Biology subjects

Dakos, V.

Publications and source records attributed to Dakos, V..

16 recordsLinked to original sources

bioRxiv2026

ClimLimits: a global database of multivariate realized climate limits for animal species

Introduction and AimAssessing the realized climate limits for a species based on the climate conditions (i.e., different aspects of temperature and precipitation) a species has experienced over its range enables us to determine the climatic boundaries of its existence, and thus its potential exposure to novel climate conditions in the future. We combine species range maps from IUCN and BirdLife International with global climate data from the ERA5 reanalysis and five Earth System Models (ESMs) to produce ClimLimits: a database of multivariate realized species climate limits based on historical temperature and precipitation for terrestrial and freshwater animal species worldwide. Main variables includedFor a total of 54,255 species (24,731 terrestrial, 18,182 freshwater, and 11,342 terrestrial-freshwater species), we estimated 44 species climate limits, which delineate the most extreme climate conditions experienced by a species over its entire range over the last 80 years (1940-2020). The database accounts for three aspects of species climate limits: a) maximum and minimum values of temperature and precipitation experienced over the historical reference period, b) maximum annual variability in temperature and precipitation, and c) maximum frequency, intensity, duration and severity of extreme events (heatwaves, cold-spells, and droughts). Climate data is sourced from the ERA5 reanalysis and from five different Earth System Models (ESMs), producing 6 different subsets of the ClimLimits database. Time coverageSpecies climate limits are estimated based on historical climate records from 1941-2014 (5 ESMs) and 1940-2020 (ERA5). Temperature-based limits are inferred at a daily scale, while precipitation-based limits are inferred at a monthly and yearly scale. Spatial coverageGlobal, over 24km x 24km grid-cells. TaxaTerrestrial and freshwater taxa, including amphibians, birds, mammals, reptiles, freshwater fish, and freshwater invertebrates, with shapefiles from IUCN and BirdLife International. Data is produced at the species level. ApplicationsClimLimits provides ready-to-use standardized realized climate limits for individual species across multiple aspects of climate, facilitating global-scale assessments of macroecological patterns and climate exposure risk for species.

ecology↗

bioRxiv2026

Predator coexistence and herbivore suppression are shaped by predator functional types in intraguild predation modules

Coexistence of multiple predators in ecological communities and their combined effects on the abundance and diversity of shared prey are often difficult to predict. In some theoretical models, predator coexistence is limited by antagonistic interactions, especially in the form of intraguild predation (IGP) that typically leads to out-competition between predators and high prey densities. However, empirical studies show that predator coexistence is common even in the presence of IGP. This discrepancy between theoretical expectations and empirical observations can be highly relevant for practical applications like using multiple natural enemies for pest suppression in agriculture. It is proposed that greater functional differences between natural enemies (i.e. predators) could reduce competition and overcome the negative effects of IGP, thereby promoting their coexistence and enhancing herbivore (i.e. prey) suppression. In this study, we theoretically explore this proposition. We develop a theoretical model based on the types of natural enemies of aphids to identify how functional differences between predators in IGP modules affect predator coexistence and herbivore suppression. We show that pairwise combinations of four functional predator types (ladybird, predatory bug, hoverfly, and parasitoid) can increase the coexistence range for different intraguild predation and competition strengths between predators (IGP symmetry), along a productivity gradient. This outcome depends on the external food input rate for the predatory bug and hoverfly types, and on their position as IG predator or IG prey. Herbivore suppression was primarily driven by IGP symmetry (i.e. the relative intraguild predation and exploitative competition strength between predators) and was especially pronounced in competitive-like modules where the IG predator was excluded for most scenarios. However, for some competitive-like IGP modules with predatory bug and hoverfly types, both predators can persist and provide a high herbivore suppression across increasing productivity. Our results can help explain experimental findings in conservation biocontrol, where coexistence between natural enemies is joined with effective herbivore suppression, and offer additional support for the role of functional diversity in reconciling theoretical predictions with experimental observations in multiple-predator communities.

ecology↗

bioRxiv2026

Fine-scale behavioural dynamics separates adaptive sickness behaviour from injury and infection pathology

Animals commonly reduce activity during infection, but it remains unclear when such "sickness behaviours" reflect adaptive host regulation versus injury responses or pathogen-driven pathology. We combined high-resolution behavioural phenotyping with experimental partitioning of injury, immune stimulation, and live bacterial infection to dissect these effects in Drosophila melanogaster. Using an outbred fly population, we tracked individual locomotor activity at 1 minute resolution for 400 hours in males and females subjected to one of four treatments: unhandled control, septic injury with buffer, immune stimulation with heat killed Pseudomonas entomophila, or septic infection with live P. entomophila. Across the early post-challenge window, total activity diverged most strongly between the unhandled control and the challenged treatments. Fine-scale analyses revealed that immune challenge primarily reshaped the microstructure of movement: the number of activity bouts changed little, whereas active bout lengths were shorter and inactive periods were modestly prolonged, especially in females. Among infected flies, individuals that died early exhibited a collapse of bout structure, showing prolonged inactivity punctuated by brief, sometimes intense, movements, whereas longer-lived infected flies maintained patterns closer to controls. These behavioural differences were detectable in the very early stages of infection: within the first 24-hours post-infection early-dying flies had both a reduced probability of initiating movement from rest and a reduced probability of sustaining on-going activity, consistent with pathogen-induced debilitation; longer-lived infected flies showed near-normal state-transition profiles. This early suppression of activity in acutely dying males was positively associated with subsequent survival time, suggesting a contribution of adaptive restraint alongside pathology. By resolving fine-scale behaviour and state-transition dynamics, our approach clarifies which aspects of "sickness behaviour" are likely adaptive and which signal pathology.

animal behavior and cognition↗

bioRxiv2025

The past and potential antagonistic effects of fishing ban against nutrient loading control on eutrophication restoration in Lake Hongze

Integrated management strategies are often implemented to achieve comprehensive environmental restoration; however, the potential antagonistic effects among such measures are seldom examined. Fishing bans, aimed at enhancing fish biodiversity, may counteract the effectiveness of nutrient control measures in mitigating eutrophication. This study employs the PCLake model and structural equation modeling (SEM) to evaluate this hypothesis in Lake Hongze, the fourth largest shallow lake in China. The PCLake model was calibrated using observational data from Lake Hongze collected between 2016 and 2020. The calibrated model was subsequently applied in a hindcast analysis from 2020 to 2024 and a forecast simulation from 2025 to 2030 to assess the impacts of fishing bans. Combined with SEM path analysis, the results support the hypothesis that fishing bans can exhibit antagonistic effects on nutrient loading control by enhancing top-down regulation relative to bottom-up processes. Specifically, the fishing ban led to increased fish biomass, phytoplankton abundance, and nutrient levels over the past four years, while reducing the abundance of submerged macrophytes, zoobenthos, and zooplankton. Projections further indicate that such antagonistic effects would persist through 2030 if the fishing ban remains in place as planned. Additionally, model forecasts suggest that even with adjustments to the duration and intensity of fishing bans, antagonistic effects could be amplified under more stringent nutrient control scenarios. This study provides valuable insights into maximizing the net benefits of combined environmental management strategies through a systematic framework that evaluates both the effects and underlying processes of different interventions.

ecology↗

bioRxiv2025

Distinct dynamic stability patterns among three Atlantic cod subpopulations in the North Sea

Atlantic cod (Gadus morhua) in the North Sea and adjacent waters has been extensively studied due to its continued population decline despite reduced fishing pressure. Recent evidence reveals that it forms a metapopulation consisting of three subpopulations-- Northwestern, Southern, and Viking--highlighting the need to understand their distinct dynamics to support spatially targeted fisheries management. We applied a dynamical systems approach to quantify two key properties for each subpopulation from 1983 to 2023: dynamic stability, indicating whether subpopulations tend to return to or move away from their state each year, and the relative sensitivity of age groups, reflecting the magnitude of change in each groups abundance in response to perturbations in the age-structured interaction network. We found distinct dynamic stability patterns among the three subpopulations. The Northwestern subpopulation fluctuated between stable and unstable states before stabilizing at low abundance. The Southern subpopulation shifted from high-abundance, stable states toward low abundance at a transient with an uncertain future. The Viking subpopulation remained stable with relatively constant abundance over time. Throughout the study period, the age-1 group remained highly sensitive to perturbations in both the Southern and Viking subpopulations, whereas no single age group showed dominant sensitivity in the Northwestern subpopulation. Fishing mortality causally influenced the abundance and/or stability of the Northwestern and Southern subpopulations, but not the Viking subpopulation. In contrast, sea bottom temperature did not affect the abundance or stability of any of the subpopulations. Our findings reveal distinct patterns in abundance, dynamic stability, relative sensitivity of age groups, and responses to external drivers across the three subpopulations, highlighting the importance of accounting for the complex population structure of Atlantic cod in future research, assessments, and management efforts.

ecology↗

bioRxiv2025

Detecting infection-related mortality using dynamical statistical indicators of high-resolution activity time series

Predicting transitions between health, disease, and death across biological systems remains an important challenge with significant implications for both ecological management and medical intervention. Although the principles underlying these transitions are increasingly recognised, accurate and tractable dynamical indicators of health-to-disease transitions remain rare, especially at the level of individual organisms. Here, we use dynamical statistical indicators of high-resolution activity time series to predict infection-related mortality. By analysing locomotor activity data from infected Drosophila melanogaster flies, we find that individual dynamical indicators, such as the mean, variance, autocorrelation, and permutation entropy, differed between flies that survived and those that died during the experiment. When these indicators were used to train a Random Forest model, the classifier performed well (AUC = 0.94), demonstrating an accuracy of 87.9% in discriminating between infected flies that would die from infection and those that would survive, with the strongest discriminatory power detected over 12 hours prior to death. Our findings show that combining these easy-to-compute, dynamical statistical indicators with machine learning enhances the ability to predict health deterioration in the Drosophila model. Conceptually, our findings emphasize that the integration of dynamical statistical metrics from physiological or behavioural time-series with machine learning approaches may offer a promising avenue for real-time health monitoring in both ecological and clinical settings. HighlightsO_LIHigh-resolution locomotor activity time series distinguish infected flies that live or die C_LIO_LISimple dynamical indicators (mean, SD, CV, lag-1 autocorrelation) jointly improve outcome discrimination C_LIO_LIPermutation entropy declines over time and is reduced in flies approaching acute infection-related death C_LIO_LIRandom Forest models classify infection survival outcomes with high accuracy (AUC 0.94) C_LIO_LIDivergence in activity dynamics is detectable over 12-16 hours before death in flies that succumb to infection C_LI

ecology↗

bioRxiv2025

Rapid structural network changes in bird communities

As biodiversity is declining, the dynamics of species interactions is a growing conservation concern. However, estimating and monitoring explicit species interactions across large spatial and temporal scales remain challenging. An alternative and yet under-explored approach is to track whether and how the interaction milieu, defined as the background of all realised interactions, is changing in space and time. Here, we assess changes in the interaction milieu of common bird communities in France. We estimate associated species pairs using spatial and temporal information for 109 species monitored across 1,969 sites during 17 years. We validate the ecological significance of associated species pairs by testing the relationship between the propensity to be associated and species functional proximity or shared habitat preference. We reconstruct association networks for these intra-guild bird communities and track temporal changes in network layout in terms of size, density of links, modularity and degree distribution. We show that, beyond changes usually documented based on species numbers and abundances, the interaction milieu is also changing non-randomly. Communities become smaller with a similar relative number of associations that becomes unevenly distributed through time. These structural changes vary among bird communities according to their habitat and may impact community functioning and how communities can cope with global change.

ecology↗

bioRxiv2025

Tracking changes in stability of North Sea Atlantic cod in 40 years

Tracking changes in the stability of low-abundance populations is vital for conservation. While the stability of natural populations is often assessed based on linear dynamics, many exhibit state-dependent dynamics, such as the iconic Atlantic cod in the North Sea (Gadus morhua). This fish population experienced an abrupt decline in the year 2000 and has not shown a clear sign of recovery despite relaxed fishing pressure. To understand the mechanisms behind the recovery dynamics, we used a dynamical systems approach to reconstruct the state space of the population from yearly abundance data of age groups between 1982-2021. Specifically, we estimated yearly interaction matrices of age groups and derived yearly population stability, defined as the rate of recovery to or departure from the current state after a small perturbation to the matrix. We found that since the abrupt decline in abundance of North Sea cod in the year 2000, the population continued to fluctuate closer to the transition threshold; some age groups experienced weaker self-regulation; and age-1 group became more sensitive to perturbations than older groups. These results provide important information on North Sea cods resilience and capacity to buffer natural and anthropogenic impacts.

ecology↗

bioRxiv2024

Co-evolution of host dispersal and parasite virulence in complex landscapes.

Spatial network structure impacts the ecological and evolutionary dynamics of species interactions. Previous work on host-parasite systems has shown that parasite virulence is driven by dispersal rates and spatial structure, assuming that dispersal is an ecologically fixed parameter. However, dispersal is also a trait under selection and can evolve. In this context, we develop an individual-based eco-evolutionary model, in which both parasite virulence and host dispersal can evolve in representative terrestrial (random-geometric graphs; RGGs) and riverine aquatic (optimal channel networks; OCNs) landscapes. We find that in riverine aquatic landscapes, evolutionarily stable (ES) dispersal rates are lower and ES virulence is greater relative to terrestrial landscapes when dispersal mortality is low. When dispersal mortality is high, both dispersal and virulence evolve to lower values in both landscape types. Diverging co-evolutionary patterns between landscapes are explained by differences in network topology. Specifically, the highly heterogeneous degree distribution in riverine aquatic landscapes 1) leads to low parasite relatedness allowing for the evolution of greater virulence and 2) leads to spatial heterogeneity in host densities that constrains the evolution of dispersal to lower values. Our work highlights the importance of considering the concurrent and co-evolution of dispersal when studying trait evolution in complex landscapes.

evolutionary biology↗

bioRxiv2023

Landscape structure drives eco-evolution in host-parasite systems.

Spatial network structure of biological systems drives ecology and evolution by distributing organisms and their genes. The ubiquitous host-parasite systems are no exception. However, past work has largely ignored relevant spatial complexity, hampering the translation of theoretical predictions to real ecosystems. Thus, we develop an eco-evolutionary metapopulation model of host-parasite dynamics where hosts and parasites disperse through realistically complex spatial networks representing major biomes: riverine aquatic and terrestrial. We generate the testable prediction that parasite virulence, or how parasites harm their hosts, is unimodal with dispersal and can reach greater values in aquatic landscapes but saturates to lower values in terrestrial systems. Moreover, we show that kin selection drives virulence evolution. Spatial networks generate characteristic patterns of parasite relatedness which drive differential virulence evolution. Finally, we show that accounting for virulence evolution allows us to predict the distribution of key epidemiological variables (e.g., parasite extinction risks) within spatial networks.

evolutionary biology↗

bioRxiv2022

Ranking species based on sensitivity to perturbations under non-equilibrium community dynamics

Managing ecological communities requires fast detection of species that are sensitive to perturbations. Yet, the focus on recovery to equilibrium has prevented us from assessing species responses to perturbations when abundances fluctuate over time. Here, we introduce two data-driven approaches (expected sensitivity and eigenvector rankings) based on the time-varying Jacobian matrix to rank species over time according to their sensitivity to perturbations on abundances. Using several population dynamics models, we demonstrate that we can infer these rankings from time-series data to predict the order of species sensitivities. We find that the most sensitive species are not always the ones with the most rapidly changing or lowest abundance, which are typical criteria used to monitor populations. Finally, using two empirical time series, we show that sensitive species tend to be harder to forecast. Our results suggest that incorporating information on species interactions can improve how we manage communities out of equilibrium.

ecology↗

bioRxiv2022

Evolutionary emergence of alternative stable states in shallow lakes

AO_SCPLOWBSTRACTC_SCPLOWEcosystems under stress may respond abruptly and irreversibly through tipping points. Although much is explored on the mechanisms that affect tipping points and alternative stable states, little is known on how ecosystems with alternative stable states could have emerged in the first place. Here, we explore whether evolution by natural selection can lead to the emergence of ecosystems with tipping points using a toy model inspired by shallow lakes. Shallow lakes are the best-known example where a shift from a submersed macrophyte dominated state to a floating macrophyte dominated state in response to excess nutrient loading corresponds to a tipping point between alternative stable states. We model the evolution of the macrophytes living depth in the lake, we identify the conditions under which the ancestor macrophyte population diversifies, and investigate whether alternate stable states dominated by different macrophyte phenotypes occur. Given the trade-off between access to light and nutrient along the water column, we show that asymmetry in competition for light is required for diversification, while alternative stable states require an additional mechanism, an unequal efficiency in nutrient removal. We find that eco-evolutionary dynamics may produce alternative stable states, but only under a restrictive range of conditions. Our analysis suggests that competitive asymmetries along opposing resource gradients may allow alternative stable states to emerge by natural selection.

ecology↗

bioRxiv2021

Remotely-sensed slowing down in spatially patterned dryland ecosystems

Regular vegetation patterns have been predicted to indicate a system slowing down and possibly desertification of drylands. However, these predictions have not yet been observed in dryland vegetation due to the inherent logistic difficulty to gather longer-term in situ data. Here, we use recently developed methods using remote-sensing EVI time-series in combination with classified regular vegetation patterns along a rainfall gradient in Sudan to test these predictions. Overall, three temporal indicators (responsiveness, temporal autocorrelation, variance) show slowing down as vegetation patterns change from gaps to labyrinths to spots towards more arid conditions, confirming predictions. However, this transition exhibits non-linearities, specifically when patterns change configuration. Model simulations reveal that the transition between patterns temporarily slows down the system affecting the temporal indicators. These transient states when vegetation patterns reorganize thus affect the systems resilience indicators in a non-linear way. Our findings suggest that spatial self-organization of dryland vegetation is associated with critical slowing down, but this transition towards reduced resilience happens in a non-linear way. Future work should aim to better understand transient dynamics in regular vegetation patterns in dryland ecosystems, because long transients make regular vegetation patterns of limited use for management in anticipating critical transitions.

ecology↗

bioRxiv2020

Linking biotic homogenisation with large-scale changes of species associations

AimThe impact of global change on biodiversity is commonly assessed in terms of changes in species distributions, community richness and community composition. Whether and how much associations between species, i.e. the degree of correlation in their spatial co-occurrence, are also changing is much less documented and mostly limited to local studies of ecological networks. In this study, we quantify changes in large-scale patterns of species associations in bird communities in relation to changes in species composition. LocationFrance. Time period2001-2017. Major taxa studiedCommon breeding birds. MethodsWe use network approaches to build three community-aggregated indices reflecting complementary aspects of species association networks. We characterise the spatio-temporal dynamics of these indices using a large-scale and high-resolution dataset of bird co-abundances of 109 species monitored for 17 years (2001-2017) from 1,969 sites across France. We finally test whether spatial and temporal changes in species association networks are related to species homogenisation estimated as the spatio-temporal dynamics of {beta}-diversity and the proportion of habitat generalists. The consistency of these relationships is tested across three main habitats, namely woodland, grassland and human settlements. ResultsWe document a directional change in association-based indices in response to modifications in {beta}-diversity and in the proportion of generalists in space and time. Weaker associations and sparser networks were related to lower {beta}-diversity and a higher proportion of generalists, suggesting an overlooked aspect of biotic homogenisation affecting species associations. We report that this overall pattern is not constant across habitats, with opposite relationships between biotic homogenisation and change in species association networks in urban versus forest communities suggesting distinct homogenisation processes. Main ConclusionsAlthough species association contain only partial signatures of species interactions, our study highlights that biotic homogenisation translates to finer changes in community structure by affecting the number, strength and type of species associations.

ecology↗

bioRxiv2019

Vulnerable species interactions are important for the stability of mutualistic networks

Species are central to ecology and conservation. However, it is the interactions between species that generate the functions on which ecosystems and humans depend. Despite the importance of interactions, we lack an understanding of the risk that their loss poses to ecological communities. Here, we quantify risk as a function of the vulnerability (likelihood of loss) and importance (contribution to network stability in terms of species coexistence) of 4330 mutualistic interactions from 41 empirical pollination and seed dispersal networks across six continents. Remarkably, we find that more vulnerable interactions are also more important: the interactions that contribute most to network stability are those that are most likely to be lost. Furthermore, most interactions tend to have more similar vulnerability and importance across networks than expected by chance, suggesting that vulnerability and importance may be intrinsic properties of interactions, rather than only a function of ecological context. These results provide a starting point for prioritising interactions for conservation in species interaction networks and, in areas lacking network data, could allow interaction properties to be inferred from taxonomy alone.

ecology↗

bioRxiv2018

Ecosystem tipping points in an evolving world

There is growing concern over tipping points arising in ecosystems due to the crossing of environmental thresholds. Tipping points lead to strong and possibly irreversible shifts between alternative ecosystem states incurring high societal costs. Traits are central to the feedbacks that maintain alternative ecosystem states, as they govern the responses of populations to environmental change that could stabilize or destabilize ecosystem states. However, we know little about how evolutionary changes in trait distributions over time affect the occurrence of tipping points, and even less about how big scale ecological shifts reciprocally interact with trait dynamics. We argue that interactions between ecological and evolutionary processes should be taken into account for understanding the balance of feedbacks governing tipping points in nature.

ecology↗