Seasonal Rainfall Research Articles

Climatic Variations and Challenges to Socio-economic Development amongst Mbororo Communities in Mbum Plateau, North West Region of Cameroon

This study sets out to investigate the challenges hindering Mbororo sources of livelihood in Mbum Plateau, North West Region of Cameroon. Explanatory research was used where it specify the nature and direction of the relationships between the studied variables. The study used mixed methods of qualitative and quantitative approaches. The study employed the primary and secondary data sources to bring out realistic results. Rainfall Seasonality Index (SI) and Standardized Precipitation Index (SPI) were employed to assess the vulnerability of the agro-hydrological system to climate variation. The major primary data sources used were field survey, interviews and questionnaires. A total of 200 questionnaires were distributed using stratified random and snow ball sampling techniques. The data obtained was complemented by secondary sources from published and unpublished materials. Data collected during the field survey were analyzed through two statistical techniques. The qualitative data obtained was analyzed through the content analysis whereas themes and codes were given to the different opinions and perceptions of the informants and their frequencies and percentages were being determined from there. Data were presented in tables, charts, maps, and graphs with some attempted interpretations. Data were analyzed using the chi-square and multiple regression models. The findings revealed that climate variability, dwindling pasture and low streams discharge are having negative effects on Mbororo communities. It was observed from satellite images that, land use over the years has been changing with reducing aerial extent and quality of pasture, reducing water points in Mbum Plateau. In order to adapt the decreasing cattle numbers on the side of the Mborroro, they have taken farming, diving, hawking arm rubbery, and schooling as new livelihoods sustenance. The study recommends a sustainable pastoral activity by encouraging the introduction of drought resistant cattle species, Bracharia and Guatemala grass to supplement the natural pasture. MINEPAI should regularly control herd size so as to ensure ecosystem balance and avoid overgrazing. Transhumance tracts and areas should be well demarcated to avoid frequent farmer-grazers’ conflicts and frequent cattle theft observed in the region.

Growth periodicity in semi-deciduous tropical tree species from the Congo Basin.

In the tropics, more precisely in equatorial dense rainforest, xylogenesis is driven by a little distinct climatological seasonality, and many tropical trees do not show clear growth rings. This makes retrospective analyses and modeling of future tree performance difficult. This research investigates the presence, the distinctness, and the periodicity of growth ring for dominant tree species in two semi-deciduous rainforests, which contrast in terms of precipitation dynamics. Eighteen tree species common to both forests were investigated. We used the cambial marking technique and then verified the presence and periodicity of growth-ring boundaries in the wood produced between pinning and collection by microscopic and macroscopic observation. The study showed that all eighteen species can form visible growth rings in both sites. However, the periodicity of ring formation varied significantly within and between species, and within sites. Trees from the site with clearly defined dry season had a higher likelihood to form periodical growth rings compared to those from the site where rainfall seasonality is less pronounced. The distinctness of the formed rings however did not show a site dependency. Periodical growth-ring formation was more likely in fast-growing trees. Furthermore, improvements can be made by a detailed study of the cambial activity through microcores taken at high temporal resolution, to get insight on the phenology of the lateral meristem.

The trends and spatiotemporal variability of temperature and rainfall in Hulbarag district, Silte Zone, Ethiopia

Ethiopia gets its agricultural water primarily from rainfall. This study was intended to investigate current climate variability and trends across space and time. Daily gridded temperature and rainfall data from 1993 to 2022 in the Hulbarag district, Silte Zone of Ethiopia was obtained from the Ethiopian National Metrological Institute and the Climate Hazard Group Infrared Precipitation with Station. The trends and variability of temperature and rainfall were analyzed using the Mann-Kendall trend test, Sen's slope, coefficient of variation, precipitation concentration index, and rainfall anomaly index. The results indicated that annual, spring, and summer rainfall revealed statistically significant decreasing trends at Hulbarag and Sankura stations, with the magnitude of −13.4, −11.6, and −10.6 mm per year and −6.8, −3.6 and −10.9 mm per year respectively. Conversely, autumn and winter season rainfall showed statistically significant increasing trends at Hulbarag and Sankura stations, with the magnitude of 5.1 and 5.5mm per year and 3.4 and 1.84mm per year consecutively. Between 43 % and 47 % of the observation periods had negative anomalies. The average yearly temperature, average yearly minimum temperature, and average yearly maximum temperatures at Sankura and Fonko stations all displayed statistically significant increasing trends, with a magnitude of 0.091 °C, 0.009 °C and 0.051 °C per year and 0.03 °C,0.01 °C and 0.0022 °C per year successively. It is advisable to develop a farming system that is climate-resilient by improving the adaptive capacity of wheat and maize-growing farmers by expanding the availability of early maturing seeds, changing crop calendars, and enhancing proactive and credible climate information services.

Spatiotemporal climate variability and extremes in Middle Awash Afar region Ethiopia: implications to pastoralists and agro-pastoralists food security

PurposeThis study aims to examine the phenomenon of climate variability and its implications for pastoralists and agro-pastoralists food security in Amibara and Awash Fentale districts of the Afar region, Ethiopia.Design/methodology/approachThe study relied on meteorological records of temperature and rainfall in the study area between 1988 and 2018. Besides, literature on the topic was reviewed to make caveats on the literal picture that comes from quantitative data, and that is the contribution of this study to the existing debate on climate change and variability. The spatiotemporal trend was determined using the Mann–Kendall test and Sen’s slope estimator, while variability was analyzed using the coefficient of variation and standardized anomaly index, and standardized precipitation index/standardized precipitation evapotranspiration index were applied to determine the drought frequency and severity.FindingsThe result reveals that the mean seasonal rainfall varies from 111.34 mm to 518.74 mm. Although the maximum and minimum rainfall occurred in the summer and winter seasons, respectively, there has been a decrease in seasonal and annual at the rate of 2.51 mm per season and 4.12 mm per year, respectively. The study sites have been experiencing highly seasonal rainfall variability. The drought analysis result confirms that a total of nine agricultural droughts ranging from moderate to extreme years were observed. Overall, the seasonal and annual rainfall of the Amibara and Awash Fentale districts showed a decreasing trend with highly temporal variations of rainfall and ever-rising temperatures, and frequent drought events means the climate situation of the area could adversely affect pastoral and agro-pastoral households’ food security. However, analysis of data from secondary sources reveals that analyzing precipitation just based on the meteorological records of the study area would be misleading. That explains why flooding, rather than drought, is becoming the main source of catastrophe to pastoral and agro-pastoral livelihoods.Practical implicationsThe analysis of temperature and rainfall dynamics in the Afar region, hence the inception of all development interventions, must take the hydrological impact of the neighboring regions which appears to be useful direction to future researchers.Originality/valueThe research is originally conducted using meteorological and existing literature, and hence, it is original. In this research, we utilized a standardized and appropriate methodology, resulting in insights that augment the existing body of knowledge within the field. These insights serve to advance scholarly discourse on the subject matter.

Sensitivity of root production to long‐term aridity under environmental perturbations in Chihuahuan Desert ecosystems

Abstract Root production influences carbon and nutrient cycles and subsidizes soil biodiversity. However, the long‐term dynamics and drivers of belowground production are poorly understood for most ecosystems. In drylands, fire, eutrophication, and precipitation regimes could affect not only root production but also how roots track interannual variability in climate. We manipulated the intra‐annual precipitation regime, soil nitrogen, and fire in four common Chihuahuan Desert ecosystem types (three grasslands and one shrubland) in New Mexico, USA, where the 100‐year record indicates both long‐term drying and increasing interannual variability in aridity. First, we evaluated how root production tracked aridity over 10–17 years using climate sensitivity functions, which quantify long‐term, nonlinear relationships between biological processes and climate. Next, we determined the degree to which perturbations by fire, nitrogen addition or intra‐annual rainfall altered the sensitivity of root production to both mean and interannual variability in aridity. All ecosystems had nonlinear climate sensitivities that predicted declines in production with increases in the interannual variance of aridity. However, root production was the most sensitive to aridity in Chihuahuan Desert shrubland, with reduced production under drier and more variable aridity. Among the perturbations, only fire altered the sensitivity of root production to aridity. Root production was more than twice as sensitive to declines with aridity following prescribed fire than in unburned conditions. Neither the intra‐annual seasonal rainfall regime nor chronic nitrogen fertilization altered the sensitivity of roots to aridity. Synthesis. Our results yield new insight into how dryland plant roots respond to climate change. Our comparison of dryland ecosystems of the northern Chihuahuan Desert predicted that root production in shrublands would be more sensitive to future climates that are drier and more variable than root production in dry grasslands. Field manipulations revealed that fire could amplify the climate sensitivity of dry grassland root production, but in contrast, the climate sensitivity of root production was largely resistant to changes in the seasonal rainfall regime or increased soil fertilization.

Investigation of the Historical Trends and Variability of Rainfall Patterns during the March–May Season in Rwanda

This study explores the spatiotemporal variability and determinants of rainfall patterns during the March to May (MAM) season in Rwanda, incorporating an analysis of teleconnections with oceanic–atmospheric indices over the period 1983–2021. Utilizing the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset, the study employs a set of statistical tools including standardized anomalies, empirical orthogonal functions (EOF), Pearson correlation, the Mann–Kendall (MK) trend test, and Sen’s slope estimator to dissect the intricacies of rainfall variability, trends, and their association with large-scale climatic drivers. The findings reveal a distinct southwest to northwest rainfall gradient across Rwanda, with the MK test signaling a decline in annual precipitation, particularly in the southwest. The analysis for the MAM season reveals a general downtrend in rainfall, attributed in part to teleconnections with the Indian Ocean Sea surface temperatures (SSTs). Notably, the leading EOF mode for MAM rainfall demonstrates a unimodal pattern, explaining a significant 51.19% of total variance, and underscoring the pivotal role of atmospheric dynamics and moisture conveyance in shaping seasonal rainfall. The spatial correlation analysis suggests a modest linkage between MAM rainfall and the Indian Ocean Dipole, indicating that negative (positive) phases are likely to result in anomalously wet (dry) conditions in Rwanda. This comprehensive assessment highlights the intricate interplay between local rainfall patterns and global climatic phenomena, offering valuable insights into the meteorological underpinnings of rainfall variability during Rwanda’s critical MAM season.

A Study of Precipitation Forecasting for the Pre-Summer Rainy Season in South China Based on a Back-Propagation Neural Network

In South China, the large quantity of rainfall in the pre-summer rainy season can easily lead to natural disasters, which emphasizes the importance of improving the accuracy of precipitation forecasting during this period for the social and economic development of the region. In this paper, the back-propagation neural network (BPNN) is used to establish the model for precipitation forecasting. Three schemes are applied to improve the model performance: (1) predictors are selected based on individual meteorological stations within the region rather than the region as a whole; (2) the triangular irregular network (TIN) is proposed to preprocess the observed precipitation data for input of the BPNN model, while simulated/forecast precipitation is the expected output; and (3) a genetic algorithm is used for the hyperparameter optimization of the BPNN. The first scheme reduces the mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the simulation by roughly 5% and more than 15 mm; the second reduces the MAPE and RMSE by more than 15% and 15 mm, respectively, while the third improves the simulation inapparently. Obviously, the second scheme raises the upper limit of the model simulation capability greatly by preprocessing the precipitation data. During the training and validation periods, the MAPE of the improved model can be controlled at approximately 35%. For precipitation hindcasting in the test period, the anomaly rate is less than 50% in only one season, and the highest is 64.5%. According to the anomaly correlation coefficient and Ps score of the hindcast precipitation, the improved model performance is slightly better than the FGOALS-f2 model. Although global climate change makes the predictors more variable, the trend of simulation is almost identical to that of the observed values over the whole period, suggesting that the model is able to capture the general characteristics of climate change.

Evaluation of Satellite-Based Rainfall Estimates against Rain Gauge Observations across Agro-Climatic Zones of Nigeria, West Africa

Satellite rainfall estimates (SREs) play a crucial role in weather monitoring, forecasting and modeling, particularly in regions where ground-based observations may be limited. This study presents a comprehensive evaluation of three commonly used SREs—African Rainfall Climatology version 2 (ARC2), Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) and Tropical Application of Meteorology using SATellite data and ground-based observation (TAMSAT)— with respect to their performance in detecting rainfall patterns in Nigeria at daily scales from 2002 to 2022. Observed data obtained from the Nigeria Meteorological Agency (NiMet) are used as reference data. Evaluation metrics such as correlation coefficient, root mean square error, mean error, bias, probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) are employed to assess the performance of the SREs. The results show that all the SREs exhibit low bias during the major rainfall season from May to October, and the products significantly overestimate observed rainfall during the dry period from November to March in the Sahel and Savannah Zones. Similarly, over the Guinea Zone, all the products indicate overestimation in the dry season. The underperformance of SREs in dry seasons could be attributed to the rainfall retrieval algorithms, intensity of rainfall occurrence and spatial-temporal resolution. These factors could potentially lead to the accuracy of the rainfall retrieval being reduced due to intense stratiform clouds. However, all the SREs indicated better detection capabilities and less false alarms during the wet season than in dry periods. CHIRPS and TAMSAT exhibited high POD and CSI values with the least FAR across agro-climatic zones during dry periods. Generally, CHIRPS turned out to be the best SRE and, as such, would provide a useful dataset for research and operational use in Nigeria.

Assessing landslide damming susceptibility in Central Asia

Abstract. Central Asia regions are characterized by active tectonics, high mountain chains with extreme topography with glaciers, and strong seasonal rainfall events. These key predisposing factors make large landslides a serious natural threat in the area, causing several casualties every year. The mountain crests are divided by wide lenticular or narrow, linear intermountain tectonic depressions, which are incised by many of the most important Central Asia rivers and are also subject to major seasonal river flood hazard. This multi-hazard combination is a source of potential damming scenarios, which can bring cascading effects with devastating consequences for the surrounding settlements and population. Different hazards can only be managed with a multi-hazard approach coherent within the different countries, as suggested by the requirements of the Sendai Framework for Disaster Risk Reduction. This work was carried out within the framework of the Strengthening Financial Resilience and Accelerating Risk Reduction in Central Asia (SFRARR) project as part of a multi-hazard approach with the aim of providing a damming susceptibility analysis at a regional scale for Central Asia. To achieve this, a semi-automated GIS-based mapping method, centered on a bivariate correlation of morphometric parameters defined by a morphological index, originally designed to assess the damming susceptibility at basin/regional scale, was modified to be adopted nationwide and applied to spatially assess the obstruction of the river network in Central Asia for mapped and newly formed landslides. The proposed methodology represents an improvement to the previously designed methodology, requiring a smaller amount of data, bringing new preliminary information on damming hazard management and risk reduction, and identifying the most critical area within the Central Asia regions.

Water use and yield response of rainfed safflower (Carthamus tinctorius L.) in Vertisols with varying soil depths

AbstractSafflower (Carthamus tinctorius L.) is an edible oilseed crop mainly cultivated in marginal lands. This study evaluates safflower crop water requirements to understand its feasibility to cultivate under rainfed ecosystem through a field experiment undertaken at the International Crops Research Institute for the Semiarid Tropics research farm, India. Eight improved and stress‐tolerant safflower cultivars (five spiny and three non‐spiny) were evaluated in Vertisols at three soil depths, that is, shallow: <0.60 m, medium: 0.60–1.20 m, and deep:1.20–1.80 m, over 3 years (2009–2012). Wet, normal, and deficit rainfall years were experienced during 2009/2010, 2010/2011, and 2011/2012, respectively. Soil moisture, crop yield, and growth parameters were measured, and field‐scale hydrology was captured through a calibrated one‐dimensional water balance model. Safflower responded to available residual soil moisture which varied with soil depth and rainfall received in different years. Total crop water use was 300–320 mm during the postrainy season, of which about 70% was extracted in deep Vertisols and 55% in medium Vertisols through residual soil moisture. In addition, 30% of water requirement was met through postrainy season rainfall. Safflower grown in shallow Vertisols could only meet 40% of crop water requirement. Spiny cultivar NARI‐H‐15 grown in deep soil recorded a maximum yield of 1890 kg ha−1 in the wet year. Seed yield from spiny cultivars grown in deep and medium soils was nearly similar (1500–1600 kg ha−1) during wet and normal years; a significant reduction in yield (>50%) occurred in shallow soils and also during a rainfall deficit year. Spiny cultivars produced 10%–50% higher seed yield compared to non‐spiny cultivars. Growing safflower in medium and deep Vertisols provides opportunities for crop intensification.

Investigating the Morphometry and Hydrometeorological Variability of a Fragile Tropical Karstic Lake of the Yucatán Peninsula: Bacalar Lagoon

Comprehensive morphometric and hydrometeorological studies on Bacalar Lagoon, Mexico’s largest tropical karstic lake and a significant aquatic system of the Yucatán Peninsula, are lacking. This study provides a detailed analysis of its bathymetry, morphometry, and hydrometeorological characteristics. The lake’s main basin stretches more than 52.7 km in length, with widths varying from 0.18 km to 2.28 km. It has a volume of 554.4 million cubic meters, with an average depth of 8.85 m, reaching depths of up to 26 m in the north and featuring sub-lacustrine dolines in the south, with depths of 38 m, 48.5 m, and 63.6 m. The study reveals seasonal variations in surface water temperature, closely linked to air temperature (r = 0.89), and immediate responses of water levels to hydrometeorological events. Water level fluctuations also exhibit seasonal patterns that are correlated with regional aquifer conditions, with a lag of 2 months after seasonal rainfall. Interannual variability in rainfall and water levels was observed. From 2010 to 2012, rainfall consistently remained below its mean climatic value, due to a prolonged La Niña event, while the exceptionally wet conditions in 2020 were also associated with La Niña. Extreme and anomalous hydrometeorological events, such as those following tropical storm Cristobal in 2020, revealed the fragility of Bacalar Lagoon, causing a notable transformation in lake color and transparency, shifting it from its typical oligotrophic state to eutrophic conditions that lasted longer than a year. These color changes raise questions about the factors impacting ecological health in tropical karstic regions. Additional factors affecting water quality in the BL in 2020, such as deforestation, coastline changes, and urban growth, warrant further investigation. Our study can serve as a starting landmark.

Climate change adaptation strategies among smallholder farmers in Senegal’s semi-arid zone: role of socio-economic factors and institutional supports

In dryland agricultural systems, developing appropriate climate-smart technology (CST) options is important to adapt agriculture to climate change and transition toward sustainability, as well as increasing productivity and incomes. This study examines the impact of socio-economic and institutional support on community responses to climate change and the impact of changes in three selected regions of Senegal (Meouane, Thiel, and Daga Birame), which fall within different rainfall gradients. It captures community perceptions of climate change, compares them to long-term meteorological data, and identifies site-specific response strategies. Communities are randomly selected from a list of communities within the target sites. We used a two-stage stratified sampling method to select sample households. First, purposive sampling was conducted to select at least six (6) villages as a cluster within each rainfall gradient. Likewise, the selection of households in each cluster was based on the main value chains of crops grown in the study area, namely groundnut, millet, black pea, and livestock. A total of 145 households participated in this study. Data from surveys conducted during the 2022 post-harvest season were analyzed using descriptive statistics and logit models. The analysis found that smallholders have a comprehensive understanding of climate indicators, including annual rainfall, shortened crop seasons, and rising temperatures, compared to historical data trends. Additionally, the results highlight how farmers view the negative impacts of seasonal rainfall deficiencies (72%), delayed start of the growing season (88%), frequent dry spells (68%), and longer dry spells (76%), which ultimately lead to decreased grain and fodder yields. The logit model also highlights the importance of socio-economic and institutional factors such as access to credit, extension services, agricultural experience, frequency of interaction with extension workers, and access to government subsidies. These factors play a crucial role in farmers’ decision to adopt CST. Given the specificity of community contexts, these insights have important implications for guiding policymakers and making it easier to reduce climate risk among smallholder farmers.

Spatio-Temporal Trend Analysis of Annual and Seasonal Rainfall in Ho Chi Minh City

Spatio-temporal variations and trends in climatic variables play an essential role in the adaptation and mitigation of climate change policy. This study analyzed spatial and temporal variability of annual and seasonal rainfall in Ho Chi Minh City based on non-parametric statistical trend tests and spatial interpolation techniques. In particular, Sen’s Slope Estimator and Inverse Distance Weighting (IDW) methods were applied to construct the spatial distribution of annual and seasonal rainfall over the city. The outcomes show that annual and seasonal rainfall experienced significant increasing trends. Generally, these findings draw out an overall picture of rainfall variability in terms of space and time, which makes it possible for local decision-makers to promote more promising action plans in order to respond to natural disasters in the context of climate change.

The Role of Atmospheric Stabilities and Moisture Convergence in the Enhanced Dry Season Precipitation over Land from 1979 to 2021

Abstract Between 1979 and 2021, global ocean regions experienced a decrease in dry season precipitation, while the trend over land areas varied considerably. Some regions, such as southeastern China, the Maritime Continent, eastern Europe, and eastern North America, showed a slight increasing trend in dry season precipitation. This study analyzes the potential mechanisms behind this trend by using the fifth major global reanalysis produced by ECMWF (ERA5) data. The analysis shows that the weakening of downward atmospheric motions played a critical role in enhancing dry season precipitation over land. An atmospheric moisture budget analysis revealed that larger convergent moisture fluxes lead to an increase in water vapor content below 400 hPa. This, in turn, induced an unstable tendency in the moist static energy profile, leading to a more unstable atmosphere and weakening downward motions, which drove the trend toward increasing dry season precipitation over land. More water vapor in the low troposphere is because of higher moisture convergence and moisture transport from ocean to land regions. In summary, this study demonstrates the intricate elements involved in altering dry season rainfall trends over land, which also emphasizes the importance of comprehending the spatial distribution of the wet-get-wetter and dry-get-drier paradigm. Significance Statement This study found that global land precipitation during the dry season slightly increased from 1979 to 2021, while precipitation over oceans declined. Moist static energy analysis showed a trend toward less stability in areas with increased dry season precipitation and the opposite trend in regions with declining precipitation. Water vapor content trends and dynamic components were the primary controlling mechanism for precipitation trends. Furthermore, the hotspots with pronounced increases or decreases in dry season precipitation reflect local circulation changes influenced by anthropogenic or natural factors.

Paediatric Neurosurgical emergency operations:Clinical spectrum, Presentation-Intervention Interval and Early operative outcome in Regional Neurosurgical center, Nigeria

BACKGROUND: Pediatric neurosurgical emergencies are prevalent worldwide, often triggered by acute, life-threatening conditions that necessitate immediate surgery to prevent disability and death. Managing these conditions perioperatively poses significant challenges for neurosurgeons and anesthetists due to potential complications like anemia, seizures, electrolyte imbalances, intracranial hypertension, and vision threats, alongside the primary neurosurgical issues. Proper correction and optimization of these physiological derangements before surgery are crucial for favorable postoperative outcomes. PATIENTS AND METHODS: This retrospective study analyzes emergency neurosurgical operations performed on children aged sixteen and under at a neurosurgical center in Sokoto, Nigeria, from January 2018 to December 2021. The center caters to a population of approximately twenty million people from three north-western and one north-central Nigerian states, as well as neighboring Niger and Benin republics. The area features a mostly arid climate with limited seasonal rainfall and experiences the Sahara’s harmattan winds. RESULTS A total of 131 children underwent emergency neurosurgical procedures during the study period. The majority were males (71%), with an average age of 5.6 years. Hydrocephalus was the most frequent emergency condition, leading to 44.3% of surgeries, primarily through ventriculoperitoneal shunt procedures, which accounted for 42.7% of interventions. Anemia was the most common comorbid condition. The mean time from presentation to intervention was 10 days. Postoperatively, 17.9% of patients suffered from surgical site infections, yet 67.9% had favorable outcomes with a mortality rate of 7.1%. CONCLUSION: This study underscores the importance of timely surgical interventions and highlights the predominance of ventriculoperitoneal shunts in treating pediatric hydrocephalus in the region, with generally positive outcomes despite delays

Reorganization of bird communities along a rainforest elevation gradient during a strong El Niño event in Papua New Guinea.

The El Niño 2015 event, most extreme since 1997, led to severe droughts in tropical wet Papua New Guinea (PNG), reducing May to October dry season rainfall by 75% in the lowlands and 25% in the highlands. Such droughts are likely to have significant effects on terrestrial ecosystems, but they have been poorly explored in Papua New Guinea. Here, we report changes in bird community composition prior to, during, and after the 2015 El Niño event along the elevational gradient ranging from 200 m to 2700 m a.s.l. at the Mt. Wilhelm rainforest in PNG. The abundance of birds in the lowlands dropped by 60% but increased by 40% at elevations above 1700 m during El Niño year. In the following year, the individual bird species reached mean population sizes similar to pre-El Niño years but did not fully recover. Species richness roughly followed the pattern of observed abundance and quickly and fully re-established after the event to the pre- El Niño values. Thus, at least some terrestrial birds seem to react quickly to the extreme droughts in lowlands and shift to less affected mountain habitats. We recorded upper elevational range limits to shifts by more than 500 m a.s.l. in 22 bird species (out of 237 recorded in total) during El Niño year, in contrast to their typical ranges. Our study suggests that a strong El Niño event can have strong but reversible effects on bird communities as long as they have an opportunity to move to more favorable sites through undisturbed habitats.

Assessing Change Impacts on Flood and Drought hazard in Thua Thien Hue province using Standardized Precipitation Index (SPI)

The objective of this study is to comprehensively analyze short- and long-term drought and flood occurrences, providing valuable insights into the potential impact of climate change in the future. Our analysis, utilizing the SPI-6 and SPI-12 indices, focuses on historical data spanning from 1979 to 2019, revealing noteworthy patterns. Notable periods of severe drought include September 1982 to August 1983, September 2004 to August 2005, and October 2014 to August 2015. Conversely, instances of elevated humidity and extreme inundation were recorded from October 1980 to August 1981, October 1995 to June 1997, November 1999 to October 2000, November 2007 to October 2008, October 2011 to August 2012, and January 2017 to August 2018. These findings are consistent with historical records of drought and flood events in Thua Thien Hue Province over the past four decades. Incorporating the SPI-6 and SPI-12 indices alongside rainfall forecasts based on updated climate change and sea-level rise scenarios for 2020 in Vietnam, our study extends its projections to the period from 2020 to 2035. These projections indicate a significant departure from typical annual conditions, with both the severity and frequency of drought and flood events expected to increase. Specifically, Thua Thien Hue weather stations estimate a flood frequency of 14% (SPI-12) and 16% (SPI-6), equivalent to approximately one dry month every seven months. High humidity events are projected to occur at an 18% frequency, roughly once every 5-6 months. Analysis of future scenarios under RCP4.5 and RCP8.5 reveals varying levels of risk associated with drought and flood occurrences. Generally, the risk of flooding is slightly lower than that of drought, with only marginal differences observed in scenario RCP8.5. When considering seasonal rainfall patterns—where half of the year experiences a dry season and the other half is rainy—the incidence of drought surpasses that of high humidity in scenario RCP4.5. In contrast, in scenario RCP8.5, the likelihood of flooding outweighs that of drought. It’s noteworthy that historically, mountainous areas within Thua Thien Hue Province have experienced fewer droughts in comparison to coastal regions. Furthermore, the severity of drought and flood events is more pronounced in scenario RCP8.5, particularly concerning flood events. This underscores that despite higher total rainfall in RCP8.5, leading to more severe inundation events, the distribution exhibits unevenness marked by extreme conditions, including more severe drought events.

Long-Term Seasonal Rainfall Forecasting using Regression Analysis and Artificial Neural Network together with Larg-Scale Circulation Indices

Long-Term Seasonal Rainfall Forecasting using Regression Analysis and Artificial Neural Network together with Larg-Scale Circulation Indices

Characterization of annual and seasonal rainfall trend using innovative trend analysis (ITA) and classical methods: the case of Wadi Sebou basin (WSB) Morocco

Characterization of annual and seasonal rainfall trend using innovative trend analysis (ITA) and classical methods: the case of Wadi Sebou basin (WSB) Morocco

Palms of the past: can morphometric phytolith analysis inform deep time evolution and palaeoecology of Arecaceae?

Palm fossils are often used as evidence for warm and wet palaeoenvironments, reflecting the affinities of most modern palms. However, several extant palm lineages tolerate cool and/or arid climates, making a clear understanding of the taxonomic composition of ancient palm communities important for reliable palaeoenvironmental inference. However, taxonomically identifiable palm fossils are rare and often confined to specific facies. Although the resolution of taxonomic information they provide remains unclear, phytoliths (microscopic silica bodies) provide a possible solution because of their high preservation potential under conditions where other plant fossils are scarce. We thus evaluate the taxonomic and palaeoenvironmental utility of palm phytoliths. We quantified phytolith morphology of 97 modern palm and other monocot species. Using this dataset, we tested the ability of five common discriminant methods to identify nine major palm clades. We then compiled a dataset of species' climate preferences and tested if they were correlated with phytolith morphology using a phylogenetic comparative approach. Finally, we reconstructed palm communities and palaeoenvironmental conditions at six fossil sites. Best-performing models correctly identified phytoliths to their clade of origin only 59 % of the time. Although palms were generally distinguished from non-palms, few palm clades were highly distinct, and phytolith morphology was weakly correlated with species' environmental preferences. Reconstructions at all fossil sites suggested that palm communities were dominated by Trachycarpeae and Areceae, with warm, equable climates and high, potentially seasonal rainfall. However, fossil site reconstructions had high uncertainty and often conflicted with other climate proxies. While phytolith morphology provides some distinction among palm clades, caution is warranted. Unlike prior spatially restricted studies, our geographically and phylogenetically broad study indicates phytolith morphology may not reliably differentiate most palm taxa in deep time. Nevertheless, it reveals distinct clades, including some likely to be palaeoenvironmentally informative.