Four fundamental processes of community assembly

Ladau, J.; Schwager, S. J.

doi:10.1101/188607

Home/Archive/bioRxiv

bioRxiv · 10.1101/188607

Four fundamental processes of community assembly

Ladau, J.·Schwager, S. J.

View original source ↗Export metadata ↓

Abstract

A central aim of ecology is understanding the mechanisms of community assembly. To address this problem, community assembly is often modeled as a sampling process, in which species are selected from a pool of available species, possibly with effects of interspecific interactions, habitat filtering, and other ecological mechanisms. However, the fundamental stochastic sampling process by which species are selected from the pool remains unexplored. Here we demonstrate the distinctness of four canonical sampling processes, the Bernoulli, Plackett-Luce, multinomial, and fractional multinomial processes. Each process can be affected by ecological mechanisms or it can occur in their absence. Although all four of the processes are a priori plausible and the first two are widely used in ecological models, we show that the multinomial and fractional multinomial processes broadly underlie community assembly.

Explore related subjects

ecology Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Ladau, J., Schwager, S. J.. 2017-09-14. Four fundamental processes of community assembly. https://doi.org/10.1101/188607

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

MillionTrees: A global benchmark for tree detection across geography, sensor, and annotation geometry

Airborne tree monitoring using remotely sensed data, combined with the growth of computer vision models for object detection and segmentation, can facilitate broad scale assessment of tree health, ecology and ecosystem function. However, datasets for airborne tree detection have been largely limited to a single geography, resolution, or annotation approach, making it difficult to develop general models and benchmark their utility for broad applications. We compile existing and newly published annotation datasets to create a comprehensive dataset for training and evaluating airborne tree detection in RGB imagery. The MillionTrees dataset has over a million individual trees from a broad range of forest types, tree species, and geographic locations. In addition, it has six million weakly supervised annotations from a range of sources including airborne LiDAR and photogrammetry, arborist surveys, and simulated landscapes. An evaluation standard is provided to facilitate rapid model development. We benchmark several existing tree detection algorithms and demonstrate that while current open-source models do not generalize across the diverse datasets in the benchmark, training on MillionTrees improves both within-domain and out-of-domain performance. Held-out validation datasets using ground truth derived from terrestrial LiDAR paired with overhead RGB show that overfitting to test data is common and hyperparameter tuning is an underappreciated challenge towards a global zero shot tree detection method. We discuss the limitations of the currently available data for airborne RGB tree detection, how to create more robust evaluation data and the need for better understanding of the uncertainty and utility of tree detection from airborne remote sensing.

ecology↗

bioRxiv2026

Individual-specific recovery of the healthy human gut microbiota after antibiotics

Following disruption by broad-spectrum antibiotics, the human gut microbiome undergoes a prolonged recovery where coarse ecological features, such as species richness and diversity, are largely restored. However, as these features are shared by most healthy individuals, it remains unclear whether, even after strong perturbation, individuals preferentially return toward their own pre-treatment composition ('individual-specific recovery') or instead switch to alternative equally healthy states. Resolving this question is fundamental for evaluating the long-term impacts of antibiotics, because an individual's health is affected by their unique microbiome composition, affecting immune regulation and metabolic processing, so a state switch, even to a broadly healthy configuration, could carry unintended consequences. Here we compare each subject's post-antibiotic endpoint with their own baseline and with the baselines of every other subject, across four cohorts (n = 121) whose regimens ranged from a five-day fluoroquinolone course to a four-day three-drug combination given to deplete the gut community. The recovered community was significantly closer to the subject's own baseline than to the alternative healthy baselines in more than 90% of individuals under the mildest regimen and in two thirds of those under regimens that broadly target the gut anaerobes, remaining above chance in every cohort and the majority outcome even where most baseline taxa fell below detection during treatment. This specificity is not merely the persistence and fast regrowth of survivors: it persists among baseline taxa that remain undetected for weeks to months, and the same taxon re-establishes more readily in a host where it was previously detected than in one where it was not. Newly established taxa are consistently more functionally similar to the pre-treatment community than transient arrivals, and their identity correlates with the surviving community's composition in a substantial fraction of subjects. State switching, in contrast, was uncommon and occurred almost exclusively among subjects with the largest reduction in detected taxa during the treatment. Together, these observations reveal the individual-specific nature of the microbiome resilience to broad-spectrum antibiotics, whereas the compositional changes are not random but rather functionally and ecologically associated with the subject's baseline.

ecology↗

bioRxiv2026

Optimal Conservation Prioritization for Waterfowl and Other Birds in Eastern Canada

Conserving and restoring high-quality habitat is widely recognized as one of the most effective means of supporting migratory and wetland bird populations. To advance this objective at a regional scale, the Eastern Habitat Joint Venture (EHJV) coordinates conservation planning for 22 focal bird species across the eastern provinces of Canada. Optimization approaches to support conservation planning are increasingly common, and can be especially valuable in large areas where resources are limited. We present an optimized geospatial prioritization scheme designed to identify regions of primary importance to species coverage objectives within the EHJV. We apply linear programming methods to species abundance data products to maximize population coverage using an adaptable variable-target approach, whose outputs generalize readily to delivery projects of any budget or coverage goal. Our base results highlight areas of high conservation value for priority waterfowl and non-waterfowl species, and we present additional examples of how region-wide solutions can be subdivided based on jurisdictional boundaries, land ownership, or existing protected status. We also address methodological decision points, with attention to how available species abundance data sources were evaluated and what considerations were involved in formulating the optimization computations. We emphasize possibilities for future work to incorporate additional conservation values, such as carbon storage and flood mitigation, and costs, such as land value, and feasibility.

ecology↗