Journal (Accounting for canopy drip effects of spatiotemporal trends of the concentration of N in mosses, astompheric N depositions and critical load exceedances : a case study from North-Western Germany)

JOURNAL
Accounting for  canopy drip effects of spatiotemporal trends of the concentration of N in mosses, astompheric N depositions and critical load exceedances : a case study from North-Western Germany.

Abstract
Background: Atmospheric nitrogen (N) deposition into terrestrial ecosystems is frequently considered as a threat to phyto-diversity. In previous investigations, the atmospheric N inputs enriched in mosses were recorded in 2004 as part of a regional investigation at 54 locations in north-west Germany and in 2005 at 726 locations across the whole country. This article deals with a study conducted in 2012 comparing N concentrations in mosses sampled within 30 forest stands and in 26 adjacent open fields in north-west Germany. The N concentration in mosses were determined and, by the use of a regression model, converted to N atmospheric deposition values. These deposition estimations enabled to calculate N critical load exceedances.
Results: Compared to the average N concentration in mosses sampled in open fields 2012 (7.4 kg/ha*a), the
average N concentrations in mosses within adjacent forests were almost four times higher (26.6 kg/ha*a), and the maximum within the stands accounted for approximately 56 kg/ha*a. Compared to 2005, there was a slight decline of the average N deposition by 2.4 kg/ha*a in open fields. However, the average N concentrations in mosses within forests stands in 2012 remained nearly the same since 2004 (29 kg/ha*a). The atmospheric N deposition as estimated from the N concentration in mosses ranged between the minimum and maximum N critical load at 71% of the 56 sites investigated. At 14% of the sites, the N deposition was close to the maximum N critical load value which was exceeded in 11%.
Conclusions: The study at hand revealed statistically significant differences between N concentrations measured in mosses sampled within forests and in open fields. The presented findings should be accounted for both modelling and mapping atmospheric N deposition into terrestrial ecosystems on the one hand and related estimations of N critical load exceedances on the other hand.

Background
Substances emitted into the atmosphere, such as nitrogen (N) and metals, come down to earth by wet, occult (i.e. cloud water) and dry atmospheric deposition. Then, in terrestrial ecosystems, they can be accumulated in soils and plants. The partitioning between dry, occult and wet deposition depends on atmospheric gas and aerosol N concentrations, meteorological conditions as well as land use and vegetation characteristics, e.g. surface roughness, canopy leaf surface area and vegetation wetness. Unlike wet deposition, which is widely monitored in regional networks of wet-only or bulk precipitation
collectors, measurements of dry N fluxes have largely remained experimental and limited to few research
sites, lasting for a few days to a few months only. Dry deposition monitoring networks across areas of
large spatial extent remain, up to now, impracticable. A comparison of results calculated by four dry deposition models for 55 European sites revealed that the differences between models reached a factor of 2 to 3 and exceeded the differences between monitoring sites.
Next to atmospheric deposition measurements and models of atmospheric compounds, environmental analyses concentrated on biomonitoring activities.


Results and discussion
Over several years, mosses collect and accumulate dry, occult and wet atmospheric deposition. Moss surveys can reveal both differences in N concentrations across large distances and within small-scale areas (e.g. sitespecific differences due to canopy drip effects). The study at hand revealed significant differences between N concentrations measured in mosses sampled within forests and on open fields. Due to its large surface, its height and its roughness, the total N deposition in forests is systematically higher than in other ecosystems also confirmed by the results of this study at hand. However, the dimension of this filtering effect depends on the air concentration and the meteorological variables such as wind speed and humidity. Furthermore, interactive effects are complex and different ecosystems react with varying sensitivity. The increased N input in the former years enhanced the N saturation of forest ecosystems additionally to an increased soil acidification. While N was the limiting factor for forest ecosystems in the past, it is nowadays a potential hazard to the vitality of tree populations and the total ecosystem functioning. The results of this study showed that there are, in part, exceedances of the maximum critical N input value. According to, short-time exceedances can be compensated by ecosystems. Biological responses to high atmospheric N deposition as for instance ecosystem stability and biodiversity are often delayed. Due to the multi-factorial relationship between the N input and the ecological reactions in forests, the dose–response relationship is very complex. High N inputs into forest ecosystems lead to an increased amount of N in leaves and needles resulting in an unbalanced nutrition. In the long term, a permanent exceedance of N inputs in combination with other factors such as pest infestations, droughts or frost periods can lead to a reduced vitality of forest ecosystems, changes in rather endemic species composition and to a limited self-regulation.


Canopy drip effects
The Wilcoxon signed-rank test carried out to compare the median values of the different sampling site categories (open field, forest stand) showed that the respective N concentrations at open fields are significantly lower than at sites directly within the forest stands (p = 0.000, Wilcoxon test).
The N concentrations in mosses sampled in forest stands (2.2%) were in average twice as high as in mosses
collected in open fields (1.1%). In addition, the N concentrations (given in %) were transferred into atmospheric N deposition values (in kg/ha*a) following. Accordingly, the minimum atmospheric N deposition
amounted for 4.6 kg/ha*a (open field), the maximum for55.9 kg/ha*a (forest stand). The average value of theopen sites was 7.4 kg/ha*a, the average of forest stands26.6 kg/ha*a.


Estimating atmospheric N deposition from N concentrations in mosses and calculation of critical load
exceedances
The comparison of N atmospheric depositions estimatedfrom N concentration in mosses sampled in 2012 withthe critical load values taken from  show that theN atmospheric deposition was at most sites investigated
between the minimum and maximum critical load value(Tables 2 and 3): the atmospheric N deposition as estimated from the N concentration in mosses ranged between the minimum and maximum critical load at
48 out of 54 sampling sites in total (89%); at 8 of these 48 sites (approximately 17%), the corresponding N deposition was close to the maximum critical load value. The maximum critical load was exceeded at 6 of 54 sites investigated (11%). Comparing deposition data estimated from measured N concentrations in mosses and such modelled by  reveals higher similarities for forest stands than for open fields (median N deposition estimated from moss concentrations for forest stands, 25.7 kg/ha*a; median N deposition estimated from moss concentrations for open fields, 7 kg/ha*a; median modelled deposition for forests without  regards to adjacent open fields, 37 kg/ha*a) . This was corroborated by the results of the correlation analysis, yielding a higher significant association between deposition data derived from moss concentrations within forest stands
and modelled deposition data (Spearman rank correlation, 0.47; p < 0.05) compared to open fields. Here, the correlation between N deposition estimated from N concentrations in mosses was lower and not significant (Spearman rank correlation, 0.37; p > 0.05). The shown differences could be explained by the fact that the critical loads were calculated with regard to forests as receptors but not for open fields .









Conclusions
The presented findings should be accounted for future monitoring activities dealing with atmospheric deposition of N in terrestrial ecosystems. Due to the results of this study, it seems important to differentiate more precisely and strictly between open fields and forest stands to ensure the comparability of the N concentration measurements over time, to avoid an over- and an underestimation of N concentrations and, thus, to yield data for validating the modelling and mapping of atmospheric N deposition and related critical loads. Thus, it should be mandatory to describe the sampling sites exactly sampled. In order to enhance the comparability to the values determined in the European moss monitoring in 2005 and in a regional study conducted in 2004 , former sites were re-sampled wherever possible. According to sampling points (66%)
located within the study area are assigned to be coniferous forests, followed by non-irrigated arable lands
(21%), by mixed forests (7%), transitional woodlandshrubs (4%) and by lands principally occupied by agriculture, with significant areas of natural vegetation (2%). Forty-six sampling points out of 56 in total (82%) are assigned to ecoregion 42 followed by ecoregion 43 (11%) and ecoregion 47 (7%).


Methods
Study area and sampling points In accordance with the investigation purposes, a study area with an overall size of 110 km × 92 km was chosen in north-west Germany (Figure 5). As calculated from the 2006 Corine Land cover map, the study area is primarily dominated by ‘non-irrigated arable land’ (approximately 82%) followed by ‘pastures’ (approximately 12%), by ‘complex cultivation’ (approximately 2%), by ‘coniferous forest’ (approximately 1%) and by ‘discontinuous urban fabric’ (approximately 1%) . Along with very high densities of animal farming, high atmospheric N deposition can be expected. According to the ecological land classification of Germany , the study area is mainly covered by ecoregions 42 (Niedersächsische Geest) (approximately 78%), 43 (Niedersächsische Geest und LüneburgerHeide) (approximately 10%) and 47 (Niedersächsische Börden) (approximately 8%). In Table 5, ecological characteristics of these ecoregions of Lower Saxony and percentages of ecological land classes in Germany and in the study area are compiled.


Moss sampling and chemical analyses
Sampling, conducted from September to October in 2012, and chemical analyses followed the European experimental protocol derived from the Scandinavian recommendations and continuously improved since then. Within the study area, both sites affected by canopy drip effects within forests with at most 2 m distance to the tree trunk and from nearby sites without any influence of canopy drip with a distance of at least 10 m from the tree trunk were chosen. The sampling locations were at least 100 m far away from streets and single houses, 300 m from settlements and 1,000 m from industrial installations. According to the guidelines, Pleurozium schreberi was sampled in first priority. Where Pleurozium schreberi was absent, Scleropodium purum was collected (Additional file 2: Table S2). In total, there were 30 sampling sites classified as being affected by canopy drip. Twenty-six moss samplings could be carried out at sites
without any influence of canopy drip.




Temporal analyses of N concentrations in mosses
The temporal analyses of N concentrations in mosses sampled in 2012 (this investigation), 2005 and 2004
[7,14] rely on the comparison of respective sites with a distance smaller than 5 km from another. In 2012, the sampling took place, both, at sites affected by canopy drip effects within forests and at nearby sites without any influence of canopy drip, thus two N concentration values per site were available for most sites. In the regional investigation conducted in 2004, moss samplings took place within forest stands . In the moss sampling campaign 2005, however, sampling took place on open fields. In this study, the N concentration
values of the study conducted in 2004 were compared to the N concentration in mosses within forest
stands determined in 2012 whereas the N concentration values of mosses on open fields sampled in 2012 were compared to the N concentrations determined in the moss campaign 2005. Subsequently, a Wilcoxon signedrank test was carried out to compare both the median values of the N concentrations at open fields 2005 and 2012 and the median values of the N concentrations in forest stands in 2004 and 2012.


Classification and regression trees analysis
Correlations between N concentrations in mosses (%) and site-specific and regional conditions potentially influencing factors were investigated by the Classification and Regression Trees (CART). In this study, the following describing variables taken from Additional file 2: Table S2 (Supplement) were integrated as potential predictors for N concentrations (target variable) into the CART model: sampling point (open field, forest stand); moss species (P. schreberi, S. purum); tree height; distances to roads, interstate roads, highways, settlements, industry, animal housings and agriculturally used areas; percentage proportion of the agrarian density in a radius of 5 km2 around the sampling sites derived from the Corine database ; percentage proportion of urban land uses around 5 km of the sampling sites also derived from Corine . CART divides iteratively heterogeneous data sets into more homogeneous classes regarding the target
value, which is the N concentration in mosses. In this way, classes (subgroups or nodes) are produced by a series of ‘if-then’ splits in order to maximise the homogeneity of the target variable step by step. Provided the target variable is metrically scaled (as holds true in this investigation), the least squared deviation is used as a measure of impurity. Such corresponds to the difference of the within-node variance between a respective node and the two resulting sub-nodes. The latter is adjusted for the different number of cases within each sub-node. Possible splits are tested for all variables until the best possible homogeneity is reached
to choose the respective split variable as a predictor. Using CART, both the target variable and the predictor
values may be of categorical, ordinal or metric scale, interval or ratio.








Estimating atmospheric N deposition from N concentrations in mosses and calculation of critical load exceedances
In order to assess whether the atmospheric N depositions as estimated from N concentration values in mosses potentially exceed ecotoxicologically critical effect levels, critical load values given were incorporated into the statistical analyses. To this end, the N critical load values given in ionic equivalents (eq/ha*a) were converted into kg/ha*a according . Critical loads are given as value ranges (minimum and maximum critical value) due to ecosystem-specific responses to N inputs, classified according to European Nature Information System with a spatial resolution of 1 km2 × 1 km2. The corresponding critical load map was made available in terms of point geometries covering mainly forests (96%) and other pristine areas in Germany . In this study, only those moss sampling sites within a distance of 2 km to the closest point with critical loads information were chosen for the analyses, hence one site (grid cell 21, see Figure 6) was not considered.


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