@article{SchmidtGertenHintzeetal.2018,
  author    = {Schmidt, Silke Regina and Gerten, Dieter and Hintze, Thomas and Lischeid, Gunnar and Livingstone, David M. and Adrian, Rita},
  title     = {Temporal and spatial scales of water temperature variability as an indicator for mixing in a polymictic lake},
  series = {Inland waters : journal of the International Society of Limnology},
  volume    = {8},
  journal   = {Inland waters : journal of the International Society of Limnology},
  number    = {1},
  publisher = {Routledge, Taylor \& Francis Group},
  address   = {Abingdon},
  issn      = {2044-2041},
  doi       = {10.1080/20442041.2018.1429067},
  pages     = {82 -- 95},
  year      = {2018},
  abstract  = {We applied coarse spectral analysis to more than 2 decades of daily near-surface water temperature (WT) measurements from Muggelsee, a shallow polymictic lake in Germany, to systematically characterize patterns in WT variability from daily to yearly temporal scales. Comparison of WT with local air temperature indicates that the WT variability patterns are likely attributable to both meteorological forcing and internal lake dynamics. We identified seasonal patterns of WT variability and showed that WT variability increases with increasing Schmidt stability, decreasing Lake number and decreasing ice cover duration, and is higher near the shore than in open water. We introduced the slope of WT spectra as an indicator for the degree of lake mixing to help explain the identified temporal and spatial scales of WT variability. The explanatory power of this indicator in other lakes with different mixing regimes remains to be established.},
  language  = {en}
}
@article{SchmidtLischeidHintzeetal.2018,
  author    = {Schmidt, Silke Regina and Lischeid, Gunnar and Hintze, Thomas and Adrian, Rita},
  title     = {Disentangling limnological processes in the time-frequency domain},
  series = {Limnology and oceanography},
  volume    = {64},
  journal   = {Limnology and oceanography},
  number    = {2},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {0024-3590},
  doi       = {10.1002/lno.11049},
  pages     = {423 -- 440},
  year      = {2018},
  abstract  = {State variables in lake ecosystems are subject to processes that act on different time scales. The relative importance of each of these processes changes over time, e.g., due to varying constraints of physical, biological, and biogeochemical processes. Correspondingly, continuous automatic measurements at high temporal resolution often reveal intriguing patterns that can rarely be directly ascribed to single processes. In light of the rather complex interplay of such processes, disentangling them requires more powerful methods than researchers have applied up to this point. For this reason, we tested the potential of wavelet coherence, based on the assumption that different processes result in correlations between different variables, on different time scales and during different time windows across the seasons. The approach was tested on a set of multivariate hourly data measured between the onset of an ice cover and a cyanobacterial summer bloom in the year 2009 in the Muggelsee, a polymictic eutrophic lake. We found that processes such as photosynthesis and respiration, the growth and decay of phytoplankton biomass, dynamics in the CO2-carbonate system, wind-induced resuspension of particles, and vertical mixing all occasionally served as dominant drivers of the variability in our data. We therefore conclude that high-resolution data and a method capable of analyzing time series in both the time and the frequency domain can help to enhance our understanding of the time scales and processes responsible for the high variability in driver variables and response variables, which in turn can lay the ground for mechanistic analyses.},
  language  = {en}
}