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In order to assess the potential impact from oil spills and decide the optimal response actions, prediction of population level effects of key resources is crucial. These assessments are usually based on acute toxicity data combined with precautionary assumptions because chronic data are often lacking. To better understand the consequences of applying precautionary approaches, two approaches for assessing population level effects on the Arctic keystone species polar cod (Boreogadus saida) were compared: a precautionary approach, where all exposed individuals die when exposed above a defined threshold concentration, and a refined (full-dose-response) approach. A matrix model was used to assess the population recovery duration of scenarios with various but constant exposure concentrations, durations and temperatures. The difference between the two approaches was largest for exposures with relatively low concentrations and short durations. Here, the recovery duration for the refined approach was less than eight times that found for the precautionary approach. Quantifying these differences helps to understand the consequences of precautionary assumptions applied to environmental risk assessment used in oil spill response decision making and it can feed into the discussion about the need for more chronic toxicity testing. An elasticity analysis of our model identified embryo and larval survival as crucial processes in the life cycle of polar cod and the impact assessment of oil spills on its population. [ABSTRACT FROM AUTHOR]

Migration can allow individuals to escape parasite infection, which can lead to a lower infection probability (prevalence) in a population and/or fewer parasites per individual (intensity). Because individuals with more parasites often have lower survival and/or fecundity, infection intensity shapes the life‐history trade‐offs determining when migration is favored as a strategy to escape infection. Yet, most theory relies on susceptible‐infected (SI) modeling frameworks, defining individuals as either healthy or infected, ignoring details of infection intensity. Here, we develop a novel modeling approach that captures infection intensity as a spectrum, and ask under what conditions migration evolves as function of how infection intensity changes over time. We show that relative timescales of migration and infection accumulation determine when migration is favored. We also find that population‐level heterogeneity in infection intensity can lead to partial migration, where less‐infected individuals migrate while more infected individuals remain resident. Our model is one of the first to consider how infection intensity can lead to migration. Our results frame migratory escape in light of infection intensity rather than prevalence, thus demonstrating that decreased infection intensity should be considered a benefit of migration, alongside other typical drivers of migration. [ABSTRACT FROM AUTHOR]

Aquatic and terrestrial environments display stark differences in key environmental factors and phylogenetic composition but their consequences for the evolution of species' life‐history strategies remain poorly understood.Here, we examine whether and how life‐history strategies vary between terrestrial and aquatic species. We use demographic information for 685 terrestrial and 122 aquatic animal and plant species to estimate key life‐history traits. We then use phylogenetically corrected least squares regression to explore potential differences in trade‐offs between life‐history traits between both environments. We contrast life‐history strategies of aquatic versus terrestrial species in a principal component analysis while accounting for body dimensions and phylogenetic relationships.Our results show that the same trade‐offs structure terrestrial and aquatic life histories, resulting in two dominant axes of variation that describe species' pace of life and reproductive strategies. Terrestrial plants display a large diversity of strategies, including the longest‐lived species in this study. Aquatic animals exhibit higher reproductive frequency than terrestrial animals. When correcting for body size, mobile and sessile terrestrial organisms show slower paces of life than aquatic ones.Aquatic and terrestrial species are ruled by the same life‐history trade‐offs, but have evolved different strategies, likely due to distinct environmental selective pressures. Such contrasting life‐history strategies have important consequences for the conservation and management of aquatic and terrestrial species. A free Plain Language Summary can be found within the Supporting Information of this article. [ABSTRACT FROM AUTHOR]

Our study is devoted to a subject popular in the field of matrix population models, namely, estimating the stochastic growth rate, λS, a quantitative measure of long-term population viability, for a discrete-stage-structured population monitored during many years. “Reproductive uncertainty” refers to a feature inherent in the data and life cycle graph (LCG) when the LCG has more than one reproductive stage, but when the progeny cannot be associated to a parent stage in a unique way. Reproductive uncertainty complicates the procedure of λS estimation following the defining of λS from the limit of a sequence consisting of population projection matrices (PPMs) chosen randomly from a given set of annual PPMs. To construct a Markov chain that governs the choice of PPMs for a local population of Eritrichium caucasicum, an short-lived perennial alpine plant species, we have found a local weather index that is correlated with the variations in the annual PPMs, and we considered its long time series as a realization of the Markov chain that was to be constructed. Reproductive uncertainty has required a proper modification of how to restore the transition matrix from a long realization of the chain, and the restored matrix has been governing random choice in several series of Monte Carlo simulations of long-enough sequences. The resulting ranges of λS estimates turn out to be more narrow than those obtained by the popular i.i.d. methods of random choice (independent and identically distributed matrices); hence, we receive a more accurate and reliable forecast of population viability.

Abstract Fire is a major disturbance driving the dynamics of the world's savannas. Almost all fires are set by humans who are increasingly altering fire timing and frequency on every continent. The world's largest protected areas of savannas are found in monsoonal northern Australia. These include relatively intact, tall, open forests where traditional indigenous fire regimes have been largely replaced in the past half century by contemporary patterns with trees experiencing fire as often as three out of five years. Eucalypt canopy trees form the basic structure of these savannas and changes to the canopy due to fire regimes cascade to affect other plants and animals. In this study, we used data from nearly three decades of field studies on the effects of fire on individual trees to define eight life‐history stages and to calculate transition rates among stages. We developed a stage‐based matrix population model that explicitly considers how fire season and understory influence growth, survival, and recruitment for each life‐history stage. Long‐term population growth rates and transient population dynamics were calculated under five different fire regimes, each in two understory types, using both deterministic and stochastic simulations of seasonal timing of fires. We found that fire was necessary for long‐term persistence of eucalypt canopy tree populations but, under annual fires, most populations did not survive. Population persistence was highly dependent on fire regime (fire season and frequency) and understory type. A stochastic model tended to yield higher population growth rates than the deterministic model with regular, periodic fires, even under the same long‐term frequency of fires. Transient population dynamics over 100 yr also depended on fire regime and understory, with implications for savanna physiognomy and management. Model predictions were tested in an independent data set from a 21‐yr longitudinal field study in Kakadu National Park. This study is a novel and integrative contribution to our understanding of fire in savanna biomes regarding the potential for long‐term persistence and transient dynamics of savanna canopy tree populations. The model is relatively simple, generalizable, and adaptable for further investigations of the population dynamics of savanna trees under fire.

The notion of a potential-growth indicator came to being in the field of matrix population models long ago, almost simultaneously with the pioneering Leslie model for age-structured population dynamics, although the term has been given and the theory developed only in recent years. The indicator represents an explicit function, R(L), of matrix L elements and indicates the position of the spectral radius of L relative to 1 on the real axis, thus signifying the population growth, or decline, or stabilization. Some indicators turned out to be useful in theoretical layouts and practical applications prior to calculating the spectral radius itself. The most senior (1994) and popular indicator, R0(L), is known as the net reproductive rate, and we consider two others, R1(L) and RRT(A), developed later on. All the three are different in terms of their simplicity and the level of generality, and we illustrate them with a case study of Calamagrostis epigeios, a long-rhizome perennial weed actively colonizing open spaces in the temperate zone. While the R0(L) and R1(L) fail, respectively, because of complexity and insufficient generality, the RRT(L) does succeed, justifying the merit of indication.

Until recently, senescence was assumed to be a universal phenomenon. Evolutionary theories of senescence predict that no organism may escape the physiological decline that results in an increase in mortality risk and/or decline in fertility with age. However, evidence both in animals and plants has emerged in the last decade defying such predictions. Researchers are currently seeking mechanistic explanations for the observed variation in ageing trajectories.We argue that the historical view on the inevitability of senescence is due, in part, to the development of its classical theories, which targeted primarily unitary organisms. In unitary species, the integration of resources and functions is high, and adult size is determined. In contrast, the architecture of modular organisms is indeterminate and built upon repeated modules. The isolation of mortality risk in species like hydra (Hydra spp.) or creosote brush Larrea tridentata may explain their null or even negative senescence.Caleb Finch hypothesized three decades ago that species with the ability to compartmentalize risk may escape senescence. Here, we first review the evidence on organisms that slow down or even avoid senescence in the context of their architecture, along a continuum of unitarity‐modularity. Then, we use open‐access databases to comparatively analyse various moments of senescence and link longevity to the degree of anatomical modularity. Our analysis compares the pace of senescence across 138 plants and 151 animals, and the shape of senescence across a subset of these. Our comparative analysis reveals that plant species that are more modular do indeed tend to escape from senescence more often than those that are unitary. The role of modularity in animal senescence is less clear.In light of novel support for Finch's hypothesis across a large diversity of plant species, and with less conclusive findings in animals, we identify new research directions. We highlight the opportunities related to age‐dependent mortality factors. Other areas for further research include the role of modularity in relation to endocrine actions, and the costs of modular anatomies. [ABSTRACT FROM AUTHOR]

Matrix population models are widely used to assess population status and to inform management decisions. Despite existing theories for building such models, model construction is often partially based on expert opinion. So far, model structure has received relatively little attention, although it may affect estimates of population dynamics. Here, we assessed the consequences of two published matrix structures (a 4 × 4 matrix based on expert opinion and a 10 × 10 matrix based on statistical modeling) for estimates of vital rates and stochastic population dynamics of the long‐lived herb Astragalus scaphoides. We explored the ways in which choice of model structure alters the accuracy (i.e., mean) and precision (i.e., variance) of predicted population dynamics. We found that model structure had a negligible effect on the accuracy and precision of vital rates and stochastic stage distribution. However, the 10 × 10 matrix produced lower estimates of stochastic population growth rates than the 4 × 4 matrix, and more accurately predicted the observed trends in population abundance for three out of four study populations. Moreover, estimates of realized variation in population growth rate due to fluctuations in population stage structure over time were occasionally sensitive to matrix structure, suggesting differential roles of transient dynamics. Our study indicates that statistical modeling for choosing categories in matrix models might be preferable over expert opinion to accurately predict population trends and can provide a more objective way for model construction when the biological knowledge of the species is limited. [ABSTRACT FROM AUTHOR]

In matrix population modeling the multi-year monitoring of a population structure results in a set of annual population projection matrices (PPMs), which gives rise to the stochastic growth rate λS, a quantitative measure of long-term population viability. This measure is usually found in the paradigm of population growth in a variable environment. The environment is represented by the set of PPMs, and λS ensues from a long sequence of PPMs chosen at random from the given set. because the known rules of random choice, such as the iid (independent and identically distributed) matrices, are generally artificial, the challenge is to find a more realistic rule. We achieve this with the a following a Markov chain that models, in a certain sense, the real variations in the environment. We develop a novel method to construct the ruling Markov chain from long-term weather data and to simulate, in a Monte Carlo mode, the long sequences of PPMs resulting in the estimates of λS. The stochastic nature of sequences causes the estimates to vary within some range, and we compare the range obtained by the “realistic choice” from 10 PPMs for a local population of a Red-Book species to those using the iid choice. As noted in the title of this paper, this realistic choice contracts the range of λS estimates, thus improving the estimation and confirming the Red-Book status of the species.

Abstract: Seed dispersal is an essential, yet often overlooked process in plant ecology and evolution, affecting adaptation capacity, population persistence and invasiveness. A species’ ability to disperse is expected to covary with other life‐history traits to form dispersal syndromes. Dispersal might be linked to the rate of life history, fecundity or generation time, depending on the relative selection pressures of bet‐hedging, kin competition or maintaining gene flow. However, the linkage between dispersal and plant life‐history strategies remains unknown because it is difficult to observe, quantify and manipulate the influence of dispersal over large spatiotemporal scales. We integrate datasets describing plant vital rates, dispersal and functional traits to incorporate dispersal explicitly into the rich spectra of plant life‐history strategies. For 141 plant species, we estimated dispersal ability by predicting maximum dispersal distances using allometric relationships based on growth form, dispersal mode, terminal velocity and seed mass. We derived life‐history traits from matrix population models parameterized with field data from the COMPADRE Plant Matrix Database. We analysed the covariation in dispersal ability and life‐history traits using multivariate techniques. We found that three main axes of variation described plant dispersal syndromes: the fast‐slow life‐history continuum, the dispersal strategy axis and the reproductive strategy axis. On the dispersal strategy axis, species’ dispersal abilities were positively correlated with aspects of fast life histories. Species with a high net reproductive rate, a long window of reproduction, low likelihood of escaping senescence and low shrinkage tendencies disperse their seeds further. The overall phylogenetic signal in our multidimensional analyses was low (Pagel's λ < 0.24), implying a high degree of taxonomic generality in our findings. Synthesis. Dispersal has been largely neglected in comparative demographic studies, despite its pivotal importance for populations. Our explicit incorporation of dispersal in a comparative life‐history framework provides key insights to bridge the gap between dispersal ecology and life‐history traits. Species with fast life‐history strategies disperse their seeds further than slow‐living plants, suggesting that longer dispersal distances may allow these species to take advantage of habitats varying unpredictably in space and time as a bet‐hedging strategy. [ABSTRACT FROM AUTHOR]

Abstract: Temporal autocorrelation in demographic processes is an important aspect of population dynamics, but a comprehensive examination of its effects on different life‐history strategies is lacking. We use matrix population models from 454 plant and animal populations to simulate stochastic population growth rates (log λs) under different temporal autocorrelations in demographic rates, using simulated and observed covariation among rates. We then test for differences in sensitivities, or changes of log λs to changes in autocorrelation among two major axes of life‐history strategies, obtained from phylogenetically informed principal component analysis: the fast‐slow and reproductive‐strategy continua. Fast life histories exhibit highest sensitivities to simulated autocorrelation in demographic rates across reproductive strategies. Slow life histories are less sensitive to temporal autocorrelation, but their sensitivities increase among highly iteroparous species. We provide cross‐taxonomic evidence that changes in the autocorrelation of environmental variation may affect a wide range of species, depending on complex interactions of life‐history strategies. [ABSTRACT FROM AUTHOR]

In the Azores, as in many other places around the world, rodents are responsible for economic losses, environmental problems, and several health problems such as fatal cases of Leptospirosis. We apply a population model of rodents to understand what are the relevant biological and economical parameters that dictate the best control strategy. The model is constructed in discrete time and it includes the effect of poison mortality and rodent migration. The optimal control solutions are obtained minimising the total adult rodent population together with the cost of control, for different migration rates and different costs of control. We find that for very small or no migration the optimal solution exhibits a phase transition as the cost of control increases. It changes from applying a large amount of poison that drives rodents close to extinction, to no poison applied. This phase transition is robust to changes in the parameters and details of the model. Increasing the rate of migration, the phase transition disappears and the total amount of poison in the optimal solution decreases towards zero as its cost increases. In the presence of migration and for very low cost, the optimal is obtained concentrating the control during the period of large population increase but for more significant costs the optimal is obtained concentrating the control in the months preceding this increase. Also, as the migration of rodents into the field under control increases, the optimal control is concentrated in a few months around the start of the high reproduction season. We conclude that the appropriate optimal control policy is strongly dependent on the balance between the cost of control and the cost resulting from rodent damage, as well as the level of migration into the field under control. • A rodent population model under variable poison control and migration is presented. • Without significant migration there is a phase transition in the optimal control. • Below the critical cost it is optimal to drive rodents close to extinction. • For costs above this critical cost, it is optimal to apply no control. • Reproduction, migration, and control cost dictate how to best apply control. [ABSTRACT FROM AUTHOR]

When prevention of invasive species' introductions fails, society faces the challenge to manage invasive species in an effective and efficient way. The success of this depends on biological aspects and on cooperation between decision makers and scientists. Using the case of the round goby Neogobius melanostomus, one of Europe's 'worst invasive species', we propose an approach guiding scientists to co-produce effective and efficient population control measures in collaboration with decision makers., We surveyed the effectiveness, urgency and simplicity perceived by decision makers as well as the support of two population control options: removal of eggs and/or adults. Using a field study and a dynamical population model, we investigated the effectiveness and efficiency for both options in different population contexts., Decision makers initially seemed to lack a clear preference for either control option. After being presented with preliminary field and modelling results, decision makers mostly approved measures being developed to implement the two control options., Starting population control early after detecting the species requires in total fewer years for eradication than controlling an established population: to reach an eradication success rate of 95%, 13 years for early start vs. 18 years for late start are needed when removing eggs and adults; when removing adults only, 20 vs. 29 years are needed. Removing eggs and adults combined results in a yearly effort of 5.01 h/m2, while removing adults only results in a yearly effort of 1.76 h/m2. Thus, removing adults only proves to be the most efficient option to eradicate the population. Nonetheless, considerable effort is needed: when removing less than 57% of the adult population, eradication is not feasible, even assuming low survival and fecundity rates for the population. Furthermore, inflow of new propagules renders eradication efforts ineffective., Synthesis and applications. Scientists who aim to support decision makers in finding an optimal control strategy for invasive species need to be able to provide scientific knowledge on effectiveness and efficiency of different options. For round goby and most non-native species, eradication is only feasible if started early in recently arrived populations and if inflow of new propagules can be prevented. [ABSTRACT FROM AUTHOR]

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In matrix population models, there cannot be any ‘reproductive uncertainty’ when the life cycle graph contains only one reproductive stage. Otherwise, it is logical to expect that aggregating all the reproductive stages into a single one would exclude the very basis of uncertainty. However, can the aggregation change principally the model characteristics such as the dominant eigenvalue λ 1 of the projection matrix, thus signifying the aggregation failure? I demonstrate that it can with the data mined in a case study on the dynamics of a local stage-structured population of Eritrichium caucasicum , a short-lived perennial plant species inhabiting an alpine lichen heath. Frobenius Theorem for nonnegative matrices specifies the upper and lower bounds for λ 1 via the row (or column) sums of matrix elements, and the lower bound, when it exceeds the maximal possible λ 1 of the original, disaggregated matrix, does explain why the aggregation may fail to eliminate reproductive uncertainty. [ABSTRACT FROM AUTHOR]

In most matrix population projection models, individuals are characterized according to, usually, one or two traits such as age, stage, size or location. A broad theory of multitrait population projection matrices (MPPMs) incorporating larger number of traits was long held back by time and space computational complexity issues. As a consequence, no study has yet focused on the influence of the structure of traits describing a life-cycle on population dynamics and life-history evolution. We present here a novel vector-based MPPM building methodology that allows to computationally-efficiently model populations characterized by numerous traits with large distributions, and extend sensitivity analyses for these models. We then present a new method, the trait level analysis consisting in folding an MPPM on any of its traits to create a matrix with alternative trait structure (the number of traits and their characteristics) but similar asymptotic properties. Adding or removing one or several traits to/from the MPPM and analyzing the resulting changes in spectral properties, allows investigating the influence of the trait structure on the evolution of traits. We illustrate this by modeling a 3-trait (age, parity and fecundity) population designed to investigate the implications of parity–fertilitytrade-offs in a context of fecundity heterogeneity in humans. The trait level analysis , comparing models of the same population differing in trait structures, demonstrates that fertility selection gradients differ between cases with or without parity–fertility trade-offs. Moreover it shows that age-specific fertility has seemingly very different evolutionary significance depending on whether heterogeneity is accounted for. This is because trade-offs can vary strongly in strength and even direction depending on the trait structure used to model the population. [ABSTRACT FROM AUTHOR]

Climate changes include concurrent changes in environmental mean, variance and extremes, and it is challenging to understand their respective impact on wild populations, especially when contrasted age-dependent responses to climate occur. We assessed how changes in mean and standard deviation of sea surface temperature (SST), frequency and magnitude of warm SST extreme climatic events (ECE) influenced the stochastic population growth rate log(ls) and age structure of a black-browed albatross population. For changes in SST around historical levels observed since 1982, changes in standard deviation had a larger (threefold) and negative impact on log(ls) compared to changes in mean. By contrast, the mean had a positive impact on log(ls). The historical SST mean was lower than the optimal SST value for which log(ls) was maximized. Thus, a larger environmental mean increased the occurrence of SST close to this optimum that buffered the negative effect of ECE. This 'climate safety margin' (i.e. difference between optimal and historical climatic conditions) and the specific shape of the population growth rate response to climate for a species determine how ECE affect the population. For a wider range in SST, both the mean and standard deviation had negative impact on log(ls), with changes in the mean having a greater effect than the standard deviation. Furthermore, around SST historical levels increases in either mean or standard deviation of the SST distribution led to a younger population, with potentially important conservation implications for black-browed albatrosses. [ABSTRACT FROM AUTHOR]

Spatial variation in habitat quality and anthropogenic factors, as well as social structure, can lead to spatially structured populations of animals. Demographic approaches can be used to improve our understanding of the dynamics of spatially structured populations and help identify subpopulations critical for the long-term persistence of regional metapopulations. We provide a regional metapopulation analysis to inform conservation management for Masai giraffes ( Giraffa camelopardalis tippelskirchi) in five subpopulations defined by land management designations. We used data from an individual-based mark-recapture study to estimate subpopulation sizes, subpopulation growth rates, and movement probabilities among subpopulations. We assessed the source-sink structure of the study population by calculating source-sink statistics, and we created a female-based matrix metapopulation model composed of all subpopulations to examine how variation in demographic components of survival, reproduction, and movement affected metapopulation growth rate. Movement data indicated no subpopulation was completely isolated, but movement probabilities varied among subpopulations. Source-sink statistics and net flow of individuals indicated three subpopulations were sources, while two subpopulations were sinks. We found areas with higher wildlife protection efforts and fewer anthropogenic impacts were sources, and less-protected areas were identified as sinks. Our results highlight the importance of identifying source-sink dynamics among subpopulations for effective conservation planning and emphasize how protected areas can play an important role in sustaining metapopulations. [ABSTRACT FROM AUTHOR]

Contents1618I.1618II.1619III.1620IV.16231623References1624 Summary: Understanding the forces that shape the great amount of variation in plant longevity, reproductive output and growth rate is fundamental to effective predictions of viability, invasions and evolutionary pressures. Here, I extend the recently introduced ‘fast–slow continuum and reproductive strategy’ framework to quantify the variation in plant life history strategies world‐wide. I use high‐resolution demographic information from 625 plant species and show that this framework predicts not only key demographic properties, such as population growth rate and demographic resilience, but also has important connections to the leaf economics spectrum, biogeographical characteristics, evolutionary biology and conservation biology. This framework may allow plant biologists to unlock powerful global plant predictions from a handful of open‐access field measurements. Editorial by Lennon & Dolan, 213: 1561. [ABSTRACT FROM AUTHOR]

Many perennial plants experience prolonged dormancy, meaning they do not grow above-ground for one or several growing seasons. When plants disappear (fail to sprout) and have not been recorded to re-emerge, they either have died or are alive and dormant. In demographic studies of such species, researchers have been forced to make assumptions about death versus dormancy. Little is known about the consequences of these assumptions for predictions from the population models used in the studies., Here, we define survival of dormancy-prone plants in three distinct ways: Separate, Instant and Slow death. In the Separate death model, plants are assumed to die either in emergent or in dormant stages. Death can also be described as a process of disappearance followed by dying, either in the first year below-ground (Instant death) or with constant mortality rate in any given dormant year (Slow death). Using simulated data with known parameter values, we test whether survival and re-emergence rates are confounded in these life-history models., Using a general model and models for two orchid species ( Epipactis atrorubens and Isotria medeoloides), we test how different assumptions about dormancy (Instant and Slow death) affect predictions about population dynamics: population growth rate, generation time, relative reproductive values, life expectancies, and sensitivity and elasticity of population growth rate to stage transitions and vital rates., Our results confirm that survival and re-emergence rates of dormancy-prone plant species are difficult to estimate; parameters were separable only with the assumptions of Instant and Slow death. Both theoretical and empirical analyses show that the predictions of population growth rate and generation time do not depend on the assumptions made about the fate of the plants after their disappearance., Synthesis. Assumptions about dormancy affect some, but not all predictions, about plant population dynamics. In the studies of species with unobservable stages, assumptions about dormancy should be carefully defined and possible consequences of these assumptions for the predictions of the population model should be evaluated. Nonetheless, if we are only interested in overall population viability, ad hoc models of prolonged dormancy are sufficient as a first step. [ABSTRACT FROM AUTHOR]

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. [Display omitted] • Matrix population model was applied to naked carp to predict management effects. • Results identified the importance of juvenile survival and early-age reproduction. • Recovering the naked carp population is feasible through artificial reproduction. • Once the population is recovered, sustainable harvest is possible. [ABSTRACT FROM AUTHOR]

Atmosphere-Ocean General Circulation Models (AOGCMs) predict changes in the sea ice environment and in atmospheric precipitations over larger areas of Antarctica. These changes are expected to affect the population dynamics of seabirds and marine mammals, but the extent of this influence is not clear. We investigated the future population trajectories of the colony of Adélie penguins at Edmonson Point, in the Ross Sea, from 2010 to 2100. To do so, we incorporated the relationship between sea ice and demographic parameters of the studied colony into a matrix population model. Specifically, we used sea ice projections from AOGCMs and a proxy for snowfall precipitation. Simulations of population persistence under future climate change scenarios showed that a reduction in sea ice extent and an increase in precipitation events during the breeding season will drive the population to extinction. However, the population growth rate estimated by the model was lower than the population growth rate observed during the last decades, suggesting that recruits from other colonies maintain the observed population dynamics at Edmonson Point. This local ‘rescue’ effect is consistent with a metapopulation dynamic for Adélie penguins in the Ross Sea, in which neighboring colonies might exhibit contrasting population trends and different density-dependent effects. In the hypothesis that connectivity with larger source colonies or that local recruitment would decrease, the sink colony at Edmonson Point is predicted to disappear.

Plant population responses are key to understanding the effects of threats such as climate change and invasions. However, we lack demographic data for most species, and the data we have are often geographically aggregated. We determined to what extent existing data can be extrapolated to predict population performance across larger sets of species and spatial areas. We used 550 matrix models, across 210 species, sourced from the COMPADRE Plant Matrix Database, to model how climate, geographic proximity and phylogeny predicted population performance. Models including only geographic proximity and phylogeny explained 5-40% of the variation in four key metrics of population performance. However, there was poor extrapolation between species and extrapolation was limited to geographic scales smaller than those at which landscape scale threats typically occur. Thus, demographic information should only be extrapolated with caution. Capturing demography at scales relevant to landscape level threats will require more geographically extensive sampling. [ABSTRACT FROM AUTHOR]

Pathogens and insect pests have become increasingly important drivers of tree mortality in forested ecosystems. Unfortunately, understanding the relative contributions of multiple mortality agents to the population decline of trees is difficult, because it requires frequent measures of tree survival, growth, and recruitment, as well as the incidence of mortality agents. We present a population model of whitebark pine ( Pinus albicaulis ), a high-elevation tree undergoing rapid decline in western North America. The loss of whitebark pine is thought to be primarily due to an invasive pathogen (white pine blister rust; Cronartium ribicola ) and a native insect (mountain pine beetle; Dendroctonus ponderosae ). We utilized seven plots in Crater Lake National Park (Oregon, USA) where 1220 trees were surveyed for health and the presence of blister rust and beetle activity annually from 2003–2014, except 2008. We constructed size-based projection matrices for nine years and calculated the deterministic growth rate (λ) using an average matrix and the stochastic growth rate (λ s ) by simulation for whitebark pine in our study population. We then assessed the roles of blister rust and beetles by calculating λ and λ s using matrices in which we removed trees with blister rust and, separately, trees with beetles. We also conducted life-table response experiments (LTRE) to determine which demographic changes contributed most to differences in λ between ambient conditions and the two other scenarios. The model suggests that whitebark pine in our plots are currently declining 1.1% per year (λ = 0.9888, λ s = 0.9899). Removing blister rust from the models resulted in almost no increase in growth (λ = 0.9916, λ s = 0.9930), while removing beetles resulted in a larger increase in growth (λ = 1.0028, λ s = 1.0045). The LTRE demonstrated that reductions in stasis of the three largest size classes due to beetles contributed most to the smaller λ in the ambient condition. Our work demonstrates a method for assessing the relative effects of different mortality agents on declining tree populations, and it shows that the effects of insects and pathogens can be markedly different from one another. In our study, beetle activity significantly reduced tree population growth while a pathogen had minimal effect, thus management actions to stabilize our study population will likely need to include reducing beetle activity. [ABSTRACT FROM AUTHOR]

Changed fire regimes have led to declines of fire-regime-adapted species and loss of biodiversity globally. Fire affects population processes of growth, reproduction, and dispersal in different ways, but there is little guidance about the best fire regime(s) to maintain species population processes in fire-prone ecosystems. We use a process-based approach to determine the best range of fire intervals for keystone plant species in a highly modified Mediterranean ecosystem in southwestern Australia where current fire regimes vary. In highly fragmented areas, fires are few due to limited ignitions and active suppression of wildfire on private land, while in highly connected protected areas fires are frequent and extensive. Using matrix population models, we predict population growth of seven Banksia species under different environmental conditions and patch connectivity, and evaluate the sensitivity of species survival to different fire management strategies and burning intervals. We discover that contrasting, complementary patterns of species life-histories with time since fire result in no single best fire regime. All strategies result in the local patch extinction of at least one species. A small number of burning strategies secure complementary species sets depending on connectivity and post-fire growing conditions. A strategy of no fire always leads to fewer species persisting than prescribed fire or random wildfire, while too-frequent or too-rare burning regimes lead to the possible local extinction of all species. In low landscape connectivity, we find a smaller range of suitable fire intervals, and strategies of prescribed or random burning result in a lower number of species with positive growth rates after 100 years on average compared with burning high connectivity patches. Prescribed fire may reduce or increase extinction risk when applied in combination with wildfire depending on patch connectivity. Poor growing conditions result in a significantly reduced number of species exhibiting positive growth rates after 100 years of management. By exploring the consequences of managing fire, we are able to identify which species are likely to disappear under a given fire regime. Identifying the appropriate complementarity of fire intervals, and their species-specific as well as community-level consequences, is crucial to reduce local extinctions of species in fragmented fire-prone landscapes. [ABSTRACT FROM AUTHOR]

Clonality is a widespread life history trait in flowering plants that may be essential for population persistence, especially in environments where sexual reproduction is unpredictable. Frequent clonal reproduction, however, could hinder sexual reproduction by spatially aggregating ramets that compete with seedlings and reduce inter-genet pollination. Nevertheless, the role of clonality in relation to variable sexual reproduction in population dynamics is often overlooked. We combined population matrix models and pollination experiments to compare the demographic contributions of clonal and sexual reproduction in three Dicentra canadensis populations, one in a well-forested landscape and two in isolated forest remnants. We constructed stage-based transition matrices from 3 years of census data to evaluate annual population growth rates, λ. We used loop analysis to evaluate the relative contribution of different reproductive pathways to λ. Despite strong temporal and spatial variation in seed set, populations generally showed stable growth rates. Although we detected some pollen limitation of seed set, manipulative pollination treatments did not affect population growth rates. Clonal reproduction contributed significantly more than sexual reproduction to population growth in the forest remnants. Only at the well-forested site did sexual reproduction contribute as much as clonal reproduction to population growth. Flowering plants were more likely to transition to a smaller size class with reduced reproductive potential in the following year than similarly sized nonflowering plants, suggesting energy trade-offs between sexual and clonal reproduction at the individual level. Seed production had negligible effects on growth and tuber production of individual plants. Our results demonstrate that clonal reproduction is vital for population persistence in a system where sexual reproduction is unpredictable. The bias toward clonality may be driven by low fitness returns for resource investment in sexual reproduction at the individual level. However, chronic failure in sexual reproduction may exacerbate the imbalance between sexual and clonal reproduction and eventually lead to irreversible loss of sex in the population. [ABSTRACT FROM AUTHOR]

The biological balance of Yakushima Island is currently being compromised by overpopulation of sika deer ( Cervus nippon yakushimae). We predicted that the island's deer population would continue to grow unless control efforts are raised threefold from their 2012 levels. To identify the best management practice for future implementation, we evaluated and compared the performances of three different zone-based management strategies. Under the current management scenario, the median population size of the sika deer on the island would temporarily decrease, but it would subsequently rebound. Under a scenario that allows management zones to be prioritized according to the occurrence of threatened plant species and deer population size, model simulations suggested that the scenario focusing on the central zone would show the best performance based on the probability of achievement of the management goal (assuming that there is no dispersal between zones). This course of action would lead to a decrease in the median deer population size and would further ensure a high probability of achieving the 2022 target population size across most zones (up to 85 %), even if catch levels were not increased. In a future study, we would need to conduct a more detailed analysis of plants and deer density distributions. [ABSTRACT FROM AUTHOR]

The open-data scientific philosophy is being widely adopted and proving to promote considerable progress in ecology and evolution. Open-data global data bases now exist on animal migration, species distribution, conservation status, etc. However, a gap exists for data on population dynamics spanning the rich diversity of the animal kingdom world-wide. This information is fundamental to our understanding of the conditions that have shaped variation in animal life histories and their relationships with the environment, as well as the determinants of invasion and extinction., Matrix population models ( MPMs) are among the most widely used demographic tools by animal ecologists. MPMs project population dynamics based on the reproduction, survival and development of individuals in a population over their life cycle. The outputs from MPMs have direct biological interpretations, facilitating comparisons among animal species as different as Caenorhabditis elegans, Loxodonta africana and Homo sapiens., Thousands of animal demographic records exist in the form of MPMs, but they are dispersed throughout the literature, rendering comparative analyses difficult. Here, we introduce the COMADRE Animal Matrix Database, an open-data online repository, which in its version 1.0.0 contains data on 345 species world-wide, from 402 studies with a total of 1625 population projection matrices. COMADRE also contains ancillary information (e.g. ecoregion, taxonomy, biogeography, etc.) that facilitates interpretation of the numerous demographic metrics that can be derived from its MPMs. We provide R code to some of these examples., Synthesis: We introduce the COMADRE Animal Matrix Database, a resource for animal demography. Its open-data nature, together with its ancillary information, will facilitate comparative analysis, as will the growing availability of databases focusing on other aspects of the rich animal diversity, and tools to query and combine them. Through future frequent updates of COMADRE, and its integration with other online resources, we encourage animal ecologists to tackle global ecological and evolutionary questions with unprecedented sample size. [ABSTRACT FROM AUTHOR]

• Culls are a popular response to manage conflict between marine mammals and fisheries. • Culls could interact with extreme climate events to impact pinniped populations. • Modelling populations with imperfect data is possible via phylogenetic imputations. • Climate uncertainty is incorporated using stochastic matrix population models. • Sea lion populations decline below minimum viable population sizes under culls and extreme climate events. Human actions led to the worldwide decline of marine mammal populations in the 18th–19th centuries. Global adoption of protective legislation during the 20th century has recently allowed many marine mammal populations to recover. This positive trend is particularly true of pinnipeds (e.g., seals and sea lions), whose recovering populations are increasingly in conflict with fisheries. Fisheries organisations have called for managed culls of sea lion populations to reduce competition for target fish species as well as damage to catch and fishing gear through operational interactions. However, despite widespread perceptions that sea lion populations are generally increasing, to-date, culls have often been considered or implemented without quantitative evidence of their impacts on seal lion population viability. This knowledge gap is particularly concerning given the expected increase in extreme climate conditions, such as extreme El Niño events, which together with culls could push sea lion populations in some parts of the world into the extinction vortex. Here, I develop stochastic matrix population models of the South American sea lion (Otaria flavescens) parameterised through a combination of species-specific field data and phylogenetic imputation using data from related species in the COMADRE animal matrix database. Using these models, I project the impact of (1) three cull scenarios with different intensity and temporal frequency targeting adult females, (2) extreme El Niño events whose frequency is modelled using a Markovian transition matrix, and (3) the interaction of culls and extreme climate events on population dynamics. I focus on the Chilean population of O. flavescens , where recent increases in sea lion numbers have triggered widespread conflict with small-scale fisheries, and where sea lion populations will increasingly be affected by extreme El Niño conditions. I find that sea lion populations decline below minimum viable population sizes within 16–28 years under all scenarios involving culls and extreme climate events. This research explicitly incorporates parameter uncertainty into population projections—in so doing, it illustrates the need for future research to collect stage-specific, annual population data to reduce uncertainty regarding marine mammal vital rates. [ABSTRACT FROM AUTHOR]

The identification of patterns in life-history strategies across the tree of life is essential to our prediction of population persistence, extinction, and diversification. Plants exhibit a wide range of patterns of longevity, growth, and reproduction, but the general determinants of this enormous variation in life history are poorly understood. We use demographic data from 418 plant species in the wild, from annual herbs to supercentennial trees, to examine how growth form, habitat, and phylogenetic relationships structure plant life histories and to develop a framework to predict population performance. We show that 55% of the variation in plant life-history strategies is adequately characterized using two independent axes: the fast-slow continuum, including fast-growing, short-lived plant species at one end and slow-growing, long-lived species at the other, and a reproductive strategy axis, with highly reproductive, iteroparous species at one extreme and poorly reproductive, semelparous plants with frequent shrinkage at the other. Our findings remain consistent across major habitats and are minimally affected by plant growth form and phylogenetic ancestry, suggesting that the relative independence of the fast-slow and reproduction strategy axes is general in the plant kingdom. Our findings have similarities with how lifehistory strategies are structured inmammals, birds, and reptiles. The position of plant species populations in the 2D space produced by both axes predicts their rate of recovery from disturbances and population growth rate. This life-history framework may complement trait-based frameworks on leaf and wood economics; together these frameworks may allow prediction of responses of plants to anthropogenic disturbances and changing environments. [ABSTRACT FROM AUTHOR]

Land use change is one of the main drivers of species extinction. In Europe, grasslands are under active conflict between conservation efforts and increasing agricultural pressures. Here, we examine the demographic effects of differential land use on the herbaceous perennial Trollius europaeus L. (Ranunculaceae), a bioindicator of species-richness and ecosystem services in wet grasslands of Central Europe. Demographic data were collected in 2006-2009 from nine populations in seven protected sites of northeastern Germany representing four land use types. We constructed stage-based matrix population models to explore the effects of various land management on demographic viability of focal populations. We show that most studied populations are declining ( λ < 1), although the estimates of local extinction vary between ≤15 years for grazed and woodland populations, and 20-99 years for mown and abandoned populations. The joint information from our elasticity analyses and life table response experiments revealed that reproduction, growth of small vegetative individuals and survival of reproductive stages are most important for population viability. Our study shows that the current land uses in protected areas where T. europaeus is found is incompatible with its long-term viability. We suggest that, when compatible with in situ practices, grasslands containing this species be mown after maturity in order to enhance seedling recruitment and to reduce competition for juveniles. Prolonged extinction times in abandoned populations offer a buffer to develop conservation schemes there. An improvement of conservation measures is urgently needed to maintain the populations of this important bioindicator and its associated community of moist species-rich fen grasslands. [ABSTRACT FROM AUTHOR]

Long-lived plant species are highly valued environmentally, economically, and socially, but can also cause substantial harm as invaders. Realistic demographic predictions can guide management decisions, and are particularly valuable for long-lived species where population response times can be long. Long-lived species are also challenging, given population dynamics can be affected by factors as diverse as herbivory, climate, and dispersal. We developed a matrix model to evaluate the effects of herbivory by a leaf-feeding biological control agent released in Australia against a long-lived invasive shrub (mesquite, Leguminoseae: Prosopis spp.). The stage-structured, density-dependent model used an annual time step and 10 climatically diverse years of field data. Mesquite population demography is sensitive to source-sink dynamics as most seeds are consumed and redistributed spatially by livestock. In addition, individual mesquite plants, because they are long lived, experience natural climate variation that cycles over decadal scales, as well as anthropogenic climate change. The model therefore explicitly considered the effects of both net dispersal and climate variation. Herbivory strongly regulated mesquite populations through reduced growth and fertility, but additional mortality of older plants will be required to reach management goals within a reasonable time frame. Growth and survival of seeds and seedlings were correlated with daily soil moisture. As a result, population dynamics were sensitive to rainfall scenario, but population response times were typically slow (20-800 years to reach equilibrium or extinction) due to adult longevity. Equilibrium population densities were expected to remain 5% higher, and be more dynamic, if historical multi-decadal climate patterns persist, the effect being dampened by herbivory suppressing seed production irrespective of preceding rainfall. Dense infestations were unlikely to form under a drier climate, and required net dispersal under the current climate. Seed input wasn't required to form dense infestations under a wetter climate. Each factor we considered (ongoing herbivory, changing climate, and source-sink dynamics) has a strong bearing on how this invasive species should be managed, highlighting the need for considering both ecological context (in this case, source-sink dynamics) and the effect of climate variability at relevant temporal scales (daily, multi-decadal, and anthropogenic) when deriving management recommendations for long-lived species. [ABSTRACT FROM AUTHOR]

The mosquito Aedes aegypti , the principal vector of dengue and yellow fever viruses, is an anthropophilic species adapted to urban environments, particularly to housing. A decisive factor in the proliferation of this species is ambient temperature, which has a direct influence on the vital rates of the species. Here we present a structured matrix population model for analyzing the effect of temperature on the population dynamics of Aedes aegypti . The model is structured following the four natural stages of the species: egg, larva, pupa and adult. A set of population projection matrices (one for each temperature between 5 and 30 °C), was constructed and parameterized using published data on the biology of the species. The output of the models showed that pupation does not occur at temperatures below 8 °C. The population's growth rate was calculated for temperatures between 11 and 30 °C, resulting in an increasing function showing that temperatures above 12 °C are sufficient for population growth. For each matrix, a sensitivity and elasticity analysis of the parameters was performed. Together with the results from the population stable distribution analysis, they suggest that policies aimed at reducing the abundance of Aedes aegypti should seek to lower the survival probability in the egg and larval stages. The population dynamics was simulated under different seasonal scenarios. This seasonal analysis allows asserting that the egg stage dominates the population dynamics at all seasons. [ABSTRACT FROM AUTHOR]

Climate change directly affects the suitability of habitats for species, but also indirectly alters natural disturbances such as fire, which can negatively impact species’ persistence. Developing accurate predictions of climate change impacts requires estimates of the interactive effects of climate and disturbance regimes at both population and landscape scales. Here we couple a habitat suitability model with a population viability model to examine the interactive effects of climate change and altered fire regimes on a fire-responsive frog species across its geographic range in south-eastern Australia. By 2100, we predict expected minimum abundances (EMA) to decline by 66% (under GFDL-CM2 A1FI climate projections) or 87% (CSIRO Mk3.5 A1FI) in the absence of fire. Increased frequency of low-intensity fires reduced EMA by less than 5%, whereas increased frequency of high-intensity fires reduced EMA by up to 40% compared with the no-fire scenario. While shifts in fire regimes are predicted to impact metapopulation viability, these indirect effects of fire are far less severe than the direct impact of climate change on habitat suitability. Exploring the interactive impacts of climate change and altered disturbance regimes can help managers prioritize threats across space and time. [ABSTRACT FROM AUTHOR]

The generation time is commonly defined as the mean age of mothers at birth. In matrix population models, a general formula is available to compute this quantity. However, it is complex and hard to interpret. Here, we present a new approach where the generation time is envisioned as a return time in an appropriate Markov chain. This yields surprisingly simple results, such as the fact that the generation time is the inverse of the sum of the elasticities of the growth rate to changes in the fertilities. This result sheds new light on the interpretation of elasticities (which as we show correspond to the frequency of events in the ancestral lineage of the population), and we use it to generalize a result known as Lebreton's formula. Finally, we also show that the generation time can be seen as a random variable, and we give a general expression for its distribution. [ABSTRACT FROM AUTHOR]

We evaluated the fourth stage of the 'Conservation and Management Plan for Sika Deer ( Cervus nippon) in Hokkaido, Japan (CMPS4)', focusing on its cost-effectiveness and sika deer migration between two management areas of eastern and western Hokkaido. To clarify these factors, we constructed a stochastic matrix population model that accounts for deer migration and several uncertainties. We assumed four different budget scenarios and simple rules regarding nuisance control, and simulated four alternative management strategies. In the stochastic simulation, we calculated the probability of successfully satisfying the population target given by the CMPS4, an average total actual management cost, and a cost-effectiveness index given four budget conditions of migration rate and budget allocation ratio. The simulation results suggest the following. First, the current management budget is so small that the probability of successfully satisfying the population targets in both areas is only 26-30 %. If the total budget remains small, it should be almost entirely invested in one area, regardless of migration situation, to maximize the probability of successfully meeting the target density in at least that area. However, these probabilities of success decrease with greater migration rate. Second, when the government invests more of its budget in the early management stage, the expected total actual cost decreases and the probability of management success increases. These findings represent cost-effective management strategies for satisfying the CMPS4 targets. [ABSTRACT FROM AUTHOR]

1. Schedules of survival, growth and reproduction are key life-history traits. Data on how these traits vary among species and populations are fundamental to our understanding of the ecological conditions that have shaped plant evolution. Because these demographic schedules determine population growth or decline, such data help us understand how different biomes shape plant ecology, how plant populations and communities respond to global change and how to develop successful management tools for endangered or invasive species. 2. Matrix population models summarize the life cycle components of survival, growth and reproduction, while explicitly acknowledging heterogeneity among classes of individuals in the population. Matrix models have comparable structures, and their emergent measures of population dynamics, such as population growth rate or mean life expectancy, have direct biological interpretations, facilitating comparisons among populations and species. 3. Thousands of plant matrix population models have been parameterized from empirical data, but they are largely dispersed through peer-reviewed and grey literature, and thus remain inaccessible for synthetic analysis. Here, we introduce the COMPADRE Plant Matrix Database version 3.0, an open-source online repository containing 468 studies from 598 species world-wide (672 species hits, when accounting for species studied in more than one source), with a total of 5621 matrices. COMPADRE also contains relevant ancillary information (e.g. ecoregion, growth form, taxonomy, phylogeny) that facilitates interpretation of the numerous demographic metrics that can be derived from the matrices. 4. Synthesis. Large collections of data allow broad questions to be addressed at the global scale, for example, in genetics (GENBANK), functional plant ecology (TRY, BIEN, D3) and grassland community ecology (NUTNET). Here, we present COMPADRE, a similarly data-rich and ecologically relevant resource for plant demography. Open access to this information, its frequent updates and its integration with other online resources will allow researchers to address timely and important ecological and evolutionary questions. [ABSTRACT FROM AUTHOR]