Carbon response of tundra ecosystems to advancing greenup and snowmelt in Alaska

Arctic ecosystems, highly sensitive to rapid regional warming, are experiencing shifts in spring greenup and snowmelt timing that influence tundra carbon dynamics. Because snowmelt timing is governed by both temperature and precipitation, while greenup is largely temperature-driven, their relative changes can differentially affect vegetation growth and net carbon exchange. The study asks how advancing greenup and variable snowmelt (including delayed snowmelt that physically prevents leaf-out) impact tundra vegetation productivity and carbon balance across climatic gradients in Alaska. The authors hypothesize that effects of early greenup and delayed snowmelt depend strongly on local climatic limitations (temperature and water) and vary throughout the growing season, with potentially greater sensitivity at higher latitudes where colimitation is strongest.

Prior work links earlier snowmelt with enhanced carbon uptake, often confounded by warmer springs, while other studies report weak or negative relationships, including frost damage following early melt. Increased snow accumulation (often implying delayed melt) has been associated with higher greenness in water-limited systems, but also with reduced reproductive success due to shortened growing seasons. Process modeling has shown hydrological controls modulate Arctic ecosystem responses, yet the net effect of changing snowmelt timing has been unclear due to covariance with meteorology. Remote sensing phenology detection at high latitudes is challenged by low sun angles, low vegetation index amplitude, cloudiness, and landscape heterogeneity, underscoring the value of integrated data–model approaches and careful evaluation against in situ observations.

Study domain: seven tundra flux tower sites in Alaska (six AmeriFlux and one KOPRI site) spanning a latitudinal climatic gradient. Climatic limits quantified using NARR reanalysis (0.3°/3-hourly) for 2001–2018; temperature, precipitation, radiation used to derive temperature, water, and radiation limitation scalars following Nemani et al. Carbon flux sensitivity to meteorological drivers assessed via forward stepwise multiple regression of tower NEE against temperature, VPD, PAR, and interactions. Remote sensing phenology and snow: MODIS daily snow cover (MOD10A1 V006, 500 m) used to estimate snowmelt and snowpack dates via logistic fits crossing 0.1; MODIS phenology (MCD12Q2 V006, 500 m) provided greenup and dormancy dates (best quality flag). Spatial representativeness of 1×1 vs 3×3 pixel windows assessed; 1×1 window adopted. Trend significance evaluated with Spearman’s rho and Mann–Kendall; bootstrap (n=3000) used to estimate 95% CIs accounting for MODIS–ground RMSE (greenup 10 d; snowmelt 6.6 d). Case study (flux data): Three sites with >5 years of flux data (US-Atq, US-EML, US-BZF). Computed meteorological phenology timings (GSI-based: 0.1 threshold and half-maximum) using NARR. Flux seasonal timings derived from smoothed daily NEP (source–sink transition) and GPP (half-max productivity) using FLUXNET2015 or ONEFlux (ERA5-driven) gap-filling. Assessed how delayed snowmelt disrupts relationships between meteorological and flux timings; quantified early-GS NEP reductions per 10-day snowmelt delay. Process-based modeling: Implemented Ecosystem Demography model version 2 (ED2). Developed snowmelt-growing season index (SGSI) by multiplying the traditional Growing Season Index (GSI) by a snowmelt index (iS=0 if snow cover fraction >0.1; 1 otherwise), ensuring leaf-out cannot begin under snow. Calibrated ED2 parameters (Monte Carlo sampling of priors; 10,000 sets) against US-Atq NEP (2004–2006) and MODIS LAI (2003–2010); validated across sites for NEP, respiration, soil temperature, snowmelt, greenup, and LAI. For soil and vegetation initialization used Ent-GVSD v1.0b LAI and PFTs, HWSD v1.1 soil texture, FAO GSOC for soil C, and moist tundra C/N for soil N. Correlation analyses of snowmelt effects: To isolate effects of snowmelt timing from interannual meteorology and greenup changes, selected years with similar weekly GSI (within 1 SD) and excluded years with greenup outside ±1 SD of mean. Applied least-squares linear regressions between deviations in snowmelt timing and seasonal deviations of modeled processes (LAI, GPP, Ra, NPP, Rh, NEP, soil moisture and temperature) under similar meteorology. To examine delayed snowmelt net effects, ran ED2 with GSI vs SGSI and regressed differences in seasonal processes against delayed snowmelt days. Seasons defined as early (May–Jun), peak (Jul–Aug), late (Sep–Oct), and full GS (May–Oct).

- Climatic gradients: Annual temperature and precipitation decreased with latitude across sites (p<0.05), yielding varying climatic limits: two northernmost sites were strongly co-limited by temperature and water (temperature limit 43–51%, water limit 38–43%); lower-latitude sites were moderately co-limited (temperature 19–27%, water 17–30%); one southern site was weakly water-limited (temperature 8%, water 19%). Radiation limits were weaker (14–16%). - Phenology and snow trends: MODIS showed earlier snowmelt and greenup at lower latitudes (snowmelt DOY 111–161; greenup DOY 125–166; site-wise SD ~6 days). From 2001–2018, mean advances were 5.0 days/decade for snowmelt and 8.4 days/decade for greenup (site SDs 3.7 and 1.5). Greenup advance correlated with increasing spring temperature (Tspring) trends (r = −0.75, p<0.05), while snowmelt advance correlated with decreasing winter precipitation (Pwinter) trends (r = 0.91, p<0.01). Tspring trends increased with latitude (r = 0.82, p<0.05), implying more frequent delayed snowmelt at higher latitudes as greenup advances faster than snowmelt. - Case study (flux): Years with delayed snowmelt disrupted tight coupling between meteorological phenology (GSI timings) and flux timings (source–sink transition; half-max productivity), indicating physical suppression of carbon uptake onset. A 10-day delay in snowmelt reduced early-GS NEP by 36.7–59.0 g C m−2 across the three sites. - Model results: Under similar meteorological conditions and constrained greenup date, early snowmelt alone had little effect on early-GS vegetation productivity and carbon fluxes; LAI modestly increased early-GS but decreased late-GS (significant at the weakly water-limited site), with non-significant GPP and Ra changes. Early snowmelt lowered early-GS soil temperatures at higher-latitude sites (p<0.05), reducing Rh. - Delayed snowmelt effects were stronger and pervasive: Early-GS LAI decreased at all sites (p<0.05), often persisting into late GS. Early-GS GPP and Ra decreased significantly across sites. Despite reduced LAI, GPP and Ra increased during peak/late GS at some higher-latitude sites, indicating strong meteorological control of physiology. Soil moisture increased most at the weakly water-limited site (significant early and peak GS), alleviating water stress; early-GS soil temperatures decreased at all sites (significant at four higher-latitude sites). Rh responses tracked soil temperature at higher latitudes but were moisture-limited at lower-latitude, wetter sites. - NEP sensitivities by climatic limit (per 10 days): Early greenup increased early-GS NEP by 67.2 g C m−2 at strongly colimited sites, 42.7 g C m−2 at moderately colimited, and 29.7 g C m−2 at weakly water-limited sites. Early-GS NEP decreases due to delayed snowmelt at strongly colimited sites were ~20% of those at moderately/weakly water-limited sites, reflecting water stress relief. Over the full GS, early-greenup NEP gains at strongly colimited sites averaged 101.1 g C m−2 per 10 days, approximately double those at other sites; delayed snowmelt caused much smaller GS-scale NEP decreases at strongly colimited sites (≈2.1 g C m−2 per 10 days) than at the other sites.

The findings demonstrate that tundra carbon dynamics respond differently to phenological controls depending on local climatic constraints. At higher latitudes where temperature and water strongly colimit growth, warming-driven early greenup substantially boosts carbon uptake, while the negative impact of delayed snowmelt on NEP is dampened by increased soil moisture that relieves water stress. In contrast, at lower-latitude, more water-limited sites, delayed snowmelt more strongly suppresses early-season NEP and can rival the benefit of early greenup. Early snowmelt alone, when decoupled from meteorology and greenup, exerts minimal direct influence on productivity, highlighting the importance of distinguishing meteorological forcing from phenological constraints. Disruption of the coupling between meteorological phenology and flux timing during delayed snowmelt years underscores the physical barrier posed by snow cover. These results clarify the mechanisms through which advancing greenup and variable snowmelt jointly shape seasonal and annual carbon budgets and emphasize the need to incorporate snow-phenology interactions in Arctic carbon cycle assessments under continued warming and changing precipitation regimes.

This study integrates remote sensing, flux observations, and process-based modeling (ED2 with a new snowmelt-constrained phenology, SGSI) to quantify how advancing greenup and changing snowmelt timing affect tundra carbon dynamics across climatic gradients in Alaska. Greenup is advancing faster than snowmelt, particularly at higher latitudes, increasing the likelihood of delayed snowmelt events that physically postpone leaf-out. Early greenup strongly enhances NEP at strongly colimited (cold, dry) sites, while the adverse effects of delayed snowmelt on NEP are mitigated there by water stress relief. Early snowmelt, in isolation, has limited direct effects. Ignoring delayed snowmelt can lead to overestimation of carbon uptake in high-latitude regions and underestimation of warming effects at lower latitudes. Future work should refine phenological representations for tundra, expand long-term in situ phenology and flux measurements (e.g., PhenoCam, NEON), improve evaluation of satellite phenology and LAI in heterogeneous Arctic landscapes, and better constrain model parameterizations of soil thermal–hydrologic controls on respiration.

- Remote sensing uncertainties: Phenology detection varies by method and index; high-latitude challenges include low sun angles, low vegetation index amplitudes, frequent cloud cover, and landscape heterogeneity, potentially biasing MODIS-based timing trends. - Spatial representativeness: Site footprints vs satellite pixel scale can mismatch; although a 1×1 pixel window was chosen, residual heterogeneity remains. - Flux data constraints: Case studies rely on limited years and few delayed snowmelt events; interannual meteorological variability cannot be fully removed, affecting inferred sensitivities. - Model limitations: ED2 LAI was slightly overestimated; parameter calibration centered on one site; soil and vegetation initializations rely on global datasets with uncertainties. The SGSI approach assumes meteorology-driven phenology without accounting for other biological controls. - Statistical significance: Not all site-specific trends in snowmelt or greenup were significant; snowpack and dormancy showed no significant long-term trends in this dataset, limiting generalization.