# Patterns of Arctic Tundra Greenness Based on Spatially Downscaled Solar-Induced Fluorescence
## 4 Discussion  
Unlike previous studies that have shown Arctic tundra greening as the overall trend with browning at some small regions [4; 13; 25; 26], our study found that most parts of the Arctic tundra below 75\({}^{\circ}\) N were browning based on SIF data. The browning trend of Arctic tundra at the Arctic Coastal Plain of northern Alaska were similar to the pattern found by [PERSON] et al. [27]. Meanwhile, [PERSON] et al. [48] also indicated the negative trend of tundra greenness from 2008. The Arctic tundra browning may be event-driven, as postulated by [PERSON] and [PERSON] [4], such as the shrub expansion in the Arctic tundra ecosystem [18; 49], extreme winter warming [20], fire [50; 51], outbreaks of defoliating insects and rust fungi, and frost drought [52]. The increase of herbivore populations is another potential  
Figure 4: Comparison between the tundra greenness (GIMMS NDVI3g, MOD13Q1 and SIF) and the maximum value of monthly GPP derived from (**a**) RU-Sam, (**b**) RU-Tks, and (**c**) RU-Cok. The greenness was calculated as the 3 pixel \(\times\) 3 pixel average value around the EC flux tower for each year. For more details about EC flux sites, see Table 2. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Site Name** & **Data** & **R\({}^{2}\)** & \(p\)**-Value** \\ \hline \multirow{4}{*}{RU-Sam} & GIMMS & 0.0536 & 0.0006 \\  & MODIS & 0.0195 & 0.0008 \\  & SIF & 0.0753 & 0.0001 \\  & GIMMS & \textless{}0.0001 & \textless{}0.0001 \\ RU-Tks & MODIS & \textless{}0.0001 & \textless{}0.0001 \\  & SIF & 0.5525 & \textless{}0.0001 \\  & GIMMS & 0.1498 & \textless{}0.0001 \\ RU-Cok & MODIS & 0.0625 & \textless{}0.0001 \\  & SIF & 0.1785 & \textless{}0.0001 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Statistical comparison of greenness (GIMMS NDVI3g, MOD13Q1, and SIF) with the three EC tower measurements (maximum value of monthly GPP, unit: g C m\({}^{-2}\) day\({}^{-1}\)). cause of tundra browning [25; 53; 54]. Additionally, landforms may be the most important predictor of browning followed by recent climate change [26]. For the greenness indicator, the NDVI is used to indicate radiation absorption rather than carbon assimilation. SIF is used to indicate actual photosynthesis rather than potential photosynthesis [31; 55]. In addition, the downscaled SIF data used for the study can be considered as a proxy for GPP [37]. Taking flux site \"RU-Tks\" as an example, the R\({}^{2}\) between the SIF and GPP was higher than for the two NDVI data, and the trends of the SIF and GPP both indicated that the tundra nearby was \"browning\" from 2007 to 2013 (Figures 2 and 4, Table 3). The low R\({}^{2}\) values may be due to these reasons: (i) Only three flux sites were available for the comparison, and the only seven years were used for the analysis. Limited ground observed data can be used for comparison and validation. (ii) The footprint of the EC-observed GPP was typically less than 1-3 km\({}^{2}\)[56], while the spatial resolution of the SIF was much coarser. The different greenness trends may have been caused by the different sensors (spatial resolution-GIMMS NDVI3g: 8 km; MOD13Q1: 250 m; SIF: 0.05 degree, approximately 5 km), spatial coverage and the sun-target-sensor geometry. Compared to the GIMMS NDVI3g, the MOD13Q1 and SIF have a finer spatial resolution with more detailed information, which may also bring more information for calculation, especially for the Arctic region. Meanwhile, the NDVIs were derived from different sensors, and not cross validated [57; 58; 27]. The spatial coverage of the NDVI was larger than SIF: No data existed higher than 75\({}^{\circ}\) N for SIF; however, the statistics region of the NDVI is whole study area. When the spatial region of the NDVI was the same as the SIF, (i) the temporal patterns (2007-2013) of GIMMS NDVI3g and MOD13Q1 were similar with the NDVI result covering the whole Arctic region, and (ii) the NDVI values of GIMMS NDVI3g and MOD13Q1 were a little larger.