Vijay Ramesh

Elevational migration is globally exhibited by montane bird species through elevational range shifts to track seasonal changes in weather patterns and resources. Studies investigating the patterns and mechanisms of such elevational shifts have been limited in spatial scale owing to the difficulty of sampling data across montane gradients. Here, we integrated data from the world's largest participatory science project (eBird) with systematic surveys to examine patterns and mechanisms that may explain bird elevational range shifts in the Nilgiri Hills of the Western Ghats Biodiversity Hotspot. We calculate the extent of shifts in elevational ranges for birds present year‐round in the Nilgiris between the hottest and coldest quarters and quantify the associations between these shifts and species traits using phylogenetic generalized least squares regressions. We found that 77% (54/70) of the species investigated showed seasonal shifts in their elevational ranges. Birds in the Nilgiris showed nearly equal proportions of downslope (37%) and upslope (33%) winter shifts. All species had significant range overlap between seasons but employed different shifting strategies. Species with narrow thermal regimes predominantly shifted downslope in winter (niche tracking), while those with the widest thermal regimes shifted upslope (niche switching), revealing that species adapt to climatic variability through contrasting thermal strategies. Our results suggest that climatic constraints, specifically thermal regime, could be a major driver of seasonal shifts in elevational ranges of birds in the Nilgiris. Understanding these elevational shift strategies is critical for conservation planning in tropical montane systems facing accelerating climate change.

1. Passive acoustic monitoring (PAM) enables non-invasive sampling of wildlife across broad spatial, temporal and taxonomic scales. Its ongoing and widespread use has generated unprecedented volumes of acoustic data, shifting the primary bottleneck from data collection to the storage, processing, integration, and interpretation of PAM outputs. Although many software tools exist to address these challenges, differences in their design, scope, and usability often create fragmented and complex analytical workflows. To identify the key barriers and opportunities shaping the implementation of PAM surveys, we conducted a structured expert solicitation involving 30 international practitioners working across terrestrial and aquatic ecosystems. Experts identified and ranked their most critical pain points in current PAM workflows, spanning data storage, processing, and interpretation. The top challenge identified related to accurate species identification using deep learning and artificial intelligence (AI) models, especially in noisy soundscapes or for underrepresented taxa. Eight additional priority challenges included workflow fragmentation, limited availability of user-friendly analytical and visualisation tools, uneven access to software, manual validation bottlenecks, computational constraints, and difficulties in data handling, standardisation, and sharing. Participants also proposed practical mitigation strategies for these priority challenges, supported by step-by-step guidance to help overcome key barriers. Together, these insights provide a roadmap toward more scalable, open-access, and collaborative software systems, which are increasingly essential to realise the full potential of PAM in global biodiversity monitoring.

Biodiversity assessment using passive acoustic monitoring has historically been challenging due to the limited availability of multi‐species acoustic detectors. In this context, acoustic indices were introduced as an alternative way to represent species diversity in acoustic datasets. Although there is increasing evidence that their effectiveness as a proxy for species diversity is limited, acoustic indices are still used and recommended for biodiversity research. Acoustic indices face structural issues, with a flawed theoretical basis and weak empirical support. Additionally, limited generalizability, dependence on context and inconsistent performance make it difficult to assess their value in the inferential process. Without a clear method to map acoustic indices into meaningful biological components, their interpretability is greatly compromised. Biodiversity assessment through acoustic monitoring benefits significantly from frameworks that use species as the fundamental analytical unit, even when misclassification might occur. In contrast, acoustic indices ignore species recognition due to their reliance on properties such as spectral distribution of acoustic energy and consequently limit the inference of causal links to species diversity. A variety of options are available to enhance species‐based biodiversity acoustic monitoring. We emphasize that manual annotation and single‐species detectors have contributed significantly to the field, and effective methods for multi‐species classification now exist. This has opened new paradigms and expanded opportunities for directly identifying target signals in audio data across a broad range of species. In the ongoing biodiversity crisis, resources should be prioritized for tools and approaches that provide managers and stakeholders with meaningful information on the composition, structure, and function of biodiversity. Acoustic indices are not suitable as reliable biodiversity indicators, and their continued use in biodiversity research is unjustifiable. Acoustic monitoring should leverage existing and emerging methods to extract species‐level data from recordings, offering more valuable and impactful contributions to ecology and conservation efforts.

Passive acoustic monitoring (PAM) enables non-invasive sampling of wildlife across broad spatial, temporal and taxonomic scales. Its ongoing and widespread use has generated unprecedented volumes of acoustic data, shifting the primary bottleneck from data collection to the storage, processing, integration, and interpretation of PAM outputs. Although many software tools exist to address these challenges, differences in their design, scope, and usability often create fragmented and complex analytical workflows. To identify the key barriers and opportunities shaping the implementation of PAM surveys, we conducted a structured expert solicitation involving 30 international practitioners working across terrestrial and aquatic ecosystems. Experts identified and ranked their most critical pain points in current PAM workflows, spanning data storage, processing, and interpretation. The top challenge identified related to accurate species identification using deep learning and artificial intelligence (AI) models, especially in noisy soundscapes or for underrepresented taxa. Eight additional priority challenges included workflow fragmentation, limited availability of user-friendly analytical and visualisation tools, uneven access to software, manual validation bottlenecks, computational constraints, and difficulties in data handling, standardisation, and sharing. Participants also proposed practical mitigation strategies for these priority challenges, supported by step-by-step guidance to help overcome key barriers. Together, these insights provide a roadmap toward more scalable, open-access, and collaborative software systems, which are increasingly essential to realise the full potential of PAM in global biodiversity monitoring.

Elevational migration is globally exhibited by montane bird species through elevational range shifts to track seasonal changes in weather patterns and resources. Studies investigating the patterns and mechanisms of such elevational shifts have been limited in spatial scale owing to the difficulty of sampling data across montane gradients. Here, we integrated data from the world's largest participatory science project (eBird) with systematic surveys to examine patterns and mechanisms that may explain bird elevational range shifts in the Nilgiri Hills of the Western Ghats Biodiversity Hotspot. We calculate the extent of shifts in elevational ranges for birds present year-round in the Nilgiris between the hottest and coldest months and quantify the associations between these shifts and species traits using phylogenetic generalized least squares regressions. We found that 77% (54/70) of the species investigated showed seasonal shifts in their elevational ranges. Birds in the Nilgiris showed nearly equal proportions of downslope (37%) and upslope (33%) winter shifts. All species had significant range overlap between seasons but employed different shifting strategies. Species with narrow thermal regimes predominantly shifted downslope in winter (niche tracking), while those with the widest thermal regimes shifted upslope (niche switching), revealing that species adapt to climatic variability through contrasting thermal strategies. Our results suggest that climatic constraints, specifically thermal regime, could be a major driver of seasonal shifts in elevational ranges of birds in the Nilgiris. Understanding these elevational shift strategies is critical for conservation planning in tropical montane systems facing accelerating climate change.

The impacts of colonial‐era ecosystem changes on tropical biodiversity are poorly understood. We analyzed a 170‐year dataset on land cover and bird observations in an Old World tropical montane landscape in the Western Ghats, India, to determine if and how historical landscape changes have impacted 85 bird species. A comparison of historical land cover and classified satellite imagery (1848–2018) revealed approximately an 80% decrease in grassland area and a concomitant increase in tea and timber plantations stemming from colonial‐era policies and associated legacies of large‐scale planting of cash crops and exotic woody species. We found that relative species abundances of about 90% of grassland birds have significantly declined while around 53% of forest bird species remained stable or even increased in relative abundance over the same period. Over 74% of generalist bird species have become more common over the same period, possibly due to reduced habitat specialization. Our findings show that colonial‐era policies, continued postindependence, of tree planting across open natural ecosystems have resulted in severe loss of grassland habitats and a concomitant decline in the relative abundance of grassland bird species.

Bird species vary widely in their diurnal vocalization patterns, and the drivers of this variation are not well understood. Using passive acoustic monitoring, we examined species-specific vocal activity patterns at dawn and dusk for a tropical bird community in the Western Ghats biodiversity hotspot in India. We tested whether environmental factors (e.g. signal transmission conditions, ambient light, and resource availability) and social factors (e.g. territoriality) best-explained patterns of diurnal variation in vocal activity. Overall, we found that species-specific vocal activity was significantly higher at dawn ( p < 0.05). Phylogenetic generalized least squares regressions revealed that territoriality and diet both predicted stronger dawn-biased activity. Specifically, highly territorial birds (standardized effect size (SES) = 1.20, lower donfidence interval (LCI)= 0.24, upper confidence interval (UCI) = 2.16, p = 0.01) and omnivores (SES = 0.82, LCI = −0.04, UCI = 1.68, p = 0.06) had higher levels of vocal activity at dawn. Surprisingly, we failed to find any evidence in support of environmental factors in explaining dawn-biased vocal activity. Our multi-taxon approach allowed us to assess the vocal activity patterns for an entire tropical bird community. Future research must incorporate additional geographic locations and combine visual and aural observations to better understand the drivers of diurnal variation in vocal activity. This article is part of the theme issue ‘Acoustic monitoring for tropical ecology and conservation’.

Aim: The urgency for remote, reliable and scalable biodiversity monitoring amidst mounting human pressures on ecosystems has sparked worldwide interest in Passive Acoustic Monitoring (PAM), which can track life underwater and on land. However, we lack a unified methodology to report this sampling effort and a comprehensive overview of PAM coverage to gauge its potential as a global research and monitoring tool. To address this gap, we created the Worldwide Soundscapes project, a collaborative network and growing database comprising metadata from 416 datasets across all realms (terrestrial, marine, freshwater and subterranean).Location: Worldwide, 12,343 sites, all ecosystem types.Time Period: 1991 to present.Major Taxa Studied: All soniferous taxa.Methods: We synthesise sampling coverage across spatial, temporal and ecological scales using metadata describing sampling locations, deployment schedules, focal taxa and audio recording parameters. We explore global trends in biological, anthropogenic and geophysical sounds based on 168 selected recordings from 12 ecosystems across all realms.Results: Terrestrial sampling is spatially denser (46 sites per million square kilometre—Mkm²) than aquatic sampling (0.3 and 1.8 sites/Mkm² in oceans and fresh water) with only two subterranean datasets. Although diel and lunar cycles are well sampled across realms, only marine datasets (55%) comprehensively sample all seasons. Across the 12 ecosystems selected for exploring global acoustic trends, biological sounds showed contrasting diel patterns across ecosystems, declined with distance from the Equator, and were negatively correlated with anthropogenic sounds.Main Conclusions: PAM can inform macroecological studies as well as global conservation and phenology syntheses, but representation can be improved by expanding terrestrial taxonomic scope, sampling coverage in the high seas and subterranean ecosystems, and spatio‐temporal replication in freshwater habitats. Overall, this worldwide PAM network holds promise to support cross‐realm biodiversity research and monitoring efforts.

Aim: Elevational migration is a globally ubiquitous animal behaviour. Understanding the mechanisms that drive variation in elevational movement can help explain the evolution of this widespread animal behaviour and its role in shaping montane life history. We examine the role of thermal regime (the intra‐annual variation in temperature experienced by a species), dispersal ability and diet in explaining the extent of elevational movements.Location: Eastern and Western Himalayas.Time Period: 2011–2022.Major Taxa Studied: Birds.Methods: We used community science data from eBird to acquire checklist‐based observations of birds and used comprehensive data cleaning procedures and randomization tests to produce estimates of seasonal elevational shifts for 302 species of Himalayan birds. Using these data, we ran phylogenetic least squares regressions (PGLS) to test if the extent of elevational shift is driven by thermal regime, dispersal ability and diet.Results: Most Himalayan birds (up to 65%) showed downslope shifts in the winter, although some (5%‐10%) low elevation species shifted upslope. Elevational shift was negatively associated with a species' thermal regime. Species that showed the greatest elevational shifts in both eastern and western Himalayas moved within the narrowest intra‐annual temperature regimes, but did not match their breeding range temperatures as closely as possible. Diet influenced elevational shift in both eastern and western Himalayas, while dispersal ability did not drive elevational shifts.Main Conclusions: Species that show the biggest elevational shifts track thermal regimes most closely. However, in addition to tracking thermal regimes, diet and potentially habitat availability/preferences may drive seasonal elevational shifts. Our results show convergent evolution of elevational shifts across clades. Low elevation habitats are important not only for conserving low elevation birds but also for conserving wintering sites of most high elevation breeders.