@article{SteinDoeringArjesFladungetal.2016,
  author    = {Stein, F. and Doering-Arjes, P. and Fladung, Erik and Br{\"a}mick, Uwe and Bendall, B. and Schroeder, B.},
  title     = {Downstream Migration of the European Eel (Anguilla Anguilla) in the Elbe River, Germany: Movement Patterns and the Potential Impact of Environmental Factors},
  series = {River Research and Applications},
  volume    = {32},
  journal   = {River Research and Applications},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {1535-1459},
  doi       = {10.1002/rra.2881},
  pages     = {666 -- 676},
  year      = {2016},
  abstract  = {Recruitment of European eels (Anguilla anguilla) has declined to the extent that they have been added to the IUCN Red List of Threatened Species. Therefore, it is critical to ensure that eels complete their outward river migration in order to contribute to the available spawning stock. We conducted a 4-year (2007-2011) telemetry study to understand the migratory behaviour and potential impact of environmental factors on the eel during this critical life stage. Out of 399 female eels tagged with acoustic transmitters, only 28\% demonstrated clear downstream migratory behaviour. Fifty-five percent were detected exhibiting no downstream migration behaviour and 17\% were not detected at any monitoring station. Movement patterns of downstream-migrating (silver) eels were characterized by nocturnal activity and seasonal migration, with distinct peaks in autumn and spring. Migration was often discontinuous and exhibited phases of active locomotion and expanded stopovers. The most important determinants of movement activity were water temperature, cumulative precipitation and moonlight, although the significance varied by season and location in the river basin. Our results evidence a discontinuous, stepwise migration over an extended period. Furthermore, our findings indicate that migration success depends on holding duration prior to tagging and environmental predictors with varying importance depending on the season, as well as the locations of capture, tagging and release. Copyright (c) 2015 John Wiley \& Sons, Ltd.},
  language  = {en}
}
@article{SchneidervanSchaikZangerleetal.2016,
  author    = {Schneider, A. -K. and van Schaik, L. and Zangerle, A. and Eccard, Jana and Schroeder, B.},
  title     = {Which abiotic filters shape earthworm distribution patterns at the catchment scale?},
  series = {European journal of soil science},
  volume    = {67},
  journal   = {European journal of soil science},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {1351-0754},
  doi       = {10.1111/ejss.12346},
  pages     = {431 -- 442},
  year      = {2016},
  abstract  = {Earthworms affect various soil ecosystem processes in their role as ecosystem engineers. The spatial distribution of earthworms determines the spatial distribution of their functional effects. In particular, earthworm-induced macropore networks may act as preferential flow pathways. In this research we aimed to determine earthworm distributions at the catchment scale with species distribution models (SDMs). We used land-use types, temporally invariant topography-related variables and plot-scale soil characteristics such as pH and organic matter content. We used data from spring 2013 to estimate probability distributions of the occurrence of ten earthworm species. To assess the robustness of these models, we tested temporal transferability by evaluating the accuracy of predictions from the models derived for the spring data with the predictions from data of two other field surveys in autumn 2012 and 2013. In addition, we compared the performance of SDMs based (i) on temporally varying plot-scale predictor variables with (ii) those based on temporally invariant catchment-scale predictors. Models based on catchment-scale predictors, especially land use and slope, experience a small loss of predictive performance only compared with plot-scale SDMs but have greater temporal transferability. Earthworm distribution maps derived from this kind of SDM are a prerequisite for understanding the spatial distribution patterns of functional effects related to earthworms.},
  language  = {en}
}