%0 Generic %A Sinoquet, Hervé %A Pincebourde, Sylvain %A Adam, Boris %A Donès, Nicolas %A Phattaralerphong, Jessada %A Combes, Didier %A Ploquin, Stéphane %A Sangsing, Krissada %A Kasemsap, Poonpipope %A Thanisawanyangkura, Sornprach %A Groussier-Bout, Géraldine %A Casas, JérÔme %D 2016 %T Data Paper. Data Paper %U https://wiley.figshare.com/articles/dataset/Data_Paper_Data_Paper/3530507 %R 10.6084/m9.figshare.3530507.v1 %2 https://ndownloader.figshare.com/files/5602694 %2 https://ndownloader.figshare.com/files/5602697 %2 https://ndownloader.figshare.com/files/5602703 %2 https://ndownloader.figshare.com/files/5602706 %2 https://ndownloader.figshare.com/files/5602709 %2 https://ndownloader.figshare.com/files/5602712 %2 https://ndownloader.figshare.com/files/5602715 %2 https://ndownloader.figshare.com/files/5602718 %K plant architecture %K leaf area %K microclimate %K light interception %K fruit tree %K leaf coordinates %K 3-D digitizing %K canopy geometry %K leaf orientation %K rubber tree %K Environmental Science %K Ecology %X

File List

ASCII text, tab delimited. No compression schemes were used. The number of rows (including header row) and columns for each file are: (Apple) 26,255 rows and 17 columns; (Mango1) 1,637 rows and 11 columns; (Mango2) 2,460 rows and 11 columns; (Rubber1) 896 rows and 10 columns; (Rubber2) 12,142 rows and 14 columns; (Walnut) 1,559 rows and 12 columns.

Apple_Tree.txt

Mango_Tree1.txt

Mango_Tree2.txt

Rubber_Tree1.txt

Rubber_Tree2.txt

Walnut_Tree.txt

Description

The geometrical structure of plant canopies has many implications for plant functioning, microclimatic conditions, and plant-pathogen/herbivore interactions. Plant geometry can be described at several scales. At the finest scale, canopy structure includes the shape, size, location, and orientation of each organ in the canopy. This data set reports the three-dimensional (3-D) geometry of a set of fruit and rubber trees at the leaf scale. A 3-D magnetic digitizer was used to measure the spatial coordinates and the orientation angles of each leaf, namely, the midrib azimuth and inclination angles, and the rolling angle of leaf lamina around the midrib. In addition, for most trees, branching or flush order is given as well as the ranking of leaves along branches and the leaf identity of leaflets in compound-leaved trees. Leaf length was also measured for most trees. Leaf width was measured or estimated based on allometric relationships. Leaf area was derived from allometric relationships with leaf length and width. The data set includes the 3-D geometry of six trees: one apple, two mangos, two rubbers, and one walnut. Plant height ranged from 1.6 m for mango trees to 5.3 m for the large rubber tree. The number of leaves ranged from 895 for the small rubber tree to 26,283 for the apple tree. Total leaf area ranged from 3.6 m2 for the small rubber tree to 36.4 m2 for the apple tree. Most of the data were used to show how canopy geometry determines light interception and subsequently plant primary production and fruit yield. The data set was also used to test the quality of innovative methods for canopy structure description at tree scale. The apple tree was used to study the thermal environment of a leaf miner insect, to show how canopy geometry leads to a strongly heterogeneous risk of mortality, in particular under heat-wave conditions. Overall, our data set provides explicit plant architectures suitable for spatial modeling of plant physiological ecology and plant–herbivore interactions, allowing us to determine the mechanisms through which climate impacts biological and ecological processes involved in these functions.

Key words: canopy geometry; fruit tree; leaf area; leaf coordinates; leaf orientation; light interception; microclimate; plant architecture; rubber tree; 3-D digitizing.

%I Wiley