Population Diversity Research Articles

Fuel Replenishment Problem of Heterogeneous Fleet in Initiative Distribution Mode

Petrol, a vital energy source for residents’ consumption and economically sustainable operation, generates substantial distribution demand. To reduce distribution costs, we propose a fuel replenishment problem using a heterogeneous fleet based on the initiative distribution mode. In this mode, the distribution center determines both the delivery orders of customers and the distribution plan. We develop a mathematical model with minimal operational costs, including transport, employment, and penalty costs. A Two-stage heuristic algorithm K-IBKA based on time-space clustering is proposed, which also combines the advantages of the butterfly optimization algorithm in quick convergence and hierarchical mutation strategy in population diversity. The results demonstrate that: (1) Heterogeneous truck distribution exhibits better cost advantages compared to homogeneous distribution, reducing total costs by 13.07%; (2) Compared to passive distribution mode, the total cost of the initiative distribution mode is reduced by 11.03% and 41.80%, respectively, through small and large-scale instances. (3) Compared with the unimproved BKA, ALNS, and GA, the total cost calculated by K-IBKA is reduced by 37.68%, 35.30%, and 27.26%, respectively, thus demonstrating the contribution of this work to reducing the cost of petrol distribution and achieving sustainable development of distribution.

Mendelian Randomization Analysis Reveals a Causal Relationship Between Membranous Nephropathy and the Gut Microbiome

Background: With the increasing prevalence of membranous nephropathy (MN), the gut microbiome (GM) is increasingly implicated in its cause, yet the intricate mechanisms remain unclear. Whether changes in the diversity and richness of gut microbial populations among MN patients contribute to disease prevalence is still unanswered, necessitating further exploration into the potential causative link between the GM and MN. Methods: We conducted a comprehensive bidirectional Mendelian randomization (MR) study. We selected 211 bacterial taxa using Genome-wide association study (GWAS) data provided by the MiBioGen consortium, while GWAS data relevant to MN were obtained from ebi-a-GCST010005. The inverse-variance weighted (IVW) method was the primary technique used to delineate the causal relationship between exposures and outcomes. To confirm the robustness of our results, we used additional methods, including MR-Egger, weighted median, simple mode, and weighted mode. Sensitivity analyses included tests for pleiotropy, heterogeneity, and leave-one-out sensitivity to ensure the integrity of our conclusions. Finally, reverse MR analyses were conducted to assess the likelihood of reverse causality. Results: Using various analytical methods, including the IVW approach, MR-Egger, weighted median, simple mode, and weighted mode, our study identified six microbial taxa with a statistically significant causal link to MN, as indicated by p-values less than 0.05. The implicated taxa are Butyrivibrio (OR= 1.25, 95 % CI: 1.001-1.565, P = 0.048), Butyricicoccus (OR = 2.15, 95 % CI: 1.005-4.621, P = 0.048), Catenibacterium (OR = 1.49, 95 % CI: 1.043-2.134, P = 0.028), Ruminiclostridium5 (OR = 1.78, 95 % CI: 1.140-2.763, P = 0.03), RuminococcaceaeUCG003 (OR = 1.78, 95 % CI: 1.140-2.763, P = 0.011) and Bacillales (OR = 1.52, 95 % CI: 1.135-2.025, P = 0.005). Each of these taxa has been established as a risk factor for MN. Notably, Ruminococcaceae UCG-003 and Bacillales were identified as having a bidirectional causal relationship with the disease. Conclusion: Our MR study has revealed a causal link between six microbial taxa and MN, highlighting their potential involvement in the disease's development. These findings represent an initial step into this complex field and underscore the need for more in-depth research.

A bi-subpopulation coevolutionary immune algorithm for multi-objective combinatorial optimization in multi-UAV task allocation

With the development of Unmanned Aerial Vehicle (UAV) technology towards multi-UAV and UAV swarm, multi-UAV cooperative task allocation has more and more influence on the success or failure of UAV missions. From the operational research point of view, such problems belong to high-dimensional combinatorial optimization problems, which makes the solving process face many challenges. One is that the discrete and high-dimensional decision variables make the quality of the solution obtained with acceptable time not guaranteed. Second, the desired solution of real missions often needs to satisfy multiple objective functions, or a set of solutions for decision-making. Therefore, this paper constructs a Multi-objective Combinatorial Optimization in Multi-UAV Task Allocation Problem (MCOTAP) model, and proposes a Bi-subpopulation Coevolutionary Immune Algorithm (BCIA). The two coevolutionary mechanisms improve the lower limit of population diversity, and the evolutionary strategy pool integrating multiple strategies and the adaptive strategy selection mechanism enhance the local search ability in the late evolution. In the experiments, BCIA competes fairly with the mainstream multi-objective evolutionary algorithms (MOEAs), multi-objective immune algorithms (MOIAs) and the recently proposed multi-UAV mission planning algorithms. The experimental results on different test problems (including several multi-objective combinatorial optimization benchmark problems and the proposed MCOTAP model) show that BCIA has superior performance in solving multi-objective combinatorial optimization problems (MCOPs). At the same time, the effectiveness of each design component of BCIA has been comprehensively verified in the ablation study.

Q-Learning-Driven Butterfly Optimization Algorithm for Green Vehicle Routing Problem Considering Customer Preference

This paper proposes a Q-learning-driven butterfly optimization algorithm (QLBOA) by integrating the Q-learning mechanism of reinforcement learning into the butterfly optimization algorithm (BOA). In order to improve the overall optimization ability of the algorithm, enhance the optimization accuracy, and prevent the algorithm from falling into a local optimum, the Gaussian mutation mechanism with dynamic variance was introduced, and the migration mutation mechanism was also used to enhance the population diversity of the algorithm. Eighteen benchmark functions were used to compare the proposed method with five classical metaheuristic algorithms and three BOA variable optimization methods. The QLBOA was used to solve the green vehicle routing problem with time windows considering customer preferences. The influence of decision makers’ subjective preferences and weight factors on fuel consumption, carbon emissions, penalty cost, and total cost are analyzed. Compared with three classical optimization algorithms, the experimental results show that the proposed QLBOA has a generally superior performance.

Genetic diversity atlas of Brucella melitensis strains from Sichuan Province, China

Human brucellosis is a re-emerging disease in Sichuan Province, China. In this study, bacteriology, conventional bio-typing, multi-locus sequence typing (MLST), and multiple locus variable-number tandem repeat analysis (MLVA) were applied to preliminarily characterize the strains in terms of genetic diversity and epidemiological links. A total of 101 Brucella strains were isolated from 16 cities (autonomous prefectures) from 2014 to 2021, and all of the strains were identified as Brucella melitensis bv. 3, suggesting that surveillance should focus on ruminants. MLST analysis identified four STs, namely, ST8 (n = 93), ST39 (n = 6), ST101 (n = 1), and ST118 (n = 1). The latter were new STs, indicating that strains displayed high population diversity. Six MLVA-8, namely, 42, 43, 45, 63, 83, and 114, and eight MLVA-11, namely, 111, 115, 116, 125, 180, 291, 298, and 342, genotypes were identified, demonstrating that all of the strains were from the Eastern Mediterranean lineage, and these strains exhibited a high genotype diversity. MLVA-16 analysis revealed that there was a co-existing transmission pattern, where sporadic cases and multiple outbreak events had a common origin. The dominant STs and MLVA genotypes of strains were epidemic in Northern, China, and 36 MLVA-16 genotypes were shared among strains (n = 51, 50.4%, 51/101) from Sichuan and strains from 22 other provinces. The findings imply that infected animals were introduced from outside the province. The surveillance and control of the disease have become public health challenges. Animal quarantines should be strengthened to prevent the spread of B. melitensis species among adjacent regions.

Cell-to-Cell Natural Transformation Mediated Efficient Plasmid Transfer Between Bacillus Species

Horizontal gene transfer (HGT) plays a pivotal role in bacterial evolution, shaping the genetic diversity of bacterial populations. It can occur through mechanisms such as conjugation, transduction, and natural transformation. Bacillus subtilis, a model Gram-positive bacterium, serves not only as a robust system for studying HGT but also as a versatile organism with established industrial applications, such as producing industrial enzymes, antibiotics, and essential metabolites. In this study, we characterize a novel method of plasmid transfer, termed Cell-to-Cell Natural Transformation for Plasmid Transfer (CTCNT-P), which efficiently facilitates plasmid transfer between naturally competent B. subtilis strains. This method involves co-culturing donor and recipient cells under antibiotic stress and achieves significantly higher efficiency compared to traditional methods such as Spizizen medium or electroporation-mediated transformation. Importantly, we demonstrate that CTCNT-P is applicable for plasmid transformation in wild B. subtilis isolates from natural environments and other Bacillus species, including Bacillus amyloliquefaciens, Bacillus licheniformis, and Bacillus thuringiensis. The simplicity and efficiency of CTCNT-P highlight its strong potential for industrial applications, including genetic modification of wild Bacillus strains for synthetic biology and the development of biocontrol agents.

Multi-Strategy Improved Whale Optimization Algorithm and Its Engineering Applications

The Whale Optimization Algorithm (WOA) is recognized for its simplicity, few control parameters, and effective local optima avoidance. However, it struggles with global search efficiency and slow convergence. This paper introduces the Improved WOA (ImWOA) to overcome these challenges. Initially, ImWOA utilizes a dynamic elastic boundary optimization strategy, which leverages boundary information and the current optimal position to guide solutions that exceed the boundaries back within permissible limits, gradually converging towards the optimal solution. Subsequently, ImWOA integrates an advanced random searching strategy that equilibrates global and local searches by focusing on the current optimal location and the mean position of all individuals. Lastly, a combined mutation mechanism is employed to enhance population diversity, prevent the algorithm from stagnating in local optima, and consequently augment its overall search capability. Performance evaluations on CEC2017 benchmark functions show ImWOA outperforming five metaheuristic algorithms and three WOA variants in optimization accuracy, stability, and convergence speed. ImWOA excelled in 25 out of 29 test functions in 30D and 26 out of 29 in 100D scenarios. Furthermore, its efficacy in addressing complex challenges is corroborated by real-world applications in reducer design, vehicle side impact design, and welded beam design, highlighting its potential utility across various engineering domains.

Retrotransposon-Based Genetic Diversity of Rhodiola rosea L. (Crassulaceae) from Kazakhstan Altai

The analysis of genetic diversity in natural populations of valuable medicinal plant species experiencing overexploitation is a key aspect of their natural conservation strategy. Mobile genetic elements and other interspersed repeats, which are major components of eukaryotic genomes, serve as effective tools for studying plant biodiversity and variability. The genetic diversity of four valuable medicinal plant Rhodiola rosea L. populations was investigated using the inter-repeat amplified PCR method with inter-priming binding sites (iPBSs) for genome profiling. At the interpopulation level, unique amplicons characteristic of specific R. rosea populations were identified. Molecular variance analysis revealed that the biodiversity of R. rosea populations in the Kazakh Altai region is 56% attributed to interpopulation differences and 44% to intrapopulation differences. It was shown that populations located in favorable environmental conditions have greater genetic diversity compared to those in extreme habitats. This study identified a high degree of polymorphism among R. rosea populations using the inter-repeat amplified PCR method. The genetic diversity of the populations ranged from 0.105 to 0.156, with an average heterozygosity of 0.134. The findings provide new insights into the population structure of R. rosea in the Kazakh Altai, enabling the identification of different genotypes, which will significantly complement traditional methods for conserving this valuable medicinal plant.

Genetic Diversity and Population Structure of Macrobrachium nipponense Populations in the Saline–Alkaline Regions of China

The oriental river prawn Macrobrachium nipponense is of great economic importance in China. However, its culture in the saline–alkaline regions is limited. This study used D-loop region sequences to analyze the genetic diversity and population structure across the saline–alkaline regions of China. A total of 264 individuals were successfully sequenced from nine sites, including Daqing in Heilongjiang Province (HLJ), Songyuan in Jilin Province (JL), Ulanhot in the east of inner Mongolia (NMG), Jingtai in Gansu Province (GS), Dongying in Shandong Province (SD), Dongtai in Jiangsu Province (JS), Nanchang in Jiangxi province (JX), Tianjin in mainland China (TJ), and Yinchuan in Ningxia Province (NX). In addition, 89 haplotypes were defined. The haplotype diversity (h) and nucleotide diversity π showed remarkable genetic diversity in the JS, NX, JL, and TJ sites. It was found that the genetic variation within sites was relatively greater. The genetic distance (D) and the pairwise genetic differentiation index (FST) revealed that SD and GS are closely related. The FST values among the nine sites were significant except for the one between SD and HLJ (p-value > 0.05). The cluster analyses and the phylogenetic tree identified two main groups. There is an association among sites by geographic location, and the JS site shows higher diversity. The results of this study provide basic information for the protection and development of M. nipponense resources in the saline–alkaline regions of China.

Genome-wide association studies in a large Korean cohort identify novel quantitative trait loci for 36 traits and illuminate their genetic architectures.

Genome-wide association studies (GWAS) have been predominantly conducted in populations of European ancestry, limiting opportunities for biological discovery in diverse populations. We report GWAS findings from 153,950 individuals across 36 quantitative traits in the Korean Cancer Prevention Study-II (KCPS2) Biobank. We discovered 301 novel genetic loci in KCPS2, including an association between thyroid-stimulating hormone and CD36. Meta-analysis with the Korean Genome and Epidemiology Study, Biobank Japan, Taiwan Biobank, and UK Biobank identified 4,588 loci that were not significant in any contributing GWAS. We describe differences in genetic architectures across these East Asian and European samples. We also highlight East Asian specific associations, including a known pleiotropic missense variant in ALDH2, which fine-mapping identified as a likely causal variant for a diverse set of traits. Our findings provide insights into the genetic architecture of complex traits in East Asian populations and highlight how broadening the population diversity of GWAS samples can aid discovery.

Genomics-Driven Monitoring of Fraxinus latifolia (Oregon Ash) to Inform Conservation and EAB-Resistance Breeding.

Understanding the evolutionary processes underlying range-wide genomic variation is critical to designing effective conservation and restoration strategies. Evaluating the influence of connectivity, demographic change and environmental adaptation for threatened species can be invaluable to proactive conservation of evolutionary potential. In this study, we assessed genomic variation across the range of Fraxinus latifolia, a foundational riparian tree native to western North America recently exposed to the invasive emerald ash borer (Agrilus planipennis; EAB). Over 1000 individuals from 61 populations were sequenced using reduced representation (ddRAD-seq) across the species' range. Strong population structure was evident along a latitudinal gradient, with population connectivity largely maintained along central valley river systems, and a centre of genetic diversity coinciding with major river systems central to the species' range. Despite evidence of connectivity, estimates of nucleotide diversity and effective population size were low across all populations, suggesting the patchy distribution of F. latifolia populations may impact its long-term evolutionary potential. Range-wide estimates of genomic offset, which indicate genomic change required to adjust to future climate projections, were greatest in the eastern and lowest in the southern portions of the species' range, suggesting the regional distribution of genomic variation may impact evolutionary potential longer-term. To preserve evolutionary capacity across populations needed for the development of breeding and restoration programmes, prioritising conservation of range-wide genomic diversity will provide a foundation for long-term species management.

Inhibition of the invasive plant Ambrosia trifida by Sigesbeckia glabrescens extracts.

Ambrosia trifida is an invasive weed that destroys the local ecological environment, and causes a reduction in population diversity and grassland decline. The evolution of herbicide resistance has also increased the difficulty of managing A. trifida, so interspecific plant competition based on allelopathy has been used as an effective and sustainable ecological alternative. However, how to control A. trifida through interspecific competition and the underlying mechanisms are unclear. Here, we found that extracts from both the roots and leaves of the medicinal plant Sigesbeckia glabrescens suppressed the growth of A. trifida by reducing the plant height and biomass. The decrease in biomass may be explained by disruption of carbon and nitrogen metabolism. These disruptions are due to a significant decrease in the expression of genes related to nitrate absorption and transport in roots and a significant decrease in the expression of key genes related to photosynthesis and carbon fixation. Consequently, genes involved in sucrose synthesis are downregulated. In addition, increases in H2O2 content and respiratory burst oxidase homologue (RbohD) gene expression suggested that A. trifida underwent oxidative stress caused by reactive oxygen species (ROS) bursts, resulting in apoptosis due to the significant upregulation of key genes associated with apoptotic pathways. Furthermore, we identified three main allelochemicals, coumarin, ferulic acid, and 5-aminolevulinic acid (5-ALA), in S. glabrescens extracts and revealed that the combination of these three compounds could suppress the growth of A. trifida seedlings. The phenotypes and transcriptome profiles of the seedlings treated with these chemicals were the same as those of the seedlings treated with the S. glabrescens extracts. Taken together, the results of this study revealed the mechanism underlying the toxic effects of S. glabrescens on A. trifida, providing a theoretical basis for the use of interspecific plant competition for invasive weed control and further application of S. glabrescens allelochemicals in weed management.

Microsatellite and mitochondrial DNA D-loop based analysis of genetic diversity in captive populations of Crocodylus siamensis in China

Reintroduction of threatened species is a common strategy used to mitigate population decline and reduce the risk of extinction. In order to assess the success of such reintroduction programs, it is critical to monitor the demographic and genetic features of reintroduced populations. In this work, we conducted a genetic assessment of the Critically Endangered crocodile species Crocodylus siamensis to determine the genetic diversity, utilising both microsatellite markers and mitochondrial DNA D-loop region. The genetic analysis revealed a moderate level of genetic diversity within the sampled populations, as indicated by the microsatellite markers (Ho = 0.505 ± 0.080; He = 0.297 ± 0.091) and mtDNA D-loop (hd = 0.622 ± 0.061; Pi = 0.01294 ± 0.00041). Notably, 22 distinct haplotypes were observed. Additionally, we identified evidence of hybridisation that might have occurred between C. siamensis and Crocodylus niloticus raising concerns about the potential compromise of the species' genetic integrity. This study represents the first genetic assessment of captive bred C. siamensis populations in China, encompassing both microsatellite and mtDNA D-loop analyses. To ensure preservation of C. siamensis, we recommend identifying and excluding hybrid individuals from conservation programmes. Our findings support the feasibility of implementing breeding and captive management plans for C. siamensis, providing a solid theoretical basis for their reintroduction and captive breeding to safeguard and augment the population of this Critically Endangered freshwater crocodile. This research marks the initial step towards establishing a scientifically sound source population for the conservation of C. siamensis in China. Keywords: protection, reintroduction genotype, haplotypic diversity, nucleotide diversity

Species-Specific Traits Shape Genetic Diversity During an Expansion-Contraction Cycle and Bias Demographic History Reconstruction.

Species ranges are dynamic, experiencing expansions, contractions or shifts in response to habitat changes driven by extrinsic factors such as climate change or human activities. While existing research examines the genetic consequences of spatial processes, few studies integrate species-specific traits to analyse how habitat changes affect co-existing species. In this study, we address this gap by investigating how genetic diversity patterns vary among species with different traits (such as generation length, population density and dispersal) experiencing similar habitat changes. Using spatial simulations and a simpler panmictic population model, we investigate the temporal genetic diversity in refugium populations undergoing range expansion of their habitat, followed by stationary and contraction periods. By varying habitat contraction speed and species traits, we identified three distinct temporal dynamics of genetic diversity during contraction: (i) a decrease in genetic diversity, (ii) an initial increase followed by a decrease and (iii) a continuous increase throughout the contraction period. We show that genetic diversity trajectories during population decline can be predicted by comparing sampled population diversity to equilibrium values expected under expanded and contracted habitat ranges. Our study also challenges the belief that high genetic diversity in a refugium population is due to a recent and rapid habitat loss. Instead, we found contrasting effects of contraction speed on genetic diversity depending on the interaction between species-specific traits and the dynamics of habitat change. Finally, using simulated genetic data, we found that demographic histories inferred from effective population size estimates may vary across species, even when they experience similar habitat changes.

Profiling lateral gene transfer events in the human microbiome using WAAFLE.

Lateral gene transfer (LGT), also known as horizontal gene transfer, facilitates genomic diversification in microbial populations. While previous work has surveyed LGT in human-associated microbial isolate genomes, the landscape of LGT arising in personal microbiomes is not well understood, as there are no widely adopted methods to characterize LGT from complex communities. Here we developed, benchmarked and validated a computational algorithm (WAAFLE or Workflow to Annotate Assemblies and Find LGT Events) to profile LGT from assembled metagenomes. WAAFLE prioritizes specificity while maintaining high sensitivity for intergenus LGT. Applying WAAFLE to >2,000 human metagenomes from diverse body sites, we identified >100,000 high-confidence previously uncharacterized LGT (~2 per microbial genome-equivalent). These were enriched for mobile elements, as well as restriction-modification functions associated with the destruction of foreign DNA. LGT frequency was influenced by biogeography, phylogenetic similarity of involved pairs (for example, Fusobacterium periodonticum and F. nucleatum) and donor abundance. These forces manifest as networks in which hub taxa donate unequally with phylogenetic neighbours. Our findings suggest that human microbiome LGT may be more ubiquitous than previously described.

Parallel genetic adaptation amid a background of changing effective population sizes in divergent yellow perch (Perca flavescens) populations.

Aquatic ecosystems are highly dynamic environments vulnerable to natural and anthropogenic disturbances. High-economic-value fisheries are one of many ecosystem services affected by these disturbances, and it is critical to accurately characterize the genetic diversity and effective population sizes of valuable fish stocks through time. We used genome-wide data to reconstruct the demographic histories of economically important yellow perch (Perca flavescens) populations. In two isolated and genetically divergent populations, we provide independent evidence for simultaneous increases in effective population sizes over both historic and contemporary time scales including negative genome-wide estimates of Tajima's D, 3.1 times more single nucleotide polymorphisms than adjacent populations, and contemporary effective population sizes that have increased 10- and 47-fold from their minimum, respectively. The excess of segregating sites and negative Tajima's D values probably arose from mutations accompanying historic population expansions with insufficient time for purifying selection, whereas linkage disequilibrium-based estimates of Ne also suggest contemporary increases that may have been driven by reduced fishing pressure or environmental remediation. We also identified parallel, genetic adaptation to reduced visual clarity in the same two habitats. These results suggest that the synchrony of key ecological and evolutionary processes can drive parallel demographic and evolutionary trajectories across independent populations.

Principal component and cluster analysis in grain appearance, milling and cooking quality traits in rice (Oryza sativa L.)

Rice grain quality characteristics such as grain appearance, milling, cooking, and eating parameters are quite complex phenotypic attributes. The rice grain quality is governed principally by the genetic makeup of the rice variety, the biochemical composition of rice grain, and the bio-physical environment where it is produced or grown. In addition to this grain quality is also affected by the moisture conditions of rice gains at the time of processing, the equipment by which rice is processed to a finished product, and to some extent how the product is stored. It is necessary to improve grain quality traits in rice to meet the consumers' demand for premium quality rice, reduce loss at the time of milling, increase production efficiency by increasing total head rice yield, and give more profit to producers and traders of the rice supply chain. This investigation aimed to evaluate the extent of diversity present in the population comprising one hundred-five genotypes for fifteen-grain quality attributes through principal component analysis and cluster analysis. The principal component analysis identified five principal components, (PCs) accounting for 73.10% of the sum total of variations perceived between the rice genotypes of the population. From the biplot analysis of PC1 and PC2, as the two axes of a 2-dimensional coordinate plain, it was found that the grain quality traits, kernel L/B ratio, water uptake, gel consistency, head rice recovery, kernel length after cooking, thousand-grain weight, milling percentage, and kernel length have a greater contribution to the total diversity of the rice population. By using UPGMA cluster analysis, all 105 genotypes of the population were classified into five discrete groups or clusters. The observed inter-cluster distance was largest between the clusters of cluster I and cluster III (149.22), the next largest inter-cluster distance was between cluster II and cluster IV (128.35), and that of cluster III and cluster IV was (109.61) which indicated significant genetic divergence among the genotypes. A larger inter-cluster distance between the clusters suggests the possibility of harnessing heterosis for the quality traits under study as they possess higher mean values for quality attributes with corresponding greater diversity.

CULTURAL COMPETENCE TRAINING AND EVALUATION AMONG NURSING HOME STAFF

Abstract The dynamics of cultural and ethnic identity in healthcare has become more salient in the United States due to the growing population diversity. In particular, significant number of nursing home staff are from diverse sociocultural groups, which necessitates cultural competency in nursing homes in order to provide quality care to older adults. Cultural competency in nursing homes is usually analyzed in terms of the interplay between staff members and the older adults, but this study investigated the relational cultural competency between staff members in the workplace. First, cultural competency training on promoting inclusion and respecting diversity, and communication/teamwork was provided to staff members working in a nursing home in Washington, D.C. To evaluate the level of cultural competency post-training, a semi-structured in-depth interview was conducted with 16 nursing home staff. Participants were purposefully selected to capture variation in cultural identity and ethnicity, national origin, work experience and position at the organization. The interviews were conducted individually and audio-recorded after consent was obtained. The audio files were transcribed verbatim and analyzed with the aid of Nvivo12. Findings show that the training was positively perceived as having impacted their outlook of culture and identity in the workplace. Most of the participants were comfortable with working with individuals from different cultures and identified techniques used in communicating when there are language barriers, including utilizing interpreters and translation tools. Participants recommended that organization’s leadership should create more opportunities for intercultural exchange among staff members through potlucks, and recognizing national holidays of staff members.

Biodiversity, spatial, and seasonal distribution of the zooplankton community in semi-intensive fish farms in Rondônia state, Brazil

In this study we determined the spatial and seasonal distribution (rainfall and drought) of the zooplankton community in 30 fish farms in the microregions of Vale do Jamari and Central-East of Rondônia. The experiment was organized in a completely randomized factorial scheme. The species were considered in composition, richness, frequency of occurrence, relative abundance and diversity indices (H’, J and S). There were records of greater richness of Copepoda (550 to 1214), Ostracoda (360 to 989.6), Rotifera (71 to 431) and Cladocera (344 to 990). In the Jamari Valley, the most abundant species (Individuals per 100 mL) were Ostracoda (323), Copepoda (160) and Rotifera (111). In the Center- East, they were Copepoda (287), Rotifera (108) and Ostracoda (106). In the two microregions there were variations in the seasonal distribution, except for the populations of the phylum Cloadocera. The diversity indices differed, registering a greater diversity of populations of Ostracoda in the Jamari Valley and Copepoda in the Center-East and in the rainy season.

First-in-Family students’ roots and routes into higher education: Familial dynamics as drivers for breaking intergenerational cycles of educational attainment

This study fills significant gaps in knowledge around how familial dynamics shape First-in-Family students’ educational pathways, inform how they engage with the higher education setting, and drive them to break intergenerational cycles of educational attainment. Twenty-seven interviews with First-in-Family students in four public universities in Austria revealed three drivers: aligning with familial expectations, leaving one’s social milieu and emancipation from familial orientations. The paper argues that these drivers inform not only the why but also the how they organise their social contacts during their university education (e.g. different forms of engagement and connection to their family milieu and community outside of university). The findings suggest that we need to take these subjective dimensions into account if we aim to improve targeted support and to enhance the quality of learning experiences for all higher education students. Furthermore, we need to acknowledge that a growing diversity in the student population might also mean a greater diversity in the reasons to pursue a higher education, which should be accompanied with critical reflections on how the needs of these students can be met in the post-pandemic university to foster student retention and success.