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1. Assessing Model Predictions of Carbon Dynamics in Global Drylands

   https://doi.org/10.3389/fenvs.2022.790200  

   Fawcett, Dominic; Cunliffe, Andrew M.; Sitch, Stephen; O’Sullivan, Michael; Anderson, Karen; Brazier, Richard E.; Hill, Timothy C.; Anthoni, Peter; Arneth, Almut; Arora, Vivek K.; et al (April 2022, Frontiers in Environmental Science)

   Drylands cover ca. 40% of the land surface and are hypothesised to play a major role in the global carbon cycle, controlling both long-term trends and interannual variation. These insights originate from land surface models (LSMs) that have not been extensively calibrated and evaluated for water-limited ecosystems. We need to learn more about dryland carbon dynamics, particularly as the transitory response and rapid turnover rates of semi-arid systems may limit their function as a carbon sink over multi-decadal scales. We quantified aboveground biomass carbon (AGC; inferred from SMOS L-band vegetation optical depth) and gross primary productivity (GPP; from PML-v2 inferred from MODIS observations) and tested their spatial and temporal correspondence with estimates from the TRENDY ensemble of LSMs. We found strong correspondence in GPP between LSMs and PML-v2 both in spatial patterns (Pearson’s r = 0.9 for TRENDY-mean) and in inter-annual variability, but not in trends. Conversely, for AGC we found lesser correspondence in space (Pearson’s r = 0.75 for TRENDY-mean, strong biases for individual models) and in the magnitude of inter-annual variability compared to satellite retrievals. These disagreements likely arise from limited representation of ecosystem responses to plant water availability, fire, and photodegradation that drive dryland carbon dynamics. We assessed inter-model agreement and drivers of long-term change in carbon stocks over centennial timescales. This analysis suggested that the simulated trend of increasing carbon stocks in drylands is in soils and primarily driven by increased productivity due to CO 2 enrichment. However, there is limited empirical evidence of this 50-year sink in dryland soils. Our findings highlight important uncertainties in simulations of dryland ecosystems by current LSMs, suggesting a need for continued model refinements and for greater caution when interpreting LSM estimates with regards to current and future carbon dynamics in drylands and by extension the global carbon cycle. 

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2. Modeled Surface‐Atmosphere Fluxes From Paired Sites in the Upper Great Lakes Region Using Neural Networks

   https://doi.org/10.1029/2021JG006363  

   Reed, David E.; Poe, Jeralyn; Abraha, Michael; Dahlin, Kyla M.; Chen, Jiquan (August 2021, Journal of Geophysical Research: Biogeosciences)

   Abstract The eddy covariance (EC) method is one of the most widely used approaches to quantify surface‐atmosphere fluxes. However, scaling up from a single EC tower to the landscape remains an open challenge. To address this, we used 63 site years of data to examine simulated annual and growing season sums of carbon fluxes from three paired land‐cover type sites of corn, restored‐prairie, and switchgrass ecosystems. This was also done across the landscape by modeling fluxes using different land‐cover type input data. An artificial neural network (ANN) approach was used to model net ecosystem exchange (NEE), ecosystem respiration (R_eco), and gross primary production (GPP) at one paired site using environmental observations from the second site only. With a mean spatial separation of 11 km between paired sites, we were able to model annual sums of NEE,R_eco, and GPP with uncertainties of 20%, 22%, and 8%, respectively, relative to observation sums. When considering the growing season only, model uncertainties were 17%, 22%, and 9%, respectively for the three flux terms. We also show that ANN models can estimate sums ofR_ecoand GPP fluxes without needing the constraint of similar land‐cover‐type, with annual uncertainties of 12% and 10%. These results provide new insights to scaling up observations from one EC site beyond the footprint of the EC tower to multiple land‐cover types across the landscape. 

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3. Does growing atmospheric CO ₂ explain increasing carbon sink in a boreal coniferous forest?

   https://doi.org/10.1111/gcb.16117  

   Launiainen, Samuli; Katul, Gabriel G.; Leppä, Kersti; Kolari, Pasi; Aslan, Toprak; Grönholm, Tiia; Korhonen, Lauri; Mammarella, Ivan; Vesala, Timo (February 2022, Global Change Biology)

   Abstract The terrestrial net ecosystem productivity (NEP) has increased during the past three decades, but the mechanisms responsible are still unclear. We analyzed 17 years (2001–2017) of eddy‐covariance measurements of NEP, evapotranspiration (ET) and light and water use efficiency from a boreal coniferous forest in Southern Finland for trends and inter‐annual variability (IAV). The forest was a mean annual carbon sink (252 [42] gC ), and NEP increased at rate +6.4–7.0 gC (or ca. +2.5% ) during the period. This was attributed to the increasing gross‐primary productivity GPP and occurred without detectable change in ET. The start of annual carbon uptake period was advanced by 0.7 d , and increase in GPP and NEP outside the main growing season contributed ca. one‐third and one‐fourth of the annual trend, respectively. Meteorological factors were responsible for the IAV of fluxes but did not explain the long‐term trends. The growing season GPP trend was strongest in ample light during the peak growing season. Using a multi‐layer ecosystem model, we showed that direct fertilization effect diminishes when moving from leaf to ecosystem, and only 30–40% of the observed ecosystem GPP increase could be attributed to . The increasing trend in leaf‐area index (LAI), stimulated by forest thinning in 2002, was the main driver of the enhanced GPP and NEP of the mid‐rotation managed forest. It also compensated for the decrease of mean leaf stomatal conductance with increasing and LAI, explaining the apparent proportionality between observed GPP and trends. The results emphasize that attributing trends to their physical and physiological drivers is challenged by strong IAV, and uncertainty of LAI and species composition changes due to the dynamic flux footprint. The results enlighten the underlying mechanisms responsible for the increasing terrestrial carbon uptake in the boreal zone. 

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4. Using atmospheric observations to quantify annual biogenic carbon dioxide fluxes on the Alaska North Slope

   https://doi.org/10.5194/bg-19-5953-2022  

   Schiferl, Luke D.; Watts, Jennifer D.; Larson, Erik J.; Arndt, Kyle A.; Biraud, Sébastien C.; Euskirchen, Eugénie S.; Goodrich, Jordan P.; Henderson, John M.; Kalhori, Aram; McKain, Kathryn; et al (January 2022, Biogeosciences)

   Abstract. The continued warming of the Arctic could release vast stores of carbon into the atmosphere from high-latitude ecosystems, especially from thawingpermafrost. Increasing uptake of carbon dioxide (CO2) by vegetation during longer growing seasons may partially offset such release of carbon. However, evidence of significant net annual release of carbon from site-level observations and model simulations across tundra ecosystems has been inconclusive. To address this knowledge gap, we combined top-down observations of atmospheric CO2 concentration enhancements from aircraft and a tall tower, which integrate ecosystem exchange over large regions, with bottom-up observed CO2 fluxes from tundraenvironments and found that the Alaska North Slope is not a consistent net source nor net sink of CO2 to the atmosphere (ranging from −6 to+6 Tg C yr−1 for 2012–2017). Our analysis suggests that significant biogenic CO2 fluxes from unfrozen terrestrial soils, and likely inland waters, during the early cold season (September–December) are major factors in determining the net annual carbon balance of the North Slope, implying strong sensitivity to the rapidly warming freeze-up period. At the regional level, we find no evidence of the previously reported large late-cold-season (January–April) CO2 emissions to the atmosphere during the study period. Despite the importance of the cold-season CO2 emissions to the annual total, the interannual variability in the net CO2 flux is driven by the variability in growing season fluxes. During the growing season, the regional net CO2 flux is also highly sensitive to the distribution of tundra vegetation types throughout the North Slope. This study shows that quantification and characterization of year-round CO2 fluxes from the heterogeneous terrestrial and aquatic ecosystems in the Arctic using both site-level and atmospheric observations are important to accurately project the Earth system response to future warming. 

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5. Dynamic Plant–Herbivore Interactions between Bison Space Use and Vegetation Heterogeneity in a Tallgrass Prairie

   https://doi.org/10.3390/rs15225269  

   Ling, Bohua; Raynor, Edward J; Joern, Anthony; Goodin, Douglas G (November 2023, Remote Sensing)

   Investigations into plant–herbivore interactions are of importance for understanding grassland ecosystem dynamics. Our research quantified the effects of vegetation heterogeneity at a patch scale of 30 m on bison space use in a tallgrass prairie through the analyses of the resource utilization function. In addition, we assessed the vegetation heterogeneity associated with bison locations by comparing the patch-scale vegetation characteristics between areas with high and low bison space use through Mann–Whitney U tests. Furthermore, we simulated the interactions between bison and vegetation patches (2 × 2 m) during the early growing season for the lowland topographic positions using agent-based modeling (ABM) as a preliminary study of linking bison foraging site selection with vegetation responses to bison grazing dynamically. The bison grazing strategy in the ABM of the grassland system was adjusted to ensure consistency in the vegetation pattern variations related to bison space use between the simulation and the empirical on-the-ground observations. The results indicated the following: (1) The effects of the patch-scale vegetation heterogeneity on the bison foraging site selection varied across the seasons, which were most evident in the middle of the growing season. (2) A relatively high level of bison space use generally resulted in diverse grassland canopies with high variability and interspersion. (3) From the ABM of the grassland system, it can be implied that bison select patches with high quality and quantity at the beginning of the growing season; as the vegetation quality and quantity improve overall, the bison graze randomly. This pattern was confirmed by observations of the bison foraging site selection in our study site. The ABM proved to be valuable in exploring and elucidating the underlying mechanisms of the grassland dynamics with a native North American grazer. 

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