Postfire succession in the Alaskan boreal forest follows several different pathways, the most common being self-replacement and species-dominance relay. In self-replacement, canopy-dominant tree species replace themselves as the postfire dominants. It implies a relatively unchanging forest composition through time maintained by trees segregated within their respective, ecophysiological niches on an environmentally complex landscape. In contrast, species-dominance relay involves the simultaneous, postfire establishment of multiple tree species, followed by later shifts in canopy dominance. It implies that stand compositions vary with time since last fire. The relative frequencies of these and other successional pathways are poorly understood, despite their importance in determining the species mosaic of the present forest and their varying, potential responses to climate changes. Here we assess the relative frequencies of different successional pathways by modeling the relationship between stand type, solar insolation, and altitude; by describing how stand age relates to species composition; and by inferring successional trajectories from stand understories. Results suggest that >70% of the study forest is the product of self-replacement, and tree distributions are controlled mainly by the spatial distribution of solar insolation and altitude, not by time since last fire. As climate warms over the coming decades, deciduous trees will invade cold sites formerly dominated by black spruce, and increased fire frequency will make species-dominance relay even rarer.Résumé : La succession après feu dans la forêt boréale de l'Alaska adopte différents modes, les plus communs étant le retour des mêmes espèces et la dominance successive de différentes espèces. Dans le cas du retour des mêmes espèces, les espèces d'arbres qui dominent la canopée sont remplacées par les mêmes espèces qui deviennent dominantes après un feu. Cela implique que la composition de la forêt qui demeure relativement stable dans le temps soit maintenue par des arbres qui sont restreints à leur niche écologique respective dans un paysage complexe du point de vue environnemental. Au contraire, la dominance successive de différentes espèces suppose l'établissement après feu de plusieurs espèces d'arbres suivi par des changements ultérieurs de dominance dans la canopée. Cela signifie que la composition du peuplement change avec le temps après un feu. Les fréquences relatives de ces modes de succession et d'autres sont peu connues malgré leur importance dans la détermination de la mosaïque d'espèces de la forêt actuelle et de leurs différentes réactions potentielles aux changements climatiques. Dans cet article, nous évaluons la fréquence relative de différents modes de succession en modélisant la relation entre le type de peuplement, l'ensoleillement et l'altitude; en décrivant comment la composition en espèces est reliée à l'âge du peuplement et en déduisant le mode de succession à partir du sous-étage d'un peuplement. Les résultats indiquent que plus de ...

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Abstract:The lowest elevation of spring snow ("snowline") is an important factor influencing recruitment and survival of wildlife in alpine areas. In this study, we assessed the spatial and temporal variability of alpine spring snowline across major Dall sheep mountain areas in Alaska and northwestern Canada. We used a daily MODIS snow fraction product to estimate the last day of 2000-2016 spring snow for each 500-m pixel within 28 mountain areas. We then developed annual (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016) regression models predicting the elevation of alpine snowline during mid-May for each mountain area. MODIS-based regression estimates were compared with estimates derived using a Normalized Difference Snow Index from Landsat-8 Operational Land Imager (OLI) surface reflectance data. We also used 2000-2009 decadal climate grids to estimate total winter precipitation and mean May temperature for each of the 28 mountain areas. Based on our MODIS regression models, the 2000-2016 mean 15 May snowline elevation ranged from 339 m in the cold arctic class to 1145 m in the interior mountain class. Spring snowline estimates from MODIS and Landsat OLI were similar, with a mean absolute error of 106 m. Spring snowline elevation was significantly related to mean May temperature and total winter precipitation. The late spring of 2013 may have impacted some sheep populations, especially in the cold arctic mountain areas which were snow-covered in mid-May, while some interior mountain areas had mid-May snowlines exceeding 1000 m elevation. We found this regional (>500,000 km 2 ) remote sensing application useful for determining the inter-annual and regional variability of spring alpine snowline among 28 mountain areas.

High-latitude systems in northwestern Canada and Alaska have warmed rapidly. The aim of this study was to examine how a remotely sensed proxy of vegetation productivity varied among mountain ranges with respect to elevation and climate from 2002-2017. Our study area included high-latitude mountains in Alaska, USA, and Yukon Territory, Canada, ranging from cold arctic mountains in the tundra biome to warmer interior mountains areas within the boreal biome. We used the annual maximum Normalized Difference Vegetation Index (NDVI) data from the 250-m MODIS NDVI product as a proxy of maximum growing season photosynthetic activity. The longterm (16-year) and interannual pattern of maximum NDVI was investigated with respect to elevation, July temperature, and July precipitation classes within four climatic mountain regions. The July temperature lapse rate was consistently linear, whereas the long-term maximum NDVI lapse rate was nonlinear. At lower elevations, the high-precipitation region had the highest NDVI, whereas the interior mountains region had the highest NDVI at higher elevations. The long-term maximum NDVI was negatively correlated with July precipitation for areas with July temperature below 12°C. Above 12°C, NDVI was positively correlated with July precipitation, with the greatest rate of NDVI increase with precipitation at the warmest July temperature class. The pattern of interannual peak NDVI with respect to July temperature was not as strong as the long-term pattern; however, the only interannual negative correlation between peak NDVI and July temperature was at lower elevations within the interior mountains. We concluded that among a regional climatic gradient of mountain areas, low growing season temperature and length were likely constraining vegetation productivity, and lower growing season moisture may be an important constraint at the warmest interior mountains region. ARTICLE HISTORY