Cryoconite holes, which can cover 0.1-10% of the surface area of glaciers, are small, water-filled depressions (typically o1 m in diameter and usually o0.5 m deep) that form on the surface of glaciers when solar-heated inorganic and organic debris melts into the ice. Recent studies show that cryoconites are colonized by a diverse range of microorganisms, including viruses, bacteria and algae. Whether microbial communities on the surface of glaciers are actively influencing biogeochemical cycles or are just present in a dormant state has been a matter of debate for long time. Here, we report primary production and community respiration of cryoconite holes upon glaciers in Svalbard, Greenland and the European Alps. Microbial activity in cryoconite holes is high despite maximum temperatures seldom exceeding 0.1 1C. In situ primary production and respiration in cryoconites during the summer is often comparable with that found in soils in warmer and nutrient richer regions. Considering only glacier areas outside Antarctica and a conservative average cryoconite distribution on glacial surfaces, we found that on a global basis cryoconite holes have the potential to fix as much as 64 Gg of carbon per year (i.e. 98 Gg of photosynthesis minus 34 Gg of community respiration). Most lakes and rivers are generally considered as heterotrophic systems, but our results suggest that glaciers, which contain 75% of the freshwater of the planet, are largely autotrophic systems.

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ABSTRACT:In both ecology and forestry, there is a high demand for structural information of forest stands. Forest structures, due to their heterogeneity and density, are often difficult to assess. Hence, a variety of technologies are being applied to account for this "difficult to come by" information. Common techniques are aerial images or ground-and airborne-Lidar. In the present study we evaluate the potential use of unmanned aerial vehicles (UAVs) as a platform for tree stem detection in open stands. A flight campaign over a test site near Freiburg, Germany covering a target area of 120 × 75[m 2 ] was conducted. The dominant tree species of the site is oak (quercus robur) with almost no understory growth. Over 1000 images with a tilt angle of 45°were shot. The flight pattern applied consisted of two antipodal staggered flight routes at a height of 55[m] above the ground. We used a Panasonic G3 consumer camera equipped with a 14 − 42[mm] standard lens and a 16.6 megapixel sensor. The data collection took place in leaf-off state in April 2013. The area was prepared with artificial ground control points for transformation of the structure-from-motion (SFM) point cloud into real world coordinates. After processing, the results were compared with a terrestrial laser scanner (TLS) point cloud of the same area. In the 0.9[ha] test area, 102 individual trees above 7[cm] diameter at breast height were located on in the TLS-cloud. We chose the software CMVS/PMVS-2 since its algorithms are developed with focus on dense reconstruction. The processing chain for the UAV-acquired images consists of six steps: a. cleaning the data: removing of blurry, under-or over exposed and off-site images; b. applying the SIFT operator [Lowe, 2004]; c. image matching; d. bundle adjustment; e. clustering; and f. dense reconstruction. In total, 73 stems were considered as reconstructed and located within one meter of the reference trees. In general stems were far less accurate and complete as in the TLS-point cloud. Only few stems were considered to be fully reconstructed. From the comparison of reconstruction achievement with respect to height above ground, we can state that reconstruction accuracy decreased in the crown layer of the stand. In addition we were cutting 50[cm] slices in z-direction and applied a robust cylinder fit to the stem slices. Radii of the TLS-cloud and the SFM-cloud surprisingly correlated well with a Pearson's correlation coefficient of r = 0.696. This first study showed promising results for UAV-based forest structure modelling. Yet, there is a demand for additional research with regard to vegetation stages, flight pattern, processing setup and the utilisation of spectral information.

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