| 1. |
- Kross, Angela, et al.
(author)
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Estimating carbon dioxide exchange rates at contrasting northern peatlands using MODIS satellite data
- 2013
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In: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257. ; 137, s. 234-243
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Journal article (peer-reviewed)abstract
- Northern hemisphere peatlands play an important role in the global carbon (C) cycle, accounting for about 30% of global soil C and similar to 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 1.16 g C m(-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. (c) 2013 Elsevier Inc. All rights reserved.
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| 2. |
- Kross, Angela, et al.
(author)
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Light use efficiency of peatlands: Variability and suitability for modeling ecosystem production
- 2016
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In: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257. ; 183, s. 239-249
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Journal article (peer-reviewed)abstract
- 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 r2 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.
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| 3. |
- Kross, Angela S. E., et al.
(author)
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Phenology and its role in carbon dioxide exchange processes in northern peatlands
- 2014
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In: Journal of Geophysical Research - Biogeosciences. - 2169-8953. ; 119:7, s. 1370-1384
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Journal article (peer-reviewed)abstract
- Ecosystem phenology plays an important role in carbon exchange processes and can be derived from continuous records of carbon dioxide (CO2) exchange data. In this study we examined the potential use of phenological indices for characterizing cumulative annual CO2 exchange in four contrasting northern peatland ecosystems. We used the approach of Jonsson and Eklundh (2004) to derive a set of phenological indices based on the daily time series of gross primary production (GPP), ecosystem respiration (R-e), and net ecosystem production (NEP) measured in the four peatland sites. The main objectives of this study were (a) to examine the variation in phenological indices across sites and (b) to determine the relationships among phenological indices, environmental conditions, and cumulative annual CO2 exchange. The phenological index used to define the "start of the growing season" showed good potential for differentiation among sites based on their average annual site GPP. Sites with earlier growing seasons had the highest average annual site GPP. The "peak CO2 exchange rate" phenological index performed best in reflecting variations among sites and for estimating annual values of GPP, R-e, and NEP (Pearson correlation coefficients ranged between 0.77 and 0.99, p<0.05 for all.). The phenological indices and annual GPP, R-e, and NEP were sensitive to winter (January-March) and summer (July-September) temperature and precipitation, but correlations, though significant, were weak.
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| 4. |
- Kross, Angela, et al.
(author)
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The effect of the temporal resolution of NDVI data on season onset dates and trends across Canadian broadleaf forests
- 2011
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In: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257. ; 115:6, s. 1564-1575
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Journal article (peer-reviewed)abstract
- Satellite remote sensing has the potential to contribute to plant phenology monitoring at spatial and temporal scales relevant for regional and global scale studies. Historically, temporal composites of satellite data, ranging from 8 days to 16 days, have been used as a starting point for satellite-derived phenology data sets. In this study we assess how the temporal resolution of such composites affects the estimation of the start of season (SOS) by: 1) calibrating a relationship between satellite derived SOS with in situ leaf unfolding (LU) of trembling aspen (Populus tremuloides) across Canada and 2) quantifying the sensitivity of calibrated satellite SOS estimates and trends, over Canadian broadleaf forests, to the temporal resolution of NDVI data. SOS estimates and trends derived from daily NDVI data were compared to SOS estimates and trends derived from multiday NDVI composites that retain the exact date of the maximum NDVI value or that assume the midpoint of the multiday interval as the observation date. In situ observations of LU dates were acquired from the PlantWatch Canada network. A new Canadian database of cloud and snow screened daily 1-km resolution National Oceanic and Atmospheric Administration advanced very high resolution radiometer surface reflectance images was used as input satellite data. The mean absolute errors of SOS dates with respect to in situ LU dates ranged between 13 and 40 days. SOS estimates from NDVI composites that retain the exact date of the maximum NDVI value had smaller errors (similar to 13 to 20 days). The sensitivity analysis reinforced these findings: SOS estimates from NDVI composites that use the exact date had smaller absolute deviations from the LU date (0 to 5 days) than the SOS estimates from NDVI composites that use the midpoint (-2 to -27 days). The SOS trends between 1985 and 2007 were not sensitive to the temporal resolution or compositing methods. However, SOS trends at individual ecozones showed significant differences with the SOS trends from daily NDVI data (Taiga plains and the Pacific maritime zones). Overall, our results suggest that satellite based estimates of vegetation green-up dates should preferably use sub-sampled NDVI composites that include the exact observation date of the maximum NDVI to minimize errors in both. SOS estimates and SOS trend analyses. For trend analyses alone, any of the compositing methods could be used, preferably with composite intervals of less than 28 days. This is an important finding, as it suggests that existing long-term 10-day or 15-day NDVI composites could be used for SOS trend analyses over broadleaf forests in Canada or similar areas. Future studies will take advantage of the growing in situ phenology networks to improve the validation of satellite derived green-up dates. (C) 2011 Elsevier Inc. All rights reserved.
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