An immune memory-structured SIS epidemiological model for hyperdiverse pathogens.

A hyperdiverse class of pathogens of humans and wildlife, including the malaria parasite Plasmodium falciparum, relies on multigene families to encode antigenic variation. As a result, high (asymptomatic) prevalence is observed despite high immunity in local populations under high-transmission settings. The vast diversity of "strains" and genes encoding this variation challenges the application of established models for the population dynamics of such infectious diseases. Agent-based models have been formulated to address theory on strain coexistence and structure, but their complexity can limit application to gain insights into population dynamics. Motivated by P. falciparum malaria, we develop an alternative formulation in the form of a structured susceptible-infected-susceptible population model in continuous time, where individuals are classified not only by age, as is standard, but also by the diversity of parasites they have been exposed to and retain in their specific immune memory. We analyze the population dynamics and bifurcation structure of this system of partial-differential equations, showing the existence of alternative steady states and an associated tipping point with transmission intensity. We attribute the critical transition to the positive feedback between parasite genetic diversity and force of infection. Basins of attraction show that intervention must drastically reduce diversity to prevent a rebound to high infection levels. Results emphasize the importance of explicitly considering pathogen diversity and associated specific immune memory in the population dynamics of hyperdiverse epidemiological systems. This statement is discussed in a more general context for ecological competition systems with hyperdiverse trait spaces.

Integrating learning into animal range dynamics under rapid human-induced environmental change.

Human-induced rapid environmental change (HIREC) is creating environments deviating considerably from natural habitats in which species evolved. Concurrently, climate warming is pushing species' climatic envelopes to geographic regions that offer novel ecological conditions. The persistence of species is likely affected by the interplay between the degree of ecological novelty and phenotypic plasticity, which in turn may shape an organism's range-shifting ability. Current modelling approaches that forecast animal ranges are characterized by a static representation of the relationship between habitat use and fitness, which may bias predictions under conditions imposed by HIREC. We argue that accounting for dynamic species-resource relationships can increase the ecological realism of range shift predictions. Our rationale builds on the concepts of ecological fitting, the process whereby individuals form successful novel biotic associations based on the suite of traits they carry at the time of encountering the novel condition, and behavioural plasticity, in particular learning. These concepts have revolutionized our view on fitness in novel ecological settings, and the way these processes may influence species ranges under HIREC. We have integrated them into a model of range expansion as a conceptual proof of principle highlighting the potentially substantial role of learning ability in range shifts under HIREC.

Nonlinear life table response experiment analysis: Decomposing nonlinear and nonadditive population growth responses to changes in environmental drivers.

Life table response experiments (LTREs) decompose differences in population growth rate between environments into separate contributions from each underlying demographic rate. However, most LTRE analyses make the unrealistic assumption that the relationships between demographic rates and environmental drivers are linear and independent, which may result in diminished accuracy when these assumptions are violated. We extend regression LTREs to incorporate nonlinear (second-order) terms and compare the accuracy of both approaches for three previously published demographic datasets. We show that the second-order approach equals or outperforms the linear approach for all three case studies, even when all of the underlying vital rate functions are linear. Nonlinear vital rate responses to driver changes contributed most to population growth rate responses, but life history changes also made substantial contributions. Our results suggest that moving from linear to second-order LTRE analyses could improve our understanding of population responses to changing environments.

The natural history of luck: A synthesis study of structured population models.

Chance pervades life. In turn, life histories are described by probabilities (e.g. survival and breeding) and averages across individuals (e.g. mean growth rate and age at maturity). In this study, we explored patterns of luck in lifetime outcomes by analysing structured population models for a wide array of plant and animal species. We calculated four response variables: variance and skewness in both lifespan and lifetime reproductive output (LRO), and partitioned them into contributions from different forms of luck. We examined relationships among response variables and a variety of life history traits. We found that variance in lifespan and variance in LRO were positively correlated across taxa, but that variance and skewness were negatively correlated for both lifespan and LRO. The most important life history trait was longevity, which shaped variance and skew in LRO through its effects on variance in lifespan. We found that luck in survival, growth, and fecundity all contributed to variance in LRO, but skew in LRO was overwhelmingly due to survival luck. Rapidly growing populations have larger variances in LRO and lifespan than shrinking populations. Our results indicate that luck-induced genetic drift may be most severe in recovering populations of species with long mature lifespan and high iteroparity.

Variety is the spice of life: nongenetic variation in life histories influences population growth and evolvability.

Individual vital rates are key determinants of lifetime reproductive success, and variability in these rates shapes population dynamics. Previous studies have found that this vital rate hetero- geneity can influence demographic properties including population growth rates, however, the explicit effects of the amount of variation within and the covariance between vital rates that can also vary throughout the lifespan on population growth remains unknown. Here, we explore the analytical consequences of nongenetic heterogeneity on long-term population growth rates and rates of evolution by modifying traditional age-structured population projection matrices to incorporate variation among individual vital rates. The model allows vital rates to be permanent throughout life ("fixed condition") or to change over the lifespan ("dynamic condition"). We reduce the complexity associated with adding individual heterogeneity to age-structured models through a novel application of matrix collapsing ("phenotypic collapsing"), showing how to col- lapse in a manner that preserves the asymptotic and transient dynamics of the original matrix. The main conclusion is that nongenetic individual heterogeneity can strongly impact the long-term growth rate and rates of evolution. The magnitude and sign of this impact depends heavily on how the heterogeneity covaries across the lifespan of an organism. Our results emphasize that nongenetic variation cannot simply be viewed as random noise, but rather that it has consistent, predictable effects on fitness and evolvability.

A potential novel treatment for cirrhosis-related ascites: Empagliflozin is safe and tolerable in advanced chronic liver disease.

AIMS: Advanced chronic liver disease and advanced chronic liver disease-related ascites have a high mortality. The pharmacological treatment of ascites and fluid overload has changed little over time. Empagliflozin, a sodium-glucose cotransporter type 2 inhibitor is an untested potential novel treatment in cirrhosis, as it has survival benefits in heart failure, which has similar pathophysiological fluid overload mechanisms. Before investigating empagliflozin's potential benefit in cirrhosis, its safety must be addressed. METHODS: Ten participants (five each with compensated or decompensated advanced chronic liver disease, based on Child-Pugh class) received empagliflozin 10 mg orally daily for 4 weeks with 2 weeks follow-up. Empagliflozin safety, pharmacokinetics and pharmacodynamics were investigated. RESULTS: In total, eight patients (80%) reported an adverse event, and three patients (30%) experienced a serious adverse event, one of which was attributed to empagliflozin. Overall, the frequency of adverse events was similar to previous phase 3 trials of gliflozins. Higher plasma empagliflozin concentrations did not significantly increase the risk of adverse events. CONCLUSIONS: Four-week treatment with empagliflozin was safe and well tolerated in patients with advanced chronic liver disease. These preliminary data support assessment of long-term treatment on disease-related and mortality outcomes in patients with cirrhosis through randomized control trials.

Robustly estimating the demographic contribution of immigration: Simulation, sensitivity analysis and seals.

Identifying important demographic drivers of population dynamics is fundamental for understanding life-history evolution and implementing effective conservation measures. Integrated population models (IPMs) coupled with transient life table response experiments (tLTREs) allow ecologists to quantify the contributions of demographic parameters to observed population change. While IPMs can estimate parameters that are not estimable using any data source alone, for example, immigration, the estimated contribution of such parameters to population change is prone to bias. Currently, it is unclear when robust conclusions can be drawn from them. We sought to understand the drivers of a rebounding southern elephant seal population on Marion Island using the IPM-tLTRE framework, applied to count and mark-recapture data on 9500 female seals over nearly 40 years. Given the uncertainty around IPM-tLTRE estimates of immigration, we also aimed to investigate the utility of simulation and sensitivity analyses as general tools for evaluating the robustness of conclusions obtained in this framework. Using a Bayesian IPM and tLTRE analysis, we quantified the contributions of survival, immigration and population structure to population growth. We assessed the sensitivity of our estimates to choice of multivariate priors on immigration and other vital rates. To do so we make a novel application of Gaussian process priors, in comparison with commonly used shrinkage priors. Using simulation, we assessed our model's ability to estimate the demographic contribution of immigration under different levels of temporal variance in immigration. The tLTRE analysis suggested that adult survival and immigration were the most important drivers of recent population growth. While the contribution of immigration was sensitive to prior choices, the estimate was consistently large. Furthermore, our simulation study validated the importance of immigration by showing that our estimate of its demographic contribution is unlikely to result as a biased overestimate. Our results highlight the connectivity between distant populations of southern elephant seals, illustrating that female dispersal can be important in regulating the abundance of local populations even when natal site fidelity is high. More generally, we demonstrate how robust ecological conclusions may be obtained about immigration from the IPM-tLTRE framework, by combining sensitivity analysis and simulation.

Pharmacokinetics of polymyxin B in different populations: a systematic review.

BACKGROUND AND OBJECTIVES: Despite being clinically utilized for the treatment of infections, the limited therapeutic range of polymyxin B (PMB), along with considerable interpatient variability in its pharmacokinetics and frequent occurrence of acute kidney injury, has significantly hindered its widespread utilization. Recent research on the population pharmacokinetics of PMB has provided valuable insights. This study aims to review relevant literature to establish a theoretical foundation for individualized clinical management. METHODS: Follow PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, Pop-PK studies of PMB were searched in PubMed and EMBASE database systems from the inception of the database until March 2023. RESULT: To date, a total of 22 population-based studies have been conducted, encompassing 756 subjects across six different countries. The recruited population in these studies consisted of critically infected individuals with multidrug-resistant bacteria, patients with varying renal functions, those with cystic fibrosis, kidney or lung transplant recipients, patients undergoing extracorporeal membrane oxygenation (ECMO) or continuous renal replacement therapy (CRRT), as well as individuals with obesity or pediatric populations. Among these studies, seven employed a one-compartmental model, with the range of typical clearance (CL) and volume (Vc) being 1.18-2.5L /h and 12.09-47.2 L, respectively. Fifteen studies employed a two-compartmental model, with the ranges of the clearance (CL) and volume of the central compartment (Vc), the volume of the peripheral compartment (Vp), and the intercompartment clearance (Q) were 1.27-8.65 L/h, 5.47-38.6 L, 4.52-174.69 L, and 1.34-24.3 L/h, respectively. Primary covariates identified in these studies included creatinine clearance and body weight, while other covariates considered were CRRT, albumin, age, and SOFA scores. Internal evaluation was conducted in 19 studies, with only one study being externally validated using an independent external dataset. CONCLUSION: We conclude that small sample sizes, lack of multicentre collaboration, and patient homogeneity are the primary reasons for the discrepancies in the results of the current studies. In addition, most of the studies limited in the internal evaluation, which confined the implementation of model-informed precision dosing strategies.

Blood Lipoproteins Shape the Phenotype and Lipid Content of Early Atherosclerotic Lesion Macrophages: A Dual-Structured Mathematical Model.

Macrophages in atherosclerotic lesions exhibit a spectrum of behaviours or phenotypes. The phenotypic distribution of monocyte-derived macrophages (MDMs), its correlation with MDM lipid content, and relation to blood lipoprotein densities are not well understood. Of particular interest is the balance between low density lipoproteins (LDL) and high density lipoproteins (HDL), which carry bad and good cholesterol respectively. To address these issues, we have developed a mathematical model for early atherosclerosis in which the MDM population is structured by phenotype and lipid content. The model admits a simpler, closed subsystem whose analysis shows how lesion composition becomes more pathological as the blood density of LDL increases relative to the HDL capacity. We use asymptotic analysis to derive a power-law relationship between MDM phenotype and lipid content at steady-state. This relationship enables us to understand why, for example, lipid-laden MDMs have a more inflammatory phenotype than lipid-poor MDMs when blood LDL lipid density greatly exceeds HDL capacity. We show further that the MDM phenotype distribution always attains a local maximum, while the lipid content distribution may be unimodal, adopt a quasi-uniform profile or decrease monotonically. Pathological lesions exhibit a local maximum in both the phenotype and lipid content MDM distributions, with the maximum at an inflammatory phenotype and near the lipid content capacity respectively. These results illustrate how macrophage heterogeneity arises in early atherosclerosis and provide a framework for future model validation through comparison with single-cell RNA sequencing data.

Impacts of estuarine habitat degradation on the modeled life history of marine estuarine-dependent and resident fish species.

Shallow coastal and estuarine habitats play an essential role in the life cycles of many fish species, providing spawning, nursery, feeding, and migration areas. However, these ecologically valuable habitats are increasingly threatened by anthropogenic activities, causing substantial changes in both habitat availability and quality. Fish species use these shallow coastal habitats and estuaries during various life stages, leading to their categorization into guilds based on how and when they rely on these areas. This differential functional use of estuaries means that changes to these habitats may affect each guild differently. To understand the impact of estuarine habitat degradation on fish populations, it is therefore necessary to consider the full life cycle of fish and when they rely on these coastal habitats. Here, we use conceptual size-structured population models to study how estuarine habitat degradation affects two functionally different guilds. We use these models to predict how reduced food productivity in the estuary affects the demographic rates and population dynamics of these groups. Specifically, we model estuarine residents, which complete their entire life cycle in estuaries, and marine estuarine-dependent species, which inhabit estuaries during early life before transitioning offshore. We find that total fish biomass for both guilds decreases with decreasing food productivity. However, the density of juveniles of the marine estuarine-dependent guild can, under certain conditions, increase in the estuary. This occurs due to a shift in the population biomass distribution over different life stages and a simultaneous shift in which life stage is most limited by food. At the individual level, somatic growth of juveniles belonging to the estuarine-dependent guild decreased with lower food supply in the estuary, due to increased competition for food. The somatic growth rates of fish belonging to the resident guild were largely unaffected by low food supply, as the total fish density decreased at the same time and therefore the per-capita food availability was similar. These outcomes challenge the assumption that responses to habitat degradation are similar between fish guilds. Our study highlights the need to assess not only fish biomass but also size distributions, survival, and somatic growth rates for a comprehensive understanding of the effects of habitat degradation on fish populations. This understanding is crucial not only for estuary fish communities but also for successful conservation and management of commercially harvested offshore population components.

A Cost-Benefit Analysis of Alternative Management Strategies for Red Deer in Denmark.

In this paper, we conduct a cost-benefit analysis (CBA) of five alternative management strategies for red deer in Denmark: free harvest, trophy hunting, maximum harvest and two cases for natural demographic population compositions. To capture the outcome under each strategy we use a biological sex- and age-structured population model. The net benefit function includes meat values, recreational values, browsing damage costs and traffic damage costs and these values and costs are assumed to differ for the various sex and age classes of red deer. We show that the maximum harvest strategy leads to a reasonably high positive total net benefit, while the free harvest strategy yields a small positive net benefit. On the other hand, the trophy hunting strategy generates a high negative net benefit, while small negative net benefits are obtained under the two strategies for natural demographic population compositions.

Ninety years of change, from commercial extinction to recovery, range expansion and decline for Antarctic fur seals at South Georgia.

With environmental change, understanding how species recover from overharvesting and maintain viable populations is central to ecosystem restoration. Here, we reconstruct 90 years of recovery trajectory of the Antarctic fur seal at South Georgia (S.W. Atlantic), a key indicator species in the krill-based food webs of the Southern Ocean. After being harvested to commercial extinction by 1907, this population rebounded and now constitutes the most abundant otariid in the World. However, its status remains uncertain due to insufficient and conflicting data, and anthropogenic pressures affecting Antarctic krill, an essential staple for millions of fur seals and other predators. Using integrated population models, we estimated simultaneously the long-term abundance for Bird Island, northwest South Georgia, epicentre of recovery of the species after sealing, and population adjustments for survey counts with spatiotemporal applicability. Applied to the latest comprehensive survey data, we estimated the population at South Georgia in 2007-2009 as 3,510,283 fur seals [95% CI: 3,140,548-3,919,604] (ca. 98% of global population), after 40 years of maximum growth and range expansion owing to an abundant krill supply. At Bird Island, after 50 years of exponential growth followed by 25 years of slow stable growth, the population collapsed in 2009 and has thereafter declined by -7.2% [-5.2, -9.1] per annum, to levels of the 1970s. For the instrumental record, this trajectory correlates with a time-varying relationship between coupled climate and sea surface temperature cycles associated with low regional krill availability, although the effects of increasing krill extraction by commercial fishing and natural competitors remain uncertain. Since 2015, fur seal longevity and recruitment have dropped, sexual maturation has retarded, and population growth is expected to remain mostly negative and highly variable. Our analysis documents the rise and fall of a key Southern Ocean predator over a century of profound environmental and ecosystem change.

Transient demographic dynamics of recovering fish populations shaped by past climate variability, harvest, and management.

Large-scale commercial harvesting and climate-induced fluctuations in ocean properties shape the dynamics of marine populations as interdependent drivers at varied timescales. Persistent selective removals of larger, older members of a population can distort its demographic structure, eroding resilience to fluctuations in habitat conditions and thus amplifying volatility in transient dynamics. Many historically depleted marine fish stocks have begun showing signs of recovery in recent decades following the implementation of stricter management measures. But these interventions coincide with accelerated changes in the oceans triggered by increasingly warmer, more variable climates. Applying multilevel models to annual estimates of demographic metrics of 38 stocks comprising 11 species across seven northeast Atlantic ecoregions, this study explores how time-varying local and regional climates contributed to the transient dynamics of recovering populations exposed to variable fishing pressures moderated by management actions. Analyses reveal that progressive reductions in fishing pressure and shifting climate conditions discontinuously shaped rebuilding patterns of the stocks through restorations of maternal demographic structure (reversing age truncation) and reproductive capacity. As the survival rate and demographic structure of reproductive fish improved, transient growth became less sensitive to variability in recruitment and juvenile survival and more to that in adult survival. As the biomass of reproductive fish rose, recruitment success also became increasingly regulated by density-dependent processes involving higher numbers of older fish. When reductions in fishing pressure were insufficient or delayed, however, stocks became further depleted, with more eroded demographic structures. Although warmer local climates in spawning seasons promoted recruitment success in some ecoregions, changing climates in recent decades began adversely affecting reproductive performances overall, amplifying sensitivities to recruitment variability. These shared patterns underscore the value of demographic transients in developing robust strategies for managing marine resources. Such strategies could form the foundation for effective applications of adaptive measures resilient to future environmental change.

Partitioning variance in population growth for models with environmental and demographic stochasticity.

How demographic factors lead to variation or change in growth rates can be investigated using life table response experiments (LTRE) based on structured population models. Traditionally, LTREs focused on decomposing the asymptotic growth rate, but more recently decompositions of annual 'realized' growth rates using 'transient' LTREs have gained in popularity. Transient LTREs have been used particularly to understand how variation in vital rates translate into variation in growth for populations under long-term study. For these, complete population models may be constructed to investigate how temporal variation in environmental drivers affect vital rates. Such investigations have usually come down to estimating covariate coefficients for the effects of environmental variables on vital rates, but formal ways of assessing how they lead to variation in growth rates have been lacking. We extend transient LTREs to further partition the contributions from vital rates into contributions from temporally varying factors that affect them. The decomposition allows one to compare the resultant effect on the growth rate of different environmental factors, as well as density dependence, which may each act via multiple vital rates. We also show how realized growth rates can be decomposed into separate components from environmental and demographic stochasticity. The latter is typically omitted in LTRE analyses. We illustrate these extensions with an integrated population model (IPM) for data from a 26 years study on northern wheatears (Oenanthe oenanthe), a migratory passerine bird breeding in an agricultural landscape. For this population, consisting of around 50-120 breeding pairs per year, we partition variation in realized growth rates into environmental contributions from temperature, rainfall, population density and unexplained random variation via multiple vital rates, and from demographic stochasticity. The case study suggests that variation in first year survival via the unexplained random component, and adult survival via temperature are two main factors behind environmental variation in growth rates. More than half of the variation in growth rates is suggested to come from demographic stochasticity, demonstrating the importance of this factor for populations of moderate size.

Evaluating the importance of individual heterogeneity in reproduction to Weddell seal population dynamics using integral projection models.

Identifying and accounting for unobserved individual heterogeneity in vital rates in demographic models is important for estimating population-level vital rates and identifying diverse life-history strategies, but much less is known about how this individual heterogeneity influences population dynamics. We aimed to understand how the distribution of individual heterogeneity in reproductive and survival rates influenced population dynamics using vital rates from a Weddell seal population by altering the distribution of individual heterogeneity in reproduction, which also altered the distribution of individual survival rates through the incorporation of our estimate of the correlation between the two rates and assessing resulting changes in population growth. We constructed an integral projection model (IPM) structured by age and reproductive state using estimates of vital rates for a long-lived mammal that has recently been shown to exhibit large individual heterogeneity in reproduction. Using output from the IPM, we evaluated how population dynamics changed with different underlying distributions of unobserved individual heterogeneity in reproduction. Results indicate that the changes to the underlying distribution of individual heterogeneity in reproduction cause very small changes in the population growth rate and other population metrics. The largest difference in the estimated population growth rate resulting from changes to the underlying distribution of individual heterogeneity was less than 1%. Our work highlights the differing importance of individual heterogeneity at the population level compared to the individual level. Although individual heterogeneity in reproduction may result in large differences in the lifetime fitness of individuals, changing the proportion of above- or below-average breeders in the population results in much smaller differences in annual population growth rate. For a long-lived mammal with stable and high adult-survival that gives birth to a single offspring, individual heterogeneity in reproduction has a limited effect on population dynamics. We posit that the limited effect of individual heterogeneity on population dynamics may be due to canalization of life-history traits.

Spatial consistency in drivers of population dynamics of a declining migratory bird.

Many migratory species are in decline across their geographical ranges. Single-population studies can provide important insights into drivers at a local scale, but effective conservation requires multi-population perspectives. This is challenging because relevant data are often hard to consolidate, and state-of-the-art analytical tools are typically tailored to specific datasets. We capitalized on a recent data harmonization initiative (SPI-Birds) and linked it to a generalized modelling framework to identify the demographic and environmental drivers of large-scale population decline in migratory pied flycatchers (Ficedula hypoleuca) breeding across Britain. We implemented a generalized integrated population model (IPM) to estimate age-specific vital rates, including their dependency on environmental conditions, and total and breeding population size of pied flycatchers using long-term (34-64 years) monitoring data from seven locations representative of the British breeding range. We then quantified the relative contributions of different vital rates and population structure to changes in short- and long-term population growth rate using transient life table response experiments (LTREs). Substantial covariation in population sizes across breeding locations suggested that change was the result of large-scale drivers. This was supported by LTRE analyses, which attributed past changes in short-term population growth rates and long-term population trends primarily to variation in annual survival and dispersal dynamics, which largely act during migration and/or nonbreeding season. Contributions of variation in local reproductive parameters were small in comparison, despite sensitivity to local temperature and rainfall within the breeding period. We show that both short- and long-term population changes of British breeding pied flycatchers are likely linked to factors acting during migration and in nonbreeding areas, where future research should be prioritized. We illustrate the potential of multi-population analyses for informing management at (inter)national scales and highlight the importance of data standardization, generalized and accessible analytical tools, and reproducible workflows to achieve them.

A Lipid-Structured Model of Atherosclerotic Plaque Macrophages with Lipid-Dependent Kinetics.

Atherosclerotic plaques are fatty growths in artery walls that cause heart attacks and strokes. Plaque formation is driven by macrophages that are recruited to the artery wall. These cells consume and remove blood-derived lipids, such as modified low-density lipoprotein. Ineffective lipid removal, due to macrophage death and other factors, leads to the accumulation of lipid-loaded macrophages and formation of a necrotic lipid core. Experimental observations suggest that macrophage functionality varies with the extent of lipid loading. However, little is known about the influence of macrophage lipid loads on plaque fate. Extending work by Ford et al. (J Theor Biol 479:48-63, 2019) and Chambers et al. (A lipid-structured model of atherosclerosis with macrophage proliferation, 2022), we develop a plaque model where macrophages are structured by their ingested lipid load and behave in a lipid-dependent manner. The model considers several macrophage behaviours, including recruitment to and emigration from the artery wall; proliferation and apotosis; ingestion of plaque lipids; and secondary necrosis of apoptotic cells. We consider apoptosis, emigration and proliferation to be lipid-dependent and we model these effects using experimentally informed functions of the internalised lipid load. Our results demonstrate that lipid-dependent macrophage behaviour can substantially alter plaque fate by changing both the total quantity of lipid in the plaque and the distribution of lipid between the live cells, dead cells and necrotic core. The consequences of macrophage lipid-dependence are often unpredictable because lipid-dependent effects introduce subtle, nonlinear interactions between the modelled cell behaviours. These observations highlight the importance of mathematical modelling in unravelling the complexities of macrophage lipid accumulation during atherosclerotic plaque formation.

Recovery of critically endangered Nassau grouper (Epinephelus striatus) in the Cayman Islands following targeted conservation actions.

Many large-bodied marine fishes that form spawning aggregations, such as the Nassau grouper (Epinephelus striatus), have suffered regional overfishing due to exploitation during spawning. In response, marine resource managers in many locations have established marine protected areas or seasonal closures to recover these overfished stocks. The challenge in assessing management effectiveness lies largely in the development of accurate estimates to track stock size through time. For the past 15 y, the Cayman Islands government has taken a series of management actions aimed at recovering collapsed stocks of Nassau grouper. Importantly, the government also partnered with academic and nonprofit organizations to establish a research and monitoring program (Grouper Moon) aimed at documenting the impacts of conservation action. Here, we develop an integrated population model of 2 Cayman Nassau grouper stocks based on both diver-collected mark-resight observations and video censuses. Using both data types across multiple years, we fit parameters for a state-space model for population growth. We show that over the last 15 y the Nassau grouper population on Little Cayman has more than tripled in response to conservation efforts. Census data from Cayman Brac, while more sparse, show a similar pattern. These findings demonstrate that spatial and seasonal closures aimed at rebuilding aggregation-based fisheries can foster conservation success.

Management strategy of the naked carp (Gymnocypris przewalskii) in the Qinghai lake using matrix population modeling.

Naked carp (Gymnocypris przewalskii) is the only fish species commercially harvested in Qinghai Lake, which is the largest inland saltwater lake in China. Multiple ecological stresses such as long-term overfishing, drying-up of riverine inflows, and decreases in spawning habitat caused the naked carp population to decrease from 320,000 tons before the 1950s to only 3000 tons by the early 2000s. We used matrix projection population modeling to quantitatively simulate the dynamics of the naked carp population from the 1950s to the 2020s. Five versions of the matrix model were developed from the field and laboratory information that represented different population states (high but declining, low abundance, very low abundance, initial recovery, pristine). Equilibrium analysis was applied to density-independent versions of the matrices and population growth rate, age composition, and elasticities were compared among versions. Stochastic, density-dependent version of the most recent decade (recovering) version was used to simulate the time-dependent responses to a range of levels of artificial reproduction (addition of age-1 from hatchery) and of the pristine version to simulate combinations of fishing rate and minimum age of harvest. Results showed the major role of overfishing in the population decline and that the population growth rate was most sensitive to the survival of juveniles and the spawning success of early-age adults. Dynamic simulations showed a rapid population response to artificial reproduction when population abundance was low and that if artificial reproduction continues at its current level, then population biomass would reach 75% of its pristine biomass after 50 years. Simulations with the pristine version identified sustainable fishing levels and the importance of protecting the first few ages of maturity. Overall, modeling results showed that artificial reproduction under conditions of no fishing is an effective approach to restoring the naked carp population. Further effectiveness should consider maximizing survival in the months just after release and maintaining genetic and phenotypic diversity. More information on density-dependent growth, survival, and reproduction, as well as on the genetic diversity and growth and migratory behavior (phenotypic variation) of released and native-spawned fish, would help inform management and conservation strategies and practices going forward.

Life history adaptations to fluctuating environments: Combined effects of demographic buffering and lability.

Demographic buffering and lability have been identified as adaptive strategies to optimise fitness in a fluctuating environment. These are not mutually exclusive, however, we lack efficient methods to measure their relative importance for a given life history. Here, we decompose the stochastic growth rate (fitness) into components arising from nonlinear responses and variance-covariance of demographic parameters to an environmental driver, which allows studying joint effects of buffering and lability. We apply this decomposition for 154 animal matrix population models under different scenarios to explore how these main fitness components vary across life histories. Faster-living species appear more responsive to environmental fluctuations, either positively or negatively. They have the highest potential for strong adaptive demographic lability, while demographic buffering is a main strategy in slow-living species. Our decomposition provides a comprehensive framework to study how organisms adapt to variability through buffering and lability, and to predict species responses to climate change.