Passive Acoustic Monitoring as a Tool to Investigate the Spatial Distribution of Invasive Alien Species

Abstract

Invasive alien species (IAS) are a threat to biodiversity and ecosystem function worldwide. Unfortunately, researchers, agencies, and other management groups face the unresolved challenge of effectively detecting and monitoring IAS at large spatial and temporal scales. To improve the detection of soniferous IAS, we introduced a pipeline for large-scale passive acoustic monitoring (PAM). Our main goal was to illustrate how PAM can be used to rapidly provide baseline information on soniferous IAS. To that aim, we collected acoustic data across Puerto Rico from March to June 2021 and used single-species occupancy models to investigate species distribution of species in the archipelago and to assess the peak of vocal activity. Overall, we detected 16 IAS (10 birds, 3 mammals, and 3 frogs) and 79 native species in an extensive data set with 1,773,287 1-minute recordings. Avian activity peaked early in the morning (between 5 a.m. and 7 a.m.), while amphibians peaked between 1 a.m. and 5 a.m. Occupancy probability for IAS in Puerto Rico ranged from 0.002 to 0.67. In general, elevation and forest cover older than 54 years were negatively associated with IAS occupancy, corroborating our expectation that IAS occurrence is related to high levels of human disturbance and present higher occupancy probabilities in places characterized by more intense human activities. The work presented here demonstrates that PAM is a workable solution for monitoring vocally active IAS over a large area and provides a reproducible workflow that can be extended to allow for continued monitoring over longer timeframes.

Rice Fields as Important Habitats for Three Anuran Species—Significance and Implications for Conservation

“…As recommended in the Arbimon Help section, the models were validated using equal numbers of recordings with presence and absence of the respective species and had the following detection accuracies: 79% for the European green toad, 82% for the Eastern tree frog and 83% for the Marsh frog. While a number of other studies [ 20 , 21 ] have successfully used the simpler template PM, setting a low threshold and manually verifying portions of the results (i.e., the PM returns a high number of false positives with a reduced possibility of false negatives), we found this approach to be inapplicable in our case, as the template PM consistently returned vastly inaccurate results (e.g., >50% false positives). The merits of RFMs for species detection have been demonstrated by other studies [ 22 ], and the verified accuracy of our RFMs in all three species was considerably higher than what could be achieved using a template PM, so their results were used for the aims of the study.…”

“…Due to their good accuracy, scalability and robustness to noise, RFMs are increasingly used in automated sound classification [ 50 ]. Recent software advancements have greatly contributed towards the automatization of analyses; however, there is still a need for manual examination of recordings and validation of models, as recommended in [ 21 , 51 , 52 , 53 ].…”

Applications and advances in acoustic monitoring for infectious disease epidemiology

“…To understand P. knowlesi epidemiology and institute control measures, studies require fine-scale data to characterise macaque movement across space and time. Using cloud-based computing and pattern-matching approaches implemented in a freely available web-based platform [65], acoustic data can be analysed to detect M. fascicularis presence across different habitats within areas endemic for P. knowlesi transmission (Figure 5). In addition to standalone sensors, the deployment of multisensor networks, microphones, and linked arrays can facilitate acoustic localisation of terrestrial species, using position estimation algorithms at later analysis stages [66].…”

Towards acoustic monitoring of bees: wingbeat sounds are related to species and individual traits

“…In combination with computational tools, PAM has proven to efficiently record animal activity for a wide variety of subjects, e.g. population density [12,13] and distribution [14], conservation [15] or climate change research [16,17]. PAM is typically aimed to record well-known species-specific acoustic signals that are emitted by specialized sound-producing structures and play a role in mating, resource defence or navigation [18].…”