Population Dynamics Model Research Articles

Structured Literature Review to Identify Human Papillomavirus's Natural History Parameters for Dynamic Population Models of Vaccine Impacts.

Human papillomavirus (HPV) is a common sexually transmitted virus that can cause cervical cancer and other diseases. Dynamic transmission models (DTMs) have been developed to evaluate the health and economic impacts of HPV vaccination. These models typically include many parameters, such as natural history of the disease, transmission, demographic, behavioral, and screening. To ensure the accuracy of DTM projections, it is important to parameterize them with the best available evidence. This study aimed to identify and synthesize data needed to parametrize DTMs on the natural history of HPV infection and related diseases. Parameters describing data of interest were grouped by their anatomical location (genital warts, recurrent respiratory papillomatosis, and cervical, anal, vaginal, vulvar, head and neck, and penile cancers), and natural history (progression, regression, death, cure, recurrence, detection), and were identified through a systematic literature review (SLR) and complementary targeted literature reviews (TLRs). The extracted data were then synthesized by pooling parameter values across publications, and summarized using the range of values across studies reporting each parameter and the median value from the most relevant study. Data were extracted and synthesized from 223 studies identified in the SLR and TLRs. Parameters frequently reported pertained to cervical cancer outcomes, while data for other anatomical locations were less available. The synthesis of the data provides a large volume of parameter values to inform HPV DTMs, such as annual progression rates from cervical intraepithelial neoplasia (CIN) 1 to CIN2+ (median of highest quality estimate 0.0836), CIN2 to CIN 3+ (0.0418), carcinoma in situ (CIS) 2 to local cancer+ (0.0396), and regional to distant cancer (0.0474). Our findings suggest that while there is a large body of evidence on cervical cancer, parameter values featured substantial heterogeneity across studies, and further studies are needed to better parametrize the non-cervical components of HPV DTMs.

Investigating the dose-dependency of the midgut escape barrier using a mechanistic model of within-mosquito dengue virus population dynamics.

Arboviruses can emerge rapidly and cause explosive epidemics of severe disease. Some of the most epidemiologically important arboviruses, including dengue virus (DENV), Zika virus (ZIKV), Chikungunya (CHIKV) and yellow fever virus (YFV), are transmitted by Aedes mosquitoes, most notably Aedes aegypti and Aedes albopictus. After a mosquito blood feeds on an infected host, virus enters the midgut and infects the midgut epithelium. The virus must then overcome a series of barriers before reaching the mosquito saliva and being transmitted to a new host. The virus must escape from the midgut (known as the midgut escape barrier; MEB), which is thought to be mediated by transient changes in the permeability of the midgut-surrounding basal lamina layer (BL) following blood feeding. Here, we present a mathematical model of the within-mosquito population dynamics of DENV (as a model system for mosquito-borne viruses more generally) that includes the interaction of the midgut and BL which can account for the MEB. Our results indicate a dose-dependency of midgut establishment of infection as well as rate of escape from the midgut: collectively, these suggest that the extrinsic incubation period (EIP)-the time taken for DENV virus to be transmissible after infection-is shortened when mosquitoes imbibe more virus. Additionally, our experimental data indicate that multiple blood feeding events, which more closely mimic mosquito-feeding behavior in the wild, can hasten the course of infections, and our model predicts that this effect is sensitive to the amount of virus imbibed. Our model indicates that mutations to the virus which impact its replication rate in the midgut could lead to even shorter EIPs when double-feeding occurs. Mechanistic models of within-vector viral infection dynamics provide a quantitative understanding of infection dynamics and could be used to evaluate novel interventions that target the mosquito stages of the infection.

Modeling potential consequences of climate‐driven sex reversal on Southern and Summer Flounder population dynamics

AbstractObjectiveWe investigate the interacting effects of fishery selectivity and sexual dimorphism by using the fisheries for Southern Flounder Paralichthys lethostigma and Summer Flounder P. dentatus as case studies. In both species, females are larger than males, and temperature‐sensitive sex determination can lead to an increased proportion of males at sexual differentiation in warmer temperatures.MethodsWe developed a size‐, age‐, and sex‐structured population dynamics model for each species to understand how temperature‐induced sex reversal will interact with harvesting to impact population productivity. We considered scenarios with realistic sex ratios and varying levels of fishing pressure.ResultOur models of these species show that population egg production, abundance, biomass, and catch will all be constrained if sex ratios at differentiation become more male‐biased. For both species, climate‐induced changes to the sex ratio in early‐life stages could have a greater impact on relative catch than fishing mortality. We demonstrate that the spawning potential ratio may not be sensitive to climate‐induced changes in the sex ratio unless we account for changes in the sex ratio at differentiation in the historic baseline reproductive potential.ConclusionThese findings underscore the importance of utilizing sex‐specific stock assessments for species with temperature‐sensitive sex determination mechanisms.

Stability and Bifurcation Analysis of a Spatially Size–Stage-Structured Model with Resting Phase

In this paper, we consider a spatially size–stage-structured population dynamics model with resting phase. The primary objective of this model is to study size structure, stage structure, resting phase and spatial location simultaneously in a single population system. At first, we reformulate the problem as an abstract nondensely defined Cauchy problem. Then, taking advantage of the integrated semigroup and bifurcation theories, we investigate the stability and Hopf bifurcation at the positive equilibrium of the model. Finally, numerical simulations are presented as evidence to support our analytical results. A discussion of related problems is also presented briefly.

Population Consequences of Parent-Offspring Competition: An Individual-Based Model

The article compares different versions of individual-based models of single population dynamics with overlapping generations with results of the model of population with non-overlapping generations. In all models, various versions of global competition for common resources and their unequal partitioning between competing individuals are analysed, i.e., when juveniles and adult individuals compete for the same resources, when juveniles and adult individuals use different resources, and a case called mother’s care. The article analyses the relationship between individual variability and population persistence measured by the time of population extinction. Persistence of a population is increased by all forms of competition between individuals not weakened by any environmental factors (e.g. diversification of resources of competing individuals) or factors arising from evolutionary history of the species (e.g. mother’s care) and related in an appropriate way to the mechanism shaping individual variability in the population. Any form of weakening competition leading to decreasing individual variability will adversely affect the persistence of the population. However, differences between versions of the model are not very big.

Editorial: Models in population, community and ecosystem dynamics

Editorial: Models in population, community and ecosystem dynamics

Warmer autumns and winters could reduce honey bee overwintering survival with potential risks for pollination services

Honey bees and other pollinators are critical for food production and nutritional security but face multiple survival challenges. The effect of climate change on honey bee colony losses is only recently being explored. While correlations between higher winter temperatures and greater colony losses have been noted, the impacts of warmer autumn and winter temperatures on colony population dynamics and age structure as an underlying cause of reduced colony survival have not been examined. Focusing on the Pacific Northwest US, our objectives were to (a) quantify the effect of warmer autumns and winters on honey bee foraging activity, the age structure of the overwintering cluster, and spring colony losses, and (b) evaluate indoor cold storage as a management strategy to mitigate the negative impacts of climate change. We perform simulations using the VARROAPOP population dynamics model driven by future climate projections to address these objectives. Results indicate that expanding geographic areas will have warmer autumns and winters extending honey bee flight times. Our simulations support the hypothesis that late-season flight alters the overwintering colony age structure, skews the population towards older bees, and leads to greater risks of colony failure in the spring. Management intervention by moving colonies to cold storage facilities for overwintering has the potential to reduce honey bee colony losses. However, critical gaps remain in how to optimize winter management strategies to improve the survival of overwintering colonies in different locations and conditions. It is imperative that we bridge the gaps to sustain honey bees and the beekeeping industry and ensure food and nutritional security.

Modeling time-varying phytoplankton subsidy reveals at-risk species in a Chilean intertidal ecosystem

The allometric trophic network (ATN) framework for modeling population dynamics has provided numerous insights into ecosystem functioning in recent years. Herein we extend ATN modeling of the intertidal ecosystem off central Chile to include empirical data on pelagic chlorophyll-a concentration. This intertidal community requires subsidy of primary productivity to support its rich ecosystem. Previous work models this subsidy using a constant rate of phytoplankton input to the system. However, data shows pelagic subsidies exhibit highly variable, pulse-like behavior. The primary contribution of our work is incorporating this variable input into ATN modeling to simulate how this ecosystem may respond to pulses of pelagic phytoplankton. Our model results show that: (1) closely related sea snails respond differently to phytoplankton variability, which is explained by the underlying network structure of the food web; (2) increasing the rate of pelagic-intertidal mixing increases fluctuations in species’ biomasses that may increase the risk of local extirpation; (3) predators are the most sensitive species to phytoplankton biomass fluctuations, putting these species at greater risk of extirpation than others. Finally, our work provides a straightforward way to incorporate empirical, time-series data into the ATN framework that will expand this powerful methodology to new applications.

“Patchiness” in mechanical stiffness across a tumor as an early-stage marker for malignancy

Mechanical phenotyping of tumors, either at an individual cell level or tumor cell population level is gaining traction as a diagnostic tool. However, the extent of diagnostic and prognostic information that can be gained through these measurements is still unclear. In this work, we focus on the heterogeneity in mechanical properties of cells obtained from a single source such as a tissue or tumor as a potential novel biomarker. We believe that this heterogeneity is a conventionally overlooked source of information in mechanical phenotyping data. We use mechanics-based in-silico models of cell-cell interactions and cell population dynamics within 3D environments to probe how heterogeneity in cell mechanics drives tissue and tumor dynamics. Our simulations show that the initial heterogeneity in the mechanical properties of individual cells and the arrangement of these heterogenous sub-populations within the environment can dictate overall cell population dynamics and cause a shift towards the growth of malignant cell phenotypes within healthy tissue environments. The overall heterogeneity in the cellular mechanotype and their spatial distributions is quantified by a “patchiness” index, which is the ratio of the global to local heterogeneity in cell populations. We observe that there exists a threshold value of the patchiness index beyond which an overall healthy population of cells will show a steady shift towards a more malignant phenotype. Based on these results, we propose that the “patchiness” of a tumor or tissue sample, can be an early indicator for malignant transformation and cancer occurrence in benign tumors or healthy tissues. Additionally, we suggest that tissue patchiness, measured either by biochemical or biophysical markers, can become an important metric in predicting tissue health and disease likelihood just as landscape patchiness is an important metric in ecology.

Functional Responses of Prey-Predator Models in Population Dynamics; A Survey

Functional Responses of Prey-Predator Models in Population Dynamics; A Survey

Inverse Problem for a Nonlinear Model of Population Dynamics with the Age Structure of Individuals and Overpopulation

Inverse Problem for a Nonlinear Model of Population Dynamics with the Age Structure of Individuals and Overpopulation

An Inverse Problem for an Age-Structured Population Dynamics Model with Migration Flows

An Inverse Problem for an Age-Structured Population Dynamics Model with Migration Flows

Testing models of increasing complexity to develop ecosystem‐informed fisheries advice

AbstractDespite continued calls for the application of ecosystem‐based fisheries management, tactical fisheries management continues to be heavily reliant on single‐species stock assessments. These stock assessments rarely quantitatively integrate the effects of ecosystem processes on fish stock productivity. This lack of integration is ultimately driven by the complexity of interactions between populations, ecosystems and fisheries, which produces uncertainty when defining which processes to include and how to include them. Models developed using a structured hypothesis testing framework would allow formalizing uncertainties while underscoring the importance of incorporating different population and ecosystem processes to explain non‐stationary stock productivity. Here, we develop a conceptual framework for extending and comparing population dynamics models of increasing complexity. We illustrate the utility of the framework by investigating the population and ecosystem processes that most likely affected the differential recovery of two flatfish populations (American plaice and yellowtail flounder) on the Newfoundland Grand Banks over the past three decades. We found that yellowtail flounder population dynamics were primarily driven by recruitment variability, which was negatively affected by warmer climatological conditions, as indicated by an integrated regional climate index. Meanwhile, American plaice population dynamics were affected by a combination of temporal variability in recruitment and natural mortality, where natural mortality increased during colder than average conditions. By exploring hypotheses about the effects of population and ecosystem processes on population dynamics, this modelling framework will improve understanding about the drivers of shifts in population productivity while serving as a transparent and robust approach to support ecosystem‐based fisheries management.

IxPopDyMod: an R package to write, run, and analyze tick population and infection dynamics models

Given the increasing prevalence of tick-borne diseases, such as Lyme disease, modeling the population and infection dynamics of tick vectors is an important public health tool. These models have applications for testing the effects of control methods or climate change on tick populations. There is an established history of tick population models, but code for them is rarely shared, especially not in a convenient format for others to modify and use. We present an R package, called IxPopDyMod, intended to function as a flexible and consistent framework for reproducible Ixodidae (hard-bodied ticks) population dynamics models. Here we focus on two key parts of the package: a function to create valid model configurations and a function to run a configured model and return the daily population over time. We provide three examples in appendices: one reproducing an existing Ixodes scapularis population model, one providing a novel Dermacentor albipictus model, and one showing Borrelia burgdorferi infection in ticks. Together these examples show the flexibility of the package to model scenarios of interest to tick researches.Graphical

Temperature-dependent dispersal and ectotherm species' distributions in a warming world.

Dispersal is a crucial component of species' responses to climate warming. Warming-induced changes in species' distributions are the outcome of how temperature affects dispersal at the individual level. Yet, there is little or no theory that considers the temperature dependence of dispersal when investigating the impacts of warming on species' distributions. Here I take a first step towards filling this key gap in our knowledge. I focus on ectotherms, species whose body temperature depends on the environmental temperature, not least because they constitute the majority of biodiversity on the planet. I develop a mathematical model of spatial population dynamics that explicitly incorporates mechanistic descriptions of ectotherm life history trait responses to temperature. A novel feature of this framework is the explicit temperature dependence of all phases of dispersal: emigration, transfer and settlement. I report three key findings. First, dispersal, regardless of whether it is random or temperature-dependent, allows both tropical and temperate ectotherms to track warming-induced changes in their thermal environments and to expand their distributions beyond the lower and upper thermal limits of their respective climate envelopes. In the absence of dispersal mortality, warming does not alter these new distributional limits. Second, an analysis based solely on trait response data predicts that tropical ectotherms should be able to expand their distributions polewards to a greater degree than temperate ectotherms. Analysis of the dynamical model confirms this prediction. Tropical ectotherms have an advantage when moving to cooler climates because they experience lower within-patch and dispersal mortality, and their higher thermal optima and maximal birth rates allow them to take advantage of the warmer parts of the year. Previous theory has shown that tropical ectotherms are more successful in invading and adapting the temperate climates than vice versa. This study provides the key missing piece, by showing how temperature-dependent dispersal could facilitate both invasion and adaptation. Third, dispersal mortality does not affect the poleward expansion of ectotherm distributions. But, it prevents both tropical and temperate ectotherms from maintaining sink populations in localities that are too warm to be viable in the absence of dispersal. Dispersal mortality also affects species' abundance patterns, causing a larger decline in abundance throughout the range when species disperse randomly rather than in response to thermal habitat suitability. In this way, dispersal mortality can facilitate the evolution of dispersal modes that maximize fitness in warmer thermal environments.

A temperature‐controlled, circular maintenance system for studying growth and development of pelagic tunicates (salps)

AbstractSalps have attracted attention as zooplankton organisms that may be able to expand their habitat range and increase their ecological importance in the face of ongoing global warming. Due to their gelatinous nature, unique feeding strategy, and reproductive ecology such changes could have profound impacts on regional marine ecosystems. While their role in the regional carbon cycle is receiving attention, our knowledge of their physiology and life cycle is still limited. This knowledge gap is mainly due to their fragile gelatinous nature, which makes it difficult to capture and maintain intact specimen in the laboratory. We present here a modified kreisel tank system that has been tested onboard a research vessel with the Southern Ocean salp Salpa thompsoni and at a research station with Salpa fusiformis and Thalia democratica from the Mediterranean Sea. Successful maintenance over days to weeks allowed us to obtain relative growth and developmental rates comparable to in situ field samples of S. thompsoni and S. fusiformis, and provided insights into previously unknown features of their life cycle (e.g., testes development). Our results show that traditional methods of estimating growth, such as cohort analysis, may lead to a general overestimation of growth rates and neglect individual strategies (e.g., shrinkage), which can affect the results and conclusions drawn from population dynamic models. By providing a starting point for the successful maintenance of different species, comparable experiments on the physiology of salps is made possible. This will contribute to refining model parameters and improving the reliability of the predictions.

Reconstructing mountain goat history in the Olympic Mountains, USA

AbstractBetween 1925 and 1930, 11 or 12 non‐native mountain goats (Oreamnos americanus) were translocated from Alaska and British Columbia to the foothills of the Olympic Range. By 1970, descendants of these goats had colonized the entire range and concerns about the management of this introduced species developed as damage to alpine soil and vegetation occurred. A series of removals reduced the population from 1175 in 1983 to 389 by 1990, eventually growing to 584 in 2016. We used demographic and genetic data to parameterize a population genetics individual‐based simulation model of the Olympic Range mountain goats. We calibrated the model to replicate the population trajectory for Olympic mountain goats from establishment in the 1920s through the 1983 first census. As expected, modeled population dynamics from 1928 to 1983 mimicked parameter initialization from expanding populations. However, simulated heterozygosity did not align with observations, suggesting a process not accounted for within the simulation model, such as a bottleneck or founder effect. Sensitivity analyses showed changes in annual reproductive rate, juvenile mortality, and adult female mortality influencing population trajectories, but variation in male mortality revealed no changes. Evaluating the population dynamics of the model after removals showed that approximately 80% of the total animals removed during the 1980s needed to be female in order for the observed population estimates to occur. This model has the potential to be used more widely with established or introduced mountain goat populations, as well as to provide an approach for studying other introduced species and their population dynamics.

Modeling and dissociation of intrinsic and input-driven neural population dynamics underlying behavior

Neural dynamics can reflect intrinsic dynamics or dynamic inputs, such as sensory inputs or inputs from other brain regions. To avoid misinterpreting temporally structured inputs as intrinsic dynamics, dynamical models of neural activity should account for measured inputs. However, incorporating measured inputs remains elusive in joint dynamical modeling of neural-behavioral data, which is important for studying neural computations of behavior. We first show how training dynamical models of neural activity while considering behavior but not input or input but not behavior may lead to misinterpretations. We then develop an analytical learning method for linear dynamical models that simultaneously accounts for neural activity, behavior, and measured inputs. The method provides the capability to prioritize the learning of intrinsic behaviorally relevant neural dynamics and dissociate them from both other intrinsic dynamics and measured input dynamics. In data from a simulated brain with fixed intrinsic dynamics that performs different tasks, the method correctly finds the same intrinsic dynamics regardless of the task while other methods can be influenced by the task. In neural datasets from three subjects performing two different motor tasks with task instruction sensory inputs, the method reveals low-dimensional intrinsic neural dynamics that are missed by other methods and are more predictive of behavior and/or neural activity. The method also uniquely finds that the intrinsic behaviorally relevant neural dynamics are largely similar across the different subjects and tasks, whereas the overall neural dynamics are not. These input-driven dynamical models of neural-behavioral data can uncover intrinsic dynamics that may otherwise be missed.

Reduction in size-at-maturity in unprecedentedly strong cohorts of redfish (Sebastes mentella and S. fasciatus) in the Gulf of St. Lawrence and Laurentian Channel.

Life-history traits, such as size-at-maturity, are key parameters to model population dynamics used to inform fisheries management. Fishery-induced evolution, density-dependent effects, and global warming have been shown to affect size- and age-at-maturity, and resulting spawning stock biomass (SSB) in a wide range of commercial fish stocks. Marked changes in redfish biomass and environmental conditions in the Gulf of St. Lawrence and Laurentian Channel over the past decade called for a review and update of size-at-maturity for commercially important deepwater redfish Sebastes mentella and Acadian redfish Sebastes fasciatus stocks. Following a 25-year moratorium, local redfish biomass has recently reached unprecedented levels, co-occurring with an overall warming of bottom water temperatures. Our objectives were (1) to perform a histological assessment of redfish reproduction stages, including the validation and fine-tuning of a robust visual chart to facilitate monitoring of size-at-maturity and SSB in a transforming environment, and (2) to evaluate changes in size-at-maturity in unprecedentedly strong cohorts of redfish, and consequences for stock status assessment and fisheries management. Each specimen was genetically identified to species, and gonad reproduction stages were determined by histology and macroscopic appearances. The present study enabled a robust visual chart for continued and cost-effective monitoring of redfish reproduction stages to be refined and validated, and has shown a large decrease in redfish length when 50% of the individuals are considered mature that led to an increase in estimates of SSB during the 2011-2021 period for S. mentella and S. fasciatus. These changes modified the perception of stock status, thus having significant implications for fisheries management. Given that fishery-induced evolution and community structure changes along with global warming are affecting numerous stocks worldwide, the present study outlines a major and global challenge for scientists and resources managers. As shown by our results, the monitoring and frequent updates of life-history traits in transforming environments are needed to provide reliable science advice for sustainable fisheries.

Local existence of solutions to a nonlinear autonomous PDE model for population dynamics with nonlocal transport and competition

In this paper, we prove that a particular nondegenerate, nonlinear, autonomous parabolic partial differential equation with nonlocal mass transfer admits the local existence of classical solutions. The equation was developed to qualitatively describe temporal changes in population densities over space through accounting for location desirability and fast, long-range travel. Beginning with sufficiently regular initial conditions, through smoothing the PDE and employing energy arguments, we obtain a sequence of approximators converging to a classical solution.