# Reconciling carbon-cycle processes from ecosystem to global scales

Ashley Ballantyne, Zhihua Liu, William Rl Anderegg, Zicheng Yu, Paul Stoy, Ben Poulter, Joseph Vanderwall, Jennifer Watts, Kathy Kelsey, Jason Neff

► To cite this version:

Ashley Ballantyne, Zhihua Liu, William Rl Anderegg, Zicheng Yu, Paul Stoy, et al. Reconciling carbon-cycle processes from ecosystem to global scales. Frontiers in Ecology and the Environment, 2021, 19 (1), pp.57-65. 10.1002/fee.2296. hal-03134026

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# Reconciling carbon-cycle processes from ecosystem to global scales

Ashley P Ballantyne<fnref n="1" />,²*†, Zhihua Liu³*†, William RL Anderegg⁴, Zicheng Yu⁵,⁶, Paul Stoy⁷, Ben Poulter⁸, Joseph Vanderwall<fnref n="1" />, Jennifer Watts⁹, Kathy Kelsey¹⁰, and Jason Neff¹¹

Understanding carbon (C) dynamics from ecosystem to global scales remains a challenge. Although expansion of global carbon dioxide (CO₂) observatories makes it possible to estimate C-cycle processes from ecosystem to global scales, these estimates do not necessarily agree. At the continental US scale, only 5% of C fixed through photosynthesis remains as net ecosystem exchange (NEE), but ecosystem measurements indicate that only 2% of fixed C remains in grasslands, whereas as much as 30% remains in needleleaf forests. The wet and warm Southeast has the highest gross primary productivity and the relatively wet and cool Midwest has the highest NEE, indicating important spatial mismatches. Newly available satellite and atmospheric data can be combined in innovative ways to identify potential C loss pathways to reconcile these spatial mismatches. Independent datasets compiled from terrestrial and aquatic environments can now be combined to advance C-cycle science across the land-water interface.

*Front Ecol Environ* 2021; 19(1): 57–65, doi:10.1002/fee.2296

Carbon (C) is the building block of life. Global photosynthesis generates approximately 100 terawatts (TW) of energy each year by converting solar radiation into stored chemical energy (Barber 2009). Photosynthesis also represents

**In a nutshell:**

* From a societal perspective, there has never been a more urgent time to advance our understanding of the carbon (C) cycle, given that the atmospheric growth rate of carbon dioxide (CO₂) has reached record levels

* From a scientific perspective, however, there has never been a better time to be a global ecologist, because global C observing systems are becoming more expansive and intensive, allowing scientists to make innovative insights at ecosystem, macrosystem, and global scales

* A fundamental goal of macrosystems research is to reconcile important processes from ecosystem to continental scales, which is now achievable using long-term and consistent measurements of C-cycle dynamics

* Comparisons across scales also reveal many CO₂ loss pathways other than respiration that may not be included in ecosystem-process models

the largest global annual C flux, of ~125 petagrams (Pg; where 1 Pg equals 10¹⁵ grams [g] and 1 Pg C is roughly equivalent to 0.47 parts per million [ppm] of CO₂), with the second greatest flux consisting of the subsequent release of CO₂ via respiration (~122 Pg C/year). Both of these fluxes are an order of magnitude greater than fossil-fuel emissions (Ballantyne et al. 2015). The atmospheric CO₂ that is fixed during photosynthesis is subsequently stored and transferred as chemical energy, which in turn fuels the metabolic reactions of most autotrophs and heterotrophs. Although C is the most common element in the terrestrial biosphere, representing approximately 50 parts per hundred (%) of all organic matter, CO₂ represents only a very small fraction of the atmosphere and is therefore measured in ppm (~415 ppm in 2020). Given the abundance of C in the terrestrial biosphere and the massive fluxes of C occurring between the biosphere and the atmosphere, it is no surprise that scientists have developed a myriad of innovative ways for measuring and simulating C-cycle processes across a range of scales in time and space. For example, chloroplast CO₂ fluxes are estimated over millimeters per second, whereas biome CO₂ fluxes may be estimated over thousands of kilometers per year. There have been many advances in C-cycle science over the past 60 years at leaf, plant, ecosystem, and global scales, but both challenges to and opportunities for scientific advancement remain. Progress is necessary, however, especially at the macrosystem scale, where human management and ecological processes are often at odds and create interesting interactions of C dynamics.

One of the greatest impediments to accurate predictions of future climate is the uncertain response of the terrestrial C cycle to impending changes in temperature, precipitation, and atmospheric CO₂ concentrations (Friedlingstein et al. 2013). Even though land-surface models have become increasingly realistic in their mechanistic representation of C-cycle processes by including nutrient limitation (Thornton et al. 2007),

<footnote n="1">¹Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, MT * (ashley ballantyne@umontana.edu); ²Laboratoire des Sciences du Climat et de l'Environnement, Gif-Sur-Yvette, France; ³CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China; ⁴School of Biological Sciences, University of Utah, Salt Lake City, UT; ⁵Department of Earth and Environmental Sciences, Lehigh University, Bethlehem, PA; ⁶Institute for Peat and Mire Research, School of Geographical Sciences, Northeast Normal University, Changchun, China; ⁷Department of Biological Systems Engineering, University of Wisconsin-Madison, Madison, WI; ⁸National Aeronautics and Space Administration, Goddard Space Flight Center, Biospheric Sciences Laboratory, Greenbelt, MD; (continued on last page)</footnote>
surface hydrology (Wang et al. 2013), and microbial processes (Wieder et al. 2013), this increased complexity does not neces- sarily reduce the range of uncertainty in projections of C uptake among models (eg see Friedlingstein et al. [2006] com- pared to Friedlingstein et al. [2013]). In parallel, there is now a globally nested CO₂ observation network that allows for unprecedented measurements of changes in CO₂ concentra- tions and fluxes (Schimel et al. 2015). These continuous meas- urements allow estimates to be made of net CO₂ exchange from ecosystem to global scales, but not necessarily the under- lying processes that regulate this net exchange (Ciais et al. 2019). In contrast, land-surface models simulate the underly- ing processes that result in net CO₂ exchange, but these are difficult to benchmark due to a lack of process-level data at the appropriate scale (Luo et al. 2012; Anav et al. 2013).

Although enhanced net C accumulation in the terrestrial biosphere can be inferred from the global C budget, identify- ing the ecosystems in which C is accumulating is still difficult. For example, at the global scale, it can be concluded with con- fidence that ~25% of CO₂ emitted to the atmosphere from fossil-fuel and land-use emissions has been taken up by the terrestrial biosphere (Ballantyne et al. 2015; Le Quéré et al. 2016), but biomass datasets are too sparse in extent or too short in duration to document which ecosystems continue to accumulate C. More detailed ocean and land measurements now make it possible to identify specific processes affecting the net CO₂ atmospheric exchange between the marine biosphere (Landschützer et al. 2015) and terrestrial biosphere (Anderegg et al. 2015), in some instances at regional scales (Ciais et al. 2019). However, partitioning net C fluxes into their compo- nent gross fluxes of photosynthesis and respiration remains a challenge (Wehr et al. 2016).

Another vexing problem in global C-cycle research is that top-down global estimates of net terrestrial C uptake do not agree with bottom-up ecosystem estimates when integrated globally. For instance, top-down estimates of global net terres- trial C uptake in 2010 are an order of magnitude less (2.2 ± 2.1 Pg C/year; Ballantyne et al. 2015) than eddy covariance esti- mates up-scaled globally (22 ± 5 Pg C/year; Jung et al. 2011). Although some of the discrepancy between top-down and bot- tom-up estimates of net terrestrial C uptake may be due to issues associated with eddy covariance methods (Keenan et al. 2019) – particularly regarding measurement of nighttime respi- ration, which often violates eddy covariance requirements of turbulent flux and biases in the sampling network – a portion can also be explained by non-respiratory CO₂ loss pathways (~7 Pg C/year; Randerson et al. 2002). This suggests that there are many C transformation and transport pathways that ultimately lead to a loss of CO₂ from ecosystems back to the atmosphere. Approximately 90% of inland lakes and streams are net sources of CO₂ to the atmosphere (Cole et al. 1994), and at a global scale approximately 2 Pg C/year is returned to the atmosphere via CO₂ loss from rivers and lakes (Raymond et al. 2013). Although this estimate of CO₂ loss from aquatic ecosystems is comparable to the magnitude of net C uptake by terrestrial ecosystems, it is

less than 2% of total inferred CO₂ respiration from the terres- trial biosphere back to the atmosphere (Ballantyne et al. 2017). As such, characterizing the C balance at the macrosystem scale for direct comparison with different biomes in Earth system models remains difficult (Peylin et al. 2013).

Although from a societal perspective there has never been a more urgent time to study the C cycle and its sensitivity to climate change (Obama 2017), from a scientific perspective there has never been a more exciting time to study C-cycle processes. The global C observation network supports innova- tive analyses and syntheses across scales from ecosystems to the entire planet. Currently, there are over 800 eddy covari- ance sites operating around the world that contribute meas- urements of net CO₂ exchange, as well as estimates of primary productivity and total respiration across a wide array of eco- systems (Chu et al. 2017). However, in the US, fewer than half of the ecosystem functional types are represented in the com- bined core sites of the AmeriFlux Network and the National Ecological Observatory Network (NEON) (Villarreal et al. 2018), and many ecosystems remain underrepresented, espe- cially in climate-sensitive Arctic tundra and tropical rainfor- ests. Other C flux databases have continued to expand, such as a recently updated database on soil respiration that has been used to identify the climate sensitivity of soil respiration over time (Bond-Lamberty and Thomson 2010), which is critical for evaluating how C supply, soil temperature, and moisture interact to regulate soil respiration (Hursh et al. 2017).

Global measurement networks and satellite observations of atmospheric CO₂ now allow for the characterization of biome- scale C fluxes at greater temporal and spatial resolutions (Figure 1). The global greenhouse observation network has grown sporadically, with approximately 90 in situ sites now in operation worldwide (GLOBALVIEW-CO₂ 1999). Several of these sites also provide atmospheric profile measurements that are essential for estimating latitudinal differences in CO₂ exchange (Stephens et al. 2007), in addition to seasonal differ- ences in regional uptake (Gatti et al. 2014). Regional atmos- pheric CO₂ monitoring networks often engage in intensive atmospheric campaigns to better define regional C fluxes in urban continental settings (Corbin et al. 2010) or to determine recent changes in the C balance of ecosystems in climate sensi- tive regions, such as the Arctic (Commane et al. 2017). When combined with three-dimensional atmospheric transport modeling and estimates of surface fossil-fuel emissions, these so-called “atmospheric inversions” deliver critical information about the net exchange of CO₂ at biome scales (Peylin et al. 2013). The array of Earth observing satellites has also grown tremendously, providing better spatiotemporal coverage of vegetation indices that are useful for assessing patterns and trends of global productivity since ~1982 (Pinzon and Tucker 2010), as well as valuable information on changes in vegetation cover (Song et al. 2018) and ecosystem stress (Anderegg et al. 2018). Recent advances in satellite observations facilitate quantification of concentration estimates integrated over the entire total atmospheric column for CO₂ (ie XCO₂) and
$CH_4$ (ie $XCH_4$). Although potentially less precise than those relying on surface measurements using infrared gas analyzers, these estimates provide more continuous global coverage, improving characterization of regional flux anomalies and attribution to specific C-cycle processes (Liu et al. 2017).

Innovative ways to combine ecosystem measurements with satellite observations have made it possible to quantify how different ecosystems are responding to concomitant changes in atmospheric composition, including $CO_2$ concentration, surface temperatures, and regional precipitation. Moreover, these top-down and bottom-up observations are helping researchers to disentangle net C exchange into its component processes of photosynthesis and respiration across various scales, which provides important diagnostics for models that are designed to simulate the concurrent ecological processes and not just net $CO_2$ exchange. For instance, combined satellite and meteorological observations have been used in a machine-learning framework to up-scale eddy covariance measurements to provide spatially and temporally continuous estimates of global primary productivity (Jung et al. 2011). Likewise, global atmospheric $CO_2$ measurements have been used to constrain net $CO_2$ exchange in combination with satellite data to constrain primary productivity to infer the uncoupling of photosynthesis and respiration on decadal timescales (Ballantyne et al. 2017). The challenge for the scientific community is figuring out ways in which emergent patterns of net $CO_2$ exchange can be used (Cox et al. 2013) to identify underlying mechanistic processes that can be diagnosed in models (Anderegg et al. 2015). Ultimately, this will lead to scientific advances and societal benefits through improved Earth system models with less uncertainty in future climate predictions.

## Theoretical representation of C-cycle processes

Although the global C observing system has been greatly expanded and advanced over the past six decades, the theoretical and conceptual framework for understanding C-cycle dynamics has not necessarily kept pace (Figure 2). There has been extensive discussion over the past several decades concerning how the biosphere-atmosphere C exchange can best be defined. The challenges in defining C exchange lie across several axes, including time, space, and C form. Additional issues arise from the different processes occurring in and the transfer of C between aquatic and terrestrial ecosystems. Although we focus solely on terrestrial processes occurring from the ecosystem to biome scale here, we acknowledge the importance of the aquatic interface (Butman et al. 2018). The evolution of C-cycle measurements and key issues regarding terminology was described by Chapin et al. (2006), who defined net ecosystem C balance (NECB) simply as the change in C per unit time, but then broke this measure down into its component fluxes:

$$NECB = NEE - F_{CO} - F_{VOC} - F_{CH_4} - F_{DIC} - F_{DOC} - F_{PC} \quad (Equation 1).$$

<figure><img src="image_3.png" /><figcaption>**Figure 1.** Image of airborne observations combined with eddy flux observations of carbon (C) fluxes to measure ecosystem-atmosphere exchanges of carbon dioxide ($CO_2$).</figcaption></figure>

A Varlagin/imaggeo.egu.eu

In this formulation, net ecosystem exchange (NEE) is a measure of the net ecosystem $CO_2$ exchange as the difference between gross primary productivity (GPP) and total ecosystem respiration (TER), and at the ecosystem scale is typically measured using eddy covariance techniques (Wofsy et al. 1993). Although the $CO_2$ flux associated with NEE is usually the dominant form of net C exchange in many ecosystems, it cannot be assumed that transformations of C do not occur as a result of ecosystem processes. For instance, fluxes of carbon monoxide ($F_{CO}$), volatile organic compounds ($F_{VOC}$), methane ($F_{CH_4}$), dissolved inorganic C ($F_{DIC}$), dissolved organic C ($F_{DOC}$), and particulate C ($F_{PC}$) all represent C loss pathways that may affect the net C balance over time. Although NEE is sometimes used synonymously with NECB, it is an approximation that can, under certain circumstances, leave out quantitatively important non-respiratory processes that contribute to ecosystem C balance.

A second key issue in C balance terminology emerges at larger spatial or temporal scales when other factors can become major contributors to C balance. Notably, large disturbances like wildfire, landslides, and insect infestations can cause large or punctuated redistributions of C. In human managed ecosystems, activities such as logging, harvest, and other forms of C transfer can result in C taken up at the ecosystem scale being lost at the biome scale, and this transfer can actually cause NECB to shift from a net C sink to a net C source. The net biome productivity (NBP) concept was first introduced by Schulze et al. (2000) to account for C transfer and subsequent
<figure><img src="image_4.png" /><figcaption>**Figure 2.** Conceptual figure showing pathways of C gain and loss from ecosystem to biome to terrestrial scales within the biosphere. Although it is often assumed that very little change occurs among the gas, particulate, and dissolved phases of C, ecosystems are very effective at transforming C, such that C gain pathways may not correspond with C loss pathways, leading to an apparent C imbalance across scales. Furthermore, C can be transported across scales via either advection through the atmosphere or fluvial processes in aquatic ecosystems.</figcaption></figure>

loss at regional scales. In Chapin *et al.* (2006), NECB represents NBP integrated over fixed space and time domains, with the assumption that additional processes analogous to those shown in Equation (1) may need to be added to account for C fluxes driven by periodic events. At the global scale, we can assume that CO₂ mass is conserved in the atmosphere and thus, given fossil-fuel emissions to the atmosphere and estimates of net CO₂ uptake by the oceans, net CO₂ uptake by the terrestrial biosphere can be inferred (Le Quéré *et al.* 2016). More importantly, the atmosphere and oceans provide constraints on global C exchange because these are relatively well-mixed homogenous reservoirs as compared to ecosystem C pools and fluxes that tend to be much more spatially and temporally heterogeneous. Resolving C-cycle processes from ecosystem to global scales may therefore require an update to C-cycle nomenclature (see WebPanel 1).

## Spatial scale differences in C balance

The “C exchange efficiency” (CEE = NEE/GPP) may provide a useful framework (see WebFigure 1) for comparing relative fluxes across ecosystem to global scales. At the global scale, only ~2% of C fixed annually through GPP remains in the biosphere as a result of NEE (2.5/125 Pg C/year), suggesting that CEE of the terrestrial biosphere is remarkably low. At the scale of the continental US, approximately 5% of C fixed annually through photosynthesis remains in the terrestrial biosphere (Figure 3). However, estimates of CEE derived from eddy

covariance methods reveal very large differences among terrestrial ecosystems. Ecosystems with lower levels of GPP tend to fall on the CEE line at the continental scale, whereas more productive ecosystems tend to deviate from the CEE line. For example, grasslands have very low CEE (~2%), a level consistent with the global CEE, whereas evergreen needleleaf forests and deciduous broadleaf forests appear to have quite high CEE values (~31% and ~24%, respectively). Therefore, our ecosystem-scale measurements suggest that these forests are strong C sinks, whereas our global-scale measurements suggest that much of this apparent forest C uptake is lost, indicating that these forests may be acting more like “C sieves”. Moreover, croplands vary considerably, with less productive croplands falling on the continental CEE line and more productive croplands deviating considerably, with an overall CEE of 23%. It should be noted, however, that according to mass balance, the integral of NEE across all ecosystems (aquatic and terrestrial) should be equal to global NEE; in other words, CEE estimates from the different ecosystems shown in Figure 3 should all fall on the continental CEE line (Chapin *et al.* 2006).

Therefore, measurements of net CO₂ exchange at the ecosystem scale are biased, or CO₂ loss pathways at the continental scale are offsetting the apparent net uptake of CO₂ by certain ecosystems.

Measurement biases of ecosystem C fluxes stem from the location of eddy flux sites or systematic biases in NEE measurements. In the US, this network bias should be reduced with the addition of more observation sites, such as NEON sites; however, there remain notable gaps in the intermountain west, northern plains, and parts of the Southeast. Also noteworthy is that eddy flux sites are often situated in rapidly regenerating ecosystems and as such may not capture the full trajectory of ecosystem C dynamics (Luyssaert *et al.* 2008). Furthermore, the eddy flux approach only measures the net ecosystem CO₂ exchange (ie NEE) directly, whereas photosynthetic fluxes and total ecosystem respiration fluxes are estimated, resulting in the potential for systematic biases to occur in these measurements. Eddy covariance methods are inherently challenging in ecosystems with dense canopies (Thomas *et al.* 2013), which can lead to nocturnal C storage within the canopy (Fu *et al.* 2018) and decoupling of the canopy and the atmosphere that may vary seasonally (Jocher *et al.* 2017). This may help explain the strong divergence between both deciduous broadleaf and evergreen needleleaf forests and the CEE line at the continental scale (Figure 3). If daytime respiration is reduced with respect to nighttime respiration, large overestimates of both photosynthetic gains and respiration losses at the ecosystem scale may result, which would increase relative ecosystem CEE (Keenan *et al.* 2019).
The discrepancy between CEE at the biome scale and the ecosystem scale can also be explained by the lack of measurements of non-respiratory loss pathways of CO₂ back to the atmosphere (Figure 2). For example, aquatic ecosystems, which are effective at transporting dissolved and particulate forms of inorganic and organic C and transforming it to CO₂ such that it may be lost to the atmosphere (Neff and Asner 2001; Hotchkiss et al. 2015), were not plotted on our diagnostic CEE plot (Figure 3). There are many measurements of the partial pressure of CO₂ in aquatic environments, which determine whether CO₂ is diffusing in or out of aquatic ecosystems, but these are not always combined with productivity estimates (albeit see Hotchkiss et al. 2015; Bernhardt et al. 2018). Volatile organic C (VOC) compounds are another major source of C loss from ecosystems, which may help to reconcile the discrepancy between ecosystem- and biome-scale C exchange efficiencies. Estimates of VOC production are tightly coupled to primary productivity and range around 450 teragrams (Tg) C/year, making them a very small fraction of terrestrial GPP (less than 0.4%) but an appreciable fraction of NEE (~15%), assuming that VOCs are rapidly oxidized to form CO₂ (Unger et al. 2013). Finally, the only ecosystem-scale C loss pathways that can help reconcile ecosystem- and global-scale estimates of CEE are oxidative pathways that ultimately lead to atmospheric CO₂ (eg CO₂ emissions from wildfires), meaning that other loss pathways leading to reduced C (eg CH₄ emissions) will not help reconcile these discrepancies of scale.

We can also look at the spatial distribution of CEE from the
biome to ecosystem scale (Figure 4). At the continental scale
in the US, it is apparent that high CEE in the midwestern
region near the Great Lakes is driven primarily by high mean
annual NEE, and very high CEE in the intermountain west is
driven by low GPP and modest NEE. In contrast, highly pro-
ductive regions, such as the Pacific Northwest and the
Southeast, do not necessarily retain a large fraction of GPP as
NEE, as reflected in their relatively low CEE values. These
regional differences in CEE seem to be corroborated by eddy
covariance sites in certain biomes, such as the Northeast and
parts of the Southwest, but less so in other regions. There
appears to be a strong mismatch in CEE near the Great Lakes,
with regional estimates suggesting a relatively high CEE,
whereas eddy flux sites indicate a much lower CEE. This may
be due to the specific locations of eddy flux sites that may not
capture the diverse array of midwestern ecosystems. A similar
mismatch is evident in the Pacific Northwest, where regional
CEE values are extremely low – and in some instances nega-
tive – due to an apparent net source of CO₂ to the atmosphere,

while eddy flux measurements from central Oregon suggest
high CEE.

■ Climate sensitivity of C-cycle processes

At the continental scale in the US, mean annual primary productivity and net CO₂ exchange do not necessarily covary spatially and appear to occupy different climate spaces at regional scales (Figure 5; Liu et al. 2018). GPP is highest in the relatively warm and wet Southeast (Figure 5a), corresponding with high levels of mean annual precipitation (MAP, >1200 mm) across a range of mean annual temperatures (MAT, ~10–20°C; Figure 5c). In contrast, NEE is more variable, with the highest values in the Midwest (Figure 5b) at intermediate to high levels of MAP (~750–1200 mm) and lower MAT (<10°C) (Figure 5d). The spatial covariance of GPP and NEE becomes decoupled as water availability increases. We found a strong precipitation threshold of ~700 mm/year over the continental US, below which NEE is regulated by photosynthetic gains and above which NEE is regulated to a greater degree by respiration losses (Liu et al. 2018). This result is consistent with ecosystem-scale studies that show the greatest response in productivity to precipitation anomalies in semiarid grassland and shrubland ecosystems (Knapp and Smith 2001). However, the lateral transport of C through river flow

<figure><img src="image_5.png" /></figure>

**Figure 3.** Comparison of C exchange efficiency (CEE) at ecosystem to biome scales across the continental US. Each point represents the mean annual gross ecosystem productivity and total ecosystem respiration for cropland (CRO), deciduous broadleaf forests (DBF), evergreen needleleaf (ENF), grassland (GRA), mixed forest (MF), open shrubland (OSH), and woody savanna (WSA) eddy covariance sites across the US. The diagonal line was derived from satellite estimates of gross primary productivity (GPP) and atmospheric estimates of net CO₂ exchange at the scale of the continental US and indicates that 95% of C fixed during photosynthesis is lost to the atmosphere through respiration, or that CEE is only 5% (1 – 0.95 = 0.05), represented by the green wedge.
<figure><img src="image_6.png" /></figure>

**Figure 4.** CEE for the continental US. Spatially continuous estimates of GPP derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite estimates and continuous estimates of net ecosystem exchange derived from atmospheric inversions over the continental US (Peters *et al.* 2007) are compared with in situ ecosystem-scale measurements made at 16 different eddy covariance core sites within the AmeriFlux Network (circle points). Positive values indicate regions where ecosystems are a net sink of C from the atmosphere, whereas negative values indicate regions where ecosystems are a net source of C to the atmosphere.

and human harvest may also be important in uncoupling GPP from NEE at continental scales. This spatial mismatch is an important finding because it is often assumed that anomalies in photosynthesis directly result in anomalies in net CO₂ exchange. In fact, it is impossible in standard eddy covariance approaches for partitioning fluxes to have increases in net exchange without increases in photosynthesis (Reichstein *et al.* 2005), and net C exchange in land-surface models is dominated by photosynthetic inputs (Liu *et al.* 2018).

At the global scale, the relationship between the interannual variability of the atmospheric CO₂ growth rate and tropical land-surface temperatures has been identified as an emergent constraint, such that higher surface temperatures diminish NEE (Cox *et al.* 2013). However, identifying the processes associated with this diminished NEE is difficult because increased tropical temperatures suppress photosynthesis and/or promote respiration, both of which lead to reduced net C exchange. It has been suggested that total respiration is the

<figure><img src="image_7.png" /></figure>

**Figure 5.** Continental-scale estimates of mean annual GPP and net CO₂ exchange (ie NEE) and their sensitivities to climate factors. (a) Continental-scale estimates of GPP from MODIS satellite observations plotted within (c) their climate space of mean annual precipitation and mean annual temperature. (b) Continental-scale estimates of NEE from atmospheric CO₂ inversion methods plotted within (d) their climate space. All flux estimates are reported as g C/m²/year and have been projected to ecosystem area (modified from Liu *et al.* [2018]; see WebTable 1).
most likely mechanism explaining the emergent relationship
between interannual variability in the atmospheric growth
rate and tropical surface temperature (Anderegg et al. 2015)
and that water limitation is important in regulating net CO2
exchange at the local scale, whereas temperature becomes
more important at global scales (Jung et al. 2017). Recent satel-
lite evidence suggests that terrestrial water availability that
integrates temperature and precipitation variability may be the
ultimate mechanism regulating interannual NEE at the global
scale (Humphrey et al. 2018). However, evidence derived from
satellite estimates of XCO2 and solar induced fluorescence
during the recent 2015/2016 El Niño event suggest that net
tropical C uptake was reduced by different processes in differ-
ent tropical regions – such as reduced photosynthesis in South
America, increased respiration in Africa, and increased fire
emissions in Southeast Asia (Liu et al. 2017). Therefore, even
though we are gaining new insight on the climate sensitivity of
important C-cycle processes, ecosystem-scale observations
are still lacking in certain regions to help reconcile different
C-cycle processes operating at different spatial scales.

■ Conclusions and frontiers in C-cycle research

A central goal of ecology at the macrosystem scale is to
understand biosphere processes and their complex interactions
with climate, land use, and changes in species distribution at
regional to continental scales This has also been a central
challenge of C-cycle research because there is a long history
of atmospheric CO2 observations that have enabled a better
understanding of the C cycle at the global scale and a network
of eddy covariance measurements of CO2 exchange at the
ecosystem scale. However, reconciling differences in net CO2
exchange measured at these different scales continues to be
difficult. We are now acquiring data from aircraft and satellites
that allow important C-cycle processes to be resolved at the
biome scale. The terrestrial and aquatic ecological research
communities are also compiling databases to elucidate impor-
tant C-cycle processes that may be merged to provide an
integrated understanding of C transport and transformations
across watersheds. Collectively, we are identifying missing
pieces of the global C puzzle that now make it possible to
reconcile and understand processes that help to explain dis-
crepancies in C dynamics across scales.

■ Acknowledgements

Publication of this Special Issue was funded by the US Na-
tional Science Foundation (NSF award number DEB 1928375).
APB was supported by the NSF Macrosystems Biology Pro-
gram (1802810). ZL acknowledges support from the National
Natural Science Foundation of China (41922006) and the
KC Wong Education Foundation. PS acknowledges support
from NSF (1552976, 1632810, 1702029) and the US Depart-
ment of Agriculture National Institute of Food and Agriculture
(USDA NIFA) Hatch project 228396. WRLA was supported

by the David and Lucille Packard Foundation, NSF grants
1714972 and 1802880, and the USDA NIFA Agricultural and
Food Research Initiative Competitive Program, Ecosystem
Services and Agro-ecosystem Management (2018-67019-
27850). BP acknowledges support from the National Aeronautics
and Space Administration Terrestrial Ecology Program.

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Supporting Information

Additional, web-only material may be found in the online
version of this article at http://onlinelibrary.wiley.com/doi/10.
1002/fee.2296/suppinfo

<figure><img src="image_8.png" /></figure>

FrontiersEcoPics

The ghost orchid mooching off fungi

The color green is a defining feature of the plant kingdom, and plants are mostly assumed to be autotrophs that can make their own food from simple inorganic substances like carbon dioxide. However, in Yokohama, Japan, we observed that a non-photosynthetic or “ghost” variant of the golden orchid *Cephalanthera falcata* reached almost the same size as its photosynthetic green counterpart, suggesting that the ghost orchid was obtaining nutrients from symbiotic fungi.

Over evolutionary time, several lineages of terrestrial plants have
independently lost their photosynthetic ability and have become totally
dependent on mycobionts. Intriguingly, recent studies have shown
that the presence of chlorophyll is insufficient to confirm full autotro-
phy. Some green plants, including *Cephalanthera* species, not only are

photosynthetically active but also obtain carbon from mycorrhizal
fungi. These "mixotrophic" plants showcase intermediate stages of
the evolutionary transition from autotrophy to heterotrophy.
Photosynthesis is one of the processes we think of as fundamental to
plants. Therefore, the loss of photosynthesis is one of the most inter-
esting topics within plant evolution.

The non-photosynthetic variants of *C. falcata* are presumably more
dependent on fungi than their photosynthetic counterparts.
Comparisons between the two varieties – albino and green – of this
same species would be an elegant way to investigate the evolution of
the loss of photosynthesis, given that they share a nearly identical
genetic background. Do achlorophyllous plants in general provide
benefits to their mycorrhizal partners? If not, why does this "cheating"
strategy, at least in *C. falcata*, appear to be stable from an evolutionary
perspective? These are important questions for future research.

Kenji Suetsugu¹ and Kazuya Arai²

¹Kobe University, Hyogo, Japan; ²Kanagawa, Japan

doi:10.1002/fee.2301

<figure><img src="image_9.png" /></figure>

<figure><img src="image_10.png" /></figure>

<footnote n="9">⁹Woods Hole Research Center, Falmouth, MA; ¹⁰Geography and Environmental Science, University of Colorado Denver, Denver, CO;</footnote>

<footnote n="11">¹¹Sustainability Innovation Laboratory and Environmental Studies, University of Colorado, Boulder, CO</footnote>

<footnote>†these authors contributed equally to this work</footnote>