Matches in SemOpenAlex for { <https://semopenalex.org/work/W2423748468> ?p ?o ?g. }
- W2423748468 endingPage "2479" @default.
- W2423748468 startingPage "2465" @default.
- W2423748468 abstract "Abstract Large uncertainties characterize forest development under global climate change. Although recent studies have found widespread increased tree mortality, the patterns and processes associated with tree death remain poorly understood, thus restricting accurate mortality predictions. Yet, projections of future forest dynamics depend critically on robust mortality models, preferably based on empirical data rather than theoretical, not well‐constrained assumptions. We developed parsimonious mortality models for individual beech ( Fagus sylvatica L.) trees and evaluated their potential for incorporation in dynamic vegetation models (DVMs). We used inventory data from nearly 19,000 trees from unmanaged forests in Switzerland, Germany, and Ukraine, representing the largest dataset used to date for calibrating such models. Tree death was modelled as a function of size and growth, i.e., stem diameter (dbh) and relative basal area increment (relBAI), using generalized logistic regression accounting for unequal re‐measurement intervals. To explain the spatial and temporal variability in mortality patterns, we considered a large set of environmental and stand characteristics. Validation with independent datasets was performed to assess model generality. Our results demonstrate strong variability in beech mortality that was independent of environmental or stand characteristics. Mortality patterns in Swiss and German strict forest reserves were dominated by competition processes as indicated by J‐shaped mortality over tree size and growth. The Ukrainian primeval beech forest was additionally characterized by windthrow and a U‐shaped size–mortality function. Unlike the mortality model based on Ukrainian data, the Swiss and German models achieved good discrimination and acceptable transferability when validated against each other. We thus recommend these two models to be incorporated and examined in DVMs. Their mortality predictions respond to climate change via tree growth, which is sufficient to capture the adverse effects of water availability and competition on the mortality probability of beech under current conditions." @default.
- W2423748468 created "2016-06-24" @default.
- W2423748468 creator A5001103795 @default.
- W2423748468 creator A5049502097 @default.
- W2423748468 creator A5063452529 @default.
- W2423748468 creator A5063465103 @default.
- W2423748468 creator A5081300492 @default.
- W2423748468 creator A5083642146 @default.
- W2423748468 date "2016-10-27" @default.
- W2423748468 modified "2023-10-18" @default.
- W2423748468 title "Does one model fit all? Patterns of beech mortality in natural forests of three European regions" @default.
- W2423748468 cites W1480376833 @default.
- W2423748468 cites W1913444490 @default.
- W2423748468 cites W1973752964 @default.
- W2423748468 cites W1975143654 @default.
- W2423748468 cites W1979637435 @default.
- W2423748468 cites W1980710118 @default.
- W2423748468 cites W1983988409 @default.
- W2423748468 cites W1991192533 @default.
- W2423748468 cites W1994911175 @default.
- W2423748468 cites W1996852081 @default.
- W2423748468 cites W1998930384 @default.
- W2423748468 cites W2000603443 @default.
- W2423748468 cites W2009323142 @default.
- W2423748468 cites W2011123130 @default.
- W2423748468 cites W2016590217 @default.
- W2423748468 cites W2022224360 @default.
- W2423748468 cites W2023024638 @default.
- W2423748468 cites W2023776934 @default.
- W2423748468 cites W2025270999 @default.
- W2423748468 cites W2029390163 @default.
- W2423748468 cites W2036809095 @default.
- W2423748468 cites W2040633567 @default.
- W2423748468 cites W2044873980 @default.
- W2423748468 cites W2058871135 @default.
- W2423748468 cites W2061903231 @default.
- W2423748468 cites W2063681704 @default.
- W2423748468 cites W2064738893 @default.
- W2423748468 cites W2065680007 @default.
- W2423748468 cites W2072307508 @default.
- W2423748468 cites W2073535988 @default.
- W2423748468 cites W2074074333 @default.
- W2423748468 cites W2078639288 @default.
- W2423748468 cites W2078710512 @default.
- W2423748468 cites W2089431318 @default.
- W2423748468 cites W2089774181 @default.
- W2423748468 cites W2095018643 @default.
- W2423748468 cites W2096603181 @default.
- W2423748468 cites W2105424374 @default.
- W2423748468 cites W2115259265 @default.
- W2423748468 cites W2119910794 @default.
- W2423748468 cites W2123287706 @default.
- W2423748468 cites W2125228380 @default.
- W2423748468 cites W2126555187 @default.
- W2423748468 cites W2134975353 @default.
- W2423748468 cites W2136641634 @default.
- W2423748468 cites W2137492415 @default.
- W2423748468 cites W2140053155 @default.
- W2423748468 cites W2140131090 @default.
- W2423748468 cites W2140657790 @default.
- W2423748468 cites W2144632834 @default.
- W2423748468 cites W2146768314 @default.
- W2423748468 cites W2148693616 @default.
- W2423748468 cites W2151162783 @default.
- W2423748468 cites W2158698691 @default.
- W2423748468 cites W2160551249 @default.
- W2423748468 cites W2171691700 @default.
- W2423748468 cites W2251943622 @default.
- W2423748468 cites W2293157089 @default.
- W2423748468 cites W2320188069 @default.
- W2423748468 cites W2325604464 @default.
- W2423748468 cites W2416259737 @default.
- W2423748468 cites W2470971115 @default.
- W2423748468 cites W4236567917 @default.
- W2423748468 cites W4238528855 @default.
- W2423748468 cites W4254703264 @default.
- W2423748468 doi "https://doi.org/10.1002/eap.1388" @default.
- W2423748468 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/27787924" @default.
- W2423748468 hasPublicationYear "2016" @default.
- W2423748468 type Work @default.
- W2423748468 sameAs 2423748468 @default.
- W2423748468 citedByCount "24" @default.
- W2423748468 countsByYear W24237484682017 @default.
- W2423748468 countsByYear W24237484682018 @default.
- W2423748468 countsByYear W24237484682019 @default.
- W2423748468 countsByYear W24237484682020 @default.
- W2423748468 countsByYear W24237484682021 @default.
- W2423748468 countsByYear W24237484682022 @default.
- W2423748468 countsByYear W24237484682023 @default.
- W2423748468 crossrefType "journal-article" @default.
- W2423748468 hasAuthorship W2423748468A5001103795 @default.
- W2423748468 hasAuthorship W2423748468A5049502097 @default.
- W2423748468 hasAuthorship W2423748468A5063452529 @default.
- W2423748468 hasAuthorship W2423748468A5063465103 @default.
- W2423748468 hasAuthorship W2423748468A5081300492 @default.
- W2423748468 hasAuthorship W2423748468A5083642146 @default.
- W2423748468 hasBestOaLocation W24237484682 @default.
- W2423748468 hasConcept C125072520 @default.