HIV Protease and Integrase Empirical Substitution Models of Evolution: Protein-Specific Models Outperform Generalist Models

Diverse phylogenetic methods require a substitution model of evolution that should mimic, as accurately as possible, the real substitution process. At the protein level, empirical substitution models have traditionally been based on a large number of different proteins from particular taxonomic levels. However, these models assume that all of the proteins of a taxonomic level evolve under the same substitution patterns. We believe that this assumption is highly unrealistic and should be relaxed by considering protein-specific substitution models that account for protein-specific selection processes. In order to test this hypothesis, we inferred and evaluated four new empirical substitution models for the protease and integrase of HIV and other viruses. We found that these models more accurately fit, compared with any of the currently available empirical substitution models, the evolutionary process of these proteins. We conclude that evolutionary inferences from protein sequences are more accurate if they are based on protein-specific substitution models rather than taxonomic-specific (generalist) substitution models. We also present four new empirical substitution models of protein evolution that could be useful for phylogenetic inferences of viral protease and integrase.

Divergence together with microbes: A comparative study of the associated microbiomes in the closely related Littorina species

Any multicellular organism during its life is involved in relatively stable interactions with microorganisms. The organism and its microbiome make up a holobiont, possessing a unique set of characteristics and evolving as a whole system. This study aimed to evaluate the degree of the conservativeness of microbiomes associated with intertidal gastropods. We studied the composition and the geographic and phylogenetic variability of the gut and body surface microbiomes of five closely related sympatric Littorina (Neritrema) spp. and a more distant species, L. littorea, from the sister subgenus Littorina (Littorina). Although snail-associated microbiomes included many lineages (207–603), they were dominated by a small number of OTUs of the genera Psychromonas, Vibrio, and Psychrilyobacter. The geographic variability was greater than the interspecific differences at the same collection site. While the microbiomes of the six Littorina spp. did not differ at the high taxonomic level, the OTU composition differed between groups of cryptic species and subgenera. A few species-specific OTUs were detected within the collection sites; notably, such OTUs never dominated microbiomes. We conclude that the composition of the high-rank taxa of the associated microbiome (“scaffolding enterotype”) is more evolutionarily conserved than the composition of the low-rank individual OTUs, which may be site- and / or species-specific.

SPATIAL-TEMPORAL DISTRIBUTION OF POLYCHAETA IN URBANIZED SANDY BEACHES OF NORTHEASTERN BRAZIL: TOOLS FOR ENVIRONMENTAL ASSESSMENT

In the last years, the use of Polychaeta as indicators of marine pollution has intensified, due to the sensitivity of these organisms to environmental variations and their significant presence in quantitative and qualitative terms when compared to other benthic fauna organisms. We aimed to analyze the Polychaeta assemblage of two urbanized beaches in São Luís – Maranhão (Brazil), focusing on spatial-temporal distribution and look for the relation of the species sampled and possible contamination to indicate if they are suitable for environmental assessment. Sediment collection was carried out in the intertidal zone of both beaches in dry (September and November/2015) and rainy periods (March and May/2016). The samples were screened for extraction of the species, which were classified at the lowest possible taxonomic level. The samples revealed the following taxa: Lumbrineridae (Scoletoma tetraura), Nereididae (Laeonereis culveri) and Spionidae (Scolelepis sp.). The diversity and abundance of Polychaeta were greater on Caolho Beach. On these beaches, organic enrichment is not the determining variable in the structure of the Polychaeta assembly. Other studies are needed to improve the knowledge on other macrofauna species of the studied areas, comparing the richness among microhabitats and seasons, and thus elaborate conservation strategies for these ecosystems; and to test the hypothesis of the influence of tourism on this assemblage.

Defining and quantifying the core microbiome: Challenges and prospects

The term “core microbiome” has become widely used in microbial ecology over the last decade. Broadly, the core microbiome refers to any set of microbial taxa, or the genomic and functional attributes associated with those taxa, that are characteristic of a host or environment of interest. Most commonly, core microbiomes are measured as the microbial taxa shared among two or more samples from a particular host or environment. Despite the popularity of this term and its growing use, there is little consensus about how a core microbiome should be quantified in practice. Here, we present a brief history of the core microbiome concept and use a representative sample of the literature to review the different metrics commonly used for quantifying the core. Empirical analyses have used a wide range of metrics for quantifying the core microbiome, including arbitrary occurrence and abundance cutoff values, with the focal taxonomic level of the core ranging from phyla to amplicon sequence variants. However, many of these metrics are susceptible to sampling and other biases. Developing a standardized set of metrics for quantifying the core that accounts for such biases is necessary for testing specific hypotheses about the functional and ecological roles of core microbiomes.

Classifying the Unknown: Identification of Insects by Deep Zero-shot Bayesian Learning

Insects represent a large majority of biodiversity on Earth, yet so few species are described. Describing new species typicallyrequires specific taxonomic expertise to identify morphological characters that distinguish it from other known species andDNA-based methods have aided in providing additional evidence of separate species. Machine learning (ML) provides apowerful method in identifying new species given its analytical processing is more sensitive to subtle physical differencesin images humans may not process. Existing ML algorithms are limited by image repositories that only contain describedspecies, leaving out the possibility of identifying new species. We develop a Bayesian deep learning method for zero-shotclassification of species. The proposed approach forms a Bayesian hierarchy of species around corresponding genera anduses deep embeddings of images and DNA barcodes to identify insects to the lowest taxonomic level possible. To demonstratethis proof of concept, we use a database of 32,848 insect images from 1,040 described species split into training and test datawherein the test data includes 243 species not present in the training data. Our results demonstrate that using DNA sequencesand images together, known insects can be classified with 96.66% accuracy while unknown (to the database) insects have anaccuracy of 81.39% in identifying the correct genus. The proposed deep zero-shot Bayesian model demonstrates a powerfulnew approach that can be used for the gargantuan task of identifying new insect species.

Life histories of 9,488 bird and 4,865 mammal species

I use 56,214 life history data to estimate equilibrium life history models for birds and mammals with body mass estimates. Missing parameters were estimated by allometric correlations at the lowest taxonomic level (genus, family, order, class) with data. The estimation is optimised to predict the existing data, with precision estimated separately for the different taxonomic levels of the estimator. This provides complete life history models for 9,488 species of birds, and 4,865 species of mammals. Each model includes estimates of metabolism, net assimilated energy, individual growth, mortality, fecundity, age of reproductive maturity, generation time, life span, home range, population density, biomass, population consumption, and a relative measure of intra-specific interactive competition, providing 387,531 parameter estimates in total.

Discerning the Management-Relevant Ecology and Distribution of Sea Pens (Cnidaria: Pennatulacea) in Norway and Beyond

Sea pens are considered to be of conservation relevance according to multiple international legislations and agreements. Consequently, any information about their ecology and distribution should be of use to management decision makers. This study aims to provide such information about six taxa of sea pen in Norwegian waters [Funiculina quadrangularis (Pallas, 1766), Halipteris spp., Kophobelemnon stelliferum (Müller, 1776), Pennatulidae spp., Umbellula spp., and Virgulariidae spp.]. Data exploration techniques and ensembled species distribution modelling (SDM) are applied to video observations obtained by the MAREANO project between 2006 and 2020. Norway-based ecological profiles and predicted distributions are provided and discussed. External validations and uncertainty metrics highlight model weaknesses (overfitting, limited training/external observations) and consistencies relevant to marine management. Comparison to international literature further identifies globally relevant findings: (a) disparities in the environmental profile of F. quadrangularis suggest differing “realised niches” in different locations, potentially highlighting this taxon as particularly vulnerable to impact, (b) none of the six sea pen taxa were found to consistently co-occur, instead partially overlapping environmental profiles suggests that grouping taxa as “sea pens and burrowing megafauna” should be done with caution post-analyses only, (c) higher taxonomic level groupings, while sometimes necessary due to identification issues, result in poorer quality predictive models and may mask the occurrence of rarer species. Community-based groupings are therefore preferable due to confirmed shared ecological niches while greater value should be placed on accurate species ID to support management efforts.

Efficiency of sampling gears (Quadrate and Core) and Taxonomic Resolution on the Soft Bottom Intertidal Macrobenthic community of Port Blair coast

Ecological studies of a region cannot proceed forward without the evaluation of species diversity. With the ever-increasing demand for studies to understand the change in the macrobenthic communities, the focus has primarily been shifted towards faster results to track down the changes from the prior environments. Therefore, studying the complete benthos faunal diversity of an area leads to an unrealistic approach. Thus, researchers tend to depend on various sampling gears, which ease the work capacity. The present study compared two samplings gears (core and quadrate) in two different habitats to understand the diversity of the macrobenthic communities. In terms of abundance, the core gear showed higher significant differences as compared to quadrate. However, the gears did not significantly differ among the diversity indices (Margalef's index and Shannon- Winer index) and the cluster analysis (Bray-Curtis similarity index and nMDS). The present study found that the 'information loss' was minimal with the aggregated data at a higher taxonomic level. Spearman rank correlation coefficient revealed that the information loss was low up to family-level and the correlation coefficient decreases as the taxonomic level increases after family-level. Nonetheless, the choice of sampling gears did not influence the diversity of the soft-bottom intertidal macrobenthic communities.

Artificial seagrass experiments in the Northeast Mediterranean

: Seagrasses provide important nursery grounds, shelter and natural habitats for juvenile fish. In this study, we evaluated if artificially created seagrass areas can play the same role as the natural seagrass (NS) habitats. The study was carried out in three different stations on the coast of Yumurtalık, Adana, selected according to the seagrass areas. Artificial seagrass (AS) was made of polypropylene ribbon and fixed on the ground in the designated areas with a depth of 0.5 m on average. Sampling was carried out with a beach seine net once a week at stations between 28 April 2016 and 11 August 2016. Sampled fish were identified to the lowest possible taxonomic level. Based on our results, the fish abundance and species richness of NS and AS habitats were not statistically different, whereas the both parameters were significantly lower in sandy (S) habitats (p<0.001). Moreover, the species composition of NS and AS habitats was found to be similar each other, whereas the composition was significantly different in S habitats. This study, conducted in the Northeast Mediterranean, shows that AS habitats effect the distribution of juvenile fish.

​Fuzzy Logic Expert System for Taxonomic Variation of Solonchaks

Background: The main objective of this research is to apply fuzzy logic to four Solonchaks, in order to determine their degree of remoteness or rapprochement with their central taxonomic concept. Therefore, we identify their possible seasonal taxonomic variation on the criteria established by World Reference Base (WRB). Methods: We have studied the seasonal evolution of salinity in a region of Algeria (Case of Rélizane), during two years 2012 and 2013 by applying fuzzy logic on the four soils. Result: The results reveal that the salinity increased during the dry period for all soils and it decreased during the wet period. On the taxonomic level, the application of fuzzy logic on the four soils revealed that the Solonchaks indices (Is) are always significantly higher than those of Calcisols indices (Ic). The four profiles have a similar behavior regarding the variation of Is. Indeed, when the salinity increases the soils come closer to the central taxonomic concept of the Solonchaks. Likewise, when the salinity decreases the soils move away from their central taxonomic concept. Consequently, they approach the central taxonomic concept of Calcisols. Thus, the variation of Isis closely related to the seasonal variation of salinity. Fuzzy logic, exhibited high precision concerning the membership value between soils over time. The application of fuzzy logic for other soil classifications in the world is possible.