The lowering of the water table resulting from peatland drainage may dramatically alter C and N cycling in peatland ecosystems, which contain one-third of the total terrestrial C. In this study, tree annual ring width and C (delta(13)C) and N (delta(15)N) isotope ratios in soil and plant tissues (tree foliage, growth rings, and understory foliage) in a black spruce-tamarack (Picea mariana-Larix laricina) mixed-wood forest were examined to study the effects of drainage on tree growth and C and N dynamics in a minerotrophic peatland in west-central Alberta, Canada. Drainage increased the delta(15)N of soil NH4+ from a range of +0.6% per hundred to +2.9% per hundred to a range of +4.6% per hundred to +7.0% per hundred most likely through increased nitrification following enhanced mineralization. Plant uptake of 15N-enriched NH4+ in the drained treatment resulted in higher plant delta15N (+0.8% per hundred to +1.8% per hundred in the drained plots and -3.9% per hundred to -5.4% per hundred in the undrained plots), and deposition of litterfall N enriched with 15N increased the delta15N of total soil N in the surface layer in the drained (+2.9% per hundred) as compared with that in the undrained plots (+0.6% per hundred). The effect of drainage on foliar delta(13)C was species-specific, i.e., only tamarack showed a considerably less negative foliar delta(13)C in the drained (-28.1% per hundred) than in the undrained plots (-29.1% per hundred), indicating improved water use efficiency (WUE) by drainage. Tree ring area increments were significantly increased following drainage, and delta(13)C and delta(15)N in tree growth rings of both species showed responses to drainage retrospectively. Tree-ring delta(13)C data suggested that drainage improved WUE of both species, with a greater and more prolonged response in tamarack than in black spruce. Our results indicate that drainage caused the studied minerotrophic peatland to become a more open ecosystem in terms of C and N cycling and loss. The effects of forested peatland drainage or drying on C and N balances deserve further research in order to better understand their roles in future global change. 相似文献
This paper discusses challenges arising in the design of networks for monitoring extreme values over the domain of a random environmental space-time field {Xij} i = 1, . . . , I denoting site and j = 1, . . . denoting time (e.g. hour). The field of extremes for time span r over site domain i = 1, . . . ,I is given by \(\{Y_{i(r+1)}=\max_{j=k}^{k+n-1} X_{ij}\}\) for k = 1 + rn, r = 0, . . . ,. Such networks must not only measure extremes at the monitored sites but also enable their prediction at the non-monitored ones. Designing such a network poses special challenges that do not seem to have been generally recognized. One of these problems is the loss of spatial dependence between site responses in going from the environmental process to the field of extremes it generates. In particular we show empirically that the intersite covariance Cov(Yi(r+1),Yi′(r+1)) can generally decline toward zero as r increases, for site pairs i ≠ i′. Thus the measured extreme values may not predict the unmeasured ones very precisely. Consequently high levels of pollution exposure of a sensitive group (e.g. school children) located between monitored sites may be overlooked. This potential deficiency raises concerns about the adequacy of air pollution monitoring networks whose primary role is the detection of noncompliance with air quality standards based on extremes designed to protect human health. The need to monitor for noncompliance and thereby protect human health, points to other issues. How well do networks designed to monitor the field monitor their fields of extremes? What criterion should be used to select prospective monitoring sites when setting up or adding to a network? As the paper demonstrates by assessing an existing network, the answer to the first question is not well, at least in the case considered. To the second, the paper suggests a variety of plausible answers but shows through a simulation study, that they can lead to different optimum designs. The paper offers an approach that circumvents the dilemma posed by the answer to the second question. That approach models the field of extremes (suitably transformed) by a multivariate Gaussian-Inverse Wishart hierarchical Bayesian distribution. The adequacy of this model is empirically assessed in an application by finding the relative coverage frequency of the predictive credibility ellipsoid implied by its posterior distribution. The favorable results obtained suggest this posterior adequately describes that (transformed) field. Hence it can form the basis for designing an appropriate network. Its use is demonstrated by a hypothetical extension of an existing monitoring network. That foundation in turn enables a network to be designed of sufficient density (relative to cost) to serve its regulatory purpose. 相似文献
We demonstrated a method to form magnetic antimicrobial POHABA (poly-N,N′-[(4,5-dihydroxy-1,2-phenylene)bis(methylene)]bisacrylamide)-based core-shell nanostructure by free-radical polymerization of OHABA on the Fe3O4 core surface. The magnetic antimicrobial agent Fe3O4@POHABA can be used in domestic water treatment against bacterial pathogens. The thickness of POHABA shell could be controlled from 10.4 ± 1.2 to 56.3 ± 11.7 nm by the dosage of OHABA. The results of antimicrobial-activity test indicated that POHABA-based core-shell nanostructure had broad-spectrum inhibitory against Gram-negative, Gram-positive bacteria and fungi. The minimum inhibitory concentration (MIC) values of Fe3O4@POHABA nanostructure against Escherichia coli and Bacillus subtilis were both 0.4 mg/mL. Fe3O4@POHABA nanostructures responded to a permanent magnet and were easily recycled. Fe3O4@POHABA nanoparticles retained 100% antimicrobial efficiency for both Gram-negative and Gram-positive bacteria throughout eight recycle procedures.