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IMPORTANCE Early-onset atrial fibrillation (AF) can be the initial manifestation of a more serious underlying inherited cardiomyopathy or arrhythmia syndrome.OBJECTIVE To examine the results of genetic testing for early-onset AF. DESIGN, SETTING, AND PARTICIPANTSThis prospective, observational cohort study enrolled participants from an academic medical center who had AF diagnosed before 66 years of age and underwent whole genome sequencing through the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine program. Participants were enrolled from

IMPORTANCE Patients with early-onset atrial fibrillation (AF) are enriched for rare variants in cardiomyopathy and arrhythmia genes. The clinical significance of these rare variants in patients with early-onset AF is unknown.OBJECTIVE To assess the association between rare variants in cardiomyopathy and arrhythmia genes detected in patients with early-onset AF and time to death. DESIGN, SETTING, AND PARTICIPANTSThis prospective cohort study included participants with AF diagnosed before 66 years of age who underwent whole-genome sequencing through the National Heart, Lung and Blood Institute's Trans-Omics for Precision Medicine program.

On the basis of vegetational physiognomy, 47 sites within 1 to 43 km of the southern James Bay coast were classified in the field into four fen types: graminoid, low shrub, graminoid-rich treed, and sphagnum-rich treed. The four types are directly related to differences in vegetational cover and in soil and water parameters, specifically depth to water level, peat thickness, selected groundwater nutrients, and distance from the coast. Detrended correspondence analysis was used to ordinate the vegetational cover of the fen sites. No one or two of the 16 soil and water parameters obtained in this study could be used to discriminate conclusively among fen types. Linear discriminant function (LDF) analysis, however, indicated that the better discriminators were pH, peat thickness, SO4−, K+, and depth to water level. When all water and soil parameters were used, regrouping by LDF analysis into the four a priori groups was achieved with 78% accuracy. Canonical analysis also showed separations when soil and water parameters for sites were plotted in two dimensions. Because of isostatic rebound, distance from the coast represents a temporal as well as a spatial gradient. Peat depth in the fens increases with distance from the coast, at a mean rate of 4.7 cm for each kilometre inland. Na+ plus Cl− in the groundwater of the fens decreases asymptotically with increasing distance from the coast.

Forest sites are diagnostic forest-landscape ecosystem units that resource managers must deal with during the planning and implementation stages of management. Forest sites are the basic building blocks for undertaking integrated resource management which weighs wildlife, recreation, environmental impact and various other concerns along with timber harvesting. Consequently, accurate and practical systems for classifying and mapping forest sites are becoming increasingly necessary to organize, communicate and use existing and new management knowledge and experience effectively.Over the past four decades in Ontario, a number of studies and resource surveys have provided important background information on forest sites. Many have considered, to varying extents, the integrative roles of vegetation, soil-site, landform and general climate on forests and forest land. Generally, the emphasis has been on description and classification, with results generating a better understanding of how various forests in different areas develop, both qualitatively and quantitatively, in relation to soil-site or other features of the basic land resource. Some of these studies and surveys have been instrumental in advancing the definitions and understanding of forested ecosystems. Others have provided new information on site dynamics, interrelationships and functions, or have contributed to the science (and art) of site evaluation and classification.This paper briefly summarizes the current status of forest site classification in Ontario. Over time, the role of forest site classification has evolved in response to new technologies and information, and to new emphases and values in resource management. In general, site classification research has become increasingly integrative and quantitative. Some of the important future challenges facing forest site classification in Ontario are briefly discussed. Key words: ecological land classification, forest ecology, forest ecosystem classification, forest management interpretations, forest site classification, land use planning, Ontario.