P
Peter Pütz
Researcher at Bielefeld University
Publications - 16
Citations - 900
Peter Pütz is an academic researcher from Bielefeld University. The author has contributed to research in topics: Population & Conditional probability distribution. The author has an hindex of 5, co-authored 14 publications receiving 741 citations. Previous affiliations of Peter Pütz include University of Göttingen.
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Journal ArticleDOI
Trade-offs between multifunctionality and profit in tropical smallholder landscapes
Ingo Grass,Ingo Grass,Christoph Kubitza,Christoph Kubitza,Vijesh V. Krishna,Marife D. Corre,Oliver Mußhoff,Peter Pütz,Jochen Drescher,Katja Rembold,Katja Rembold,Eka Sulpin Ariyanti,Andrew D. Barnes,Nicole Brinkmann,Ulrich Brose,Bernhard Brümmer,Damayanti Buchori,Rolf Daniel,Kevin Darras,Heiko Faust,Lutz Fehrmann,Jonas Hein,Nina Hennings,Purnama Hidayat,Dirk Hölscher,Malte Jochum,Malte Jochum,Alexander Knohl,Martyna M. Kotowska,Valentyna Krashevska,Holger Kreft,Christoph Leuschner,Neil Jun S. Lobite,Rawati Panjaitan,Andrea Polle,Anton M. Potapov,Anton M. Potapov,Edwine Setia Purnama,Matin Qaim,Alexander Röll,Stefan Scheu,Dominik Schneider,Aiyen Tjoa,Teja Tscharntke,Edzo Veldkamp,Meike Wollni +45 more
TL;DR: Landscape compositions that can mitigate trade-offs under optimal land-use allocation but also show that intensive monocultures always lead to higher profits are identified, suggesting that targeted landscape planning is needed to increase land- use efficiency while ensuring socio-ecological sustainability.
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Measuring sound detection spaces for acoustic animal sampling and monitoring
TL;DR: In this paper, the authors measured understory vegetation, tree structure, sound transmission, ambient sound pressure level, and derived sound detection spaces of 38 plots in lowland rainforest, jungle rubber, and oil palm and rubber plantations, using different combinations of sound frequency (0.05 to 40 kHz) and source height (0 to 5 meters).
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Prevalence and Risk Factors of Infection in the Representative COVID-19 Cohort Munich.
Michael Pritsch,Katja Radon,Abhishek Bakuli,Ronan Le Gleut,Laura Olbrich,Jessica Michelle Guggenbuehl Noller,Elmar Saathoff,Noemi Castelletti,Mercè Garí,Peter Pütz,Yannik Schälte,Turid Frahnow,Roman Wölfel,Camilla Rothe,Michel Pletschette,Dafni Metaxa,Felix Forster,Verena Thiel,Friedrich Rieß,Maximilian N. Diefenbach,Günter Fröschl,Jan Bruger,Simon Winter,Jonathan Frese,Kerstin Puchinger,Isabel Brand,Inge Kroidl,Jan Hasenauer,Jan Hasenauer,Christiane Fuchs,Andreas Wieser,Michael Hoelscher +31 more
TL;DR: In this article, a population-based study on SARS-CoV-2 prevalence in a large German municipality not affected by a superspreading event was conducted. But the results showed that at least one in four cases in private households was reported and known to the health authorities.
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From first to second wave: follow-up of the prospective COVID-19 cohort (KoCo19) in Munich (Germany).
Katja Radon,Abhishek Bakuli,Peter Pütz,Ronan Le Gleut,Jessica Michelle Guggenbuehl Noller,Laura Olbrich,Elmar Saathoff,Mercè Garí,Yannik Schälte,Turid Frahnow,Roman Wölfel,Michael Pritsch,Camilla Rothe,Michel Pletschette,Raquel Rubio-Acero,Jessica Beyerl,Dafni Metaxa,Felix Forster,Verena Thiel,Noemi Castelletti,Friedrich Rieß,Maximilian N. Diefenbach,Günter Fröschl,Jan Bruger,Simon Winter,Jonathan Frese,Kerstin Puchinger,Isabel Brand,Inge Kroidl,Andreas Wieser,Michael Hoelscher,Jan Hasenauer,Jan Hasenauer,Christiane Fuchs +33 more
TL;DR: In this article, the authors describe the course of the COVID-19 pandemic in the Munich general population living in private households from April 2020 to January 2021, using a self-sampling kit to take a capillary blood sample (dry blood spot; DBS).
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Treatment effects beyond the mean using distributional regression: Methods and guidance.
TL;DR: This paper introduces distributional regression also known as generalized additive models for location, scale and shape (GAMLSS) as a modeling framework for analyzing treatment effects beyond the mean and provides practical guidance on the usage of GAMLSS by reanalyzing data from the Mexican Progresa program.