Testing predictions used to build an agrivoltaics installation on a small-scale educational model

Models are valuable tools for explaining and testing systems. Small-scale models can be especially useful for educational purposes. For models to be useful, they have to accurately depict the larger system that they are describing. A novel man-made system, known as an agrivoltaic structure, is being constructed at Biosphere 2 near Oracle, Arizona. The word agrivoltaic is a combination of agriculture and photovoltaics, or solar farming. My research involved creating a small-scale version of this system for educational purposes. The model of this system tested two predictions: that plants will grow better in the shade of a panel and that the plants will cool the solar panel through transpiration. These two predictions were tested using low-tech solutions that are affordable for classroom teachers. Predictions were tested using water and scales to measure soil moisture; infrared guns to measure plant and panel temperature; and HOBO air temperature sensors. There was little quantitative data to support the claim that plants grew better in shade than sun; however, the model system is young and may need time to grow. While some observational evidence supported the second prediction, the data was not significant. Both sets of data appeared to be highly dependent on environmental factors, such as sun position. Even without upholding the predictions, this model worked well as an educational tool, allowing students to better understand the value of research and the benefits and limitations of models

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]

Does the Production of Isoprene Affect the Productivity of Poplars?

Poplar trees are known to produce a chemical called isoprene that plays a complex, and not fully understood, role in the chemical process of photosynthesis. Understanding why plants produce isoprene and under what conditions will help scientists make more accurate predictions about poplars’ photosynthetic capabilities in future climates. What benefit could isoprene provide a plant? The literature suggests its production could help plants tolerate heat stress. We studied two genetic lines of trees in a common garden of Populus, one line with the gene for producing isoprene and a second line without that gene. We subjected some trees of each line to low water conditions to investigate if isoprene played a role in allowing plants to cope with water stress. We then compared the ability of these 4 treatment groups of poplars to photosynthesize over a range of temperatures. Poplars with and without isoprene showed similar rates of photosynthesis over the range of temperatures measured. Poplars subjected to low water conditions and poplars with normal water conditions also recorded similar rates of photosynthesis. This suggests that isoprene does not offer a photosynthetic benefit, and also that the low water conditions may not have triggered a water stressed state in the poplars. However, the poplars’ rate of photosynthesis differed between morning and afternoon, suggesting that time of day could play a role in photosynthesis. Future work is needed to understand how the influence of time of day on photosynthesis may overshadow any differences due to isoprene production

Increasing Food Production in Drylands Using Agrivoltaics

In the desert, native plants respond to the hottest part of the day by either closing their stomata, which would stop photosynthesis, or by simply reducing their photosynthesis rates due to heat stress. Soil water resources are also impacted due to significant evaporation. If plants have more shade during the day, will they photosynthesize more in the afternoon than plants without shade? Will these plants with shade transpire less, and thus need to be watered less? This study takes a look at plants which have grown under a photovoltaics array (a new agriculture practice called agrivoltaics) as well as plants which have grown in the open (modeling traditional agriculture practices). It was hypothesized the agrivoltaics practice will benefit plants by providing them shade and retaining soil moisture during the day as well as benefiting the photovoltaics by keeping them cooler to increase their efficiency. This study was designed to determine whether growing under the photovoltaic panels is beneficial, by collecting and analyzing data on photosynthesis (carbon uptake) and transpiration (water loss) rates of 8+ different species. These measurements will help answer which plants are best suited for being planted in an agrivoltaics installation

Biotic soil-plant interaction processes explain most of hysteretic soil CO2 efux response to temperature in cross-factorial mesocosm experiment

Ecosystem carbon fux partitioning is strongly infuenced by poorly constrained soil CO2 efux (Fsoil). Simple model applications (Arrhenius and Q10) do not account for observed diel hysteresis between Fsoil and soil temperature. How this hysteresis emerges and how it will respond to variation in vegetation or soil moisture remains unknown. We used an ecosystem-level experimental system to independently control potential abiotic and biotic drivers of the Fsoil-T hysteresis. We hypothesized a principally biological cause for the hysteresis. Alternatively, Fsoil hysteresis is primarily driven by thermal convection through the soil profle. We conducted experiments under normal, fuctuating diurnal soil temperatures and under conditions where we held soil temperature near constant. We found (i) signifcant and nearly equal amplitudes of hysteresis regardless of soil temperature regime, and (ii) the amplitude of hysteresis was most closely tied to baseline rates of Fsoil, which were mostly driven by photosynthetic rates. Together, these fndings suggest a more biologically-driven mechanism associated with photosynthate transport in yielding the observed patterns of soil CO2 efux being out of sync with soil temperature. These fndings should be considered on future partitioning models of ecosystem respiration.French governmentFrench National Research Agency (ANR) ANR-10-IDEX-0001-02 PSL ANR-11-INBS-0001ENSUniversity of Arizona (UofA)Philecology Foundation (Fort Worth, Texas, USA)Thomas R. Brown Family FoundationRegion Ile-de-France I-05-098/R 2011-11017735European Union (EU)National Science Foundation (NSF) 1417101 1331408European Union (EU) 625988UofA Office of Global InitiativesOffice of the Vice President of Research at the UofAUMI iGLOBES program at the Uof

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

TEMPERATURE AND PRECIPITATION CONTROLS OVER SOIL, LEAF AND ECOSYSTEM LEVEL CO2 FLUX ALONG A WOODY PLANT ENCROACHMENT GRADIENT

Woody plant encroachment (WPE) into historic grasslands not only alters ecosystem structure but also yields a mosaic of vegetative growth-forms that differ in their inherent physiological capacities and physical attributes. C₃ plants tend to have a relatively broad range of temperature function but at the expensive of a lower optimum rate of photosynthesis. In contrast, C₄ grasses have a greater capacity for maximum uptake but across a relatively narrow range of temperatures. In considering which of these functional groups will outcompete the other within these regions undergoing WPE, one must account not only for these leaf physiological traits, but also the growth form induced differences in rooting depth, and therefore, potential access to deeper subsurface water. Laid upon these competitive interactions is an ever-changing environment, which for the semiarid southwestern US is predicted to become progressively warmer and characterized by highly variable precipitation with longer interstorm periods. In addition to aboveground changes in CO₂ assimilation, WPE influences soil nutrient, water, and carbon cycling. The objectives of this dissertation were to quantify: (1) the influence that temperature and available soil moisture have on regulating soil respiratory efflux within the microhabitats that results from WPE to estimate the influence this vegetative change will have on ecosystem CO₂ efflux; (2) the sensitivity of CO₂ uptake within grassland and woodland ecosystems to temperature and precipitation input in an effort to characterize how WPE might influence regional carbon and water balance; and (3) the role access to stable groundwater has in regulating the temperature sensitivity of ecosystems and their component fluxes. Major findings and contributions of this research include illustrating seasonal patterns of soil respiration within the microhabitats that result from WPE, such that an analysis of the relative contributions of these different components could be made. We found that soil respiration was not only consistently greater under mesquites, but that the relative contributions of these microhabitats varied significantly throughout the year, the duration of soil respiration after each rain was habitat-specific, and that the relationship between soil respiration and temperature followed a hysteretic pattern rather than a linear function (Appendix A). We found that a woodland ecosystem demonstrated a lower temperature sensitivity than a grassland across all seasonal periods of varying soil moisture availability, and that by maintaining physiological function across a wider range of temperatures throughout periods of limited precipitation, C₃ mesquites were acquiring large amounts of carbon while C₄ grasses were limited to functioning within a narrower range of temperatures (Appendix B). Finally, we found that having a connectivity to stable groundwater decoupled leaf and ecosystem scale temperature sensitivities relative to comparable sites lacking such access. Access to groundwater not only resulted in the temperature sensitivity of a riparian shrubland being nearly half that of the upland site throughout all seasonal periods, but also actual rates of net ecosystem productivity and leaf level rates of photosynthesis being dramatically enhanced (Appendix C)