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Risk Assessment Methodologies of Soil Threats in Europe

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the SOM content, e.g. fertiliser recommendations and consequently methods <strong>of</strong> data collection<br />

are <strong>of</strong>ten not optimized for identify<strong>in</strong>g SOM decl<strong>in</strong>es.<br />

Sampl<strong>in</strong>g schemes differ between countries and even with<strong>in</strong> a country. Several forms <strong>of</strong><br />

sampl<strong>in</strong>g schemes can be dist<strong>in</strong>guished; amongst others:<br />

1. None systematic schemes for characteriz<strong>in</strong>g a soil type;<br />

2. Systematic schemes;<br />

3. Data collected from soil sample analysis for establish<strong>in</strong>g fertilizer recommendations<br />

based on soil test<strong>in</strong>g.<br />

4. <strong>Soil</strong> chronosequences.<br />

The use <strong>of</strong> different monitor<strong>in</strong>g network is extensively revised <strong>in</strong> the ENVASSO project. They<br />

concluded that georeferenced monitor<strong>in</strong>g is currently performed <strong>in</strong> Belgium (Wallonia) and<br />

Poland, but that the use <strong>of</strong> georeferenced soil pr<strong>of</strong>iles is not common throughout EU (Jones et<br />

al. 2004, 2005). Grid methods are much more common and are currently used and/or developed<br />

<strong>in</strong> Austria, France, Denmark, United K<strong>in</strong>gdom (England, Wales, and Scotland), Northern<br />

Ireland, Ireland, Germany, Hungary and Poland). These are national grids which were<br />

established for national soil surveys. Grids can be complete systematic or heterogeneous and<br />

based on a spatially irregular selection <strong>of</strong> sampl<strong>in</strong>g locations us<strong>in</strong>g expert judgement (Morvan<br />

et al., 2008). The differences <strong>in</strong> scale lead to differences <strong>in</strong> resolution. With<strong>in</strong> the ENVASSO<br />

project 65 monitor<strong>in</strong>g networks were identified with <strong>in</strong> total 36104 locations where soil quality<br />

is measured. Of these 33334 locations provide <strong>in</strong>formation on SOM.<br />

Table 5.1. Scales reported <strong>in</strong> questionnaires on sampl<strong>in</strong>g schemes <strong>of</strong> soil.<br />

Country Scale<br />

Belgium (Flanders) 1:1,000,000<br />

Belgium (Wallonia) 1:20,000, 1:25,0000<br />

France 1:250,000 to 1:1,000,000<br />

Greece 1:5,000<br />

Poland 1:10,000<br />

Slovak republic 1:400,000<br />

Slovenia 1:10,000, 1:20,000, 1:25,000<br />

Spa<strong>in</strong> 1:50,000<br />

United K<strong>in</strong>gdom 1:250,000<br />

<strong>Soil</strong> sample analysis for establish<strong>in</strong>g fertiliser recommendations provides large databases on<br />

soil characteristics. These samples are not send <strong>in</strong> by cooperation’s, advisers or farmers for<br />

guidance on the use <strong>of</strong> fertilisers and therefore may be biased. However, they can be used to<br />

detect SOM changes, as e.g. <strong>in</strong> the case <strong>of</strong> The Netherlands (Reijneveld et al, 2009).<br />

<strong>Soil</strong> chronosequences are genetically related suites <strong>of</strong> soils evolved under similar conditions <strong>of</strong><br />

vegetation, topography, and climate (Harden, 1982). They translate spatial differences between<br />

soils <strong>in</strong>to temporal differences (Huggett, 1998). <strong>Soil</strong> chronosequences (space for time<br />

substitutions with confound<strong>in</strong>g <strong>of</strong> space and time) are <strong>in</strong>struments <strong>of</strong> pedological <strong>in</strong>vestigations.<br />

They have been used to determ<strong>in</strong>e carbon sequestration is soil and biomass follow<strong>in</strong>g<br />

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