With rapid urbanization worldwide, anthropogenic impacts such as human settlements and invasive carnivores (dogs Canis familiaris, cats Felis catus) are altering spatial distributions and temporal activity patterns of native species. In this study, we focused on spatiotemporal responses of native mammals to anthropogenic impacts in a protected area surrounded by a large metropolis (i.e. Yangmingshan National Park inside Taipei-Keelung metropolis in northern Taiwan). We collected site use data of 11 mammal species (i.e. dogs, cats, nine native species) between 2012 and 2017 with a camera system comprising 121 camera sites. We quantified anthropogenic disturbances as distance to human settlements and activity levels of free-roaming dogs and cats. Species richness and occurrences of the native mammals increased with increasing distances to human settlements and decreasing activity level of dogs, with the latter having a stronger effect than the former. Diel activity overlap between native mammals and dogs was lower during April–July season, coinciding with the breeding season for several native mammals. In contrast, activity level of cats showed no relationships with species richness, occurrences or diel activities of the native mammals. This study demonstrated negative impacts of human settlements and free-roaming dogs on native mammal communities for protected areas in urban environments, and highlights dog activity as a major anthropogenic threat to wildlife.

Soundscapes contain rich acoustic information associated with animal behaviours, environmental characteristics and human activities, providing opportunities for predicting biodiversity changes and associated drivers. However, assessing the diversity of animal vocalizations remains challenging due to the interference of environmental and anthropogenic noise. A tool for separating sound sources and delineating changes in acoustic signals is crucial for an effective assessment of acoustic diversity. We present soundscape_IR, an open‐source Python toolbox dedicated to soundscape information retrieval in which nonnegative matrix factorization is applied. This toolbox provides algorithms for supervised and unsupervised source separation (SS). It also enables the use of a snapshot recording for model training and subsequently applying adaptive and semi‐supervised SS when target species produce sounds with varying features and when unseen sound sources are encountered. Our results demonstrated that SS could enhance the vocalizations of target species, characterize the complexity of vocal repertoires and investigate the spatio‐temporal divergence of soundscapes. In tropical forest soundscapes, the application of SS effectively detected the rutting vocalizations of sika deer and revealed a graded structure in their acoustic characteristics. In subtropical estuarine soundscapes, SS automated the process of identifying distinct biotic and abiotic sounds, and the result uncovered divergent sound compositions between inshore and offshore waters. Implementation of SS in soundscape analysis offers a promising method for streamlining the assessment of acoustic diversity in diverse environments. Future application of SS will open new directions to acoustically quantify ecological interactions across individual, species and ecosystem levels.

Wildlife tracking and ecological monitoring are important for scientific monitoring, wildlife rehabilitation, disease control, and sustainable ecological development. Yet technologies for both of them are expensive and not scalable. Also it is important to tune the monitoring system parameters for different species to adapt their behavior and gain the best result of monitoring. In this paper, we propose using wireless sensor networks to build both short term and long term wildlife and ecological monitoring systems. For the short term system, everything used is off-the-shelf and can be easily purchased from the market. We suggest that before establishing a large scale wildlife/ecological monitoring network, it is worthwhile to first spend a short period of time constructing a rapid prototype of the targeted network. Through verifying the correctness of the prototype network, ecologists can find potential problems, avoid total system failure, and use the best-tuned parameters for the long-term monitoring network.

Hunting and habitat loss led to the extinction of the Formosan sika deer Cervus nippon taiouanus population in the wild in 1969. A sika deer restoration program has been in place in Kenting National Park (KTNP), Taiwan since 1984. Human—deer conflicts have increased following wild deer population growth. Understanding residents' attitudes toward reintroduced sika deer is vital to management policies. To investigate the local residents' attitudes, we collected 228 questionnaires through personal interviews in 2010. A majority of the respondents agreed that they would be happy to encounter a wild sika deer (78.1%), and a majority supported the restoration program in the KTNP (75.4%). However, 59.1% of the respondents knew little concerning the restoration program. Approximately half of the respondents (47.8%) thought that sika deer caused damages to crops, and 18.4% of the respondents actually suffered crop damages from deer. The farmers and people living within the deer's range were more vulnerable to deer damage; therefore, they were more aware of deer damage to their crops and livelihoods than non‐farmers and people living outside of the deer's range. In addition, most respondents (87.2%) considered sika deer as an attractive tourism resource and were supportive of the development of ecotourism (87.3%). We recommend that the KTNP should improve public participation, environmental education, and communication with the local people. The development of community‐based ecotourism would increase the benefits of the reintroduction of sika deer and would help to mitigate human—deer conflicts.

In sika deer Cervus nippon, rutting vocalizations play an important role in breeding behavior. This study investigated two types of rutting vocalizations, the moan and the howl, of the Formosan sika deer C. n. taiouanus, including the acoustic characteristics of the vocalizations, the diurnal and seasonal variations of vocal activity, and individual acoustic variation and identification. The results showed that the sound levels were approximately 81-88 dB(A) for the moan and 92-96 dB(A) for the howl, at a distance of 7 m from the sources. From October 2006 to January 2007, eight days of continuous observations were conducted to record the type and amount of vocalizations. Both moan and howl began to occur in the middle of October and reached peaks in the middle and end of November. Thereafter, few vocalizations were recorded until mid-January 2007. Moreover, we found that 74.5% of the first portion of moan, 65.3% of the second portion of moan, and 64.2% of howl could be identified on an individual basis by using discriminant analysis with 200 iterations of cross-validation test. These results revealed that the sounds differed among individuals, and also that they could be correctly identified. Our findings add to the scientific knowledge of sika deer behavior and provide the basis for a novel method of monitoring sika deer populations.