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231225s2022 xx |||||o 00| ||eng c |
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|a 10.1111/gcb.16046
|2 doi
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|a pubmed25n1115.xml
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|a (DE-627)NLM334575761
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|a (NLM)34921474
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|a DE-627
|b ger
|c DE-627
|e rakwb
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|a eng
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| 100 |
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|a Wu, Donghai
|e verfasserin
|4 aut
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| 245 |
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|a Reduced ecosystem resilience quantifies fine-scale heterogeneity in tropical forest mortality responses to drought
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|c 2022
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|a Text
|b txt
|2 rdacontent
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|a ƒaComputermedien
|b c
|2 rdamedia
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|a ƒa Online-Ressource
|b cr
|2 rdacarrier
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|a Date Completed 24.02.2022
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|a Date Revised 24.02.2022
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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| 520 |
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|a © 2021 John Wiley & Sons Ltd.
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|a Sensitivity of forest mortality to drought in carbon-dense tropical forests remains fraught with uncertainty, while extreme droughts are predicted to be more frequent and intense. Here, the potential of temporal autocorrelation of high-frequency variability in Landsat Enhanced Vegetation Index (EVI), an indicator of ecosystem resilience, to predict spatial and temporal variations of forest biomass mortality is evaluated against in situ census observations for 64 site-year combinations in Costa Rican tropical dry forests during the 2015 ENSO drought. Temporal autocorrelation, within the optimal moving window of 24 months, demonstrated robust predictive power for in situ mortality (leave-one-out cross-validation R2 = 0.54), which allows for estimates of annual biomass mortality patterns at 30 m resolution. Subsequent spatial analysis showed substantial fine-scale heterogeneity of forest mortality patterns, largely driven by drought intensity and ecosystem properties related to plant water use such as forest deciduousness and topography. Highly deciduous forest patches demonstrated much lower mortality sensitivity to drought stress than less deciduous forest patches after elevation was controlled. Our results highlight the potential of high-resolution remote sensing to "fingerprint" forest mortality and the significant role of ecosystem heterogeneity in forest biomass resistance to drought
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|a Journal Article
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| 650 |
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4 |
|a EVI
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| 650 |
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|a ecosystem resilience
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| 650 |
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4 |
|a extreme drought
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| 650 |
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4 |
|a forest mortality
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| 650 |
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4 |
|a remote sensing
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| 650 |
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4 |
|a spatial heterogeneity
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| 650 |
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|a tropical dry forests
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| 650 |
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4 |
|a vegetation index
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| 700 |
1 |
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|a Vargas G, German
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Powers, Jennifer S
|e verfasserin
|4 aut
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| 700 |
1 |
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|a McDowell, Nate G
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Becknell, Justin M
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Pérez-Aviles, Daniel
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Medvigy, David
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Liu, Yanlan
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Katul, Gabriel G
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Calvo-Alvarado, Julio César
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Calvo-Obando, Ana
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Sanchez-Azofeifa, Arturo
|e verfasserin
|4 aut
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| 700 |
1 |
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|a Xu, Xiangtao
|e verfasserin
|4 aut
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| 773 |
0 |
8 |
|i Enthalten in
|t Global change biology
|d 1999
|g 28(2022), 6 vom: 01. März, Seite 2081-2094
|w (DE-627)NLM098239996
|x 1365-2486
|7 nnas
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| 773 |
1 |
8 |
|g volume:28
|g year:2022
|g number:6
|g day:01
|g month:03
|g pages:2081-2094
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| 856 |
4 |
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|u http://dx.doi.org/10.1111/gcb.16046
|3 Volltext
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|d 28
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