Species Abundance Distribution Research Articles

Vertical distribution of arthropod assemblages in native and exotic forests of Terceira Island (Azores, Portugal).

In the summer of 2024, a study was conducted on Terceira Island in the Azores Archipelago, Portugal, aiming to characterise the vertical diversity and spatial distribution patterns of arthropods within native and exotic forest ecosystems. This study forms part of a broader research initiative designed to investigate how alterations in habitat structure influence the complexity and stability of arthropod food webs in Azorean forest habitats. By systematically sampling arthropods across multiple vertical strata -from forest floor to canopy the study aimed to generate detailed insights into the ecological dynamics governing biodiversity patterns and species interactions. Results from this monitoring will contribute significantly to understanding the ecological impacts of forest composition and management strategies, ultimately providing information for conservation planning and habitat restoration efforts aimed at preserving arthropod diversity and ecological resilience in island ecosystems. The current dataset comprises identified terrestrial arthropods collected using SLAM (Sea, Land and Air Malaise) traps and Pitfall traps across diverse forest strata. A total of 32,797 specimens were collected from the Arachnida, Diplopoda, Chilopoda and Insecta classes. A total of 18,372 (56%) were identified at the species or subspecies level, including 12,745 adults and 5,627 juveniles for taxa, such as Araneae and Hemiptera due to the availability of reliable identification methods. The resulting dataset encompasses 150 species and 11 subspecies, distributed across 21 orders, 81 families and 148 genera.Hemiptera emerged as the most abundant identified order, with a total of 7,697 recorded specimens and Coleoptera stood as the most taxonomically diverse, encompassing 19 distinct families and 50 species and sub-species. The ten most abundant species comprise predominantly endemic and native non-endemic species, with two exotic species detected amongst them.This comprehensive dataset serves as a significant augmentation of the existing baseline knowledge concerning the diversity of Azorean arthropods, thereby facilitating the formulation of future long-term ecological comparisons. It offers valuable insights into the vertical distribution of species abundance within both native and exotic forests of the Azores.

Dominant species predict plant richness and biomass in global grasslands.

The bidirectional relationship between plant species richness and community biomass is often variable and poorly resolved in natural grassland ecosystems, impeding progress in predicting impacts of environmental changes. Most biological communities have long-tailed species abundance distributions (for example, biomass, cover, number of individuals), a general property that may provide predictive power for species richness and community biomass. Here we show mathematical relationships between community characteristics and the abundance of dominant species arising from long-tailed distributions and test these predictions using observational and experimental data from 76 grassland sites across 6 continents. We find that community biomass provides little predictive ability for community richness, consistent with previous findings. By contrast, the relative abundance of dominant species quantitatively predicts species richness, whereas their absolute abundance quantitatively predicts community biomass under both ambient and altered environmental conditions, as expected mathematically. These results are robust to the type of abundance measure used. Three types of simulated data further show the generality of these results. Our integrative framework, arising from a few dominant species and mathematical properties of species abundance distributions, fills a persistent gap in our ability to predict community richness and biomass under ambient and anthropogenically altered conditions.

Ecosystem assessment to support innovative advancements in soil sustainability in the major land resource areas of Mississippi through geochemical and metagenomics studies.

In the present study, the ecosystem of Roebuck (RF) and Nesbit blueberry plantation (NBP) farms in Mississippi state, USA that differed by type of fertilizer treatment was assessed using soil samples through geophysical-chemical parameters and metagenomics studies. Soil geophysical-chemical parameters such as pH, moisture, organic content, nutrients, and toxic metal concentrations were measured. Metagenomic analysis was performed to identify the bacterial communities in the soil samples. The results revealed that the pH of the NBP farm (organic fertilizer) was lower than that of the RF farm (chemical fertilizer). The NBP soil samples exhibited higher moisture and organic contents than the RF soil samples. The tested heavy metal concentrations in both farm soil samples were within the limits recommended by the EPA (United States Environmental Protection Agency). Different concentrations of nutrients were observed between these two farms soil samples. RF soil indicated greater species richness and a more balanced distribution of species abundances. Proteobacteria, Bacteroidota, and Actinobacteriota were the most abundant phyla observed in RF soil, whereas Proteobacteria, Acidobacteriota, and Actinobacteriota were the most abundant phyla observed in NBP soil. This study clearly demonstrated the effects of fertilizer type on the soil through variations in geophysical-chemical parameters, which subsequently changed the microbial communities. This study suggests that organic fertilizer application could be an effective method for sustainable soil quality as the organic fertilized soils exhibited higher moisture and organic content that promotes plant growth.

Current Affairs: Examining the Use of Environmental DNA for Relative Abundance Monitoring in a Dynamic Tidal Habitat

ABSTRACTAssessing the abundance and spatiotemporal distribution of fish species is crucial for informing sustainable fishing practices and developing effective conservation management plans. Recently, environmental DNA (eDNA) has emerged as a promising tool for estimating not only marine species richness but also species abundance, with several studies demonstrating a positive correlation between eDNA concentration and species abundance. Consequently, eDNA surveys not only enhance the monitoring of species requiring conservation attention but may also serve as a method to quantify relative abundance, a critical indicator of ecosystem health. This study investigates the feasibility of using eDNA metabarcoding to estimate relative abundance of marine species in a tidal environment, using Sussex Bay, UK, as a case study. We compared eDNA relative abundance indices, estimated by the metabarcoding method, using two different primer pairs and found strong positive correlations between the results from each primer. Additionally, we evaluated the relationship between relative abundance estimates derived from eDNA metabarcoding index and those obtained from Baited Remote Underwater Video (BRUV) counts. Out of 14 species, only one significant positive correlation was found between eDNA index and BRUV counts. The BRUV surveys detected fewer species overall compared to eDNA, leading to a higher number of zero counts for several species, which may explain the lack of statistically significant relationships. This indicates that eDNA index and BRUV counts do not strongly correlate in dynamic marine environments, highlighting the differences between these survey methods. This study also estimated that eDNA can be detected at least 2–8 km from its assumed source in a marine tidal environment, with an average minimum travel speed of 1.8 km/h. Our findings illustrate the effectiveness of eDNA metabarcoding as a nondestructive biomonitoring method, while also highlighting its limitations as well as the challenges in comparing relative abundances of different methods in tidal environments.

The powerbend distribution provides a unified model for the species abundance distribution across animals, plants and microbes

Remarkably, almost every ecological community investigated to date is composed of many rare species and a few abundant species. While the precise nature of this species abundance distribution is believed to reflect fundamental ecological principles underlying community assembly, ecologists have yet to identify a single model that comprehensively explains all species abundance distributions. Recent studies using large datasets have suggested that the logseries distribution best describes animal and plant communities, while the Poisson lognormal distribution is the best model for microbes, thereby challenging the notion of a unifying species abundance distribution model across the tree of life. Here, using a large dataset of ~30,000 globally distributed communities spanning animals, plants and microbes from diverse environments, we show that the powerbend distribution, predicted by a maximum information entropy-based theory of ecology, emerges as a unifying model that accurately captures species abundance distributions of all life forms, habitats and abundance scales. Our findings challenge the notion of pure neutrality, suggesting instead that community assembly is driven by a combination of random fluctuations and deterministic mechanisms shaped by interspecific trait variation.

Wildflower Strips Increase Aculeate Pollinator Diversity but Not Abundance in Agricultural Landscapes with Rapeseed in Crop Rotations

The decline of pollinators in agricultural environments poses a significant threat to pollination ecosystem services. Wildflower strips are proposed as a strategy to support pollinator populations and enhance their species richness and diversity. We investigated the efficacy of flowering plant mixture in maintaining aculeate pollinator diversity (wild bees, predatory wasps, and their kleptoparasites) within intensively managed agricultural environments where rapeseed is a common rotational crop. Over four years, pollinators were counted five times per season using 250 m transect walks. Our results demonstrated that the diversity and the evenness of species abundance distribution of aculeate pollinators were higher in the sown wildflower strips, whereas mean abundance per transect was greater in the remnants of semi-natural grassland. The low diversity and evenness within the aculeate pollinator assemblage of the semi-natural habitat were attributed to the dominance of the sweat bee Lasioglossum pauxillum, which thrived on mass-flowering rapeseed and concentrated in the flowering grassland fragments after the rapeseed harvest. We conclude that wildflower strips enriched with sown flowering plant mixtures effectively enhance pollinator diversity. Furthermore, both wildflower strips and preserved patches of unmanaged or minimally managed semi-natural grassland habitats can essentially contribute to maintaining pollination ecosystem services within intensive agricultural environments.

Unveiling the Forensic Potential of Oral and Nasal Microbiota in Post-Mortem Interval Estimation.

Microbiota have emerged as a promising tool for estimating the post-mortem interval (PMI) in forensic investigations. The role of oral and nasal microbiota in cadaver decomposition is crucial; however, their distribution across human cadavers at different PMIs remains underexplored. In this study, we collected 88 swab samples from the oral and nasal cavities of 10 healthy volunteers and 34 human cadavers. Using 16S rRNA gene sequencing, we conducted comprehensive analyses of the alpha diversity, beta diversity, and relative abundance distribution to characterize the microbial communities in both healthy individuals and cadavers at varying PMIs and under different freezing conditions. Random forest models identified Firmicutes, Proteobacteria, Bacteroidota, Actinobacteriota, and Fusobacteriota as potential PMI-associated biomarkers at the phylum level for both the oral and nasal groups, along with genus-level biomarkers specific to each group. These biomarkers exhibited nonlinear changes over increasing PMI, with turning points observed on days 5, 12, and 22. The random forest inference models demonstrated that oral biomarkers at both the genus and phylum levels achieved the lowest mean absolute error (MAE) values in the training dataset (MAE = 2.16 days) and the testing dataset (MAE = 5.14 days). Additionally, freezing had minimal impact on the overall phylum-level microbial composition, although it did affect the relative abundance of certain phyla. At the genus level, significant differences in microbial biomarkers were observed between frozen and unfrozen cadavers, with the oral group showing greater stability compared to the nasal group. These findings suggest that the influence of freezing should be considered when using genus-level microbial data to estimate PMIs. Overall, our results highlight the potential of oral and nasal microbiota as robust tools for PMI estimation and emphasize the need for further research to refine predictive models and explore the environmental factors shaping microbial dynamics.

Use of cover data to model species abundance distributions through continuous probability functions

Species abundance distribution (SAD) models describe the abundances of the species within ecological communities. SAD modelling has been developed using frequency distributions that require the use of count data (number of individuals). However, many organisms, such as most plants, cannot be counted. Instead, abundance is estimated using cover values. We show here how SAD approaches conceived for modelling frequency distributions based on counts can be modified to deal with continuous distributions and provide an application using relative plant cover as a continuous measure of abundance. We applied several SAD models using continuous probability functions to investigate how plant SADs changed along a wide (2,500 m) elevational gradient in the Alborz Mountains (Iran). We found that most communities were adequately fitted by the Weibull distribution, whose parameters changed along the gradient in response to the interplay between biotic and environmental filtering processes. The use of continuous probability functions in SAD modelling should be encouraged in research dealing with plant communities and other organisms for which counting individuals is theoretically or practically impossible.

Resampling a carrion beetle fauna after 40 years (Coleoptera, Staphylinidae, Silphinae, and Leiodidae, Cholevinae).

From 29 May until 5 June 1982, the first author placed baited pitfall traps to sample the Staphylinidae, Silphinae and Leiodidae, Cholevinae (Coleoptera) fauna in a mixed forest in the Netherlands. Exactly 40 years later (29 May until 5 June 2022), as a project on insect declines with high school students at a nearby school, a resampling was carried out. We report the silphine and cholevine specimens recorded both in 1982 and 2022. We found that total species richness and biomass had not noticeably changed, but there were some distinct appearances and disappearances of species. In addition, the species abundance distribution has become more skewed in favour of locally common species, such as Sciodrepoideswatsoni and Fissocatopswesti. We discuss our results in the context of insect declines worldwide.

Should Regional Species Loss Be Faster or Slower Than Local Loss? It Depends on Density-Dependent Rate of Death.

Assessment of the rate of species loss, which we also label extinction, is an urgent task. However, the rate depends on spatial grain (average area A) over which it is assessed-local species loss can be, on average, faster or slower than regional or global loss. Ecological mechanisms behind this discrepancy are unclear. We propose that the relationship between extinction rate and A is driven by a classical ecological phenomenon: density-dependent mortality. Specifically, we hypothesize that (i) when per-individual probability of death (P death) decreases with the number of individuals in a region N (i.e., negative density dependence), per-species extinction rate (Px) should be high at regional grains and low locally. (ii) In contrast, when P death increases with N (i.e., positive density dependence), Px should be low regionally but high locally. (iii) Total counts of extinct species (Ex) should follow a more complex relationship with A, as they also depend on drivers of the species-area relationship (SAR) prior to extinctions, such as intraspecific aggregation, species pools, and species-abundance distributions. We tested these hypotheses using simulation experiments, the first based on point patterns and the second on a system of generalized Lotka-Volterra equations. In both experiments, we used a single continuous parameter that moved between the negative, zero, and positive relationship between P death and N. We found support for our hypotheses, but only when regional species-abundance distributions were uneven enough to provide sufficiently rare or common species for density dependence to act on. In all, we have theoretically demonstrated a mechanism behind different rates of biodiversity change at different spatial grains, which has been observed in empirical data.

Design of Multiplexed, Live Cell Imaging Experiments Using Excitation Scan-Based Hyperspectral Imaging Microscopy.

In the last 20 years there have been remarkable advances in our ability to track movement and activities of proteins within cells. This is largely due to improved chemical probes and fluorescent proteins, and technical advances in microscopy. A remaining challenge is real-time multiplexed imaging. Excitation scan-based hyperspectral imaging (HSI) approaches are well suited for multiplexed imaging. However, excitation scan-based HSI has not been widely adopted, in part due to a lack of protocols for selection of combinations of fluorescent labels and proteins, and determining the range of excitation wavelengths and dichroic filters. Here we address this issue by outlining considerations for the selection of multiple labels for excitation scan-based HSI. HEK-293 cells were transfected with fluorescent protein constructs and/or loaded with dyes or labels for measurement of excitation spectra. Cells were imaged using a custom-built excitation scan-based HSI microscope that utilizes tunable thin film filters to filter fluorescence excitation from 360 nm to 550 nm in 5 nm increments in conjunction with a long pass dichroic filter and long pass emission filter. We observed that we can effectively quantify the relative abundance and spatial distributions of NucBlue, AlexaFluor 488, AlexaFluor 514, and AlexaFluor 555, Cal520, Cal590, as well as the fluorescent proteins GFP, Cerulean, Turquoise, Venus, tdTomato, and mCherry, individually and in combinations. We are currently assessing the spectra of these fluorophores using excitation scan-based HSI microscope systems.

Environmental assessment of Sungai Perai, Penang, by using zooplankton as a bio-indicator

Zooplankton are crucial as bioindicators and aid in determining the level of water contamination. The effects of environmental disturbances can be detected through changes in species composition, abundance, and body size distribution of zooplankton. Using a plankton net, samples were collected from eight sampling sites during the neap and spring tides of January, February, April and May 2024. A total of 67 zooplankton taxa were recorded, including 44 Rotifera, 12 Cladocera, and 11 Copepoda. The predominant species viz: Brachionus calyciflorus, Anuraeopsis fissa, Filnia longiseta, Filinia terminalis, Moina sp, Calanus sp, Cyclops sp, Brachionus angularis, Brachionus urceolaris, Argonotholca foliaceae, Asplachna sp, Testudinella sp, and Adineta vaga were recorded in all the sampling sites in the river. The abundance of these species in any water body indicates a high degree of eutrophication in the river. Moina, Daphnia, and Cyclops also indicate the intrusion of organic matter and nutrients from runoffs and drains into the river. The Shannon H’ are 1.37, 1.34, 1.27, 1.33, 1.28, 1.36, 1.42, and 1.31 for sites A, B, C, D, E, F, G, and H respectively indicating the presence of contaminants in the river. The community structure of the zooplankton of Sungai Perai is influenced by factors such as tidal events and water quality parameters such as nutrients, dissolved oxygen, and temperature. This study demonstrated that zooplankton could indicate the condition of the Sungai Perai through changes in its community structure, distribution pattern, and abundance of vulnerable genera and species.

Potential resilience of forest birds in the Appalachian Mountains to future climate change during the breeding season

ContextGlobal climate change is predicted to cause long-term changes in bird distributions and populations. Although previous studies often prioritized understanding avian responses to shifting climate conditions, recent efforts increasingly incorporate landscape change as an additional factor.ObjectivesWe evaluated current and potential future effects of both climate and landscape change on the breeding distributions and relative abundance of 14 forest songbird species in the Appalachian Mountains.MethodsFor each species, we compiled route-level total count data from 322 North American Breeding Bird Survey routes that were sampled between 1997–2017. Using Bayesian modeling techniques, we determined the relative influence of temperature, precipitation, and proportions of land cover types on route-level annual total species counts. We then projected future changes in relative abundance, regional occupancy, and distribution of relative abundance from 2000 to 2100, based on multiple greenhouse gas emission scenarios.ResultsOur models showed that proportions of land cover types tended to be more influential and had higher effect sizes than climate variables on forest songbird relative abundance during the breeding season. In our future predictions, most changes in relative abundance and regional occupancy were modest.ConclusionsThese results indicated that net projected impacts of climate change on the 14 focal forest songbird species during the breeding season were minimal at a broad scale in the Appalachian Mountains. Instead, land use changes that result in reduced forest cover and increased urban cover may pose a more immediate threat than climate change to forest songbirds breeding in this region.

Experimental evidence quantifying effects of nocturnal light conditions on predation levels by riverine predators on larval prey

Larval fish and aquatic macroinvertebrates are believed to be at greater predation risk by visual riverine predators during periods of higher lunar illumination. Predation rates may also be affected by the taxonomic composition and relative abundance of alternative co-distributed prey. We experimentally tested whether differences in larval lake sturgeon (Acipenser fulvescens) predation levels were attributed to changes in prey selectivity, or to an overall decrease in consumption of co-distributed and dispersing prey consumed by predatory riverine species under different light conditions. Larvae from three common riverine prey taxa observed nocturnally dispersing together (lake sturgeon, white suckers (Catostomus commersonii), and Hetptageniid mayflies) were released concurrently into raceway mesocosms. Raceways contained one of two abundant predacious riverine fishes [either rock bass (Ambloplites rupestris) or hornyhead chub (Nocomis biguttatus)]. Trials were conducted in light conditions simulating a full or new moon. Both predators consumed fewer prey under new moon relative to full moon light conditions. In full moon conditions, rock bass selected for mayflies and against white suckers, but in new moon conditions rock bass selectivity was similar for all prey. Hornyhead chub selected for mayflies under both light conditions. Results indicate rock bass and hornyhead chub rely on visual cues to detect prey. Rock bass also appeared to visually differentiate between prey taxa, whereas hornyhead chub may use alternative senses to select prey. Variation in larval lake sturgeon mortality during the downstream drifting period was a function of the taxonomic composition and size distribution of predators, and composition and relative abundance of alternative co-distributed prey. Nocturnal light levels likely also influence predation rates in natural populations of nocturnally dispersing aquatic larvae. Light levels during larval dispersal should be considered when interpreting intra- and inter-annual variation in recruitment in species of regional conservation concern.

Identifying unmeasured heterogeneity in microbiome data via quantile thresholding (QuanT).

Microbiome data, like other high-throughput data, suffer from technical heterogeneity stemming from differential experimental designs and processing. In addition to measured artifacts such as batch effects, there is heterogeneity due to unknown or unmeasured factors, which lead to spurious conclusions if unaccounted for. With the advent of large-scale multi-center microbiome studies and the increasing availability of public datasets, this issue becomes more pronounced. Current approaches for addressing unmeasured heterogeneity in high-throughput data were developed for microarray and/or RNA sequencing data. They cannot accommodate the unique characteristics of microbiome data such as sparsity and over-dispersion. Here, we introduce Quantile Thresholding (QuanT), a novel non-parametric approach for identifying unmeasured heterogeneity tailored to microbiome data. QuanT applies quantile regression across multiple quantile levels to threshold the microbiome abundance data and uncovers latent heterogeneity using thresholded binary residual matrices. We validated QuanT using both synthetic and real microbiome datasets, demonstrating its superiority in capturing and mitigating heterogeneity and improving the accuracy of downstream analyses, such as prediction analysis, differential abundance tests, and community-level diversity evaluations.

Evaluating the Effectiveness of an Acoustic Camera for Monitoring Three Large Jellyfish Species in the Coastal Waters of Liaodong Bay, China

A survey was conducted to evaluate the effectiveness of adaptive resolution imaging sonar (ARIS), also known as an acoustic camera, for monitoring large jellyfish in the Liaodong Bay area, China. The abundance and vertical distribution of large jellyfish species, such as Nemopilema nomurai, Aurelia coerulea, and Cyanea nozakii, were obtained from acoustic camera observation images, and the effectiveness of the acoustic camera method was determined. The acoustic camera method provided visual information on the number of large jellyfish and their positions in the water column and demonstrated that they were more frequently located in the mid-upper water column of the surveyed area. The results show that it is possible to identify three different types of large jellyfish using acoustic camera sonar images, based on their size, shape, outline, and movement trajectory. The acoustic camera method enables the effective monitoring of jellyfish abundance and enables the observation of their vertical distribution, demonstrating its suitability for monitoring large jellyfish in shallow waters. The results show that observations through an acoustic camera can be used to study the horizontal and vertical spatial distribution characteristics of large jellyfish and to observe their behavior.

Impact of Silver and Copper Oxide Nanoparticles on Anaerobic Digestion of Sludge and Bacterial Community Structure.

The effect of metal nanoparticles on the anaerobic digestion of sludge and the sludge bacterial community are still not well-understood, and both improvements and inhibitions have been reported. This study investigated the impact of 2, 10, and 30 mg/g TS silver and copper oxide nanoparticles (AgNPs and CuONPs) on the mesophilic anaerobic digestion of sludge and the bacterial community structure. The reactors were monitored for changes in tCOD, sCOD, TS, VS, biogas generation, and cell viability. Also, the relative abundance and taxonomic distribution of the bacterial communities were analyzed at the phylum and genus levels, including the genera involved in anaerobic digestion. Both AgNPs and CuONPs exhibited some inhibition on anaerobic digestion of sludge and biogas generation, and the inhibition was more evident at higher concentrations. CuONPs had a stronger inhibitory effect compared to AgNPs. After the introduction of AgNPs and CuONPs, cell viability initially decreased over the first two weeks but recovered after that. At high concentrations, AgNPs and CuONPs decreased the overall bacterial diversity, and inhibited the dominant bacterial species, allowing those in less abundance to flourish. The relative abundance of the bacteria responsible for hydrolysis and acidogenesis increased and the relative abundance of acetogenic bacteria decreased with higher AgNP and CuONP concentrations. The majority of the parameters measured for monitoring the anaerobic digestion performance and bacterial community were not statistically significant at 2 mg/g TS of AgNPs and CuONPs, which represents naturally present concentrations in wastewater sludge that are below the USEPA ceiling concentration limits.

Mapping Butterfly Species Richness and Abundance in Mountain Grasslands—Spatial Application of a Biodiversity Indicator

ABSTRACTAimThe integration of high‐quality field data with high‐resolution remote sensing data can give detailed insights into the spatial distribution of biodiversity and provide valuable information for biodiversity conservation at a scale relevant for management action. We developed a framework based on remote sensing data and field surveys for modelling species richness and abundance of butterflies at high spatial resolution to inform about the spatial distribution of butterfly species richness and abundance and analyse their drivers and the scale of effect of landscape factors.LocationWestern Austria.MethodsWe combined structured butterfly surveys at 175 grassland sites in western Austria with remote sensing variables describing topography, grassland characteristics, and the landscape composition and configuration at different radii around a site. For spatial predictions of butterfly species richness and abundance, generalised linear models with elastic net regularisation were used and compared with stepwise variable selection. To analyse the influence of selected variables and their scale of effect, models with landscape variables in different radii around the sites and variables describing topography were applied.ResultsFor species richness, the Spearman rank correlation between predicted and measured values was 0.62. For abundance, predictive power was lower with a correlation of 0.52. Models with variables from smaller radii (125 and 250 m) generally showed better predictive performance than those at larger radii (500 and 1000 m). We found an effect of elevation, maximum grassland productivity, northness, and forest ecotone density in most models.Main ConclusionsIntegrating remote sensing data with spatial modelling techniques substantially enhances our ability to understand patterns and identify key drivers of butterfly species richness at high spatial resolution. Our study highlights the positive influence of forest edges, small woody features, and moderate grassland productivity on butterfly species richness and abundance.

Characteristics of the distribution of minerals among the space groups

Abstract The RRUFF online database (a project by Robert Downs, University of Arizona) catalogs the occurrence of point and space group symmetries of over 4800 of the nearly 6000 currently accepted mineral species. Of these, over 90% are monomorphic, while the remaining species have been recognized to be polymorphic. To avoid issues of reliability and inconsistency of characterization, the 4499 monomorphic minerals are the subject of this analysis. It has long been recognized that minerals are non-uniformly distributed among the space groups as well as their corresponding point groups and crystal systems. However, this non-uniformity is not non-systematic. A random distribution of minerals among the space groups would result in an average of about 20 species per group. In fact, the observed distribution of minerals is highly skewed. Analysis of the frequency distribution of minerals among the space groups reveals three distinct populations: those without currently known monomorphic species (52), those sparsely populated by minerals that exhibit an exponential distribution of species abundances (170), and those most populous space groups (8) that are differentiated from the others by an inflection in the slope of the species frequency distribution. Additionally, a series of relationships have been identified, and they collectively characterize crystallographic controls on and resultant distributions of mineral occurrence. First, there is a strong preference across all crystal systems for minerals to exhibit structures associated with the holohedral space groups relative to those pedial groups of the lowest symmetry. Second, mineral species exhibit a strong preference for the Laue class space groups over their paired Sohncke groups. Furthermore, it is recognized that the space groups that make up the 11 enantiomorphic pairs are either sparsely populated or devoid of known mineral species. Third, the centering types of the Bravais lattices and structures defined by the Wyckoff multiplicities of the various space groups are recognized to strongly influence the distribution of mineral species such that more structurally and symmetrically complex space groups (those with non-primitive lattice structures) tend to be represented by more minerals. Fourth, when considering the 73 arithmetic space group classes, in most cases non-symmorphic space groups are more richly populated than their linked symmorphic space groups, and in those cases where both hemisymmorphic and asymmorphic space groups are present in the same arithmetic class, the asymmorphic space groups typically contain more species. Together, these observations and interpretations augment and advance previously achieved understandings of mineral frequency distributions among the point groups and imply four future lines of inquiry: extending consideration to polymorphic species as well as relating distributions among the space groups to terrestrial mineral species abundance, mineral chemistry, as well as the evolution of mineral chemistry and paragenesis.

A prospective multi-site translational study investigating the association of gut microbiome (GM) diversity with pathological complete response (pCR) after neoadjuvant treatment in early stage rectal and esophageal cancer.

TPS849 Background: The diversity of the GM is defined as the number and relative abundance distribution of distinct types of microorganisms colonizing within the gut. Studies have suggested that dysbiosis of the GM confers a predisposition to certain malignancies and impacts response to immunomodulating therapies. The influence of the GM diversity on the pathological response after neoadjuvant chemotherapy and radiotherapy is unclear. Some studies have suggested that the GM may offer predictive biomarkers for response to chemoradiation in rectal cancer. Other studies in early-stage rectal cancer patients indicated an association between GM diversity and pathological outcomes following neo-adjuvant therapy (NAT). We hypothesize that a more diverse GM constitution at baseline leads to an improved pathological response at the time of definitive surgery. Methods: We designed a cross-institutional translational study investigating the impact of the GM diversity on the efficacy of NAT in GI cancers by assessing its association with pathological response. The study population includes patients with early-stage rectal or esophageal cancer due to commence NAT (including chemotherapy and chemoradiation) who are planned for definitive surgery. Exclusion criteria includes prior allogenic tissue/solid organ transplantation and prior receipt of anti-cancer therapy. The study assessments include fecal sampling of the GM prior to NAT, upon completion and again six months post completion of therapy. Fecal samples are analysed by 16S RNA sequencing. Pathological response will be examined at time of surgery and patients will be classified as responders (complete pathological response) or non-responders. The primary endpoint of the study is to examine the association between the GM diversity and pathological response. Exploratory analysis will include the assessment of the association between cf-DNA and the GM diversity as well as an assessment of the association between cf-DNA at baseline and pCR. Species richness (Alpha Diversity) will be analysed using the Shannon diversity index and Jaccard similarity index will be used to calculate beta diversity. Following planned study recruitment, classification and clustering analysis will be performed with Principal Component Analysis (PCA) and Random Forest analysis. Logistic regression analysis adjusting for potential confounding factors will be employed to assess the primary endpoint of the association between GM and complete pCR in the final statistical analysis. Adjusted odds ratios (OR) and 95% confidence intervals will be presented. This trial accrued 11 patients between May 2023 and Sept 2024. Out of the 11 patients enrolled, 9 patients have undergone their planned surgery. We are expecting to have 30 patients accrued prior to Jan 2025.