@unpublished{AcharyaActisAghajanietal.2013,
  author    = {Acharya, B. S. and Actis, M. and Aghajani, T. and Agnetta, G. and Aguilar, J. and Aharonian, Felix A. and Ajello, M. and Akhperjanian, A. G. and Alcubierre, M. and Aleksic, J. and Alfaro, R. and Aliu, E. and Allafort, A. J. and Allan, D. and Allekotte, I. and Amato, E. and Anderson, J. and Ang{\"u}ner, Ekrem Oǧuzhan and Antonelli, L. A. and Antoranz, P. and Aravantinos, A. and Arlen, T. and Armstrong, T. and Arnaldi, H. and Arrabito, L. and Asano, K. and Ashton, T. and Asorey, H. G. and Awane, Y. and Baba, H. and Babic, A. and Baby, N. and Baehr, J. and Bais, A. and Baixeras, C. and Bajtlik, S. and Balbo, M. and Balis, D. and Balkowski, C. and Bamba, A. and Bandiera, R. and Barber, A. and Barbier, C. and Barcelo, M. and Barnacka, Anna and Barnstedt, J{\"u}rgen and Barres de Almeida, U. and Barrio, J. A. and Basili, A. and Basso, S. and Bastieri, D. and Bauer, C. and Baushev, Anton N. and Becerra Gonzalez, J. and Becherini, Yvonne and Bechtol, K. C. and Tjus, J. Becker and Beckmann, Volker and Bednarek, W. and Behera, B. and Belluso, M. and Benbow, W. and Berdugo, J. and Berger, K. and Bernard, F. and Bernardino, T. and Bernl{\"o}hr, K. and Bhat, N. and Bhattacharyya, S. and Bigongiari, C. and Biland, A. and Billotta, S. and Bird, T. and Birsin, E. and Bissaldi, E. and Biteau, Jonathan and Bitossi, M. and Blake, S. and Blanch Bigas, O. and Blasi, P. and Bobkov, A. A. and Boccone, V. and Boettcher, Markus and Bogacz, L. and Bogart, J. and Bogdan, M. and Boisson, Catherine and Boix Gargallo, J. and Bolmont, J. and Bonanno, G. and Bonardi, A. and Bonev, T. and Bonifacio, P. and Bonnoli, G. and Bordas, Pol and Borgland, A. W. and Borkowski, Janett and Bose, R. and Botner, O. and Bottani, A. and Bouchet, L. and Bourgeat, M. and Boutonnet, C. and Bouvier, A. and Brau-Nogue, S. and Braun, I. and Bretz, T. and Briggs, M. S. and Bringmann, T. and Brook, P. and Brun, Pierre and Brunetti, L. and Buanes, T. and Buckley, J. H. and Buehler, R. and Bugaev, V. and Bulgarelli, A. and Bulik, Tomasz and Busetto, G. and Buson, S. and Byrum, K. and Cailles, M. and Cameron, R. A. and Camprecios, J. and Canestrari, R. and Cantu, S. and Capalbi, M. and Caraveo, P. A. and Carmona, E. and Carosi, A. and Carr, John and Carton, P. H. and Casanova, Sabrina and Casiraghi, M. and Catalano, O. and Cavazzani, S. and Cazaux, S. and Cerruti, M. and Chabanne, E. and Chadwick, Paula M. and Champion, C. and Chen, Andrew and Chiang, J. and Chiappetti, L. and Chikawa, M. and Chitnis, V. R. and Chollet, F. and Chudoba, J. and Cieslar, M. and Cillis, A. N. and Cohen-Tanugi, J. and Colafrancesco, Sergio and Colin, P. and Calome, J. and Colonges, S. and Compin, M. and Conconi, P. and Conforti, V. and Connaughton, V. and Conrad, Jan and Contreras, J. L. and Coppi, P. and Corona, P. and Corti, D. and Cortina, J. and Cossio, L. and Costantini, H. and Cotter, G. and Courty, B. and Couturier, S. and Covino, S. and Crimi, G. and Criswell, S. J. and Croston, J. and Cusumano, G. and Dafonseca, M. and Dale, O. and Daniel, M. and Darling, J. and Davids, I. and Dazzi, F. and De Angelis, A. and De Caprio, V. and De Frondat, F. and de Gouveia Dal Pino, E. M. and de la Calle, I. and De La Vega, G. A. and Lopez, R. de los Reyes and De Lotto, B. and De Luca, A. and de Mello Neto, J. R. T. and de Naurois, M. and de Oliveira, Y. and de Ona Wilhelmi, E. and de Souza, V. and Decerprit, G. and Decock, G. and Deil, C. and Delagnes, E. and Deleglise, G. and Delgado, C. and Della Volpe, D. and Demange, P. and Depaola, G. and Dettlaff, A. and Di Paola, A. and Di Pierro, F. and Diaz, C. and Dick, J. and Dickherber, R. and Dickinson, H. and Diez-Blanco, V. and Digel, S. and Dimitrov, D. and Disset, G. and Djannati-Ata{\"i}, A. and Doert, M. and Dohmke, M. and Domainko, W. and Prester, Dijana Dominis and Donat, A. and Dorner, D. and Doro, M. and Dournaux, J-L. and Drake, G. and Dravins, D. and Drury, L. and Dubois, F. and Dubois, R. and Dubus, G. and Dufour, C. and Dumas, D. and Dumm, J. and Durand, D. and Dyks, J. and Dyrda, M. and Ebr, J. and Edy, E. and Egberts, Kathrin and Eger, P. and Einecke, S. and Eleftheriadis, C. and Elles, S. and Emmanoulopoulos, D. and Engelhaupt, D. and Enomoto, R. and Ernenwein, J-P and Errando, M. and Etchegoyen, A. and Evans, P. and Falcone, A. and Fantinel, D. and Farakos, K. and Farnier, C. and Fasola, G. and Favill, B. and Fede, E. and Federici, S. and Fegan, S. and Feinstein, F. and Ferenc, D. and Ferrando, P. and Fesquet, M. and Fiasson, A. and Fillin-Martino, E. and Fink, D. and Finley, C. and Finley, J. P. and Fiorini, M. and Firpo Curcoll, R. and Flores, H. and Florin, D. and Focke, W. and Foehr, C. and Fokitis, E. and Font, L. and Fontaine, G. and Fornasa, M. and Foerster, A. and Fortson, L. and Fouque, N. and Franckowiak, A. and Fransson, C. and Fraser, G. and Frei, R. and Albuquerque, I. F. M. and Fresnillo, L. and Fruck, C. and Fujita, Y. and Fukazawa, Y. and Fukui, Y. and Funk, S. and Gaebele, W. and Gabici, S. and Gabriele, R. and Gadola, A. and Galante, N. and Gall, D. and Gallant, Y. and Gamez-Garcia, J. and Garcia, B. and Garcia Lopez, R. and Gardiol, D. and Garrido, D. and Garrido, L. and Gascon, D. and Gaug, M. and Gaweda, J. and Gebremedhin, L. and Geffroy, N. and Gerard, L. and Ghedina, A. and Ghigo, M. and Giannakaki, E. and Gianotti, F. and Giarrusso, S. and Giavitto, G. and Giebels, B. and Gika, V. and Giommi, P. and Girard, N. and Giro, E. and Giuliani, A. and Glanzman, T. and Glicenstein, J. -F. and Godinovic, N. and Golev, V. and Gomez Berisso, M. and Gomez-Ortega, J. and Gonzalez, M. M. and Gonzalez, A. and Gonzalez, F. and Gonzalez Munoz, A. and Gothe, K. 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  title     = {Introducing the CTA concept},
  series = {Astroparticle physics},
  volume    = {43},
  journal   = {Astroparticle physics},
  number    = {2},
  publisher = {Elsevier},
  address   = {Amsterdam},
  organization    = {CTA Consortium},
  issn      = {0927-6505},
  doi       = {10.1016/j.astropartphys.2013.01.007},
  pages     = {3 -- 18},
  year      = {2013},
  abstract  = {The Cherenkov Telescope Array (CTA) is a new observatory for very high-energy (VHE) gamma rays. CTA has ambitions science goals, for which it is necessary to achieve full-sky coverage, to improve the sensitivity by about an order of magnitude, to span about four decades of energy, from a few tens of GeV to above 100 TeV with enhanced angular and energy resolutions over existing VHE gamma-ray observatories. An international collaboration has formed with more than 1000 members from 27 countries in Europe, Asia, Africa and North and South America. In 2010 the CTA Consortium completed a Design Study and started a three-year Preparatory Phase which leads to production readiness of CTA in 2014. In this paper we introduce the science goals and the concept of CTA, and provide an overview of the project.},
  language  = {en}
}
@article{ActisAgnettaAharonianetal.2011,
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A. and Bogacz, L. and Bogdan, M. and Boisson, Catherine and Boix Gargallo, J. and Bolmont, J. and Bonanno, G. and Bonardi, A. and Bonev, T. and Borkowski, Janett and Botner, O. and Bottani, A. and Bourgeat, M. and Boutonnet, C. and Bouvier, A. and Brau-Nogue, S. and Braun, I. and Bretz, T. and Briggs, M. S. and Brun, Pierre and Brunetti, L. and Buckley, H. and Bugaev, V. and Buehler, R. and Bulik, Tomasz and Busetto, G. and Buson, S. and Byrum, K. and Cailles, M. and Cameron, R. A. and Canestrari, R. and Cantu, S. and Carmona, E. and Carosi, A. and Carr, John and Carton, P. H. and Casiraghi, M. and Castarede, H. and Catalano, O. and Cavazzani, S. and Cazaux, S. and Cerruti, B. and Cerruti, M. and Chadwick, M. and Chiang, J. and Chikawa, M. and Cieslar, M. and Ciesielska, M. and Cillis, A. N. and Clerc, C. and Colin, P. and Colome, J. and Compin, M. and Conconi, P. and Connaughton, V. and Conrad, Jan and Contreras, J. 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J. and Garrido, D. and Garrido, L. and Gascon, D. and Gasq, C. and Gaug, M. and Gaweda, J. and Geffroy, N. and Ghag, C. and Ghedina, A. and Ghigo, M. and Gianakaki, E. and Giarrusso, S. and Giavitto, G. and Giebels, B. and Giro, E. and Giubilato, P. and Glanzman, T. and Glicenstein, J. -F. and Gochna, M. and Golev, V. and Gomez Berisso, M. and Gonzalez, A. and Gonzalez, F. and Granena, F. and Graciani, R. and Granot, J. and Gredig, R. and Green, A. and Greenshaw, T. and Grimm, O. and Grube, J. and Grudzinska, M. and Grygorczuk, J. and Guarino, V. and Guglielmi, L. and Guilloux, F. and Gunji, S. and Gyuk, G. and Hadasch, D. and Haefner, D. and Hagiwara, R. and Hahn, J. and Hallgren, A. and Hara, S. and Hardcastle, M. 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C. and Maccarone, T. and Maier, G. and Majumdar, P. and Maltezos, S. and Malkiewicz, P. and Mana, C. and Manalaysay, A. and Maneva, G. and Mangano, A. and Manigot, P. and Marin, J. and Mariotti, M. and Markoff, S. and Martinez, G. and Martinez, M. and Mastichiadis, A. and Matsumoto, H. and Mattiazzo, S. and Mazin, D. and McComb, T. J. L. and McCubbin, N. and McHardy, I. and Medina, C. and Melkumyan, D. and Mendes, A. and Mertsch, P. and Meucci, M. and Michalowski, J. and Micolon, P. and Mineo, T. and Mirabal, N. and Mirabel, F. and Miranda, J. M. and Mirzoyan, R. and Mizuno, T. and Moal, B. and Moderski, R. and Molinari, E. and Monteiro, I. and Moralejo, A. and Morello, C. and Mori, K. and Motta, G. and Mottez, F. and Moulin, Emmanuel and Mukherjee, R. and Munar, P. and Muraishi, H. and Murase, K. and Murphy, A. Stj. and Nagataki, S. and Naito, T. and Nakamori, T. and Nakayama, K. and Naumann, C. L. and Naumann, D. and Nayman, P. and Nedbal, D. and Niedzwiecki, A. and Niemiec, J. and Nikolaidis, A. and Nishijima, K. and Nolan, S. J. and Nowak, N. and O'Brien, P. T. and Ochoa, I. and Ohira, Y. and Ohishi, M. and Ohka, H. and Okumura, A. and Olivetto, C. and Ong, R. A. and Orito, R. and Orr, M. and Osborne, J. P. and Ostrowski, M. and Otero, L. and Otte, A. N. and Ovcharov, E. and Oya, I. and Ozieblo, A. and Paiano, S. and Pallota, J. and Panazol, J. L. and Paneque, D. and Panter, M. and Paoletti, R. and Papyan, G. and Paredes, J. M. and Pareschi, G. and Parsons, R. D. and Arribas, M. Paz and Pedaletti, G. and Pepato, A. and Persic, M. and Petrucci, P. O. and Peyaud, B. and Piechocki, W. and Pita, S. and Pivato, G. and Platos, L. and Platzer, R. and Pogosyan, L. and Pohl, Martin and Pojmanski, G. and Ponz, J. D. and Potter, W. and Prandini, E. and Preece, R. and Prokoph, H. and Puehlhofer, G. and Punch, M. and Quel, E. and Quirrenbach, A. and Rajda, P. and Rando, R. and Rataj, M. and Raue, M. and Reimann, C. and Reimann, O. and Reimer, A. and Reimer, O. and Renaud, M. and Renner, S. and Reymond, J. -M. and Rhode, W. and Ribo, M. and Ribordy, M. and Rico, J. and Rieger, F. and Ringegni, P. and Ripken, J. and Ristori, P. and Rivoire, S. and Rob, L. and Rodriguez, S. and Roeser, U. and Romano, Patrizia and Romero, G. E. and Rosier-Lees, S. and Rovero, A. C. and Roy, F. and Royer, S. and Rudak, B. and Rulten, C. B. and Ruppel, J. and Russo, F. and Ryde, F. and Sacco, B. and Saggion, A. and Sahakian, V. and Saito, K. and Saito, T. and Sakaki, N. and Salazar, E. and Salini, A. and Sanchez, F. and Sanchez Conde, M. A. and Santangelo, A. and Santos, E. M. and Sanuy, A. and Sapozhnikov, L. and Sarkar, S. and Scalzotto, V. and Scapin, V. and Scarcioffolo, M. and Schanz, T. and Schlenstedt, S. and Schlickeiser, R. and Schmidt, T. and Schmoll, J. and Schroedter, M. and Schultz, C. and Schultze, J. and Schulz, A. and Schwanke, U. and Schwarzburg, S. and Schweizer, T. and Seiradakis, J. and Selmane, S. and Seweryn, K. and Shayduk, M. and Shellard, R. C. and Shibata, T. and Sikora, M. and Silk, J. and Sillanpaa, A. and Sitarek, J. and Skole, C. and Smith, N. and Sobczynska, D. and Sofo Haro, M. and Sol, H. and Spanier, F. and Spiga, D. and Spyrou, S. and Stamatescu, V. and Stamerra, A. and Starling, R. L. C. and Stawarz, L. and Steenkamp, R. and Stegmann, Christian and Steiner, S. and Stergioulas, N. and Sternberger, R. and Stinzing, F. and Stodulski, M. and Straumann, U. and Suarez, A. and Suchenek, M. and Sugawara, R. and Sulanke, K. H. and Sun, S. and Supanitsky, A. 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P. and Videla, M. and Vincent, P. and Vink, J. and Vlahakis, N. and Vlahos, L. and Vogler, P. and Vollhardt, A. and Volpe, F. and Von Gunten, H. P. and Vorobiov, S. and Wagner, S. and Wagner, R. M. and Wagner, B. and Wakely, S. P. and Walter, P. and Walter, R. and Warwick, R. and Wawer, P. and Wawrzaszek, R. and Webb, N. and Wegner, P. and Weinstein, A. and Weitzel, Q. and Welsing, R. and Wetteskind, H. and White, R. and Wierzcholska, A. and Wilkinson, M. I. and Williams, D. A. and Winde, M. and Wischnewski, R. and Wisniewski, L. and Wolczko, A. and Wood, M. and Xiong, Q. and Yamamoto, T. and Yamaoka, K. and Yamazaki, R. and Yanagita, S. and Yoffo, B. and Yonetani, M. and Yoshida, A. and Yoshida, T. and Yoshikoshi, T. and Zabalza, V. and Zagdanski, A. and Zajczyk, A. and Zdziarski, A. and Zech, Alraune and Zietara, K. and Ziolkowski, P. and Zitelli, V. and Zychowski, P.},
  title     = {Design concepts for the Cherenkov Telescope Array CTA an advanced facility for ground-based high-energy gamma-ray astronomy},
  series = {Experimental astronomy : an international journal on astronomical instrumentation and data analysis},
  volume    = {32},
  journal   = {Experimental astronomy : an international journal on astronomical instrumentation and data analysis},
  number    = {3},
  publisher = {Springer},
  address   = {Dordrecht},
  organization    = {CTA Consortium},
  issn      = {0922-6435},
  doi       = {10.1007/s10686-011-9247-0},
  pages     = {193 -- 316},
  year      = {2011},
  abstract  = {Ground-based gamma-ray astronomy has had a major breakthrough with the impressive results obtained using systems of imaging atmospheric Cherenkov telescopes. Ground-based gamma-ray astronomy has a huge potential in astrophysics, particle physics and cosmology. CTA is an international initiative to build the next generation instrument, with a factor of 5-10 improvement in sensitivity in the 100 GeV-10 TeV range and the extension to energies well below 100 GeV and above 100 TeV. CTA will consist of two arrays (one in the north, one in the south) for full sky coverage and will be operated as open observatory. The design of CTA is based on currently available technology. This document reports on the status and presents the major design concepts of CTA.},
  language  = {en}
}
@article{KhiderEmileGeayMcKayetal.2019,
  author    = {Khider, D. and Emile-Geay, J. and McKay, N. P. and Gil, Y. and Garijo, D. and Ratnakar, V and Alonso-Garcia, M. and Bertrand, S. and Bothe, O. and Brewer, P. and Bunn, A. and Chevalier, M. and Comas-Bru, L. and Csank, A. and Dassie, E. and DeLong, K. and Felis, T. and Francus, P. and Frappier, A. and Gray, W. and Goring, S. and Jonkers, L. and Kahle, M. and Kaufman, D. and Kehrwald, N. M. and Martrat, B. and McGregor, H. and Richey, J. and Schmittner, A. and Scroxton, N. and Sutherland, E. and Thirumalai, Kaustubh and Allen, K. and Arnaud, F. and Axford, Y. and Barrows, T. and Bazin, L. and Birch, S. E. Pilaar and Bradley, E. and Bregy, J. and Capron, E. and Cartapanis, O. and Chiang, H-W and Cobb, K. M. and Debret, M. and Dommain, R{\´e}ne and Du, J. and Dyez, K. and Emerick, S. and Erb, M. P. and Falster, G. and Finsinger, W. and Fortier, D. and Gauthier, Nicolas and George, S. and Grimm, E. and Hertzberg, J. and Hibbert, F. and Hillman, A. and Hobbs, W. and Huber, M. and Hughes, A. L. C. and Jaccard, S. and Ruan, J. and Kienast, M. and Konecky, B. and Le Roux, G. and Lyubchich, V and Novello, V. F. and Olaka, L. and Partin, J. W. and Pearce, C. and Phipps, S. J. and Pignol, C. and Piotrowska, N. and Poli, M-S and Prokopenko, A. and Schwanck, F. and Stepanek, C. and Swann, G. E. A. and Telford, R. and Thomas, E. and Thomas, Z. and Truebe, S. and von Gunten, L. and Waite, A. and Weitzel, N. and Wilhelm, B. and Williams, J. and Winstrup, M. and Zhao, N. and Zhou, Y.},
  title     = {PaCTS 1.0: A Crowdsourced Reporting Standard for Paleoclimate Data},
  series = {Paleoceanography and paleoclimatology},
  volume    = {34},
  journal   = {Paleoceanography and paleoclimatology},
  number    = {10},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {2572-4517},
  doi       = {10.1029/2019PA003632},
  pages     = {1570 -- 1596},
  year      = {2019},
  abstract  = {The progress of science is tied to the standardization of measurements, instruments, and data. This is especially true in the Big Data age, where analyzing large data volumes critically hinges on the data being standardized. Accordingly, the lack of community-sanctioned data standards in paleoclimatology has largely precluded the benefits of Big Data advances in the field. Building upon recent efforts to standardize the format and terminology of paleoclimate data, this article describes the Paleoclimate Community reporTing Standard (PaCTS), a crowdsourced reporting standard for such data. PaCTS captures which information should be included when reporting paleoclimate data, with the goal of maximizing the reuse value of paleoclimate data sets, particularly for synthesis work and comparison to climate model simulations. Initiated by the LinkedEarth project, the process to elicit a reporting standard involved an international workshop in 2016, various forms of digital community engagement over the next few years, and grassroots working groups. Participants in this process identified important properties across paleoclimate archives, in addition to the reporting of uncertainties and chronologies; they also identified archive-specific properties and distinguished reporting standards for new versus legacy data sets. This work shows that at least 135 respondents overwhelmingly support a drastic increase in the amount of metadata accompanying paleoclimate data sets. Since such goals are at odds with present practices, we discuss a transparent path toward implementing or revising these recommendations in the near future, using both bottom-up and top-down approaches.},
  language  = {en}
}
@article{MeliAuclercPalmqvistetal.2013,
  author    = {Meli, Mattia and Auclerc, Apolline and Palmqvist, Annemette and Forbes, Valery E. and Grimm, Volker},
  title     = {Population-level consequences of spatially heterogeneous exposure to heavy metals in soil an individual-based model of springtails},
  series = {Ecological modelling : international journal on ecological modelling and engineering and systems ecolog},
  volume    = {250},
  journal   = {Ecological modelling : international journal on ecological modelling and engineering and systems ecolog},
  number    = {1},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0304-3800},
  doi       = {10.1016/j.ecolmodel.2012.11.010},
  pages     = {338 -- 351},
  year      = {2013},
  abstract  = {Contamination of soil with toxic heavy metals poses a major threat to the environment and human health. Anthropogenic sources include smelting of ores, municipal wastes, fertilizers, and pesticides. In assessing soil quality and the environmental and ecological risk of contamination with heavy metals, often homogeneous contamination of the soil is assumed. However, soils are very heterogeneous environments. Consequently, both contamination and the response of soil organisms can be assumed to be heterogeneous. This might have consequences for the exposure of soil organisms and for the extrapolation of risk from the individual to the population level. Therefore, to explore how soil contamination of different spatial heterogeneity affects population dynamics of soil invertebrates, we developed a spatially explicit individual-based model of the springtail, Folsomia candida, a standard test species for ecotoxicological risk assessment. In the model, individuals were assumed to sense and avoid contaminated habitat with a certain probability that depends on contamination level. Avoidance of contaminated areas thus influenced the individuals' movement and feeding, their exposure, and in turn all other biological processes underlying population dynamics. Model rules and parameters were based on data from the literature, or were determined via pattern-oriented modelling. The model correctly predicted several patterns that were not used for model design and calibration. Simulation results showed that the ability of the individuals to detect and avoid the toxicant, combined with the presence of clean habitat patches which act as "refuges", made equilibrium population size due to toxic effects less sensitive to increases in toxicant concentration. Additionally, the level of heterogeneity among patches of soil (i.e. the difference in concentration) was important: at the same average concentration, a homogeneously contaminated scenario was the least favourable habitat, while higher levels of heterogeneity corresponded to higher population growth rate and equilibrium size. Our model can thus be used as a tool for extrapolating from short-term effects at the individual level to long-term effects at the population level under more realistic conditions. It can thus be used to develop and extrapolate from standard ecotoxicological tests in the laboratory to ecological risk assessments.},
  language  = {en}
}
@article{ZurellGrimmRossmanithetal.2012,
  author    = {Zurell, Damaris and Grimm, Volker and Rossmanith, Eva and Zbinden, Niklaus and Zimmermann, Niklaus E. and Schr{\"o}der-Esselbach, Boris},
  title     = {Uncertainty in predictions of range dynamics black grouse climbing the Swiss Alps},
  series = {Ecography : pattern and diversity in ecology ; research papers forum},
  volume    = {35},
  journal   = {Ecography : pattern and diversity in ecology ; research papers forum},
  number    = {7},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {0906-7590},
  doi       = {10.1111/j.1600-0587.2011.07200.x},
  pages     = {590 -- 603},
  year      = {2012},
  abstract  = {Empirical species distribution models (SDMs) constitute often the tool of choice for the assessment of rapid climate change effects on species vulnerability. Conclusions regarding extinction risks might be misleading, however, because SDMs do not explicitly incorporate dispersal or other demographic processes. Here, we supplement SDMs with a dynamic population model 1) to predict climate-induced range dynamics for black grouse in Switzerland, 2) to compare direct and indirect measures of extinction risks, and 3) to quantify uncertainty in predictions as well as the sources of that uncertainty. To this end, we linked models of habitat suitability to a spatially explicit, individual-based model. In an extensive sensitivity analysis, we quantified uncertainty in various model outputs introduced by different SDM algorithms, by different climate scenarios and by demographic model parameters. Potentially suitable habitats were predicted to shift uphill and eastwards. By the end of the 21st century, abrupt habitat losses were predicted in the western Prealps for some climate scenarios. In contrast, population size and occupied area were primarily controlled by currently negative population growth and gradually declined from the beginning of the century across all climate scenarios and SDM algorithms. However, predictions of population dynamic features were highly variable across simulations. Results indicate that inferring extinction probabilities simply from the quantity of suitable habitat may underestimate extinction risks because this may ignore important interactions between life history traits and available habitat. Also, in dynamic range predictions uncertainty in SDM algorithms and climate scenarios can become secondary to uncertainty in dynamic model components. Our study emphasises the need for principal evaluation tools like sensitivity analysis in order to assess uncertainty and robustness in dynamic range predictions. A more direct benefit of such robustness analysis is an improved mechanistic understanding of dynamic species responses to climate change.},
  language  = {en}
}
@article{MeliPalmqvistForbesetal.2014,
  author    = {Meli, Mattia and Palmqvist, Annemette and Forbes, Valery E. and Groeneveld, J{\"u}rgen and Grimm, Volker},
  title     = {Two pairs of eyes are better than one: Combining individual-based and matrix models for ecological risk assessment of chemicals},
  series = {Ecological modelling : international journal on ecological modelling and engineering and systems ecolog},
  volume    = {280},
  journal   = {Ecological modelling : international journal on ecological modelling and engineering and systems ecolog},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0304-3800},
  doi       = {10.1016/j.ecolmodel.2013.07.027},
  pages     = {40 -- 52},
  year      = {2014},
  abstract  = {Current chemical risk assessment procedures may result in imprecise estimates of risk due to sometimes arbitrary simplifying assumptions. As a way to incorporate ecological complexity and improve risk estimates, mechanistic effect models have been recommended. However, effect modeling has not yet been extensively used for regulatory purposes, one of the main reasons being uncertainty about which model type to use to answer specific regulatory questions. We took an individual-based model (IBM), which was developed for risk assessment of soil invertebrates and includes avoidance of highly contaminated areas, and contrasted it with a simpler, more standardized model, based on the generic metapopulation matrix model RAMAS. In the latter the individuals within a sub-population are not treated as separate entities anymore and the spatial resolution is lower. We explored consequences of model aggregation in terms of assessing population-level effects for different spatial distributions of a toxic chemical. For homogeneous contamination of the soil, we found good agreement between the two models, whereas for heterogeneous contamination, at different concentrations and percentages of contaminated area, RAMAS results were alternatively similar to IBM results with and without avoidance, and different food levels. This inconsistency is explained on the basis of behavioral responses that are included in the IBM but not in RAMAS. Overall, RAMAS was less sensitive than the IBM in detecting population-level effects of different spatial patterns of exposure. We conclude that choosing the right model type for risk assessment of chemicals depends on whether or not population-level effects of small-scale heterogeneity in exposure need to be detected. We recommend that if in doubt, both model types should be used and compared. Describing both models following the same standard format, the ODD protocol, makes them equally transparent and understandable. The simpler model helps to build up trust for the more complex model and can be used for more homogeneous exposure patterns. The more complex model helps detecting and understanding the limitations of the simpler model and is needed to ensure ecological realism for more complex exposure scenarios. (C) 2013 Elsevier B.V. All rights reserved.},
  language  = {en}
}
@misc{JeltschGrimmReegetal.2019,
  author    = {Jeltsch, Florian and Grimm, Volker and Reeg, Jette and Schl{\"a}gel, Ulrike E.},
  title     = {Give chance a chance},
  series = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam Mathematisch-Naturwissenschaftliche Reihe},
  number    = {742},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-43532},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-435320},
  pages     = {19},
  year      = {2019},
  abstract  = {A large part of biodiversity theory is driven by the basic question of what allows species to coexist in spite of a confined number of niches. A substantial theoretical background to this question is provided by modern coexistence theory (MCT), which rests on mathematical approaches of invasion analysis to categorize underlying mechanisms into factors that reduce either niche overlap (stabilizing mechanisms) or the average fitness differences of species (equalizing mechanisms). While MCT has inspired biodiversity theory in the search for these underlying mechanisms, we feel that the strong focus on coexistence causes a bias toward the most abundant species and neglects the plethora of species that are less abundant and often show high local turnover. Given the more stochastic nature of their occurrence, we advocate a complementary cross-level approach that links individuals, small populations, and communities and explicitly takes into account (1) a more complete inclusion of environmental and demographic stochasticity affecting small populations, (2) intraspecific trait variation and behavioral plasticity, and (3) local heterogeneities, interactions, and feedbacks. Focusing on mechanisms that drive the temporary coviability of species rather than infinite coexistence, we suggest a new approach that could be dubbed coviability analysis (CVA). From a modeling perspective, CVA builds on the merged approaches of individual-based modeling and population viability analysis but extends them to the community level. From an empirical viewpoint, CVA calls for a stronger integration of spatiotemporal data on variability and noise, changing drivers, and interactions at the level of individuals. The resulting large volumes of data from multiple sources could be strongly supported by novel techniques tailored to the discovery of complex patterns in high-dimensional data. By complementing MCT through a stronger focus on the coviability of less common species, this approach can help make modern biodiversity theory more comprehensive, predictive, and relevant for applications.},
  language  = {en}
}
@article{JeltschGrimmReegetal.2019,
  author    = {Jeltsch, Florian and Grimm, Volker and Reeg, Jette and Schl{\"a}gel, Ulrike E.},
  title     = {Give chance a chance},
  series = {Ecosphere},
  volume    = {10},
  journal   = {Ecosphere},
  number    = {5},
  publisher = {ESA},
  address   = {Ithaca, NY},
  issn      = {2150-8925},
  doi       = {10.1002/ecs2.2700},
  pages     = {19},
  year      = {2019},
  abstract  = {A large part of biodiversity theory is driven by the basic question of what allows species to coexist in spite of a confined number of niches. A substantial theoretical background to this question is provided by modern coexistence theory (MCT), which rests on mathematical approaches of invasion analysis to categorize underlying mechanisms into factors that reduce either niche overlap (stabilizing mechanisms) or the average fitness differences of species (equalizing mechanisms). While MCT has inspired biodiversity theory in the search for these underlying mechanisms, we feel that the strong focus on coexistence causes a bias toward the most abundant species and neglects the plethora of species that are less abundant and often show high local turnover. Given the more stochastic nature of their occurrence, we advocate a complementary cross-level approach that links individuals, small populations, and communities and explicitly takes into account (1) a more complete inclusion of environmental and demographic stochasticity affecting small populations, (2) intraspecific trait variation and behavioral plasticity, and (3) local heterogeneities, interactions, and feedbacks. Focusing on mechanisms that drive the temporary coviability of species rather than infinite coexistence, we suggest a new approach that could be dubbed coviability analysis (CVA). From a modeling perspective, CVA builds on the merged approaches of individual-based modeling and population viability analysis but extends them to the community level. From an empirical viewpoint, CVA calls for a stronger integration of spatiotemporal data on variability and noise, changing drivers, and interactions at the level of individuals. The resulting large volumes of data from multiple sources could be strongly supported by novel techniques tailored to the discovery of complex patterns in high-dimensional data. By complementing MCT through a stronger focus on the coviability of less common species, this approach can help make modern biodiversity theory more comprehensive, predictive, and relevant for applications.},
  language  = {en}
}
@article{CrawfordJeltschMayetal.2018,
  author    = {Crawford, Michael and Jeltsch, Florian and May, Felix and Grimm, Volker and Schl{\"a}gel, Ulrike E.},
  title     = {Intraspecific trait variation increases species diversity in a trait-based grassland model},
  series = {Oikos},
  volume    = {128},
  journal   = {Oikos},
  number    = {3},
  publisher = {Wiley},
  address   = {Hoboken},
  issn      = {0030-1299},
  doi       = {10.1111/oik.05567},
  pages     = {441 -- 455},
  year      = {2018},
  abstract  = {Intraspecific trait variation (ITV) is thought to play a significant role in community assembly, but the magnitude and direction of its influence are not well understood. Although it may be critical to better explain population persistence, species interactions, and therefore biodiversity patterns, manipulating ITV in experiments is challenging. We therefore incorporated ITV into a trait- and individual-based model of grassland community assembly by adding variation to the plants' functional traits, which then drive life-history tradeoffs. Varying the amount of ITV in the simulation, we examine its influence on pairwise-coexistence and then on the species diversity in communities of different initial sizes. We find that ITV increases the ability of the weakest species to invade most, but that this effect does not scale to the community level, where the primary effect of ITV is to increase the persistence and abundance of the competitively-average species. Diversity of the initial community is also of critical importance in determining ITV's efficacy; above a threshold of interspecific diversity, ITV does not increase diversity further. For communities below this threshold, ITV mainly helps to increase diversity in those communities that would otherwise be low-diversity. These findings suggest that ITV actively maintains diversity by helping the species on the margins of persistence, but mostly in habitats of relatively low alpha and beta diversity.},
  language  = {en}
}