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The latitudinal diversity gradient (LDG) is one of the most recognized global patterns of species richness exhibited across a wide range of taxa. Numerous hypotheses have been proposed in the past two centuries to explain LDG, but rigorous tests of the drivers of LDGs have been limited by a lack of high-quality global species richness data. Here we produce a high-resolution (0.025° × 0.025°) map of local tree species richness using a global forest inventory database with individual tree information and local biophysical characteristics from ~1.3 million sample plots. We then quantify drivers of local tree species richness patterns across latitudes. Generally, annual mean temperature was a dominant predictor of tree species richness, which is most consistent with the metabolic theory of biodiversity (MTB). However, MTB underestimated LDG in the tropics, where high species richness was also moderated by topographic, soil and anthropogenic factors operating at local scales. Given that local landscape variables operate synergistically with bioclimatic factors in shaping the global LDG pattern, we suggest that MTB be extended to account for co-limitation by subordinate drivers., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

One of the most fundamental questions in ecology is how many species inhabit the Earth. However, due to massive logistical and financial challenges and taxonomic difficulties connected to the species concept definition, the global numbers of species, including those of important and well-studied life forms such as trees, still remain largely unknown. Here, based on global ground-sourced data, we estimate the total tree species richness at global, continental, and biome levels. Our results indicate that there are ~73,000 tree species globally, among which ~9,000 tree species are yet to be discovered. Roughly 40% of undiscovered tree species are in South America. Moreover, almost one-third of all tree species to be discovered may be rare, with very low populations and limited spatial distribution (likely in remote tropical lowlands and mountains). These findings highlight the vulnerability of global forest biodiversity to anthropogenic changes in land use and climate, which disproportionately threaten rare species and thus, global tree richness. [ABSTRACT FROM AUTHOR]

Addressing serious environmental challenges, or wicked problems, locally and globally, we argue here that working collaboratively as scientist and humanist we are in a strategic position to help address biodiversity crises. We outline synergies that combine the strengths, tools, and fresh perspectives of soundscape ecology and sound studies in ethnomusicology. Our unique collaboration places sound at the core of our process but utilizes a community acoustics lens to bring both the sounds of nature and those of people together to couple our epistemologies, methodologies, and deep commitment to addressing the ecological needs today. [ABSTRACT FROM AUTHOR]

Non-invasive bioacoustic monitoring is becoming increasingly popular for biodiversity conservation. Two automated methods for acoustic classification of bird species currently used are frame-based methods, a model that uses Hidden Markov Models (HMMs), and event-based methods, a model consisting of descriptive measurements or restricted to tonal or harmonic vocalizations. In this work, we propose a new method for automated field recording analysis with improved automated segmentation and robust bird species classification. We used a Gaussian Mixture Model (GMM)-based frame selection with an event-energy-based sifting procedure that selected representative acoustic events. We employed a Mel, band-pass filter bank on each event's spectrogram. The output in each subband was parameterized by an autoregressive (AR) model, which resulted in a feature consisting of all model coefficients. Finally, a support vector machine (SVM) algorithm was used for classification. The significance of the proposed method lies in the parameterized features depicting the species-specific spectral pattern. This experiment used a control audio dataset and real-world audio dataset comprised of field recordings of eleven bird species from the Xeno-canto Archive, consisting of 2762 bird acoustic events with 339 detected “unknown” events (corresponding to noise or unknown species vocalizations). Compared with other recent approaches, our proposed method provides comparable identification performance with respect to the eleven species of interest. Meanwhile, superior robustness in real-world scenarios is achieved, which is expressed as the considerable improvement from 0.632 to 0.928 for the F-score metric regarding the “unknown” events. The advantage makes the proposed method more suitable for automated field recording analysis. [ABSTRACT FROM AUTHOR]

Modern biogeography now encompasses an impressive diversity of patterns and phenomena of the geography of nature, providing insights fundamental to understanding the forces influencing the spatial and temporal dynamics of biological diversity. However, rather than praise our discipline for its great breadth of visions, our purpose here is to point out our glaring oversight of a potentially transformative frontier in the geography of nature. A new, emerging area called soundscape ecology, if guided by the principles of biogeography, holds the promise of 'opening the ears' of our field and providing fresh perspectives on fundamental problems being addressed by biogeographers. [ABSTRACT FROM AUTHOR]

We determined the relationship between acoustic diversity and metrics of vertical forest structure derived from light detection and ranging (LIDAR) data in a neotropical rainforest in Costa Rica. We then used the LIDAR-derived metrics to predict acoustic diversity across the forest landscape. Sound recordings were obtained from 14 sites for six consecutive days during dusk chorus (6 pm). Acoustic diversity was calculated for each day as the total intensity across acoustic frequency bands using the Shannon index and then averaged over the 6 days at each site. A 10 m radius around each site was used to obtain several LIDAR-derived metrics describing the vertical structural attributes of the forest canopy. Multiple linear regression (MLR) with Akaike information criterion was used to determine a top-ranked model with acoustic diversity as the dependent variable and the LIDAR metrics as independent variables. Acoustic diversity was modeled for forested areas (where canopy height was >20 m) at 20 m resolution using coefficients obtained from the MLR, and a hotspot analysis was conducted on the resulting layer. Acoustic diversity was strongly correlated ( R = 0.75) with the LIDAR metrics suggesting that LIDAR-derived metrics can be used to determine canopy structural attributes important to vocal fauna species. The hotspot analysis revealed that the spatial distribution of these canopy structural attributes across the La Selva forest is not random. Our approach can be used to identify forest patches of potentially high acoustic diversity for conservation or management purposes. [ABSTRACT FROM AUTHOR]

Aim Human land use activities are creating a biodiversity crisis. However, it is not clear how species respond to different intensities of land use at a global scale. We used spatial analyses to determine the relationships between human settlements, croplands, rangelands and forests of varying intensities and the endangerment status of mammal species across the globe. In doing so, we sought to assess the role of different land use and land management strategies in global biodiversity conservation. Location Global. Methods A GIS database with distribution ranges for 4734 Red- Listed and non-threatened terrestrial mammal species was obtained from the IUCN and combined with the global anthropogenic biomes dataset, which uses population density class (dense, residential, populated and remote) as a proxy for land use intensity. Ordered logistic regression was used to predict the effect of each land use intensity class on the probability of having a more endangered IUCN status for all mammal species together and for species within major mammal groups separately. Results The probability of having a more endangered status generally increased for mammal species as the proportion of urban settlements, mosaic and cropped 'villages', and residential and populated croplands within their distribution ranges increased. In contrast, endangerment probability of mammals decreased with proportion of irrigated, pastoral and rainfed 'villages', remote croplands and all rangeland classes. Endangerment probability also decreased with proportion of wildlands and remote forests, but increased with proportion of populated forests for several mammal groups. Main conclusions Urbanization and high-intensity crop production pose a significant threat to mammals worldwide. In contrast, rangelands, low-intensity croplands and certain low-intensity human settlements may in fact help maintain mammal diversity at global scales. While the area of wild habitat available to species is also highly important for biodiversity conservation, forested lands that are disturbed or over utilized by humans do not benefit and may even endanger species. [ABSTRACT FROM AUTHOR]

• Seven acoustic indices are tested using three controlled computational experiments. • Three acoustic dimensions of bird vocalizations affect acoustic indices' performance. • H, ADI, and AEI show moderate correlations with avian species richness. • ADI is relatively more robust regarding bird species richness surveys. Passive acoustic monitoring of biotic sounds is increasingly popular in conservation biology. Among vocalizing animals, birds are most frequently studied and multiple acoustic indices have been proposed for rapid acoustic assessment of avian diversity. Preliminary results suggest that several indices can be used as proxies for bird species richness, however it is still unclear to what extent different conditions of bird vocalizations affect the relationship between indices and bird species richness – should it matter if the bird vocalizations contain different sound unit shapes, or if the frequency of vocalization occurrence differs, or if the vocalizations are made with various intensities? In this work, seven commonly used acoustic indices were tested using three controlled computational experiments with real-world recordings to provide an objective measure of each index's performance for answering the aforementioned questions. In the experiments, different options of sound unit shape and frequency of vocalization occurrence were precisely controlled and intensity variations were expressed as different signal-to-noise ratios (SNR) of the vocalizations. The first experiment showed that three indices (the acoustic entropy index (H), acoustic diversity index (ADI), and acoustic evenness index (AEI)) performed better than the other four, showing moderate correlations with avian species richness. The second experiment revealed that ADI for each sound unit shape tended towards a constant value with increasing frequency of vocalization occurrence while the influence from frequency of vocalization occurrence on H and AEI varied with different sound unit shape options. Our third experiment showed that the vocalization intensity affected the values of these three indices while the performance disparity among different sound unit shapes for only ADI explicitly appeared a decreasing tendency with increasing vocalization intensities. We conclude that ADI, among the tested indices, is relatively more robust with regard to bird species richness surveys when sound unit shape, frequency of vocalization occurrence, and vocalization intensity are considered. Meanwhile, since multiple indices are usually applied together to provide a comprehensive observation, the above acoustic dimensions should be taken into account especially in comparative research of different bird communities. [ABSTRACT FROM AUTHOR]