Spaceborne potential for examining taiga–tundra ecotone form and vulnerability

Abstract

Abstract. In the taiga-tundra ecotone (TTE), site-dependent forest structure characteristics can influence the subtle and heterogeneous structural changes that occur across the broad circumpolar extent. Such changes may be related to ecotone form, described by the horizontal and vertical patterns of forest structure (e.g., tree cover, density, and height) within TTE forest patches, driven by local site conditions, and linked to ecotone dynamics. The unique circumstance of subtle, variable, and widespread vegetation change warrants the application of spaceborne data including high-resolution (< 5 m) spaceborne imagery (HRSI) across broad scales for examining TTE form and predicting dynamics. This study analyzes forest structure at the patch scale in the TTE to provide a means to examine both vertical and horizontal components of ecotone form. We demonstrate the potential of spaceborne data for integrating forest height and density to assess TTE form at the scale of forest patches across the circumpolar biome by (1) mapping forest patches in study sites along the TTE in northern Siberia with a multi-resolution suite of spaceborne data and (2) examining the uncertainty of forest patch height from this suite of data across sites of primarily diffuse TTE forms. Results demonstrate the opportunities for improving patch-scale spaceborne estimates of forest height, the vertical component of TTE form, with HRSI. The distribution of relative maximum height uncertainty based on prediction intervals is centered at ∼ 40 %, constraining the use of height for discerning differences in forest patches. We discuss this uncertainty in light of a conceptual model of general ecotone forms and highlight how the uncertainty of spaceborne estimates of height can contribute to the uncertainty in identifying TTE forms. A focus on reducing the uncertainty of height estimates in forest patches may improve depiction of TTE form, which may help explain variable forest responses in the TTE to climate change and the vulnerability of portions of the TTE to forest structure change.

Patterns of Arctic Tundra Greenness Based on Spatially Downscaled Solar-Induced Fluorescence

“…Arctic tundra greening was also observed or simulated at the circumpolar Arctic region [5][6][7][8], Eurasian Arctic [9][10][11], Alaska [2,12,13], and Canada [14]. It is speculated that a positive NDVI trend may be in response to climate warming or reduced snow cover, which would lead to the expansion of vegetation in the tundra [15][16][17][18][19], changing phenological periods [20,21], increased biomass [22,23], and surface water variation associated with thermokarst [24]. Since 2011, regional surface browning trends have been observed that have reversed the direction of the Arctic greening trend after nearly 33 years [4,5,25,26].…”

Space‐Based Observations for Understanding Changes in the Arctic‐Boreal Zone

“…For example, LAI and the fraction of absorbed photosynthetically active radiation (fAPAR) are critical constraints on carbon cycling and have been derived from a variety of sensors (Myneni et al, ; Zhu et al, ). Properties such as percent tree cover (Montesano et al, ) and land cover type, including forest genera and even species (Beaudoin et al, ), are essential for quantifying large‐scale vegetation distributions and their changes. Finally, forest volume characteristics, such as biomass, tree height, and related canopy properties, can be derived most successfully from lidar (Neigh et al, ).…”

“…Landsat science was revolutionized in 2008 when the USGS provided open access to the archive in a consistent and user‐friendly format (Kennedy et al, ; Wulder et al, ). With subsequent consolidation of the Landsat archive (Wulder et al, ) and increases in computing power, a variety of processing tools (e.g., Google Earth Engine) and circumpolar data products related to tree cover, productivity, and disturbance history (e.g., Hansen et al, ; Ju & Masek, ; Montesano, Sun, et al, ; Sexton et al, ; White et al, ) are now available to the community. Although at a much coarser spatial resolution (1–8 km), the AVHRR family of satellites has provided continuous data since 1978, and particularly since 1981 with the operation of AVHRR/2 on board NOAA‐7.…”

Implementing spatially explicit wind-driven seed and pollen dispersal in the individual-based larch simulation model: LAVESI-WIND 1.0

“…How fast vegetation communities can follow their shifting climate envelope in a changing environment is determined by their ability to migrate. This is exceptionally challenging under current global change and plants might strongly lag behind their moving climate envelope (Harsch et al, 2009;Loarie et al, 2009;Moran and Clark, 2012). Temperatures are increasing most strongly in the Arctic.…”

“…During the past decades treeline stands in the Siberian Arctic were densifying, but only rather slowly colonizing the tundra (Frost et al, 2014;Kharuk et al, 2006;Montesano et al, 2016), which could be attributed to seed limitation (Wieczorek et al, 2017). We developed the Larix vegetation simulator, LAVESI, to simulate tree stand dynamics at the Siberian treeline on the southern Taymyr Peninsula and use it as a framework to explore impacts of climate change on larch forests .…”