Population Ecology

Recent research indicates that marine reserves can both improve fisheries yields of target species and maintain the persistence of bycatch species. However, the prevalent equilibrium analyses prevent our understandings in transient behavior at short-time scales. Here, we develop high dimensional theoretical frameworks by considering age structure to assess the relative advantages between reserve-only and no-reserve fisheries management strategies. Our results show that whether strategies with only reserves can achieve higher fisheries yields (measured by both weight and number) and maintain bycatch persistence depends on the life histories of both target and bycatch species through perspectives of transient oscillations. Our research has important practical applications especially for the West Coast groundfish fishery in the USA, as it suggests that reserves can perform benefits in both fisheries and conservation goals for target species with older ages at maturity and lower adult survivorship.

The occurrence of wolf populations in human-dominated landscapes is challenging worldwide because of conflicts with human activities. Modeling is an important tool to predict wolf dynamics and expansion, and help in decision making concerning management and conservation. However, some individual behaviors and pack dynamics of the wolf life cycle are still unclear to ecologists. Here we present an individual-based model (IBM) to project wolf populations while exploring the lesser-known processes of the wolf life cycle. IBMs are bottom-up models that simulate the fate of individuals interacting with each other, with population-level properties emerging from the individual-level simulations. IBMs are particularly adapted to represent social species such as the wolf that exhibits complex individual interactions. Our IBM predicts wolf demography including fine-scale individual behavior and pack dynamics based on up-to-date scientific literature. We explore four processes of the wolf life cycle whose consequences on population dynamics are still poorly understood: the pack dissolution following the loss of a breeder, the adoption of young dispersers by packs, the establishment of new packs through budding, and the different types of breeder replacement. While running different versions of the IBM to explore these processes, we also illustrate the modularity and flexibility of our model, an asset to model wolf populations experiencing different ecological and demographic conditions. The different parameterization of pack dissolution, territory establishment by budding, and breeder replacement processes influence the most the projections of wolf populations. As such, these processes require further field investigation to be better understood. The adoption process has a lesser impact on model predictions. Being coded in R to facilitate its understanding, we expect that our model will be used and further adapted by ecologists for their own specific applications.

In many butterfly species, males emerge earlier than females as part of a strategy to maximize male reproductive success. Although behavioral ecological studies using mathematical models have been conducted to explain this phenomenon, certain emergence patterns remain unexplained. In the butterfly species Fabriciana nerippe, some males emerge at the same time as females, in addition to males that emerge earlier than the females. However, it is unclear what emergence patterns occur in populations with male dimorphism, as observed in this species. In this study, we showed the existence of male body size dimorphism in Fabriciana nerippe by conducting a comparative analysis of forewing lengths between males and females. In addition, we developed a comprehensive mathematical model to investigate emergence patterns in the presence of dimorphic males. By introducing a trade-off between large size and early emergence, the model considered a scenario where small early-emerging and large late-emerging males could coexist. Numerical analysis demonstrated the emergence patterns of these two male types with a switch in emergence time. Furthermore, the higher the death rate before emergence, the earlier the emergence switch. These findings suggested that the timing of the switch depends on the death rate and is influenced by environmental factors. This work contributes to ecological and theoretical studies on timing dimorphism in life-history strategies across a broader range of species. HighlightsO_LIWe confirmed the existence of male body-size dimorphism corresponding to emergence timing in Fabriciana nerippe. C_LIO_LIWe developed a comprehensive model of male emergence patterns incorporateing male dimorphism. C_LIO_LIWe assumed a trade-off between early emergence and large body size. C_LIO_LIThe timing of male emergence switching is influenced by death rate and reproductive advantage of large males. C_LI

Fisheries management in Japan is currently at a turning point. MSY based reference points have historically been rejected because of impacts on the fishing industry that would result from their adoption. We propose and evaluate a new harvest control rule (HCR) that uses the biological reference points based on sustainable yield from the stochastic hockey-stick stock recruitment relationship. Management strategy evaluation simulations conditioned on data from Japanese stocks demonstrate that the new HCR avoided recruitment overfishing while providing stable and near maximum catch. The new HCR outperformed Japans traditional HCR in terms of conservation, and it outperformed an alternative HCR which is widely used around the world in terms of initial catch reduction and future catch variation. For forecasting and hindcasting simulations, the new HCR showed considerable improvements over traditional HCRs in terms of biomass and catch. This new management procedure can improve the current and future status of many overfished stocks in Japan as well as increase economic efficiency and better protect ecosystems.

The hockey-stick (HS) stock recruitment relationship (SRR) has been widely used as an empirical alternative to conventional SRRs such as the Beverton-Holt (BH) and Ricker (RI) models. However, the management performance and risks associated with estimating maximum-sustainable-yield (MSY) reference points (RPs) based on HS remain insufficiently understood. This study first defines deterministic and stochastic MSY RPs under the HS model and provides an overview of their properties. We then conduct simulation experiments to investigate the bias and management consequences that arise when MSY RPs are estimated from the HS model (HS-derived MSY RPs) rather than from the true SRR (e.g., BH) across a range of biological and stochastic parameters, with particular focus on scenarios with insufficient data contrast. Our results show that HS-derived MSY RPs tend to exhibit higher bias but lower variance than MSY RPs derived from the true SRR. Management strategy evaluation simulations further reveal that management procedures combining HS-derived MSY RPs with adaptive model learning and some precautionary measures gradually reduce this bias and achieve average spawning biomass and yield that are comparable to those obtained under management based on the true BH SRR. We also show that the management effectiveness of the precautionary measures depends on life-history traits and recruitment variability. These findings indicate that although HS-derived MSY RPs may be biased and require cautious use, combining them with appropriate precautionary measures allows management to remain robust while limiting variability and yield losses. This broadens the range of management options that are available for supporting sustainable fisheries management.

Despite its importance in ecological studies and pest controls, the lack of knowledge of the life cycle and the ambiguity of data challenge the accurate determination of insect nymphs regarding many insect species. Finite mixture models are often utilized to classify instars without knowing the instar number. This study derives parsimonious gaussian mixture models using parameter constraints motivated by Dyars rule. Dyars rule explains the growth pattern of larvae and nymphs of insects by assuming a constant ratio of head capsule width for every two adjacent development stages. Accordingly, every mean value of log-transformed data in each instar stage is considered a linear function, where two Dyar constants are an intercept and a slope for the instar stages, respectively, to infer the instar stage of samples. The common variance for every instar stage regarding log-transformed data can be assumed in a mixture model, as well. If valid, these assumptions will allow an efficient estimation of the model by reducing free parameters. As a result, four model hypotheses are proposed for each assumption of instar counts depending on whether these two parameter constraints are applied. After model estimation, the proposed method uses the ICL criterion to choose the optimal counts of nymphal stages, and parametric bootstrap LR tests are applied to decide the most efficient model regarding parameter constraints. The proposed method could attain the correct model settings during the simulation study. This study also discusses the interpretation of the results of real insect data sets that concord with Dyars rule or not.

In this work, we show by means of numerical bifurcation that two alternative stable states exhibit a hydra effect in a continuous-time stage-structured predator-prey model. We denote this behavior as a stage multiple hydra effect. This concomitant effect can have significant implications in population dynamics as well as in population management.

Population models used to set limits for whaling, fisheries bycatch and other human-caused mortality (HCM) usually focus on relatively large populations and do not include Allee effects (declines in population growth rate at small population sizes). These models are not suitable for managing small and endangered populations of marine mammals. We use a stochastic age-structured population model to investigate the effect of HCM on extinction risk. Compared to environmental variability and catastrophes, Allee effects had a strong influence on risk. Depending on the scenario, HCM (1) delayed the rate of population recovery (with no increased risk), (2) increased extinction risk because populations lingered at low levels, (3) increased extinction risk because the population was pushed below an Allee threshold, or (4) increased extinction risk over 100 years because the rate of extinction for a doomed population was accelerated. Population dynamics in small populations are poorly known for most marine mammals. Therefore, we recommend that managers consider the range of potential population dynamics for the species under consideration and make precautionary decisions on allowable levels of HCM. For critically depleted populations (e.g., small populations, well below historic levels) even low levels of HCM have the potential to substantially increase extinction risk.

Conservation and ethical consideration for animal welfare in the wild appear to be synergetic because they both care for non-human animals. However, many practices such as culling seem to achieve conservation purposes but at the cost of producing a lot of wild-animal suffering, antagonizing conservationists and animal rights advocates. To explore this tension, we model the suffering of animals in wild ecosystems by resorting to classical population dynamics equations and using death rates as a metric of suffering. Our results show that, depending on the structure and parameters of the ecosystem, animal rights advocates and conservationists can have either opposing or compatible interests, where conserving species can go hand in hand with reducing the overall suffering. These models contribute to the concrete question of how to cope with suffering in the wild and may help ecosystem managers who are regularly confronted with interventions in the wild.

O_LIMany populations are affected by hunting or fishing. Models designed to assess the sustainability of harvest management require accurate estimates of demographic parameters (e.g. survival, reproduction) hardly estimable with limited data collected on exploited populations. The joint analysis of different data sources with integrated population models (IPM) is an optimal framework to obtain reliable estimates for parameters usually difficult to estimate, while accounting for imperfect detection and observation error. The IPM built so far for exploited populations have integrated count-based surveys and catch-at-age data into ageclass structured population models. But the age of harvested individuals is difficult to assess and often not recorded, and population counts are often not performed on a regular basis, limiting their use for the monitoring of exploited populations.\nC_LIO_LIHere, we propose an IPM that makes efficient use of data commonly collected in exploited marine and terrestrial populations of vertebrates. As individual measures of body mass at both capture and death are often collected in fish and terrestrial game species, our model integrates capture-mark-recapture-recovery data and data collected at death into a body mass-structured population model. It allows the observed number of individuals harvested to be compared with the expected number and provides accurate estimates of demographic parameters.\nC_LIO_LIWe illustrate the usefulness of this IPM using an emblematic game species distributed worldwide, the wild boar Sus scrofa, as a case study. For this species that has increased in distribution and abundance over the last decades, the model provides accurate and precise annual estimates of key demographic parameters (survival, reproduction, growth) and of population size while accounting for imperfect detection and observation error.\nC_LIO_LITo avoid an overexploitation of declining populations or an under-exploitation of increasing populations, it is crucial to gain a good understanding of the dynamics of exploited populations. When managers or conservationists have limited demographic data, the IPM offers a powerful framework to assess population dynamics. Being highly flexible, the approach is broadly applicable to both terrestrial and marine exploited populations for which measures of body mass are commonly recorded and more generally, to all populations suffering from anthropogenic mortality causes.\nC_LI

Matrix models are widely used in population ecology studies and are valuable for analysing population dynamics. Nonetheless, this approach is somewhat rigid in terms of generating complex scenarios. Starting from the values of the transition matrix, we can build a dynamic model to incorporate more biological-based reality into the model (e.g. polyp stage) and provide a higher flexibility in generating scenarios. As an example, we used the transition matrix calculated for a time series data of a population of the box jellyfish Carybdea marsupialis (L. 1758) in the Western Mediterranean in a previously published study. Dynamic models can help us to better understand the complex relationships that drive populations, test different hypotheses and compare scenarios. The dynamic model was developed in STELLA Architect, calibrated and optimised and it has been used to simulate various scenarios of ecological interest, including a decline in food supply, jellyfish removal strategies, changes in drift currents and changes in substrate availability for planulae to settle. A sensitivity analysis showed that polyp strobilation rate and strobilation pattern were two of the most sensitive variables. This matrix-to-dynamic model approach could be useful to integrate more biological complexity into population models and, in turn, obtain a better fit to the field data.

Marine reserves are an essential component of modern fishery management. Marine reserves, which represent a management tradeoff between harvesting and conservation, are fundamental to maintenance of fisheries. Finding optimal reserve sizes that improve fishing yields is not only of theoretical interest, but also of practical importance to facilitate decision making. Also, since the migratory behavior of some species influences the spillover effect of a marine reserve, this is a key consideration when assessing performance of marine reserves. The relationship between optimal reserve size and migration rate/mode has not been well studied, but it is fundamental to management success. Here, I investigate optimal reserve size and its management outcome with different levels of spillover via a simple two-patch mathematical model. In this model, one patch is open to fishing, and the other is closed. The two-patch model is aggregated by single-population dynamics when the migration rate is sufficiently larger than the growth rate of a target species. At this limit, I show that an optimal reserve size exists when pre-reserve fishing occurs at fishing mortality larger than fMSY, the fishing mortality at the maximum sustainable yield (MSY). Also, the fishing yield at an optimal reserve size becomes as large as MSY at the limit. Numerical simulations at various migration rates between the two patches suggest that the maximum harvest under management with a marine reserve is achieved at this limit. This contrasts with the conservation benefit which is maximized at an intermediate migration rate. Numerical simulations show that the above-mentioned condition derived from the aggregated model is necessary when the migration rate is not sufficiently large, and that a moderate migration rate is further necessary for an optimal reserve size to exist. However, high fishing mortality reduces this requirement.Competing Interest StatementThe authors have declared no competing interest.View Full Text

Whether fishing around the marine reserve edge can enhance harvested yields is an important issue in fisheries management. To solve the conundrum is difficult because of the lack of a matched boundary condition. Here, we derive a new boundary condition by considering individual losing at habitat boundaries. With the suitable boundary condition, our results suggest that individuals with high growth rate inside but low growth rate outside the reserve and high movement preference to a large marine reserve boundary can enhance yields benefits from fishing around the marine reserve edge. The findings provide theoretical cautions for fishing near some new reserves in which population growth rate might be low. Moreover, our boundary condition is general enough for the universal phenomenon of losing individual at habitat boundaries such as being applied into classic theories in refuge design to explain some previous counter-intuitive phenomena more reasonably.

Methods for estimating and modeling the long-term and short-term adult flight dynamics of the conifer silk moth Dendrolimus superans (Lepidoptera: Lasiocampidae) are examined. The analysis uses light trap adult catch data collected over 21 years, from 2005 to 2025. Three models of adult flight are considered: a flight-initiation model driven by weather factors, an autoregressive model of long-term catch dynamics, and a binary model of seasonal catch. For the flight-initiation model, we propose estimating the accumulated temperature sum ST from the date when the first derivative of the remote sensing vegetation index NDVI becomes positive until the date of the first adult capture of the season. ST is shown to be sufficiently stable across all years of observation, with flight each year beginning after this temperature sum is reached. The second model demonstrates that the long-term light trap catch time series is well described by a second-order autoregressive model AR(2), in which the catch of the current year depends on catches from the two preceding years. This long-term series is compared with a previously studied larval population density series of the Siberian silk moth; both are shown to be AR(2) series with similar coefficient values, which suggesting that adult catch data may serve as a proxy for absolute larval population density. In the third model, we describe the transition from absolute-scale seasonal catch dynamics (number of adults per day) to a binary scale (0, 1), where 0 denotes days on which no adults were attracted to the trap, and 1 denotes days on which at least one individual was captured. The seasonal absolute catch series is thereby transformed into a binary series of zeros and ones, and relationships between adjacent values in such a binary series are examined. A linear relationship between the absolute and binary seasonal dynamics series is demonstrated, making it possible to estimate absolute catches from binary catch values and to analyze seasonal flight in sparse pest populations. This potentially opens new avenues for understanding how outbreak populations function at chronically low density. Author summaryForest pests can cause catastrophic damage, yet predicting their outbreaks remains challenging. During periods of low population density, standard monitoring methods become labor-intensive and uninformative, while the transition to an outbreak often occurs unexpectedly. Using a 21-year dataset of adult Siberian silk moth (Dendrolimus superans) captures from light traps, we developed an approach combining three complementary models. First, we showed that moth flight begins upon reaching a specific temperature sum, with the starting point determined by NDVI vegetation index dynamics rather than a calendar date--making the forecast more ecologically relevant. Second, long-term adult population dynamics follow a second-order autoregressive model AR(2), matching the dynamics previously observed for larval populations. This establishes light trap data as a reliable proxy for absolute population density when ground surveys are impractical. Third, we introduced a method to analyze seasonal flight using binary data (presence/absence of moths per day), which we showed is linearly related to absolute abundance. This enables studying population dynamics during periods of extremely low density, when traditional methods fail. Our approach opens new possibilities for early warning systems to detect when a population risks transitioning from a latent state to an outbreak phase.

Assessing the effects of a plant-host shift is important for monitoring insect populations over long time periods and for interventions in a conservation or pest management framework. In a heterogeneous environment, individuals may disperse between sources and sinks in order to persist. Here we propose a single-species two-patch model that aims to capture the generational movement of an insect that exhibits density-dependent dispersal, to see how shifting between hosts could alter its viability and asymptotic dynamics. We then analyse the stability and persistence properties of the model and further validate it using parameter estimates derived from laboratory experiments. In order to evaluate the potential of this model, we applied it to Drosophila suzukii (Diptera: Drosophilidae), which has become a harmful pest in several countries around the world. Although many studies have investigated the preference and attractiveness of potential hosts on this invasive drosophilid, no studies thus far have investigated whether a shift of fruit host could affect such a species ecological viability or spatiotemporal persistence. The model results show that a shift in host choice can significantly affect the growth potential and fecundity of a species such as D. suzukii, which ultimately could aid such invasive populations in their ability to persist within a changing environment.

Population management requires predictions of extinction risk based on a general understanding of these risks and on system-specific modelling. Life tables, available for numerous populations and species, permit calculating population growth and the construction of multi-type branching process models which predict population survivorship and ultimate extinction probabilities. We exemplify this approach and tailor it to an experimental model to predict extinction probabilities per unit of time. In age-structured populations, founders from different age classes lead to different predicted extinction probabilities. Age effects interact with environmental effects such as culling levels, which influence population growth rates. We assess the accuracy of predictions based on an age-structured matrix model, in an extinction experiment over an eight-week period on the springtail Folsomia candida, with crossed founder age and culling level treatments. Using parameter estimates from an accessory experiment, the fit of model predictions to observed extinction probabilities was generally good. A modified branching process model which allowed culling events between and at observations reduced prediction error. However, additionally maximizing the likelihood of observed extinction probabilities based on survival and fecundity parameters, or on a parameter which concentrated fecundity within a subinterval, did not significantly reduce prediction error according to the AICc. Our study shows that satisfactory predictions of establishment probabilities and of the initial persistence of small populations can be made using multi-type branching processes and available parameter estimates. Predictions can be improved by integrating knowledge of when events occur within intervals. This can be done without additional parameter estimation.

In ecology and evolutionary biology, understanding the relationship between vital rates (e.g., survival, development, reproduction) and population growth is essential to elucidate how life history strategies are shaped by natural selection. However, the established demographic methods to decipher the relationship between vital rates and population growth often analyse only the linear changes in population fitness as a result of changes in vital rates, thus simplifying the complexities of said relationships. To overcome the widespread linearity simplification, here we introduce the second-order elasticities of mean population fitness, the S-elasticity. The S-elasticity quantifies how changes in one or more vital rates can produce a second-order change in mean fitness. We provide a systematic mathematical framework behind the S-elasticity, revealing its ability to identify the convex and concave responses of mean fitness to perturbations of vital rates. Through structured population models, we demonstrate the distinct roles of linear and nonlinear mean fitness responses, and their combination, enabling to characterise local concavity/convexity of the mean population fitness function. We illustrate the application and the differences of S-elasticities and their biological meanings using matrix population models of the armadillo (Dasupys novemcinctus) and Pynes plum (Astragallus bibullatus). These two case studies showcase how the S-elasticity provides key insights into mean fitness responses to perturbations on demographic process and their correlations. We discuss the improvements that the S-elasticity provides for species management and our understanding of how natural populations cope with environmental change.

1The blue octopus (Octopus cyanea) fishery off the southwest coast of Madagascar is important for coastal communities. This fishery is a key economic resource for the local community as blue octopus catch is sold by local fishers to international and local export markets. Thus, it is important to monitor and evaluate the status of octopus to ensure its sustainability. One common octopus management approach is through the use of temporary spatial closures. Models can be a useful support tool to evaluate the status of a population and assess different possible management strategies. To better understand the biology and assess the sustainability of blue octopus, we parameterize a Levkovitch population matrix model using existing catch data. We found that the octopus population was experiencing a 1.8% decline per month at the time of data collection in 2006. However, since 2006, a number of management practices, including temporary closures lasting several weeks to several months have been implemented successfully. In line with these efforts, our model indicates that the fishery has likely been sustained since 2006 due to these annual closures. Our model provides support to the idea that temporary closures have restored this population and that temporary closures provide flexibility in management strategies that local communities can tailor to their economic and social needs. In addition, we were able to estimate several important life history metrics, such as time in each stage, stable stage distribution, reproductive value, and per stage survivability, that can be used in future work. Collectively, our study provides insight into the biology of blue octopus as well as demonstrate how temporary closures can be an effective conservation strategy due to the wide range of implementation options.

Demographic models are crucial for uncovering the mechanisms underlying changing populations trajectories and structure and to identify the drivers of such changes. Common pochard populations of North east/North west Europe have experienced a sharp decline accompanied by an increase in male proportions among adults since the mid-1990. We used a two-sex, two-stage deterministic matrix population model, to perform a prospective perturbation analysis and to explore, through simulations, some plausible causes underlying the observed decline and change in sex structure. We show that Common pochard populations are more sensitive to changing survival than to changes in productivitys components (clutch size, nest survival...). However, due to an environmental variance much higher than that of survival, components of productivity, especially nest survival, would be the main drivers of Common pochard populations growth rate, a finding supported by empirical data. More importantly, we show that although sex-specific changes in survival at any stage of the life cycle are potent drivers of both population growth rate and changing sex ratio, there is no need to resort to them for explaining the increasing proportions of males such as observed in Common pochard. Because adult males display higher survival than adult females (0.74 against 0.64 on average), any factor affecting recruitment (nest or first year survival) increases the weight of adults into the populations and hence the proportion of males. Thus, in species displaying sex-biased mortality, such as many ducks, decreasing recruitment can underly declining population size and changes in sex structure at the same time, emphasising the importance of accounting for males in monitoring schemes and demographic models.

The Allee effect is a phenomenon where individual fitness is reduced in small populations, for example because of mate-finding difficulties or increased predation. Allee effects matter in conservation biology because they can drive small populations to extinction. The severity of Allee effects can depend on traits such as mate-search rate and defense against predators. Many natural populations exhibit considerable intraspecific trait variation (ITV) in such traits, but most studies so far assume these traits to be constant. Thus the impact of ITV on populations with Allee effect is largely unknown. Here we create two individual-based stochastic models that simulate a small population experiencing either a mate-finding Allee effect or a predator-driven Allee effect. We analyze how ITV, trait inheritance, and mutation affect the proportion of surviving populations. Under the mate-finding Allee effect, higher ITV hindered population survival and increased Allee thresholds. This can be explained by Jensens inequality and the negative curvature of the mate-finding function. Under the predator-driven Allee effect, ITV effects were weak, but higher mutation standard deviations were beneficial, likely because they provided more substrate for selection to act on. We thus recommend to take into account ITV when dealing with threatened populations with an Allee effect.