Diversity and abundance of pollinators in different winter crops at Sher-e-Bangla Agricultural University Campus, Dhaka

The study was conducted at Sher-e-Bangla Agricultural University campus to document the diversity and abundance of pollinators of five commonly grown winter crops, viz., mustard, coriander, niger, black cumin and linseed from October 2020 to February 2021. A total number of fifteen species was identified under eleven genera, nine subfamilies, nine families and seven super families. The study revealed that honey bees, halictids, nymphalids, coccinellids, butterflies and dipterans of genera Apis, Halictus, Lasioglossum, Aglais, Coccinella, Pieris, Eurema, Musca, Syrphid and Calliphora belonging to the families Apidae, Halictidae, Nymphalidae, Coccinellidae, Pieridae, Muscidae, Syrphidae and Calliphoridae, respectively were present in the field. The species diversity was high in mustard with 15 species while it was low in linseed (5 species). The honey bees, Apis sp. and sweat bees, Halictus sp. were common pollinators of all five oilseed crops, while the housefly, Musca domestica was specific to mustard. The honey bee, Apis sp. was predominant among all the insect pollinators in five oilseed crops. The Species Richness (SR), Shannon-Weaver index (H’), Community dominance and Question of similarity indices were applied to determine the diversity and abundance of pollinators. J. Biodivers. Conserv. Bioresour. Manag. 2021, 7(1): 33-42

Homogeneity of Arabian Peninsula dromedary camel populations with signals of geographic distinction based on whole genome sequence data

Dromedary camels in the Arabian Peninsula distribute along different geographical and ecological locations, e.g. desert, mountains and coasts. Here, we are aiming to explore the whole genome sequence data of ten dromedary populations from the Arabian Peninsula to assess their genetic structure, admixture levels, diversity and similarity indices. Upon including reference dromedary and Bactrian camel populations from Iran and Kazakhstan, we characterise inter-species and geographic genetic distinction between the dromedary and the Bactrian camels. Individual-based alpha genetic diversity profiles are found to be generally higher in Bactrian camels than dromedary populations, with the exception of five autosomes (NC_044525.1, NC_044534.1, NC_044540.1, NC_044542.1, NC_044544.1) at diversity orders (q ≥ 2). The Arabian Peninsula camels are generally homogenous, with a small degree of genetic distinction correlating with three geographic groups: North, Central and West; Southwest; and Southeast of the Arabian Peninsula. No significant variation in diversity or similarity indices are observed among the different Arabian Peninsula dromedary populations. This study contributes to our understanding of the genetic diversity of Arabian Peninsula dromedary camels. It will help conserve the genetic stock of this species and support the design of breeding programmes for genetic improvement of favorable traits.

Prevalence and Distribution of Weed Flora in Some Major Sugarcane Growing Areas of Southern Guinea Savanna, Nigeria

Weed population survey was undertaken to determine prevalence and distribution of weeds, and asses weed flora shift in major sugarcane growing areas in Southern guinea savanna of Nigeria. The selected areas surveyed are namely Badeggi, Sulti, and Isenyi. The Sugarcane fields were assessed using 1.0 m x 1.0 m quadrat placed randomly at vegetative stage. Weed seedlings in each quadrat were clipped at the soil level and identified according to standards. Result revealed that a total of 38 weed species were recorded. Graminaea and compositae were most abundant and diversified families based on the number of species recorded. Individual weed species shows variation in their abundance, dominance and frequency. The most frequent weed species in the Sugarcane fields irrespective of the soil, climate and crop varieties were Hyptis suaveolens, Paspalum scrobiculata, Kyllinga squamulata, Dactylactenum aegypium and Cynadon dactylon and were considered as the most important species in the surveyed areas. From Similarity indices, variations were observed between locations. Accordingly, areas having similarity indices more than 60 % indicate similarities in weed community. Thus, when devising a weed control strategies same control option should be considered for the location that have similar weed flora and vise-versa.

Beta Diversity along an Elevational Gradient at the Pico da Neblina (Brazil): Is Spider (Arachnida-Araneae) Community Composition Congruent with the Guayana Region Elevational Zonation?

Beta diversity is usually high along elevational gradients. We studied a spider community at the Pico da Neblina (Brazil), an Amazonian mountain which is one of the southern components of the Guayana region. We sampled six elevations and investigated if beta diversity patterns correspond to the elevational division proposed for the region, between lowlands (up to 500 m), uplands (500 m to 1500 m), and highlands (>1500 m). Patterns of dominance increased with elevation along the gradient, especially at the two highest elevations, indicating that changes in composition may be accompanied by changes in species abundance distribution. Beta diversity recorded was very high, but the pattern observed was not in accordance with the elevationaldivision proposed for the region. While the highlands indeed harbored different fauna, the three lowest elevationshad similar species compositions, indicating that the lowlands spider community extends into the uplands zone. Other measures of compositional change, such as similarity indices and species indicator analysis, also support this pattern. Our results, in addition to a revision of the literature, confirm the high diversity and endemism rates of montane spider communities, and we stress the importance of protecting those environments, especially considering the climate crisis.

Diversity of endophytic fungal species from Styrax benzoin found in benzoin-producing locations in North Sumatra

Styrax benzoin is a native tree to Indonesia, particularly in North Sumatra. This plant species produces benzoin resin, which is beneficial for medicinal treatments, hence its commercial value. Endophytic fungi help produce bioactive metabolites and contribute to resin production. However, the diversity of endophytic fungal species from S. benzoin grown in North Sumatra remained largely unexplored. This study aims to determine the distribution and diversity of culturable endophytic fungi from two kemenyan-producing locations in North Sumatra, Simalungun and North Tapanuli, as well as their tree part origin. A total of 7 and 8 endophytic fungal species were obtained from barks, stems, and/or leaves of S. benzoin grown in Simalungun and North Tapanuli, respectively, and identified by internal transcribed spacer sequence analysis. Endophytic fungi from North Tapanuli showed higher diversity, with a Shannon-Wiener index of 2.31 than those from Simalungun (1.95). Morisita-Horn similarity indices for bark-stem, stem-leaf, and bark-leaf were 0.47, 0.08, and 0, respectively, hinting at organ-specificity colonization. This study offers insights into the diversity of endophytic fungi isolated from S. benzoin which may contribute to future improvement of benzoin resin production.

An abundance- and morphology-based similarity index

Classic similarity indices measure community resemblance in terms of incidence (the number of shared species) and abundance (the extent to which the shared species are an equivalently large component of the ecosystem). Here we describe a general method for increasing the amount of information contained in the output of these indices and describe a new “soft” ecological similarity measure (here called “soft Chao-Jaccard similarity”). The new measure quantifies community resemblance in terms of shared species, while accounting for intraspecific variation in abundance and morphology between samples. We demonstrate how our proposed measure can reconstruct short ecological gradients using random samples of taxa, recognizing patterns that are completely missed by classic measures of similarity. To demonstrate the utility of our new index, we reconstruct a morphological gradient driven by river flow velocity using random samples drawn from simulated and real-world data. Results suggest that the new index can be used to recognize complex short ecological gradients in settings where only information about specimens is available. We include open-source R code for calculating the proposed index.

Avian Diversity and Bird-Aircraft Strike Problems in Bahir Dar International Airport, Bahir Dar, Ethiopia

Background Bahir Dar International Airport is known by its rich avifaunal diversity, and bird-aircraft collisions is becoming a serious problem in the area. Study on bird-aircraft strike problems in Bahir Dar International Airport was carried out from February - August 2020. The study area was classified into four habitat types based on its vegetation structures namely: bushland, grassland, wetland, and modified habitat. Point and transect count methods were used to collect data on diversity and abundance of birds. Interviews to people working at the Airport were used to gather information about the incident and prevention of bird-airport strike problems. Shannon-Wiener diversity, Simpson’s similarity indices, ANOVA, and chi-square tests were used for data analysis. Results A total of 80 bird species belonging to 15 orders and 40 families were identified in the present study area. The highest species diversity (H’=3.59) and species evenness (E=0.96) were recorded in the modified habitat during the wet season. The majority of birds in the present study area were uncommon species both during the dry (85.5%) and wet (84.8%) seasons. Birds pose severe threats to aircrafts in Bahir Dar International Airport. Bird-aircraft strike problem has mainly been prevented by expelling of birds using different techniques, which is found to be encouraging from the perspective of conservation of birds. Conclusion Bahir Dar International Airport is rich in its avifauna that requires the Aviation Authority to work in collaborative with different organizations to avoid bird-aircraft strike problems without affecting conservation of birds in the area.

An effective community-based link prediction model for improving accuracy in social networks

Link prediction plays a predominant role in complex network analysis. It indicates to determine the probability of the presence of future links that depends on available information. The existing standard classical similarity indices-based link prediction models considered the neighbour nodes have a similar effect towards link probability. Nevertheless, the common neighbor nodes residing in different communities may vary in real-world networks. In this paper, a novel community information-based link prediction model has been proposed in which every neighboring node’s community information (community centrality) has been considered to predict the link between the given node pair. In the proposed model, the given social network graph can be divided into different communities and community centrality is calculated for every derived community based on degree, closeness, and betweenness basic graph centrality measures. Afterward, the new community centrality-based similarity indices have been introduced to compute the community centralities which are applied to nine existing basic similarity indices. The empirical analysis on 13 real-world social networks datasets manifests that the proposed model yields better prediction accuracy of 97% rather than existing models. Moreover, the proposed model is parallelized efficiently to work on large complex networks using Spark GraphX Big Data-based parallel Graph processing technique and it attains a lesser execution time of 250 seconds.

Improving the analysis of biological ensembles through extended similarity measures

We present new algorithms to classify structural ensembles of macromolecules, based on the recently proposed extended similarity measures. Molecular Dynamics provides a wealth of structural information on systems of biologically interest. As computer power increases we capture larger ensembles and larger conformational transitions between states. Typically, structural clustering provides the statistical mechanics treatment of the system to identify relevant biological states. The key advantage of our approach is that the newly introduced extended similiarity indices reduce the computational complexity of assessing the similarity of a set of structures from O(N2) to O(N). Here we take advantage of this favorable cost to develop several highly efficient techniques, including a linear-scaling algorithm to determine the medoid of a set (which we effectively use to select the most representative structure of a cluster). Moreover, we use our extended similarity indices as a linkage criterion in a novel hierarchical agglomerative clustering algorithm. We apply these new metrics to analyze the ensembles of several systems of biological interest such as folding and binding of macromolecules (peptide, protein, DNA-protein). In particular, we design a new workflow that is capable of identifying the most important conformations contributing to the protein folding process. We show excellent performance in the resulting clusters (surpassing traditional linkage criteria), along with faster performance and an efficient cost-function to identify when to merge clusters.