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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.

Abstract 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.

Abstract 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.

Abstract 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.

Abstract Background The persistence of racial/ethnic inequities in rates of engagement along the HIV care continuum signals the need for novel approaches. We developed six behavioral intervention components for use in an optimization trial, grounded in a model that integrates critical race theory, harm reduction, and self-determination theory, designed to address various barriers that African American/Black and Latino persons living with HIV (PLWH) experience to the HIV care continuum. The components were: health education, motivational interviewing sessions, pre-adherence skill building, peer mentorship, focused support groups, and navigation. The present qualitative exploratory study describes participants’ perspectives on the components’ acceptability, feasibility, and impact. Methods Participants were African American/Black and Latino PLWH poorly engaged in HIV care and with non-suppressed HIV viral load in New York City. From a larger trial, we randomly selected 46 participants for in-depth semi-structured interviews. Interviews were audio-recorded and transcribed verbatim, and data were analyzed using directed content analysis. Quantitative data on sociodemographic and background characteristics and components’ acceptability and feasibility were also collected. Results On average, participants were 49 years old and had lived with HIV for 19 years. Most were cisgender-male and African American/Black. Participants reported a constellation of serious social and structural challenges to HIV management including chronic poverty, unstable housing, and stigma. Across components, a non-judgmental and pressure-free approach and attention to structural and cultural factors were seen as vital to high levels of engagement, but lacking in most medical/social service settings. Prominent aspects of individual components included establishing trust (health education); developing intrinsic motivation, goals, and self-reflection (motivational interviewing sessions); learning/practicing adherence strategies and habits (pre-adherence skill building); reducing social isolation via peer role models (peer mentorship); reflecting on salient goals and common challenges with peers without stigma (focused support groups); and circumventing structural barriers to HIV management with support (navigation). Components were found acceptable and feasible. Findings suggested ways components could be improved. Conclusions The present study advances research on interventions for African American/Black and Latino PLWH, who experience complex barriers to engagement along the HIV care continuum. Future study of the components is warranted to address racial/ethnic health inequities in HIV.

IntroductionVirtual and low-touch behavioral interventions are needed for African American/Black and Latino persons living with HIV (PLWH) with barriers to HIV viral suppression, particularly during COVID-19. Guided by the multiphase optimization strategy, we explored three components for PLWH without viral suppression, grounded in motivational interviewing and behavioral economics: (1) motivational interviewing counseling, (2) 21-weeks of automated text messages and quiz questions about HIV management, and (3) financial rewards for viral suppression (lottery prize vs. fixed compensation).MethodsThis pilot optimization trial used sequential explanatory mixed methods to explore the components' feasibility, acceptability, and preliminary evidence of effects using an efficient factorial design. The primary outcome was viral suppression. Participants engaged in baseline and two structured follow-up assessments over an 8-month period, and provided laboratory reports to document HIV viral load. A subset engaged in qualitative interviews. We carried out descriptive quantitative analyses. Then, qualitative data were analyzed using directed content analysis. Data integration used the joint display method.ResultsParticipants (N = 80) were 49 years old, on average (SD = 9), and 75% were assigned male sex at birth. Most (79%) were African American/Black, and the remainder were Latino. Participants were diagnosed with HIV 20 years previously on average (SD = 9). Overall, components were feasible (>80% attended) and acceptability was satisfactory. A total of 39% (26/66) who provided laboratory reports at follow-up evidenced viral suppression. Findings suggested no components were entirely unsuccessful. The lottery prize compared to fixed compensation was the most promising component level. In qualitative analyses, all components were seen as beneficial to individual wellbeing. The lottery prize appeared more interesting and engaging than fixed compensation. However, structural barriers including financial hardship interfered with abilities to reach viral suppression. The integrated analyses yielded areas of convergence and discrepancy and qualitative findings added depth and context to the quantitative results.ConclusionsThe virtual and/or low-touch behavioral intervention components tested are acceptable and feasible and show enough potential to warrant refinement and testing in future research, particularly the lottery prize. Results must be interpreted in the context of the COVID-19 pandemic.Trial registrationNCT04518241 (https://clinicaltrials.gov/ct2/show/NCT04518241).

Humanity benefits immensely from nature, including through cultural ecosystem services. Geotagged crowdsourced data provide an opportunity to characterize these services at large scales. Flickr data, for example, have been widely used as an indicator of recreational value, while Wikipedia data are increasingly being used as a measure of public interest, potentially capturing often overlooked and less-tangible aspects of socio-cultural values (such as educational, inspirational, and spiritual values). So far, few studies have explored how various geotagged crowdsourced data complement each other, or how correlated these may be, particularly at national scales. To address this knowledge gap, we compare Flickr and Wikipedia datasets in their ability to help characterize the sociocultural value of designated areas in England and assess how this value relates to species richness. Our results show that there was at least one Flickr photo in 35% of all designated areas in England, and at least one Wikipedia page in 60% of them. The Wikipedia and Flickr data were shown not to be independent of each other and were significantly correlated. Species richness was positively and significantly associated with the presence of at least one geotagged Wikipedia page; more biodiverse designated areas, however, were not any more likely to have at least one Flickr photo within them. Our results highlight the potential for new, emerging datasets to capture and communicate the socio-cultural value of nature, building on the strengths of more established crowdsourced data.

Abstract We are in the midst of a revolution in satellite technology, with the rapid development and advancement of small satellites (or SmallSats, i.e., satellites

To effectively combat the biodiversity crisis, we need ambitious targets and reliable indicators to accurately track trends and measure conservation impact. In Canada, the Living Planet Index (LPI) has been adapted to produce a national indicator by both World Wildlife Fund-Canada (Canadian Living Planet Index; C-LPI) and Environment and Climate Change Canada (Canadian Species Index) to provide insight into the status of Canadian wildlife, by evaluating temporal trends in vertebrate population abundance. The indicator includes data for just over 50% of Canadian vertebrate species. To assess whether the current dataset is representative of the distribution of life history characteristics of Canadian wildlife, we analyzed the representation of species-specific biotic variables (i.e., body size, trophic level, lifespan) for vertebrates within the C-LPI compared to native vertebrates lacking LPI data. Generally, there was considerable overlap in the distribution of biotic variables for species in the C-LPI compared to native Canadian vertebrate species lacking LPI data. Nevertheless, some differences among distributions were found, driven in large part by discrepancy in the representation of fishes—where the C-LPI included larger-bodied and longer-lived species. We provide recommendations for targeted data collection and additional analyses to further strengthen the applicability, accuracy, and representativity of biodiversity indicators.

Abstract Ranger‐led law enforcement patrols are the primary, site‐level response to – and the most common source of data on – illegal activity threatening wildlife in protected areas. Yet evidence that patrols effectively deter rule‐breaking is limited, and common management metrics for evaluating deterrence, which use ranger‐collected data, are particularly vulnerable to bias. “Differenced plots” (of the association between change in patrol effort and subsequent change in illegal activity) were recently proposed as a simple, new metric for deterrence, which, in tests with simulated patrol data, were more robust than the common alternatives. Here, we trial application of differenced plots to real patrol data collected in four protected areas, and explore methods for applying the metric in practice, using two indicators of rule‐breaking: snares, and people. We find evidence which is consistent with deterrence in some but not all sites, over shorter timescales than observed hitherto: increases in patrol effort were associated with subsequent reductions in snaring in one site, and in the presence of people in two sites. However, whether pressure on wildlife had been reduced or merely displaced was unclear from differenced plots, nor could the metric confirm absence of deterrence, raising questions for future applications. Our findings suggest differenced plots can be a useful metric, particularly for exploring variation in deterrence within sites, but should be applied and interpreted with care, and further work is urgently needed to determine whether and how patrols deter illegal activity, and to evaluate the effect reliably.

Abstract Mutual reinforcement between abiotic and biotic factors can drive small populations into a catastrophic downward spiral to extinction—a process known as the “extinction vortex.” However, empirical studies investigating extinction dynamics in relation to species' traits have been lacking. We assembled a database of 35 vertebrate populations monitored to extirpation over a period of at least ten years, represented by 32 different species, including 25 birds, five mammals, and two reptiles. We supplemented these population time series with species‐specific mean adult body size to investigate whether this key intrinsic trait affects the dynamics of populations declining toward extinction. We performed three analyses to quantify the effects of adult body size on three characteristics of population dynamics: time to extinction, population growth rate, and residual variability in population growth rate. Our results provide support for the existence of extinction vortex dynamics in extirpated populations. We show that populations typically decline nonlinearly to extinction, while both the rate of population decline and variability in population growth rate increase as extinction is approached. Our results also suggest that smaller‐bodied species are particularly prone to the extinction vortex, with larger increases in rates of population decline and population growth rate variability when compared to larger‐bodied species. Our results reaffirm and extend our understanding of extinction dynamics in real‐life extirpated populations. In particular, we suggest that smaller‐bodied species may be at greater risk of rapid collapse to extinction than larger‐bodied species, and thus, management of smaller‐bodied species should focus on maintaining higher population abundances as a priority.

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.

Multi-species indices (MSI) are widely used as ecological indicators and as instruments to inform environmental policies. Many of these indices combine species-specific estimates of relative population sizes using the geometric mean. Because the geometric mean is not defined when values of zero occur, usually only commoner species are included in MSIs and zero values are replaced by a small non-zero value. The latter can exhibit an arbitrary influence on the geometric mean MSI. Here, we show how the compound Poisson and the negative binomial model can be used in such cases to obtain an MSI that has similar features to the geometric mean, including weighting halving and doubling of a species’ population equally. In contrast to the geometric mean, these two statistical models can handle zero values in population sizes and thus accommodate newly occurring and temporarily or permanently disappearing species in the MSI. We compare the MSIs obtained by the two statistical models with the geometric mean MSI and measure sensitivity to changes in evenness and to population trends in rare and abundant species. Additionally, we outline sources of uncertainty and discuss how to measure them. We found that, in contrast to the geometric mean and the negative binomial MSI, the compound Poisson MSI is less sensitive to changes in evenness when total abundance is constant. Further, we found that the compound Poisson model can be influenced more than the other two methods by trends of species showing a low interannual variance. The negative binomial MSI is less sensitive to trends in rare species compared with the other two methods, and similarly sensitive to trends in abundant species as the geometric mean. While the two new MSIs have the advantage that they are not arbitrarily influenced by rare, newly appearing and disappearing species, both do not weight all species equally. We recommend replacing the geometric mean MSI with either compound Poisson or negative binomial when there are species with a population size of zero in some years having a strong influence on the geometric mean MSI. Further, we recommend providing additional information alongside the MSIs. For example, it is particularly important to give an evenness index in addition to the compound Poisson MSI and to indicate the number of disappearing and newly occurring species alongside the negative binomial MSI.

Monitoring wildlife populations is essential if global targets to reverse biodiversity declines are to be met. Recent analysis of data from the UK’s long-term National Bat Monitoring Programme (NBMP) suggests stable or increasing population trends for many bat species, and these statistics help inform progress towards national biodiversity targets. However, although based on robust citizen science survey designs, it is unknown how sensitive these trends are to spatial and environmental biases. Here we use Bayesian hierarchical modelling with integrated nested Laplace approximation (INLA), to examine the impact of these types of biases on the population trends using relative occupancy of four species monitored by the NBMP Field Survey in Great Britain (GB): Pipistrellus pipistrellus, P. pygmaeus, Nyctalus noctula and Eptesicus serotinus. Where possible, we also disaggregated trends to national levels using the best model per species to determine if national differences in trends remain once sampling biases are accounted for. Although we found evidence of spatial clustering in the NBMP Field Survey locations, the previously reported GB-wide population trends are broadly robust to spatial autocorrelation. In most species, accounting for spatial autocorrelation and species-environment relationships improved model fit. The nationally disaggregated models highlighted that GB-wide trends mask differences between England and Scotland, consistent with previous analysis of these data, as well as illustrating large gaps in survey effort, especially in Wales. We suggest that although bat population trends were found to be broadly robust to sampling biases present in these data, small differences could propagate over time and this impact is likely to be more severe in less structured citizen science data. Therefore, ensuring trends are robust to sampling biases present in citizen science datasets is critical to effective monitoring of progress towards biodiversity targets, managing populations sustainably, and ultimately a reversal of global declines.

We produced a biodiversity indicator, the Canadian Species Index (CSI), by gathering abundance data for Canadian vertebrate populations and adapting the Living Planet Index methodology. The final indicator incorporates over 3000 abundance time series and contains data for more than 50% of Canadian native vertebrate species. Species abundance declined by an average 10% between 1970 and 2014, with trends varying across taxonomic groups. To facilitate the interpretation of the indicator and contribute to the transparency of the reporting process, here we present a discussion of the indicator’s coverage, data quality and data gaps. Using data collected for other purposes means the dataset inherits the biases in biodiversity monitoring. We therefore assessed taxonomic and geographic coverage of the data underlying the indicator to highlight which areas and groups are under-represented. Birds are comprehensively monitored across Canada and are considered good indicators of the state of the environment. Other taxonomic groups are less well monitored, and the data available for these groups often consist of shorter and less full time series, representing smaller segments of the national population. A disaggregation based on data quality appears to show that trends based on species with lower quality data are more negative than for species with higher quality data. We discuss possible sources of the difference, including the relationship between taxon and data quality. Additional data collection on species contributing to the lower-quality subsets is needed to confirm negative trends.

The production of palm oil has considerable implications for tropical biodiversity. Increasing the environmental, social and governance (ESG) transparency and disclosure of the industry will contribute towards sustainable consumption and production practices. Here, we present a method for producing an index to measure changes in ESG disclosure in the palm oil sector over time based on data collected on SPOTT (Sustainability Policy Transparency Toolkit). The SPOTT Index is based on the number of points scored by a company during an annual assessment, and the number of companies that were included in that assessment time period. The SPOTT Index shows that ESG disclosure of palm oil companies measured improved between 2014 and 2018. Although we demonstrate proof of concept based on a limited number of companies, continued growth of SPOTT will enable the production of a powerful metric in ESG disclosure beyond palm oil and also serve to incentivise sustainable production and consumption in the sector.

Abstract Given the current biodiversity crisis, pragmatic approaches to detect global conservation trends across a broad range of taxa are critical. A sampled approach to the Red List Index (RLI) was proposed, as many groups are highly speciose. However, a decade after its conception, the recommended 900 species sample has only been implemented in six groups and trend data are available for none, potentially because this sample is unfeasibly high. Using a broader set of all available data we show that when re‐assessments are conducted every 10 years, 200 species (400 in some cases) should be sufficient to detect a RLI trend. Correctly detecting changes in slope still requires samples of 900 species (11,000 in some cases). Sampled assessments can accelerate biodiversity monitoring and complement current metrics, but the time‐period between assessments and the approaches’ purpose should be carefully considered, as there is a trade‐off between sample size and the resulting indices.

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.

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.

The sun has long been thought to guide bird navigation as the second step in a two-stage process, in which determining position using a map is followed by course setting using a compass, both over unfamiliar and familiar terrain. The animal's endogenous clock time-compensates the solar compass for the sun's apparent movement throughout the day, and this allows predictable deflections in orientation to test for the compass' influence using clock-shift manipulations. To examine the influence of the solar compass during a highly familiar navigational task, 24 clock-shifted homing pigeons were precision-tracked from a release site close to and in sight of their final goal, the colony loft. The resulting trajectories displayed significant partial deflection from the loft direction as predicted by either fast or slow clock-shift treatments. The partial deflection was also found to be stable along the entire trajectory indicating regular updating of orientation via input from the solar compass throughout the final approach flight to the loft. Our results demonstrate that time-compensated solar cues are deeply embedded in the way birds orient during homing flight, are accessed throughout the journey and on a remarkably fine-grained scale, and may be combined effectively simultaneously with direct guidance from familiar landmarks, even when birds are flying towards a directly visible goal.

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.

BACKGROUND: Determining the foraging movements of pelagic seabirds is fundamental for their conservation. However, the vulnerability and elusive lifestyles of these animals have made them notoriously difficult to study. Recent developments in satellite telemetry have enabled tracking of smaller seabirds during foraging excursions. METHODOLOGY/PRINCIPAL FINDINGS: Here, we report the first successful precision tracking of a c. 700 g seabird, the vulnerable Black Petrel, Procellaria parkinsoni, foraging at sea during the breeding season, using miniature GPS-logging technology. Employing a combination of high-resolution fixes and low-power duty-cycles, we present data from nine individual foraging excursions tracked during the chick-rearing period in February 2006. CONCLUSIONS/SIGNIFICANCE: We provide a snapshot of the species' foraging range and behaviour in relation to detailed underlying bathymetry off the coast of New Zealand, finding a significant relationship between foraging movements and regions of the shelf-break. We also highlight the potential of more sophisticated analyses to identify behavioural phenomena from position data alone.

This article describes the methods that were used to evaluate the "Blackboard Basics" and "Teaching in Blackboard" courses that are currently being offered by the Office of e-Learning at a southeastern university in the United States. This report includes a description of the background of this course, the purpose of the evaluation, the key questions that were investigated, data collection methods and instrumentation, and limitations. (Contains 2 tables and 1 figure.)