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首页> 外文期刊>Fisheries Research >The effect of methodological options on geostatistical modelling ofanimal distribution: A case study with Liocarcinus depurator(Crustacea: Brachyura) trawl survey data
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The effect of methodological options on geostatistical modelling ofanimal distribution: A case study with Liocarcinus depurator(Crustacea: Brachyura) trawl survey data

机译：方法选项对动物分布的地统计学模型的影响：以利奥卡迪努斯净化器（甲壳纲：Brachyura）拖网调查数据为例

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摘要

Geostatistical methods have been applied to the problem of accurately mapping animal densities derived from trawl surveys. Sample data are often sparse, highly skewed in distribution and quite unlike the examples used to investigate the adequacy of the methodological options available. We analysed the data from a trawl survey of the portunid crab Liocarcinus depurator using two approaches: (a) removal of outliers and (b) logarithmic transformation of the densities. Within each approach we compared a range of options for both the estimation of the underlying spatial structure (variogram) and modelling of crab density through kriging. The results indicated that log-transformation produced the least robust and most unrealistic assessment of L. depurator spatial distribution. Removing outliers gave consistent estimates, regardless of small changes in methodology except when inappropriate spatial models were applied (exponential and Gaussian models did not fit the variogram well). Differences in the number of lags used to build the variogram or the number of outliers removed from the data had more effect on the spatial model parameters than did most of the procedural alterations. Density estimates from kriging highlighted the difference between the two approaches. For example, estimates of the coefficient of variation were most unrealistic from the log-transformation approach but were roughly half that of the original sample when the spatial model was fitted with data without outliers. In general, the failure of the methods to reflect the original sample were related to the assumptions underlying the methods. Thus, the log-transformation approach produces a peculiar distribution of densities, with zero densities creating considerable departure from log-normality. The resulting parameter and density estimates were thus erratic and unrealistic. Removal of outliers helped uncover the spatial structure in the crab population and led to very realistic parameter and density estimates. However, the lack of symmetry in the distribution led to unrealistic (negative) minimum density estimates when kriging forced a symmetrical distribution on the data. L. depurator populations along the Spanish coast showed high spatial dependency with densities aggregated in patches. Patch sizes were estimated to have diameter of around 20 km. Density decreases with depth and this was adequately represented by the 'removal of outlier approach', using depth as a covariate.
机译：地统计方法已应用于精确绘制从拖网调查得出的动物密度的问题。样本数据通常是稀疏的，分布严重偏斜的，并且与用于调查可用方法论的充分性的示例完全不同。我们使用两种方法分析了对拖网蟹Licarcarcinus净化器的拖网调查数据：（a）消除异常值和（b）密度的对数变换。在每种方法中，我们都比较了各种选择范围，既可以用于估计基本的空间结构（变异函数），也可以通过克里金法对螃蟹密度进行建模。结果表明，对数变换产生了对净化器的空间分布的最不稳健和最不现实的评估。除去方法外的异常值，可以得到一致的估计值，而不论方法上的微小变化，除非应用了不适当的空间模型（指数模型和高斯模型都不能很好地拟合变异函数）。与大多数程序更改相比，用于构建变异函数的滞后次数差异或从数据中删除的异常值的差异对空间模型参数的影响更大。克里金法估计的密度突出了两种方法之间的差异。例如，从对数转换方法估计变异系数是最不现实的，但是当空间模型中装有没有异常值的数据时，变异系数的估计大约是原始样本的一半。通常，该方法无法反映原始样本与该方法所基于的假设有关。因此，对数转换方法会产生奇特的密度分布，而零密度会导致极大地偏离对数正态。因此，所得的参数和密度估计是不稳定且不现实的。离群值的去除有助于揭示蟹种群的空间结构，并导致非常现实的参数和密度估计。但是，当克里金法对数据进行对称分布时，分布中缺乏对称性会导致不切实际的（负）最小密度估计。西班牙沿海沿岸的提纯劳德氏菌种群表现出高度的空间依赖性，其密度聚集在一块。据估计，斑块的直径约为20 km。密度随深度而降低，并且使用深度作为协变量来充分表示为“消除离群值方法”。

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