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Climate dynamics across scales in a mountain landscape: Macro- and microclimatic modelling in the Río Puelo basin, northern Patagonia

dc.contributor.advisorKappas, Martin Prof. Dr.
dc.contributor.authorFierke, Jonas
dc.date.accessioned2025-11-26T18:36:33Z
dc.date.available2025-12-03T00:50:06Z
dc.date.issued2025-11-26
dc.identifier.urihttp://resolver.sub.uni-goettingen.de/purl?ediss-11858/16366
dc.identifier.urihttp://dx.doi.org/10.53846/goediss-11661
dc.format.extent143de
dc.language.isoengde
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject.ddc910de
dc.subject.ddc550de
dc.titleClimate dynamics across scales in a mountain landscape: Macro- and microclimatic modelling in the Río Puelo basin, northern Patagoniade
dc.typecumulativeThesisde
dc.contributor.refereeKappas, Martin Prof. Dr.
dc.date.examination2025-11-20de
dc.description.abstractengMountain forests in northern Patagonia are exposed to rapid climatic changes, with increasing temperatures, changing precipitation regimes, and more frequent and severe extreme events threatening their current structure and resilience. Understanding these short- and long-term dynamics requires integrating climate information across scales: from macroclimatic datasets that inform broad biogeographic analyses to microclimatic measurements that capture the conditions organisms directly experience. This dissertation addresses how macroclimatic and microclimatic modelling can be combined to improve ecological assessments in mountainous forest landscapes, focusing on the Río Puelo watershed of northern Patagonia. Three empirical studies form the core of this work. The first compares two widely used high- resolution climate datasets (CHELSA v2.1 and WorldClim v2.1), showing substantial differences in precipitation estimates and associated bioclimatic classifications, with direct implications for how forest distribution may be projected under future climate scenarios. The second develops spatial models of microclimatic variability based on a dense network of in- situ sensors combined with remote sensing, as well as weather station and reanalysis data. Results highlight the strong and dynamic influence of vegetation structure and topographic position on forest microclimates, affecting both near-ground and sub-canopy (2 m) temperature and moisture conditions, and demonstrate the feasibility of modelling these patterns at 30 m resolution. The third study examines microclimatic buffering during summer heat extremes, revealing that forest structure and elevation consistently reduce maximum temperatures and moderate diurnal warming and cooling rates, while slope orientation exerts weaker and more variable effects. Importantly, buffering strength increases under extreme heat, underscoring the temperature-sensitive character of microclimatic regulation. Taken together, the findings show that the regions of highest ecological sensitivity are also those where climate representation is most uncertain, and where fine scale vegetation and topographic features exert the greatest influence on local conditions. By integrating macroclimatic uncertainty with microclimatic evidence, this dissertation advances conceptual and methodological links between climate and ecosystem research across scales. The results have direct implications for modelling species distributions, understanding forest regeneration dynamics, and informing ecosystem-based management strategies in the fire prone temperate forests of northern Patagonia. Beyond the case study region, the work shows how combining climate data across scales supports more robust evaluations of climate–ecosystem relationships in mountainous terrain. It also provides a framework that can be applied to other forested landscapes where microclimatic processes are critical for resilience. Finally, it highlights the need to account for both uncertainty in global climate products and the buffering capacity of local ecosystems when assessing biodiversity responses to climate change.de
dc.contributor.coRefereeWalentowski, Helge Prof. Dr.
dc.subject.engClimate modellingde
dc.subject.engCHELSAde
dc.subject.engWorldClimde
dc.subject.engClimate datade
dc.subject.engUncertaintyde
dc.subject.engLandscape heterogeneityde
dc.identifier.urnurn:nbn:de:gbv:7-ediss-16366-0
dc.affiliation.instituteFakultät für Geowissenschaften und Geographiede
dc.subject.gokfullGeographie (PPN621264008)de
dc.description.embargoed2025-12-03de
dc.identifier.ppn1942652038
dc.identifier.orcid0009-0008-6794-8310de
dc.notes.confirmationsentConfirmation sent 2025-11-26T19:45:01de


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