Different Beta‐Diversity Frameworks Reveal Contrasting Roles of Species Abundance Distributions and Spatial Aggregation - Jackson Barratt Heitmann; Daniel J. McGlinn; S. K. Morgan Ernest; Corey T. Callaghan (Journal of Biogeography, 2026)
Aim Determining why community composition changes from place‐to‐place (spatial β‐diversity) is central to advancing biodiversity theory and conservation of threatened species. Spatial β‐diversity can occur most simply due to random sampling effects from the larger species‐pool, such as the random placement and distribution of individuals and species. However, ecological processes can also generate intraspecific aggregation changes that also produce changes in spatial β‐diversity. We decomposed changes in β‐diversity among birds in geographically isolated wetlands to understand the relative contributions of intraspecific aggregation and random sampling processes. Specifically, we compared two analytical approaches from the Measurement of Biodiversity framework: multi‐metric versus multi‐scale. We also examined how estimates of β‐diversity are sensitive to changes in spatial extent and environmental context. Location Continental United States. Time Period 2010–2024. Major Taxa Studied Birds. Methods We integrated a dataset of n = 207 geographically isolated wetlands with eBird data from 2010 to 2024 from across the continental United States to investigate how β‐diversity changes in these wetland systems at two different spatial extents: (1) within ecoregions and (2) between wetlands continentally, regardless of ecoregion. We used both the multi‐metric and the multi‐scale approaches of the Measurement of Biodiversity framework, which account for changes in abundance and the species‐abundance distribution, to test if β‐diversity in these systems reflects intraspecific aggregation across ecoregions. Results The multi‐metric β‐diversity approach was largely consistent with random sampling effects due to variation in community size and the species‐abundance distribution at both ecoregion and continental extents evidenced by low β C . However, our multi‐scale β‐diversity analysis using spatially explicit rarefaction curves revealed a strong divergence from the random sampling effects indicating that β‐diversity is also due to intraspecific aggregation generated by ecological processes both at the ecoregion and continental extents. Main Conclusions Our two analytical frameworks uncovered different explanations for spatial β‐diversity in wetlands. The β‐diversity metrics did not differ from random sampling presumably due to the homogenous distribution of a few hyperabundant species. However, the spatial accumulation of species was slower than expected under random sampling which indicates that ecological processes, such as environmental filtering and/or dispersal limitation, are driving nearby wetlands to have more similar composition than expected. Both of these signals were present within and across ecoregions, highlighting the need for a pluralistic approach to analysing β‐diversity and disentangling these non‐mutually exclusive processes.

Ecological network structure in response to community assembly processes over evolutionary time - Natalie R. Graham; Henrik Krehenwinkel; Jun Ying Lim; Phillip Staniczenko; Jackson Callaghan; Jeremy C. Andersen; Daniel S. Gruner; Rosemary G. Gillespie (Molecular Ecology, 2023)
The dynamic structure of ecological communities results from interactions among taxa that change with shifts in species composition in space and time. However, our ability to study the interplay of ecological and evolutionary processes on community assembly remains relatively unexplored due to the difficulty of measuring community structure over long temporal scales. Here, we made use of a geological chronosequence across the Hawaiian Islands, representing 50 years to 4.15 million years of ecosystem development, to sample 11 communities of arthropods and their associated plant taxa using semiquantitative DNA metabarcoding. We then examined how ecological communities changed with community age by calculating quantitative network statistics for bipartite networks of arthropod–plant associations. The average number of interactions per species (linkage density), ratio of plant to arthropod species (vulnerability) and uniformity of energy flow (interaction evenness) increased significantly in concert with community age. The index of specialization has a curvilinear relationship with community age. Our analyses suggest that younger communities are characterized by fewer but stronger interactions, while biotic associations become more even and diverse as communities mature. These shifts in structure became especially prominent on East Maui (~0.5 million years old) and older volcanos, after enough time had elapsed for adaptation and specialization to act on populations in situ. Such natural progression of specialization during community assembly is probably impeded by the rapid infiltration of non‐native species, with special risk to younger or more recently disturbed communities that are composed of fewer specialized relationships.

Richness and resilience in the Pacific: DNA metabarcoding enables parallelized evaluation of biogeographic patterns - Susan Kennedy; Jerilyn Calaor; Yazmín Zurápiti; Julian Hans; Masashi Yoshimura; Juanita Choo; Jeremy C. Andersen; Jackson Callaghan; George K. Roderick; Henrik Krehenwinkel; Haldre Rogers; Rosemary G. Gillespie; et al. (Molecular Ecology, 2023)
Islands make up a large proportion of Earth's biodiversity, yet are also some of the most sensitive systems to environmental perturbation. Biogeographic theory predicts that geologic age, area, and isolation typically drive islands' diversity patterns, and thus potentially impact non‐native spread and community homogenization across island systems. One limitation in testing such predictions has been the difficulty of performing comprehensive inventories of island biotas and distinguishing native from introduced taxa. Here, we use DNA metabarcoding and statistical modelling as a high throughput method to survey community‐wide arthropod richness, the proportion of native and non‐native species, and the incursion of non‐natives into primary habitats on three archipelagos in the Pacific – the Ryukyus, the Marianas and Hawaii – which vary in age, isolation and area. Diversity patterns largely match expectations based on island biogeography theory, with the oldest and most geographically connected archipelago, the Ryukyus, showing the highest taxonomic richness and lowest proportion of introduced species. Moreover, we find evidence that forest habitats are more resilient to incursions of non‐natives in the Ryukyus than in the less taxonomically rich archipelagos. Surprisingly, we do not find evidence for biotic homogenization across these three archipelagos: the assemblage of non‐native species on each island is highly distinct. Our study demonstrates the potential of DNA metabarcoding to facilitate rapid estimation of biogeographic patterns, the spread of non‐native species, and the resilience of ecosystems.

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity - Chiara Fallerini; Nicola Picchiotti; Margherita Baldassarri; Kristina Zguro; Sergio Daga; Francesca Fava; Elisa Benetti; Sara Amitrano; Mirella Bruttini; Maria Palmieri; Susanna Croci; Mirjam Lista; et al. (Human Genetics, 2022)
The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.