Coral bleaching due to increased sea surface temperature in Gulf of Kachchh Region, India, during June 2016

327-332The 2015-2016 E1 Niño Southern Oscillation event was one of the extreme climate events which elevated the sea surface temperature (SST) of tropical oceans, which in turn increased the level of thermal stress on corals. Coral bleaching event is mainly caused due to high positive SST anomaly, i.e., when SST exceeds its normal summer maxima. Corals in the Gulf of Kachchh region of Gujarat earlier experienced coral bleaching events during 1988, 2010 and 2014. For this study, SST was derived from NOAA OISST data set which is available daily at 0.25° global grids from 1982 to present. The climatologically warmest month for the Gulf of Kachchh region is June when the maximum monthly mean temperature is 29.31°C, as observed from NOAA OISST. The present study focuses on monitoring daily SST anomalies during summer 2016 for the Gulf of Kachchh reefs and field observations on early responses of coral bleaching from Laku Point reef, a site known for high coral diversity. It was found that in summer 2016, SST rose to 30.62 °C and recorded a maximum positive anomaly of 1.31°C in the month of June. A total of 72 days out of 122-day monitoring period showed positive SST anomaly, including 28 days of continuous positive thermal stress in June 2016.To validate coral bleaching forecast at the end of the regional warmest quarter, a field visit was carried out at Laku Point reef near Poshitra village in the southern coast of the Gulf of Kachchh. A total of 13 coral species and a sea anemone were found bleached in various proportions during the field sampling after two months of prolonged thermal stress. The field data showed an average of 3.9% bleaching of corals at colony scale. The maximum proportion of colony scale bleaching was observed in Porites lutea species

Assessment of spatial and temporal variations in coastal water quality of Gulf of Kachchh, Gujarat using GIS application

2313-2320The monitoring of coastal water quality was done on seasonal basis in pre-monsoon, monsoon and post-monsoon for three years duration (November 2011 to December 2014). Data obtained were applied to Arc-GIS software 10.3 for the preparation of thematic maps to evaluate the spatial and temporal variation in water quality parameters. Cluster analysis showed formation of two clusters which grouped 17 sites in two dominant ecosystems namely mangrove and coral

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press