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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]

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 8days to 16days, 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 40days. SOS estimates from NDVI composites that retain the exact date of the maximum NDVI value had smaller errors (~13 to 20days). 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 −5days) than the SOS estimates from NDVI composites that use the midpoint (−2 to −27days). 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 28days. 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. [Copyright &y& Elsevier]

Abstract: Semi-arid areas, defined as those areas of the world where water is an important limitation for plant growth, have become the subject of increased interest due to the impacts of current global changes and sustainability of human lifestyles. While many ground-based reports of declining vegetation productivity have been published over the last decades, a number of recent publications have shown a nuanced and, for some regions, positive picture. With this background, the paper provides an analysis of trends in vegetation greenness of semi-arid areas using AVHRR GIMMS from 1981 to 2007. The vegetation index dataset is used as a proxy for vegetation productivity and trends are analyzed for characterization of changes in semi-arid vegetation greenness. Calculated vegetation trends are analyzed with gridded data on potential climatic constraints to plant growth to explore possible causes of the observed changes. An analysis of changes in the seasonal variation of vegetation greenness and climatic drivers is conducted for selected regions to further understand the causes of observed inter-annual vegetation changes in semi-arid areas across the globe. It is concluded that semi-arid areas, across the globe, on average experience an increase in greenness (0.015 NDVI units over the period of analysis). Further it is observed that increases in greenness are found both in semi-arid areas where precipitation is the dominating limiting factor for plant production (0.019 NDVI units) and in semi-arid areas where air temperature is the primarily growth constraint (0.013 NDVI units). Finally, in the analysis of changes in the intra-annual variation of greenness it is found that seemingly similar increases in greenness over the study period may have widely different explanations. This implies that current generalizations, claiming that land degradation is ongoing in semi-arid areas worldwide, are not supported by the satellite based analysis of vegetation greenness. [Copyright &y& Elsevier]