At the start of the LIFE-MICA project, it was proposed that all the waterways in the test areas (approximately 12,000 km in Noord-Holland and 30,000 km in Fryslân) were going to be sampled and analysed for muskrat eDNA. In line with the ultimate goal of sampling all ~ 300,000 km waterways in the Netherlands post LIFE-MICA. Complete sampling of all the waterways in dedicated polders in Noord-Holland and Fryslân was indeed performed by the trappers. The results showed a Fryslân polder completely negative for muskrat eDNA and conversely a Noord-Holland polder with a higher number of eDNA positive tracks than practically usable.

Important feedback from the trappers revealed that sampling many ditches in a polder with complete coverage is extremely time and labour intensive as well as tedious. It also does not match with their current muskrat management strategy, where only in areas with higher populations of muskrat more hours are spent tracking. Areas with lower populations is less intensively monitored.

Based on the eDNA results and the feedback from the trappers, we decided to investigate the possibility of sampling only a representative subset of the waterways, while still maintaining high certainty of the actual muskrat population in an area. This approach was set-up using a so-called statistical power analysis, in which the entire management area is divided into smaller areas. To determine whether an area is empty of muskrat, the power analysis showed that sampling 80 5 km tracks in an area will suffice.

To further limit the necessary number of samples, the test was separated in to 2 phases. In phase I, 40 samples are taken in a defined area. Depending on the results, an area is then categorized as “full” “mid-full” or “possibly empty”. If an area is determined full, further use of the eDNA method has no added value, and the area is more suitable for tracking using the traditional approach. If an area is “mid-full” the entire area should be eDNA sampled. However, in the event muskrats are non-evenly spread over an area, the “mid-full” area can be further subdivided. These sub-areas are subsequently sampled again to add up to a total of 40 samples for each sub-area (for example if in one sub-area had 18 samples in the 1st round, 22 extra samples are taken to get to 40 samples in total and for the other area with 22 samples in the 1st round 18 extra samples are taken). The sub-areas can then be re-classified based on the results of the 2nd round. For any area that is classified as “possibly empty” in phase I or II, 40 additional samples need to be taken to get to the 80 samples required to confirm that it is indeed empty (phase II) table I.

To confirm if this approach is indeed feasible, a retrospective experiment was designed using already available sampling and muskrat catch data of certain sampled areas. This experiment showed that the approach does indeed work. Because muskrat have preferential areas, the selection of tracks within an area is not entirely random. Waterways in which muskrats have been caught in the past few years are always sampled. The area is subsequently sampled with random tracks in the other waterways to gain equal distribution of tracks in the entire area. For the power analysis, the size/number of waterways in an area does not matter. It is however important that an area is not so small that taking 80 samples constitutes full coverage. Depending on muskrat presence history one can choose to make areas with no or few catches larger, and areas with many recent catches smaller (Image I). The aim for the remainder of Life-MICA is to implement the approach in Noord-Holland and Fryslân.

The most important aspect of this approach is that by reducing the number of necessary samples, large areas, and eventually the whole of the Netherlands, can efficiently be monitored for muskrat presence and therefore provides a means on how to employ the trapper’s capacity most effectively.

After the successful Open Day on September 16 in Gendt, LifeMICA organized another Open Day in Lemmer. On 12 December, the attendees were updated on the latest status of the sub-projects. Everyone could also with their own eyes see what 2 of innovations look like ‘in real life’.

The program started with eDNA. Timo Breit of the University of Amsterdam was positive about this technique of using eDNA to demonstrate the presence of muskrats and coypu in the water. “The muskrat trappers spend 70 percent of their time searching along the banks”, he said. “By taking water samples and thus determining whether there are muskrats or coypu in a place, the work becomes more efficient. And less heavy for the trappers.” According to Breit, other advantages are that with eDNA you have a more objective picture of the presence of muskrats with eDNA, and that complete removal is achievable.

Muskrat families

Dolf Moerkens of the Unie van Waterschappen talked about DNA Mapping. In this subproject, an answer was sought to the question of whether muskrats trapped in Friesland originate from other areas, or whether they are there due to an increase in the local population. It turns out that there are familial relationships between muskrats in different regions. Most muskrats trapped in Friesland come from surrounding areas with relatively larger populations.

Faster software

Pascal van der Linden of waterschap Rivierenland told about the smart life-trapping cage. 25 have now been deployed at the test locations. 3 coypu and 9 muskrats were trapped with it. According to Van der Linden, the biggest challenge in this project is to enrich the Artificial Intelligence: “The software must learn to recognize muskrats and coypu. There is even a smart life trap in a zoo now for that purpose!” The traps have also improved in the meantime: the batteries last longer, the magnet is better, the housing of the trap is reinforced, the GPS is stronger and the software has become faster. This last topic was especially necessary, because the muskrat sometimes walked out of the trap before it closed.

Empty pictures

Finally, Emma Cartuyvels of the Flemish Institute for Nature and Forest Research talked about the smart camera traps. They are mainly used in areas where there are (almost) no muskrats left: you can quickly see if there is influx from new animals. The problem is that many ’empty photos’ are taken, and that half of the remaining photos show a duck. That is why the image recognition platform Agouti is used. This allows you to assess images more quickly and you no longer has to be done manually.

Demonstrations

In the afternoon, Mirjam Boonstra of the University of Amsterdam showed how samples for eDNA monitoring are collected with a ‘sailing drone’. Muskrat trapper Kees Schep demonstrated the life-trapping cage. Special observation: even if you keep a picture of a muskrat in the trap, it will close…

End of project

The Life MICA project will end in September 2023. According to project leader Hans Giskes, the next year will be exciting. “Next year we will deliver the final report, in which we account for what we have done and what the results are. And of course we will determine how we continue after Life.”

In Friesland, based on the analysis results of the first year, the trap intensity along the presumed inflow locations in Friesland has been increased. More traps have also been placed here. This evaluates management efficiency through a second round of DNA analysis.

DNA will be collected from a maximum of 100 muskrats trapped in Friesland in 2022. The DNA of the individual muskrats will be compared to the base map created after the first year. In this way it is possible to trace migration and link it to the most likely source location.

The evaluation report will be available in September 2023.

On the 13th of July 2022 in Brussels, the 2nd joint workshop Life MICA/Life RIPARIAS took place. About 30 participants from different countries and institutions dealing with invasive alien species (IAS) attended the hybrid event.

Photo 1: Invitation page

The workshop started with a plenary session in which the Life MICA and the Life RIPARIAS project were presented to the auditorium. Thereafter, two break out groups were created and participants could join either the group of the MICA project or that of the RIPARIAS project.

The aim of the Life MICA parallel session was to discuss transfer and replication opportunities for the innovative techniques for monitoring and management of IAS developed by Life MICA: smart camera traps, eDNA analysis, DNA mapping and smart life traps were presented.

There was high interest in how to use the Agouti platform for analysis of camera trap images with the Artificial Intelligence (AI) for other projects dealing with IAS. The high adaptability of the AI to be trained in recognizing other IAS was pointed out and the possible reduction in work effort for a broad scale monitoring with camera traps was discussed.

Furthermore, the e-DNA method was intensively discussed by the participants who asked about the suitability of the sampling protocol and analysis method for detection of other IAS or protected species in water samples.

Interest in the prototype of the smart life traps was manifested by participants, who were curious about the operating principle of the AI and the suitability in areas in which protected (non-target) species occur.

Photo 2: One of the Mentimeter questions with results

At the end of the break out session, participants were asked to answer some ‘Mentimeter’ questions about transfer and replication opportunities for each presented method and to share their opinion about which other invasive or non-invasive species could be monitored and managed using the techniques of the Life MICA project.

The day before, on the 12th of July, the follow-up ‘Conference on the management of vertebrate invasive alien species of Union concern – incorporating animal welfare’ coordinated by the International Union for Nature Conservation (IUCN) had taken place. Here you can find the very interesting documentation and reports.

> EASIN page
> EC IAS page

On September 16, Life Mica organized an open day in Gendt. This is located in the Geldersepoort nature reserve, one of the project areas. Local residents and various (nature) organizations attended the open day.

The morning started with an introduction to the muskrat and coypu and the problems these animals cause. Then all of Life Mica’s innovative methods to detect and trap muskrats and coypu were discussed: environmental DNA (eDNA), DNA mapping, smart cameras and smart life traps.

Also other animal species?

The attendees were enthusiastic and asked many questions. There were also some interesting discussions, for example about whether these innovative methods can also be used to detect other animal species.

With their own eyes

After the presentations, it was time to see the innovations with their own eyes. The participants went into the nature reserve and saw how water samples for analyzing eDNA were taken with a sailing drone. They also learned about the difference between a traditional and a smart trap.

Efficiency

Muskrat trapper Kees Schep sees the advantages of the smart life trap . “Traditional traps have to be checked regularly and that is hard work,” he told the visitors. “Thanks to the smart traps, we will be able to work more efficiently in the future.”

 

This project aims to develop smart life traps that use AI image-recognition. By incorporating AI we prevent unwanted bycatches of protected species as European beaver or otter and only catch target species like coypu and muskrat. More catches are made in the field and more details on the traps are improving.

By now, ten smart life traps are in use in Germany, five in Belgium and ten in the Netherlands. Two coypu and six muskrats were caught on either side of the Dutch-German border. In the past months AI image-recognition software was improved by using field images from the smart life traps. Also, the module works now both on- and offline, even when it is not connected to the internet.

Hardware

On hardware, the traps are improved as well. Mesh is mounted on both sides of the cage and the ground plate is elevated in order to obtain better pictures from animals that enter the trap. Also, mesh is mounted in front of the camera system for protection.

This summer the hardware will further develop with improvements like a stronger magnet and battery. Also, the AI image-recognition software will be enriched with images of otters and raccoons. The online message sent to the trapper will soon improve by always sending correct information on battery, GPS and trap status.

Active smart life trap at Sint-Maartensheide – De Luysen, April 1th 2022.

The message that is send to the trapper.

A survey was made on methods and materials for eDNA, DNA sequencing/mapping, smart cameras and smart traps. Although responses were few, preliminary results include excellent scores for DNA methods and useful field results for smart systems.

A total of 21 responses was too few for statistical analysis. This was the first survey, so possible effects may be analysed over time.

However, the first results include excellence in protocols for handling both DNA methods. It looks like eDNA is an excellent warning system and DNA sequencing/mapping is extremely effective for determining migration routes.

Challenges

Challenges are the intensive maintenance of materials (eDNA and DNA sequencing/mapping), the slow process (DNA sequencing/mapping) and the contradictory in work: trappers understandably prefer to work in areas with dense populations of rats, whereas eDNA methods focus on areas with few muskrats (eDNA).

Smart systems

For the smart systems (cameras and traps) the first results show that they are both multifunctional and can be used for different species. Smart life traps tend to render better catches. Design of the smart cameras is considered excellent.

Improvement

Improvement on the traps is needed on the hardware (battery and magnet), software (AI image-recognition) and the message to trappers (battery level, GPS and trap status). On the smart cameras there is room for improvement on the AI image-recognition software used for detecting muskrat or coypu and on the speed of processing.

A new survey will be held in October.
 

In January 2022, the results of the first round of DNA mapping in Friesland were presented to the muskrat fighters. Based on the results, the catch intensity along the probable inflow locations in Friesland will be increased by placing a cordon of traps here. Smart wildlife cameras have been installed at the intake locations.

Red cross: influx from outside Friesland
Yellow cross: transfer in Friesland

Tail tips

In addition, in the period from February 2022 – February 2023, the tail tips of all muskrats caught in Friesland will be collected for follow-up research. The aim is to collect 100 muskrats this year, spread as much as possible across Friesland. More than 50 muskrats have already been collected.

The current aim for the muskrat eDNA part of Life-MICA is scaling-up and real-life implementation of the eDNA approach and transference of sample processing to the water laboratories.

In order to compare results between the lab at the University of Amsterdam and the labs at Wetterskip Fryslân and Waterproef (Noord-Holland) we started sampling this year in regions with a higher chance of muskrat presence. For Fryslân this meant sampling near the borders, and for Noord-Holland sampling in a region where they have trapped the most muskrats in the past few years. Both regions have a low population of muskrat compared to other parts of the Netherlands.

Fryslân

In Fryslân a polder that has been designated as empty of muskrat was also sampled to determine if the eDNA results matched the evaluation based on traditional tracking methods (polder empty of muskrat), this did indeed match (Fig 1, region indicated by blue arrow). Figure one shows the results of sampling in Fryslân.

As of 29-06-22, 449 monitoring samples haven been taken in Fryslân, most by boat, as well as 78 localisation tracks, 70 point samples and 9 control samples (taken to confirm no more muskrat are present after catch actions).

As of 22-06-22, 34 muskrats had been trapped in the sampled areas (27 in waterways/tracks with eDNA and 7 in tracks without eDNA, but that were adjacent to tracks with eDNA).

Noord-Holland

In North Holland, there were many more traces of muskrat eDNA in the sampled region than in previously sampled areas. This allowed us to make a good comparison between the laboratories. But the high number of samples containing muskrat eDNA makes this region less suitable for the mainstream eDNA approach. Because of the significant population of muskrat in the area in the period of May/June the trappers focussed on catching the muskrats in this area. Figure 2 shows the catches of the muskrat overlayed on the eDNA results.

As of 22-06-22, 215 muskrat had been caught in the sampled area (182 in waterways/tracks with eDNA and 33 in tracks without eDNA, but again these were adjacent to tracks with eDNA). In Noord-Holland 167 monitoring tracks were sampled, as well as 163 localisation tracks and 181 point samples.

Most tracks in Noord-Holland were sampled by hand, which is more labour intensive and time consuming than sampling by boat. Areas with these population levels are more suited for follow up with eDNA after an intensive trapping effort, to determine if there are remaining muskrats, rather than the method used for monitoring areas that are historically empty or have very low presence.

Coypu

For the Coypu the aim is not so much scaling up but determining how to best integrate the eDNA method in the tracking efforts. Coypu behave differently from muskrat and are also caught alive in cages instead of traps in burrows. This makes certain parts of the field approach less useful for coypu (localisation of burrows). 31 areas were sampled for coypu presence, and as of 22-06-22, there were 23 catches, of which 21 corresponded with eDNA signal.

Wetterskip Fryslân and Waterproef processed all the samples of their respective regions for this year, and are thus capable of routinely processing samples. Transfer of analysis of coypu eDNA samples has been initiated with Aqualysis.

In the different project areas 47 camera traps have been placed to detect muskrat and coypu presence. These cameras take a sequence of images when they are triggered by movement.

Afterwards trappers need to annotate these sequences to see which species is on there. Over 80.000 sequences have been annotated so far. The most commonly seen species on the cameras are mallards.

Artificial Intelligence

Since June of 2021 we have been using the Artificial Intelligence (AI) developed by the Agouti team to help annotate our images and ease the workload. We started a project with the team from Agouti to retrain their AI to better work for water conditions. Hopefully this will further optimize the workflow for detecting muskrats and coypu with camera traps.