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Naslov:Modelling seasonal dynamics of secondary growth in R
Avtorji:ID Jevšenak, Jernej (Avtor)
ID Gričar, Jožica (Avtor)
ID Rossi, Sergio (Avtor)
ID Prislan, Peter (Avtor)
Datoteke:URL URL - Izvorni URL, za dostop obiščite https://onlinelibrary.wiley.com/doi/10.1111/ecog.06030
 
.pdf PDF - Predstavitvena datoteka, prenos (1,26 MB)
MD5: 4A22D0099883D42840822B0DBC30D3AD
 
Jezik:Angleški jezik
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:Logo SciVie - Gozdarski inštitut Slovenije
Povzetek:The monitoring of seasonal radial growth of woody plants addresses the ultimate question of when, how and why trees grow. Assessing the growth dynamics is important to quantify the effect of environmental drivers and understand how woody species will deal with the ongoing climatic changes. One of the crucial steps in the analyses of seasonal radial growth is to model the dynamics of xylem and phloem formation based on increment measurements on samples taken at relatively short intervals during the growing season. The most common approach is the use of the Gompertz equation, while other approaches, such as general additive models (GAMs) and generalised linear models (GLMs), have also been tested in recent years. For the first time, we explored artificial neural networks with Bayesian regularisation algorithm (BRNNs) and show that this method is easy to use, resistant to overfitting, tends to yield s-shaped curves and is therefore suitable for deriving temporal dynamics of secondary tree growth. We propose two data processing algorithms that allow more flexible fits. The main result of our work is the XPSgrowth() function implemented in the radial Tree Growth (rTG) R package, that can be used to evaluate and compare three modelling approaches: BRNN, GAM and the Gompertz function. The newly developed function, tested on intra-seasonal xylem and phloem formation data, has potential applications in many ecological and environmental disciplines where growth is expressed as a function of time. Different approaches were evaluated in terms of prediction error, while fitted curves were visually compared to derive their main characteristics. Our results suggest that there is no single best fitting method, therefore we recommend testing different fitting methods and selection of the optimal one.
Ključne besede:artificial neural networks, cambium, generalized additive model, Gompertz function, growing season, intra-annual time series
Status publikacije:Objavljeno
Verzija publikacije:Objavljena publikacija
Leto izida:2022
Št. strani:8 str.
Številčenje:Vol. 2022, iss. 9, e06030
PID:20.500.12556/DiRROS-15308 Novo okno
UDK:630*811
ISSN pri članku:1600-0587
DOI:10.1111/ecog.06030 Novo okno
COBISS.SI-ID:116105475 Novo okno
Opomba:Nasl. z nasl. zaslona; Opis vira z dne 21. 7. 2022;
Datum objave v DiRROS:21.07.2022
Število ogledov:963
Število prenosov:607
Metapodatki:XML DC-XML DC-RDF
:
JEVŠENAK, Jernej, GRIČAR, Jožica, ROSSI, Sergio in PRISLAN, Peter, 2022, Modelling seasonal dynamics of secondary growth in R. Ecography [na spletu]. 2022. Vol. 2022, no. 9, e06030. [Dostopano 8 april 2025]. DOI 10.1111/ecog.06030. Pridobljeno s: https://dirros.openscience.si/IzpisGradiva.php?lang=slv&id=15308
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Gradivo je del revije

Naslov:Ecography
Založnik:Munksgaard International Publishers
ISSN:1600-0587
COBISS.SI-ID:517696537 Novo okno

Gradivo je financirano iz projekta

Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:J4-9297-2018
Naslov:Skladnost in časovno ujemanje med ogljikom vezanim v lesno biomaso in "eddy covariance" oceno neto ekosistemske produkcije za presvetljen gozdnat ekosistem" oceno neto ekosistemske produkcije za presvetljen gozdnat ekosistem
Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:J4-7203-2016
Naslov:Kratkoročni in dolgoročni odzivi hrastov v submediteranu na ekstremne vremenske dogodke s pomočjo drevesno-anatomskih analiz in eko-fizioloških meritev
Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:Z4-7318-2016
Naslov:Vpliv klimatskih sprememb na kambijevo aktivnosti, nastajanje in zgradbo lesa ter produktivnost bukve (Fagus sylvatica L.) in smreke (Picea abies L.) v Sloveniji
Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:P4-0430-2022
Naslov:Gozdno-lesna veriga in podnebne spremembe: prehod v krožno biogospodarstvo
Financer:ARRS - Agencija za raziskovalno dejavnost Republike Slovenije
Številka projekta:J4-2541-2020
Naslov:Vpliv podnebnih sprememb na dinamiko akumulacije lesne biomase bukve in smreke v Sloveniji in ovrednotenje s tem povezanih potencialov rasti biogospodarstva

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

Jezik:Ni določen
Ključne besede:umetne nevronske mreže, kambij, generalizirani linearni modeli, Gompertzova funkcija, rastna sezona, znotraj-letne časovne vrste


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