Frontiers for Young Minds

Frontiers for Young Minds
New Discovery Earth and its Resources Collection Article Published: May 20, 2022

Fish Ear Stones Offer Climate Change Clues In Alaska’s Lakes


Otoliths, also known as ear stones, are small body parts that help fish with hearing and balance. Like tree rings, otoliths form one light and one dark band per year, creating rings. These rings can be measured to understand fish growth. The wider the ring, the greater the growth. In our study, we used otoliths to understand how one fish species—lake trout—responds to rising temperature in the state of Alaska. We found that warmer spring air temperature and earlier lake ice melt were related to faster lake trout growth. This finding is consistent with other studies that link warmer water temperature and earlier lake ice melt to increased plankton in Alaska’s lakes. Together, these findings suggest that climate-driven increases at the bottom of the food web might benefit top predators like lake trout. However, the relationship between warmer temperature and faster growth may not last.

Things With Rings

Have you ever noticed the rings on a cross-cut tree trunk? Counting those rings can tell you the age of a tree. This is because each ring is made of two parts: a light-colored band of wood that formed in the spring and early summer, and a dark-colored band of wood that formed in late summer and fall. Therefore, a light band and a neighboring dark band represent 1 year of life for a tree.

But age is not the only thing revealed by tree rings. The width of the rings contains information about the growth of a tree and the environmental conditions it experienced. This is because trees respond to conditions like temperature, moisture, and nutrients. In warmer, wetter years, trees tend to grow more, and their rings are wider than in colder, drier years. Similarly, trees tend to grow more in years when nutrients like fertilizers are plentiful in the soil. Because trees stay in one place and grow for many years, their rings offer a record of conditions in that place over time.

Believe it or not, other organisms also form rings every year that they live. For example, corals and clams create yearly growth rings in their skeletons and shells. Some fish also do so, within their scales and ear stones. Ear stones—also called otoliths—are small, flat structures that help fish with hearing and balance (Figure 1). They are located just under the brain in a fish’s skull. Like tree rings, otoliths form one light and one dark band per year, creating a ring. These rings can be counted to determine fish age. They can also be measured to understand fish growth. The wider the ring, the greater the growth in a single year.

Figure 1 - A magnified cross-section of an otolith from an 18-year-old lake trout.
  • Figure 1 - A magnified cross-section of an otolith from an 18-year-old lake trout.
  • The black dots mark the edges of the rings. Rings for years 1, 10, and 18 are labeled. The white line shows the scale for this otolith (2.4 cm on the page is 1.0 mm in real life), and the yellow arrow shows its approximate location in a lake trout.

What Controls Fish Growth?

Fish grow faster or slower depending on how old they are and how well their environment meets their needs. Like humans, fish grow more slowly as they age. They also grow more slowly when they lack nutrients and energy from food. Unlike humans, fish grow more slowly in cold temperatures. The reason for this is simple. Most fish are ectothermic or cold-blooded, so their body temperatures are controlled by the water temperatures around them. When water temperatures are cold, everything in an ectotherm’s body slows down, including its breathing, digestion, and growth.

In our study, we used otoliths to explore the growth of one fish species—lake trout. We wanted to know how lake trout growth responds to temperature and nutrients. We were particularly interested in lake trout from Lake Clark National Park & Preserve in southwest Alaska, USA.

Why Study Lake Trout in Lake Clark?

Lake trout are top predators that thrive in cold, deep lakes. We focused on this species for two main reasons. First, we chose lake trout because they are common in Alaska. This makes them easier to find than rarer species. Second, we chose lake trout because they have long lifespans (20+ years). This means their otoliths contain a longer record of growth than other common fish species in Alaska, like sockeye salmon.

Lake Clark National Park & Preserve is known for its cold, deep lakes and surrounding wilderness. Human impacts, like buildings and roads, are scarce inside park boundaries. However, like the rest of Alaska, the park is experiencing climate change. Average annual air temperature in Alaska is warming about twice as fast as the world-wide pace [1]. Warmer air temperature is shortening the number of days that lakes have ice in winter [2]. Both air temperature and lake ice affect the conditions experienced by fish.

The park is also known for the thousands of sockeye salmon that spawn there. Salmon begin and end their lives in fresh water. Between those endpoints, they gain most of their body weight in the ocean, where the waters are high in nutrients. When salmon return to fresh water to spawn and die, their bodies are like bundles of nutrients delivered from the ocean. Some scientists think that those bundles of salmon nutrients help other freshwater fish grow faster [3].

What Was Our Question and Approach?

Lake trout are long-lived fish that prefer cold, deep lakes. Lake Clark National Park & Preserve has lots of cold, deep lakes, plus nutrients from dead salmon. However, Alaska’s changing climate is warming its lakes. Therefore, we asked whether lake trout grow faster or slower in warmer years, and whether sockeye salmon nutrients affect lake trout growth as well.

To study this, we caught 240 lake trout from 7 lakes, during the summers of 2004, 2011, 2012, and 2013. All the lakes had cool waters with low levels of nutrients. However, they differed in one basic trait: only 4 lakes were accessible to salmon. The other 3 lakes were upstream of barriers to salmon migration, like waterfalls.

After catching the lake trout, we removed their otoliths by dissection. We then used a multi-step process to count and measure the otolith rings. First, we covered each otolith with a gel that dried to a hard, clear block. Next, we cut the blocks with a special saw, to obtain a slice about as thick as a fingernail from the middle of each otolith. Then, we glued the otolith slices to glass microscope slides and photographed the slides using a camera attached to a microscope. The microscope made each otolith slice look 40 times bigger in the photograph than in real life.

Using the magnified photographs, we counted the otolith rings to age each fish. We also assigned a year of formation to each ring by counting backward from the year we caught the fish. Then, we measured the ring widths on the photographs. By the end of this multi-step process, we had measured 964 otolith rings. Although 964 seems like a lot, it is fewer than expected because only 80 of the 240 fish had distinct otolith rings.

Next, we used statistical models to summarize the 964 ring widths from the 80 lake trout into a single width per year, applicable to all lake trout in our study. We called that summarized version our master growth record because it applied to many different fish, like a master key that opened many different locks. The master growth record showed years when fish grew less than average, about average, and more than average. It included years from 1990 to 2011.

Finally, we compared the master growth record to temperature, ice, and salmon data from the same years. This was challenging because these types of data were not measured at each of our study lakes that far back in time. Therefore, we used the best available data from other sources. For temperature, we used monthly average air temperature at a weather station near one study lake (Lake Clark). For ice, we used the date when lake ice melted at another study lake (Telaquana Lake). For salmon, we used the number of adult sockeye salmon returning to spawn downstream of those two lakes. Using these datasets, we analyzed the relationships between lake trout growth, temperature, ice, and salmon.

What Did We Find?

We found that lake trout grew faster in warmer years. In particular, lake trout grew faster in years with warmer air temperatures in April (Figure 2). This pattern existed in February and July too but was not as strong. Lake trout also grew faster in years with earlier dates of lake ice melt. However, we did not see a pattern between lake trout growth and salmon. Lake trout did not grow faster in lakes with salmon compared to lakes without salmon. In lakes with salmon, lake trout did not grow faster in years with more spawning salmon.

Figure 2 - Our master growth record (black line) compared with average April air temperature (red line) for years 1990–2011.
  • Figure 2 - Our master growth record (black line) compared with average April air temperature (red line) for years 1990–2011.
  • Both variables were scaled to a mean value of 0 and a standard deviation of 1 to make their original units of measure (millimeters of growth and degrees Celsius) equal. You can see that lake trout growth (in black) and April air temperature (in red) track each other across years.

How Do Our Findings Fit Within the “Big Picture”?

Our study found that lake trout grow faster in years with warmer air temperature in April because warmer air causes earlier lake ice melt. Warmer air and earlier melt probably increase spring water temperature at the lake surface toward the 9°C preferred by lake trout. At this preferred temperature, lake trout can eat more and grow more without overheating, if food is available.

Interestingly, more food might be available in warmer years (Figure 3). Other studies in nearby lakes have shown that plankton counts increase with warmer surface water and earlier spring melt [2, 4]. Warmer springs are also linked to higher counts and faster growth of small plankton-eating fish, like young sockeye salmon [4, 5]. And guess what likes to eat young sockeye salmon as prey? Lake trout!

Figure 3 - Diagram of a simple lake food web showing phytoplankton, zooplankton, prey fish, and predator fish under two possible scenarios: cooler and warmer springs.
  • Figure 3 - Diagram of a simple lake food web showing phytoplankton, zooplankton, prey fish, and predator fish under two possible scenarios: cooler and warmer springs.
  • We expect that warmer springs lead to higher plankton counts, increased numbers and size of plankton-eating fish, and faster growing lake trout.

These results suggest that lake trout in Lake Clark National Park & Preserve might be climate change winners. They can benefit from the increased food linked to warmer water near the lake surface, while still having the option to use cooler water at deeper depths if they need to slow down their bodies to conserve food. These results hold true with or without the added nutrients from salmon. Whether these results will hold true over time, as climate warming continues, remains a question.


Nutrients: Chemicals that provide materials needed by living things to survive, grow, and reproduce. The nutrients that often limit growth at the bottom of lake food webs are nitrogen and phosphorus.

Otoliths: Small structures used by vertebrates for balance and hearing. In fish, otoliths grow by adding new layers of seashell-like material year after year, throughout life.

Ectothermic: Cold-blooded. An ectothermic animal is one whose internal body temperature depends on external heat sources for warmth.

Spawn: Reproduce, by adult salmon, through building a gravel nest, laying eggs in the nest, and fertilizing the eggs.

Statistical Model: A math “sentence” that compares two or more different pieces of information as numbers or categories to see if and how they are related.

Data: A group of facts, like numbers, measurements, or observations. The word “data” is the plural form of the word “datum,” which is a single fact.

Plankton: Tiny organisms that drift near the surface of a body of water, like a lake or ocean. These organisms may be plant-like phytoplankton or animal-like zooplankton. Zooplankton eat phytoplankton.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


We acknowledge the Natural Resources Protection Program of the U.S. Geological Survey for funding this project and contributing artists of the IAN Image Library ( for the clip art in Figure 3. Finally, we thank Nina Chambers, Jessica Levine, and our reviewers for helpful suggestions. Any use of trade names or products is for descriptive purposes only and does not imply endorsement of the U.S. Government.

Original Source Article

von Biela, V. R., Black, B. A., Young, D. B., van der Sleen, P., Bartz, K. K., and Zimmerman, C. E. 2020. Lake trout growth is sensitive to spring temperature in southwest Alaska lakes. Ecol. Freshw. Fish. 30:88–99. doi: 10.1111/eff.12566


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[2] Carter, J. L., and Schindler, D. E. 2012. Responses of zooplankton populations to four decades of climate warming in lakes of southwestern Alaska. Ecosystems 15:1010–26. doi: 10.1007/s10021-012-9560-0

[3] Wipfli, M. S., Hudson, J. P., Caouette, J. P., and Chaloner, D. T. 2003. Marine subsidies in freshwater ecosystems: salmon carcasses increase the growth rates of stream-resident salmonids. Trans. Am. Fish. Soc. 132:371–81. doi: 10.1577/1548-8659(2003)132<0371:MSIFES>2.0.CO;2

[4] Schindler, D. E., Rogers, D. E., Scheuerell, M. D., and Abrey, C. A. 2005. Effects of changing climate on zooplankton and juvenile sockeye salmon growth in Southwestern Alaska. Ecology 86:198–209. doi: 10.1890/03-0408

[5] Rich, H. B., Quinn, T. P., Scheuerell, M. D., and Schindler, D. E. 2009. Climate and intraspecific competition control the growth and life history of juvenile sockeye salmon (Oncorhynchus nerka) in Iliamna Lake, Alaska. Can. J. Fish. Aquat. Sci. 66:238–46. doi: 10.1139/F08-210