Tall shrubs and trees are advancing into many tundra and wetland ecosystems but at a rate that often falls short of that predicted due to climate change. For forest, tall shrub, and tundra ecosystems in two pristine mountain ranges of Alaska, we apply a Bayesian, error-propagated calculation of expected elevational rise (climate velocity), observed rise (biotic velocity), and their difference (biotic inertia). We show a sensitive dependence of climate velocity on lapse rate and derive biotic velocity as a rigid elevational shift. Ecosystem presence identified from recent and historic orthophotos ~50 years apart was regressed on elevation. Biotic velocity was estimated as the difference between critical point elevations of recent and historic logistic fits divided by time between imagery. For both mountain ranges, the 95% highest posterior density of climate velocity enclosed the posterior distributions of all biotic velocities. In the Kenai Mountains, mean tall shrub and climate velocities were both 2.8 m y(-1). In the better sampled Chugach Mountains, mean tundra retreat was 1.2 m y(-1) and climate velocity 1.3 m y(-1). In each mountain range, the posterior mode of tall woody vegetation velocity (the complement of tundra) matched climate velocity better than either forest or tall shrub alone, suggesting competitive compensation can be important. Forest velocity was consistently low at 0.1-1.1 m y(-1), indicating treeline is advancing slowly. We hypothesize that the high biotic inertia of forest ecosystems in south-central Alaska may be due to competition with tall shrubs and/or more complex climate controls on the elevational limits of trees than tall shrubs. Among tall shrubs, those that disperse farthest had lowest inertia. Finally, the rapid upward advance of woody vegetation may be contributing to regional declines in Dall's sheep (Ovis dalli), a poorly dispersing alpine specialist herbivore with substantial biotic inertia due to dispersal reluctance.

[1] The complex response of the forest-tundra ecotone (FT) to climate change may not generalize well geographically. We document FT changes in a nonpermafrost region of southcentral Alaska during a known warming period. Using 1951 and 1996 orthophotos overlain on digital elevation models across 800 km 2 of the west Kenai Mountains, we identified cover classes and topography for 978 random points and the highest closedcanopy conifer patches along 205 random altitudinal gradients. Results show 29% of FT area increased in woodiness, with closed-canopy forest expanding 14%/decade and shrubs 4%/decade; unvegetated areas decreased 17.4%/decade and tundra 5%/decade. Area of open woodland remained constant but changed location. Timberline, estimated using both the 205 altitudinal gradients and the upper quartile elevations of closed-canopy forest among the 978 points, rose very little. Tree line, identified using upper quartiles of open woodland, rose $50 m on cool, northerly aspects, but not on other aspects. Dendrochronology on high-elevation seedlings showed a congruence between decadal recruitment and regional changes in climate from 1945 to 2005. Patterns observed in the climatic FT of the Kenai Mountains corroborate other studies that show regional and landscape specificity of the structural response of FT to climate change. FT shifted upwards on cooler, presumably more mesic aspects near seed sources; however, on warm aspects the density of shrubs and trees increased, but FT did not rise. If current conditions continue for the next 50-100 years, the Kenai FT will markedly change to a far woodier landscape with less tundra and more closed-canopy forest.Citation: Dial, R. J., E. E. Berg, K. Timm, A. McMahon, and J. Geck (2007), Changes in the alpine forest-tundra ecotone commensurate with recent warming in southcentral Alaska: Evidence from orthophotos and field plots,

ABSTRACT. We analyzed glacier surface elevations (1957, 2010 and 2015) and surface mass-balance measurements (2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) shifting the glacier hypsometry downward and resulting in more negative mass balances: an altitudemass-balance feedback. Net mass loss from Eklutna Glacier accounts for 7 ± 1% of the average inflow to Eklutna Reservoir, which is entirely used for water and power by Anchorage, Alaska's largest city.If the altitude-mass-balance feedback continues, this 'deglaciation discharge dividend' is likely to increase over the short-term before it eventually decreases due to diminishing glacier area.

Summary Tall‐shrub expansion into low‐statured communities, a hallmark of recent vegetative change across tundra ecosystems, involves three major genera: Alnus, Betula and Salix. Which genus expands most into tundra landscapes will determine ecosystem properties. We show that Alnus and Salix shrubs segregate thermal space (elevation × insolation) and colonize tundra landscapes differently in response to climate warming, thereby replacing different tundra types. Vegetative change estimated from repeat photography should account for hill‐slope. Methodologically, slope determines surface area estimated from orthophotos as projected pixel area times secant of pixel slope. Ecologically, the change in thermally responsive vegetative area is sensitive to terrain steepness, scaling as the cosecant of hill‐slope, so that studies should expect more shrub expansion in areas of shallow slopes than steep slopes. Repeat aerial photography in Alaska's Chugach Mountains from 1972 to 2012 orthorectified on a high‐resolution lidar digital elevation model indicated tall Salix was rare in 1972 and colonized warmer slopes by 2012. Tall Alnus colonized steeper, cooler slopes both by 2012 and by 1972. Salix and forest colonized similar thermal space. Colonization probability for both shrub genera was maximized at intermediate elevations. Alnus colonization adjacent to dwarf‐shrub tundra was twenty times as likely as Salix colonization. Salix colonization adjacent to low‐shrub/herbaceous tundra was three times as likely as Alnus colonization. Replacement of dwarf‐shrub tundra by Alnus and of low‐shrub/herbaceous communities by Salix will affect herbivores and soil properties. Good agreement between observations of plant functional type and multinomial predictions in a thermal space defined by elevation and insolation suggested that these two variables were sufficient for forecast modelling. Spatially explicit, climate‐driven generalized linear multinomial and random forest classification models in available thermal space forecast surface areas of forest, Alnus, Salix and tundra over a range of warming, modelled as upward shifted isotherms, including expected IPCC scenarios. Both modelling approaches indicated that shrubs may respond nonlinearly to warming. Synthesis. The provision of taxon‐specific coefficients for climate‐driven, spatially explicit models using high‐resolution digital elevation models is necessary for accurately forecasting vegetative change due to climate warming in montane and arctic regions.

Abstract. Datasets from a 4-year monitoring effort at Lake Peters, a glacier-fed lake in Arctic Alaska, are described and presented with accompanying methods, biases, and corrections. Three meteorological stations documented air temperature, relative humidity, and rainfall at different elevations in the Lake Peters watershed. Data from ablation stake stations on Chamberlin Glacier were used to quantify glacial melt, and measurements from two hydrological stations were used to reconstruct continuous discharge for the primary inflows to Lake Peters, Carnivore and Chamberlin creeks. The lake's thermal structure was monitored using a network of temperature sensors on moorings, the lake's water level was recorded using pressure sensors, and sedimentary inputs to the lake were documented by sediment traps. We demonstrate the utility of these datasets by examining a flood event in July 2015, though other uses include studying intra- and inter-annual trends in this weather–glacier–river–lake system, contextualizing interpretations of lake sediment cores, and providing background for modeling studies. All DOI-referenced datasets described in this paper are archived at the National Science Foundation Arctic Data Center at the following overview web page for the project: https://arcticdata.io/catalog/view/urn:uuid:df1eace5-4dd7-4517-a985-e4113c631044 (last access: 13 October 2019; Kaufman et al., 2019f).