CLM(ED) and the end of `vegeta4on dynamics
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1 Land Model Working Group, NCAR, 3rd March 2012 CLM(ED) and the end of `vegeta4on dynamics Rosie Fisher Na4onal Center for Atmospheric Research, Boulder, CO Thanks to: Gordon Bonan, Keith Oleson, Chonggang Xu, Erik Kluzek, Nate McDowell, Sönke Zaehle, Quinn Thomas & Paul Moorcro\ BIOLOGICAL AND ENVIRONMENTAL RESEARCH
2 What is vegeta4on dynamics? Recruitment? Compe44on & Co- existence? Mortality? Pioneer Weeds Grasses Shrubs Soft hardwoods Expanding saplings Mature trees
3 Ecosystem Demography Model (ED) Moorcro\, Hur` and Pacala (2001) Plant compe44on as an emergent property of plant physiology Cohorts of plants, Binned according to: 1. Successional stage of land 2. Func4onal type of plant 3. Height class of plant Provides a framework to simulate 1. Compe44on for light 2. Coexistence between plant types Post- disturbance succession 4. Variable vegeta4on complexity
4 CLM(ED) changes to 4ling structure PFT- based 4le structure. e.g. CLM, TRIFFID, LPJ, SDGVM Age- based 4le structure. ED NL tree C3 60 y.o. 30 y.o. BL tree C4 90 y.o. 15 y.o. Bare Gd Shrub 1 y.o. 5 y.o.
5 Mortality as a func4on of plant physiology v1.0: Carbon starva4on Not a threshold! Accoun4ng for within- cohort variability at landscape scale.
6 Trying to grow semi- arid plants in New Mexico. Too much LAI= water stress Too much LAI Carbon Starva4on Overcompensa4ng mortality Mortality crash Grey shaded areas are the range of observa4ons from the Sevilleta Pinon- Juniper throughfall exclusion in Central New Mexico Pangle R, Plaut J, Pockman W, Lemarc JF, Pockman W, McDowell N in prep.
7 Exis4ng CLM4(ED) evergreen alloca4on Why are plants starving so catastrophically? R auto Tissue turnover Storage GPP NPP C balance Growth - Priority given to 4ssue turnover at the expense of storage - Extra leaf area uses up both carbon and water during drought (RISK). - Keeping leaf area is advantageous a\er drought (GROWTH).
8 New CLM4(ED) evergreen alloca4on R auto GPP Tissue turnover NPP T max.α NPP - T max.α Storage Growth Do plants a) lose leaves or b) use up carbon stores during stress?
9 What if storage gets priority over 4ssue turnover? Leaves adjust to stress No stress induced mortality Conserve carbon store Alloca4on to 4ssue turnover under stress = 50% of demand Alloca4on to 4ssue turnover under stress = 100% of demand
10 Grey bars = data from Caxiuana rainforest through- fall experiment: Fisher et al. 2007, Metcalfe et al Applica4on to rainforest drought experiment Rainfall halved to simulate drought treatment Too much dry season stress? Storage conserved leaf area adjusts to stress Alloca4on to 4ssue turnover under stress (α) = 0% of demand Alloca4on to 4ssue turnover under stress (α) = 100% of demand
11 Community interac4ons and compe44on Before drought, non- lethal seasonal stress rewards risk takers A\er drought, conserva4ve, adap4ve leaf strategies do be`er. Leaf carbon Risk takers use up reserves and die Exclusion of most conserva4ve strategies
12 Amazon benchmark figure Benchmarking of CLM(ED) canopy physiology
13 Maintain leaves Amazon p\ figure Frac4onal cover of 6 PFT s with differing alloca4on strategies Maintain stores
14 Summary Plant alloca4on strategies have implica4ons for mortality Under good climate condi4ons, risk- taking strategies (leaves staying on) are advantageous Under more stressful condi4ons, conserva4ve strategies are more appropriate In ED, vegeta4on growth, compe44on and mortality all emerge from vegeta4on physiology but, once we link plant demography and physiology together, we need to be even more confident that our plant physiology models are accurate.
15 CLM(ED) to- do list Data structure Radia4on transfer scheme (Norman) Energy balance closure Photosynthesis code (CLM4) Water stress update Cold Phenology (Bo`a et al. 2001) Drought Phenology (?) Restarts Parameter fusion Allometry priori4es Carbon starva4on mortality (NM) Flexible canopy architecture Canopy closure/space filling (PPA) Timestep/numerics Leaf Op4miza4on Point tests Paralleliza4on Tests Regional Tests Global Tests PFT reclassifica4on (TRY database) Snow interac4ons (DL,SS) Stem area index Grass allometry (AS) Fire & Insects & Windthrow Nitrogen Cycle (CN+CX,RQT,SZ) Migra4on (MIT) Land Use/Harvest/Crops (CX,PL,SL,AS) Benchmark, Publish, Coupled runs, etc... GOAL: Develop a model to inves4gate physiological hypotheses for why- plants- live- where- they- do. Inves4gate their behaviour in future climate systems
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