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Tai X, Trugman AT, Anderegg WRL. Linking remotely sensed ecosystem resilience with forest mortality across the continental United States. GLOBAL CHANGE BIOLOGY 2023; 29:1096-1105. [PMID: 36468232 DOI: 10.1111/gcb.16529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 11/10/2022] [Accepted: 11/14/2022] [Indexed: 06/17/2023]
Abstract
Episodes of forest mortality have been observed worldwide associated with climate change, impacting species composition and ecosystem services such as water resources and carbon sequestration. Yet our ability to predict forest mortality remains limited, especially across large scales. Time series of satellite imagery has been used to document ecosystem resilience globally, but it is not clear how well remotely sensed resilience can inform the prediction of forest mortality across continental, multi-biome scales. Here, we leverage forest inventories across the continental United States to systematically assess the potential of ecosystem resilience derived using different data sets and methods to predict forest mortality. We found high resilience was associated with low mortality in eastern forests but was associated with high mortality in western regions. The unexpected resilience-mortality relation in western United States may be due to several factors including plant trait acclimation, insect population dynamics, or resource competition. Overall, our results not only supported the opportunity to use remotely sensed ecosystem resilience to predict forest mortality but also highlighted that ecological factors may have crucial influences because they can reverse the sign of the resilience-mortality relationships.
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Affiliation(s)
- Xiaonan Tai
- Department of Biological Sciences, New Jersey Institute of Technology, Newark, New Jersey, USA
| | - Anna T Trugman
- Department of Geography, University of California Santa Barbara, Santa Barbara, California, USA
| | - William R L Anderegg
- School of Biological Sciences, University of Utah, Salt Lake City, Utah, USA
- Wilkes Center for Climate Science and Policy, University of Utah, Salt Lake City, Utah, USA
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2
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Saunders A, Drew DM. Stomatal responses of Eucalyptus spp. under drought can be predicted with a gain-risk optimization model. TREE PHYSIOLOGY 2022; 42:815-830. [PMID: 34791492 DOI: 10.1093/treephys/tpab145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 11/05/2021] [Indexed: 06/13/2023]
Abstract
The frequency and severity of drought events are expected to increase due to climate change, with optimal environmental conditions for forestry likely to shift. Modeling plant responses to a changing climate is therefore vital. We tested the process-based gain-risk model to predict stomatal responses to drought of two Eucalyptus hybrids. The process-based gain-risk model has the advantage that all the parameters used within the model are based on measurable plant traits. The gain-risk model proposes that plants optimize photosynthetic gain while minimizing a hydraulic cost. Previous versions of the model used hydraulic risk as a cost function; however, they did not account for delayed or reduced hydraulic recovery rates from embolism post-drought. Hydraulic recovery has been seen in many species, however it is still unclear how this inclusion of a partial or delayed hydraulic recovery would affect the predictive power of the gain-risk model. Many hydraulic parameters required by the model are also difficult to measure and are not freely available. We therefore tested a simplified gain-risk model that includes a delayed or reduced hydraulic recovery component post-drought. The simplified gain-risk model performed well at predicting stomatal responses in both Eucalyptus grandis × camaldulensis (GC) and Eucalyptus urophylla × grandis (UG). In this study two distinct strategies were seen between GC and UG, with GC being more resistant to embolism formation, however it could not recover hydraulic conductance compared with UG. The inclusion of a delayed or reduced hydraulic recovery component slightly improved model predictions for GC, however not for UG, which can be related to UG being able to recover lost hydraulic conductance and therefore can maintain stomatal conductance regardless of hydraulic risk. Even though the gain-risk model shows promise in predicting plant responses, more information is needed regarding hydraulic recovery after drought.
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Affiliation(s)
- Alta Saunders
- Department of Forest and Wood Science, Stellenbosch University, Paul Sauer Building, Bosman St, Stellenbosch Central, Stellenbosch, 7599, South Africa
| | - David M Drew
- Department of Forest and Wood Science, Stellenbosch University, Paul Sauer Building, Bosman St, Stellenbosch Central, Stellenbosch, 7599, South Africa
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3
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Potkay A, Hölttä T, Trugman AT, Fan Y. Turgor-limited predictions of tree growth, height and metabolic scaling over tree lifespans. TREE PHYSIOLOGY 2022; 42:229-252. [PMID: 34296275 DOI: 10.1093/treephys/tpab094] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 07/18/2021] [Indexed: 06/13/2023]
Abstract
Increasing evidence suggests that tree growth is sink-limited by environmental and internal controls rather than by carbon availability. However, the mechanisms underlying sink-limitations are not fully understood and thus not represented in large-scale vegetation models. We develop a simple, analytically solved, mechanistic, turgor-driven growth model (TDGM) and a phloem transport model (PTM) to explore the mechanics of phloem transport and evaluate three hypotheses. First, phloem transport must be explicitly considered to accurately predict turgor distributions and thus growth. Second, turgor-limitations can explain growth-scaling with size (metabolic scaling). Third, turgor can explain realistic growth rates and increments. We show that mechanistic, sink-limited growth schemes based on plant turgor limitations are feasible for large-scale model implementations with minimal computational demands. Our PTM predicted nearly uniform sugar concentrations along the phloem transport path regardless of phloem conductance, stem water potential gradients and the strength of sink-demands contrary to our first hypothesis, suggesting that phloem transport is not limited generally by phloem transport capacity per se but rather by carbon demand for growth and respiration. These results enabled TDGM implementation without explicit coupling to the PTM, further simplifying computation. We test the TDGM by comparing predictions of whole-tree growth rate to well-established observations (site indices) and allometric theory. Our simple TDGM predicts realistic tree heights, growth rates and metabolic scaling over decadal to centurial timescales, suggesting that tree growth is generally sink and turgor limited. Like observed trees, our TDGM captures tree-size- and resource-based deviations from the classical ¾ power-law metabolic scaling for which turgor is responsible.
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Affiliation(s)
- Aaron Potkay
- Department of Earth and Planetary Sciences, Rutgers University, New Brunswick, NJ 08854, USA
| | - Teemu Hölttä
- Institute for Atmospheric and Earth System Research/Forest Sciences, University of Helsinki, Helsinki FI-00014, Finland
| | - Anna T Trugman
- Department of Geography, University of California at Santa Barbara, Santa Barbara, CA 93106, USA
| | - Ying Fan
- Department of Earth and Planetary Sciences, Rutgers University, New Brunswick, NJ 08854, USA
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Potkay A, Trugman AT, Wang Y, Venturas MD, Anderegg WRL, Mattos CRC, Fan Y. Coupled whole-tree optimality and xylem hydraulics explain dynamic biomass partitioning. THE NEW PHYTOLOGIST 2021; 230:2226-2245. [PMID: 33521942 DOI: 10.1111/nph.17242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 01/25/2021] [Indexed: 06/12/2023]
Abstract
Trees partition biomass in response to resource limitation and physiological activity. It is presumed that these strategies evolved to optimize some measure of fitness. If the optimization criterion can be specified, then allometry can be modeled from first principles without prescribed parameterization. We present the Tree Hydraulics and Optimal Resource Partitioning (THORP) model, which optimizes allometry by estimating allocation fractions to organs as proportional to their ratio of marginal gain to marginal cost, where gain is net canopy photosynthesis rate, and costs are senescence rates. Root total biomass and profile shape are predicted simultaneously by a unified optimization. Optimal partitioning is solved by a numerically efficient analytical solution. THORP's predictions agree with reported tree biomass partitioning in response to size, water limitations, elevated CO2 and pruning. Roots were sensitive to soil moisture profiles and grew down to the groundwater table when present. Groundwater buffered against water stress regardless of meteorology, stabilizing allometry and root profiles as deep as c. 30 m. Much of plant allometry can be explained by hydraulic considerations. However, nutrient limitations cannot be fully ignored. Rooting mass and profiles were synchronized with hydrological conditions and groundwater even at considerable depths, illustrating that the below ground shapes whole-tree allometry.
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Affiliation(s)
- Aaron Potkay
- Department of Earth and Planetary Sciences, Rutgers University, New Brunswick, NJ, 08854, USA
| | - Anna T Trugman
- Department of Geography, University of California, Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Yujie Wang
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Martin D Venturas
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - William R L Anderegg
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - Caio R C Mattos
- Department of Earth and Planetary Sciences, Rutgers University, New Brunswick, NJ, 08854, USA
| | - Ying Fan
- Department of Earth and Planetary Sciences, Rutgers University, New Brunswick, NJ, 08854, USA
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5
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Venturas MD, Todd HN, Trugman AT, Anderegg WRL. Understanding and predicting forest mortality in the western United States using long-term forest inventory data and modeled hydraulic damage. THE NEW PHYTOLOGIST 2021; 230:1896-1910. [PMID: 33112415 DOI: 10.1111/nph.17043] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 10/20/2020] [Indexed: 06/11/2023]
Abstract
Global warming is expected to exacerbate the duration and intensity of droughts in the western United States, which may lead to increased tree mortality. A prevailing proximal mechanism of drought-induced tree mortality is hydraulic damage, but predicting tree mortality from hydraulic theory and climate data still remains a major scientific challenge. We used forest inventory data and a plant hydraulic model (HM) to address three questions: can we capture regional patterns of drought-induced tree mortality with HM-predicted damage thresholds; do HM metrics improve predictions of mortality across broad spatial areas; and what are the dominant controls of forest mortality when considering stand characteristics, climate metrics, and simulated hydraulic stress? We found that the amount of variance explained by models predicting mortality was limited (R2 median = 0.10, R2 range: 0.00-0.52). HM outputs, including hydraulic damage and carbon assimilation diagnostics, moderately improve mortality prediction across the western US compared with models using stand and climate predictors alone. Among factors considered, metrics of stand density and tree size tended to be some of the most critical factors explaining mortality, probably highlighting the important roles of structural overshoot, stand development, and biotic agent host selection and outbreaks in mortality patterns.
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Affiliation(s)
- Martin D Venturas
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - Henry N Todd
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - Anna T Trugman
- Department of Geography, University of California Santa Barbara, Santa Barbara, CA, 93106, USA
| | - William R L Anderegg
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
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Wang Y, Anderegg WRL, Venturas MD, Trugman AT, Yu K, Frankenberg C. Optimization theory explains nighttime stomatal responses. THE NEW PHYTOLOGIST 2021; 230:1550-1561. [PMID: 33576001 DOI: 10.1111/nph.17267] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/22/2020] [Accepted: 02/02/2021] [Indexed: 06/12/2023]
Abstract
Nocturnal transpiration is widely observed across species and biomes, and may significantly impact global water, carbon, and energy budgets. However, it remains elusive why plants lose water at night and how to model it at large scales. We hypothesized that plants optimize nighttime leaf diffusive conductance (gwn ) to balance potential daytime photosynthetic benefits and nocturnal transpiration benefits. We quantified nighttime benefits from respiratory reductions due to evaporative leaf cooling. We described nighttime costs in terms of a reduced carbon gain during the day because of water use at night. We measured nighttime stomatal responses and tested our model with water birch (Betula occidentalis) saplings grown in a glasshouse. The gwn of water birch decreased with drier soil, higher atmospheric CO2 , wetter air, lower leaf temperature, and lower leaf respiration rate. Our model predicted all these responses correctly, except for the response of gwn to air humidity. Our results also suggested that the slow decrease in gwn after sunset could be associated with decreasing leaf respiration. The optimality-based nocturnal transpiration model smoothly integrates with daytime stomatal optimization approaches, and thus has the potential to quantitatively predict nocturnal transpiration across space and time.
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Affiliation(s)
- Yujie Wang
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, 91125, USA
| | - William R L Anderegg
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - Martin D Venturas
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - Anna T Trugman
- Department of Geography, University of California Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Kailiang Yu
- Le Laboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCECEA/CNRS/UVSQ Saclay, Gif-sur-Yvette, 91191, France
| | - Christian Frankenberg
- Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, 91125, USA
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, 91109, USA
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7
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Kim JH, Jung S, Lin KYA, Rinklebe J, Kwon EE. Comparative study on carbon dioxide-cofed catalytic pyrolysis of grass and woody biomass. BIORESOURCE TECHNOLOGY 2021; 323:124633. [PMID: 33412496 DOI: 10.1016/j.biortech.2020.124633] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 12/23/2020] [Accepted: 12/24/2020] [Indexed: 06/12/2023]
Abstract
This study investigated the mechanistic functions of CO2 on the pyrolysis of two different biomasses to elucidate the effect of CO2 on syngas formations during pyrolysis. To this end, CO2-assisted pyrolysis of cellulosic biomass (barnyard grass, Echinochloa) and lignin-rich woody biomass (retinispora, Chamaecyparis obtusa) were compared. The confirmed mechanistic effectiveness of CO2 on pyrolysis of biomass was gas phase reactions between CO2 and volatile matters from biomass pyrolysis. Lignin-rich biomass had more CO2 susceptibility, resulting in more enhanced CO formation via the gas phase reactions. To expedite the slow reaction rate of the gas phase reactions during biomass pyrolysis, earth-abundant catalysts (Co/SiO2 and Ni/SiO2) were employed for pyrolysis of two biomass substrates. With Co and Ni catalysts, the syngas formations were 2 and 3 times higher comparing to the pyrolysis of without catalyst. The cumulative formations of syngas from lignin-rich biomass was nearly doubled than that from cellulosic biomass.
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Affiliation(s)
- Jung-Hun Kim
- Department of Environment and Energy, Sejong University, Seoul 05006, Republic of Korea
| | - Sungyup Jung
- Department of Environment and Energy, Sejong University, Seoul 05006, Republic of Korea
| | - Kun-Yi Andrew Lin
- Department of Environmental Engineering & Innovation and Development Center of Sustainable Agriculture, National Chung Hsing University, 250 Kuo-Kuang Road, Taichung, Taiwan
| | - Jörg Rinklebe
- Department of Environment and Energy, Sejong University, Seoul 05006, Republic of Korea; Soil and Groundwater Management, Institute of Foundation Engineering, Water- and Waste-Management, School of Architecture and Civil Engineering, University of Wuppertal, Pauluskirchstraße 7, 42285 Wuppertal, Germany
| | - Eilhann E Kwon
- Department of Environment and Energy, Sejong University, Seoul 05006, Republic of Korea.
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8
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Wang Y, Sperry JS, Anderegg WRL, Venturas MD, Trugman AT. A theoretical and empirical assessment of stomatal optimization modeling. THE NEW PHYTOLOGIST 2020; 227:311-325. [PMID: 32248532 DOI: 10.1111/nph.16572] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Accepted: 03/09/2020] [Indexed: 05/13/2023]
Abstract
Optimal stomatal control models have shown great potential in predicting stomatal behavior and improving carbon cycle modeling. Basic stomatal optimality theory posits that stomatal regulation maximizes the carbon gain relative to a penalty of stomatal opening. All models take a similar approach to calculate instantaneous carbon gain from stomatal opening (the gain function). Where the models diverge is in how they calculate the corresponding penalty (the penalty function). In this review, we compare and evaluate 10 different optimization models in how they quantify the penalty and how well they predict stomatal responses to the environment. We evaluate models in two ways. First, we compare their penalty functions against seven criteria that ensure a unique and qualitatively realistic solution. Second, we quantitatively test model against multiple leaf gas-exchange datasets. The optimization models with better predictive skills have penalty functions that meet our seven criteria and use fitting parameters that are both few in number and physiology based. The most skilled models are those with a penalty function based on stress-induced hydraulic failure. We conclude by proposing a new model that has a hydraulics-based penalty function that meets all seven criteria and demonstrates a highly predictive skill against our test datasets.
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Affiliation(s)
- Yujie Wang
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - John S Sperry
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - William R L Anderegg
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - Martin D Venturas
- School of Biological Sciences, University of Utah, Salt Lake City, UT, 84112, USA
| | - Anna T Trugman
- Department of Geography, University of California Santa Barbara, Santa Barbara, CA, 93106, USA
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9
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Sabot MEB, De Kauwe MG, Pitman AJ, Medlyn BE, Verhoef A, Ukkola AM, Abramowitz G. Plant profit maximization improves predictions of European forest responses to drought. THE NEW PHYTOLOGIST 2020; 226:1638-1655. [PMID: 31840249 DOI: 10.1111/nph.16376] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 12/03/2019] [Indexed: 05/16/2023]
Abstract
Knowledge of how water stress impacts the carbon and water cycles is a key uncertainty in terrestrial biosphere models. We tested a new profit maximization model, where photosynthetic uptake of CO2 is optimally traded against plant hydraulic function, as an alternative to the empirical functions commonly used in models to regulate gas exchange during periods of water stress. We conducted a multi-site evaluation of this model at the ecosystem scale, before and during major droughts in Europe. Additionally, we asked whether the maximum hydraulic conductance in the soil-plant continuum kmax (a key model parameter which is not commonly measured) could be predicted from long-term site climate. Compared with a control model with an empirical soil moisture function, the profit maximization model improved the simulation of evapotranspiration during the growing season, reducing the normalized mean square error by c. 63%, across mesic and xeric sites. We also showed that kmax could be estimated from long-term climate, with improvements in the simulation of evapotranspiration at eight out of the 10 forest sites during drought. Although the generalization of this approach is contingent upon determining kmax , it presents a mechanistic trait-based alternative to regulate canopy gas exchange in global models.
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Affiliation(s)
- Manon E B Sabot
- ARC Centre of Excellence for Climate Extremes and Climate Change Research Centre, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Martin G De Kauwe
- ARC Centre of Excellence for Climate Extremes and Climate Change Research Centre, University of New South Wales, Sydney, NSW, 2052, Australia
- Evolution and Ecology Research Centre, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Andy J Pitman
- ARC Centre of Excellence for Climate Extremes and Climate Change Research Centre, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Belinda E Medlyn
- Hawkesbury Institute for the Environment, Western Sydney University, Locked Bag 1797, Penrith, NSW, 2751, Australia
| | - Anne Verhoef
- Department of Geography and Environmental Science, The University of Reading, PO Box 227, Reading, RG6 6AB, UK
| | - Anna M Ukkola
- ARC Centre of Excellence for Climate Extremes and Research School of Earth Sciences, Australian National University, Canberra, ACT 0200, Australia
| | - Gab Abramowitz
- ARC Centre of Excellence for Climate Extremes and Climate Change Research Centre, University of New South Wales, Sydney, NSW, 2052, Australia
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Grossiord C, Buckley TN, Cernusak LA, Novick KA, Poulter B, Siegwolf RTW, Sperry JS, McDowell NG. Plant responses to rising vapor pressure deficit. THE NEW PHYTOLOGIST 2020; 226:1550-1566. [PMID: 32064613 DOI: 10.1111/nph.16485] [Citation(s) in RCA: 337] [Impact Index Per Article: 84.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Accepted: 02/04/2020] [Indexed: 05/24/2023]
Abstract
Recent decades have been characterized by increasing temperatures worldwide, resulting in an exponential climb in vapor pressure deficit (VPD). VPD has been identified as an increasingly important driver of plant functioning in terrestrial biomes and has been established as a major contributor in recent drought-induced plant mortality independent of other drivers associated with climate change. Despite this, few studies have isolated the physiological response of plant functioning to high VPD, thus limiting our understanding and ability to predict future impacts on terrestrial ecosystems. An abundance of evidence suggests that stomatal conductance declines under high VPD and transpiration increases in most species up until a given VPD threshold, leading to a cascade of subsequent impacts including reduced photosynthesis and growth, and higher risks of carbon starvation and hydraulic failure. Incorporation of photosynthetic and hydraulic traits in 'next-generation' land-surface models has the greatest potential for improved prediction of VPD responses at the plant- and global-scale, and will yield more mechanistic simulations of plant responses to a changing climate. By providing a fully integrated framework and evaluation of the impacts of high VPD on plant function, improvements in forecasting and long-term projections of climate impacts can be made.
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Affiliation(s)
- Charlotte Grossiord
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland
- École Polytechnique Fédérale de Lausanne EPFL, School of Architecture, Civil and Environmental Engineering ENAC, 1015, Lausanne, Switzerland
| | - Thomas N Buckley
- Department of Plant Sciences, University of California, Davis, Davis, CA, 95616, USA
| | - Lucas A Cernusak
- College of Science and Engineering, James Cook University, Cairns, Qld, 4814, Australia
| | - Kimberly A Novick
- School of Public and Environmental Affairs, Indiana University Bloomington, Bloomington, IN, 47405, USA
| | - Benjamin Poulter
- Biospheric Sciences Lab, NASA Goddard Space Flight Center, Greenbelt, MD, 20771, USA
| | - Rolf T W Siegwolf
- Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Zürcherstrasse 111, 8903, Birmensdorf, Switzerland
| | - John S Sperry
- Department of Biology, University of Utah, Salt Lake City, UT, 84112, USA
| | - Nate G McDowell
- Earth Systems Science Division, Pacific Northwest National Laboratory, Richland, WA, 99354, USA
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11
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Eller CB, Rowland L, Mencuccini M, Rosas T, Williams K, Harper A, Medlyn BE, Wagner Y, Klein T, Teodoro GS, Oliveira RS, Matos IS, Rosado BHP, Fuchs K, Wohlfahrt G, Montagnani L, Meir P, Sitch S, Cox PM. Stomatal optimization based on xylem hydraulics (SOX) improves land surface model simulation of vegetation responses to climate. THE NEW PHYTOLOGIST 2020; 226:1622-1637. [PMID: 31916258 PMCID: PMC7318565 DOI: 10.1111/nph.16419] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Accepted: 01/03/2020] [Indexed: 05/23/2023]
Abstract
Land surface models (LSMs) typically use empirical functions to represent vegetation responses to soil drought. These functions largely neglect recent advances in plant ecophysiology that link xylem hydraulic functioning with stomatal responses to climate. We developed an analytical stomatal optimization model based on xylem hydraulics (SOX) to predict plant responses to drought. Coupling SOX to the Joint UK Land Environment Simulator (JULES) LSM, we conducted a global evaluation of SOX against leaf- and ecosystem-level observations. SOX simulates leaf stomatal conductance responses to climate for woody plants more accurately and parsimoniously than the existing JULES stomatal conductance model. An ecosystem-level evaluation at 70 eddy flux sites shows that SOX decreases the sensitivity of gross primary productivity (GPP) to soil moisture, which improves the model agreement with observations and increases the predicted annual GPP by 30% in relation to JULES. SOX decreases JULES root-mean-square error in GPP by up to 45% in evergreen tropical forests, and can simulate realistic patterns of canopy water potential and soil water dynamics at the studied sites. SOX provides a parsimonious way to incorporate recent advances in plant hydraulics and optimality theory into LSMs, and an alternative to empirical stress factors.
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Affiliation(s)
- Cleiton B. Eller
- College of Life and Environmental SciencesUniversity of ExeterExeterEX4 4QFUK
- Department of Plant BiologyUniversity of CampinasCampinas13083‐862Brazil
| | - Lucy Rowland
- College of Life and Environmental SciencesUniversity of ExeterExeterEX4 4QFUK
| | - Maurizio Mencuccini
- CREAFBellaterra08193BarcelonaSpain
- ICREAPg. Lluís Companys 2308010BarcelonaSpain
| | - Teresa Rosas
- CREAFBellaterra08193BarcelonaSpain
- ICREAPg. Lluís Companys 2308010BarcelonaSpain
| | | | - Anna Harper
- College of Engineering, Mathematics and Physical SciencesUniversity of ExeterExeterEX4 4QFUK
| | - Belinda E. Medlyn
- Hawkesbury Institute for the EnvironmentWestern Sydney UniversityLocked Bag 1797PenrithNSW2751Australia
| | - Yael Wagner
- Department of Plant & Environmental SciencesWeizmann Institute of Science76100RehovotIsrael
| | - Tamir Klein
- Department of Plant & Environmental SciencesWeizmann Institute of Science76100RehovotIsrael
| | | | - Rafael S. Oliveira
- Department of Plant BiologyUniversity of CampinasCampinas13083‐862Brazil
| | - Ilaine S. Matos
- Department of Ecology – IBRAGRio de Janeiro State University (UERJ)Rio de Janeiro20550‐013Brazil
| | - Bruno H. P. Rosado
- Department of Ecology – IBRAGRio de Janeiro State University (UERJ)Rio de Janeiro20550‐013Brazil
| | - Kathrin Fuchs
- Department of Environmental Systems ScienceETH ZurichUniversitätstrasse 28092ZurichSwitzerland
| | - Georg Wohlfahrt
- Department of EcologyUniversity of InnsbruckInnsbruck6020Austria
| | - Leonardo Montagnani
- Forest ServicesAutonomous Province of BolzanoVia Brennero 639100BolzanoItaly
| | - Patrick Meir
- Research School of BiologyThe Australian National UniversityActonACT2601Australia
- School of GeosciencesUniversity of EdinburghEdinburghEH9 3FFUK
| | - Stephen Sitch
- College of Life and Environmental SciencesUniversity of ExeterExeterEX4 4QFUK
| | - Peter M. Cox
- College of Engineering, Mathematics and Physical SciencesUniversity of ExeterExeterEX4 4QFUK
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12
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Sun P, Wu Y, Xiao J, Hui J, Hu J, Zhao F, Qiu L, Liu S. Remote sensing and modeling fusion for investigating the ecosystem water-carbon coupling processes. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 697:134064. [PMID: 31476506 DOI: 10.1016/j.scitotenv.2019.134064] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2019] [Revised: 07/20/2019] [Accepted: 08/21/2019] [Indexed: 06/10/2023]
Abstract
The water and carbon cycles are tightly linked and play a key role in the material and energy flows between terrestrial ecosystems and the atmosphere, but the interactions of water and carbon cycles are not quite clear. The global climate change and intensive human activities could also complicate the water and carbon coupling processes. Better understanding the coupled water-carbon cycles and their spatiotemporal evolution can inform management and decision-making efforts regarding carbon uptake, food production, water resources, and climate change. The integration of remote sensing and numeric modeling is an attractive approach to address the challenge. Remote sensing can provide extensive data for a number of variables at regional scale and support models, whereas process-based modeling can facilitate investigating the processes that remote sensing cannot well handle (e.g., below-ground and lateral material movement) and backcast/forecast the impacts of environmental change. Over the past twenty years, an increasing number of studies using a variety of remote sensing products together with numeric models have examined the water-carbon interactions. This article reviewed the methodologies for integrating remote sensing data into these models and the modeling of water-carbon coupling processes. We first summarized the major remote sensing datasets and models used for studying the coupled water-carbon cycles. We then provided an overview of the methods for integrating remote sensing data into water-carbon models, and discussed their strengths and challenges. We also prospected the development of potential new remote sensing datasets, modeling methods, and their potential applications in the field of eco-hydrology.
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Affiliation(s)
- Pengcheng Sun
- Department of Earth & Environmental Science, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, China; Key Laboratory of Degraded and Unused Land Consolidation Engineering, The Ministry of Natural Resources of China, Xi'an, Shaanxi Province 710075, China
| | - Yiping Wu
- Department of Earth & Environmental Science, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, China.
| | - Jingfeng Xiao
- Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
| | - Jinyu Hui
- Department of Earth & Environmental Science, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, China
| | - Jingyi Hu
- Department of Earth & Environmental Science, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, China
| | - Fubo Zhao
- Department of Earth & Environmental Science, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, China
| | - Linjing Qiu
- Department of Earth & Environmental Science, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, China
| | - Shuguang Liu
- National Engineering Laboratory for Applied Technology of Forestry & Ecology in South China, Central South University of Forestry and Technology, Changsha, Hunan Province 410004, China
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13
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Sperry JS, Venturas MD, Todd HN, Trugman AT, Anderegg WRL, Wang Y, Tai X. The impact of rising CO 2 and acclimation on the response of US forests to global warming. Proc Natl Acad Sci U S A 2019; 116:25734-25744. [PMID: 31767760 PMCID: PMC6926066 DOI: 10.1073/pnas.1913072116] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The response of forests to climate change depends in part on whether the photosynthetic benefit from increased atmospheric CO2 (∆Ca = future minus historic CO2) compensates for increased physiological stresses from higher temperature (∆T). We predicted the outcome of these competing responses by using optimization theory and a mechanistic model of tree water transport and photosynthesis. We simulated current and future productivity, stress, and mortality in mature monospecific stands with soil, species, and climate sampled from 20 continental US locations. We modeled stands with and without acclimation to ∆Ca and ∆T, where acclimated forests adjusted leaf area, photosynthetic capacity, and stand density to maximize productivity while avoiding stress. Without acclimation, the ∆Ca-driven boost in net primary productivity (NPP) was compromised by ∆T-driven stress and mortality associated with vascular failure. With acclimation, the ∆Ca-driven boost in NPP and stand biomass (C storage) was accentuated for cooler futures but negated for warmer futures by a ∆T-driven reduction in NPP and biomass. Thus, hotter futures reduced forest biomass through either mortality or acclimation. Forest outcomes depended on whether projected climatic ∆Ca/∆T ratios were above or below physiological thresholds that neutralized the negative impacts of warming. Critically, if forests do not acclimate, the ∆Ca/∆T must be above ca 89 ppm⋅°C-1 to avoid chronic stress, a threshold met by 55% of climate projections. If forests do acclimate, the ∆Ca/∆T must rise above ca 67 ppm⋅°C-1 for NPP and biomass to increase, a lower threshold met by 71% of projections.
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Affiliation(s)
- John S Sperry
- School of Biological Sciences, University of Utah, Salt Lake City, UT 84112
| | - Martin D Venturas
- School of Biological Sciences, University of Utah, Salt Lake City, UT 84112;
| | - Henry N Todd
- School of Biological Sciences, University of Utah, Salt Lake City, UT 84112
| | - Anna T Trugman
- School of Biological Sciences, University of Utah, Salt Lake City, UT 84112
- Department of Geography, University of California, Santa Barbara, CA 93106
| | | | - Yujie Wang
- School of Biological Sciences, University of Utah, Salt Lake City, UT 84112
| | - Xiaonan Tai
- Department of Geology and Geophysics, University of Utah, Salt Lake City, UT 84112
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14
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Trugman AT, Anderegg LDL, Sperry JS, Wang Y, Venturas M, Anderegg WRL. Leveraging plant hydraulics to yield predictive and dynamic plant leaf allocation in vegetation models with climate change. GLOBAL CHANGE BIOLOGY 2019; 25:4008-4021. [PMID: 31465580 DOI: 10.1111/gcb.14814] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Accepted: 08/09/2019] [Indexed: 06/10/2023]
Abstract
Plant functional traits provide a link in process-based vegetation models between plant-level physiology and ecosystem-level responses. Recent advances in physiological understanding and computational efficiency have allowed for the incorporation of plant hydraulic processes in large-scale vegetation models. However, a more mechanistic representation of water limitation that determines ecosystem responses to plant water stress necessitates a re-evaluation of trait-based constraints for plant carbon allocation, particularly allocation to leaf area. In this review, we examine model representations of plant allocation to leaves, which is often empirically set by plant functional type-specific allometric relationships. We analyze the evolution of the representation of leaf allocation in models of different scales and complexities. We show the impacts of leaf allocation strategy on plant carbon uptake in the context of recent advancements in modeling hydraulic processes. Finally, we posit that deriving allometry from first principles using mechanistic hydraulic processes is possible and should become standard practice, rather than using prescribed allometries. The representation of allocation as an emergent property of scarce resource constraints is likely to be critical to representing how global change processes impact future ecosystem dynamics and carbon fluxes and may reduce the number of poorly constrained parameters in vegetation models.
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Affiliation(s)
- Anna T Trugman
- Department of Geography, University of California Santa Barbara, Santa Barbara, CA, USA
- School of Biological Sciences, University of Utah, Salt Lake City, UT, USA
| | - Leander D L Anderegg
- Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, USA
- Department of Integrative Biology, University of California Berkeley, Berkeley, CA, USA
| | - John S Sperry
- School of Biological Sciences, University of Utah, Salt Lake City, UT, USA
| | - Yujie Wang
- School of Biological Sciences, University of Utah, Salt Lake City, UT, USA
| | - Martin Venturas
- School of Biological Sciences, University of Utah, Salt Lake City, UT, USA
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