Forests on the move: Tracking climate-related treeline changes in mountains of the northeastern United States

Aim Alpine treeline ecotones are influenced by environmental drivers and are anticipated to shift their locations in response to changing climate. Our goal was to determine the extent of recent climate-induced treeline advance in the northeastern United States, and we hypothesized that treelines have advanced upslope in complex ways depending on treeline structure and environmental conditions. Location White Mountain National Forest (New Hampshire) and Baxter State Park (Maine), USA. Taxon High-elevation trees – Abies balsamea, Picea mariana, and Betula cordata. Methods We compared current and historical high-resolution aerial imagery to quantify the advance of treelines over the last four decades, and link treeline changes to treeline form (demography) and environmental drivers. Spatial analyses were coupled with ground surveys of forest vegetation and topographical features to ground-truth treeline classification and provide information on treeline demography and additional potential drivers of treeline locations. We used multiple linear regression models to examine the importance of both topographic and climatic variables on treeline advance. Results Regional treelines have significantly shifted upslope over the past several decades (on average by 3 m/decade). Diffuse treelines (low tree densities and temperature limited) experienced significantly greater upslope shifts (5 m/decade) compared to other treeline forms, suggesting that both climate warming and treeline demography are important drivers of treeline shifts. Topographical features (slope, aspect) as well as climate (accumulated growing degree days, AGDD) explained significant variation in the magnitude of treeline advance (R2 = 0.32). Main conclusions The observed advance of regional treelines suggests that climate warming induces upslope treeline shifts particularly at higher elevations where greater upslope shifts occurred in areas with lower AGDD. Overall, our findings suggest that diffuse treelines at high-elevations are more a of a result of climate warming than other alpine treeline ecotones and thus they can serve as key indicators of ongoing climatic changes.Associated csv's require R (or Excel) to be loaded and for data to be analyzed. Funding provided by: Edna Bailey Sussman FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100006517Award Number: Funding provided by: National Science FoundationCrossref Funder Registry ID: http://dx.doi.org/10.13039/100000001Award Number: 1759724Remote sensing analysis Physical copies of true color high resolution historical aerial imagery (sub-meter resolution) were acquired from the Appalachian Mountain Club (AMC) and the USFS White Mountain National Forest Headquarters. Imagery for the Presidential Range was taken in 1978 and Katahdin imagery was taken in 1991. Hard copy images were scanned and converted to TIFF format at 300 dpi (resulting in 0.5 m resolution images). Spatial analyses of change in treeline positions over time were enabled by acquiring high resolution 2018 false-color near-infrared imagery from the National Agriculture Inventory Program (NAIP 2021). Both sets of imagery were taken during summer months (1:40,000 scale). Using ArcGIS 10.8 (ESRI 2011, Redlands, CA, USA), historic imagery was ortho- and georectified to newer imagery via a spline function along 60 ground control points, and then converted into one orthomosaic image (RMSE < 1m). Exact error was always below 5 m for each individual image. All areas above treeline were manually digitized based on observed tree cover for both sets of images, and the resulting polygons were converted to raster format at 2 m resolution (all raster pixels within each polygon had a value of 1). We identified forest cover only as areas with overlapping crowns and seen as green reflectance in historic imagery and red reflectance in contemporary false-color near-infrared imagery (no visible bare earth or easily identified alpine vegetation). Isolated tree island edges were also digitized and included as treeline if they were >20 m in diameter in any direction (determined in ArcGIS) and included an individual >2 m in height as validated in the field. Alpine rasters were aligned to and multiplied by Lidar-derived digital elevation models (DEMs; 2 m resolution) acquired from New Hampshire and Maine state GIS repositories in order to determine treeline elevations. A total of 400 random sample points (200 for each range, using the ArcGIS random sample point tool) were placed along the outer boundary of the alpine rasters derived from our contemporary imagery, and for each of them we established a paired point at the nearest location along the alpine raster boundary derived from our historic imagery. Field surveys Field sampling was carried out in the summer of 2021 to characterize tree demography and demographic variation among different treeline forms identified from the current imagery. A subset of contemporary points from our GIS-based sample point pairs (n = 54, 33 in the Presidential Range, 21 in the Katahdin Range, see above) were selected using a random number generator to serve as sites for establishing belt transects. Each belt transect was 100 m in length and 4 m wide (2 m on either side of transect for a total area of 400 m2) and perpendicular to elevation contours, spanning the ecotone between closed forest interior and open alpine habitat. The start of each transect (the lowest elevation on the transect, set as 0 m) was located 50 m downslope (straight-line distance) of contemporary sample points. The start and end of each belt transect were recorded using a Garmin GPSMAP 64 (Garmin, Olathe, Kansas, USA). Each tree > 0.1 m in height with a stem rooted within the transect was recorded noting species, basal diameter (10 cm from the ground), height, horizontal distance from the transect, and distance along the transect (to estimate stem density of trees). Slope, aspect, elevation, and soil depth to bedrock (using a metal soil probe) were recorded at 20 m intervals along the belt transect centerline (0 m, 20 m, 40 m, 60 m, 80 m, 100 m). For all belt transects, treeline form was assigned based on visual assessments (based on changes in tree height and density across the ecotone). Additionally, we visited a majority of our other accessible contemporary random sample points (~80%) in order to assign treeline form and ground-truth remote sensed treeline classifications. For all visited sample points we took a new GPS point at the field-verified treeline location (continuous canopy cover and at least one individual >2 m in height) nearest to our random sample points (assigned from our treeline delineation procedure). The new points were compared to the original sample point locations and assessed for accuracy (measuring linear distance between points). Eye-level photos of treelines were taken at all sample points to keep a permanent record of treeline appearance. We stress that because tree height could not be extracted or field validated from our historic imagery, some krummholz individuals (