The enigma of progress in denitrification research.

Humans have dramatically increased the amount of reactive nitrogen (primarily ammonium, nitrogen oxides, and organically bound N) circulating in the biosphere and atmosphere, creating a wide array of desirable products (e.g., food production) and undesirable consequences (e.g., eutrophication of aquatic ecosystems and air pollution). Only when this reactive N is converted back to the chemically unreactive dinitrogen (N2) form, do these cascading effects of elevated reactive N cease to be of concern. Among the quantitatively most important processes for converting reactive N to N2 gas is the biological process of classical denitrification, in which oxides of nitrogen are used as terminal electron acceptors in anaerobic respiration. This Invited Feature on denitrification includes a series of papers that integrate our current state of knowledge across terrestrial, freshwater, and marine systems on denitrification rates, controlling factors, and methodologies for measuring and modeling denitrification. In this paper, we present an overview of the role of denitrification within the broader N cycle, the environmental and health concerns that have resulted from human alteration of the N cycle, and a brief historical perspective on why denitrification has been so difficult to study. Despite over a century of research on denitrification and numerous recent technological advances, we still lack a comprehensive, quantitative understanding of denitrification rates and controlling factors across ecosystems. Inherent problems of measuring spatially and temporally heterogeneous N2 production under an N2-rich atmosphere account for much of this slow progress, but lack of interdisciplinary communication of research results and methodological developments has also impeded denitrification research. An integrated multidisciplinary approach to denitrification research, from upland terrestrial ecosystems, to small streams, river systems, estuaries, and continental shelf ecosystems, and to the open ocean, may yield new insights into denitrification across landscapes and waterscapes.     

Denitrification across landscapes and waterscapes: a synthesis.

Denitrification is a critical process regulating the removal of bioavailable nitrogen (N) from natural and human-altered systems. While it has been extensively studied in terrestrial, freshwater, and marine systems, there has been limited communication among denitrification scientists working in these individual systems. Here, we compare rates of denitrification and controlling factors across a range of ecosystem types. We suggest that terrestrial, freshwater, and marine systems in which denitrification occurs can be organized along a continuum ranging from (1) those in which nitrification and denitrification are tightly coupled in space and time to (2) those in which nitrate production and denitrification are relatively decoupled. In aquatic ecosystems, N inputs influence denitrification rates whereas hydrology and geomorphology influence the proportion of N inputs that are denitrified. Relationships between denitrification and water residence time and N load are remarkably similar across lakes, river reaches, estuaries, and continental shelves. Spatially distributed global models of denitrification suggest that continental shelf sediments account for the largest portion (44%) of total global denitrification, followed by terrestrial soils (22%) and oceanic oxygen minimum zones (OMZs; 14%). Freshwater systems (groundwater, lakes, rivers) account for about 20% and estuaries 1% of total global denitrification. Denitrification of land-based N sources is distributed somewhat differently. Within watersheds, the amount of land-based N denitrified is generally highest in terrestrial soils, with progressively smaller amounts denitrified in groundwater, rivers, lakes and reservoirs, and estuaries. A number of regional exceptions to this general trend of decreasing denitrification in a downstream direction exist, including significant denitrification in continental shelves of N from terrestrial sources. Though terrestrial soils and groundwater are responsible for much denitrification at the watershed scale, per-area denitrification rates in soils and groundwater (kg N x km(-2) x yr(-1)) are, on average, approximately one-tenth the per-area rates of denitrification in lakes, rivers, estuaries, continental shelves, or OMZs. A number of potential approaches to increase denitrification on the landscape, and thus decrease N export to sensitive coastal systems exist. However, these have not generally been widely tested for their effectiveness at scales required to significantly reduce N export at the whole watershed scale.     

Methods for measuring denitrification: diverse approaches to a difficult problem.

Denitrification, the reduction of the nitrogen (N) oxides, nitrate (NO3-) and nitrite (NO2-), to the gases nitric oxide (NO), nitrous oxide (N2O), and dinitrogen (N2), is important to primary production, water quality, and the chemistry and physics of the atmosphere at ecosystem, landscape, regional, and global scales. Unfortunately, this process is very difficult to measure, and existing methods are problematic for different reasons in different places at different times. In this paper, we review the major approaches that have been taken to measure denitrification in terrestrial and aquatic environments and discuss the strengths, weaknesses, and future prospects for the different methods. Methodological approaches covered include (1) acetylene-based methods, (2) 15N tracers, (3) direct N2 quantification, (4) N2:Ar ratio quantification, (5) mass balance approaches, (6) stoichiometric approaches, (7) methods based on stable isotopes, (8) in situ gradients with atmospheric environmental tracers, and (9) molecular approaches. Our review makes it clear that the prospects for improved quantification of denitrification vary greatly in different environments and at different scales. While current methodology allows for the production of accurate estimates of denitrification at scales relevant to water and air quality and ecosystem fertility questions in some systems (e.g., aquatic sediments, well-defined aquifers), methodology for other systems, especially upland terrestrial areas, still needs development. Comparison of mass balance and stoichiometric approaches that constrain estimates of denitrification at large scales with point measurements (made using multiple methods), in multiple systems, is likely to propel more improvement in denitrification methods over the next few years.     

Biogeochemical consequences of rapid microbial turnover and seasonal succession in soil

Soil microbial communities have the metabolic and genetic capability to adapt to changing environmental conditions on very short time scales. In this paper we combine biogeochemical and molecular approaches to reveal this potential, showing that microbial biomass can turn over on time scales of days to months in soil, resulting in a succession of microbial communities over the course of a year. This new understanding of the year-round turnover and succession of microbial communities allows us for the first time to propose a temporally explicit N cycle that provides mechanistic hypotheses to explain both the loss and retention of dissolved organic N (DON) and inorganic N (DIN) throughout the year in terrestrial ecosystems. In addition, our results strongly support the hypothesis that turnover of the microbial community is the largest source of DON and DIN for plant uptake during the plant growing season. While this model of microbial biogeochemistry is derived from observed dynamics in the alpine, we present several examples from other ecosystems to indicate that the general ideas of biogeochemical fluxes being linked to turnover and succession of microbial communities are applicable to a wide range of terrestrial ecosystems.     

Ontogenetic and sex-specific differences in density-dependent habitat selection of a marine fish population

The spatial dynamics of species are the result of complex interactions between density-independent and density-dependent sources of variability. Disentangling these two sources of variability has challenged ecologists working in both terrestrial and aquatic ecosystems. Using a novel spatially explicit statistical model, we tested for the presence of density-independent and density-dependent habitat selection in yellowfin sole (Limanda aspera) in the eastern Bering Sea. We found specificities in the density-dependent processes operating across ontogeny and particularly with gender. Density-dependent habitat expansion occurred primarily in females, and to a lesser degree in males. These patterns were especially evident in adult stages, while juvenile stages of both sexes exhibited a mix of different dynamics. Association of yellowfin sole with substrate type also varied by sex and to a lesser degree with size, with large females distributed over a wider range of substrates than males. Moreover, yellowfin sole expanded northward as cold subsurface waters retracted in summer, suggesting high sensitivity to arctic warming. Our findings illustrate how marginal habitats can play an important role in buffering density-dependent habitat expansion, with direct implications for resource management. Our spatially explicit modeling approach is effective in evaluating density-dependent spatial dynamics, and can easily be used to test similar hypotheses from a variety of aquatic and terrestrial ecosystems.     

Comparing resource pulses in aquatic and terrestrial ecosystems

Resource pulses affect productivity and dynamics in a diversity of ecosystems, including islands, forests, streams, and lakes. Terrestrial and aquatic systems differ in food web structure and biogeochemistry; thus they may also differ in their responses to resource pulses. However, there has been a limited attempt to compare responses across ecosystem types. Here, we identify similarities and differences in the causes and consequences of resource pulses in terrestrial and aquatic systems. We propose that different patterns of food web and ecosystem structure in terrestrial and aquatic systems lead to different responses to resource pulses. Two predictions emerge from a comparison of resource pulses in the literature: (1) the bottom-up effects of resource pulses should transmit through aquatic food webs faster because of differences in the growth rates, life history, and stoichiometry of organisms in aquatic vs. terrestrial systems, and (2) the impacts of resource pulses should also persist longer in terrestrial systems because of longer generation times, the long-lived nature of many terrestrial resource pulses, and reduced top-down effects of consumers in terrestrial systems compared to aquatic systems. To examine these predictions, we use a case study of a resource pulse that affects both terrestrial and aquatic systems: the synchronous emergence of periodical cicadas (Magicicada spp.) in eastern North American forests. In general, studies that have examined the effects of periodical cicadas on terrestrial and aquatic systems support the prediction that resource pulses transmit more rapidly in aquatic systems; however, support for the prediction that resource pulse effects persist longer in terrestrial systems is equivocal. We conclude that there is a need to elucidate the indirect effects and long-term implications of resource pulses in both terrestrial and aquatic ecosystems.     

Resource users as land-sea links in coastal and marine socioecological systems

Coastal zones, which connect terrestrial and aquatic ecosystems, are among the most resource-rich regions globally and home to nearly 40% of the global human population. Because human land-based activities can alter natural processes in ways that affect adjacent aquatic ecosystems, land-sea interactions are increasingly recognized as critical to coastal conservation planning and governance. However, the complex socioeconomic dynamics inherent in coastal and marine socioecological systems (SESs) have received little consideration. Drawing on knowledge generalized from long-term studies in Caribbean Nicaragua, we devised a conceptual framework that clarifies the multiple ways socioeconomically driven behavior can link the land and sea. In addition to other ecosystem effects, the framework illustrates how feedbacks resulting from changes to aquatic resources can influence terrestrial resource management decisions and land uses. We assessed the framework by applying it to empirical studies from a variety of coastal SESs. The results suggest its broad applicability and highlighted the paucity of research that explicitly investigates the effects of human behavior on coastal SES dynamics. We encourage researchers and policy makers to consider direct, indirect, and bidirectional cross-ecosystem links that move beyond traditionally recognized land-to-sea processes.     

Predicting intertidal organism temperatures with modified land surface models

Animals and plants in the marine intertidal zone live at the interface between terrestrial and marine environments. This zone is likely to be a sensitive indicator of the effects of climate change in coastal ecosystems, because of several key characteristics including steep environmental gradients, rapid temperature changes during tide transitions, fierce competition for limited space, and a community of mostly sessile organisms. Here we describe a modular modeling approach using modifications to a meteorological land surface model to determine body temperatures of the ecologically dominant rocky intertidal mussel Mytilus californianus, as a tool that can be used as a proxy for ecological performance. We validate model results against in situ measurements made with biomimetic body temperature sensors. Model predictions lie within the range of variability of biomimetic measurements, based on observations over a 4-year period at sites along 1700 km of the US west coast from southern California (34.5°N) to northern Washington (48.4°N). Our modular approach can be easily applied to many situations in the intertidal zone, including bare rock, mussel, barnacle, and algal beds, salt-marsh grasses, and sand- and mud-flats, by modifying the “vegetation layer” in a standard meteorological land surface model. Biophysical models such as these, which link ecological processes to changing climates through predictions of body temperature, are essential for understanding biogeographic patterns of physiological stress and mortality risk.     

A climatic driver for abrupt mid-Holocene vegetation dynamics and the hemlock decline in New England

The mid-Holocene decline of eastern hemlock is widely viewed as the sole prehistorical example of an insect- or pathogen-mediated collapse of a North American tree species and has been extensively studied for insights into pest-host dynamics and the consequences to terrestrial and aquatic ecosystems of dominant-species removal. We report paleoecological evidence implicating climate as a major driver of this episode. Data drawn from sites across a gradient in hemlock abundance from dominant to absent demonstrate: a synchronous, dramatic decline in a contrasting taxon (oak); changes in lake sediments and aquatic taxa indicating low water levels; and one or more intervals of intense drought at regional to continental scales. These results, which accord well with emerging climate reconstructions, challenge the interpretation of a biotically driven hemlock decline and highlight the potential for climate change to generate major, abrupt dynamics in forest ecosystems.     

Appreciating Ecological Complexity: Habitat Contours as a Conceptual Landscape Model

Abstract:  Organisms respond to their surroundings at multiple spatial scales, and different organisms respond differently to the same environment. Existing landscape models, such as the "fragmentation model" (or patch-matrix-corridor model) and the "variegation model," can be limited in their ability to explain complex patterns for different species and across multiple scales. An alternative approach is to conceptualize landscapes as overlaid species-specific habitat contour maps. Key characteristics of this approach are that different species may respond differently to the same environmental conditions and at different spatial scales. Although similar approaches are being used in ecological modeling, there is much room for habitat contours as a useful conceptual tool. By providing an alternative view of landscapes, a contour model may stimulate more field investigations stratified on the basis of ecological variables other than human-defined patches and patch boundaries. A conceptual model of habitat contours may also help to communicate ecological complexity to land managers. Finally, by incorporating additional ecological complexity, a conceptual model based on habitat contours may help to bridge the perceived gap between pattern and process in landscape ecology. Habitat contours do not preclude the use of existing landscape models and should be seen as a complementary approach most suited to heterogeneous human-modified landscapes.     

Impact of microphytobenthos on the sediment biogeochemical cycles: A modeling approach

In marine biogeochemical modeling, the sediment is usually represented by diagenetic models, but in shallow ecosystems these models are incomplete, because they do not take into account the benthic primary production. While microphytobenthos (MPB) is known to strongly impact mineralization pathways and nutrient fluxes, MPB is rarely integrated as an explicit variable. To investigate the impact of microphytobenthos on early diagenesis in sediment, we built a fine-scale dynamic model, based on the diagenetic model OMEXDIA and including MPB and associated processes. The model outputs were similar to a data set of MPB-colonized sediment sampled in Florida Bay, suggesting that the model can recreate a realistic situation. The model showed that MPB activities induced a strong diurnal rhythm on concentration profiles, fluxes, and mineralization processes. When MPB was present at the sediment surface, the total mineralization was strongly enhanced thanks to the supply of labile organic matter. In contrast, coupled nitrification–denitrification was inhibited by a factor of 3.8. This inhibition can be explained by the competition for nitrate and ammonium between MPB and bacteria. Nitrogen uptake of MPB represented 96% of the daily supply of dissolved inorganic nitrogen. This was more than 50 times greater than N consumption by denitrification. With MPB, sediment nitrogen flux to the water column was reduced by a factor of 70, suggesting that sediment colonized by MPB represents a minor source of nutrients for phytoplankton and bacterioplankton. Results showed that current diagenetic models are not well-suited for shallow ecosystems with significant MPB primary production.     

Scaling-up spatially-explicit ecological models using graphics processors

How the properties of ecosystems relate to spatial scale is a prominent topic in current ecosystem research. Despite this, spatially explicit models typically include only a limited range of spatial scales, mostly because of computing limitations. Here, we describe the use of graphics processors to efficiently solve spatially explicit ecological models at large spatial scale using the CUDA language extension. We explain this technique by implementing three classical models of spatial self-organization in ecology: a spiral-wave forming predator-prey model, a model of pattern formation in arid vegetation, and a model of disturbance in mussel beds on rocky shores. Using these models, we show that the solutions of models on large spatial grids can be obtained on graphics processors with up to two orders of magnitude reduction in simulation time relative to normal pc processors. This allows for efficient simulation of very large spatial grids, which is crucial for, for instance, the study of the effect of spatial heterogeneity on the formation of self-organized spatial patterns, thereby facilitating the comparison between theoretical results and empirical data. Finally, we show that large-scale spatial simulations are preferable over repetitions at smaller spatial scales in identifying the presence of scaling relations in spatially self-organized ecosystems. Hence, the study of scaling laws in ecology may benefit significantly from implementation of ecological models on graphics processors.     

Wildfire, landscape diversity and the Drossel-Schwabl model

How simple can a model be that still captures essential aspects of wildfire ecosystems at large spatial and temporal scales? The Drossel-Schwabl model (DSM) is a metaphorical forest-fire model developed to reproduce only one pattern of real systems: a frequency distribution of fire sizes resembling a power law. Consequently, and because it appears oversimplified, it remains unclear what bearings the DSM has in reality. Here, we test whether the DSM is capable of reproducing a pattern that was not considered in its design, the hump-shaped relation between the diversity of succession stages and average annual area burnt. We found that the model, once reformulated to represent succession, produces realistic landscape diversity patterns. We investigated four succession scenarios of forest-fire ecosystems in the USA and Canada. In all scenarios, landscape diversity is highest at an intermediate average annual area burnt as predicted by the intermediate disturbance hypothesis. These results show that a model based solely on the dynamics of the fuel mosaic has surprisingly high predictive power with regard to observed statistical properties of wildfire systems at large spatial scales. Parsimonious models, such as the DSM can be used as starting points for systematic development of more structurally realistic but tractable wildfire models. Due to their simplicity they allow analytical approaches that further our understanding under increasing complexity.     

Priming effect: bridging the gap between terrestrial and aquatic ecology

Understanding how ecosystems store or release carbon is one of ecology's greatest challenges in the 21st century. Organic matter covers a large range of chemical structures and qualities, and it is classically represented by pools of different recalcitrance to degradation. The interaction effects of these pools on carbon cycling are still poorly understood and are most often ignored in global-change models. Soil scientists have shown that inputs of labile organic matter frequently tend to increase, and often double, the mineralization of the more recalcitrant organic matter. The recent revival of interest for this phenomenon, named the priming effect, did not cross the frontiers of the disciplines. In particular, the priming effect phenomenon has been almost totally ignored by the scientific communities studying marine and continental aquatic ecosystems. Here we gather several arguments, experimental results, and field observations that strongly support the hypothesis that the priming effect is a general phenomenon that occurs in various terrestrial, freshwater, and marine ecosystems. For example, the increase in recalcitrant organic matter mineralization rate in the presence of labile organic matter ranged from 10% to 500% in six studies on organic matter degradation in aquatid ecosystems. Consequently, the recalcitrant organic matter mineralization rate may largely depend on labile organic matter availability, influencing the CO2 emissions of both aquatic and terrestrial ecosystems. We suggest that (1) recalcitrant organic matter may largely contribute to the CO2 emissions of aquatic ecosystems through the priming effect, and (2) priming effect intensity may be modified by global changes, interacting with eutrophication processes and atmospheric CO2 increases. Finally, we argue that the priming effect acts substantially in the carbon and nutrient cycles in all ecosystems. We outline exciting avenues for research, which could provide new insights on the responses of ecosystems to anthropogenic perturbations and their feedbacks to climatic changes.     

The Influence of Model Structure on Conclusions about the Viability and Harvesting of Serengeti Wildebeest

We investigate how the viability and harvestability predicted by population models are affected by details of model construction. Based on this analysis we discuss some of the pitfalls associated with the use of classical statistical techniques for resolving the uncertainties associated with modeling population dynamics. The management of the Serengeti wildebeest (Connochaetes taurinus) is used as a case study. We fitted a collection of age-structured and unstructured models to a common set of available data and compared model predictions in terms of wildebeest viability and harvest. Models that depicted demographic processes in strikingly different ways fitted the data equally well. However, upon further analysis it became clear that models that fit the data equally well could nonetheless have very different management implications. In general, model structure had a much larger effect on viability analysis (e.g., time to collapse) than on optimal harvest analysis (e.g., harvest rate that maximizes harvest). Some modeling decisions, such as including age-dependent fertility rates, did not affect management predictions, but others had a strong effect (e.g., choice of model structure). Because several suitable models of comparable complexity fitted the data equally well, traditional model selection methods based on the parsimony principle were not practical for judging the value of alternative models. Our results stress the need to implement analytical frameworks for population management that explicitly consider the uncertainty about the behavior of natural systems.     

Combining data and simulated data for space–time fields: application to ozone

This paper presents a theory for modeling random environmental spatial-temporal fields that allows simulated data (numerical-physical model output) to be combined with measurements made at fixed monitoring sites. That theory involves Bayesian hierarchical models that provide temporal forecasts and spatial predictions along with appropriate credibility intervals. A by-product is a method for re-calibrating the simulated data to bring it into line with the measurements for certain applications. While the approach covers a broad domain of potential applications, this paper addresses a field of particular importance, ground level ozone concentrations over the eastern and central USA. A univariate model is developed and illustrated with hourly ozone fields. A multivariate alternative is also provided and illustrated with daily concentration fields. The forecasts and predictions they provide are compared with those from other approaches.     

污水再生处理工艺中卡马西平的去除过程模拟及其生态风险评价

卡马西平在污水和水环境中广泛存在,且对水生生态系统安全构成风险,因此成为目前研究较多的药品之一。以北京清河再生水厂为例,研究"超滤—臭氧氧化—氯消毒"处理工艺中卡马西平的去除特性,并针对臭氧氧化和氯消毒工艺建立模拟卡马西平去除过程的机理模型。同时,利用美国环境保护署ECOTOX数据库,获取卡马西平对北京市水生生物物种的毒性数据,并基于毒性数据建立物种敏感度分布(species sensitivity distribution,SSD)模型,评价再生水厂出水补给地表水体时卡马西平产生的生态风险。臭氧氧化和氯消毒模型对卡马西平、总有机碳、氨氮等指标的模拟误差总体低于20%,模型的灵敏参数均可以被较好地识别,且其不确定性显著下降。对比7种SSD模型发现,对数正态分布和对数Logistic分布模型较好地拟合了北京市6个物种的卡马西平毒性数据,二者预测得到的总体生态风险期望值分别为7.4%和8.5%。     

Sensitivity Analyses of Spatial Population Viability Analysis Models for Species at Risk and Habitat Conservation Planning

Abstract:  Population viability analysis (PVA) is an effective framework for modeling species- and habitat-recovery efforts, but uncertainty in parameter estimates and model structure can lead to unreliable predictions. Integrating complex and often uncertain information into spatial PVA models requires that comprehensive sensitivity analyses be applied to explore the influence of spatial and nonspatial parameters on model predictions. We reviewed 87 analyses of spatial demographic PVA models of plants and animals to identify common approaches to sensitivity analysis in recent publications. In contrast to best practices recommended in the broader modeling community, sensitivity analyses of spatial PVAs were typically ad hoc, inconsistent, and difficult to compare. Most studies applied local approaches to sensitivity analyses, but few varied multiple parameters simultaneously. A lack of standards for sensitivity analysis and reporting in spatial PVAs has the potential to compromise the ability to learn collectively from PVA results, accurately interpret results in cases where model relationships include nonlinearities and interactions, prioritize monitoring and management actions, and ensure conservation-planning decisions are robust to uncertainties in spatial and nonspatial parameters. Our review underscores the need to develop tools for global sensitivity analysis and apply these to spatial PVA.     

Hierarchical analysis of species distributions and abundance across environmental gradients

Abiotic and biotic processes operate at multiple spatial and temporal scales to shape many ecological processes, including species distributions and demography. Current debate about the relative roles of niche-based and stochastic processes in shaping species distributions and community composition reflects, in part, the challenge of understanding how these processes interact across scales. Traditional statistical models that ignore autocorrelation and spatial hierarchies can result in misidentification of important ecological covariates. Here, we demonstrate the utility of a hierarchical modeling framework for testing hypotheses about the importance of abiotic factors at different spatial scales and local spatial autocorrelation for shaping species distributions and abundances. For the two orchid species studied, understory light availability and soil moisture helped to explain patterns of presence and abundance at a microsite scale (<4 m2), while soil organic content was important at a population scale (<400 m2). The inclusion of spatial autocorrelation is shown to alter the magnitude and certainty of estimated relationships between abundance and abiotic variables, and we suggest that such analysis be used more often to explore the relationships between species life histories and distributions. The hierarchical modeling framework is shown to have great potential for elucidating ecological relationships involving abiotic and biotic processes simultaneously at multiple scales.     

Moosmonitoring als Spiegel der Landnutzung?

Goal, Scope and Background

The study was conducted to test the hypothesis that the regional variability of nitrogen (N) and metal accumulations in terrestrial ecosystems are due to historical and recent ways of land use. To this end, in two regions of Central Europe the metal and N accumulations in both regions should be examined by comparative moss analysis. The regions should be of quantitatively specified representativity for selected ecological characteristics of Europe. Within both regions these characteristics should be covered by the sites where the moss samples were collected. The number of samples should allow for geostatistical estimation of the measured nitrogen and metal loads.

Methods

The two regions of investigation were selected according to an ecological land classification of Europe which was computed by classification trees. Within each of both research areas the sampling points were localized according to the areas occupied by the ecologically defined land classes. The sampling and chemical analysis of mosses was conducted in accordance with an appropriate UNECE guideline by means of ICP-MS (metals) and combustion analysis (N). The quality of measurements was assured using certified reference materials. The differences of deposition loads were tested for statistical significance with regard to time and space. Variogram analysis was used to examine and model the spatial autocorrelation function of the measurements. Ordinary kriging was then applied for surface estimations.

Results

By use of the ecological regionalisation of Europe the Weser-Ems Region (WER) and the Euro Region Nissa (ERN) were selected for investigation. The sampling sites represent quite well the natural landscapes and the land use categories of both regions. The measurement values corroborate the decline of metal accumulation observed since the beginning of the European Mosses Monitoring Survey in 1990. The metal loads of the mosses in the ERN exceed those in the WER significantly. The opposite holds true for the N concentrations: those in the WER are significantly higher than those in the ERN.

Discussion

The decrease of heavy metal emissions is correlated with lowered deposition and accumulation rates in terrestrial ecosystems. The accumulation of nitrogen in the biosphere is not following this trend.

Conclusions

The technique of moss analysis is adequate for spatially valid biomonitoring of spatial and temporal trends of metals and nitrogen in terrestrial ecosystems. By this, it enables to prove the efficiency of environmental policies.

Recommendations and Perspectives

The accumulation of N in ecosystems is still a serious environmental problem. Related ecological impacts are the eutrophication of aquatic ecosystems like ground waters, lakes, rivers and oceans as well as the biocoenotic changes in terrestrial ecosystems. Thus, a statistically valid exposure analysis must encompass both, accumulation of metals and N bioaccumulation. Further, the bioaccumulation of persistent organic pollutants should be monitored. Finally, environmental biomonitoring should be conducted in much closer contact with human health aspects.