A picture is worth a thousand data points

Building a Habitat Suitability Model Part 2.

In part 1 of “Building a habitat suitability model”, you learned how researchers track animals’ movements, identify the home ranges and core areas of use, and why that information is important for conservation. But why are those areas important? What is the environment animals prefer? How does the habitat change over time?

How do we find out what makes an animals’ home range a ‘home’?

home.gif

Just like in case of tracking animal movements, some environments are easy and relatively inexpensive to characterize over time. When I worked at a wetland restoration center, I would pull on my wellies every other week, walk out to the lakes and streams, and take measurements of the habitat features. I’d record the temperature and dissolved oxygen with a handheld monitor at a number of standard sites, and take soil and water samples back to the lab for analysis. These collections provided information on seasonal, weather-associated, and geographic changes in the environment and could be used to determine the types of habitats different animals preferred.

Irrigation water testing training

Would the same methods work for understanding the habitat features for juvenile Steller sea lions (below)?

ssl_dist

Even getting a handful of samples in the ocean can be difficult: boat time is expensive which can limit how often you can go collect samples, samples are nearly impossible to gather year-round due to rough seas and weather, and the sheer size of the area makes it hard to monitor fine-scale habitat changes.

Look to the stars

Once again, satellites come to the rescue! Satellites like those operated by NASA and NOAA (VIIRSGOES, SeaWiFS) are constantly orbiting the earth taking photographs. Just like our eyes are constantly sensing the environment and categorizing information based on what we see, sensors on satellites take images that can be decoded to reveal information about the environment.

nasa_iotd
On May 29, 2017, the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA’s Aqua satellite captured the data for this image of an ongoing phytoplankton bloom in the Black Sea. The image is a mosaic, composed from multiple satellite passes over the region. Source: NASA Image of the Day

Color images (above) are representations of the visible light spectrum (good old ROY G BIV). In marine habitats, phytoplankton blooms can be mapped from color images by identifying areas of high chlorophyll a, or the degree of ‘greenness’. This metric is useful because plankton is the bottom of the food chain; therefore, areas of high chlorophyll a are often associated with high fish productivity.

sst
Global sea surface temperature from August 2015; if you look closely you can see the El Niño in the Pacific. Source: NOAA ERD and CoastWatch West Coast Regional Node 

 

Infrared images (above) can detect the thermal properties of the image. For example, sea surface temperature is often an important habitat feature to consider when dealing with species that have narrow temperature niches like sea turtles (check out TurtleWatch: a program that uses satellite temperature maps to help fishing boats avoid turtle bycatch!!).

Both of these measurements have a big problem though—clouds.  If it is too cloudy—like much of the year here in Seward—the sea surface color can’t be seen and the infrared waves are blocked.

Thankfully, some modern satellites can also conduct active sensing using microwaves and lasers to reveal information about sea surface temperature, height, and roughness, wind direction, and ice coverage even in the presence of clouds. These two videos show how laser altimeters can provide information on ice heights and how satellites like ICESat-2 will help us understand changes in the polar regions!

 

For our juvenile SSL habitat modeling project, we are most interested in environmental patterns that might shape the behaviors of the juveniles including but not limited to: ocean current patterns, temperature, food availability, etc. Much of this information will be collected from satellite images and paired with the movement data.

Next Time: “Putting it all together—Building a Habitat Use Model”

Written by: Dr. Amy Bishop

 

BONUS Trivia:

The answer to the last trivia question was—The Pythagorean Theorem!

This week: In October, it will be the 60th anniversary of the first artificial satellite launched into space orbit. What was it named?

Photo Credits:

Star Wars Gif: https://goo.gl/images/g5YpCN

Water Sampling: http://www.goodfruit.com/simple-steps-for-water-sampling/

Steller’s sea lions resting on rocks: © Eric Baccega / naturepl.com

Steller sea lion range map: https://www.afsc.noaa.gov/archives/stellers/range.htm

Satellite thumbnail: https://nasa.tumblr.com/post/131493842134/nasas-fleet-of-planet-hunters-and-world-explorers

One thought on “A picture is worth a thousand data points

Leave a Reply