Influence Of Climate Variability Research Articles

Diversity and seasonality of horse flies (Diptera: Tabanidae) in Amazon Forest fragments of Monte Negro, Rondônia, Western Amazon.

Tabanidae are considered a nuisance to humans, wild animals, and livestock due to their painful, annoying, and insistent biting. Tabanids transmit some pathogens and parasites biologically and mechanically. In humans, there are relatively few pathogens transmitted regularly. Still, tabanids serve as vectors of a number of disease agents of animals, including viruses, bacteria, protozoans, and nematodes. They are more abundant in tropical and humid regions, and their seasonal patterns are affected by habitat changes such as deforestation and fragmentation. Here, we analyze the tabanid fauna in Monte Negro, a central municipality of Rondônia, Brazil, comparing abundance, richness, and diversity in forest and pasture habitats. Traps were set for 5days a month for 12 consecutive months. We also examined how abiotic factors (humidity, temperature, and rainfall) affected the abundance, diversity, and richness and the effectiveness of Malaise and Nzi traps as sample methods. The influence of climatic variables on the richness and abundance of the species was tested using generalized linear models, and we used non-parametric dimensional scaling (nMDS) for analysis of species composition and diversity in different traps and environments. We collect 1032 specimens of 25 species. The most abundant species were Tabanus antarcticus, Dichelacera tetradelta, Tabanus mucronatus, and Leucotabanus albovarius. Forest habitats had the highest number of tabanids, followed by pasture and the anthropized area, and there was no significant difference regarding the effectiveness of the Malaise and Nzi traps. The study provides new information on the distribution and ecology of tabanids in Brazil.

Does Climate Variability Influence Internal Migration Flows in Senegal? An Empirical Analysis

This paper aims to estimate the total effect of climate variability on interregional migration flows in Senegal. We match regional climate data at origin, represented by normalised rainfall and normalised temperatures (maximum and minimum), with regional migration flow data from Senegal’s Agence Nationale de la Statistique et de la Démographie (ANSD) censuses to construct a panel database covering the five-yearly internal migration waves of 1976, 1988, 2001 and 2013. Using a gravity equation model where migration flows are explained by measures of climatic variability at origin, controlled for geographical, socioeconomic and demographic factors traditionally identified in the literature. Our results show that only negative precipitation anomalies at the origin area act as a push factor and accelerate emigration. In the predominantly agricultural regions, rainfall deficits appear, alongside traditional socioeconomic variables, as an additional significant factor shaping mobility across the country.

Estimating Chemical Concentrations of Dust PM2.5 in Iraq: A Climatic Perspective Using Polynomial Model and Remote Sensing Technology

Air pollution and climate change are interrelated issues, with air pollution levels in Iraq currently exceeding World Health Organization standards. This study aimed to evaluate air quality in Iraq by utilizing climatic data, such as temperature, humidity, and gaseous pollutants for assessing the health effects based on processed and estimated data. The research was conducted between August and November 2020, using remotely sensed images and geographical information techniques. Two methods; Geographic Information Systems GIS-based multiple regression and a polynomial model, were employed to estimate PM2.5 levels in the study area. The results showed a significant influence of climatic variables on air pollution in Iraq, with varying effects on PM2.5 estimation. The health impact ranged from good to unhealthy, with most provinces experiencing poor air quality. Southern parts of Iraq exhibited PM2.5 levels surpassing the healthy threshold. The predictive linear and polynomial model's accuracy was assessed through regression, yielding high correlation coefficients (R2 ) of 0.89, 0.95, 0.98, and 0.96 for August to November, respectively. While model validation accuracy ranged between 85–94 %. The study emphasizes the vital role of climate data in understanding the dispersion of air pollutants and their significant impacts on the environment. Addressing air pollution and climate change, as per the SGS-13 "Climate Action", are interconnected and require comprehensive strategies for mitigation.

Estimating Chemical Concentrations of Dust PM2.5 in Iraq: A Climatic Perspective Using Polynomial Model and Remote Sensing Technology

Air pollution and climate change are interrelated issues, with air pollution levels in Iraq currently exceeding World Health Organization standards. This study aimed to evaluate air quality in Iraq by utilizing climatic data, such as temperature, humidity, and gaseous pollutants for assessing the health effects based on processed and estimated data. The research was conducted between August and November 2020, using remotely sensed images and geographical information techniques. Two methods; Geographic Information Systems GIS-based multiple regression and a polynomial model, were employed to estimate PM2.5 levels in the study area. The results showed a significant influence of climatic variables on air pollution in Iraq, with varying effects on PM2.5 estimation. The health impact ranged from good to unhealthy, with most provinces experiencing poor air quality. Southern parts of Iraq exhibited PM2.5 levels surpassing the healthy threshold. The predictive linear and polynomial model's accuracy was assessed through regression, yielding high correlation coefficients (R2 ) of 0.89, 0.95, 0.98, and 0.96 for August to November, respectively. While model validation accuracy ranged between 85–94 %. The study emphasizes the vital role of climate data in understanding the dispersion of air pollutants and their significant impacts on the environment. Addressing air pollution and climate change, as per the SGS-13 "Climate Action", are interconnected and require comprehensive strategies for mitigation.

Influence of climatic variability on rainfall of western region of Haryana

Influence of climatic variability on rainfall of western region of Haryana

Disentangling influences of climate variability and lake-system evolution on climate proxies derived from isoprenoid and branched glycerol dialkyl glycerol tetraethers (GDGTs): the 250 kyr Lake Chala record

Abstract. High-resolution paleoclimate records from tropical continental settings are greatly needed to advance understanding of global climate dynamics. The International Continental Scientific Drilling Program (ICDP) project DeepCHALLA recovered a 214.8 m long sediment sequence from Lake Chala, a deep and permanently stratified (meromictic) crater lake in eastern equatorial Africa, covering the past ca. 250 000 years (250 kyr) of continuous lacustrine deposition since the earliest phase of lake-basin development. Lipid biomarker analyses on the sediments of Lake Chala can provide quantitative records of past variation in temperature and moisture balance from this poorly documented region. However, the degree to which climate proxies derived from aquatically produced biomarkers are affected by aspects of lake developmental history is rarely considered, even though it may critically influence their ability to consistently register a particular climate variable through time. Modern-system studies of Lake Chala revealed crucial information about the mechanisms underpinning relationships between proxies based on isoprenoid (iso-) and branched (br-) glycerol dialkyl glycerol tetraethers (GDGTs) and the targeted climate variables, but the persistence of these relationships in the past remains unclear. Here we assess the reliability of long-term climate signals registered in the sediments of Lake Chala by comparing downcore variations in GDGT distributions with major phases in lake-system evolution as reflected by independent proxies of lake depth, mixing regime and nutrient dynamics: seismic reflection data, lithology and fossil diatom assemblages. Together, these records suggest that during early lake history (before ca. 180–200 ka) the distinct mixing-related depth zones with which specific GDGT producers are associated in the modern-day lake were not yet formed, likely due to more open lake hydrology and absence of chemical water-column stratification. Consequently absolute GDGT concentrations dating to this period are relatively low, proxies sensitive to water-column stratification (e.g., branched versus isoprenoid tetraether (BIT) index) display highly irregular temporal variability, and correlations between proxies are dissimilar to expectations based on modern-system understanding. A sequence of lake-system changes between ca. 180–200 and ca. 80 ka first established and then strengthened the chemical density gradient, promoting meromictic conditions despite the overall decrease in lake depth due to the basin gradually being filled up with sediments. From ca. 180 ka onward some GDGTs and derived proxies (e.g., crenarchaeol concentration, BIT index and IR6Me) display strong ∼ 23 kyr periodicity, likely reflecting the predominantly precession-driven insolation forcing of Quaternary climate variability in low-latitude regions. Our results suggest that GDGT-based temperature and moisture-balance proxies in Lake Chala sediments reflect the climate history of eastern equatorial Africa from at least ca. 160 ka onwards, i.e., covering the complete last glacial–interglacial cycle and the penultimate glacial maximum. This work confirms the potential of lacustrine GDGTs for elucidating the climate history of tropical regions at Quaternary timescales, provided they are applied to suitably high-quality sediment archives. Additionally, their interpretation should incorporate a broader understanding of the extent to which lake-system evolution limits the extrapolation back in time of proxy-climate relationships established in the modern system.

Comparative analysis of mycorrhizal communities associated with Struthiopteris spicant (L.) Weiss across Europe and North America.

Ferns constitute the second largest group of vascular plants. Previous studies have shown that the diversity and composition of fern communities are influenced by resource availability and water stress, among other factors. However, little is known about the influence of these environmental factors on their biotic interactions, especially regarding the relationship between mycorrhizal fungi and ferns. The present study compares the mycorrhizal communities associated with 36 populations of Struthiopteris spicant L. Weiss across Europe and North America. This species exhibits a great tolerance to variations in light, nutrient, and pH conditions, and it can survive with and without mycorrhizae. With the aim of determining which environmental factors impact the composition and abundance of the root-associated fungal communities in this species, we used an ITS-focused metabarcoding approach to identify the mycorrhizal fungi present and analyzed the influence of climatic and edaphic variables at global and regional scales. We encountered striking differences in the relative abundance of arbuscular mycorrhizal fungi (AMF) between S. spicant populations at both spatial levels. We recorded a total of 902 fungal ASVs, but only 2- 4% of the total fungal diversity was observed in each individual, revealing that each fern had a unique fungal community. Light availability and the interactive action of pH and soil nitrogen concentration showed a positive influence on AMF relative abundance, explaining 89% of the variance. However, environmental factors could only explain 4- 8% of the variability in AMF community composition, indicating that it might be determined by stochastic processes. These results support the hypothesis that ferns may be more independent of mycorrhization than other plant groups and interact with fungi in a more opportunistic manner.

Influence of climate variability and land cover dynamics on the spatio-temporal NDVI patterns in western hydrological regions of Bangladesh

Analyzing vegetation greenness considering climate and land cover changes is crucial for Bangladesh given the historically drier North-West and South-West regions of Bangladesh have shown prominent climatic and hydrological variations. Therefore, this study assessed the spatial and temporal variation of NDVI and its relationship with climate and land cover changes from 2000 to 2022 for these regions. In this study, Moran's I and Getis Ord Gi* were employed for spatial autocorrelation and Mann-Kendall, Sen's slope test along with Innovative Trend Analysis were deployed to identify temporal trends of NDVI. RMSE, MAE and R-squared values were assessed between computed and observed PET. Correlation of NDVI with climate variables were assessed through multivariate correlation analysis and correlation mapping. Additionally, Pearson product moment correlation was applied between different types of land cover and NDVI. Spatial autocorrelation outcomes showed that NDVI values have been clustered in distinct hotspots and cold-spots over the years. Temporal trend detection results indicate that NDVI values are rising significantly all over the regions. Multivariate correlation analysis identified no climate variable to be the limiting factor for NDVI changes. Similarly, the precipitation-NDVI correlation map displayed no significant correlation. Nonetheless, temperature-NDVI correlation map illustrated varying degrees of mostly moderate and strong positive correlations with distinct negative correlation results in the Sundarbans of South-West region. Land cover pattern analysis with NDVI showed a positive correlation to forest, cropland and vegetation area increasing and negative correlation to grassland and barren area decreasing. In this regard, Rangpur division exhibited stronger correlations than Rajshahi division in North-West. The findings indicate that NDVI changes in the regions are largely dependent on land cover changes in comparison to climate trends. This can instigate further research in other hydrological regions to explore the natural and man-made factors that can affect the greenery and vegetation density in specific regions.

Influence of global teleconnections on long-term variability in flood seasonality across peninsular India

Climate change and natural climate variability impact not only the frequency and magnitude of floods but also flood seasonality. However, limited to no study has investigated the seasonality in flood occurrence in peninsular Indian rivers. The Central Water Commission opening its long-term records of river stage and discharge gathered from many monitoring stations offers a unique opportunity to analyse flood seasonality. The primary aims of this study are to identify the time of the year when floods are most likely, investigate whether the occurrence of floods has changed over time due to the influence of climate change and natural climate variability, and determine the most significant large-scale and local climate drivers of flood seasonality. Stage and discharge data from 281 gauging stations across ten peninsular river basins are considered to identify the annual maximum gauge level for a gauging point while retaining the corresponding Julian day (also known as the date of occurrence or DO) for further analysis. Several attributes related to circular statistics are calculated from the DO series to find that 68% of the gauging stations experience floods during August, indicating the dominance of the monsoon system on DO. Preliminary analysis confirms that while most stations experience a non-stationarity in the DO series, a few stations exhibit a non-linear trend. Furthermore, our study develops a machine learning model with DO as predictand and 36 local and large-scale predictors to identify the dominant predictors of DO. The predictor importance metric shows that the Pacific Decadal Oscillation (PDO) and the El Niño and Southern Oscillation (ENSO) explain DO variability better than other drivers. Moreover, since ENSO and PDO are teleconnected with the onset of monsoon and annual maximum rainfall (Pradhan et al 2017 Sci. Rep. 7 14229; Choudhury et al 2021a Q. J. R. Meteorol. Soc. 147 3111–23), flood seasonality demonstrates a connection with both PDO and ENSO.

The Role of the Aleutian Low in the Relationship between Spring Pacific Meridional Mode and Following ENSO

Abstract The spring Pacific meridional mode (PMM) is an important precursor of El Niño–Southern Oscillation (ENSO). However, recent studies reported that only about half of the spring PMM events were followed by ENSO events. This study examines the role of internal climate variability in modulating the impact of PMM on ENSO using 100-member ensemble simulations of the Max Planck Institute Earth System Model (MPI-ESM). The relationship between spring PMM and following winter ENSO shows a large spread among the 100 members. The variation of spring Aleutian low (AL) intensity is identified to be an important factor modulating the PMM–ENSO relation. The spring AL affects the PMM–ENSO relationship by modifying PMM-generated low-level zonal wind anomalies over the tropical western Pacific. The strengthening of the spring AL is accompanied by westerly wind anomalies over the midlatitude northwestern Pacific, leading to sea surface temperature (SST) cooling there via an enhancement of upward surface heat flux. This results in increased meridional SST gradient and leads to northerly wind anomalies over the subtropical northwestern Pacific, which turn to surface westerly wind anomalies after reaching the equatorial western Pacific due to the conservation of potential vorticity. Thus, the low-level westerly (easterly) wind anomalies over the tropical western Pacific associated with the positive (negative) spring PMM were strengthened (weakened), which further contributes to an enhanced (a weakened) PMM–ENSO relation. The mechanism for the modulation of the AL on the spring PMM–ENSO relationship is verified by a set of AGCM simulations. This study suggests that the condition of the spring AL should be considered when predicting ENSO on the basis of the PMM. Significance Statement Spring Pacific meridional mode (PMM) is a predictor of ENSO, but not all spring PMM events are accompanied by the occurrence of ENSO events. This study aims to explore the influence of internal climate variability on the relationship between spring PMM and following ENSO. It is revealed that the Aleutian low exerts a crucial modulation on the spring PMM–ENSO relationship. The underlying physical mechanisms for the impact of the Aleutian low on the relationship between spring PMM and ENSO are further examined. The results of this study have important implications for improving the prediction of ENSO.

Mapping sub-surface distribution of soil organic carbon stocks in South Africa's arid and semi-arid landscapes: Implications for land management and climate change mitigation

Soil organic carbon (SOC) stocks are critical for land management strategies and climate change mitigation. However, understanding SOC distribution in South Africa's arid and semi-arid regions remains a challenge due to data limitations, and the complex spatial and sub-surface variability in SOC stocks driven by desertification and land degradation. Thus, to support soil and land-use management practices as well as advance climate change mitigation efforts, there is an urgent need to provide more precise SOC stock estimates within South Africa's arid and semi-arid regions. Hence, this study adopted remote-sensing approaches to determine the spatial sub-surface distribution of SOC stocks and the influence of environmental co-variates at four soil depths (i.e., 0-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm). Using two regression-based algorithms, i.e., Extreme Gradient Boosting (XGBoost) and Random Forest (RF), the study found the former (RMSE values ranging from 7.12 t/ha to 29.55 t/ha) to be a superior predictor of SOC in comparison to the latter (RMSE values ranging from 7.36 t/ha to 31.10 t/ha). Nonetheless, both models achieved satisfactory accuracy (R2 ≥ 0.52) for regional-scale SOC predictions at the studied soil depths. Thereafter, using a variable importance analysis, the study demonstrated the influence of climatic variables like rainfall and temperature on SOC stocks at different depths. Furthermore, the study revealed significant spatial variability in SOC stocks, and an increase in SOC stocks with soil depth. Overall, these findings enhance the understanding of SOC dynamics in South Africa's arid and semi-arid landscapes and emphasizes the importance of considering site specific topo-climatic characteristics for sustainable land management and climate change mitigation. Furthermore, the study offers valuable insights into sub-surface SOC distribution, crucial for informing carbon sequestration strategies, guiding land management practices, and informing environmental policies within arid and semi-arid environments.

Metaanalysis of Public Wastewater Metagenomes: Revealing the Influence of Climatic Variations on the Abundance of the Bacterial Members

As per the present trend, earth may experience severe hike in temperature by 2040. Therefore, global surveillance is required to combat against the upcoming climatic extremities. Emerging and re-emerging infectious diseases are part of the key pressing issues which can affect millions of people worldwide. Wastewater associated metagenomic data representing the wastewater samples collected from sewer networks in Newcastle (United Kingdom); Zimbabwe (Africa) and West Bengal (India), available in public databases were collected. It was observed that of the top 10 abundant genera, the prevalent genera in samples from United Kingdom, Africa, India were Desulfitobacterium, Prevotella, Sulfurospirillum respectively. By comparing all the three samples under study; it was observed that three microbial genera Bacteroides, Dechloromonas and Faecalibacterium were common throughout the samples. Metagenome-wide association studies were conducted to link microbes in the sample to the host disorders. Our study could predict overexpression of several enriched pathways like Vancomycin resistance, Platinum drug resistance across the samples. These findings prove efficacies of the community genomics approach to serve as a public health monitoring tool through detection of spatial variation as well as degree of commonness in wastewater bacterial profiles and also through the prediction of the pathogenic quantum of wastewater systems.

The influence of multidecadal climate variability and abrupt landscape change on terrestrial ecosystem composition and fire regime in the upper Columbia River basin - A high-resolution Holocene perspective

High-resolution paleoclimatic and paleoecologic datasets from a small lake in eastern Washington (USA) help elucidate Holocene environmental dynamics in the interior Pacific Northwest. Round Lake lies near the ecotone between sagebrush steppe and dry pine forest, making it highly sensitive to changes in precipitation-evaporation (P-E) balance. We present isotopic, sedimentological, and paleoecological data from a single sedimentary sequence analyzed at sufficient resolution to detect sub-decadal climatic variability. During the early Holocene (11,000–8500 cal yr BP), when summer insolation was higher than present, Round Lake experienced persistent aridity that led to reduced forest cover and small, probably frequent surface fires. Sub-centennial hydroclimate fluctuations during this period were muted, as indicated by low multi-decadal variability in δ18Ocarbonate records from the region. Oxygen isotopes indicate increased cool-season moisture during the middle Holocene (8500-5300 BP), but stratigraphic evidence suggests intermediate and variable lake levels. The deposition of the Mazama tephra (ca. 7600 cal yr BP) immediately preceded to a protracted expansion of steppe at the expense of forest. Increased hydroclimate variability and fire activity following ash deposition likely restricted conifer taxa even when elevated cool-season moisture would have facilitated their growth. The late Holocene was marked by persistently high lake levels, as indicated by the lithostratigraphic and pollen records. Comparatively large multidecadal variations in precipitation, which peaked during the last millennium, were also prominent features of late-Holocene hydroclimate, and may have been related to the strengthening of the El Niño Southern Oscillation and Pacific Decadal Oscillation. Pinus and Pseudotsuga show a 60–100 year lag in their response to hydroclimatic variations inferred from the oxygen isotope records. These results highlight how millennial-to-decadal scale hydroclimate conditions, along with abrupt landscape change, influence ecology in a water-stressed region of western North America.

Surface water and geomorphological changes of the Blue Nile dynamics associated with the Grand Ethiopian Renaissance Dam (GERD): a multi-temporal analysis

ABSTRACT The Blue Nile River is an indispensable source of livelihood for over 90 million people in Ethiopia, Sudan, and Egypt. Recently, Ethiopia has constructed the Grand Ethiopian Renaissance Dam (GERD), the largest in Africa, which could potentially alter the geomorphology of the river regime, and impact downstream countries. This study offers the first comprehensive analysis of the geomorphological alterations and water surface coverage changes of the Blue Nile River due to the construction and operation of the GERD. For this, we use multi-temporal Landsat 5 and Sentinel-2 satellite imagery spanning the period from 2009 to 2022, supplemented with Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) precipitation products to discern the potential influence of climate variability on the observed changes. The findings are examined using the Before-After-Control-Impact (BACI) model, revealing significant fluctuations in the water surface coverage area across different sections of the river, particularly following the filling stages of the GERD. An analysis at every 10 km is performed to assess the extent of GERD’s influence on the Blue Nile, which indicates no notable alterations in surface area or geomorphology within the first 30 km of downstream river flow. The study also determines that changes from 2011 to 2018 are primarily associated with the upgrade activities of the Roseires Dam, while alterations along the Blue Nile from 2018 to 2019 are linked to climate variability. The observed changes between 2020 and 2022 can largely be attributed to the filling stages of the GERD. Notably, these changes are most pronounced in the water retaining areas upstream of the GERD dam. The results also show that Roseires Dam could play a crucial role as a buffer, mitigating potential impacts imposed by the GERD, and serving as a conduit between the GERD and downstream communities.

Hydrogeological trends in an alluvial valley in the Brazilian semiarid: Impacts of observed climate variables change and exploitation on groundwater availability and salinity

Study regionMimoso Alluvial Valley, Semiarid Brazil. Study focusThis study aims to assess the influence of climate variability and exploitation on groundwater accessibility, quantity and quality, based on a spatiotemporal data analysis from long-term monitoring field campaigns, conducted monthly from 2000 to 2019. This study successfully identified representative stable monitoring points, piezometers and wells, for piezometric and salinity levels employing the technique of relative differences, taking into account aquifer hydraulic properties. Trend analysis was then carried out adopting the Mann-Kendall Method, Sen's Slope test, Pettitt test, and the Seasonal Trend decomposition through the Loess (STL) method. Principal Component Multivariate Analysis (PCA) was also employed to validate long-term analysis of annual groundwater levels, rainfall, evapotranspiration, and pumping rates. New hydrological insights for the regionThe spatial-temporal variability of salinity is closely linked to the salt balance in regions with low hydraulic permeability and groundwater use for irrigation. Groundwater salinity presented a strong link between rainfall and groundwater levels. A temporal rise in evapotranspiration alongside declines in rainfall and groundwater levels was observed, potentially exacerbating groundwater scarcity alongside intensified aquifer exploitation. Furthermore, groundwater salinity presented a decreasing trend for the pumping wells and no trends for piezometers. This could potentially disrupt future irrigation plans and cause long-term water shortages in a region already under severe water scarcity. Hence, groundwater pumping constitutes a positive management alternative for controlling groundwater salinity in the domain.

The Influence of Climate Variability and Future Climate Change on Atlantic Hurricane Season Length

AbstractAtlantic hurricane season length is important for emergency management preparation, motivating the need to understand its variability and change. We investigated the influence of ocean variability on Atlantic hurricane season length in observations and a future climate simulated by the Energy Exascale Earth System Model (E3SM). We found that multiple factors influence hurricane season length, through their influence on season start and end. Warm western subtropical Atlantic sea‐surface temperature anomalies (SSTAs) during boreal spring (before the official hurricane season start) drive early starts to the hurricane season, and vice versa for cool SSTAs. Meanwhile, La Niña in autumn (before the official hurricane season end) drives late ends to the hurricane season, and vice versa for El Niño. E3SM projects a 27‐day increase in future Atlantic hurricane season length given La Niña and warm northern tropical Atlantic SSTAs. This research documents sources of predictability for Atlantic hurricane season length.

Influence of climate, physical and chemical variables on the taxonomic and functional responses of macroinvertebrate communities in tropical island rivers

Influence of climate, physical and chemical variables on the taxonomic and functional responses of macroinvertebrate communities in tropical island rivers

Assessing the impact of climate change on landslide recurrence intervals in Nakhon Si Thammarat Province, Thailand, using CMIP6 climate models

Climate variability and climate change may influence the frequency and recurrence interval of landslides. Precipitation, as a main triggering factor of landslides, may be influenced by climate variability and climate change. Changes in precipitation may directly affect landslide frequency and recurrence intervals. Considering the influence of climate variability and climate change, the partial duration series method and critical rainfall threshold are combined with the simulated precipitation of Phase 6 of the Coupled Model Intercomparison Project (CMIP6) general circulation models (GCMs) to predict changes in future landslide recurrence intervals in Nakhon Si Thammarat Province, Thailand. The analytical results predicted changes in the landslide frequency over the next 20 years (2023 to 2042). SSP1–2.6 and SSP2–4.5 are adopted as future socioeconomic development scenarios. According to the predictions, the results showed that the return period of landslide occurrence in the future will be shorter than the return period of landslide occurrence in the historical period; moreover, the landslide recurrence interval will fluctuate greatly. The Nakhon Si Thammarat DWR meteorological station shows the most fluctuation in landslide recurrence intervals for SSP1–2.6. In addition, the Nakhon Si Thammarat meteorological Station experiences a significant decrease of approximately 35% in landslide recurrence intervals under SSP1–2.6. For SSP2–4.5, the Nakhon Si Thammarat meteorological station shows the most fluctuation in landslide return period. In addition, the Nakhon Si Thammarat meteorological station observed a decline in landslide recurrence intervals, with a reduction of approximately 40%. Hence, the frequency of landslides may increase in the future. A comparison between SSP1–2.6 and SSP2–4.5 revealed that SSP2–4.5 yielded lower landslide return periods.

Influence of Climatic Variables on the Stem Growth Rate in Trees of a Tropical Wet Forest

The growth of tropical wet forests has a significant relationship with the climate; aspects such as temperature and precipitation affect the species; however, few studies have characterized the stem growth rate of tropical tree species. This study’s objective was to characterize the effects of climatic variation on the interannual stem growth rate of eight species in tropical wet forest. Six trees per species were selected (n = 48 trees), and a dendrometer was installed to measure diametric growth bi-monthly between 2015 and 2018 (3 years), complemented with environmental measurements, to determine their growth equations from environmental variables and, finally, to define the relationship between the wood density and the stem growth rate. The results showed an average stem growth from 0.45 to 4.35 mm year−1, and 40 to 70% growth occurred in the months with the highest rainfall. Also, species with higher wood densities were found to have lower stem growth rates. Finally, the analysis of stem growth rate showed a significant relationship in all species between the variables of temperature and precipitation (R2 adj 0.88 to 0.96). Our results suggest that species with greater stem growth rates in wet tropical forests are more susceptible to climate changes, which may affect their dynamics in the face of potential drought scenarios and heat waves associated with climate change.

Influence of anthropogenic effects and climate variability on streamflow in a Brazilian tropical watershed

Influence of anthropogenic effects and climate variability on streamflow in a Brazilian tropical watershed