Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Matthias Speich"'
Publikováno v:
Frontiers in Sustainable Cities, Vol 6 (2024)
IntroductionThermal grids are key to decarbonizing heating and cooling. However, their development is a complex socio-technical process. This study aims to (1) understand the thermal grid ecosystem’s development under changing political, economic a
Externí odkaz:
https://doaj.org/article/11d72d0b13394476a4b5952089a0c898
Autor:
Matthias Speich, Silvia Ulli-Beer
Publikováno v:
Journal of Cleaner Production. 398:136429
Publikováno v:
Journal of Cleaner Production. 375:133884
Autor:
Matthias Speich
Publikováno v:
iForest-Biogeosciences and Forestry, Vol 12, Iss 1, Pp 1-16 (2019)
Climatic water availability is a major determinant of forest structure and composition, while drought events may severely impact forest dynamics. In recent decades, an increasing number of severe drought events has been reported in forests around the
Autor:
Richard L. Peters, Christoforos Pappas, Elisabeth Graf Pannatier, Matthias Speich, Kathy Steppe, Ansgar Kahmen, Patrick Fonti, Georg von Arx, Ana Stritih, Kerstin Treydte
Publikováno v:
Plant, Cell & Environment. 42:1674-1689
Conifers growing at high elevations need to optimize their stomatal conductance (g(s)) for maximizing photosynthetic yield while minimizing water loss under less favourable thermal conditions. Yet the ability of high-elevation conifers to adjust thei
Publikováno v:
Sustainability, Vol 13, Iss 7264, p 7264 (2021)
Sustainability
Volume 13
Issue 13
Sustainability
Volume 13
Issue 13
Creating new business models is crucial for the implementation of clean technologies for industrial decarbonization. With incomplete knowledge of market processes and uncertain conditions, assessing the prospects of a technology-based business model
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ac56a06f00791baa53b9cda363d9529
https://doi.org/10.20944/preprints202103.0165.v1
https://doi.org/10.20944/preprints202103.0165.v1
Autor:
Katharina Albrich, Matthias Speich, Gunnar Petter, Peter Bebi, Austin Haffenden, Paola Mairota, Harald Bugmann, Robert M. Scheller, Dirk R. Schmatz, Rupert Seidl, Heike Lischke, Josef Brůna, Giorgio Vacchiano
Publikováno v:
Environmental Modelling and Software
Environmental Modelling and Software, Elsevier, 2020, 134, pp.104844. ⟨10.1016/j.envsoft.2020.104844⟩
Environmental Modelling & Software, 134
Environmental Modelling and Software, Elsevier, 2020, 134, pp.104844. ⟨10.1016/j.envsoft.2020.104844⟩
Environmental Modelling & Software, 134
International audience; Projections of landscape dynamics are uncertain, partly due to uncertainties in model formulations. However, quantitative comparative analyses of forest landscape models are lacking. We conducted a systematic comparison of all
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c8e9598ecc61ad9c629aec5b3f7915f6
https://hal.inrae.fr/hal-03259391
https://hal.inrae.fr/hal-03259391
Autor:
Matthias Speich, Paola Ovando
Publikováno v:
Forests, Vol 11, Iss 903, p 903 (2020)
Forests
Volume 11
Issue 9
Digital.CSIC. Repositorio Institucional del CSIC
instname
Forests
Volume 11
Issue 9
Digital.CSIC. Repositorio Institucional del CSIC
instname
We developed an uneven-aged forest economic decision-making framework that combines: (i) a size-structured matrix model, based on growth and mortality predictions of a dynamic process-based forest landscape model, (ii) an optimal control model that d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ccfbecd47959cde70413a6da31fa258c
Publikováno v:
Environmental Modelling & Software. 102:213-232
A global sensitivity analysis was conducted on a dynamic water balance model with 19 parameters describing canopy structure, stomatal regulation and soil characteristics, to quantify the importance of vegetation and soil properties in coupled models
Publikováno v:
Ecological Modelling. 455:109608
Bayesian inference has become an important framework for calibrating complex ecological and environmental models. Markov-Chain Monte Carlo (MCMC) algorithms are the methodological backbone of this framework, but they are not easily parallelizable and