A multi-species evaluation of digital wildlife monitoring using the Sigfox IoT network

DATA AVAILABILITY : The Amazon rainforest datasets are publicly available at Movebank (www. movebank.org [26]) (Movebank study ID: 2122748764). The other datasets generated and or analysed during the current study are not publicly avail able due to ongoing studies and to protect animals from poaching but are almost entirely archived on Movebank (Movebank study IDs: 2155070222, 1409712816, 894254831, 1365616235, 1493312931, 1296030530, 1725249380, 1431850095, 1323242594, 1732512659, 1286005281, 1291290503, 1600771155, 1670322706, 1623175929, 1323163019, 1323668146, 2057805903, 2198940839), and can be made available by the authors upon reasonable request.Bio-telemetry from small tags attached to animals is one of the principal methods for studying the ecology and behaviour of wildlife. The field has constantly evolved over the last 80 years as technological improvement enabled a diversity of sensors to be integrated into the tags (e.g., GPS, accelerometers, etc.). However, retrieving data from tags on free-ranging animals remains a challenge since satellite and GSM networks are relatively expensive and or power hungry. Recently a new class of low-power communication networks have been developed and deployed worldwide to connect the internet of things (IoT). Here, we evaluated one of these, the Sigfox IoT network, for the potential as a real-time multi-sensor data retrieval and tag commanding system for studying fauna across a diversity of species and ecosystems. We tracked 312 individuals across 30 species (from 25 g bats to 3 t elephants) with seven different device concepts, resulting in more than 177,742 successful transmissions. We found a maximum line of sight communication distance of 280 km (on a flying cape vulture [Gyps coprotheres]), which sets a new documented record for animal-borne digital data transmission using terrestrial infrastructure. The average transmission success rate amounted to 68.3% (SD 22.1) on flying species and 54.1% (SD 27.4) on terrestrial species. In addition to GPS data, we also collected and transmitted data products from accelerometers, barometers, and thermometers. Further, we assessed the performance of Sigfox Atlas Native, a low-power method for positional estimates based on radio signal strengths and found a median accuracy of 12.89 km (MAD 5.17) on animals. We found that robust real-time communication (median message delay of 1.49 s), the extremely small size of the tags (starting at 1.28 g without GPS), and the low power demands (as low as 5.8 µAh per transmitted byte) unlock new possibilities for ecological data collection and global animal observation.The Deutsche Forschungsgemeinschaft (DFG, German Research Foundation). Open Access funding enabled and organized by Projekt DEAL.https://animalbiotelemetry.biomedcentral.comVeterinary Tropical Disease

Kartierung von Wildschäden verursacht durch Schwarzwild (Sus scrofa) an Grünlandflächen

In Niedersachsen/Deutschland wurden von März bis September 2012 durch Schwarzwild (Sus scrofa) verursachte Grünlandschäden auf 1163 ha Grünlandflächen auf zeitliche/räumliche Zusammenhänge sowie Unterschiede bei Grünlandnutzungsformen (Wiese, Graseinsaat, Standweide, Mähweide, Brache, Streu /Feuchtwiese), Bewirtschaftungsmaßnahmen (Mahd, Düngung) und Schadenscharakteristiken (Bewuchshöhe, Feuchte, Tiefe) analysiert. Schäden wurden in halbmonatlichen Intervallen via GPS flächenmäßig erfasst. Durch die Einteilung der Schäden in Intensitätsklassen wurde das ökonomische Schadensausmaß eruiert. Zeitlich fanden sich Schadensschwerpunkte im März bis Mitte April sowie variierend von Juni bis September, mit häufigen Umbruchswiederholungen. Räumlich konnte der Großteil der Schäden in Waldnähe (50 %) mit Schwerpunkten um den Winter bzw. im unterschiedlichen Zusammenhang mit weiteren Strukturen über den Jahresverlauf ausgemacht werden. Nach linearen gemischten Modellen waren häufigeres Düngen (Gülle und Kunstdüngung) und nasse Böden signifikant (p < 0,05) für ein höheres Schadensausmaß verantwortlich. Lineare Modelle zeigten Meidungen der Graseinsaaten (p < 0,05), jedoch konnten keine deutlichen Umbruchspräferierungen anhand der Grünlandtypen alleine ausgemacht werden. Geringere Bewuchshöhen, Witterung und Mondphasen könnten je nach Situation zusätzlich einen positiven Einfluss haben. Schadenseintritte und -ausmaße scheinen aber am stärksten von räumlichen Gegebenheiten der Wald-Feldstruktur mit möglichst kurzer Distanz zu einer Deckung, sowie genereller Nahrungsverfügbar-/Erreichbarkeit - teils beeinflusst durch Bodenqualitäten und Witterung - zusammenhängen. Mit den bekannten umbruchsfördernden Faktoren können oft wenige besonders gefährdete und oft wiederholt umgebrochene Grünlandflächen eruiert werden um Schadensmaßnahmen effektiv einzusetzen.From May to September 2012 in Lower Saxony, Germany, wild boar (Sus scrofa) rooting over 1163 ha of grassland was analyzed for temporal/geographical relationships and differences between uses of grassland (meadow, grass cultivation, seasonal grazing, rotational grazing, fallow land, dispersive meadow/wet meadow), management measures (mowing, fertilization) and rooting characteristics (vegetation height, moisture, depth). The surface area of rooting was recorded at bimonthly intervals using GPS. The extent of economic loss was determined by classifying the damage into levels of rooting intensity. With regard to time, rooting occurred most significantly from March to the middle of April and varyingly from June to September, with frequent, repeated rooting on the same plot. With regard to geography, the majority of rooting could be identified close to woodland (50%), most significantly around winter and in relation with other patterns over the course of the year. According to linear mixed models, frequent fertilization (liquid manure and artificial fertilizers) and wet soils were significantly responsible (p < 0,05) for a higher degree of rooting. Linear models showed lands used for grass cultivation were avoided (p < 0,05). However, it was not possible to identify any positive rooting preferences based on grassland type. Low vegetation height, weather and phases of the moon could have a positive effect as well, depending on conditions. The occurrence and extent of rooting appear to be greatest in the geographical patterns of a forest-field structure with the shortest possible distance from cover and general availability and accessibility of food - partially influenced by soil quality and weather. Known factors promoting rooting can often be used to determine a few vulnerable, repeatedly affected grassland areas and thereby effectively apply measures against damage.eingereicht von: Andreas DaimMit englischer ZusammenfassungUniversität für Bodenkultur Wien, Masterarbeit, 2015(VLID)112736

Accelerometer-based detection of African swine fever infection in wild boar

Open access funding provided by the Max Planck Society.Infectious wildlife diseases that circulate at the interface with domestic animals pose significant threats worldwide and require early detection and warning. Although animal tracking technologies are used to discern behavioural changes, they are rarely used to monitor wildlife diseases. Common disease-induced behavioural changes include reduced activity and lethargy (‘sickness behaviour’). Here, we investigated whether accelerometer sensors could detect the onset of African swine fever (ASF), a viral infection that induces high mortality in suids for which no vaccine is currently available. Taking advantage of an experiment designed to test an oral ASF vaccine, we equipped 12 wild boars with an accelerometer tag and quantified how ASF affects their activity pattern and behavioural fingerprint, using overall dynamic body acceleration. Wild boars showed a daily reduction in activity of 10–20% from the healthy to the viremia phase. Using change point statistics and comparing healthy individuals living in semi-free and free-ranging conditions, we show how the onset of disease-induced sickness can be detected and how such early detection could work in natural settings. Timely detection of infection in animals is crucial for disease surveillance and control, and accelerometer technology on sentinel animals provides a viable complementary tool to existing disease management approaches.European CommissionAustrian Research Promotion Agency (FFG)Depto. de Sanidad AnimalCentro de Vigilancia Sanitaria Veterinaria (VISAVET)Fac. de VeterinariaTRUEpu

Long-term monitoring of high-elevation terrestrial and aquatic ecosystems in the Alps - a five-year synthesis

Whether and how alpine organismic communities respond to ongoing environmental changes is difficult to assess quantitatively, given their intrinsically slow responses, remote locations and limited data. Here we provide a synthesis of the first five years of a multidisciplinary, highly standardized, long-term monitoring programme of terrestrial and aquatic ecosystems in the Austrian Hohe Tauern National Park and companion sites in northern Italy and the central Swiss Alps. The programme aims at evidencing the ecological state and trends in largely late-successional, high-elevation ecosystems. We present the conceptual framework, the study design and first results. Replicated over five regions, different sites and a multitude of permanent plots, the abiotic (microclimate, physics and chemistry of soils and water bodies), biodiversity (plants, animals, microbes), and productivity data (alpine grassland, lakes, streams) provide a representative reference for future re-assessments. The wide spectrum of biological baseline data presented and their spatial and temporal variation also illustrate the degree of uncertainty associated with smaller-scale and short-term studies and the role of stochasticity in long-term biological monitoring

A multi-species evaluation of digital wildlife monitoring using the Sigfox IoT network

Bio-telemetry from small tags attached to animals is one of the principal methods for studying the ecology and behaviour of wildlife. The field has constantly evolved over the last 80 years as technological improvement enabled a diversity of sensors to be integrated into the tags (e.g., GPS, accelerometers, etc.). However, retrieving data from tags on free-ranging animals remains a challenge since satellite and GSM networks are relatively expensive and or power hungry. Recently a new class of low-power communication networks have been developed and deployed worldwide to connect the internet of things (IoT). Here, we evaluated one of these, the Sigfox IoT network, for the potential as a real-time multi-sensor data retrieval and tag commanding system for studying fauna across a diversity of species and ecosystems. We tracked 312 individuals across 30 species (from 25 g bats to 3 t elephants) with seven different device concepts, resulting in more than 177,742 successful transmissions. We found a maximum line of sight communication distance of 280 km (on a flying cape vulture [Gyps coprotheres]), which sets a new documented record for animal-borne digital data transmission using terrestrial infrastructure. The average transmission success rate amounted to 68.3% (SD 22.1) on flying species and 54.1% (SD 27.4) on terrestrial species. In addition to GPS data, we also collected and transmitted data products from accelerometers, barometers, and thermometers. Further, we assessed the performance of Sigfox Atlas Native, a low-power method for positional estimates based on radio signal strengths and found a median accuracy of 12.89 km (MAD 5.17) on animals. We found that robust real-time communication (median message delay of 1.49 s), the extremely small size of the tags (starting at 1.28 g without GPS), and the low power demands (as low as 5.8 µAh per transmitted byte) unlock new possibilities for ecological data collection and global animal observation.ISSN:2050-338