Simulation of small bird populations. II. Reduced breeding in two British raptor species

A computer model was developed to simulate the fate of small populations of birds. It uses general and easily available data as input. Monte-Carlo techniques are used and a survival probability is calculated for every population member four times per simulated year. The model allows for density-dependence in winter survival and also in fecundity.Simulation results are used to compile standard age-specific life-tables for all complete cohorts generated. A mean life-table is also made. The survivor functions, both accumulated and mean, are contrasted with control functions and tested for significance.The model has been applied to classical population data in ornithology, namely those for the great tit and the tawny owl in Wytham Woods (Oxford, UK). There was a fair agreement between simulation results and field data.     

Simulated Responses of a Forest-Interior Bird Population to Forest Management Options in Central Hardwood Forests of the United States

I used estimates of carrying capacity, survival, fecundity, and edge effects to simulate the responses of a forest-interior bird population to selection cutting clearcutting, and no timber harvest. I also modeled population sensitivity to changes in fecundity, survival, K , and edge relationships. Because model parameters are based on scant data, results should he regarded as hypotheses to be further investigated or measures of the relative impact or sensitivity (given model assumptions). Simulated population size was greater with no timber harvest than with clearcutting and greater with clearcutting than with group selection when edge effects were included in the model. Without edge effects, population levels were only slightly lower under group selection than under no timber harvest, and greater than clearcutting. Edge effects had only a small impact on population levels under clearcutting. Clearcut size did not have much effect on population levels, but longer and shorter rotation ages resulted in higher and lower population levels, respectively. The model was very sensitive to declines in mean fecundity and survival, suggesting that factors affecting mean demographic rates could be more important than local edge effects. Some methods of timber harvest may be compatible with the conservation of forest-interior birds, but better demographic data and information on habitat suitability of selectively cut forests and young even-aged stands is needed to adequately evaluate management options.     

Invasion dynamics of the varnish clam (Nuttallia obscurata): a matrix demographic modeling approach

Marine invaders have become a significant threat to native biodiversity and ecosystem function. In this study, the invasion of the varnish clam (Nuttallia obscurata) in British Columbia, Canada, is investigated using a matrix modeling approach to identify the life history characteristics most crucial for population growth and to investigate population differences. Mark-recapture analyses and field collections from 2003 to 2004 were used to determine individual growth, survival rates, and fecundity for two sites. A multi-state matrix model was used to determine population growth rates and to conduct sensitivity and elasticity analyses. A life table response experiment was also used to determine what life history stage contributed most to observed differences in population growth rates. Population survey data were used in conjunction with the matrix model to determine plausible recruitment levels and to investigate recruitment scenarios. Both populations are currently declining but are likely sustainable because of the pulsed nature of large recruitment events. Survival of larger clams (>40 mm) is the most important for population growth based on elasticity and sensitivity analyses. Adult survival also had the largest influence on observed differences between site-specific population growth rates. The two populations studied differed in recruitment dynamics; one experiencing annual recruitment with higher post-settlement mortality and the other, episodic recruitment and lower post-settlement mortality. The most influential factor for the successful invasion of the varnish clam appears to be survival of the larger size classes. Therefore, any process that decreases adult survival (e.g., predation, commercial harvest) will have the greatest impact on population growth.     

Spatio-temporal modeling of striped-bass egg, larval movement, and fate in the San Francisco Bay-Delta

Most models developed for the movement and fate of eggs and larvae of aquatic species are based on a particle tracking approach. Although this method has many advantages due to its high flexibility, particle tracking may become computationally intensive for complex geometries and when large numbers of particles are needed to simulate the population properly. In continuous models based on advection and dispersion mechanisms, the computational burden is independent of the size of the population. We developed a continuous fate and transport model for striped bass eggs and larvae in the San Francisco Bay-Delta. The model predicts the concentration of eggs and larvae at any location over time. The method of moments was used to account for the effect of temperature and age on the transition of eggs to larvae and larvae to juveniles. Egg and larval mortality were represented as functions of temperature, and eggs also experienced settling mortality. The fate and transport model used the same one-dimensional spatial grid as the existing Delta Simulation Model II (DSM2) hydrodynamics model. DSM2 output of flow rates, water depths, and cross-sectional areas were inputted into the fate and transport model to determine transport. The model was applied to striped bass eggs and larvae data collected during years 1990-1994; agreement between the modeled and the measured data was acceptable in most cases. Exploratory simulations were performed to demonstrate how the model could be used to evaluate the effects on egg and larval survival and total juvenile production of water diversions for supply and agricultural use and changes in the long-term mean water temperature. The model can be further used to examine the impact of various operation strategies in the San Francisco Bay-Delta, where diversion losses of early life stages of fishes remain a major management issue.     

Albatross populations in peril: a population trajectory for black-browed albatrosses at south Georgia.

Simulation modeling was used to reconstruct Black-browed Albatross (Diomedea melanophris) population trends. Close approximations to observed data were accomplished by annually varying survival rates, reproductive success, and probabilities of returning to breed given success in previous years. The temporal shift in annual values coincided with the start of longline fishing at South Georgia and potential changes in krill abundance. We used 23 years of demographic data from long-term studies of a breeding colony of this species at Bird Island, South Georgia, to validate our model. When we used annual parameter estimates for survival, reproductive success, and probabilities of returning to breed given success in previous years, our model trajectory closely followed the observed changes in breeding population size over time. Population growth rate was below replacement (lambda < 1) in most years and was most sensitive to changes in adult survival. This supports the recent IUCN uplisting of this species from "Vulnerable" to "Endangered." Comparison of pre-1988 and post-1988 demography (before and after the inception of a longline fishery in the breeding area) reveals a decrease in lambda from 0.963 to 0.910. A life table response experiment (LTRE) showed that this decline in lambda was caused mostly by declines in survival of adults. If 1988-1998 demographic rates are maintained, the model predicts a 98% chance of a population of fewer than 25 pairs within 78 years. For this population to recover to a status under which it could be "delisted," a 10% increase in survival of all age classes would be needed.     

Joint modelling of breeding and survival in the kittiwake using frailty models

Assessment of population dynamics is central to population dynamics and conservation. In structured populations, matrix population models based on demographic data have been widely used to assess such dynamics. Although highlighted in several studies, the influence of heterogeneity among individuals in demographic parameters and of the possible correlation among these parameters has usually been ignored, mostly because of difficulties in estimating such individual-specific parameters. In the kittiwake (Rissa tridactyla), a long-lived seabird species, differences in survival and breeding probabilities among individual birds are well documented. Several approaches have been used in the animal ecology literature to establish the association between survival and breeding rates. However, most are based on observed heterogeneity between groups of individuals, an approach that seldom accounts for individual heterogeneity. Few attempts have been made to build models permitting estimation of the correlation between vital rates. For example, survival and breeding probability of individual birds were jointly modelled using logistic random effects models by [Cam, E., Link, W.A., Cooch, E.G., Monnat, J., Danchin, E., 2002. Individual covariation in life-history traits: seeing the trees despite the forest. Am. Naturalist, 159, in press]. This is the only example in wildlife animal populations we are aware of. Here we adopt the survival analysis approaches from epidemiology. We model the survival and the breeding probability jointly using a normally distributed random effect (frailty). Conditionally on this random effect, the survival time is modelled assuming a lognormal distribution, and breeding is modelled with a logistic model. Since the deaths are observed in year-intervals, we also take into account that the data are interval censored. The joint model is estimated using classic frequentist methods and also MCMC techniques in Winbugs. The association between survival and breeding attempt is quantified using the standard deviation of the random frailty parameters. We apply our joint model on a large data set of 862 birds, that was followed from 1984 to 1995 in Brittany (France). Survival is positively correlated with breeding indicating that birds with greater inclination to breed also had higher survival.     

Projecting population trends of endangered amphibian species in the face of uncertainty: A pattern-oriented approach

Amphibian populations have been declining worldwide for the last three decades. Determining the risk of extinction is one of the major goals of amphibian conservation, yet few quantitative models have been developed for amphibian populations. Like most rare or threatened populations, there is a paucity of life history data available for most amphibian populations. Data on the critical juvenile life stage are particularly lacking. Pattern oriented modeling (POM) has been used successfully to estimate life history parameters indirectly when critical data lacking, but has not been applied to amphibian populations. We describe a spatially explicit, individual-based, stochastic simulation model developed to project population dynamics of pond-breeding amphibian populations. We parameterized the model with life history and habitat data collected for the endangered Houston toad (Bufohoustonensis), a species for which there is a high degree of uncertainty for juvenile and adult male survival. During model evaluation, we focused on explicitly reducing this uncertainty, evaluating 16 different versions of the model that represented the range of parametric uncertainty for juvenile and adult male survival. Following POM protocol, we compared simulation results to four population-level patterns observed in the field: population size, adult sex ratio, proportion of toads returning to their natal pond, and mean maximum distance moved. Based on these comparisons, we rejected 11 of the 16 model versions. Results of the remaining versions confirmed that population persistence depends heavily on juvenile survival, and further suggested that probability of juvenile survival is likely between 0.0075 and 0.015 (previous estimates ranged from 0.003 to 0.02), and that annual male survival is near 0.15 (previous estimates ranged up to 0.43).     

Robust, comparable population metrics through collaborative photo-monitoring of whale sharks Rhincodon typus.

The formulation of conservation policy for species that are rare and migratory requires broad cooperation to ensure that adequate levels of standardized data collection are achieved and that the results of local analyses are comparable. Estimates of apparent survival rate, relative change in abundance, and proportions of newly marked and returning individuals can inform local management decisions while highlighting corresponding changes at other linked research stations. We have applied computer-assisted photo-identification and mark-recapture population modeling to whale sharks Rhincodon typus at Ningaloo Marine Park (NMP), Western Australia, to create a baseline trend for comparison with other regional aggregations of the species. We estimate several ecological parameters of interest, including an average apparent survival rate of 0.55 yr(-1) for sharks newly marked (new) and 0.83 yr(-1) for sharks captured in multiple seasons (philopatric). The average proportion of philopatric sharks is found to be 0.65 of the total population, and we derive an average population growth rate of 1.12 yr(-1) for them. Our analysis uncovered significant heterogeneity in capture and survival probabilities in this study population; our chosen model structures and data analysis account for these influences and demonstrate a good overall fit to the time-series data. The results show good correspondence between capture probability and an available measure of recapture effort, suggesting that unmodeled systematic effects contribute insignificantly to the model fits. We find no evidence of a decline in the whale shark population at NMP, and our results provide metrics of value to their future management. Overall, our study suggests an effective approach to analyzing and modeling mark-recapture data for a rare species using computer-assisted photo-identification and opportunistic data collection from ecotourism to ensure the quality and volume of data required for population analysis.     

Hidden process models for animal population dynamics.

Hidden process models are a conceptually useful and practical way to simultaneously account for process variation in animal population dynamics and measurement errors in observations and estimates made on the population. Process variation, which can be both demographic and environmental, is modeled by linking a series of stochastic and deterministic subprocesses that characterize processes such as birth, survival, maturation, and movement. Observations of the population can be modeled as functions of true abundance with realistic probability distributions to describe observation or estimation error. Computer-intensive procedures, such as sequential Monte Carlo methods or Markov chain Monte Carlo, condition on the observed data to yield estimates of both the underlying true population abundances and the unknown population dynamics parameters. Formulation and fitting of a hidden process model are demonstrated for Sacramento River winter-run chinook salmon (Oncorhynchus tshawytsha).     

Spatial methods for plot-based sampling of wildlife populations

Classical sampling methods can be used to estimate the mean of a finite or infinite population. Block kriging also estimates the mean, but of an infinite population in a continuous spatial domain. In this paper, I consider a finite population version of block kriging (FPBK) for plot-based sampling. The data are assumed to come from a spatial stochastic process. Minimizing mean-squared-prediction errors yields best linear unbiased predictions that are a finite population version of block kriging. FPBK has versions comparable to simple random sampling and stratified sampling, and includes the general linear model. This method has been tested for several years for moose surveys in Alaska, and an example is given where results are compared to stratified random sampling. In general, assuming a spatial model gives three main advantages over classical sampling: (1) FPBK is usually more precise than simple or stratified random sampling, (2) FPBK allows small area estimation, and (3) FPBK allows nonrandom sampling designs.     

Incorporating diverse data and realistic complexity into demographic estimation procedures for sea otters.

Reliable information on historical and current population dynamics is central to understanding patterns of growth and decline in animal populations. We developed a maximum likelihood-based analysis to estimate spatial and temporal trends in age/sex-specific survival rates for the threatened southern sea otter (Enhydra lutris nereis), using annual population censuses and the age structure of salvaged carcass collections. We evaluated a wide range of possible spatial and temporal effects and used model averaging to incorporate model uncertainty into the resulting estimates of key vital rates and their variances. We compared these results to current demographic parameters estimated in a telemetry-based study conducted between 2001 and 2004. These results show that survival has decreased substantially from the early 1990s to the present and is generally lowest in the north-central portion of the population's range. The greatest temporal decrease in survival was for adult females, and variation in the survival of this age/sex class is primarily responsible for regulating population growth and driving population trends. Our results can be used to focus future research on southern sea otters by highlighting the life history stages and mortality factors most relevant to conservation. More broadly, we have illustrated how the powerful and relatively straightforward tools of information-theoretic-based model fitting can be used to sort through and parameterize quite complex demographic modeling frameworks.     

Assessing plausible rates of population growth in humpback whales from life-history data

The rate of growth of any population is a quantity of interest in conservation and management and is constrained by biological factors. In this study, recent data on life-history parameters influencing rates of population growth in humpback whales, including survival, age at first parturition and calving rate are reviewed. Monte Carlo simulations are used to compute a distribution of rates of increase (ROIs) taking into account uncertainty in biological parameter estimates. Two approaches for computing juvenile survival are proposed, which taken into account along with other life-history data, resulted in the following estimates of the rate of population growth: Approach A: mean of 7.3%/year (95% CI = 3.5–10.5%/year) and Approach B: mean of 8.6%/year (95% CI = 5.0–11.4%/year). It is proposed that the upper 99% quantile of the resulting distribution of the ROI for Approach B (11.8%/year) be established as the maximum plausible ROI for humpback whales and be used in population assessment of the species. Possible sources of positive and negative biases in the present estimates are presented and include measurement error in estimation of life-history parameters, changes in the environment within the period these quantities are measured, density dependence or other natural factors. However, it is difficult to evaluate potential biases without additional data. The methods presented in this study can be applied to other species for which life-history parameters are available and are useful in assessing plausibility in the estimation of population growth rates from time series of abundance estimates.     

Interactive Effects of Water Diversion and Climate Change for Juvenile Chinook Salmon in the Lemhi River Basin (U.S.A.)

The combined effects of water diversion and climate change are a major conservation challenge for freshwater ecosystems. In the Lemhi Basin, Idaho (U.S.A.), water diversion causes changes in streamflow, and climate change will further affect streamflow and temperature. Shifts in streamflow and temperature regimes can affect juvenile salmon growth, movement, and survival. We examined the potential effects of water diversion and climate change on juvenile Chinook salmon (Oncorhynchus tshawytscha), a species listed as threatened under the U.S. Endangered Species Act (ESA). To examine the effects for juvenile survival, we created a model relating 19 years of juvenile survival data to streamflow and temperature and found spring streamflow and summer temperature were good predictors of juvenile survival. We used these models to project juvenile survival for 15 diversion and climate‐change scenarios. Projected survival was 42–58% lower when streamflows were diverted than when streamflows were undiverted. For diverted streamflows, 2040 climate‐change scenarios (ECHO‐G and CGCM3.1 T47) resulted in an additional 11–39% decrease in survival. We also created models relating habitat carrying capacity to streamflow and made projections for diversion and climate‐change scenarios. Habitat carrying capacity estimated for diverted streamflows was 17–58% lower than for undiverted streamflows. Climate‐change scenarios resulted in additional decreases in carrying capacity for the dry (ECHO‐G) climate model. Our results indicate climate change will likely pose an additional stressor that should be considered when evaluating the effects of anthropogenic actions on salmon population status. Thus, this type of analysis will be especially important for evaluating effects of specific actions on a particular species. Efectos Interactivos de la Desviación del Agua y el Cambio Climático en Individuos Juveniles de Salmón Chinook en la Cuenca del Río Lemhi (E.U.A.)     

Robust population management under uncertainty for structured population models.

Structured population models are increasingly used in decision making, but typically have many entries that are unknown or highly uncertain. We present an approach for the systematic analysis of the effect of uncertainties on long-term population growth or decay. Many decisions for threatened and endangered species are made with poor or no information. We can still make decisions under these circumstances in a manner that is highly defensible, even without making assumptions about the distribution of uncertainty, or limiting ourselves to discussions of single, infinitesimally small changes in the parameters. Suppose that the model (determined by the data) for the population in question predicts long-term growth. Our goal is to determine how uncertain the data can be before the model loses this property. Some uncertainties will maintain long-term growth, and some will lead to long-term decay. The uncertainties are typically structured, and can be described by several parameters. We show how to determine which parameters maintain long-term growth. We illustrate the advantages of the method by applying it to a Peregrine Falcon population. The U.S. Fish and Wildlife Service recently decided to allow minimal harvesting of Peregrine Falcons after their recent removal from the Endangered Species List. Based on published demographic rates, we find that an asymptotic growth rate lambda > 1 is guaranteed with 5% harvest rate up to 3% error in adult survival if no two-year-olds breed, and up to 11% error if all two-year-olds breed. If a population growth rate of 3% or greater is desired, the acceptable error in adult survival decreases to between 1% and 6% depending of the proportion of two-year-olds that breed. These results clearly show the interactions between uncertainties in different parameters, and suggest that a harvest decision at this stage may be premature without solid data on adult survival and the frequency of breeding by young adults.     

Synergistic influences of phase, density, and climatic variation on the dynamics of fluctuating populations

Although ecologists have long recognized that certain mammalian species exhibit high-amplitude, often multiannual, fluctuations in abundance, their causes have remained poorly understood and the subject of intense debate. A key contention has been the relative role of density-dependent and density-independent processes in governing population dynamics. We applied capture-mark-recapture analysis to 25 years of monthly trapping data from a fluctuating prairie vole Microtus ochrogaster population in Illinois, USA, to estimate realized population growth rates and associated vital rates (survival and recruitment) and modeled them as a function of vole density and density-independent climatic variation. We also tested for phase dependence and seasonality in the effects of the above processes. Variation in the realized population growth rate was best explained by phase-specific changes in vole density lagged by one month and mean monthly temperatures with no time lags. The underlying vital rates, survival and recruitment, were influenced by the additive and interactive effects of phase, vole density, and mean monthly temperatures. Our results are consistent with the observation that large-scale population fluctuations are characterized by phase-specific changes in demographic and physiological characteristics. Our findings also support the growing realization that the interaction between climatic variables and density-dependent factors may be a widespread phenomenon, and they suggest that the direction and magnitude of such interactive effects may be phase specific. We conclude that density-dependent and density-independent climatic variables work in tandem during each phase of density fluctuations to drive the dynamics of fluctuating populations.     

Fitting probability models to population dynamics data

Methods for modeling population dynamics in probability using the generalized point process approach are developed. The life history of these populations is such that seasonal reproduction occurs during a short time. Several models are developed and analyzed. Data about two species: colonial spiders (Stegodyphus dumicola) and a migratory bird (wood thrush, Hylocichla mustelina) are used to estimate model parameters with appropriate log maximum likelihood functions. For the spiders, the model is fitted to provide evolutionary feasible colony size based on maximum likelihood estimates of fecundity and survival data. For the migratory bird species, a maximum likelihood estimates are derived for the fecundity and survival rates of young and adult birds and immigration rate. The presented approach allows computation of quantities of interest such as probability of extinction and average time to extinction.     

Use of individual-based models for population parameters estimation

A method for parameters estimation of stage-specific mortality and fecundity rate functions in poikilotherm organisms, and in particular for arthropod structured population, is proposed. The application of this method requires three types of information: stage-frequency data of a sampled population, development rate function and time evolution of forcing variables affecting the rate functions. By means of an individual-based model (a microscopic model) the number of eggs produced by the adults is generated starting from the number of individuals collected at each sampling time. Using a compartmental model (a macroscopic model) a stage-structured population dynamics is described and compared with observations. Non-linear regression methods based on least square principle are used to estimate the optimal parameters of the mortality and fecundity rate functions combining microscopic and macroscopic models. As a case study, the parameter estimation of the temperature-dependent mortality function of olives fruit fly Bactrocera oleae is presented.     

Modelling environmental stochasticity in adult survival for a long-lived species

Stochastic matrix population models are often used to help guide the management of animal populations. For a long-lived species, environmental stochasticity in adult survival will play an important role in determining outcomes from the model. One of the most common methods for modelling such stochasticity is to randomly select the value of adult survival for each year from a distribution with a specified mean and standard deviation. We consider four distributions that can provide realistic models for stochasticity in adult survival. For values of the mean and standard deviation that cover the range we would expect for long-lived species, all four distributions have similar shapes, with small differences in their skewness and kurtosis. This suggests that many of the outcomes from a population model will be insensitive to the choice of distribution, assuming that distribution provides a realistic model for environmental stochasticity in adult survival. For a generic age-structured model, the estimate of the long-run stochastic growth rate is almost identical for the four distributions, across this range of values for the mean and standard deviation. Model outcomes based on short-term projections, such as the probability of a decline over a 20-year period, are more sensitive to the choice of distribution.     

An architectural model of spring wheat: Evaluation of the effects of population density and shading on model parameterization and performance

ADELwheat is an architectural model that describes development of wheat in 3D. This paper analyzes the robustness of the parameterization of ADELwheat for spring wheat cultivars in relation to plant population density and shading. The model was evaluated using data from two spring wheat experiments with three plant population densities and two light regimes. Model validation was done at two levels of aggregation: (a) by comparing parameterization functions used as well as parameter values to the data (leaf and tiller appearance, leaf number, blade dimensions, sheath length, internode length) and (b) by comparing ground cover (GC) and leaf area index (LAI) of simulated virtual wheat plots with GC and LAI calculated from data. A sensitivity analysis was performed by modulating parameters defining leaf blade dimensions and leaf or tiller appearance rate.In contrast to population density, shading generally increased phyllochron and delayed tiller appearance. Both at the level of the organ and at the level of the canopy the model performed satisfactorily. Parameterization functions in the model that had been established previously applied to independent data for different conditions; GC and LAI were simulated adequately at three population densities. Sensitivity analysis revealed that calibration of phyllochron and blade area needs to be accurate to prevent disproportional deviations in output.The robustness of the model parameterization and the simulation performance confirmed that the model is a complete architectural model for aboveground development of spring wheat. It can be used in studies that require simulation of spring wheat structure, such as studies on plant–insect interaction, remote sensing, and light interception.