Increasing the Accuracy of Productivity and Survival Estimates in Assessing Landbird Population Status

Abstract:  The conservation of species with declining populations requires information on population demography and identification of factors that limit population growth. For landbird species, an understanding of large-scale population declines often requires assessment of local population processes, including the production of offspring, the survival of those offspring, and adult survival. Population growth has been modeled for several species of landbirds to date, and these studies have provided important information on relationships between population status and population-limiting factors. Several recent studies have illuminated field methods and analytical techniques that can aid in increasing the accuracy of productivity and survival estimates for population models. We reviewed these methods and recommend their implementation, including quantification of the season-long productivity of individuals, collection of empirical data on juvenile survival during the postfledging and overwintering periods, and incorporation of adult breeding dispersal into annual adult survival estimates. Such methods will allow for more accurate assessment of population status and provide a better understanding of the factors on which to focus our conservation efforts.     

The effect of patch constellation on the exchange of individuals between habitat-islands

Metapopulation models assume that inter-patch dispersal dominantly depends on distance between patches and the dispersal capability of organisms in question. We used a spatially explicit, individual-based model to investigate the potential effect of patch constellation on the exchange of individuals between patches. We simulated migration of individuals from a start- into a target-patch with both patches having the same size and shape. Simulation experiments were carried out for four patch constellations and two different movement patterns. Our results demonstrate a substantial effect of patch constellation on the exchange of individuals. They also show that the magnitude and even the direction of this effect crucially depends on their movement pattern. We conclude that particularly for highly correlated movement patterns patch shape and constellation can not readily be ignored when modelling inter-patch dispersal between habitat-islands.     

treedyn3 forest simulation model

The treedyn3 forest simulation model is a process model of tree growth, carbon and nitrogen dynamics in a single-species, even-aged forest stand. It is based on the treedyn model. Major changes include the computation of sun angle and radiation as a function of latitude and day of the year, the closed-form integration of canopy production as a function of day and hour, the introduction of tree number, height, and diameter as separate state variables, and different growth strategies, mortalities, and resulting self-thinning as function of crowding competition.The tree/soil system is described by a set of nonlinear ordinary differential equations for the state variables: tree number, base diameter, tree height, wood biomass, nitrogen in wood, leaf mass, fine root mass, fruit biomass, assimilate, carbon and nitrogen in litter, carbon and nitrogen in soil organic matter, and plant-available nitrogen. The model includes explicit formulations of all relevant ecophysiological processes such as: computation of radiation as a function of seasonal time, daytime and cloudiness, light attenuation in the canopy, and canopy photosynthesis as function of latitude, seasonal time, and daytime, respiration of all parts, assimilate allocation, increment formation, nitrogen fixation, mineralization, humification and leaching, forest management (thinning, felling, litter removal, fertilization etc.), temperature effects on respiration and decomposition, and environmental effects (pollution damage to photosynthesis, leaves, and fine roots). Only ecophysiological parameters which can be either directly measured or estimated with reasonable certainty are used. treedyn3 is a generic process model which requires species- and site-specific parametrization. It can be applied to deciduous and coniferous forests under tropical, as well as temperate or boreal conditions.The paper presents a full documentation of the mathematical model as well as representative simulation results for spruce and acacia.     

柠檬酸固态发酵过程的研究

本文研究了以甘薯为原料，以黑曲霉为菌种，固态发酵制柠檬酸的最佳发酵条件和发酵动力学。探讨了接种方式、灭菌与否以及温度、含水量、ｐＨ值、颗粒度、通气速率等因素对柠檬酸固态发酵过程的影响，提出了适宜的发酵参数。在此基础上，进一步研究甘薯固态发酵制取柠檬酸的动力学模型，确定了模型参数与操作条件的关系。该模型反映了基质消耗、产物生成、菌体生长及ＣＯ２释放速率的变化过程和温度、颗粒度的影响。模型的模拟结果与     

Extending the Dewanji and Kalbfleisch model to incorporate marker data

The model of Dewanji and Kalbfleisch for the estimation of time to tumour onset from a serial-sacrifice experiment is extended to include a marker state prior to the onset of the tumour. There are two versions of the model, one where a tumour is allowed to develop without the onset of marker, the other where a tumour develops after the marker but in which the marker later becomes unobservable.     

A general model for tagging on multiple component fisheries: an integration of age-dependent reporting rates and mortality estimation

A major objective of analyzing multiple year tag return data in fisheries is to estimate fishing and natural mortality rates which may vary by age class and calendar year. To do this one needs to be able to estimate the reporting rates for the tags recovered. Some fisheries such as that for Southern Bluefin Tuna (Thunnus maccoyii) have multiple components with potentially different reporting rates for the tag returns. In this paper we develop a general model for multi-cohort, multi-year tag return analyses where there are multiple components to the fishery with potentially different reporting rates. We require the assumption that one component has a reporting rate of 100% (i.e., this could be the component of a boat based fishery where scientific observers are present). We show further how it is possible to partition the overall likelihood developed into two conditionally independent components. The first component of the likelihood is the standard multinomial likelihood that allows estimation of fishing and natural mortality rates. It uses the tag return matrix summed over all the components of the fishery. It requires an average reporting rate for the tag returns (where the average reporting rate is a weighted average of the individual reporting rates of the different components). The second component is also multinomial for the individual component tag returns and allows us to estimate individual component reporting rates. However, this requires that we augment our second component tag return likelihood with a catch data likelihood for the corresponding components. The methodology is illustrated on some Southern Bluefin Tuna tagging and catch data. We also discuss important model assumptions and give suggestions for future research including the integration of tag-return and catch at age data analyses.     

Direct calculation of likelihood-based benchmark dose levels for quantitative responses

A benchmark dose (BMD) for quantitative responses is a lower confidence limit (LCL) on the effective dose corresponding to a specified risk level r. A commonly adopted method for calculating the BMD is to obtain a pointwise upper confidence curve U(d) on the risk function and then invert this relationship by solving the equation U(d)=r. The solution d is taken to be the BMD. Sciullo et al. (2000) have shown that the coverage achieved by this inversion method is at least as great as the coverage achieved by U (·) but that there is otherwise no general relationship between the two coverage probabilities. The present paper develops a method for direct calculation of the BMD based on the asymptotic distribution of the likelihood ratio statistic. It is further shown that the direct method and the inversion method are equivalent when U (·) is also based on the likelihood ratio. Since the direct method is known to be asymptotically correct, it follows that the LR-based inversion method is also asymptotically correct. However, the direct method is computationally faster and easier to program. Finally, some simulation studies are conducted to assess the small sample coverage probabilities of the direct method when responses follow either a normal or a gamma distribution.     

Modelling heterogeneity in the recoveries of marked animal populations with covariates of individual animals, groups of animals or recovery time

A general framework is developed for modelling rates of survival and recovery of marked animal populations in terms of auxiliary information collected at the time of marking. The framework may be used to estimate differences in survival or recovery among individual animals, groups of animals, and recovery times. Analyses of the recoveries of tagged fish and banded bird populations are used to illustrate the specification and selection of various models.     

A weight-adjusted Peto’s test when cause of death is not assigned

A new statistical testing approach using a weighted logrank statistic is developed for rodent tumorigenicity assays that have a single terminal sacrifice but not cause-of-death data. Instead of using cause-of-death assignment by pathologists, the number of fatal tumors is estimated by a constrained nonparametric maximum likelihood estimation method. For data lacking cause-of-death information, the Peto test is modified with estimated numbers of fatal tumors and a Fleming–Harrington-type weight, which is based on an estimated tumor survival function. A bootstrap resampling method is used to estimate the weight function. The proposed testing method with the weight adjustment appears to improve the performance in various situations of single-sacrifice animal experiments. A Monte Carlo simulation study for the proposed test is conducted to assess size and power of the test. This testing approach is illustrated using a real data set.