Cold-blooded animals such as fish, reptiles, amphibians, and insects comprise most species on Earth. Since their growth, reproductive success, and survival is strongly coupled to environmental temperatures, climate change represents a major threat to them.
Although understanding the future effects of climate change on biodiversity is a global priority, predicting where a species will exist and in what abundance under future temperatures is highly difficult, since it implies estimating responses to temperatures which the animals have never experienced before.
To more accurately estimate how climate change will affect cold-blooded animals, a team of scientists led by Pennsylvania State University has recently developed a statistical method that links data collected on the field regarding the distribution and abundance of various cold-blooded species with laboratory-derived information about species-specific temperature performance and tolerance.
This new, innovative statistical modeling approach – called the “Physiologically Guided Abundance Model,” or PGA Model – can be applied across most cold-blooded animals to help inform climate adaptation and management strategies.
In contrast to previous approaches assuming that species-environment relationships are biologically meaningful under future temperatures, the PGA Model includes laboratory derived data on the physiological response of cold-blooded animals to temperature in order to more accurately predict how temperature changes may impact their performance and survival.
“Although cold-blooded animals are understudied when it comes to understanding how their distributions and abundance will respond to climate change, these animals are relatively well-studied when it comes to laboratory-derived information about how changes in environmental temperatures affect physiology and performance. In fact, most cold-blooded animals share a similar functional response in relative performance with increasing temperatures, which can be generalized across a diversity of taxa,” explained lead author Tayler Wagner, an adjunct professor of Fisheries Ecology at Penn State.
The researchers developed their model using data from three fish species (the cisco, the yellow perch, and the bluegill), which differ in their thermal preference and performance, and predicted their distribution and abundance in over 1,300 lakes from the U.S. Midwest at different future temperatures.
While, according to traditional models none of these fish species would be extirpated, or locally driven out, by temperature rises, the PGA model revealed that cold-adapted fish such as the cisco would in fact be extirpated in 61 percent of their current habitat. Thus, models that fail to include physiological references may lead to underestimates of the risk climate change poses to many cold-adapted species.
“We showed that temperature-driven changes in distribution, local extinction, and abundance of cold-, cool-, and warm-adapted species varied substantially when physiological information was incorporated into the model. The PGA model provided more realistic predictions under future climate scenarios compared with traditional approaches and has great potential for more realistically estimating the effects of climate change on cold-blooded species,” concluded co-author Gretchen Hansen, an assistant professor of Freshwater Ecology at the University of Minnesota.
The study is published in the journal Proceedings of the National Academy of Sciences.
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