Effects Of Climate Change Research Articles

Advancing an integrated understanding of land–ocean connections in shaping the marine ecosystems of coastal temperate rainforest ecoregions

AbstractLand and ocean ecosystems are strongly connected and mutually interactive. As climate changes and other anthropogenic stressors intensify, the complex pathways that link these systems will strengthen or weaken in ways that are currently beyond reliable prediction. In this review we offer a framework of land–ocean couplings and their role in shaping marine ecosystems in coastal temperate rainforest (CTR) ecoregions, where high freshwater and materials flux result in particularly strong land–ocean connections. Using the largest contiguous expanse of CTR on Earth—the Northeast Pacific CTR (NPCTR)—as a case study, we integrate current understanding of the spatial and temporal scales of interacting processes across the land–ocean continuum, and examine how these processes structure and are defining features of marine ecosystems from nearshore to offshore domains. We look ahead to the potential effects of climate and other anthropogenic changes on the coupled land–ocean meta‐ecosystem. Finally, we review key data gaps and provide research recommendations for an integrated, transdisciplinary approach with the intent to guide future evaluations of and management recommendations for ongoing impacts to marine ecosystems of the NPCTR and other CTRs globally. In the light of extreme events including heatwaves, fire, and flooding, which are occurring almost annually, this integrative agenda is not only necessary but urgent.

Regenerative agriculture: A paradigm shift for food production in South Africa

Agriculture and other land use practices have severely affected the quality of soils and food production systems in South Africa. In addition, these practices significantly contribute to greenhouse gas (GHG) emissions. Soil quality is generally associated with soil organic matter (SOM) along with elemental Carbon (C) and Nitrogen (N). Approximately 58% of South African soils contain <0.5% organic C, 38% contain 0.5–2% organic C, and 4% contain >2% organic C. The extensive aridity and lack of SOM content in South African soils cause them to lack resilience and have a delicate nature compared to soils in temperate regions. In a country where almost 60% of the land is degraded, and 91% is prone to desertification, farming practices require a revised framework for land management. The challenge of producing food on degraded land that is often water-scarce and particularly vulnerable to the effects of climate change is a threat to South Africa's food and nutritional security. Therefore, this review aims to equip farmers with knowledge and principles of innovative and sustainable alternatives such as regenerative agriculture that naturally and progressively improves soil quality/fertility and ecosystem health; and reduces GHG emissions through carbon sequestration. Quantitative studies in South Africa show that during 5–90 years of crop cultivation in the Free State province resulted in a 10–73% reduction in C and N relative to natural grasslands. Similar studies reported a 50% reduction in C after 50 years of cultivation on Hutton soil in Pretoria; and a 50% reduction in C after only 3.5 years of cultivation in the Free State. Considering that the world's food systems are responsible for more than a third of anthropogenic GHG emissions, we are convinced that the shifting trend toward regenerative agriculture is a sustainable climate-smart solution for global food production systems.

The Effect of Climate Change on Spatio-Temporal Activity in Burrowing Frogs of the Smilisca Group

Measuring the potential effects of future climate changes on the spatio-temporal variance of optimal conditions for seasonal species is a key conservation issue. This study assesses the impact of climate change on the spatial and temporal patterns of optimal conditions for activity in two burrowing frogs, Smilisca fodiens and S. dentata. Ecological Niche Modeling was used to implement niche seasonality models, with calibration performed during the peak activity (July). These models were then transferred to current and future conditions for the remainder of the year, predicting future scenarios up to 2070 with an intermediate trajectory greenhouse gas concentration of 4.5 W/m2. Climate change transferability was assessed for four potential scenarios: 1) high precipitation and low temperature, 2) high precipitation and high temperature, 3) low precipitation and low temperature, and 4) low precipitation and high temperature. We examined the impact across future projected areas and analyzed geographic change trends based on latitude, longitude, and elevation. For both species, the best scenario would involve increased precipitation in the future. However, the worst-case would be a combination of reduced precipitation and higher temperatures. Due to large area loss, northern populations of S. fodiens may be highly vulnerable. Concerning S. dentata, the outlook is worrisome, with all known populations experiencing losses in most months. Area gains may not help either species since they tend to occur at elevations above their known ranges. Using a seasonal approach in spatio-temporal analysis enhances comprehension of the behavioral adaptations of seasonal species and their vulnerability to current and future climatic variations

Measuring butterfly persistence in the face of deep uncertainty: a case study using the regal fritillary

Scientists have documented effects of climate and land use change across a range butterfly species. However, incorporating future climate and land use change into butterfly conservation plans is a difficult task. These difficulties arise mainly from assumptions that future processes are the same as past processes (stationarity) and because scientists cannot reliably predict the future (deep uncertainty). In this case study, I used land use and climate change scenarios to compare possible futures for the regal fritillary, a grassland butterfly in the central United States. My analysis indicated that climate and land use change have the potential to influence species persistence, but that climate change has the larger effect. Moderate warming scenarios may improve the possibility of persistence, whereas extreme warming reduces this possibility. My analysis demonstrates the importance of considering nonstationarity and alternative plausible futures in butterfly conservation planning.

Identifying time patterns of highland and lowland air temperature trends in Italy and the UK across monthly and annual scales

Abstract. This paper presents a statistical analysis of air temperature data from 32 stations in Italy and the UK up to 2000 m above sea level from 2002 to 2021. The data came from both highland and lowland areas in order to evaluate the differences due to both location and elevation. The analysis focused on detecting trends at annual and monthly timescales, employing ordinary least-squares (OLS), robust S-estimator regression, and Mann–Kendall (MK) and Sen's slope methods. Hierarchical clustering (HCA) using dynamic time warping (DTW) was then applied to the monthly data to analyze the intra-annual pattern similarity of trends within and across the groups. Two different regions of Europe were chosen because of the different climate and temperature trends – namely, the northern UK (smaller trends) and the northwest Italian Alps (larger trends). The main novelty of the work is to show that stations with similar locations and altitudes have similar monthly slopes by quantifying them using DTW and clustering. These results reveal the nonrandomness of different trends throughout the year and between different parts of Europe, with a modest influence of altitude in wintertime. The findings revealed that group average trends were close to the National Oceanic and Atmospheric Administration (NOAA) values for the areas in Italy and the UK, confirming the validity of analyzing a small number of stations. More interestingly, intra-annual patterns were detected commonly at the stations of each of the groups and are clearly different between them. Confirming the different climates, most highland and lowland stations in Italy exhibit statistically significant positive trends, while in the UK, both highland and lowland stations show statistically nonsignificant negative trends. Hierarchical clustering in combination with DTW showed consistent similarity between monthly patterns of means and trends within the group of stations and inconsistent similarity between patterns across groups. The use of the 12 distance correlation matrices (dcor) (one for each month) also contributes to what is the main result of the paper, which is to clearly show the different temporal patterns in relation to location and (in some months) altitude. The anomalous behaviors detected at 3 of the 32 stations, namely Valpelline, Fossano, and Aonoch Mòr, can be attributed, respectively, to the facts that Valpelline is the lowest-elevation station in its group; Fossano is the southernmost of the Italian stations, with some sublittoral influence; and Aonoch Mòr has a large number of missing values. In conclusion, these results improve our understanding of temperature spatio-temporal dynamics in two very different regions of Europe and emphasize the importance of consistent analysis of data to assess the ongoing effects of climate change. The intra-annual time patterns of temperature trends could also be compared with climate model results.

Restructuring the Basic Design of Several Accelerator-Based Concrete Mixes by Integrating Superplasticizers

The increasing demand for infrastructure, the need to consolidate aging structures, and the effects of climate change imply the replacement or improvement of traditional concrete. This study investigates three accelerators and their mixtures (Ca(NO3)2·4H2O, Al2(SO4)3·18H2O, and Na2S2O3·5H2O) (series I) and their counterparts with superplasticizers (Dynamon SR41) (series II) as additives in standard concrete to improve its functionality. The standard concrete and new concrete mixes were analyzed using X-ray diffraction (XRD), scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDX), and tests for water absorption, bulk density, and compressive strength. XRD analysis showed that all concrete mixes had similar structures composed of quartz, portlandite, larnite, calcium silicate, ettringite, albite, and muscovite in varying proportions. Their microstructures, as shown by SEM images, revealed the presence of ettringite, portlandite, and C-S-H gel at high magnification (1–5 kx). The addition of the superplasticizer remodeled the surface of the concrete mix, reducing the pore radius and increasing its compaction. These changes helped to reduce its bulk density while increasing the compressive strength. The results showed that all the concrete mixtures are similar to the standard concrete and can replace it for better functionality, but Na2S2O3·5H2O with superplasticizer concrete mixture had the higher compressive strength, supplying additional benefits.

Climate Change and Mental Health in Bhutan

Bhutan remains a largely non-industrialized country, making minimal contributions to global warming and climate change. Yet, the country suffers from the clutches of the adverse effects of climate change. Among them, the impact of climate change on mental health including psychological distress, acute stress disorder, post-traumatic stress disorder, major depressive disorder and anxiety disorder is well known. In this article, we aim to describe the various mental health issues that the country is facing or is likely to face in the future as a result of climate change.

Assessing the Moisture Resilience of Wood Frame Wall Assemblies

Resilience has been used as a building performance metric that measures the building’s capability of absorption, response, and recovery from one or a series of disruptive events, e.g., extreme weather events or power outage events. With respect to resilience, in relation to the moisture performance of the building envelope (moisture resilience), this aspect has not yet been thoroughly explored nor defined. Given the expected increase in annual precipitation in certain regions of Canada as induced by climate change effects occurring both currently and in the future, the moisture resilience of building envelops will require immediate attention given that wall assemblies of buildings are predicted to be subjected to excessive moisture loads in the coming years. In this study, the moisture resilience of wood frame wall assemblies to mould growth was described from three aspects: (i) absorption—the ability of the wall to maintain a low level of relative humidity on the OSB; (ii) response—the fluctuation of the relative humidity on the OSB; and (iii) recovery—the rate at which the relative humidity recovers to an acceptable level. The metrics used to demonstrate the relative impact of these factors on moisture performance were also developed. The results have revealed a robust correlation between moisture performance and the relative influence of various newly defined aspects of moisture resilience.

Effect of climate change on the habitat suitability of the relict species Zelkova carpinifolia Spach using ensembled species distribution modelling.

Zelkova carpinifolia is a Tertiary relict tree distributed in Hyrcanian and Colchic forests. Most of its habitat has been destroyed in the last century. This study aimed to model potentially suitable habitat areas for Zelkova carpinifolia from the past to the future. The Last Glacial Maximum (LGM) and Future (2061-2080) models include 19 bioclimatic variables from the CCSM4 global circulation model Pearson correlation coefficient was used to assess collinearity between variables and ten variables were selected for distribution modelling. Habitat suitability was estimated using the Biodiversity Modelling (BIOMOD) ensemble modelling method by combining the results of ten algorithm models using the R package "biomod2". The area under the curve (AUC) of the receiver operating characteristic (ROC) curve and true skills statistics (TSS) were calculated to evaluate the performance of the models. The contributions of the environmental variables were calculated separately for each algorithm model. According to the results obtained, the most effective bioclimatic variable in the distribution of the species is temperature seasonality (Bio4). The modelling results revealed that Zelkova carpinifolia survived in suitable refuge areas in western Asia during the LGM. These distribution areas have remained largely unchanged and even expanded. The future model results predict that the suitable habitats of the species will narrow in the Hyrcanian forests south of Caspian Sea and that more suitable conditions will be found around the Caucasus. Given the increasing destruction of these valuable plant species due to human activities and the expected negative impacts of climate change in the future, it is important to develop policies and strategies for the protection of Zelkova carpinifolia's habitat, the creation of nature reserves, and sustainability.

Study protocol of the planetary health action survey PACE: a serial cross-sectional survey to assess the readiness to act against climate change

IntroductionClimate change is a paramount global health threat with multifaceted implications. Societal change is required to mitigate the negative effects of climate change, as well as help people adapt to...

Projections of future bioclimatic indicators using bias-corrected CMIP6 models: a case study in a tropical monsoon region.

This study evaluates the potential impacts of climate change on Bangladesh by analyzing 19 bioclimatic indicators based on temperature and precipitation. Data from 18 bias-corrected CMIP6 global climate models (GCMs) were used, covering four Shared Socioeconomic Pathways (SSPs)-SSP126, SSP245, SSP370, and SSP585-across three future timeframes: near-term (2015-2044), mid-term (2045-2074), and long-term (2075-2100). Under the high-emission SSP585 scenario, average temperatures are projected to rise by up to 3.76°C, and annual precipitation could increase by 52.6%, reaching up to 3446.38mm by the end of the century. The maximum temperature (Bio5) could reach 32.91°C, while the minimum temperature (Bio6) might rise by 4.43°C, particularly during winter. Precipitation seasonality (Bio15) is projected to increase by as much as 7.9% in the northwest, indicating heightened variability between wet and dry seasons. The diurnal temperature range (Bio2) is expected to decrease by up to - 1.3°C, signifying reduced nighttime cooling, which could exacerbate heat stress. Significant reductions in temperature seasonality (Bio4) are forecast for the northeast, with notable declines in isothermality (Bio3) under SSP585, pointing to increased climatic extremes. These climatic shifts pose severe risks to agricultural productivity, water resource availability, and biodiversity, particularly in flood-prone regions. The findings highlight the need for urgent adaptation measures, including improved flood management systems, efficient water resource use, and climate-resilient agricultural practices. By providing robust region-specific projections, this study offers critical insights for policymakers and stakeholders to mitigate the adverse effects of climate change and safeguard environmental and economic sustainability in Bangladesh.

Application of the Bruun rule in evaluating the effect of water level fall on the Caspian Sea profile evolution

ABSTRACT The combined effects of climate change and anthropogenic activities induce significant sea-level alterations, changing beach morphologies. While the effects of water level rise on coastal regions have been extensively studied, the consequences caused by water level fall, particularly in enclosed water basins, have received limited attention. The Bruun rule is an empirical approach for estimating the erosion of sandy beaches in response to sea level rise. This study evaluates the efficacy of the Bruun rule and associated methods under water-level fall conditions. An extensive investigation was followed to understand Bruun’s rule application and its hypotheses in this context. Cross-shore profiles were collected from three stations: Larim, Farahabad, and Miankaleh, located along the southeastern coast of the Caspian Sea between 2013 and 2021. Results indicate that Bruun’s predictions are more reliable, considering their accuracy and applicability. Additionally, active zone bed slope emerges as the most significant factor influencing Bruun prediction, performing well with slopes between 0.013 and 0.016. Moreover, Bruun’s hypotheses were assessed by comparing the observed profiles and water levels over 7 months, 2 years, and 3 years, revealing a lag time contradicting Bruun’s hypothesis. Results further indicate that the Bruun rule overlooks the impacts of water level fluctuations.

Exploring the Motives Behind the Adoption of Climate Change Adaptation Strategies among Farmers in the Czech Republic

AbstractClimate change threatens agriculture in the EU and is a primary issue discussed in the European Green Deal within the Common Agricultural Policy. Central and Eastern European countries are particularly prone to climate change effects, such as droughts and extreme weather. Therefore, agriculture in Central and Eastern Europe is expected to be increasingly affected by shifting climatic patterns. This study examines the motivation for adopting adaptation strategies derived from climate-smart agriculture among farmers in the Czech Republic. We drew particular attention to analyzing the influence of farm-level and information source variables on the adaptation behavior of Czech farmers. The dataset comprises 358 respondents who were asked about climate change adaptation through a quantitative survey. We analyzed the collected data via descriptive statistics and binary logit regression models. The analysis results reveal a high degree of awareness and a diversified usage of climate change adaptation strategies among the respondents. The close linkage between perceived profitability and the willingness to adapt to climate change requires policymakers to communicate economic benefits within this context further. Information sources, such as topic-specific journals, research institutions, and field training, positively influenced the adaptation rates among the sample. Therefore, we recommend focusing on these media channels to communicate targets set within the European Green Deal.

Enhancing the SDG 6 Index: Implementing New Directions and Trends in Priorities of Integrated Water Resources Management Principles in the Republic of Korea

Enhancement of water and sanitation management acts as a significant component of global development as it is part of the United Nation’s sixth Sustainable Development Goal. Due to peculiar geographical and climatic attributes of the country and sincere efforts toward implementing IWRM, South Korea has improved its position in the SDG 6 index. The purpose of this research work is to evaluate the advancements that have been made in the IWRM of South Korea from 2018 to 2023 concerning policy changes, technical advancements, and societal engagement. Thus, this paper, through surveys and literature review, examines the measures that have been taken in the recent past to address the hydrological vulnerabilities resulting from climate change, as depicted by the UN Environment Program. Centrally, since South Korea has become more sensitive to climate change effects, and thus hydrological issues, the findings will assist in the improvement of current IWRM processes and help them achieve the SDG 6 goals. This study implies that there should be sustainable water management practices that balance natural and human interferences amidst prevailing climate change effects.

Assessing climate change threats and urbanization impacts on surface runoff in Gdańsk (Poland): insights from remote sensing, machine learning and hydrological modeling

AbstractThis study investigates the impacts of Land Use/Land Cover (LULC) changes and climate change on surface runoff in Gdańsk, Poland, which is crucial for local LULC planning and urban flood risk management. The analysis employs two primary methodologies: remote sensing and hydrological modeling. Remote sensing was conducted using Google Earth Engine and Land Change Modeler in IDRISI Terrset software to analyze historical (1985–2022) and future (2050–2100) LULC. Hydrological modeling was performed using the Natural Resources Conservation Service curve number method to assess the overall impact of LULC changes on Gdańsk’s hydrology at the local scale. The Orunia basin, a critical area due to intensive LULC development, was selected for detailed hydrological analysis using the Hydrologic Modeling System (HEC-HMS). The analysis encompassed three scenarios: LULC changes, climate change, and combined LULC and climate change effects. The LULC analysis revealed a marked increase in urban area, a shift in forest and vegetation cover, and a reduction in agricultural land. HEC-HMS simulations showed an increase in the runoff coefficient across selected decades, which was attributed to the combined effect of LULC and climate change. The projected increases under the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios for 2050 and 2100 are projected to surpass those observed during the baseline period. The findings highlight that the synergistic effects of LULC and climate change have a more significant impact on Gdańsk’s hydrology at both local and basin scales than their separate effects. These insights into LULC shifts and urban hydrological responses hold implications for sustainable urban planning and effective flood risk management in Gdańsk and similar urban settings.

Perception of Farmers about Impact of Climate Change on Agriculture in Uttarakhand, India

The development process is being threatened by climate change, which is also negatively affecting the Indian economy in a number of areas, most notably the agriculture sector. Planting, transplanting, weeding, thinning, harvesting, processing, selling, winnowing, storing, kitchen gardening, and other methods are some of the crop production techniques that farmers use. Unpredictable, and chaotic climate change is threatening agricultural productivity and the stability of rural communities' livelihoods. Farmers that are aware of these disruptive variables may be able to lessen the detrimental effects of climate change on agriculture. This study aimed to evaluate farmers' perceptions regarding the impacts of climate change on agriculture within the Almora district of Uttarakhand, India. The study was carried out in the Almora district of Uttarakhand state. Purposive sampling technique and Random sampling was used to select the study area and samples. Total sample size was 120. Data on perception of farmers about impact of climate change reveals that 63 percent of respondents reported a decrease in overall food production. Results on change in availability of water for irrigation revealed that there was no change as reported by 43.33 percent of respondents in Almora district. Availability of drinking water decreased in Almora (54 %). The frequency of forest fire was reported to be increased as reported by respondents (65 %). When we talk about crop diversity and climate change, it was found that crop diversity decreases as reported by majority of respondents (82%) in Almora showing that crop rotation and other practices were not followed properly. The wild animal attack to the crop was increased in present time and causes serious damage to the crop. To effectively address these difficulties, policy measures and guidelines can be designed with more insight if location-specific farmers' perceptions and adaptive behaviors are understood.

Heterogeneous effects of climate change on displacement-inducing disasters

With an estimated 357.7 million internal displacements caused since 2008, weather-related disasters are a major driver of human mobility worldwide. As climate change is projected to increase the frequency and intensity of extreme weather events in many parts of the world, it is important to better understand how trends in weather patterns related to global warming have affected the intensity of disasters that have caused displacements. Here we combined observational and counterfactual climate data with global internal displacement records to estimate how climate change has affected precipitation and wind speeds at the time and location of floods and storms that led to internal displacements. We estimate that, on average, climate change increased precipitation and decreased wind speeds during such events by +3.7% and − 1.4%, respectively. However, the variability across events is considerable (±28.6 and ± 6.6%, respectively), highlighting the large signal of natural variability of the weather system as compared to the global warming signal. Our results caution against overstating the role of climate change in displacement-inducing disasters in the past, especially compared to socio-economic and development factors of vulnerability and adaptive capacity that determine whether weather-related hazards turn into disasters.’

A model estimating the level of floral transition in olive trees exposed to warm periods during winter.

Rising winter temperatures jeopardize the fruit yield of trees that require a prolonged and sufficiently cold winter to flower. Predicting the exact risk to different crop varieties is the first step in mitigating the harmful effects of climate change. This work focused on olive (Olea europaea) - a traditional crop in the Mediterranean basin whose flowering depends on the sufficiency of cold periods and the lack of warm ones during the preceding winter. Yet, a satisfactory quantitative model forecasting its expected flowering under natural temperature conditions is still lacking. The effect of different temperature regimes on olive flowering level and flowering-gene expression was empirically tested. A modified 'dynamic model' describing the response of a putative flowering factor to the temperature signal was constructed. The crucial component of the model was an unstable intermediate, produced and degraded at temperature-dependent rates. The model accounts for both the number of cold and warm hours but also for their sequence. Empirical flowering and temperature data were applied to fit the model parameters, applying numerical constrained optimization techniques; the model outcomes were successfully validated. The model accurately predicted low-to-moderate flowering under winters with warm periods and properly accounted for the effects of warm periods during winter.

Brazil nut journey under future climate change in Amazon.

Climate change is among the principal threats to global terrestrial biodiversity, especially to megadiverse ecosystems such as the Amazon rainforest. In this study, we investigate how it could affect an iconic forest species-Bertholletia excelsa-(the Brazil nut) which has values in multiple dimensions in an Amazonian context. We used an ensemble from various distribution modeling methods designed for four different climate scenarios from CMIP6 by the end of the century. Then, we simulate how spatial dynamics under climate change, including explicitly dispersal events, can affect the persistence, colonization, and potential extinction of Bertholletia excelsa in the future. Our results show that by the end of the century there would be a generalized loss of suitability on the Amazon biome, regardless of the climate scenario evaluated, which could promote a significant loss (up to 94%) of the area available for the species via extinction. Our results also show that, in the future, the species would colonize higher altitudes in search of favorable conditions for its survival. Finally, we detected that areas that had previously become unsuitable because of climate change would have favorable conditions by the end of the century. Such an outcome could be useful in fostering an active restoration agenda that can mitigate the negative effects of climate change on species in this study.

Low-carbon agricultural technologies improve forage and feed production in the Caatinga biome, Brazil: Characteristics, comparison, effects of climate change, resilience, local development, and food security

Adjustments in Brazilian livestock are necessary to minimize greenhouse gas (GHG) emissions, since the largest source of methane comes from ruminants’ enteric fermentation, and of carbon from deforestation. Low-carbon agriculture technologies (LCAT) contribute to mitigating these emissions and this study evaluates the role of these technologies on ruminant forage production in Caatinga. A Strength, Weakness, Opportunity, and Threats analysis was used to elucidate the main features, followed by an Analytic Hierarchical Process, ranking the LCAT, and a risk analysis. Integrated Crop-Livestock-Forest System (ICLFS) is the most recommended technology, followed by Sustainable Forest Management (SFM) and Recovery of Degraded Areas with Pastures (RDA-P). The results can aid in the choice of the LCAT to be implemented by the smallholder in Caatinga, demonstrating the need to strengthen rural technical assistance, so that there is a real benefit to the producer and the environment.