, color, bunch weight, and rheological properties. The treatments were (1) calcium chloride (CaCl2), (2) calcium chloride + salicylic acid (CaCl2 + SA), and (3) calcium chloride + Ascophyllum nodosum (CaCl2 + AN), with and without girdling, plus an untreated control. This research was conducted over the 2021–2022 growing season in a commercial vineyard in Licodia Eubea, Sicily, Italy. The results indicate significant variations in cuticle thickness and other qualitative traits throughout the growth and ripening phases, with notable differences depending on the treatment used. This study’s findings suggest that specific treatments can influence the structural integrity of the grape cuticle, potentially impacting the fruit’s susceptibility to cracking and overall marketability. The findings provide valuable insights into the role of chemical treatments and cultural techniques in enhancing fruit quality and resistance to environmental stresses in table grape cultivation.

Research on Changes in Travel Insurance Premiums Driven by Climate Change: A Case Study of Hong Kong Region

This research aims to study the impacts of climate change on worldwide general travel insurance in Hong Kong and to provide a scientific basis for premium pricing strategies in a climate-driven context. The study adopts both qualitative and quantitative research methods to reveal the relationship between climate change and travel insurance. The qualitative analysis part constructs a theoretical framework through literature review. Taking into account the current state of research, the impact of climate change on the demand for travel insurance as well as the challenges and opportunities of premium pricing strategies are discussed in depth. The quantitative analysis section collected data on flights at the Hong Kong International Airport (departures, delays, and cancellations) and travel insurance claim occurrence. The weather conditions were also checked through the weather website to analyze the correlation between climate factors and insurance claims. The findings indicated that climate change has a significant impact on the demand for travel insurance, especially during the prolonged rainy season in Hong Kong, when extreme weather events lead to an increased risk of cancellation or delay of travel plans. Meanwhile, the quantitative analysis results demonstrated a significant correlation between weather factors and flight status and insurance occurrence, which provided empirical evidence for risk assessment and premium pricing of worldwide travel insurance in Hong Kong.

Whole Genome Sequences of Cryptotympana Atrata Fabricius, 1775 (Hemiptera: Cicadidae) in the Korean Peninsula: Insights into Population Structure with Novel Pathogenic Or Symbiotic Candidates

Background: The blackish cicada (Cryptotympana atrata) exhibits unique characteristics and is one of the model cicadas found in the Korean Peninsula. It is a species of southern origin, prefers high temperatures, and is listed as a climate-sensitive indicator species in South Korea. Therefore, this species can be utilized to study the impact of climate change on the genetic diversity and structure of populations. However, research on the genome of C. atrata is limited. Methods: We sequenced the genome of an individual collected from South Korea and constructed a draft genome. Additionally, we collected ten specimens from each of the five regions in South Korea and identified single nucleotide variants (SNVs) for population genetic analysis. The sequencing library was constructed using the MGIEasy DNA Library Prep Kit and sequenced using the MGISEQ-2000 platform with 150-bp paired-end reads. Results: The draft genome of C. atrata was approximately 5.0 Gb or 5.2 Gb, making it one of the largest genomes among insects. Population genetic analysis, which was conducted on four populations in South Korea, including both previously distributed and newly expanded regions, showed that Jeju Island, a remote southern island with the highest average temperature, formed an independent genetic group. However, there were no notable genetic differences among the inland populations selected based on varying average temperatures, indicating that the current population genetic composition on the Korean Peninsula is more reflective of biogeographic history rather than climate- induced genetic structures. Additionally, we unexpectedly observed that most individuals of C. atrata collected in a specific locality were infected with microbes not commonly found in insects, necessitating further research on the pathogens within C. atrata. Conclusion: This study introduces the draft genome of C. atrata, a climate-sensitive indicator species in South Korea. Population analysis results indicate that the current genetic structure of C. atrata is driven by biogeographic history rather than just climate. The prevalence of widespread pathogen infections raises concerns about their impact on C. atrata. Considering the scarcity of publicly available genomic resources related to the family Cicadidae, this draft genome and population data of C. atrata are expected to serve as a valuable resource for various studies utilizing cicada genomes.

Cover cropping enhanced soil aggregation and associated carbon and nitrogen storage in semi-arid silage cropping systems

Wind and water erosion in arid and semi-arid regions significantly degraded soil, reduced soil organic carbon (SOC) storage, and exacerbated the impact of climate change on agricultural productivity. Cover cropping is one of the approaches to improve soil health and reduce climate change impacts, yet its impacts on soil aggregation and associated SOC and nitrogen (N) storage in water-limited environments are poorly understood. This study aimed to evaluate soil aggregate dynamics and aggregate-associated SOC and soil total N in irrigated silage sorghum [Sorghum bicolor L. (Moench)] − corn (Zea mays L.) rotations with various cover crop mixtures: grasses + brassicas + legumes (GBL), grasses + brassicas (GB), grasses + legumes (GL), and no cover crops (NCC). Results showed in the second year of the study that, at 0–0.1 m depth, mean weight diameter and geometric mean diameter of dry aggregates were 22–23 % and 6 % greater, respectively, with cover crops than NCC. At the same depth, cover crop treatments had 15–17 %, 15–16 %, and 13 % greater SOC in 0.25–2, 0.053–0.25, and < 0.053 mm aggregate classes, respectively, compared to NCC. Similarly, at 0–0.1 m depth, N in < 0.053 mm fraction was 8–10 % greater with cover crops than without. In the fourth year of the study, water-stable aggregates (WSA) percent did not differ among treatments, but WSA-associated SOC was 31–37 % and 12–16 % greater with cover crops at 0–0.1 and 0.1–0.2 m depths, respectively, than without. The WSA-associated N at 0–0.1 m was 21–33 % greater with cover crops than without. Despite the inconsistencies in soil aggregate stability results, cover crop-integrated silage systems showed greater SOC and N within aggregate classes and water stable aggregates. This insight is crucial for advancing sustainability in silage production systems, particularly in the context of increasing climate change and variability in erosion-prone soils of arid and semi-arid regions.

Evaluating the Impact of Climate Change on Sustainable Economic Development: Empirical Research in the Coastal Area of Kien Giang, Vietnam

Alongside the economic growth in various coastal regions, including Kien Giang, the area faces non-traditional security issues, most notably marine environmental pollution due to the impacts of climate change. This study surveyed 130 households in several coastal regions of Kien Giang. It employed a multivariate regression model to assess the implications and quantify climate change's effects on economic activities. The findings indicate that most factors harm the financial activities of households living in these coastal regions of Kien Giang. This paper underscores the significance of addressing the adverse impacts of climate change on local economies. It highlights the urgent need for comprehensive strategies to mitigate these effects, ensuring the sustainable development of coastal communities in Kien Giang.

Climate Change Impacts on and Response Strategies for Kiwifruit Production: A Comprehensive Review

Climate Change Impacts on and Response Strategies for Kiwifruit Production: A Comprehensive Review

Impact of climate change on agriculture in Australia: an interactive fixed effects model approach

ABSTRACT Developing policies and programmes aimed at mitigating the impacts of climate change on crop yield requires methods that correctly quantify the dependence of crop yield on weather. This article utilizes recent advances in econometric methodology and proposes an interactive fixed effects model for modelling crop yield. An attractive feature of the proposed model is that it allows for the varying degrees to which different farmers adapt to global events, such as, an increase in the global fertilizer price and an introduction of a new technology. Thus, the proposed method is an improvement over the standard method based on the fixed effects model, which is widely used in the literature for modelling crop yield. We apply the proposed approach to model wheat yields across 24 statistical areas that cover the wheat belt of the state of Victoria, Australia. Our forecasts point to a potential 14% loss in yields in the state of Victoria and a 27% loss in North-West Victoria, under the Hotter & Drier climate scenario, which the IPCC predicts to be more likely for Victoria in the medium term. Should this eventuate, it would have significant negative impacts on the wheat industry, food security and the economy.

Assessment of the Impacts of Climate and Land Use Changes on Water Yield in the Ebinur Lake Basin

Assessment of the Impacts of Climate and Land Use Changes on Water Yield in the Ebinur Lake Basin

A new method to quantify the impacts of human activity on soil conservation service

Human activities and climate change impact ecosystem services, thereby affecting economic and social sustainable development. Measuring the heterogeneity in space and time of how human activities affect ecosystem services poses a challenge for the sustainable management of land resources. Based on “human appropriation of net primary production (HANPP) - Fractional Vegetation Cover (FVC) - Soil Conservation Service (SCS)” cascading effect, first, a geographically and temporally weighted regression (GTWR) model was employed to assess the impact of HANPP in percent of potential NPP (hereafter HANPP%) on the FVC; second, changes in the FVC caused by human activities were quantified; and third, the potential soil conservation service (SCSp) and actual soil conservation service (SCSa) were estimated using the Revised Universal Soil Loss Equation (RUSLE) model, and the difference between them represented the changes in soil conservation service caused by human activities (SCSh). Taking the Qinghai-Tibet Plateau as a case study, we found that the GTWR model was well suited for analyzing the relationship between the HANPP% and the FVC (R2 = 0.897). The HANPP resulted in a decrease in the FVC from 0.222 in 2001 to 0.199 in 2019 and correspondingly resulted in a decrease in the ratio of SCSh to SCSp from 8.95% to 7.24%. This study provides a quantitative method that allows quantifying the influence of human activity on ecosystem services closely related to the FVC.

Forestat: An R package for computing forest carbon sequestration and potential productivity

1. Forest ecosystem is a basic component of terrestrial ecosystem that mitigates the impact of climate change through absorbing significant amount of carbon dioxide. Forest is crucial in maintaining ecological equilibrium, reducing greenhouse gas emission, and preserving biodiversity. Thus, standardised and precise methodologies for measuring forest carbon sequestration and assessing its potential are of paramount importance in evaluating the impacts of climate change.2. We presented the “forestat”, an approach for assessing forest carbon sequestration and its potential based on annual growth of biomass, considering site class and forest age conditions, wrapped in an R package, which is applicable to all forest types. By using a comprehensive system of forest stand models, “forestat” contributes to a refined comprehension of relationships between forest biomass and carbon sequestration and offers an evaluation of the carbon sequestration potential in forest ecosystem, unifying the methods of carbon measurement and its potential estimation in both natural and plantation forests.3. Based on the two applications, this study (a) introduces and demonstrates the methods in R package “forestat”; (b) uses the 6th, 7th, 8th, and 9th National Forest Inventory data to investigate carbon sequestration and potential productivity of degraded forests in China; and (c) conducts suitability analysis for tree species in the Yellow River Basin.4. “forestat” provides a unified, efficient, and standardized analytical tool for forest carbon sequestration and its potential. This study also highlights the primary forest functionalities.

Gender Inequities in the Impact of Climate Change on Health: A Scoping Review.

In the 21st century, climate change has emerged as a critical global public health challenge. Women experience the most severe impacts of climate change, intensifying pre-existing gender inequalities. This scoping review aims to explore the intersection of climate change, health, and gender, considering the social determinants of health. The methods for this review follow the Arksey and O'Malley framework for a scoping review and the PRISMA-ScR checklist. The review, covering January 2019 to February 2024, included PubMed, LILACS, and SciELO databases. We identified 71 studies with 19 meeting the inclusion criteria. The results revealed the differential effects of climate change on health according to gender in areas such as mental health, reproductive health, gender-based violence, occupational health, and health issues associated with heat and air pollution. Our findings also elucidated how socio-economic and gender inequities intersect, exacerbating the risk of experiencing these effects. In conclusion, the study highlights a clear need for gender-sensitive climate policies and interventions to address these disparities and protect vulnerable populations from the health impacts of climate change.

Frequency Bias Causes Overestimation of Climate Change Impacts on Global Flood Occurrence

AbstractThe frequency change of 100‐year flood events is often determined by fitting extreme value distributions to annual maximum discharge from a historical base period. This study demonstrates that this approach may significantly bias the computed flood frequency change. An idealized experiment shows frequency bias exceeding 100% for a 50‐year base period. Further analyses using Monte Carlo simulations, mathematical derivations, and hydrological model outputs reveal that bias magnitude inversely relates to base period length and is weakly influenced by the generalized extreme value distribution's shape parameter. The bias, persisting across different estimation methods, implies floods may exceed local defenses designed based on short historical records more often than expected, even without climate change. We introduce a frequency bias adjustment method, which significantly reduces the projected rise in global flood occurrence. This suggests a substantial part of the earlier projected increase in flood occurrence and impacts is not attributable to climate change.

Differential impact of climate and land use change on habitat suitability of migrant passerines according to habitat preferences

Our study contributes to the ongoing dialogue on the impact of climate and habitat changes on migratory bird species, particularly focusing on how these effects vary based on species’ habitat preferences. We used citizen science data for 22 African-Eurasian migratory bird species and categorized them into five groups based on habitat preferences, following the classification methodology of Atkinson et al. (2014). Using ensemble species distribution modeling (SDM), we projected changes in potentially suitable habitats across Africa from 2040 to 2100 under contrasting climate and land use scenarios. Our results indicate a differential impact of climate and land use changes on habitat suitability, with species preferring habitats with shrubs and trees being the most vulnerable. Conversely, other group species, such as open country-grassland and farmland birds could experience a significant increase in suitable habitat. We anticipate a profound change in habitat suitability, with the western part of South Africa becoming unsuitable for most species, while an increase in suitable habitat is expected in the Sahel. Bioclimatic rather than land use variables emerged as the primary drivers of these changes. The extent of change in habitat suitability will be strongly influenced by the Shared Socio-economic Pathways followed by human societies.

The key role of extreme weather and climate change in the occurrence of exceptional fire seasons in south-central Chile

Unprecedentedly large areas were burned during the 2016/17 and 2022/23 fire seasons in south-central Chile (34-39°S). These seasonal-aggregated values were mostly accounted for human-caused wildfires within a limited period in late January 2017 and early February 2023. In this paper, we provide a comprehensive analysis of the meteorological conditions during these events, from local to hemispheric scales, and formally assess the contribution of climate change to their occurrence. To achieve this, we gathered monthly fire data from the Chilean Forestry Corporation and daily burned area estimates from satellite sources. In-situ and gridded data provided near-surface atmospheric insights, ERA5 reanalysis helped analyze broader wildfire features, high-resolution simulations were used to obtain details of the wind field, and large-ensemble simulations allowed the assessment of climate change's impact on extreme temperatures during the fires. This study found extraordinary daily burned area values (>65,000 ha) occurring under extreme surface weather conditions (temperature, humidity, and winds), fostered by strong mid-level subsidence ahead of a ridge and downslope winds converging towards a coastal low. Daytime temperatures and the water vapor deficit reached the maximum values observed across the region, well above the previous historical records. We hypothesize that these conditions were crucial in exacerbating the spread of fire, along with longer-term atmospheric processes and other non-climatic factors such as fuel availability and increasing human-driven ignitions. Our findings further reveal that climate change has increased the probability and intensity of extremely warm temperatures in south-central Chile, underscoring anthropogenic forcing as a significant driver of the extreme fire activity in the region.

Developing an annual global Sub-National scale economic data from 1992 to 2021 using nighttime lights and deep learning

The Gross Domestic Product (GDP) per capita is one of the most widely used socioeconomic indicators, serving as an integral component for climate change impact analysis. However, a national scale assessment may induce considerable bias because it conceals any internal variations within a country. The lack of a long-term sub-national scale GDP data is a substantive hinderance. Leveraging the close relationship between nighttime lights and GDP, we address this gap by developing a novel methodological framework in two steps. First, under the modeling philosophy of spatial statistics, we developed a novel approach based on deep and machine learning techniques to establish a complex mapping between two inconsistent nighttime lights (NTL) datasets: the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP) and the National Polar-Orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (VIIRS). The models achieve accuracies ranging from 0.945 to 0.980 (correlation coefficients). By taking the estimations ensemble of the two techniques, the time series of DMSP data was extended to 2021. Next, a novel modeling strategy based on multi-layer perceptron was developed to derive the non-linear relationship between NTL and GDP per capita at sub-national scale to alleviate scale effects at this granularity, while explicitly capturing regional heterogeneity effect. The trained models achieve average accuracies of 0.967, 0.959, and 0.959 on the training, validation, and test sets, respectively. We evaluate the developed dataset at the global, national, and sub-national scales from various perspective, and the results offer solid evidence on the reliability of the estimated economic data. By linking to historical global climate change data, we quantify global economic losses attributed to extreme heat to demonstrate how the estimated GDP data can be useful in the climate change impact analysis.

Assessing the impact of climate change on aircraft engine performance during different flight phases (take-off and cruise) and the environmental consequences

PurposeClimate change significantly impacts global temperatures, posing challenges to various sectors, including aviation. The purpose of this study is to assess the impact of climate change on aircraft engine performance during different flight phases (take-off and cruise) and the environmental consequences.Design/methodology/approachThis study examines the effects of rising temperatures on aircraft engine performance using real-time data from a Boeing 787-8 equipped with GEnx-1B engines, which are collected via Flight Data Recorder of the engines and were analyzed for the take-off and cruise phases on the ground. Exhaust gas temperature (EGT), fuel flow and take-off weights were evaluated.FindingsThe analysis revealed a significant increase in EGT at the cruising altitude of 38,000 ft during the summer months compared to expected standard atmospheric values. This increase, averaging over 200 °C, is attributed to global warming. Such elevated temperatures are likely to accelerate the degradation of turbine components, resulting in increased fuel consumption: higher EGT signifies inefficient engine operation, resulting in more fuel burned per unit thrust; early engine aging: elevated temperatures accelerate wear and tear on turbine components, potentially reducing engine lifespan and increasing maintenance costs and enhanced atmospheric pollution: incomplete combustion at high EGTs generates additional emissions, contributing to local air quality concerns.Practical implicationsThe research findings have practical implications for understanding the potential operational challenges and environmental impacts of climate change on aircraft engine performance. This lets us explore mitigation strategies and adapt operational procedures to ensure sustainable regional aviation practices.Originality/valueThis research enhances environmental consequences by assessing the impact of climate change on aircraft performance.

Perceptions and Knowledge on the Impact of Climate Change on Health: A Multinational Study in Latin America

Perceptions and Knowledge on the Impact of Climate Change on Health: A Multinational Study in Latin America