A considerable fraction of soil-respired CO2 is not emitted directly to the atmosphere

All data used in this study are freely available (http://criticalzone.org/ catalina-jemez/data/datasets/). The authors wish to thank Rebecca Larkin Minor and Nate Abramson for their careful operation and maintenance of the field measurement devices. The program “Unidades de Excelencia Científica del Plan Propio de Investigación de la Universidad de Granada” funded the cost of this publicationSoil CO2 efflux (Fsoil) is commonly considered equal to soil CO2 production (Rsoil), and both terms are used interchangeably. However, a non-negligible fraction of Rsoil can be consumed in the subsurface due to a host of disparate, yet simultaneous processes. The ratio between CO2 efflux/O2 influx, known as the apparent respiratory quotient (ARQ), enables new insights into CO2 losses from Rsoil not previously captured by Fsoil. We present the first study using continuous ARQ estimates to evaluate annual CO2 losses of carbon produced from Rsoil. We found that up to 1/3 of Rsoil was emitted directly to the atmosphere, whereas 2/3 of Rsoil was removed by subsurface processes. These subsurface losses are attributable to dissolution in water, biological activities and chemical reactions. Having better estimates of Rsoil is key to understanding the true influence of ecosystem production on Rsoil, as well as the role of soil CO2 production in other connected processes within the critical zoneThis project and data were supported by NSF awards 1417101 and 1331408, as well as by the European Commission project DIESEL (FP7-PEOPLE-2013-IOF, 625988) and the Spanish Ministry of Economy and Competitiveness (IJCI-2016-30822)

Bayesian inference and predictive performance of soil respiration models in the presence of model discrepancy

Bayesian inference of microbial soil respiration models is often based on the assumptions that the residuals are independent (i.e., no temporal or spatial correlation), identically distributed (i.e., Gaussian noise), and have constant variance (i.e., homoscedastic). In the presence of model discrepancy, as no model is perfect, this study shows that these assumptions are generally invalid in soil respiration modeling such that residuals have high temporal correlation, an increasing variance with increasing magnitude of CO2 efflux, and non-Gaussian distribution. Relaxing these three assumptions stepwise results in eight data models. Data models are the basis of formulating likelihood functions of Bayesian inference. This study presents a systematic and comprehensive investigation of the impacts of data model selection on Bayesian inference and predictive performance. We use three mechanistic soil respiration models with different levels of model fidelity (i.e., model discrepancy) with respect to the number of carbon pools and the explicit representations of soil moisture controls on carbon degradation; therefore, we have different levels of model complexity with respect to the number of model parameters. The study shows that data models have substantial impacts on Bayesian inference and predictive performance of the soil respiration models such that the following points are true: (i) the level of complexity of the best model is generally justified by the cross-validation results for different data models; (ii) not accounting for heteroscedasticity and autocorrelation might not necessarily result in biased parameter estimates or predictions, but will definitely underestimate uncertainty; (iii) using a non-Gaussian data model improves the parameter estimates and the predictive performance; and (iv) accounting for autocorrelation only or joint inversion of correlation and heteroscedasticity can be problematic and requires special treatment. Although the conclusions of this study are empirical, the analysis may provide insights for selecting appropriate data models for soil respiration modeling.U.S. Department of Energy [DE-SC0019438, DE-SC0008272]; U.S. National Science Foundation [EAR-1552329, OIA-1557349]Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Temperature response surfaces for mortality risk of tree species with future drought

Widespread, high levels of tree mortality, termed forest die-off, associated with drought and rising temperatures, are disrupting forests worldwide. Drought will likely become more frequent with climate change, but even without more frequent drought, higher temperatures can exacerbate tree water stress. The temperature sensitivity of drought-induced mortality of tree species has been evaluated experimentally for only single-step changes in temperature (ambient compared to ambient + increase) rather than as a response surface (multiple levels of temperature increase), which constrains our ability to relate changes in the driver with the biological response. Here we show that time-to-mortality during drought for seedlings of two western United States tree species, Pinus edulis (Engelm.) and Pinus ponderosa (Douglas ex C. Lawson), declined in continuous proportion with increasing temperature spanning a 7.7 °C increase. Although P. edulis outlived P. ponderosa at all temperatures, both species had similar relative declines in time-to-mortality as temperature increased (5.2% per °C for P. edulis; 5.8% per °C for P. ponderosa). When combined with the non-linear frequency distribution of drought duration—many more short droughts than long droughts—these findings point to a progressive increase in mortality events with global change due to warming alone and independent of additional changes in future drought frequency distributions. As such, dire future forest recruitment patterns are projected assuming the calculated 7–9 seedling mortality events per species by 2100 under business-as-usual warming occur, congruent with additional vulnerability predicted for adult trees from stressors like pathogens and pests. Our progressive projection for increased mortality events was driven primarily by the non-linear shape of the drought duration frequency distribution, a common climate feature of drought-affected regions. These results illustrate profound benefits for reducing emissions of carbon to the atmosphere from anthropogenic sources and slowing warming as rapidly as possible to maximize forest persistence.Peer reviewedPlant Biology, Ecology and Evolutio

Controlled Experiments of Hillslope Coevolution at the Biosphere 2 Landscape Evolution Observatory: Toward Prediction of Coupled Hydrological, Biogeochemical, and Ecological Change

Understanding the process interactions and feedbacks among water, porous geological media, microbes, and vascular plants is crucial for improving predictions of the response of Earth’s critical zone to future climatic conditions. However, the integrated coevolution of landscapes under change is notoriously difficult to investigate. Laboratory studies are limited in spatial and temporal scale, while field studies lack observational density and control. To bridge the gap between controlled laboratory and uncontrollable field studies, the University of Arizona built a macrocosm experiment of unprecedented scale: the Landscape Evolution Observatory (LEO). LEO comprises three replicated, heavily instrumented, hillslope-scale model landscapes within the environmentally controlled Biosphere 2 facility. The model landscapes were designed to initially be simple and purely abiotic, enabling scientists to observe each step in the landscapes’ evolution as they undergo physical, chemical, and biological changes over many years. This chapter describes the model systems and associated research facilities and illustrates how LEO allows for tracking of multiscale matter and energy fluxes at a level of detail impossible in field experiments. Initial sensor, sampler, and soil coring data are already providing insights into the tight linkages between water flow, weathering, and microbial community development. These interacting processes are anticipated to drive the model systems to increasingly complex states and will be impacted by the introduction of vascular plants and changes in climatic regimes over the years to come. By intensively monitoring the evolutionary trajectory, integrating data with mathematical models, and fostering community-wide collaborations, we envision that emergent landscape structures and functions can be linked, and significant progress can be made toward predicting the coupled hydro-biogeochemical and ecological responses to global change

Agrivoltaic system design tools for managing trade-offs between energy production, crop productivity and water consumption

Agrivoltaic systems that locate crop production and photovoltaic energy generation on the same land have the potential to aid the transition to renewable energy by reducing the competition between food, habitat, and energy needs for land while reducing irrigation requirements. Experimental efforts to date have not adequately developed an understanding of the interaction among local climate, array design and crop selection sufficient to manage trade-offs in system design. This study simulates the energy production, crop productivity and water consumption impacts of agrivoltaic array design choices in arid and semi-arid environments in the Southwestern region of the United States. Using the Penman–Monteith evapotranspiration model, we predict agrivoltaics can reduce crop water consumption by 30%–40% of the array coverage level, depending on local climate. A crop model simulating productivity based on both light level and temperature identifies afternoon shading provided by agrivoltaic arrays as potentially beneficial for shade tolerant plants in hot, dry settings. At the locations considered, several designs and crop combinations exceed land equivalence ratio values of 2, indicating a doubling of the output per acre for the land resource. These results highlight key design axes for agrivoltaic systems and point to a decision support tool for their development

Ecosystem hydrologic and metabolic flashiness are shaped by plant community traits and precipitation

Understanding the hydrologic and carbon cycling consequences of precipitation variability in dryland ecosystems requires improved appreciation and accounting of how above- and belowground biophysical processes differ in their response to rainfall. Our objective was to contrast the sensitivity of dryland ecosystem evapotranspiration (ET), gross ecosystem productivity (GEP), and ecosystem respiration (R-e) in response to inter- and intra-annual precipitation variability in a nearby grassland, savanna, and shrubland ecosystems in southeastern Arizona. To do this, we modified the Richards-Baker index, which quantifies the flashiness of a stream's hydrograph, to calculate analogous indices of ecosystem hydrologic and metabolic flashiness. In this way, ecosystem flashiness describes the frequency and rapidity of short-term fluctuations in H2O and CO2 exchange in response to precipitation while preserving the sequence of day-to-day variation in fluxes using tower-based time-series of daily averaged ET, GEP and R-e. We calculated annual hydrologic, GEP, and R-e flashiness (f(ET), f(GEP) and f(Re) respectively) using 6 years of daily-averaged fluxes estimated from eddy covariance. In contrast to our prediction, annual f(GEP) was consistently greater than annual f(Re). Furthermore, we predicted that increasing rooting depth would correlate with a decline in annual f(ET) and f(GEP). In fact, annual f(GEP) was similar between the grassland, savanna, and shrubland. Whereas the response of annual f(ET) and f(GEP) to annual precipitation was plant community dependent and generally declined with increasing rainfall, annual f(Re) did not vary in response to precipitation. The effect of late summer storms on f(GEP) was plant community dependent such that shrubland f(GEP) and f(Re) strongly declined in response to rainfall whereas grassland and savanna f(GEP) was relatively unresponsive. Conceptually similar to hydrologic flashiness, ecosystem flashiness may provide an additional lens through which to observe the influence of resource availability, shifts in community composition, and disturbance on ecosystem hydrologic and carbon cycling.NSF Earth Sciences award [EAR 1417101]; United States Department of Energy (DOE); United States Department of Agriculture (USDA)24 month embargo; published online: 27 August 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Intraspecific competition for host resources in a parasite

Intraspecific competition among parasites should, in theory, increase virulence, but we lack clear evidence of this from nature.1-3 Parasitic plants, which are sessile and acquire carbon-based resources through both autotrophy (photosynthesis) and heterotrophy (obtaining carbon from the host), provide a unique opportunity to experimentally study the role of intraspecific competition for nutrients in shaping the biology of both parasite and host.4-6 Here, we manipulated the spatial position of naturally occurring individuals of desert mistletoe (Phoradendron californicum), a xylem hemiparasite, by removing parasites from co-infected branches of a common nitrogen-fixing host, velvet mesquite (Prosopsis velutina), in the Sonoran Desert. We measured physiological performance of both host and parasite individuals under differing competitive environments-parasite location along the xylem stream-through time. Performance was determined by measuring resource availability and use, given that resource demand changed with competitor removal and monsoon-driven amelioration of seasonal drought. Our principal finding was that intraspecific competition exists for xylem resources between mistletoe individuals, including host carbon. Host performance and seasonal climate variation altered the strength of competition and virulence. Hemiparasitic desert mistletoes demonstrated high heterotrophy, yet experimental removals revealed density- and location-dependent effects on the host through feedbacks that reduced mistletoe autotrophy and improved resource availability for the remaining mistletoe individual. Trophic flexibility tempered intraspecific competition for resources and reduced virulence. Mistletoe co-infections might therefore attenuate virulence to maintain access to resources in particularly stressful ecological environments. In summary, experimental field manipulations revealed evidence for intraspecific competition in a parasite species

Ecosystem carbon and water cycling from a sky island montane forest

Sky islands are characteristic of sequential mountain-valley terrain where mountains form an island archipelago rising from surrounding valleys of desert "sea". At high elevations in the Madrean sky islands of the southwestern United States (USA) and Mexico, mixed evergreen conifer forests occur near the latitudinal extent of their distribution. This setting provides a unique opportunity to explore the ecosystem response to warmer and drier conditions that are forecasted to become more common throughout the species range. Accordingly, this work used the eddy covariance method to quantify carbon and water cycling dynamics from a Madrean sky island forest ecosystem for nine years between 2009 and 2018. The forest functioned as net sink of carbon dioxide throughout the year, which resulted in more carbon sequestration than other monitored montane forests in the continental western USA. Sustained forest activity was made possible by the combination of mild winter temperatures and a bimodal precipitation regime that delivered moisture during both summer and winter. Seasonally, gross primary production (GPP) was temperature limited in winter and could become moisture limited during the dry early summer period depending on antecedent snowmelt moisture. Ecosystem respiration was more sensitive than GPP to moisture availability throughout the rest of the non-winter period. Forecasted warming could thus stimulate forest carbon gains during the winter and either increase or decrease respiratory carbon loss during summer as a function of moisture. Overall, a metric of snow aridity that included snow depth and potential evapotranspiration was the best predictor of the warm season carbon balance (R-2 = 0.86). The seasonally dissimilar impacts of warming and drying identified by this work inform current understanding of how climate change and/or variability may affect forest water and carbon cycling dynamics throughout the montane forest biome.24 month embargo; published online: 20 November 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Cool-season whole-plant gas exchange of exotic and native semiarid bunchgrasses

The success of invasive aridland plants may depend on their utilization of precipitation not fully exploited by native species, which could lead to seasonally altered ecosystem carbon and water fluxes. We measured volumetric soil water across 25-cm profiles (θ25cm) and springtime whole-plant water- and carbon-fluxes of the exotic Lehmann lovegrass (Eragrostis lehmanniana) and a native bunchgrass, bush muhly (Muhlenbergia porteri), following typical (55 mm in 2009) and El Niño-enhanced accumulations (154 mm in 2010) in a SE Arizona savanna. Across both years, h25cm was higher under lovegrass plots, with similar evapotranspiration (ET) between lovegrass and bush muhly plots. However, in 2010 transpiration (T) was higher in bush muhly than lovegrass, implying higher soil evaporation in lovegrass plots maintained similar ET. Net ecosystem carbon dioxide exchange (NEE) was similar between lovegrass and bush muhly plots in 2009, but was more negative in bush muhly plots following El Niño, indicating greater CO2 assimilation. Ecosystem respiration (Reco) and gross ecosystem photosynthesis (GEP) were similar between lovegrass and bush muhly plots in 2009, but were higher in bush muhly plots in 2010. As a result, lovegrass plots reduced ecosystem water-use efficiency (WUEe = NEE/ET), while bush muhly WUEe remained constant between 2009 and 2010. Concurrent whole-plant WUE (WUEp = GEP/T) did not change in lovegrass plots, but increased in bush muhly plots between these years. We concluded that cool-season precipitation use is not a component of Lehmann lovegrass invasive success, but that the change in ET partitioning and attendant shifts in cool-season WUEe may increase interannual variation in ecosystem water- and carbon-exchange dynamics in the water-limited systems it dominates

Improving the accuracy of the gradient method for determining soil carbon dioxide efflux

Soil CO2 efflux (F-soil) represents a significant source of ecosystem CO2 emissions that is rarely quantified with high-temporal-resolution data in carbon flux studies. F-soil estimates can be obtained by the low-cost gradient method (GM), but the utility of the method is hindered by uncertainties in the application of published models for the diffusion coefficient. Therefore, to address and resolve these uncertainties, we compared F-soil measured by 2 soil CO2 efflux chambers and F-soil estimated by 16 gas transport models using the GM across 1year. We used 14 published empirical gas diffusion models and 2 in situ models: (1) a gas transfer model called Chamber model obtained using a calibration between the chamber and the gradient method and (2) a diffusion model called SF6 model obtained through an interwell conservative tracer experiment. Most of the published models using the GM underestimated cumulative annual F-soil by 55% to 361%, while the Chamber model closely approximated cumulative F-soil (0.6% error). Surprisingly, the SF6 model combined with the GM underestimated F-soil by 32%. Differences between in situ models could stem from the Chamber model implicitly accounting for production of soil CO2, while the conservative tracer model does not. Therefore, we recommend using the GM only after calibration with chamber measurements to generate reliable long-term ecosystem F-soil measurements. Accurate estimates of F-soil will improve our understanding of soil respiration's contribution to ecosystem fluxes.NSF [1417101, 1331408]; Marie Curie International Outgoing Fellowship within the Seventh European Community, DIESEL project [625988]6 month embargo; First published: 5 January 2017This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]