WildTrax is an online platform for managing, storing, processing, and sharing biological data collected by environmental sensors. WildTrax provides tools for managing large data sets, and also creates opportunities to address broad-scale questions using novel approaches. Supported environmental sensors currently include autonomous recording units (ARUs) and remote wildlife cameras, while a third sensor, point counts, provides access to manage avian count data collected by humans.

WildTrax is available for organizations using cameras and / or ARUs⁠—simply create an online account to begin. Contact info@wildtrax.ca or see The Guide on how to get started.

WildTrax offers several benefits for users of environmental sensors, including:

• Improvement in processing speed
• More accurate, and higher quality data using the species verification
• Unlimited, online access to your data
• Seamless and flexible data sharing options with teams and collaborators
• Standardized approaches to data collection across networks of organizations and individuals
• Opportunities to discover data in your region of interest, coordinate with other groups, and address broad-scale ecological questions 
• Centralized repository for long term data archiving
   

Sensors can be deployed in many ways, depending on the monitoring objective. Examples of methods and protocols are found here.  

ABMI set-up methods are summarized  below:

Creating an account, setting up an organization and processing and publishing projects is free. 

Exceptions may occur if an organization attempts to upload 10’s of millions of images or recordings per year, in which case there may be some required cost recovery for the storage fees on AWS, where the media are stored. 

Your upload and download speed are limiting factors when you interface with WildTrax - it attempts to resolve these issues by providing asynchronous uploading and caching large data sets. But be mindful of the volume of data you're uploading and downloading and your internet connectivity before proceeding. 

Currently, the system natively supports the Reconyx HF2 and HC600 models. If another model is used, please contact support@wildtrax.ca so we can add it to the list of supported units.

The ABMI uses Reconyx PC900 and HF2 cameras. These cameras are great for first-time users as they are user-friendly and intuitive. High-quality SanDisk SD cards or Kingstone Class 4 and 10 SD cards are also used. 

For more information on camera brands, please click here.

WildTrax integrates the following:

• Microsoft's Megadetector, that automatically tags images of vehicles, animals, humans or none
• An “auto-cattle” model that automatically identifies images of cows
• A "staff/setup" tagger designed to filter out images of humans at the camera's deployment and retrieval. When enabled in your project's settings these settings will automatically filter and tag your images.

This results in:

• Less time spent sifting through false fires
• More time spent focusing on the species you want to tag

Cameras can sometimes capture images that do not contain wildlife—‘false fires’—due to movement in vegetation or changes in sunlight. These false fires can increase processing cost and time. To aid in processing these images, WildTrax contains a model to automatically identify false fires, allowing them to be removed before further processing. The model uses training data from 1,325 camera deployments as well as a trained network, CaffeNet, specifically modified for WildTrax. This tool results in less human time spent sifting through images of vegetation movement. The model was validated with an additional 121 camera deployments with 79,451 false-fire images. The model identified 34,456 (43.6%) of false fires with a 0.2% error (false positive) rate. That is, more than 40% of false fires can be reliably (0.2% error) removed before processing. Depending on the camera unit used, image quality and habitat type results may vary.

WildTrax does not remove any image by default but instead allows you to both filter images of humans using the results from the Megadetector (if it is enabled on your project) as well as opt-in for image facial blurring (if it is enabled at the organization level).

Wildlife bioacoustics is the study of animals using the vocalizations that they produce. Sounds are identified to the species or even individual level using unique patterns known as spectral signatures. These data are used to answer research and monitoring questions about individual species or groups of species.

The Bioacoustic Unit is a collaboration between the Bayne Lab at the University of Alberta and the Alberta Biodiversity Monitoring Institute. Our research group develops tools, protocols and recommendations for acoustic monitoring programs across the country.

To learn more about the Bioacoustic Unit, please click here.

The BU uses robust environmental sensors, called Autonomous Recording Units (ARUs)—essentially sophisticated battery-operated microphones⁠—to record sounds produced by vocalizing animals⁠. There are recommended settings that can be used to optimize recordings of birds, mammals, and other taxa. 

The Bioacoustic Unit uses Song Meter Autonomous Recording Units made by Wildlife Acoustics. Most of our Song Meters are the SM2+ and SM4 models. Other less frequently used models include the SM3, the SM2 with GPS, and the SM2+BAT. The GPS-enabled units permit more precise localization of animals in space. For memory cards, we often use high-quality SanDisk SD cards. We also occasionally use the Kingstone Class 4 and 10 SD cards.  Wildtrax can take data from any type of digital sound recorder.

For more information on Autonomous Recording Unit brands, please click here.

Deciding on a recording schedule for an ARU-based program will depend somewhat on the taxa of interest and the objectives of the program; however, there are some general recommendations and standards based on BU research. Firstly, to save storage space, there is often little value in collecting afternoon data. Secondly, recording from the last week of May to the first week of July (in Alberta) yields the highest detection rates for the most species, with the exception of some amphibians and owls which are more likely to be detected in April and May. For more information click here.

Cumulatively more species are observed by going to new stations within a study area than by listening to more recordings of the same locations; however, the difference is not that large. If sufficient funding exists to go to more locations, that will provide a better estimate of total species. However, when restrained by field costs, leaving ARUs in the same location and repeatedly sub-sampling is recommended, particularly if you are interested in multiple taxa (e.g., owls and songbirds)

For songbirds, leaving an ARU out for several days will yield higher occupancy rates and probability of detection than repeatedly sampling in a single day. The additional benefit of leaving an ARU out for a month is relatively small for songbirds. However, there is evidence that more species will be detected with more sampling effort and owls, amphibians, and mammals have very different calling behaviours from those of songbirds.

Minimum sampling effort recommended by the BU in order to maximize detection for most acoustic species is 3–7 days. Each sampling event is recommended to be at least 3 minutes long, either at dawn or dusk and at least one day apart. 

The question here is whether you could achieve the same results by listening to the same total number of recordings from a single day vs. a week vs. a month. Sampling for approximately a week results in higher estimates of species richness at a station compared to sampling for a day. In our tests, there was no significant difference between leaving an ARU out for a week vs. a month but that was only for songbirds.

This is entirely dependent on the frequency with which a species sings. The Bioacoustic Unit and the Boreal Avian Modelling project has estimates for all species, however, so you can assess the effort required to ensure you detect a species if it is present.

Calling rate has the greatest effect on detection rate, explaining 49% of the variance in detection rate. Calling rate coupled with the abundance of a species, time period, and a species’ log body weight explained 69% of the variance in detection rate. When the abundance of a species is high, there is higher detectability. Species that call at night have lower detection rates than those that call during the day. Also, larger species generally have lower calling rates. In general, species that are less abundant, have a large body weight, and vocalize infrequently and/or more often during the night have a lower detection rate and will require more extensive sampling.

There are consistent benefits to repeatedly sampling at the same station when estimating trends for a species as you are more certain if the species is present or absent. However, the statistical power of trends is driven by the number of stations and the number of years observed.

Within the first minute of a 10-minute point count, 49.8% of all vocalizing species are detected. Within the first five minutes, 79.2% of all vocalizing species are detected. However, if you have the choice between 10 1-minute samples taken at different times of day or year and 1, 10-minute period you will detect far more species using 10 1-minute segments.

Using more point counts with shorter duration detected a larger proportion of all species compared to fewer, longer duration point counts.

If you sample only a few points from the total number of available recordings, there is strong evidence that afternoon sampling can be avoided altogether if you are relying on listening.

Recognizers can be used when you are targeting a specific species, and a manual scanning spectrogram can be very effective in processing data when vocalizations are visually distinctive and recognizable. In short, the training data is used to create a template (“recognizer”) and is then matched to a recording segment from the test data. More information can be found here.

You must first create an Organization to house your data and metadata. The WildTrax team will review your request and confirm your identity after which point you will have the ability to create projects under your newly created Organization and upload media into those projects. 

There can only be one Organization for a Project. You must choose who owns that data. This must also be the organization who collects and uploads the data. The owner of the data can then add the collaborating users to their project or organization pending on the level of collaboration

In your Organization settings change all locations to the specific buffer you are comfortable with. For each project you wish to share choose "Published - Map + Report" as non-authorized users will not be able to see the media or the un-buffered location this way

WildTrax uses various permission and privacy levels throughout the system to ensure your data is secure to the level you choose

WildTrax has two basic membership levels : Admin and Read-Only. See below for more details on what each membership level can do

Organizations are the framework of your data on WildTrax. It contains your locations, visits, equipment and summaries of your acoustic recordings and camera data upload to your Projects.

An organization usually contains a collection of people who collect data, publish projects and manage equipment and teams. Administrators can read and write un-buffered locations on all organizational locations, add users to Organizations and Projects. read and write location, visit and equipment metadata and inherit administrator privileges on all organization projects. Read-Only members have read un-buffered on all organizational locations, can read location visit metadata and equipment and can read all organization projects. 

Projects are a targeted study or objective to accomplish or learn something using environmental sensor data. It is populated using locations, visit and contains a collection of tasks to achieve this work. Project administrators manage and coordinate the project, assign tasks and users and publish projects. Read-Only members can view and download data depending on their level of access via the Project Privacy Levels:

• Active
• Test Only - Hidden
• Published - Private
• Published - Map + Report Only
• Published - Public

Choose Published - Private if you don't want to receive access requests or Active if you are still working on completing your project.

Locations are a physical location associated with the deployment of an environmental sensor. It contains subsequent visit and equipment metadata that were collected on behalf of the organization. Locations can be either hidden, buffered, true location + buffer and true location. This allows for flexibility with specific locations requiring a higher level of privacy. 

Tasks are recordings or deployments assigned to a specific user and tagging protocol. Read-Only member can gain privileges to write at the task level in order to perform tagging. Organization or project administrators can also change the tags in the tasks which is subsequently tracked in the audit table

Recordings (ARUs) / deployments (cameras): an audio file or a series of images corresponding to an ARU / camera deployment. 

For each project make sure you choose Published – Private when it is complete.  In order to give someone access to a project add the user into the Project as a member (will give access to just the current project + buffered access) or add the user as a member into the Organization (will give all projects + un-buffered access). You can also remove members from the project or Organization or reduce their access at any time.

• Active
• Test Only
• Published - Private
• Published - Map + Report Only​​​​​​​
• Published - Public

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Make your locations true without a buffer - you can buffer individual locations if they specifically are sensitive. Make sure your projects when completed are set to Published – Public.  Anyone will be able to see your project metadata, media associated with published projects as well as download a report on your project.

Buffer your locations in organization settings - this tells WildTrax this location is already buffered and no one will know the true location because WildTrax was never given that information.

You must add yourself as a project member to see the projects in the default view. You can simply hit the “View Only My projects” toggle to the top right to see all projects you are eligible to see. WildTrax does this to try to help simplify the amount a user sees at once as it would be overwhelming and most of the time people are only interested in their own projects.

Organization investigators are the ones who receive all access requests. If no investigators have been assigned only then will the requests go to the admins of the project/organization.

Make sure your Organization has an investigator set to handle all of these requests. You can do this in organization settings.

All data uploaded to WildTrax is by default private and only viewable by the project member depending on their level of membership (Admin or Read-Only). Project and organization administrators maintain ownership and privacy rights over uploaded data, regardless of whether the data is private or publicly available. When you upload data to WildTrax, you have the option of releasing your data publicly or not.