A probability-based approach to setting annual catch levels.

The requirement of setting annual catch limits to prevent overfishing has been added to the Magnuson-Stevens Fishery Conservation and Management Reauthorization Act of 2006 (MSRA). Because this requirement is new, a body of applied scientific practice for deriving annual catch limits and accompanying targets does not yet exist. This article demonstrates an approach to setting levels of catch that is intended to keep the probability of future overfishing at a preset low level. The proposed framework is based on stochastic projection with uncertainty in population dynamics. The framework extends common projection methodology by including uncertainty in the limit reference point and in management implementation, and by making explicit the risk of overfishing that managers consider acceptable. The approach is illustrated with application to gag (Mycteroperca microlepis), a grouper that inhabits the waters off the southeastern United States. Although devised to satisfy new legislation of the MSRA, the framework has potential application to any fishery where the management goal is to limit the risk of overfishing by controlling catch.

User’s Guide to ADMB2R: A Set of AD Model Builder Output Routines Compatible with the R Statistics Language

ADMB2R is a collection of AD Model Builder routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 ADMB2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the ADMB2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer ADMB2R to others in the hope that they will find it useful. (PDF contains 30 pages)

User’s Guide to C2R: A Set of C Language Output Routines Compatible with the R Statistics Language

C2R is a collection of C routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 C2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the C2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer C2R to others in the hope that they will find it useful. (PDF contains 27 pages)

User’s Guide to For2R: A Module of Fortran 95 Output Routines Compatible with the R Statistics Language

For2R is a collection of Fortran routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 For2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the For2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer For2R to others in the hope that they will find it useful. (PDF contains 31 pages)

土的本构模型及其工程应用

第一章 绪论
1、1土的本构特性
1、2土本构模型的发展简史
1、3土本构模型的研究动向
2、1应力分析
第二章 连续介质力学的基本概念
2、1、1一点的应力状态、应力张量
2、1、2Cauchy公式、求和协定
2、1、3主应力
2、1、4偏应力
2、1、5八面体应力、纯剪应力、主剪应力
2、1、6应力空间、应力路径
2、1、7应力Mohr圆和应力Lode参数
2、2应变分析
2、2、1一点的应变状态、应变张量
2、2、2应变Cauchy公式
2、2、3主应变
2、2、4偏应变
2、2、5八面体应变、纯应变、主剪应变
2、2、6应变空间、应变路径
2、2、7应变率张量、应变增量张量
2、2、8应变Mohr圆
2、2、9有限应变
2、3基本方程
2、3、1连续方程
2、3、2运动微分方程
2、3、3协调方程
2、3、4能量方程
2、3、5本构方程
2、3、6边界条件和初始条件
第三章 经典塑性理论简述
3、1屈服准则
3、1、1初始屈服
3、1、2后继屈服
3、1、3几种屈服条件
3、2加载和卸载准则
3、2、1理想塑性材料的加载和卸载
3、2、2硬化材料的加载和卸载准则
3、3硬化规律
3、3、1各向同性硬化模型
3、3、2随动硬化模型
3、3、3混合硬化模型
3、4塑性公设
3、4、1Drucker塑性公设
3、4、2Ильюшин塑性公设
3、5流动规则
3、5、1塑性位势理论的基本概念
3、5、2流动规则
3、6塑性形变理论与塑性增量理论
3、6、1塑性形变理论
3、6、2塑性增量理论
第四章 土的弹性本构模型
4、1线弹性模型
4、1、1广义Hook定律
4、1、2正交各向异性线弹性体
4、1、3横观各向同性线弹性体
4、1、4各向同性线弹性体
4、2应变能和应变余能
4、3能量正定性与弹性材料稳定性
4、4具有割线模量的非线性弹性模型
4、4、1全量型应力—应变关系
4、4、2增量型应力—应变关系
4、5Cauchy弹性模型
4、5、1全量型Cauchy弹性模型应力—应变关系
4、5、2增量型Cauchy弹性模型应力—应变关系
4、6超弹性模型
4、6、1全量型超弹性模型应力—应变关系
4、6、2增量型超弹性模型的应力—应变关系
4、7次弹性模型
4、8结语
5、1本构关系的普遍表达式
第五章 土的弹性—理想塑性模型
5、2本构模型中材料常数的确定
5、3本构模型的数值计算
5、4Prandtl—Reuss模型
5、5Drucker—Prager模型
5、6Coulomb模型
6、1本构关系的普遍表达式
第六章 土的弹性—硬化塑性模型
6、2剑桥模型
6、3修正剑桥模型
6、4Lade—Duncan模型
6、5帽盖模型
6、5、1一般增量应力—应变关系与刚度矩阵的推导
6、5、2模型的拟合过程
6、5、3帽盖模型的数值计算
第七章 土的粘弹塑性模型
7、1土的流变学基本模型
7、2Maxwell体模型
7、3Kelvin体模型
7、4粘塑性体模型
7、5三元模型
7、6多元件组合模型
8、1弹塑性横观各向同性模型
第八章 土本构模型的近期发展
8、2非线性弹性—硬化塑性帽盖模型
8、3弹/粘塑性动态帽盖模型
8、4多重屈服面模型
8、5边界面模型
8、6内时本构方程
9、1基础的沉降与塌陷
第九章 土本构模型在工程中的应用
9、1、1具有不同材料常数的Drucker—Prager模型
9、1、2具有非相关联流动的Drucker—Prager模型
9、1、3具有相关流动的帽盖模型
9、2堤坝的非线性分析
9、3基坑开挖的非线性分析
9、3、1基坑竣工后状况
9、3、2边坡对地震过程的响应
9、3、3地震后的滑移
参考文献

Population characteristics of gulf menhaden, Brevoortia patronus

The status of the Gulf menhaden, Brevoortia patronus, fishery was assessed with purse-seine landings data from 1946 to 1997 and port sampling data from 1964 to 1997. These data were analyzed to determine growth rates, biological reference points for fi shing mortality from yield per recruit and maximum spawning potential analyses, spawner-recruit relationships, and maximum sustainable yield (MSY). The separable virtual population approach was used for the period 1976–97 (augmented by earlier analyses for 1964–75) to obtain point estimates of stock size, recruits to age 1, spawning stock size, and fishing mortality rates. Exploitation rates for age-1 fi sh ranged between 11% and 45%, for age-2 fi sh between 32% and 72%, and for age-3 fi sh between 32% and 76%. Biological reference points from yield per recruit (F0.1: 1.5–2.5/yr) and spawning potential ratio (F20: 1.3–1.9/yr and F30: 0.8–1.2/yr) were obtained for comparison with recent estimates of F (0.6–0.8/yr). Recent spawning stock estimates (as biomass or eggs) are above the long-term average, while recent recruits to age 1 are comparable to the long-term average. Parameters from Ricker-type spawner-recruit relations were estimated, although considerable unexplained variability remained. Recent survival to age-1 recruitment has generally been below that expected based on the Ricker spawner-recruit relation. Estimates of long-term MSY from PRODFIT and ASPIC estimation of production model ranged between 717,000 t and 753,000 t, respectively. Declines in landings between 1988 and 1992 raised concerns about the status of the Gulf menhaden stock. Landings have fl uctuated without trend since 1992, averaging about 571,000 t. However, Gulf menhaden are short lived and highly fecund. Thus, variation in recruitment to age 1, largely mediated by environmental conditions, infl uences fi shing success over the next two years (as age-1 and age-2 fi sh). Comparisons of recent estimates of fi shing mortality to biological reference points do not suggest overfishing. (PDF file contains 22 pages.)