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High-latitude treeless ecosystems represent spatially highly heterogeneous landscapes with small net carbon fluxes and a short growing season. Reliable observations and process understanding are critical for projections of the carbon balance of the climate-sensitive tundra. Space-borne remote sensing is the only tool to obtain spatially continuous and temporally resolved information on vegetation greenness and activity in remote circumpolar areas. However, confounding effects from persistent clouds, low sun elevation angles, numerous lakes, widespread surface inundation, and the sparseness of the vegetation render it highly challenging. Here, we conduct an extensive analysis of the timing of peak vegetation productivity as shown by satellite observations of complementary indicators of plant greenness and photosynthesis. We choose to focus on productivity during the peak of the growing season, as it importantly affects the total annual carbon uptake. The suite of indicators are as follows: (1) MODIS-based vegetation indices (VIs) as proxies for the fraction of incident photosynthetically active radiation (PAR) that is absorbed (fPAR), (2) VIs combined with estimates of PAR as a proxy of the total absorbed radiation (APAR), (3) sun-induced chlorophyll fluorescence (SIF) serving as a proxy for photosynthesis, (4) vegetation optical depth (VOD), indicative of total water content and (5) empirically upscaled modelled gross primary productivity (GPP). Averaged over the pan-Arctic we find a clear order of the annual peak as APAR <= GPP < SIF < VIs/VOD. SIF as an indicator of photosynthesis is maximised around the time of highest annual temperatures. The modelled GPP peaks at a similar time to APAR. The time lag of the annual peak between APAR and instantaneous SIF fluxes indicates that the SIF data do contain information on light-use efficiency of tundra vegetation, but further detailed studies are necessary to verify this. Delayed peak greenness compared to peak photosynthesis is consistently found across years and land-cover classes. A particularly late peak of the normalised difference vegetation index (NDVI) in regions with very small seasonality in greenness and a high amount of lakes probably originates from artefacts. Given the very short growing season in circumpolar areas, the average time difference in maximum annual photosynthetic activity and greenness or growth of 3 to 25 days (depending on the data sets chosen) is important and needs to be considered when using satellite observations as drivers in vegetation models.
Sulfate deprivation triggers high methane production in a disturbed and rewetted coastal peatland
(2019)
In natural coastal wetlands, high supplies of marine sulfate suppress methanogenesis. Coastal wetlands are, however, often subject to disturbance by diking and drainage for agricultural use and can turn to potent methane sources when rewetted for remediation. This suggests that preceding land use measures can suspend the sulfate-related methane suppressing mechanisms. Here, we unravel the hydrological relocation and biogeochemical S and C transformation processes that induced high methane emissions in a disturbed and rewetted peatland despite former brackish impact. The underlying processes were investigated along a transect of increasing distance to the coastline using a combination of concentration patterns, stable isotope partitioning, and analysis of the microbial community structure. We found that diking and freshwater rewetting caused a distinct freshening and an efficient depletion of the brackish sulfate reservoir by dissimilatory sulfate reduction (DSR). Despite some legacy effects of brackish impact expressed as high amounts of sedimentary S and elevated electrical conductivities, contemporary metabolic processes operated mainly under sulfate-limited conditions. This opened up favorable conditions for the establishment of a prospering methanogenic community in the top 30-40 cm of peat, the structure and physiology of which resemble those of terrestrial organic-rich environments. Locally, high amounts of sulfate persisted in deeper peat layers through the inhibition of DSR, probably by competitive electron acceptors of terrestrial origin, for example Fe(III). However, as sulfate occurred only in peat layers below 30-40 cm, it did not interfere with high methane emissions on an ecosystem scale. Our results indicate that the climate effect of disturbed and remediated coastal wetlands cannot simply be derived by analogy with their natural counterparts. From a greenhouse gas perspective, the re-exposure of diked wetlands to natural coastal dynamics would literally open up the floodgates for a replenishment of the marine sulfate pool and therefore constitute an efficient measure to reduce methane emissions.
The Northeast German Lowland Observatory (TERENO-NE) was established to investigate the regional impact of climate and land use change. TERENO-NE focuses on the Northeast German lowlands, for which a high vulnerability has been determined due to increasing temperatures and decreasing amounts of precipitation projected for the coming decades. To facilitate in-depth evaluations of the effects of climate and land use changes and to separate the effects of natural and anthropogenic drivers in the region, six sites were chosen for comprehensive monitoring. In addition, at selected sites, geoarchives were used to substantially extend the instrumental records back in time. It is this combination of diverse disciplines working across different time scales that makes the observatory TERENO-NE a unique observation platform. We provide information about the general characteristics of the observatory and its six monitoring sites and present examples of interdisciplinary research activities at some of these sites. We also illustrate how monitoring improves process understanding, how remote sensing techniques are fine-tuned by the most comprehensive ground-truthing site DEMMIN, how soil erosion dynamics have evolved, how greenhouse gas monitoring of rewetted peatlands can reveal unexpected mechanisms, and how proxy data provides a long-term perspective of current ongoing changes.