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3.1.        Deriving the Broad European Agricultural Regions (BEARs)

To generate homogeneous groups of agricultural land use featuring similar farming-related freshwater pressures, existing landscape classifications were combined and associated with the pressure data as described below.

Step 1: Identifying dominant agricultural archetypes

Out of the 15 different Land-system Archetypes of Levers et al. (2018), the twelve agriculture-related archetypes were selected for further processing. Data of these were provided in 3 x 3 km raster-cells and transferred into FEC-level. A total number of 30,540 FECs were identified, for which a specific archetype was prevailing (i.e. ≥50 % FEC coverage), accounting for 32.6% of Europe’s terrestrial area (European Member States in 2012). These dominant agricultural archetypes (separated into crop-related and livestock-related archetypes) formed the basis for the subsequent linkage to the freshwater pressures at FEC-level. FECs without a dominant archetype were not further analysed.


Step 2: Combining dominant agricultural archetypes and major agricultural regions

To determine the dominant agricultural archetypes per major agricultural region, these two landscape classifications were combined. This resulted in a total of 48 combined ‘regionalized archetypes’.

Step 3: Defining pressure-profiles

Using boxplots, pressure-ranges per regionalized archetype were allocated and median values were compared to identify archetypes with similar levels of pressure. These pressure levels were ranked, ranging from 1 (‘very low’) to 4 (‘high’) according to their medians (Table 1) referring to either existing classifications of pressure intensity for nitrogen surplus (Rega et al., 2019; Figure 7) and pesticides (van Gils et al., 2019; Figure 8), or expert judgement for water abstraction (Figure 9) and floodplain agricultural land use in the floodplain (Figure 10). These rankings of individual pressure-ranges established a ‘pressure-profile’ for each regionalized archetype. Note that pesticide pressure levels were not assigned to livestock archetypes and abstraction pressure levels were not assigned to low intensity grassland and fallow farmland archetypes, as these pressures were deemed irrelevant for these archetypes.

Step 4: Merging regionalized archetypes with similar pressure-profiles

To reduce the total number of types, the regional archetypes showing similar pressure-profiles were merged. In this step, the cropland-archetypes of high and medium management intensity (using the classification of Levers et al., 2018) were combined into the category of ‘intensive cropland’ featuring substantial areas with nitrogen application rates > 50 kg ha-1 a-1 and higher amounts of harvested biomass. The cropland-archetypes of low management intensity (nitrogen application rates < 50 kg
ha-1 a-1, lower amounts of harvested biomass) were categorised as ‘extensive cropland’. Pressure-profiles of intensive and extensive livestock-archetypes did not differ between regions except for the Western region, for which a distinction between ‘intensive livestock’ and ‘extensive livestock’ was made. For all other regions a single livestock category was devised. Archetypes belonging to different major agricultural regions were generally not merged except for ‘fallow farmland’ and ‘low-intensity grassland’, which were combined across all areas.

Step 5: Delineating the BEARs

The merging of regionalized archetypes done in the previous step resulted in 15 Broad European Agricultural Regions (BEARs), representing large-scale landscape units of similar agricultural land use and farming-related pressures on freshwater ecosystems.

Step 6: Calculating the pressure index

To summarize the farming-related pressures exerted on the freshwater ecosystems across Europe, a composite multi-pressure index was calculated for each BEAR by summing up the numerical values of all individual pressure levels divided by the number of pressures considered for the respective BEAR.

Table 1: Pressure indicators and levels ranked into four classes of pressure intensity

 

Pressure indicator

(All values relate to entire FEC area (including ≥50% agricultural area). It is not based on utilised agricultural area.)

Unit

Very low (1)

Low (2)

Medium (3)

High (4)

Nitrogen surplus

kg/ha/year

≤ 20

> 20 - 30

> 30 - 40

> 40

Potentially Affected Fraction of species by pesticides

--

≤ 0.20

> 0.20 -0.35

> 0.35 - 0.50

> 0.50

Water abstracted for irrigation

m³/ha/year

≤ 2,000

> 2,000 – 4,500

> 4,500 – 8,000

> 8,000

Agricultural land use in the floodplain

%

≤ 50

> 50 -65

> 65 - 80

> 80

 

 

Figure 7: Nitrogen surplus ranges identified for the different Broad European Agricultural regions (BEARs)

Large cow = Intensive livestock farming; Small cow = Extensive livestock farming; Medium-sized cow = Livestock farming (incl. intensive and extensive); Three ears = Intensive cropland; One ear = Extensive cropland; Lemon = Large-scale permanent cropland; Grass = Extensive grassland and fallow farmland; Across = Defined across all major agricultural regions.
Pressure ranking: Red band = High; Yellow band = Medium; Green band = Low; Blue band = Very low.

Median values for each BEAR are given in green numbers above each plot. Extreme values (=outliers) are not plotted.

 

Figure 8: Pesticides msPAF ranges identified for the different Broad European Agricultural regions (BEARs). See Figure 7 for for further details.


Figure 9: Water abstraction ranges identified for the different Broad European Agricultural regions (BEARs). See Figure 7 for details.

Figure 10: Agricultural land use in the floodplain ranges identified for the different Broad European Agricultural regions (BEARs). See Figure 7 for details.

 

Previous comments

  • farrereg (Regis Farret) 14 Sep 2021 17:18:08

    coucou

  • silvaagu (Agueda Silva) 14 Sep 2021 18:55:37

    The analysis refers in step 3 “expert judgement for water abstraction”, which should be avoided as there is no real knowledge of each Member State.

    Step 6 does not refer the criteria used to establish thresholds of Table 1: Pressure indicators and levels ranked into four classes of pressure intensity.

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