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.     

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。     

小麦条锈病气象预测方法及遥感监测研究进展

从影响小麦条锈病发生发展的大尺度气候背景、局地气象因子两方面,对小麦条锈病发生发展的气象预测研究进行了综述,指出了常规预测方法存在的问题和难点。概述了高光谱遥感在小麦条锈病监测中的应用,并对遥感与作物模型的结合进行了探讨,在此基础上展望了基于大气环流的小麦条锈病中、长期预测及G IS辅助的遥感技术在小麦条锈病监测方面的应用前景。     

贵州烟区烟蚜发生规律及其预测模型的初步研究

通过2002-2008年对贵州代表性烟区烟蚜的系统调查,初步了解了有翅蚜迁飞规律、烟田蚜虫种群消长动态及其历史演变情况,分析了烟蚜发生期内气温、雨日雨量、相对湿度和日照时数对烟蚜发生量的影响效应。在此基础上,结合以往的调查数据,应用DPS统计软件进行逐步回归分析,初步建立了烟蚜发生程度短期预测模型Y=-24.87+1.27X1+0.13X2+1.54X4+2.70X6+4.06X11-3.85X13(其中,X1=移栽前期10 d内日诱蚜量;X2=上年12月日气温≥10℃的积温;X4=2月均温;X6=3月均温;X11=4月均温,X13=4月雨日数),经显著性检验和预报验证,回归方程达极显著水平,回测准确率平均达93.45%,实报验证误差率仅为1.80%~5.11%,说明入选预报因子比较切合贵州实际,预测模型具有较大的实用价值。     

遗传算法优化神经网络的坡面入渗产流模型

引入遗传算法优化BP神经网络权重和阈值的方法建立黄土坡面产流入渗模型.模型以雨强、降雨历时、表层40 cm土壤前期含水量、坡度值为输入项,径流量、入渗量为输出项,用实测资料对网络进行模拟和预测.模拟结果平均误差6.32%和1.93%,预测结果平均误差为5.71%和1.92%.并与传统BP神经网络模型和定雨强Philip...     

新疆呼图壁河径流时间序列分析

基于呼图壁河石门水文站1956—2011年的年径流数据,采用Morlet小波分析和R/S分析方法,对新疆呼图壁河流域径流周期、变化特征和未来趋势进行分析和预测。研究结果表明:(1)通过对呼图壁河1956—2011年径流量的分析发现,径流时间序列存在5 a、10 a、18 a和28 a左右的震荡周期,18 a尺度震荡周期最强,其次是28a尺度。18 a时间尺度上的震荡在56 a研究时段内均较强,且存在4个丰水期和5个枯水期;28 a震荡周期在56 a尺度时段内相对较强,存在3个丰水期和3个枯水期,目前处于偏丰期;(2)利用R/S分析呼图壁河径流量序列,Hurst指数为0.6442,存在明显的赫斯特现象,这就意味着未来一段时间的径流量与过去具有同样的增加趋势。     

Distribution and diversity of leaf-cutting ants in Northeastern Argentina: species most associated with forest plantations

Abstract

Leaf-cutting ants (LCA) are considered one of the main herbivores and one of the most destructive pest insects of the Neotropics. Northeastern Argentina harbors the greatest species richness of these ants and in turn comprises the highest surface with forest plantations. Our aim was to establish which species of leaf-cutting ants are most commonly associated with forest plantations by analyzing their geographic distribution using published and unpublished species occurrence data. Also, estimate their potential areas of distribution along a latitudinal gradient that entirely encompasses northeastern Argentina using Ecological Niche Modeling. Only seven of the 20 species recorded were strongly associated with productive systems along the gradient, but only 2–3 species in each region could be considered high-risk species for forest plantations. High-risk species composition shows a turnover between regions. Our models show the potential distribution areas where LCA could become more abundant and dominant, and possibly causing a detrimental effect on the forest plantations in the studied region. We find that ecological niche models are useful tools to assess the environmental suitability of important LCA.