Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Processing Description
• Data Files
• Related Publications
• Parameters
• Instruments
• Project Information
• Funding

Organism and Culturing

Tetraselmis suecica (UTEX LB 2286) was cultured in 250 mL Erlenmeyer flasks containing sterilized natural seawater. We used natural seawater as artificial seawater such as Instant Ocean has been shown to sometimes affect experimental outcomes (Pechenik et al. 2019). Seawater was sterilized using vacuum filtration to remove particulate matter and sediment, and subsequently autoclaved at 121ºC for 60 minutes. Non-experimental lineages were created at least every 10 days, and Micro Algae Grow nutrient media (Florida Aqua Farms Inc., Dade City, FL) was added every day beginning on day 0 to prevent nutrient limitation. These cultures were used to seed the experiments. Stock cultures were maintained in Darwin environmental chambers (Darwin Chambers Company, St. Louis, MO) at a constant temperature of 20ºC under continuous light provided by LED light strips. Stock cultures were gently swirled for 10 seconds daily to ensure homogeneity and proper aeration.

Experimental Setup

The experimental design involved acclimating cultures to eight different base temperatures (10ºC, 15ºC, 18ºC, 20ºC, 25ºC, 28ºC, 30ºC, 35ºC) over the course of 5 days in a Darwin environmental chamber. At the beginning of the experiment, cultures were placed on Peltier devices (Adafruit, New York, NY) housed in plastic egg-crate cages to prevent spillage. White LED strip lights were fastened inside the cages. Light was measured using a PAR sensor to verify that each cage was receiving at least 150 µmol m^-2 s^-2 (saturating irradiance (Bernhardt et al., 2018), and under 200 µmol m^-2 s^-2 to maintain consistent light conditions between cages. 

Temperature Control and Manipulation

To control temperature during the experiment, we used TEC (thermoelectric cooling) Controllers (Meerstetter Engineering, Rubigen, Switzerland) to control the Peltier devices. Cultures were exposed to one of 5 fluctuating temperature treatments +/- 5ºC around the base temperature, or the constant temperature (n=18 per base temperature, n=3 per treatment within each base temperature). The five fluctuating temperature treatments for each mean temperature were characterized by the following frequencies: (i) frequency of 1 or period of 144 hours, (ii) frequency of 3 or period of 48 hours, (iii) frequency of 6 or period of 24 hours, (iv) frequency of 18 or period of 8 hours, and (v) frequency of 24 or period of 6 hours.

In order to ensure that cultures were in the exponential growth phase for the duration of the experiment, we used cultures at a known concentration of between 1,000,000 and 2,000,000 cells/mL on Day 1 of the experiment. To achieve this, we inoculated cultures the previous week at a lower concentration (i.e. 25,000 cells/mL) such that they would reach 1,000,000 by the end of their pre-experimental acclimation period. This lower concentration depended on the temperature to which they were being acclimated, as cultures further away from their T_OPT would grow more slowly.

Cells were counted daily for each of the five days using a Beckman Coulter Z2 Particle Counter (Beckman Coulter, Indianapolis, IN) set to count particles between 5–16 µm. This size range was experimentally determined by photographing cells on a Hemacytometer and analyzing size with ImageJ. Samples were diluted in ISOTON II Diluent (Beckman Coulter, Indianapolis, IN), with a dilution factor such that cell counts ranged from 10,000 to 200,000 before factoring in a dilution factor. Three samples were taken per culture, and three counts were run on each sample to ensure consistency.

The raw data are provided (no processing performed).

- Imported "experimental_data.csv" into BCO-DMO system
- Converted datetime to ISO format (added 'T' between the date and time) and converted to UTC
- Renamed "full_date" to "measurement_datetime"
- Exported file as "953492_v1_tsuecica_exp.csv"

NSF Award Abstract:
Although it is well established that temperature extremes associated with heatwaves or cold snaps can have strong and immediate impacts on biological populations, much less is known about the longer-term effects of these short-term events. The investigators are filling this critical knowledge gap by conducting a series of laboratory experiments and developing a new set of mathematical models to identify how temperature fluctuations influence population growth and size. Additionally, the mathematical models are being extended to generate a baseline understanding of how changes in temperature anticipated under global climate change will likely affect populations around the globe over the course of the 21st century. This project addresses important societal needs by cross-training graduate students in biology, statistics, mathematical modeling, and computer programming. The results of this research are being integrated into undergraduate courses in biostatistics, mathematical modeling, and environmental science in order to demonstrate the importance of quantitative and interdisciplinary STEM training for addressing important questions in biology. Finally, multiple interactive web modules are being created to disseminate the results of this research beyond academic circles, including Northeastern University’s K-12 outreach programs.

Current empirical and theoretical approaches do not account for the cryptic population structure that emerges when organisms are exposed to variable temperature regimes. The investigators are addressing this limitation by using marine algae as a model system to (i) establish an empirical protocol for properly evaluating the effects of temperature variability on population growth, (ii) develop a novel mathematical modeling framework for accurately predicting the dynamics of populations exposed to temperature fluctuations, and (iii) determine species extinction risk under future ocean temperatures. Overall, this project is expected to yield a new set of empirical and theoretical tools to better forecast the biological effects of environmental change.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.