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首页> 外文期刊>Tropical Conservation Science >Moving Beyond Simple Descriptive Statistics in the Analysis of Online Wildlife Trade: An Example From Clustering and Ordination
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Moving Beyond Simple Descriptive Statistics in the Analysis of Online Wildlife Trade: An Example From Clustering and Ordination

机译：在线野生动物贸易分析中超越简单的描述性统计数据：来自聚类和排序的示例

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Collecting data for reports on online wildlife trade is resource-intensive and time-consuming. Learning often focuses on the main item traded by each country only. However, online trade is increasing, providing potential to update the conversation from a national scale to a global scale. We demonstrate how hierarchical clustering can identify wildlife items that follow similar trading patterns. We also ordinate the clusters, and seek correlations between the clusters and global measures, such as Worldwide Governance Indicators. We primarily use a sample dataset from a published report of online traded wildlife, covering 16 countries and 31 taxa or product types. Clustering provided immediate insights, such as rhinos and pangolins were traded similarly to ivory and suspected ivory. Five out of eight clusters represented items predominately traded by one country. An ordination of these clusters, and representation of global measures on the ordination axis, show a strong correlation of the ‘Voice and accountability' score with the clusters. Consequently, from the ‘Voice and accountability' score of the United States, a country not included in our dataset, we inferred that it traded elephant items (not ivory) and owl items during 2014.
机译：收集在线野生动物贸易报告数据是资源密集型和耗时的资源。学习通常专注于每个国家交易的主要项目。然而，在线贸易正在增加，提供从全国规模到全球范围内更新谈话的潜力。我们演示了分层聚类如何识别遵循类似交易模式的野生动物项目。我们还园林，寻求集群与全球措施之间的相关性，例如全球治理指标。我们主要使用来自在线交易野生动物的已发布报告的示例数据集，涵盖16个国家和31个分类群或产品类型。聚类提供了立即见解，例如犀牛和植物素与象牙和疑似象牙同样进行交易。八个集群中的五个代表了一个国家主要交易的物品。这些集群的秩序，以及对排序轴上的全球措施的表现，表现出与群集的“语音和问责制”得分的强烈关联。因此，来自美国的“语音和问责制”得分，我们将在我们的数据集中包含的国家，我们推断出2014年交易大象项目（不是象牙）和猫头鹰物品。

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