Ruete Alejandro, Arlt Debora, Berg Åke, Knape Jonas, Żmihorski Michał, Pärt Tomas
Greensway AB Uppsala Sweden.
Department of Ecology Swedish University of Agricultural Sciences Uppsala Sweden.
Ecol Evol. 2020 Aug 22;10(18):10057-10065. doi: 10.1002/ece3.6665. eCollection 2020 Sep.
Abundant citizen science data on species occurrences are becoming increasingly available and enable identifying composition of communities occurring at multiple sites with high temporal resolution. However, for species displaying temporary patterns of local occurrences that are transient to some sites, biodiversity measures are clearly dependent on the criteria used to include species into local species lists. Using abundant opportunistic citizen science data from frequently visited wetlands, we investigated the sensitivity of α- and β-diversity estimates to the use raw versus detection-corrected data and to the use of inclusion criteria for species presence reflecting alternative site use. We tested seven inclusion criteria (with varying number of days required to be present) on time series of daily occurrence status during a breeding season of 90 days for 77 wetland bird species. We show that even when opportunistic presence-only observation data are abundant, raw data may not produce reliable local species richness estimates and rank sites very differently in terms of species richness. Furthermore, occupancy model based α- and β-diversity estimates were sensitive to the inclusion criteria used. Total species lists (all species observed at least once during a season) may therefore mask diversity differences among sites in local communities of species, by including vagrant species on potentially breeding communities and change the relative rank order of sites in terms of species richness. Very high sampling effort does not necessarily free opportunistic data from its inherent bias and can produce a pattern in which many species are observed at least once almost everywhere, thus leading to a possible paradox: The large amount of biological information may hinder its usefulness. Therefore, when prioritizing among sites to manage or preserve species diversity estimates need to be carefully related to relevant inclusion criteria depending on the diversity estimate in focus.
关于物种出现情况的丰富公民科学数据越来越容易获取，这使得我们能够以高时间分辨率识别多个地点出现的群落组成。然而，对于那些在某些地点出现短暂局部发生模式的物种，生物多样性测量显然取决于用于将物种纳入当地物种列表的标准。利用来自经常有人到访的湿地的大量机会性公民科学数据，我们研究了α多样性和β多样性估计值对使用原始数据与经过检测校正的数据以及对反映不同地点使用情况的物种存在纳入标准的敏感性。我们针对77种湿地鸟类在90天繁殖季节的每日出现状态时间序列，测试了七种纳入标准（所需出现天数不同）。我们发现，即使机会性仅存在观测数据丰富，原始数据也可能无法产生可靠的当地物种丰富度估计值，并且在物种丰富度方面对地点的排名差异很大。此外，基于占有率模型的α多样性和β多样性估计值对所使用的纳入标准很敏感。因此，总物种列表（在一个季节中至少被观测到一次的所有物种）可能会掩盖当地物种群落中各地点之间的多样性差异，因为它将漂泊物种纳入了潜在的繁殖群落，并改变了各地点在物种丰富度方面的相对排名顺序。非常高的采样工作量不一定能消除机会性数据固有的偏差，反而可能产生一种模式，即几乎在每个地方都至少观测到许多物种一次，从而导致一个可能的悖论：大量的生物信息可能会阻碍其有用性。因此，在对管理或保护物种多样性的地点进行优先级排序时，需要根据所关注的多样性估计，将估计值与相关的纳入标准仔细关联起来。
