欧洲的氮状况

欧洲(不包括前苏联)的氮收支表明,欧洲氮循环加速的三个主要驱动力是肥料生产(14MtN/a)、矿物燃料燃烧及其它工业(3.3MtN/a)和各种产品中的氮输入(7.6MtN/a).本文估计了欧洲粮食、能源和工业产品系统中活性氮元素的各种泄漏,评估了它们对人类健康及水陆生态系统的影响.考虑到氮流转中的可能后果,未来欧洲有关封闭氮循环和减少活性氮泄漏的环境政策措施最好集中于三个主要驱动力.在确定氮排放上限和制定氯流控制的综合政策方面,如肥料使用、输入和氮水平,临界负载可能是非常有用的工具.     

Sharing environmental space: the role of law,economics and politics

The concept of ‘environmental space’ has been put forward as a means for providing specific meaning to sustainability. The concept combines the idea of the existence of environmental limits with a strong principle of environmental justice. It has been used as a basis for the development of sustainable action plans for many European countries, and has attracted political interest. However, thus far, the concept has found limited application by governments. The paper identifies and discusses several issues that need to be addressed for the environmental space approach to be implemented. Three main options for the institutionalization of the approach are discussed: within the legal‐constitutional framework (as rights and obligations), within the economic system (as environmental property rights), and through green planning (as specific objectives and targets contained in national environmental plans or strategies). The paper discusses the ability of the three options to deal with the issues identified, assessing their relative advantages and disadvantages, and to what extent these options are complementary. Finally, conclusions are drawn about the viability of the concept of ‘environmental space’.     

NUTRIENT CONCENTRATION CRITERIA AND CHARACTERIZATION OF PATTERNS IN TROPHIC STATE FOR RIVERS IN HETEROGENEOUS LANDSCAPES1

ABSTRACT: A method is demonstrated for the development of nutrient concentration criteria and large scale assessment of trophic state in environmentally heterogeneous landscapes. The method uses the River Environment Classification (REC) as a spatial framework to partition rivers according to differences in processes that control the accrual and loss of algae biomass. The method is then applied to gravel bed rivers with natural flow regimes that drain hilly watersheds in New Zealand's South Island. An existing model is used to characterize trophic state (in terms of chlorophyll a as a measure of maximum biomass) using nutrient concentration, which controls the rate of biomass accrual, and flood frequency, which controls biomass loss. Variation in flood frequency was partitioned into three classes, and flow data measured at 68 sites was used to show that the classes differ with respect to flood frequency. Variation in nutrient concentration was partitioned at smaller spatial scales by subdivision of higher level classes into seven classes. The median of flood frequency in each of the three higher level classes was used as a control variable in the model to provide spatially explicit nutrient concentration criteria by setting maximum chlorophyll a to reflect a desired trophic state. The median of mean monthly soluble reactive phosphorus and soluble inorganic nitrogen measured at 68 water quality monitoring sites were then used to characterize the trophic state of each of the seven lower level classes. The method models biomass and therefore allows variation in this response variable to provide options for trophic state and the associated nutrient concentrations to achieve these. Thus it is less deterministic than using reference site water quality. The choice from among these options is a sociopolitical decision, which reflects the management objectives rather than purely technical considerations.     

MULTISCALE RIVER ENVIRONMENT CLASSIFICATION FOR WATER RESOURCES MANAGEMENT1

ABSTRACT: River Environment Classification (REC) is a new system for classifying river environments that is based on climate, topography, geology, and land cover factors that control spatial patterns in river ecosystems. REC builds on existing principles for environmental regionalization and introduces three specific additions to the “ecoregion” approach. First, the REC assumes that ecological patterns are dependent on a range of factors and associated landscape scale processes, some of which may show significant variation within an ecoregion. REC arranges the controlling factors in a hierarchy with each level defining the cause of ecological variation at a given characteristic scale. Second, REC assumes that ecological characteristics of rivers are responses to fluvial (i.e., hydrological and hydraulic) processes. Thus, REC uses a network of channels and associated watersheds to classify specific sections of river. When mapped, REC has the form of a linear mosaic in which classes change in the downstream direction as the integrated characteristics of the watershed change, producing longitudinal spatial patterns that are typical of river ecosystems. Third, REC assigns individual river sections to a class independently and objectively according to criteria that result in a geographically independent framework in which classes may show wide geographic dispersion rather than the geographically dependent schemes that result from the ecoregion approach. REC has been developed to provide a multiscale spatial framework for river management and has been used to map the rivers of New Zealand at a 1:50,000 mapping scale.     

Constructing land-use maps of the Netherlands in 2030

The National Environmental Assessment Agency of the RIVM in the Netherlands is obliged to report on future trends in the environment and nature every 4 years. The last report, Nature Outlook 2, evaluated the effects of four alternative socio-economic and demographic scenarios on nature and the landscape. Spatially detailed land-use maps are needed to assess effects on nature and landscape. The objective of the study presented here was how to create spatially detailed land-use maps of the Netherlands in 2030 using the Environment Explorer, a Cellular Automata-based land-use model to construct land-use maps from four scenarios. One of these is discussed in great detail to show how the maps were constructed from the various scenario elements, story lines and additional data and assumptions on national, regional and local land-use developments. It was the first time in the history of our outlooks that consistent, spatially detailed land-use maps of the Netherlands for 2030 were constructed from national economic and demographic scenarios. Each map represents a direct reflection of model input and assumptions. The maps do not show the most probable developments in the Netherlands but describe the possible change in land use if Dutch society were to develop according to one of the four scenarios. The large (societal) uncertainties are reflected in the total set of future land-use maps. The application of a land-use model such as the Environment Explorer ensures that all relevant aspects of a scenario, i.e. economic and demographic developments, zoning policies and urban growth, are integrated systematically into one consistent framework.     

Uncertainty Models for Estimates of Physical Characteristics of River Segments Over Large Areas

Spatially comprehensive estimates of the physical characteristics of river segments over large areas are required in many large‐scale analyses of river systems and for the management of multiple basins. Remote sensing and modeling are often used to estimate river characteristics over large areas, but the uncertainties associated with these estimates and their dependence on the physical characteristics of the segments and their catchments are seldom quantified. Using test data with varying degrees of independence, we derived analytical models of the uncertainty associated with estimates of upstream catchment area (CA), segment slope, and mean annual discharge for all river segments of a digital representation of the hydrographic network of France. Although there were strong relationships between our test data and estimates at the scale of France, there were also large relative local uncertainties, which varied with the physical characteristics of the segments and their catchments. Discharge and CA were relatively uncertain where discharge was low and catchments were small. Discharge uncertainty also increased in catchments with large rainfall events and low minimum temperature. The uncertainty of segment slope was strongly related to segment length. Our uncertainty models were consistent across large regions of France, suggesting some degree of generality. Their analytical formulation should facilitate their use in large‐scale ecological studies and simulation models.     

Inter-sexual differences in T-cell-mediated immunity of black-headed gull chicks (<Emphasis Type="Italic">Larus ridibundus</Emphasis>) depend on the hatching order

Hatching asynchrony in avian species leads to age and size differences between nestlings within a brood, handicapping last-hatched chicks in the sibling rivalry. Starvation due to this competitive disadvantage has been regarded as the primary cause of an increase in mortality with hatching order. However, for gulls it has also been suggested that disease is the cause of mortality for last-hatched chicks, possibly through reduced immunocompetence and thereby an enhanced susceptibility to infection. In addition, the male-biased mortality reported for several gull species may be related to a higher vulnerability to diseases in males compared to females. To determine the potential influence of the immune system on these mortality patterns, we investigated the T-cell-mediated immunity (CMI) of black-headed gull chicks in relation to hatching order and sex. We found a significant decrease in the CMI with hatching order. This result may be causally related to systematic changes in maternal yolk steroids and carotenoids within the laying sequence. For second-laid eggs, male CMI was significantly lower than female CMI. This is possibly linked to higher plasma levels of testosterone in male embryos which might have an immunosuppressive effect. If so, this effect is masked in eggs of either high (first egg) or low (last egg) quality. Chicks with low CMI showed enhanced mortality rates. Thus the differences in immune response are likely to contribute to the observed mortality patterns. However, hatching order significantly affected mortality independently of CMI, suggesting that competitive disadvantage due to hatching asynchrony is also important.Communicated by M. Webster     

Social stimulation,nuptial colouration,androgens and immunocompetence in a sexual dimorphic cichlid fish

The nature of the costs maintaining honesty of sexual signalling in inter- and intrasexual interactions remains a contentious issue. For carotenoid-based colour ornaments, it has been hypothesized that the honesty of the signal is enforced when carotenoid allocation to colour expression is traded off against carotenoid availability for immunocompetence. In addition, honesty is enforced if androgens required for colour expression are immunosuppressive. We tested whether there is a trade-off between colour expression and immunocompetence in a lek-breeding haplochromine cichlid fish, Pundamilia nyererei, from Lake Victoria with a carotenoid-based nuptial dress. First, we showed that expression of red nuptial colouration and social rank in a group were positively correlated. We then successfully manipulated the level of colour advertisement by socially stimulating individually housed males with a rival male: Stimulated males developed larger areas of red nuptial colouration and had higher levels of circulating 11-ketotestosterone (11-KT) than non-stimulated males. We subsequently tested the humoral immune response to a novel antigen (sheep red blood cells). There was no overall significant effect of social stimulation on antibody production, but in the stimulated males, the degree of red colouration and the antibody response were negatively correlated. This significant interaction between colour and treatment thus shows that the negative correlation between colouration and antibody production is dependent on the (manipulated) social environment. This study provides correlational and experimental evidence for a trade-off between expression of a sexual trait and one component of immune function in fish. We found no evidence for a direct effect of 11-KT on antibody production, and we discuss alternative mechanisms that could mediate the trade-off.     

Effect of Classification Procedure on the Performance of Numerically Defined Ecological Regions

Ecological regionalizations define geographic regions exhibiting relative homogeneity in ecological (i.e., environmental and biotic) characteristics. Multivariate clustering methods have been used to define ecological regions based on subjectively chosen environmental variables. We developed and tested three procedures for defining ecological regions based on spatial modeling of a multivariate target pattern that is represented by compositional dissimilarities between locations (e.g., taxonomic dissimilarities). The procedures use a “training dataset” representing the target pattern and models this as a function of environmental variables. The model is then extrapolated to the entire domain of interest. Environmental data for our analysis were drawn from a 400 m grid covering all of Switzerland and consisted of 12 variables describing climate, topography and lithology. Our target patterns comprised land cover composition of each grid cell that was derived from interpretation of aerial photographs. For Regionalization 1 we used conventional cluster analysis of the environmental variables to define 60 hierarchically organized levels comprising from 5 to 300 regions. Regionalization 1 provided a base-case for comparison with the model-based regionalizations. Regionalization 2, 3 and 4 also comprised 60 hierarchically organized levels and were derived by modeling land cover composition for 4000 randomly selected “training” cells. Regionalization 2 was based on cluster analysis of environmental variables that were transformed based on a Generalized Dissimilarity Model (GDM). Regionalization 3 and 4 were defined by clustering the training cells based on their land cover composition followed by predictive modeling of the distribution of the land cover clusters using Classification and Regression Tree (CART) and Random Forest (RF) models. Independent test data (i.e. not used to train the models) were used to test the discrimination of land cover composition at all hierarchical levels of the regionalizations using the classification strength (CS) statistic. CS for all the model-based regionalizations was significantly higher than for Regionalization 1. Regionalization 3 and 4 performed significantly better than Regionalization 2 at finer hierarchical levels (many regions) and Regionalization 4 performed significantly better than Regionalization 3 for coarse levels of detail (few regions). Compositional modeling can significantly increase the performance of numerically defined ecological regionalizations. CART and RF-based models appear to produce stronger regionalizations because discriminating variables are able to change at each hierarchic level.     

Strong Influence of Variable Treatment on the Performance of Numerically Defined Ecological Regions

Numerical clustering has frequently been used to define hierarchically organized ecological regionalizations, but there has been little robust evaluation of their performance (i.e., the degree to which regions discriminate areas with similar ecological character). In this study we investigated the effect of the weighting and treatment of input variables on the performance of regionalizations defined by agglomerative clustering across a range of hierarchical levels. For this purpose, we developed three ecological regionalizations of Switzerland of increasing complexity using agglomerative clustering. Environmental data for our analysis were drawn from a 400 m grid and consisted of estimates of 11 environmental variables for each grid cell describing climate, topography and lithology. Regionalization 1 was defined from the environmental variables which were given equal weights. We used the same variables in Regionalization 2 but weighted and transformed them on the basis of a dissimilarity model that was fitted to land cover composition data derived for a random sample of cells from interpretation of aerial photographs. Regionalization 3 was a further two-stage development of Regionalization 2 where specific classifications, also weighted and transformed using dissimilarity models, were applied to 25 small scale “sub-domains” defined by Regionalization 2. Performance was assessed in terms of the discrimination of land cover composition for an independent set of sites using classification strength (CS), which measured the similarity of land cover composition within classes and the dissimilarity between classes. Regionalization 2 performed significantly better than Regionalization 1, but the largest gains in performance, compared to Regionalization 1, occurred at coarse hierarchical levels (i.e., CS did not increase significantly beyond the 25-region level). Regionalization 3 performed better than Regionalization 2 beyond the 25-region level and CS values continued to increase to the 95-region level. The results show that the performance of regionalizations defined by agglomerative clustering are sensitive to variable weighting and transformation. We conclude that large gains in performance can be achieved by training classifications using dissimilarity models. However, these gains are restricted to a narrow range of hierarchical levels because agglomerative clustering is unable to represent the variation in importance of variables at different spatial scales. We suggest that further advances in the numerical definition of hierarchically organized ecological regionalizations will be possible with techniques developed in the field of statistical modeling of the distribution of community composition.