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Plant phenological dataset collected at 42 sites across the mainland of Finland and covering the years 1997–2017 is presented and analysed for temporal trends. The dataset of n = 16,257 observations represents eleven plant species and fifteen phenological stages and results in forty different variables, i.e. phenophases. Trend analysis was carried out for n = 808 phenological time-series that contained at least 10 observations over the 21-year study period. A clear signal of advancing spring and early-summer phenology was detected, 3.4 days decade−1, demonstrated by a high proportion of negative trends for phenophases occurring in April through June. Latitudinal correlation indicated stronger signal of spring and early-summer phenology towards the northern part of the study region. The autumn signal was less consistent and showed larger within-site variations than those observed in other seasons. More than 60% of the dates based on single tree/monitoring square were exactly the same as the averages from multiple trees/monitoring squares within the site. In particular, the reliability of data on autumn phenology was increased by multiple observations per site. The network is no longer active. Electronic supplementary material The online version of this article (10.1007/s00484-020-01961-6) contains supplementary material, which is available to authorized users.

The use of transplanted moss (Pleurozium schreberi) in active biomonitoring of traffic-related emissions of Pd, Pt, and Rh was studied. Moss mats were transplanted to three locations along highway E75 (in Oulu, Finland) at three different distances from the highway. Five samples were collected from a background site after the same exposure period. Mass fractions of Pd, Pt, and Rh as well as mass fractions of 18 other elements were determined in these samples. The results indicated that P. schreberi is well suited for active biomonitoring of Pd, Pt, and Rh. Mass fractions above the background values were observed in the samples exposed to traffic-related emissions. When the results were compared with those of the other elements, high correlations of Pd, Pt, and Rh with commonly traffic-related elements (e.g., Cu, Ni, Sb, Zn, etc.) were found. It was also found that the amounts of Pd, Pt, and Rh in moss samples decreased when the distance to the highway increased. This trend gives evidence for the suitability of P. schreberi for active biomonitoring of Pd, Pt, and Rh. Furthermore, it can be concluded that the mass fractions determined in this study provide valuable evidence about the current state of Pd, Pt, and Rh emissions in Oulu, Finland.

Mosses take up nitrogen (N) mainly from precipitation through their surfaces, which makes them competent bioindicators of N deposition. We found positive relationships between the total N concentration (mossN%) of common terrestrial moss species (feather mosses Pleurozium schreberi and Hylocomium splendens, and a group of Dicranum species) and different forms of N deposition in 11-16 coniferous forests with low N deposition load in Finland. The mosses were collected either inside (Dicranum group) or both inside and outside (feather mosses) the forests. Deposition was monitored in situ as bulk deposition (BD) and stand throughfall (TF) and detected for ammonium (NH4+-N), nitrate (NO3--N), dissolved organic N (DON), and total N (N-tot, kg ha(-1)yr(-1)). N-tot deposition was lower in TF than BD indicating that tree canopies absorbed N from deposition in N limited boreal stands. However, mossN % was higher inside than outside the forests. In regression equations, inorganic N in BD predicted best the mossN% in openings, while DON in TF explained most variation of mossN% in forests. An asymptotic form of mossN% vs. TF N-tot curves in forests and free NH4+-N accumulation in tissues in the southern plots suggested mosses were near the N saturation state already at the N-tot deposition level of 3-5 kg ha(-1) yr(-1). N leachate from ground litterfall apparently also contributed the N supply of mosses. Our study yielded new information on the sensitivity of boreal mosses to low N deposition and their response to different N forms in canopy TF entering moss layer. The equations predicting the N-tot deposition with mossN% showed a good fit both in forest sites and openings, especially in case of P. schreberi. However, the open site mossN% is a preferable predictor of N deposition in monitoring studies to minimize the effect of tree canopies and N leachate from litterfall on the estimates. (C) 2020 Elsevier Ltd. All rights reserved.

Background This paper aims to investigate the correlations between the concentrations of nine heavy metals in moss and atmospheric deposition within ecological land classes covering Europe. Additionally, it is examined to what extent the statistical relations are affected by the land use around the moss sampling sites. Based on moss data collected in 2010/2011 throughout Europe and data on total atmospheric deposition modelled by two chemical transport models (EMEP MSC-E, LOTOS-EUROS), correlation coefficients between concentrations of heavy metals in moss and in modelled atmospheric deposition were specified for spatial subsamples defined by ecological land classes of Europe (ELCE) as a spatial reference system. Linear discriminant analysis (LDA) and logistic regression (LR) were then used to separate moss sampling sites regarding their contribution to the strength of correlation considering the areal percentage of urban, agricultural and forestry land use around the sampling location. After verification LDA models by LR, LDA models were used to transform spatial information on the land use to maps of potential correlation levels, applicable for future network planning in the European Moss Survey. Results Correlations between concentrations of heavy metals in moss and in modelled atmospheric deposition were found to be specific for elements and ELCE units. Land use around the sampling sites mainly influences the correlation level. Small radiuses around the sampling sites examined (5 km) are more relevant for Cd, Cu, Ni, and Zn, while the areal percentage of urban and agricultural land use within large radiuses (75–100 km) is more relevant for As, Cr, Hg, Pb, and V. Most valid LDA models pattern with error rates of

Trends in the timing of spring and autumn phenophases of Betula pubescens were investigated in the southern, middle, and northern boreal zones in Finland. The field observations were carried out at 21 sites in the Finnish National Phenological Network in 1997-2013. The effective temperature sum of the thermal growth period, i.e. the sum of the positive differences between diurnal mean temperatures and 5 °C (ETS1), increased annually on average by 6-7 degree day units. Timing of bud burst remained constant in the southern and middle boreal zones but advanced annually by 0.5 day in the northern boreal zone. The effective temperature sum at bud burst (ETS2) showed no trend in the southern and middle boreal zones, whereas ETS2 increased on average from 20-30 to 50 degree day units in the northern boreal zone, almost to the same level as in the other zones. Increase in ETS2 indicates that the trees did not start their growth in very early spring despite warmer spring temperatures. The timing of leaf colouring and leaf fall remained almost constant in the southern boreal zones, whereas these advanced annually by 0.3 and 0.6 day in the middle boreal zone and by 0.6 and 0.4 day in the northern boreal zone, respectively. The duration of the growth period remained constant in all boreal zones. The results indicate high buffering capacity of B. pubescens against temperature changes. The study also shows the importance of the duration of phenological studies: some trends in spring phenophases had levelled out, while new trends in autumn phases had emerged after earlier studies in the same network for a shorter observation period.

In recent decades, naturally growing mosses have been used successfully as biomonitors of atmospheric deposition of heavy metals and nitrogen. Since 1990, the European moss survey has been repeated at five-yearly intervals. In 2010, the lowest concentrations of metals and nitrogen in mosses were generally found in northern Europe, whereas the highest concentrations were observed in (south-)eastern Europe for metals and the central belt for nitrogen. Averaged across Europe, since 1990, the median concentration in mosses has declined the most for lead (77%), followed by vanadium (55%), cadmium (51%), chromium (43%), zinc (34%), nickel (33%), iron (27%), arsenic (21%, since 1995), mercury (14%, since 1995) and copper (11%). Between 2005 and 2010, the decline ranged from 6% for copper to 36% for lead ; for nitrogen the decline was 5%. Despite the Europe-wide decline, no changes or increases have been observed between 2005 and 2010 in some (regions of) countries.

International audience; AbstractKey messageMoss surveys provide spatially dense data on environmental concentrations of heavy metals and nitrogen which, together with other biomonitoring and modelling data, can be used for indicating deposition to terrestrial ecosystems and related effects across time and areas of different spatial extension.ContextFor enhancing the spatial resolution of measuring and mapping atmospheric deposition by technical devices and by modelling, moss is used complementarily as bio-monitor.AimsThis paper investigated whether nitrogen and heavy metal concentrations derived by biomonitoring of atmospheric deposition are statistically meaningful in terms of compliance with minimum sample size across several spatial levels (objective 1), whether this is also true in terms of geostatistical criteria such as spatial auto-correlation and, by this, estimated values for unsampled locations (objective 2) and whether moss indicates atmospheric deposition in a similar way as modelled deposition, tree foliage and natural surface soil at the European and country level, and whether they indicate site-specific variance due to canopy drip (objective 3).MethodsData from modelling and biomonitoring atmospheric deposition were statistically analysed by means of minimum sample size calculation, by geostatistics as well as by bivariate correlation analyses and by multivariate correlation analyses using the Classification and Regression Tree approach and the Random Forests method.ResultsIt was found that the compliance of measurements with the minimum sample size varies by spatial scale and element measured. For unsampled locations, estimation could be derived. Statistically significant correlations between concentrations of heavy metals and nitrogen in moss and modelled atmospheric deposition, and concentrations in leaves, needles and soil were found. Significant influence of canopy drip on nitrogen concentration in moss was proven.ConclusionMoss surveys should complement modelled atmospheric deposition data as well as other biomonitoring approaches and offer a great potential for various terrestrial monitoring programmes dealing with exposure and effects.

Objective This study explores the statistical relations between the concentration of nine heavy metals (HM) (arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), mercury (Hg), nickel (Ni), lead (Pb), vanadium (V), zinc (Zn)), and nitrogen (N) in moss and potential explanatory variables (predictors) which were then used for mapping spatial patterns across Europe. Based on moss specimens collected in 2010 throughout Europe, the statistical relation between a set of potential predictors (such as the atmospheric deposition calculated by use of two chemical transport models (CTM), distance from emission sources, density of different land uses, population density, elevation, precipitation, clay content of soils) and concentrations of HMs and nitrogen (N) in moss (response variables) were evaluated by the use of Random Forests (RF) and Classification and Regression Trees (CART). Four spatial scales were regarded: Europe as a whole, ecological land classes covering Europe, single countries participating in the European Moss Survey (EMS), and moss species at sampling sites. Spatial patterns were estimated by applying a series of RF models on data on potential predictors covering Europe. Statistical values and resulting maps were used to investigate to what extent the models are specific for countries, units of the Ecological Land Classification of Europe (ELCE), and moss species. Results Land use, atmospheric deposition and distance to technical emission sources mainly influence the element concentration in moss. The explanatory power of calculated RF models varies according to elements measured in moss specimens, country, ecological land class, and moss species. Measured and predicted medians of element concentrations agree fairly well while minima and maxima show considerable differences. The European maps derived from the RF models provide smoothed surfaces of element concentrations (As, Cd, Cr, Cu, N, Ni, Pb, Hg, V, Zn), each explained by a multivariate RF model and verified by CART, and thereby more information than the dot maps depicting the spatial patterns of measured values. Conclusions RF is an eligible method identifying and ranking boundary conditions of element concentrations in moss and related mapping including the influence of the environmental factors.

For analysing element input into ecosystems and associated risks due to atmospheric deposition, element concentrations in moss provide complementary and time-integrated data at high spatial resolution every 5 years since 1990. The paper reviews (1) minimum sample sizes needed for reliable, statistical estimation of mean values at four different spatial scales (European and national level as well as landscape-specific level covering Europe and single countries); (2) trends of heavy metal (HM) and nitrogen (N) concentrations in moss in Europe (19902010); (3) correlations between concentrations of HM in moss and soil specimens collected across Norway (19902010); and (4) canopy drip-induced site-specific variation of N concentration in moss sampled in seven European countries (19902013). While the minimum sample sizes on the European and national level were achieved without exception, for some ecological land classes and elements, the coverage with sampling sites should be improved. The decline in emission and subsequent atmospheric deposition of HM across Europe has resulted in decreasing HM concentrations in moss between 1990 and 2010. In contrast, hardly any changes were observed for N in moss between 2005, when N was included into the survey for the first time, and 2010. In Norway, both, the moss and the soil survey data sets, were correlated, indicating a decrease of HM concentrations in moss and soil. At the site level, the average N deposition inside of forests was almost three times higher than the average N deposition outside of forests. © 2016, Springer-Verlag Berlin Heidelberg.

High atmospheric deposition of nitrogen (N) impacts functions and structures of N limited ecosystems. Due to filtering and related canopy drip effects forests are particularly exposed to N deposition. Up to now, this was proved by many studies using technical deposition samplers but there are only some few studies analysing the canopy drip effect on the accumulation of N in moss and related small scale atmospheric deposition patterns. Therefore, we investigated N deposition and related accumulation of N in forests and in (neighbouring) open fields by use of moss sampled across seven European countries. Sampling and chemical analyses were conducted according to the experimental protocol of the European Moss Survey. The ratios between the measured N content in moss sampled inside and outside of forests were computed and used to calculate estimates for non-sampled sites. Potentially influencing environmental factors were integrated in order to detect their relationships to the N content in moss. The overall average N content measured in moss was 20.0mgg(-1) inside and 11.9mgg(-1) outside of forests with highest N values in Germany inside of forests. Explaining more than 70% of the variance, the multivariate analyses confirmed that the sampling site category (site with/without canopy drip) showed the strongest correlation with the N content in moss. Spatial variances due to enhanced dry deposition in vegetation stands should be considered in future monitoring and modelling of atmospheric N deposition.