Evaluations of Climate and Land Management Effects on Lake Carbon Cycling Need to Account for Temporal Variability in CO2 Concentrations. Klaus, M., Seekell, D. A., Lidberg, W., & Karlsson, J. Global Biogeochemical Cycles, 33(3):243–265, 2019. _eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2018GB005979![Evaluations of Climate and Land Management Effects on Lake Carbon Cycling Need to Account for Temporal Variability in CO2 Concentrations [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Carbon dioxide (CO2) concentrations in lakes vary strongly over time. This variability is rarely captured by environmental monitoring but is crucial for accurately assessing the magnitude of lake CO2 emissions. However, it is unknown to what extent temporal variability needs to be captured to understand important drivers of lake carbon cycling such as climate and land management. We used environmental monitoring data of Swedish forest lakes collected in autumn (n = 439) and throughout the whole open water season (n = 22) from a wet and a dry year to assess temporal variability in effects of climate and forestry on CO2 concentrations across lakes. Effects differed depending on the season and year sampled. According to cross-lake comparisons based on autumn data, CO2 concentrations increased with annual mean air temperature (dry year) or catchment forest productivity (wet year) but were not related to colored dissolved organic matter concentrations. In contrast, open water-season averaged CO2 concentrations were similar across temperature and productivity gradients but increased with colored dissolved organic matter. These contradictions resulted from scale mismatches in input data, lead to weak explanatory power (R2 = 9–32%), and were consistent across published data from 79 temperate, boreal, and arctic lakes. In a global survey of 144 published studies, we identified a trade-off between temporal and spatial coverage of CO2 sampling. This trade-off clearly determines which conclusions are drawn from landscape-scale CO2 assessments. Accurate evaluations of the effects of climate and land management require spatially and temporally representative data that can be provided by emerging sensor technologies and forms of collaborative sampling.
@article{klaus_evaluations_2019,
title = {Evaluations of {Climate} and {Land} {Management} {Effects} on {Lake} {Carbon} {Cycling} {Need} to {Account} for {Temporal} {Variability} in {CO2} {Concentrations}},
volume = {33},
copyright = {©2019. American Geophysical Union. All Rights Reserved.},
issn = {1944-9224},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2018GB005979},
doi = {10.1029/2018GB005979},
abstract = {Carbon dioxide (CO2) concentrations in lakes vary strongly over time. This variability is rarely captured by environmental monitoring but is crucial for accurately assessing the magnitude of lake CO2 emissions. However, it is unknown to what extent temporal variability needs to be captured to understand important drivers of lake carbon cycling such as climate and land management. We used environmental monitoring data of Swedish forest lakes collected in autumn (n = 439) and throughout the whole open water season (n = 22) from a wet and a dry year to assess temporal variability in effects of climate and forestry on CO2 concentrations across lakes. Effects differed depending on the season and year sampled. According to cross-lake comparisons based on autumn data, CO2 concentrations increased with annual mean air temperature (dry year) or catchment forest productivity (wet year) but were not related to colored dissolved organic matter concentrations. In contrast, open water-season averaged CO2 concentrations were similar across temperature and productivity gradients but increased with colored dissolved organic matter. These contradictions resulted from scale mismatches in input data, lead to weak explanatory power (R2 = 9–32\%), and were consistent across published data from 79 temperate, boreal, and arctic lakes. In a global survey of 144 published studies, we identified a trade-off between temporal and spatial coverage of CO2 sampling. This trade-off clearly determines which conclusions are drawn from landscape-scale CO2 assessments. Accurate evaluations of the effects of climate and land management require spatially and temporally representative data that can be provided by emerging sensor technologies and forms of collaborative sampling.},
language = {en},
number = {3},
urldate = {2024-03-26},
journal = {Global Biogeochemical Cycles},
author = {Klaus, Marcus and Seekell, David A. and Lidberg, William and Karlsson, Jan},
year = {2019},
note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2018GB005979},
keywords = {\#nosource, carbon cycling, greenhouse gas, lake, sampling, seasonality, structural equation modeling},
pages = {243--265},
}
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However, it is unknown to what extent temporal variability needs to be captured to understand important drivers of lake carbon cycling such as climate and land management. We used environmental monitoring data of Swedish forest lakes collected in autumn (n = 439) and throughout the whole open water season (n = 22) from a wet and a dry year to assess temporal variability in effects of climate and forestry on CO2 concentrations across lakes. Effects differed depending on the season and year sampled. According to cross-lake comparisons based on autumn data, CO2 concentrations increased with annual mean air temperature (dry year) or catchment forest productivity (wet year) but were not related to colored dissolved organic matter concentrations. In contrast, open water-season averaged CO2 concentrations were similar across temperature and productivity gradients but increased with colored dissolved organic matter. These contradictions resulted from scale mismatches in input data, lead to weak explanatory power (R2 = 9–32%), and were consistent across published data from 79 temperate, boreal, and arctic lakes. In a global survey of 144 published studies, we identified a trade-off between temporal and spatial coverage of CO2 sampling. This trade-off clearly determines which conclusions are drawn from landscape-scale CO2 assessments. 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