Biology subjects

Arroyo, J. I.

Publications and source records attributed to Arroyo, J. I..

13 recordsLinked to original sources

bioRxiv2025

Modeling the effect of temperature on species coexistence

O_LITemperature reshapes organismal performance and species interactions, yet competition models rarely treat the declining warm side of thermal performance curves explicitly, even though that regime is likely to become increasingly important under climate warming. C_LIO_LIWe develop a density-dependent generalized Lotka-Volterra framework for pairwise exploitative competition in which effective competition coefficients depend on relative temperature-dependent consumption, and we analyse coexistence using the structural feasibility domain. C_LIO_LIWithin this model class, one result is robust: pairwise structural coexistence is maximized when competitors have equal effective consumption, so with symmetric overlap the temperature of maximal coexistence is the temperature at which their consumption thermal performance curves intersect. C_LIO_LIStronger ecological predictions are parameter dependent. In particular, whether coexistence declines more steeply under warming than under cooling, and whether the coexistence maximum for species with different thermal optima is shifted toward the lower optimum, depend on thermal-curve shape, relative peak heights, baseline competition, resource overlap, and any temperature dependence in carrying capacities. C_LIO_LIFor the illustrative asymmetric unimodal curves analysed here, shared optima produce maximal coexistence near the optimum and a steeper decline under warming than under cooling, whereas different optima produce an intermediate coexistence peak biased toward the lower optimum. A qualitative comparison with classic Drosophila pairwise competition experiments at 19{degrees}C and 25{degrees}C is consistent with these expectations. C_LIO_LIBecause the empirical comparison relies on broad thermal categories, unequal species groups, and binary pairwise outcomes, it should be interpreted as a proof of concept rather than a definitive quantitative test. More generally, our results clarify which aspects of temperature-dependent pairwise coexistence are robust consequences of thermal asymmetry and which are contingent on parameterization. C_LI

ecology↗

bioRxiv2025

A database of biological thermal performances

We built a database of thermal performance curves that includes different variables --mostly population growth rates --for species in representative groups across major domains, including viruses, bacteria, archaea, unicellular eukaryotes (such as fungi), and multicellular eukaryotes (including plants and both invertebrates and vertebrates). To build the database, we integrated previous databases and compiled additional data from individual studies, all of which were normalized to the same units when corresponding. Our database contains data for 1300 curves across 1125 different species and 38 variable types. The database consists of four (.csv) tables and an R code that can be explored through an R package or a Shiny app. Applications of our dataset include providing a resource to studies in thermal ecology and integration with other types of data, such as geographic temperatures. This would allow us to make further predictions, such as potential species distributions based on their thermal tolerances and their changes with climate warming.

bioinformatics↗

bioRxiv2025

Scaling laws in biological thermal performances

Understanding the extent to which genetic correlations change in response to environmental factors, such as temperature, is a poorly explored question, despite the importance of understanding how different processes will change with climate warming. Despite correlations between thermal performance traits having been reported in the literature for a few taxa and performance tasks, such as population growth rate, a comprehensive global analysis of the entire tree of life and multiple performance tasks remains an open challenge. To advance in this open question, we compile a database of 1,300 thermal response curves, encompassing 38 variable types related to individuals performance (including per capita population growth rate, photosynthetic rate, among others) and 1,125 different species, ranging from viruses to mammals, encompassing all major lineages of the tree of life. Our analysis reveals that among all possible relationships between traits and optimal performance, four traits form a line with a high goodness-of-fit, while the remaining traits exhibit a polygonal pattern, either a triangle or a tetrahedron. We derive a thermodynamic framework that explains the relationships described by a curve or line (as opposed to a surface or polygon), highlighting the linear relationship between maximum and minimum temperatures, as well as between maximum and optimum temperatures. We also discuss other generic trait evolution models, which could account for the other significant sublinear relationships, as well as the more general model, Pareto optimality theory, which could account for relationships in the form of lines or polygons. Our theoretical framework and empirical evidence suggest that, based on a single data point (e.g., minimum temperature), all critical temperature limits and maximum performance boundaries can be predicted using the estimated parameter from this study. Our results reveal universal scaling relationships in thermal performance, which could be useful for predicting changes in performance under scenarios of climate warming.

biophysics↗

bioRxiv2025

A general model for genomic traits evolution

A large body of data indicates that genomic elements, including gene families and entire genomes, exhibit diverse types of evolutionary dynamics. Several models have been developed to describe the dynamics of, for example, genome size; however, a simple deterministic model with interpretable parameters that could be useful for fitting a variety of data remains an open problem. Here, we show that (a continuous form of) the Breeders equation for the evolution of quantitative traits/characters leads to a general model that explains the dynamics of genomic elements generated by indel mutations (duplications, insertions, and deletions) and selection. Our framework consists of a general exponential-linear model that predicts at least six different types of dynamical behaviors, including exponential growth and decay. The equations fit data, such as evolution experiments across generations, field observational data of genome sizes across time, and data from phylogenetic reconstructions of ancestral states of genome size across millions of years of a variety of taxa, including viruses, bacteria, fungi, unicellular eukaryotes, plants, and animals, at both intra- and interspecific levels. To test the universality of the dynamics, we derived a dimensionless equation that enables the (re)scaling and subsequent collapse of all data for growth or decay onto a single universal curve. Thus, our model provides a general basis not only for explaining the dynamics in the size of gene families or whole genomes of populations across taxonomic and environmental scales, but also other traits, providing a foundation for further theoretical developments.

evolutionary biology↗

bioRxiv2025

Metabolic ecology, microbial community structure, and gene-centric metagenomics

Metabolic ecology includes predictions for biological rates from molecules to ecosystems, but despite the broad range of its scope, its applicability to metagenomes remains an open question. Here, we integrate metabolic ecology with principles of DNA shotgun sequencing to generate specific testable predictions for the metagenomic structure of microbial communities. We start by predicting a scaling relationship between population and assemblage abundance with genome size. This allows us to simplify DNA shotgun sequencing equations for the reads of a population and a gene. Then we derive the temperature dependence of population and assemblage abundance using the volume-temperature and abundance-volume rules and integrate them with simplified DNA sequencing equations to show that these predictions are compatible with a metagenomic framework. In addition, we derive predictions for the temperature dependence of the structure (abundance and richness) of genes and groups of related genes (e.g., metabolic pathways). To test our model, we provide some example data from human, aquatic, and terrestrial microbiomes from recent global projects. All predictions were supported by the observed data. Our model, derived from the integration of first principles, provides a mechanistic basis for variation in the structure of microbial community genomes in environmental and host-associated ecosystems.

ecology↗

bioRxiv2025

Global patterns of taxonomic and functional diversity in hot springs microbiomes

A reformulation of the metabolic theory of ecology has been proposed based on a derivation of the Eyring-Polanyi equation, leading to a reduced model with the form of a power-law with exponential cut-off (PLECO). Moreover, the recent integration of this new model and metagenomic DNA sequencing theory has led to the hypothesis that, given that temperature affects cell size and assemblage abundance, it should also affect the number of genes, metabolisms, and populations in a microbial community. In particular, for microbial communities, the model predicts that the diversity of taxa, their genes, and metabolisms should respond to temperature according to the PLECO model, and after scaling the data using the estimated parameters, all data should collapse into a single curve. To test these predictions, we use global hot springs microbial communities; geothermally heated environments that include aquatic and terrestrial habitats with large temperature gradients. We analyzed a global database (five continents) of 19 hot springs metagenomes covering a wide gradient of temperature (32-90{degrees}C). We found that the alpha diversity of taxa, genes, and their metabolisms decreases with temperature, in agreement with the predictions of the PLECO model. Further, after non-dimensionalization of the model, we derive a single nondimensional curve for taxa and functions. Finally, using general linear models, we analyzed the effects of pH, latitude, and substrate (soil, water, or both), in addition to temperature, to explain the observed diversity pattern. We find that they explain a lower proportion of the variance, but pH can explain up to half of the variance in global diversity in these ecosystems, indicating the need to include pH in the theory. Our study supports the hypothesis that temperature regulates the structure of community genomes.

ecology↗

bioRxiv2025

Fine-scale spatial patterns in hot springs mat bacterial communities

Some of the most widely recognized spatial scaling relationships in ecology include the species-area, the abundance-occupancy, and the community compositional similarity-geographic distance relationships. These patterns have been shown to emerge from common mechanisms, such as habitat heterogeneity and colonization-extinction dynamics, and are predicted by various ecological models and theories, including Island Biogeography, Metapopulation theory, and Neutral Theory of Biodiversity and Biogeography. These patterns have been studied in microbial communities at large-scale, but studies at fine grain and small extent are rare, despite at a fine-scale, emerging patterns can be tested with a higher resolution. In this study, we explored these macroecological patterns in bacterial communities inhabiting hot springs mats, which have been shown to exhibit fine-scale spatial heterogeneity in fundamental environmental parameters such as temperature. In three different localities, we sampled a grid with a heterogeneous temperature at a fine-scale, a small extent (approximately 150 cm2), and fine grain (each containing 30 cells spaced about 1 or 2 cm apart). Our findings revealed sublinear scaling for the species-area relationship, with similar parameters across localities, indicating a low rate of spatial species turnover. For the abundance-occupancy relationship, we observed increasing trends, meaning that species that occupied more patches were, on average, more abundant. Additionally, we identified a decay in community compositional similarity with distance in two of the localities, though with low parameter values, indicating minimal geographic isolation at this scale. These results are consistent with different models that predict that spatial ecological patterns arise from spatial heterogeneity, as different species can partition their niches in space and constitute an example of predictable spatial patterns at a fine scale.

ecology↗

bioRxiv2024

An algorithm for predicting per-cell proteomic properties

Proteomic studies have traditionally focused on population-level analyses with an emphasis on the relative abundance of various proteins. Such studies have been useful in uncovering physiological differences across diverse species, the physiological response of individual species to distinct environmental conditions, and the function of individual proteins in the context of cellular networks. However, the absolute value of protein abundance in a cell is important for understanding single-cell physiology, detailed biophysical considerations, connecting diverse quantitative data, and for comparisons across species. Such detailed quantification will naturally occur as singlecell proteomics becomes more prevalent, but it is also of current interest to leverage population studies. There are several challenges here. First, most population studies do not measure the quantity of cells associated with a proteome. Second, recent work has shown that cell physiology radically shifts with cell size, and these effects need to be accounted for in going from population to single-cell estimates. Here we develop and implement a method to estimate the basic properties of proteomes, based on well-established scaling relationships among cell components, including genome size, cell size, and proteome volume. Our method estimates similar but higher total proteins per cell compared to previous theoretical and empirical estimations. Our algorithm has applications for interpreting proteomes, analyzing environmental samples, and designing artificial cells. While focusing on prokaryotes, we discuss how the method can be extended to unicellular and multicellular eukaryotes.

bioinformatics↗

bioRxiv2023

Foraging guild structure of seabirds

An ecological guild is a group of species that exploit the same resources, or that exploit the same or different resources in a related way. We built The Foraging Guilds of Seabirds database (FGSdb) by compiling a global database of 311 seabird species (from a total of 346 known) and assigning to each of them their diet types and foraging strategy. Across all seabirds, there were found 22 diets and 30 strategies. The number of diet categories for a species varied between 1 and 11, and the number of strategies varied from 1 to 9, with averages of 2.71 and 3.65, being the ratio diet/strategies of 0.74 ([~]3/4), meaning that on average with four strategies they can exploit up to 3 diet items. Beyond this description, we show that the Gusein-Zade model fits well both the frequency rank and number of species per guild distributions. Our database and analyses provide a useful resource database for future studies and demonstrate simple rules behind guild structure.

ecology↗

bioRxiv2023

Foraging specialization and body size in seabirds

Body size affects many biological processes since it predicts traits, timing, and biological rates. Some of these relationships are explained by the metabolic theory of ecology, which predicts that they should scale according to a power law with exponents multiples of [Formula]. Here we study the relationships between foraging specialization, particularly the number of dietary categories and prey capture strategies, and seabird species size, based on a database of 342 species (representing more than 95 % of all species). In our analysis, we found a negative relationship between the number of dietary categories and the number of capture strategies with body size with exponents of -0.83{+/-}0.31 and -0.76{+/-}0.06. To explain these relationships in terms of first principles, we developed a simple model to explain the origin of this scaling based on well-established ecological scaling relationships. Our study suggests that foraging specialization is constrained by the energy used by an organism, providing a basis for future theoretical developments.

ecology↗

bioRxiv2023

Linking metabolic scaling and coexistence theories

Metabolic scaling theory has been pivotal in formalizing the expected energy expenditures across populations as a function of body size. Coexistence theory has provided a mathematization of the environmental conditions compatible with multispecies coexistence. Yet, it has been challenging to explain how observed community-wide patterns, such as the inverse relationship between population abundance density and body size, can be unified under both theories. Here, we provide the foundation for a tractable, scalable, and extendable framework to study the coexistence of resource-mediated competing populations as a function of their body size. For a given thermal domain and response, this integration reveals that the metabolically predicted 1/4 power dependence of carrying capacity of biomass density on body size can be understood as the average distribution of carrying capacities across feasible environmental conditions, especially for large communities. In line with empirical observations, our integration predicts that such average distribution leads to communities in which population biomass densities at equilibrium are independent from body size, and consequently, population abundance densities are inversely related to body size. This integration opens new opportunities to increase our understanding of how metabolic scaling relationships at the population level can shape processes at the community level under changing environments.

ecology↗

bioRxiv2021

A general model for temperature-dependence in biology

At present, there is no simple, complete, and first principles-based model for quantitatively describing the full range of observed biological temperature responses. Here, we derive a theory exhibiting these features based on the Eyring-Evans-Polanyi theory governing chemical reaction rates, and which is applicable across all scales from the micro to the macro. Assuming only that the conformational entropy of molecules changes with temperature, we derive a theory for the temperature dependence which takes the form of an exponential function modified by a power-law. Our framework leads to six deductions applicable to any biological trait that depends on temperature, and elucidates novel aspects of universal temperature responses across the tree of life, from quantum to classical scales. All predictions are well supported by data for a wide variety of biological rates and steady states, from molecular to ecological scales and across multiple taxonomic groups. In addition, we provide novel explanations of several empirical relationships including optimal values in temperature response curves. One-Sentence SummaryWe derive a simple and universal formulae to characterize temperature responses of biological processes across the tree of life.

ecology↗

bioRxiv2019

The tuatara genome: insights into vertebrate evolutionfrom the sole survivor of an ancient reptilian order

The tuatara (Sphenodon punctatus), the only living member of the archaic reptilian order Rhynchocephalia (Sphenodontia) once widespread across Gondwana, is an iconic and enigmatic terrestrial vertebrate endemic to New Zealand. A key link to the now extinct stem reptiles from which dinosaurs, modern reptiles, birds and mammals evolved, the tuatara provides exclusive insights into the ancestral amniotes. The tuatara genome, at [~]5 Gbp, is among the largest vertebrate genomes assembled. Analysis of this genome and comparisons to other vertebrates reinforces the uniqueness of the tuatara. Phylogenetic analyses indicate tuatara diverged from the snakes and lizards [~]250 MYA. This lineage also shows moderate rates of molecular evolution, with instances of punctuated evolution. Genome sequence analysis identifies expansions of protein, non-protein-coding RNA families, and repeat elements, the latter of which show an extraordinary amalgam of reptilian and mammalian features. Sequencing of this genome provides a valuable resource for deep comparative analyses of tetrapods, as well as for tuatara biology and conservation. It also provides important insights into both the technical challenges and the cultural obligations associated with genome sequencing.

genomics↗