The climate crisis can especially be felt in the Arctic: in the High North, the average air temperature has risen by more than two degrees Celsius over the past 50 years – far more than anywhere else. And this trend will only continue. If ambitious greenhouse-gas reduction measures (Emissions Scenario RCP 2.6) are taken, the further warming of the Arctic through the end of the century could be limited to just below two degrees. According to supercomputer model-based forecasts, if the emissions remain high (Scenario RCP 8.5), we could see a dramatic rise in the average summer temperatures in the Arctic – by up to 14 degrees Celsius over today’s norm by 2100. 

“For the Arctic Ocean and the sea ice, the current and future warming will have serious consequences,” says Prof Ulrike Herzschuh, Head of the Polar Terrestrial Environmental Systems Division at the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research (AWI) in Germany. “But the environment on land will also change drastically. The broad expanses of tundra in Siberia and North America will be massively reduced, as the treeline, which is already slowly changing, rapidly advances northward shortly. In the worst-case scenario, there will be virtually no tundra left by the middle of the millennium. In the course of our study, we simulated this process for the tundra in northeast Russia. The central question that concerned us was: which emissions path does humanity have to follow to preserve the tundra as a refuge for flora and fauna, as well its role for the cultures of indigenous peoples and their traditional ties to the environment?”

The tundra is home to a unique community of plants, roughly five percent of which are endemic, i.e., can only be found in the Arctic. Typical species include the mountain avens, Arctic poppy, and prostrate shrubs like willows and birches, all of which have adapted to the harsh local conditions: brief summers and long, arduous winters. It also offers a home for rare species like reindeer, lemmings, and insects like the Arctic bumblebee.

For their simulation, Ulrike Herzschuh and AWI modeler Dr Stefan Kruse employed the AWI vegetation model LAVESI. “What sets LAVESI apart is that it allows us to display the entire treeline at the level of individual trees,” Kruse explains. “The model portrays the entire lifecycle of Siberian larches in the transition zone to the tundra – from seed production and distribution, to germination, to fully grown trees. In this way, we can very realistically depict the advancing treeline in a warming climate.”

The findings speak for themselves: the larch forests could spread northward at a rate of up to 30 kilometers per decade. The tundra expenses, which can’t shift to colder regions due to the adjacent Arctic Ocean, would increasingly dwindle. Since trees aren’t mobile and each one’s seeds can only reach a limited distribution radius, initially the vegetation would significantly lag behind the warming, but then catch up to it again. In the majority of scenarios, by mid-millennium less than six percent of today’s tundra would remain; saving roughly 30 percent would only be possible with the aid of ambitious greenhouse-gas reduction measures. Otherwise, Siberia’s once 4,000-kilometre-long, unbroken tundra belt would shrink to two patches, 2,500 kilometers apart, on the Taimyr Peninsula to the west and Chukotka Peninsula to the east. Interestingly, even if the atmosphere cooled again in the course of the millennium, the forests would not completely release the former tundra areas.

“At this point, it’s a matter of life and death for the Siberian tundra,” says Eva Klebelsberg, Project Manager Protected Areas and Climate Change / Russian Arctic at the WWF Germany, about the study. “Larger areas can only be saved with very ambitious climate protection targets. And even then, in the best case, there will ultimately be two discrete refuges, with smaller flora and fauna populations that are highly vulnerable to disrupting influences. That’s why we must intensify and expand protective measures and protected areas in these regions, to preserve refuges for the tundra’s unparalleled biodiversity,” adds Klebelsberg, who, in collaboration with the Alfred Wegener Institute, is an advocate for the establishment of protected areas. “After all, one thing is clear: if we continue with business as usual, this ecosystem will gradually disappear.”

The iconic Red List of Threatened Species, published by the International Union for Conservation of Nature (IUCN), identifies species at risk of extinction. A study in PLOS Biology publishing May 26^th by Gabriel Henrique de Oliveira Caetano at Ben-Gurion University of the Negev, Israel, and colleagues presents a novel machine learning tool for assessing extinction risk and then use this tool to show that reptile species which are unlisted due to lack of assessment or data are more likely to be threatened than assessed species. 

The IUCN’s Red List of Threatened Species is the most comprehensive assessment of the extinction risk of species and informs conservation policy and practices globally. However, the process for categorizing species is laborious and subject to bias, depending heavily on manual curation by human experts; many animal species have therefore not been evaluated, or lack sufficient data, creating gaps in protective measures.

To assess 4,369 reptile species that were previously unable to be prioritized for conservation and develop accurate methods for assessing the extinction risk of obscure species, these researchers created a machine learning supercomputer model. The model assigned IUCN extinction risk categories to the 40% of the world’s reptiles that lacked published assessments or are classified as “DD” (“Data Deficient”) at the time of the study. The researchers validated the model’s accuracy, comparing it to the Red List risk categorizations.

The researchers found that the number of threatened species is much higher than reflected in the IUCN Red List and that both unassessed (“Not Evaluated” or “NE”) and Data Deficient reptiles were more likely to be threatened than assessed species. Future studies are needed to better understand the specific factors underlying extinction risk in threatened reptile taxa, to obtain better data on obscure reptile taxa, and to create conservation plans that include newly identified threatened species.

According to the authors, “Altogether, our models predict that the state of reptile conservation is far worse than currently estimated and that immediate action is necessary to avoid the disappearance of reptile biodiversity. Regions and taxa we identified as likely to be more threatened should be given increased attention in new assessments and conservation planning. Lastly, the method we present here can be easily implemented to help bridge the assessment gap on other less known taxa”.

Coauthor Shai Meiri adds, “Importantly, the additional reptile species identified as threatened by our models are not distributed randomly across the globe or the reptilian evolutionary tree. Our added information highlights that there are more reptile species in peril – especially in Australia, Madagascar, and the Amazon basin – all of which have a high diversity of reptiles and should be targeted for the extra conservation efforts. Moreover, species-rich groups, such as geckos and elapids (cobras, mambas, coral snakes, and others), are probably more threatened than the Global Reptile Assessment currently highlights, these groups should also be the focus of more conservation attention”

Coauthor Uri Roll adds, “Our work could be very important in helping the global efforts to prioritize the conservation of species at risk – for example using the IUCN red-list mechanism. Our world is facing a biodiversity crisis, and severe man-made changes to ecosystems and species, yet funds allocated for conservation are very limited. Consequently, it is key that we use these limited funds where they could provide the most benefits. Advanced tools- such as those we have employed here, together with accumulating data, could greatly cut the time and cost needed to assess extinction risk, and thus pave the way for more informed conservation decision making.”