Spatial disconnections between locations where ecosystem services are produced and where they are used are common. To date most ecosystem service assessments have relied on static indicators of provision and often do not incorporate relations with the corresponding beneficiaries or benefiting areas. Most studies implicitly assume spatial and temporal connections between ecosystem service provision and beneficiaries, while the actual connections, i.e., ecosystem service flows, are poorly understood. In this paper, we present a generic framework to analyze the spatial connections between the ecosystem service provisioning and benefiting areas. We introduce an indicator that shows the proportion of benefiting areas supported by spatial ecosystem service flows from provisioning areas. We illustrate the application of the framework and indicator by using global maps of provisioning and benefitting areas for pollination services. We also illustrate our framework and indicator using water provision and climate regulation services, as they portray important differences in spatiotemporal scale and process of service flow. We also describe the possible application of the framework for other services and other scales of assessment. We highlight how, depending on the ecosystem service being studied, the spatial service flows between provisioning and benefiting areas can limit service delivery, thereby reducing the local value of ecosystem service supply

Tracking devices and bio-loggers provide crucial information on the ecology and behaviour of birds in their natural environment. An optimal tracking system should be lightweight, measure three-dimensional locations, enable flexible measurement schemes, transmit data remotely and measure environmental variables and biological parameters of the individual. Giving full consideration to the traits of birds and the constraints of technology, we have developed a GPS tracking system that attempts to achieve most of the aspirations of an optimal tracking system for free ranging birds without the need to recapture them. Here, we describe the design, performance and limitations of the system. We also present measurements on the tracked Lesser Black-backed Gull Larus fuscus to show how such a system can generate new opportunities for research at multiple scales. The GPS tracker weighs 12 g and includes a GPS receiver, micro-processor, 4 MB of memory for data storage, solar panel and battery. It has a tri-axial accelerometer to monitor behaviour. To maximize flexibility, it is equipped with a radio transceiver for bi-directional communication with a ground-based antenna network, which enables data to be downloaded and new measurement schemes to be uploaded remotely. The system facilitates a multi-scale approach to studying bird movement, from fine-scale movements (3-s measurement intervals) to long-distance migratory movements (intervals of 20–30 min) of the same individual. We anticipate that flexible tracking systems that enable researchers to optimize their measurement protocols will contribute to revolutionizing research on animal behaviour and ecology in the next decade. Ein tragbares GPS-Tracking-Gerät mit großer Mess-Bandbreite zur Untersuchung von Vogel-Verhalten Tracking-Geräte und Apparate zur Aufzeichnung biologischer Daten liefern wichtige Informationen zu Ökologie und Verhalten von Vögeln in ihrer natürlichen Umgebung. Ein optimales Tracking-Gerät müsste sehr leicht sein, dreidimensionale Ortsangaben liefern, flexible Mess-Programme zulassen, Daten drahtlos übertragen sowie Umweltwerte und biologische Parameter individueller Tiere erfassen. Unter Berücksichtigung der Eigenheiten von Vögeln einerseits und der Einschränkungen technischer Apparaturen andererseits, haben wir ein GPS-Tracking-Gerät entwickelt und dabei versucht, möglichst viele der Anforderungen an ein optimales Gerät für freilebende Vögel zu realisieren, ohne die Tiere einfangen zu müssen. Wir beschreiben hier das Design, die Leistung und auch die Grenzen dieses Tracking-Geräts. Ferner präsentieren wir damit durchgeführte Messungen bei fern-verfolgten Heringsmöwen (Larus fuscus), um zu zeigen, wie solch ein Gerät neue Möglichkeiten für derartige Untersuchungen mit großer Mess-Bandbreite eröffnen kann. Das Gerät wiegt 12 Gramm und beinhaltet einen GPS-Empfänger, einen Mikroprozessor, 4 MB Speicherplatz für Daten, eine Solarzelle und eine Batterie; ferner hat es einen drei-achsialen Beschleunigungsmesser zur Registrierung relevanter Verhaltensweisen. Um ein Höchstmaß an Flexibilität zu erzielen, ist es mit einem Sender/Empfänger für Zwei-Wege-Kommunikation ausgestattet, um über eine bodengestützten Antennenanlage das drahtlose Herunterladen von Messdaten und Heraufladen von neuen Mess-Programmen zu ermöglichen. Ferner realisiert das Gerät die Erfassung von Ortsveränderungen bei Vögeln in verschiedenen Messbereichen: von einem hoch auflösenden Bereich (Messintervalle von 3 Sekunden) bis zur Erfassung von Langstrecken-Bewegungen im Bereich von 20–30 Minuten beim selben Individuum. Wir denken, dass tragbare Tracking-Geräte Wissenschaftler helfen werden, ihre Messverfahren zu optimieren, was in den nächsten zehn Jahren zu ganz neuen Forschungsansätzen in Verhaltensforschung und Ökologie führen wird.

Weather surveillance radars are increasingly used for monitoring the movements and abundances of animals in the airspace. However, analysis of weather radar data remains a specialised task that can be technically challenging. Major hurdles are the difficulty of accessing and visualising radar data on a software platform familiar to ecologists and biologists, processing the low‐level data into products that are biologically meaningful, and summarizing these results in standardized measures. To overcome these hurdles, we developed the open source R package bioRad, which provides a toolbox for accessing, visualizing and analyzing weather radar data for biological studies. It provides functionality to access low‐level radar data, process these data into meaningful biological information on animal speeds and directions at different altitudes in the atmosphere, visualize these biological extractions, and calculate further summary statistics. The package aims to standardize methods for extracting and reporting biological signals from weather radars. Here we describe a roadmap for analyzing weather radar data using bioRad. We also define weather radar equivalents for familiar measures used in the field of migration ecology, such as migration traffic rates, and recommend several good practices for reporting these measures. The bioRad package integrates with low‐level data from both the European radar network (OPERA) and the radar network of the United States (NEXRAD). bioRad aims to make weather radar studies in ecology easier and more reproducible, allowing for better inter‐comparability of studies.

Long-distance dispersal (LDD) promotes the colonization of isolated and remote habitats, and thus it has been proposed as a mechanism for explaining the distributions of many species. Birds are key LDD vectors for many sessile organisms such as plants, yet LDD beyond local and regional scales has never been directly observed nor quantified. By sampling birds caught while in migratory flight by GPS-tracked wild falcons, we show that migratory birds transport seeds over hundreds of kilometres and mediate dispersal from mainland to oceanic islands. Up to 1.2% of birds that reached a small island of the Canary Archipelago (Alegranza) during their migration from Europe to Sub-Saharan Africa carried seeds in their guts. The billions of birds making seasonal migrations each year may then transport millions of seeds. None of the plant species transported by the birds occurs in Alegranza and most do not occur on nearby Canary Islands, providing a direct example of the importance of environmental filters in hampering successful colonization by immigrant species. The constant propagule pressure generated by these LDD events might, nevertheless, explain the colonization of some islands. Hence, migratory birds can mediate rapid range expansion or shifts of many plant taxa and determine their distribution.

Animal-borne accelerometers measure body orientation and movement and can thus be used to classify animal behaviour. To univocally and automatically analyse the large volume of data generated, we need classification models. An important step in the process of classification is the segmentation of acceleration data, i.e. the assignment of the boundaries between different behavioural classes in a time series. So far, analysts have worked with fixed-time segments, but this may weaken the strength of the derived classification models because transitions of behaviour do not necessarily coincide with boundaries of the segments. Here we develop random forest automated supervised classification models either built on variable-time segments generated with a so-called ‘change-point model’, or on fixed-time segments, and compare for eight behavioural classes the classification performance. The approach makes use of acceleration data measured in eight free-ranging crab plovers Dromas ardeola. Useful classification was achieved by both the variable-time and fixed-time approach for flying (89% vs. 91%, respectively), walking (88% vs. 87%) and body care (68% vs. 72%). By using the variable-time segment approach, significant gains in classification performance were obtained for inactive behaviours (95% vs. 92%) and for two major foraging activities, i.e. handling (84% vs. 77%) and searching (78% vs. 67%). Attacking a prey and pecking were never accurately classified by either method. Acceleration-based behavioural classification can be optimized using a variable-time segmentation approach. After implementing variable-time segments to our sample data, we achieved useful levels of classification performance for almost all behavioural classes. This enables behaviour, including motion, to be set in known spatial contexts, and the measurement of behavioural time-budgets of free-living birds with unprecedented coverage and precision. The methods developed here can be easily adopted in other studies, but we emphasize that for each species and set of questions, the presented string of work steps should be run through.

The aerial environment is heterogeneous in space and time and directly influences the costs of animal flight. Volant animals can reduce these costs by using different flight modes, each with their own benefits and constraints. However, the extent to which animals alter their flight modes in response to environmental conditions has rarely been studied in the wild. To provide insight into how a flight generalist can reduce the energetic cost of movement, we studied flight behaviour in relation to the aerial environmental and landscape using hundreds of hours of global positioning system and triaxial acceleration measurements of the lesser black-backed gull ( Larus fuscus ). Individuals differed largely in the time spent in flight, which increased linearly with the time spent in flight at sea. In general, flapping was used more frequently than more energetically efficient soaring flight. The probability of soaring increased with increasing boundary layer height and time closer to midday, reflecting improved convective conditions supportive of thermal soaring. Other forms of soaring flight were also used, including fine-scale use of orographic lift. We explore the energetic consequences of behavioural adaptations to the aerial environment and underlying landscape and implications for individual energy budgets, foraging ecology and reproductive success. This article is part of the themed issue ‘Moving in a moving medium: new perspectives on flight’.