Kaleidoscope Pro軟件在被動聲學監測與紅外觸發相機在鹿類和靈長類動物監測效率上的對比評估中的應用

Abstract

In recent years, camera traps have rapidly become popular for the large-scale monitoring of wildlife distribution and population; however, we should not ignore the uncertainty regarding the reliability of camera-based monitoring by inexperienced data gatherers. This study introduces passive acoustic monitoring (PAM) as an easier technique for monitoring terrestrial mammals that uses the sound cues that they produce. To validate the efficacy of PAM, we quantitatively compared the detection areas and rates between sound cues (from PAM) and visual cues (from camera traps) of two mammals—the sika deer Cervus nippon and the Japanese macaque Macaca fuscata—across seven study sites in eastern Japan with different population densities. To collect sound cues, we set up multiple autonomous recording units at the sites and continuously recorded ambient sounds, following a pre-determined schedule. The total recording time reached 9081h for deer and 8235h for macaques. We then built sound recognizers to automatically detect eight target call types from the recorded data. To collect visual cues, we also set multiple camera traps at the same sites and for the same observation periods. The key findings were as follows: (1) the fully automated procedures that only used the recognizers to detect sound cues produced numerous false positive detections when the call type possessed vocal plasticity and variations; (2) the semi automated procedures, which included an additional step to validate the automated detections by manual screening, exhibited a great improvement in the detectability and recall rates of the half of the target calls, reaching >0.70; (3) when using the semi-automated procedures, the frequency of deer and macaque detections per trap-day derived from the sound cues were in most cases approximately dozens of times and several times, respectively, higher than that derived from the visual cues; (4) the main advantage of PAM may be its superior detection areas, which were 100–7000 times wider than those of camera traps; and (5) the current success of the recognition of different call types of each species could broaden the use of PAM, which is not possible for camera traps. PAM could provide socio-behavioral data (i.e., the frequencies and types of inter-individual vocal com munications) that could help understand the status of population dynamics and the group compositions, in addition to information related to the presence or absence of species.

摘要：

近年來，相機在大規模監測野生動物分布和種群方面迅速流行起來；然而，我們不應該忽視缺乏經驗的數據采集人員對基于攝像頭的監控可靠性的不確定性。這項研究引入了被動聲學監測（PAM）作為一種更容易監測陸生哺乳動物的技術，該技術利用它們產生的聲音線索。為了驗證PAM的有效性，我們在日本東部七個不同種群密度的研究地點定量比較了兩種哺乳動物——梅花鹿、日本鹿和日本獼猴——的聲音線索（來自PAM）和視覺線索（來自相機）之間的檢測區域和比率。為了收集聲音線索，我們在現場設置了多個自主錄音單元，并按照預定的時間表連續錄制環境聲音。鹿和獼猴的總記錄時間分別為9081小時和8235小時。然后，我們構建了聲音識別器，從記錄的數據中自動檢測八種目標呼叫類型。為了收集視覺線索，我們還在相同的地點和相同的觀察期設置了多個相機。主要發現如下：（1）當呼叫類型具有聲音可塑性和變異性時，僅使用識別器檢測聲音線索的全自動程序會產生大量誤報；（2）半自動程序，包括通過手動篩查驗證自動檢測的額外步驟，在一半目標呼叫的可檢測性和召回率方面有了很大提高，達到>0.70；（3）當使用半自動程序時，在大多數情況下，從聲音線索中得出的每個誘捕日鹿和獼猴的檢測頻率分別比從視覺線索中得出，大約高出幾十倍和幾倍；（4） PAM的主要優點可能是其優越的檢測區域，比相機寬100-7000倍；以及（5）目前成功識別每種物種的不同叫聲類型可以擴大PAM的使用范圍，而PAM對于相機來說是不可能的。PAM可以提供社會行為數據（即個體間聲音交流的頻率和類型），除了與物種存在或不存在相關的信息外，還可以幫助了解種群動態和群體組成的狀態。

關鍵詞：Kaleidoscope Pro軟件，Wildlife Acoustics，聲學追蹤監測，野生動物聲學監測，聲學分析軟件，野生鹿監測。