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1. Climate-driven tradeoffs between landscape connectivity and the maintenance of the coastal carbon sink

   https://doi.org/10.1038/s41467-023-36803-7  

   Valentine, Kendall ; Herbert, Ellen R. ; Walters, David C. ; Chen, Yaping ; Smith, Alexander J. ; Kirwan, Matthew L. ( March 2023 , Nature Communications)

   Ecosystem connectivity tends to increase the resilience and function of ecosystems responding to stressors. Coastal ecosystems sequester disproportionately large amounts of carbon, but rapid exchange of water, nutrients, and sediment makes them vulnerable to sea level rise and coastal erosion. Individual components of the coastal landscape (i.e., marsh, forest, bay) have contrasting responses to sea level rise, making it difficult to forecast the response of the integrated coastal carbon sink. Here we couple a spatially-explicit geomorphic model with a point-based carbon accumulation model, and show that landscape connectivity, in-situ carbon accumulation rates, and the size of the landscape-scale coastal carbon stock all peak at intermediate sea level rise rates despite divergent responses of individual components. Progressive loss of forest biomass under increasing sea level rise leads to a shift from a system dominated by forest biomass carbon towards one dominated by marsh soil carbon that is maintained by substantial recycling of organic carbon between marshes and bays. These results suggest that climate change strengthens connectivity between adjacent coastal ecosystems, but with tradeoffs that include a shift towards more labile carbon, smaller marsh and forest extents, and the accumulation of carbon in portions of the landscape more vulnerable to seamore »level rise and erosion.

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2. Recovering wetland biogeomorphic feedbacks to restore the world’s biotic carbon hotspots

   https://doi.org/10.1126/science.abn1479  

   Temmink, Ralph J. ; Lamers, Leon P. ; Angelini, Christine ; Bouma, Tjeerd J. ; Fritz, Christian ; van de Koppel, Johan ; Lexmond, Robin ; Rietkerk, Max ; Silliman, Brian R. ; Joosten, Hans ; et al ( May 2022 , Science)

   BACKGROUND Evaluating effects of global warming from rising atmospheric carbon dioxide (CO 2 ) concentrations requires resolving the processes that drive Earth’s carbon stocks and flows. Although biogeomorphic wetlands (peatlands, mangroves, salt marshes, and seagrass meadows) cover only 1% of Earth’s surface, they store 20% of the global organic ecosystem carbon. This disproportionate share is fueled by high carbon sequestration rates per unit area and effective storage capacity, which greatly exceed those of oceanic and forest ecosystems. We highlight that feedbacks between geomorphology and landscape-building wetland vegetation underlie these critical qualities and that disruption of these biogeomorphic feedbacks can switch these systems from carbon sinks into sources. ADVANCES A key advancement in understanding wetland functioning has been the recognition of the role of reciprocal organism-landform interactions, “biogeomorphic feedbacks.” Biogeomorphic feedbacks entail self-reinforcing interactions between biota and geomorphology, by which organisms—often vegetation—engineer landforms to their own benefit following a positive density-dependent relationship. Vegetation that dominates major carbon-storing wetlands generate self-facilitating feedbacks that shape the landscape and amplify carbon sequestration and storage. As a result, per unit area, wetland carbon stocks and sequestration rates greatly exceed those of terrestrial forests and oceans, ecosystems that worldwide harbor large stocks because of their largemore »areal extent. Worldwide biogeomorphic wetlands experience human-induced average annual loss rates of around 1%. We estimate that associated carbon losses amount to 0.5 Pg C per year, levels that are equivalent to 5% of the estimated overall anthropogenic carbon emissions. Because carbon emissions from degraded wetlands are often sustained for centuries until all organic matter has been decomposed, conserving and restoring biogeomorphic wetlands must be part of global climate solutions. OUTLOOK Our work highlights that biogeomorphic wetlands serve as the world’s biotic carbon hotspots, and that conservation and restoration of these hotspots offer an attractive contribution to mitigate global warming. Recent scientific findings show that restoration methods aimed at reestablishing biogeomorphic feedbacks can greatly increase establishment success and restoration yields, paving the way for large-scale restoration actions. Therefore, we argue that implementing such measures can facilitate humanity in its pursuit of targets set by the Paris Agreement and the United Nations Decade on Ecosystem Restoration. Carbon storage in biogeomorphic wetlands. Organic carbon ( A ) stocks, ( B ) densities, and ( C ) sequestration rates in the world’s major carbon-storing ecosystems. Oceans hold the largest stock, peatlands (boreal, temperate, and tropical aggregated) store the largest amount per unit area, and coastal ecosystems (mangroves, salt marshes, and seagrasses aggregated) support the highest sequestration rates. ( D and E ) Biogeomorphic feedbacks, indicated with arrows, can be classified as productivity stimulating or decomposition limiting. Productivity-stimulating feedbacks increase resource availability and thus stimulate vegetation growth and organic matter production. Although production is lower in wetlands with decomposition-limiting feedbacks, decomposition is more strongly limited, resulting in net accumulation of organic matter. (D) In fens, organic matter accumulation from vascular plants is amplified by productivity-stimulating feedbacks. Once the peat rises above the groundwater and is large enough to remain waterlogged by retaining rainwater, the resulting bog maintains being waterlogged and acidic, resulting in strong decomposition-limiting feedbacks. (E) Vegetated coastal ecosystems generate productivity-stimulating feedbacks that enhance local production and trapping of external organic matter.« less
3. Climate Change Driving Widespread Loss of Coastal Forested Wetlands Throughout the North American Coastal Plain

   https://doi.org/10.1007/s10021-021-00686-w  

   White, Elliott E. ; Ury, Emily A. ; Bernhardt, Emily S. ; Yang, Xi ( August 2021 , Ecosystems)

   Coastal forested wetlands support many endemic species, sequester substantial carbon stocks, and have been reduced in extent due to historic drainage and agricultural expansion. Many of these unique coastal ecosystems have been drained, while those that remain are now threatened by saltwater intrusion and sea level rise in hydrologically modified coastal landscapes. Several recent studies have documented rapid and accelerating losses of coastal forested wetlands in small areas of the Atlantic and Gulf coasts of North America, but the full extent of loss across North America’s Coastal Plain (NACP) has not been quantified. We used classified satellite imagery to document a net loss of  13,682 km2 (8%) of forested coastal wetlands across the NACP between 1996 and 2016. Most forests transitioned to scrub-shrub (53%) and marsh habitats (24%). Even within protected areas, we measured substantial rates of wetland deforestation and significant fragmentation of forested wetland habitats. Variation in the rate of sea level rise, the number of tropical storm landings, and the average elevation of coastal watersheds explained about 78% of the variation in coastal wetland deforestation extent along the south Atlantic and Gulf Coasts. The rate of coastal forest loss within the NACP (684 km2/y) exceeds the recentmore »estimate of global losses of coastal mangroves (210 km2/y). At the current rate of deforestation, in the absence of widespread protection or restoration efforts, coastal forested wetlands may not persist into the next century.« less
4. Consumer regulation of the carbon cycle in coastal wetland ecosystems

   https://doi.org/10.1098/rstb.2019.0451  

   He, Qiang ; Li, Haoran ; Xu, Changlin ; Sun, Qingyan ; Bertness, Mark D. ; Fang, Changming ; Li, Bo ; Silliman, Brian R. ( December 2020 , Philosophical Transactions of the Royal Society B: Biological Sciences)

   Despite escalating anthropogenic alteration of food webs, how the carbon cycle in ecosystems is regulated by food web processes remains poorly understood. We quantitatively synthesize the effects of consumers (herbivores, omnivores and carnivores) on the carbon cycle of coastal wetland ecosystems, ‘blue carbon’ ecosystems that store the greatest amount of carbon per unit area among all ecosystems. Our results reveal that consumers strongly affect many processes of the carbon cycle. Herbivores, for example, generally reduce carbon absorption and carbon stocks (e.g. aboveground plant carbon by 53% and aboveground net primary production by 23%) but may promote some carbon emission processes (e.g. litter decomposition by 32%). The average strengths of these effects are comparable with, or even times higher than, changes driven by temperature, precipitation, nitrogen input, CO 2 concentration, and plant invasions. Furthermore, consumer effects appear to be stronger on aboveground than belowground carbon processes and vary markedly with trophic level, body size, thermal regulation strategy and feeding type. Despite important knowledge gaps, our results highlight the powerful impacts of consumers on the carbon cycle and call for the incorporation of consumer control into Earth system models that predict anthropogenic climate change and into management strategies of Earth's carbon stocks.more »This article is part of the theme issue ‘Integrative research perspectives on marine conservation’.« less
5. Florida mangrove saltmarsh reference surface soils

   https://doi.org/10.6073/pasta/0e08cbe07c84488cb7b9dd16669946d0  

   Lewis, David Bruce ( January 2021 )

   Abstract

   Site description. This data package consists of data obtained from sampling surface soil (the 0-7.6 cm depth profile) in black mangrove (Avicennia germinans) dominated forest and black needlerush (Juncus roemerianus) saltmarsh along the Gulf of Mexico coastline in peninsular west-central Florida, USA. This location has a subtropical climate with mean daily temperatures ranging from 15.4 °C in January to 27.8 °C in August, and annual precipitation of 1336 mm. Precipitation falls as rain primarily between June and September. Tides are semi-diurnal, with 0.57 m median amplitudes during the year preceding sampling (U.S. NOAA National Ocean Service, Clearwater Beach, Florida, station 8726724). Sea-level rise is 4.0 ± 0.6 mm per year (1973-2020 trend, mean ± 95 % confidence interval, NOAA NOS Clearwater Beach station). The A. germinans mangrove zone is either adjacent to water or fringed on the seaward side by a narrow band of red mangrove (Rhizophora mangle). A near-monoculture of J. roemerianus is often adjacent to and immediately landward of the A. germinans zone. The transition from the mangrove to the J. roemerianus zone is variable in our study area. An abrupt edge between closed-canopy mangrove and J. roemerianus monoculture may extend for up to several hundred meters in some locations, while other stretches of ecotone present a gradual transition where smaller, widely spaced trees are interspersed into the herbaceous marsh. Juncus roemerianus then extends landward to a high marsh patchwork of succulent halophytes (including Salicornia bigellovi, Sesuvium sp., and Batis maritima), scattered dwarf mangrove, and salt pans, followed in turn by upland vegetation that includes Pinus sp. and Serenoa repens. Field design and sample collection. We established three study sites spaced at approximately 5 km intervals along the western coastline of the central Florida peninsula. The sites consisted of the Salt Springs (28.3298°, -82.7274°), Energy Marine Center (28.2903°, -82.7278°), and Green Key (28.2530°, -82.7496°) sites on the Gulf of Mexico coastline in Pasco County, Florida, USA. At each site, we established three plot pairs, each consisting of one saltmarsh plot and one mangrove plot. Plots were 50 m^2 in size. Plots pairs within a site were separated by 230-1070 m, and the mangrove and saltmarsh plots composing a pair were 70-170 m apart. All plot pairs consisted of directly adjacent patches of mangrove forest and J. roemerianus saltmarsh, with the mangrove forests exhibiting a closed canopy and a tree architecture (height 4-6 m, crown width 1.5-3 m). Mangrove plots were located at approximately the midpoint between the seaward edge (water-mangrove interface) and landward edge (mangrove-marsh interface) of the mangrove zone. Saltmarsh plots were located 20-25 m away from any mangrove trees and into the J. roemerianus zone (i.e., landward from the mangrove-marsh interface). Plot pairs were coarsely similar in geomorphic setting, as all were located on the Gulf of Mexico coastline, rather than within major sheltering formations like Tampa Bay, and all plot pairs fit the tide-dominated domain of the Woodroffe classification (Woodroffe, 2002, "Coasts: Form, Process and Evolution", Cambridge University Press), given their conspicuous semi-diurnal tides. There was nevertheless some geomorphic variation, as some plot pairs were directly open to the Gulf of Mexico while others sat behind keys and spits or along small tidal creeks. Our use of a plot-pair approach is intended to control for this geomorphic variation. Plot center elevations (cm above mean sea level, NAVD 88) were estimated by overlaying the plot locations determined with a global positioning system (Garmin GPS 60, Olathe, KS, USA) on a LiDAR-derived bare-earth digital elevation model (Dewberry, Inc., 2019). The digital elevation model had a vertical accuracy of ± 10 cm (95 % CI) and a horizontal accuracy of ± 116 cm (95 % CI). Soil samples were collected via coring at low tide in June 2011. From each plot, we collected a composite soil sample consisting of three discrete 5.1 cm diameter soil cores taken at equidistant points to 7.6 cm depth. Cores were taken by tapping a sleeve into the soil until its top was flush with the soil surface, sliding a hand under the core, and lifting it up. Cores were then capped and transferred on ice to our laboratory at the University of South Florida (Tampa, Florida, USA), where they were combined in plastic zipper bags, and homogenized by hand into plot-level composite samples on the day they were collected. A damp soil subsample was immediately taken from each composite sample to initiate 1 y incubations for determination of active C and N (see below). The remainder of each composite sample was then placed in a drying oven (60 °C) for 1 week with frequent mixing of the soil to prevent aggregation and liberate water. Organic wetland soils are sometimes dried at 70 °C, however high drying temperatures can volatilize non-water liquids and oxidize and decompose organic matter, so 50 °C is also a common drying temperature for organic soils (Gardner 1986, "Methods of Soil Analysis: Part 1", Soil Science Society of America); we accordingly chose 60 °C as a compromise between sufficient water removal and avoidance of non-water mass loss. Bulk density was determined as soil dry mass per core volume (adding back the dry mass equivalent of the damp subsample removed prior to drying). Dried subsamples were obtained for determination of soil organic matter (SOM), mineral texture composition, and extractable and total carbon (C) and nitrogen (N) within the following week. Sample analyses. A dried subsample was apportioned from each composite sample to determine SOM as mass loss on ignition at 550 °C for 4 h. After organic matter was removed from soil via ignition, mineral particle size composition was determined using a combination of wet sieving and density separation in 49 mM (3 %) sodium hexametaphosphate ((NaPO_3)_6) following procedures in Kettler et al. (2001, Soil Science Society of America Journal 65, 849-852). The percentage of dry soil mass composed of silt and clay particles (hereafter, fines) was calculated as the mass lost from dispersed mineral soil after sieving (0.053 mm mesh sieve). Fines could have been slightly underestimated if any clay particles were burned off during the preceding ignition of soil. An additional subsample was taken from each composite sample to determine extractable N and organic C concentrations via 0.5 M potassium sulfate (K_2SO_4) extractions. We combined soil and extractant (ratio of 1 g dry soil:5 mL extractant) in plastic bottles, reciprocally shook the slurry for 1 h at 120 rpm, and then gravity filtered it through Fisher G6 (1.6 μm pore size) glass fiber filters, followed by colorimetric detection of nitrite (NO_2^-) + nitrate (NO_3^-) and ammonium (NH_4^+) in the filtrate (Hood Nowotny et al., 2010,Soil Science Society of America Journal 74, 1018-1027) using a microplate spectrophotometer (Biotek Epoch, Winooski, VT, USA). Filtrate was also analyzed for dissolved organic C (referred to hereafter as extractable organic C) and total dissolved N via combustion and oxidation followed by detection of the evolved CO_2 and N oxide gases on a Formacs HT TOC/TN analyzer (Skalar, Breda, The Netherlands). Extractable organic N was then computed as total dissolved N in filtrate minus extractable mineral N (itself the sum of extractable NH_4-N and NO_2-N + NO_3-N). We determined soil total C and N from dried, milled subsamples subjected to elemental analysis (ECS 4010, Costech, Inc., Valencia, CA, USA) at the University of South Florida Stable Isotope Laboratory. Median concentration of inorganic C in unvegetated surface soil at our sites is 0.5 % of soil mass (Anderson, 2019, Univ. of South Florida M.S. thesis via methods in Wang et al., 2011, Environmental Monitoring and Assessment 174, 241-257). Inorganic C concentrations are likely even lower in our samples from under vegetation, where organic matter would dilute the contribution of inorganic C to soil mass. Nevertheless, the presence of a small inorganic C pool in our soils may be counted in the total C values we report. Extractable organic C is necessarily of organic C origin given the method (sparging with HCl) used in detection. Active C and N represent the fractions of organic C and N that are mineralizable by soil microorganisms under aerobic conditions in long-term soil incubations. To quantify active C and N, 60 g of field-moist soil were apportioned from each composite sample, placed in a filtration apparatus, and incubated in the dark at 25 °C and field capacity moisture for 365 d (as in Lewis et al., 2014, Ecosphere 5, art59). Moisture levels were maintained by frequently weighing incubated soil and wetting them up to target mass. Daily CO_2 flux was quantified on 29 occasions at 0.5-3 week intervals during the incubation period (with shorter intervals earlier in the incubation), and these per day flux rates were integrated over the 365 d period to compute an estimate of active C. Observations of per day flux were made by sealing samples overnight in airtight chambers fitted with septa and quantifying headspace CO_2 accumulation by injecting headspace samples (obtained through the septa via needle and syringe) into an infrared gas analyzer (PP Systems EGM 4, Amesbury, MA, USA). To estimate active N, each incubated sample was leached with a C and N free, 35 psu solution containing micronutrients (Nadelhoffer, 1990, Soil Science Society of America Journal 54, 411-415) on 19 occasions at increasing 1-6 week intervals during the 365 d incubation, and then extracted in 0.5 M K_2SO_4 at the end of the incubation in order to remove any residual mineral N. Active N was then quantified as the total mass of mineral N leached and extracted. Mineral N in leached and extracted solutions was detected as NH_4-N and NO_2-N + NO_3-N via colorimetry as above. This incubation technique precludes new C and N inputs and persistently leaches mineral N, forcing microorganisms to meet demand by mineralizing existing pools, and thereby directly assays the potential activity of soil organic C and N pools present at the time of soil sampling. Because this analysis commences with disrupting soil physical structure, it is biased toward higher estimates of active fractions. Calculations. Non-mobile C and N fractions were computed as total C and N concentrations minus the extractable and active fractions of each element. This data package reports surface-soil constituents (moisture, fines, SOM, and C and N pools and fractions) in both gravimetric units (mass constituent / mass soil) and areal units (mass constituent / soil surface area integrated through 7.6 cm soil depth, the depth of sampling). Areal concentrations were computed as X × D × 7.6, where X is the gravimetric concentration of a soil constituent, D is soil bulk density (g dry soil / cm^3), and 7.6 is the sampling depth in cm.
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