Penone Caterina, Kerbiriou Christian, Julien Jean-François, Marmet Julie, Le Viol Isabelle
Institute of Plant Sciences, University of Bern, Bern, Switzerland.
CESCO UMR7204 MNHN-UPMC-CNRS-Sorbonne Université, Université Pierre et Marie Curie (Paris VI), Paris, France.
PeerJ. 2018 Aug 24;6:e5370. doi: 10.7717/peerj.5370. eCollection 2018.
Citizen monitoring programs using acoustic data have been useful for detecting population and community patterns. However, they have rarely been used to study broad scale patterns of species traits. We assessed the potential of acoustic data to detect broad scale patterns in body size. We compared geographical patterns in body size with acoustic signals in the bat species . Given the correlation between body size and acoustic characteristics, we expected to see similar results when analyzing the relationships of body size and acoustic signals with climatic variables.
We assessed body size using forearm length measurements of 1,359 bats, captured by mist nets in France. For acoustic analyses, we used an extensive dataset collected through the French citizen bat survey. We isolated each bat echolocation call ( = 4,783) and performed automatic measures of signals, including the frequency of the flattest part of the calls (characteristic frequency). We then examined the relationship between forearm length, characteristic frequencies, and two components resulting from principal component analysis for geographic (latitude, longitude) and climatic variables.
Forearm length was positively correlated with higher precipitation, lower seasonality, and lower temperatures. Lower characteristic frequencies (i.e., larger body size) were mostly related to lower temperatures and northern latitudes. While conducted on different datasets, the two analyses provided congruent results.
Acoustic data from citizen science programs can thus be useful for the detection of large-scale patterns in body size. This first analysis offers a new perspective for the use of large acoustic databases to explore biological patterns and to address both theoretical and applied questions.
利用声学数据的公民监测项目在检测种群和群落模式方面很有用。然而,它们很少被用于研究物种特征的广泛尺度模式。我们评估了声学数据检测体型广泛尺度模式的潜力。我们将蝙蝠物种的体型地理模式与声学信号进行了比较。鉴于体型与声学特征之间的相关性,我们预计在分析体型和声学信号与气候变量的关系时会得到类似的结果。
我们通过测量在法国用雾网捕获的1359只蝙蝠的前臂长度来评估体型。对于声学分析,我们使用了通过法国公民蝙蝠调查收集的大量数据集。我们分离出每只蝙蝠的回声定位叫声(n = 4783),并对信号进行自动测量,包括叫声最平缓部分的频率(特征频率)。然后,我们研究了前臂长度、特征频率以及地理(纬度、经度)和气候变量主成分分析得出的两个成分之间的关系。
前臂长度与较高的降水量、较低的季节性和较低的温度呈正相关。较低的特征频率(即较大的体型)大多与较低的温度和较高的纬度有关。虽然这两项分析是在不同的数据集上进行的,但结果是一致的。
公民科学项目的声学数据因此可用于检测体型中的大规模模式。这一初步分析为利用大型声学数据库探索生物模式以及解决理论和应用问题提供了一个新的视角。