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bioRxiv2025

Ecological plasticity explains the distribution of sympatric and allopatric mouse lemurs (Microcebus spp.) in northeastern Madagascar

Species distributions are shaped by complex biotic and abiotic interactions. We studied major ecological drivers of the distribution of four cryptic mouse lemur species (Microcebus spp.) in northeastern Madagascar, across sympatric and allopatric ranges. Using structural habitat characteristics, adaptability to habitat degradation, bioclimatic niches, and morphology, we estimated n-dimensional hypervolumes of niche sizes and overlaps. Annual body mass variability was analyzed as an indicator of heterothermy, a potential indicator for ecological plasticity. M. jonahi and M. simmonsi were found almost equally often in forest- and fallow-derived habitats (52% and 58%, respectively), while M. lehilahytsara predominantly occupied fallow habitats (71%), likely driven by the coexistence with other species. M. lehilahytsara exhibited the largest niche and range size, followed by M. jonahi and M. simmonsi. In contrast, M. macarthurii was restricted to a narrow niche and range. M. jonahi and M. simmonsi displayed significant fat deposition before the austral winter, indicating heterothermy as an adaptation to unpredictable environmental conditions. These species were only found in allopatry, likely due to competition for critical resources like sleeping sites. The smaller M. lehilahytsara coexisted with M. jonahi and M. macarthurii potentially by adjusting its niche to avoid competition with these larger-bodied species. We hypothesize that heterothermy allowed M. jonahi, M. simmonsi, and M. macarthurii to persist in lowlands during Pleistocene climatic challenges but that it did not promote coexistence. In contrast, M. lehilahytsara may have lost lowland distributions due to a lower ability to store fat. Our findings require further testing but provide a plausible explanation for a complex distributional pattern of sympatric and allopatric occurrences.

ecology↗

bioRxiv2025

Revealing the organization of species stability in ecological communities

Ecological communities are often composed of many species, each interacting in complex ways. This complexity makes predictions of species responses to disturbances challenging. Here, we analyze dynamical community models and reveal an unexpectedly simple principle: species stability is governed by a single metric--self-regulation loss (SL). SL quantifies the importance of self-regulatory processes in species population dynamics. In effect, SL captures a collective outcome of species interactions, organizing how individual species respond to disturbances. When applied to data from protist community experiments, SL accurately forecasts species responses to temperature changes. Our work reveals that, despite the complexity of ecological systems, species stability follows a remarkably simple organizing principle.

ecology↗

bioRxiv2025

A Method for Preparing Morphologically Preserved Wildlife Fecal Specimens for Long-Term Ecological Studies

O_LIWildlife feces are a valuable noninvasive resource in ecological and conservation research. However, traditional preservation methods are unable to maintain morphological integrity while simultaneously preserving the biological and chemical composition of fecal samples. C_LIO_LIThis study presents a novel method for the preparation of fecal specimens through a multistep immersion process using sodium carboxymethyl cellulose, sodium benzoate, clotrimazole, ethanol, pyrethroid emulsion and polyvinylpyrrolidone solution. C_LIO_LIThe specimens produced by this method exhibited high mechanical strength, ensuring durability and resistance to handling damage. During a storage period of six months, this method successfully preserved the morphological characteristics of fecal samples while maintaining DNA integrity, with no signs of mold or insect damage. DNA extraction achieved a 100% success rate and species identification remained consistent with fresh samples, with BLAST match rates exceeding 99% in 15 specimens. In addition, heavy metals such as chromium, arsenic, and lead were detected in fecal samples from different species. C_LIO_LIBy allowing long-term preservation of fecal samples, this method transforms urine from a short-term diagnostic tool into a durable resource for monitoring biodiversity. It can extend the applications of fecal samples across spatial and temporal scales, reinforcing their role in ecological research and global conservation of biodiversity. C_LI

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bioRxiv2025

Predicting long and short-term species persistence following invasion of ecological communities

Large ecological communities are underpinned by a complex web of interactions whose exact structure, strength and signs are tremendously elusive. While many large-scale patterns in such communities are well-understood and predictable, the outcomes of processes such as invasions are still difficult to analyze. Given that the assembly history of communities is marked by invasion events at many points in time, it is useful to identify those aspects of invasions that can be reliably predicted even if the exact invasion outcomes cannot be determined. We introduce the notion of proximate uninvadable systems and use these to develop a framework for predicting the structural outcomes of invasion events, i.e., what species are present/absent in the eventual equilibrium. The method is particularly illuminating in large ecological communities and applies even when the invading species is initially abundant. We test this method on a broad class of settings and also demonstrate its robustness against imperfect knowledge of species interactions. Using an example of a large food-web from peri-Alpine lakes, we show how this framework can be applied to systems with fluctuating species abundances. Given that these systems exhibit large fluctuations for prolonged periods of time, we make forecasts for extinction risk in the short term thereby extending the purview of our predictive apparatus.

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bioRxiv2025

Ecological Toxicity Effects of Marine Pollutants Based on Microalgal Locomotory Behavior

Understanding the ecological toxicity of marine pollutants is essential for assessing marine environmental quality and developing effective protection strategies. This study presents a novel approach using the motility of the marine microalgae as a sensitive physiological indicator for rapid toxicity assessment. Results demonstrated that both copper (0{micro}mol l-1-4.4{micro}mol l-1) and phenol (0mmol l-1-9.1mmol l-1) significantly inhibited algal locomotory behavior parameters (movement patterns, mobility, and swimming speed) within 2 hours, exhibiting clear dose-response relationships. The 2 h-EC50 values determined by logistic regression were 2.2{micro}mol l-1-2.7{micro}mol l-1 for copper and 4.5{micro}mol l-1-5.7 mmol l-1 for phenol. Notably, combined exposure showed antagonistic effects (2 h-EC50 >1 TU). The motility-based assay showed strong correlation with traditional toxicity tests (72h growth inhibition, 24-48 h Daphnia immobilization, and 96h fish mortality), while providing significant advantages in speed and sensitivity. These findings establish microalgal motility as an efficient, ecologically relevant biomarker for comprehensive marine pollutant assessment, offering great potential for environmental monitoring and risk evaluation.

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bioRxiv2025

Dogs gone wild: habitat use and ecological impacts of feral dogs in sub-Antarctic Chile

Feral dogs (Canis familiaris) are an emerging threat to biodiversity on Navarino Island, Chile, where they have become apex predators in the absence of natural carnivores. This study evaluated the spatial distribution of feral dogs and their impacts on native species, including guanacos (Lama guanicoe), upland geese (Chloephaga picta), and flightless steamer ducks (Tachyeres pteneres). Presence-only data collected during two field expeditions were analysed using species distribution models (MaxEnt) to predict habitat suitability for feral dogs and guanacos. Habitat connectivity analyses identified at least two potentially isolated feral dog populations. Using generalised linear and non-linear models, we assessed the ecological impacts of feral dogs, finding significant habitat overlap with guanacos, particularly in central areas of the island. This overlap corresponded to a reduced likelihood of guanaco occurrence, suggesting behavioural adaptations to disturbance and predation pressure. Upland geese exhibited a negative association with both actual and predicted feral dog presence, while flightless steamer ducks appeared unaffected. Furthermore, NDVI changes observed on Navarino Island compared to Torres del Paine, where no invasive species are present, are likely linked to the spread of invasive species and the decline of guanacos in the Magellanic forest, highlighting the cascading ecological consequences of feral dog invasion. Our findings emphasise the urgent need for feral dog management to protect vulnerable species and maintain ecosystem health, particularly in fragile environments where invasive predators can have disproportionate impacts. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=115 SRC="FIGDIR/small/652634v2_ufig1.gif" ALT="Figure 1"> View larger version (46K): org.highwire.dtl.DTLVardef@8a746borg.highwire.dtl.DTLVardef@1e12027org.highwire.dtl.DTLVardef@10617c6org.highwire.dtl.DTLVardef@102ccca_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIInvasive species presence leads to environmental changes and potential tipping points C_LIO_LIFeral dogs pose major harm as an invasive species C_LIO_LIEndemic wildlife adapts their behaviour such as habitat use to avoid dog predation C_LIO_LISpecies diversity and population stability are higher in areas with no feral dogs C_LIO_LIDogs in general should be removed from the wild C_LI

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bioRxiv2025

The roles of space and food web complexity in mediating ecological recovery

Landscape-scale ecological restoration is a key strategy for halting and reversing biodiversity decline. However, ensuring the long-term sustainability of restoration efforts requires guiding the recovery of complex ecological systems with many interdependent species at a landscape scale. Due to these challenges, our understanding of recovery trajectories remains limited. Using experiments and metapopulation models, we explore how the spatial configuration of communities and food web complexity jointly influence species recovery at different spatial scales. We find that the number and spatial placement of communities affects the colonisation of empty habitat patches, but does not influence population recovery in patches where communities are introduced. Food web complexity reduces the recovery of lower trophic levels, both at population and metapopulation scales. However, this negative effect may be partially mitigated at higher levels of food web complexity. Our results demonstrate that the joint consideration of spatial configuration and species interactions could enhance the effectiveness of restoration actions.

ecology↗

bioRxiv2025

The environmental dependence of ecological interactionnetworks

Interactions between species are often assumed to occur whenever species pairs co-occur, allowing us to reconstruct local ecological networks from a deterministic "metaweb". Thus, a species set of metaweb interactions defines its Eltonian niche - the biotic conditions under which it can exist. However, both species and interactions may also have Grinnellian niches, reflecting relationships between probability of occurrence and environmental conditions. Over the past few years, we have explored how stochasticity in the occurrence of species and links, and environmental imprints on these, shape ecological interaction networks. In this perspective, we use a set of our empirically-characterised networks to show that both species and link occurrence are stochastic, with probabilities conditional on the environment. This insight improves our ability to model observed variation in network structures. We argue that future research should incorporate environmental impacts on both species and links, thus merging the Grinnellian and the Eltonian niche concept.

ecology↗

bioRxiv2025

monitoraSom: an easy path from Soundscapes to Ecology

Soundscape analysis for biodiversity monitoring with data from autonomous recorders has become a vital tool for biodiversity research. Yet, workflows fragmented across multiple software and technical barriers make the analysis of such large datasets a challenging task. Here, we present monitoraSom, an efficient and user-friendly toolbox that facilitates the path between Passive Acoustic Monitoring (PAM) with ecological studies. This R package includes (1) modular workflows adaptable to diverse study designs, (2) an efficient and responsive user interface for fast soundscape recording segmentation; (3) validation methods adaptable to most data availability scenarios, including an interface for manual validation, and (4) dynamic diagnostics for threshold optimization to refine detection performance. The package is designed for scalability, with simple and easy to use batch processing and parallelization options, as well as simple data formats, making it accessible to beginners and advanced users. By reducing the technical hurdles and ensuring reproducibility, it accelerates the transformation of acoustic data into ecological information from rare species monitoring to community level surveys.

ecology↗

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

Automated quantification of ecological interactions from video

O_LIEcological interactions, such as predation, are fundamental events that underlie the flow and distribution of energy through food webs. Yet, directly measuring interaction rates in nature and how they vary across space and time remains a core challenge in ecology. C_LIO_LITo address this, we developed a machine learning pipeline that combines object detection, tracking, behavioural classification, and bias correction to automatically quantify interaction rates from video. We applied this pipeline to estimate feeding rates of the planktivorous reef fish Chromis multilineata in situ. C_LIO_LIWe show that the tool generates precise, unbiased estimates of planktivory at fine temporal and spatial scales, and use it to reveal how feeding rate changes in response to predator presence and proximity to refuge. C_LIO_LIMore broadly, this method provides a scalable, non-invasive framework for quantifying interactions in the wild, enabling new opportunities to test ecological theory and quantify energetic fluxes in nature. C_LI

ecology↗

bioRxiv2025

Stochastic Forces in Microbial Community Assembly: Founding Community Size Governs Divergent Ecological Trajectories

Biological community dynamics are organized by the interplay of deterministic and stochastic processes. While species responses to biotic and abiotic environments determine the attractors of community compositions, stochastic processes, especially those in early stages of community assembly, can drastically influence the direction of temporal ecological dynamics. Nonetheless, establishing quantitative insights into the roles of stochastic processes has remained a major challenge. By developing a multi-replicated experimental system for tracking community assembly, we quantitatively evaluated the extent to which stochasticity could cause the divergence of community dynamics. We constructed soil- and freshwater-derived experimental microbial assemblages (microbiomes) with varying foundation community size, thereby controlling variation in initial community compositions among replicate communities (i.e., initial stochasticity). An analysis of > 3,000 community samples across four time points then indicated that higher levels of initial stochasticity could result in greater divergence of population- and community-level consequences. From the quantitative perspective, conspicuous differentiation into alternative trajectories of community assembly occurred when the absolute number of founding prokaryotic cells was less than the order of 104. Furthermore, the replicate microbiomes differed in dominant Pseudomonas species, suggesting divergence into alternative transient/stable states through competitive exclusion between species occupying similar niches. Overall, our experiment showed that quantitative differences in stochasticity could result in qualitative differences in the fate of ecological communities. Further quantitative insights into stochasticity in community assembly will reorganize our views on biological invasions, agroecosystem microbiome management, and therapeutics of human-associated microbiomes.

ecology↗

bioRxiv2025

High throughput in situ imaging reveals complex ecological behaviour of giant marine mixotrophic protists

Mixotrophic organisms have the ability to combine photosynthetic and heterotrophic nutrition, and are ubiquitous in marine ecosystems. Here, we focus on Rhizaria, a diverse group of planktonic protists that included both mixotrophic and non-mixotrophic taxa, and that are particularly delicate and poorly sampled by standard plankton nets. Using high-frequency in situ imaging, we study the ecology of these organisms directly in their undisturbed environment. We examined the fine-scale distribution and orientation of ~230,000 organisms belonging to three groups of Rhizaria, including the mixotrophic taxa Acantharia and Collodaria, and the non-mixotrophic Phaeodaria. Overall, our results suggest that mixotrophic protists have better ability to control their position within the water column (depth, orientation) than non-mixotrophic ones. Our observations also point to several steps in the obscure life cycle of the mixotrophic Collodaria, during which de novo symbiont acquisition appears to involve active fine-scale buoyancy control. Taken together, these unprecedented results demonstrate that complex ecological behaviour can be achieved by "simple" organisms.

ecology↗

bioRxiv2025

Ecological processes shaping marine microbial assemblages diverge between equatorial and temperate time-series

Marine microbial communities are structured by a complex interplay of deterministic and stochastic processes, yet how these vary across latitudes remains poorly understood. Most long-term microbial observatories are restricted to temperate regions, limiting our ability to assess latitudinal contrasts in microbial dynamics. Here, we compare coastal microbial communities from two contrasting marine time-series stations using standardized molecular protocols: a new tropical site in the Equatorial Atlantic (EAMO, 6{degrees}S) and a well-studied temperate site in the Mediterranean Sea (BBMO, 41{degrees}N). Monthly 16S and 18S rRNA gene sequencing of two size-fractions (0.22-3 {micro}m and >3 {micro}m) over 41 months (from April 2013 to August 2016) revealed marked differences in taxonomic composition, temporal variability, and ecological assembly processes. Temperate communities exhibited strong seasonal turnover, higher beta-diversity, and tighter coupling with environmental variables such as temperature and daylength. In contrast, tropical communities were compositionally more stable and more governed by biotic factors and stochastic processes such as historical contingency and ecological drift. These patterns were consistent across taxonomic domains and size-fractions, though selection was generally stronger in prokaryotes and the smallest size-fraction. Co-occurrence networks at the temperate site were more densely connected and environmentally responsive compared to tropical networks, where stochastic processes and putative biological interactions gain prominence. This study highlights the importance of integrating observatories from underrepresented latitudes into global microbial monitoring efforts, particularly as climate change alters the amplitude and frequency of environmental drivers across the ocean.

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bioRxiv2025

Seeing the forest and the trees: a workflow for automatic acquisition of ultra-high resolution drone photos of tropical forest canopies to support botanical and ecological studies

Tropical forest canopies contain many tree and liana species, and foliar and reproductive characteristics useful for taxonomic identification are often difficult to see from the forest floor. As such, taxonomic identification often becomes a bottleneck in tropical forest inventories. Here we present a drone-based workflow to automatically acquire large volumes of close-up, ultra-high resolution photos of selected tree crowns (or specific locations over the canopy) to support tropical botanical and ecological studies (https://youtu.be/80goMEifpc4). Our workflow is built around the small, easy-to-use DJI Mavic 3 Enterprise (M3E) drone, which is equipped with a wide-angle and a telephoto camera. On day one, the pilot maps a forest area of up to [~]200 ha with the wide-angle camera to generate a high-resolution digital surface model (DSM) and orthomosaic using structure-from-motion (SfM) photogrammetry. On subsequent days, the pilot acquires close-up photos with the telephoto camera from up to 300 selected canopy trees per day. These close-up photos are acquired from 6 m above the canopy and contain a high level of visual detail that allows botanists to reliably identify many tree and liana species. The photos are geolocated with survey-grade accuracy using RTK GNSS, thus facilitating spatial co-registration with other data sources, including the photogrammetry products. The primary operational challenge of our workflow is the need to maintain RTK corrections with the drone to ensure that close-up photos are acquired exactly at the predefined locations. The maximum operational range we achieved was 3 km, which would allow the pilot to reach any tree within a [~]2800 ha area from the take-off point. Although our workflow was developed to support taxonomic identification of tropical trees and lianas, it could be extended to any other forest or vegetation type to support botanical, phenological, and ecological studies. We provide harpia, an open-source Python library to program these automatic close-up photo missions with the M3E drone (https://github.com/traitlab/harpia). Data/code for peer review statementWe provide harpia, an open-source Python library to program these automatic close-up photo missions (https://github.com/traitlab/harpia). Drone imagery and labelled close-up photo data are not yet publicly available because they were acquired with the goal of publishing benchmark machine learning datasets and models for tree and liana species classification and prior publication of the data would jeopardize this future publication.

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bioRxiv2025

A system dynamics model to understand the integrated ecological and human dimension aspects of wildlife health and disease management

Chronic wasting disease (CWD) presents an ongoing challenge for the management of deer populations and sustaining harvest opportunities across North America. Existing disease models often fail to fully capture the complex interplay between disease dynamics, host ecology, and socio-economic factors. We developed a comprehensive system dynamics (SD) model that integrates demographic, epidemiological, ecological, and socio-economic processes within a single model to more fully characterize the complex network of causal feedbacks throughout the system. The model was calibrated using a Bayesian approach that incorporates prior knowledge to generate biologically interpretable outcomes, even with sparse data. For estimating the joint posterior distribution of model parameters, we leveraged time series of deer abundance, harvest composition, genetic profiles, CWD surveillance, and hunter demographics and behavior. Model outputs reproduced key system behaviors, including observed CWD prevalence trends, deer population dynamics, and hunter license purchasing patterns. Model predictions were most sensitive to parameters governing initial deer population size and recruitment. While model predictions generally aligned with observed data, discrepancies in early CWD detection and overestimation of the reactivation of long-inactive hunters reflect data limitations and modeling challenges. Key results suggest that indirect transmission is necessary to explain observed prevalence, that transmission is moderately density-dependent, and that observed population-level genetic shifts driven by CWD may play a role in transmission and progression. The SD modelling approach enabled estimation of difficult-to-measure parameters and identified potential leverage points for management--such as prioritizing increasing participation in antlerless harvest of existing hunters over the recruitment of new hunters. This integrated modeling approach offers a flexible foundation for adaptive wildlife disease management and emphasizes the value of unifying biological and human dimension processes to better inform effective, evidence-based policy.

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bioRxiv2025

Generating ecological baselines on short-grass formations or grazing lawns in Central Terai landscape

Short-grass formations or the "grazing lawns" as they are popularly called support large congregations of mammalian herbivores globally. These systems are known to be maintained by cyclic process of grazing and nutrient deposition in the soil by foraging animals. The basic ecological characteristics of these short-grass systems have extensively been studied in the African context with little understanding particularly from the Himalayan foothills in Terai. In this study, we focused on understanding the ecological baselines such as grass species associations and associated nutrient content in these grazing lawns and tall grass formations across two protected areas of the Uttar Pradesh Terai in India. Our results show that, the protected areas had relatively similar grass species composition and associated nutrient content in the short-grass formations. However, when compared with tall grass formations, the grazing lawns differed markedly in both their grass associations and thus forage quality. Therefore, the results from this study indicate the need to maintain such grazing lawn habitats within the characteristic tall-wet grasslands of the Terai. This also indicates the importance of short-grass formations in providing palatable forage to the mammalian herbivores particularly in peak dry seasons of autumn and winters.

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bioRxiv2025

Ecological context shapes microbial contributions to nutrition and development in Drosophila melanogaster

Microbial symbionts play a critical role in shaping insect development by supplying essential nutrients, influencing host phenotype, and mediating context-dependent mutualistic outcomes. In the fruit fly Drosophila melanogaster, larvae develop in ephemeral breeding substrates such as decaying fruits, where they acquire maternally transmitted bacterial and fungal symbionts. These substrates vary in their structural and chemical properties, potentially altering the composition and function of associated microbial communities. Here, we combine semi-natural microcosm experiments with compound-specific isotope analysis of essential amino acids to assess how variation in fruit substrate and symbiont origin affect larval nutrition, development, and adult phenotypes. We find that microbial community composition and environmental context jointly shape amino acid flow, with larvae deriving variable proportions of their nutrition from plant, bacterial, and fungal sources. These differences translate into distinct developmental outcomes, including shifts in larval development time - either delayed or accelerated, depending on the symbiont-substrate combination - and significant variation in adult body weight. Our findings introduce symbiont-environment interactions as a framework for understanding how ecological context shapes nutritional mutualisms, showing that environmental heterogeneity can alter microbial composition, nutrient sources, and larval performance. Together, these results reveal how ecological context modulates mutualistic dependence and underscores the context sensitivity of host-microbe associations.

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