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Salt marshes are highly productive ecosystems relevant for Blue Carbon assessments, but information for estimating gross primary productivity (GPP) from proximal remote sensing (PRS) is limited. Temperate salt marshes have seasonal canopy structure and metabolism changes, defining different canopy phenological phases, GPP rates, and spectral reflectance. We combined multi-annual PRS data (i.e., PhenoCam, discrete hyperspectral measurements, and automated spectral reflectance sensors) with GPP derived from eddy covariance. We tested the performance of empirical models to predict GPP from 12 common vegetation indices (VIs; e.g., NDVI, EVI, PSRI, GCC), Sun-Induced Fluorescence (SIF), and reflectance from different areas of the electromagnetic spectrum (i.e., VIS-IR, RedEdge, IR, and SIF) across the annual cycle and canopy phenological phases (i.e., Greenup, Maturity, Senescence, and Dormancy). Plant Senescence Reflectance Index (PSRI) from hyperspectral data and the Greenness Index (GCC) from PhenoCam, showed the strongest relationship with daily GPP across the annual cycle and within phenological phases (r2=0.30–0.92). Information from the visible-infrared electromagnetic region (VIS-IR) coupled with a partial least square approach (PLSR) showed the highest data-model agreement with GPP, mainly because of its relevance to respond to physiological and structural changes in the canopy, compared with indices (e.g., GCC) that particularly react to changes in the greenness of the canopy. The most relevant electromagnetic regions to model GPP were ∼550 nm and ∼710 nm. Canopy phenological phases impose challenges for modeling GPP with VIs and the PLSR approach, particularly during Maturity, Senescence, and Dormancy. As more eddy covariance sites are established in salt marshes, the application of PRS can be widely tested. Our results highlight the potential to use canopy reflectance from the visible spectrum region for modeling annual GPP in salt marshes as an example of advances within the AmeriFlux network. 

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Abstract. Over the past decade, Brazil has experienced severe droughts across its territory, with important implications for soil moisture dynamics. Soil moisture variability has a direct impact on agriculture, water security and ecosystem services. Nevertheless, there is currently little information on how soil moisture across different biomes responds to drought. In this study, we used satellite soil moisture data from the European Space Agency, from 2009 to 2015, to analyze differences in soil moisture responses to drought for each biome of Brazil: Amazon, Atlantic Forest, Caatinga, Cerrado, Pampa and Pantanal. We found an overall soil moisture decline of −0.5 % yr−1 (p<0.01) at the national level. At the biome level, Caatinga presented the most severe soil moisture decline (−4.4 % yr−1), whereas the Atlantic Forest and Cerrado biomes showed no significant trend. The Amazon biome showed no trend but had a sharp reduction of soil moisture from 2013 to 2015. In contrast, the Pampa and Pantanal biomes presented a positive trend (1.6 % yr−1 and 4.3 % yr−1, respectively). These trends are consistent with vegetation productivity trends across each biome. This information provides insights into drought risk reduction and soil conservation activities to minimize the impact of drought in the most vulnerable biomes. Furthermore, improving our understanding of soil moisture trends during periods of drought is crucial to enhance the national drought early warning system and develop customized strategies for adaptation to climate change in each biome. 

Abstract Mangroves cover less than 0.1% of Earth’s surface, store large amounts of carbon per unit area, but are threatened by global environmental change. The capacity of mangroves productivity could be characterized by their canopy greenness, but this property has not been systematically tested across gradients of mangrove forests and national scales. Here, we analyzed time series of Normalized Difference Vegetation Index (NDVI), mean air temperature and total precipitation between 2001 and 2015 (14 years) to quantify greenness and climate variability trends for mangroves not directly influenced by land use/land cover change across Mexico. Between 2001 and 2015 persistent mangrove forests covered 432 800 ha, representing 57% of the total current mangrove area for Mexico. We found a temporal greenness increase between 0.003_{[0.001–0.004]}and 0.004_{[0.002–0.005]}yr⁻¹(NDVI values ± 95%CI) for mangroves located over the Gulf of California and the Pacific Coast, with many mangrove areas dominated byAvicennia germinans.Mangroves developed along the Gulf of Mexico and Caribbean Sea did not show significant greenness trends, but site-specific areas showed significant negative greenness trends. Mangroves with surface water input have above ground carbon stocks (AGC) between 37.7 and 221.9 Mg C ha⁻¹and soil organic carbon density at 30 cm depth (SOCD) between 92.4 and 127.3 Mg C ha⁻¹. Mangroves with groundwater water input have AGC of 12.7 Mg C ha⁻¹and SOCD of 219 Mg C ha⁻¹. Greenness and climate variability trends could not explain the spatial variability in carbon stocks for most mangrove forests across Mexico. Site-specific characteristics, including mangrove species dominance could have a major influence on greenness trends. Our findings provide a baseline for national-level monitoring programs, carbon accounting models, and insights for greenness trends that could be tested around the world. 

Abstract Salt marsh ecosystems are underrepresented in process‐based models due to their unique location across the terrestrial–aquatic interface. Particularly, the role of leaf nutrients on canopy photosynthesis (F_A) remains unclear, despite their relevance for regulating vegetation growth. We combined multiyear information of canopy‐level nutrients and eddy covariance measurements with canopy surface hyperspectral remote sensing (CSHRS) to quantify the spatial and temporal variability of F_Ain a temperate salt marsh. We found that F_Ashowed a positive relationship with canopy‐level N at the ecosystem scale and for areas dominated bySpartina cynosuroides, but not for areas dominated by shortS. alterniflora. F_Ashowed a positive relationship with canopy‐level P, K, and Na, but a negative relationship with Fe, for areas associated withS. cynosuroides,S. alterniflora, and at the ecosystem scale. We used partial least squares regression (PLSR) with CSHRS and found statistically significant data–model agreements to predict canopy‐level nutrients and F_A. The red‐edge electromagnetic region and ∼770 nm showed the highest contribution of variance in PLSR models for canopy‐level nutrients and F_A, but we propose that underlying sediment biogeochemistry can complicate interpretation of reflectance measurements. Our findings highlight the relevance of spatial variability in salt marshes vegetation and the promising application of CSHRS for linking information of canopy‐level nutrients with F_A. We call for further development of canopy surface hyperspectral methods and analyses across salt marshes to improve our understanding of how these ecosystems will respond to global environmental change. 

Abstract Measurements of atmospheric ammonia (NH₃) concentrations and fluxes are limited in coastal regions in the eastern U.S. In this study, continuous and high temporal resolution measurements (5s) of atmospheric NH₃concentrations were recorded using a cavity ring‐down spectrometer in a temperate tidal salt marsh at the St Jones Reserve (Dover, DE). Micrometeorological variables were measured using an eddy covariance system which is part of the AmeriFlux network (US‐StJ). Soil, plant, and water chemistry were also analyzed to characterize the sources and sinks of atmospheric NH₃. A new analytical methodology was used to estimate the average ecosystem‐scale diurnal cycle of NH₃fluxes by replicating the characteristics of a chamber experiment. This virtual chamber approach estimates positive surface fluxes in continuing strongly stable conditions when mixing with the air above is minimal. Our findings show that tidal water level may have a significant impact on NH₃emissions from the marsh. The largest fluxes were observed at low tide when more soil was exposed. While it is expected that NH₃fluxes will peak when the air temperature maximizes, high tide occurred concurrently with midday peaks in solar irradiance led to a decrease in NH₃fluxes. Furthermore, soil, plant, and water chemistry measurements underpinning the NH₃concentrations and fluxes lead us to conclude that this coastal wetland ecosystem can act as either a sink or a source of NH₃. Such measurements provide novel data on which we can base reliable parameterizations to simulate NH₃emissions from coastal salt marsh ecosystems using surface‐atmosphere transfer models. 

Abstract Coastal salt marshes store large amounts of carbon but the magnitude and patterns of greenhouse gas (GHG; i.e., carbon dioxide (CO₂) and methane (CH₄)) fluxes are unclear. Information about GHG fluxes from these ecosystems comes from studies of sediments or at the ecosystem‐scale (eddy covariance) but fluxes from tidal creeks are unknown. We measured GHG concentrations in water, water quality, meteorological parameters, sediment CO₂efflux, ecosystem‐scale GHG fluxes, and plant phenology; all at half‐hour intervals over 1 year. Manual creek GHG flux measurements were used to calculate gas transfer velocity (k) and parameterize a model of water‐to‐atmosphere GHG fluxes. The creek was a source of GHGs to the atmosphere where tidal patterns controlled diel variability. Dissolved oxygen and wind speed were negatively correlated with creek CH₄efflux. Despite lacking a seasonal pattern, creek CO₂efflux was correlated with drivers such as turbidity across phenological phases. Overall, nighttime creek CO₂efflux (3.6 ± 0.63 μmol/m²/s) was at least 2 times higher than nighttime marsh sediment CO₂efflux (1.5 ± 1.23 μmol/m²/s). Creek CH₄efflux (17.5 ± 6.9 nmol/m²/s) was 4 times lower than ecosystem‐scale CH₄fluxes (68.1 ± 52.3 nmol/m²/s) across the year. These results suggest that tidal creeks are potential hotspots for CO₂emissions and could contribute to lateral transport of CH₄to the coastal ocean due to supersaturation of CH₄(>6,000 μmol/mol) in water. This study provides insights for modeling GHG efflux from tidal creeks and suggests that changes in tide stage overshadow water temperature in determining magnitudes of fluxes.