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  • 1
    Publication Date: 2021-10-15
    Description: Abstract
    Description: The file corresponds to a code written using the R software version 4.0.5 (R Core Team, 2021). We used a Bayesian robust regression to predict the posterior probability P(L) at which a given location yi in our study areas (north Patagonia, Chile) is classified as part of a landslide source, transport, or deposition area. We used the NUTS sampling scheme implemented in the STAN probabilistic programming language (Carpenter et al., 2017) to draw samples from the joint posterior distribution via the R package brms (Bürkner, 2017). We ran four independent Hamiltonian Monte Carlo chains based on 2000 iterations including 500 warm-up samples and checked each chain for convergence. We assessed the performance of this classifier based on its posterior predictive distribution and recorded the fraction of correct classifications compared to the observed frequency of landslides in all study areas and for all landform types. We find that higher crown openness and wind speeds credibly predict higher probabilities of detecting landslides regardless of topographic location, though much better in low-order channels and on midslope locations than on open slopes. Wind speed has less predictive power in areas that were impacted by tephra fall from recent volcanic eruptions, while the influence of forest cover in terms of crown openness remains.
    Description: Other
    Description: Copyright (C) 2021 University Potsdam (Oliver Korup). Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
    Keywords: Landslide prediction ; EARTH SCIENCE 〉 LAND SURFACE 〉 LANDSCAPE 〉 LANDSCAPE PROCESSES ; EARTH SCIENCE SERVICES 〉 MODELS 〉 GEOLOGIC/TECTONIC/PALEOCLIMATE MODELS
    Type: Model , Model
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  • 2
    Publication Date: 2022-03-25
    Description: Large earthquakes can increase the amount of water feeding stream flows, raise groundwater levels, and thus grant plant roots more access to water in water‐limited environments. We examine growth and photosynthetic responses of Pine plantations to the Maule Mw 8.8 earthquake in headwater catchments of Chile's Coastal Range. We combine high‐resolution wood anatomic (lumen area) and biogeochemical (δ13C of wood cellulose) proxies of daily to weekly tree growth sampled from trees on floodplains and close to ridge lines. We find that, immediately after the earthquake, at least two out of six tree trees on valley floors had increased lumen area and decreased δ13C, while trees on hillslopes had a reverse trend. Our results indicate a control of soil water on this response, largely consistent with models that predict how enhanced postseismic vertical soil permeability causes groundwater levels to rise on valley floors, but fall along the ridges. Statistical analysis with boosted regression trees indicates that streamflow discharge gained predictive importance for photosynthetic activity on the ridges, but lost importance on the valley floor after the earthquake. We infer that earthquakes may stimulate ecohydrological conditions favoring tree growth over days to weeks by triggering stomatal opening. The weak and short‐lived signals that we identified, however, show that such responses are only valid under water‐limited, rather than energy‐limited tree, growth. Hence, dendrochronological studies targeted at annual resolution may overlook some earthquake effects on tree vitality.
    Description: Plain Language Summary: Earthquakes deform and shake Earth's surface and the ground below. These changes may affect groundwater flow. Groundwater level may rise in the valley bottom and drop along higher elevated ridges. Trees depend on such groundwater resources, particularly in dry climates. Hence, we expect contrasting responses of trees after earthquakes: at higher elevations, access to groundwater may be impeded, but enabled in the valley bottoms. Thus, earthquake‐enhanced tree growth should be pronounced only on valley floors, with opposite responses happening along ridges. We test this hypothesis in pine forest plantations that were affected by the 2010 Maule earthquake, Chile. We find that tree growth increased following the earthquake because of enhanced photosynthesis on valley floors, but decreased on upper hillslopes due to increased water stress. Overall, these responses are small but measurable. Our study is the first to combine state‐of‐the‐art isotopic and wood anatomic proxies that we quantified at the cellular scale. Our results provide novel insights into the impacts of earthquakes on soil water and tree growth at an unprecedented daily to weekly resolution.
    Description: Key Points: Earthquakes may stimulate tree growth by promoting photosynthesis. Direction of tree growth change depends on local topographic position. First dendroecohydrological study to explore earthquake‐water‐vegetation interactions at scale of cells.
    Description: German Federal Ministry of Education and Research
    Description: NSF, BFA, Division of Grants and Agreements (DGA) http://dx.doi.org/10.13039/100005445
    Keywords: ddc:577.2 ; ddc:582.16
    Language: English
    Type: doc-type:article
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