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Monitoring wetland vegetation and carbon stocks remotely via satellites and airborne instruments is increasingly common, but field‐based monitoring remains fundamental to understanding and quantifying wetland characteristics. Several important biogeochemical pathways unique to wetlands form important links between wetland vegetation, water, and soil (Ardón et al., 2013; Herbert et al., 2015; Osland et al., 2016). Therefore, monitoring both vegetation and soil over time are requisite to more comprehensively understanding wetland responses to global change (Taillie et al., 2019).

Both the vegetation composition and ecosystem structure contribute to the ecological function and value of wetlands. Though wetlands are often characterized according to the dominant plant species (e.g., “pond pine pocosin”), threshold responses to stressors can make certain species indicators for given stressors (Dufrêne & Legendre, 1997). As such, inventory of canopy species, as well as herbaceous and woody groundcover, may be necessary to adequately describe wetlands, particularly in temperate regions (Bratton, 1976). Aside from species composition, variation in vegetation structure (e.g., height, density, heterogeneity) may be dramatically different within and among wetlands. In addition, some variation in vegetation structure, such as mid‐ and under‐story vegetation density, may be difficult to estimate via remote sensing and will be best quantified via field‐based inventory (Riegel et al., 2013). Given the effort required to survey plants within a plot, care should be taken to balance the number and size of experimental units that are appropriate for the research objectives and capturing landscape heterogeneity. In forested settings, 11‐m radius plots are often used (Henttonen & Kangas, 2015). Selecting in‐situ measurements to match the scale of observation of airborne and spaceborne remotely sensed data (e.g., canopy height) may allow for scaling up field‐collected measurements (Hudak et al., 2012; Riegel et al., 2013).

Because of the value of wetlands for carbon storage, researchers often aim to translate vegetation inventories to biomass or carbon stocks. Such calculations are often made with the use of allometric equations which estimate the volume or biomass stored in an individual plant based on the species and either height or diameter‐at‐breast‐height, DBH (Jenkins et al., 2004). Canopy height, and various derived metrics, are often measured to verify models based on remote sensing, but field measurement with a clinometer can be time intensive and logistically impractical when vegetation is dense. Regardless, documented relationships between DBH and height for a given species can be used to extrapolate aboveground biomass to large spatial extent if canopy height and species composition are available via remote sensing (Smart et al., 2020). Though more commonly employed in forested settings, this method may also be used in herbaceous wetlands (Trilla et al., 2009).

Field sampling of soil characteristics, such as the depth of the organic profile, bulk density and its vertical profile, and chemical composition, is particularly important for estimating belowground carbon stocks. Specifically, the quantity and quality of soil pore water drive carbon accumulation and long‐term storage. For example, salinity is among the dominant drivers of vegetation change in coastal wetlands (Taillie et al., 2019; Williams et al., 1999), while hydroperiod holds this role in inland wetlands (Ross et al., 2003). While more sophisticated soil sampling may reveal changes with depth, a crude sample collected with a small shovel and a Mehlich III extraction is often sufficient to determine salinity, cation exchange capacity, and the ratio of organic to mineral soil (Taillie et al., 2019). In wetlands with standing water, contamination with surface water is inevitable, and thus is susceptible to daily fluctuation in salinity as a function of precipitation, evapotranspiration, and other water processes (Herbert et al., 2015). As such, coastal wetlands should be sampled during both dry and wet periods to best understand the variation in salinity as a function of precipitation and salinization (Herbert et al., 2015). Though evidence of salinization may persist longer in soils compared to surface waters (Chagué‐Goff et al., 2012), soil cation concentrations may not accurately reflect the history of saltwater exposure over multiple years.