RESUMO
In this Technical Advance, we describe a novel method to improve ecological interpretation of remotely sensed vegetation greenness measurements that involved sampling 24,395 Landsat pixels (30 m) across 639 km of Alaska's central Brooks Range. The method goes well beyond the spatial scale of traditional plot-based sampling and thereby more thoroughly relates ground-based observations to satellite measurements. Our example dataset illustrates that, along the boreal-Arctic boundary, vegetation with the greatest Landsat Normalized Difference Vegetation Index (NDVI) is taller than 1 m, woody, and deciduous; whereas vegetation with lower NDVI tends to be shorter, evergreen, or non-woody. The field methods and associated analyses advance efforts to inform satellite data with ground-based vegetation observations using field samples collected at spatial scales that closely match the resolution of remotely sensed imagery.
Assuntos
Imagens de Satélites , Tundra , Alaska , Regiões Árticas , Tecnologia de Sensoriamento Remoto/métodos , Taiga , Monitoramento Ambiental/métodosRESUMO
Climate-induced northward advance of boreal forest is expected to lessen albedo, alter carbon stocks, and replace tundra, but where and when this advance will occur remains largely unknown. Using data from 19 sites across 22 degrees of longitude along the tree line of northern Alaska, we show a stronger temporal correlation of tree ring growth with open water uncovered by retreating Arctic sea ice than with air temperature. Spatially, our results suggest that tree growth, recruitment, and range expansion are causally linked to open water through associated warmer temperatures, deeper snowpacks, and improved nutrient availability. We apply a meta-analysis to 82 circumarctic sites, finding that proportionally more tree lines have advanced where proximal to ongoing sea ice loss. Taken together, these findings underpin how and where changing sea ice conditions facilitate high-latitude forest advance.