@article{DeFrenneRodriguezSanchezCoomesetal.2013,
  author    = {De Frenne, Pieter and Rodriguez-Sanchez, Francisco and Coomes, David Anthony and B{\"a}ten, Lander and Verstr{\"a}ten, Gorik and Vellend, Mark and Bernhardt-R{\"o}mermann, Markus and Brown, Carissa D. and Brunet, J{\"o}rg and Cornelis, Johnny and Decocq, Guillaume M. and Dierschke, Hartmut and Eriksson, Ove and Gilliam, Frank S. and Hedl, Radim and Heinken, Thilo and Hermy, Martin and Hommel, Patrick and Jenkins, Michael A. and Kelly, Daniel L. and Kirby, Keith J. and Mitchell, Fraser J. G. and Naaf, Tobias and Newman, Miles and Peterken, George and Petrik, Petr and Schultz, Jan and Sonnier, Gregory and Van Calster, Hans and Waller, Donald M. and Walther, Gian-Reto and White, Peter S. and Woods, Kerry D. and Wulf, Monika and Graae, Bente Jessen and Verheyen, Kris},
  title     = {Microclimate moderates plant responses to macroclimate warming},
  series = {Proceedings of the National Academy of Sciences of the United States of America},
  volume    = {110},
  journal   = {Proceedings of the National Academy of Sciences of the United States of America},
  number    = {46},
  publisher = {National Acad. of Sciences},
  address   = {Washington},
  issn      = {0027-8424},
  doi       = {10.1073/pnas.1311190110},
  pages     = {18561 -- 18565},
  year      = {2013},
  abstract  = {Recent global warming is acting across marine, freshwater, and terrestrial ecosystems to favor species adapted to warmer conditions and/or reduce the abundance of cold-adapted organisms (i.e., "thermophilization" of communities). Lack of community responses to increased temperature, however, has also been reported for several taxa and regions, suggesting that "climatic lags" may be frequent. Here we show that microclimatic effects brought about by forest canopy closure can buffer biotic responses to macroclimate warming, thus explaining an apparent climatic lag. Using data from 1,409 vegetation plots in European and North American temperate forests, each surveyed at least twice over an interval of 12-67 y, we document significant thermophilization of ground-layer plant communities. These changes reflect concurrent declines in species adapted to cooler conditions and increases in species adapted to warmer conditions. However, thermophilization, particularly the increase of warm-adapted species, is attenuated in forests whose canopies have become denser, probably reflecting cooler growing-season ground temperatures via increased shading. As standing stocks of trees have increased in many temperate forests in recent decades, local microclimatic effects may commonly be moderating the impacts of macroclimate warming on forest understories. Conversely, increases in harvesting woody biomass-e.g., for bioenergy-may open forest canopies and accelerate thermophilization of temperate forest biodiversity.},
  language  = {en}
}
@article{AmbergausdemMooreBekketal.2022,
  author    = {Amberg, Maximilian and aus dem Moore, Nils and Bekk, Anke and Bergmann, Tobias and Edenhofer, Ottmar and Flachsland, Christian and George, Jan and Haywood, Luke and Heinemann, Maik and Held, Anne and Kalkuhl, Matthias and Kellner, Maximilian and Koch, Nicolas and Luderer, Gunnar and Meyer, Henrika and Nikodinoska, Dragana and Pahle, Michael and Roolfs, Christina and Schill, Wolf-Peter},
  title     = {Reformoptionen f{\"u}r ein nachhaltiges Steuer- und Abgabensystem},
  series = {Perspektiven der Wirtschaftspolitik},
  volume    = {23},
  journal   = {Perspektiven der Wirtschaftspolitik},
  number    = {3},
  publisher = {De Gruyter},
  address   = {Berlin},
  issn      = {1465-6493},
  doi       = {10.1515/pwp-2021-0051},
  pages     = {165 -- 199},
  year      = {2022},
  abstract  = {Steuern und Abgaben auf Produkte oder Verbrauch mit gesellschaftlichen Folgekosten (externe Kosten) - sogenannte Pigou- oder Lenkungssteuern - sind ein gesellschaftliches „Win-Win-Instrument". Sie verbessern die Wohlfahrt und sch{\"u}tzen gleichzeitig die Umwelt und das Klima. Dies wird erreicht, indem umweltsch{\"a}digende Aktivit{\"a}ten einen Preis bekommen, der m{\"o}glichst exakt der H{\"o}he des Schadens entspricht. Eine konsequente Bepreisung der externen Kosten nach diesem Prinzip k{\"o}nnte in Deutschland erhebliche zus{\"a}tzliche Einnahmen erbringen: Basierend auf bisherigen Studien zu externen Kosten w{\"a}ren zus{\"a}tzliche Einnahmen in der Gr{\"o}ßenordnung von 348 bis 564 Milliarden Euro pro Jahr (44 bis 71 Prozent der gesamten Steuereinnahmen) m{\"o}glich. Die Autoren warnen allerdings, dass die Bezifferung der externen Kosten mit erheblichen Unsicherheiten verbunden ist. Damit Lenkungssteuern und -abgaben ihre positiven Lenkungs- und Wohlstandseffekte voll entfalten k{\"o}nnen, seien zudem institutionelle Reformen notwendig.},
  language  = {de}
}
@article{BreuerWillemsBormannetal.2009,
  author    = {Breuer, Lutz and Willems, Patrick and Bormann, Helge and Bronstert, Axel and Croke, Barry and Frede, Hans Georg and Gr{\"a}ff, Thomas and Hubrechts, Lode and Kite, Geoffrey and Lanini, Jordan and Leavesley, George and Lettenmaier, Dennis P. and Lindstroem, Goeran and Seibert, Jan and Sivapalan, Mayuran and Viney, Neil R.},
  title     = {Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM) : I: model intercomparison with current land use},
  issn      = {0309-1708},
  doi       = {10.1016/j.advwatres.2008.10.003},
  year      = {2009},
  abstract  = {This paper introduces the project on 'Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM)' that aims at investigating the envelope of predictions on changes in hydrological fluxes due to land use change. As part of a series of four papers, this paper outlines the motivation and setup of LUCHEM, and presents a model intercomparison for the present-day simulation results. Such an intercomparison provides a valuable basis to investigate the effects of different model structures on model predictions and paves the ground for the analysis of the performance of multi-model ensembles and the reliability of the scenario predictions in companion papers. in this study, we applied a set of 10 lumped, semi-lumped and fully distributed hydrological models that have been previously used in land use change studies to the low mountainous Dill catchment. Germany. Substantial differences in model performance were observed with Nash-Sutcliffe efficiencies ranging from 0.53 to 0.92. Differences in model performance were attributed to (1) model input data, (2) model calibration and (3) the physical basis of the models. The models were applied with two sets of input data: an original and a homogenized data set. This homogenization of precipitation, temperature and leaf area index was performed to reduce the variation between the models. Homogenization improved the comparability of model simulations and resulted in a reduced average bias, although some variation in model data input remained. The effect of the physical differences between models on the long-term water balance was mainly attributed to differences in how models represent evapotranspiration. Semi-lumped and lumped conceptual models slightly outperformed the fully distributed and physically based models. This was attributed to the automatic model calibration typically used for this type of models. Overall, however, we conclude that there was no superior model if several measures of model performance are considered and that all models are suitable to participate in further multi-model ensemble set-ups and land use change scenario investigations.},
  language  = {en}
}
@article{BreuerBormannBronstertetal.2009,
  author    = {Breuer, Lutz and Bormann, Helge and Bronstert, Axel and Croke, Barry F. W. and Frede, Hans-Georg and Gr{\"a}ff, Thomas and Hubrechts, Lode and Kite, Geoffrey and Lanini, Jordan and Leavesley, George and Lettenmaier, Dennis P. and Lindstroem, Goeran and Seibert, Jan and Sivapalan, Mayuran and Viney, Neil R. and Willems, Patrick},
  title     = {Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM) III : scenario analysis},
  issn      = {0309-1708},
  doi       = {10.1016/j.advwatres.2008.06.009},
  year      = {2009},
  abstract  = {An ensemble of 10 hydrological models was applied to the same set of land use change scenarios. There was general agreement about the direction of changes in the mean annual discharge and 90\% discharge percentile predicted by the ensemble members, although a considerable range in the magnitude of predictions for the scenarios and catchments under consideration was obvious. Differences in the magnitude of the increase were attributed to the different mean annual actual evapotranspiration rates for each land use type. The ensemble of model runs was further analyzed with deterministic and probabilistic ensemble methods. The deterministic ensemble method based on a trimmed mean resulted in a single somewhat more reliable scenario prediction. The probabilistic reliability ensemble averaging (REA) method allowed a quantification of the model structure uncertainty in the scenario predictions. It was concluded that the use of a model ensemble has greatly increased our confidence in the reliability of the model predictions.},
  language  = {en}
}
@misc{MarceGeorgeBuscarinuetal.2016,
  author    = {Marce, Rafael and George, Glen and Buscarinu, Paola and Deidda, Melania and Dunalska, Julita and de Eyto, Elvira and Flaim, Giovanna and Grossart, Hans-Peter and Istvanovics, Vera and Lenhardt, Mirjana and Moreno-Ostos, Enrique and Obrador, Biel and Ostrovsky, Ilia and Pierson, Donald C. and Potuzak, Jan and Poikane, Sandra and Rinke, Karsten and Rodriguez-Mozaz, Sara and Staehr, Peter A. and Sumberova, Katerina and Waajen, Guido and Weyhenmeyer, Gesa A. and Weathers, Kathleen C. and Zion, Mark and Ibelings, Bas W. and Jennings, Eleanor},
  title     = {Automatic High Frequency Monitoring for Improved Lake and Reservoir Management},
  series = {Frontiers in plant science},
  volume    = {50},
  journal   = {Frontiers in plant science},
  publisher = {American Chemical Society},
  address   = {Washington},
  issn      = {0013-936X},
  doi       = {10.1021/acs.est.6b01604},
  pages     = {10780 -- 10794},
  year      = {2016},
  abstract  = {Recent technological developments have increased the number of variables being monitored in lakes and reservoirs using automatic high frequency monitoring (AHFM). However, design of AHFM systems and posterior data handling and interpretation are currently being developed on a site-by-site and issue-by-issue basis with minimal standardization of protocols or knowledge sharing. As a result, many deployments become short-lived or underutilized, and many new scientific developments that are potentially useful for water management and environmental legislation remain underexplored. This Critical Review bridges scientific uses of AHFM with their applications by providing an overview of the current AHFM capabilities, together with examples of successful applications. We review the use of AHFM for maximizing the provision of ecosystem services supplied, by lakes and reservoirs (consumptive and non consumptive uses, food production, and recreation), and for reporting lake status in the EU Water Framework Directive. We also highlight critical issues to enhance the application of AHFM, and suggest the establishment of appropriate networks to facilitate knowledge sharing and technological transfer between potential users. Finally, we give advice on how modern sensor technology can successfully be applied on a larger scale to the management of lakes and reservoirs and maximize the ecosystem services they provide.},
  language  = {en}
}
@article{VineyBormannBreueretal.2009,
  author    = {Viney, Neil R. and Bormann, Helge and Breuer, Lutz and Bronstert, Axel and Croke, Barry F. W. and Frede, Hans-Georg and Gr{\"a}ff, Thomas and Hubrechts, Lode and Huisman, Johan A. and Jakeman, Anthony J. and Kite, Geoffrey W. and Lanini, Jordan and Leavesley, George and Lettenmaier, Dennis P. and Lindstroem, Goeran and Seibert, Jan and Sivapalan, Murugesu and Willems, Patrick},
  title     = {Assessing the impact of land use change on hydrology by ensemble modelling (LUCHEM) II : ensemble combinations and predictions},
  issn      = {0309-1708},
  doi       = {10.1016/j.advwatres.2008.05.006},
  year      = {2009},
  abstract  = {This paper reports on a project to compare predictions from a range of catchment models applied to a mesoscale river basin in central Germany and to assess various ensemble predictions of catchment streamflow. The models encompass a large range in inherent complexity and input requirements. In approximate order of decreasing complexity, they are DHSVM, MIKE-SHE, TOPLATS, WASIM-ETH, SWAT, PRMS, SLURP, HBV, LASCAM and IHACRES. The models are calibrated twice using different sets of input data. The two predictions from each model are then combined by simple averaging to produce a single-model ensemble. The 10 resulting single-model ensembles are combined in various ways to produce multi-model ensemble predictions. Both the single-model ensembles and the multi-model ensembles are shown to give predictions that are generally superior to those of their respective constituent models, both during a 7-year calibration period and a 9- year validation period. This occurs despite a considerable disparity in performance of the individual models. Even the weakest of models is shown to contribute useful information to the ensembles they are part of. The best model combination methods are a trimmed mean (constructed using the central four or six predictions each day) and a weighted mean ensemble (with weights calculated from calibration performance) that places relatively large weights on the better performing models. Conditional ensembles. in which separate model weights are used in different system states (e.g. summer and winter, high and low flows) generally yield little improvement over the weighted mean ensemble. However a conditional ensemble that discriminates between rising and receding flows shows moderate improvement. An analysis of ensemble predictions shows that the best ensembles are not necessarily those containing the best individual models. Conversely, it appears that some models that predict well individually do not necessarily combine well with other models in multi-model ensembles. The reasons behind these observations may relate to the effects of the weighting schemes, non- stationarity of the climate series and possible cross-correlations between models.},
  language  = {en}
}