Assessing the dynamics of vegetation productivity in circumpolar regions with different satellite indicators of greenness and photosynthesis

Abstract

Abstract. High latitude treeless ecosystems represent spatially highly heterogeneous landscapes with small net carbon fluxes and a short growing season. Reliable observations and process understanding are critical for projections of the carbon balance of climate sensitive tundra. Spaceborne remote sensing is the only tool to obtain spatially continuous and temporally resolved information on vegetation greenness and activity in remote circumpolar areas. However, confounding effects from persistent clouds, low sun elevation angles, numerous lakes, widespread surface inundation, and the sparseness of the vegetation render this. Delayed peak greenness compared to peak photosynthesis is consistently found across years and land cover classes. A particularly late peak of NDVI in regions with very small seasonality in greenness and a high amount of lakes probably originates from artefacts. Given the very short growing season in circumpolar areas, the average time difference in maximum annual photosynthetic activity and greenness/growth of 3 to 25 days (depending on the data sets chosen) is important and needs to be considered when using satellite observations as drivers in vegetation models.

Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress

“…Those studies found a good correspondence between the temporal trajectories of retrieved far-red SIF and GPP, which performed as well as remote sensing-based vegetation parameters. Initial indications are that far-red SIF might also contain information about LUE -in this case, in tundra vegetationand this aspect warrants further study (Walther et al, 2018).…”

“…Several satellite-based trials have reported the potential of far-red SIF to indicate drought and temperature stress at ecosystem scales (Berkelhammer et al, 2017;Koren et al, 2018;Song et al, 2018;Sun et al, 2015;Wang et al, 2018Wang et al, , 2016Wu et al, 2018;Yoshida et al, 2015;Zuromski et al, 2018). Others have used far-red SIF to monitor the dynamics of photosynthesis in the Amazon forest (e.g., Alden et al, 2016;Guan et al, 2015;Köhler et al, 2018b;Koren et al, 2018;Lee et al, 2013;Parazoo et al, 2013;Yang et al, 2018a), high-latitude forests (Jeong et al, 2017;Walther et al, 2016), tundra ecosystems (Luus et al, 2017;Walther et al, 2018), dryland ecosystems of southwestern North America (Smith et al, 2018;Zhang et al, 2016c), and across Australia (Ma et al, 2016;Sanders et al, 2016). The links between large-scale far-red SIF and GPP (e.g., He et al, 2017;Koffi et al, 2015;Zhang et al, 2018b) have resulted in the use of SIF to analyse the coupling between carbon and water fluxes at regional to global scales (e.g., Alemohammad et al, 2017;Cui et al, 2017b;Green et al, 2017;Madani et al, 2017;Qiu et al, 2018;Wagle et al, 2016;Zhang et al, 2016b) and to benchmark GPP representations and other parameters in global models (e.g., Chang et al, 2016;Lee et al, 2015;…”

Canopy reflectance models illustrate varying NDVI responses to change in high latitude ecosystems

“…In high latitude ecosystems NDVI has been related to characteristics such as plant cover, green leaf area index (LAI), aboveground biomass, and vegetation productivity (Steltzer and Welker 2006, Riedel et al 2005a, Huemmrich et al 2010a, b, Pattison et al 2015, Walker et al 2003, Epstei et al 2012, Rocha et al 2012, Kobayashi et al 2018, Walther et al 2018. High latitudes are experiencing rapid climate change and the observed widespread NDVI changes are presumed to indicate ecosystem responses to climate (Myneni et al 1997, Jia et al 2009, Bhatt et al 2013.…”