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ABSTRACT The population regulation of animals depends on fertility and survivorship. Hunting can affect population growth through changes in reproduction and survivorship. Understanding these changes in vital rates is crucial for the control of invasive mammals. With the objective to assess the influence of different population removal pressures on the finite population growth rate (흀) of an invasive mammal, this research used demographic data estimated from 922 invasive beavers (Castor canadensis) eradicated from seven areas from Isla Grande de Tierra del Fuego, Argentina. Areas were classified into four removal pressures: higher, high‐intermediate, low‐intermediate, and lower removal pressure. The hypothesis states that the higher removal pressure produces higher population growth and resilience. Leslie matrix models were used to estimate 흀, generation time, damping ratio, stable age distribution, reproductive value, and the sensitivity–elasticity of survivorship and fertility of the females for each removal pressure. The 흀 and damping ratio increased with the removal pressure, as expected; the inverse occurred with the generation time. The survivorship of the younger age classes was the most sensitive and elastic vital rate regardless of removal pressure, followed by the breeding onset. The fertility was less relevant on 흀. The beaver population would depend more on the survival of kits, 1‐year‐olds, and subadults, than the number of offspring produced. A management strategy is proposed focusing on affecting the survivorship of younger age classes, eliminating first the adult animals and then the younger beavers. [ABSTRACT FROM AUTHOR]

Isolation caused by anthropogenic habitat fragmentation can destabilize populations. Populations relying on the inflow of immigrants can face reduced fitness due to inbreeding depression as fewer new individuals arrive. Empirical studies of the demographic consequences of isolation are critical to understand how populations persist through changing conditions. We used a 34‐year demographic and environmental dataset from a population of cooperatively breeding Florida Scrub‐Jays (Aphelocoma coerulescens) to create mechanistic models linking environmental and demographic factors to population growth rates. We found that the population has not declined despite both declining immigration and increasing inbreeding, owing to a coinciding response in breeder survival. We find evidence of density‐dependent immigration, breeder survival and fecundity, indicating that interactions between vital rates and local density play a role in buffering the population against change. Our study elucidates the impacts of isolation on demography and how long‐term stability is maintained via demographic responses. [ABSTRACT FROM AUTHOR]

Savannas are the major biome in tropical regions of the globe, defined as sparsely wooded regions with a continuous herbaceous layer of mainly C4 grasses where rainfall is distinctly seasonal. Fire is a common feature of most savannas. The largest protected areas of savannas are found in sparsely populated monsoonal northcentral Australia with strong annual wet and dry seasons. The most common vegetation type is relatively intact, tall (<15 m), open forests where Eucalyptus canopy trees form the basic structure. Over the past half century, traditional indigenous fire regimes were largely replaced by contemporary fires where individual trees may experience fire as often as 3 out of 5 years. The potential for long‐term persistence of the canopy tree populations is an open question. A stage‐based population model of the canopy trees was previously developed to address this question, drawing on data from three decades of experimental field studies wherein the survival, growth, and reproduction of individual marked trees were recorded under different seasonal fires and understory types to produce transition matrices among eight life history stages, and used to calculate population growth rates (λ). Here, we apply that model to determine how λ varies across a range of fire return intervals from 1 to 12 years for both early and late dry season fires, in two different understory types. We also explore the sensitivity of λ to two key life history parameters: recruitment and seedling survival. Minimum fire return intervals of 2–5 years were generally required for λ ≥1 that would allow populations to persist; these were shorter with stochastic year‐to‐year timing of fires and with higher recruitment rates. Uniquely, under certain conditions, there was also a maximum fire return interval above which λ <1, creating a "window" of fire return intervals that allowed canopy tree populations to persist. Mechanisms underpinning results as well as implications for savanna structure, alternate states, cyclical dynamics, future research, and management by fire are discussed. [ABSTRACT FROM AUTHOR]

Environmental factors and individual attributes, and their interactions, impact survival, growth and reproduction of an individual throughout its life. In the clonal rotifer Brachionus, low food conditions delay reproduction and extend lifespan. This species also exhibits maternal effect senescence; the offspring of older mothers have lower survival and reproductive output. In this paper, we explored the population consequences of the individual‐level interaction of maternal age and low food availability. We built matrix population models for both ad libitum and low food treatments, in which individuals are classified both by their age and maternal age. Low food conditions reduced population growth rate (Δλ=−0.0574$$ \Delta \lambda =-0.0574 $$) and shifted the population structure to older maternal ages, but did not detectably impact individual lifetime reproductive output. We analysed hypothetical scenarios in which reduced fertility or survival led to approximately stationary populations that maintained the shape of the difference in demographic rates between the ad libitum and low food treatments. When fertility was reduced, the populations were more evenly distributed across ages and maternal ages, while the lower‐survival models showed an increased concentration of individuals in the youngest ages and maternal ages. Using life table response experiment analyses, we compared populations grown under ad libitum and low food conditions in scenarios representing laboratory conditions, reduced fertility and reduced survival. In the laboratory scenario, the reduction in population growth rate under low food conditions is primarily due to decreased fertility in early life. In the lower‐fertility scenario, contributions from differences in fertility and survival are more similar, and show trade‐offs across both ages and maternal ages. In the lower‐survival scenario, the contributions from decreased fertility in early life again dominate the difference in λ$$ \lambda $$. These results demonstrate that processes that potentially benefit individuals (e.g. lifespan extension) may actually reduce fitness and population growth because of links with other demographic changes (e.g. delayed reproduction). Because the interactions of maternal age and low food availability depend on the population structure, the fitness consequences of an environmental change can only be fully understood through analysis that takes into account the entire life cycle. [ABSTRACT FROM AUTHOR]

Individual vital rates, such as mortality and birth rates, are key determinants of lifetime reproductive success, and variability in these rates shapes population dynamics. Previous studies have found that this vital rate heterogeneity can influence demographic properties, including population growth rates. However, the explicit effects of the variation within and the covariance between vital rates that can also vary throughout the lifespan on population growth remain 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 collapse 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 depend 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. [ABSTRACT FROM AUTHOR]

Reconstructing past ecological population dynamics and demographic events is crucial for understanding the dynamics of ecological processes, evaluating the impact of environmental changes and making informed conservation decisions. In forest ecosystems, retrodiction (i.e. the backward projection of ecological populations) plays a pivotal role in understanding historical forest carbon levels and the factors that have influenced their variation over time, because forest demography is a major determinant of the amount of carbon stored in forest ecosystems. The persistent lack of quantitative methods has been a significant obstacle in retrodicting forest demography, especially in applications of a broad geographical scale. While there is a wealth of models for predicting future forest conditions, models that can project these conditions backward in time are scarce.This study presents reverse matrix model (RMM), an innovative retrodiction modelling approach grounded in the principles of transition matrix models. RMM is designed to deduce past demographic characteristics of ecological populations using current data, making it one of the first models capable of projecting the fine‐scale dynamics of forest demography into the past.We assessed the retrodictive performance of RMM by fitting it to a dataset of a disturbed tropical rainforest in French Guiana in 2001–2023, then comparing the retrodictions to observations back to 1983 when the disturbance occurred. We further empirically evaluated the viability of retrodiction over a defined duration by inverting the density‐dependent matrix model by Lin et al. (1996), which predicts the dynamics of northern hardwoods in the United States.The case studies demonstrate significant potential for RMM application in various domains of forestry and conservation, including ecosystem management and conservation planning, global change impact assessment and biodiversity monitoring. [ABSTRACT FROM AUTHOR]

Abstract Reconstructing past ecological population dynamics and demographic events is crucial for understanding the dynamics of ecological processes, evaluating the impact of environmental changes and making informed conservation decisions. In forest ecosystems, retrodiction (i.e. the backward projection of ecological populations) plays a pivotal role in understanding historical forest carbon levels and the factors that have influenced their variation over time, because forest demography is a major determinant of the amount of carbon stored in forest ecosystems. The persistent lack of quantitative methods has been a significant obstacle in retrodicting forest demography, especially in applications of a broad geographical scale. While there is a wealth of models for predicting future forest conditions, models that can project these conditions backward in time are scarce. This study presents reverse matrix model (RMM), an innovative retrodiction modelling approach grounded in the principles of transition matrix models. RMM is designed to deduce past demographic characteristics of ecological populations using current data, making it one of the first models capable of projecting the fine‐scale dynamics of forest demography into the past. We assessed the retrodictive performance of RMM by fitting it to a dataset of a disturbed tropical rainforest in French Guiana in 2001–2023, then comparing the retrodictions to observations back to 1983 when the disturbance occurred. We further empirically evaluated the viability of retrodiction over a defined duration by inverting the density‐dependent matrix model by Lin et al. (1996), which predicts the dynamics of northern hardwoods in the United States. The case studies demonstrate significant potential for RMM application in various domains of forestry and conservation, including ecosystem management and conservation planning, global change impact assessment and biodiversity monitoring.

The work presented a general discrete-time model of a population of trees affected by a parasite. The tree population was considered size-structured, and the parasite was represented by a single scalar variable. Parasite dynamics were assumed to act on a faster timescale than tree dynamics. The model was studied based on an associated nonlinear matrix model, in which the presence of the parasites was only reflected in the value of its parameters. For the model in all its generality, an explicit condition of viability/extinction of the parasite/tree community was found. In a simplified model with two size-classes of trees and particular forms of the vital rates, it was shown that the model undergoes a transcritical bifurcation and, likewise, a period-doubling bifurcation. It was found that, for any tree fertility rate that makes them viable without a parasite, if the parasite sufficiently reduces the survival of young trees, it can lead to the extinction of the entire community. The same cannot be assured if the parasite acts on adult trees. In situations where a high fertility rate coupled with a low survival rate of adult trees causes a non-parasitized population of trees to fluctuate, a parasite sufficiently damaging only young trees can stabilize the population. If, instead, the parasite acts on adult trees, we can find a destabilization condition on the tree population that brings them from a stable to an oscillating regime.

The effects of climate change are now more pervasive than ever. Marine ecosystems have been particularly impacted by climate change, with marine heatwaves (MHWs) being a strong driver of mass mortality events. Even in the most optimistic greenhouse gas emission scenarios, MHWs will continue to increase in frequency, intensity and duration. For this reason, understanding the resilience of marine species to the increase of MHWs is crucial to predicting their viability under future climatic conditions. In this study, we explored the consequences of MHWs on the resilience (the ability of a population to resist and recover after a disturbance) of a Mediterranean key octocoral species, Paramuricea clavata, to further disturbances to their population structure. To quantify P. clavata's capacity to resist and recover from future disturbances, we used demographic information collected from 1999 to 2022, from two different sites in the NW Mediterranean Sea to calculate the transient dynamics of their populations. Our results showed that the differences in the dynamics of populations exposed and those not exposed to MHWs were driven mostly by differences in mean survivorship and growth. We also showed that after MHWs P. clavata populations had lower resistance and slower rates of recovery than those not exposed to MHWs. Populations exposed to MHWs had lower resistance elasticity to most demographic processes compared to unexposed populations. In contrast, the only demographic process showing some differences when comparing the speed of recovery elasticity values between populations exposed and unexposed to MHWs was stasis. Finally, under scenarios of increasing frequency of MHWs, the extinction of P. clavata populations will accelerate and their capacity to resist and recover after further disturbances will be hampered. Overall, these findings confirm that future climatic conditions will make octocoral populations even more vulnerable to further disturbances. These results highlight the importance of limiting local impacts on marine ecosystems to dampen the consequences of climate change. [ABSTRACT FROM AUTHOR]

Abstract Savannas are the major biome in tropical regions of the globe, defined as sparsely wooded regions with a continuous herbaceous layer of mainly C4 grasses where rainfall is distinctly seasonal. Fire is a common feature of most savannas. The largest protected areas of savannas are found in sparsely populated monsoonal northcentral Australia with strong annual wet and dry seasons. The most common vegetation type is relatively intact, tall (

Many population statistics describe the characteristics of populations within and among species. These are useful for describing population dynamics, understanding how environmental factors alter demographic patterns, testing hypotheses related to the evolution of life history characteristics and informing the effective management of populations.In this study, we propose a population statistic: the interstage flow. The interstage flow is defined as the product of the element in the ith row, the jth column of the population projection matrix and the jth element of the normalized stable stage distribution.The sum of the interstage flow matrix elements is equal to the population growth rate (PGR), which is the dominant eigenvalue of the population projection matrix. The interstage flow matrix elements allow decomposition of PGR into component contributions made by transitions between developmental stages.We demonstrate the utility of interstage flow matrices using matrix population models from the COMPADRE plant matrix database. We compared interstage flows among four life history/functional groups (FGs) (semelparous herbs, iteroparous herbs, shrubs and trees) and described how PGR reflected individual transitions related to stasis, fecundity and growth. We found that the individual flows are different among FGs.Synthesis. The proposed population statistic, the interstage flow matrix, describes the contribution of individual developmental stage transitions to the PGR. The flow of individuals between developmental stages differs in distinctive ways among different life histories and FGs. The interstage flow matrix is a valuable statistic for describing these differences. [ABSTRACT FROM AUTHOR]

That anti-predator behavior can have large demographic consequences (called risk effects) is theoretically well-founded and experimentally supported. Here we investigate whether this mechanism could be contributing to population declines reported over recent decades for many shorebird species, especially long-distance migrants. Sandpipers are known to have adjusted behavioral and morphological traits to counter the migratory danger posed by the increase in abundance of an important predator, the Peregrine Falcon ( Falco peregrinus ), ongoing steadily since the mid-1970s. Individuals in some shorebird species skip migration and breeding (over-summer), remaining instead on or near non-breeding areas. Over-summering can be considered an anti-predator tactic because it avoids all exposure to predators during migration, though at the expense of a foregone breeding season. We hypothesize that over-summering by the Semipalmated Sandpiper ( Calidris pusilla ) has increased during recent decades as migration became more dangerous. A stage-structured matrix population model based on survival rates measured in Perú 2011–2017 indicates that Semipalmated Sandpiper population growth is negative at current over-summering levels (adults 19%, yearlings 28%). A substantial proportion of the large reduction in their numbers since 1980 could theoretically be accounted for if over-summering levels rose to this level after ~1980. Though good data are scanty, the historical level of over-summering appears to have been lower. The powerful ecological effects of apex predators have been recognized in many systems, but to date the recovery of falcon populations has not been considered as a possible factor in shorebird declines. Closer scrutiny of this hypothesis is warranted.

Recent studies have opened the way for using elicitor‐induced resistance in plants as a method to control arthropod pests. In this study, 1,3‐β‐glucan laminarin, an elicitor of disease resistance in plants, was tested on the green peach aphid, Myzus persicae (Sulzer) (Hemiptera: Aphididae), on peach [Prunus persica (L.) Batsch, Rosaceae] plantlets and evaluated its effects on short‐term mortality and population growth. Laminarin exposure did not affect aphid survival in the short term; however, laminarin‐treated peach plants sustained fewer nymphs and adults in comparison with the control. Aphid populations on plants treated with laminarin declined significantly over the sampling period compared to the control. Moreover, the demographic parameters net reproductive rate (R0), finite rate of increase (λ), and intrinsic rate of increase (rm), all showed decreasing trends in aphid populations reared on laminarin‐treated plants. The decline in aphid populations exposed to laminarin seemed to mainly be linked to reduced adult survival, slower nymph development, and lower nymph survival and only marginally to changes in reproduction outcome. Changes in gene expression causing the final production of defence chemicals by peach plants may contribute to explaining the results. However, potential direct effects of laminarin on M. persicae feeding activity and probing behaviour cannot be ruled out. This study provides evidence that, although laminarin did not display insecticidal activity in the short term, this elicitor caused sublethal effects, significantly reducing aphid populations. [ABSTRACT FROM AUTHOR]

Harvesting and culling are methods used to monitor and manage wildlife diseases. An important consequence of these practices is a change in the genetic dynamics of affected populations that may threaten their long‐term viability. The effective population size (Ne) is a fundamental parameter for describing such changes as it determines the amount of genetic drift in a population. Here, we estimate Ne of a harvested wild reindeer population in Norway. Then we use simulations to investigate the genetic consequences of management efforts for handling a recent spread of chronic wasting disease, including increased adult male harvest and population decimation. The Ne/N ratio in this population was found to be 0.124 at the end of the study period, compared to 0.239 in the preceding 14 years period. The difference was caused by increased harvest rates with a high proportion of adult males (older than 2.5 years) being shot (15.2% in 2005–2018 and 44.8% in 2021). Increased harvest rates decreased Ne in the simulations, but less sex biased harvest strategies had a lower negative impact. For harvest strategies that yield stable population dynamics, shifting the harvest from calves to adult males and females increased Ne. Population decimation always resulted in decreased genetic variation in the population, with higher loss of heterozygosity and rare alleles with more severe decimation or longer periods of low population size. A very high proportion of males in the harvest had the most severe consequences for the loss of genetic variation. This study clearly shows how the effects of harvest strategies and changes in population size interact to determine the genetic drift of a managed population. The long‐term genetic viability of wildlife populations subject to a disease will also depend on population impacts of the disease and how these interact with management actions. [ABSTRACT FROM AUTHOR]

As wildlife is increasingly affected by environmental change, identifying how vital rates vary with ecological factors is essential to predict the consequences of environmental perturbations on wild population dynamics. We explored the effects of habitat constraints on the demographic and life history patterns of two Barbary macaque (Macaca sylvanus) populations living in two contrasted habitats in Algeria. Using 11 years of field data, we estimated age‐specific survival rates of females and of infants of both sexes, as well as female reproduction rates. We investigated how these vital rates were influenced by both intra‐ and inter‐habitat environmental variations. We parameterized age‐structured female‐only transition matrices and conducted a prospective analysis to estimate the contribution of each vital rate to the populations' asymptotic growth rates (λ). A retrospective analysis (LTRE, Life Table Response Experiment) was also conducted to determine how each vital rate contributed to the observed differences in λ between populations. The macaques exhibited common patterns of survival and reproduction (low rates at young ages, and then high and stable until a decrease at old ages), with first evidence of both actuarial and reproductive senescence. Both populations were growing. In both populations, adult and immature survival had the highest elasticities, and remained stable in changing environmental conditions. By contrast, infant survival and female reproduction had low elasticities, and varied more with environmental variations. As Barbary macaque habitats are increasingly degrading, we provide robust estimates of their vital rates with conservation implications, in particular to predict population responses to anthropogenic perturbations. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Life history traits are used to predict asymptotic odds of extinction from dynamic conditions. Less is known about how life history traits interact with stochasticity and population structure of finite populations to predict near‐term odds of extinction. Through empirically parameterized matrix population models, we study the impact of life history (reproduction, pace), stochasticity (environmental, demographic), and population history (existing, novel) on the transient population dynamics of finite populations of plant species. Among fast and slow pace and either a uniform or increasing reproductive intensity or short or long reproductive lifespan, slow, semelparous species are at the greatest risk of extinction. Long reproductive lifespans buffer existing populations from extinction while the odds of extinction of novel populations decrease when the reproductive effort is uniformly spread across the reproductive lifespan. Our study highlights the importance of population structure, pace, and two distinct aspects of parity for predicting near‐term odds of extinction. [ABSTRACT FROM AUTHOR]

Mast seeding is the episodic, massive production of plant seeds synchronized over large areas. The resulting superabundance of seeds represents a resource pulse that can profoundly affect animal populations across trophic levels. Following years of high seed production, the abundance of both seed consumers and their predators increase. Higher predator abundance leads to increased predation pressure across the trophic web, impacting nonseed consumers such as the wood warbler Phylloscopus sibilatrix through increased nest predation after tree mast years. Over the past 30 years, the frequency of tree seed masts has increased, while wood warbler populations have declined in several regions of Europe. We hypothesized that increasing mast frequencies may have contributed to the observed population declines by creating suboptimal breeding conditions in years after masting. We measured reproductive output in four study areas in central Europe, which was between 0.61 and 1.24 fledglings lower in the years following masting than nonmasting. For each study area, we used matrix population models to predict population trends based on the estimated reproductive output and the local mast frequencies. We then compared the predicted with the observed population trends to assess if the frequency of mast years had contributed to the population dynamics. In Wielkopolska National Park (PL) and Hessen (DE), masting occurred on average only every 4 years and populations were stable or nearly so, whereas in Jura (CH) and Białowieża National Park (PL), masting occurred every 2 and 2.5 years, respectively, and populations were declining. The simple matrix population models predicted the relative difference among local population trends over the past 10–20 years well, suggesting that the masting frequency may partly explain regional variation in population trends. Simulations suggest that further increases in mast frequency will lead to further declines in wood warbler populations. We show that changes in a natural process, such as mast seeding, may contribute to the decline in animal populations through cascading effects. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Reintroductions are increasingly used for re‐establishing populations, though the documented success rates are variable. Success is typically measured by the survival and breeding success of released individuals and subsequent establishment and growth of the population. However, few studies quantify demographic rates of reintroduced populations of long‐lived species, with slower dynamics and lower reproductive rates, and the demographic rates of subsequent generations, which determine population growth and persistence, are often unknown. We document the success of the reintroduction of the Common Crane Grus grus to south‐west England in the UK, using survival analysis and population modelling to determine whether the overarching aim of establishing a self‐sustaining population is likely to be achieved. Between 2010 and 2014, 93 Common Cranes were hatched from wild eggs, custom‐reared and soft‐released into suitable habitat. Survival of all age‐classes was apparently higher than survival of healthy wild individuals, particularly in juvenile age‐classes, and was higher in females than in males. Productivity was relatively low, but increased with age. Assuming that the demographic rates of subsequent generations are at the levels estimated for the captive‐reared population, slow positive population growth is predicted over the next 30 years. Sensitivity analyses showed that the persistence of this population is sensitive to even a slight decrease in values of adult survival, and growth is impacted to a lesser extent by juvenile survival and levels of productivity. This study highlights the ability to achieve persistence in a reintroduced population despite low levels of productivity when survival is exceptionally high. It also illustrates the need for long‐term monitoring to establish reintroduction success in animals that have slow life histories: 9 years after initial releases, the Common Crane population remains dominated by first‐generation birds and productivity is skewed by transient age‐structure and the late onset of reproductive success. [ABSTRACT FROM AUTHOR]

Abstract Matrix population models are frequently built and used by ecologists to analyse demography and elucidate the processes driving population growth or decline. Life Table Response Experiments (LTREs) are comparative analyses that decompose the realized difference or variance in population growth rate (λ) into contributions from the differences or variances in the vital rates (i.e. the matrix elements). Since their introduction, LTREs have been based on approximations and have not included biologically relevant interaction terms. We used the functional analysis of variance framework to derive an exact LTRE method, which calculates the exact response of λ to the difference or variance in a given vital rate, for all interactions among vital rates—including higher‐order interactions neglected by the classical methods. We used the publicly available COMADRE and COMPADRE databases to perform a meta‐analysis comparing the results of exact and classical LTRE methods. We analysed 186 and 1487 LTREs for animal and plant matrix population models, respectively. We found that the classical methods often had small errors, but that very high errors were possible. Overall error was related to the difference or variance in the matrices being analysed, consistent with the Taylor series basis of the classical method. Neglected interaction terms accounted for most of the errors in fixed design LTRE, highlighting the importance of two‐way interaction terms. For random design LTRE, errors in the contribution terms present in both classical and exact methods were comparable to errors due to neglected interaction terms. In most examples we analysed, evaluating exact contributions up to three‐way interaction terms was sufficient for interpreting 90% or more of the difference or variance in λ. Relative error, previously used to evaluate the accuracy of classical LTREs, is not a reliable metric of how closely the classical and exact methods agree. Error compensation between estimated contribution terms and neglected contribution terms can lead to low relative error despite faulty biological interpretation. Trade‐offs or negative covariances among matrix elements can lead to high relative error despite accurate biological interpretation. Exact LTRE provides reliable and accurate biological interpretation, and the R package exactLTRE makes the exact method accessible to ecologists.

Given several nonnegative matrices with a single pattern of allocation among their zero/nonzero elements, the average matrix should have the same pattern, too. This is the first tenet of the pattern-multiplicative average (PMA) concept, while the second one suggests the multiplicative (or geometric) nature of averaging. The original concept of PMA was motivated by the practice of matrix population models as a tool to assess the population viability from long-term monitoring data. The task has reduced to searching for an approximate solution to an overdetermined system of polynomial equations for unknown elements of the average matrix (G), and hence to a nonlinear constrained minimization problem for the matrix norm. Former practical solutions faced certain technical problems, which required sophisticated algorithms but returned acceptable estimates. Now, we formulate (for the first time in ecological modeling and nonnegative matrix theory) the PMA problem as an eigenvalue approximation one and reduce it to a standard problem of linear programing (LP). The basic equation of averaging also determines the exact value of λ1(G), the dominant eigenvalue of matrix G, and the corresponding eigenvector. These are bound by the well-known linear equations, which enable an LP formulation of the former nonlinear problem. The LP approach is realized for 13 fixed-pattern matrices gained in a case study of Androsace albana, an alpine short-lived perennial, monitored on permanent plots over 14 years. A standard software routine reveals the unique exact solution, rather than an approximate one, to the PMA problem, which turns the LP approach into ''the best of versatile optimization tools". The exact solution turns out to be peculiar in reaching zero bounds for certain nonnegative entries of G, which deserves modified problem formulation separating the lower bounds from zero. [ABSTRACT FROM AUTHOR]

While the recent population recovery of bald eagles (Haliaeetus leucocephalus) in New York State, USA, is a conservation success, evidence from necropsies suggest that ingested lead (Pb) from ammunition fragments is causing morbidity and mortality to wild eagles. Wildlife managers and officials at the New York State Department of Environmental Conservation would benefit from analysis of their necropsy data to understand how documented morbidities or mortalities impact dynamics of the remaining wild eagle population. We integrated necropsy data on bald eagles in New York State collected between 1990 and 2018 by the New York State Department of Environmental Conservation into a matrix population model. We compared annual survival of hatchling, non‐breeding, and breeding eagles under factual (Pb) and counter factual (Pb‐reduced or Pb‐free) scenarios. We found no evidence that Pb altered annual survival of hatchlings. Lead was associated with a reduction in the annual survival of non‐breeders by 0–0.056 (females) and 0.052–0.057 (males), and a reduction in the annual survival of breeders by 0.051–0.057 (females) and 0–0.032 (males). Lead was associated with a reduction in the long‐term growth rate (λ) by 0.009–0.036 (females) and 0.023–0.035 (males). Due to altered dynamics over the prior 3 decades, abundances of eagles in the most recent year of the study (2018) differed between Pb and non‐Pb systems; Pb was associated with a reduction in the number of total females by 15–610 birds, but an increase in the number of total males by 43–95 birds. The interactive software depicting these and other results is available for public use. Our study provides state‐specific evidence of the population‐scale impact of Pb ammunition on bald eagles and may be helpful to wildlife officials in the creation of educational materials or regulatory measures in habitats that support free‐ranging bald eagles. [ABSTRACT FROM AUTHOR]

Abstract While the recent population recovery of bald eagles (Haliaeetus leucocephalus) in New York State, USA, is a conservation success, evidence from necropsies suggest that ingested lead (Pb) from ammunition fragments is causing morbidity and mortality to wild eagles. Wildlife managers and officials at the New York State Department of Environmental Conservation would benefit from analysis of their necropsy data to understand how documented morbidities or mortalities impact dynamics of the remaining wild eagle population. We integrated necropsy data on bald eagles in New York State collected between 1990 and 2018 by the New York State Department of Environmental Conservation into a matrix population model. We compared annual survival of hatchling, non‐breeding, and breeding eagles under factual (Pb) and counter factual (Pb‐reduced or Pb‐free) scenarios. We found no evidence that Pb altered annual survival of hatchlings. Lead was associated with a reduction in the annual survival of non‐breeders by 0–0.056 (females) and 0.052–0.057 (males), and a reduction in the annual survival of breeders by 0.051–0.057 (females) and 0–0.032 (males). Lead was associated with a reduction in the long‐term growth rate (λ) by 0.009–0.036 (females) and 0.023–0.035 (males). Due to altered dynamics over the prior 3 decades, abundances of eagles in the most recent year of the study (2018) differed between Pb and non‐Pb systems; Pb was associated with a reduction in the number of total females by 15–610 birds, but an increase in the number of total males by 43–95 birds. The interactive software depicting these and other results is available for public use. Our study provides state‐specific evidence of the population‐scale impact of Pb ammunition on bald eagles and may be helpful to wildlife officials in the creation of educational materials or regulatory measures in habitats that support free‐ranging bald eagles.

To estimate abundance, surveys of marine mammals often rely on samples of satellite‐tagged individuals to correct counts for the proportion of animals that are unavailable to be detected. However, naïve application of this correction relies on the key assumption that availability of the tagged sample resembles that of the population. Here, we show how matrix population models can be used to estimate stable age‐ and stage‐proportions, and how these can be used to adjust aerial survey correction factors so that they represent population‐level availability. We illustrate this procedure using data from ice‐associated seals in the Bering, Chukchi, and Beaufort Seas. After compiling life history data for bearded (Erignathus barbatus), ribbon (Histriophoca fasciata), ringed (Pusa hispida), and spotted seals (Phoca largha), we find that correction factors ignoring age‐sex composition can positively bias spotted seal abundance by an average of 13% and negatively bias ribbon seal abundance by an average of 5%. Note that we did not examine potential bias for bearded or ringed seals due to low sample sizes; as such, we urge caution in interpretation of abundance estimates for these species. [ABSTRACT FROM AUTHOR]

Environmental contamination due to pest control in general, and mosquito control in particular, is an important issue expected to increase with climate change. We use a validated model for population dynamics of mosquitoes and historical environmental data to explore performance of larvicidal, adulticidal, and combined treatments. Results show that depending on treatment timing, larvicidal treatments can induce very good results, or have negative outcomes that increase overall mosquito population. Combined larvicidal and adulticidal treatments, however, exhibit much lesser dependence on timing, and therefore give the greatest chance of positive outcomes if environmental conditions are not known. Based on the results, we argue for adaptive mosquito management, in which weather data and forecasts are used to drive a model that identifies best intervals for insecticide use. Such an approach can have considerably better results than static, calendar-driven management and, therefore, considerably reduce environmental contamination. Adaptive management could consider larvicidal treatment because it gives good results if the timing is correct. Static management should, however, combine larvicidal and adulticidal treatments for the greatest chance of success. [ABSTRACT FROM AUTHOR]

The fate of natural populations is mediated by complex interactions among vital rates, which can vary within and among years. Although the effects of random, among‐year variation in vital rates have been studied extensively, relatively little is known about how periodic, nonrandom variation in vital rates affects populations. This knowledge gap is potentially alarming as global environmental change is projected to alter common periodic variations, such as seasonality. We investigated the effects of changes in vital‐rate periodicity on populations of three species representing different forms of adaptation to periodic environments: the yellow‐bellied marmot (Marmota flaviventer), adapted to strong seasonality in snowfall; the meerkat (Suricata suricatta), adapted to inter‐annual stochasticity as well as seasonal patterns in rainfall; and the dewy pine (Drosophyllum lusitanicum), adapted to fire regimes and periodic post‐fire habitat succession. To assess how changes in periodicity affect population growth, we parameterized periodic matrix population models and projected population dynamics under different scenarios of perturbations in the strength of vital‐rate periodicity. We assessed the effects of such perturbations on various metrics describing population dynamics, including the stochastic growth rate, log λS. Overall, perturbing the strength of periodicity had strong effects on population dynamics in all three study species. For the marmots, log λS decreased with increased seasonal differences in adult survival. For the meerkats, density dependence buffered the effects of perturbations of periodicity on log λS. Finally, dewy pines were negatively affected by changes in natural post‐fire succession under stochastic or periodic fire regimes with fires occurring every 30 years, but were buffered by density dependence from such changes under presumed more frequent fires or large‐scale disturbances. We show that changes in the strength of vital‐rate periodicity can have diverse but strong effects on population dynamics across different life histories. Populations buffered from inter‐annual vital‐rate variation can be affected substantially by changes in environmentally driven vital‐rate periodic patterns; however, the effects of such changes can be masked in analyses focusing on inter‐annual variation. As most ecosystems are affected by periodic variations in the environment such as seasonality, assessing their contributions to population viability for future global‐change research is crucial. [ABSTRACT FROM AUTHOR]

Matrix population models are frequently built and used by ecologists to analyse demography and elucidate the processes driving population growth or decline. Life Table Response Experiments (LTREs) are comparative analyses that decompose the realized difference or variance in population growth rate (λ) into contributions from the differences or variances in the vital rates (i.e. the matrix elements). Since their introduction, LTREs have been based on approximations and have not included biologically relevant interaction terms.We used the functional analysis of variance framework to derive an exact LTRE method, which calculates the exact response of λ to the difference or variance in a given vital rate, for all interactions among vital rates—including higher‐order interactions neglected by the classical methods. We used the publicly available COMADRE and COMPADRE databases to perform a meta‐analysis comparing the results of exact and classical LTRE methods. We analysed 186 and 1487 LTREs for animal and plant matrix population models, respectively.We found that the classical methods often had small errors, but that very high errors were possible. Overall error was related to the difference or variance in the matrices being analysed, consistent with the Taylor series basis of the classical method. Neglected interaction terms accounted for most of the errors in fixed design LTRE, highlighting the importance of two‐way interaction terms. For random design LTRE, errors in the contribution terms present in both classical and exact methods were comparable to errors due to neglected interaction terms. In most examples we analysed, evaluating exact contributions up to three‐way interaction terms was sufficient for interpreting 90% or more of the difference or variance in λ.Relative error, previously used to evaluate the accuracy of classical LTREs, is not a reliable metric of how closely the classical and exact methods agree. Error compensation between estimated contribution terms and neglected contribution terms can lead to low relative error despite faulty biological interpretation. Trade‐offs or negative covariances among matrix elements can lead to high relative error despite accurate biological interpretation. Exact LTRE provides reliable and accurate biological interpretation, and the R package exactLTRE makes the exact method accessible to ecologists. [ABSTRACT FROM AUTHOR]

Given several nonnegative matrices with a single pattern of allocation among their zero/nonzero elements, the average matrix should have the same pattern as well. This is the first tenet of the pattern-multiplicative average (PMA) concept, while the second one suggests the multiplicative nature of averaging. The concept of PMA was motivated in a number of application fields, of which we consider the matrix population models and illustrate solving the PMA problem with several sets of model matrices calibrated in particular botanic case studies. The patterns of those matrices are typically nontrivial (they contain both zero and nonzero elements), the PMA problem thus having no exact solution for a fundamental reason (an overdetermined system of algebraic equations). Therefore, searching for the approximate solution reduces to a constrained minimization problem for the approximation error, the loss function in optimization terms. We consider two alternative types of the loss function and present a general algorithm of searching the optimal solution: basin-hopping global search, then local descents by the method of conjugate gradients or that of penalty functions. Theoretical disadvantages and practical limitations of both loss functions are discussed and illustrated with a number of practical examples. [ABSTRACT FROM AUTHOR]

Human perturbations affect many aquatic ecosystems globally. We use age‐structured matrix population models to explore how population growth rates in short‐lived freshwater fish are affected by recurrent environmental perturbations to river ecosystems. Simulations are summarized to reveal how species‐specific fitness characteristics contribute to population sustainability in habitats subject to recurrent perturbation. Deterministic calculations are used to estimate time to population recovery with successive years of intermittence disturbance, followed by post‐perturbation equilibrium conditions. Perturbation that reduces only juvenile survival has a shorter recovery time to initial population size and greater resilience of population growth than when adult survival is reduced. Consecutive occurrences of perturbation lengthen recovery time nonlinearly, more notably when adults experience perturbation mortality. We illustrate with an example how managers could identify multiple options to mitigate recurrent ecosystem perturbations by reducing perturbation frequency and/or mitigating perturbation mortality. Our simulations suggest parameter approximations for a hypothetical species provide a useful frame of reference for river restoration and conservation when life history data are lacking for a specific species of concern. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Lake Sturgeon (Acipenser fulvescens) is a species of conservation concern throughout North America, and healthy populations are rare. Earlier sampling efforts identified the Goulais Bay population in Lake Superior as a potentially healthy population after three years of sampling. With seven additional years of sampling, we updated the earlier analysis and developed a matrix population model to conduct a population viability analysis (PVA). We identified a non-linear relationship between cohort strength and May river discharge rate which was incorporated into the population model to evaluate the influence of future discharge scenarios on population persistence. Population size was estimated, with an open-population mark-recapture model, at approximately 5,200 juvenile Lake Sturgeon. This estimate equates to approximately 440 mature females and 625 mature males in the population. A population of this size has a probability of extinction of 4 % and 18 % over 250 and 1000 years under status quo conditions. If the May river discharge were to decrease in the future, which may represent the most likely scenario under future climate conditions, our model predicts an increased risk of population extirpation. This indicates that increased management actions may be required to ensure this population remains resilient. [ABSTRACT FROM AUTHOR]

We examine population trends in light of male harvest data considering the long-time series of population data on northern fur seals at Tyuleniy Island. To answer the question has the way males were harvested influenced the population trajectory, we analyzed the visual harem size and birth rate dynamics of the population, as well as the strategy and intensity of the harvest. We analyzed the dynamics of the sex ratio in the early (1958–1988) period to estimate parameters in the late period (1989–2013) based on the observed number of bulls and pups, while utilizing the distribution of reproductive rates obtained from pelagic sealing. Using a matrix population model for the observed part of the population (i.e., the male population), we analyzed the population growth rate associated with changes in both birth and survival rates considering the stochastic effects. Observations allow us to reject the hypothesis of nonselective harvest. Among the variety of natural and anthropogenic factors that could contribute to the decrease in the birth rate in the population, the effect of selective harvesting seems to be the most realistic. [ABSTRACT FROM AUTHOR]

Cacti are threatened mainly by loss of habitat and illegal commerce. Because of this, it is essential to know their demographic characteristics. We systematically reviewed the publications with matrix population models (MPM) and integral projection models (IPM) in indexed journals, databases like the COMPADRE Plant Matrix Database and grey literature. In each publication, we recorded the literature characteristics, the population attributes, and the methods and metrics applied to describe them. We reviewed studies published until April 2022. We found 83 publications applied demographic modeling, 43 of which were of grey literature. Most studies were conducted in North America and on the tribe Cacteae, with a scarce representation of South American cactus. Compared to a previous review from 20 years ago, our study recorded a 488% increase in the number of publications and a 33.3% increase in the COMPADRE demographic database. We found demographic data for 65 taxa and very few studies covered a medium-to long-term period. MPMs were the most used until the 2009 when IPMs began to gain popularity. Population growth rates were commonly close to the unit ( λ ≈ 1), but we identified a wide range of λ values. Species position in the demographic triangle showed that the populations in the tribes Echinocereae, Cereeae and Cylindropuntieae were located towards the end of the survival axis, while those in the tribes Cacteae, and Opuntieae had a more variable location. Applications of demographic models have focused on the analysis of life history traits (growth and turnover) and employing numerical simulations to simulate the consequences of variations in vital rates on λ . Interactions with the climate and the nurse-protected system are analyzed frequently. Nonetheless, a limited number of research explores the socioeconomic and political components of management and conservation. Finally, even though Cactaceae is the plant group with the most extensive demographic research, models are available for only 3.5% of the species. • In the last two decades, the number of published works on the demography of cactus increased by nearly 30%. • Most of the published data about cactus demography come from North America, with a small contribution from South America. • Matrix models continue to be the most used in this field. • The growth rates and life histories of cacti vary widely among taxa. [ABSTRACT FROM AUTHOR]

Pathogens can cause host extinction, affect population dynamics and influence natural selection. Host susceptibility to pathogens can vary by species, demographics and genetics which affect epizootic and population dynamics, ultimately determining population trends and evolution.Chronic wasting disease (CWD), a fatal neuro‐degenerative prion disease of cervids, has varying host susceptibility conferred by polymorphisms of the prion protein gene (PRNP) at codon 96 for white‐tailed deer Odocoileus virginianus.Deer with the homozygous Glycine allele (96GG) are most susceptible and a single Serine allele (96GS/96SS) reduces the risk of infection and mortality.We developed epizootiological models that demonstrate CWD infection and disease‐associated mortality were higher for the more susceptible (96GG) genotype; and, infection was higher for males than females. We used population models to evaluate future shifts in genotype frequencies under alternative harvest and infection rate scenarios.Genetic shifts towards less susceptible genotypes were predicted as CWD prevalence increased during the course of an outbreak. This further increased CWD prevalence, and likely environmental contamination from prion shedding, due to longer incubation periods. Alternative harvest management strategies directly influenced CWD prevalence and spread, the rate of genetic selection and deer population growth.Synthesis and applications. We show that chronic wasting disease (CWD) transmission varied by sex, age class and PRNP genotype, and that CWD disease‐associated mortality varied by genotype. Together, these forces lead to CWD‐mediated genetic selection for a white‐tailed deer population. We predict that genetic selection pressure increases when hunter harvest pressure is lowered, and conversely, increasing hunter harvest can reduce genetic selection rates of antlered deer. Our results support the control of CWD prevalence by aggressive harvest of adult males, because they have the highest infection rates. Our results have strong implications for evolution, disease ecology, geographical spread, disease mitigation and cervid population management. [ABSTRACT FROM AUTHOR]

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Alpine plants are likely to be particularly vulnerable to climate change because of their restricted distributions and sensitivity to rapid environmental shifts occurring in high-elevation ecosystems. The well-studied Haleakalā silversword (‘āhinahina, Argyroxiphium sandwicense subsp. macrocephalum) already exhibits substantial climate-associated population decline, and offers the opportunity to understand the ecological and demographic mechanisms that underlie ongoing and predicted range shifts. We use nearly four decades of demographic monitoring for this threatened Hawaiian species, in combination with other biological, ecological and climate data to explore demographic responses across its entire range. We construct and independently validate population models for two elevation zones representing the species’ lower trailing and higher stable regions. Differences in population growth rate (lambda) between trailing and stable regions were influenced most strongly by lower survival of juvenile and small adult size classes, as well as by lower recruitment and lower survival of seedlings and large adults in the trailing region. Furthermore, seed production appears to have decreased from the 1980’s to present in the trailing region, and is now significantly less than in the stable region. Lambda and several underlying vital rates were significantly associated with wetter dry season conditions in the lower trailing region, indicating water limitation. In the higher elevation stable region, in contrast, lambda and vital rates were associated with warmer air temperatures, indicating cold limitation. These contrasting demographic patterns and climate dependencies lead to a high probability of extinction over the next century in the lower region, where most plants occur, but zero probability of the same in the higher region, according to stochastic population projections. Drier future scenarios further increase the probability of extinction at low elevations. The combined results illustrate the complexity in the demographic response and future viability that can occur across the range of a single species.

The social environment in which individuals live affects their fitness and in turn population dynamics as a whole. Birds with facultative cooperative breeding can live in social groups with dominants, subordinate helpers that assist with the breeding of others, and subordinate non‐helpers. Helping behaviour benefits dominants through increased reproductive rates and reduced extrinsic mortality, such that cooperative breeding might have evolved in response to unpredictable, harsh conditions affecting reproduction and/or survival of the dominants. Additionally, there may be different costs and benefits to both helpers and non‐helpers, depending on the time‐scale. For example, early‐life costs might be compensated by later‐life benefits. These differential effects are rarely analysed in the same study.We examined whether helping behaviour affects population persistence in a stochastic environment and whether there are direct fitness consequences of different life‐history tactics adopted by helpers and non‐helpers.We parameterised a matrix population model describing the population dynamics of female Seychelles warblers Acrocephalus sechellensis, birds that display facultative cooperative breeding. The stochastic density‐dependent model is defined by a (st)age structure that includes life‐history differences between helpers and non‐helpers and thus can estimate the demographic mechanisms of direct benefits of helping behaviour.We found that population dynamics are strongly influenced by stochastic variation in the reproductive rates of the dominants, that helping behaviour promotes population persistence and that there are only early‐life differences in the direct fitness of helpers and non‐helpers.Through a matrix population model, we captured multiple demographic rates simultaneously and analysed their relative importance in determining population dynamics of these cooperative breeders. Disentangling early‐life versus lifetime effects of individual tactics sheds new light on the costs and benefits of helping behaviour. For example, the finding that helpers and non‐helpers have similar lifetime reproductive outputs and that differences in reproductive values between the two life‐history tactics arise only in early life suggests that overall, helpers and non‐helpers have a similar balance of costs and benefits when analysing direct benefits. We recommend analysing the consequence of different life‐history tactics, during both early life and over the lifetime, as analyses of these different time frames may produce conflicting results. [ABSTRACT FROM AUTHOR]

Many wild populations are suffering from the loss of genetic diversity caused by habitat fragmentation, while the degree of diversity loss differs among species and populations based on their life history characteristics. Trillium camschatcense, an understory perennial plant, has undergone intensive habitat fragmentation in the Tokachi region, Hokkaido, Japan. Although demographic deteriorations, such as reduced seed production, were already reported, genetic consequences of fragmentation have not been studied with reference to its life history. Here, we examined how life history events (e.g., growth and reproduction) and the stochasticity therein influence genetic diversity in two (each large and small) fragmented T. camschatcense populations. Genetic diversity was evaluated using genome‐wide 2,008 single nucleotide polymorphisms (SNPs). In the small population, genetic diversity of newly germinated seedlings was significantly lower than that of matured life history stages, and effective number of breeders (Nb) was smaller than that of the large population. Simulations using a matrix population model showed that the diversity loss at seedlings is caused by genetic drift during reproduction, which was intensified by smaller Nb. Besides, simulations using randomly perturbed transition matrices suggested that stasis at juvenile stages, which is a common characteristics of T. camschatcense, maintains genetic diversity by buffering stochastic decrease, possibly contributing to population viability. While previous studies showed the importance to facilitate reproduction and recruitment for demographic recovery, this study highlighted the crucial roles of juvenile survival in terms of genetic diversity for the conservation of fragmented T. camschatcense populations in the Tokachi region. [ABSTRACT FROM AUTHOR]

Assessing the effects of climate and interspecific relationships on communities is challenging because of the complex interplay between species population dynamics, their interactions, and the need to integrate information across several biological levels (individuals, populations, communities). Usually used to quantify single‐species demography, integrated population models (IPMs) have recently been extended to communities. These models allow fitting multispecies matrix models to data from multiple sources while simultaneously accounting for uncertainty in each data source. We used multispecies IPMs accommodating climatic variables to quantify the relative contribution of climate vs. interspecific interactions on demographic parameters, such as survival and breeding success, in the dynamics of a predator–prey system. We considered a stage‐structured predator–prey system combining 22 yr of capture–recapture data and population counts of two seabirds, the Brown Skua (Catharacta lönnbergi) and its main prey the Blue Petrel (Halobaena caerulea), both breeding on the Kerguelen Islands in the Southern Ocean. Our results showed that climate and predator–prey interactions drive the demography of skuas and petrels in different ways. The breeding success of skuas appeared to be largely driven by the number of petrels and to a lesser extent by intraspecific density dependence. In contrast, there was no evidence of predation effects on the demographic parameters of petrels, which were affected by oceanographic factors. We conclude that bottom‐up mechanisms are the main drivers of this skua–petrel system. [ABSTRACT FROM AUTHOR]

Feral cats are some of the most destructive invasive predators worldwide, particularly in insular environments; hence, density‐reduction campaigns are often applied to alleviate the predation mortality they add to native fauna. Density‐reduction and eradication efforts are costly procedures with important outcomes for native fauna recovery, so they require adequate planning to be successful. These plans should include empirical density‐reduction models that can guide yearly culling quotas, and resource roll‐out for the duration of the culling period. This ensures densities are reduced over the long term and that resources are not wasted. We constructed a stochastic population model with cost estimates to test the relative effectiveness and cost‐efficiency of two main culling scenarios for a 10‐year eradication campaign of cats on Kangaroo Island, Australia: (a) constant proportional annual cull (one‐phase), and (b) high initial culling followed by a constant proportional maintenance cull (two‐phase). A one‐phase cull of at least 0.35 of the annual population size would reduce the final population to 0.1 of its original size, while a two‐phase cull with an initial cull of minimum 0.6 and minimum 0.5 maintenance cull would reduce the final population to 0.01 of its initial size within the 10‐year time frame. Cost estimates varied widely depending on the methods applied (shooting, trapping, aerial poison baits, Felixer™ poison‐delivery system), but using baiting, trapping and Felixers with additional shooting to meet culling quotas was the most cost‐effective combination (minimum cost: AU$19.56 million; range: AU$16.87 million–AU$20.69 million). Our model provides an adaptable and general assessment tool for cat reductions in Australia and potentially elsewhere, and provides relative culling costs for the Kangaroo Island campaign specifically. [ABSTRACT FROM AUTHOR]

Knowledge of age‐specific movement and vital rates is important for understanding metapopulation dynamics yet difficult to obtain without capturing/marking individual animals. The development of dynamic N‐mixture models allows for the inference of recruitment and apparent survival while accounting for imperfect detection in count data of unmarked populations. Recent studies have further developed dynamic N‐mixture models to account for age structures or movement among local populations; however, there has yet to be a dynamic N‐mixture model that simultaneously accounts for both age structure and movement despite the fact that natural populations are composed of individuals of different ages with different movement and vital rates. In this study, I developed a dynamic N‐mixture model that allows different movement and vital rates between age classes while accounting for imperfect detection in age‐structured count data. I then conducted a simulation study to evaluate the inferential performance of the model while considering different local abundances, number of sites, and detection probabilities. The simulation study showed that the model could provide unbiased estimates of adult‐related parameters under a high detection probability, but bias was found for young‐related parameters regardless of detection probability. The bias in young‐related parameters also tended to be lower when local abundance was lower, probably due to more frequent extinction‐recolonization events in these populations. Overall, the results indicated that cautions should be taken when using dynamic N‐mixture models alone. However, these models may be useful sub‐models under integrated modeling frameworks, and thus improve our understanding of metapopulation dynamics. [ABSTRACT FROM AUTHOR]

Understanding the demographic responses of wild animal populations to different factors is fundamental to make reliable prediction of population dynamics. Both bottom–up processes and top–down regulation operate in terrestrial and marine ecosystems, but their relative contribution remains insufficiently known. In addition, direct weather effects on demographic rates have been overlooked in marine ecosystems and inferences on the demographic effects of environmental drivers were overwhelmingly made from single study sites. Here, we evaluate the relative effects of bottom–up, top–down and weather processes on four vital rates and on population growth rates of a long‐lived seabird, the snow petrel Pagodroma nivea, within three different breeding colonies. We used multistate capture–recapture modelling and perturbation analyses from a matrix population model based on a 36‐year‐long (1981–2017) individual monitoring dataset to quantify the different drivers (predation, climatic and weather covariates) of probabilities of survival, breeding, hatching and fledging according to colony, sex and breeding status of individuals. Results show that bottom–up forces and local weather affected breeding parameters, and that survival was driven by top–down regulation pressure and bottom–up processes. Breeding parameters differed between colonies and survival was sex‐specific. Sensitivity analysis revealed that population regulation was mainly driven by bottom–up processes and that top–down processes played a minor role. However, there were major differences between colonies about the importance of how local weather processes affected population growth rate. Our study brings new insights into the drivers of demographic processes in a marine meso‐predator, and how these drivers vary according to colonies and individual characteristics. We emphasize the importance of considering multiple study sites to make robust inferences on the effects of environmental drivers on wildlife demography. More generally, robust conclusions about the importance of environmental drivers on demography rely on considering multiple causal effects at multiple sites, while accounting for individual characteristics. [ABSTRACT FROM AUTHOR]

Life history strategies are fundamental to the ecology and evolution of organisms and are important for understanding extinction risk and responses to global change. Using global datasets and a multiple response modelling framework we show that trait‐climate interactions are associated with life history strategies for a diverse range of plant species at the global scale. Our modelling framework informs our understanding of trade‐offs and positive correlations between elements of life history after accounting for environmental context and evolutionary and trait‐based constraints. Interactions between plant traits and climatic context were needed to explain variation in age at maturity, distribution of mortality across the lifespan and generation times of species. Mean age at maturity and the distribution of mortality across plants' lifespan were under evolutionary constraints. These findings provide empirical support for the theoretical expectation that climatic context is key to understanding trait to life history relationships globally. [ABSTRACT FROM AUTHOR]

Conservation planning for rare and threatened species is often made more difficult by a lack of research and monitoring data. In such cases, managers may rely on qualitative assessments of species risk that lack explicit acknowledgement of uncertainty. Snakes are a group of conservation concern that are also notoriously difficult to monitor. Here, we demonstrate a quantitative population projection for a data‐deficient species, the Puerto Rican boa (Chilabothrus inornatus) using expert knowledge and published information about species life history and threats to persistence. Using this model, we simulated population dynamics over 30 years under four scenarios of future urbanization and found that there was an increased probability of population decline as urbanization rates increased. We conduct a sensitivity analysis to evaluate the sensitivity of outcomes to model inputs, a practice that may also be useful in recovery planning. The sensitivity analyses also provide insight into how the future trajectories would change if the elicited demographic rates are incorrect. Even when data are sparse, quantitative methods can often be used to produce rigorous and reproducible estimates of future status with quantifiable uncertainty. [ABSTRACT FROM AUTHOR]

Context: The population of saltwater crocodiles, Crocodylus porosus , in the Northern Territory, Australia, has been recovering from a period of intensive, unregulated harvest (1945–1971) since protection in 1971. Consequently, the management goal is shifting from restoring a seriously depleted population to managing an abundant population through controlled harvests for both commercial purposes and public safety. Aims: We conducted this study to (1) examine whether the controlled harvest of eggs and adults since protection has had an adverse effect on population size and structure, and (2) explore the effect of future harvest scenarios on population size and structure by adjusting harvest levels of both eggs and adults. Methods: On the basis of 40 years of population monitoring data and knowledge of population attributes from previous research, we developed density-dependent, structured matrix population models to explore our aims. Key results: The models supported that the depleted population recovered rapidly under protection and that the harvest rates since protection were benign. The model estimated the 2017 harvested population, 46 years after protection, to be ~102 000 non-hatchlings (>0.6 m crocodiles), of which 42.2% are large (>2.1 m total length) individuals. This is similar to the estimated population before the period of intensive, unregulated harvest. Like other crocodilians, the harvest simulations showed that the viability of the population is highly sensitive to adult survival rates. The estimated population should be able to sustain an annual harvest of up to 135 500 eggs if the harvest of large crocodiles remains small (<500 per year). Conclusions: Although egg harvest has little impact on population size and structure, population size is sensitive to adult harvest. Implications: Crocodile populations are highly sensitive to adult survival, which needs to be taken into account when considering future harvest scenarios. Management of saltwater crocodiles in the Northern Territory is shifting from restoring depleted population to managing an abundant population through controlled harvests for commercial purposes and public safety. Simulations suggested that harvesting since protection has had no adverse impact and survival of adults has a much larger impact than egg harvest, which should be accounted for in future harvest scenarios. Photograph by Yusuke Fukuda. [ABSTRACT FROM AUTHOR]

Accurately predicting species ranges is a primary goal of ecology. Demographic distribution models (DDMs), which correlate underlying vital rates (e.g. survival and reproduction) with environmental conditions, can potentially predict species ranges through time and space. However, tests of DDM accuracy across wide ranges of species' life histories are surprisingly lacking. Using simulations of 1.5 million hypothetical species' range dynamics, we evaluated when DDMs accurately predicted future ranges, to provide clear guidelines for the use of this emerging approach. We limited our study to deterministic demographic models ignoring density dependence, since these models are the most commonly used in the literature. We found that density‐independent DDMs overpredicted extinction if populations were near carrying capacity in the locations where demographic data were available. However, DDMs accurately predicted species ranges if demographic data were limited to sites with mean initial abundance less than one half of carrying capacity. Additionally, the DDMs required demographic data from at least 25 sites, over a short time‐interval (< 10 time‐steps), as populations initially below carrying capacity can saturate in long‐term studies. For species with demographic data from many low density sites, DDMs predicted occurrence more accurately than correlative species distribution models (SDMs) in locations where the species eventually persisted, but not where the species went extinct. These results were insensitive to differences in simulated dispersal, levels of environmental stochasticity, the effects of the environmental variables and the functional forms of density dependence. Our findings suggest that deterministic, density‐independent DDMs are appropriate for applications where locating all possible sites the species might occur in is prioritized over reducing false presence predictions in absent sites. This makes DDMs a promising tool for mapping invasion risk. However, demographic data are often collected at sites where a species is abundant. Density‐independent DDMs are inappropriate in this case. [ABSTRACT FROM AUTHOR]