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Biomass production from grassland - Supply

General description

The approach presented here is comprised of two main parts. The first part (steps 1 and 2) assesses the optimal yield (ES potential) according to the length of the growing season, the respective growth functions and the specific land use types. The second part refines the biomass productivity according to region-specific precipitation patterns (steps 3 to 7) and local small-scale topographic conditions (steps 8 to 10), in order to provide more reliable local yield estimates (ES status). Flowchart below describes in detail the calculation procedure to derive the Supply (DM kg/ha) for each local administrative units (LAU2) of the Alpine Space.

Input data

  • DEM (slope, aspect)
  • Precipitation (in mm)
  • Climate Data (number of Vegetation days, start of growing season)
  • Land use types (intensively used, moderately used and extensively used grassland, Natural Grassland (CLC)…)

Calculation processes

<font 14px/inherit;;black;;inherit>(1) Calculate Vegetation Days (days with T</font><font inherit/inherit;;black;;inherit>mean</font><font inherit/inherit;;black;;inherit>≥ 5 C)</font>

<font 14px/inherit;;inherit;;inherit>The approach is based on the assumption that biomass production does not start if the daily average temperature is below 5°C, hence the year is divided into a growing season and a dormant season.</font>

<font 14px/inherit;;inherit;;inherit>(2) Calculate Optimal Yield</font>

<font 14px/inherit;;inherit;;inherit>This is done according to the productivity type of the grassland types of your study area. In the table below you find the factors we used for the Alpine-wide approach according to the dataset we had at our disposal.</font>

<font 14px/inherit;;inherit;;inherit>Land use type</font>

<font 14px/inherit;;inherit;;inherit>Productivity type</font>

<font 14px/inherit;;inherit;;inherit>Permanent Grassland</font>

<font 14px/inherit;;inherit;;inherit>4</font>

<font 14px/inherit;;inherit;;inherit>Natural Grassland (CLC)</font>

<font 14px/inherit;;inherit;;inherit>3</font>

<font 14px/inherit;;inherit;;inherit>Natural Grassland (HRL)</font>

<font 14px/inherit;;inherit;;inherit>3</font>

<font 14px/inherit;;inherit;;inherit>Bogs</font>

<font 14px/inherit;;inherit;;inherit>2</font>

<font 14px/inherit;;inherit;;inherit>Dwarf bushes</font>

<font 14px/inherit;;inherit;;inherit>2</font>

<font 14px/inherit;;inherit;;inherit>Larch meadows</font>

<font 14px/inherit;;inherit;;inherit>1</font>

<font 14px/inherit;;inherit;;inherit>Alpine grasses</font>

<font 14px/inherit;;inherit;;inherit>1</font>

<font 14px/inherit;;inherit;;inherit>The optimal yield is then derived using the following functions, where x is the number of vegetation days.</font>

<font 14px/inherit;;inherit;;inherit>Forage type</font>

<font 14px/inherit;;inherit;;inherit>Yield function (dt/ha)</font>

<font 14px/inherit;;inherit;;inherit>4</font>

<font 14px/inherit;;inherit;;inherit>y=(0.0021*(x²))-(0.419*x)+93.774</font>

<font 14px/inherit;;inherit;;inherit>3</font>

<font 14px/inherit;;inherit;;inherit>y=(0.0007*(x²))-(0.1513*x)+26.585</font>

<font 14px/inherit;;inherit;;inherit>2</font>

<font 14px/inherit;;inherit;;inherit>y=(0.0006*(x²))-(0.1613*x)+25.321</font>

<font 14px/inherit;;inherit;;inherit>1</font>

<font 14px/inherit;;inherit;;inherit>y=(-0.00007*(x²))+(0.1084*x)-4.7726</font>

<font 9.0pt/inherit;;inherit;;inherit>(Yield calculations Source: Egger, G., et al.</font> <font 9.0pt/inherit;;inherit;;inherit>(2004). GIS-gestützte Ertragsmodellierung zur Optimierung des Weidemanagements auf Almweiden.</font> <font 9.0pt/inherit;;inherit;;inherit>Irdning, Irdning: BAL. Modified by Jaeger and Tasser)</font>

<font 14px/inherit;;inherit;;inherit>(5) Indicate Growing SeasonStart and End in days of the year (DOY)</font><font 14px/inherit;;inherit;;inherit>If no specific data is available for your test region, you can use a DEM-based method (i.e. Krautzer et. al. 2012) to approximate the start of the growing-seaso</font>n.

  • <font 14px/inherit;;inherit;;inherit>(3) Calculate start of growing season based on DEM (DOY)</font>. <font 14px/inherit;;inherit;;inherit>Here the example function we used for the entire Alpine space:</font>[(0.0689*DEM)+0.4444]
  • <font 14px/inherit;;inherit;;inherit>(4) Calculate end of growing season. </font><font 14px/inherit;;inherit;;inherit>Start of Growing Season + Vegetation Days (in DOY)</font>.

<font 14px/inherit;;inherit;;inherit>(6) Calculate average precipitation needed during growing season</font>

  • <font 14px/inherit;;inherit;;inherit>Sum the average precipitation data for the growing season (in mm).</font>

<font 14px/inherit;;inherit;;inherit>(7) Optimizing (reducing) regional yield by applying a correction factor if precipitation during the growing season is below a certain threshold</font>

  • <font 14px/inherit;;inherit;;inherit>precipitation sums (in mm) in vegetation season are lower than (Vegetation days * 3.33) then the regional yield (unit: dt) ⇒ regional yield =</font>[<font 14px/inherit;;inherit;;inherit>(Precipitation in growing season (in mm) / Vegetation days * 3.33) * optimal yield</font>]
  • <font 14px/inherit;;inherit;;inherit>else use optimal yield.</font>

<font 14px/inherit;;inherit;;inherit>(8) Calculate slope yield</font>

  • <font 14px/inherit;;inherit;;inherit>Calculate the yield reduction caused by slope because of radiation reduction</font>* <font 14px/inherit;;inherit;;inherit>the slope is > 10, then use the following formula [(1- (Slope/ 100)) * regional yield], else keep the regional yield value.</font>

<font 14px/inherit;;inherit;;inherit>(9) Reclassify the “Aspect raster” to “Aspect modified” in preparation of step (10)</font>

  • <font 14px/inherit;;inherit;;inherit>For the purposes of the model, simplified aspect values are required that account for losses caused by radiation decrease due to unfavorable exposition. Only values between 0° (north) – 180° (south) are valid inputs, where 90° refers to both east and west exposition. The reduction factors range between 0% and 20%, respectively for southerly and northerly facing slopes. We applied a linear distribution of the reduction factor from south to north.</font>* <font 14px/inherit;;inherit;;inherit>Hence, first aspect values have to be reclassified and inverted using the following form</font>ula: <font 14px/inherit;;inherit;;inherit>aspect_recl =</font><font 14px/inherit;;inherit;;inherit>180 - (180 - (Aspect - 180)</font>
  • <font 14px/inherit;;inherit;;inherit>And second, this raster has to be multiplied with its specific reduction factor. Aspect modified = aspect_recl * reduction factor</font>

<font 14px/inherit;;inherit;;inherit>The result is the layer „Aspect modified“ with cell values ranging from 0 (for southern faced slopes) up to 20 (for northern faced slopes).</font>

<font 14px/inherit;;inherit;;inherit>(10) Calculate local yield</font>

  • <font 14px/inherit;;inherit;;inherit>In the final step local yield is calculated without the losses caused by exposition:</font>* <font 14px/inherit;;inherit;;inherit>the Annual Precipitation ⇐ 1500 mm then use the following formula: [(100 - (Aspect modified / 2)) / 100) * Slope Yield] else this other formula [((100 – Aspect modified) / 100) * Slope Yield)].</font>



<font 12px/inherit;;inherit;;inherit>References:</font>

<font 12px/inherit;;inherit;;inherit>Krautzer, Bernhard, Christian Uhlig, and Helmut Wittmann. “Restoration of Arctic–Alpine Ecosystems.”Restoration Ecology: The New Frontier 189 (2012)</font>

<font 12px/inherit;;inherit;;inherit>Egger, G., et al. (2004). GIS-gestützte Ertragsmodellierung zur Optimierung des Weidemanagements auf Almweiden.Irdning, Irdning: BAL. modified by Jaeger and Tasser et al.</font>

<font 12px/inherit;;inherit;;inherit>Urthaler, K. (2016). Modellierung und Validierung des landwirtschaftlichen Ertrages der Grünlandflächen Südtirols. Institut für Ökologie. Innsbruck, Leopold Franzens Universität. Master of Science</font>

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