Occupancy modelling as a new approach to assess supranational trends using opportunistic data: a pilot study for the damselfly Calopteryx splendens
Occupancy modelling as a new approach to assess supranational trends using opportunistic data: a pilot study for the damselfly Calopteryx splendens
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占用建模作为利用机会数据评估超国家趋势的新方法：豆娘 Calopteryx splendens 的试点研究
DOI：
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发表时间：
2013
影响因子：
3.4
通讯作者：
Wouter Vanreusel
中科院分区：
文献类型：
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作者：
A. J. Strien;T. Termaat;V. Kalkman;Marijn Prins;G. Knijf;Anne;X. Houard;B. Nelson;Calijn Plate;Stephen Prentice;E. Regan;D. Smallshire;Cédric Vanappelghem;Wouter Vanreusel
在欧洲范围内，关于生物多样性变化的信息有限，因为缺乏对大多数物种群体进行标准化监测的数据。然而，在许多国家，许多物种在没有标准化现场协议的情况下进行了大量的观察。这种机会主义数据提供了另一种信息来源，但不幸的是，这种数据受到非标准化观察工作和地理偏见的影响。在这里，我们描述了一种新的方法来编制超国家的趋势，利用机会主义的数据，调整这两个主要的缺陷。非标准化的观察工作通过占用建模来处理，并通过加权程序来处理站点的不平等地理分布。选择美丽蜻蜓Calopteryx splendens作为我们的测试物种。数据收集自五个国家（爱尔兰、英国、荷兰、比利时和法国），涵盖1990-2008年。我们使用占用模型来估计每个国家每年占用1 × 1 km站点的数量。占领模式使用存在-不存在的数据，占物种的不完善的检测，从而纠正观测工作的年间变异。使用JAGS以贝叶斯推理模式对每个国家运行占用模型。然后将每个国家的占用率估计数汇总，以评估占用的1x 1平方公里数量的超国家趋势。为了调整调查地点的不平等地理分布，我们根据调查地点的数量和每个国家的物种范围对国家进行加权。在这五个国家中，一串红的分布显著增加。我们的试验表明，超国家的分布趋势可以从机会主义数据中得出，同时调整观察工作和地理偏见。这为生物多样性的国际监测开辟了新的前景。
There is limited information available on changes in biodiversity at the European scale, because there is a lack of data from standardised monitoring for most species groups. However, a great number of observations made without a standardised field protocol is available in many countries for many species. Such opportunistic data offer an alternative source of information, but unfortunately such data suffer from non-standardised observation effort and geographical bias. Here we describe a new approach to compiling supranational trends using opportunistic data which adjusts for these two major imperfections. The non-standardised observation effort is dealt with by occupancy modelling, and the unequal geographical distribution of sites by a weighting procedure. The damselfly Calopteryx splendens was chosen as our test species. The data were collected from five countries (Ireland, Great Britain, the Netherlands, Belgium and France), covering the period 1990–2008. We used occupancy models to estimate the annual number of occupied 1 × 1 km sites per country. Occupancy models use presence-absence data, account for imperfect detection of species, and thereby correct for between-year variability in observation effort. The occupancy models were run per country in a Bayesian mode of inference using JAGS. The occupancy estimates per country were then aggregated to assess the supranational trend in the number of occupied 1 × 1 km2. To adjust for the unequal geographical distribution of surveyed sites, we weighted the countries according to the number of sites surveyed and the range of the species per country. The distribution of C.splendens has increased significantly in the combined five countries. Our trial demonstrated that a supranational trend in distribution can be derived from opportunistic data, while adjusting for observation effort and geographical bias. This opens new perspectives for international monitoring of biodiversity.