Sensitivity of a subregional scale atmospheric inverse CO 2 modeling framework to boundary conditions

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95175/1/jgrd16614.pd

Atmospheric inverse modeling to constrain regional‐scale CO 2 budgets at high spatial and temporal resolution

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95480/1/jgrd15697.pd

Sensitivity of a subregional scale atmospheric inverse CO₂ modeling framework to boundary conditions

We present an atmospheric inverse modeling framework to constrain terrestrial biosphere CO₂ exchange processes at subregional scales. The model is operated at very high spatial and temporal resolution, using the state of Oregon in the northwestern United States as the model domain. The modeling framework includes mesoscale atmospheric simulations coupled to Lagrangian transport, a biosphere flux model that considers, e.g., the effects of drought stress and disturbance on photosynthesis and respiration CO₂ fluxes, and a Bayesian optimization approach. This study focuses on the impact of uncertainties in advected background mixing ratios and fossil fuel emissions on simulated flux fields, both taken from external data sets. We found the simulations to be highly sensitive to systematic changes in advected background CO₂, while shifts in fossil fuel emissions played a minor role. Correcting for offsets in the background mixing ratios shifted annual CO₂ budgets by about 47% and improved the correspondence with the output produced by bottom-up modeling frameworks. Inversion results were robust against shifts in fossil fuel emissions, which is likely a consequence of relatively low emission rates in Oregon

Lowering water table reduces carbon sink strength and carbon stocks in northern peatlands

Peatlands at high latitudes have accumulated \u3e400 Pg carbon (C) because saturated soil and cold temperatures suppress C decomposition. This substantial amount of C in Arctic and Boreal peatlands is potentially subject to increased decomposition if the water table (WT) decreases due to climate change, including permafrost thaw-related drying. Here, we optimize a version of the Organizing Carbon and Hydrology In Dynamic Ecosystems model (ORCHIDEE-PCH4) using site-specific observations to investigate changes in CO and CH fluxes as well as C stock responses to an experimentally manipulated decrease of WT at six northern peatlands. The unmanipulated control peatlands, with the WT (seasonal max up to 45 cm) below the surface, currently act as C sinks in most years (58 ± 34 g C m year ; including 6 ± 7 g C-CH m year emission). We found, however, that lowering the WT by 10 cm reduced the CO sink by 13 ± 15 g C m year and decreased CH emission by 4 ± 4 g CH m year , thus accumulating less C over 100 years (0.2 ± 0.2 kg C m ). Yet, the reduced emission of CH , which has a larger greenhouse warming potential, resulted in a net decrease in greenhouse gas balance by 310 ± 360 g CO m year . Peatlands with the initial WT close to the soil surface were more vulnerable to C loss: Non-permafrost peatlands lost \u3e2 kg C m over 100 years when WT is lowered by 50 cm, while permafrost peatlands temporally switched from C sinks to sources. These results highlight that reductions in C storage capacity in response to drying of northern peatlands are offset in part by reduced CH emissions, thus slightly reducing the positive carbon climate feedbacks of peatlands under a warmer and drier future climate scenario

Earlier snowmelt may lead to late season declines in plant productivity and carbon sequestration in Arctic tundra ecosystems

Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO2 sequestration and higher gross primary productivity (GPP) only in June and July, but with lower net carbon sequestration and lower GPP in August. Although higher evapotranspiration (ET) can result in soil drying with the progression of the summer, we did not find significantly lower soil moisture with earlier snowmelt, nor evidence that water stress affected GPP in the late growing season. Our results suggest that the expected increased CO2 sequestration arising from Arctic warming and the associated increase in growing season length may not materialize if tundra ecosystems are not able to continue sequestering CO2 later in the season

Earlier snowmelt may lead to late season declines in plant productivity and carbon sequestration in Arctic tundra ecosystems

Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO2 sequestration and higher gross primary productivity (GPP) only in June and July, but with lower net carbon sequestration and lower GPP in August. Although higher evapotranspiration (ET) can result in soil drying with the progression of the summer, we did not find significantly lower soil moisture with earlier snowmelt, nor evidence that water stress affected GPP in the late growing season. Our results suggest that the expected increased CO2 sequestration arising from Arctic warming and the associated increase in growing season length may not materialize if tundra ecosystems are not able to continue sequestering CO2 later in the season.Peer reviewe

Vegetation type is an important predictor of the arctic summer land surface energy budget

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994-2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm(-2)) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.An international team of researchers finds high potential for improving climate projections by a more comprehensive treatment of largely ignored Arctic vegetation types, underscoring the importance of Arctic energy exchange measuring stations.Peer reviewe

Vegetation type is an important predictor of the arctic summer land surface energy budget

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm−2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types

Data_Sheet_1_Responses of soil micro-eukaryotic communities to decadal drainage in a Siberian wet tussock tundra.docx

Climate warming holds the potential to cause extensive drying of wetlands in the Arctic, but the warming-drying effects on belowground ecosystems, particularly micro-eukaryotes, remain poorly understood. We investigated the responses of soil micro-eukaryotic communities, including fungi, protists, and microbial metazoa, to decadal drainage manipulation in a Siberian wet tundra using both amplicon and shotgun metagenomic sequencing. Our results indicate that drainage treatment increased the abundance of both fungal and non-fungal micro-eukaryotic communities, with key groups such as Ascomycota (mostly order Helotiales), Nematoda, and Tardigrada being notably abundant in drained sites. Functional traits analysis showed an increase in litter saprotrophic fungi and protistan consumers, indicating their increased activities in drained sites. The effects of drainage were more pronounced in the surface soil layer than the deeper layer, as soils dry and warm from the surface. Marked compositional shifts were observed for both communities, with fungal communities being more strongly influenced by drainage-induced vegetation change than the lowered water table itself, while the vegetation effect on non-fungal micro-eukaryotes was moderate. These findings provide insights into how belowground micro-eukaryotic communities respond to the widespread drying of wetlands in the Arctic and improve our predictive understanding of future ecosystem changes.</p

The three major axes of terrestrial ecosystem function

The leaf economics spectrum(1,2) and the global spectrum of plant forms and functions(3) revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species(2). Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities(4). However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability(4,5). Here we derive a set of ecosystem functions(6) from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems(7,8).Peer reviewe