Genetic structure and diversity within and among six populations of Capparis decidua (forssk.) edgew. from Saudi Arabia

Capparis decidua is a rangeland plant species growing in isolated populations in Saudi Arabia. Genetic diversity within and among six populations (Madina, Farasan island, Hawayer Assos, Khor Assos, Raudhat Khuraim, and Taif) of C. decidua was studied using RAPD technique. Of the 25 random primers were used, eighteen (18) primers generated discernible and reproducible bands. A total of 152 reproducible RAPD bands across the 36 individuals were amplified. Out of those, 117 (76.2%) RAPD bands were polymorphic. The number of polymorphic bands per primer ranged between 3 and 11 with an average of 6.5 bands per primer. Populations differed in the level of genetic diversity as shown from the percentage of polymorphic bands. Farasan population had the highest level of genetic diversity (24.3%) and two populations Khor Assos (5.9%) and Taif (4.6%) had the lowest genetic diversity. Analysis of molecular variance (AMOVA) showed highly significant differences among populations. Among the population variance accounted, there is a higher percentage of the total variance (average 77.67%, SD±8.21) than within populations (average 22.33%, SD±8.21). There is no significant correlation between geographical distance and genetic distance was found. However, there was a significant positive correlation between molecular genetic variation and actual population size. The implication of the results of this study in devising strategy for conservation of C. decidua is discussed.Key words: Capparis decidua, Tandhab, Assos, Population size, RAPD markers, Genetic diversity

Drone-Based Vegetation Assessment in Arid Ecosystems

Proof of long-term vegetation change in arid rangelands is often insufficient to influence policy, even when the change is clear to ecologists. Drones provide a way to collect unbiased evidence of plant spatiotemporal distribution at a dramatically reduced cost for the scales needed in these habitats. Assessment of phytomass spatial distribution by drone has become a routine, but further analysis requires advanced skills in data collection and post-flight processing. Accurate assessment of phytomass temporal change will require protocols to be developed for data collection and analysis. Biodiversity assessment by drone is unreliable, but there is potential for assessing phytomass change within and among taxonomic groups in arid rangelands, by repeatedly sampling areas in which perennial plants have been classified manually

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 research