Temperature Response of Respiration Across the Heterogeneous Landscape of the Alaskan Arctic Tundra

AbstractPredictions of the response of ecosystem respiration to warming in the Arctic are not well constrained, partly due to the considerable spatial heterogeneity of these permafrost‐dominated areas. Accurate calculations of in situ temperature sensitivities of respiration (Q10) are vital for the prediction of future Arctic emissions. To understand the impact of spatial heterogeneity on respiration rates and Q10, we compared respiration measured from automated chambers across the main local polygonized landscape forms (high and low centers, polygon rims, polygon troughs) to estimates from the flux‐partitioned net ecosystem exchange collected in an adjacent eddy covariance tower. Microtopographic type appears to be the most important variable explaining the variability in respiration rates, and low‐center polygons and polygon troughs show the greatest cumulative respiration rates, possibly linked to their deeper thaw depth and higher plant biomass. Regardless of the differences in absolute respiration rates, Q10 is surprisingly similar across all microtopographic features, possibly indicating a similar temperature limitation to decomposition across the landscape. Q10 was higher during the colder early summer and lower during the warmer peak growing season, consistent with an elevated temperature sensitivity under colder conditions. The respiration measured by the chambers and the estimates from the daytime flux‐partitioned eddy covariance data were within uncertainties during early and peak seasons but overestimated respiration later in the growing season. Overall, this study suggests that it is possible to simplify estimates of the temperature sensitivity of respiration across heterogeneous landscapes but that seasonal changes in Q10 should be incorporated into model simulations

Effect of thaw depth on fluxes of CO2 and CH4 in manipulated Arctic coastal tundra of Barrow, Alaska

The manipulation treatment consisted of draining, controlling, and flooding treated sections by adjusting standing water. Inundation increased CH4 emission by a factor of 4.3 compared to non-flooded sections. This may be due to the decomposition of organic matter under a limited oxygen environment by saturated standing water. On the other hand, CO2 emission in the dry section was 3.9-fold higher than in others. CH4 emission tends to increase with deeper thaw depth, which strongly depends on the water table; however, CO2 emission is not related to thaw depth. Quotients of global warming potential (GWPCO2) (dry/control) and GWPCH4 (wet/control) increased by 464 and 148 %, respectively, and GWPCH4 (dry/control) declined by 66 %. This suggests that CO2 emission in a drained section is enhanced by soil and ecosystem respiration, and CH4 emission in a flooded area is likely stimulated under an anoxic environment by inundated standing water. The findings of this manipulation experiment during the autumn period demonstrate the different production processes of CO2 and CH4, as well as different global warming potentials, coupled with change in thaw depth. Thus the outcomes imply that the expansion of tundra lakes leads the enhancement of CH4 release, and the disappearance of the lakes causes the stimulated CO2 production in response to the Arctic climate change.This research was conducted under the JAMSTEC-IARC Collaboration Study with funding provided by the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) under a grant to the International Arctic Research Center (IARC)

Increased CO₂ loss from vegetated drained lake tundra ecosystems due to flooding

Tundra ecosystems are especially sensitive to climate change, which is particularly rapid in high northern latitudes resulting in significant alterations in temperature and soil moisture. Numerous studies have demonstrated that soil drying increases the respiration loss from wet Arctic tundra. And, warming and drying of tundra soils are assumed to increase CO2 emissions from the Arctic. However, in this water table manipulation experiment (i.e., flooding experiment), we show that flooding of wet tundra can also lead to increased CO2 loss. Standing water increased heat conduction into the soil, leading to higher soil temperature, deeper thaw and, surprisingly, to higher CO2 loss in the most anaerobic of the experimental areas. The study site is located in a drained lake basin, and the soils are characterized by wetter conditions than upland tundra. In experimentally flooded areas, high wind speeds (greater than ~4 m s−1) increased CO2 emission rates, sometimes overwhelming the photosynthetic uptake, even during daytime. This suggests that CO2 efflux from C rich soils and surface waters can be limited by surface exchange processes. The comparison of the CO2 and CH4 emission in an anaerobic soil incubation experiment showed that in this ecosystem, CO2 production is an order of magnitude higher than CH4 production. Future increases in surface water ponding, linked to surface subsidence and thermokarst erosion, and concomitant increases in soil warming, can increase net C efflux from these arctic ecosystems

Understanding spatial variability of methane fluxes in Arctic wetlands through footprint modelling

The Arctic is warming at twice the rate of the global mean. This warming could further stimulate methane (CH4) emissions from northern wetlands and enhance the greenhouse impact of this region. Arctic wetlands are extremely heterogeneous in terms of geochemistry, vegetation, microtopography, and hydrology, and therefore CH4 fluxes can differ dramatically within the metre scale. Eddy covariance (EC) is one of the most useful methods for estimating CH4 fluxes in remote areas over long periods of time. However, when the areas sampled by these EC towers (i.e. tower footprints) are by definition very heterogeneous, due to encompassing a variety of environmental conditions and vegetation types, modelling environmental controls of CH4 emissions becomes even more challenging, confounding efforts to reduce uncertainty in baseline CH4 emissions from these landscapes. In this study, we evaluated the effect of footprint variability on CH4 fluxes from two EC towers located in wetlands on the North Slope of Alaska. The local domain of each of these sites contains well developed polygonal tundra as well as a drained thermokarst lake basin. We found that the spatiotemporal variability of the footprint, has a significant influence on the observed CH4 fluxes, contributing between 3% and 33% of the variance, depending on site, time period, and modelling method. Multiple indices were used to define spatial heterogeneity, and their explanatory power varied depending on site and season. Overall, the normalised difference water index had the most consistent explanatory power on CH4 fluxes, though generally only when used in concert with at least one other spatial index. The spatial bias (defined here as the difference between the mean for the 0.36 km2 domain around the tower and the footprint-weighted mean) was between mid51mid% and mid18mid% depending on the index. This study highlights the need for footprint modelling to infer the representativeness of the carbon fluxes measured by EC towers in these highly heterogeneous tundra ecosystems, and the need to evaluate spatial variability when upscaling EC site-level data to a larger domain

Changes in fire intensity have carry-over effects on plant responses after the next fire in southern California chaparral

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Sensitivity of Pan-Arctic Terrestrial Net Primary Productivity Simulations to Daily Surface Meterology From NCEP-NCAR and ERA-40 Reanalyses

We applied a terrestrial net primary production (NPP) model driven by satellite remote sensing observations of vegetation properties and daily surface meteorology from the 45-year ECMWF Re-Analysis (ERA-40) and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP-NCAR) reanalysis (NNR) to assess NPP spatial and temporal variability for the pan-Arctic basin and Alaska from 1982 to 2000. Sensitivity analysis of the production efficiency model (PEM) to uncertainties in surface meteorological inputs indicate that ERA-40 solar radiation and NNR solar radiation and surface temperatures are the primary sources of PEM-based NPP uncertainty for the region. Considerable positive bias in solar radiation inputs relative to surface observation networks resulted in overprediction of annual NPP by approximately 35.2 and 61.6% using ERA-40 and NNR inputs, respectively. Despite these uncertainties, both reanalysis products captured the major annual anomalies and trends in surface meteorology for the domain. The two reanalysis products also produced similar NPP spatial patterns for 74.7% of the domain, and similar annual anomalies and temporal trends, though there were significant regional differences particularly for Eurasia. A simple correction method based on a sensitivity experiment between reanalysis and surface station meteorological measurements produced generally consistent NPP results that were considerably smaller than PEM simulations derived from uncorrected reanalysis drivers. The results of this study identify major sources of uncertainty in reanalysis-based surface meteorology, and associated impacts on regional NPP simulations of the northern high latitudes

Satellite-based model detection of recent climate-driven changes in northern high-latitude vegetation productivity

We applied a satellite remote sensing based production efficiency model (PEM) using an integrated AVHRR and MODIS FPAR/LAI time series with a regionally corrected NCEP/NCAR reanalysis daily surface meteorology and NASA/GEWEX Surface Radiation Budget shortwave solar radiation inputs to assess annual terrestrial net primary productivity (NPP) for the pan-Arctic basin and Alaska from 1983 to 2005. Our results show that low temperature constraints on Boreal-Arctic NPP are decreasing by 0.43% per year (P \u3c 0.001), whereas a positive trend in vegetation moisture constraints of 0.49% per year (P = 0.04) are offsetting the potential benefits of longer growing seasons and contributing to recent disturbances in NPP. The PEM simulations of NPP seasonality, annual anomalies and trends are similar to stand inventory network measurements of boreal aspen stem growth (r = 0.56; P = 0.007) and atmospheric CO2 measurement based estimates of the timing of growing season onset (r = 0.78; P \u3c 0.001). Our results indicate that summer drought led to marked NPP decreases in much of the boreal forest region after the late-1990s. However, seasonal low temperatures are still a dominant limitation on regional NPP. Despite recent drought events, mean annual NPP for the pan-Arctic region showed a positive growth trend of 0.34% per year (20.27 TgC/a; P = 0.002) from 1983 to 2005. Drought induced NPP decreases may become more frequent and widespread as regional ecosystems adjust to a warmer, drier atmosphere, though the occurrence and severity of drought events will depend on future patterns of plant-available moisture

Temporal and spatial differences of methane flux at arctic tundra in Alaska

High latitude ecosystems were thought to enhance CH_4 emission in relation to the current arctic warming. However, we have little information about this potential feedback mechanisms on climate change, thus, model parameterization is insufficient and the observational data are required. We observed CH_4 flux at several types of tundra in Alaska over the growing seasons since 1995. From these observed data, we examined current CH_4 emission and its controlling factors on Alaskan tundra. Then we discussed about spatial and temporal differences in CH_4 flux. Daily trend of half hourly CH_4 flux had little relation with soil temperature, but the seasonal trend of daily flux changed with soil or water temperature. Cumulative CH_4 fluxes during the growing seasons were 8.1gCH_4m^(-2) on wet sedge tundra at Happy Valley in 1995, 3.3gCH_4m^(-2) on non-acidic moist tundra in 1996, and 3.58-8.24gCH_4m^(-2) on wet sedge tundra at Barrow between 1999-2003. Non-acidic tundra had low CH_4 emission with low CO_2 accumulation. There was large spatial difference in CH_4 flux caused by tundra type, and the large temporal difference at the wet sedge tundra reflected yearly weather variability

VvEPFL9-1 Knock-Out via CRISPR/Cas9 reduces stomatal density in grapevine

10openInternationalInternational coauthor/editorEpidermal Patterning Factor Like 9 (EPFL9), also known as STOMAGEN, is a cysteine-rich peptide that induces stomata formation in vascular plants, acting antagonistically to other epidermal patterning factors (EPF1, EPF2). In grapevine there are two EPFL9 genes, EPFL9-1 and EPFL9-2 sharing 82% identity at protein level in the mature functional C-terminal domain. In this study, CRISPR/Cas9 system was applied to functionally characterize VvEPFL9-1 in ‘Sugraone’, a highly transformable genotype. A set of plants, regenerated after gene transfer in embryogenic calli via Agrobacterium tumefaciens, were selected for evaluation. For many lines, the editing profile in the target site displayed a range of mutations mainly causing frameshift in the coding sequence or affecting the second cysteine residue. The analysis of stomata density revealed that in edited plants the number of stomata was significantly reduced compared to control, demonstrating for the first time the role of EPFL9 in a perennial fruit crop. Three edited lines were then assessed for growth, photosynthesis, stomatal conductance, and water use efficiency in experiments carried out at different environmental conditions. Intrinsic water-use efficiency was improved in edited lines compared to control, indicating possible advantages in reducing stomatal density under future environmental drier scenarios. Our results show the potential of manipulating stomatal density for optimizing grapevine adaptation under changing climate conditions.openClemens, Molly; Faralli, Michele; Lagreze, Jorge; Bontempo, Luana; Piazza, Stefano; Varotto, Claudio; Malnoy, Mickael; Oechel, Walter; Rizzoli, Annapaola; Dalla Costa, LorenzaClemens, M.; Faralli, M.; Lagreze, J.; Bontempo, L.; Piazza, S.; Varotto, C.; Malnoy, M.; Oechel, W.; Rizzoli, A.; Dalla Costa, L

Upscaling CH4 Fluxes Using High-Resolution Imagery in Arctic Tundra Ecosystems

© 2017 by the author. Arctic tundra ecosystems are a major source of methane (CH 4 ), the variability of which is affected by local environmental and climatic factors, such as water table depth, microtopography, and the spatial heterogeneity of the vegetation communities present. There is a disconnect between the measurement scales for CH 4 fluxes, which can be measured with chambers at one-meter resolution and eddy covariance towers at 100-1000 m, whereas model estimates are typically made at the ~100 km scale. Therefore, it is critical to upscale site level measurements to the larger scale for model comparison. As vegetation has a critical role in explaining the variability of CH 4 fluxes across the tundra landscape, we tested whether remotely-sensed maps of vegetation could be used to upscale fluxes to larger scales. The objectives of this study are to compare four different methods for mapping and two methods for upscaling plot-level CH 4 emissions to the measurements from EC towers. We show that linear discriminant analysis (LDA) provides the most accurate representation of the tundra vegetation within the EC tower footprints (classification accuracies of between 65% and 88%). The upscaled CH 4 emissions using the areal fraction of the vegetation communities showed a positive correlation (between 0.57 and 0.81) with EC tower measurements, irrespective of the mapping method. The area-weighted footprint model outperformed the simple area-weighted method, achieving a correlation of 0.88 when using the vegetation map produced with the LDA classifier. These results suggest that the high spatial heterogeneity of the tundra vegetation has a strong impact on the flux, and variation indicates the potential impact of environmental or climatic parameters on the fluxes. Nonetheless, assimilating remotely-sensed vegetation maps of tundra in a footprint model was successful in upscaling fluxes across scales