Soil warming affects sap flow and stomatal gas exchange through altering functional traits in a subtropical forest

Climate warming influences the structure and function of ecosystems. However, the mechanisms of plant water use and gas exchange responses to climate warming have been less studied, especially from the perspective of different functional traits. We conducted a field experiment to investigate how soil warming (+2 °C) affects sap flow and stomatal gas exchange through plant functional traits and nutrient characteristics in a subtropical forest. We measured stomatal gas exchange of trees (Acacia auriculiformis and Schima superba) and shrubs (Castanea henryi and Psychotria asiatica), and monitored long-term sap flow of both tree species. Besides, plant leaf nutrient contents, functional traits, and soil nutrients were also studied. It is demonstrated that soil warming significantly increased maximum sap flow density (Js_max, 35.1 %) and whole-tree transpiration (EL, 46.0 %) of A. auriculiformis, but decreased those of S. superba (15.6 % and 14.9 %, respectively). Warming increased the photosynthetic rate of P. asiatica (18.0 %) and water use efficiency of S. superba (47.2 %). Leaf nutrients and stomatal anatomical characteristics of shrubs were less affected by soil warming. Soil warming increased (+42.7 %) leaf K content of A. auriculiformis in dry season. Decomposition of soil total carbon, total nitrogen, and available nitrogen was accelerated under soil warming, and soil exchangeable Ca2+ and Mg2+ were decreased. Trees changed stomatal and anatomic traits to adapt to soil warming, while shrubs altered leaf water content and specific leaf area under soil warming. Warming had a greater effect on sap flow of trees, as well as on their leaf gas exchange (total effect: -0.27) than on that of shrubs (total effect: 0.06). In summary, our results suggest that the combination of functional and nutrient traits can help to better understand plant water use and gas exchange responses under climate warming.

Panarchy theory for convergence

Coping with surprise and uncertainty resulting from the emergence of undesired and unexpected novelty or the sudden reorganization of systems at multiple spatiotemporal scales requires both a scientific process that can incorporate diverse expertise and viewpoints, and a scientific framework that can account for the structure and dynamics of interacting social-ecological systems (SES) and the inherent uncertainty of what might emerge in the future. We argue that combining a convergence scientific process with a panarchy framework provides a pathway for improving our understanding of, and response to, emergence. Emergent phenomena are often unexpected (e.g., pandemics, regime shifts) and can be highly disruptive, so can pose a significant challenge to the development of sustainable and resilient SES. Convergence science is a new approach promoted by the U.S. National Science Foundation for tackling complex problems confronting humanity through the integration of multiple perspectives, expertise, methods, tools, and analytical approaches. Panarchy theory is a framework useful for studying emergence, because it characterizes complex systems of people and nature as dynamically organized and structured within and across scales of space and time. It accounts for the fundamental tenets of complex systems and explicitly grapples with emergence, including the emergence of novelty, and the emergent property of social-ecological resilience. We provide an overview of panarchy, convergence science, and emergence. We discuss the significant data and methodological challenges of using panarchy in a convergence approach to address emergent phenomena, as well as state-of-the-art methods for overcoming them. We present two examples that would benefit from such an approach: climate change and its impacts on social-ecological systems, and the relationships between infectious disease and social-ecological systems.

Effects of Vegetation Phenology on Ecosystem Water Use Efficiency in a Semiarid Region of Northern China

Water use efficiency (WUE) is an important ecosystem functional property for measuring coupled relationships of the carbon-water cycle. Both biotic and environmental factors significantly impact WUE in terrestrial ecosystems. Relationships between environmental factors and WUE have been well discussed in previous studies. Although the crucial role of vegetation phenology, a common indicator of climate-vegetation interactions, in regulating the WUE has been widely reported, the underlying mechanism has not yet to be fully elucidated. Here, we utilized multiple long-term remote sensing datasets to analyze the interannual changes in seasonal WUE, and discussed the potential associations between phenology and WUE in the Luanhe River basin, which is a typical semiarid region of China, from 1988 to 2015. Most of the pixels across Luanhe River basin showed increasing spring WUE and decreasing autumn WUE. The start of the growing season (SOS) was slightly advanced by an average of 0.06 days per year (d/y) in the whole study area, with a delayed trend (0.04 d/y) in the upper reaches region (UR) and an advanced trend (0.20 d/y) in the middle-lower reaches region (MLR). The end of the growing season (EOS) showed a generally delayed trend (0.11 d/y) across the basin. Furthermore, negative correlations were detected between spring WUE and SOS in the UR, while positive correlations were detected in the MLR. The opposite patterns of the relationship of autumn WUE and EOS were also found between UR and MLR. The results were attributed to the balance and compensation of biotic and abiotic factors in the regulation of ecosystem WUE. Our findings provide new insights into the interaction between vegetation dynamics and carbon-water cycle coupling.

Community Composition and Structure Affect Ecosystem and Canopy Water Use Efficiency Across Three Typical Alpine Ecosystems

Unique ecosystems distributed in alpine areas of the Qinghai-Tibetan Plateau play important roles in climate change mitigation, local food supply, and conservation of species diversity. To understand the water use efficiency (WUE) of this fragile and sensitive region, this study combined observed data from the eddy covariance system and the Shuttleworth-Wallace (S-W) model to measure the continuous mass exchange, including gross primary productivity (GPP), evapotranspiration (ET), and canopy transpiration (T) throughout 2 or 3 years (2016-2018) in three common alpine ecosystems (i.e., alpine steppe, alpine meadow, and alpine swamp). These ecosystems represent a water availability gradient and thus provide the opportunity to quantify environmental and biological controls on WUE at various spatiotemporal scales. We analyzed the ecosystem WUE (WUEe; defined as the ratio of GPP to ET) and canopy WUE (WUEc; defined as the ratio of GPP and canopy T). It was found that the yearly WUEe was 1.40, 1.63, and 2.16 g C kg-1 H2O, and the yearly WUEc was 8.93, 2.46, and 5.19 g C kg-1 H2O in the three typical ecosystems, respectively. The controlling factors of yearly WUE diverged between WUEe and WUEc. We found that plant functional group proportion (e.g., gramineous and Cyperaceae) highly explained the yearly WUEe variation across sites, and a good correlation was observed between community species diversity and WUEc. These findings suggest that community composition and trait change are critical in regulating WUEe and WUEc across different alpine ecosystems and that the regulation mechanisms may differ fundamentally between WUEe and WUEc.

Relating coccidioidomycosis (valley fever) incidence to soil moisture conditions

Coccidioidomycosis (also called Valley fever) is caused by a soilborne fungus, Coccidioides spp., in arid regions of the southwestern United States. Though some who develop infections from this fungus remain asymptomatic, others develop respiratory disease as a consequence. Less commonly, severe illness and death can occur when the infection spreads to other regions of the body. Previous analyses have attempted to connect the incidence of coccidioidomycosis to broadly available climatic measurements, such as precipitation or temperature. However, with the limited availability of long-term, in situ soil moisture data sets, it has not been feasible to perform a direct analysis of the relationships between soil moisture levels and coccidioidomycosis incidence on a larger temporal and spatial scale. Utilizing in situ soil moisture gauges throughout the southwest from the U.S. Climate Reference Network and a model with which to extend those estimates, this work connects periods of higher and lower soil moisture in Arizona and California between 2002 and 2014 to the reported incidence of coccidioidomycosis. The results indicate that in both states, coccidioidomycosis incidence is related to soil moisture levels from previous summers and falls. Stated differently, a higher number of coccidioidomycosis cases are likely to be reported if previous bands of months have been atypically wet or dry, depending on the location.

Nonlinear responses of soil respiration to precipitation changes in a semiarid temperate steppe

Extreme precipitation events are predicted to occur more frequently and will have significant influences on terrestrial ecosystem carbon (C) cycling in the future. However, response patterns of soil respiration to precipitation changes remain uncertain in terrestrial ecosystems. A field experiment with seven precipitation treatments (i.e. from −60% to +60% of ambient precipitation to form a drought to wet precipitation gradient) was conducted over three growing seasons (2010–2012) in a semiarid temperate steppe of Northern China. Results showed a nonlinear response pattern of soil respiration along the experimental precipitation gradient, with soil respiration suppressed by decreased precipitation and enhanced by increased precipitation. Over the three growing seasons, soil respiration was reduced more under the three drought treatments (by 45.8, 32.8, and 15.9% under the −60, −40, and −20% treatments, respectively) than stimulated under the three wet treatments (by 8.9, 14.3, and 18.5% under the +20, +40, and +60% treatments, respectively). Our results indicate that soil respiration was more sensitive to decreased than increased precipitation treatments. The nonlinear and asymmetric responses of soil respiration to precipitation changes should be built into ecosystem models to project ecosystem C cycling associated with climate change.

Change in terrestrial ecosystem water-use efficiency over the last three decades

Defined as the ratio between gross primary productivity (GPP) and evapotranspiration (ET), ecosystem-scale water-use efficiency (EWUE) is an indicator of the adjustment of vegetation photosynthesis to water loss. The processes controlling EWUE are complex and reflect both a slow evolution of plants and plant communities as well as fast adjustments of ecosystem functioning to changes of limiting resources. In this study, we investigated EWUE trends from 1982 to 2008 using data-driven models derived from satellite observations and process-oriented carbon cycle models. Our findings suggest positive EWUE trends of 0.0056, 0.0007 and 0.0001 g C m(-2)  mm(-1)  yr(-1) under the single effect of rising CO2 ('CO2 '), climate change ('CLIM') and nitrogen deposition ('NDEP'), respectively. Global patterns of EWUE trends under different scenarios suggest that (i) EWUE-CO2 shows global increases, (ii) EWUE-CLIM increases in mainly high latitudes and decreases at middle and low latitudes, (iii) EWUE-NDEP displays slight increasing trends except in west Siberia, eastern Europe, parts of North America and central Amazonia. The data-driven MTE model, however, shows a slight decline of EWUE during the same period (-0.0005 g C m(-2)  mm(-1)  yr(-1) ), which differs from process-model (0.0064 g C m(-2)  mm(-1)  yr(-1) ) simulations with all drivers taken into account. We attribute this discrepancy to the fact that the nonmodeled physiological effects of elevated CO2 reducing stomatal conductance and transpiration (TR) in the MTE model. Partial correlation analysis between EWUE and climate drivers shows similar responses to climatic variables with the data-driven model and the process-oriented models across different ecosystems. Change in water-use efficiency defined from transpiration-based WUEt (GPP/TR) and inherent water-use efficiency (IWUEt , GPP×VPD/TR) in response to rising CO2 , climate change, and nitrogen deposition are also discussed. Our analyses will facilitate mechanistic understanding of the carbon-water interactions over terrestrial ecosystems under global change.

A mechanistic-bioclimatic modeling analysis of the potential impact of climate change on biomes of the Tibetan Plateau

The Tibetan Plateau (TP) is experiencing high rates of climatic change. We present a novel combined mechanistic-bioclimatic modeling approach to determine how changes in precipitation and temperature on the TP may impact net primary production (NPP) in four major biomes (forest, shrub, grass, desert) and if there exists a maximum rain use efficiency (RUE(MAX)) that represents Huxman et al.'s "boundary that constrain[s] site-level productivity and efficiency." We used a daily mechanistic ecosystem model to generate 40-yr outputs using observed climatic data for scenarios of decreased precipitation (25-100%); increased air temperature (1 degrees - 6 degrees C); simultaneous changes in both precipitation (+/- 50%, +/- 25%) and air temperature (+1 to +6 degrees C) and increased interannual variability (IAV) of precipitation (+1 sigma to +3 sigma, with fixed means, where sigma is SD). We fitted model output from these scenarios to Huxman et al.'s RUE(MAX) bioclimatic model, NPP = alpha + RUE x PPT (where alpha is the intercept, RUE is rain use efficiency, and PPT is annual precipitation). Based on these analyses, we conclude that there is strong support (when not explicit, then trend-wise) for Huxman et al.'s assertion that biomes converge to a common RUE(MAX) during the driest years at a site, thus representing the boundary for highest rain use efficiency; the interactive effects of simultaneously decreasing precipitation and increasing temperature on NPP for the TP is smaller than might be expected from additive, single-factor changes in these drivers; and that increasing IAV of precipitation may ultimately have a larger impact on biomes of the Tibetan Plateau than changing amounts of rainfall and air temperature alone.

Net primary productivity and rain-use efficiency as affected by warming, altered precipitation, and clipping in a mixed-grass prairie

Grassland productivity in response to climate change and land use is a global concern. In order to explore the effects of climate change and land use on net primary productivity (NPP), NPP partitioning [fBNPP , defined as the fraction of belowground NPP (BNPP) to NPP], and rain-use efficiency (RUE) of NPP, we conducted a field experiment with warming (+3 °C), altered precipitation (double and half), and annual clipping in a mixed-grass prairie in Oklahoma, USA since July, 2009. Across the years, warming significantly increased BNPP, fBNPP , and RUEBNPP by an average of 11.6%, 2.8%, and 6.6%, respectively. This indicates that BNPP was more sensitive to warming than aboveground NPP (ANPP) since warming did not change ANPP and RUEANPP much. Double precipitation stimulated ANPP, BNPP, and NPP but suppressed RUEANPP , RUEBNPP , and RUENPP while half precipitation decreased ANPP, BNPP, and NPP but increased RUEANPP , RUEBNPP , and RUENPP . Clipping interacted with altered precipitation in impacting RUEANPP , RUEBNPP , and RUENPP , suggesting land use could confound the effects of precipitation changes on ecosystem processes. Soil moisture was found to be a main factor in regulating variation in ANPP, BNPP, and NPP while soil temperature was the dominant factor influencing fBNPP . These findings suggest that BNPP is critical point to future research. Additionally, results from single-factor manipulative experiments should be treated with caution due to the non-additive interactive effects of warming with altered precipitation and land use (clipping).