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As threats to species continue to increase, precise and unbiased measures of the impact these pressures are having on global biodiversity are urgently needed. Some existing indicators of the status and trends of biodiversity largely rely on publicly available data from the scientific and grey literature, and are therefore prone to biases introduced through over-representation of well-studied groups and regions in monitoring schemes. This can give misleading estimates of biodiversity trends. Here, we report on an approach to tackle taxonomic and geographic bias in one such indicator (Living Planet Index) by accounting for the estimated number of species within biogeographical realms, and the relative diversity of species within them. Based on a proportionally weighted index, we estimate a global population decline in vertebrate species between 1970 and 2012 of 58% rather than 20% from an index with no proportional weighting. From this data set, comprising 14,152 populations of 3,706 species from 3,095 data sources, we also find that freshwater populations have declined by 81%, marine populations by 36%, and terrestrial populations by 38% when using proportional weighting (compared to trends of -46%, +12% and +15% respectively). These results not only show starker declines than previously estimated, but suggests that those species for which there is poorer data coverage may be declining more rapidly.

Pollinating species are in decline globally, with land use an important driver. However, most of the evidence on which these claims are made is patchy, based on studies with low taxonomic and geographic representativeness. Here, we model the effect of land-use type and intensity on global pollinator biodiversity, using a local-scale database covering 303 studies, 12,170 sites, and 4502 pollinating species. Relative to a primary vegetation baseline, we show that low levels of intensity can have beneficial effects on pollinator biodiversity. Within most anthropogenic land-use types however, increasing intensity is associated with significant reductions, particularly in urban (43% richness and 62% abundance reduction compared to the least intensive urban sites), and pasture (75% abundance reduction) areas. We further show that on cropland, the strongly negative response to intensity is restricted to tropical areas, and that the direction and magnitude of response differs among taxonomic groups. Our findings confirm widespread effects of land-use intensity on pollinators, most significantly in the tropics, where land use is predicted to change rapidly. Anthropogenic losses of animal pollinators threaten ecosystem functioning. Here the authors report a global analysis showing geographically varied yet widespread declines of pollinator diversity and abundance with land use intensification, particularly in tropical biomes.

Passive acoustic sensing has emerged as a powerful tool for quantifying anthropogenic impacts on biodiversity, especially for echolocating bat species. To better assess bat population trends there is a critical need for accurate, reliable, and open source tools that allow the detection and classification of bat calls in large collections of audio recordings. The majority of existing tools are commercial or have focused on the species classification task, neglecting the important problem of first localizing echolocation calls in audio which is particularly problematic in noisy recordings. We developed a convolutional neural network based open-source pipeline for detecting ultrasonic, full-spectrum, search-phase calls produced by echolocating bats. Our deep learning algorithms were trained on full-spectrum ultrasonic audio collected along road-transects across Europe and labelled by citizen scientists from www.batdetective.org. When compared to other existing algorithms and commercial systems, we show significantly higher detection performance of search-phase echolocation calls with our test sets. As an example application, we ran our detection pipeline on bat monitoring data collected over five years from Jersey (UK), and compared results to a widely-used commercial system. Our detection pipeline can be used for the automatic detection and monitoring of bat populations, and further facilitates their use as indicator species on a large scale. Our proposed pipeline makes only a small number of bat specific design decisions, and with appropriate training data it could be applied to detecting other species in audio. A crucial novelty of our work is showing that with careful, non-trivial, design and implementation considerations, state-of-the-art deep learning methods can be used for accurate and efficient monitoring in audio.

Navigational control of avian migration is understood, largely from the study of terrestrial birds, to depend on either genetically or culturally inherited information. By tracking the individual migrations of Atlantic Puffins, Fratercula arctica, in successive years using geolocators, we describe migratory behaviour in a pelagic seabird that is apparently incompatible with this view. Puffins do not migrate to a single overwintering area, but follow a dispersive pattern of movements changing through the non-breeding period, showing great variability in travel distances and directions. Despite this within-population variability, individuals show remarkable consistency in their own migratory routes among years. This combination of complex population dispersion and individual route fidelity cannot easily be accounted for in terms of genetic inheritance of compass instructions, or cultural inheritance of traditional routes. We suggest that a mechanism of individual exploration and acquired navigational memory may provide the dominant control over Puffin migration, and potentially some other pelagic seabirds, despite the apparently featureless nature of the ocean.

Time series are a critical component of ecological analysis, used to track changes in biotic and abiotic variables. Information can be extracted from the properties of time series for tasks such as classification (e.g., assigning species to individual bird calls); clustering (e.g., clustering similar responses in population dynamics to abrupt changes in the environment or management interventions); prediction (e.g., accuracy of model predictions to original time series data); and anomaly detection (e.g., detecting possible catastrophic events from population time series). These common tasks in ecological research all rely on the notion of (dis‐) similarity, which can be determined using distance measures. A plethora of distance measures have been described, predominantly in the computer and information sciences, but many have not been introduced to ecologists. Furthermore, little is known about how to select appropriate distance measures for time‐series‐related tasks. Therefore, many potential applications remain unexplored. Here, we describe 16 properties of distance measures that are likely to be of importance to a variety of ecological questions involving time series. We then test 42 distance measures for each property and use the results to develop an objective method to select appropriate distance measures for any task and ecological dataset. We demonstrate our selection method by applying it to a set of real‐world data on breeding bird populations in the UK and discuss other potential applications for distance measures, along with associated technical issues common in ecology. Our real‐world population trends exhibit a common challenge for time series comparisons: a high level of stochasticity. We demonstrate two different ways of overcoming this challenge, first by selecting distance measures with properties that make them well suited to comparing noisy time series and second by applying a smoothing algorithm before selecting appropriate distance measures. In both cases, the distance measures chosen through our selection method are not only fit‐for‐purpose but are consistent in their rankings of the population trends. The results of our study should lead to an improved understanding of, and greater scope for, the use of distance measures for comparing ecological time series and help us answer new ecological questions.

Camera trap surveys are a popular ecological monitoring tool that produce vast numbers of images making their annotation extremely time‐consuming. Advances in machine learning, in the form of convolutional neural networks, have demonstrated potential for automated image classification, reducing processing time. These networks often have a poor ability to generalise, however, which could impact assessments of species in habitats undergoing change. Here, we (i) compare the performance of three network architectures in identifying species in camera trap images taken from tropical forest of varying disturbance intensities; (ii) explore the impacts of training dataset configuration; (iii) use habitat disturbance categories to investigate network generalisability and (iv) test whether classification performance and generalisability improve when using images cropped to bounding boxes. Overall accuracy (72.8%) was improved by excluding the rarest species and by adding extra training images (76.3% and 82.8%, respectively). Generalisability to new camera locations within a disturbance level was poor (mean F1‐score: 0.32). Performance across unseen habitat disturbance levels was worse (mean F1‐score: 0.27). Training the network on multiple disturbance levels improved generalisability (mean F1‐score on unseen disturbance levels: 0.41). Cropping images to bounding boxes improved overall performance (F1‐score: 0.77 vs. 0.47) and generalisability (mean F1‐score on unseen disturbance levels: 0.73), but at a cost of losing images that contained animals which the detector failed to detect. These results suggest researchers should consider using an object detector before passing images to a classifier, and an improvement in classification might be seen if labelled images from other studies are added to their training data. Composition of training data was shown to be influential, but including rarer classes did not compromise performance on common classes, providing support for the inclusion of rare species to inform conservation efforts. These findings have important implications for use of these methods for long‐term monitoring of habitats undergoing change, as they highlight the potential for misclassifications due to poor generalisability to impact subsequent ecological analyses. These methods therefore need to be considered as dynamic, in that changes to the study site would need to be reflected in the updated training of the network.

Background Racial/ethnic inequities along the HIV care continuum persist in the United States despite substantial federal investment. Numerous studies highlight individual and social-level impediments in HIV, but fewer foreground systemic barriers. The present qualitative study sought to uncover and describe systemic barriers to the HIV care continuum from the perspectives of African American/Black and Latino persons living with HIV (PLWH) with unsuppressed HIV viral load, including how barriers operated and their effects. Methods Participants were African American/Black and Latino PLWH with unsuppressed HIV viral load (N = 41). They were purposively sampled for maximum variability on key indices from a larger study. They engaged in semi-structured in-depth interviews that were audio-recorded and professionally transcribed. Data were analyzed using directed content analysis. Results Participants were 49 years old, on average (SD = 9), 76% were assigned male sex at birth, 83% were African American/Black and 17% Latino, 34% were sexual minorities (i.e., non-heterosexual), and 22% were transgender/gender-nonbinary. All had indications of chronic poverty. Participants had been diagnosed with HIV 19 years prior to the study, on average (SD = 9). The majority (76%) had taken HIV medication in the six weeks before enrollment, but at levels insufficient to reach HIV viral suppression. Findings underscored a primary theme describing chronic poverty as a fundamental cause of poor engagement. Related subthemes were: negative aspects of congregate versus private housing settings (e.g., triggering substance use and social isolation); generally positive experiences with health care providers, although structural and cultural competency appeared insufficient and managing health care systems was difficult; pharmacies illegally purchased HIV medication from PLWH; and COVID-19 exacerbated barriers. Participants described mitigation strategies and evidenced resilience. Conclusions To reduce racial/ethnic inequities and end the HIV epidemic, it is necessary to understand African American/Black and Latino PLWH’s perspectives on the systemic impediments they experience throughout the HIV care continuum. This study uncovers and describes a number of salient barriers and how they operate, including unexpected findings regarding drug diversion and negative aspects of congregate housing. There is growing awareness that systemic racism is a core determinant of systemic barriers to HIV care continuum engagement. Findings are interpreted in this context.

Background American/Black and Latine (AABL) young/emerging adults living with HIV in the United States (US) have consistently failed to meet targets for HIV care/medication engagement. Among this population, those with non-suppressed HIV viral load are understudied, along with immigrants and those with serious socioeconomic deprivation. Guided by social action theory, we took a mixed methods approach (sequential explanatory design) to describe sociodemographic, background, and contextual factors, and their relationships to HIV management, among a diverse cohort. Methods Participants ( N  = 271) received structured baseline assessments and HIV viral load testing. Primary outcomes were being well-engaged in HIV care and HIV viral suppression. A subset ( N  = 41) was purposively sampled for maximum variability for in-depth interviews. Quantitative data were analyzed with descriptive statistics and logistic regression, and used to develop a research question about life contexts. Qualitative data were analyzed with directed content analysis, and the joint display method was used to integrate results. Results Participants were 25 years old, on average (SD = 2). The majority (59%) were Latine/Hispanic and the reminder African American/Black. Almost all were assigned male sex at birth (96%) and sexual minorities (93%). Half (49%) were born outside the US and 33% spoke primarily Spanish. They were diagnosed with HIV four years prior on average (SD = 3). Most were well-engaged in HIV care (72%) and evidenced viral suppression (81%). Speaking Spanish was associated with a higher odds of care engagement, and adverse childhood experiences and income from federal benefits were associated with a lower odds. None of the factors predicted viral suppression. Qualitative results highlighted both developmentally typical (insufficient financial resources, unstable housing) and atypical challenges (struggles with large bureaucracies, HIV disclosure, daily medication use). Federal benefits and the local HIV social services administration were critical to survival. Immigrant participants came to the US to escape persecution and receive HIV care, but HIV management was often disrupted. Overall qualitative results highlighted both risk and protective factors, and resilience. Qualitative results added detail, nuance, and richness to the quantitative findings. Conclusions The present study advances what is known about the backgrounds and contexts of diverse and understudied AABL young/emerging adults living with HIV.

Bio‐logging has revealed much about high‐latitude seabird migratory strategies, but migratory behaviour in tropical species may differ, with implications for understanding nutrient deposition. Here we use combined light‐level and saltwater immersion loggers to study the year‐round movement behaviour of adult red‐footed boobies Sula sula rubripes from the Chagos Archipelago, tropical Indian Ocean, to assess migratory movements and estimate nutrient deposition rates based on the number of days they spent ashore. Light levels suggest that red‐footed boobies are resident in the Chagos Archipelago year‐round, although there are large latitudinal errors this close to the equator. Immersion data also indicate residency with tracked birds returning to land every one or two days. Spending an average of 79.86 ± 2.80 days and 280.84 ± 2.64 nights per year on land allows us to estimate that the 21 670 pairs of red‐footed boobies deposit 37.34 ± 0.56 tonnes year−1 of guano‐derived nitrogen throughout the archipelago. Our findings have implications for tropical seabird conservation and phylogenetics, as well as for assessing the impact of seabird nutrients on coral reef ecosystems.