Camtrap DP: an open standard for the FAIR exchange and archiving of camera trap data

Camera trapping has revolutionized wildlife ecology and conservation by providing automated data acquisition, leading to the accumulation of massive amounts of camera trap data worldwide. Although management and processing of camera trap-derived Big Data are becoming increasingly solvable with the help of scalable cyber-infrastructures, harmonization and exchange of the data remain limited, hindering its full potential. There is currently no widely accepted standard for exchanging camera trap data. The only existing proposal, “Camera Trap Metadata Standard” (CTMS), has several technical shortcomings and limited adoption. We present a new data exchange format, the Camera Trap Data Package (Camtrap DP), designed to allow users to easily exchange, harmonize and archive camera trap data at local to global scales. Camtrap DP structures camera trap data in a simple yet flexible data model consisting of three tables (Deployments, Media and Observations) that supports a wide range of camera deployment designs, classification techniques (e.g., human and AI, media-based and event-based) and analytical use cases, from compiling species occurrence data through distribution, occupancy and activity modeling to density estimation. The format further achieves interoperability by building upon existing standards, Frictionless Data Package in particular, which is supported by a suite of open software tools to read and validate data. Camtrap DP is the consensus of a long, in-depth, consultation and outreach process with standard and software developers, the main existing camera trap data management platforms, major players in the field of camera trapping and the Global Biodiversity Information Facility (GBIF). Under the umbrella of the Biodiversity Information Standards (TDWG), Camtrap DP has been developed openly, collaboratively and with version control from the start. We encourage camera trapping users and developers to join the discussion and contribute to the further development and adoption of this standard. Biodiversity data, camera traps, data exchange, data sharing, information standardspublishedVersio

Camtrap DP: an open standard for the FAIR exchange and archiving of camera trap data

Camera trapping has revolutionized wildlife ecology and conservation by providing automated data acquisition, leading to the accumulation of massive amounts of camera trap data worldwide. Although management and processing of camera trap-derived Big Data are becoming increasingly solvable with the help of scalable cyber-infrastructures, harmonization and exchange of the data remain limited, hindering its full potential. There is currently no widely accepted standard for exchanging camera trap data. The only existing proposal, “Camera Trap Metadata Standard” (CTMS), has several technical shortcomings and limited adoption. We present a new data exchange format, the Camera Trap Data Package (Camtrap DP), designed to allow users to easily exchange, harmonize and archive camera trap data at local to global scales. Camtrap DP structures camera trap data in a simple yet flexible data model consisting of three tables (Deployments, Media and Observations) that supports a wide range of camera deployment designs, classification techniques (e.g., human and AI, media-based and event-based) and analytical use cases, from compiling species occurrence data through distribution, occupancy and activity modeling to density estimation. The format further achieves interoperability by building upon existing standards, Frictionless Data Package in particular, which is supported by a suite of open software tools to read and validate data. Camtrap DP is the consensus of a long, in-depth, consultation and outreach process with standard and software developers, the main existing camera trap data management platforms, major players in the field of camera trapping and the Global Biodiversity Information Facility (GBIF). Under the umbrella of the Biodiversity Information Standards (TDWG), Camtrap DP has been developed openly, collaboratively and with version control from the start. We encourage camera trapping users and developers to join the discussion and contribute to the further development and adoption of this standar

Agouti: A platform for processing and archiving of camera trap images

Camera traps placed in the field, photograph warm-bodied animals that pass in front of an infrared sensor. The imagery represents a rich source of data on mammals larger than ~200 grams, providing information at the level of species and communities. Camera-trap surveys generate observations of specific mammals at a certain location and time, including photo evidence that can be evaluated by experts to map species distribution patterns. The imagery also provides information on the species composition of local communities, identifying which species co-occur and in what proportion. Moreover, the images contain information on activity patterns and other interesting aspects of animal behaviour. Because surveys can be standardized relatively easily, camera traps are well suited for documenting shifts in the behaviour, distribution and community composition, for example in response to climate and land-use change. Imagery from camera traps can thus serve as a baseline for subsequent surveys. In less than two decades, camera traps have become the standard tool for surveying mammals. They are simple to use and non-invasive, requiring no special permits. As a consequence they are widely used by professionals and hobbyists alike. Together, tens of thousands of users have the potential to form a huge sensor network. Unfortunately however, imagery and data collected are currently rarely integrated. Rather, they are lost at a massive scale. Users tend to retain only a subset of the photos and discard the rest. Or the material ends up on an external hard disk that will at some point fail or be erased as these scientific data tend to be used within the scope of specific projects. Very few of the wealth of material becomes available for scientific research and monitoring. Moreover, joint projects are rare and there is little coordination between camera-trap users. A solution to this problem is provided by Agouti, a platform for the organization, processing and storage of camera-trap imagery (www.agouti.eu). The aim of Agouti is, on the one hand, to standardize and facilitate collaborative camera-trap surveys, and on the other hand to compile and secure imagery and data for scientific research and monitoring, by encouraging users to share their material. Agouti provides an interface that allows users to collaborate on projects, organize and manage their surveys, upload and store imagery, and annotate images with species identifications and characteristics. Images can also be annotated through basic image recognition and crowd sourcing via a connection with the citizen science platform Zooniverse, which creates the potential to reach new audiences. Exporting data and imagery in the Camera Trap Metadata Standard (Forrester et al. 2016) will be supported in the near future. This will allow data to be archived outside of Agouti in research repositories such as Zenodo and by further mapping to Darwin Core to be made discoverable on the Global Biodiversity Information Facility (GBIF). Agouti provides both professionals and the public with a practical solution for retaining camera-trap surveys and simultaneously engages people in contributing data to science in a standardized and organized manner, to the benefit of science and conservation

Local host-tick coextinction in neotropical forest fragments

Ticks are obligatory parasites with complex life cycles that often depend on larger bodied vertebrates as final hosts. These traits make them particularly sensitive to local coextinction with their host. Loss of wildlife abundance and diversity should thus lead to loss of tick abundance and diversity to the point where only generalist tick species remain. However, direct empirical tests of these hypotheses are lacking, despite their relevance to our understanding of tick-borne disease emergence in disturbed environments. Here, we compare vertebrate and tick communities across 12 forest islands and peninsulas in the Panama Canal that ranged 1000-fold in size (2.6–2811.3 ha). We used drag sampling and camera trapping to directly assess the abundance and diversity of communities of questing ticks and vertebrate hosts. We found that the abundance and species richness of ticks were positively related to those of wildlife. Specialist tick species were only present in fragments where their final hosts were found. Further, less diverse tick communities had a higher relative abundance of the generalist tick species Amblyomma oblongoguttatum, a potential vector of spotted fever group rickettsiosis. These findings support the host-parasite coextinction hypothesis, and indicate that loss of wildlife can indeed have cascading effects on tick communities. Our results also imply that opportunities for pathogen transmission via generalist ticks may be higher in habitats with degraded tick communities. If these patterns are general, then tick identities and abundances serve as useful bioindicators of ecosystem health, with low tick diversity reflecting low wildlife diversity and a potentially elevated risk of interspecific disease transmission via remaining host species and generalist ticks.</p

Spatial risk analysis for the introduction and circulation of six arboviruses in the Netherlands

BACKGROUND: Arboviruses are a growing public health concern in Europe, with both endemic and exotic arboviruses expected to spread further into novel areas in the next decades. Predicting where future outbreaks will occur is a major challenge, particularly for regions where these arboviruses are not endemic. Spatial modelling of ecological risk factors for arbovirus circulation can help identify areas of potential emergence. Moreover, combining hazard maps of different arboviruses may facilitate a cost-efficient, targeted multiplex-surveillance strategy in areas where virus transmission is most likely. Here, we developed predictive hazard maps for the introduction and/or establishment of six arboviruses that were previously prioritized for the Netherlands: West Nile virus, Japanese encephalitis virus, Rift Valley fever virus, tick-borne encephalitis virus, louping-ill virus and Crimean-Congo haemorrhagic fever virus. METHODS: Our spatial model included ecological risk factors that were identified as relevant for these arboviruses by an earlier systematic review, including abiotic conditions, vector abundance, and host availability.

MICA - Muskrat and coypu camera trap observations in Belgium, the Netherlands and Germany

This camera trap dataset is derived from the Agouti project MICA - Management of Invasive Coypu and muskrAt in Europe. Data have been standardized to Darwin Core using the camtraptor R package and only include observations (and associated media) of animals. Excluded are records that document blank or unclassified media, vehicles and observations of humans. Geospatial coordinates are rounded to 0.001 degrees. The original dataset description follows. MICA - Muskrat and coypu camera trap observations in Belgium, the Netherlands and Germany is an occurrence dataset published by the Research Institute of Nature and Forest (INBO). It is part of the LIFE project MICA, in which innovative techniques are tested for a more efficient control of muskrat and coypu populations, both invasive species. The dataset contains camera trap observations of muskrat and coypu, as well as many other observed species. Issues with the dataset can be reported at https://github.com/inbo/mica-occurrences/issues We have released this dataset to the public domain under a Creative Commons Zero waiver. We would appreciate it if you follow the INBO norms for data use (https://www.inbo.be/en/norms-data-use) when using the data. If you have any questions regarding this dataset, don't hesitate to contact us via the contact information provided in the metadata or via [email protected]. This dataset was collected using infrastructure provided by INBO and funded by Research Foundation - Flanders (FWO) as part of the Belgian contribution to LifeWatch. The data were collected as part of the MICA project, which received funding from the European Union’s LIFE Environment sub-programme under the grant agreement LIFE18 NAT/NL/001047. The dataset was published with funding from Stichting NLBIF - Netherlands Biodiversity Information Facility

Additional file 1 of Spatial risk analysis for the introduction and circulation of six arboviruses in the Netherlands

Additional file 1: Table S1. Bird species that migrate from Africa and/or the Mediterranean area to North-western Europe during spring. Table S2. Bird species that have overlapping migratory flyways with conspecifics migrating from JEV-endemic regions in southeast Asia. Table S3. Ardeid bird species of the Netherlands. Table S4. Wetland bird species of the Netherlands. Table S5. Land cover classes of the Netherlands (LGN7) that were included as habitat for Ixodes ricinus and Hyalomma marginatum ticks. Habitat suitability ranged from 0 (not suitable) to 3 (very suitable)

Spatial risk analysis for the introduction and circulation of six arboviruses in the Netherlands

Abstract Background Arboviruses are a growing public health concern in Europe, with both endemic and exotic arboviruses expected to spread further into novel areas in the next decades. Predicting where future outbreaks will occur is a major challenge, particularly for regions where these arboviruses are not endemic. Spatial modelling of ecological risk factors for arbovirus circulation can help identify areas of potential emergence. Moreover, combining hazard maps of different arboviruses may facilitate a cost-efficient, targeted multiplex-surveillance strategy in areas where virus transmission is most likely. Here, we developed predictive hazard maps for the introduction and/or establishment of six arboviruses that were previously prioritized for the Netherlands: West Nile virus, Japanese encephalitis virus, Rift Valley fever virus, tick-borne encephalitis virus, louping-ill virus and Crimean-Congo haemorrhagic fever virus. Methods Our spatial model included ecological risk factors that were identified as relevant for these arboviruses by an earlier systematic review, including abiotic conditions, vector abundance, and host availability. We used geographic information system (GIS)-based tools and geostatistical analyses to model spatially continuous datasets on these risk factors to identify regions in the Netherlands with suitable ecological conditions for arbovirus introduction and establishment. Results The resulting hazard maps show that there is spatial clustering of areas with either a relatively low or relatively high environmental suitability for arbovirus circulation. Moreover, there was some overlap in high-hazard areas for virus introduction and/or establishment, particularly in the southern part of the country. Conclusions The similarities in environmental suitability for some of the arboviruses provide opportunities for targeted sampling of vectors and/or sentinel hosts in these potential hotspots of emergence, thereby increasing the efficient use of limited resources for surveillance