1c:I[419806,["/_next/static/chunks/bb923814e1f4d2e9.js","/_next/static/chunks/dd3ee9f5b7716ca6.js","/_next/static/chunks/4204a0ae82542ca8.js","/_next/static/chunks/30036bedc5269936.js","/_next/static/chunks/6e1aa89a642f40be.js","/_next/static/chunks/cd5e572bc3e4eb92.js","/_next/static/chunks/8ffd0b71567920d8.js","/_next/static/chunks/67ea6dfd21f16c5f.js","/_next/static/chunks/24eb4379f68013fd.js","/_next/static/chunks/b8cd775ffdf935bd.js","/_next/static/chunks/983103cd9eb7b428.js","/_next/static/chunks/d4ac9dcf27f6ff52.js","/_next/static/chunks/294b9525248c8e5f.js"],"default"] 1d:T50b,Boreal and subarctic peatlands comprise a carbon pool of 455 Pg that has accumulated during the postglacial period at an average net rate of 0.096 Pg/yr (1 Pg = 10¹⁵ g). Using Clymo's (1984) model, the current rate is estimated at 0.076 Pg/yr. Longterm drainage of these peatlands is estimated to be causing the oxidation to CO₂ of a little more than 0.0085 Pg/yr, with conbustion of fuel peat adding °0.026 Pg/yr. Emissions of CH₄ are estimated to release ° 0.046 Pg of carbon annually. Uncertainties beset estimates of both stocks and fluxes, particularly with regard to Soviet peatlands. The influence of water table alterations upon fluxes of both CO₂ and CH₄ is in great need of investigation over a wide range of peatland environments, especially in regions where permafrost melting, thermokarst erosion, and the development of thaw lakes are likely results of climatic warming. The role of fire in the carbon cycle of peatlands also deserves increased attention. Finally, satellite-monitoring of the abundance of open water in the peatlands of the West Siberian Plain and the Hudson/James Bay Lowland is suggested as a likely method of detecting early effects of climatic warming upon boreal and subarctic peatlands.1e:T4de,The method of choice for multivariate representation of community structure is often non-metric multi-dimensional scaling (MDS). This has great flexibility in accomn~odating biologically relevant (i.e. non correlation-based) definitions of similarity In species composition of 2 samples, and in preserving the rank-order relations amongst those similarities in the placing of samples in an ordination. Correlation-based techniques (such as Canonical Correlation) are then inappropriate in linking the observed biotic structure to measured environmental variables; a more natural approach is simply to compare separate sample ordinations from biotic and abiotic variables and choose that subset of environmental variables which provides a good match between the 2 configurations. In fact, the fundamental constructs here are not the ordination plots but the (rank) similarity matrices which underlie them: a suitable measure of agreement between 2 such matrices is therefore proposed and used to define an optimal subset of environmental variables w h ~c h 'best explains' the biotic structure. This simple technique is illustrated wlth 3 data sets, from studles of macrobenthic, meiobenthic and diatom communities in estuarine and coastal waters.

	Year	Citations

References