Biology subjects

Miller, Z. R.

Publications and source records attributed to Miller, Z. R..

At least 19 recordsLinked to original sources

bioRxiv2026

Convergent genome- and gene-level constraints shape repeated environmental adaptation in grasses

Grasses (Poaceae) dominate terrestrial ecosystems and sustain global food security, yet the genomic principles enabling their repeated adaptation to extreme environments remain unresolved. Combining dense phylogenomic sampling, global environmental data, and genomic large language models (gLLMs), we characterize the mutational targets underlying environmental adaptation across 707 genomes from 569 species spanning 17 climate zones. We identify 19-30 phylogenetically independent transitions into extreme temperature, water, and soil environments, accompanied by convergent shifts in genome-scale molecular properties, including the Nitrogen-to-Carbon balance and the biosynthetic cost of the proteome. Our gLLMs-informed phylogenetic mixed modeling framework identifies 330 genes that repeatedly underlie distinct axes of environmental adaptation, highlighting the importance of protein modification and localization within extracellular and organellar compartments. Overlaying independent convergent adaptation tests identifies 17 high-confidence candidates for further characterization. Together, our results show that grass adaptation is canalized by layered constraints at genome-wide and gene-specific scales, producing predictable evolutionary trajectories.

evolutionary biology↗

bioRxiv2026

Dormancy stabilizes structured food webs

Theory predicts that strong species interactions drive ecological instability, but strong interactions are common in ecosystems while strong instability appears rare. This discrepancy motivates enduring interest in ecological mechanisms that limit or counteract instability. Dormancy - reversible metabolic suppression - may be one. Dormancy is a ubiquitous life history trait found in organisms ranging from bacteria to trees. Dormant individuals form "seed banks" that are temporarily disengaged from demographic processes and species interactions, creating a memory of past ecological dynamics. Seed banks can stabilize predator-prey interactions, but whether, when, and how they affect the stability of larger ecological networks is uncertain. We show that dormancy stabilizes oscillatory dynamics in a minimal mathematical model and illustrate how dormancy converts high oscillation frequency into strong restoring force. We find that dormancy can have qualitative stabilizing effects in structured food webs that undergo Hopf bifurcations and exhibit oscillatory instability, but not in unstructured networks or those dominated by competitive or mutualistic interactions. This classification remains accurate when only a subset of species go dormant and drive stabilization. Our results clarify when dormancy can promote stability, indicating that dormancy may be an important but overlooked stabilizing factor in food webs.

ecology↗

bioRxiv2026

Tipping points are typical in ecosystems with higher-order interactions

Whether species-rich communities erode gradually or collapse abruptly under environmental change is a central question in ecology [1]. Classical pairwise theory predicts that coexistence is always lost gradually, through smooth declines to extinction [2], yet real ecological interactions are often strongly state-dependent - shaped by nonlinearities that fixed pairwise coefficients cannot capture [3]. Here we show that higher-order (nonlinear) interactions make abrupt, irreversible loss of coexistence a typical route to community collapse: across diverse random communities, the equilibrium supporting coexistence disappears suddenly at a fold bifurcation. Using polynomial homotopy continuation [4] to track equilibria as environmental conditions change, we find that folds progressively dominate the boundary of the coexistence domain as nonlinearity strengthens, replacing the gradual extinctions of pairwise theory. Furthermore, the sign structure of higher-order interactions controls both the onset of tipping-points and whether biodiversity buffers or amplifies collapse. Because higher-order and nonlinear interactions are intimately linked, tipping points also arise generically in pairwise models with strong nonlinearity. Applying our continuation framework to a canonical model of plant-pollinator collapse [5], we formally resolve its bifurcation structure as fold-mediated, and we show that fold bifurcations are typical across published multispecies models spanning mutualistic, competitive, and consumer-resource interactions. These results challenge the expectation that monitoring abundances suffices to anticipate collapse, and unify structural-stability theory, which delineates the safe operating space for coexistence, with critical transition theory, which characterizes the nature of its boundaries.

ecology↗

bioRxiv2025

Multispecies coexistence emerges from pairwise exclusions in communities with competitive hierarchy

Competitive coexistence is often understood as an additive process where coexisting species pairs, triplets, etc. combine to form larger communities. However, emergent coexistence - where multi-species persistence occurs without pairwise coexistence - can arise through mechanisms including intransitive loops, facilitation, or higher-order interactions. Emergent coexistence has functional consequences, for example constraining community assembly and reducing robustness to extinctions. Here, we demonstrate that emergent coexistence can arise without intransitivity in competitive communities with pairwise interactions. First, we develop a simple trade-off model where interactions are competitive, transitive, and pairwise, yet coexistence is emergent. Second, we show that coexistence is typically emergent in well-known hierarchical trade-off models. Third, we find that emergent coexistence frequently occurs without pronounced intransitivity in random model communities. Our results suggest that competitive coexistence may often be emergent, highlighting a need to better understand the mechanisms and prevalence of this phenomenon in order to reliably predict community assembly, robustness, and biodiversity maintenance.

ecology↗

bioRxiv2024

Stabilization of fluctuating population dynamics via the evolution of dormancy

Dormancy is usually understood as a strategy for coping with extrinsically variable environments, but intrinsic population fluctuations also create conditions where dormancy is adaptive. By analyzing simple population models, we show that, very generally, population fluctuations favor the evolution of dormancy, but dormancy stabilizes population dynamics. This sets up a feedback loop that can enable the coexistence of alternative dormancy strategies. Over longer timescales, we show that evolution of dormancy to an evolutionary stable state can drive populations to the edge of stability, where dynamics are only weakly stabilized. We briefly consider how these conclusions are likely to apply in more complex community contexts. Our results suggest that chaos and high-amplitude population cycles are highly vulnerable to invasion and subsequent stabilization by dormancy, potentially explaining their rarity. At the same time, the propensity of ecological dynamics to fluctuate may be an underappreciated driver of the evolution of dormancy.

ecology↗

bioRxiv2024

Cross-species plant genomes modeling at single nucleotide resolution using a pre-trained DNA language model

Interpreting function and fitness effects in diverse plant genomes requires transferable models. Language models (LMs) pre-trained on large-scale biological sequences can learn evolutionary conservation and offer cross-species prediction better than supervised models through fine-tuning limited labeled data. We introduce PlantCaduceus, a plant DNA LM based on the Caduceus and Mamba architectures, pre-trained on a curated dataset of 16 Angiosperm genomes. Fine-tuning PlantCaduceus on limited labeled Arabidopsis data for four tasks, including predicting translation initiation/termination sites and splice donor and acceptor sites, demonstrated high transferability to 160 million year diverged maize, outperforming the best existing DNA LM by 1.45 to 7.23-fold. PlantCaduceus is competitive to state-of-the-art protein LMs in terms of deleterious mutation identification, and is threefold better than PhyloP. Additionally, PlantCaduceus successfully identifies well-known causal variants in both Arabidopsis and maize. Overall, PlantCaduceus is a versatile DNA LM that can accelerate plant genomics and crop breeding applications.

bioinformatics↗

bioRxiv2023

Fishing for a reelGene: evaluating gene models with evolution and machine learning

Assembled genomes and their associated annotations have transformed our study of gene function. However, each new assembly generates new gene models. Inconsistencies between annotations likely arise from biological and technical causes, including pseudogene misclassification, transposon activity, and intron retention from sequencing of unspliced transcripts. To evaluate gene model predictions, we developed reelGene, a pipeline of machine learning models focused on (1) transcription boundaries, (2) mRNA integrity, and (3) protein structure. The first two models leverage sequence characteristics and evolutionary conservation across related taxa to learn the grammar of conserved transcription boundaries and mRNA sequences, while the third uses conserved evolutionary grammar of protein sequences to predict whether a gene can produce a protein. Evaluating 1.8 million gene models in maize, reelGene found that 28% were incorrectly annotated or nonfunctional. By leveraging a large cohort of related species and through learning the conserved grammar of proteins, reelGene provides a tool for both evaluating gene model accuracy and genome biology.

genomics↗

bioRxiv2023

Phylogeny structures species' interactions in experimental ecological communities

The advent of molecular phylogenetics provided a new perspective on the structure and function of ecological communities. In particular, the hypothesis that traits responsible for species interactions are largely determined by shared evolutionary history has suggested the possibility of connecting the phylogeny of ecological communities to their functioning. However, statistical tests of this link have yielded mixed results. Here we propose a novel framework to test whether phylogeny influences the patterns of coexistence and abundance of species assemblages, and apply it to analyze data from large biodiversity-ecosystem functioning experiments. In our approach, phylogenetic trees are used to parameterize species interactions, which in turn determine the abundance of species in a specified assemblage. We use a maximum likelihood-based approach to score models parameterized with a given phylogenetic tree. To test whether evolutionary history structures interactions, we fit and score ensembles of randomized trees, allowing us to determine if phylogenetic information helps to predict species abundances. Moreover, we can determine the contribution of each branch of the tree to the likelihood, revealing particular clades in which interaction strengths are closely tied to phylogeny. We find strong evidence of phylogenetic signal across a range of published experiments and a variety of models. The flexibility of our framework permits incorporation of ecological information beyond phylogeny, such as functional groups or traits, and provides a principled way to test hypotheses about which factors shape the structure and function of ecological communities.

ecology↗

bioRxiv2023

Metabolic trade-offs can reverse the resource-diversityrelationship

For species that partition resources, the classic expectation is that increasing resource diversity allows for increased species diversity. On the other hand, for neutral species, such as those competing equally for a single resource, diversity reflects a balance between the rate of introduction of novelty (for example by immigration or speciation) and the rate of extinction. Recent models of microbial metabolism have identified scenarios where metabolic trade-offs among species partitioning multiple resources can produce emergent neutral-like dynamics. In this hybrid scenario, one might expect that both resource diversity and immigration will act to boost species diversity. We show, however, that the reverse may be true: when metabolic trade-offs hold and population sizes are sufficiently large, increasing resource diversity can act to reduce species diversity, sometimes drastically. This reversal is explained by a generic transition between neutral- and niche-like dynamics, driven by the diversity of resources. The inverted resource-diversity relationship that results may be a signature of consumer-resource systems with strong metabolic trade-offs.

ecology↗

bioRxiv2023

Coexistence of many species under a random competition-colonization trade-off

The competition-colonization trade-off is a well-studied coexistence mechanism for metacommunities. In this setting, it is believed that coexistence of all species requires their traits to satisfy restrictive conditions limiting their similarity. To investigate whether diverse metacommunities can assemble in a competition-colonization trade-off model, we study their assembly from a probabilistic perspective. From a pool of species with parameters (corresponding to traits) sampled at random, we compute the probability that any number of species coexist and characterize the set of species that emerges through assembly. Remarkably, almost exactly half of the species in a large pool typically coexist, with no saturation as the size of the pool grows, and with little dependence on the underlying distribution of traits. Through a mix of analytical results and simulations, we show that this unlimited niche packing emerges as assembly actively moves communities toward overdispersed configurations in niche space. Our findings also apply to a realistic assembly scenario where species invade one-at-a-time from a fixed regional pool. When diversity arises de novo in the metacommunity, richness still grows without bound, but more slowly. Together, our results suggest that the competition-colonization trade-off can support the robust emergence of diverse communities, even when coexistence of the full species pool is exceedingly unlikely.

ecology↗

bioRxiv2022

Habitat heterogeneity, environmental feedbacks, and species coexistence across timescales

A large body of ecological theory explains the coexistence of multiple species in variable environments. While spatial variation is often treated as an intrinsic feature of a landscape, it may be shaped and even generated by the resident community. All species modify their local environment to some extent, driving changes that can feed back to affect the composition and coexistence of the community, potentially over timescales very different from population dynamics. We introduce a simple, nested modeling framework that describes species coexistence in heterogeneous environments, as well as the evolution of this heterogeneity over time due to feedbacks from the biotic community. We derive analytical conditions for the coexistence of any number of species in environments with intrinsic heterogeneity or feedbacks, and identify essential differences between these scenarios. Our model is naturally simplified in the limit of very fast or very slow environmental feedbacks, allowing us to treat these two scenarios - which bookend the full range of dynamics - in detail. Among other results, we demonstrate how dispersal and environmental specialization interact to shape realized patterns of habitat association. We also show that environmental feedbacks can tune landscape conditions to promote stable coexistence, although feedbacks can give rise to complex dynamics such as limit cycles, priority effects, and episodic dynamics, as well. Our flexible modeling framework helps explain how and when each of these behaviors arise, and offers a generic mathematical platform for exploring the interplay between species and landscape diversity.

ecology↗

bioRxiv2022

Modeling ecological communities when composition is manipulated experimentally

O_LIIn an experimental setting, the composition of ecological communities can be manipulated directly. Starting from a pool of n species, one can co-culture species in different combinations, spanning mono-cultures, pairs of species, and all the way up to the full pool. Here we advance methods aimed at inferring species interactions from data sets reporting the density attained by species in a variety of sub-communities formed from the same pool. C_LIO_LIFirst, we introduce a fast and robust algorithm to estimate parameters for simple statistical models describing these data, which can be combined with likelihood maximization approaches. Second, we derive from consumer-resource dynamics statistical models with few parameters, which can be applied to study systems where only a small fraction of the potential sub-communities have been observed. Third, we show how a Weighted Least Squares (WLS) framework can be used to account for the fact that species abundances often display a strong relationship between means and variances. C_LIO_LITo illustrate our approach, we analyze data sets spanning plants, bacteria, phytoplankton, as well as simulations, recovering a good fit to the data and demonstrating the ability to predict experiments out-of-sample. C_LIO_LIWe greatly extend the applicability of recently proposed methods, opening the door for the analysis of larger pools of species. C_LI

ecology↗

bioRxiv2021

Stability criteria for the consumption and exchange of essential resources

Models of pairwise interactions have informed our understanding of when ecological communities will have stable equilibria. However, these models do not explicitly include the effect of the resource environment, which has the potential to refine or modify our understanding of when a group of interacting species will coexist. Recent consumer-resource models incorporating the exchange of resources alongside competition exemplify this: such models can lead to either stable or unstable equilibria, depending on the resource supply. On the other hand, these recent models focus on a simplified version of microbial metabolism where the depletion of resources always leads to consumer growth. Here, we model an arbitrarily large system of consumers governed by Liebigs law, where species require and deplete multiple resources, but each consumers growth rate is only limited by a single one of these multiple resources. Consumed resources that do not lead to growth are leaked back into the environment, thereby tying the mismatch between depletion and growth to cross-feeding. For this set of dynamics, we show that feasible equilibria can be either stable or unstable, once again depending on the resource environment. We identify special consumption and production networks which protect the community from instability when resources are scarce. Using simulations, we demonstrate that the qualitative stability patterns we derive analytically apply to a broader class of network structures and resource inflow profiles, including cases in which species coexist on only one externally supplied resource. Our stability criteria bear some resemblance to classic stability results for pairwise interactions, but also demonstrate how environmental context can shape coexistence patterns when ecological mechanism is modeled directly. Author summaryOne of the longstanding challenges in community ecology is to understand how diverse ecosystems assemble and stably persist. Microbial communities are a particularly acute example of this open problem, because thousands of different bacterial species can coexist in the same environment. Interactions between bacteria are of central importance across a wide variety of systems, from the dynamics of the human gut microbiome to the functioning of industrial bioreactors. As a result, a predictive understanding of which microbes can coexist together, and how they do it, will have far-reaching applications. In this paper, we incorporate a more realistic understanding of microbial metabolism into classic mathematical models of consumer-resource dynamics. In our model, bacteria deplete multiple abiotic nutrients but only grow on one of these resources. In addition, they recycle some of the nutrients they consume back into the environment as new resources. We analytically derive criteria which, if satisfied, guarantee that any number of microbes will coexist. We find that there are special types of interaction networks which remain stable even when resources are scarce. Our theory can be used in conjunction with experimentally determined interaction networks to predict which species assemblages are likely to stably coexist in a specified resource environment.

ecology↗

bioRxiv2021

No robust coexistence in a canonical model of plant-soil feedbacks

Plant-soil feedbacks (PSFs) are considered a key mechanism generating frequency-dependent dynamics in plant communities. Negative feedbacks, in particular, are often invoked to explain coexistence and the maintenance of diversity in species-rich communities. However, the primary modeling framework used to study PSFs considers only two plant species, and we lack clear theoretical expectations for how these complex interactions play out in communities with natural levels of diversity. Here, we demonstrate that this canonical model for PSFs is equivalent to a well-studied model from evolutionary game theory, and use this equivalence to characterize the dynamics with an arbitrary number of plant species. Surprisingly, we find that coexistence of more than two species is virtually impossible, suggesting that alternative theoretical frameworks are needed to describe feedbacks observed in diverse natural communities. Drawing on our analysis, we discuss future directions for PSF models and implications for experimental study of PSF-mediated coexistence in the field.

ecology↗

bioRxiv2021

Intraspecific variation stabilizes classic predator-prey dynamics

In 1920, Alfred J. Lotka found that, to his "considerable surprise", the dynamics of a simple predatorprey model he had devised led "to undamped, and hence indefinitely continued, oscillations" 1,2-- which he thought epitomized the "rhythm of Nature" dear to the Victorians. In 1926, the same model was proposed independently by mathematician Vito Volterra 3,4, who was inspired by the work of his son-in-law, fish biologist Umberto DAncona 5. For over a century, the equations that now bear their names have served as a template for the development of sophisticated models for population dynamics 6-10. Coexistence in this classic predator-prey model is fragile--stochasticity or temporal variability in parameter values result in extinctions. The dynamics can be stabilized by intraspecific competition or other forms of self-regulation, but the prevalence of these processes in large food webs has been questioned 11,12. Here we show that when we consider populations characterized by intraspecific variability, dynamics are stable--despite the absence of any direct self-regulation. Our results can be generalized further, defining a new class of consumer-resource models 8,13. By accounting for intraspecific variation, which is manifest in all biological populations, we obtain dynamics that differ qualitatively and quantitatively from those found for homogeneous populations--challenging a central assumption of many ecological models.

ecology↗

bioRxiv2021

The Practical Haplotype Graph, a platform for storing and using pangenomes for imputation

MotivationPangenomes provide novel insights for population and quantitative genetics, genomics, and breeding not available from studying a single reference genome. Instead, a species is better represented by a pangenome or collection of genomes. Unfortunately, managing and using pangenomes for genomically diverse species is computationally and practically challenging. We developed a trellis graph representation anchored to the reference genome that represents most pangenomes well and can be used to impute complete genomes from low density sequence or variant data. ResultsThe Practical Haplotype Graph (PHG) is a pangenome pipeline, database (PostGRES & SQLite), data model (Java, Kotlin, or R), and Breeding API (BrAPI) web service. The PHG has already been able to accurately represent diversity in four major crops including maize, one of the most genomically diverse species, with up to 1000-fold data compression. Using simulated data, we show that, at even 0.1X coverage, with appropriate reads and sequence alignment, imputation results in extremely accurate haplotype reconstruction. The PHG is a platform and environment for the understanding and application of genomic diversity. AvailabilityAll resources listed here are freely available. The PHG Docker used to generate the simulation results is https://hub.docker.com/ as maizegenetics/phg:0.0.27. PHG source code is at https://bitbucket.org/bucklerlab/practicalhaplotypegraph/src/master/. The code used for the analysis of simulated data is at https://bitbucket.org/bucklerlab/phg-manuscript/src/master/. The PHG database of NAM parent haplotypes is in the CyVerse data store (https://de.cyverse.org/de/) and named /iplant/home/shared/panzea/panGenome/PHG_db_maize/phg_v5Assemblies_20200608.db. Contactpjb39@cornell.edu

bioinformatics↗

bioRxiv2021

Development of the Wheat Practical Haplotype Graph Database as a Resource for Genotyping Data Storage and Genotype Imputation

To improve the efficiency of high-density genotype data storage and imputation in bread wheat (Triticum aestivum L.), we applied the Practical Haplotype Graph (PHG) tool. The wheat PHG database was built using whole-exome capture sequencing data from a diverse set of 65 wheat accessions. Population haplotypes were inferred for the reference genome intervals defined by the boundaries of the high-quality gene models. Missing genotypes in the inference panels, composed of wheat cultivars or recombinant inbred lines genotyped by exome capture, genotyping-by-sequencing (GBS), or whole-genome skim-seq sequencing approaches, were imputed using the wheat PHG database. Though imputation accuracy varied depending on the method of sequencing and coverage depth, we found 93% imputation accuracy with 0.01x sequence coverage, which was only slightly lower than the accuracy obtained using the 0.5x sequence coverage (96.9%). Compared to Beagle, on average, PHG imputation was ~4% (p-value = 0.00027) more accurate, and showed 27% higher accuracy at imputing a rare haplotype introgressed from a wild relative into wheat. The reduced accuracy of imputation with GBS data (90.4%) is likely associated with the small overlap between GBS markers and the exome capture dataset, which was used for constructing PHG. The highest imputation accuracy was obtained with exome capture for the wheat D genome, which also showed the highest levels of linkage disequlibrium and proportion of identity-by-descent regions among accessions in our reference panel. We demonstrate that genetic mapping based on genotypes imputed using PHG identifies SNPs with a broader range of effect sizes that together explain a higher proportion of genetic variance for heading date and meiotic crossover rate compared to previous studies.

genomics↗

bioRxiv2021

Metapopulations with habitat modification

Across the tree of life, organisms modify their local environment, rendering it more or less hospitable for other species. Despite the ubiquity of these processes, simple models that can be used to develop intuitions about the consequences of widespread habitat modification are lacking. Here we extend the classic Levins metapopulation model to a setting where each of n species can colonize patches connected by dispersal, and when patches are vacated via local extinction, they retain a "memory" of the previous occupant--modeling habitat modification. While this model can exhibit a wide range of dynamics, we draw several overarching conclusions about the effects of modification and memory. In particular, we find that any number of species may potentially coexist, provided that each is at a disadvantage when colonizing patches vacated by a conspecific. This notion is made precise through a quantitative stability condition, which provides a way to unify and formalize existing conceptual models. We also show that when patch memory facilitates coexistence, it generically induces a positive relationship between diversity and robustness (tolerance of disturbance). Our simple model provides a portable, tractable framework for studying systems where species modify and react to a shared landscape.

ecology↗