the expansion of boreal forests into the tundra reduces habitat for the numerous species that depend on this unique ecosystem. Caribou is one of the species that has perfectly adapted to survive tundra’s harsh conditions. In the summer months, large herds graze head to head on its rich grasses. During this time of abundance of feed, one animal can eat up to 5 kilograms of vegetation a day to prepare for the extremely cold winter. In the past two decades, numerous herds of those beautiful animals have suffered population decline; from 4.8 million animals today they are only 2.89 million¹. The culprit behind this decline is the loss of habitat caused, beyond human expansion in the far North, by global warming. The effects of global warming in the Arctic are diverse and for Caribou they come with a whole set of challenges such as changes in feed availability, extreme weather events and shifts in snow fall and thawing – events especially dangerous for the survival of newborn calves.
The Caribou story is one of many examples illustrating the challenges that many endangered species are facing globally. One million species around the world will be on the brink of extinction as a result of climate change in the next 50 years. Being aware of these grim predictions, scientists have to take a decision on whether to step in and physically relocate species at high risk. Managed relocation, or assisted migration, is a method whereby a species is deliberately moved from their original habitat to new areas with more favorable conditions.
The first cases of relocation involved moving species to habitats where they had been historically present. A successful example was the reintroduction of gray wolves to Yellowstone National Park. The U.S. Fish and Wildlife service transferred 8 animals from Jasper National Park in Alberta, Canada to Yellowstone in January 1995. The wolf population has been thriving in the Park since then². Other known cases of relocation have been performed to save species endangered by the expansion of invasive species in their original habitat. The release of the Guam rail on the island of Rota after nearly 20 years of being extinct in the wild due to the extensive predation of brown tree snakes in Guam, is a good example of such practice³.
Climate-driven managed relocation, however, is much more complex as scientists need to evaluate many different factors. Computer modelling of ecological data is often used to help predict whether new areas will be suitable for the species in question in the long term. The first climate-driven relocation project was carried out by the community of self-organized ecologists, the Torreya Guardians, in the southeast of the United States. Their aim was to help conserve Torreya taxifolia, an endangered coniferous tree. Similarly, giant sequoia trees (Sequoiadendron giganteum) have been planted for many years outside their historical range. Although in their case, the reasons behind this practice are unclear².
The most significant risk of managed relocation is that some past activities have led to the spread of invasive species. Therefore, it is crucial to determine which species are likely to do so well in their new environment that they would drive its original inhabitants to extinction. On the one hand, scientists in favor of managed relocation believe that thanks to the combination of modern technology and experience we can assess ecological factors better than in the past. On the other hand, we also know that when it comes to complex processes triggered by the diversity of species, ecological predictions could be refuted in practice; and if managed relocation becomes common practice, accidents are likely to happen.
In response to climate change, managed relocation entails risks, but so does doing nothing. Moving species to new areas might not prevent further biodiversity loss and it is not a suitable method for all endangered species. But on the basis of the data we have today, it can be successful for some of them. And even the slightest chance to save the diversity of life on Earth makes it worth a try.