Individual identification in acoustic recordings.

Recent advances in bioacoustics combined with acoustic individual identification (AIID) could open frontiers for ecological and evolutionary research because traditional methods of identifying individuals are invasive, expensive, labor-intensive, and potentially biased. Despite overwhelming evidence that most taxa have individual acoustic signatures, the application of AIID remains challenging and uncommon. Furthermore, the methods most commonly used for AIID are not compatible with many potential AIID applications. Deep learning in adjacent disciplines suggests opportunities to advance AIID, but such progress is limited by training data. We suggest that broadscale implementation of AIID is achievable, but researchers should prioritize methods that maximize the potential applications of AIID, and develop case studies with easy taxa at smaller spatiotemporal scales before progressing to more difficult scenarios.

Aquatic Soundscape Recordings Reveal Diverse Vocalizations and Nocturnal Activity of an Endangered Frog.

AbstractAutonomous sensors provide opportunities to observe organisms across spatial and temporal scales that humans cannot directly observe. By processing large data streams from autonomous sensors with deep learning methods, researchers can make novel and important natural history discoveries. In this study, we combine automated acoustic monitoring with deep learning models to observe breeding-associated activity in the endangered Sierra Nevada yellow-legged frog (Rana sierrae), a behavior that current surveys do not measure. By deploying inexpensive hydrophones and developing a deep learning model to recognize breeding-associated vocalizations, we discover three undocumented R. sierrae vocalization types and find an unexpected temporal pattern of nocturnal breeding-associated vocal activity. This study exemplifies how the combination of autonomous sensor data and deep learning can shed new light on species' natural history, especially during times or in locations where human observation is limited or impossible.

Influence of microclimate and forest management on bat species faced with global change.

Climate refugia, areas where climate is expected to remain relatively stable, can offer a near-term safe haven for species sensitive to warming temperatures and drought. Understanding the influence of temperature, moisture, and disturbance on sensitive species is critical during this time of rapid climate change. Coastal habitats can serve as important refugia. Many of these areas consist of working forestlands, and there is a growing recognition that conservation efforts worldwide must consider the habitat value of working lands, in addition to protected areas, to effectively manage large landscapes that support biodiversity. The sensitivity of forest bats to climate and habitat disturbance makes them a useful indicator taxon. We tested how microclimate and forest management influence habitat use for 13 species of insectivorous bats in a large climate refugium in a global biodiversity hotspot. We examined whether bat activity during the summer dry season is greater in forests where coastal fog provides moisture and more stable temperatures across both protected mature stands and those regularly logged. Acoustic monitoring was conducted at a landscape scale with 20 study sites, and generalized linear mixed models were used to examine the influence of habitat variables. Six species were positively associated with warmer nighttime temperature, and 5 species had a negative relationship with humidity or a positive relationship with climatic moisture deficit. Our results suggest that these mammals may have greater climate adaptive capacity than expected, and, for now, that habitat use may be more related to optimal foraging conditions than to avoidance of warming temperatures and drought. We also determined that 12 of the 13 regionally present bat species were regularly detected in commercial timberland stands. Because forest bats are highly mobile, forage over long distances, and frequently change roosts, the stewardship of working forests must be addressed to protect these species.

Influencia del microclima y el manejo forestal sobre especies de murciélagos ante el cambio global Resumen Los refugios climáticos, áreas en donde se espera que el clima permanezca relativamente estable, pueden ofrecer un santuario a corto plazo para las especies sensibles al aumento de temperaturas y la sequía. Es muy importante entender la influencia de la temperatura, la humedad y las perturbaciones sobre las especies sensibles durante estos tiempos de cambio climático repentino. Los hábitats costeros pueden funcionar como refugios importantes. Muchas de estas áreas consisten en bosques funcionales y cada vez hay más reconocimiento de que los esfuerzos mundiales de conservación deben considerar el valor del hábitat de los suelos funcionales, además de las áreas protegidas, para manejar de manera efectiva los extensos paisajes que mantienen a la biodiversidad. La sensibilidad de los murciélagos de los bosques ante las perturbaciones climáticas y de hábitat hace que sean un taxón indicador útil. Analizamos cómo los microclimas y el manejo forestal influyen sobre el uso de hábitat de 13 especies de murciélagos insectívoros en un refugio climático amplio dentro de un punto caliente de biodiversidad mundial. Examinamos si la actividad de los murciélagos durante la temporada seca de verano es mayor en los bosques en donde la niebla costera proporciona humedad y temperaturas más estables tanto en los árboles maduros como aquellos que son talados con regularidad. Realizamos el monitoreo acústico a escala de paisaje en 20 estudios de sitio y usamos modelos lineales mixtos generalizados para examinar la influencia de las variables del hábitat. Seis especies estuvieron asociadas positivamente con la temperatura nocturna más cálida y cinco especies tuvieron una relación negativa con la humedad o una relación positiva con el déficit climático de humedad. Nuestros resultados sugieren que estos mamíferos pueden tener una mayor capacidad de adaptación climática de lo que se pensaba y, por ahora, que el uso de hábitat puede estar más relacionado con las condiciones óptimas de forrajeo que con la evasión de las temperaturas elevadas y la sequía. También determinamos que 12 de las 13 especies con presencia regional fueron detectadas con regularidad en los puntos de tala comercial. Ya que los murciélagos del bosque tienden a moverse mucho, forrajear a lo largo de grandes distancias y con frecuencia cambiar de nido, debemos abordar la administración de los bosques funcionales para proteger a estas especies.

A landmark environmental law looks ahead.

In late December 1973, the United States enacted what some would come to call "the pitbull of environmental laws." In the 50 years since, the formidable regulatory teeth of the Endangered Species Act (ESA) have been credited with considerable successes, obliging agencies to draw upon the best available science to protect species and habitats. Yet human pressures continue to push the planet toward extinctions on a massive scale. With that prospect looming, and with scientific understanding ever changing, Science invited experts to discuss how the ESA has evolved and what its future might hold. -Brad Wible.

A Quantitative Evaluation of the Performance of the Low-Cost AudioMoth Acoustic Recording Unit.

The AudioMoth is a popular autonomous recording unit (ARU) that is widely used to record vocalizing species in the field. Despite its growing use, there have been few quantitative tests on the performance of this recorder. Such information is needed to design effective field surveys and to appropriately analyze recordings made by this device. Here, we report the results of two tests designed to evaluate the performance characteristics of the AudioMoth recorder. First, we performed indoor and outdoor pink noise playback experiments to evaluate how different device settings, orientations, mounting conditions, and housing options affect frequency response patterns. We found little variation in acoustic performance between devices and relatively little effect of placing recorders in a plastic bag for weather protection. The AudioMoth has a mostly flat on-axis response with a boost above 3 kHz, with a generally omnidirectional response that suffers from attenuation behind the recorder, an effect that is accentuated when it is mounted on a tree. Second, we performed battery life tests under a variety of recording frequencies, gain settings, environmental temperatures, and battery types. We found that standard alkaline batteries last for an average of 189 h at room temperature using a 32 kHz sample rate, and that lithium batteries can last for twice as long at freezing temperatures compared to alkaline batteries. This information will aid researchers in both collecting and analyzing recordings generated by the AudioMoth recorder.

A unified framework for species spatial patterns: Linking the occupancy area curve, Taylor's Law, the neighborhood density function and two-plot species turnover.

The description of spatial patterns in species distributions is central to research throughout ecology. In this manuscript, we demonstrate that five of the most widely used species-level spatial patterns are not only related, but can in fact be quantitatively derived from each other under minimal assumptions: the occupancy area curve, Taylor's Law, the neighborhood density function, a two-plot variant of Taylor's Law and two-plot single-species turnover. We present an overarching mathematical framework and derivations for several theoretical example cases, along with a simulation study and empirical analysis that applies the framework to data from the Barro Colorado Island tropical forest plot. We discuss how knowledge of this mathematical relationship can support the testing of ecological theory, suggest efficient field sampling schemes, highlight the relative importance of plot area and abundance in driving turnover patterns and lay the groundwork for future unified theories of community-level spatial metrics and multi-patch spatial patterns.

An annotated set of audio recordings of Eastern North American birds containing frequency, time, and species information.

Acoustic recordings of soundscapes are an important category of audio data that can be useful for answering a variety of questions, and an entire discipline within ecology, dubbed "soundscape ecology," has risen to study them. Bird sound is often the focus of studies of soundscapes due to the ubiquitousness of birds in most terrestrial environments and their high vocal activity. Autonomous acoustic recorders have increased the quantity and availability of recordings of natural soundscapes while mitigating the impact of human observers on community behavior. However, such recordings are of little use without analysis of the sounds they contain. Manual analysis currently stands as the best means of processing this form of data for use in certain applications within soundscape ecology, but it is a laborious task, sometimes requiring many hours of human review to process comparatively few hours of recording. For this reason, few annotated data sets of soundscape recordings are publicly available. Further still, there are no publicly available strongly labeled soundscape recordings of bird sounds that contain information on timing, frequency, and species. Therefore, we present the first data set of strongly labeled bird sound soundscape recordings under free use license. These data were collected in the Northeastern United States at Powdermill Nature Reserve, Rector, Pennsylvania, USA. Recordings encompass 385 minutes of dawn chorus recordings collected by autonomous acoustic recorders between the months of April through July 2018. Recordings were collected in continuous bouts on four days during the study period and contain 48 species and 16,052 annotations. Applications of this data set may be numerous and include the training, validation, and testing of certain advanced machine-learning models that detect or classify bird sounds. There are no copyright or propriety restrictions; please cite this paper when using materials within.

Automated detection of frog calls and choruses by pulse repetition rate.

Anurans (frogs and toads) are among the most globally threatened taxonomic groups. Successful conservation of anurans will rely on improved data on the status and changes in local populations, particularly for rare and threatened species. Automated sensors, such as acoustic recorders, have the potential to provide such data by massively increasing the spatial and temporal scale of population sampling efforts. Analyzing such data sets will require robust and efficient tools that can automatically identify the presence of a species in audio recordings. Like bats and birds, many anuran species produce distinct vocalizations that can be captured by autonomous acoustic recorders and represent excellent candidates for automated recognition. However, in contrast to birds and bats, effective automated acoustic recognition tools for anurans are not yet widely available. An effective automated call-recognition method for anurans must be robust to the challenges of real-world field data and should not require extensive labeled data sets. We devised a vocalization identification tool that classifies anuran vocalizations in audio recordings based on their periodic structure: the repeat interval-based bioacoustic identification tool (RIBBIT). We applied RIBBIT to field recordings to study the boreal chorus frog (Pseudacris maculata) of temperate North American grasslands and the critically endangered variable harlequin frog (Atelopus varius) of tropical Central American rainforests. The tool accurately identified boreal chorus frogs, even when they vocalized in heavily overlapping choruses and identified variable harlequin frog vocalizations at a field site where it had been very rarely encountered in visual surveys. Using a few simple parameters, RIBBIT can detect any vocalization with a periodic structure, including those of many anurans, insects, birds, and mammals. We provide open-source implementations of RIBBIT in Python and R to support its use for other taxa and communities.

Los anuros (ranas y sapos) se encuentran dentro de los grupos taxonómicos más amenazados a nivel mundial. La conservación exitosa de los anuros dependerá de información mejorada sobre el estado y los cambios en las poblaciones locales, particularmente para las especies raras y amenazadas. Los sensores automatizados, como las grabadoras acústicas, tienen el potencial para proporcionar dicha información al incrementar masivamente la escala espacial y temporal de los esfuerzos de muestreo poblacional. El análisis de dicha información requerirá herramientas robustas y eficientes que puedan identificar automáticamente la presencia de una especie en las grabaciones de audio. Como las aves y los murciélagos, muchas especies de anuros producen vocalizaciones distintivas que pueden ser capturadas por las grabadoras acústicas autónomas y también son excelentes candidatas para el reconocimiento automatizado. Sin embargo, a diferencia de las aves y los murciélagos, todavía no se cuenta con una disponibilidad extensa de herramientas para el reconocimiento acústico automatizado de los anuros. Un método efectivo para el reconocimiento automatizado del canto de los anuros debe ser firme ante los retos de los datos reales de campo y no debería requerir conjuntos extensos de datos etiquetados. Diseñamos una herramienta de identificación de las vocalizaciones: la herramienta de identificación bioacústica basada en el intervalo de repetición (RIBBIT), el cual clasifica las vocalizaciones de los anuros en las grabaciones de audio con base en su estructura periódica. Aplicamos la RIBBIT a las grabaciones de campo para estudiar a dos especies: la rana coral boreal (Pseudacris maculata) de los pastizales templados de América del Norte y la rana arlequín variable (Atelopus varius), críticamente en peligro de extinción, de las selvas tropicales de América Central. Mostramos que RIBBIT puede identificar correctamente a las ranas corales boreales, incluso cuando vocalizan en coros con mucha superposición, y puede identificar las vocalizaciones de la rana arlequín variable en un sitio de campo en donde rara vez se le ha visto durante censos visuales. Mediante relativamente unos cuantos parámetros simples, RIBBIT puede detectar cualquier vocalización con una estructura periódica, incluyendo aquellas de muchos anuros, insectos, aves y mamíferos. Proporcionamos implementaciones de fuente abierta de RIBBIT en Python y en R para fomentar su uso para otros taxones y comunidades.

Bird-friendly wine country through diversified vineyards.

Vinecology, the integration of ecological and viticultural practices, focuses on the working landscapes of the Mediterranean-climate biomes to make wine-grape production compatible with species conservation. We examined how maintaining remnant native vegetation and surrounding natural areas in and around vineyards, two primary practices of vinecology, may influence bird community richness and composition across a vineyard landscape. We conducted bird surveys over spring and summer (October-January) at 120 sites across a wine-grape growing region in central Chile. The sites were equally divided across vineyards with and without remnant native vegetation, and sites had varying amounts of adjacent natural land cover. We used generalized linear mixed models to examine individual species responses to remnant vegetation in the vineyard at plot scale (within a 50-m radius) in the surrounding natural area (within a 500-1000 m radius). We used the Horn similarity index to explore overall community differences to quantify variations in endemic species, guild detection levels, and species richness between site types. At the plot scale, 9 out of 30 species were positively associated with the proportion of remnant vegetation and 3 species were negatively associated. Six were positively influenced by the proportion of native vegetation in the surrounding landscape and 3 species were negatively associated with proportion of native vegetation. Although overall total detections and richness were significantly greater in continuous mixed Mediterranean forest, 84.9% of these species were also detected in forest remnants within vineyards. Endemics, insectivores, granivores, and omnivores were all more abundant in vineyards with remnant native vegetation than in vineyards without remnant native vegetation. Our results show the value of maintaining and restoring natural vegetation remnants in vineyards as a tool for bird conservation that can be applied in working landscapes of the New World Mediterranean climate regions.

Campos Vitivinícolas Amigables con las Aves mediante Viñedos Diversificados Resumen La vinecología, la integración de prácticas ecológicas y vinícolas, se enfoca en los paisajes productivos de los biomas pertenecientes al clima mediterráneo para lograr que la producción de uvas sea compatible con la conservación de especies. Analizamos cómo la conservación de la vegetación nativa remanente y las áreas naturales vecinas dentro y alrededor de los viñedos, dos prácticas primordiales de la vinecología, pueden influir sobre la riqueza y composición comunitaria de aves en todo un paisaje vinícola. Realizamos censos de aves durante la primavera y el verano (octubre - enero) en 120 sitios a través de una región en la que se cultivan uvas en la zona central de Chile. Los sitios estuvieron divididos de manera igualitaria en viñedos con y sin vegetación nativa remanente. Los sitios también tuvieron cantidades variables de cobertura natural de suelo adyacente. Usamos modelos lineales mixtos generalizados para examinar las respuestas individuales por especie a la vegetación remanente en el viñedo a escala de parcela (dentro de un radio de 50m) en el área natural vecina (dentro de un radio de 500-1000m). Usamos el índice de similitud de Horn para explorar las diferencias comunitarias generales para cuantificar las variaciones en las especies endémicas, los niveles de detección de gremios y la riqueza de especies entre los tipos de sitio. A escala de parcela, nueve de cada 30 especies estuvieron asociadas positivamente con la proporción de vegetación remanente y tres especies estuvieron asociadas negativamente. Seis especies fueron influenciadas positivamente por la proporción de la vegetación nativa en el paisaje vecino y tres especies estuvieron asociadas negativamente con la proporción de vegetación nativa. Aunque el total general de detecciones y de la riqueza fueron significativamente mayores en el bosque mediterráneo mixto continuo, el 84.9% de estas especies también fue detectada en los bosques remanentes dentro de los viñedos. Las especies endémicas, insectívoras, granívoras y omnívoras fueron más abundantes en los viñedos con vegetación nativa remanente que en los viñedos sin ésta. Nuestros resultados muestran la importancia de la conservación y restauración de los remanentes de vegetación nativa en los viñedos como herramientas para la conservación de aves que pueden ser aplicadas en paisajes funcionales en las regiones con clima mediterráneo del Nuevo Mundo.

Using Convolutional Neural Networks to Efficiently Extract Immense Phenological Data From Community Science Images.

Community science image libraries offer a massive, but largely untapped, source of observational data for phenological research. The iNaturalist platform offers a particularly rich archive, containing more than 49 million verifiable, georeferenced, open access images, encompassing seven continents and over 278,000 species. A critical limitation preventing scientists from taking full advantage of this rich data source is labor. Each image must be manually inspected and categorized by phenophase, which is both time-intensive and costly. Consequently, researchers may only be able to use a subset of the total number of images available in the database. While iNaturalist has the potential to yield enough data for high-resolution and spatially extensive studies, it requires more efficient tools for phenological data extraction. A promising solution is automation of the image annotation process using deep learning. Recent innovations in deep learning have made these open-source tools accessible to a general research audience. However, it is unknown whether deep learning tools can accurately and efficiently annotate phenophases in community science images. Here, we train a convolutional neural network (CNN) to annotate images of Alliaria petiolata into distinct phenophases from iNaturalist and compare the performance of the model with non-expert human annotators. We demonstrate that researchers can successfully employ deep learning techniques to extract phenological information from community science images. A CNN classified two-stage phenology (flowering and non-flowering) with 95.9% accuracy and classified four-stage phenology (vegetative, budding, flowering, and fruiting) with 86.4% accuracy. The overall accuracy of the CNN did not differ from humans (p = 0.383), although performance varied across phenophases. We found that a primary challenge of using deep learning for image annotation was not related to the model itself, but instead in the quality of the community science images. Up to 4% of A. petiolata images in iNaturalist were taken from an improper distance, were physically manipulated, or were digitally altered, which limited both human and machine annotators in accurately classifying phenology. Thus, we provide a list of photography guidelines that could be included in community science platforms to inform community scientists in the best practices for creating images that facilitate phenological analysis.

Acoustic localization of terrestrial wildlife: Current practices and future opportunities.

Autonomous acoustic recorders are an increasingly popular method for low-disturbance, large-scale monitoring of sound-producing animals, such as birds, anurans, bats, and other mammals. A specialized use of autonomous recording units (ARUs) is acoustic localization, in which a vocalizing animal is located spatially, usually by quantifying the time delay of arrival of its sound at an array of time-synchronized microphones. To describe trends in the literature, identify considerations for field biologists who wish to use these systems, and suggest advancements that will improve the field of acoustic localization, we comprehensively review published applications of wildlife localization in terrestrial environments. We describe the wide variety of methods used to complete the five steps of acoustic localization: (1) define the research question, (2) obtain or build a time-synchronizing microphone array, (3) deploy the array to record sounds in the field, (4) process recordings captured in the field, and (5) determine animal location using position estimation algorithms. We find eight general purposes in ecology and animal behavior for localization systems: assessing individual animals' positions or movements, localizing multiple individuals simultaneously to study their interactions, determining animals' individual identities, quantifying sound amplitude or directionality, selecting subsets of sounds for further acoustic analysis, calculating species abundance, inferring territory boundaries or habitat use, and separating animal sounds from background noise to improve species classification. We find that the labor-intensive steps of processing recordings and estimating animal positions have not yet been automated. In the near future, we expect that increased availability of recording hardware, development of automated and open-source localization software, and improvement of automated sound classification algorithms will broaden the use of acoustic localization. With these three advances, ecologists will be better able to embrace acoustic localization, enabling low-disturbance, large-scale collection of animal position data.

Consumption-Based Conservation Targeting: Linking Biodiversity Loss to Upstream Demand through a Global Wildlife Footprint.

Although most conservation efforts address the direct, local causes of biodiversity loss, effective long-term conservation will require complementary efforts to reduce the upstream economic pressures, such as demands for food and forest products, which ultimately drive these downstream losses. Here, we present a wildlife footprint analysis that links global losses of wild birds to consumer purchases across 57 economic sectors in 129 regions. The United States, India, China, and Brazil have the largest regional wildlife footprints, while per-person footprints are highest in Mongolia, Australia, Botswana, and the United Arab Emirates. A US$100 purchase of bovine meat or rice products occupies approximately 0.1 km2 of wild bird ranges, displacing 1-2 individual birds, for 1 year. Globally significant importer regions, including Japan, the United Kingdom, Germany, Italy, and France, have large footprints that drive wildlife losses elsewhere in the world and represent important targets for consumption-focused conservation attention.

Good enough practices in scientific computing.

Computers are now essential in all branches of science, but most researchers are never taught the equivalent of basic lab skills for research computing. As a result, data can get lost, analyses can take much longer than necessary, and researchers are limited in how effectively they can work with software and data. Computing workflows need to follow the same practices as lab projects and notebooks, with organized data, documented steps, and the project structured for reproducibility, but researchers new to computing often don't know where to start. This paper presents a set of good computing practices that every researcher can adopt, regardless of their current level of computational skill. These practices, which encompass data management, programming, collaborating with colleagues, organizing projects, tracking work, and writing manuscripts, are drawn from a wide variety of published sources from our daily lives and from our work with volunteer organizations that have delivered workshops to over 11,000 people since 2010.

Estimating biodiversity impacts without field surveys: A case study in northern Borneo.

In many regions of the world, biodiversity surveys are not routinely conducted prior to activities that lead to land conversion, such as development projects. Here we use top-down methods based on global range maps and bottom-up methods based on macroecological scaling laws to illuminate the otherwise hidden biodiversity impacts of three large hydroelectric dams in the state of Sarawak in northern Borneo. Our retrospective impact assessment finds that the three reservoirs inundate habitat for 331 species of birds (3 million individuals) and 164 species of mammals (110 million individuals). A minimum of 2100 species of trees (900 million individuals) and 17 700 species of arthropods (34 billion individuals) are estimated to be affected by the dams. No extinctions of bird, mammal, or tree species are expected due to habitat loss following reservoir inundation, while 4-7 arthropod species extinctions are predicted. These assessment methods are applicable to any data-limited system undergoing land-use change.

Predicting extinction debt from community patterns.

A significant challenge in both measuring and predicting species extinction rates at global and local scales is the possibility of extinction debt, time-delayed extinctions that occur gradually following an initial impact. Here we examine how relative abundance distributions and spatial aggregation combine to influence the likely magnitude of future extinction debt following habitat loss or climate-driven range contraction. Our analysis is based on several fundamental premises regarding abundance distributions, most importantly that species abundances immediately following habitat loss are a sample from an initial relative abundance distribution and that the long-term, steady-state form of the species abundance distribution is a property of the biology of a community and not of area. Under these two hypotheses, the results show that communities following canonical lognormal and broken-stick abundance distributions are prone to exhibit extinction debt, especially when species exhibit low spatial aggregation. Conversely, communities following a logseries distribution with a constant Fisher's α parameter never demonstrate extinction debt and often show an "immigration credit," in which species richness rises in the long term following an initial decrease. An illustration of these findings in 25 biodiversity hotspots suggests a negligible immediate extinction rate for bird communities and eventual extinction debts of 30-50% of initial species richness, whereas plant communities are predicted to immediately lose 5-15% of species without subsequent extinction debt. These results shed light on the basic determinants of extinction debt and provide initial indications of the magnitude of likely debts in landscapes where few empirical data are available.

Inferring regional-scale species diversity from small-plot censuses.

Estimation of the number of species at spatial scales too large to census directly is a longstanding ecological challenge. A recent comprehensive census of tropical arthropods and trees in Panama provides a unique opportunity to apply an inference procedure for up-scaling species richness and thereby make progress toward that goal. Confidence in the underlying theory is first established by showing that the method accurately predicts the species abundance distribution for trees and arthropods, and in particular accurately captures the rare tail of the observed distributions. The rare tail is emphasized because the shape of the species-area relationship is especially influenced by the numbers of rare species. The inference procedure is then applied to estimate the total number of arthropod and tree species at spatial scales ranging from a 6000 ha forest reserve to all of Panama, with input data only from censuses in 0.04 ha plots. The analysis suggests that at the scale of the reserve there are roughly twice as many arthropod species as previously estimated. For the entirety of Panama, inferred tree species richness agrees with an accepted empirical estimate, while inferred arthropod species richness is significantly below a previous published estimate that has been criticized as too high. An extension of the procedure to estimate species richness at continental scale is proposed.

Large roads reduce bat activity across multiple species.

Although the negative impacts of roads on many terrestrial vertebrate and bird populations are well documented, there have been few studies of the road ecology of bats. To examine the effects of large roads on bat populations, we used acoustic recorders to survey bat activity along ten 300 m transects bordering three large highways in northern California, applying a newly developed statistical classifier to identify recorded calls to the species level. Nightly counts of bat passes were analyzed with generalized linear mixed models to determine the relationship between bat activity and distance from a road. Total bat activity recorded at points adjacent to roads was found to be approximately one-half the level observed at 300 m. Statistically significant road effects were also found for the Brazilian free-tailed bat (Tadarida brasiliensis), big brown bat (Eptesicus fuscus), hoary bat (Lasiurus cinereus), and silver-haired bat (Lasionycteris noctivagans). The road effect was found to be temperature dependent, with hot days both increasing total activity at night and reducing the difference between activity levels near and far from roads. These results suggest that the environmental impacts of road construction may include degradation of bat habitat and that mitigation activities for this habitat loss may be necessary to protect bat populations.

Taxon categories and the universal species-area relationship (a comment on Sizling et al., "between geometry and biology:the problem of universality of the species-area relationship").

A theory of macroecology based on the maximum information entropy (MaxEnt) inference procedure predicts that the log-log slope of the species-area relationship (SAR) at any spatial scale is a specified function of the ratio of abundance, N(A), to species richness, S(A), at that scale. The theory thus predicts, in generally good agreement with observation, that all SARs collapse onto a specified universal curve when local slope, z(A), is plotted against N(A)/S(A). A recent publication, however, argues that if it is assumed that patterns in macroecology are independent of the taxonomic choices that define assemblages of species, then this principle of "taxon invariance" precludes the MaxEnt-predicted universality of the SAR. By distinguishing two dimensions of the notion of taxon invariance, we show that while the MaxEnt-based theory predicts universality regardless of the taxonomic choices that define an assemblage of species, the biological characteristics of assemblages should under MaxEnt, and do in reality, influence the realism of the predictions.

Approaching a state shift in Earth's biosphere.

Localized ecological systems are known to shift abruptly and irreversibly from one state to another when they are forced across critical thresholds. Here we review evidence that the global ecosystem as a whole can react in the same way and is approaching a planetary-scale critical transition as a result of human influence. The plausibility of a planetary-scale 'tipping point' highlights the need to improve biological forecasting by detecting early warning signs of critical transitions on global as well as local scales, and by detecting feedbacks that promote such transitions. It is also necessary to address root causes of how humans are forcing biological changes.

Shrink and share: humanity's present and future Ecological Footprint.

Sustainability is the possibility of all people living rewarding lives within the means of nature. Despite ample recognition of the importance of achieving sustainable development, exemplified by the Rio Declaration of 1992 and the United Nations Millennium Development Goals, the global economy fails to meet the most fundamental minimum condition for sustainability--that human demand for ecosystem goods and services remains within the biosphere's total capacity. In 2002, humanity operated in a state of overshoot, demanding over 20% more biological capacity than the Earth's ecosystems could regenerate in that year. Using the Ecological Footprint as an accounting tool, we propose and discuss three possible global scenarios for the future of human demand and ecosystem supply. Bringing humanity out of overshoot and onto a potentially sustainable path will require managing the consumption of food, fibre and energy, and maintaining or increasing the productivity of natural and agricultural ecosystems.