Chapter 5 Stand Dynamics & Gap Models I work at large to global scale. When we use bgc models over large scales we use static landcover maps. If we project into the future a static landcover map is not accurate because as climate changes the potential vegetation community changes which can greatly influence factors such as carbon stocks, npp, c sink/source strength, nutrient demand and cycling, et, ect. In addition, we still only simply represent disturbance which is the mechanism that can reset vegetation structure, free up resources, and act as a catalyst for large-scale vegetation composition changes. NRSM 532, BIOS 534 Spring 2014

Tree Growth (live fast, die young) Height 25 50 100 Age (years) Douglas fir (Montana) Southern Pines Cottonwood What biophysical gradient are these strategies occurring along? Southeastern trees grow faster initially and mature earlier foresters take advantage of this for commercial logging Montana trees end up growing bigger

The Stages of Succession Stand Initiation Stage: high resource availability (water nutrients light), top competitors dominate while some under story facilitation can occur Stem Exclusion Stage: overstory reaches its maximum. Growth efficiency or the wood increment per unit leaf area due to growth suppression. Understory Reinitiation Stage: mortality creates gaps that allow understory species to establish Old Growth Stage: dominant tree show little to no height increase, variable canopy height due to mortality and gap filling.

Restricted Growth (uneven walls) This trees also has the same potential shape as the first one. The wall is at irregular distances from the tree asymmetric crown Wall stops rising – what happens to the crown as the tree grows above it? Crown size increases with tree height since the base no longer recedes.

Site Index Age Height 25 50 100 SI25 = 40 SI50 = 60 SI100 = 90

Stand Density LAI / NPP 100 1000 Stand Density (trees ha-1) How does basal area change from 100 to 1000 trees ha-1? 100 1000 Stand Density (trees ha-1)

Stand Density (Self-Thinning Rule)

Inter-tree Competition Light Canopy Water Interception Inter-plant species competition: in this simple schematic we see a few types of abiotic resources species must compete for. -light, water, and the main missing factor is nutrients. Mention competition, complementarity, facilitation Soil Water

Carbon Allocation A main factor determining plant adaptive strategy is carbon allocation or how plants chose to partion the CO2 fixed from the atmosphere. Options include shoot growth, root growth, reproduction, defense, mycorrhizae etc. In figure a which species is most likely to have a more developed root system??

Growth Efficiency (Gst-limited) HW HW 5 HW 5

Growth Efficiency (Gst-limited) Hypothesis: hydraulic limitation on photosynthesis and the amount of lai that can be supported are sufficient to account for most observed decreases in tree and stand growth.

Growth Efficiency

Growth Efficiency (Ntr-limited) Hypothesis: areduction in the rate at which nutrients are recycled explains decreased tree and stand growth with age. Go back two slides and ask which mechanism is limiting LAI?

Biogeochemistry & Gap Models

Biome-BGC

Forest-BGC

If you own forest land, you are taxed based on this. Used to be based on standing volume Champion and International cut down all their trees = no taxes Based on fundamental principles of tree growth Not a single formal challenge to this Doesn’t require presence of trees Good for land swaps (1:1, 3:1?)

Gap Models Represent the regeneration in a forest based on the ‘gaps’ generated by the mortality of large trees

Individual Based Models

Gap Models Individual-based models of forest growth and succession Simulate the establishment, growth and mortality of each tree in the plot ‘individually’ Overtopped trees are suppressed by canopy dominant trees as a function of light interception

Competition for light Based on Beer’s Law “The taller the glass, the darker the brew, the less light gets through” Simply put, farther down from the top of the canopy means less light for growth i.e. The glass is taller

Difference between transmitted and absorbed

Simple Gap Model Establish Establish Establish Grow Grow Grow Die Die

Gap model interactions Most important factor is shade tolerance Models have been expanded to incorporate other competition effects that are locally important Nutrients Water availability Soil temperature (Phenology)

Example of a scaled up individual-based model (ZELIG)

What can you get from an individual-based model?

Best Known Models JABOWA Botkin, D.B., J.F. Janak, and JR. Wallis. (1972).J. Ecol., 60: 849-872 FORET – the ‘GAP’ model from the JABOWA family of models. Simulates growth and competition for resources, particularly light, on patches of 1/10 Ha Shugart et al. (1977) J. of Eviron. Man. 5:161-179.

JABOWA FOREST III Ngugi et al., Ecol Mod (2011)

Hybrid Models

3-PG Acronym Physiological Processes Predicting Growth Simple, process-based model to predict growth and development of even-aged stands. Uses basic mean-monthly climatic data, and simple site factors and soil descriptors. Runs on monthly time step. Parameterized using stand-level data. Deterministic

3-PG Flow Chart

Main Components of 3-PG Production of biomass – Based on environmental modification of light use efficiency and constant ratio of NPP to GPP. Biomass partitioning – Affected by growing conditions and tree size. Stem morality – Based on self-thinning rule. Soil water balance – A single soil layer model with evapo-transpiration determined from Penman-Monteith equation. Stand properties – Determined from biomass pools and assumptions about specific leaf area, branch+bark fraction, and wood density.

Environmental constraints on photosynthesis for Douglas-fir vary seasonally in the Pacific NW, U.S.A. soil water evaporative demand suboptimal temperature Frost limitations Autumn Summer Winter Spring

3-PG Uses Stand dynamics for single age, monoculture stands of mostly evergreen trees Generates: foliage (Leaf Area Index), woody tissue and root biomass, conventional stand attributes (volume, BA, stocking), soil water content and water usage.

(1976 - 2006)

Predicted stressed (red) and improved areas (green) since 1950-75 period

StandCarb Gap Model Multi species Has neighboring effects Can mimic different types of Disturbance Can model succession

StandCarb Spatially explicit interactive cell structure, multiple species, allows for various disturbances. StandCarb Harmon and Moreno 2009

StandCarb Limitations: Much slower to run than BiomeBGC Impractical over large landscapes. Harder to use real data over large areas or long times. Not a lot of documentation Hard to learn how to use correctly No nutrient cycling

Ecosystem Deomgraphic (ED) Model