Methane and Carbon Dioxide Fluxes in a Temperate Tidal Salt Marsh: Comparisons Between Plot and Ecosystem Measurements

Hill, Andrew C.; Vargas, Rodrigo

doi:10.1029/2022jg006943

Cited by 17 publications

(21 citation statements)

References 129 publications

(171 reference statements)

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“…Our results require confirmation using site‐specific nutrient manipulation experiments and testing across different saltmarshes. A further challenge relates with the partition method used to derive F A from NEE, where the standardized approaches (e.g., Reichstein et al., 2005) do not consider the influence of key biophysical variables (i.e., tidal fluctuations and soil biogeochemistry) that may locally influence F A in these coastal ecosystems (Hill & Vargas, 2022; Vázquez‐Lule & Vargas, 2021). We also recognize the need for improving spatially implicit assessments of the spatial variability of F A considering uncertainties associated with micrometeorology (Hill et al., 2017; Tuovinen et al., 2019) and structural differences (e.g., vegetation types, water channels, and ecosystem scale) within salt marshes (Trifunovic et al., 2020).…”

Section: Discussionmentioning

confidence: 99%

“…After we assigned F A estimations to a vegetation category, we gap filled each F A time series using the marginal distribution sampling technique with global radiation, soil temperature, air temperature, water dissolve oxygen, and water flux as covariates in “ReddyProc” R package (Wutzler et al., 2018). We selected these independent variables for gap filling because of their high explanatory power for NEE variability as discussed in previous studies at this research site (Hill & Vargas, 2022; Trifunovic et al., 2020; Vázquez‐Lule & Vargas, 2021).…”

Section: Methodsmentioning

confidence: 99%

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Hyperspectral Reflectance for Measuring Canopy‐Level Nutrients and Photosynthesis in a Salt Marsh

et al. 2022

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Canopy photosynthesis (F A ) in salt marshes is a major carbon flux that is at least 12% higher than F A from terrestrial ecosystems and other freshwater wetlands (Lu et al., 2017;Xiao, 2004;Zhang et al., 2007). Despite the global relevance of F A from these ecosystems, salt marshes have been underrepresented in process-based models due to their unique spatial and temporal variability (Ward et al., 2020) and the limited information about the biophysical controls of their carbon cycle (Delwiche et al., 2021;Knox et al., 2019;. In particular, the role of macro-and micronutrients on F A is largely missing at the ecosystem and canopy scales, despite the importance of nutrients on the optimal growth of vegetation (Marschner & Marschner, 2012). Because of the relevant role of salt marshes on the local-to-global carbon budget, there is a need to identify the influence of leaf-and canopy-level nutrients on F A to better explain the underlying mechanisms of spatial variability of

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Hyperspectral Reflectance for Measuring Canopy‐Level Nutrients and Photosynthesis in a Salt Marsh

et al. 2022

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“…(2022). For comparing to top‐down measurements, such as flux towers to satellites, source areas and (non‐)linearities in downscaling need to be taken into account, whether that is for carbon emissions in a salt marsh (Hill & Vargas, 2022), hotspots of methane in eddy covariance flux tower footprints (Rey‐Sanchez et al., 2022), or land surface temperature over heterogeneous landscapes (Desai, Khan, et al., 2021).…”

Section: A Scale For All Silosmentioning

confidence: 99%

“…Levy et al (2022) reviewed the key challenges for upscaling when it comes to the UK greenhouse gas program and finds an essential role for uncertainty propagation, a factor also evaluated for gross primary productivity upscaling by Xie et al (2022). For comparing to top-down measurements, such as flux towers to satellites, source areas and (non-)linearities in downscaling need to be taken into account, whether that is for carbon emissions in a salt marsh (Hill & Vargas, 2022), hotspots of methane in eddy covariance flux tower footprints (Rey-Sanchez et al, 2022), or land surface temperature over heterogeneous landscapes (Desai, Khan, et al, 2021).…”

Section: A Scale For All Silosmentioning

confidence: 99%

Scaling Land‐Atmosphere Interactions: Special or Fundamental?

et al. 2022

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Viewed from billions of kilometers away in space, Earth appears as a single "Pale Blue Dot," in the immortalized phrase of Carl Sagan bestowed upon the image taken by the Voyager 1 space probe. Coming closer, though, a sharper image emerges (Figure 1).One finds structure to that dot, shades of green and brown continents, a dark ocean, a bright cryosphere, and a hazy, thin blue atmosphere. Zooming further in, those components break into patterns of mountains and rivers, seas and bays, forests and grasslands, layers, and cloud decks. And getting closer, one finds each component has oscillations and variations of branches and rivulets, canyons and plateaus, currents and coastlines. These objects keep revealing more structure in finer, often self-similar form, like Mandelbrot's fractals, down to eddies and organisms, and further into leaves, cells, enzymes, molecules, and atoms.And then, if you wait seconds, days, decades, or eons, landscape patterns change. Bigger things typically take longer than smaller ones. As a result, the pattern changes-sometimes occurring slowly and subtly, ebbing and flowing in an oscillatory manner, or they can occur quickly and abruptly, morphing into a new state of order.Each element and its dynamics come with variations in space and time that can be encompassed by the concept of scale. Earth systems science is preoccupied with the interactions of these elements, which cannot be understood without a stipulation of the scales of interest (Ge et al., 2019). The most straightforward of these interactions are ones where common processes at all scales can be defined by a single relationship, often a power-law, leading to the concept of scale invariance (Paleri et al., 2022). The most interesting interactions are the ones that break those rules and lead to "upscale" and "downscale" behavior, whereby processes at one scale determine the shape and function of another scale. These are most common at the intersections of biology, hydrology, geology, and meteorology, often within what is termed the "critical zone." This interlocking also harkens to the origins of

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“…A few studies have demonstrated the potential and benefits of utilizing both techniques in heterogeneous wetland ecosystems (Hill & Vargas, 2022; Rey‐Sanchez et al., 2018; Schäfer et al., 2014). Cross‐scale measurements have improved the quantification of CO 2 and CH 4 exchange in several wetland studies (Acosta et al., 2019; Morin et al., 2017; Rey‐Sanchez et al., 2018; Schrier‐Uijl et al., 2010), but have been rarely applied in tidal wetland ecosystems (Hill & Vargas, 2022; Krauss et al., 2016).…”

Section: Introductionmentioning

confidence: 99%

Combining Eddy Covariance and Chamber Methods to Better Constrain CO₂ and CH₄ Fluxes Across a Heterogeneous Restored Tidal Wetland

et al. 2022

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Tidal wetlands are among the most effective natural ecosystems in sequestrating carbon on the planet, storing 0.4-6.5 Pg C globally (Duarte et al., 2013;Windham-Myers et al., 2018). However, their spatial extents have drastically reduced due to land-use change and rising sea levels (Lewis et al., 2019). Around 43%-48% of tidal wetlands in the U.S. are vulnerable to sea-level rise (Holmquist et al., 2021), which puts these significant carbon stocks at risk (Spivak et al., 2019). Even though tidal wetlands release relatively small amounts of methane (CH 4 ) compared to freshwater wetlands, the estimates of tidal wetlands' methane budgets are highly uncertain (±75%) on the global scale (Rosentreter et al., 2021). This uncertainty impedes our ability to inventory greenhouse gas budgets and thereby assess the radiative forcing of coastal wetlands (Holmquist et al., 2018). It also impedes our ability to represent tidal wetlands in Earth System Models (Ward et al., 2020). Improved accounting and

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Methane and Carbon Dioxide Fluxes in a Temperate Tidal Salt Marsh: Comparisons Between Plot and Ecosystem Measurements

Cited by 17 publications

References 129 publications

Hyperspectral Reflectance for Measuring Canopy‐Level Nutrients and Photosynthesis in a Salt Marsh

Hyperspectral Reflectance for Measuring Canopy‐Level Nutrients and Photosynthesis in a Salt Marsh

Scaling Land‐Atmosphere Interactions: Special or Fundamental?

Combining Eddy Covariance and Chamber Methods to Better Constrain CO₂ and CH₄ Fluxes Across a Heterogeneous Restored Tidal Wetland

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Methane and Carbon Dioxide Fluxes in a Temperate Tidal Salt Marsh: Comparisons Between Plot and Ecosystem Measurements

Cited by 17 publications

References 129 publications

Hyperspectral Reflectance for Measuring Canopy‐Level Nutrients and Photosynthesis in a Salt Marsh

Hyperspectral Reflectance for Measuring Canopy‐Level Nutrients and Photosynthesis in a Salt Marsh

Scaling Land‐Atmosphere Interactions: Special or Fundamental?

Combining Eddy Covariance and Chamber Methods to Better Constrain CO2 and CH4 Fluxes Across a Heterogeneous Restored Tidal Wetland

Contact Info

Product

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Combining Eddy Covariance and Chamber Methods to Better Constrain CO₂ and CH₄ Fluxes Across a Heterogeneous Restored Tidal Wetland