Chapter 3: Drifting continents
Quaternary atmospheric CO2

Duke University

ENV 323/623 Biodiversity and climate change

Drifting continents combined with changing atmospheric concentration and climate to generate experiments in biodiversity. More recently, CO2 concentrations during the Quaternary have fluctuated with temperature over ice ages. We’ll use R to find the pacing of these quasi-periodic fluctuations.

From last time

• sign up for camera trap project: To access and download data go to wildlifeinsights.org. The account is approved by submitting this form. Approval can take a few days; do this now so we can download on thursday.
• Chapter 2: Drifing continents

Activities today

• Chapter 3: Drifing continents
• Climate data in R

For next time

1. Chapter 3
2. Questions at the end of this vignette
3. Qiu seminar: Tuesday 3:30, Room A158 LSRC; Biodiversity and forest regeneration in a rapidly changing world: consumers, habitat, and climate change

• Readings for discussion, pick 2 for your group:

  • Chevalier, Pollen-based climate reconstruction techniques for late Quaternary studies

  • McIntyre, Global biogeography since Pangaea

  • Woodburne, The Great American Biotic Interchange: Dispersals, Tectonics, Climate, Sea Level and Holding Pens

  • Lyson, Exceptional continental record of biotic recovery after the Cretaceous–Paleogene mass extinction

  • Osborne, Atmosphere, ecology and evolution: what drove the Miocene expansion of C4 grasslands?

  • Johnson, A progressively wetter climate in southern East Africa over the past 1.3 million years

  • Mumma, A 28,000 year history of vegetation and climate from Lower Red Rock Lake, Centennial Valley, Southwestern Montana

Long term CO2 extracted from glacial ice

To put contemporary CO2 in perspective, we’ll look at fluctuations across glacial stages. From the Halversen vignette, you can read in the CO2 concentrations extracted from Antarctic ice here:

antarctic <- read.table(
  'https://www1.ncdc.noaa.gov/pub/data/paleo/icecore/antarctica/antarctica2015co2composite.txt',
  skip = 138 )

Consider the following questions now, then we’ll work in groups to construct code.

1. Use the colnames function to give columns these names: 'BP', 'co2ppm', 'uncertainty'

The acronym 'BP' refers to years before present, where present is taken to be 1950.

2. create a plot of co2ppm against BP. Note that time runs from right to left. To turn it around, create a new column called year, as 1950 - BP.

3. Plot co2ppm against year.

4. In groups, we will draft pseudocode to suggest how you might find the glacial maxima (low CO2) and minima (high CO2). For example, I would find the extreme values based on some criteria. Or something else. Together, we’ll try to put this into R code.

5. Can you create an evenly-spaced time series that looks something like this? Try creating an evenly spaced sequence with tapply to aggregate points to the new sequence:

6. How many “interglacials” are there over the last 800 Ky BP?

7. How do glacial periods compare with interglacials in terms of length and duration?