NDVI Changes Show Warming Increases the Length of the Green Season at Tundra Communities in Northern Alaska: A Fine-Scale Analysis

May, Jeremy L.; Hollister, Robert D.; Betway, Katlyn R.; Harris, Jacob; Tweedie, C. E.; Welker, Jeffrey M.; Gould, William A.; Oberbauer, Steven F.

doi:10.3389/fpls.2020.01174

Cited by 21 publications

(16 citation statements)

References 80 publications

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“…Our results suggest that because more GDD contribute to an earlier start and end to the growing season in every vegetation community, warmer conditions are unlikely to extend the growing season in these communities. This finding corroborates Arctic plot‐scale field studies indicating warming does not lengthen the growing season but can shift it earlier (Starr et al, 2000; Khorsand Rosa et al, 2015 but see May et al, 2020), and complements remote sensing observations that show no or little trend of lengthening growing season in much of the Arctic (Gamon et al, 2013; Gonsamo et al, 2018; Zhao et al, 2015). The absence of a change in growing season length for Arctic plants in response to warming is likely due to the accumulation of water deficit due greater evapotranspiration during the warmer spring, a phenomenon which has been recently observed in many ecosystems, including those typically thought to be temperature‐limited (Angert et al, 2005; Buermann et al, 2018; Gonsamo et al, 2019).…”

Section: Discussionsupporting

confidence: 82%

Winter snow and spring temperature have differential effects on vegetation phenology and productivity across Arctic plant communities

Kelsey

Pedersen

Leffler

et al. 2021

Global Change Biology

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Tundra dominates two‐thirds of the unglaciated, terrestrial Arctic. Although this region has experienced rapid and widespread changes in vegetation phenology and productivity over the last several decades, the specific climatic drivers responsible for this change remain poorly understood. Here we quantified the effect of winter snowpack and early spring temperature conditions on growing season vegetation phenology (timing of the start, peak, and end of the growing season) and productivity of the dominant tundra vegetation communities of Arctic Alaska. We used daily remotely sensed normalized difference vegetation index (NDVI), and daily snowpack and temperature variables produced by SnowModel and MicroMet, coupled physically based snow and meteorological modeling tools, to (1) determine the most important snowpack and thermal controls on tundra vegetation phenology and productivity and (2) describe the direction of these relationships within each vegetation community. Our results show that soil temperature under the snowpack, snowmelt timing, and air temperature following snowmelt are the most important drivers of growing season timing and productivity among Arctic vegetation communities. Air temperature after snowmelt was the most important control on timing of season start and end, with warmer conditions contributing to earlier phenology in all vegetation communities. In contrast, the controls on the timing of peak season and productivity also included snowmelt timing and soil temperature under the snowpack, dictated in part by the snow insulating capacity. The results of this novel analysis suggest that while future warming effects on phenology may be consistent across communities of the tundra biome, warming may result in divergent, community‐specific productivity responses if coupled with reduced snow insulating capacity lowers winter soil temperature and potential nutrient cycling in the soil.

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Section: Discussionsupporting

confidence: 82%

Winter snow and spring temperature have differential effects on vegetation phenology and productivity across Arctic plant communities

Kelsey

Pedersen

Leffler

et al. 2021

Global Change Biology

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“…Our study showed that tussocks across all populations stayed green for 3.76 days longer in response to direct warming but little else was responsive, therefore it is not clear whether the response of E. vaginatum to a gradual temperature increase will have tangible ecosystem effects. OTC experiments have recently shown that tundra plant communities (including moist acidic tundra, dominated by E. vaginatum) extend their growing season when warmed (May et al 2020). This suggests that contemporary plant communities can take advantage of milder growing conditions, at least in the short term.…”

Section: Effects Of Transplanting On Phenology Of Eriophorum Vaginatummentioning

confidence: 99%

“…At the beginning of the growing season, earlier snowmelt should result in earlier green-up, as abundant sunshine and the disappearance of snow produces good growing conditions. Many studies have documented the importance of snowmelt timing for controlling the phenology of arctic plants with earlier snowmelt, which usually results in earlier onset of growth (Høye et al 2007;Bjorkman et al 2015;Khorsand Rosa et al 2015;Semenchuk et al 2016;May et al 2020). Once the growing season is underway, it is less clear whether higher average temperatures will affect plant phenology in part because of interactions with snowmelt timing (Oberbauer et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Intraspecific variation in phenology offers resilience to climate change for Eriophorum vaginatum

et al. 2022

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Phenology of arctic plants is an important determinant of the pattern of carbon uptake and may be highly sensitive to continued rapid climate change. Eriophorum vaginatum has a disproportionate influence over ecosystem processes in moist acidic tundra, but it is unclear whether its growth and phenology will remain competitive in the future. We asked whether northern tundra ecotypes of E. vaginatum could extend their growing season in response to direct warming and transplanting into southern ecosystems. At the same time, we asked whether southern ecotypes could adjust their growth patterns in order to thrive further north, should they disperse quickly enough. Detailed phenology measurements across three reciprocal transplant gardens and two years showed that some northern ecotypes were capable of growing for longer when conditions were favourable, but their biomass and growing season length was still shorter than the southern ecotype. Southern ecotypes retained large leaf length when transplanted north and mirrored the growing season length better than the others, mainly due to immediate green-up after snowmelt. All ecotypes retained the same senescence timing, regardless of environment, indicating a strong genetic control. E. vaginatum may remain competitive in a warming world if southern ecotypes can migrate north.

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“…Therefore, for each grassland grid, the slope value of NDVI (NDVIs) from 2005 to 2018 could be used to indicate the trend of grassland change, and NDVIs values less than 0 could be regarded as grassland degradation. However, it is worth noting that NDVIs values lower than 0 do not indicate grassland degradation, because shrubencroached grasslands in alpine regions are an important form of grassland degradation and do not necessarily lead to a reduction in NDVI (Fraser et al, 2014;May et al, 2020). Therefore, to more comprehensively identify the pattern of grassland degradation, we defined grassland degradation as non-encroached degraded Taking into account the non-stationarity of ecological processes, the diversity and incompleteness of data, and the complex relationships among factors, we selected 18 potential factors based on previous research results (Kane et al, 2017;Chen et al, 2020).…”

Section: Establish the Grassland Degradation Risk Inference Modelmentioning

confidence: 99%

Applying Bayesian Belief Networks to Assess Alpine Grassland Degradation Risks: A Case Study in Northwest Sichuan, China

Zhou

2021

Front. Plant Sci.

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Grasslands are crucial components of ecosystems. In recent years, owing to certain natural and socio-economic factors, alpine grassland ecosystems have experienced significant degradation. This study integrated the frequency ratio model (FR) and Bayesian belief networks (BBN) for grassland degradation risk assessment to mitigate several issues found in previous studies. Firstly, the identification of non-encroached degraded grasslands and shrub-encroached grasslands could help stakeholders more accurately understand the status of different types of alpine grassland degradation. In addition, the index discretization method based on the FR model can more accurately ascertain the relationship between grassland degradation and driving factors to improve the accuracy of results. On this basis, the application of BBN not only effectively expresses the complex causal relationships among various variables in the process of grassland degradation, but also solves the problem of identifying key factors and assessing grassland degradation risks under uncertain conditions caused by a lack of information. The obtained result showed that the accuracies based on the confusion matrix of the slope of NDVI change (NDVIs), shrub-encroached grasslands, and grassland degradation indicators in the BBN model were 85.27, 88.99, and 74.37%, respectively. The areas under the curve based on the ROC curve of NDVIs, shrub-encroached grasslands, and grassland degradation were 75.39% (P < 0.05), 66.57% (P < 0.05), and 66.11% (P < 0.05), respectively. Therefore, this model could be used to infer the probability of grassland degradation risk. The results obtained using the model showed that the area with a higher probability of degradation (P > 30%) was 2.22 million ha (15.94%), with 1.742 million ha (78.46%) based on NDVIs and 0.478 million ha (21.54%) based on shrub-encroached grasslands. Moreover, the higher probability of grassland degradation risk was mainly distributed in regions with lower vegetation coverage, lower temperatures, less potential evapotranspiration, and higher soil sand content. Our research can provide guidance for decision-makers when formulating scientific measures for alpine grassland restoration.

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NDVI Changes Show Warming Increases the Length of the Green Season at Tundra Communities in Northern Alaska: A Fine-Scale Analysis

Abstract: dependent on community composition and abundance of specific growth forms and therefore will likely impact net primary productivity and trophic interactions.

Cited by 21 publications

References 80 publications

Winter snow and spring temperature have differential effects on vegetation phenology and productivity across Arctic plant communities

Winter snow and spring temperature have differential effects on vegetation phenology and productivity across Arctic plant communities

Intraspecific variation in phenology offers resilience to climate change for Eriophorum vaginatum

Applying Bayesian Belief Networks to Assess Alpine Grassland Degradation Risks: A Case Study in Northwest Sichuan, China

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