The digestive mechanisms of an intertidal grazer, the sea urchin Parechinus angulosus

Echinoids are important grazers in the near-shore ecosystem and can significantly effect their ecology. The sea urchin Parechinus angulosus occurs inter- and subtidally along the southern African coast. Within this range it consumes an extremely wide variety of algae. Since algal cell walls have an almost species specific chemical composition, the question arises as to how it can digest the algae that it consumes. In order to investigate the digestive mechanisms employed by P. angulosus, an ultrastructural study of the gut was undertaken to characterize the tissue and identify functional regions in the gut. Ten structural and storage polysaccharides commonly found in macroalgae were used as substrates to assay the digestive polysaccharidases of the sea urchin. The enteric bacteria of the sea urchin were isolated and tested separately for polysaccharidase activity using the same substrates. The results shown that the gut of Parechinus angulosus is regionally specialized, with the foregut primarily responsible for the production of hydrolytic enzymes, while the hindgut is primarily absorptive. The occurrence of lamellar bodies, heterolysosomes, cytoplasmic blebs and paddle cilia among other characteristic features of the digestive epithelium are described and discussed. Two levels of enzyme activity are apparent. Generally the urchin could hydrolyze the reserve polysaccharides, but only partially hydrolyze the structural polysaccharides, of red and green algae. P.angulosus was unable to digest alginic acid, the main structural polysaccharide of brown algae. Mixed cultures of bacteria utilized only the reserve polysaccharides of red and green algae. Significantly, the bacteria were able to hydrolyze alginic acid. Enteric bacteria also showed agarolytic activity. Parechinus angulosus has the ability to digest red and green algae. No lysozyme activity was detected. The enteric bacteria can digest the same algal reserve polysaccharides and so may compete for carbon in the gut. However, in the case of brown algae, bacteria have a potentially important endosymbiotic role as agents of digestion. These results correspond with food preference studies which have shown that, although P.angulosus consumes the kelp Ecklonia maxima, in the western Cape, it is amongst its least preferred food species. The reasons for this are its unpalatability and the urchin's inability to digest brown algae. The digestibility of algal material can be an important factor in determining algal-herbivore interactions

Where have all the flowers gone? – Changing climate, seasons and weather and the challenges and opportunities for public health research

Since the United Nations Framework Convention on Climate Change (UNFCCC) negotiations produced the Paris Agreement1 of December 2015, despite its subsequent notorious political challenges, the zeitgeist of global warming and subsequent climate change (GWCC) concerns has moved on from debating its very existence, toward understanding the way in which GWCC is and will manifest now and in the future. Any dispute regarding the attribution of global warming, and the consequences of climate change, to industrial-era emissions of greenhouse gasses emanating from anthropogenic origins, is now in the realm of ‘Flat-Earthers’. The more relevant questions are now about how we rehabilitate the worldwide fossil fuel addiction (mitigation) and how we respond to the impacts of GWCC (adaptation).http://www.tandfonline.com/loi/ojid20am2019Geography, Geoinformatics and Meteorolog

Predicting diarrhoea outbreaks with climate change

Climate change is expected to exacerbate diarrhoea outbreaks across the developing world, most notably in Sub-Saharan countries such as South Africa. In South Africa, diseases related to diarrhoea outbreak is a leading cause of morbidity and mortality. In this study, we modelled the impacts of climate change on diarrhoea with various machine learning (ML) methods to predict daily outbreak of diarrhoea cases in nine South African provinces

The development and prudent application of climate-based forecasts of seasonal malaria in the Limpopo province in South Africa

Seasonal Climate Forecasting (SCF) in South Africa has a history spanning several decades. During this period a number of SCF systems have been developed for the prediction of seasonal-to-interannual variability of rainfall and surface temperatures. Areas of highest predictability, albeit relatively modest, have also been identified. The north-eastern parts of South Africa that includes the Limpopo province has been demonstrated to be one of the areas of highest SCF skill in the country. Statistical post-processing techniques applied to global climate model output were part of this forecast system development, and were subsequently successfully used in the construction of forecasts systems for applications in sectors which are associated with ENSO-driven climate variability, such as dry-land crop yields and river flows. Here we follow a similar post-model processing approach to test SCF systems for application to the incidence of seasonal malaria in Limpopo. The malaria forecast system introduced here makes use of the seasonal rainfall output fields of one of the North American Multi-Model Ensemble (NMME) climate models, which is then linked statistically through multiple linear regression to observed malaria incidence. The verification results as calculated over a 20-year hindcast period show that the season of highest malaria incidence forecast skill is during the austral mid-summer time of December to February. Moreover, the hindcasts based on the NMME model outscore those of statistical forecast models that separately use Indian and Pacific Ocean sea-surface temperatures as predictors, thus justifying the use of physical global climate models for this kind of application. Additional results indicate that model skill levels may include quasi-decadal variability, that the periods over which forecast verification is performed strongly influences forecast skill, and that poorly predicted malaria seasons may have serious financial implications on public health operations.The Japan Agency for Medical Research and Development (AMED; Japan International Cooperation Agency (JICA) through Science and Technology Research Partnership for Sustainable Development (SATREPS) project for iDEWS South Africa.http://www.elsevier.com/locate/envdevhj2021Geography, Geoinformatics and Meteorolog

Exploring the association between ambient temperature and daily hospital admissions for diarrhea in Mopani district, Limpopo province, South Africa

DATA AVAILABILITY STATEMENT: Data are available upon request from the corresponding author.Please read abstract in article.Sustainable Development (SATREPS) Program of JAPAN International Cooperation Agency (JICA)/Japan Agency; Climate and Earth Systems Science (ACCESS) program of National Research Foundation (NRF); Department of Science and Technology in South Africa (DST).https://www.mdpi.com/journal/healthcareGeography, Geoinformatics and Meteorolog

Exploring rural hospital admissions for diarrhoeal disease, malaria, pneumonia, and asthma in relation to temperature, rainfall and air pollution using wavelet transform analysis

BACKGROUND : Climate variables impact human health and in an era of climate change, there is a pressing need to understand these relationships to best inform how such impacts are likely to change. OBJECTIVES : This study sought to investigate time series of daily admissions from two public hospitals in Limpopo province in South Africa with climate variability and air quality. METHODS : We used wavelet transform cross-correlation analysis to monitor coincidences in changes of meteorological (temperature and rainfall) and air quality (concentrations of PM2.5 and NO2) variables with admissions to hospitals for gastrointestinal illnesses including diarrhoea, pneumonia-related diagnosis, malaria and asthma cases. We were interested to disentangle meteorological or environmental variables that might be associated with underlying temporal variations of disease prevalence measured through visits to hospitals. RESULTS : We found preconditioning of prevalence of pneumonia by changes in air quality and showed that malaria in South Africa is a multivariate event, initiated by co-occurrence of heat and rainfall. We provided new statistical estimates of time delays between the change of weather or air pollution and increase of hospital admissions for pneumonia and malaria that are addition to already known seasonal variations. We found that increase of prevalence of pneumonia follows changes in air quality after a time period of 10 to 15 days, while the increase of incidence of malaria follows the co-occurrence of high temperature and rainfall after a 30-day interval. DISCUSSION : Our findings have relevance for early warning system development and climate change adaptation planning to protect human health and well-being.The SAMRC; this research was carried out for the iDEWS (infectious Diseases Early-Warning System) project supported by SATREPS (Science and Technology Research Partnership for Sustainable Development) Program of JICA (JAPAN International Cooperation Agency)/AMED (Japan Agency for Medical Research and Development) in Japan and the ACCESS (Alliance for Collaboration on Climate and Earth Systems Science) program of NRF (National Research Foundation) and DST (Department of Science and Technology in South Africa) as well as the Serbian Scientific Research Fund.http://www.elsevier.com/locate/scitotenvhj2022Geography, Geoinformatics and Meteorolog

Winter is coming: A southern hemisphere perspective of the environmental drivers of sars-cov-2 and the potential seasonality of covid-19

SARS-CoV-2 virus infections in humans were first reported in December 2019, the boreal winter. The resulting COVID-19 pandemic was declared by the WHO in March 2020. By July 2020, COVID-19 was present in 213 countries and territories, with over 12 million confirmed cases and over half a million attributed deaths. Knowledge of other viral respiratory diseases suggests that the transmission of SARS-CoV-2 could be modulated by seasonally varying environmental factors such as temperature and humidity. Many studies on the environmental sensitivity of COVID-19 are appearing online, and some have been published in peer-reviewed journals. Initially, these studies raised the hypothesis that climatic conditions would subdue the viral transmission rate in places entering the boreal summer, and that southern hemisphere countries would experience enhanced disease spread. For the latter, the COVID-19 peak would coincide with the peak of the influenza season, increasing misdiagnosis and placing an additional burden on health systems. In this review, we assess the evidence that environmental drivers are a significant factor in the trajectory of the COVID-19 pandemic, globally and regionally. We critically assessed 42 peer-reviewed and 80 preprint publications that met qualifying criteria

Malaria predictions based on seasonal climate forecasts in South Africa: A time series distributed lag nonlinear model

Although there have been enormous demands and efforts to develop an early warning system for malaria, no sustainable system has remained. Well-organized malaria surveillance and high-quality climate forecasts are required to sustain a malaria early warning system in conjunction with an effective malaria prediction model. We aimed to develop a weather-based malaria prediction model using a weekly time-series data including temperature, precipitation, and malaria cases from 1998 to 2015 in Vhembe, Limpopo, South Africa and apply it to seasonal climate forecasts. The malaria prediction model performed well for short-term predictions (correlation coefficient, r?>?0.8 for 1- and 2-week ahead forecasts). The prediction accuracy decreased as the lead time increased but retained fairly good performance (r?>?0.7) up to the 16-week ahead prediction. The demonstration of the malaria prediction process based on the seasonal climate forecasts showed the short-term predictions coincided closely with the observed malaria cases. The weather-based malaria prediction model we developed could be applicable in practice together with skillful seasonal climate forecasts and existing malaria surveillance data. Establishing an automated operating system based on real-time data inputs will be beneficial for the malaria early warning system, and can be an instructive example for other malaria-endemic areas.Publisher Correction: A supplementary file containing Fig S1 was omitted from the original version of this Article. This has been corrected in the HTML version of the Article; the PDF version was correct at time of publication. https://doi.org/10.1038/s41598-020-58890-

Climate change is catchy ? but when will it really hurt?

Concern and general awareness about the impacts of climate change in all sectors of the social-ecological-economic system is growing as a result of improved climate science products and information, as well as increased media coverage of the apparent manifestations of the phenomenon in our society. However, scales of climate variability and change, in space and time, are often confused and so attribution of impacts on various sectors, including the health sector, can be misunderstood and misrepresented. In this review, we assess the mechanistic links between climate and infectious diseases in particular, and consider how this relationship varies, and may vary according to different time scales, especially for aetiologically climate-linked diseases. While climate varies in the medium (inter-annual) time frame, this variability itself may be oscillating and/or trending on cyclical and long-term (climate change) scales because of regional and global scale climate phenomena such as the El-Nino southern oscillation coupled with global-warming drivers of climate change. As several studies have shown, quantifying and modelling these linkages and associations at appropriate time and space scales is both necessary and increasingly feasible with improved climate science products and better epidemiological data. The application of this approach is considered for South Africa, and the need for a more concerted effort in this regard is supported

Editorial

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Policy Analysi