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…     

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。     

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.     

利用体外培养法建立饲料营养成分与瘤胃丙酸产量的回归模型

根据美国康乃尔净碳水化合物和蛋白质体系 (CNCPS) ,分析测定了 4类 2 4种饲料的营养成分 ,利用体外批次培养技术测定了它们在体外培养一定时间后的丙酸产量 ,并由此建立了饲料中产丙酸的营养成分和瘤胃丙酸产量的回归方程     

基于GFM和GAMM模型分析对虾白斑综合征(WSSV)对黄海和东海北部水域虾类生物量的影响

虾类是海洋生态系统功能群的重要组成部分,其生物量变化受到多重因素的影响。本研究在开展黄海和东海北部水域虾类白斑综合征病毒(white spot syndrome virus, WSSV)流行病学调查的基础上,利用梯度随机森林模型(gradient random forest model, GFM)和广义加性混合模型(generalized additive mixed models, GAMM),分析了2016—2018年间黄海和东海北部水域WSSV流行对虾类生物量的影响。分子检测结果显示,调查所获取的26种虾类中,11种被检测为WSSV阳性;2016、2017和2018年WSSV阳性采样站点的比率分别为48.40%、38.75%和21.74%,虾类样品中WSSV阳性检出比率分别为16.86%、9.60%和4.80%。GFM模型分析显示,解释变量“阳性样品数的对数(ln_posi)”对响应变量“虾类生物量的对数(ln_Abu)”的重要性最高。GAMM分析中,根据赤池信息准则(Akaike information criterion, AIC)最小原则筛选出的最优模型为：ln_Abu~WSSV阳性率(P_rate)+ln_posi+经度(Long),该模型中ln_posi和P_rate是影响虾类生物量的极显著相关因子,ln_Abu随着P_rate的升高而降低。研究表明,WSSV在黄海和东海北部水域虾类中流行,推测对该海域的虾类生物量存在影响。     

基于GAM的长江口鱼类资源时空分布及影响因素

根据2006至2017年长江口及其邻近海域鱼类资源调查,运用广义加性模型研究长江口鱼类资源密度与环境因子之间的关系,并对2017年鱼类资源密度的时空分布进行预测。结果显示,春夏秋冬四个季节最佳GAM偏差解释率分别为69.6%、55.9%、51.4%和47.4%,交叉验证回归线斜率的平均效应为0.62～0.88。盐度、水温和溶解氧是影响长江口鱼类资源密度的主要环境影响因子且在不同季节对鱼类资源密度有不同的影响机制。总体上,在春、夏、秋季,盐度与鱼类资源密度之间存在正向相关性;在夏、秋、冬季,水温对鱼类资源密度有显著影响,在秋季与鱼类资源密度之间存在正向相关性;在春、秋、冬季,溶解氧对鱼类资源密度有显著影响,在冬季与鱼类资源密度之间存在正向线性相关。研究表明,2017年夏季鱼类资源密度较高;在长江口南支的自然延伸水域存在鱼类资源密度的相对低值,在崇明岛向海自然延伸方向水域存在鱼类资源密度的相对高值。后续研究将对长江口鱼类资源进行不同生态类型区分,以期更加准确地掌握影响各生态类型鱼类时空分布的环境因素及其时空分布信息。