@article{WeithoffRochaGaedke2015,
  author    = {Weithoff, Guntram and Rocha, Marcia R. and Gaedke, Ursula},
  title     = {Comparing seasonal dynamics of functional and taxonomic diversity reveals the driving forces underlying phytoplankton community structure},
  series = {Freshwater biology},
  volume    = {60},
  journal   = {Freshwater biology},
  number    = {4},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {0046-5070},
  doi       = {10.1111/fwb.12527},
  pages     = {758 -- 767},
  year      = {2015},
  abstract  = {In most biodiversity studies, taxonomic diversity is the measure for the multiplicity of species and is often considered to represent functional diversity. However, trends in taxonomic diversity and functional diversity may differ, for example, when many functionally similar but taxonomically different species co-occur in a community. The differences between these diversity measures are of particular interest in diversity research for understanding diversity patterns and their underlying mechanisms. We analysed a temporally highly resolved 20-year time series of lake phytoplankton to determine whether taxonomic diversity and functional diversity exhibit similar or contrasting seasonal patterns. We also calculated the functional mean of the community in n-dimensional trait space for each sampling day to gain further insights into the seasonal dynamics of the functional properties of the community. We found an overall weak positive relationship between taxonomic diversity and functional diversity with a distinct seasonal pattern. The two diversity measures showed synchronous behaviour from early spring to mid-summer and a more complex and diverging relationship from autumn to late winter. The functional mean of the community exhibited a recurrent annual pattern with the most prominent changes before and after the clear-water phase. From late autumn to winter, the functional mean of the community and functional diversity were relatively constant while taxonomic diversity declined, suggesting competitive exclusion during this period. A further decline in taxonomic diversity concomitant with increasing functional diversity in late winter to early spring is seen as a result of niche diversification together with competitive exclusion. Under these conditions, several different sets of traits are suitable to thrive, but within one set of functional traits only one, or very few, morphotypes can persist. Taxonomic diversity alone is a weak descriptor of trait diversity in phytoplankton. However, the combined analysis of taxonomic diversity and functional diversity, along with the functional mean of the community, allows for deeper insights into temporal patterns of community assembly and niche diversification.},
  language  = {en}
}
@article{RungeGrosse2019,
  author    = {Runge, Alexandra and Grosse, Guido},
  title     = {Comparing Spectral Characteristics of Landsat-8 and Sentinel-2 Same-Day Data for Arctic-Boreal Regions},
  series = {Remote Sensing},
  volume    = {11},
  journal   = {Remote Sensing},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2072-4292},
  doi       = {10.3390/rs11141730},
  pages     = {29},
  year      = {2019},
  abstract  = {The Arctic-Boreal regions experience strong changes of air temperature and precipitation regimes, which affect the thermal state of the permafrost. This results in widespread permafrost-thaw disturbances, some unfolding slowly and over long periods, others occurring rapidly and abruptly. Despite optical remote sensing offering a variety of techniques to assess and monitor landscape changes, a persistent cloud cover decreases the amount of usable images considerably. However, combining data from multiple platforms promises to increase the number of images drastically. We therefore assess the comparability of Landsat-8 and Sentinel-2 imagery and the possibility to use both Landsat and Sentinel-2 images together in time series analyses, achieving a temporally-dense data coverage in Arctic-Boreal regions. We determined overlapping same-day acquisitions of Landsat-8 and Sentinel-2 images for three representative study sites in Eastern Siberia. We then compared the Landsat-8 and Sentinel-2 pixel-pairs, downscaled to 60 m, of corresponding bands and derived the ordinary least squares regression for every band combination. The acquired coefficients were used for spectral bandpass adjustment between the two sensors. The spectral band comparisons showed an overall good fit between Landsat-8 and Sentinel-2 images already. The ordinary least squares regression analyses underline the generally good spectral fit with intercept values between 0.0031 and 0.056 and slope values between 0.531 and 0.877. A spectral comparison after spectral bandpass adjustment of Sentinel-2 values to Landsat-8 shows a nearly perfect alignment between the same-day images. The spectral band adjustment succeeds in adjusting Sentinel-2 spectral values to Landsat-8 very well in Eastern Siberian Arctic-Boreal landscapes. After spectral adjustment, Landsat and Sentinel-2 data can be used to create temporally-dense time series and be applied to assess permafrost landscape changes in Eastern Siberia. Remaining differences between the sensors can be attributed to several factors including heterogeneous terrain, poor cloud and cloud shadow masking, and mixed pixels.},
  language  = {en}
}
@article{RungeNitzeGrosse2021,
  author    = {Runge, Alexandra and Nitze, Ingmar and Grosse, Guido},
  title     = {Remote sensing annual dynamics of rapid permafrost thaw disturbances with LandTrendr},
  series = {Remote sensing of environment : an interdisciplinary journal},
  volume    = {268},
  journal   = {Remote sensing of environment : an interdisciplinary journal},
  publisher = {Elsevier},
  address   = {New York},
  issn      = {0034-4257},
  doi       = {10.1016/j.rse.2021.112752},
  pages     = {18},
  year      = {2021},
  abstract  = {Permafrost is warming globally which leads to widespread permafrost thaw. Particularly ice-rich permafrost is vulnerable to rapid thaw and erosion, impacting whole landscapes and ecosystems. Retrogressive thaw slumps (RTS) are abrupt permafrost disturbances that expand by several meters each year and lead to an increased soil organic carbon release. Local Remote Sensing studies identified increasing RTS activity in the last two decades by increasing number of RTS or heightened RTS growth rates. However, a large-scale assessment across diverse permafrost regions and at high temporal resolution allowing to further determine RTS thaw dynamics and its main drivers is still lacking. In this study we apply the disturbance detection algorithm LandTrendr for automated large-scale RTS mapping and high temporal thaw dynamic assessment to North Siberia (8.1 x 106km2). We adapted and parametrised the temporal segmentation algorithm for abrupt disturbance detection to incorporate Landsat+Sentinel-2 mosaics, conducted spectral filtering, spatial masking and filtering, and a binary machine-learning object classification of the disturbance output to separate between RTS and false positives (F1 score: 0.609). Ground truth data for calibration and validation of the workflow was collected from 9 known RTS cluster sites using very highresolution RapidEye and PlanetScope imagery. Our study presents the first automated detection and assessment of RTS and their temporal dynamics at largescale for 2001-2019. We identified 50,895 RTS and a steady increase in RTS-affected area from 2001 to 2019 across North Siberia, with a more abrupt increase from 2016 onward. Overall the RTS-affected area increased by 331\% compared to 2000 (2000: 20,158 ha, 2001-2019: 66,699 ha). Contrary to this, 5 focus sites show spatiotemporal variability in their annual RTS dynamics, with alternating periods of increased and decreased RTS development, indicating a close relationship to thaw drivers. The majority of identified RTS was active from 2000 onward and only a small proportion initiated during the assessment period, indicating that the increase in RTS-affected area was mainly caused by enlarging existing RTS and not by new RTS. The detected increase in RTS dynamics suggests advancing permafrost thaw and underlines the importance of assessing abrupt permafrost disturbances with high spatial and temporal resolution at large-scales. Obtaining such consistent disturbance products will help to parametrise regional and global climate change models.},
  language  = {en}
}