Paper 1

The first deliverable is a paper documenting biomass as a function of landscape metrics.

• A conceptual model of topographic water subsidy
  • Considered in terms of the 3 zone model.
  • Use SAGA to generate the relative slope positions and standardized heights of hillslopes as a way to interpret the 3-zone model.
    
    Figure: Distribution of mean aboveground C (mAGC kg / 0.1 ha^-1) by (A) elevation above mean sea level (m amsl) and (B) aspect of exposure (degrees). First, regardless of elevation the mean distribution of biomass is between ~200 and 800 kg. Biomass decreases in each catchment at higher elevation because of the topographic position. Second, the variation in biomass C by aspect is least pronounced in Betasso, the lowest elevation catchment, and most pronounced in the Como Creek catchment which is the highest elevation site. The variation suggests the impact of temperature limitation on the highest elevation sites where east aspects (~90 degrees) receive the earliest sunlight in the day and warm up the fastest, while west and northwest aspects (225 - 270 degrees) have the least biomass because of their cooler temperatures.
    
    
• Water table is defined by linear head gradient constrained by stream water surfacing at lower elevation end and ground water deposition at upper end.
• Looking for topographic areas where local land surface, e.g. slope and profile curvature approach the linear ground water surface
  
  Figure: Each panel reflects a different topographic variable. (A) General Curvature is the sum of the Profile (vertical) and Planiform (contour) curvatures where negative values are convergent hillslope positions and positive values are divergent positions. For all sites, increasingly divergent positions resulted in a decline in total C. (B) Normalized hillslope heights are the range of height above channel based on the respective catchment area from a specific terrain point (Bohner and Selige 2006, Dietrich and Bohner XXXX) with values ranging from 0 = valley bottom or stream channel position to 1 = ridge or peak position. There is a continuous decline in total C as hillslope position increases from the channel level up to the ridgelines. (C) Topographic Wetness Index calculated using the TOPMODEL (XXXX) framework. The strongest response to increasing wetness is in the lowest elevation site which is also the driest, the weakest response is in the highest elevation site, which is the wettest. (D) Topographic Position Index (XXXX) calculated using a 100 meter moving window and inverse distance weighting. Similar to the Normalized Height function there is a continuous decline in C from the valley bottoms to the ridge lines. (E) The slope of the terrain in units of degrees. There is no significant trend in variation of C with Slope until ~25 degrees, then there is a decline in C. (F) Catchment Area calculated with a deterministic infinity function (Tarboton 1997). Increasing the catchment area (inversely related to hillslope position, e.g. panels B and D) results in increasing C. The strongest response is seen in the lowest elevation site and the weakest response in the highest elevation site. Also, note the similarity of panel (F) to panel (C) above, suggesting that catchment area has a signfiicantly greater role in influencing C than does slope in the TWI equation. 
  
  
• Topographic Wetness Index uses catchment area and slope which is a good start, but is not sufficient for explaining ground water subsidy.
  • Added curvature metrics to the derivation of TWI

Paper 2

The second deliverable is a paper that looks at the rate of biomass accretion over time. 

• Does vegetation structure reflect topographic/geological structure?
  • Biomass peaks on toe slopes
  • C_13 data suggest trees in this location do not experience water stress (Ref.)
• How does vegetation structure reflect topograhic/geologic structure?
• What evidence is there that geologic structure results in ground water subsidy?
  • O_18 and O_2 indicate that forest in the upper elevation of Boulder Creek CZO sites are using a deep water source recharged by snow melt 
    • Source is deeper than soil moisture
  • Mid-elevation sites in Boulder Creek CZO also show strong isotopic evidence of vegetation accessing snowmelt stored in the deep subsurface
    • LiDAR derived biomass reflects changes in geological structure.
      
      

References

BÖHNER, J. & T. SELIGE (2006): Spatial prediction of soil attributes using terrain analysis and climate regionalisation. – – In: BÖHNER, J. MCCLOY K.R. & J. STROBL (Eds.): Göttinger Geographische Abhandlungen 115: 13-28, 118-120.