A new perspective on tree growing season determination

Abstract Defining plant development timing through seasonal growth and dormancy phases is a valuable proxy for studying climate change and serves as an annual bioindicator. However, current methods for determining the growing season vary due to species‐specific interpretations and differing understandings of its main drivers. Körner et al. (2023) introduced four non‐interchangeable definitions of growing seasons to clarify this complex issue. While some studies have paired different methods, none have simultaneously applied a full set of methods at the individual tree or species level. Here, I aim to present a new perspective to understanding growing season timing by focusing on all facets of above‐ground tree growth and measurable biological and phenological markers. This approach calls for simultaneous, continuous monitoring during active and dormancy periods on the same trees and across different species at a large spatial scale. The goal is to comprehensively understand each method's errors, temporal lags, and the factors determining each growing season, as defined by Körner et al. (2023, Ecology Letters, 26, 1277). Accurate estimation of growing season timing can reshape our understanding of its environmental drivers, improve terrestrial ecosystem models, assess the impact of climate change on tree growth, determine the biological zero for various species, verify remote sensing indices and forecast species distribution.

Authors

Institutions

Publication Details

Journal
Journal of Biogeography
Published
2024-08-21
DOI
https://doi.org/10.1111/jbi.14993
Citations
4
Primary Topic
Plant Water Relations and Carbon Dynamics
Type
article
Field-Weighted Citation Impact
1.13
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A new perspective on tree growing season determination

Alma Piermattei
4 citations
Journal of Biogeography
Plant Water Relations and Carbon Dynamics
1.13
article

A new perspective on tree growing season determination

Alma Piermattei
article en
4 citations

Abstract

Abstract Defining plant development timing through seasonal growth and dormancy phases is a valuable proxy for studying climate change and serves as an annual bioindicator. However, current methods for determining the growing season vary due to species‐specific interpretations and differing understandings of its main drivers. Körner et al. (2023) introduced four non‐interchangeable definitions of growing seasons to clarify this complex issue. While some studies have paired different methods, none have simultaneously applied a full set of methods at the individual tree or species level. Here, I aim to present a new perspective to understanding growing season timing by focusing on all facets of above‐ground tree growth and measurable biological and phenological markers. This approach calls for simultaneous, continuous monitoring during active and dormancy periods on the same trees and across different species at a large spatial scale. The goal is to comprehensively understand each method's errors, temporal lags, and the factors determining each growing season, as defined by Körner et al. (2023, Ecology Letters, 26, 1277). Accurate estimation of growing season timing can reshape our understanding of its environmental drivers, improve terrestrial ecosystem models, assess the impact of climate change on tree growth, determine the biological zero for various species, verify remote sensing indices and forecast species distribution.

Journal of BiogeographyVol. 51(12)
Ştefan cel Mare University of Suceava (RO), University of Turin (IT)
Openalex Percentile: Top 23%
Plant Water Relations and Carbon Dynamics
1.13
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.