Description:
Ellenberg N values estimate the position along a productivity/macro-nutient availability gradient at which a species reaches peak abundance. The Ellenberg N Index consists of allocating a N score to each plant species, so that the overall mean score for the community lies on a scale of nutrient poor (1) to nutrient rich (10)Calculating mean values for sampled vegetation allows spatial or temporal changes in productivity to be inferred. Many calibration studies support the reliability of these values in signal detection, but attributing change to a specific cause is difficult because the N values integrate a range of effects.
Previous experience:
There is an extensive published literature on the application Ellenberg N values in Briatin and Europe. These include:
- Quantification of vegetation change and inferring shifts in productivity or/and macro-nutrient availability; Smart (2000), Ejrnaes et al (2003), Lameire et al (2000).
- Correlative studies linking vegetation change and N deposition; Pitcairn et al (2002), Diekmann & Dupre (1997; Falkengren-Grerup 1996; van Dobben, 1992). The index has been used at a local scale (e.g. Pitcairn et al. 2002;) and also at a national scale (Haines-Young et al., 2000).
- Calibration studies that validate N values or modify them for specific regions; Schaffers & Sykora (2000), Hill et al (2000), Thompson et al (1993), Diekmann (1995), Ertsen et al (1998).
Suitability to indicate atmospheric concentrations:
No inherent discriminatory power between different N forms, unsuited.
Suitability to indicate atmospheric depositions:
No inherent discriminatory power to quantify deposition. However, there is clear evidence of a relationship between the Ellenberg index and atmospheric N deposition (See Pitcairn et al, 2002).
Suitability to indicate environmental impacts:
By definition the method represents the status of a plant community, with differences attributed to the impact of varying N availability. It is therefore well suited to indicate N deposition impacts. The corresponding limitation is that the method cannot descriminate between the different drivers of eutrophication.. The method has been used to indicate species change in relation to enhanced N inputs from both fertilisation and atmospheric deposition.
Sensitivity to other factors:
Spatial and temporal change in mean N values can be influenced by a range of additional factors. These include; nutrient limitation, pH, disturbance, climate, light levels, presence of responsive species, frequency distribution of values within plots and within local species pools.
Timescale:
The method reflects the time constant of colonization and species change. While differences as small as 3 years have been examined, in general the method reflects the responses occurring over several decades.
Limitations:
The method is applicable to 1791 taxa in GB flora, which includes 239 introduced species, all native, non-critical taxa. Indicator values for bryophytes and lichens can be obtained from Siebel (1993) and Wirth (1991), respectively.
The method has a fine spatial resolution, depending on the averaging scale of the plant community being considered. For forest ground flora the approach has been applied across transects of <100 m.
Expertise in field:
The method can be applied by agency staff skilled in botanical identification. The simplicity depends on species diversity and/or survey of cover vs presence/absence. There is no requirement for plant sample collection and transport.
Expertise in laboratory:
Mean Ellenberg scores (frequency weighted or unweighted) are extremely simple to compute.Analyses of spatial or temporal change need to take account of standard statistical issues not unique to the manipulation of N values.
Cost (per unit sample): £unknown
Cost Comment: The method is difficult to cost because it is dependant on the biodiversity of the site. Species identification and recording can be very time consuming in species rich sites.e.g. for typical mixed woodland ground flora.
Robustness: 
