Risk-sensitive response of soaring birds to crosswind over dangerous sea highlights age-specific differences in migratory performance.

Challenges imposed by geographical barriers during migration are selective agents for animals. Juvenile soaring landbirds often cross large water bodies along their migratory path, where they lack updraft support and are vulnerable to harsh weather. However, the consequences of inexperience in accomplishing these water crossings remain largely unquantified. To address this knowledge gap, we tracked the movements of juvenile and adult black kites Milvus migrans over the Strait of Gibraltar using high-frequency tracking devices in variable crosswind conditions. We found that juveniles crossed under higher crosswind speeds and at wider sections of the strait compared with adults during easterly winds, which represent a high risk owing to their high speed and steady direction towards the Atlantic Ocean. Juveniles also drifted extensively with easterly winds, contrasting with adults who strongly compensated for lateral displacement through flapping. Age differences were inconspicuous during winds with a west crosswind speed component, as well as for airspeed modulation in all wind conditions. We suggest that the suboptimal sea-crossing behaviour of juvenile black kites may impact their survival rates, either by increasing chances of drowning owing to exhaustion or by depleting critical energy reserves needed to accomplish their first migration.

Nature 4.0: A networked sensor system for integrated biodiversity monitoring.

Ecosystem functions and services are severely threatened by unprecedented global loss in biodiversity. To counteract these trends, it is essential to develop systems to monitor changes in biodiversity for planning, evaluating, and implementing conservation and mitigation actions. However, the implementation of monitoring systems suffers from a trade-off between grain (i.e., the level of detail), extent (i.e., the number of study sites), and temporal repetition. Here, we present an applied and realized networked sensor system for integrated biodiversity monitoring in the Nature 4.0 project as a solution to these challenges, which considers plants and animals not only as targets of investigation, but also as parts of the modular sensor network by carrying sensors. Our networked sensor system consists of three main closely interlinked components with a modular structure: sensors, data transmission, and data storage, which are integrated into pipelines for automated biodiversity monitoring. We present our own real-world examples of applications, share our experiences in operating them, and provide our collected open data. Our flexible, low-cost, and open-source solutions can be applied for monitoring individual and multiple terrestrial plants and animals as well as their interactions. Ultimately, our system can also be applied to area-wide ecosystem mapping tasks, thereby providing an exemplary cost-efficient and powerful solution for biodiversity monitoring. Building upon our experiences in the Nature 4.0 project, we identified ten key challenges that need to be addressed to better understand and counteract the ongoing loss of biodiversity using networked sensor systems. To tackle these challenges, interdisciplinary collaboration, additional research, and practical solutions are necessary to enhance the capability and applicability of networked sensor systems for researchers and practitioners, ultimately further helping to ensure the sustainable management of ecosystems and the provision of ecosystem services.

Toward Real-Time Animal Tracking with Integrated Stimulus Control for Automated Conditioning in Aquatic Eco-Neurotoxicology.

Aquatic eco-neurotoxicology is an emerging field that requires new analytical systems to study the effects of pollutants on animal behaviors. This is especially true if we are to gain insights into one of the least studied aspects: the potential perturbations that neurotoxicants can have on cognitive behaviors. The paucity of experimental data is partly caused by a lack of low-cost technologies for the analysis of higher-level neurological functions (e.g., associative learning) in small aquatic organisms. Here, we present a proof-of-concept prototype that utilizes a new real-time animal tracking software for on-the-fly video analysis and closed-loop, external hardware communications to deliver stimuli based on specific behaviors in aquatic organisms, spanning three animal phyla: chordates (fish, frog), platyhelminthes (flatworm), and arthropods (crustacean). The system's open-source software features an intuitive graphical user interface and advanced adaptive threshold-based image segmentation for precise animal detection. We demonstrate the precision of animal tracking across multiple aquatic species with varying modes of locomotion. The presented technology interfaces easily with low-cost and open-source hardware such as the Arduino microcontroller family for closed-loop stimuli control. The new system has potential future applications in eco-neurotoxicology, where it could enable new opportunities for cognitive research in diverse small aquatic model organisms.

Behavioral changes of food allergic model mice during light and dark period.

Although an animal model of food allergy has been used to investigate its progression mechanism, most researcher could not assess its symptoms for long especially under dark environment. We assessed the behavioral changes of food allergic mice using an image analysis system to track a mouse under both light and dark environments. Mice were sensitized with intraperitoneal ovalbumin (OVA) injections and challenged ten times with oral OVA administration. The OVA challenges induced weight loss and diarrhea. We assessed their behavior and found that the OVA challenges decreased their total moving distance during the dark period. We also revealed that the OVA challenges increased the inactive time of mice during the dark period. Interestingly, these changes were not observed or very small during the light period. We next assessed the location of mice in the home-cage and found that the OVA challenges increased the time when mice stayed at corners and decreased the time at the center during the dark period. These observations suggest mental abnormality of mice. Indeed, the OVA challenges increased the immobility time of mice in the tail suspension test. Thus, food allergic mice exhibited reduced activity and might exhibit psychological symptoms during dark period.

Satellite tracking reveals sex-specific migration distance in green turtles (Chelonia mydas).

Satellite tracking is a key tool for studying sea turtles in the wild. Most tracking has been performed on adult females however, leaving knowledge gaps regarding other population segments, such as adult males. By satellite tracking 12 male green turtles (Chelonia mydas) at a breeding site in West Africa, we describe their movements from the breeding to the foraging grounds and compare migrations with those of 13 females tracked in the same season. During the mating period, some males remained near the focal nesting site, while others performed exploratory movements, apparently to visit other nearby rookeries. Males migrated on average shorter distances to foraging grounds (377 km, range 50-1081, n = 9) compared to females (1038 km, range 957-1850, n = 11]). Importantly, male foraging areas overlapped with previously described areas for females, suggesting sex-specific migration distances are not derived from differences in habitat selection. Strong support for differential migration by sex in sea turtles has hitherto been found in just one other species, but indications are that it may be a general feature in this group. These findings have important implications for our understanding of the interplay between reproductive roles and movement ecology of these emblematic animals.

Individual-Level Memory Is Sufficient to Create Spatial Segregation among Neighboring Colonies of Central Place Foragers.

AbstractCentral place foragers often segregate in space, even without signs of direct agonistic interactions. Using parsimonious individual-based simulations, we show that for species with spatial cognitive abilities, individual-level memory of resource availability can be sufficient to cause spatial segregation in the foraging ranges of colonial animals. The shapes of the foraging distributions are governed by commuting costs, the emerging distribution of depleted resources, and the fidelity of foragers to their colonies. When colony fidelity is weak and foragers can easily switch to colonies located closer to favorable foraging grounds, this leads to space partitioning with equidistant borders between neighboring colonies. In contrast, when colony fidelity is strong-for example, because larger colonies provide safety in numbers or individuals are unable to leave-it can create a regional imbalance between resource requirements and resource availability. This leads to nontrivial space-use patterns that propagate through the landscape. Interestingly, while better spatial memory creates more defined boundaries between neighboring colonies, it can lower the average intake rate of the population, suggesting a potential trade-off between an individual's attempt for increased intake and population growth rates.

High accuracy tracking reveals how small conservation areas can protect marine megafauna.

Space use estimates can inform conservation management but relaying high-accuracy locations is often not straightforward. We used Fastloc-GPS Argos satellite tags with the innovation of additional data relay via a ground station (termed a "Mote") to record high volumes (typically >20 locations per individual per day) of high accuracy tracking data. Tags were attached in the Chagos Archipelago (Indian Ocean) in 2018-2019 to 23 immature turtles of two species for which there have been long-standing conservation concerns: 21 hawksbill turtles (Eretmochelys imbricata) and two green turtles (Chelonia mydas). Over long tracking durations (mean 227.6 d per individual), most turtles moved very little. For example, 17 of 21 hawksbill turtles remained continuously in the lagoon where they were equipped, with 95% and 50% utilization distributions (UDs) averaging only 1.03 and 0.18 km2 , respectively. Many individuals, and both species, could use the same small spaces, i.e., individuals did not maintain unique home ranges. However, three hawksbill turtles travelled hundreds of kilometers from the tagging site. Our results show that, for some large marine vertebrates, even small protected areas of only a few square kilometers can encompass the movements of a large proportion of individuals over long periods. High accuracy tracking may likewise reveal the details of space use for many other animals that move little and/or use important focal areas and where previous low-accuracy tracking techniques have tended to overestimate space use.

Population trends in Vermivora warblers are linked to strong migratory connectivity.

Migratory species can experience limiting factors at different locations and during different periods of their annual cycle. In migratory birds, these factors may even occur in different hemispheres. Therefore, identifying the distribution of populations throughout their annual cycle (i.e., migratory connectivity) can reveal the complex ecological and evolutionary relationships that link species and ecosystems across the globe and illuminate where and how limiting factors influence population trends. A growing body of literature continues to identify species that exhibit weak connectivity wherein individuals from distinct breeding areas co-occur during the nonbreeding period. A detailed account of a broadly distributed species exhibiting strong migratory connectivity in which nonbreeding isolation of populations is associated with differential population trends remains undescribed. Here, we present a range-wide assessment of the nonbreeding distribution and migratory connectivity of two broadly dispersed Nearctic-Neotropical migratory songbirds. We used geolocators to track the movements of 70 Vermivora warblers from sites spanning their breeding distribution in eastern North America and identified links between breeding populations and nonbreeding areas. Unlike blue-winged warblers (Vermivora cyanoptera), breeding populations of golden-winged warblers (Vermivora chrysoptera) exhibited strong migratory connectivity, which was associated with historical trends in breeding populations: stable for populations that winter in Central America and declining for those that winter in northern South America.

A Frequency-Programmable Miniaturized Radio Frequency Transmitter for Animal Tracking.

In animal tracking applications, smaller transmitters can reduce the impact of the transmitter on the tagged animal and thus provide more accurate data about animal behavior. By combining a novel circuit design and a newly developed micro-battery, we developed frequency-programmable and more powerful radio frequency transmitters that are about 40% smaller and lighter in weight than the smallest commercial counterpart for animal monitoring at the time of development. The new radio frequency transmitter has a miniaturized form factor for studying small animals. Designs of two coding schemes were developed: one transmits unmodulated signals (weight: 152 mg; dimensions: Ø 2.95 mm × 11.22 mm), and the other transmits modulated signals (weight: 160 mg; dimensions: Ø 2.95 mm × 11.85 mm). To accommodate different transmitter life requirements, each design can be configured to transmit in high or low signal strength. Prototypes of these transmitters were evaluated in the laboratory and exhibited comparable or longer service life and higher signal strength compared to their smallest commercial counterparts.

Familiarity breeds success: pairs that meet earlier experience increased breeding performance in a wild bird population.

In socially monogamous animals, including humans, pairs can meet and spend time together before they begin reproduction. However, the pre-breeding period has been challenging to study in natural populations, and thus remains largely unexplored. As such, our understanding of the benefits of mate familiarity is almost entirely limited to assessments of repeated breeding with a particular partner. Here, we used fine-scale tracking technology to gather 6 years of data on pre-breeding social associations of individually marked great tits in a wild population. We show that pairs which met earlier in the winter laid their eggs earlier in all years. Clutch size, number of hatched and fledged young, and hatching and fledging success were not influenced by parents' meeting time directly, but indirectly: earlier laying pairs had larger clutches (that also produce higher number of young), and higher hatching and fledging success. We did not detect a direct influence of the length of the initial pairing period on future mating decisions (stay with a partner or divorce). These findings suggest a selective advantage for a new pair to start associating earlier (or for individuals to mate with those they have known for longer). We call for more studies to explore the generality of fitness effects of pair familiarity prior to first breeding, and to elucidate the mechanisms underlying these effects.

Light-level geolocator analyses: A user's guide.

Light-level geolocator tags use ambient light recordings to estimate the whereabouts of an individual over the time it carried the device. Over the past decade, these tags have emerged as an important tool and have been used extensively for tracking animal migrations, most commonly small birds. Analysing geolocator data can be daunting to new and experienced scientists alike. Over the past decades, several methods with fundamental differences in the analytical approach have been developed to cope with the various caveats and the often complicated data. Here, we explain the concepts behind the analyses of geolocator data and provide a practical guide for the common steps encompassing most analyses - annotation of twilights, calibration, estimating and refining locations, and extraction of movement patterns - describing good practices and common pitfalls for each step. We discuss criteria for deciding whether or not geolocators can answer proposed research questions, provide guidance in choosing an appropriate analysis method and introduce key features of the newest open-source analysis tools. We provide advice for how to interpret and report results, highlighting parameters that should be reported in publications and included in data archiving. Finally, we introduce a comprehensive supplementary online manual that applies the concepts to several datasets, demonstrates the use of open-source analysis tools with step-by-step instructions and code and details our recommendations for interpreting, reporting and archiving.

The gateway to Africa: What determines sea crossing performance of a migratory soaring bird at the Strait of Gibraltar?

Large bodies of water represent major obstacles for the migration of soaring birds because thermal updrafts are absent or weak over water. Soaring birds are known to time their water crossings with favourable weather conditions and there are records of birds falling into the water and drowning in large numbers. However, it is still unclear how environmental factors, individual traits and trajectory choices affect their water crossing performance, this being important to understand the fitness consequences of water barriers for this group of birds. We addressed this problem using the black kite Milvus migrans as model species at a major migration bottleneck, the Strait of Gibraltar. We recorded high-resolution GPS and triaxial accelerometer data for 73 birds while crossing the Strait of Gibraltar, allowing the determination of sea crossing duration, length, altitude, speed and tortuosity, the flapping behaviour of birds and their failed crossing attempts. These parameters were modelled against wind speed and direction, time of the day, solar irradiance (proxy of thermal uplift), starting altitude and distance to Morocco, and age and sex of birds. We found that sea crossing performance of black kites is driven by their age, the wind conditions, the starting altitude and distance to Morocco. Young birds made longer sea crossings and reached lower altitude above the sea than adults. Crosswinds promoted longer sea crossings, with birds reaching lower altitudes and with higher flapping effort. Birds starting at lower altitudes were more likely to quit or made higher flapping effort to complete the crossing. The location where birds started the sea crossings impacted crossing distance and duration. We present evidence that explains why migrating soaring birds accumulate at sea passages during adverse weather conditions. Strong crosswinds during sea crossings force birds to extended flap-powered flight at low altitude, which may increase their chances of falling in the water. We also showed that juvenile birds assume more risks than adults. Finally, the way in which birds start the sea crossing is crucial for their success, particularly the starting altitude, which dictates how far birds can reach with reduced flapping effort.

Improved 3D tracking and automated classification of rodents' behavioral activity using depth-sensing cameras.

Analysis of rodents' behavior/activity is of fundamental importance in many research fields. However, many behavioral experiments still rely on manual scoring, with obvious problems in reproducibility. Despite important advances in video-analysis systems and computational ethology, automated behavior quantification is still a challenge. The need for large training datasets, background stability requirements, and reduction to two-dimensional analysis (impairing full posture characterization), limit their use. Here we present a novel integrated solution for behavioral analysis of individual rats, combining video segmentation, tracking of body parts, and automated classification of behaviors, using machine learning and computer vision methods. Low-cost depth cameras (RGB-D) are used to enable three-dimensional tracking and classification in dark conditions and absence of color contrast. Our solution automatically tracks five anatomical landmarks in dynamic environments and recognizes seven distinct behaviors, within the accuracy range of human annotations. The developed free software was validated in experiments where behavioral differences between Wistar Kyoto and Wistar rats were automatically quantified. The results reveal the capability for effective automated phenotyping. An extended annotated RGB-D dataset is also made publicly available. The proposed solution is an easy-to-use tool, with low-cost setup and powerful 3D segmentation methods (in static/dynamic environments). The ability to work in dark conditions means that natural animal behavior is not affected by recording lights. Furthermore, automated classification is possible with only ~30 minutes of annotated videos. By creating conditions for high-throughput analysis and reproducible quantitative measurements of animal behavior experiments, we believe this contribution can greatly improve behavioral analysis research.

Using individual-based movement information to identify spatial conservation priorities for mobile species.

The optimal design of reserve networks and fisheries closures depends on species occurrence information and knowledge of how anthropogenic impacts interact with the species concerned. However, challenges in surveying mobile and cryptic species over adequate spatial and temporal scales can mask the importance of particular habitats, leading to uncertainty about which areas to protect to optimize conservation efforts. We investigated how telemetry-derived locations can help guide the scale and timing of fisheries closures with the aim of reducing threatened species bycatch. Forty juvenile speartooth sharks (Glyphis glyphis) were monitored over 22 months with implanted acoustic transmitters and an array of hydrophone receivers. Using the decision-support tool Marxan, we formulated a permanent fisheries closure that prioritized areas used more frequently by tagged sharks and considered areas perceived as having high value to fisheries. To explore how the size of the permanent closure compared with an alternative set of time-area closures (i.e., where different areas were closed to fishing at different times of year), we used a cluster analysis to group months that had similar arrangements of selected planning units (informed by shark movements during that month) into 2 time-area closures. Sharks were consistent in their timing and direction of migratory movements, but the number of tagged sharks made a big difference in the placement of the permanent closure; 30 individuals were needed to capture behavioral heterogeneity. The dry-season (May-January) and wet-season (February-April) time-area closures opened 20% and 25% more planning units to fishing, respectively, compared with the permanent closure with boundaries fixed in space and time. Our results show that telemetry has the potential to inform and improve spatial management of mobile species and that the temporal component of tracking data can be incorporated into prioritizations to reduce possible impacts of spatial closures on established fisheries.

Uso de Información de Movimiento Basada en Individuos para Identificar las Prioridades de Conservación Espacial para las Especies Móviles Resumen El diseño óptimo de redes de reservas y los cierres de pesquerías depende de la información sobre la presencia de especies y del conocimiento sobre cómo los impactos antropogénicos interactúan con las especies afectadas. Sin embargo, las dificultades que existen al monitorear especies móviles y crípticas en escalas espaciales y temporales adecuadas pueden enmascarar la importancia de los hábitats particulares, lo que resulta en incertidumbre con respecto a cuáles áreas proteger para optimizar los esfuerzos de conservación. Investigamos cómo las ubicaciones derivadas de la telemetría pueden ayudar a guiar la escala y el momento justo del cierre de las pesquerías con el objetivo de reducir la captura accesoria de especies amenazadas. Se monitorearon 40 tiburones lanza juveniles (Glyphis glyphis) durante 22 meses con transmisores acústicos implantados y una selección de receptores hidrofónicos. Con la herramienta de apoyo para la toma de decisiones Marxan, formulamos un cierre de pesquerías permanente que priorizó las áreas usadas con frecuencia por los tiburones marcados y que consideraba a las áreas percibidas como altamente valiosas para las pesquerías. Para explorar cómo el tamaño del cierre permanente se comparaba con un conjunto de cierres con áreas y tiempos alternativos (es decir, donde las áreas se cerraron a la pesca en diferentes momentos del año) usamos un análisis de clúster para agrupar los meses que tuvieron arreglos similares a las unidades de planeación seleccionadas (informadas por el movimiento de los tiburones durante ese mes) en dos cierres de tiempo-área. Los tiburones fueron consistentes en el tiempo y dirección de sus movimientos migratorios, pero el número de tiburones marcados generó una gran diferencia en la ubicación del cierre permanente; se necesitaron 30 individuos para capturar la heterogeneidad del comportamiento. Los cierres de tiempo-área de la temporada de secas (mayo - enero) y la de lluvias (febrero - abril) abrieron a la pesca un 20% y 25% más de unidades de planeación, respectivamente, en comparación con el cierre permanente con barreras fijas en el tiempo y el espacio. Nuestros resultados muestran que la telemetría tiene el potencial para informar y mejorar el manejo espacial de las especies móviles y que el componente temporal de los datos de rastreo puede ser incorporado a las priorizaciones para reducir los posibles impactos del manejo sobre las pesquerías establecidas.

Use of passive radio frequency identification technologies to monitor nest usage in the northern carmine bee-eater (Merops n. nubicus).

The use of radio frequency identification (RFID) technology is common in animal-monitoring applications in the wild and in zoological and agricultural settings. RFID is used to track animals and to collect information about movements and other behaviors, as well as to automate or improve husbandry. Disney's Animal Kingdom® uses passive RFID technology to monitor nest usage by a breeding colony of northern carmine bee-eaters. We implemented RFID technologies in various equipment configurations, initially deploying low-frequency (LF) 125 kHz RFID and later changing to high-frequency (HF) 13.56 MHz RFID technology, to monitor breeding behavior in the flock. We installed antennas connected to RFID readers at the entrances of nest tunnels to detect RFID transponders attached to leg bands as birds entered and exited tunnels. Both LF-RFID and HF-RFID systems allowed the characterization of nest visitation, including the timing of nest activity, breeding pair formation, identification of egg-laying females, participation by nonresidents, and detection of nest disruptions. However, we collected a substantially larger volume of data using the increased bandwidth and polling speed inherent with HF-RFID, which permitted tag capture of multiple birds simultaneously and resulted in fewer missed nest visits in comparison to LF-RFID. Herein, we describe the evolution of the RFID setups used to monitor nest usage for more than 7 years, the types of data that can be gained using RFID at nests, and how we used these data to gain insights into carmine bee-eater breeding behavior and improve husbandry.

Correcting for missing and irregular data in home-range estimation.

Home-range estimation is an important application of animal tracking data that is frequently complicated by autocorrelation, sampling irregularity, and small effective sample sizes. We introduce a novel, optimal weighting method that accounts for temporal sampling bias in autocorrelated tracking data. This method corrects for irregular and missing data, such that oversampled times are downweighted and undersampled times are upweighted to minimize error in the home-range estimate. We also introduce computationally efficient algorithms that make this method feasible with large data sets. Generally speaking, there are three situations where weight optimization improves the accuracy of home-range estimates: with marine data, where the sampling schedule is highly irregular, with duty cycled data, where the sampling schedule changes during the observation period, and when a small number of home-range crossings are observed, making the beginning and end times more independent and informative than the intermediate times. Using both simulated data and empirical examples including reef manta ray, Mongolian gazelle, and African buffalo, optimal weighting is shown to reduce the error and increase the spatial resolution of home-range estimates. With a conveniently packaged and computationally efficient software implementation, this method broadens the array of data sets with which accurate space-use assessments can be made.

A multi-animal tracker for studying complex behaviors.

BACKGROUND: Animals exhibit astonishingly complex behaviors. Studying the subtle features of these behaviors requires quantitative, high-throughput, and accurate systems that can cope with the often rich perplexing data. RESULTS: Here, we present a Multi-Animal Tracker (MAT) that provides a user-friendly, end-to-end solution for imaging, tracking, and analyzing complex behaviors of multiple animals simultaneously. At the core of the tracker is a machine learning algorithm that provides immense flexibility to image various animals (e.g., worms, flies, zebrafish, etc.) under different experimental setups and conditions. Focusing on C. elegans worms, we demonstrate the vast advantages of using this MAT in studying complex behaviors. Beginning with chemotaxis, we show that approximately 100 animals can be tracked simultaneously, providing rich behavioral data. Interestingly, we reveal that worms' directional changes are biased, rather than random - a strategy that significantly enhances chemotaxis performance. Next, we show that worms can integrate environmental information and that directional changes mediate the enhanced chemotaxis towards richer environments. Finally, offering high-throughput and accurate tracking, we show that the system is highly suitable for longitudinal studies of aging- and proteotoxicity-associated locomotion deficits, enabling large-scale drug and genetic screens. CONCLUSIONS: Together, our tracker provides a powerful and simple system to study complex behaviors in a quantitative, high-throughput, and accurate manner.

BATS: Adaptive Ultra Low Power Sensor Network for Animal Tracking.

In this paper, the BATS project is presented, which aims to track the behavior of bats via an ultra-low power wireless sensor network. An overview about the whole project and its parts like sensor node design, tracking grid and software infrastructure is given and the evaluation of the project is shown. The BATS project includes a lightweight sensor node that is attached to bats and combines multiple features. Communication among sensor nodes allows tracking of bat encounters. Flight trajectories of individual tagged bats can be recorded at high spatial and temporal resolution by a ground node grid. To increase the communication range, the BATS project implemented a long-range telemetry system to still receive sensor data outside the standard ground node network. The whole system is designed with the common goal of ultra-low energy consumption while still maintaining optimal measurement results. To this end, the system is designed in a flexible way and is able to adapt its functionality according to the current situation. In this way, it uses the energy available on the sensor node as efficient as possible.

A Holistic Approach to the Evaluation of the Montado Ecosystem Using Proximal Sensors.

The Montado is a silvo-pastoral system characterized by open canopy woodlands with natural or cultivated grassland in the undercover and grazing animals. The aims of this study were to present several proximal sensors with potential to monitor relevant variables in the complex montado ecosystem and demonstrate their application in a case study designed to evaluate the effect of trees on the pasture. This work uses data collected between March and June 2016, at peak of dryland pasture production under typical Mediterranean conditions, in twenty four sampling points, half under tree canopy (UTC) and half outside tree canopy (OTC). Correlations were established between pasture biomass and capacitance measured by a commercial probe and between pasture quality and normalized difference vegetation index (NDVI) measured by a commercial active optical sensor. The interest of altimetric and apparent soil electrical conductivity maps as the first step in the implementation of precision agriculture projects was demonstrated. The use of proximal sensors to monitor soil moisture content, pasture photosynthetically active radiation and temperature helped to explain the influence of trees on pasture productivity and quality. The significant and strong correlations obtained between capacitance and pasture biomass and between NDVI and pasture nutritive value (in terms of crude protein, CP and neutral detergent fibre, NDF) can make an important contribution to determination of key components of pasture productivity and quality and implementation of site-specific pasture management. Animal tracking demonstrated its potential to be an important tool for understanding the interaction between various factors and components that interrelate in the montado ecosystem and to support grazing management decisions.

Breeding density, fine-scale tracking, and large-scale modeling reveal the regional distribution of four seabird species.

Population-level estimates of species' distributions can reveal fundamental ecological processes and facilitate conservation. However, these may be difficult to obtain for mobile species, especially colonial central-place foragers (CCPFs; e.g., bats, corvids, social insects), because it is often impractical to determine the provenance of individuals observed beyond breeding sites. Moreover, some CCPFs, especially in the marine realm (e.g., pinnipeds, turtles, and seabirds) are difficult to observe because they range tens to ten thousands of kilometers from their colonies. It is hypothesized that the distribution of CCPFs depends largely on habitat availability and intraspecific competition. Modeling these effects may therefore allow distributions to be estimated from samples of individual spatial usage. Such data can be obtained for an increasing number of species using tracking technology. However, techniques for estimating population-level distributions using the telemetry data are poorly developed. This is of concern because many marine CCPFs, such as seabirds, are threatened by anthropogenic activities. Here, we aim to estimate the distribution at sea of four seabird species, foraging from approximately 5,500 breeding sites in Britain and Ireland. To do so, we GPS-tracked a sample of 230 European Shags Phalacrocorax aristotelis, 464 Black-legged Kittiwakes Rissa tridactyla, 178 Common Murres Uria aalge, and 281 Razorbills Alca torda from 13, 20, 12, and 14 colonies, respectively. Using Poisson point process habitat use models, we show that distribution at sea is dependent on (1) density-dependent competition among sympatric conspecifics (all species) and parapatric conspecifics (Kittiwakes and Murres); (2) habitat accessibility and coastal geometry, such that birds travel further from colonies with limited access to the sea; and (3) regional habitat availability. Using these models, we predict space use by birds from unobserved colonies and thereby map the distribution at sea of each species at both the colony and regional level. Space use by all four species' British breeding populations is concentrated in the coastal waters of Scotland, highlighting the need for robust conservation measures in this area. The techniques we present are applicable to any CCPF.