Quantifying uncertainty in the wild‐caught fisheries goal of the Ocean Health Index

Sustainability indices are proliferating, both to help synthesize scientific understanding and inform policy. However, it remains poorly understood how such indices are affected by underlying assumptions of the data and modelling approaches used to compute indicator values. Here, we focus on one such indicator, the fisheries goal within the Ocean Health Index (OHI), which evaluates the sustainable provision of food from wild fisheries. We quantify uncertainty in the fisheries goal status arising from the (a) approach for estimating missing data (i.e., fish stocks with no status) and (b) reliance on a data‐limited method (catch‐MSY) to estimate stock status (i.e., B/B_MSY). We also compare several other models to estimate B/B_MSY, including an ensemble approach, to determine whether alternative models might reduce uncertainty and bias. We find that the current OHI fisheries goal model results in overly optimistic fisheries goal statuses. Uncertainty and bias can be reduced by (a) using a mean (vs. median) gap‐filling approach to estimate missing stock scores and (b) estimating fisheries status using the central tendency from a simulated distribution of status scores generated by a bootstrap approach that incorporates error in B/B_MSY. This multitiered approach to measure and describe uncertainty improves the transparency and interpretation of the indicator and allows us to better understand uncertainty around our OHI fisheries model and outputs for country‐level interpretation and use.     

黄土高原半干旱区油松人工林林冠截留模型及其参数特征研究

利用2008—2011年定位观测数据,采用回归分析方法对黄土高原半干旱区油松人工林林冠截留与林外降雨之间的关系进行建模研究,并运用Bootstrap方法,对模型参数特征进行分析。结果表明:林冠截留量(I)与林外降雨量(P)可用非线性模型I=a Pb进行回归模拟,回归方程为I=0.584P0.576;该模型不仅具有较高的拟合精度,且拟合方程参数稳定性良好,经检验,方程均达到显著性要求,可在该区域油松人工林应用。     

STUDY ON SELF -SCANNING CIRCUIT OF LOW POWER DISSIPATION MOS IMAGE SENSOR

The paper studies a self- scanned circuit used in MOS image sensor with the demand of developing of high -order.low power disspation MOS image sensor and puts forward a kind of self -scanned circuit .which uses a three tramister dynamic nocomparing circuit whith a changing capacitor bootstrap circuit as MOS image sensor. The circuit adopted a silicon gote P -MOS technique, which is a high -speed low-dissipation dynamic no-coparing circuit. It is a practical unit circuit in the high -order array and solves the problem that the power dissipation of array rises with the increase of the array bite.     

森林资源监测Spot5遥感图像几何精校正方法研究

为探索空间分辨率为 2 5m的Spot5遥感图像用于森林资源监测的可行性 ,需进行遥感图像几何精校正 .该文在理论分析遥感图像校正模型的基础上 ,借助GPS虚拟网络参考站定位系统 ,以cm级精度测定校正遥感图像的地面控制点 ,通过实例计算 ,详细研究了在通用遥感图像处理软件ENVI、ERDAS及PCI中各种可能的几何精校正方法及实际精度状况 .综合考虑几何位置变换精度、灰度重采样精度及不同校正方法对地面控制点数量和分布的要求 ,结合林区Spot5遥感图像的特点和GPS定位现状 ,确定了适合森林资源调查的Spot5遥感图像几何精校正方法 .     

A method for calculating numerical estimates of gear selectivity curve

The present paper proposes a method for estimating the numerical curve of gear selectivity without the assumption of function of selectivity curve and estimating confidence intervals, using data of catch per unit effort at length for several nets of different mesh sizes obtained from fishing experiments. The paper assumes such geometric similarity as the selectivity is the same if the rate of fish length to mesh size is the same. The basic idea is due to a technique of numerical integration that uses the derivatives at various points. The natural logarithm of selectivity is expressed by an approximation equation using its cumulated derivatives. The values of derivatives at various lengths are calculated from the data. The confidence intervals are made from the bootstrap samples. The method was applied to the data of catch at length by mesh size of gill net for pink salmon Oncorhynchus gorbuscha . Data collection, modification and issues of the method are discussed.     

Roles of bootstrap resampling,measure of central tendency,and method for calculating thermal units when developing phenology models for pest management

The successful development of phenology models from field studies depends on many factors, some of which are entirely under the control of pest managers. For example, one such factor is the choice of method for calculating thermal units. In this study, we have demonstrated that four methods for calculating thermal units provided for acceptable predictions of one phenological event of one insect species, while another method for calculating thermal units did not. The measure of central tendency (mean or median) that is used to estimate lower developmental temperatures and required thermal summations is another factor that pest managers can control when developing phenology models from field studies. Here, we show that predictions that were made when using phenology models based on median lower developmental temperatures and median required thermal summations were superior to predictions that were made when using phenology models based on mean lower developmental temperatures and mean required thermal summations. The use of bootstrap vs. non-bootstrap estimates of lower developmental temperatures and required thermal summations is yet another factor that pest managers can control when developing phenology models from field studies. In this study, we found that calculating and using bootstrap estimates of lower developmental temperatures and required thermal summations in phenology models did not improve the predictions of one phenological event for one insect species. The implications of these and other findings are discussed.     

重采样方法对DEM数据质量的影响

[目的]针对在数字地形分析的实际应用问题,利用重采样方法得到的DEM数据精度,旨在分析不同的重采样方法对所获得的DEM数据质量的影响。[方法]从数据误差的角度,以陕西省绥德县窑家湾沟流域的以全数字摄影测量得到的DEM数据为基准,计算并比较利用重采样方法得到的DEM的数据误差。[结果]无论采用何种重采样方法,得到DEM数据质量均未得到提高,其高程误差的空间分布与重采样方法相关,地形变化剧烈的地方,误差较大;中误差的大小则取决于重采样方法与原始格网尺寸。[结论]最近邻法得到的重采样DEM数据的中误差最高,三次立方卷积法的最小,双线性内插法则略高于三次立方卷积法。     

水土保持监测中SPOT5遥感图像几何精校正方法研究

为探索空间分辨率为2.5 m的SPOT5遥感图像用于水土保持监测的可行性,须进行遥感图像几何精校正。在理论分析遥感图像校正模型的基础上,通过实例计算,详细研究各种可能的几何精校正方法及实际精度状况。综合考虑几何位置变换精度、灰度重采样精度,确定适合水土保持监测的SPOT5遥感图像的几何精校正方法。     

Considering recreational catch and harvest in fisheries management at the bio‐regional scale

Abstract The Gulf of Carpentaria in northern Australia supports several commercial fisheries and a largely tourist‐based recreational fishery. The results of a survey of 427 recreational fishing parties visiting the main town, Karumba, between March and September 2006 were examined using the bootstrap method to estimate confidence intervals for mean tourist catch and harvest of grunter, Pomadasys kaakan (Cuvier), and other recreational target species. Tourist anglers harvested between 99.8 and 117 t of P. kaakan and 32.6–38.2 t of blue salmon, Eleutheronema tetradactylum (Shaw), during the survey period. Resident recreational anglers harvested an additional 15–35 t of P. kaakan, but very little E. tetradactylum. In comparison, commercial harvest was 19 t of P. kaakan and 64 t of E. tetradactylum in the whole of the Queensland section of the Gulf of Carpentaria. The results underscore the need for appropriately collected recreational fishing data to support integrated fisheries management at the bioregional scale, and in the case of angling‐based tourist destinations, underpin a diversification of the tourist product.