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Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Belgium

This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision (EU) 2020/1729. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision (EU) 2020/172. The quantitative minimum inhibitory concentration (MIC) data from dilution methods are included. Reporting authorities contributing to 2021 AMR data collection SCIENSANO

Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – France

Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Austria

Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Lithuania

Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Romania

Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Germany

This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision (EU) 2020/1729. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision (EU) 2020/172. The quantitative minimum inhibitory concentration (MIC) data from dilution methods, as well as the voluntary reporting of and Whole Genome Sequencing (WGS) data are included. Reporting authorities contributing to 2021 AMR data collection: Federal Institute for Risk Assessment

Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Estonia

Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Finland

This dataset contains AMR monitoring results in animals and food at the isolate level pursuant to Article 9 of Directive 2003/99/EC and to Annex, part B, of Commission implementing Decision (EU) 2020/1729. In addition, the dataset includes any other results from isolates than the ones mentioned in the Commission implementing Decision (EU) 2020/172. The quantitative minimum inhibitory concentration (MIC) data from dilution methods, as well as the voluntary reporting of and Whole Genome Sequencing (WGS) data are included. Reporting authorities contributing to 2021 AMR data collection: Finnish Food Authority

Antimicrobial resistance monitoring results complementing the European Union Summary Report on Antimicrobial Resistance in zoonotic and indicator bacteria from humans, animals and food in 2020/2021 – Luxembourg

opencc-zeroAug 2020View details →

Potential short-term earthquake forecasting by farm animal monitoring

Whether changes in animal behavior allow for short-term earthquake predictions has been debated for a long time. Before, during and after the 2016/2017 earthquake sequence in Italy, we deployed bio-logging tags to continuously observe the activity of farm animals (cows, dogs, sheep) close to the epicenter of the devastating magnitude M6.6 Norcia earthquake (Oct-Nov 2016) and over a subsequent longer observation period (Jan-Apr 2017). Relating 5304 (in 2016) and 12948 (in 2017) earthquakes with a wide magnitude range (0.4 ≤ M ≤ 6.6) to continuously measured animal activity, we detected how the animals collectively reacted to earthquakes. We also found consistent anticipatory activity prior to earthquakes during times when the animals were in a building (stable), but not during their time on a pasture. We detected these anticipatory patterns not only in periods with high, but also in periods of low seismic activity. Earthquake anticipation times (1-20hrs) are negatively correlated with the distance between the farm and earthquake hypocenters. Our study suggests that continuous bio-logging of animal collectives has the potential to provide statistically reliable patterns of pre-seismic activity that could yield valuable insights for short-term earthquake forecasting. Based on a-priori model parameters we provide empirical threshold values for pre-seismic animal activities to be used in real-time observation stations.

opencc-zeroDec 2014View details →

Data from: Smart nest box: a tool and methodology for monitoring of cavity-dwelling animals

1.Camera recording and video analysis have emerged as a successful non-invasive method for collecting a wide range of biological data on many different taxa of animals. However, camera monitoring has rarely been applied to long term surveillance of cavity or box-nesting species and ordinary off-the-shelf cameras are employed. 2.We present methodology and data on the effectiveness of nest box monitoring using a camera system embedded in four "smart nest boxes" (SNBoxes). We applied the SNBoxes to eight Tengmalm's owl (Aegolius funereus) nests in the Czech Republic during a five-month period in 2014. Each SNBox consisted of a pair of cameras with infrared lighting, an event detector, a radio-frequency identification reader, auxiliary sensors, and a 60 Ah 12 V battery to power the whole system. All devices used were centrally managed by an embedded computer with specifically developed software. 3.Using four SNBoxes, we observed owl nesting continually during the incubation, nestling, and fledgling phases, in total 309 days, resulting in 3382 owl video events. Batteries were changed every 6.5 days. A memory of 4 GB was found sufficient to store monthly data. We identified 12 types of male and female parental activities and their timing, the diet composition and frequency of prey delivery, the manner of prey storage, the light intensity at the time of each parental activity, the temperature inside the clutch and outside the box, and the duration of nestling period of each young. We also produced a video on owl nesting for the general public. 4.The SNBox and related methodology show enormous potential as a non-invasive tool for monitoring animals using boxes or natural cavities. The main advantage of the SNBox is the possibility to study both nocturnal and diurnal animal species and great flexibility in use of the software and hardware for different tasks. As a result, the SNBox provides an opportunity for novel insights into the breeding, roosting, hibernating, and food storage activities of a wide range of cavity-living birds, mammals, and reptiles.

opencc-zeroMar 2024View details →

A systematic review of global road ecology camera trap studies that monitored animals' use of wildlife crossings in road-fragmented landscapes

Much research has emphasised the importance of incorporating wildlife crossing-structures in the design of road networks to facilitate connectivity of wildlife crossings in road-fragmented landscapes. Although camera traps have been effective in monitoring wildlife crossing structures, limited studies explore camera trap protocol to monitor wildlife use of crossing structures, particularly in Africa. Our study reviewed and assessed camera trap peer-reviewed research that monitored the use of crossing-structures by wildlife to navigate landscapes fragmented by roads. We found 70 camera trap peer-reviewed publications from 2001 to 2022 that monitored wildlife use of crossing-structures in landscapes intersected by roads, and these were from 22 countries and six continents. The included peer-reviewed studies varied significantly globally, with geographical trends indicating that most studies were conducted in North America. However, the methods used varied considerably between studies, especially in terms of camera trap placement protocol (placement height of camera trap, survey length, and camera multi-shot settings). This showed that camera trap usage for monitoring animal use of crossing structures is still an emerging area of research, and there is a potential for developing a standardised protocol for each type of crossing structure design and size. Future camera trap studies exploring wildlife use of crossing-structures should consider monitoring existing crossing structures (culverts, bridges, and tunnels) as this provides a less costly method of restoring landscape connectivity. We recommend that further research develop a standardised camera trap protocol for monitoring wildlife using crossing-structures to reduce the threats to biodiversity.

opencc-zeroSep 2023View details →

Monitoring the birds and the bees: Environmental DNA metabarcoding of flowers detects plant–animal interactions

Animal pollinators are vital for the reproduction of ~90% of flowering plants. However, many of these pollinating species are experiencing declines globally, making effective pollinator monitoring methods more important than ever before. Pollinators can leave DNA on the flowers they visit, and metabarcoding of these environmental DNA (eDNA) traces provides an opportunity to detect the presence of flower visitors. Our study, collecting flowers from seven plant species with diverse floral morphologies, for eDNA metabarcoding analysis, illustrated the value of this novel survey tool. eDNA metabarcoding using three assays, including one developed in this study to target common bush birds, recorded more animal species visiting flowers than visual surveys conducted concurrently, including birds, bees, and other species. We also recorded the presence of a flower visit from a western pygmy possum; to our knowledge, this is the first eDNA metabarcoding study to simultaneously identify the interaction of insect, mammal, and bird species with flowers. The highest diversity of taxa was detected on large inflorescence flower types found on Banksia arborea and Grevillea georgeana. The study demonstrates that the ease of sample collection and the robustness of the metabarcoding methodology have profound implications for future management of biodiversity, allowing us to monitor both plants and their attendant cohort of potential pollinators. This opens avenues for rapid and efficient comparison of biodiversity and ecosystem health between different sites and may provide insights into surrogate pollinators in the event of pollinator declines.

publicNov 2016View details →

Data from: Smart nest box: a tool and methodology for monitoring of cavity-dwelling animals

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publicSep 2023View details →

Monitoring the birds and the bees: Environmental DNA metabarcoding of flowers detects plant–animal interactions

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publicAug 2020View details →

Potential short-term earthquake forecasting by farm animal monitoring

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