In this blog post, Emily Hague and team discuss their latest research into the importance of careful consideration of collision-mapping approach and data selection when it comes to predicting high-risk vessel collision areas for whales.
For conservationists and those that care about nature and our planet, the news can feel incredibly bleak, with daily (deservedly) scary stories of extreme climate change related temperatures, species fighting extinction, and nature suffering at the hands of humans.
However, in recent years, many large whale species have been offering an alternative narrative. A number of species and populations are now recovering from historic commercial whaling, increasing in number, and expanding their range. They are returning to waters their ancestors once used. It’s a remarkable, ever-evolving story, which fills me with hope and positivity for the future of our planet alongside these great ocean giants, especially given the numerous well-documented positive impacts whales have on the local area (including whale fall, blue health benefits, providing ecosystem services, and being known ecosystem engineers).
The modern day equivalent of whaling?
But, whales must now coexist with a number of modern day threats – pollution, fishing gear, and ships, to name a few. Whilst impressive efforts are being made globally to help reduce such threats to our recovering whales, sadly, fatalities are still happening, and for some populations these occur at an alarming rate. Fatalities from entanglement in fishing gear and vessel strikes may be the ‘new’ modern day whaling for the North Atlantic right whale (I hugely recommend Michael Moore’s ‘We are all Whalers’ for a both enlightening and uncomfortable read on this topic).
The good news is, unlike the days of whaling, the vast majority of the globe no longer wants to harm whales. As such, there is a real drive to reduce our human footprint on whale recovery, including reducing and mitigating the impacts of maritime traffic.
Reducing vessel-whale impacts
In some areas, vessel operators are already taking action to reduce their impacts on whales – from slowing down to altering their course when whales are known to be in the area. But there are many areas where we are still learning where whales and vessels overlap, and where the risk might be. In these cases, academics and managers rely on risk prediction tools to help them understand where to focus their efforts. A number of approaches have been developed to predict the risk of collision between whales and vessels, but so far, they haven’t been compared to figure out whether they can be used and interpreted interchangeably.
To dive into this further, we used a dataset collected on a fascinating whale species unique to Arctic waters – the bowhead whale. Historically, they might not have encountered many vessels, given a large portion of their habitat remains ice covered for much of the year, limiting vessel traffic. However, climate change means the Arctic ice-free season is extending, allowing more traffic to transit these waters year on year. Given this, we thought bowhead whales in the Davis-Baffin Arctic marine area would make the perfect case study for comparing vessel-risk prediction models, as despite having low historic exposure levels, we know bowheads are vulnerable to vessel collisions.
Our study
We used the same dataset of predicted bowhead whale distribution, and vessel data (as Automatic Identification System (AIS) data – which gives information on vessel identity, size, location and speed). We applied these datasets to eight different pre-published methodologies, that have previously been used to evaluate and forecast the likelihood of ships striking whales.
Our results
Interestingly, we found some significant inconsistencies in the total area each approach predicted as high risk, and in the actual geographical area identified as high risk.
Implications
Our study dives into the reasons for the inconsistencies, and highlights the importance of careful consideration when deciding upon which data to use, and which approaches are most appropriate for a given risk mapping circumstance. The choices of data and approach have real implications on the areas identified, which means they have subsequent implications for management or policy decisions that are made based on the results.
We hope this work can improve the transparency when it comes to risk mapping, and that it sparks a healthy discussion in terms of the limitations and strengths of each approach, and the data we need collect to inform and improve these models going forward.
Take home message
We now have a second chance with these animals, after commercial hunting pushed many species to the brink of extinction. Fortunately, there are many species now showing signs of recovery, but our maritime sector has largely evolved without the presence of large whales in any great numbers. We know that for some populations of whales, vessel strikes are now one of the primary threats to their recovery, so we need to be proactive and take the steps needed to protect them.
Through informed risk mapping and modelling, accompanied by positive collaborations with ship operators and other maritime sectors, and adaptive management able to evolve to mitigate new or changing impacts, we can help support these fantastic ocean giants continue to recover and thrive.
Read the full article “Not all maps are equal: Evaluating approaches for mapping vessel collision risk to large baleen whales“ in Journal of Applied Ecology.