@article{BraeunigerKnappKuehnetal.2010,
  author    = {Braeuniger, Claudia and Knapp, Sonja and Kuehn, Ingolf and Klotz, Stefan},
  title     = {Testing taxonomic and landscape surrogates for biodiversity in an urban setting},
  issn      = {0169-2046},
  doi       = {10.1016/j.landurbplan.2010.07.001},
  year      = {2010},
  abstract  = {Cities often have higher species diversity than the surrounding landscape. This diversity is important for both nature conservation and urban planning. The recreation of residents and the protection of species and habitats are simultaneous targets of maintaining urban green spaces. Data about the distribution and richness of species and their habitats have been compiled frequently; however, it is difficult and costly to measure the complete biodiversity of a region, necessitating useful surrogates. We tested species and habitat data in 27 protected areas in a Central German city and asked (1) whether the diversity of selected taxa acts as a surrogate for the diversity of other taxa and total investigated diversity, and (2) whether landscape structure and human impact explain species richness. Landscape structure metrics were based on soil and habitat types; human influence was measured as the degree of hemeroby. We tested and accounted for sample bias prior to analyses. (1) Vascular plant species richness explained total richness and single taxon richness best. (2) The size of a protected area was the most important predictor of species richness. After correcting for the effect of size, shape complexity, isolation, and matrix properties remained significant. Accordingly, the type of data frequently used for urban planning - collected over several years, by various persons for various purposes - is suitable regarding systematic conservation planning for species richness. The surrogate taxa concept applies in urban areas but with restrictions. Additionally, species richness should be examined in the context of both the city and its surrounding countryside.},
  language  = {en}
}
@misc{BeckBallesterosMejiaBuchmannetal.2012,
  author    = {Beck, Jan and Ballesteros-Mejia, Liliana and Buchmann, Carsten M. and Dengler, J{\"u}rgen and Fritz, Susanne A. and Gruber, Bernd and Hof, Christian and Jansen, Florian and Knapp, Sonja and Kreft, Holger and Schneider, Anne-Kathrin and Winter, Marten and Dormann, Carsten F.},
  title     = {What's on the horizon for macroecology?},
  series = {Ecography : pattern and diversity in ecology ; research papers forum},
  volume    = {35},
  journal   = {Ecography : pattern and diversity in ecology ; research papers forum},
  number    = {8},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {0906-7590},
  doi       = {10.1111/j.1600-0587.2012.07364.x},
  pages     = {673 -- 683},
  year      = {2012},
  abstract  = {Over the last two decades, macroecology the analysis of large-scale, multi-species ecological patterns and processes has established itself as a major line of biological research. Analyses of statistical links between environmental variables and biotic responses have long and successfully been employed as a main approach, but new developments are due to be utilized. Scanning the horizon of macroecology, we identified four challenges that will probably play a major role in the future. We support our claims by examples and bibliographic analyses. 1) Integrating the past into macroecological analyses, e.g. by using paleontological or phylogenetic information or by applying methods from historical biogeography, will sharpen our understanding of the underlying reasons for contemporary patterns. 2) Explicit consideration of the local processes that lead to the observed larger-scale patterns is necessary to understand the fine-grain variability found in nature, and will enable better prediction of future patterns (e.g. under environmental change conditions). 3) Macroecology is dependent on large-scale, high quality data from a broad spectrum of taxa and regions. More available data sources need to be tapped and new, small-grain large-extent data need to be collected. 4) Although macroecology already lead to mainstreaming cutting-edge statistical analysis techniques, we find that more sophisticated methods are needed to account for the biases inherent to sampling at large scale. Bayesian methods may be particularly suitable to address these challenges. To continue the vigorous development of the macroecological research agenda, it is time to address these challenges and to avoid becoming too complacent with current achievements.},
  language  = {en}
}