How Should Biologists Measure Climate Change?

Post provided by Christopher Nadeau

Climate change could cause the extinction of one in six species and change the abundance and distribution of those that remain (Urban, 2015). This doesn’t necessarily mean that one in six species in your backyard will go extinct though. Climate change impacts will vary greatly around the globe, with some regions seeing disproportionate effects.

The degree to which climate change will affect species in your region depends on many factors (e.g., land use and species traits), but the amount of climate change that species experience in your region – known as climate change exposure – will certainly be important. For that reason, measuring and mapping climate change exposure is critical for predicting where climate change will have the biggest impacts. Yet, biologists have no agreed upon method to measure exposure and different methods can produce dramatically different results.

A Simple Measure of Exposure and its Limitations

Climate can be defined as a statistical description of weather (e.g., temperature, precipitation) over the course of a long time period, usually 30 years. Most often climate is reduced to the average value of a particular weather variable over a 30-year period of interest. Climate change is then measured as the difference between the averages in two time periods; say the predicted average between 2070-2099 minus the average between 1971-2000.

Projected changes in annual average temperature between 1971-2000 and 2070-2099

Projected changes in annual average temperature between 1971-2000 and 2070-2099.

For example, the map to the left shows projected exposure to changes in average annual temperature. This map suggests that species in the arctic will be exposed to the most temperature change while species in the southern hemisphere will experience the least change. However, there are many problems with this interpretation. Continue reading

Why Do We Need Digital Elevation Models to Infer the Local Adaptation of Alpine Plants?

Post provided by Kevin Leempoel

dsc_4214-crest-flight-27-06-11It’s not easy to characterise the local environment of species living in mountains because these habitats are highly heterogeneous. At a large scale, we typically assume that temperature varies with altitude, but at a local scale, we understand that exposure to wind or being in the shade has a great influence on climatic conditions. If you go from the south-facing to the north-facing side of a mountain, it can be easily 5°C colder. If we can feel that, so can the organisms that live up there. Plants in particular are submitted to tremendous climatic variations over a year. What we want to know is: how did they adapt to these climatic variations and how localised is their adaptation?

Overcoming the Challenges of Measuring Local Adaptation

We don’t know much about how organisms adapt locally because it’s so difficult to measure the environmental conditions that these plants are facing. Existing weather stations can’t capture micro-habitat conditions because they are few and far between. What we can do instead, is use topographic models of mountains to model their environment. After all, if orientation, slope or shade have an impact on climatic conditions, why couldn’t we use them to model local variations in temperature for example? Continue reading

Biogeography at a Global Scale: The Benefits of Distributed Experimental Networks

Post provided by Elizabeth Borer



I have always loved the Blue Marble image of Earth from the Apollo 17 mission, yet a large part of my science is focused on experimental responses at the scale of meter squared grassland plots or even individual grass plants. While I spent my early career wanting to be able to say something important about regional or global processes, I found myself feeling like generating any experimental insights into processes and ecosystem responses at larger scales would be an impossible fiction.

As a postdoc, I had the opportunity to do a multi-site study across a north-south precipitation gradient in California and jumped at it. Among other questions, I decided to ask about whether plants and insects varied similarly across sites in response to replicated experimental treatments. Yet, the idea of actually sampling – and then processing samples from – more than about four sites for more than a year or two was utterly daunting. Continue reading