Estimates Of Diversity Research Articles

Convergence of dominance and neglect in flying insect diversity

Most of arthropod biodiversity is unknown to science. Consequently, it has been unclear whether insect communities around the world are dominated by the same or different taxa. This question can be answered through standardized sampling of biodiversity followed by estimation of species diversity and community composition with DNA barcodes. Here this approach is applied to flying insects sampled by 39 Malaise traps placed in five biogeographic regions, eight countries and numerous habitats (>225,000 specimens belonging to >25,000 species in 458 families). We find that 20 insect families (10 belonging to Diptera) account for >50% of local species diversity regardless of clade age, continent, climatic region and habitat type. Consistent differences in family-level dominance explain two-thirds of variation in community composition despite massive levels of species turnover, with most species (>97%) in the top 20 families encountered at a single site only. Alarmingly, the same families that dominate insect diversity are ‘dark taxa’ in that they suffer from extreme taxonomic neglect, with little signs of increasing activities in recent years. Taxonomic neglect tends to increase with diversity and decrease with body size. Identifying and tackling the diversity of ‘dark taxa’ with scalable techniques emerge as urgent priorities in biodiversity science.

Distribution of genetic diversity of neotropical Biomphalaria (Preston 1910) (Basommatophora: Planorbidae) intermediate hosts for schistosomiasis in Southeast Brazil

IntroductionBiomphalaria glabrata, B. tenagophila, and B. straminea occurrence are crucial for estimating the risk of infectious human schistosomiasis in the neotropics. How different geographic sample strategies influence snail genetic diversity estimations were here investigated for three Schistosoma mansoni hosts.MethodsMitochondrial gene sequences were employed for Cytochrome C Oxidase I (COI), ribosomal RNA (rRNA) 16S, and a dataset with concatenated gene sequences (COI+16S), resulting in an improved scientific hypothesis regarding the geographical distribution of snail species. This study compared the sequences of snails from the Middle Paranapanema (MP) hydrographic basin in a geographically restricted area (inner group) to snails widely distributed across a broad geographical range in São Paulo (outer group), Brazil from 1999 to 2017. DNA sequence polymorphisms and haplotype diversity were estimated using DNAsp software. Haplotype network trees were constructed using a network program. The geographical distribution of the haplotypes was mapped using QGIS. Haplotype variation and distribution were tested for population structure using analysis of molecular variance (AMOVA).Results and discussionThe genetic diversity of B. glabrata, sampled from disconnected but geographically close freshwater collections, was partitioned into two sequence groups. The haplotype network showed that the diversity of B. straminea was more spatially partitioned than in B. tenagophila, which exhibited two population groups. The haplotype distribution pattern for B. tenagophila showed many unique and exclusive haplotypes for all three loci. AMOVA showed that genetic diversity could be high in species inhabiting small geographical areas, and a large river is not a local geographical barrier for snail migration. This study found that the survey dimensions and snail samplings influenced the genetic diversity results obtained by mitochondrial DNA molecular markers.

Integrating spaceborne estimates of structural diversity of habitat into wildlife occupancy models

Vegetation structure is a crucial dimension of wildlife habitat, responsive to global changes in human activities and ecosystem processes. NASA’s recent Global Ecosystem Dynamics Investigation (GEDI) provides an exciting opportunity to explore how spaceborne waveform observations can improve our ability to measure wildlife habitat and advance animal ecology in the Anthropocene. We tested the utility of GEDI data in univariate occupancy models to estimate habitat use in a remote mountain system in central Idaho, USA. We collected data from 49 camera trap stations from two surveys in 2018–2019 and modeled the occupancy for each of seven mammal species representing different trophic levels and feeding strategies: American black bear (Ursus americanus), deer (Odocoileus hemionus), elk (Cervus canadensis), moose (Alces alces), coyote (Canis latrans), wolf (Canis lupus), and mountain lion (Puma concolor). We first derived structural diversity indices (richness, evenness, and divergence) of GEDI-derived canopy height, plant area index, and foliage height diversity to represent different dimensions of vegetation structure. This spatial aggregation is necessary due to gaps in GEDI footprints and parallels commonly used functional diversity metrics applied to biological communities that are calculated using trait probability densities. We measured these indices across three spatial scales that reflect different species movement and habitat selection patterns. We found the structural diversity indices of canopy height, foliage height diversity, and plant area index had the strongest effects on the occupancy of most mammals compared to two-dimensional (2D) variables (e.g. tree cover, normalized difference vegetation index). The spatial extent of these indices also influenced the strength of response, highlighting the importance of selecting a scale large enough to capture sufficient GEDI footprints but small enough to reflect site-level variance. Compared to 2D covariates, our results suggest that GEDI variables allow researchers to generate more detailed inference on the forms of habitat that wildlife use. We discuss the implications of these findings for habitat management and future wildlife research from local to global scales.

Capturing long‐tailed individual tree diversity using an airborne imaging and a multi‐temporal hierarchical model

AbstractMeasuring forest biodiversity using terrestrial surveys is expensive and can only capture common species abundance in large heterogeneous landscapes. In contrast, combining airborne imagery with computer vision can generate individual tree data at the scales of hundreds of thousands of trees. To train computer vision models, ground‐based species labels are combined with airborne reflectance data. Due to the difficulty of finding rare species in a large landscape, many classification models only include the most abundant species, leading to biased predictions at broad scales. For example, if only common species are used to train the model, this assumes that these samples are representative across the entire landscape. Extending classification models to include rare species requires targeted data collection and algorithmic improvements to overcome large data imbalances between dominant and rare taxa. We use a targeted sampling workflow to the Ordway Swisher Biological Station within the US National Ecological Observatory Network (NEON), where traditional forestry plots had identified six canopy tree species with more than 10 individuals at the site. Combining iterative model development with rare species sampling, we extend a training dataset to include 14 species. Using a multi‐temporal hierarchical model, we demonstrate the ability to include species predicted at <1% frequency in landscape without losing performance on the dominant species. The final model has over 75% accuracy for 14 species with improved rare species classification compared to 61% accuracy of a baseline deep learning model. After filtering out dead trees, we generate landscape species maps of individual crowns for over 670 000 individual trees. We find distinct patches of forest composed of rarer species at the full‐site scale, highlighting the importance of capturing species diversity in training data. We estimate the relative abundance of 14 species within the landscape and provide three measures of uncertainty to generate a range of counts for each species. For example, we estimate that the dominant species, Pinus palustris accounts for c. 28% of predicted stems, with models predicting a range of counts between 160 000 and 210 000 individuals. These maps provide the first estimates of canopy tree diversity within a NEON site to include rare species and provide a blueprint for capturing tree diversity using airborne computer vision at broad scales.

Soil filtration-sedimentation improves shelled protist recovery in eukaryotic eDNA surveys.

A large part of the soil protist diversity is missed in metabarcoding studies based on 0.25 g of soil environmental DNA (eDNA) and universal primers due to ca. 80% co-amplification of non-target plants, animals and fungi. To overcome this problem, enrichment of the substrate used for eDNA extraction is an easily implemented option but its effect has not yet been tested. In this study, we evaluated the effect of a 150 μm mesh size filtration and sedimentation method to improve the recovery of protist eDNA, while reducing the co-extraction of plant, animal and fungal eDNA, using a set of contrasted forest and alpine soils from La Réunion, Japan, Spain and Switzerland. Total eukaryotic diversity was estimated by V4 18S rRNA metabarcoding and classical amplicon sequence variant calling. A 2- to 3-fold enrichment in shelled protists (Euglyphida, Arcellinida and Chrysophyceae) was observed at the sample level with the proposed method, with, at the same time, a 2-fold depletion of Fungi and a 3-fold depletion of Embryophyceae. Protist alpha diversity was slightly lower in filtered samples due to reduced coverage in Variosea and Sarcomonadea, but significant differences were observed in only one region. Beta diversity varied mostly between regions and habitats, which explained the same proportion of variance in bulk soil and filtered samples. The increased resolution in soil protist diversity estimates provided by the filtration-sedimentation method is a strong argument in favour of including it in the standard protocol for soil protist eDNA metabarcoding studies.

N‐dimensional hypervolumes in trait‐based ecology: Does occupancy rate matter?

Abstract Many methods for estimating the functional diversity of biological communities rely on measuring geometrical properties of n‐dimensional hypervolumes in a trait space. To date, these properties are calculated from individual hypervolumes or their pairwise combinations. Our capacity to detect functional diversity patterns due to the overlap of multiple hypervolumes is, thus, limited. Here, we propose a new approach for estimating functional diversity from a set of hypervolumes. We rely on the concept of occupancy rate, defined as the mean or absolute number of hypervolumes enclosing a given point in the trait space. Furthermore, we describe a permutation test to identify regions of the trait space in which the occupancy rate of two sets of hypervolumes differs. We illustrate the utility of our approach over existing methods with two examples on aquatic macroinvertebrates. The first example shows how occupancy rate relates to the stability of trait space utilisation due to increased flow intermittency and allows the identification of taxa in regions of the trait space with low occupancy rates. The second example shows how the permutation test based on occupancy rates can detect differences in trait space utilisation due to river morphology variation even with a high degree of overlap among input hypervolumes. Our newly developed approach is particularly suitable in functional diversity analysis when investigating patterns of overlap among multiple hypervolumes. We emphasise the need to consider analyses based on occupancy rate into functional diversity estimation. Read the free Plain Language Summary for this article on the Journal blog.

Global patterns and drivers of genetic diversity among marine habitat‐forming species

AbstractAimIntraspecific genetic diversity is one of the pillars of biodiversity, supporting the resilience and evolutionary potential of populations. Yet, our knowledge regarding the patterns of genetic diversity at macroecological scales, so‐called macrogenetic patterns, remains scarce, particularly in marine species. Marine habitat‐forming (MHF) species are key species in some of the most diverse but also most impacted marine ecosystems, such as coral reefs and marine forests. We characterize the patterns and drivers of genetic diversity in MHF species and provide a macrogenetic baseline, which can be used for conservation planning and for future genetic monitoring programmes.LocationGlobal.Time periodContemporary.Major taxa studiedBryozoans, hexacorals, hydrozoans, octocorals, seagrasses, seaweeds, sponges.MethodsWe analysed a database including genetic diversity estimates based on microsatellites in more than 9,000 georeferenced populations from 140 species, which belong to seven animal and plant taxa. Focusing on expected heterozygosity, we used generalized additive models to test the effect of latitude, taxon, and conservation status. We tested the correlation between the species richness and the genetic diversity.ResultsWe reveal a significant but complex biogeographic pattern characterized by a bimodal latitudinal trend influenced by taxonomy. We also report a positive species genetic diversity correlation at the scale of the ecoregions. The difference in genetic diversity between protected and unprotected areas was not significant.Main conclusionsThe contrasting results between MHF animals and plants suggest that the latitudinal genetic diversity patterns observed in MHF species are idiosyncratic, as reported in terrestrial species. Our results support the existence of shared drivers between genetic and species diversities, which remain to be formally identified. Concerning, these macrogenetic patterns are not aligned from the existing network of marine protected areas. Providing the first macrogenetic baseline in MHF species, this study echoes the call regarding the need to consider genetic diversity in biodiversity assessments and management.

Bee diversity decreases rapidly with time since harvest in intensively managed conifer forests.

Despite widespread concerns about the anthropogenic drivers of global pollinator declines, little information is available about the impacts of land management practices on wild bees outside of agricultural systems, including in forests managed intensively for wood production. We assessed changes in wild bee communities with time since harvest in 60 intensively managed Douglas-fir (Pseudotsuga menziesii) stands across a gradient in stand ages spanning a typical harvest rotation. We measured bee abundance, species richness, and alpha and beta diversity, as well as habitat characteristics (i.e., floral resources, nesting substrates, understory vegetation, and early seral forest in the surrounding landscape) during the spring and summer of 2018 and 2019. We found that bee abundance and species richness declined rapidly with stand age, decreasing by 61% and 48%, respectively, for every 5 years since timber harvest. Asymptotic estimates of Shannon and Simpson diversity were highest in stands 6-10 years post-harvest and lowest after the forest canopy had closed, ~11 years post-harvest. Bee communities in older stands were nested subsets of bee communities found in younger stands, indicating that changes were due to species loss rather than turnover as the stands aged. Bee abundance-but not species richness-was positively associated with floral resource density, and neither metric was associated with floral richness. The amount of early seral forest in the surrounding landscape seemed to enhance bee species richness in older, closed-canopy stands, but otherwise had little effect. Changes in the relative abundance of bee species did not relate to bee functional characteristics such as sociality, diet breadth, or nesting substrate. Our study demonstrates that Douglas-fir plantations develop diverse communities of wild bees shortly after harvest, but those communities erode rapidly over time as forest canopies close. Therefore, stand-scale management activities that prolong the precanopy closure period and enhance floral resources during the initial stage of stand regeneration will provide the greatest opportunity to enhance bee diversity in landscapes dominated by intensively managed conifer forests.

Genomic evaluation of native Walleye in the Appalachian region and the effects of stocking

AbstractObjectiveCreate a quicker and more accurate genetic assignment tool for Walleye Sander vitreus broodstock in the Eastern Highlands region and to quantify genetic diversity of four Walleye populations using next‐generation sequencing.MethodsTo determine the impacts of stocking nonnative Great Lakes strain Walleye on local populations, three Appalachian populations were sampled: two native populations (Rockcastle River, Kentucky, and New River, Virginia) and one population founded from the Great Lakes strain (Tygart Lake, West Virginia). Walleye from Lake Erie were used as a reference for the Great Lakes strain. Utilization of a genotype‐by‐sequencing approach supported genome‐wide estimates of genetic diversity, population structure, and creation of two single‐nucleotide polymorphism assays that can be used to rapidly identify Great Lakes‐strain, native Eastern Highland‐strain, and F1 hybrid Walleye.ResultResults indicate that the four populations we evaluated were genetically distinct from one another and that each population contains varying degrees of genetic differentiation relative to its source population. The stocked Tygart Lake population displayed lower genetic diversity in metrics such as nucleotide diversity (0.172 vs. 0.184), private alleles (4057 vs. 7623), and observed heterozygosity (0.163 vs. 0.204), likely indicative of genetic drift stemming from a founder effect. The two native populations displayed varying levels of genetic diversity. The New River population was found to have a higher ancestry of the Great Lakes strain in their genome than the Rockcastle River population, reflecting the known admixture of New River Walleye following historic stocking of Great Lakes‐derived Walleye. Our results also identified a pure native Eastern Highlands strain population that can be used for future augmentation and restoration of Eastern Highlands Walleye.ConclusionOur results provide a diagnostic single‐nucleotide polymorphism assay to quickly identify Great Lake strain, Eastern Highland strain, and their F1 hybrid for future management efforts and provide key population genetic insights to managers to enhance best management practices.

Diversity, Composition and Abundance of Avian Species of Oxbow Lake and Surrounding Area in Purbasthali, West Bengal, India

Purbasthali oxbow lake is an important habitat for thousands of migratory and resident avian species. This study aimed to determine the current status of avifaunal diversity of Purbasthali oxbow lake and its surrounding area. During this study, diversity, composition and abundance, feeding guilds and the relationship between their habitat preferences and the numbers of individuals were determined. Direct observation, line transects and point count methods were applied for bird surveys for three consecutive years from 2019 to 2022. A total of 145 species of birds were documented, belonging to 19 orders and 49 families. Among the total species, 57 are migratory in nature and 47 are showing declining global trend. Quantitative diversity estimation were performed during the study are the Shannon-Weiner index, Simpson's Diversity Index, Shannon equitability index and relative diversity. Density and diversity of avian species was highest during post-monsoon and lowest in pre monsoon. This indicates the winter assemblages of many migratory birds choose this lake as their feeding and resting grounds.

Cryptomonas pyrenoidifera organellar genomes and estimation of its ITS2 sequence diversity using lineage directed barcode primers

ABSTRACT Cryptomonas is a common metropolitan freshwater microalgal genus that is easily recognizable due to its distinctive asymmetric cellular morphology and swimming pattern. There are currently 71 recognized Cryptomonas species but these can be difficult to identify by cellular morphology alone. This makes estimation of Cryptomonas diversity from environmental samples challenging as it requires culturing of strains followed by sequencing of genetic markers for clear identifications. In this paper we describe the isolation and culture of Cryptomonas pyrenoidifera from a small ephemeral pool in Southwestern Virginia, USA, with an annual recurrent population of this genus. Genomic resources from this isolate, including complete chloroplast and mitochondrial genomes, and nuclear and nucleomorph rRNA regions, were completed and archived. Metabarcoding, using lineage-directed primers designed to amplify the ITS2 region of Cryptomonas, was used to estimate an intra-specific variation of 99.3% for the C. pyrenoidifera ITS2 barcode from this natural environment. Metabarcoding also revealed that at least twelve phylogenetic species were present in this body of water. Our results provide new genomic resources for C. pyrenoidifera and suggest that metabarcoding with the ITS2 marker is a feasible approach to estimating Cryptomonas diversity and identification.

Microbial Diversity Biased Estimation Caused by Intragenomic Heterogeneity and Interspecific Conservation of 16S rRNA Genes.

The 16S rRNA gene has been extensively used as a molecular marker to explore evolutionary relationships and profile microbial composition throughout various environments. Despite its convenience and prevalence, limitations are inevitable. Variable copy numbers, intragenomic heterogeneity, and low taxonomic resolution have caused biases in estimating microbial diversity. Here, analysis of 24,248 complete prokaryotic genomes indicated that the 16S rRNA gene copy number ranged from 1 to 37 in bacteria and 1 to 5 in archaea, and intragenomic heterogeneity was observed in 60% of prokaryotic genomes, most of which were below 1%. The overestimation of microbial diversity caused by intragenomic variation and the underestimation introduced by interspecific conservation were calculated when using full-length or partial 16S rRNA genes. Results showed that, at the 100% threshold, microbial diversity could be overestimated by as much as 156.5% when using the full-length gene. The V4 to V5 region-based analyses introduced the lowest overestimation rate (4.4%) but exhibited slightly lower species resolution than other variable regions under the 97% threshold. For different variable regions, appropriate thresholds rather than the canonical value 97% were proposed for minimizing the risk of splitting a single genome into multiple clusters and lumping together different species into the same cluster. This study has not only updated the 16S rRNA gene copy number and intragenomic variation information for the currently available prokaryotic genomes, but also elucidated the biases in estimating prokaryotic diversity with quantitative data, providing references for choosing amplified regions and clustering thresholds in microbial community surveys. IMPORTANCE Microbial diversity is typically analyzed using marker gene-based methods, of which 16S rRNA gene sequencing is the most widely used approach. However, obtaining an accurate estimation of microbial diversity remains a challenge, due to the intragenomic variation and low taxonomic resolution of 16S rRNA genes. Comprehensive examination of the bias in estimating such prokaryotic diversity using 16S rRNA genes within ever-increasing prokaryotic genomes highlights the importance of the choice of sequencing regions and clustering thresholds based on the specific research objectives.

No (Cambrian) explosion and no (Ordovician) event: A single long-term radiation in the early Palaeozoic

The Cambrian ‘Explosion’, located by many authors between 540 and 520 million years ago (Ma), is considered to be an abrupt appearance in the fossil record of most animal phyla, with a sudden increase of complex morphologies across metazoan groups. In a few recent papers, the Great Ordovician Biodiversification ‘Event’ (GOBE) has similarly been restricted to a single dramatic biodiversification ‘event’ in the Darriwilian Stage of the Middle Ordovician Series, between 470 and 455 Ma, although historically the biodiversification is considered as an aggregation of radiation ‘events’ capturing a large and complex increase of taxonomic diversity of marine invertebrates covering the entire Ordovician. A review of biodiversity curves of marine organisms during the early Palaeozoic, including some based on data in the Paleobiology Database (PBDB) and the Geobiodiversity Database (GBDB), points towards a single, large-scale, long-term early Palaeozoic radiation of life that already started in the late Precambrian. An abrupt ‘explosion’ of diversity in the Cambrian or a significant ‘event’ in the Ordovician are not visible in our biodiversity studies, because they are either regional, or only reflect a single group of organisms. It is evident that the datasets remain incomplete, in particular those for many geographical areas and for several fossil groups, that are not covered by the PBDB and GBDB; also, such areas remain so far poorly or entirely unstudied. Some recently published biodiversity curves have to be considered with care, as the truly global diversity estimates of marine organisms during the early Palaeozoic remain elusive. Here, we argue that published curves of taxonomic richness, which show distinct periods of diversification, cannot sufficiently be disentangled from biases. We therefore question the existence of a distinct Cambrian ‘Explosion’ and global Ordovician ‘Event’ in the global datasets. Both terms, Cambrian ‘Explosion’ and Great Ordovician Biodiversification ‘Event should be used as conceptional terms only. The first represents the appearance of almost all animal phyla during the late Precambrian and early Cambrian, whereas the second term embraces the numerous and complex radiations that occurred during the entire Ordovician.

A second unveiling: Haplotig masking of the eastern oyster genome improves population-level inference.

Genome assembly can be challenging for species that are characterized by high amounts of polymorphism, heterozygosity, and large effective population sizes. High levels of heterozygosity can result in genome mis-assemblies and a larger than expected genome size due to the haplotig versions of a single locus being assembled as separate loci. Here, we describe the first chromosome-level genome for the eastern oyster, Crassostrea virginica. Publicly released and annotated in 2017, the assembly has a scaffold N50 of 54 mb and is over 97.3% complete based on BUSCO analysis. The genome assembly for the eastern oyster is a critical resource for foundational research into molluscan adaptation to a changing environment and for selective breeding for the aquaculture industry. Subsequent resequencing data suggested the presence of haplotigs in the original assembly, and we developed a post hoc method to break up chimeric contigs and mask haplotigs in published heterozygous genomes and evaluated improvements to the accuracy of downstream analysis. Masking haplotigs had a large impact on SNP discovery and estimates of nucleotide diversity and had more subtle and nuanced effects on estimates of heterozygosity, population structure analysis, and outlier detection. We show that haplotig masking can be a powerful tool for improving genomic inference, and we present an open, reproducible resource for the masking of haplotigs in any published genome.

Geodiversity estimate of the Arxan–Chaihe Volcanic Field extending across two geoparks in Inner Mongolia, NE China

Abstract The Arxan–Chaihe Volcanic Field is located SW of the Great Xing'an Range in Inner Mongolia, NE China. This monogenetic volcanic field formed in the Pleistocene, with its latest activity a fissure eruption c. 2000 years ago. Here we present the first geodiversity estimate for the region, applying a method combining the geomorphological and geological elements into a grading system, weighting their rarity, significance and uniqueness. To outline the geomorphological diversity, the geomorphon concept was used alongside a watershed analysis of the theoretical fluvial network of the region. In addition volcanic geomorphological elements were provided. Available geological maps, field surveys and volcano geology classification were utilized for the geological diversity estimates. Geology and geomorphology are the core parameters of the qualitative–quantitative assessment of geodiversity. Geographical Information Systems (GIS) were used for calculations of geomorphological and geological parameters to provide geodiversity estimates for the Arxan–Chaihe Volcanic Field region. The variables used to estimate the geodiversity include geology (rock rareness from a global perspective) and geomorphology (slope variations). In addition we used channel systems and terrain characterization (geomorphon) to describe the morphodiversity of the study area. Our study assessed recent volcanic features and concluded that they have a high geodiversity and elevated geoheritage value. However, the uplifted and structurally complicated old terrains with mature fluvial networks provide high geomorphological diversity to the region, therefore keeping the overall geodiversity score high.

Metabarcoding of soil environmental DNA to estimate plant diversity globally.

Traditional approaches to collecting large-scale biodiversity data pose huge logistical and technical challenges. We aimed to assess how a comparatively simple method based on sequencing environmental DNA (eDNA) characterises global variation in plant diversity and community composition compared with data derived from traditional plant inventory methods. We sequenced a short fragment (P6 loop) of the chloroplast trnL intron from from 325 globally distributed soil samples and compared estimates of diversity and composition with those derived from traditional sources based on empirical (GBIF) or extrapolated plant distribution and diversity data. Large-scale plant diversity and community composition patterns revealed by sequencing eDNA were broadly in accordance with those derived from traditional sources. The success of the eDNA taxonomy assignment, and the overlap of taxon lists between eDNA and GBIF, was greatest at moderate to high latitudes of the northern hemisphere. On average, around half (mean: 51.5% SD 17.6) of local GBIF records were represented in eDNA databases at the species level, depending on the geographic region. eDNA trnL gene sequencing data accurately represent global patterns in plant diversity and composition and thus can provide a basis for large-scale vegetation studies. Important experimental considerations for plant eDNA studies include using a sampling volume and design to maximise the number of taxa detected and optimising the sequencing depth. However, increasing the coverage of reference sequence databases would yield the most significant improvements in the accuracy of taxonomic assignments made using the P6 loop of the trnL region.

Levels, trends, and determinants of cause-of-death diversity in a global perspective: 1990–2019

BackgroundWhile much is known about the leading causes of death (CoD) and how they have evolved over time, much less is known about the diversity of such causes of death. CoD diversity is an important marker of population health heterogeneity that has been largely overlooked in the study of contemporary health dynamics.MethodsWe provide regional and national estimates of CoD diversity from 1990 to 2019. We rely on data from the Global Burden of Disease project, using information on 21 CoD. Results are presented for 204 countries and territories, for women and men separately. CoD diversity is measured with the index of Fractionalization. Results are disaggregated by age and cause of death.ResultsCoD diversity has declined across world regions, except for Latin America and the Caribbean, the region of High-income countries and women in Central Europe, Eastern Europe, and Central Asia. Changes in mortality at adult and older ages have been mostly responsible for CoD diversity dynamics, except for the regions of South Asia and Sub-Saharan Africa, where infant and child mortality still play a non-negligible role. The relationship between CoD diversity, life expectancy, and lifespan inequality is strongly non-monotonic, with turning points differing by sex and indicator. Among longevity vanguard countries, further increases in life expectancy are associated with decreasing lifespan inequality but increasing CoD diversity.ConclusionAs mortality declines, there is no universal pathway toward low CoD diversity, thus casting doubts on the ability of Epidemiological Transition Theory to predict prospective CoD dynamics among high- and middle-mortality countries. Despite the postponement and increasing predictability of the ages at which individuals die, low-mortality populations are composed of an increasingly heterogenous mix of robust and frail individuals, thus increasing the diversity of health profiles among older persons – an issue that could potentially complicate further improvements in longevity.

Effects of seining effort on estimates of fish diversity in a sand-bed river

Changes in species diversity can be an indicator of ecosystem disturbance, impairment, or recovery. Estimating sampling effort needed to adequately represent stream fish assemblages is necessary for informing conservation actions. Increased sampling intensity can increase species detection, affecting the accuracy and precision of biodiversity indices. Seining is commonly used in fish surveys in sand-bottomed streams of the western USA. Here, we sampled 20, 200-m long stream sites each with 40 consecutive seine hauls to determine how increased within-site effort affected measures of species diversity. An average of 10 seine hauls were required to collect 75% of species present at sites in 40 seine hauls, while 18 seine hauls were required to collect 100% of species observed at a site sampled with 40 hauls. Simpson’s diversity index was highly variable when fewer than 7 seine hauls were performed at each site but stabilized when effort was > 15 seine hauls per site. Total dissimilarity and β-diversity components were variable under low sampling effort and also stabilized when effort reached 15 seine hauls per site. However, sampling with more than 18–20 seine hauls per site yielded few additional species. In shallow, sand-bed streams, we suggest sampling with < 5 seine hauls per 200 m of stream can result in unreliable estimates of α-diversity and variation in β-diversity. Increased effort of 15–20 seine hauls per 200 m of stream captured nearly all species present in 40 hauls per 200 m and stabilized species evenness and β-diversity indices.

Multivariate analysis in pearl millet parental lines for diversity estimation and association study of yield contributing traits for genetic improvement of hybrids

Sixty parental lines of pearl millet containing R and B lines were evaluated at ICAR-AICRP on Pearl millet, Mandor, Rajasthan during Kharif-2020 to determine the extent of genetic diversity and association among yield and yield contributing traits. Multivariate techniques such as Principal component analysis (PCA) and cluster analysis were used to analyze the data. The results of PCA revealed four principal components with eigen values greater than one, explaining 33.53%, 18.51%, 14.06% and 8.49% of the total variability, respectively, with a cumulative effect of 74.59%. The study identified the traits such as number of productive tillers, dry fodder yield and plant height as excellent selection indicators that exhibit positive loading toward genetic diversity. Cluster analysis sorted all the parental lines into seven distinct clusters, with cluster VII having the highest number of lines followed by cluster III due to similar ancestry of parental lines. The parental lines J-2591, PPMI-1267 and RIB-109-120-S/19, RIB 3135-18, ICMB 95222, ICMB 94555, ICMB 04999, ICMB 93333 and ICMB 97111 display diversity in both cluster and PCA analyses, indicating the utilization of these lines for hybridization programme to harness heterosis and to select superior segregants in pearl millet.

Genetic Diversity and Spatiotemporal Distribution of SARS-CoV-2 Alpha Variant in India

After the spill to humans, in the evolutionary timeline of SARS-CoV-2, several positively selected variants have emerged. A phylogeographic study on these variants can reveal their spatial and temporal distribution. In December 2020, the alpha variant of the severe acute respiratory syndrome coronavirus (SARS-CoV-2), which has been designated as a variant of concern (VOC) by the WHO, was discovered in the south-eastern United Kingdom (UK). Slowly, it expanded across India, with a considerable number of cases, particularly in North India. This study focuses on determining the prevalence and expansion of the Alpha variants in various parts of India mainly by using phylospatial analysis. The genetic diversity estimation has helped us to understand various evolutionary forces that have shaped the spatial distribution of this variant during its peak. Overall, our study paves the way to understanding the evolution and expansion of a virus variant, which may help to mitigate in the case of any future wave.