By: Erin Pickett, MS student, Oregon State University
They were climbing on their hands and knees along a high, narrow ridge that was in places only two inches wide. The path, if you could call it that, was layered with sand and loose stones that shifted whenever touched. Down to the left was a steep cliff encrusted with ice that glinted when the sun broke down through the thick clouds. The view to the right, with a 1,000ft drop, wasn’t much better.
–The Invention of Nature by Andrea Wulf
This is a description of Alexander von Humboldt and the two men that accompanied him when attempting to summit Chimborazo, which in 1802 was believed to be the highest mountain in the world. The trio was thwarted about 1,000 ft from the top of the peak by an impassable crevice but set a record for the highest any European had ever climbed. This was a scientific expedition. With them the men brought handfuls of scientific instruments and Humboldt identified and recorded every plant and animal species along the way. Humboldt was an explorer, a naturalist, and an observer of everything. He possessed a memory that allowed him to recount details of nature that he had observed on a mountain in Asia, and find patterns and connections between that mountain and another in South America. His perspective of nature as being interconnected, and theories as to why and how this was so, led to him being called the father of Ecology. In less grandeur terms, Humboldt was a biodiversity explainer.
In a recent guest post on Carbon Brief, University of Connecticut Professor Mark Urban summarized one of his latest publications in the journal Science, and called on scientists to progress from biodiversity explainers to biodiversity forecasters. Today, as global biodiversity is threatened by climate change, one of our greatest scientific problems has become accurately forecasting the responses of species and ecosystems to climate change. Earlier this month, Urban and his colleagues published a review paper in Science titled “Improving the forecast for biodiversity under climate change”. Many of our current models aimed at predicting species responses to climate change, the authors noted, are missing crucial data that hamper the accuracy and thus the predictive capabilities of these models. What does this mean exactly?
Say we are interested in determining whether current protected areas will continue to benefit the species that exist inside their boundaries over the next century. To do this, we gather basic information about these species: what habitat do they live in, and where will this habitat be located in 100 years? We tally up the number of species currently inhabiting these protected areas, figure out the number of species that will relocate as their preferred habitat shifts (e.g. poleward, or higher in elevation) and then we subtract those species from our count of those who currently exist within the boundaries of this protected area. Voilà, we can now predict that we will lose up to 20% of the species within these protected areas over the next 100 years*. Now we report our findings to the land managers and environmental groups tasked with conserving these species and we conclude that these protected areas will not be sufficient and they must do more to protect these species. Simple right? It never is.
This predication, like many others, was based on a correlation between these species ranges and climate. So what are we missing? In their review, Urban et al. outline six key factors that are commonly left out of predictive models, and these are: species interactions, dispersal, demography, physiology, evolution and environment (specifically, environment at appropriate spatiotemporal scales) (Figure 1). In fact, they found that more than 75% of models aimed at predicting biological responses to climate change left out these important biological mechanisms. Since my master’s project is centered on species interactions, I will now provide you with a little more information about why this specific mechanism is important, and what we might have overlooked by not including species interactions in the protected area example above.
I study Adelie and gentoo penguins, two congeneric penguin species whose breeding ranges overlap in a few locations along the Western Antarctic Peninsula. You can read more about my research in previous blog posts like this one. Similar to many other species around the world, both of these penguins are experiencing poleward range shifts due to atmospheric warming. The range of the gentoo penguin is expanding farther south than ever before, while the number of Adelie penguins in these areas is declining rapidly (Figure 2). A correlative model might predict that Adelie penguin populations will continue to decline due to rising temperatures, while gentoo populations will increase. This model doesn’t exactly inform us of the underlying mechanisms behind what we are observing. Are these trends due to habitat shifts? Declines in key prey species? Interspecific competition? If Adelie populations are declining due to increased competition with other krill predators (e.g. gentoo penguins), then any modelling we do to predict future Adelie population trends will certainly need to include this aspect of species interaction.
Range expansion can result in novel or altered species interactions, which ultimately can affect entire ecosystems. Our prediction above that 20% of species within protected areas will be lost due to habitat shifts does not take species interactions into account. While some species may move out of these areas, others may move in. These new species may potentially outcompete those who remain, resulting in a net loss of species larger than originally predicted. Urban et al. outline the type of data needed to improve the accuracy of predictive models. They openly recognize the difficulties of such a task but liken it to the successful, collective effort of climate scientists over the past four decades to improve the predictive capabilities of climate forecasts.
As a passionate naturalist and philosopher, there is no doubt Humboldt would agree with Urban et al.’s conclusion that “ultimately, understanding how nature works will provide innumerable benefits for long-term sustainability and human well-being”. I encourage you to read the review article yourself if you’re interested in more details on Urban et al.’s views of a ‘practical way forward’ in the field of biodiversity forecasting. For a historical and perhaps more romantic account of the study of biodiversity, check out Andrea Wulf’s biography of Alexander von Humboldt, called The Invention of Nature.
*This is an oversimplified example based off of a study on biodiversity and climate change in U.S. National parks (Burns et al. 2003)
References:
Burns, C. E., Johnston, K. M., & Schmitz, O. J. (2003). Global climate change and mammalian species diversity in US national parks. Proceedings of the National Academy of Sciences, 100(20), 11474-11477.
Urban, M. 14 September 2016. Carbon Brief. Guest post: How data is key to conserving wildlife in a challenging environment. From: https://www.carbonbrief.org/guest-post-data-key-conserving-wildlife-changing-climate (Accessed: 22 September 2016)
Urban, M. C., Bocedi, G., Hendry, A. P., Mihoub, J. B., Pe’er, G., Singer, A., … & Gonzalez, A. (2016). Improving the forecast for biodiversity under climate change. Science, 353(6304), aad8466.
Wulf, A. (2015). The Invention of Nature: Alexander Von Humboldt’s New World. Knopf Publishing Group.
