Tree Physiology 35, 581–584 doi:10.1093/treephys/tpv059
Commentary
Where does the carbon go?—Plant carbon allocation under climate change Sanna Sevanto1,2 and L. Turin Dickman1 and Environmental Sciences Division, Los Alamos National Laboratory, Bikini Atoll Road MS J495, Los Alamos, NM 87545, USA; 2Corresponding author ([email protected])
Received April 6, 2015; accepted May 13, 2015; handling Editor Danielle Way
The ability of terrestrial vegetation to both take up and release carbon and water makes understanding climate change effects on plant function critical. These effects could alter the impacts and feedbacks of vegetation on climate and either slow down or accelerate climatic warming (Bonan 2008). As a result, studies on plant responses to increased atmospheric CO2 concentration and elevated temperatures have become abundant in the last 20 years (for reviews, see Way and Oren 2010, Franks et al. 2013). Predictions of future increases in the frequency and severity of drought in many areas of the world (IPCC 2013) have also led to an emphasis on plant drought responses and tolerance to climate change (McDowell et al. 2008, Adams et al. 2009, Breshears et al. 2009, Allen et al. 2010). Changes in the environment, however, will not occur separately, and the combined effects of two or more global change factors will likely be complex (e.g., Norby and Luo 2004). There is evidence, for example, that increased atmospheric CO2 and temperature may increase plant productivity, resource-use efficiency and growth rates (e.g., Drake et al. 1997, Wullschleger et al. 2002, Way and Oren 2010). But these changes could lead to changes in structure and hydraulics that increase drought vulnerability (Maherali and DeLucia 2000, Wullschleger et al. 2002, Way et al. 2013). Further, increased atmospheric CO2 concentration may increase plant water-use efficiency (e.g., Franks et al. 2013) while elevated temperature may reduce it (Way et al. 2013). To predict future vegetation changes and the influence of these interactions correctly, parsing plant responses as independent factors is essential. For understanding ecosystem-scale responses and verifying models, combined effects have to be quantified. Allocation of carbon to different plant organs is central to this discussion and provides a mechanism by which plants can adapt to changes in the environment (Chaves et al. 2002). The term ‘allocation’ has been used to describe everything from fine-scale
carbon dynamics within a plant to coarse-scale carbon dynamics within an ecosystem (e.g., Litton et al. 2007, Epron et al. 2012). Measuring and defining it in a meaningful way has therefore become one of the greatest challenges in plant science. In a review of carbon allocation in forests, Litton et al. (2007) defined three constituents of allocation for use in the context of forest ecosystems: biomass (the amount of material present); flux (carbon flow to a component per unit time); and partitioning (the fraction of gross primary productivity used by a component). When working on the individual scale, however, it is important to distinguish between the mass of all organic components (biomass) and the carbon quantity in a component (concentration), which is a subset of the former. When evaluating allocation under stress, it is also important to distinguish partitioning of recent photosynthates (none if stomata are closed) from partitioning or redistribution of carbon stores. The utility of each definition varies depending on the problem at hand and the measurement techniques available. For example, to model ecosystem carbon cycling at a seasonal time scale, measuring carbon allocation using biomass is sufficient to capture ecosystem response (e.g., De Kauwe et al. 2014). But if the goal is to model climate-induced vegetation mortality mechanistically (for review of theories, see e.g., McDowell 2011), partitioning and fluxes during and after environmental stress (e.g., drought) become important (Xu et al. 2013). If, for example, carbon is stored in leaves, as is typical during drought (Sala et al. 2010 and references therein), but cannot be transported to roots following drought, lack of resources available to re-establish soil– root connection may result in plant mortality. At the individual scale, measuring changes in biomass or concentration is easier than capturing fluxes, so the former are often used as indicators of carbon movement. Yet changes in fluxes could be the only indicator of a stress response and therefore critical to measure.
Published by Oxford University Press 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.
Downloaded from http://treephys.oxfordjournals.org/ by guest on November 14, 2015
1Earth
582 Sevanto and Dickman
Tree Physiology Volume 35, 2015
Oren 2010); drought severity (McDowell and Sevanto 2010, Sala et al. 2010); temperature elevation (Atkin and Tjoelker 2003); treatment interactions; and duration of the study (Way and Oren 2010)—on the allocation component in question. Relatively mild drought is generally thought to increase partitioning to roots to the detriment of aboveground organs, as shown by Blessing et al. (2015). But more severe drought could result in reduced flux and partitioning belowground (Figure 1) if the transport pathway is disrupted or stress defense mechanisms aboveground require a larger portion of the limited carbon supply. Though Blessing et al. (2015) found no significant differences in minimum transport times (maximum transport velocity) among treatments, they did observe longer mean transfer time of recent photoassimilates to the roots with elevated temperature. This could have serious implications for plant vigor or recovery from drought under future climates, as severe disruptions in carbon transport can lead to starvation and mortality of tissues downstream (McDowell and Sevanto 2010, Sala et al. 2010). Given the important function of roots as carbon storage organs, this decoupling of shoot source from root sink could impair a plant’s ability to buffer stress under climate change. Elevated temperatures generally increase aboveground partitioning and growth in temperature-limited (high latitude, high altitude) environments (Way and Oren 2012, see also Allen et al. 2010), while, as seen by Blessing et al. (2015), they have little or no effect on carbon concentrations in roots. But if heat increases to the limit of plant tolerance, higher partitioning of resources to these tissues for damage control and repair can be expected. Elevated temperature may also increase metabolic rates, increasing soil CO2 efflux (as observed by Blessing et al. 2015) and plant respiration (Atkin and Tjoelker 2003, Smith and Dukes 2013), potentially shifting plants from carbon sinks to carbon sources. Lack of consistency in treatments and their severity relative to plant tolerance (Figure 1) makes the synthesis of the effects of changing climate on plant function almost impossible, and calls for a metric to allow for comparison. In plant hydraulics, the concept of safety margins (drought severity relative to plant hydraulic failure limits; see e.g., Meinzer et al. 2009; Skelton et al. 2015) is an attempt at such relativization. Blessing et al. (2015) provided the first steps toward quantifying response thresholds for carbon allocation by defining an ‘excess carbon’ scale to allow for comparison of partitioning between individuals of differing tissue biomass. In both cases of hydraulics and carbon dynamics, however, we are still far from understanding how response thresholds and points of no return should be defined to allow predictions of vegetation changes under changing climate (Figure 1). In addition to determining tipping points and placing current conditions relative to tipping points, we need to understand cause–response relationships to model allocation changes mechanistically. The various components of carbon allocation mentioned here are outcomes of many interacting processes (Cannell and Dewar 1994, Brüggemann et al. 2011), and detecting whether a shift in biomass, concentration, flux or
Downloaded from http://treephys.oxfordjournals.org/ by guest on November 14, 2015
In this issue, Blessing et al. (2015) present a unique study to determine the effects of drought and elevated temperature on allocation. They used 13CO2 pulse labeling to track the recovery of 13C in different tissues and compounds of beech saplings during a 9-day chase period. This method offers an elegant way to measure all three allocation constituents by tracking transport velocity (flux), distribution (partitioning) and concentration (biomass) of labeled photoassimilates. The authors’ evaluation of several compounds in which the carbon label could be incorporated and use of this technique in conjunction with both temperature and water manipulation allows for assessment of allocation priorities under climate change-type stress. Evaluation of diverse carbon-containing compounds, in addition to the traditionally measured starch and simple sugars (sucrose, glucose and fructose), is critical for evaluating tree mortality mechanisms—in particular, the carbon starvation hypothesis. If these compounds serve as energy reserves or are essential for cellular metabolism or osmoregulation, they may play important roles in postponing starvation (Sala et al. 2010) or maintaining phloem turgor (see Sevanto et al. 2014). Analyzing these compounds could also shed light on how partitioning between primary growth or storage and stress defense mechanisms is altered by drought and elevated temperatures. Starch and simple sugars are known to be the primary substances responsible for growth and storage (Heldt and Piechulla 2004). Consistent with the literature, Blessing et al. (2015) found rapid increases in labeled carbon in leaf sugars and starch, followed by a rapid decline as recent photoassimilates were transported from the leaves to the roots in preparation for autumnal root expansion and long-term storage, as indicated by sustained residence of the carbon label in root starch. These results highlight the different functions of starch in different tissues, and the importance of root sampling in order to capture tree carbon storage. Amino acids and organic acids have been shown to increase in concentration under stress in many plants (e.g., López-Bucio et al. 2000), suggesting the use for stress defense such as osmoregulation (Fougere et al. 1991) or controlling cell-wall properties (see e.g., López-Bucio et al. 2000). Despite apparently low partitioning of newly assimilated carbon to acidic compounds in Blessing et al. (2015), this is one of the few studies addressing possible changes in partitioning to these compounds. Under changing environment, similar studies are needed before the consequences of climate change on vegetation can be thoroughly understood and modeled mechanistically. In combining these comprehensive methods for carbon allocation assessment with drought and temperature manipulation, Blessing et al. (2015) provided a template for future studies of plant physiological response to climate change. Based on current knowledge, the effects of drought and elevated temperature on allocation are varied (Figure 1) and depend on the impacts of many factors—including species and habitat (Way and Oren 2010); life cycle stage (both seasonality and age; see Way and
Plant carbon allocation under climate change 583
artitioning is the cause or response (active or passive) to some p other physiological change is a challenge. Although data interpretation for carbon-labeling studies is limited by label-detection methods and possible label dilution, which can make determination of tissue carbon budgets difficult, studies like that of Blessing et al. (2015) that measure fluxes combined with partitioning and biomass show a path toward this goal, one that is becoming increasingly important for improving predictions of climateinduced vegetation changes (Xu et al. 2013). Reallocation of stored carbon seems to play a crucial role in plant survival strategies (Dietze et al. 2014, Dickman et al. 2015, see also Klein and Hoch 2015) and studies that can quantify this redistribution and reuse are critical for the new generation of models to predict vegetation dynamics of the future.
References Adams HD, Guardiola M, Barron-Gafford GA, Villegas JC, Breshears DD, Zou CB, Torch PA, Huxman TE (2009) Temperature sensitivity of drought-induced tree mortality portends increased regional die-off under global change-type drought. Proc Natl Acad Sci USA 106:7063–7066.
Allen CD, Macalady AK, Chenchouni H et al. (2010) A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For Ecol Manag 259:660–684. Atkin OK, Tjoelker MG (2003) Thermal acclimation and the dynamic response of plant respiration to temperature. Trends Plant Sci 8: 343–351. Blessing CH, Werner RA, Siegwolf R, Buchmann N (2015) Allocation dynamics of recently fixed carbon in beech saplings in response to increased temperatures and drought. Tree Physiol 35:585–598. Bonan GB (2008) Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320:1444–1449. Breshears DD, Myers OB, Meyer CW, Barnes FJ, Zou CB, Allen CD, McDowell NG, Pockman WT (2009) Tree die-off in response to global change-type drought: mortality insights from a decade of plant water potential measurements. Front Ecol Environ 7:185–189. Brüggemann N, Gessler A, Kayler Z et al. (2011) Carbon allocation and carbon isotope fluxes in the plant-soil-atmosphere continuum: a review. Biogeosciences 8:3457–3489. Cannell M, Dewar R (1994) Carbon allocation in trees: a review of concepts for modelling. Adv Ecol Res 25:59–104. Chaves MM, Pereira JS, Maroco J, Rodrigues ML, Ricardo CPP, Osório ML, Carvalho I, Faria T, Pinheiro C (2002) How plants cope with water stress in the field. Photosynthesis and growth. Ann Bot 89:907–916. De Kauwe MG, Medlyn BE, Zaehle S et al. (2014) Where does the carbon go? A model-data intercomparison of vegetation carbon
Tree Physiology Online at http://www.treephys.oxfordjournals.org
Downloaded from http://treephys.oxfordjournals.org/ by guest on November 14, 2015
Figure 1. A schematic of potential outcomes for above- (top panel) and belowground (bottom panel) carbon (C) allocation (defined here as partitioning) and carbon transport velocity (flux, middle panel) under changing drought and heat conditions based on current knowledge. Uses of carbon above- and belowground are indicated on the left. Vertical dashed lines indicate possible tipping points along the stress continuum relative to optimal conditions for some plant groups or species, with tipping points for transport connected to responses in partitioning. These locations are uncertain, and the relative locations of heat vs drought conditions and optimal conditions vs tipping points are not fixed. The dashed lines joining the curves indicate possible variation in responses, and question marks indicate knowledge gaps. Optimal conditions are defined in relation to longevity and resilience to stress rather than maximum productivity. Comments in blue and red highlight current hypotheses for heat and drought responses assuming that the carbon source is not limited. For drought, higher stress indicates drier conditions and lower stress more moist conditions. For heat, higher stress can be caused by temperatures that are either too high or too low.
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McDowell N, Pockman WT, Allen CD et al. (2008) Mechanisms of plant survival and mortality during drought: why do some plants survive while others succumb to drought? New Phytol 178:719–739. McDowell NG (2011) Mechanisms linking drought, hydraulics, carbon metabolism, and vegetation mortality. Plant Physiol 155:1051–1059. McDowell NG, Sevanto S (2010) The mechanisms of carbon starvation: how, when, or does it even occur at all? New Phytol 186:264–266. Meinzer FC, Johnson DM, Lachenbruch B, McCulloh KA, Woodruff DR (2009) Xylem hydraulic safety margins in woody plants: coordination of stomatal control of xylem tension with hydraulic capacitance. Funct Ecol 23:922–930. Norby RJ, Luo Y (2004) Evaluating ecosystem responses to rising atmospheric CO2 and global warming in a multi-factor world. New Phytol 162:281–293. Plaut JA, Yepez EA, Hill J, Pangle R, Sperry JS, Pockman WT, McDowell NG (2012) Hydraulic limits preceding mortality in a piñon-juniper woodland under experimental drought. Plant Cell Environ 35:1601–1617. Sala A, Piper F, Hoch G (2010) Physiological mechanisms of droughtinduced tree mortality are far from being resolved. New Phytol 186:274–281. Sevanto S, McDowell NG, Dickman LT, Pangle R, Pockman WT (2014) How do trees die? A test of the hydraulic failure and carbon starvation hypotheses. Plant Cell Environ 37:153–161. Skelton RP, West AG, Dawson TE (2015) Predicting plant vulnerability to drought in biodiverse regions using functional traits. Proc Natl Acad Sci USA 112:5744–5749. Smith NG, Dukes JS (2013) Plant respiration and photosynthesis in global-scale models: incorporating acclimation to temperature and CO2. Glob Change Biol 19:45–63. Way DA, Oren R (2010) Differential responses to changes in growth temperature between trees from different functional groups and biomes: a review and synthesis of data. Tree Physiol 30:669–688. Way DA, Domec J-C, Jackson RB (2013) Elevated growth temperatures alter hydraulic characteristics in trembling aspen (Populus tremuloides) seedlings: implications for tree drought tolerance. Plant Cell Environ 36:103–115. Wullschleger SD, Tschaplinski TJ, Norby RJ (2002) Plant water relations at elevated CO2—implications for water-limited environments. Plant Cell Environ 25:319–331. Xu C, McDowell NG, Sevanto S, Fisher RA (2013) Our limited ability to predict vegetation dynamics under water stress. New Phytol 200: 298–300.
Downloaded from http://treephys.oxfordjournals.org/ by guest on November 14, 2015
allocation and turnover processes at two temperate forest free-air CO2 enrichment sites. New Phytol 203:883–899. Dickman LT, McDowell NG, Sevanto S, Pangle RE, Pockman WT (2015) Carbohydrate dynamics and mortality in a piñon-juniper woodland under three future precipitation scenarios. Plant Cell Environ 38:729–739. Dietze MC, Sala A, Carbone MS, Czimczik CI, Mantooth JA, Richardson AD, Vargas R (2014) Nonstructural carbon in woody plants. Annu Rev Plant Biol 65:667–687. Drake BG, Gonzalez-Meler MA, Long SP (1997) More efficient plants— a consequence of rising atmospheric CO2? Annu Rev Plant Physiol Plant Mol Biol 48:609–639. Epron D, Nouvellon Y, Ryan MG (2012) Introduction to the invited issue on carbon allocation of trees and forests. Tree Physiol 32:639–643. Fougere F, Le Rudulier D, Streeter JG (1991) Effects of salt stress on amino acid, organic acid, and carbohydrate composition of roots, bacteroids, and cytosol of Alfalfa (Medicago sativa L.). Plant Physiol 96:1228–1236. Franks PJ, Adams MA, Amthor JS et al. (2013) Sensitivity of plants to changing atmospheric CO2 concentration: from the geological past to the next century. New Phytol 197:1077–1094. Heldt HW, Piechulla B (2004) Polysaccharides are storage and transport forms of carbohydrates produced by photosynthesis. In: Plant biochemistry. Academic Press, Burlington, pp 243–273. IPCC (2013) Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker TF, Qin D, Plattner G-K et al. (eds.)]. Cambridge University Press, Cambridge, NY. Klein T, Hoch G (2015) Tree carbon allocation dynamics determined using a carbon mass balance approach. New Phytol 205:147–159. Knight CA, Ackerly DD (2002) An ecological and evolutionary analysis of photosynthetic thermotolerance using the temperature-dependent increase in fluorescence. Oecologia 130:505–514. Litton CM, Raich JW, Ryan MG (2007) Carbon allocation in forest ecosystems. Glob Change Biol 13:2089–2109. López-Bucio J, Nieto-Jacobo MF, Ramírez-Rodríguez V, Herrera-Estrella L (2000) Organic acid metabolism in plants: from adaptive physiology to transgenic varieties for cultivation in extreme soils. Plant Sci 160:1–13. Maherali H, DeLucia EH (2000) Interactive effects of elevated CO2 and temperature on water transport in ponderosa pine. Am J Bot 87:243–249.
Commentary
Where does the carbon go?—Plant carbon allocation under climate change Sanna Sevanto1,2 and L. Turin Dickman1 and Environmental Sciences Division, Los Alamos National Laboratory, Bikini Atoll Road MS J495, Los Alamos, NM 87545, USA; 2Corresponding author ([email protected])
Received April 6, 2015; accepted May 13, 2015; handling Editor Danielle Way
The ability of terrestrial vegetation to both take up and release carbon and water makes understanding climate change effects on plant function critical. These effects could alter the impacts and feedbacks of vegetation on climate and either slow down or accelerate climatic warming (Bonan 2008). As a result, studies on plant responses to increased atmospheric CO2 concentration and elevated temperatures have become abundant in the last 20 years (for reviews, see Way and Oren 2010, Franks et al. 2013). Predictions of future increases in the frequency and severity of drought in many areas of the world (IPCC 2013) have also led to an emphasis on plant drought responses and tolerance to climate change (McDowell et al. 2008, Adams et al. 2009, Breshears et al. 2009, Allen et al. 2010). Changes in the environment, however, will not occur separately, and the combined effects of two or more global change factors will likely be complex (e.g., Norby and Luo 2004). There is evidence, for example, that increased atmospheric CO2 and temperature may increase plant productivity, resource-use efficiency and growth rates (e.g., Drake et al. 1997, Wullschleger et al. 2002, Way and Oren 2010). But these changes could lead to changes in structure and hydraulics that increase drought vulnerability (Maherali and DeLucia 2000, Wullschleger et al. 2002, Way et al. 2013). Further, increased atmospheric CO2 concentration may increase plant water-use efficiency (e.g., Franks et al. 2013) while elevated temperature may reduce it (Way et al. 2013). To predict future vegetation changes and the influence of these interactions correctly, parsing plant responses as independent factors is essential. For understanding ecosystem-scale responses and verifying models, combined effects have to be quantified. Allocation of carbon to different plant organs is central to this discussion and provides a mechanism by which plants can adapt to changes in the environment (Chaves et al. 2002). The term ‘allocation’ has been used to describe everything from fine-scale
carbon dynamics within a plant to coarse-scale carbon dynamics within an ecosystem (e.g., Litton et al. 2007, Epron et al. 2012). Measuring and defining it in a meaningful way has therefore become one of the greatest challenges in plant science. In a review of carbon allocation in forests, Litton et al. (2007) defined three constituents of allocation for use in the context of forest ecosystems: biomass (the amount of material present); flux (carbon flow to a component per unit time); and partitioning (the fraction of gross primary productivity used by a component). When working on the individual scale, however, it is important to distinguish between the mass of all organic components (biomass) and the carbon quantity in a component (concentration), which is a subset of the former. When evaluating allocation under stress, it is also important to distinguish partitioning of recent photosynthates (none if stomata are closed) from partitioning or redistribution of carbon stores. The utility of each definition varies depending on the problem at hand and the measurement techniques available. For example, to model ecosystem carbon cycling at a seasonal time scale, measuring carbon allocation using biomass is sufficient to capture ecosystem response (e.g., De Kauwe et al. 2014). But if the goal is to model climate-induced vegetation mortality mechanistically (for review of theories, see e.g., McDowell 2011), partitioning and fluxes during and after environmental stress (e.g., drought) become important (Xu et al. 2013). If, for example, carbon is stored in leaves, as is typical during drought (Sala et al. 2010 and references therein), but cannot be transported to roots following drought, lack of resources available to re-establish soil– root connection may result in plant mortality. At the individual scale, measuring changes in biomass or concentration is easier than capturing fluxes, so the former are often used as indicators of carbon movement. Yet changes in fluxes could be the only indicator of a stress response and therefore critical to measure.
Published by Oxford University Press 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.
Downloaded from http://treephys.oxfordjournals.org/ by guest on November 14, 2015
1Earth
582 Sevanto and Dickman
Tree Physiology Volume 35, 2015
Oren 2010); drought severity (McDowell and Sevanto 2010, Sala et al. 2010); temperature elevation (Atkin and Tjoelker 2003); treatment interactions; and duration of the study (Way and Oren 2010)—on the allocation component in question. Relatively mild drought is generally thought to increase partitioning to roots to the detriment of aboveground organs, as shown by Blessing et al. (2015). But more severe drought could result in reduced flux and partitioning belowground (Figure 1) if the transport pathway is disrupted or stress defense mechanisms aboveground require a larger portion of the limited carbon supply. Though Blessing et al. (2015) found no significant differences in minimum transport times (maximum transport velocity) among treatments, they did observe longer mean transfer time of recent photoassimilates to the roots with elevated temperature. This could have serious implications for plant vigor or recovery from drought under future climates, as severe disruptions in carbon transport can lead to starvation and mortality of tissues downstream (McDowell and Sevanto 2010, Sala et al. 2010). Given the important function of roots as carbon storage organs, this decoupling of shoot source from root sink could impair a plant’s ability to buffer stress under climate change. Elevated temperatures generally increase aboveground partitioning and growth in temperature-limited (high latitude, high altitude) environments (Way and Oren 2012, see also Allen et al. 2010), while, as seen by Blessing et al. (2015), they have little or no effect on carbon concentrations in roots. But if heat increases to the limit of plant tolerance, higher partitioning of resources to these tissues for damage control and repair can be expected. Elevated temperature may also increase metabolic rates, increasing soil CO2 efflux (as observed by Blessing et al. 2015) and plant respiration (Atkin and Tjoelker 2003, Smith and Dukes 2013), potentially shifting plants from carbon sinks to carbon sources. Lack of consistency in treatments and their severity relative to plant tolerance (Figure 1) makes the synthesis of the effects of changing climate on plant function almost impossible, and calls for a metric to allow for comparison. In plant hydraulics, the concept of safety margins (drought severity relative to plant hydraulic failure limits; see e.g., Meinzer et al. 2009; Skelton et al. 2015) is an attempt at such relativization. Blessing et al. (2015) provided the first steps toward quantifying response thresholds for carbon allocation by defining an ‘excess carbon’ scale to allow for comparison of partitioning between individuals of differing tissue biomass. In both cases of hydraulics and carbon dynamics, however, we are still far from understanding how response thresholds and points of no return should be defined to allow predictions of vegetation changes under changing climate (Figure 1). In addition to determining tipping points and placing current conditions relative to tipping points, we need to understand cause–response relationships to model allocation changes mechanistically. The various components of carbon allocation mentioned here are outcomes of many interacting processes (Cannell and Dewar 1994, Brüggemann et al. 2011), and detecting whether a shift in biomass, concentration, flux or
Downloaded from http://treephys.oxfordjournals.org/ by guest on November 14, 2015
In this issue, Blessing et al. (2015) present a unique study to determine the effects of drought and elevated temperature on allocation. They used 13CO2 pulse labeling to track the recovery of 13C in different tissues and compounds of beech saplings during a 9-day chase period. This method offers an elegant way to measure all three allocation constituents by tracking transport velocity (flux), distribution (partitioning) and concentration (biomass) of labeled photoassimilates. The authors’ evaluation of several compounds in which the carbon label could be incorporated and use of this technique in conjunction with both temperature and water manipulation allows for assessment of allocation priorities under climate change-type stress. Evaluation of diverse carbon-containing compounds, in addition to the traditionally measured starch and simple sugars (sucrose, glucose and fructose), is critical for evaluating tree mortality mechanisms—in particular, the carbon starvation hypothesis. If these compounds serve as energy reserves or are essential for cellular metabolism or osmoregulation, they may play important roles in postponing starvation (Sala et al. 2010) or maintaining phloem turgor (see Sevanto et al. 2014). Analyzing these compounds could also shed light on how partitioning between primary growth or storage and stress defense mechanisms is altered by drought and elevated temperatures. Starch and simple sugars are known to be the primary substances responsible for growth and storage (Heldt and Piechulla 2004). Consistent with the literature, Blessing et al. (2015) found rapid increases in labeled carbon in leaf sugars and starch, followed by a rapid decline as recent photoassimilates were transported from the leaves to the roots in preparation for autumnal root expansion and long-term storage, as indicated by sustained residence of the carbon label in root starch. These results highlight the different functions of starch in different tissues, and the importance of root sampling in order to capture tree carbon storage. Amino acids and organic acids have been shown to increase in concentration under stress in many plants (e.g., López-Bucio et al. 2000), suggesting the use for stress defense such as osmoregulation (Fougere et al. 1991) or controlling cell-wall properties (see e.g., López-Bucio et al. 2000). Despite apparently low partitioning of newly assimilated carbon to acidic compounds in Blessing et al. (2015), this is one of the few studies addressing possible changes in partitioning to these compounds. Under changing environment, similar studies are needed before the consequences of climate change on vegetation can be thoroughly understood and modeled mechanistically. In combining these comprehensive methods for carbon allocation assessment with drought and temperature manipulation, Blessing et al. (2015) provided a template for future studies of plant physiological response to climate change. Based on current knowledge, the effects of drought and elevated temperature on allocation are varied (Figure 1) and depend on the impacts of many factors—including species and habitat (Way and Oren 2010); life cycle stage (both seasonality and age; see Way and
Plant carbon allocation under climate change 583
artitioning is the cause or response (active or passive) to some p other physiological change is a challenge. Although data interpretation for carbon-labeling studies is limited by label-detection methods and possible label dilution, which can make determination of tissue carbon budgets difficult, studies like that of Blessing et al. (2015) that measure fluxes combined with partitioning and biomass show a path toward this goal, one that is becoming increasingly important for improving predictions of climateinduced vegetation changes (Xu et al. 2013). Reallocation of stored carbon seems to play a crucial role in plant survival strategies (Dietze et al. 2014, Dickman et al. 2015, see also Klein and Hoch 2015) and studies that can quantify this redistribution and reuse are critical for the new generation of models to predict vegetation dynamics of the future.
References Adams HD, Guardiola M, Barron-Gafford GA, Villegas JC, Breshears DD, Zou CB, Torch PA, Huxman TE (2009) Temperature sensitivity of drought-induced tree mortality portends increased regional die-off under global change-type drought. Proc Natl Acad Sci USA 106:7063–7066.
Allen CD, Macalady AK, Chenchouni H et al. (2010) A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. For Ecol Manag 259:660–684. Atkin OK, Tjoelker MG (2003) Thermal acclimation and the dynamic response of plant respiration to temperature. Trends Plant Sci 8: 343–351. Blessing CH, Werner RA, Siegwolf R, Buchmann N (2015) Allocation dynamics of recently fixed carbon in beech saplings in response to increased temperatures and drought. Tree Physiol 35:585–598. Bonan GB (2008) Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320:1444–1449. Breshears DD, Myers OB, Meyer CW, Barnes FJ, Zou CB, Allen CD, McDowell NG, Pockman WT (2009) Tree die-off in response to global change-type drought: mortality insights from a decade of plant water potential measurements. Front Ecol Environ 7:185–189. Brüggemann N, Gessler A, Kayler Z et al. (2011) Carbon allocation and carbon isotope fluxes in the plant-soil-atmosphere continuum: a review. Biogeosciences 8:3457–3489. Cannell M, Dewar R (1994) Carbon allocation in trees: a review of concepts for modelling. Adv Ecol Res 25:59–104. Chaves MM, Pereira JS, Maroco J, Rodrigues ML, Ricardo CPP, Osório ML, Carvalho I, Faria T, Pinheiro C (2002) How plants cope with water stress in the field. Photosynthesis and growth. Ann Bot 89:907–916. De Kauwe MG, Medlyn BE, Zaehle S et al. (2014) Where does the carbon go? A model-data intercomparison of vegetation carbon
Tree Physiology Online at http://www.treephys.oxfordjournals.org
Downloaded from http://treephys.oxfordjournals.org/ by guest on November 14, 2015
Figure 1. A schematic of potential outcomes for above- (top panel) and belowground (bottom panel) carbon (C) allocation (defined here as partitioning) and carbon transport velocity (flux, middle panel) under changing drought and heat conditions based on current knowledge. Uses of carbon above- and belowground are indicated on the left. Vertical dashed lines indicate possible tipping points along the stress continuum relative to optimal conditions for some plant groups or species, with tipping points for transport connected to responses in partitioning. These locations are uncertain, and the relative locations of heat vs drought conditions and optimal conditions vs tipping points are not fixed. The dashed lines joining the curves indicate possible variation in responses, and question marks indicate knowledge gaps. Optimal conditions are defined in relation to longevity and resilience to stress rather than maximum productivity. Comments in blue and red highlight current hypotheses for heat and drought responses assuming that the carbon source is not limited. For drought, higher stress indicates drier conditions and lower stress more moist conditions. For heat, higher stress can be caused by temperatures that are either too high or too low.
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