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bioRxiv2026

Resource availability and dimensionality result in ecology-dependent selection in bacteriophage spatial expansions

In microbial populations, fitness, which is essential to understand and predict evolution, is often defined and measured as the net growth rate of a population in isolation. Applying the same definition to viruses is challenging, both because viral replication involves a host infection process, which is determined by several parameters that are context-dependent, and because viruses compete heavily for resources (susceptible cells). These challenges are particularly exacerbated in spatial range expansions, where multiplicity of infection is often high and resource availability varies in time and space. To assess different fitness definitions and their generalizability, we investigate a model of coupled partial differential equations for phage plaque expansion in one and two dimensions. We find that two commonly used metrics for phage fitness in plaque expansions, i.e., steady state phage densities and front expansion speed in isolation, are unable to reliably predict the winner in one- and two-dimensional direct competitions. More generally, we find that optimal phage traits depend on the dimensionality of the system and the make-up of the phage population, leading to unexpected behaviours, e.g., rock-paper-scissor dynamics and, in high dimensions, enhanced phage density due to the nearby presence of a competitor. We show that the phenomenon stems from the interplay between resource consumption and replication and thus may apply more broadly to any population competing for shared resources.

ecology↗

bioRxiv2026

Stopover Population Estimate and Migration Ecology of Red Knots C. c. rufa at Delaware Bay, USA, 2025

Red Knots (Calidris canutus rufa) rely on Atlantic horseshoe crab (Limulus polyphemus) eggs in the Delaware Bay to refuel during northward migration. Intensive harvest of horseshoe crabs in the 1990s contributed to declines in Red Knot numbers. In 2013, the Atlantic States Marine Fisheries Commission adopted an Adaptive Resource Management (ARM) framework to balance sustainable horseshoe crab harvest with ecosystem integrity and Red Knot recovery, requiring annual stopover population estimates. We estimated the 2025 passage population of Red Knots at Delaware Bay using a Bayesian analysis of a Jolly-Seber mark-resight model which accounts for population turnover and imperfect detection. We also evaluated change in migration timing between 2011 and 2025 with model-derived estimates of arrival at the Delaware Bay each year. The 2025 passage population was 54,043 individuals (95% credible interval: 47,926-61,928), an increase of approximately 17% over 2024 and only the second year since 2011 to exceed 50,000 individuals. Despite the increase, overlapping credible intervals across years indicate a stable stopover population. Migration timing has remained consistent, with 50% of the population typically arriving by 18 May and no evidence of advancement since 2011. These findings provide meaningful input for the ARM framework, supporting sustainable harvest of horseshoe crabs while maintaining adequate foraging opportunities for Red Knots and other shorebirds. Parts of the Introduction, Methods, and Appendices were originally published in Lyons (2024) and are summarized herein.

ecology↗

bioRxiv2026

Ecological tristability driven by total carbon availability over resource complexity in a synthetic microbial community

Even though complex microbial communities are ubiquitous and provide essential services for natural and human-associated ecosystems, our knowledge about their assembly and dynamics is incomplete. There is an ongoing debate whether the behavior of complex communities can be predicted from the outcome of pairwise competition of species, and whether communities reach alternative stable states depending on the level and complexity of resource provided for growth. To estimate the effect of two resource gradients, total carbon availability and resource complexity, on the compositional dynamics of a complex microbial community, we conducted a 16-day serial passage experiment, transferring a 16-species synthetic community in 96 different resource environments. We observed that although both resource dimensions influenced community composition, total carbon exerted a considerably larger effect. Additionally, we saw the emergence of a tristable pattern along the total carbon gradient, a feature not observed for the resource complexity gradient. Using monoculture assays, we identified lag phase duration as the dominant predictor of competitive success at carbon extremes, with maximum growth rate increasing in importance as lag times converged. Total carbon availability thus structured community state transitions and regulated which growth trait governed competitive sorting. These results suggest the importance of total carbon level over resource complexity and identifying dominant species for the quest to successfully manage, maintain and manipulate complex microbial communities.

ecology↗

bioRxiv2026

Algal-derived extracts act as selective ecological filters shaping soil microbiomes, bacterial traits, and tomato performance under biotic stress

Modern agriculture faces the dual challenge of increasing food production while reducing reliance on synthetic inputs that degrade soil ecosystems and compromise long-term sustainability. Algal biomasses have emerged as promising biostimulants, yet their capacity to selectively modulate soil microbiomes and plant growth-promoting bacterial (PGPB) functions remains poorly understood. Here, we evaluated 17 phylogenetically and biochemically diverse macro- and microalgal extracts to determine their effects on soil microbial communities, bacterial functional traits, and tomato (Solanum lycopersicum) performance. Algal supplementation selectively restructured microbial communities without disrupting overall diversity, promoting taxa associated with plant-beneficial functions, including Bacillus, Pseudomonas, and Actinobacteria. In soil microcosms, specific treatments increased culturable bacterial abundance by up to [~]200-fold relative to the initial soil. Functional assays revealed strong extract- and strain-dependent responses. Siderophore production and ACC-associated activity were the most consistently stimulated traits, whereas auxin production, biofilm formation, and proline synthesis showed more variable or context-dependent responses. Notably, Ulva sp. (AP11.2) enhanced siderophore production across the majority of isolates, with over four-fold increases in individual strains, while Arthrospira-derived extracts (NG4.1, N14.1) consistently promoted bacterial growth across multiple taxa. In contrast, extracts such as Nannochloropsis sp. (NG6.1) and Tetraselmis sp. (NG5.1) induced more selective or inhibitory responses, highlighting extract-dependent functional trade-offs. Integration of biochemical and biological datasets identified fatty acid composition as a key axis associated with microbial functional responses, whereas volatile organic compound profiles showed weaker and less consistent associations. These microbiome and functional shifts translated into improved plant performance, with algal treatments increasing tomato growth and reducing mortality by approximately 20% under non-sterile soil conditions characterized by pathogen-associated pressure. Together, these findings demonstrate that algal extracts act as selective modulators of soil microbiomes, enhancing specific bacterial functions and improving plant performance in a context-dependent manner. This work provides a mechanistic framework for the development of targeted algal-based biostimulants aimed at reducing agrochemical inputs and advancing microbiome-informed agriculture.

ecology↗

bioRxiv2026

Pollination ecology of a threatened lupine from the core to northern edge of its geographic range

Lack of sexual reproduction limits the fitness and long-term viability of many plant populations. This may pose a particular problem for populations at the edges of species ranges, which are often small and isolated and therefore may be less likely to attract pollinators. But despite the fact that many range-edge populations are of significant conservation concern and value, there is often little information about which visitors are effective pollinators, and few explicit tests of whether range-edge populations experience reduced pollination. Here, we assess which visitors are effective pollinators of sundial lupine (Lupinus perennis), a legume that is threatened in much of its range, and whether pollination success varies between populations in the range core and those at the species northern range edge. Across six populations in the northern USA and southern Canada (Ontario), sundial lupine was visited almost exclusively by bees, but only large bees (Bombus, Xylocopa) could be confirmed as effective pollinators in single-visit experiments. While seed production varied significantly among populations, visitation rates did not. Neither pollinator visitation, pollen receipt, nor seed production declined at sundial lupines northern range edge. We therefore found no evidence that pollination success constrains either performance of at-risk populations of sundial lupine or the species northern range limit.

ecology↗

bioRxiv2026

Predicting Valley Fever Outbreaks: Novel Mechanistic Models Incorporating Climate and Ecological Interactions

Coccidioidomycosis (Valley fever) is an environmentally acquired fungal infection endemic to the arid Americas, presenting a growing public health challenge as changing environmental patterns threaten to amplify exposure risks across both established and newly recognized endemic zones. Historically, forecasting efforts have relied on statistical correlations with meteorological variables. These phenomenological models often fail to capture the complex, non-linear interactions between the saprobic (environmental) and parasitic (host) life cycles of Coccidioides, particularly under non-stationary climate conditions. Here, we present a hierarchy of mechanistic Ordinary Differential Equation (ODE) models that explicitly map environmental drivers to the distinct biological stages of the fungal life cycle. We developed successive model iterations, incrementally incorporating soil moisture retention, temperature-dependent growth rates, and wildlife reservoir dynamics, and calibrated them against human case data from various regions of Arizona. We derive a time-variant environmental reproduction number and test how transmission potential fluctuates dynamically with environmental forcing. The comparative forecasting analysis, utilizing various statistical tests, information criteria, Relative Root Mean Square Error, the Diebold-Mariano test, and the Modified Diebold-Mariano, shows how the models progress. Mechanistic models based solely on continuous fungal growth perform worse than statistical baselines. By integrating climate data, we increase predictive power to a level comparable to that of the statistical model. Explicitly incorporating a wildlife reservoir as a biological amplifier significantly improves model forecasting over statistical baselines. This framework offers public health officials a biologically grounded tool to predict disease burden and guide targeted interventions responding to changing climate patterns.

ecology↗

bioRxiv2026

Rethinking the movement ecology of Andean bears: temperature-driven cathemerality and seasonal space-use cycles

BackgroundThe Andean bear (Tremarctos ornatus), South Americas only ursid, is one of the worlds most elusive large mammals, making movement data collection exceptionally rare. Addressing this gap, we present the largest telemetry dataset ever assembled, spanning 19 individuals tracked across three Ecuadorian National Parks over two decades, paired with a novel analytical approach. MethodsWe integrated Continuous-Time Movement Models (CTMM), Auto-correlated Kernel Density Estimates (AKDEs), Hidden Markov Models (HMM) and a diel niche theoretical framework to mitigate biases previously unaccounted for the species in telemetry studies. Fine-scale AKDEs and non-linear movement metrics were calculated to understand seasonal space use and movement behaviors. Speed and diffusion from CTMM and behavioral states from HMM were modelled with environmental covariates to investigate which conditions shape diel and seasonal activity. ResultsPopulation mean home range was 138.2 km2 (95% Confidence Intervals 78.7-225.5), with males (239.8 km2, 182.8-307.5), significantly exceeding females (58.5 km2, 35.5-90.3). Notably, three females exhibited ranges comparable to some males. Weekly and monthly AKDEs uncovered cyclic home range dynamics potentially driven by resource availability, with contractions around corn harvests and berry seasons, and expansions during paramo transitions. Decoupling speed from diffusion rates showed region-specific behaviors: intensive patch exploitation in Llanganates, broad exploratory ranging in Cayambe-Coca, and suppressed female locomotion in Cotacachi-Cayapas. Statistical analyses identified temperature as a key diel modulator and precipitation as the seasonal driver. Foraging probability increased between 2:00-6:00, large displacements between 7:00-14:00, and nocturnal movement rose significantly under colder conditions. Across diel hypothesis frameworks, bears were classified as cathemeral rather than strictly diurnal, corroborated by camera-trap records from Colombia, Ecuador, and Peru. ConclusionsWe propose a cathemeral diel phenotype that responds to thermal fluctuations and situates Andean bears within a broader ursid context of thermoregulatory niche plasticity. This dataset reveals unprecedented resolution of regional and sex specific behaviors that will facilitate and accelerate comparative studies in rapidly changing Andean landscapes. By releasing this long-term dataset as an open resource, we provide a foundation for climate-resilient conservation strategies. More broadly, we advocate for data democratization and invite collaboration.

ecology↗

bioRxiv2026

Ecological bleaching trajectories under severe heat stress are only partially captured by acute heat stress assays

Global marine heatwaves have devastated tropical coral reefs, and further mortality is projected under ongoing climate change. Identifying thermally tolerant coral colonies is therefore a priority for conservation, restoration, and research. Portable acute heat stress assays (e.g., CBASS) enable rapid, standardized estimates of coral thermal tolerance under field conditions. However, it remains unresolved whether such experimentally derived metrics (ED5, ED50, DW) predict bleaching and mortality in situ. Here, we quantified acute thermal tolerance metrics for 2,068 coral colonies across 12 common Indo-Pacific species, six months prior to an unprecedented heat stress event in northeastern Peninsular Malaysia and compared experimentally derived ED and DW values to subsequent bleaching severity and mortality in the field. Experimental thermal tolerance metrics explained only a limited proportion of variation in bleaching outcomes and survival. Predictive power varied among species and was higher in slow-growing species. Our findings suggest that while acute heat stress assays capture substantial variation in coral thermal tolerance, their ability to predict in situ outcomes is context-dependent and diminishes under severe thermal stress. Ultimately, in situ coral bleaching under severe heat stress may reduce the discriminatory capacity of acute assay-derived tolerance metrics.

ecology↗

bioRxiv2026

Bayesian optimal designs for common single-driver experiments in ecology

O_LIEcological experiments often characterize species responses to environmental drivers by estimating parameters of well-known nonlinear functions. However, the standard experimental designs used for these experiments waste precious experimental resources by making measurements at uninformative driver levels. C_LIO_LIClassical methods to optimize experimental designs require the parameter values we intend to estimate - circularity that undermines the usefulness of optimization. Bayesian Optimal Experimental Design (BOED) solves this problem by using prior distributions of the parameters to calculate designs that optimize properties of the posterior distribution. Thus, they circumvent the parameter dependence and result in robust, efficient experimental designs. C_LIO_LIHere, we develop and evaluate Bayesian optimal designs for four commonly used nonlinear drivers measuring per-capita growth rate against: nutrients/food (Monod or Holling type 2 function), light (Eilers-Peeters function), temperature (Norberg function) and toxins (log-logistic function). C_LIO_LIWe show using simulations that Bayesian optimal designs consistently outperform standard uniform designs in terms of parameter estimation and prediction accuracy, especially at low sample sizes. For some functions, Bayesian designs with 5 data points outperformed uniform designs with 15 data points. BOED can therefore allow us to allocate scarce experimental resources more efficiently. We provide detailed explanations and code to enable readers to apply these methods. We also provide rules of thumb that would improve experimental efficiency even without following the entire BOED procedure. C_LI

ecology↗

bioRxiv2026

Freshwater input and tidal position regulate species turnover and interaction rewiring in intertidal ecological networks

The effect that environmental conditions have on community and network assembly processes remains unclear, in part because these processes operate at multiple scales. Because marine primary producers and microinvertebrates have limited mobility, are susceptible to multiple stressors, and can be observed interacting in situ, their habitat-based interactions provide an informative system for disentangling network organising processes. We sampled 646 habitat-use networks, quantifying interactions involving habitat-users and biogenic habitat-formers over 12 months at 9 sites within Te Ihutai/Avon-Heathcote estuary in Christchurch, Aotearoa New Zealand. Using generalised dissimilarity mixed-effect models, we examined whether changes to species interactions - deconstructed into species turnover and interaction rewiring - were modulated by environmental covariates, including freshwater discharge, elevation, temperature, spatial location and season. We found that with increasing dissimilarity in sites proximity to freshwater, interaction change was more driven by rewiring, whereas differences in elevation (i.e., between channels and non-channel habitats) were driven by species turnover, with more sessile species inhabiting tidal channels. The proximity of habitats also played a strong role, with nearby networks comprising more similar interactions, and species turnover becoming more prevalent with increasing distance. Our results highlight that the relative influence and magnitude of rewiring and species turnover in controlling estuarine interaction networks was affected by the individual species distributions across the estuary and their responses to separate, but co-occurring, environmental factors. Quantification of habitat-former/user interaction networks offers robust, albeit understudied, measures of processes that can underpin community assembly, highlighting their potential importance in research, management and conservation. Open research statementData are provided for peer review. The code for produced from the project analysis and used to draft this manuscript is shared via a public GitHub repository hosted by the Tonkin Research group (repo name: EstInteractTurn). The data used in the formal analysis is hosted on Zenodo, under the corresponding authors profile (doi: 10.5281/zenodo.20619091). The data and code was prepared following strict adherence to the FAIR principles, meaning all data was saved as comma-separated values (.csv) or native R data structures (.rds).

ecology↗

bioRxiv2026

The Dark Ecology Dataset: Measurements of Aerial Biomass in US Weather Radar from 1995 to 2025

The US NEXRAD radar network has monitored the aerosphere over the US and its territories continuously since the 1990s and archived nearly 300 million radar volume scans. These data contain a wealth of information about the movements of birds, bats, and insects. Historically, this biological information was difficult to access due to the amount of data and challenges in analyzing it. In the last 15 years, fueled by computational and methodological advances, large-scale aeroecology research has blossomed. However, comprehensive analyses of the NEXRAD archive remain very costly. We collected measurements from every volume scan in the NEXRAD archive--nearly 300 million data files total--to assemble a dataset of aerial biological activity over the US from 1995 to 2025. The core data are vertical profiles, which summarize biological activity at different heights above the radar station for each volume scan. We also provide time series data products that aggregate vertical profiles to point measurements at radar stations across time. These data products can support a range of aeroecology analyses at significantly reduced effort.

ecology↗

bioRxiv2014

Average genome size estimation enables accurate quantification of gene family abundance and sheds light on the functional ecology of the human microbiome

Average genome size (AGS) is an important, yet often overlooked property of microbial communities. We developed MicrobeCensus to rapidly and accurately estimate AGS from short-read metagenomics data and applied our tool to over 1,300 human microbiome samples. We found that AGS differs significantly within and between body sites and tracks with major functional and taxonomic differences. For example, in the gut, AGS ranges from 2.5 to 5.8 megabases and is positively correlated with the abundance of Bacteroides and polysaccharide metabolism. Furthermore, we found that AGS variation can bias comparative analyses, and that normalization improves detection of differentially abundant genes.

Bioinformatics↗

bioRxiv2015

Intragenomic homogeneity on Liberibacter 16S rDNA confirms phylogeny and explains ecological strategy

Three of the five currently recognized \"Candidatus Liberibacter\" spp., \"Ca. L. asiaticus\" (Las), \"Ca. L. americanus\" (Lam) and \"Ca. L. solanacearum\", and the newly erected genus Liberibacter species, L. crescens (Lcr), have had their genomes sequenced. In all four cases there are three homogeneous copies of the 16S rRNA gene, one present as the reverse complement of the other two. 16S intragenic homogeneity is common within the -Proteobacteria. The presence of three 16S rRNA copies indicates an advantage for a rapid response of population increase to favourable growth conditions. The metabolic cost of carrying multiple copies is avoided during periods of low cellular activity as this situation occurs at low temperatures, for example overwintering in deciduous plants or in a dormant insect host.\n\nA large insertion in the 16S rDNA sequence of three species compared to the other three species indicates a dichotomy in the Liberibacter genus and provides a phylogenetic signal of closeness to the proximal node within the Rhizobiaceae. In spite of similar symptoms in Citrus crops associated with Lam and Las infections, these species belong on either side of this dichotomy, thus confirming Lam as phylogenetically closer to the proximal node than Las.

Microbiology↗

bioRxiv2015

Evolution of ecological dominance of yeast species in high-sugar environments

In budding yeasts, fermentation in the presence of oxygen evolved around the time of a whole genome duplication (WGD) and is thought to confer dominance in high-sugar environments because ethanol is toxic to many species. While there are many fermentative yeast species, only Saccharomyces cerevisiae consistently dominates wine fermentations. In this study, we use co-culture experiments and intrinsic growth rate assays to examine the relative fitness of non-WGD and WGD yeast species across environments to assess when S. cerevisiaes ability to dominate high-sugar environments arose. We show that S. cerevisiae dominates nearly all other non-WGD and WGD species except for its sibling species S. paradoxus in both grape juice and a high-sugar rich medium. Of the species we tested, S. cerevisiae and S. paradoxus have evolved the highest ethanol tolerance and intrinsic growth rate in grape juice. However, the ability of S. cerevisiae and S. paradoxus to dominate certain species depends on the temperature and the type of high-sugar environment. Our results indicate that dominance of high-sugar environments evolved much more recently than the WGD, most likely just prior to or during the differentiation of Saccharomyces species, and that evolution of multiple traits contributes to S. cerevisiaes ability to dominate wine fermentations.

Evolutionary Biology↗

bioRxiv2015

Evolution of color phenotypes in two distantly related species of stick insect: different ecological regimes acting on similar genetic architectures

Recurrent (e.g. parallel or convergent) evolution is widely cited as evidence for natural selections central role in evolution but can also highlight constraints affecting evolution. Here we describe the evolution of green and melanistic color phenotypes in two species of stick insect: Timema podura and T. cristinae. We show that similar color phenotypes of these species (1) cluster in phenotypic space and (2) confer crypsis on different plant microhabitats. We then use genome-wide association mapping to determine the genetic architecture of color in T. podura, and compare this to previous results in T. cristinae. In both species, color is under simple genetic control, dominance relationships of melanistic and green alleles are the same, and SNPs associated with color phenotypes colocalize to the same genomic region. These results differ from those of typical parallel phenotypes because the form of selection acting on color differs between species: a balance of multiple sources of selection acting within host species maintains the color polymorphism in T. cristinae whereas T. podura color phenotypes are under divergent selection between hosts. Our results highlight how different adaptive landscapes can result in the evolution of similar phenotypic variation, and suggest the same genomic region is involved.

Evolutionary Biology↗

bioRxiv2016

Revealing complex ecological dynamics via symbolic regression

Complex ecosystems, from food webs to our gut microbiota, are essential to human life. Understanding the dynamics of those ecosystems can help us better maintain or control them. Yet, reverse-engineering complex ecosystems (i.e., extracting their dynamic models) directly from measured temporal data has not been very successful so far. Here we propose to close this gap via symbolic regression. We validate our method using both synthetic and real data. We firstly show this method allows reverse engineering two-species ecosystems, inferring both the structure and the parameters of ordinary differential equation models that reveal the mechanisms behind the system dynamics. We find that as the size of the ecosystem increases or the complexity of the inter-species interactions grow, using a dictionary of known functional responses (either previously reported or reverse-engineered from small ecosystems using symbolic regression) opens the door to correctly reverse-engineer large ecosystems.

Bioinformatics↗

bioRxiv2016

Bacterial but not protist gut microbiota align with ecological specialization in a set of lower termite species

The role of microbes in adaptation of higher organisms to the environment is becoming increasingly evident, but remains poorly understood. Protist and bacterial microbes facilitate that lower termites thrive on wood and are directly involved in substrate break down. During the course of evolution lower termites adapted to different diets and lifestyles. In order to test whether there are changes of the termite gut microbiota that co-occur and hence could be related to diet and lifestyle adaptation, we assessed the bacterial and protist communities in a multispecies framework profiling three wood-dwelling and two foraging lower termite species using 16S and 18S rRNA gene amplicon sequencing. Termites were kept under controlled conditions on the same diet to minimize environmental effects on their gut microbiota. We found that protist communities group according to host phylogeny while bacterial communities group according to lifestyle. The change from the ancestral wood-dwelling to a foraging lifestyle coincides with exposure to more diverse and higher concentrations of pathogens as well as a more diverse diet. Accordingly, we identified bacteria that are associated with foraging termites of the genus Reticulitermes and could function as probiotics or be metabolically important on a more diverse diet. Furthermore, protist and bacterial diversity are correlated, suggesting not only that many termite gut bacteria are associated with protists, but also suggesting a role of protist diversity in the evolution of bacterial diversity in the termite gut or vice versa.

evolutionary biology↗

bioRxiv2017

Epidemiological and ecological determinants of Zika virus transmission in an urban setting.

Zika has emerged as a global public health concern. Although its rapid geographic expansion can be attributed to the success of its Aedes mosquito vectors, local epidemiological drivers are still poorly understood. The city of Feira de Santana played a pivotal role in the early phases of the Chikungunya and Zika epidemics in Brazil. Here, using a climate-driven transmission model, we show that low Zika observation rates and a high vectorial capacity in this region were responsible for a high attack rate during the 2015 outbreak and the subsequent decline in cases in 2016, when the epidemic was peaking in the rest of the country. Our projections indicate that the balance between the loss of herd-immunity and the frequency of viral re-importation will dictate the transmission potential of Zika in this region in the near future. Sporadic outbreaks are expected but unlikely to be detected under current surveillance systems.

epidemiology↗