Biomass production from grassland - Supply [WIKIAlps

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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><sub><font inherit/inherit;;black;;inherit>mean</font></sub><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 ****Season****Start**** 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>

{{:en:biomass_grassland_supply.jpg?nolink&500x1000}}

{{:en:test_legens.jpg?nolink&500x297}}

__<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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