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用于系统性保护规划的不同类型物种出现数据的权衡。

Tradeoffs of different types of species occurrence data for use in systematic conservation planning.

作者信息

Rondinini Carlo, Wilson Kerrie A, Boitani Luigi, Grantham Hedley, Possingham Hugh P

机构信息

Department of Animal and Human Biology, Università di Roma La Sapienza, Viale dell'Università 32, 00185 Roma, Italy.

出版信息

Ecol Lett. 2006 Oct;9(10):1136-45. doi: 10.1111/j.1461-0248.2006.00970.x.

DOI:10.1111/j.1461-0248.2006.00970.x
PMID:16972877
Abstract

Data on the occurrence of species are widely used to inform the design of reserve networks. These data contain commission errors (when a species is mistakenly thought to be present) and omission errors (when a species is mistakenly thought to be absent), and the rates of the two types of error are inversely related. Point locality data can minimize commission errors, but those obtained from museum collections are generally sparse, suffer from substantial spatial bias and contain large omission errors. Geographic ranges generate large commission errors because they assume homogenous species distributions. Predicted distribution data make explicit inferences on species occurrence and their commission and omission errors depend on model structure, on the omission of variables that determine species distribution and on data resolution. Omission errors lead to identifying networks of areas for conservation action that are smaller than required and centred on known species occurrences, thus affecting the comprehensiveness, representativeness and efficiency of selected areas. Commission errors lead to selecting areas not relevant to conservation, thus affecting the representativeness and adequacy of reserve networks. Conservation plans should include an estimation of commission and omission errors in underlying species data and explicitly use this information to influence conservation planning outcomes.

摘要

物种出现的数据被广泛用于为保护区网络的设计提供信息。这些数据包含误判误差(当一个物种被错误地认为存在时)和遗漏误差(当一个物种被错误地认为不存在时),并且这两种误差的发生率呈负相关。点位置数据可以将误判误差降至最低,但从博物馆藏品中获得的数据通常很稀疏,存在严重的空间偏差,并且包含大量遗漏误差。地理范围会产生较大的误判误差,因为它们假设物种分布是均匀的。预测分布数据对物种出现情况进行明确推断,其误判和遗漏误差取决于模型结构、决定物种分布的变量的遗漏以及数据分辨率。遗漏误差会导致确定的保护行动区域网络比所需的小,并且以已知物种出现地点为中心,从而影响所选区域的全面性、代表性和效率。误判误差会导致选择与保护无关的区域,从而影响保护区网络的代表性和充分性。保护计划应包括对基础物种数据中的误判和遗漏误差的估计,并明确利用这些信息来影响保护规划结果。

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