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Peatland net ecosystem production is a key variable to assess changes in the functional role of peatlands in the global carbon cycle. Light use efficiency (LUE) models in combination with satellite data have been used to estimate production for most major ecosystems, but peatlands have been largely ignored. The objectives of this study were: 1) to examine how the LUE parameter epsilon, ε (the amount of carbon fixed or converted to biomass per unit absorbed photosynthetically active radiation), varies between and within four different peatlands; 2) to examine how the variations in ε relate to variations in environmental conditions; and 3) to evaluate a LUE-based model for estimation of ε in peatlands. We achieve these objectives using a combination of eddy covariance flux measurements, climate data and satellite data and estimate ε using the LUE-based vegetation photosynthesis model (VPM). The results show that: 1) mean site-specific flux-derived ε values (± standard deviation) were split into three statistically different groups: lowest values at the two colder fens, Kaamanen and Sandhill (0.22 ± 0.18 and 0.23 ± 0.20 g C MJ − 1 , respectively), highest values at the treed fen La Biche (0.47 ± 0.27 g C MJ − 1 ) and intermediate values at the bog, Mer Bleue (0.34 ± 0.18 g C MJ − 1 ); 2) Variations in monthly ε within sites related mainly to air temperature, while variations in annual ε within sites related mainly to wetness variables; 3) relative mean absolute errors of estimates of ε for the four sites ranged between 19% and 35%, with r 2 values ranging between 72% and 93%. LUE models are appealing as they are relatively simple formulations of variables that are easily obtained from satellite data. Challenges associated with the use of satellite data derived input variables are further discussed in the paper. [ABSTRACT FROM AUTHOR]

Abstract: Northern hemisphere peatlands play an important role in the global carbon (C) cycle, accounting for about 30% of global soil C and ~10–25% of global natural methane (CH4) emissions. Satellite remote sensing has the potential for extracting continuous information related to C exchange rates at regional and global extents, yet, few studies have focused on peatlands. In this study we examined the potential of moderate resolution imaging spectroradiometer (MODIS) vegetation indices (normalized difference vegetation index, NDVI and simple ratio, SR), MODIS light use efficiency (LUE) based gross primary production (GPP) and a MODIS derived phenological index (annual peak photosynthetic rate) for the estimation of eddy covariance (EC) flux-derived GPP and net ecosystem production (NEP) at four contrasting northern peatlands. At the four sites of this study MODIS NDVI and SR explained between 39% and 71%, and between 42% and 69% of the variation in EC-derived GPP, respectively; and between 25% and 53%, and between 29% and 39% of the variation in EC-derived NEP, respectively. The relationships were mostly consistent across sites and within sites, suggesting that data may be pooled across years and sites, which could simplify the prediction of gross and net C dioxide (CO2) uptake over large areas dominated by northern peatlands based on MODIS data. MODIS GPP explained between 68% and 89% of the variation in EC-derived GPP at the four study sites. The root mean square errors ranged between 0.62 and 1.16gCm−2 d−1 and were similar to errors from ecosystem process model estimates reported in the literature. Annual peak MODIS GPP, NDVI and SR rates explained up to 50% of the variations in annual cumulative EC-derived GPP and NEP at two of the study sites. Our results show the potentials and limitations of MODIS data to monitor the C dynamics of northern peatlands; among the three studied approaches the MODIS LUE-based GPP approach showed better performance as a predictor of GPP and NEP. The other approaches (VIs and phenology) can provide important input data for LUE models. [Copyright &y& Elsevier]