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.     

运用模糊数学和灰色系统理论分析评价夏播花生区试品种

运用模糊数学和灰色系统理论，对2007年河南省夏播花生区试品种进行了多因素综合评价和分析，结果表明：周花4号评价指标是0．7089，综合表现最优；其次是W9847—1—3—4—1，其综合评价指标是0．6352；豫花6号评价指标是0．3630，综合表现最差。此结果与试验地实际表现基本相一致。     

DYNAMIC MODELS OF AQUIFEROUS CONTENT OF LIVING FUELS

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

大豆灰斑病Fuzzy测报模型

本文运用模糊数学理论建立了大豆灰斑病预测预报模型。经对国营350农场种植的大豆中熟品种“合丰25”十年的资料拟合,符合率达90%,对中熟品种“黑农26”九年的资料拟合,符合率达89%,对早熟品种“黑河3号”九年的资料拟合,符合率达78%。     

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。     

企业家生成机制的博弈分析

研究了在企业家生成过程中,企业家之间由于行为的互动性而引起的均衡结果的变化,以及均衡结果的协调,达到帕累托最优的问题.     

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.     

景观生态学原理与方法在荒漠化研究中应用的理论分析

荒漠化发生发展的过程实际上是指在自然和人为因素的作用下，生态系统结构遭受破坏、功能过程受阻和演变发生异化的过程，其防治的根本措施是恢复和重建健康的生态系统。所以，景观生态学理念在荒漠化的研究和防治中有着重要的意义。本文从荒漠化与生态系统结构、功能变化、荒漠化与生物多样性、荒漠化生态系统的物质循环和能量流动以及荒漠化生态系统的稳定性等方面论述了景观生态学理念在荒漠化研究中应用的可行性，并重点分析了景观生态学关于景观格局变化的评价指标与荒漠化土地动态变化之间的关系。