Using aerial lidar to understand the role of climate and herbivory in shaping forest demographics at the Arctic forest-tundra ecotone
Abstract
Climate change may cause spatial shifts in the Arctic forest-tundra ecotone (FTE). Spatially explicit data on the current age structure of FTE forest stands may provide insight on the influence of historical environmental changes. However, accessing remote FTE locations with sufficient in situ sampling to construct demographic data is challenging. Our goal is to study FTE forest stand population dynamics secondary to changes in climate and herbivory using lidar remote sensing.
For this, we built a linear regression model predicting tree age (tree cores extracted at basal height) from tree height (via terrestrial lidar scans; <1 cm point spacing) using 62 white spruce (Picea glauca) trees at six FTE sites in Northern Alaska. Tree height ranged between 0.29 and 15.2 m tall and age between 14 and 230 years old. This model shows a good predictive relationship between tree height and age (R2 = 0.6951, RMSE = 29.32 years). By applying this model to tree height extracted from five aerial lidar scenes via an individual tree detection algorithm, we predicted age for white spruce trees (N = 41,722) across 278 hectares at the FTE. The resulting demographic data is being analyzed in the context of 20th century climate and herbivory at the FTE using a linear mixed effects analysis. Fixed effects include seasonal averages of temperature, precipitation (CRU TS V4.01), snow accumulation (NOAA), annual herbivore density (Lepus americanus; Olnes and Kielland 2017) and year of tree establishment; season is considered a random effect. Preliminary results suggest that temporal variability in both herbivory and environmental conditions play important, although varying, roles in tree population dynamics at our FTE study region. Our analysis demonstrates that lidar-derived tree height can describe FTE forest demography, and may be a valuable tool to understanding the vulnerability of this rapidly changing ecosystem to climate change.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.B21E..01J
- Keywords:
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- 0414 Biogeochemical cycles;
- processes;
- and modeling;
- BIOGEOSCIENCESDE: 0439 Ecosystems;
- structure and dynamics;
- BIOGEOSCIENCESDE: 0475 Permafrost;
- cryosphere;
- and high-latitude processes;
- BIOGEOSCIENCESDE: 1640 Remote sensing;
- GLOBAL CHANGE