Developing an Agroecological Approach

1. Developing an Agroecological Approach to Branching Architecture and Biomass Scaling Using Orchard Trees A Weecology Production Zachary T. Brym, Utah State University, Department of Biology and Ecology Center Agriculture Intensification Gradient Current Research Direction Opposing Forces Anthropogenic – “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 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 High Reproductive Yield High Initial Cost High Economic Efficiency Low Reproductive Yield Low Initial Cost Low Economic Efficiency Human Manipulation Evolutionary Trade-offs Orchard Tree Broader Impacts • 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? (Niklas & Enquist, 2001) Expected Branching Ratio: 2:1 3:1 5:1 9:1 Orchard Tree Low Leaf Mass : Wood Mass Slow Maturity High Self Shading Water Wise Vascular Structure High Leaf Mass : Wood Mass Fast Maturity Max Light Interception “Optimal Foraging” Vascular Structure (Niklas & Spatz, 2004) Natural Selection Data Collection H - canopy height W - canopy width D - branch diameter L - branch length  - branch angle / declination C - branch bearing / heading P - parent branch ID Nt,s,b - total count (twig, scar, spur) ML,S,R- biomass (leaves, stems, roots)  - wood density LAI - total leaf area / ground area SLA - individual leaf area / leaf mass  C ( LAI ML SLA P H y = 1.52x – 0.88 R2 = 0.796 Acknowledgements L D MS Thank 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. W MR 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