17. Read the text attached.
Passage 1
Critical information needed in fight to save wildlife
“Right now, we’re treating a mouse the same way as an elephant or a fish or a tree. Yet we know that those are all very different organisms and they are going to respond to their environment in different ways,” says University of Connecticut Ecologist Mark Urban, the Science article’s lead author. “We need to
The 22 top biologists affiliated with the article identify six key types of biological information, including life history, physiology, genetic variation, species interactions, and dispersal, that will significantly improve prediction outcomes for individual species. Obtaining that information will not only help the scientific community better identify the most at-risk populations and ecosystems, the scientists say, it will also allow for a more targeted distribution of resources as global temperatures continue to rise at a record rate.
Current climate change predictions for biodiversity draw on broad statistical correlations and can vary widely, making it difficult for policymakers and others to respond accordingly. Many of those predictions tend not to hold up over time if they fail to account for the full range of biological factors that can influence an organism’s survival rate: species demographics, competition from other organisms, species mobility, and the capacity to adapt and evolve.
“We haven’t been able to sufficiently determine what species composition future ecosystems will have, and how their functions and services for mankind will change,” says co-author Dr. Karin Johst of the Helmholtz Centre for Environmental Research and the German Centre for Integrative Biodiversity Research. “This is because current ecological models often do not include important biological processes and mechanisms: so far only 23 percent of the reviewed studies have taken into account biological mechanisms.”
Generating more accurate predictions is essential for global conservation efforts. Many species are already moving to higher ground or toward the poles to seek cooler temperatures as global temperatures rise. But the capacity of different organisms to survive varies greatly. Some species of frog, for instance, can traverse their terrain for miles to remain in a habitable environment. Other species, such as some types of salamander, are less mobile and capable of moving only a few meters over generations.
“New Zealand’s strong foundation in ecological research will help,” explains study co-author Dr. William Godsoe, a Lincoln University lecturer and member of New Zealand’s Bio-Protection Research Centre. “One of our hopes is to build on these strengths and highlight new opportunities to improve predictions by explicitly considering evolution, interactions among species, and dispersal.” This will aid in the development of strategies to manage impacts on species and ecosystems before they become critical.
With more than 8.7 million species worldwide, gathering the necessary biological information to improve predictions is a daunting task. Even a sampling of key species would be beneficial, the authors say, as the more sophisticated models will allow scientists to extrapolate their predictions and apply them to multiple species with similar traits.
The researchers are calling for the launch of a global campaign to be spearheaded by the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services or IPBES. The IPBES operates under the auspices of four United Nations entities and is dedicated to providing scientific information to policymakers worldwide. One thousand scientists from all over the world currently contribute to the work of IPBES on a voluntary basis. The scientists are also encouraging conservation strategies to support biodiversity such as maintaining dispersal corridors, and preserving existing natural habitats and genetic diversity.
“Our biggest challenge is pinpointing which species to concentrate on and which regions we need to allocate resources,” says UConn Associate Professor Urban. In an earlier study in Science , Urban predicted that as many as one in six species internationally could be wiped out by climate change. “We are at a triage stage at this point. We have limited resources and patients lined up at the door.”
Passage 2
Forecasting climate change’s effects on biodiversity hindered by lack of data
In a paper published in Science on Thursday (Sept. 8), biologists cite a critical lack of data on key biological mechanisms C such as how animals and plants spread during their lifetime and how they evolve in response to changes in the environment - as the main obstacle to improving models’ ability to forecast species’ response to climate change.
“This paper is a call to arms,” said Patrick Zollner, article co-author and Purdue associate professor of wildlife science. “The world is in dire circumstances. We’re losing a lot of species, and we’re largely unaware why. How do we need to rethink the kind of data we’re collecting so we can take advantage of modern modeling tools to understand the outcomes of climate change for ecological systems? This could help us forestall losing wildlife that we later deeply regret.”
The group outlines two key problems that hinder the capability of current models to make realistic predictions about biological responses to climate change.
Most models are descriptive, based on statistical correlations and observations, and fail to capture the underlying processes that produce observed changes. For example, a descriptive model might show that lynx in the northern U.S. are declining while bobcat populations in the same region are on the rise. Understanding what is driving this change requires a different sort of model, one that incorporates biological mechanisms. A mechanistic model that accounts for how warming temperatures affect snow depth, for instance, could provide insights into why bobcats - better adapted to habitats with less snow - are gaining a competitive edge over lynx. But 77 percent of current models of climate change’s impacts on wildlife do not include biological mechanisms.
Another challenge is that as models have grown in sophistication, they have far outpaced data collection. Put another way, a model is like a state-of-the-art kitchen, but the cupboards are bare.
“We can now build videogame-like environments with computers where we can create multiple versions of Earth and ask what the implications under different scenarios are,” Zollner said. “But our ability to learn from these tools is constrained by the kinds of data we have.”
They identified six biological mechanisms that influence wildlife’s responses to climate change: physiology; demography and life history; evolutionary potential and adaptation; interactions between species; movement over land or water; and responses to changes in the environment. They ranked the information needed to account for these mechanisms in models and suggested proxies for data that are missing or hard to collect.
A globally coordinated effort to fill data gaps could greatly advance improvements in models and informed conservation approaches, the researchers wrote. They point to the Intergovernmental Panel on Climate Change and its consistent improvements in climate change modeling as a valuable blueprint for such a project.
But local and regional conservation groups need not wait for a global body to coalesce to start using a mechanistic approach in their own region, Zollner said “If the ideas put forth in this paper start to be adopted and integrated into climate change work in a grass roots way, that could make a big difference in a region and could scale up over time,” he said.
Citizen scientists also have an important role to play in pitching in with data collection, he said.
Working with citizen scientists offers “an opportunity to get huge amounts of data, and it’s foolish not to take advantage of it,” Zollner said. “The data might not be as rigorous and needs to be treated differently, but it’s one more source of valuable information.
Reread this excerpt from Passage 2 in the attached text.
“Working with citizen scientists offers “an opportunity to get huge amounts of data and it’s foolish not to take advantage of it,” Zollner said. “The data might not be as rigorous and needs to be treated different, but it’s one more source of valuable information.”
