SM2BAT自動聲學識別軟件在新熱帶地區蝙蝠調查中的應用
Abstract
Bat populations are known to be affected by anthropogenic activities because bats are an extremely diverse group occupying almost all available niches in terrestrial environment. Hence, bats are considered bioindicators to monitor changes in the environment, but their value as such also depends on the ease to monitor and detect demographic trends in their populations. The long-term interest of researchers in the acoustic of bats results from the fact that it is a non- invasive, time-efficient method to monitor spatiotemporal patterns of bat diversity and activity.The analysis of sounds emitted by organisms has been considered useful to gain insight into species-specific biotic and abiotic interactions, which can further be applied to conservation. Besides manual identifications of bat calls, some automated species identification programs using regional call classifiers have been introduced into the market as an effective tool in the monitoring of bat populations. Most of these programs have not been validated using field data. This study evaluates the reliability of two automated software, SonoChiro, and Kaleidoscope Pro, in comparison to manual identifications of field data collected from the Neotropical region. There was low agreement between the two automated methods at the species level, fair agreement at the genus level and moderate agreement at the family level. There was also a significant difference between the proportions of correctly identified calls of the two-automated software at the species level identifications. Major challenges for using automated identification software include the need for comprehensive call libraries of the regions under scope; significant opportunities, on the other hand, include the widespread possibility to monitor spatiotemporal patterns of bat activity. Overall, there are serious gaps that preclude a widespread application of automated programs ecological and conservation studies of bats, but it has the potential to serve as a useful tool.
摘要：
眾所周知，蝙蝠種群受到人為活動的影響，因為蝙蝠是一個極其多樣化的群體，幾乎占據了陸地環境中所有可用的生態位。因此，蝙蝠被認為是監測環境變化的生物指標，但它們的價值也取決于監測和檢測其種群人口趨勢的難易程度。研究人員對蝙蝠聲學的長期興趣源于這樣一個事實，即這是一種非侵入性、省時的方法來監測蝙蝠多樣性和活動的時空模式。分析生物體發出的聲音被認為有助于深入了解物種特異性的生物和非生物相互作用，這可以進一步應用于保護。除了手動識別蝙蝠叫聲外，一些使用區域叫聲分類器的自動物種識別程序也被引入市場，作為監測蝙蝠種群的有效工具。這些程序中的大多數尚未使用現場數據進行驗證。本研究評估了兩種自動化軟件SonoChiro和Kaleidoscope Pro的可靠性，并與從新熱帶地區收集的現場數據的手動識別進行了比較。兩種自動化方法在物種水平上的一致性較低，在屬水平上一致性較好，在科水平上一致度適中。在物種級別的識別中，兩種自動化軟件正確識別的呼叫比例也存在顯著差異。使用自動識別軟件的主要挑戰包括需要范圍內區域的綜合呼叫庫；另一方面，重要的機會包括監測蝙蝠活動的時空模式的廣泛可能性。總體而言，存在嚴重的差距，阻礙了自動化程序在蝙蝠生態和保護研究中的廣泛應用，但它有可能成為一種有用的工具。
關鍵詞：SM2+聲學記錄器，Wildlife Acoustics，野生動物聲學記錄，動物被動聲學監測，聲景生態學、快速生物多樣性評估、生態聲學
