Elsevier

Global and Planetary Change

Volume 53, Issue 3, September 2006, Pages 169-175
Global and Planetary Change

Power laws governing hydrology and carbon dynamics in northern peatlands

https://doi.org/10.1016/j.gloplacha.2006.03.013Get rights and content

Abstract

Environmental and biological variables fluctuate over different time scales. On the basis of power spectral analysis of 14 time series at four sites from northern peatlands (fens and raised bogs), the temporal variability of physical environment (temperatures, water tables) and biological variables (CO2 flux) shows power-law behaviour, with a scaling exponent ranging from about 0.5 to 1.5. The scaling exponents of air temperatures change from 1.5 at high frequency to 0.5 at low frequency, with a break point at diurnal period. Comparison with similar analysis of temperature data from climate stations suggests that the atmosphere above peatlands has more active heat exchange with waterlogged peatlands than with upland terrestrial ecosystems. Water tables from different peatlands show almost identical power spectra, with a scaling exponent of 1.0 over all time scales. CO2 exchange has more complex spectral structure, with two break points at daily and monthly periods. This spectral structure suggests scale-dependent influence of climatic and hydrological fluctuations on CO2 fluxes. CO2 flux responds to air temperature with a distinct diurnal spectral peak. These results indicate that time scales are important in discussing hydrology and carbon dynamics in peatlands, and that scaling up of short-term experimental results may be inadvisable. Further statistical analysis on drained and harvested peatlands would provide insights into understanding shift in peatland dynamics due to human disturbance.

Introduction

Environmental and ecological variables fluctuate over different time scales. To describe this variability and to understand the underlying mechanisms, we often need to separate “noise” from “signal”. After removing predictable signal components from time series such as secular trends and periodicities, the residual variability “can be considered as inherently unpredictable in a strictly deterministic sense” (Steele, 1985). However, the structure of environmental fluctuation is well described by a phenomenon called “1/f-noise”, and the understanding of this phenomenon would have important consequences for the interpretation of ecological time series and for ecological modelling (Halley, 1996).

Environmental fluctuations arise from various factors that may correlate on different time scales, so the noise cannot be assumed as “white noise” that has no temporal correlation. In a 1/f-noise model, the correlation of fluctuations falls off as a power law. The 1/f-noise was so named because of the shape of its spectral density, which is characterised by power-law spectra of the form: S(f)  1/fβ, where 0  β  2 (β = 0: white noise/flat spectra; β = 1: pink noise; β = 2: brown noise (Brownian motion/random walk)). The 1/f-spectra have been associated with some ecological and geophysical time series (e.g., Mandelbrot and Wallis, 1969, Steele, 1985, Pimm and Redfearn, 1988, Rhodes and Anderson, 1996, Pelletier and Turcotte, 1997, Pelletier, 1998, Keitt and Stanley, 1988). Temporal variation of the physical environment usually has a reddened spectrum, which means that the amplitude of low frequency in a spectral analysis is consistently greater than that of high frequency and variability appears to increase at the longer time scales. In practice, the spectrum yields an approximately straight-line relationship between log variance and log frequency. Comparison of power-spectral structure between environmental and biological time series would help in understanding the causal mechanisms of ecological changes, such as population fluctuation. If both time series show reddened spectra, changing physical processes may have driven populations (climatic school of population regulation) (Sugihara, 1995). In contrast, different biological fluctuation patterns may suggest independent behaviour or self-regulation of dynamics.

Peatlands are important land surface feature of the globe, and understanding feedback mechanisms of their components is crucial in the study of the global carbon cycle. Northern peatlands have accumulated up to 450 Gt of carbon over the last 12,000 years (e.g., Clymo et al., 1998). Their large C pool raises concerns that peatlands may become significant sources for atmospheric C under a changing climate. However, significant uncertainties exist in addressing the environmental controls of C dynamics and peatlands sensitivity to environmental change. The credible assessment of C sink–source relationships would need to consider processes operating over short and long time scales (Yu et al., 2003, Bauer, 2004).

Numerous studies have been carried out in recent years on environmental controls of carbon fluxes in peatland ecosystems. Most of these studies are trying to find correlative relations statistically or visually between CO2/CH4 and environmental measurements (Moore and Knowles, 1989, Moore and Roulet, 1993, Suyker et al., 1997, Lafleur et al., 1997, Lafleur, 1999, Joiner et al., 1999, Carroll and Crill, 1997, Silvola et al., 1996; among others). Here I explore the differences and similarities of temporal variability in physical environment (temperatures, water tables) and biological variables (CO2 fluxes) from four northern peatlands. Spectral analysis was used to derive the scaling exponents of time series and to understand the underlying fundamental dynamics of these systems. The comparison of physical and biological variability would provide some insights into the environmental controls of carbon dynamics over short time scale (1 h to 1 year). I find that many of these time series have scaling exponents of between 0.5 and 1.5. These 1/f-power spectra suggest that variations of these variables correlate with each other through time.

Section snippets

Peatland data

The data sets (Fig. 1) are from peatlands in central Alberta (Wolf Creek fen), central Saskatchewan (BOREAS Southern Study Area (SSA) fen), northern Manitoba (BOREAS NSA fen) and southwest Scotland (Ellergower Moss raised bog). The Wolf Creek site (lat. 53°25′N, long. 116°03′W; elevation 950 m asl) is a treed fen and is one of several peatland sites for peatland drainage and forestry experiments (Hillman, 1997). It is in a subhumid continental climate. The mean annual temperature from nearby

Power spectral analysis

There are several methods in analysing the dynamic behaviours of time series, including power spectral analysis, rescaled-range analysis and autocorrelation analysis (Schepers et al., 1992). It has been found that the power spectral analysis is better than other methods because it yields the least biased results (Schepers et al., 1992, Pelletier and Turcotte, 1997). The power spectral analysis was carried out using the periodogram method in the computer program AnalySeries (Paillard et al., 1996

Power-law behaviour of peatland time series and its interpretation

The results from spectral analysis of peatland time series show power-law behaviour of peatland hydrology and carbon dynamics. They all show that log (frequency) vs. log (power spectra) plots have a non-flat spectrum with scaling exponents of between 0.5 and 1.5. The spectral structure of air temperatures from four data sets has scaling exponents of ∼ 1.5 at high frequency but of ∼ 0.5 at lower frequency (Fig. 3A). It has a breaking point at 24 h, which show a diurnal temperature cycle. The water

Implication for peatland dynamics

A key feature of peatland ecosystems is their long-term accumulation of peat at slow rates over millennia, in addition to their short-term C flux dynamics. As a result, integration and interactions of these diverse processes at various time scales are an important issue in peatland C dynamics studies (e.g., Bauer, 2004). The analysis results from this paper indicate that time scales are important in discussing hydrology and carbon dynamics in northern peatlands. Possible self-regulation of

Acknowledgments

I thank R.S. Clymo, G.R. Hillman, P.M. Lafleur and A.E. Suyker for making the peatland data available; M.J. Apps, I.D. Campbell, G.R. Hillman, E.D. Hogg, P.M. Lafleur, D.T. Price, N.T. Roulet and D.H. Vitt for discussion; and two anonymous reviewers for helpful comments and suggestions. This work was supported by the Climate Change Action Fund of Canada and U.S. National Science Foundation.

References (31)

  • G.R. Hillman

    Effects of engineered drainage on water tables and peat subsidence in an Alberta treed fen

  • H.A.P. Ingram

    Size and shape in raised mire ecosystems: a geophysical model

    Nature

    (1982)
  • D.W. Joiner et al.

    Interannual variability in carbon dioxide exchanges at a boreal wetland in the BOREAS northern study area

    Journal of Geophysical Research

    (1999)
  • T.H. Keitt et al.

    Dynamics of North American breeding bird populations

    Nature

    (1988)
  • P.M. Lafleur et al.

    Seasonal trends in energy, water, and carbon dioxide fluxes at a northern boreal wetland

    Journal of Geophysical Research

    (1997)
  • Cited by (0)

    View full text