How are physiological constraints which govern biomass scaling and vascular architecture maintained in managed orchard systems?

- “a tree is a tree”- selective breeding programs cannot fundamentally alter the

physiological constraints acting on tree physiology

Do deviations from branching architecture relationships derived in natural forest ecosystems demonstrate a deliberate human manipulation (e.g., pruning) on the system?

- branching ratio will vary with canopy height- higher order branches: optimize resource transport & growth- scaffolds, high influence from pruning (i.e. scars)

Photosynthetic Biomass Mp vs. Annual Growth Rate G

Stem Basal Diameter D vs. Total Stem Biomass MS

Before Tree Reconstruction After

Stem Midpoint Diameter D vs. Number of Supported Twigs

Developing an Agroecological Approach to Branching Architecture and Biomass Scaling Using Orchard Trees

Zachary T. Brym, Utah State University, Department of Biology and Ecology Center

Current Research DirectionAnthropogenic – “Human Manipulation” – Domestic Fruit Trees

- graft / scion union: disease resistance- dwarfing: increase xylem resistance,

poor nutrient transport / water use efficiency- precocity: early maturation- pruning regiment: increased light, reduced vigor- unlimited nutrients and water- biomass approximation: trunk cross-sectional

area, canopy volume, yield efficiency

Evolutionary – “Natural Selection” – Forest Trees

- grow tall to light source- reproduce late once established in canopy- maximize water efficiency- self shading “poor” light interception- biomass scales: Mp ~ G, D ~ Ms

Agriculture Intensification Gradient

Natural Selection

High Leaf Mass : Wood MassFast Maturity

Max Light Interception“Optimal Foraging” Vascular Structure

Low Leaf Mass : Wood MassSlow MaturityHigh Self ShadingWater Wise Vascular Structure

A Weecology Production

Evolutionary Trade-offs

Human Manipulation

Low Reproductive YieldLow Initial CostLow Economic Efficiency

High Reproductive YieldHigh Initial Cost

High Economic Efficiency

Expected Branching Ratio:

Biomass and Architecture Model

- first test of this theory in agricultural system- first spatially explicit tree- tests the consequences of various horticultural

management strategies (e.g. pruning)- explores avenues of research likely to increase

the efficiency of tree growth- predict water use for diffuse-porous fruit trees

Economics and Management Model

- politico-economic parameters included to suggest sustainable horticultural systems- explore optimal management strategies adapted

under social / climate change

Extension Decision- making Model

- growers, plant breeders, urban planners- graphical user interface for interactions in a

survey-like fashion - generalizes physiological constraints, water-use

and management decisions - What yield and resource use do we expect

under predicted environmental conditions?

Broader Impacts

Opposing Forces

AcknowledgementsThank you for the funding support from the Utah State University Graduate Student Senate Research and Project Grant and the Ecology Center Ph.D. Assistantship and Research Support Award and the field support from the staff and researchers at the Kaysville Experimental Orchard that make this project possible. Niklas K.J. & Enquist B.J. (2001) Invariant scaling relationships for interspecific plant biomass production rates and body size. PNAS, 98(5): 2922-2927

Niklas K.J. & Spatz H.C. (2004) Growth and hydraulic (not mechanical) constraints govern the scaling of tree height and mass. PNAS,101(44): 15661-15663

Data Collection

H

W

LAI

D L

SLA

MS

H - canopy heightW - canopy widthD - branch diameterL - branch length - branch angle / declinationC - branch bearing / headingP - parent branch IDNt,s,b - total count (twig, scar, spur)ML,S,R - biomass (leaves, stems, roots) - wood densityLAI - total leaf area / ground areaSLA - individual leaf area / leaf mass

(

C

P

MR

ML

Orchard

Tree

Orchard

Tree

(Niklas & Enquist, 2001)

(Niklas & Spatz, 2004)

2:1 3:1 5:1 9:1

y = 1.52x – 0.88R2 = 0.796