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1. Multi-variable, multi-configuration testing of ORCHIDEE land surface model water flux and storage estimates across semi-arid sites in the southwestern US

   https://doi.org/10.5194/hess-2019-598  

   MacBean, N. ; Scott, R. ; Biederman, J. ; Ottlé, C. ; Vuichard, N. ; Ducharne, A. ; Kolb, T. ; Dore, S. ; Litvak, M.E. ; Moore, D. ( December 2019 , Hydrology and Earth System Sciences Discussions)

   null (Ed.)

   Abstract. Plant activity in semi-arid ecosystems is largely controlled by pulses of precipitation, making them particularly vulnerable to increased aridity expected with climate change. Simple bucket-model hydrology schemes in land surface models (LSMs) have had limited ability in accurately capturing semi-arid water stores and fluxes. Recent, more complex, LSM hydrology models have not been widely evaluated against semi-arid ecosystem in situ data. We hypothesize that the failure of older LSM versions to represent evapotranspiration, ET, in arid lands is because simple bucket models do not capture realistic fluctuations in upper layer soil moisture. We therefore predict that including a discretized soil hydrology scheme based on a mechanistic description of moisture diffusion will result in an improvement in model ET when compared to data because the temporal variability of upper layer soil moisture content better corresponds to that of precipitation inputs. To test this prediction, we compared ORCHIDEE LSM simulations from (1) a simple conceptual 2-layer bucket scheme with fixed hydrological parameters; and (2) a 11-layer discretized mechanistic scheme of moisture diffusion in unsaturated soil based on Richards equations against daily and monthly soil moisture and ET observations, together with data-derived transpiration / evaporation, T / ET, ratios, from six semi-arid grass, shrub and forest sites in the southwestern USA. The 11-layer scheme also has modified calculations of surface runoff, bare soil evaporation, and water limitation to be compatible with the more complex hydrology configuration. To diagnose remaining discrepancies in the 11-layer model, we tested two further configurations: (i) the addition of a term that captures bare soil evaporation resistance to dry soil; and (ii) reduced bare soil fraction. We found that the more mechanistic 11-layer model results better representation of the daily and monthly ET observations. We show that is likely because of improved simulation of soil moisture in the upper layers of soil (top 5 cm). Some discrepancies between observed and modelled soil moisture and ET may allow us to prioritize future model development. Adding a soil resistance term generally decreased simulated E and increased soil moisture content, thus increasing T and T / ET ratios and reducing the negative T / ET model-data bias. By reducing the bare soil fraction in the model, we illustrated that modelled leaf T is too low at sparsely vegetated sites. We conclude that a discretized soil hydrology scheme and associated developments improves estimates of ET by allowing the model to more closely match the pulse precipitation dynamics of these semi-arid ecosystems; however, the partitioning of T from bare soil evaporation is not solved by this modification alone. 

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2. The influence of rising tropospheric carbon dioxide and ozone on plant productivity

   https://doi.org/10.1111/plb.12973  

   Ainsworth, E. A. ; Lemonnier, P. ; Wedow, J. M. ; Tausz‐Posch, ed., S. ( March 2019 , Plant Biology)

   Human activities result in a wide array of pollutants being released to the atmosphere. A number of these pollutants have direct effects on plants, including carbon dioxide (CO₂), which is the substrate for photosynthesis, and ozone (O₃), a damaging oxidant. How plants respond to changes in these atmospheric air pollutants, both directly and indirectly, feeds back on atmospheric composition and climate, global net primary productivity and ecosystem service provisioning. Here we discuss the past, current and future trends in emissions ofCO₂and O₃and synthesise the current atmosphericCO₂and O₃budgets, describing the important role of vegetation in determining the atmospheric burden of those pollutants. While increased atmosphericCO₂concentration over the past 150 years has been accompanied by greaterCO₂assimilation and storage in terrestrial ecosystems, there is evidence that rising temperatures and increased drought stress may limit the ability of future terrestrial ecosystems to buffer against atmospheric emissions. Long‐term Free AirCO₂or O₃Enrichment (FACE) experiments provide critical experimentation about the effects of futureCO₂and O₃on ecosystems, and highlight the important interactive effects of temperature, nutrients and water supply in determining ecosystem responses to air pollution. Long‐term experimentation in both natural and cropping systems is needed to provide critical empirical data for modelling the effects of air pollutants on plant productivity in the decades to come.

    

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3. Climate warming alters photosynthetic responses to elevated CO 2 in prairie plants

   https://doi.org/10.1002/ajb2.1532  

   Sage, Emma ; Heisler‐White, Jana ; Morgan, Jack ; Pendall, Elise ; Williams, David G. ( September 2020 , American Journal of Botany)

   The impact of elevated CO₂concentration ([CO₂]) and climate warming on plant productivity in dryland ecosystems is influenced strongly by soil moisture availability. We predicted that the influence of warming on the stimulation of photosynthesis by elevated [CO₂] in prairie plants would operate primarily through direct and indirect effects on soil water.

   We measured light‐saturated photosynthesis (A_net), stomatal conductance (g_s), maximum Rubisco carboxylation rate (V_cmax), maximum electron transport capacity (J_max) and related variables in four C₃plant species in the Prairie Heating and CO₂Enrichment (PHACE) experiment in southeastern Wyoming. Measurements were conducted over two growing seasons that differed in the amount of precipitation and soil moisture content.

   A_netin the C₃subshrubArtemisia frigidaand the C₃forbSphaeralcea coccineawas stimulated by elevated [CO₂] under ambient and warmed temperature treatments. Warming by itself reducedA_netin all species during the dry year, but stimulated photosynthesis inS. coccineain the wet year. In contrast,A_netin the C₃grassPascopyrum smithiiwas not stimulated by elevated [CO₂] or warming under wet or dry conditions. Photosynthetic downregulation under elevated [CO₂] in this species countered the potential stimulatory effect under improved water relations. Warming also reduced the magnitude of CO₂‐induced down‐regulation in this grass, possibly by sustaining high levels of carbon utilization.

   Direct and indirect effects of elevated [CO₂] and warming on soil water was an overriding factor influencing patterns ofA_netin this semi‐arid temperate grassland, emphasizing the important role of water relations in driving grassland responses to global change.

    

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4. Modeling seasonal vegetation phenology from hydroclimatic drivers for contrasting plant functional groups within drylands of the Southwestern USA

   https://doi.org/10.1088/2752-664X/acb9a0  

   Warter, Maria Magdalena ; Singer, Michael Bliss ; Cuthbert, Mark O ; Roberts, Dar ; Caylor, Kelly K ; Sabathier, Romy ; Stella, John ( March 2023 , Environmental Research: Ecology)

   Abstract In dryland ecosystems, vegetation within different plant functional groups exhibits distinct seasonal phenologies that are affected by the prevailing hydroclimatic forcing. The seasonal variability of precipitation, atmospheric evaporative demand, and streamflow influences root-zone water availability to plants in water-limited environments. Increasing interannual variations in climate forcing of the local water balance and uncertainty regarding climate change projections have raised the potential for phenological shifts and changes to vegetation dynamics. This poses significant risks to plant functional types across large areas, especially in drylands and within riparian ecosystems. Due to the complex interactions between climate, water availability, and seasonal plant water use, the timing and amplitude of phenological responses to specific hydroclimate forcing cannot be determined a priori , thus limiting efforts to dynamically predict vegetation greenness under future climate change. Here, we analyze two decades (1994–2021) of remote sensing data (soil adjusted vegetation index (SAVI)) as well as contemporaneous hydroclimate data (precipitation, potential evapotranspiration, depth to groundwater, and air temperature), to identify and quantify the key hydroclimatic controls on the timing and amplitude of seasonal greenness. We focus on key phenological events across four different plant functional groups occupying distinct locations and rooting depths in dryland SE Arizona: semi-arid grasses and shrubs, xeric riparian terrace and hydric riparian floodplain trees. We find that key phenological events such as spring and summer greenness peaks in grass and shrubs are strongly driven by contributions from antecedent spring and monsoonal precipitation, respectively. Meanwhile seasonal canopy greenness in floodplain and terrace vegetation showed strong response to groundwater depth as well as antecedent available precipitation (aaP = P − PET) throughout reaches of perennial and intermediate streamflow permanence. The timings of spring green-up and autumn senescence were driven by seasonal changes in air temperature for all plant functional groups. Based on these findings, we develop and test a simple, empirical phenology model, that predicts the timing and amplitude of greenness based on hydroclimate forcing. We demonstrate the feasibility of the model by exploring simple, plausible climate change scenarios, which may inform our understanding of phenological shifts in dryland plant communities and may ultimately improve our predictive capability of investigating and predicting climate-phenology interactions in the future. 

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5. ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO₂, water, and energy fluxes on daily to annual scales

   https://doi.org/10.5194/gmd-11-497-2018  

   Qiu, Chunjing ; Zhu, Dan ; Ciais, Philippe ; Guenet, Bertrand ; Krinner, Gerhard ; Peng, Shushi ; Aurela, Mika ; Bernhofer, Christian ; Brümmer, Christian ; Bret-Harte, Syndonia ; et al ( January 2018 , Geoscientific Model Development)

   Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO₂ fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (V_cmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r² =  0.76; Nash–Sutcliffe modeling efficiency, MEF  =  0.76) and ecosystem respiration (ER, r² =  0.78, MEF  =  0.75), with lesser accuracy for latent heat fluxes (LE, r² =  0.42, MEF  =  0.14) and and net ecosystem CO₂ exchange (NEE, r² =  0.38, MEF  =  0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r² values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r² values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r² < 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized V_cmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average V_cmax value. 

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