Protected areas (PAs) are a cornerstone of conservation efforts and now cover nearly 13% of the world's land surface, with the world's governments committed to expand this to 17%. However, as biodiversity continues to decline, the effectiveness of PAs in reducing the extinction risk of species remains largely untested. We analyzed PA coverage and trends in species' extinction risk at globally significant sites for conserving birds (10,993 Important Bird Areas, IBAs) and highly threatened vertebrates and conifers (588 Alliance for Zero Extinction sites, AZEs) (referred to collectively hereafter as ‘important sites’). Species occurring in important sites with greater PA coverage experienced smaller increases in extinction risk over recent decades: the increase was half as large for bird species with>50% of the IBAs at which they occur completely covered by PAs, and a third lower for birds, mammals and amphibians restricted to protected AZEs (compared with unprotected or partially protected sites). Globally, half of the important sites for biodiversity conservation remain unprotected (49% of IBAs, 51% of AZEs). While PA coverage of important sites has increased over time, the proportion of PA area covering important sites, as opposed to less important land, has declined (by 0.45–1.14% annually since 1950 for IBAs and 0.79–1.49% annually for AZEs). Thus, while appropriately located PAs may slow the rate at which species are driven towards extinction, recent PA network expansion has under-represented important sites. We conclude that better targeted expansion of PA networks would help to improve biodiversity trends.

Conservation planning is crucial for megadiverse countries where biodiversity is coupled with incomplete reserve systems and limited resources to invest in conservation. Using Peru as an example of a megadiverse country, we asked whether the national system of protected areas satisfies biodiversity conservation needs. Further, to complement the existing reserve system, we identified and prioritized potential conservation areas using a combination of species distribution modeling, conservation planning and connectivity analysis. Based on a set of 2,869 species, including mammals, birds, amphibians, reptiles, butterflies, and plants, we used species distribution models to represent species' geographic ranges to reduce the effect of biased sampling and partial knowledge about species' distributions. A site-selection algorithm then searched for efficient and complementary proposals, based on the above distributions, for a more representative system of protection. Finally, we incorporated connectivity among areas in an innovative post-hoc analysis to prioritize those areas maximizing connectivity within the system. Our results highlight severe conservation gaps in the Coastal and Andean regions, and we propose several areas, which are not currently covered by the existing network of protected areas. Our approach helps to find areas that contribute to creating a more representative, connected and efficient network.

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Acoustic indices are increasingly employed in the analysis of soundscapes to ascertain biodiversity value. However, conflicting results and lack of consensus on best practices for their usage has hindered their application in conservation and land‐use management contexts. Here we propose that the sensitivity of acoustic indices to ecological change and fidelity of acoustic indices to ecological communities are negatively impacted by signal masking. Signal masking can occur when acoustic responses of taxa sensitive to the effect of interest are masked by less‐sensitive acoustic groups, or target taxa sonification is masked by non‐target noise. We argue that by calculating acoustic indices at ecologically appropriate time and frequency bins, masking effects can be reduced and the efficacy of indices increased. We test this on a large acoustic dataset collected in Eastern Amazonia spanning a disturbance gradient of undisturbed, logged, burned, logged‐and‐burned and secondary forests. We calculated values for two acoustic indices: the Acoustic Complexity Index and the Bioacoustic Index, across the entire frequency spectrum (0–22.1 kHz), and four narrower subsets of the frequency spectrum; at dawn, day, dusk and night. We show that signal masking has a large impact on the sensitivity of acoustic indices to forest disturbance classes. Calculating acoustic indices at a range of narrower time–frequency bins substantially increases the classification accuracy of forest classes by random forest models. Furthermore, signal masking led to misleading correlations, including spurious inverse correlations, between biodiversity indicator metrics and acoustic index values compared to correlations derived from manual sampling of the audio data. Consequently, we recommend that acoustic indices are calculated either at a range of time and frequency bins, or at a single narrow bin, predetermined by a priori ecological understanding of the soundscape.

The increasing demand for cost-efficient biodiversity data at large spatiotemporal scales has led to an increase in the collection of large ecoacoustic datasets. Whilst the ease of collection and storage of audio data has rapidly increased and costs fallen, methods for robust analysis of the data have not developed so quickly. Identification and classification of audio signals to species level is extremely desirable, but reliability can be highly affected by non-target noise, especially rainfall. Despite this demand, there are few easily applicable pre-processing methods available for rainfall detection for conservation practitioners and ecologists. Here, we use threshold values of two simple measures, Power Spectrum Density (amplitude) and Signal-to-Noise Ratio at two frequency bands, to differentiate between the presence and absence of heavy rainfall. We assess the effect of using different threshold values on Accuracy and Specificity. We apply the method to four datasets from both tropical and temperate regions, and find that it has up to 99% accuracy on tropical datasets (e.g. from the Brazilian Amazon), but performs less well in temperate environments. This is likely due to the intensity of rainfall in tropical forests and its falling on dense, broadleaf vegetation amplifying the sound. We show that by choosing between different threshold values, informed trade-offs can be made between Accuracy and Specificity, thus allowing the exclusion of large amounts of audio data containing rainfall in all locations without the loss of data not containing rain. We assess the impact of using different sample sizes of audio data to set threshold values, and find that 200 15s audio files represents an optimal trade-off between effort, accuracy and specificity in most scenarios. This methodology and accompanying R package 'hardRain' is the first automated rainfall detection tool for pre-processing large acoustic datasets without the need for any additional rain gauge data.

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The continued loss, fragmentation, and degradation of forest habitats are driving an extinction crisis for tropical and subtropical bird species. This loss is particularly acute in the Atlantic Forest of South America, where it is unclear whether several endemic bird species are extinct or extant. We collate and model spatiotemporal distributional data for one such “lost” species, the Purple-winged Ground Dove Paraclaravis geoffroyi, a Critically Endangered endemic of the Atlantic Forest biome, which is nomadic and apparently dependent on masting bamboo stands. We compared its patterns of occurrence with that of a rare “control” forest pigeon, the Violaceous Quail-Dove Geotrygon violacea, which occurs in regional sympatry. We also solicit information from aviculturists who formerly kept the species. We find that the two species share a similar historical recording rate but can find no documentary evidence (i.e., specimens, photos, video, sound recordings) for the persistence of Purple-winged Ground Dove in the wild after the 1980s, despite periodic sighting records, and after which time citizen scientists frequently documented the control species in the wild. Assessments of the probability that the species is extant are sensitive to the method of analysis, and whether records lacking documentary evidence are considered credible. Analysis of the temporal sequence of past records reveals the extent of the historical range contraction of the Purple-winged Ground Dove, while our species distribution model highlights the geographic search priorities for field ornithologists hoping to rediscover the species—aided by the first recording of the species vocalizations which we obtained from interviews with aviculturists. Our interviews also revealed that the species persisted in captivity from the 1970s until the 1990s (up to 150 birds), until a law was passed obstructing captive breeding efforts by private individuals, putting an end to perhaps the best chance we had to save the species from extinction.

Aim Understanding patterns and drivers of variation in abundance across full species ranges is crucial in conservation science, but our knowledge of these forms and processes is limited, especially in the tropics. This study aims to: (1) identify patterns in variation of abundance across sites; (2) examine congruence of abundance hotspots across species and spatial autocorrelation of abundance within species; and (3) assess the nature and strength of environmental correlates of abundance (topography, habitat and human pressure). Location Twenty‐six sites across the full ranges of 14 dry forest bird species in northern Peru. Methods Study sites in this patchy habitat were selected within strata derived from species distribution models, while also ensuring geographic representation. Species abundance data from variable‐width transects were compared across sites and across range core versus edge; relationships between abundance and environmental variables were examined using GAMs, and spatial autocorrelation was examined with multivariate Mantel tests. Results Although most species were recorded at most sites, local abundance varied by one or two orders of magnitude. Several species showed a humped rather than the classic skewed abundance distribution, with abundance not necessarily highest at the centre of species’ ranges. Spatial autocorrelation in species’ local abundance was evident only at distances less than 55 km. Sites of maximum abundance for individual species did not coincide—nine different sites held highest densities of at least one species. Relationships between local abundance and almost all environmental correlates were non‐linear. Main conclusions The extreme variation in species abundances and the complexity in their relationships with environmental variables have important implications, both for design of conservation‐motivated surveys for which we offer some recommendations, and for the need for multiple reserves to capture high local abundances of key species.