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South Africa spans the subtropics at the interface between tropical, subtropical, and temperate weather systems, and consequently experiences distinct summer-, winter- and year-round rainfall zones (SRZ, WRZ and YRZ). Spatio-temporal characteristics of the various weather systems are broadly understood, however, the rainfall seasonality classification at the transition between these rainfall zones remains disputed. This surrounds the complexity of rainfall regimes, however, metrics with dissimilar rainfall seasonality definitions have been applied, hindering comparability. To address this dispute, meteorological data spanning 1987–2016 from 46 weather stations is used to assess the utility of a metric posited to quantify rainfall seasonality through a seasonality score derived from a ratio of monthly rainfall: temperature. This score statistically discriminates SRZ, WRZ and YRZ conditions, fulfilling an important requirement for a metric applied to South Africa. Nelspruit (NEL; score = 1.59) represents the strongest SRZ conditions across 30 eastern and central locations with scores > 0.30. Cape Town Wo (CTW; score = − 1.04) represents the strongest WRZ conditions across seven southwestern Cape and west coast locations with scores < − 0.30. Characterising the SRZ-to-WRZ transition region with scores from − 0.30 to 0.30, nine YRZ locations were classified. With the weakest score, Oudtshoorn (OUD; score = − 0.05), within the Cape Fold mountains, most represents YRZ conditions. Applicability across all weather stations, compatibility with known rainfall drivers, and agreement with known spatial rainfall seasonality characteristics demonstrates the ratio’s utility. Strong correspondence of scores between station and gridded data applications demonstrates additional confidence in the ratio, establishing its value for further application.

1. The environmental filtering hypothesis predicts that the abiotic environment selects species with similar trait values within communities. Testing this hypothesis along multiple — and interacting — gradients of climate and soil variables constitutes a great opportunity to better understand and predict the responses of plant communities to ongoing environmental changes. 2. Based on two key plant traits, maximum plant height and specific leaf area (SLA), we assessed the filtering effects of climate (mean annual temperature and precipitation, precipitation seasonality), soil characteristics (soil pH, sand content and total phosphorus) and all potential interactions on the functional structure and diversity of 124 dryland communities spread over the globe. The functional structure and diversity of dryland communities were quantified using the mean, variance, skewness and kurtosis of plant trait distributions. 3. The models accurately explained the observed variations in functional trait diversity across the 124 communities studied. All models included interactions among factors, i.e. climate-climate (9% of explanatory power), climate-soil (24% of explanatory power) and soil—soil interactions (5% of explanatory power). Precipitation seasonality was the main driver of maximum plant height, and interacted with mean annual temperature and precipitation. Soil pH mediated the filtering effects of climate and sand content on SLA. Our results also revealed that communities characterized by a low variance can also exhibit low kurtosis values, indicating that functionally contrasting species can co-occur even in communities with narrow ranges of trait values. 4. Synthesis. We identified the particular set of conditions under which the environmental filtering hypothesis operates in drylands world-wide. Our findings also indicate that species with functionally contrasting strategies can still co-occur locally, even under prevailing environmental filtering. Interactions between sources of environmental stress should be therefore included in global trait-based studies, as this will help to further anticipate where the effects of environmental filtering will impact plant trait diversity under climate change.

Changes in precipitation seasonality or redistribution of precipitation could exert significant influences on regional water resources availability and the well-being of the ecosystem. However, due to the nonuniform distribution of precipitation stations and intermittency of precipitation, precise detection of changes in precipitation seasonality on the global scale is absent. This study identifies and inter-compares trends in precipitation seasonality within seven precipitation datasets during the past three decades, including two gauge-based datasets derived from the Climatic Research Unit (CRU) and the Global Precipitation Climatology Centre (GPCC), one remote sensing-retrieval obtained from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), three reanalysis datasets obtained from National Centers for Environmental Prediction reanalysis II (NCEP2), European Centre for Medium-Range Weather Forecasts Interim Reanalysis (ERA-Interim), and Modern Era Reanalysis for Research and Applications Version 2 (MERRA2), and one precipitation dataset merged from above three types, Multi-Source Weighted Ensemble Precipitation Version 1.2 (MSWEP_V1.2). Values of two indices representing the precipitation seasonality, the normal seasonality index (SI) and the dimensionless seasonality index (DSI), are estimated for each land grid in each precipitation dataset. The results show that DSI is more sensitive to changes in the temporal distribution of precipitation as it considers both annual amount and monthly fluctuations of precipitation, compared to SI that only considers monthly fluctuations of precipitation. There are large differences in precipitation seasonality at annual and climatologic scales between precipitation datasets for both SI and DSI. Within the seven precipitation datasets, PERSIANN-CDR SI and DSI show high precipitation seasonality while CRU SI, and ERA-Interim and MERRA2 DSI show the low precipitation seasonality in all continental regions. During 1988–2013, PERSIANN-CDR, NCEP2 and ERA-Interim show more widespread, statistically significant trends in precipitation seasonality than other four precipitation datasets. PERSIANN-CDR and NCEP2 show statistically significant decreases in SI over Middle East and Central Asia, while ERA-Interim, MERRA2 and MSWEP_V1.2 SI increase over Central and South Africa. Increases in SI over the most of South America are significant. Regions of Canada/Greenland/Iceland, East and South Africa show significant increases in precipitation seasonality, while South Europe/Mediterranean and Central Africa show significant decreases in precipitation seasonality in most datasets. Although time series of seasonality indices values fluctuate correlatively in recent three decades, there are no regions on which all precipitation datasets show a consistent, statistically significant, positive or negative trend in indices of precipitation seasonality. These inconsistent changes in precipitation seasonality within various precipitation datasets imply the importance of choosing dataset when studying changes in regional precipitation seasonality.

Seasonal birth weight has been identified across different climate zones. Finland has wide seasonal and regional variation in climate within the country. We explore the potential seasonality of birth weight in singleton full-term births in Finland, and its variations across time and within the country. We apply descriptive time-series graphs, linear regression across regions, and linear regression with mother fixed effects using Finnish register data consisting of more than 1,800,000 infants born from 1987 to 2021. The descriptive findings indicate a decline in birth weight from 1987 to 2021. A monthly seasonal trend with peaks in spring and autumn and troughs in summer and winter is observed. The pattern gets less distinct with time and shows within-country variations. The seasonal pattern is also present when applying mother fixed effects. We suggest that the seasonal variation is more related to variations in climate than stable characteristics at the family level.

The Covid-19 pandemic has spread across the world during early 2020, with unforeseen consequences. Beyond social measures and biomedical research, it is important to assess the seasonality of the epidemic to inform strategies, with limited available data in the short period of time between the March equinox and the June solstice. While the effect of multiple factors is being investigated, little attention has been paid to ultraviolet (UV) radiation, a key parameter of seasonal forcing. We review the effects of UV radiation, proposing it as a potential element of seasonality, and provide evidence from the current literature and scant, yet revealing, observations. Explicit consideration should be given to UV radiation for the seasonality of Covid-19 at high latitudes and altitudes, based on the SARS and MERS epidemics and coronavirus diseases, and not just the 'warmer days' of summer.

Although seasonality is an old tourism phenomenon, the advent of global hypermobilities and the changing features of the tourism industry requires a considerable revisit to the longstanding assumption of tourism. This study provokes further research on various seasonality aspects implicated in the discussion based on the broad range of the literature review and the subsequent findings. The article explores the current seasonality research in tourism and hospitality and proposes a typology and literature-based agenda for future scholarly investigations. Results provide an overview of seasonality research in tourism and hospitality by examining key themes in theory, methodology, research topics, and geographical features. We underscore the importance of theoretical and conceptual development and a comprehensive approach to seasonality research in tourism and hospitality.

Abstract Respiratory syncytial virus (RSV) is the leading cause of acute lower respiratory infections in children. By the age of 1 year, 60%–70% of children have been infected by RSV. In addition, early-life RSV infection is associated with the development of recurrent wheezing and asthma in infancy and childhood. The need for precise epidemiologic data regarding RSV as a worldwide pathogen has been growing steadily as novel RSV therapeutics are reaching the final stages of development. To optimize the prevention, diagnosis, and treatment of RSV infection in a timely manner, knowledge about the differences in the timing of the RSV epidemics worldwide is needed. Previous analyses, based on literature reviews of individual reports obtained from medical databases, have failed to provide global country seasonality patterns. Until recently, only certain countries have been recording RSV incidence through their own surveillance systems. This analysis was based on national RSV surveillance reports and medical databases from 27 countries worldwide. This is the first study to use original-source, high-quality surveillance data to establish a global, robust, and homogeneous report on global country-specific RSV seasonality. Respiratory syncytial virus (RSV) is the leading cause of acute lower respiratory infections in children. This is the first study to use original-source, high-quality surveillance data to establish a global, robust, and homogeneous report on global country-specific RSV seasonality.

PurposeThe aim of the paper is to examine and analyse the thematic literature on tourism seasonality and the causes and effects thereof.Design/methodology/approachThe paper is based on a review of scientific and theoretical research by various authors on tourism seasonality, in order to systematically analyse the causes and effects of the seasonal patterns in tourism activity.FindingsSeasonality is one of the most important features of tourism demand, and it has a significant effect on many aspects of the tourism industry. The literature review suggests that tourism seasonality is caused by natural and anthropogenic factors that have a very significant bearing on the geographical location of a tourist destination, as well as institutional and economic factors. Assessments of the effects of seasonality in the scientific literature differ. The effects of seasonality analysed in the relevant literature can be divided into four major categories: economic, employment, social and cultural as well as ecological.Originality/valueThe paper presents a systematic literature review on tourism seasonality and the causes and effects thereof.

The idea that tropical forest and savanna are alternative states is crucial to how we manage these biomes and predict their future under global change. Large-scale empirical evidence for alternative stable states is limited, however, and comes mostly from the multimodal distribution of structural aspects of vegetation. These approaches have been criticized, as structure alone cannot separate out wetter savannas from drier forests for example, and there are also technical challenges to mapping vegetation structure in unbiased ways. Here, we develop an alternative approach to delimit the climatic envelope of the two biomes in Africa using tree species lists gathered for a large number of forest and savanna sites distributed across the continent. Our analyses confirm extensive climatic overlap of forest and savanna, supporting the alternative stable states hypothesis for Africa, and this result is corroborated by paleoecological evidence. Further, we find the two biomes to have highly divergent tree species compositions and to represent alternative compositional states. This allowed us to classify tree species as forest vs. savanna specialists, with some generalist species that span both biomes. In conjunction with georeferenced herbarium records, we mapped the forest and savanna distributions across Africa and quantified their environmental limits, which are primarily related to precipitation and seasonality, with a secondary contribution of fire. These results are important for the ongoing efforts to restore African ecosystems, which depend on accurate biome maps to set appropriate targets for the restored states but also provide empirical evidence for broad-scale bistability.

Mounting evidence across South Africa’s southwestern winter rainfall zone (WRZ) reflects consistent drying since ~ 1980, and projected trends suggest this will continue. However, limited evidence exists for changes in the region’s rainfall seasonality. To improve our understanding of these WRZ drying trends, especially within the context of Cape Town’s 2015–2017 “Day Zero” drought, it is necessary to explore long-term rainfall seasonality trends. Thus, we use the longest WRZ meteorological record from the South African Astronomical Observatory (SAAO) in Cape Town to investigate rainfall seasonality shifts during 1841–2020. Consistent with recorded poleward migrations of the subtropical high-pressure belt and mid-latitude westerlies, known drivers behind the drought and drying trends, calculated trends demonstrate strengthening of WRZ conditions, primarily from a later start-date trend leading to a shorter wet-season. Long-term drying trends are quantified for the wet and dry seasons; however, analysis of trend evolution reveals much variability, reflecting that drying has only persisted since ~ 1892. Comparative analyses of the first and last 59 years of 1841–2020 reveal a rainfall decline of almost 10% across both seasons—highlighting that the extreme “Day Zero” drought was not only driven by wet-season rainfall declines. Results demonstrate that these drying trends were consistently driven by a long-term decline in rain day counts and a more recent decline in average rainfall per rain day. Correspondence between our results and projected rainfall seasonality trends suggests the trends we quantified will likely continue; thus, improvements and continuation of existing water conservation and management strategies are imperative for Cape Town.