Summer warming explains widespread but not uniform greening in the Arctic tundra biome

Berner, L. T.; Massey, Richard; Jantz, Patrick; Forbes, Bruce C.; Macias‐Fauria, Marc; Myers‐Smith, Isla H.; Kumpula, Timo; Gauthier, Gilles; Andreu‐Hayles, Laia; Gaglioti, Benjamin V.; Burns, Patrick J.; Zetterberg, Pentti; D’Arrigo, Rosanne; Goetz, Scott J.

doi:10.1038/s41467-020-18479-5

Cited by 249 publications

(270 citation statements)

References 102 publications

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“…Our results highlight that at finer spatial resolution, the relationship between satellite-derived spectra and biomass is not straightforward. This has implications for the observed Arctic greening or browning (Myers-Smith et al 2020;Berner et al 2020), as our results suggest that an increase in NDVI is not necessarily linked to increased biomass. This further complicates the interpretation of greening patterns (Myers-Smith et al 2020).…”

Section: Discussionmentioning

confidence: 74%

Aboveground biomass patterns across treeless northern landscapes

Räsänen

Wagner

Hugelius

et al. 2021

International Journal of Remote Sensing

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Aboveground vegetation biomass in northern treeless landscapespeatlands and Arctic tundra -has been modelled with spectral information derived from optical remote sensing in several studies. However, synthesized overviews of biomass patterns across circumpolar sites have been limited. Based on data from eight study sites in Europe, Siberia and Canada, we ask (1) how biomass is divided between plant functional types (PFTs) and ( 2) how well biomass patterns can be detected with widely available, moderate spatial resolution (3-10 m) satellite imagery and topographic data. We explain biomass patterns using random forest regressions with the predictors being spectral bands and indices calculated from multi-temporal Sentinel-2 and PlanetScope imagery and topographic information calculated from ArcticDEM data. Our results indicate that there are notable differences in vegetation composition between northern landscapes with mosses, graminoids and deciduous shrubs being the most dominant PFTs. Remote sensing data detects biomass patterns, but regression performance varies between sites (explained variance 36-70%, normalized root mean square error 9-19%). There is also variability between sites whether Sentinel-2 or PlanetScope data is more suitable to detect biomass patterns and which the most important predictors are. Topographic information has a minor or negligible importance in most of the sites. Our results suggest that there is no easily generalizable relationship between satellite-derived vegetation greenness and biomass.

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Section: Discussionmentioning

confidence: 74%

Aboveground biomass patterns across treeless northern landscapes

Räsänen

Wagner

Hugelius

et al. 2021

International Journal of Remote Sensing

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“…Previous studies based on remote sensing data or field simulation experiments have provided strong evidence that greening across Siberia is mainly driven by warming (Elmendorf et al 2012;Phoenix & Bjerke 2016). However, some studies have also indicated that the effect of warming on vegetation depends on soil moisture, with more positive effects in humid regions (Berner et al 2020). In other cases, changes in surface albedo, permafrost and soil nutrients could also influence the vegetation response to warming and even affect the key environmental constraints that limit vegetation activities (Myers-Smith et al 2015).…”

Section: Discussionmentioning

confidence: 99%

“…Vegetation greenness in Siberia has been observed to increase with climate warming, especially in regions primarily characterized by tundra shrubs, where considerable greening has been reported (Forbes, Fauria & Zetterberg 2010;Berner et al 2020). In the boreal forests and grasslands, the greening trend was relatively small (Fig.…”

Section: Discussionmentioning

confidence: 99%

“…Taiga and tundra have undergone significant changes in recent decades, so it is meaningful to assess them as clear examples of the influence of climate change on terrestrial ecosystems (Myers-Smith et al 2020). With climate warming, potential drivers of vegetation greenness in this region include permafrost, land cover, topography, and fire (Berner et al 2020). Previous studies have enriched our knowledge of the climate factors related to vegetation activities across Siberia.…”

Section: Introductionmentioning

confidence: 99%

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Warming enhanced the climate temporal effects on vegetation across Siberia

Shi¹,

Wang²,

Zhang³

et al. 2021

Preprint

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Widespread climate warming and growing season greening have been observed across most of the Northern Hemisphere in recent decades. However, the response of greening to amplified warming remains unclear with regard to the temporal effects (cumulative and time-lag effects) in cold regions of the Northern Hemisphere. We therefore provide a comprehensive analysis of the relationship between the enhanced vegetation index (EVI) and climate factors (e.g., land surface temperature (LST), precipitation, and solar radiation) across Siberia, which is experiencing rapid warming and greening, during 2000–2016 by using a random forest regression model. We found that solar radiation was the dominant driving factor of vegetation greening in 55.95% of the study area (concentrated in southwest Siberia), followed by temperature (41.28%, concentrated in northeast Siberia) and precipitation (2.78%). Furthermore, the cumulative and time-lag effects increased the explanation of vegetation variation by climate factors, from 0.71 to 0.78, and were observed in more than 80% of the area of Siberia. The average cumulative duration was 3.61 ± 1.97 months, and the time-lag period was 1.51 ± 1.20 months, with the longest term found in deciduous broadleaf forests and the shortest term found in shrublands. Our results indicated that the vegetation activities were influenced by cumulative effects combined with time-lag effects. The temporal effects varied with land cover categories, and the complex ecosystem generally corresponded to long-term temporal effects, and vice versa. Hence, the tundra shrub converted to boreal forest caused by warming in Siberia enhanced the climate temporal effects.

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“…Many recent studies have demonstrated a "greening" trend in vegetation cover both globally [85][86][87] and regionally, from the Arctic [88] to the tropics [85]. While obvious increases in vegetation greenness are associated with anthropogenic land use and land cover change (LULCC), such as expansion of irrigated agriculture and afforestation, greening is also occurring in regions with less direct human influence [85,88]. Potential causes of such increases involve nitrogen deposition [87], CO2 fertilization, and climate change [85].…”

Section: Discussionmentioning

confidence: 99%

Spatiotemporal Analysis of Vegetation Cover Change in a Large Ephemeral River: Multi-Sensor Fusion of Unmanned Aerial Vehicle (UAV) and Landsat Imagery

et al. 2020

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Ephemeral rivers in arid regions act as linear oases, where corridors of vegetation supported by accessible groundwater and intermittent surface flows provide biological refugia in water-limited landscapes. The ecological and hydrological dynamics of these systems are poorly understood compared to perennial systems and subject to wide variation over space and time. This study used imagery obtained from an unmanned aerial vehicle (UAV) to enhance satellite data, which were then used to quantify change in woody vegetation cover along the ephemeral Kuiseb River in the Namib Desert over a 35-year period. Ultra-high resolution UAV imagery collected in 2016 was used to derive a model of fractional vegetation cover from five spectral vegetation indices, calculated from a contemporaneous Landsat 8 Operational Land Imager (OLI) image. The Normalized Difference Vegetation Index (NDVI) provided the linear best-fit relationship for calculating fractional cover; the model derived from the two 2016 datasets was subsequently applied to 24 intercalibrated Landsat images to calculate fractional vegetation cover for the Kuiseb extending back to 1984. Overall vegetation cover increased by 33% between 1984 and 2019, with the most highly vegetated reach of the river exhibiting the greatest positive change. This reach corresponds with the terminal alluvial zone, where most flood deposition occurs. The spatial and temporal trends discovered highlight the need for long-term monitoring of ephemeral ecosystems and demonstrate the efficacy of a multi-sensor approach to time series analysis using a UAV platform.

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Summer warming explains widespread but not uniform greening in the Arctic tundra biome

Cited by 249 publications

References 102 publications

Aboveground biomass patterns across treeless northern landscapes

Aboveground biomass patterns across treeless northern landscapes

Warming enhanced the climate temporal effects on vegetation across Siberia

Spatiotemporal Analysis of Vegetation Cover Change in a Large Ephemeral River: Multi-Sensor Fusion of Unmanned Aerial Vehicle (UAV) and Landsat Imagery

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