Biology subjects

Krkosek, M.

Publications and source records attributed to Krkosek, M..

9 recordsLinked to original sources

bioRxiv2026

A single attractor governs the population dynamics of marine fishes worldwide

Population fluctuations are now empirically recognized to be nonlinear, but the governing attractors are poorly understood. Here we show that population dynamics of 457 marine fish stocks from 121 species worldwide are governed by a single attractor that partitions into three archetypes reflecting top predators, mesopredators and forage fish, with stock-specific ecological and evolutionary variation. Correlation between attractors was high across all stocks (mean 0.53 to 0.63), greater within archetypes (0.57 to 0.77), and increased with geographic, phylogenetic and life history similarity. Leveraging shared attractors increased prediction skill in ~90% of cases, raising mean recruitment skill from 0.38 to 0.75 and even enabling moderate prediction for otherwise poorly predictable stocks. These results reveal that marine fish population dynamics are not heterogeneous but are realizations of a single attractor structured by trophic level, with immediate predictive benefits for global fisheries.

ecology↗

bioRxiv2026

Evaluating the estimability of within-host population dynamics models

Despite the impacts of within-host disease dynamics on disease outcomes in individual hosts and disease spread among-hosts, generic models of within-host population dynamics have received far less attention than their among-host counterparts. While a number of models have been proposed to explore theoretical eco-evolutionary dynamics, they have yet to be evaluated for estimability, raising questions about their ability to provide reliable inference when confronted with data. We evaluated the estimability of two generic within-host population dynamics models by assessing: (1) parameter estimation, our ability to recover correct values of model parameters from data, (2) the consequences of mis-assigning the underlying mechanistic model on parameter estimation, and (3) the reproduction of qualitative dynamics, or, our ability to use parameter estimates to reproduce observed dynamical behaviours. In some cases, fitting a mis-matched mechanistic model to time series data produced reasonable parameter estimates that were able to reproduce system dynamics, and that when provided the data-generating model, parameter uncertainty can produce substantial behavioural uncertainty. Our findings highlight the impacts of structural, parametric, and behavioural uncertainty on inference, and demonstrate the value of improving system-specific knowledge to prevent the use of incorrect functional forms and of measuring consequential parameters to improve estimability.

ecology↗

bioRxiv2026

The effects of fox movement and landscape heterogeneity on the spread of sarcoptic mange in urban settings

ContextThe movement of vertebrate hosts across urbanized landscapes can play a key role in the transmission of direct-contact diseases. Understanding how wildlife hosts move in urban landscapes, and how transmission is affected by their landscape-constrained and disease-altered movements, is imperative for better predicting the spread of disease. ObjectiveWe assess how the movement of red foxes (Vulpes vulpes) according to landcover type, and their infection status, affect the spread of mange (caused by Sarcoptes scabiei) in an urbanized landscape. MethodsWe developed a mange transmission model (MTM) using an agent-based model to compare two movement behaviours of foxes in Scarborough (Ontario, Canada): random and landcover-based. We further assessed the effects of movement on disease transmission by considering the foxs infection status and comparing a range of movement probability scenarios. We quantified the number of effective contact events and the effective reproduction number (Re) according to each scenario. ResultsWe found that both landcover-dependent movement and infection status influenced the spread of mange within fox populations. The number of effective contact events and effective reproduction number Re was greatest when landscape heterogeneity was included in the model and foxes moved through paths of least resistance to movement, and when susceptible and infected foxes had an equal probability of leaving a fragmented habitat patch. ConclusionsOur findings suggest that mange spread may be accelerated along movement corridors in fragmented, heterogenous landscapes. As urban areas expand and remnant habitat within these is further lost and animals are relegated to fewer movement pathways, disease transmission may increase.

ecology↗

bioRxiv2025

Identifying Priority Stepping Stone Reefs to Maintain Global Networks of Connected Coral Reefs

Conserving coral reef climate refugia is a key conservation strategy to address climate change. Yet, the accelerating impacts of coral bleaching and other anthropogenic pressures can jeopardize refugia persistence. The dispersal of coral larvae can increase long-term reef persistence through metapopulation dynamics if connected reefs can share beneficial adaptations to bleaching and facilitate demographic recovery. Here, we modelled reef connectivity using a network approach to identify present-day coral larval dispersal networks of predicted climate refugia and then determined locations of stepping stone reefs that can be used to connect these global networks of refugia. We identify 10 key locations of coral reef stepping stones in Indonesia, Mozambique, Glorioso Islands, and Malaysia that may ensure that 84,564km2 of refugia could remain connected together even if other (non-refugia) reefs become degraded. Global coral reef conservation efforts should consider prioritizing these stepping stones to build more redundancy and resilience into future-proofing conservation strategies.

ecology↗

bioRxiv2025

Temperature variation and life history mediate the degree of nonlinearity in fluctuations of global marine fish populations

Nonlinear dynamics readily occur in natural ecosystems and can drive irregular population fluctuations through oscillations, chaos and alternative stable states. However, the effects of anthropogenic changes, such as to demography and the climate, on nonlinearity of population fluctuations is unknown. We evaluated the extent and magnitude of nonlinearity and its environmental and life history correlates in 243 recruitment and 267 spawner time series of 143 marine fish species, worldwide. Here we show that temperature variation amplifies nonlinearity in recruitment and spawner biomass, while life history mediates the degree of nonlinearity for the latter, dampening it in slow-lived species. Nonlinearity was displayed by 81% of populations and correlated with the magnitude of fluctuations. These nonlinear dynamics were low-dimensional and causally forced by temperature in 60% of populations with the probability of forcing increasing for recruits in variable temperature environments and fast-lived spawners. Our results challenge assumptions of stable dynamics and sustainable yield common to fisheries management, and suggests nonlinear fluctuations of fish populations are magnified by size-selective fisheries and environmental variability from global climate change.

ecology↗

bioRxiv2025

Early warning signals do not predict a warming-induced experimental epidemic

Climate change can impact the rates at which parasites are transmitted between hosts, ultimately determining if and when an epidemic will emerge. As such, our ability to predict climate-mediated epidemic emergence will become increasingly important in our efforts to prepare for and mitigate the effects of disease outbreaks on ecological systems and human health. Theory suggests that statistical signatures termed "early warning signals" (EWS), can function as predictors of disease emergence. Here, we analyze experimental and simulated time series of disease spread within populations of the model disease system Daphnia magna-Ordospora colligata for EWS of epidemic emergence. In this system, low temperatures prevent disease emergence, while sufficiently high temperatures force the system through a critical transition to an epidemic state. We found that EWS of epidemic emergence were nearly as likely to be detected in populations maintained at a sub-epidemic temperature as they were to be detected in populations subjected to a warming treatment that induced epidemic spread. Our findings suggest that the detection of false positives may limit the reliability of EWS as predictors of climate-mediated epidemic emergence.

ecology↗

bioRxiv2023

Environmental variability can promote parasite diversity within hosts and transmission among hosts

While the mechanisms that govern disease emergence and spread among hosts are increasingly well-described, the mechanisms that promote parasite diversity within-hosts, affecting host outcomes and spillover potential, have been comparatively understudied. Furthermore, while attention has been paid to the effects of increasing temperatures on disease systems, the effects of environmental variability have been left underexplored, despite rising climatic variability. To investigate the impacts of environmental variability on parasite diversity within-hosts, we analyzed a model of within-host population dynamics wherein two parasites indirectly compete through the hosts immune response. We simulated the model under constant, demographically stochastic, environmentally stochastic, and demographically and environmentally stochastic conditions, and analysed the viability and longevity of non-equilibrium parasite co-occurrence. We found that environmental stochasticity increased the viability and longevity of parasite co-occurrence, suggesting that thermal variability arising from climatic change and as a physiological trait may promote parasite diversity within ectotherms and help explain bats propensity to support diverse communities of parasites. Further, we found that under certain conditions, the transmissibility of co-occurring parasites can surpass the transmissibility of single parasites, suggesting that thermal variability may increase the transmissibility of co-occurring parasites.

ecology↗

bioRxiv2022

Dynamic coastal pelagic habitat drives rapid changes in growth and condition of juvenile sockeye salmon (Oncorhynchus nerka) during early marine migration

Migrating marine taxa encounter diverse habitats that differ environmentally and in foraging conditions over a range of spatial scales. We examined body (RNA/DNA, length-weight residuals) and nutritional (fatty acid composition) condition of juvenile sockeye salmon (Oncorhynchus nerka) in British Columbia, while migrating through varied oceanographically waters. Fish were sampled in the stratified northern Strait of Georgia (NSoG); the highly mixed Johnstone Strait (JS); and the transitional zone of Queen Charlotte Strait (QCS). In 2015, body and nutritional condition were high in the NSoG and responded rapidly to reach lowest levels in JS with its low prey availability, and showing signs of compensatory growth in QCS. In 2016, juvenile salmon had significantly lower condition in the NSoG than in 2015, although zooplankton biomass was similar, condition remained low in JS, and no compensatory growth was observed in QCS. We provide evidence that differences in juvenile salmon condition between the two years being due to changes in the food quality available to juvenile fish. Further, we propose that the TGH needs to be extended to incorporate food quality as a parameter to understand changes in fish condition and survival between years.

ecology↗

bioRxiv2020

Inferring Models with Alternative Stable States from Independent Observations

Multiple attractors and alternative stable states are defining features of scientific theories in ecology and evolution, implying that abrupt regime shifts can occur and that outcomes can be hard to reverse. Here we describe a statistical inferential framework that uses independent, noisy observations with low temporal resolution to support or refute multiple attractor process models. The key is using initial conditions to choose among a finite number of expected outcomes using a nonstandard finite mixture methodology. We apply the framework to contemporary issues in social-ecological systems, coral ecosystems, and chaotic systems, showing that incorporating history allows us to statistically infer process models with alternative stable states while minimizing false positives. Further, in the presence of disturbances and oscillations, alternative stable states can help rather than hamper inference. The ability to infer models with alternative stable states across natural systems can help accelerate scientific discoveries, change how we manage ecosystems and societies, and place modern theories on firmer empirical ground.

ecology↗