Back

Tree Surface Area Allometry

Shenkin, A.; Wilkes, P.; Enquist, B. J.; Lau Sarmiento, A.; Burt, A.; Calders, K.; Raumonen, P.; Patrick Bentley, L.; Disney, M.; Malhi, Y.

2024-04-28 ecology
10.1101/2024.04.23.590783 bioRxiv
Show abstract

Utilizing terrestrial laser scanning (TLS) and three-dimensional modeling, this study quantitatively assessed the woody surface areas of 2161 trees across ecosystems encompassing both tropical and temperate forests. TLS enables precise measurement of tree structures at unprecedented scales. This research builds on theoretical scaling relationships with empirical data, significantly refining our understanding of tree woody surface area. Key findings indicate that direct measurements diverge from theoretical predictions, particularly in the finer branch structures, suggesting modifications to existing allometric models might be necessary. This integration of direct measurements with TLS not only challenges established theories but also enhances our capability to accurately model tree surface area, which is key for understanding forest carbon dynamics and metabolic scaling in ecological systems.

Matching journals

The top 6 journals account for 50% of the predicted probability mass.

1
Methods in Ecology and Evolution
○ 176 papers in training set
Top 0.2%
15.1%
Similar papers in this journal
2
Ecosphere
○ 57 papers in training set
Top 0.1%
12.7%
Similar papers in this journal
3
PLOS ONE
● 5266 papers in training set
Top 22%
7.3%
Similar papers in this journal
4
Ecology and Evolution
○ 267 papers in training set
Top 0.8%
6.8%
Similar papers in this journal
5
Ecology
○ 85 papers in training set
Top 0.3%
5.5%
Similar papers in this journal
6
Forest Ecology and Management
○ 27 papers in training set
Top 0.2%
4.1%
50% of probability mass above
7
PeerJ
◐ 308 papers in training set
Top 2%
3.4%
8
Tree Physiology
◐ 24 papers in training set
Top 0.1%
3.2%
9
Biotropica
○ 17 papers in training set
Top 0.2%
2.5%
10
Journal of Theoretical Biology
○ 162 papers in training set
Top 1%
2.5%
11
Frontiers in Ecology and Evolution
○ 69 papers in training set
Top 1.0%
2.1%
12
eLife
● 5828 papers in training set
Top 45%
2.1%
13
Journal of Ecology
○ 49 papers in training set
Top 0.5%
1.7%
14
American Journal of Botany
○ 47 papers in training set
Top 0.5%
1.7%
15
The American Naturalist
● 125 papers in training set
Top 1%
1.4%
16
Oikos
○ 84 papers in training set
Top 1%
1.1%
17
Ecological Informatics
○ 33 papers in training set
Top 0.5%
1.1%
18
Ecological Modelling
○ 28 papers in training set
Top 0.4%
1.1%
19
Ecography
○ 54 papers in training set
Top 1.0%
1.1%
20
AoB PLANTS
◐ 13 papers in training set
Top 0.1%
1.1%
21
Frontiers in Plant Science
○ 256 papers in training set
Top 4%
1.1%
22
PLOS Computational Biology
● 1863 papers in training set
Top 18%
1.1%
23
New Phytologist
○ 346 papers in training set
Top 4%
1.1%
24
Science of The Total Environment
○ 186 papers in training set
Top 3%
1.0%
25
Ecological Monographs
○ 21 papers in training set
Top 0.5%
0.9%
26
Ecological Applications
○ 34 papers in training set
Top 0.8%
0.9%
27
Annals of Botany
◐ 50 papers in training set
Top 0.8%
0.8%
28
Applications in Plant Sciences
○ 23 papers in training set
Top 0.4%
0.8%
29
Scientific Reports
○ 3612 papers in training set
Top 76%
0.6%
30
Oecologia
○ 28 papers in training set
Top 0.8%
0.6%

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.