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1. Seasonal timing of fluorescence and photosynthetic yields at needle and canopy scales in evergreen needleleaf forests

   https://doi.org/10.1002/ecy.4402  

   Pierrat, Zoe Amie; Magney, Troy; Maguire, Andrew; Brissette, Logan; Doughty, Russell; Bowling, David R; Logan, Barry; Parazoo, Nicholas; Frankenberg, Christian; Stutz, Jochen (October 2024, Ecology)

   Abstract The seasonal timing and magnitude of photosynthesis in evergreen needleleaf forests (ENFs) has major implications for the carbon cycle and is increasingly sensitive to changing climate. Earlier spring photosynthesis can increase carbon uptake over the growing season or cause early water reserve depletion that leads to premature cessation and increased carbon loss. Determining the start and the end of the growing season in ENFs is challenging due to a lack of field measurements and difficulty in interpreting satellite data, which are impacted by snow and cloud cover, and the pervasive “greenness” of these systems. We combine continuous needle‐scale chlorophyll fluorescence measurements with tower‐based remote sensing and gross primary productivity (GPP) estimates at three ENF sites across a latitudinal gradient (Colorado, Saskatchewan, Alaska) to link physiological changes with remote sensing signals during transition seasons. We derive a theoretical framework for observations of solar‐induced chlorophyll fluorescence (SIF) and solar intensity‐normalized SIF (SIF_relative) under snow‐covered conditions, and show decreased sensitivity compared with reflectance data (~20% reduction in measured SIF vs. ~60% reduction in near‐infrared vegetation index [NIRv] under 50% snow cover). Needle‐scale fluorescence and photochemistry strongly correlated (r² = 0.74 in Colorado, 0.70 in Alaska) and showed good agreement on the timing and magnitude of seasonal transitions. We demonstrate that this can be scaled to the site level with tower‐based estimates of LUE_Pand SIF_relativewhich were well correlated across all sites (r² = 0.70 in Colorado, 0.53 in Saskatchewan, 0.49 in Alaska). These independent, temporally continuous datasets confirm an increase in physiological activity prior to snowmelt across all three evergreen forests. This suggests that data‐driven and process‐based carbon cycle models which assume negligible physiological activity prior to snowmelt are inherently flawed, and underscores the utility of SIF data for tracking phenological events. Our research probes the spectral biology of evergreen forests and highlights spectral methods that can be applied in other ecosystems. 

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2. Phenology of Photosynthesis in Winter‐Dormant Temperate and Boreal Forests: Long‐Term Observations From Flux Towers and Quantitative Evaluation of Phenology Models

   https://doi.org/10.1029/2023JG007839  

   Bowling, David R.; Schädel, Christina; Smith, Kenneth R.; Richardson, Andrew D.; Bahn, Michael; Arain, M Altaf; Varlagin, Andrej; Ouimette, Andrew P.; Frank, John M.; Barr, Alan G.; et al (May 2024, Journal of Geophysical Research: Biogeosciences)

   Abstract We examined the seasonality of photosynthesis in 46 evergreen needleleaf (evergreen needleleaf forests (ENF)) and deciduous broadleaf (deciduous broadleaf forests (DBF)) forests across North America and Eurasia. We quantified the onset and end (Start_GPPand End_GPP) of photosynthesis in spring and autumn based on the response of net ecosystem exchange of CO₂to sunlight. To test the hypothesis that snowmelt is required for photosynthesis to begin, these were compared with end of snowmelt derived from soil temperature. ENF forests achieved 10% of summer photosynthetic capacity ∼3 weeks before end of snowmelt, while DBF forests achieved that capacity ∼4 weeks afterward. DBF forests increased photosynthetic capacity in spring faster (1.95% d⁻¹) than ENF (1.10% d⁻¹), and their active season length (End_GPP–Start_GPP) was ∼50 days shorter. We hypothesized that warming has influenced timing of the photosynthesis season. We found minimal evidence for long‐term change in Start_GPP, End_GPP, or air temperature, but their interannual anomalies were significantly correlated. Warmer weather was associated with earlier Start_GPP(1.3–2.5 days °C⁻¹) or later End_GPP(1.5–1.8 days °C⁻¹, depending on forest type and month). Finally, we tested whether existing phenological models could predict Start_GPPand End_GPP. For ENF forests, air temperature‐ and daylength‐based models provided best predictions for Start_GPP, while a chilling‐degree‐day model was best for End_GPP. The root mean square errors (RMSE) between predicted and observed Start_GPPand End_GPPwere 11.7 and 11.3 days, respectively. For DBF forests, temperature‐ and daylength‐based models yielded the best results (RMSE 6.3 and 10.5 days). 

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3. Importance of seasonality and watershed size on carbon dioxide evasion in Arctic streams

   https://doi.org/10.1088/2752-664X/ae212d  

   Hock, Macall; Liljedahl, Anna K; Zona, Donatella (December 2025, Environmental Research: Ecology)

   Abstract Arctic headwater streams play a crucial role in the carbon cycle, contributing disproportionately to carbon dioxide (CO₂) evasion despite their small size and surface area. In this study, we examined how seasonal hydrologic patterns, such as spring snowmelt (freshet), mid-summer low-flows (baseflow) and the late summer period in August and early September (late-season), influence CO₂evasion in Arctic headwater streams (1–9 km²basin size; 1–4 stream orders) near Utqiagvik, Alaska. During three summers, we measured key environmental parameters (CO₂partial pressure, water temperature, discharge, dissolved organic carbon (DOC), gas transfer velocity) and CO₂evasion using a floating chamber. CO₂evasion followed distinct seasonal patterns with the highest evasion rates during freshet, followed by the late-season, and the lowest during baseflow. Despite its short duration (10 d), freshet accounted for 22% more total CO₂evasion than the 36 d late-season period. The descending peakflow within freshet had the highest median evasion rate (2486 mg C–CO₂m⁻²d⁻¹) of the entire season, while the ascending portion of the peakflow had the lowest (448 mg C–CO₂m⁻²d⁻¹). These two freshet periods showed a statistically significant difference (p< 0.05). Water temperature, DOC, andpCO₂explained 35%, 30% and 67% of freshet evasion variability, respectively. No measured parameters reliably predicted CO₂evasion for the baseflow or late-season periods, suggesting increased hydrologic and biological complexity. The stream showed supply-limitation during freshet but transitioned to chemostatic behavior thereafter. By synthesizing our measurements with previously published data, we show that small streams (<1 km²watersheds) exhibit ∼10-times the CO₂evasion rates than large waterways (>1000 km²). We also find that across the Arctic, only ∼15% of riverine CO₂measurements capture the freshet period. Together, the omission of small streams and the underrepresentation of freshet likely lead to a systematic underestimation of CO₂losses from Arctic surface waters to the atmosphere. 

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4. Synthetic aperture radar (SAR) detects large gas seeps in Alaska lakes

   https://doi.org/10.1088/1748-9326/ad2b2a  

   Engram, Melanie; Anthony, Katey Walter (March 2024, Environmental Research Letters)

   Abstract Reservoirs of¹⁴C-depleted methane (CH₄), a potent greenhouse gas, residing beneath permafrost are vulnerable to escape where permafrost thaw creates open-talik conduits. However, little is known about the magnitude and variability of this methane source or its response to climate change. Remote-sensing detection of large gas seeps would be useful for establishing a baseline understanding of sub-permafrost methane seepage, as well as for monitoring these seeps over time. Here we explored synthetic aperture radar’s (SAR) response to large sub-permafrost gas seeps in an interior Alaskan lake. In SAR scenes from 1992 to 2011, we observed high perennial SAR L-band backscatter (σ⁰) from a ∼90 m-wide feature in the winter ice of interior Alaska’s North Blair Lake (NBL). Spring and fall optical imagery showed holes in the ice at the same location as the SAR anomaly. Through field work we (1) confirmed gas bubbling at this location from a large pockmark in the lakebed, (2) measured flux at the location of densest bubbles (1713 ± 290 mg CH₄m⁻²d⁻¹), and (3) determined the bubbles’ methane mixing ratio (6.6%), radiocarbon age (18 470 ± 50 years BP), and δ¹³C_CH4values (−44.5 ± 0.1‰), which together may represent a mixture of sources and processes. We performed a first order comparison of SARσ⁰from the NBL seep and other known sub-permafrost methane seeps with diverse ice/water interface shapes in order to evaluate the variability of SAR signals from a variety of seep types. Results from single-polarized intensity and polarimetric L-band SAR decompositions as well as dual-polarized C-band SAR are presented with the aim to find the optimal SAR imaging parameters to detect large methane seeps in frozen lakes. Our study indicates the potential for SAR remote sensing to be used to detect and monitor large, sub-permafrost gas seeps in Arctic and sub-Arctic lakes. 

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5. Controls on Stable Methane Isotope Values in Northern Peatlands and Potential Shifts in Values Under Permafrost Thaw Scenarios

   https://doi.org/10.1029/2023JG007837  

   Kuhn, McKenzie A; Varner, Ruth K; McCalley, Carmody K; Perryman, Clarice R; Aurela, Mika; Burke, Sophia A; Chanton, Jeffrey P; Crill, Patrick M; DelGreco, Jessica; Deng, Jia; et al (July 2024, Journal of Geophysical Research: Biogeosciences)

   Abstract Northern peatlands are a globally significant source of methane (CH₄), and emissions are projected to increase due to warming and permafrost loss. Understanding the microbial mechanisms behind patterns in CH₄production in peatlands will be key to predicting annual emissions changes, with stable carbon isotopes (δ¹³C‐CH₄) being a powerful tool for characterizing these drivers. Given that δ¹³C‐CH₄is used in top‐down atmospheric inversion models to partition sources, our ability to model CH₄production pathways and associated δ¹³C‐CH₄values is critical. We sought to characterize the role of environmental conditions, including hydrologic and vegetation patterns associated with permafrost thaw, on δ¹³C‐CH₄values from high‐latitude peatlands. We measured porewater and emitted CH₄stable isotopes, pH, and vegetation composition from five boreal‐Arctic peatlands. Porewater δ¹³C‐CH₄was strongly associated with peatland type, with δ¹³C enriched values obtained from more minerotrophic fens (−61.2 ± 9.1‰) compared to permafrost‐free bogs (−74.1 ± 9.4‰) and raised permafrost bogs (−81.6 ± 11.5‰). Variation in porewater δ¹³C‐CH₄was best explained by sedge cover, CH₄concentration, and the interactive effect of peatland type and pH (r² = 0.50,p < 0.001). Emitted δ¹³C‐CH₄varied greatly but was positively correlated with porewater δ¹³C‐CH₄. We calculated a mixed atmospheric δ¹³C‐CH₄value for northern peatlands of −65.3 ± 7‰ and show that this value is more sensitive to landscape drying than wetting under permafrost thaw scenarios. Our results suggest northern peatland δ¹³C‐CH₄values are likely to shift in the future which has important implications for source partitioning in atmospheric inversion models. 

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