A context for recruitment correlations: why marine fisheries biologists should still look for them

In many cases when ecologists want to investigate a process, they often look for the best system on which to conduct the research, "best" meaning that the possibility of discovering mechanisms is optimized or made easier in some way. In fisheries we do it backwards. The species and system are given to us by economics, and we then fly in the face of the difficult circumstances to find mechanisms that are elusive anyway. These difficult circumstances constitute in some sense the first set of statistical problems. Using examples from the Northeast Pacific, I review the characteristics of cohort time series that make some species more tractable; propose a conscious process of conceptualization to assist in the formulation of clear, germane hypotheses; highlight the contrast between modeling in the sense of statistical fitting versus simulation models of processes; explore how the first round of models integrates with the second round of planning for new data collection at sea and in the lab; and, finally, propose how to judge success in terms of an operational approach.     

Evaluation of two N cycle models for the prediction of N mineralization from grassland soils in the UK

Abstract. The ability of two nitrogen cycle models, of contrasting complexity, to predict N mineralization from a range of grassland soils in the UK, was evaluated. These were NCYCLE, a simple mass balance model of the N cycle in UK grasslands, and CENTURY, a more complex model simulating long-term C, N, P & S dynamics in grassland ecosystems. The models were tested using field measurements of net N mineralization from a range of grassland soils (differing in soil type, history & management practice), obtained over a 2 year period using a soil core incubation technique. This method was considered to measure the total net release of mineral N from the soil organic matter over a specified time, including N which may have been recycled several times. NCYCLE consistently under-estimated mineralization rates at all sites. By contrast, there was some correlation between CENTURY predictions of net N mineralization and field measurements. This may have reflected the different abilities of the two models to simulate N recycling. Neither model, however, was able to predict adequately the effect of cultivation and reseeding on net N mineralization.     

DYNAMIC MODELS OF AQUIFEROUS CONTENT OF LIVING FUELS

RESEARCHSITELivingfue1splayedanimportantroleinheatconcentrationactionorinheatsourceofforestfire.Whenitshumiditydecreasestoacertainlevel,theybecameaheatsourcewhenthelivingcombustibl-eswerecombinedwithfire.Thus,itwasessentialhowtodeterminethemoisturesituationandthefOrestfiredangerdegreetobeforecastedaccurately.Thedynamicmodelspresentedinthispaperwereusefultosolvethisproblem.Everyyear,-therewerealotofforestfires,especiallythefireoccurrenceinDaxinganMountains,inthespringofl987.Itwasveryimpo…     

区域证券市场发展潜力评价模型的建立及实证分析

建立了评价区域证券市场发展潜力的数学模型－定权聚类评估模型，并对河南各地区证券发展潜力进行了实证研究。     

线性规划模型在农村能源建设中的运用

本文分析了线性规划模型在农村能源开发利用中运用的必要性和可行性。系统阐述了如何将农村能源多元结构的优化问题表达为线性规划数学模型，并以四川米易县农村能源开发利用优化设计为例进行了分析求解。     

维酶素生产菌阿舒假囊酵母的发酵培养基优选

本研究采用二次通用旋转组合回归设计方法，对维酶素发酵培养基豆腐渣中添加麦麸、小米和玉米粉的最优化组合进行定量研究。建立了维酶素产量形成的培养基的反应模式，利用回归模式对培养基的最优化组合和各单因子要素反应规律及其互作效应进行了探讨。     

刺槐单株生物量动态研究

本文依据420株刺槐生物量及23株树干解析资料,应用灰色Verhulst模型,对太行山坡地刺槐林单株干、枝、叶、根生物量动态进行了研究,分别建立了预测模型,预测了各器官生长的速生期和停止生长林龄,为实现刺槐林的多目标经营提供决策依据。     

一类挖坑机械钻头横向振动系统的最优控制问题

建立了一类挖坑机械钻头横向振动系统的数学模型,并以阻尼函数作为控制变量,研究了该系统的最优控制问题,得出了两个定理。     

Predicting the spatial distribution of ground flora on large domains using a hierarchical Bayesian model

Accomodation of important sources of uncertainty in ecological models is essential to realistically predicting ecological processes. The purpose of this project is to develop a robust methodology for modeling natural processes on a landscape while accounting for the variability in a process by utilizing environmental and spatial random effects. A hierarchical Bayesian framework has allowed the simultaneous integration of these effects. This framework naturally assumes variables to be random and the posterior distribution of the model provides probabilistic information about the process. Two species in the genus Desmodium were used as examples to illustrate the utility of the model in Southeast Missouri, USA. In addition, two validation techniques were applied to evaluate the qualitative and quantitative characteristics of the predictions.This revised version was published online in May 2005 with corrections to the Cover Date.     

Landscape patterns as habitat predictors: building and testing models for cavity-nesting birds in the Uinta Mountains of Utah,USA

The ability to predict species occurrences quickly is often crucial for managers and conservation biologists with limited time and funds. We used measured associations with landscape patterns to build accurate predictive habitat models that were quickly and easily applied (i.e., required no additional data collection in the field to make predictions). We used classification trees (a nonparametric alternative to discriminant function analysis, logistic regression, and other generalized linear models) to model nesting habitat of red-naped sapsuckers (Sphyrapicus nuchalis), northern flickers (Colaptes auratus),tree swallows (Tachycineta bicolor), and mountain chickadees (Parus gambeli) in the Uinta Mountains of northeastern Utah, USA. We then tested the predictive capability of the models with independent data collected in the field the following year. The models built for the northern flicker, red-naped sapsucker, and tree swallow were relatively accurate (84%, 80%, and 75% nests correctly classified,respectively)compared to the models for the mountain chickadee (50% nests correctly classified). All four models were more selective than a null model that predicted habitat based solely on a gross association with aspen forests. We conclude that associations with landscape patterns can be used to build relatively accurate, easy to use, predictive models for some species. Our results stress, however, that both selecting the proper scale at which to assess landscape associations and empirically testing the models derived from those associations are crucial for building useful predictive models. This revised version was published online in July 2006 with corrections to the Cover Date.