The founding of a southern elephant seal colony

The only large mainland colony of southern elephant seals (Mirounga leonina) is on Península Valdés, at 42°S, in Argentine Patagonia. Censuses of pups have been carried out regularly there since 1970, and the population grew five‐fold by 2010. Here we use Bayesian modeling tools to make rigorous estimates of the rate of population growth, r, and to estimate survival and recruitment parameters that could account for the growth, incorporating observation error across different census methods. In the 1970s, r= 8%/yr, but has slowed to <1%/yr over the past decade. Using explicit demographic models, we established that the high growth of the 1970s was consistent with adult and juvenile survival at the upper end of published values (0.87/yr adult female survival; 0.40 juvenile survivorship to age four); the decline in the rate of population growth from 1970 to 2010 can be described by density‐dependent reductions in adult and juvenile survival that fall well within published variation. Extrapolating empirical models of population growth rate backwards illustrates that the population could have been an established colony, with 100 pups born per year, between 1915 and 1945, consistent with qualitative observations prior to 1950. We conclude that the Valdés colony was founded by a few immigrants early in the 20th century and has been growing mostly by internal recruitment, with unknown density‐dependent processes causing a reduction in growth and stabilization at 15,000–16,000 pups born.     

Changes in Demographic Parameters of <Emphasis Type="Italic">Macaca fuscata</Emphasis> at Takasakiyama in Relation to Decrease of Provisioned Foods

Though researchers have studied population dynamics extensively in many free-ranging primate populations, information on the relationship between food abundance and demographic parameters based on long-term data is sparse. We examined changes in demographic parameters in relation to decreased provisioning of foods based on data gathered for >50 yr in a provisioned, free-ranging Japanese macaque (Macaca fuscata) population at Takasakiyama, Oita Prefecture, in the southern region of Japan. At Takasakiyama, population size increased linearly because of heavy provisioning in the 1950s and 1960s. The provisioning of food to macaques decreased from 1965. We examined changes in the physique index of full adult females, primiparous age, birth percentage, infant mortality rate, population density, and annual population growth rate relative to the decrease of provisioned foods between the 1970s and 1990s. As a result of the drastic decrease in the amount of foods provisioned, the physique index of full adult females decreased, primiparous age increased, birth percentage decreased, and infant mortality rate increased, such that annual population growth rate diminished substantially. Ours is the first study to demonstrate quantitatively the relationship between provisioned food abundance and demographic parameters based on long-term data.     

Inferring the temperature dependence of population parameters: the effects of experimental design and inference algorithm

Understanding and quantifying the temperature dependence of population parameters, such as intrinsic growth rate and carrying capacity, is critical for predicting the ecological responses to environmental change. Many studies provide empirical estimates of such temperature dependencies, but a thorough investigation of the methods used to infer them has not been performed yet. We created artificial population time series using a stochastic logistic model parameterized with the Arrhenius equation, so that activation energy drives the temperature dependence of population parameters. We simulated different experimental designs and used different inference methods, varying the likelihood functions and other aspects of the parameter estimation methods. Finally, we applied the best performing inference methods to real data for the species Paramecium caudatum. The relative error of the estimates of activation energy varied between 5% and 30%. The fraction of habitat sampled played the most important role in determining the relative error; sampling at least 1% of the habitat kept it below 50%. We found that methods that simultaneously use all time series data (direct methods) and methods that estimate population parameters separately for each temperature (indirect methods) are complementary. Indirect methods provide a clearer insight into the shape of the functional form describing the temperature dependence of population parameters; direct methods enable a more accurate estimation of the parameters of such functional forms. Using both methods, we found that growth rate and carrying capacity of Paramecium caudatum scale with temperature according to different activation energies. Our study shows how careful choice of experimental design and inference methods can increase the accuracy of the inferred relationships between temperature and population parameters. The comparison of estimation methods provided here can increase the accuracy of model predictions, with important implications in understanding and predicting the effects of temperature on the dynamics of populations.     

Continuous cultivation of fission yeast: Analysis of single-cell protein synthesis kinetics

A fundamental problem in microbial reactor analysis is identification of the relationship between environment and individual cell metabolic activity. Population balance equations provide a link between experimental measurements of composition frequency functions in microbial populations on the one hand and macromolecular synthesis kinetics and cell division control parameters for single cells on the other. Flow microfluorometry measurements of frequency functions for single-cell protein content in Schizosaccharomyces pombe in balanced exponential growth have been analyzed by two different methods. One approach utilizes the integrated form of the population balance equation known as the Collins-Richmond equation, and the other method involves optimization of parameters in assumed kinetic and cell division functional forms in order to best fit measured frequency functions with corresponding model solutions. Both data interpretation techniques indicate that rates of protein synthesis increase most in small protein content cells as the population specific growth rate increases, leading to parabolic single-cell protein synthesis kinetics at large specific growth rates. Utilization of frequency function data for an asynchronous population is shown in this case to be a far more sensitive method for determination of single-cell kinetics than is monitoring the metabolic dynamics of a single cell or, equivalently, synchronous culture analyses.     

A mathematical model of the food-consumer system I. A case without food replenishment

A simple mathematical model was proposed to describe the dynamics of a food-consumer system. The model was based on the Logistic Theory and consisted of Eqs. (4), (5) and (6). The model was divided into the following three cases for further analyss; i) without food supply except at the initial time, ii) with continuous food supply at a constant rate, and iii) with food supply at varying rates. Only the first model was dealth with in this paper. The assumptions of the model 1 are that a definite amount of food is given only once at the initial time and only the feeding by animals is responsible for the decrease of food, and that the rate of decrease is proportional to the amount of animals. It is also assumed that the growth of animal population is represented by the logistic curve, and that the upper limit of the population is proportional to the amount of food at that time. For simplicity the parameters of basic differential equations are assumed to be constant throughout the time course. Analytical solutions of this non-linear model were given by Eqs. (8), (9), (10) and (11). The properties of time course of the food amount and consumer population were discussed from the mathematical and biological points of view. The method of the estimation of the three constants λ,b, and c from the experimental data was also suggested. Since we had no available data for animal populations, we applied the model, regarding reserve substance as x and new plant body as y, to the data of the initial growth of Azuki bean plant in the dark. This model is very simple, but it may be useful for analyzing the behavior of food-consumer system. And it may give some clue to the analysis of the more complex systems.     

A Rapid Method to Estimate Population Variables for African Elephants

Abstract: We developed a noninvasive method to estimate reproductive and survival parameters for free-ranging African savannah elephants (Loxodonta africana africana) and used these to estimate finite population growth rates. We used published data from 2 populations with known growth rates and birth and survival histories to validate our technique. Based on body measurements, our method yielded estimates of age at first and last calving, calving interval, and age-specific survival rates that were similar to those determined during long-term studies at both Addo Elephant National Park and Amboseli National Park. Our technique generated population data required to estimate population growth rates. The method may be particularly useful where censuses yield imprecise estimates or where long-term population data are unavailable. (JOURNAL OF WILDLIFE MANAGEMENT 72(3):822–829; 2008)     

Dispersal kernel of green rice leafhopper estimated from truncated data

Characterizing dispersal kernels from truncated data is important for managing and predicting population dynamics. We used mark-recapture data from 10 previously published replicated experiments at three host plant development stages (seedling, tillering, and heading) to estimate parameters of the normal and exponential dispersal kernels for green rice leafhopper, Nephotettix cincticeps (Uhler). We compared classic statistical methods for estimating untruncated distribution parameters from truncated data with maximum likelihood (MLE) and the method of statistical moments for simulated and empirical data. Simulations showed that both methods provided accurate parameter estimates with similar precision. The method of moments is algebraically complex, but simple to calculate, while the MLE methods require numerical solutions of nonlinear equations. Simulations also showed that accurate, precise estimates of the parameters of the untruncated distributions could be attained even under severe truncation with sufficient numbers of recaptures. Both diffusivity and the exponential mean were higher with later plant growth stage, showing that insects moved farther and faster at the heading stage. Precision of the estimates was not strongly related to percent capture, size of the experimental field, or the number of leafhoppers captured. The leptokurtic exponential kernel fit the data better than the normal kernel for all the experiments. These results support an alternative explanation for the strong density-dependent population regulation of this species at the heading stage. Instead of leafhopper density per se, the increase in movement at this stage could integrate the populations in the separate fields, leveling densities throughout the landscape.     

Emigration and Density Dependence in Yellowstone Bison

Abstract: Understanding the relative importance of density-dependent and density-independent feedback on population growth is essential for developing management strategies to conserve wildlife. We examined a 99-year time series of annual counts and removals for 2 bison (Bison bison) herds occupying northern and central Yellowstone National Park in the western United States. Yellowstone's aggressive management intervention effectively recovered bison from 46 animals in 1902 to > 1,500 animals in 1954. Supplemental feeding of the northern herd facilitated rapid growth (r = 0.16) during 1902 to 1952. Augmentation of the central herd with 71 animals also led to rapid growth over 1936 to 1954 (r = 0.10). In 1969, manipulative management ceased in the park, and we detected evidence of density-dependent changes in population growth rates for both herds during 1970 to 2000 as numbers increased to >3,000 animals. The central herd showed evidence of a constant density-dependent response over 1970 to 2000. In contrast, density dependence had a stronger effect on the northern herd's growth rate during 1970 to 1981 than during 1982 to 2000. We found evidence to suggest that these trends resulted from pulses of emigration from the central herd to the northern range beginning in 1982 in response to resource limitation generated by an interaction between density and severe snow pack. Corroborative evidence supporting this interpretation included 1) the annual growth of the central herd was negatively correlated with snow pack but that of the northern herd was not, 2) growth rates of the central and northern herds were uncorrelated during 1970 to 1981 but significantly and negatively correlated during 1982 to 2000, and 3) the northern herd could not have sustained the high removals experienced during 1984 to 2000 without immigration. Density-related emigration from the central herd to the northern range may be fueling bison emigration onto private and public lands where large-scale removals occur, exacerbating the brucellosis controversy for natural resource managers.     

The association between Barrett's esophagus and Helicobacter pylori infection: a meta-analysis

Objective: The effect of Helicobacter pylori on Barrett’s esophagus is poorly understood. We conducted a meta‐analysis to summarize the existing literature examining the effect that H. pylori has on Barrett’s esophagus. Design: We performed a comprehensive search to identify studies pertaining to the association between H. pylori and Barrett’s esophagus. We conducted meta‐regression analyses to identify sources of variation in the effect of H. pylori on Barrett’s esophagus. Results: Our analysis included a total of 49 studies that examined the effect of H. pylori on Barrett’s esophagus and seven studies that examined the effect of cag A positivity on Barrett’s esophagus. Overall, H. pylori, and even more so cag A, tended to be protective for Barrett’s esophagus in most studies; however, there was obvious heterogeneity across studies. The effect of H. pylori on Barrett’s esophagus varied by geographic location and in the presence of selection and information biases. Only four studies were found without obvious selection and information bias, and these showed a protective effect of H. pylori on Barrett’s esophagus (Relative risk = 0.46 [95% CI: 0.35, 0.60]). Conclusions: Estimates for the effect of H. pylori on Barrett’s esophagus were heterogeneous across studies. We identified selection and information bias as potential sources of this heterogeneity. Few studies without obvious selection and information bias have been conducted to examine the effect of H. pylori on Barrett’s esophagus, but in these, H. pylori infection is associated with a reduced risk of Barrett’s esophagus.     

Modelling urban populations of the Australian White Ibis (Threskiornis molucca) to inform management

Since the 1970s, populations of the Australian White Ibis (Threskiornis molucca) have dramatically increased in many Australian urban centres. Managers of ibis are currently focusing on limiting this bird's reproductive success in order to reduce population sizes or at least halt further increases in urban areas. Here we use data on nesting success and survival for three populations of ibis around greater Sydney to develop an age-structured population model. The estimated growth rate for all populations combined was about 1.5 % per year and for individual sites were more variable at −1, −7, and 9 %. For all populations, growth rates were most sensitive (based on elasticity analyses) to the survival of adults and least sensitive to fecundity, especially of 3 year olds. Further exploration of the importance of fecundity rates, which are relatively poorly known for these populations, suggests that rates of <0.4 fledglings per nest per year is very likely to lead to a population decline (λ less than lower bound of 95 % CI). Conversely, positive population growth is nearly assured (λ greater than upper bound of 95 % CI) for fecundities of >0.7 fledgling per nest per year. The results suggest that ibis from other locations (probably their traditional breeding areas in inland Australia) have immigrated into urban environments as estimated growth rates cannot account for current population sizes. Management strategies must take these findings into account and also consider that ibis are declining in their traditional habitats to avoid exacerbating their decline at a regional scale.     

Phenotypic Stability of Mixtures – Relations Between the Stability Parameters of a Mixture and Its Components

For each of the two stability parameters (‘regression coefficient’ and ‘sum of squared deviations from the regression’) of the common regression approach (= regression of the yield of population i in environment j on the environmental index of this evironment j which often has been estimated by the mean of all tested populations in this environment j) the phenotypic stability of a mixture and it's components have been analysed theoretically. It can be shown that in practical applications (for example: variety testing) the regression coefficient of a mixture often can be sufficiently approximated by the arithmetic mean of the regression coefficients of the components grown singly. This simple relation between a mixture and it's components don't hold for the second stability parameter ‘sum of squared deviations from the regression’. The exact relation has been deduced and useful and clear approximations are discussed. All the theoretical results are demonstrated and applied using the well-known experimental barley data of Sandfaer (1970).     

Incorporating experimental design and error into coalescent/mutation models of population history

Coalescent theory provides a powerful framework for estimating the evolutionary, demographic, and genetic parameters of a population from a small sample of individuals. Current coalescent models have largely focused on population genetic factors (e.g., mutation, population growth, and migration) rather than on the effects of experimental design and error. This study develops a new coalescent/mutation model that accounts for unobserved polymorphisms due to missing data, sequence errors, and multiple reads for diploid individuals. The importance of accommodating these effects of experimental design and error is illustrated with evolutionary simulations and a real data set from a population of the California sea hare. In particular, a failure to account for sequence errors can lead to overestimated mutation rates, inflated coalescent times, and inappropriate conclusions about the population. This current model can now serve as a starting point for the development of newer models with additional experimental and population genetic factors. It is currently implemented as a maximum-likelihood method, but this model may also serve as the basis for the development of Bayesian approaches that incorporate experimental design and error.     

Status,trends, and equilibrium abundance estimates of the translocated sea otter population in Washington State

Sea otters (Enhydra lutris kenyoni) historically occurred in Washington State, USA, until their local extinction in the early 1900s as a result of the maritime fur trade. Following their extirpation, 59 sea otters were translocated from Amchitka Island, Alaska, USA, to the coast of Washington, with 29 released at Point Grenville in 1969 and 30 released at La Push in 1970. The Washington Department of Fish and Wildlife has outlined 2 main objectives for sea otter recovery: a target population level and a target geographic distribution. Recovery criteria are based on estimates of population abundance, equilibrium abundance (K), and geographic distribution; therefore, estimates of these parameters have important management implications. We compiled available survey data for sea otters in Washington State since their translocation (1977–2019) and fit a Bayesian state-space model to estimate past and current abundance, and equilibrium abundance at multiple spatial scales. We then used forward projections of population dynamics to explore potential scenarios of range recolonization and as the basis of a sensitivity analysis to evaluate the relative influence of movement behavior, frontal wave speed, intrinsic growth, and equilibrium density on future population recovery potential. Our model improves upon previous analyses of sea otter population dynamics in Washington by partitioning and quantifying sources of estimation error to estimate population dynamics, by providing robust estimates of K, and by simulating long-term population growth and range expansion under a range of realistic parameter values. Our model resulted in predictions of population abundance that closely matched observed counts. At the range-wide scale, the population size in our model increased from an average of 21 independent sea otters (95% CI = 13–29) in 1977 to 2,336 independent sea otters (95% CI = 1,467–3,359) in 2019. The average estimated annual growth rate was 12.42% and varied at a sub-regional scale from 6.42–14.92%. The overall estimated mean K density of sea otters in Washington was 1.71 ± 0.90 (SD) independent sea otters/km² of habitat (1.96 ± 1.04 sea otters/km², including pups), and estimated densities within the current range correspond on average to 87% of mean sub-regional equilibrium values (range = 66–111%). The projected value of K for all of Washington was 5,287 independent sea otters (95% CI = 2,488–8,086) and 6,080 sea otters including pups (95% CI = 2,861–9,300), assuming a similar range of equilibrium densities in currently un-occupied habitats. Sensitivity analysis of simulations of sea otter population growth and range expansion suggested that mean K density estimates in currently occupied sub-regions had the largest impact on predicted future population growth (r² = 0.52), followed by the rate of southward range expansion (r² = 0.26) and the mean K density estimate of currently unoccupied sub-regions to the south of the current range (r² = 0.04). Our estimates of abundance and sensitivity analysis of simulations of future population abundance and geographic range help determine population status in relation to population recovery targets and identify the most influential parameters affecting future population growth and range expansion for sea otters in Washington State.     

Modelling the population dynamics of <Emphasis Type="Italic">Daphnia obtusa</Emphasis> (Kurz) in Lake Orta (N. Italy) under pre- and post-liming conditions

A mathematical matrix model was formulated to investigate the response of Daphnia obtusa population dynamics to the changes in the water chemistry of Lake Orta before and after the liming operation. Model parameters were estimated from experimental laboratory data. Model analysis showed that water chemistry changes induced by liming affected mainly egg survival and predicted the highest population growth at pH␣6. Whereas increased egg mortality heavily inhibits population growth rate, the model still predicts a long term tendency of the population to increase in number. However, both before and after the liming operation due to high food availability in the laboratory, egg production was higher under all experimental conditions than in the field. When food limitation is accounted for and more realistic, field based estimates of egg production are used, the model predicts the extinction of D. obtusa population in the lake. This suggests that the effects of water chemistry changes on egg mortality had a critical role in the disappearance of D. obtusa from Lake Orta and may even adequately explain the extinction of this population.     

Radial basis function neural networks for modeling growth rates of the basidiomycetes Physisporinus vitreus and Neolentinus lepideus

A radial basis function (RBF) neural network was developed and compared against a quadratic response surface (RS) model for predicting the specific growth rates of the biotechnologically important basidiomycetous fungi, Physisporinus vitreus and Neolentinus lepideus, under three environmental conditions: temperature (10–30 °C), water activity (0.950–9.998), and pH (4–6). Both the RBF network and polynomial RS model were mathematically evaluated against experimental data using graphical plots and several statistical indices. The evaluation showed that both models gave reasonably good predictions, but the performance of the RBF neural network was superior to that of the classical statistical method for all three data sets used (training, testing, full). Sensitivity analysis revealed that of the three experimental factors the most influential on the growth rate of P. vitreus was water activity, followed by temperature and pH to a lesser extent. In contrast, temperature in particular and then water activity were the key determinants of the development of N. lepideus. RBF neural networks could be a powerful technique for modeling fungal growth behavior under certain parameters and an alternative to time-consuming, traditional microbiological techniques.     

Genomic inference accurately predicts the timing and severity of a recent bottleneck in a nonmodel insect population

The analysis of molecular data from natural populations has allowed researchers to answer diverse ecological questions that were previously intractable. In particular, ecologists are often interested in the demographic history of populations, information that is rarely available from historical records. Methods have been developed to infer demographic parameters from genomic data, but it is not well understood how inferred parameters compare to true population history or depend on aspects of experimental design. Here, we present and evaluate a method of SNP discovery using RNA sequencing and demographic inference using the program δaδi, which uses a diffusion approximation to the allele frequency spectrum to fit demographic models. We test these methods in a population of the checkerspot butterfly Euphydryas gillettii. This population was intentionally introduced to Gothic, Colorado in 1977 and has as experienced extreme fluctuations including bottlenecks of fewer than 25 adults, as documented by nearly annual field surveys. Using RNA sequencing of eight individuals from Colorado and eight individuals from a native population in Wyoming, we generate the first genomic resources for this system. While demographic inference is commonly used to examine ancient demography, our study demonstrates that our inexpensive, all‐in‐one approach to marker discovery and genotyping provides sufficient data to accurately infer the timing of a recent bottleneck. This demographic scenario is relevant for many species of conservation concern, few of which have sequenced genomes. Our results are remarkably insensitive to sample size or number of genomic markers, which has important implications for applying this method to other nonmodel systems.     

A demographic analysis of population responses to the manipulation of adult males in <Emphasis Type="Italic">Calomys venustus</Emphasis> (Rodentia,Sigmodontinae)

In many species of mammals, adults play an important role in influencing the survival and/or reproduction of juveniles. Adult males could have a negative effect on population density when their absence becomes a limiting factor in female fertilization. We tested the hypotheses that the absence of overwintering males (adult males) reduces the population growth rate through a delay in the onset of reproductive activity of Cohort 1 females in Calomys venustus populations. The study was carried out in two control and two experimental enclosures (0.25 ha). Adult males were removed after their offspring were born. Weekly trapping sessions were carried out from spring to autumn. To estimate population growth rates (λ), apparent survival (ϕ) and seniority probability (γ) were estimated using capture–mark-recapture models. Models were constructed with these two parameters and recapture probability (p) constrained to vary as a function of time, enclosure and/or treatment. We derived estimates of population growth rates through the estimates of ϕ and γ. The best models for ϕ and γ did not show a treatment effect. Variability between the four enclosures was greater than between control and experimental enclosures. Enclosures had different growth rates at the beginning of the study but were equaled at the end. Temporal variation in population growth rates was a result of temporal variation of γ. The two controls showed the highest growth rates earlier in time. The results did not support the hypothesis tested in this study. It seems that the number of overwintering males do not affect the population growth rate.     

Algal Population Growth Model Integrated with Toxicokinetics for Ecological Risk Assessment under Time-Varying Pesticide Exposure

An algal population growth model integrated with toxicokinetics was developed for assessing the effect of pesticides on population dynamics. This model is a simple one-compartment, first-order kinetic model in which toxicity (growth inhibition and mortality) depends on the intracellular effective concentration of a pesticide at a target site. The model's parameters were derived using an experimental study that investigated the effects of pretilachlor, bensulfuron-methyl, pentoxazone, and quinoclamine on the growth, mortality, and subsequent population recovery of the green alga Pseudokirchneriella subcapitata. Modeled and measured trajectories of algal population dynamics agreed well. The effect on population recovery was underestimated by the model that ignored the toxicokinetics. The four tested herbicides had a variety of toxicity characteristics and physicochemical properties, indicating the wide range of the model's applicability. Moreover, the developed model and the obtained model's parameters were extrapolated to predict long-term algal population dynamics under time-varying herbicide exposure. The calculated integral biomass lost compared with the control was considered a quantitative index of the population-level ecological risk. The model's prediction showed that the same exposure level (peak concentration is equivalent to EC50) indicated much different population-level effect depending on the herbicide.