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Century-Long Warming Trends in the Upper Water Column of Lake Tanganyika.

Kraemer BM, Hook S, Huttula T, Kotilainen P, O'Reilly CM, Peltonen A, Plisnier PD, Sarvala J, Tamatamah R, Vadeboncoeur Y, Wehrli B, McIntyre PB - PLoS ONE (2015)

Bottom Line: However, after accounting for spatiotemporal variation in temperature and warming rates, the TEX86 paleolimnological proxy yields lower surface temperatures (1.46 °C lower on average) and faster warming rates (by a factor of three) than in situ measurements.Based on the ecology of Thaumarchaeota (the microbes whose biomolecules are involved with generating the TEX86 proxy), we offer a reinterpretation of the TEX86 data from Lake Tanganyika as the temperature of the low-oxygen zone, rather than of the lake surface temperature as has been suggested previously.Our analyses provide a thorough accounting of spatiotemporal variation in warming rates, offering strong evidence that thermal and ecological shifts observed in this massive tropical lake over the last century are robust and in step with global climate change.

View Article: PubMed Central - PubMed

Affiliation: Center for Limnology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.

ABSTRACT
Lake Tanganyika, the deepest and most voluminous lake in Africa, has warmed over the last century in response to climate change. Separate analyses of surface warming rates estimated from in situ instruments, satellites, and a paleolimnological temperature proxy (TEX86) disagree, leaving uncertainty about the thermal sensitivity of Lake Tanganyika to climate change. Here, we use a comprehensive database of in situ temperature data from the top 100 meters of the water column that span the lake's seasonal range and lateral extent to demonstrate that long-term temperature trends in Lake Tanganyika depend strongly on depth, season, and latitude. The observed spatiotemporal variation in surface warming rates accounts for small differences between warming rate estimates from in situ instruments and satellite data. However, after accounting for spatiotemporal variation in temperature and warming rates, the TEX86 paleolimnological proxy yields lower surface temperatures (1.46 °C lower on average) and faster warming rates (by a factor of three) than in situ measurements. Based on the ecology of Thaumarchaeota (the microbes whose biomolecules are involved with generating the TEX86 proxy), we offer a reinterpretation of the TEX86 data from Lake Tanganyika as the temperature of the low-oxygen zone, rather than of the lake surface temperature as has been suggested previously. Our analyses provide a thorough accounting of spatiotemporal variation in warming rates, offering strong evidence that thermal and ecological shifts observed in this massive tropical lake over the last century are robust and in step with global climate change.

No MeSH data available.


Long-term TEX86 temperature data compared to model estimates.Each large orange circular dot is a raw TEX86 surface temperature measurement. Each TEX86 measurement represents the annual mean surface temperature at the location of the TEX86 core site ± 0.4°C (95% confidence interval). The three lines are the modeled annual surface temperature at the location of the TEX86 core site at three different depths (0, 50, 100 m). There is a strong disagreement between TEX86 and modeled in situ temperatures, especially early in the time series. Deviations between the TEX86 temperature measurements and the modeled surface temperature may reflect model error, error in the TEX86 calibration procedure, or long-term shifts in the depth range of Thaumarchaeota (the microbes whose biomolecules are involved with generating the TEX86 proxy).
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pone.0132490.g006: Long-term TEX86 temperature data compared to model estimates.Each large orange circular dot is a raw TEX86 surface temperature measurement. Each TEX86 measurement represents the annual mean surface temperature at the location of the TEX86 core site ± 0.4°C (95% confidence interval). The three lines are the modeled annual surface temperature at the location of the TEX86 core site at three different depths (0, 50, 100 m). There is a strong disagreement between TEX86 and modeled in situ temperatures, especially early in the time series. Deviations between the TEX86 temperature measurements and the modeled surface temperature may reflect model error, error in the TEX86 calibration procedure, or long-term shifts in the depth range of Thaumarchaeota (the microbes whose biomolecules are involved with generating the TEX86 proxy).

Mentions: TEX86-based temperatures were 1.46°C colder on average than the modeled in situ surface temperatures (Fig 3). TEX86-based warming rates were faster than in situ temperatures by a factor of 3 over the period from 1918 to 1996 (0.248 ± 0.053°C decade -1 for TEX86 versus 0.079 ± 0.052°C decade -1 for modeled in situ data, Fig 4). After accounting for uncertainty in the TEX86 temperature calibration using monte carlo simulations with 100 permutations, there was still a significant difference in warming rates between TEX86 and the modeled in situ temperature trend (analysis of covariance p < 0.01, Figs 4 and 6). The slope between annual modeled in situ surface temperature (x axis) and TEX86 temperature (y axis) was significantly greater than one (slope = 5.29, 95% confidence interval = 2.96–20.91, MA regression with 100 permutations, Fig 4).


Century-Long Warming Trends in the Upper Water Column of Lake Tanganyika.

Kraemer BM, Hook S, Huttula T, Kotilainen P, O'Reilly CM, Peltonen A, Plisnier PD, Sarvala J, Tamatamah R, Vadeboncoeur Y, Wehrli B, McIntyre PB - PLoS ONE (2015)

Long-term TEX86 temperature data compared to model estimates.Each large orange circular dot is a raw TEX86 surface temperature measurement. Each TEX86 measurement represents the annual mean surface temperature at the location of the TEX86 core site ± 0.4°C (95% confidence interval). The three lines are the modeled annual surface temperature at the location of the TEX86 core site at three different depths (0, 50, 100 m). There is a strong disagreement between TEX86 and modeled in situ temperatures, especially early in the time series. Deviations between the TEX86 temperature measurements and the modeled surface temperature may reflect model error, error in the TEX86 calibration procedure, or long-term shifts in the depth range of Thaumarchaeota (the microbes whose biomolecules are involved with generating the TEX86 proxy).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4492510&req=5

pone.0132490.g006: Long-term TEX86 temperature data compared to model estimates.Each large orange circular dot is a raw TEX86 surface temperature measurement. Each TEX86 measurement represents the annual mean surface temperature at the location of the TEX86 core site ± 0.4°C (95% confidence interval). The three lines are the modeled annual surface temperature at the location of the TEX86 core site at three different depths (0, 50, 100 m). There is a strong disagreement between TEX86 and modeled in situ temperatures, especially early in the time series. Deviations between the TEX86 temperature measurements and the modeled surface temperature may reflect model error, error in the TEX86 calibration procedure, or long-term shifts in the depth range of Thaumarchaeota (the microbes whose biomolecules are involved with generating the TEX86 proxy).
Mentions: TEX86-based temperatures were 1.46°C colder on average than the modeled in situ surface temperatures (Fig 3). TEX86-based warming rates were faster than in situ temperatures by a factor of 3 over the period from 1918 to 1996 (0.248 ± 0.053°C decade -1 for TEX86 versus 0.079 ± 0.052°C decade -1 for modeled in situ data, Fig 4). After accounting for uncertainty in the TEX86 temperature calibration using monte carlo simulations with 100 permutations, there was still a significant difference in warming rates between TEX86 and the modeled in situ temperature trend (analysis of covariance p < 0.01, Figs 4 and 6). The slope between annual modeled in situ surface temperature (x axis) and TEX86 temperature (y axis) was significantly greater than one (slope = 5.29, 95% confidence interval = 2.96–20.91, MA regression with 100 permutations, Fig 4).

Bottom Line: However, after accounting for spatiotemporal variation in temperature and warming rates, the TEX86 paleolimnological proxy yields lower surface temperatures (1.46 °C lower on average) and faster warming rates (by a factor of three) than in situ measurements.Based on the ecology of Thaumarchaeota (the microbes whose biomolecules are involved with generating the TEX86 proxy), we offer a reinterpretation of the TEX86 data from Lake Tanganyika as the temperature of the low-oxygen zone, rather than of the lake surface temperature as has been suggested previously.Our analyses provide a thorough accounting of spatiotemporal variation in warming rates, offering strong evidence that thermal and ecological shifts observed in this massive tropical lake over the last century are robust and in step with global climate change.

View Article: PubMed Central - PubMed

Affiliation: Center for Limnology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.

ABSTRACT
Lake Tanganyika, the deepest and most voluminous lake in Africa, has warmed over the last century in response to climate change. Separate analyses of surface warming rates estimated from in situ instruments, satellites, and a paleolimnological temperature proxy (TEX86) disagree, leaving uncertainty about the thermal sensitivity of Lake Tanganyika to climate change. Here, we use a comprehensive database of in situ temperature data from the top 100 meters of the water column that span the lake's seasonal range and lateral extent to demonstrate that long-term temperature trends in Lake Tanganyika depend strongly on depth, season, and latitude. The observed spatiotemporal variation in surface warming rates accounts for small differences between warming rate estimates from in situ instruments and satellite data. However, after accounting for spatiotemporal variation in temperature and warming rates, the TEX86 paleolimnological proxy yields lower surface temperatures (1.46 °C lower on average) and faster warming rates (by a factor of three) than in situ measurements. Based on the ecology of Thaumarchaeota (the microbes whose biomolecules are involved with generating the TEX86 proxy), we offer a reinterpretation of the TEX86 data from Lake Tanganyika as the temperature of the low-oxygen zone, rather than of the lake surface temperature as has been suggested previously. Our analyses provide a thorough accounting of spatiotemporal variation in warming rates, offering strong evidence that thermal and ecological shifts observed in this massive tropical lake over the last century are robust and in step with global climate change.

No MeSH data available.