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bioRxiv2026

An ecological model of masting reproduction matches empirical dynamics

Masting, characterized by highly variable, synchronized, and intermittent seed or fruit production, represents a common reproductive strategy among perennial plants and has profound ecological consequences. Resource provisioning and pollen limitation have long been viewed as central physiological mechanisms underlying this strategy, recent empirical evidence also highlights the role of weather cues in initiating and synchronizing reproductive effort. Drawing on mechanisms that drive periodicity in disease dynamics, this study proposes an alternative proximate mechanism for masting. We develop and analyze a stage-structured population growth model in which developmental delays create population-level cycles, and demographic stochasticity adds individual-level variation; together, yielding masting-like patterns. We compare the behaviour of this novel model with that of the widely used resource budget model and empirically observed patterns of masting in perennial plants. To quantify and compare model outputs and empirical observations, we employ three continuous metrics of masting that capture volatility, synchrony, and periodicity. Our study provides an alternative proximate mechanism for masting. Comparison of this novel mechanism and the established resource-budget model to empirical time-series reveals that both represent realistic yet distinct forms of masting reproduction. Together, these models provide a foundation for further exploration of the conditions under which this reproductive strategy can evolve. Beyond masting, our results highlight the general importance of life-history timing and demographic stochasticity in shaping population ecology.

ecology↗

bioRxiv2026

Adult corals enhance juvenile recruitment through cumulative ecological niche construction

Ecosystem engineers are ecological niche constructors: by modifying local environments, they alter the conditions under which organisms establish, persist and interact. Although niche construction is often framed as a population-level evolutionary feedback, it could also operate at the assemblage level when communities collectively shape their environments and filter future recruitment. Reef-building corals provide a perfect system to test this idea because adult colonies form three-dimensional carbonate structures that can persist after colony death, creating an inherited habitat for subsequent coral generations. Here, we tested whether coral recruitment to the juvenile stage was associated with local adult coral abundance, reef structure, and larval settlement supply. Combining spatially explicit coral censuses, photogrammetric reef digital elevation models and data from settlement tiles across 15 reef sites at two time points at Jiigurru, Great Barrier Reef, we found that juvenile abundance increased additively on the log scale with adult abundance and with fractal dimension, a metric of fine-scale structural complexity. Surface rugosity had weaker effects, and interactions between adult abundance and habitat structure were limited, indicating largely additive, rather than synergistic or antagonistic, effects. Our results show that both adult assemblages and the concurrent structural complexity, consistent with assemblage-level niche construction and ecological inheritance theory, shape coral recruitment.

ecology↗

bioRxiv2026

Towards predictive ecological biogeography: Predicting vegetation type using fine-scale measurements of the abiotic environment

One of the goals of ecological biogeography is to accurately predict where major vegetation types, such as forests or grasslands, can establish themselves. Alas, our current understanding of the mechanisms by which environmental variables jointly influence vegetation types does not allow for such predictions. Here, we compile a database of local measurements of soil, weather, topography, and bedrock lithology for 6404 sites across the continental United States, which we complement with information about the vegetation around the measurement sites. By applying machine learning methods to a subset of the sites, we are able to train a machine that predicts - using only information about abiotic variables - the presence of forests or grasslands with nearly 90% accuracy on the rest of the sites. We find that while weather variables are statistically important for these predictions, a few soil variables prove to be the most powerful predictors. By separating the combined contributions of weather and soil, we show that soil texture is a better predictor under dry conditions than under wet conditions, while pH is important predictor regardless of the weather. Furthermore, from 136 sites undergoing grassland-to-forest succession, our analysis indicates that soil pH changes with a certain lag relative to vegetation change. Sites that have recently undergone a transition exhibit a higher pH, closer to that of grasslands, despite the presence of trees. The pH then decreases by about one unit over a 30-year period of forest development. Ultimately, our results indicate that fine-scale environmental measurements and historical ecological data can serve as a basis for quantitative bio-geographical predictions, which could eventually guide targeted conservation interventions.

ecology↗

bioRxiv2026

When does heterogeneity average out in coarse-grained ecological communities?

Ecological coarse-graining of individuals or species into aggregate variables, such as total biomass or regional abundance, is common practice, yet differences among species can still influence aggregate dynamics. We propose a metric for quantifying this irreducible dynamical heterogeneity. For small fluctuations near a stable equilibrium, we compare the aggregate fluctuation spectrum of the full dynamical system with that of the best Ornstein-Uhlenbeck model having the same dimension as the aggregate. The remaining spectral mismatch quantifies the dynamical effects of hidden differences that the fitted aggregate model cannot capture. For weakly interacting random community models at fixed collective interaction strength, we show that increasing species richness can either reduce or increase this heterogeneity, depending on how species interact. Our framework helps understand when ecological and evolutionary differences average out versus when their dynamical effects persist.

ecology↗

bioRxiv2026

Human-wildlife conflict shows shared spatial predictors across ecological and geographic contexts

Human-wildlife conflict (HWC) is a global challenge for biodiversity conservation, food security, and human well-being. Effective management towards human-wildlife coexistence, recognized as a priority in Target 4 of the Kunming-Montreal Global Biodiversity Framework, requires understanding the drivers of HWC. However, the strong influence of local human and ecological context means that most HWC research focuses on individual case studies, limiting transferability of patterns across contexts. Here, we link local contexts and transferable drivers by testing whether HWC exhibits an intermediate level of organization, in which local predictor profiles are structured by broader ecological, geographic, and taxonomic contexts. After compiling ~11,000 conflict incidents, we construct and compare random forest models across 29 mammalian HWC scenarios spanning diverse species, conflict types, biomes, and continents to identify contexts in which predictor profiles converge. While predictors varied among individual conflicts, HWC scenarios were organized by shared context: conflicts occurring within the same biome tended to have similar predictor profiles, with continent and taxonomic group providing additional structure. Proximity to protected areas was the most consistently important predictor of HWC globally. The likelihood of conflict increased with human population density across nearly all scales and contexts, while distance to roads was also an important predictor in many contexts. Together, these results demonstrate an intermediate level of organization in HWC that reconciles case-specific variation with broader patterns across biomes, continents, and taxonomic groups. This framework provides a basis for scaling mitigation strategies beyond individual case studies while avoiding one-size-fits-all approaches.

ecology↗

bioRxiv2026

Evidence for a central ecological function of predatory Myxococcota in soil ecosystems

Myxococcota is a recently classified phylum including bacteria renowned for their predatory lifestyle. However, ecological functions of these bacteria remain under studied. Here, we examined the ecological position and potential impact of Myxococcota communities across diverse soil habitats using the global geographical collection of 16S microbial communities structured by the Earth Microbiome Project (EMP). First, we found that the abundance of Myxococcota varied greatly from 6.3% to 0.8% across 13 soil habitats. A deeper microbial analysis in two selected habitats showed that Myxococcota was highly abundant (4.9%) ranking 5 in field soil (a grassland planted with switchgrass) than in sand biofilter (an engineered system for water quality production, 1.3% and 11, resp.). Moreover, both Myxococcota and microbial communities displayed a significantly higher -diversity in field soil than in sand biofilter environments, suggesting that diversity of Myxococcota seems to be associated with that of microbial communities in these habitats. Using co-occurrence network analysis, we found that Myxococcota exhibited a high eigenvector centrality (5.1%) and one hub taxon, Polyangiales, in field soil habitat. In contrast, Myxococcota centrality was less pronounced (1.1%) in the sand biofilter, where consistent negative correlations were also detected. Altogether, these results suggest that Myxococcota communities experienced beneficial interactions in field soil environment, whereas they may have faced competitive relationships in sand biofilter habitat. Overall, our findings provide further insights into the status of Myxococcota communities in soil environments, suggesting their fundamental roles in the structure of soil microbial communities.

ecology↗

bioRxiv2026

Stop guessing thinning distances: a data-driven framework for spatial thinning parametrization for ecological modelling

Spatially heterogeneous sampling and uneven publication effort in biodiversity repositories limit ecological niche characterization and habitat suitability modelling, affecting downstream inferences at regional and global scales. Spatial thinning offers a widely used strategy to mitigate these biases due to its simplicity and scalability. However, researchers typically select thinning parameters using heuristic or arbitrary criteria, often independent of species-specific characteristics, which introduces an additional, largely unquantified source of potential error. Here, we propose a data-driven framework for spatial thinning parameterization that replaces heuristic decision-making with principled, reproducible criteria. We define optimality as the stability of thermal niche estimates derived from empirical data, rather than as an agreement with a known true distribution. The framework integrates two complementary approaches. The Last Stable Thinning Parameterization (LS-TP) identifies the largest thinning intensity that preserves the stability of species-specific niche descriptors. Biogeographic-size Dependent Thinning Parameterization (BD-TP) links thinning intensity to species' geographic range size and scales spatial filtering across taxa with different distributional properties. Using seagrasses as a model system, we evaluated the framework across a global compilation of more than 100,000 occurrence records. Our results showed that optimal thinning parameters varied systematically with species range size and that uniform thinning approaches led to either excessive information loss or reduction of spatial clustering. Furthermore, the framework identified species for which available data did not support stable niche characterization, as these species failed to meet stability criteria even at the smallest thinning parameters. We recommend explicitly acknowledging this limitation in future studies and prioritizing increased sampling effort for such undersampled taxa. Our approaches provide a first step toward explicit, data-driven spatial thinning parameterization, with direct implications for ecological niche modelling, biodiversity assessment, and climate-driven distribution analyses.

ecology↗

bioRxiv2026

The ecological niche and seasonality of Theileria equi in Portugal

Equine piroplasmosis, caused by the tick-borne protozoan Theileria equi, is an evolving concern in Europe. In recent years, it has been associated with substantial economic costs and with transmission showing signs of pushing into previously free or marginal northern regions. While piroplasmosis is endemic in Portugal, not much is known about the interplay of seasonally varying and spatial abiotic drivers that may modulate infection. In this study, we leveraged unique field-surveillance data based on equine PCR testing together with publicly available data to unravel and characterize the spatio-temporal dynamics and ecological niche of Theileria equi. Infection probability was estimated to increase with local bovine abundance, temperature and the presence of planosol soils, and to decrease with local equine density due to an intraspecific dilution effect of vector exposure. At an individual level, the highest infection probabilities were estimated among female and pasture-kept equids. We estimate strong seasonal signatures in local and national infection probability, maximized in August and minimized in February, and a spatially heterogeneous ecological niche landscape. Far northern and north-eastern regions combined low infection probability both in- and off-season with prolonged off-seasons, whereas centre and north-western regions combined high probability both in- and off-season with brief off-seasons. The former plausibly function as unsuitable reservoirs, and the latter as suitable year-round reservoirs. Our results provide a first quantitative, risk-stratified basis for regional and individual targeted Theileria equi surveillance, awareness and control in Portugal.

ecology↗

bioRxiv2026

Ecology of gene drives: Organism fitness under larval competition determines gene drive performance

Gene drives are a promising technology to control disease vectors, such as mosquitoes. However, as these interventions aim to modify and/or control the population of disease vectors, a full understanding of how gene drives interact with the ecology of the target species is essential. In this study, we explore how larval competition determines gene drive performance. We first extend an agent-based model of the larval behaviour of Aedes aegypti mosquitoes to obtain detailed predictions for gene drive designs under realistic larval competition. Using Bayesian optimisation techniques, we explore the performance of different gene drive designs and find the Pareto frontier of optimal underdominant drives with different release thresholds. To understand what determines the structure of the Pareto frontier, we conduct both local and global sensitivity analyses to assess the role different parameters play in determining gene drive performance. We find that ecological parameters, which determine the behaviour of the organism, dominate over genetic parameters for much of the parameter space, although genetic parameters play an important role at the frontier. Finally, we develop stochastic and deterministic surrogate models to enable efficient comparison and simulation without imposing the computational costs of agent-based approaches.

ecology↗

bioRxiv2014

Ecological and Evolutionary Oscillations in Host-Parasite Population Dynamics, and The Red Queen

In a host-parasite system, the constitutive interaction among the species, regulated by the growth rates and functional response, may induce populations to approach equilibrium or sometimes to exhibit simple cycles or peculiar oscillations, such as chaos. A large carrying capacity coupled with appropriate parasitism effectiveness frequently drives long-term apparent oscillatory dynamics in population size. We name these oscillations due to the structure of the constitutive interaction among species as ecological.\n\nOn the other hand, there are also exceptional cases when the evolving quantitative traits of the hosts and parasites induce oscillating population size, which we call as evolutionary. This oscillatory behavior is dependent on the speed of evolutionary adaptation and degree of evolutionary trade-off. A moderate level of negative trade-off is essential for the existence of oscillations. Evolutionary oscillations due to the host-parasite coevolution (known as the Red Queen) can be observed beyond the ecological oscillations, especially when there are more than two competing species involved.\n\nOne Sentence SummaryWe investigate several cases yielding to oscillating host-parasite populations, and we found that the Red Queen hypothesis can explain some of the exceptional cases.\n\nGraphical Abstract:\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=114 SRC=\"FIGDIR/small/001735_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (28K):\norg.highwire.dtl.DTLVardef@1280478org.highwire.dtl.DTLVardef@3d6e28org.highwire.dtl.DTLVardef@10b2718org.highwire.dtl.DTLVardef@133a78d_HPS_FORMAT_FIGEXP M_FIG C_FIG

Evolutionary Biology↗

bioRxiv2014

The dark side of theoretical ecology

Good science must be clearly transparent in its theories, models and experiments. Earlier David Tilman drew attention to the fact that ecologists investigate interspecific competition phenomenologically, rather than mechanistically. To create a mechanistic model of a complex dynamic system we need to logically describe interactions of its subsystems which lead to emergence of new properties on the macro-level. There are black-box, grey-box and white-box models of complex systems. Black-box models are completely nonmechanistic. We cannot investigate interactions of subsystems of such non-transparent model. A white-box model of a complex system has \"transparent walls\" and directly shows underlined mechanistic mechanisms - all events at micro-, meso-and macro-levels of the modeled dynamic system are directly visible at all stages. Grey-box models are intermediate. Basic ecological models are of black-box type, e.g. Malthusian, Verhulst, Lotka-Volterra models. These models are not individual-based and cannot show features of local interactions of individuals of competing species. That is why they principally cannot provide a mechanistic insight into interspecific competition. To create a white-box model we need a physical theory of the object domain and its intrinsic axiomatic system. On the basis of axiomatic system there is a possibility to logically generate a new knowledge by logical deterministic cellular automata. Understanding of biodiversity mechanisms is the global research priority. Only knowledge of mechanisms of interspecific interactions can allow us to efficiently operate in the field of biodiversity conservation. Obviously that such knowledge must be based on mechanistic models of species coexistence. In order to create a serviceable theory of biodiversity it is necessary to renew attempts to create a basic mechanistic model of species coexistence. But the question arises: Why ecological modelers prefer to use the heaviest black-box mathematical methods which cannot produce mechanistic models of complex dynamic systems in principle, and why they do not use simple and long-known pure logical deterministic cellular automata, which easily can produce white-box models and directly generate clear mechanistic insights into dynamics of complex systems?

Preprint↗

bioRxiv2014

SpeciesGeoCoder: Fast categorisation of species occurrences for analyses of biodiversity, biogeography, ecology and evolution

Understanding the patterns and processes underlying the uneven distribution of biodiversity across space and time constitutes a major scientific challenge in evolutionary biology. With rapidly accumulating species occurrence data, there is an increasing need for making the process of coding species into operational units for biogeographic and evolutionary analyses faster, automated, transparent and reproducible. Here we present SpeciesGeoCoder, a free software package written in Python and R, that allows for easy coding of species into user-defined areas. These areas may be of any size and be purely geographical (i.e., polygons) such as political units, conservation areas, biomes, islands, biodiversity hotspots, and areas of endemism, but may also include altitudinal ranges. This flexibility allows scoring species into complex categories, such as those encountered in topographically and ecologically heterogeneous landscapes. In addition, SpeciesGeoCoder can be used to facilitate sorting and cleaning of occurrence data. The various outputs of SpeciesGeoCoder include quantitative biodiversity statistics, global and local distribution maps, and NEXUS files that can be directly used in many phylogeny-based applications for ancestral state reconstruction, investigations on biome evolution, and diversification rate analyses. Our simulations indicate that even datasets containing hundreds of millions of records can be analysed in relatively short time using a regular desktop computer. We exemplify the use of our program through two contrasting examples: i) inferring historical dispersal of birds across the Isthmus of Panama, separating lowland vs. montane species and optimising the results onto a species-level, dated phylogeny; and ii) exploring seasonal variations in the occurrence of 10 GPS-tracked individuals of moose (Alces alces) over one year in northern Sweden. These analyses show that SpeciesGeoCoder allows an easy, flexible and fast categorisation of species distribution data for various analyses in ecology and evolution, with potential use at different spatial, taxonomic and temporal scales.

Evolutionary Biology↗

bioRxiv2016

Integrating ecological genomics and eco-evo-devo reveals multiple adaptive peaks in ant populations of the Arizona Sky Islands

Uncovering the genetic basis of adaptation is one of the greatest challenges facing modern evolutionary biology, often sparking much controversy, especially among practitioners within different subfields. Here we ask where is the locus of adaptation from the perspective of ecological genomics (ecogen) and evolutionary developmental biology (evodevo). Ecogen focuses on identifying loci under selection between populations living in different environments by scanning genome-wide patterns of genetic divergence, while evodevo focuses on candidate developmental regulatory genes and networks underlying phenotypic differences between species and higher taxa. We attempt to reconcile these alternative perspectives by studying the response of ant populations to past climate change on the Arizona Sky Islands, which are high elevation mountain ranges that represents a replicated natural experiment. We previously showed that adaptation to climatic changes in the Arizona Sky Islands in ant species Monomorium emersoni occurred through repeatable changes within the gene network underlying the development of dispersal alternative phenotypes: winged and wingless queens. Here, we uncover several loci under positive selection which associate with habitat temperature, a pattern consistent with a predictable and repeated increase in frequency following climatic changes on each of the Sky Islands. Furthermore, we show that gene flow between locations within a Sky Island is not a consequence of dispersal phenotypes and its gene network, but rather, is restricted by temperature adaptation along the ecological gradient. This suggests that the determination of winged and wingless queens may be developmentally plastic, and this plasticity and may facilitate jumps between adaptive peaks on the fitness landscape. This complex interplay promotes predictability on both genetic and phenotypic levels for multiple traits in the same species.

Evolutionary Biology↗

bioRxiv2016

Phylogenetic scale in ecology and evolution

AimMany important patterns and processes vary across the phylogeny and depend on phylogenetic scale. Yet, phylogenetic scale has never been formally conceptualized and its potential remains largely unexplored. Here, we formalize the concept of phylogenetic scale, review how phylogenetic scale has been considered across multiple fields, and provide practical guidelines for the use of phylogenetic scale to address a range of biological questions.\n\nMethodsWe summarize how phylogenetic scale has been treated in macroevolution, community ecology, biogeography, and macroecology, illustrating how it can inform, and possibly resolve, some of the longstanding controversies in these fields. To promote the concept empirically, we define phylogenetic grain and extent, scale-dependence, scaling, and the domains of phylogenetic scale. We illustrate how existing phylogenetic data and statistical tools can be employed to investigate the effects of scale on a variety of well-known patterns and processes, including diversification rates, community structure, niche conservatism, or species-abundance distributions.\n\nMain conclusionsExplicit consideration of phylogenetic scale can provide new and more complete insight into many longstanding questions across multiple fields (macroevolution, community ecology, biogeography, macroevolution). Building on the existing resources and isolated efforts across fields, future research centered on phylogenetic scale might enrich our understanding of the processes that together, but over different scales, shape the diversity of life.

Evolutionary Biology↗

bioRxiv2016

Social ecology of a woodland songbird community: from individual movements to the emergence of population social structure

Social structure can have profound evolutionary and ecological implications for animal populations. Structure can arise and be maintained via social preferences or be indirectly shaped by habitat structure. Understanding how social structure emerges is important for understanding the potential links between social structure and evolutionary and ecological processes. Here, we study a large community of wild birds fitted with uniquely-coded passive integrated transponder (PIT) tags and recorded on a grid of automated feeders fitted with radio frequency identification (RFID) antennae. We show that both large-scale and fine-scale network communities are consistent across years in this population, despite high generational turn-over. Studying the process that generates community structure, here the movement of individual birds across the woodland, suggests an important role of habitat geometry in shaping population-level social community structure. Our study highlights how relatively simple factors can produce apparent emergent social structure at the population scale, which has widespread implications for understanding eco-evolutionary dynamics.

animal behavior and cognition↗

bioRxiv2016

Buchnera has changed flatmate but the repeated replacement of co-obligate symbionts is not associated with the ecological expansions of their aphid hosts

Symbiotic associations with bacteria have facilitated important evolutionary transitions in insects and resulted in long-term obligate interactions. Recent evidence suggests that these associations are not always evolutionarily stable and that symbiont replacement and/or supplementation of an obligate symbiosis by an additional bacterium has occurred during the history of many insect groups. Yet, the factors favoring one symbiont over another in this evolutionary dynamic are not well understood; progress has been hindered by our incomplete understanding of the distribution of symbionts across phylogenetic and ecological contexts. While many aphids are engaged into an obligate symbiosis with a single Gammaproteobacterium, Buchnera aphidicola, in species of the Lachninae subfamily, this relationship has evolved into a \"menage a trois\", in which Buchnera is complemented by a cosymbiont, usually Serratia symbiotica. Using deep sequencing of 16S rRNA bacterial genes from 128 species of Cinara (the most diverse Lachninae genus), we reveal a highly dynamic dual symbiotic system in this aphid lineage. Most species host both Serratia and Buchnera but, in several clades, endosymbionts related to Sodalis, Erwinia or an unnamed member of the Enterobacteriaceae have replaced Serratia. Endosymbiont genome sequences from four aphid species+confirm that these coresident symbionts fulfill essential metabolic functions not ensured by Buchnera. We further demonstrate through comparative phylogenetic analyses that co-symbiont replacement is not associated with the adaptation of aphids to new ecological conditions. We propose that symbiont succession was driven by factors intrinsic to the phenomenon of endosymbiosis, such as rapid genome deterioration or competitive interactions between bacteria with similar metabolic capabilities.

evolutionary biology↗

bioRxiv2016

Maximizing ecological and evolutionary insight from bisulfite sequencing data sets

The role of DNA methylation in development, divergence, and the response to environmental stimuli is of substantial interest in ecology and evolutionary biology. Measuring genome-wide DNA methylation is increasingly feasible using sodium bisulfite sequencing. Here, we analyze simulated and published data sets to demonstrate how effect size, kinship/population structure, taxonomic differences, and cell type heterogeneity influence the power to detect differential methylation in bisulfite sequencing data sets. Our results reveal that the effect sizes typical of evolutionary and ecological studies are modest, and will thus require data sets larger than those currently in common use. Additionally, our findings emphasize that statistical approaches that ignore the properties of bisulfite sequencing data (e.g., its count-based nature) or key sources of variance in natural populations (e.g., population structure or cell type heterogeneity) often produce false negatives or false positives, thus leading to incorrect biological conclusions. Finally, we provide recommendations for handling common issues that arise in bisulfite sequencing analyses and a freely available R Shiny application for simulating and performing power analyses on bisulfite sequencing data. This app, available at www.tung-lab.org/protocols-and-software.html, allows users to explore the effects of sequencing depth, sample size, population structure, and expected effect size, tailored to their own system.

genomics↗

bioRxiv2016

Ecological speciation within the Phytophthora group

Over the past few years, symptoms akin to late blight disease have been reported on a variety of crop plants in South America. Despite the economic importance of these crops, the causal agents of the diseases belonging to the genus Phytophthora have not been completely characterized. In this study, we used an integrative approach that leveraged morphological, ecological, and genetic approaches to explore cryptic speciation within P. infestans sensu lato. We described a new Phytophthora species collected in Colombia from tree tomato (Solanum betaceum), a semi-domesticated fruit. All morphological traits and population genetic analyses, using microsatellite data and a reduced representation of single nucleotide polymorphism (SNP) data, support the description of the new species, Phytophthora betacei sp. nov. We have demonstrated that ecological differences are important in the persistence of P. infestans and P. betacei as genetically isolated units across an overlapping area in the northern Andes.

evolutionary biology↗