Disentangling limnological processes in the time‐frequency domain

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 Müggelsee, 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.

Subarctic catchment water storage and carbon cycling – Leading the way for future studies using integrated datasets at Pallas, Finland

“…The high‐frequency in‐stream monitoring efforts at the Pallas catchment enable the use of new methods of data analysis such as wavelet transform (Crawford et al, 2017; Riml et al, 2019; Schmidt et al, 2019), which can improve knowledge of carbon sources and related hydrological connectivity in subarctic catchments (Figure 4(b)–(d)). For example, Figure 4(b) shows the development of diurnal periodicity in TOC dynamics after snowmelt begins, which likely reflects the onset of increased microbial activity and greater in‐stream processing of TOC as stream temperatures become warmer.…”

“…The high-frequency in-stream monitoring efforts at the Pallas catchment enable the use of new methods of data analysis such as wavelet transform (Crawford et al, 2017;Riml et al, 2019;Schmidt et al, 2019), which can improve knowledge of carbon sources and related hydrological connectivity in subarctic catchments (Figure 4 . This relationship between discharge and TOC suggests that discharge and TOC increase concurrently in snowmelt season at longer-term periodicities, thereby indicating that the process which increases flow across this timescale may be linked to the process which increases TOC.…”

“…The snowy and rainy seasons are based on a rain-snow threshold temperature of 1 C(Jennings et al, 2018).We used peat and streamwater CH 4 concentration and eddy covariance measurements at Lompolojänkkä mire to examine the role of hydrological processes on biogeochemistry in subarctic conditions during the spring freshet. We assessed dominant in-stream carbon processes using fdom (a surrogate for TOC, measured in 15 min intervals) datasets and wavelet analysis(Crawford et al, 2017;Riml et al, 2019;Schmidt et al, 2019). Wavelet transform is a form of spectral decomposition that transforms time-series into timedependent spectral series.…”

Spectral Decomposition Reveals New Perspectives on CO2Concentration Patterns and Soil‐Stream Linkages

“…Conventional approaches to resolving aquatic transport problems are based on assessments of hydrochemical observations in the time domain. However, novel approaches transforming the problem into the frequency domain have emerged, allowing to analyze temporal patterns (Crawford et al, 2017;Kirchner & Neal, 2013;Schmidt et al, 2018;Weigand et al, 2017;Yan et al, 2017) and provide quantitative estimates of transport rates (Godsey et al, 2010;Guan et al, 2011;Riml & Wörman, 2015) as functions of the inherent time scales of the observed dynamics. The Fourier representation is a way to complement time domain analyses that unlocks new possibilities to utilize high-frequency hydrochemical observations.…”

Climate Change‐Legacy Phosphorus Synergy Hinders Lake Response to Aggressive Water Policy Targets

“…However, while increasing water temperatures and riverine inputs due to climate change have been frequently observed (e.g., Isles et al., 2017 for Lake Champlain), and the mechanisms for climate change synergistically interacting with legacy nutrient reserves are well‐established (e.g., Nazarai‐Sharabian et al., 2018; Orihel et al., 2017), we are not aware of observational studies that have conclusively demonstrated such an effect over time. This is partly because it can be difficult to disentangle internal versus external drivers of change in highly dynamic shallow lake systems (Schmidt et al., 2019).…”