The review was based on a Scopus search conducted on 6 November 2025 using terms related to invasive species and acoustic monitoring while excluding the non-invasive term. The search returned 143 papers, from which the researchers screened 44 potentially relevant abstracts and assessed their full texts. They retained 26 studies that directly examined passive acoustic monitoring of invasive animals.

The earliest study in the retained dataset was published in 2012, and the number of publications increased in more recent years. Amphibians accounted for 11 studies, birds and fish for five each, arthropods for three, and mammals and reptiles for one each. Research was concentrated in the USA and Australia, with fewer studies from Europe, Asia and South America and none identified from Africa. The geographic pattern partly reflected repeated studies of cane toads in Australia and barred owls in the USA.

The literature showed that acoustic monitoring was moving from exploratory sound characterization toward automated detection, machine learning, long-term monitoring and large-scale networks. Automated or semi-automated detection appeared in 17 of the 26 studies, and manual or expert validation was reported in 18, with four more using behavioural, experimental, laboratory or methodological validation. In amphibian studies, distinctive and relatively stereotyped mating calls supported automated identification. Other examples included deep-learning classifiers for cane toads, real-time monitoring of barred owls, acoustic classification of invasive fish and a model developed from 3,500 field-recorded common brushtail possum vocalizations in New Zealand.

For the case study, the researchers deployed 20 AudioMoth recorders at 11 water bodies in the Upper Rhine region. The devices were placed less than five metres from shorelines and programmed to record for 55 seconds every minute from two hours before sunset until three hours after sunset at a sampling frequency of 48 kHz. Simultaneous recordings covered 16 days from 13 to 29 June 2025, corresponding with the regional peak of bullfrog vocal activity and breeding season. Visual shoreline surveys were also conducted where possible, and all available iNaturalist records in the study region were compiled.

The 1,600 recorded hours were analysed with BirdNET Analyzer V2.4, which produced 56,298 three-second snippets identified as containing bullfrog calls. The researchers randomly selected 500 segments spanning confidence scores from 0.25 to 1.00 and assessed spectrograms and audio. Of these, 485 were judged correct and 15 incorrect. Logistic regression estimated that identifications with confidence scores above 0.703 had a 99% probability of being correct, with a 95% confidence interval for the threshold of 0.602 to 0.932.

Applying a multi-step classification process, the study classified 10 of the 20 recorders as having detected bullfrogs and thereby confirmed presence at five of the 11 monitored lakes. Recorders with more than 100 detections above the threshold were classified directly. For lower counts, the researchers examined the 15 highest-scoring detections; these were classified as positive if all exceeded the upper limit of the confidence interval, while uncertain cases were checked manually by listening to the audio. Tadpoles were observed at five sites, which were also the only sites with available citizen-science bullfrog records in the region.

Two lakes with confirmed bullfrog presence were within one kilometre of the protected nature reserves Altrhein Kleiner Bodensee and Altrhein-Königsee. The case study nevertheless has bounded scope: it covered one 16-day recording period, 11 lakes and two confirmed presence locations, and failure to confirm calls at the other lakes did not establish that bullfrogs were absent. Detection also depended on animals vocalizing during the deployment period. Across the broader literature, suitability varied among taxa, with acoustic monitoring most applicable to species producing frequent, distinctive and predictable sounds and less comprehensive for weakly vocal or non-vocal animals.

The authors concluded that passive acoustic monitoring has strong potential to support repeated and scalable invasive-species surveillance, particularly when automated identification is paired with transparent validation, defined thresholds, manual checks and integration with visual surveys and citizen science. It can help confirm persistence at known sites, identify likely breeding activity through repeated mating calls and prioritize follow-up in areas with limited resources. The review did not establish a uniform detection rate across species or environments, and the case study demonstrates feasibility rather than a comprehensive estimate of monitoring accuracy across all invasive animals.

Subject of Research: Evaluation of passive acoustic monitoring for detecting invasive animal species through literature synthesis and an American bullfrog field case study.

Article Title: Passive acoustic monitoring as a tool for early detection of invasive animal species: a systematic review and a case study

Article References: Becker, D., Kasten, M. K., Weber, T., Grass, I., & Hiller, T. (2026). Passive acoustic monitoring as a tool for early detection of invasive animal species: a systematic review and a case study. Environmental Monitoring and Assessment, 198(9), Article 1003. https://doi.org/10.1007/s10661-026-15873-2

Image Credits: AI Generated

DOI: 10.1007/s10661-026-15873-2

Keywords: passive acoustic monitoring, invasive species, American bullfrog, automated species detection, BirdNET, AudioMoth, systematic review, early detection, biodiversity monitoring, Passive, acoustic, monitoring

The findings carry weight far beyond a single warbler species. The Hermit Warbler has previously been identified as a surrogate species for the California Spotted Owl, and among more than 60 Sierra Nevada bird species analyzed in prior work, 13 are co-associated with the Spotted Owl, none more strongly than the Hermit Warbler. Because the warbler’s small body size means a small home range, researchers can monitor it with far greater sample sizes than the owl, giving them the statistical power to detect subtle population responses to environmental change that will likely apply to the larger, more charismatic species sharing the same old-forest habitat. In this sense, the warbler functions as a biological barometer for an entire community of old-forest specialists facing the combined pressures of warming and intensifying fire regimes.

To capture population dynamics at an ecosystem scale, the research team deployed autonomous recording units, known as ARUs, at 876 locations spanning six National Forests across the western slope of the Sierra Nevada. Each summer from 2021 through 2024, pairs of recorders were placed 500 to 900 meters apart, with 1.5 to 3 kilometers between pairs, and left running for approximately five weeks. The devices recorded continuously through a single omni-directional microphone at a sample rate of 32 kilohertz. For analysis, the team focused on audio captured between 5:00 and 9:00 in the morning and 6:00 to 8:00 in the evening, the windows when Hermit Warbler vocalizations are most likely to be heard. The study area ranged from 328 meters above sea level, where black oak mingles with ponderosa pine, up to 2,528 meters, where white fir dominates the canopy.

The acoustic data were processed with BirdNET, a convolutional neural network capable of identifying Hermit Warbler songs and the vocalizations of thousands of other species by sound. To ensure the AI’s predictions were trustworthy, the researchers manually validated 200 randomly selected BirdNET detections of Hermit Warbler vocalizations, half drawn from a broad score range and half from the upper range, then fit a logistic regression relating the prediction score to the probability that a given detection was correct. Only predictions with a probability of being a true positive of at least 0.99 were retained as observations. At this stringent threshold, precision was a perfect 1.0, meaning every retained detection was correct, while recall was 0.78, meaning the detector captured 78 percent of the target sounds actually present. This combination of extremely high precision and strong recall meant false positives and false negatives would have minimal influence on the final results.

Quantifying the environmental conditions at each recording site required equally sophisticated remote sensing. The team characterized fire severity and history using 30-meter resolution rasters of the Composite Burn Index, generated in Google Earth Engine from random forest models parameterized with latitude, climatic water deficit, and spectral indices from Landsat imagery spanning 1985 to 2023. Composite Burn Index values of 2.25 or higher were categorized as high-severity fire, corresponding to at least 75 percent canopy mortality. Fire data were summarized within a 120-meter buffer around each recorder as the proportion of unburned, low-to-moderate, and high-severity fire occurring 1 to 10 and 11 to 35 years before each sampling year. For the thermal environment, the researchers used 30-meter resolution mean relative summer temperature derived from the Landsat 8 Thermal Infrared Sensor, calculated from 2013 to 2018 as a median across a six-year time series. This in situ thermal measurement, rather than coarser gridded weather data interpolated from sparse stations, captured fine-scale conditions such as slope and aspect in the Sierra’s complex terrain.

A critical statistical challenge emerged because relative temperature and mean tree diameter were strongly negatively correlated, with a correlation coefficient of negative 0.77. Sites with larger trees are simply cooler. To disentangle these effects, the team fit a linear model of relative temperature as a function of tree diameter and used the residuals as a forest-structure-corrected measure of the thermal environment. Positive residuals indicated sites warmer than expected given their tree diameter, negative residuals indicated sites cooler than expected, and the resulting corrected measure was uncorrelated with tree diameter. This allowed the researchers to ask whether the warbler responded to temperature itself, independent of the forest structure that both creates cooler microclimates and defines the species’ preferred habitat.

The population dynamics were analyzed with a dynamic occupancy model, a hierarchical statistical framework that estimates site occupancy, colonization, and local extinction while accounting for imperfect detection. Each breeding season was divided into eight six-day secondary sampling periods, and the team applied careful filters to create encounter histories: observations before June 1 or after July 18 were excluded because they could reflect migration or post-breeding movement rather than stable breeding behavior, and any site with only a single vocalization in June was treated as unoccupied to guard against transient individuals or rare high-scoring false positives. Detection probability was modeled as a function of survey effort and ordinal date. Initial occupancy was modeled as a function of elevation, latitude, mean tree diameter, the temperature-corrected residuals, and the amount of high-severity fire in the prior ten years, while colonization and extinction were modeled against the same covariates. All covariates were scaled to allow direct effect size comparisons, and the team considered a covariate influential if the 85 percent confidence interval around its estimate did not overlap zero.

The results painted a coherent picture of a species contracting its range under pressure from both direct and indirect effects of climate change. Site occupancy fell from 0.658 in 2021 to 0.603 in 2024, an 8.3 percent decline. Initial occupancy was most strongly influenced by mean tree diameter, confirming the warbler’s old-forest association, but even after controlling for forest structure, birds were more likely to occupy sites cooler than expected for their tree diameter. Occupancy showed a striking non-linear latitudinal gradient: approximately 0.1 at the southern end of the study area, climbing to 0.78 slightly north of the midpoint near the South Fork of the American River, and reaching 0.84 at the northernmost extent. Colonization rates were higher in the north while extinction rates were higher in the south, producing a clear northward shift in the relative density of occupied sites. Elevation told a more complicated story: colonization increased with elevation, but extinction displayed a positive quadratic relationship, meaning the lower elevational boundary shifted upslope while the upper boundary did not show an unambiguous corresponding expansion.

The fire response was dramatic. At a completely unburned site, the annual probability of local extinction was 0.106 and the probability of colonization was 0.383. At a fully burned site, extinction probability soared to 0.883 while colonization collapsed to 0.0292. The warbler showed a strong extinction response to severe fire over a 1-to-10-year post-fire period and failed to colonize such areas over the same span, effectively treating locally extensive high-severity fire as a decadal loss of habitat. Notably, colonization was unaffected by high-severity fire occurring 11 to 35 years before the study period, suggesting some capacity for resilience if enough unburned habitat remains. The observed population decline could plausibly be attributed to the several large, severe fires that occurred during the study window, including the Dixie Fire, which burned almost 3,900 square kilometers of the northern Sierra Nevada with more than 20 percent at high severity, along with the Caldor and KNP Complex Fires. The apparent northward shift of the warbler population may have partially offset the Dixie Fire’s local effects, underscoring the importance of regional context when interpreting local studies.

The study’s implications for conservation are sobering but actionable. Limiting the occurrence of large, severe fires will be necessary to preserve this old-forest indicator, the authors conclude, but not sufficient: rising temperatures will lead to population declines even in the absence of habitat loss due to fire. Without proactive strategies that move away from strict fire suppression and incorporate principles of pre-colonial fire stewardship, continued intensification of contemporary fire regimes could drive further declines for the Hermit Warbler and the species that share its habitat. Meanwhile, the mixed evidence for upslope shifts suggests that simply moving to higher elevations may not be a viable climate adaptation strategy for the warbler, the Spotted Owl, or their co-associated species, particularly since high-elevation Sierra forests are not expected to provide short- to intermediate-term climate refugia due to complex interactions between canopy cover, microclimate, and prey. As climate change accelerates, understanding how species respond to shifting environmental conditions will be crucial for guiding adaptive management and ensuring the persistence of biodiversity in fire-prone landscapes, and this four-year bioacoustic monitoring framework offers a scalable template for tracking those responses across entire ecosystems.

Subject of Research: Combined effects of warming temperatures and high-severity wildfire on the range dynamics of an old-forest bird species in the Sierra Nevada

Article Title: Warm temperatures and severe fire drive a range contraction of an avian old-forest specialist in the Sierra Nevada, USA

Article References: Bielski, L., Keyser, S. R., Peery, M. Z., & Wood, C. M. (2026). Warm temperatures and severe fire drive a range contraction of an avian old-forest specialist in the Sierra Nevada, USA. Frontiers in Bird Science, 5, Article 1737313. https://doi.org/10.3389/fbirs.2026.1737313

Image Credits: AI Generated

DOI: 10.3389/fbirs.2026.1737313

Keywords: Hermit Warbler, Sierra Nevada, climate change, high-severity fire, passive acoustic monitoring, dynamic occupancy model, old-growth forest, range contraction, BirdNET, wildfire, bird conservation, Spotted Owl

The technical heart of the project is passive acoustic monitoring, or PAM, a technique that replaces human observers with weatherproof recorders that capture the soundscape continuously. Between January 2023 and December 2025, Wildlife Acoustics Song Meter SM4 units mounted 1.5 meters above the ground at each site recorded for one minute every ten minutes, day and night. After a phase-aware resampling procedure that corrected archived files deviating from the intended schedule, the team assembled 436,775 unique one-minute recordings, of which 483 complete site-days, each containing all 144 expected recording bins, entered the final analysis. That volume of data would be unmanageable without machine learning, so the researchers turned to BirdNET-Analyzer, a deep-learning classifier trained to identify bird vocalizations, to convert raw audio into detection records.

Because automated classifiers make mistakes, the team layered a series of safeguards on top of the raw output. Detections were first filtered against the 2025 regional checklist curated by the Bird Records Committee of the Shanghai Wild Bird Society, removing geographically implausible species. Confidence thresholds were then evaluated from 0.10 to 0.70; at the lenient 0.10 cutoff, 479,343 records covering 212 species survived, while a stricter 0.30 threshold retained 127,256 records and 172 species. The researchers chose 0.30 as a practical compromise between reliability and taxonomic completeness, then excluded any species with five or fewer total detections to weed out isolated misidentifications, leaving 135 species. A random manual quality check across all seasons and eight common species achieved an overall accuracy of 88.7 percent, providing reassurance that the common post-filtered detections could be trusted.

The three monitoring sites were deliberately chosen to span Shanghai’s urbanization gradient. Zhongshan Park, embedded in the dense urban core, sits amid high nighttime light intensity and heavy human presence. Jinhai Wetland Park occupies a suburban position with intermediate context, while the ecological forest belt on Chongming Island represents a peri-urban setting with the tallest trees, the highest tree density at 2,141 stems per hectare, and the strongest vegetation signal as measured by the normalized difference vegetation index. Cumulative acoustic richness over three years proved remarkably similar across the gradient, with 131 species detected at Chongming, 128 at Jinhai, and 127 at Zhongshan Park, a finding that on its own might suggest urbanization matters little. The seasonal breakdown told a very different story.

Monthly richness followed a consistent annual cycle at all three sites, peaking in spring, dipping through summer, and recovering in autumn and winter. But the peri-urban Chongming site, despite its lush vegetation, consistently recorded fewer species than the suburban and urban sites during the cooler months. Community composition analysis using Jaccard dissimilarity and principal coordinates ordination confirmed that site and season both significantly shaped assemblages, with PERMANOVA tests attributing roughly 16 percent of compositional variation to site and 14 percent to season. Most striking were the seasonal centroid trajectories: Chongming’s community traveled the longest distance through ordination space across the year, 0.738 units, followed by Jinhai at 0.614, while the urban park’s community moved only 0.296 units, suggesting the city-center assemblage is comparatively stable while wilder sites undergo dramatic seasonal reassembly.

To connect these patterns to temperature, the team fitted generalized additive models, a flexible statistical framework capable of capturing nonlinear relationships. Daily land surface temperature came from the MODIS MOD11A1 satellite product at one-kilometer resolution, averaged across valid daytime and nighttime observations, while background meteorology came from the ERA5-Land reanalysis dataset. After screening candidate predictors for multicollinearity using generalized variance inflation factors and concurvity diagnostics, and comparing all 64 possible predictor subsets by AIC, the final quasi-Poisson model retained land surface temperature as a smooth thin-plate spline alongside wind speed and shortwave radiation, with site, season, and year as categorical effects. Fitted to 483 complete site-days, the model explained 61.02 percent of the deviance in daily acoustic species richness.

The fitted temperature response was decisively nonlinear. The partial effect of land surface temperature rose across cool conditions, peaked at 12.46 degrees Celsius, and then declined, crossing from a positive to a negative effect at 21.69 degrees Celsius. Sensitivity analyses confirmed this was no statistical artifact: models with larger basis dimensions produced transition estimates between 21.60 and 21.97 degrees, an autoregressive mixed model accounting for temporal autocorrelation yielded 21.44 degrees, and leave-one-site-out refits kept the zero-crossing within 21.00 to 22.40 degrees regardless of which site was excluded. The seasonal implications were stark. Winter surface temperatures at the urban park averaged 7.92 degrees Celsius, significantly warmer than the suburban and peri-urban sites, and 27.4 percent of winter site-days there fell within the range where the fitted thermal effect was at least 90 percent of its maximum, compared with only 9.1 percent at Jinhai and 8.3 percent at Chongming. In summer, by contrast, every site’s temperatures sat squarely in the negative portion of the curve, with means of 28.18, 29.98, and 31.94 degrees at Chongming, Jinhai, and Zhongshan respectively.

The migratory component of the avifauna drove most of the seasonal redistribution. Of the 135 retained species, 103 were classified as migratory and only 29 as residents, and migratory richness ranged from 67 to 91 species across site-season combinations, comprising up to 79.6 percent of the classified assemblage. Site-sharing analysis revealed a clear annual rhythm: 70 migratory species were detected at all three sites in spring, a figure that collapsed to 43 in summer, when ten migratory species vanished from all sites entirely, before recovering to 52 in autumn and 62 in winter. Critically, the summer contraction did not shift toward the cooler Chongming site; spatially restricted states appeared across all three locations, indicating that summer heat acted as a broad seasonal bottleneck rather than simply pushing birds toward the coolest refuge. In winter, the most frequent two-site combination was Jinhai with the urban park, a pattern the authors note could reflect either shared thermal conditions or simply similar habitat structure.

The findings carry a pointed message for urban planners betting on greening as a climate solution. The urban park’s winter warmth, combined with predictable food resources and sheltered vegetation, appears consistent with a winter thermal refuge role, echoing evidence that milder cities can lower thermoregulatory costs and improve overwinter survival. Yet the same heat-island effect that buffers winter cold becomes a liability in summer, when extreme temperatures constrain foraging, parental care, nestling growth, and even survival. Notably, even the cooler peri-urban forest failed to prevent the summer decline, suggesting that no single green space in the study provided adequate summer thermal refuge. The authors are careful to frame the 21.69-degree zero-crossing as a local, community-level statistical feature of their fitted model, not a universal physiological threshold or a validated management trigger, and they acknowledge that each urbanization context was represented by a single site, that acoustic richness may partly reflect temperature-dependent changes in calling behavior rather than true occurrence, and that site identity cannot be fully disentangled from vegetation structure and management history.

Even with those caveats, the study points toward a concrete shift in how cities might manage biodiversity under intensifying heat. Rather than uniform annual greening targets, the authors advocate season-specific habitat actions: maintaining continuous canopy shade, shallow water sources, and blue-green cooling features where summer exposure is high, while retaining sheltered vegetated cover and reliable food resources where winter refuge potential matters. They also propose a site-level thermal surveillance framework in which locally monitored surface temperatures and independently validated ecological indicators, rather than fixed seasonal calendars, guide adaptive planning as conditions approach adverse levels. In a megacity of 24.87 million people on the East Asian-Australasian Flyway, where built-up area has nearly doubled since 2000 and habitat quality indices have fallen sharply, the message is that a park’s worth to birds depends on when you ask, and that climate-resilient urban design must account for the full annual cycle of thermal life.

Subject of Research: Seasonal effects of urban land surface temperature on bird community richness and migratory redistribution across green spaces in Shanghai

Article Title: Urban thermal seasonality modulates avian community responses across contrasting green spaces

Article References: Zhang, Y., Zhang, W., Long, Y., Zheng, J., & Yin, S. (2026). Urban thermal seasonality modulates avian community responses across contrasting green spaces. Environmental and Sustainability Indicators, 32, Article 101543. https://doi.org/10.1016/j.indic.2026.101543

Image Credits: AI Generated

DOI: 10.1016/j.indic.2026.101543

Keywords: urban ecology, passive acoustic monitoring, BirdNET, land surface temperature, urban heat island, migratory birds, species richness, green infrastructure, Shanghai, generalized additive models, seasonal dynamics, climate adaptation