Metrics details The Calcium Silicate Hydrate (C-S-H) nucleation is a crucial step during cement hydration and determines to a great extent the rheology Recent evidence indicates that the C-S-H nucleation involves at least two steps the nature of the primary particles and their stability or how they merge/aggregate to form larger structures is unknown to investigate the structure and formation of C-S-H primary particles (PPs) from the ions in solution and then discuss a possible formation pathway for the C-S-H nucleation Our simulations indicate that even for small sizes the most stable clusters encode C-S-H structural motifs and we identified a C4S4H2 cluster candidate to be the C-S-H basic building block We suggest a formation path in which small clusters formed by silicate dimers merge into large elongated aggregates the C-S-H basic building blocks can be formed within the aggregates the reaction of silicate dimers with the portlandite PPs will induce a topochemical phase transition to form C-S-H monolayers we will investigate the structure and stability of C-S-H primary particles using atomistic simulation methods specifically DFT and evolutionary algorithms (EA) Our goal is to determine the structure of energetically accessible small clusters (with the composition nCaO + nSiO2 + xH2O where n = 1 4) that might appear during the initial stages of C-S-H nucleation we compare the structural resemblances of the PPs with the bulk C-S-H and study their aggregation kinetics with MD Based on our simulations and the available experimental data we suggest a formation pathway for the C-S-H nucleation The general belief is that the prevalent silicate species in the pore solution are CaSiO4H2 complexes (log K = 4.6) and the extra Ca will be in the form of a hydrated Ca2+ ion so we assume as a working hypothesis that the CSHx complexes will aggregate and form dimeric species (C2S2Hx) We cannot rule out that additional Ca+2 ions will participate in the aggregation forming dimeric clusters with Ca/Si > 1 given the structure of the C2S2Hx that we will present in Discussion (2) we consider that the existence of Ca/Si = 1 dimers is plausible additional Ca should take part in the C-S-H structure in the aggregation stage for the MD simulations in Discussion (5) we added Ca(OH)2 in the solution to increase the Ca/Si ratio to 1.5 a value closer to the actual C-S-H composition First we seek for the most stable coordination complex of a silicate monomer with one Ca ion Following the above criteria we chose CSH10 as initial stoichiometry which would corresponds to a neutral CaSi(OH)2O2 system plus 7 or 8 water molecules It must be notice that the EA does not assume any charge state for the different units in the complex it just keeps the atoms in the system constant Therefore the EA can explore both complexes with Si-OH + Ca-OH or Si-O-Ca + water Each point represents a different primary particle (PP) and the distances between points represent the structural similarity between the PPs the more similar their structures are and vice versa The colormap in (a) represents the energy difference ΔE with respect to the lowest energy PP The atomic structure of the best PPs are also shown The regions I and II each represent a group of low energy PPs with similar structural properties b–g Collection of structural properties of the clusters color mapped into the same Sketch-map nCa−O and nSi−O−Ca represent respectively the number of Si-O dSi−Ca represents the distance between the Si and Ca atom in the PP n\({}_{{{{{{{{{\rm{H}}}}}}}}}_{2}{{{{{{{\rm{O}}}}}}}}}\) and nOH represent the number of water molecules and hydroxil groups in the PP Source data are provided as a Source Data file Decreasing the water content does not change the formed complexes substantially: the best clusters also contain a silicate tetrahedron linked to the Ca atom but the coordination of the Ca atoms decreases due to the lack of water molecules their conformation is fixed and the protonation state is not the same as the the predicted by EA The next step in the C-S-H nucleation would be the formation of primary particles by the interaction (merging) of complexes in solution we have explored the most stable PPs for the stoichiometry C2S2H20 At this stage is clear the potential of EA to unravel the structure of the PPs: the complexes from “CSHx complexes” have a relatively simple structure that can be guessed by chemical intuition we do not need to assume any initial structure or feature and the global optimization will lead us to the lowest energy structures nSi−O−Si and nCa−O−Ca represent respectively the number of Si-O We performed simulations decreasing the water content of the C2S2Hx cluster from x = 20 to x = 12, 4 (see the SI) but the main structure of the silicate arrangement remains with the two Ca atoms linked to each other and to silicate monomers or dimmers We found that the number of low-energy structures containing monomers increases as the water content decreases probably to maximize the coordination of Ca atoms The colormap in (a–f) represents the energy difference ΔE with respect to the lowest energy PP for each stoichiometry b–d Collection of structural properties of the clusters color mapped into the same Sketch-map for C4S4H8 PPs e The different silicate arrangements found in the PPs g–i Collection of structural properties of the clusters color mapped into the same Sketch-map for C4S4H2 PPs nchain shows the silicate arrangement as shown in (e) perpendicular in the former and parallel in the latter The fact that EA predict a low-energy structure with the same atomic arrangement as tobermorite strongly suggests that the C4S4H2 cluster could indeed be the C-S-H basic building block After determining the lowest energy clusters for the different sizes we explored different steps of the possible C-S-H aggregation pathway we computed the sequential enthalpy of formation of the complexes/PPs formed by merging smaller structures the lowest energy cluster was relaxed using DFT including an implicit solvent effect e Evolution of the averaged aggregate size < S > over time The size is defined in terms of number of atoms that for the aggregate normalized by the number of atoms in a primary particle (PP) S0 f Average water loss < H2O > from the aggregates over time g Asphericity of the aggregates as a function of the gyration radius Rg This suggests that the silicate dimerization stage is the critical step that directs the formation of the C-S-H gel towards tobermorite-like lamellar structures The mass density was ρ = 1.02 ± 0.02 g cm−3 which indicates a liquid-like nature of the amorphous spheroids We observe that the C2S2H20 PPs do not dissociate the calcium atoms remain attached to the silicate dimers with primary species that form aggregates without any coherent diffraction signal despite their large size The solvation water that we observe in this work may be the reason for the misalignment and disorder between the aggregates and the water contribution was eliminated by subtracting the weighted G(r) of bulk water Below 3 Å the peaks correspond to the first Ca-O and therefore are similar for the aggregates and the bulk systems Above 3 Å the peaks for the aggregate are dominated by the contribution of the heavy atoms Ca and Si and Ca-Si signals are considerably stronger than in C-S-H and tobermorite and the correlation is lost after 6 Å due to the shape of the particles The lack of defined peaks for the X-O pairs beyond the bonded atoms suggest a considerable disorder: the short-range coordination of metal cations is the expected one with SiO4 silicate tetrahedra and CaO6 heptahedra but the orientation and arrangement of these species does not have any medium-range order we cannot state that the aggregates present a C-S-H-like structure yet the mean number of water molecules attached to the aggregates decreases with time The decrease is due to the aggregation itself since the PPs lose water molecules from their hydration shells and also due to rearrangements within clusters including condensation reactions between the C2S2H20 and Ca(OH)2 Despite only observing the initial steps of dehydration we suggest that C4S4H2 clusters will be progressively formed within the aggregates leading to crystallization The suggested nucleation path can be described in 4 steps the two initial ones within the first stage of nucleation: so the formation of the complexes is expected to be fast The complexes merge into C2S2H20 primary particles (PPs) The silicate dimers are formed via condensation reaction within the PP The large aggregates slowly dehydrate, and C4S4H2 structures are formed within them. These C4S4H2 structures present a tobermorite-like structure and can be seen as the basic building block for the C-S-H formation. Finally, a slow process of dehydration and rearrangement of the C4S4H2 within the aggregates will result in the C-S-H layers. If present, branched silicate oligomers should de-polimerise during this crystallization stage to form linear chains. and represent the connectivity of the silicate groups we have used atomistic simulation methods to investigate the structure and formation of C-S-H complexes and PPs and then discuss a possible C-S-H nucleation pathway based on the simulations and evidence from the literature This work is the first computational step in the challenging path toward understanding and controlling C-S-H nucleation and have significant implications for advancing in the design and optimization of cementitious materials A deeper understanding of the nucleation mechanisms can aid in tailoring additives to regulate it we must keep in mind that the actual nucleation path may be different depending on the C-S-H formation process (synthetic from cement hydration) and the presence of guest ions the role of these variables should be explored as well as seek for a more detailed and quantitative description of the aggregate formation and the dehydration/crystallization stage Four independent simulations were done starting from different configurations generated by random packing of 8 C2S2H20 clusters and 8 Ca(OH)2 molecules with 700 H2O molecules in a 7 nm side box After 200 ps for density equilibration in the NPT ensemble the simulations were run for 15 ns in the NPT ensemble with a 0.2 fs timestep and using the Verlet integrator and the output data of all the structures are provided as a supplementary material All the software used in this work is open source No specific software was developed for this work Advances in understanding cement hydration mechanisms Hydration of tricalcium silicate in the presence of synthetic calcium–silicate–hydrate Nucleation seeding with calcium silicate hydrate–a review Experimental investigation of calcium silicate hydrate (C-S-H) nucleation A comprehensive review of C-S-H empirical and computational models Two-step nucleation process of calcium silicate hydrate A tem study on the very early crystallization of C-S-H in the presence of polycarboxylate superplasticizers: transformation from initial c-s-h globules to nanofoils Study on the early crystallization of calcium silicate hydrate (C-S-H) in the presence of polycarboxylate superplasticizers New insights into the non-classical nucleation of C-S-H The atomic-level structure of cementitious calcium silicate hydrate Prenucleation clusters and non-classical nucleation Nonclassical nucleation and growth of inorganic nanoparticles A review of classical and nonclassical nucleation theories Formation of calcium sulfate through the aggregation of sub-3 nanometre primary species The initial stages of template-controlled CaCo3 formation revealed by Cryo-TEM Pre-nucleation clusters as solute precursors in crystallisation Microscopic evidence for liquid-liquid separation in supersaturated CaCo3 solutions Stable prenucleation mineral clusters are liquid-like ionic polymers Water dynamics from THz spectroscopy reveal the locus of a liquid–liquid binodal limit in aqueous caco3 solutions Ion-association complexes unite classical and non-classical theories for the biomimetic nucleation of calcium phosphate Molecular mechanisms of [Bi6O4 (OH)4](No3)6 precursor activation Atomistic structures and dynamics of prenucleation clusters in MOF-2 and MOF-5 synthesis The structure of CaSo4 nanorods: the precursor of gypsum Simulation of calcium phosphate prenucleation clusters in aqueous solution: association beyond ion pairing Understanding the kinetics of barium sulfate precipitation from water and water–methanol solutions A TEM study on the very early crystallization of C-S-H in the presence of polycarboxylate superplasticizers: transformation from initial C-S-H globules to nanofoils Nonclassical crystallization of calcium hydroxide via amorphous precursors and the role of additives Role of impurities in the kinetic persistence of amorphous calcium carbonate: a nanoscopic dynamics view Modeling of aqueous species interaction energies prior to nucleation in cement-based gel systems Ab initio metadynamics simulations on the formation of calcium silicate aqua complexes prior to the nuleation of calcium silicate hydrate On the formation of cementitious C-S-H nanoparticles A potential C-S-H nucleation mechanism: atomistic simulations of the portlandite to C-S-H transformation Nagra/psi chemical thermodynamic data base 01/01 Thermodynamic modelling of the hydration of portland cement Characterization of silicate monomer with sodium calcium and strontium but not with lithium and magnesium ions by fast atom bombardment mass spectrometry Atomistic simulations of silicate species interaction with portlandite surfaces Theoretical reaction pathways for the formation of [Si (OH)5]1− and the deprotonation of orthosilicic acid in basic solution Quantitative x-ray pair distribution function analysis of nanocrystalline calcium silicate hydrates: a contribution to the understanding of cement chemistry Local structure and ca/si ratio in C-S-H gels from hydration of blends of tricalcium silicate and silica fume Understanding silicate hydration from quantitative analyses of hydrating tricalcium silicates A comprehensive study on the dominant formation of the dissolved Ca(OH)2(aq) in strongly alkaline solutions saturated by Ca(ii) Thermochemistry of aqueous silicate solution precursors to ceramics Water is the key to nonclassical nucleation of amorphous calcium carbonate Hydration of calcium oxide surface predicted by reactive force field molecular dynamics Crystal structure prediction using ab initio evolutionary techniques: principles and applications How evolutionary crystal structure prediction works and why New developments in evolutionary structure prediction algorithm USPEX The ReaxFF reactive force-field: development Reaxffsio reactive force field for silicon and silicon oxide systems Confined water dissociation in microporous defective silicates: mechanism Gulp: A computer program for the symmetry-adapted simulation of solids The SIESTA method for ab initio order-n materials simulation Generalized gradient approximation made simple Semiempirical gga-type density functional constructed with a long-range dispersion correction Dielectric relaxation of dilute aqueous NaOH Efficient diffuse function-augmented basis sets for anion calculations the 3-21+ g basis set for first-row elements Comparing molecules and solids across structural and alchemical space How to quantify energy landscapes of solids Simplifying the representation of complex free-energy landscapes using sketch-map Chemiscope Visualization Tool. Chemiscope: Interactive Structure/Property Explorer for Materials and Molecules. https://chemiscope.org/ (2022) LAMMPS—a flexible simulation tool for particle-based materials modeling at the atomic Manzano, H. Hegoimanzano/reaxff_cement: v01. Zenodo https://doi.org/10.5281/zenodo.8379302 (2023) Nanoscale shear cohesion between cement hydrates: the role of water diffusivity under structural and electrostatic confinement Download references was supported by the “Departamento de Educación Política Lingüística y Cultura del Gobierno Vasco” (Grant No the “Ministerio de Ciencia e Innovación" (PID2019-106644GB-I00 and TED2021-130860B-I00) the University of the Basque Country UPV/EHU (Colab22/06) and the Laboratory for Trans-border Cooperation “Aquitaine-Euskadi Network in Green Concrete and Cement-based Materials” (LTC-Green Concrete) The authors thank for technical and human support provided by SGIker (UPV/EHU/ ERDF acknowledges the financial support from the University of the Basque Country UPV/EHU (PIF17/118) the financial support from the Basque Country Government (PRE_2019_1_0025) The authors declare no competing interests Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations Download citation DOI: https://doi.org/10.1038/s41467-023-43500-y Anyone you share the following link with will be able to read this content: a shareable link is not currently available for this article Sign up for the Nature Briefing newsletter — what matters in science The dates displayed for an article provide information on when various publication milestones were reached at the journal that has published the article activities on preceding journals at which the article was previously under consideration are not shown (for instance submission All content on this site: Copyright © 2025 Elsevier B.V., its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply. Environmental Informatics and Remote Sensing Volume 9 - 2021 | https://doi.org/10.3389/fenvs.2021.616319 which provide valuable ecosystem services such as flood mitigation and carbon sequestration converting available upland into salt marsh In the coastal-plain surrounding Chesapeake Bay conversion of coastal forest to salt marsh is well-documented and may offset salt marsh loss due to sea level rise Land slope at the marsh-forest boundary is an important factor determining migration likelihood the standard method of using field measurements to assess slope across the marsh-forest boundary is impractical on the scale of an estuary we developed a general slope quantification method that uses high resolution elevation data and a repurposed shoreline analysis tool to determine slope along the marsh-forest boundary for the entire Chesapeake Bay coastal-plain and find that less than 3% of transects have a slope value less than 1%; these low slope environments offer more favorable conditions for forest to marsh conversion we combine the bay-wide slope and elevation data with inundation modeling from Hurricane Isabel to determine likelihood of coastal forest conversion to salt marsh This method can be applied to local and estuary-scale research to support management decisions regarding which upland forested areas are more critical to preserve as available space for marsh migration the mechanisms that control this process are less firmly established Additional research is needed to better understand the interplay between slope and other factors influencing migration rates These methods are time and resource intensive which make regional assessments impractical generated from remote sensing methods such as lidar is a more appropriate option for regional analyses this requires a new method to calculate slope across land use boundaries land cover and land use datasets that improve the precision of this method are available for the region Ongoing field studies of marsh migration in the region provide measurements of slope across the marsh-forest boundary in several locations to assess the accuracy of our results We also discuss additional factors that contribute to marsh migration and demonstrate the use of a dynamic inundation model to estimate marsh migration likelihood This method quantifies the geospatial variability of slope across the marsh-forest boundary that can be applied both locally and regionally to provide valuable information to land managers for prioritizing acquisition of coastal forests to allow for future marsh transgression The method was developed using ArcDesktop version 10.6.1 and the Digital Shoreline Analysis Software (DSAS) version 5.0 (Himmelstoss et al., 2018) All data layers used in this study were converted to the same projected coordinate system North American Datum (NAD) 1983 Universal Transverse Mercator (UTM) Zone 18N Marsh coverage in the coastal-plain surrounding the Chesapeake Bay was created by combining the Maryland and Virginia state marsh extents Forest coverage was obtained from the Chesapeake Conservancy’s Chesapeake Bay High-Resolution Land Cover and Land Use Data Projects datasets (Chesapeake Conservancy, 2018a; Chesapeake Conservancy, 2018b) The land cover dataset is based on land cover conditions in the National Agriculture Imagery Program images from 2013/2014 The land use dataset was created from the land cover dataset that was then further modified using 13 ancillary datasets Accuracy of the dataset is discussed in Results We developed and tested our slope quantification method along the coast of Chesapeake Bay, United States (Figure 1). The Chesapeake Bay is one of the largest estuaries in the world, draining 166,000 km2 of watershed across 6 states and Washington, D.C. (Perry et al., 2001). The Bay is microtidal with a maximum mean tidal range of approximately 1 m near the mouth (Perry et al., 2001) FIGURE 1. Study area with the NWI estuarine intertidal emergent wetlands in teal and forest extent obtained from Chesapeake Conservancy Land Use and Land Cover datasets in tan. Inset has been rotated 90° clockwise from actual position and is the same location as Figure 2 High rates of sea level rise force ecosystems to adapt on a shorter time scale which makes the Chesapeake Bay an ideal location for studying marsh-forest conversion on event-based and decadal timescales Due to the large geographic extent and density of marsh-forest boundaries in the study area, the analyses were performed in 10 tiles (2 columns x 5 rows) of the total extent (Molino et al., 2020) Marsh extent was based on the NWI categorization of “Estuarine Intertidal Emergent” wetlands The original projection was NAD 1983 Albers and we converted it to UTM Zone 18N The forest extent was determined by merging the areas classified as “forest” from the land use dataset and the areas classified as “tree canopy and shrubland” from the land cover dataset Both raster datasets were projected from their original United States Contiguous Albers Equal Area Conic USGS version projection to UTM Zone 18N The land cover and land use forest rasters were converted to shapefiles and merged to create a single forest layer Any overlap between the wetlands layer and forest layer was assumed to be wetlands as later verified by examining aerial images Forest polygons that were within 10 m of wetlands were considered potential migration zones for marshes and their boundaries were considered marsh-forest boundary Interior holes in the forest polygons were removed to limit the selection to the exterior forest boundaries were usually from a house or pond inside the forested area forest polygons with areas less than 900 m2 were excluded from analysis These polygons represented 1.5% of the total forest area considered in the study While they were present across the study area more were removed from the area to the east of Chesapeake Bay Once the forest polygons representing marsh-forest boundary were identified, multiple steps were taken to simplify the geometry created when the forest raster was converted to polygons in a previous step (Molino et al., 2020) Buffers were created inside the forest polygons to remove complex edge features and then buffers were created back out to the original extent Overlapping forest features created from the buffering were merged which removed dissecting roads This was followed by a polynomial approximation with exponential kernel (PAEK) smoothing with a 30 m tolerance to reduce sharp angles along the boundaries The sharp angles were often a remnant of the original forest raster file which approximates a forest edge using square pixels which is necessary to reduce the file size and processing time in subsequent steps We repurposed the USGS Digital Shoreline Analysis System (DSAS) version 5.0 to cast transects perpendicular across the marsh-forest boundary. Although predominantly used to compute changes in beach shorelines, DSAS has previously been used to cast transects at the marsh-forest boundary (Smith, 2013) DSAS requires a baseline from which to cast perpendicular transects and shorelines to determine the length of transects As DSAS was created to study shoreline change of beaches we were interested in the slope values within 10 m of the marsh-forest boundary therefore we created a “shoreline” and a “baseline” on opposite sides of the marsh-forest boundary we first generalized the marsh-forest boundary by smoothing with a PAEK algorithm with a 30 m tolerance and then created a 10 m offset outside and inside of the boundary to define a shoreline and a baseline As these polyline features extend for the entire perimeter of the original forest polygon they include areas of the forest which do not border marsh Transects cast along these areas are removed in a later step We chose 20 m transects to increase the likelihood that this method captured the marsh-forest boundary in scenarios where the boundary based on the geospatial data might have been offset from the physical boundary due to inaccuracies in the original marsh and forest files or due to the smoothing algorithm (Marsh-Forest Boundary) Following the requirements in the DSAS User Guide (Himmelstoss et al., 2018) we set transect spacing to 30 m apart along the baseline with a smoothing distance of 0 m DSAS requires that all resulting transect files be saved in an ArcGIS personal geodatabase The resulting transect file is limited in size to approximately 65,000 transects per DSAS run If the estimated number of transects (total forest polygon perimeter for a subregion divided by the transect interval) is larger than this number the subregion must be divided into sub-subregions the parameters used in this section of the study such as transect length and distance between transects were customized for the Chesapeake Bay coastal-plain and can be modified for other regions with different coastal morphology and marsh-forest characteristics we removed any transects cast further than 10 m from salt marsh using the estuarine intertidal emergent wetlands shapefile created in a previous step We also removed any transects which were cast across artificial forest edges created when we split the polygons into subregions and sub-subregions as these did not reflect a true marsh-forest boundary Using the “Add Surface Information” tool in ArcMap, transects were then assigned an average slope in percent rise based on the TBDEM (Figure 2) A single slope for each transect was calculated from the weighted average of slopes between 1 m cells that the transect crosses Transects with a slope value of exactly 0 were removed as this meant they spanned areas that had artificial elevation data Transects that have very low slope are typically not exactly 0 a value of exact 0 reflects a transect located entirely over an area with a single fill value for elevation The origin of the fill values in the TBDEM is discussed in Uncertainty and Completeness FIGURE 2. Location of marsh-forest boundary is the same as the inset in Figure 1 (A) Shoreline (yellow) and baseline (pink) input files for DSAS set 20 m apart are cast with a 30 m spacing (C) Removed extraneous transects cast between forest and non-marsh land types and assigned remaining transects a slope value from TBDEM (indicated by color gradient of green Finally, transects from each tile and subregion were merged into a single dataset that describes the geospatial distribution of slope across the Chesapeake Bay coastal-plain (Molino et al., 2020) (Figure 3) Average slope (percent rise) along transects across marsh-forest boundaries throughout the Chesapeake Bay coastal-plain Areas of artificial elevation also occurred where the underlying source datasets for the TBDEM were extrapolated to a 1 m resolution from a lower resolution We used a focal statistics tool in ArcMap to identify these areas and the impacted transects Transects spanning areas with fill values represent 2.5% of the entire dataset Transects that partially overlap areas with artificial elevation values from either of these processes have been left as part of the dataset for future updates as new TBDEM data become available these transects are not considered during our analysis of the slope dataset nor the assessment of marsh migration likelihood We did not include transects with a negative elevation value at the midpoint in our analysis given that these commonly reflected artifacts from hydro flattening or processing steps This impacted less than 10% of our transects this method of determining slope along the marsh-forest boundary provides the first geospatial product of slope values across the entire Chesapeake Bay coastal-plain As more accurate information becomes available the marsh-forest boundary and slope values themselves can be updated if extreme accuracy is required for localized analyses of specific forested areas this method can easily be scaled down and used with site-specific elevation and land cover data We conducted several assessments to determine how the parameters set in DSAS influence the slope values of the transects Given that the parameter values we chose were generalized to work for the entire region with its highly variable geomorphology we wanted to understand how altering these parameters might change our results Each test was conducted on two arbitrarily selected marsh-forest boundaries one in a higher slope environment on the western side of Chesapeake Bay (sample boundary point: 37.675206°N 76.450971°W) and one in a low slope environment on the Delmarva peninsula (sample boundary point: 37.852614°N The first test assessed the effect of transect resolution transects along the marsh-forest boundary in both locations were cast at 20 and 30 m resolutions The second test assessed how the placement of the transects influenced the results by shifting the transects by 15 m we also assessed how smoothing forest polygons influenced the slope values of the intersecting transects to assess how the vertical accuracy of the TBDEM influences the transect slope we took elevation measurements in the field at three locations around Chesapeake Bay which represent low a GNSS base station was set on a tripod over a temporary benchmark set up near the transect The wooden stake used for the benchmark was driven into the marsh approximately 1 m in a position with open skies to the south for good satellite coverage The base station collected satellite readings continuously for approximately 4 h while a GNSS rover and total station were connected to the base station in order to conduct an integrated survey a topography survey was conducted perpendicular to the marsh-forest boundary that gives latitude and elevation with an average precision of 0.0092 m in the horizontal 0.0109 m in the vertical dimensions and 0.0360 m in terms of elevation (averages based on fifteen surveys completed in the summer of 2019) The start and end points for the low slope transect are (38.2146°N 75.8094°W) and (38.21458°N for the medium slope transect (38.40398°N 75.98234°W) and (38.4040385°N and for the high slope transect (37.94665°N 76.90067°W) and (37.94657°N We then compared the average percent rise along those transects to the slope value determined from the TBDEM are an example of a cluster of low slope values in the dataset (A) Average slope of transects within elevation bins where R2 = 0.99 p<0.001 and (B) percent of total transects in each elevation bin Median slope value of transects within 10 regions comprised of the coastal counties surrounding the Chesapeake Bay Locations of the two test sites for the accuracy assessments are depicted by white triangles Locations of the three field transects used to determine vertical uncertainty are depicted by black circles The lowest slope values across the marsh-forest boundary are in region 7 which has median slope of 2.6% (Figure 5). The highest slope values are located in region 6 which has a median slope of 6.3% (Figure 5) The results of these tests lead to the conclusion that the parameters and processing steps do not strongly influence the slope value for transects produced by this method Results of accuracy assessments for slope values at two test locations The test location on the Delmarva Peninsula (37.723705°N 76.460207°W) is representative of low slope environments; the test location on the western shore of Chesapeake Bay (37.870196°N 75.642964°W) is representative of higher slope environments along river channels Additionally, in our assessment of how vertical accuracy of the TBDEM influences the transect slope, the average percent rise calculated for the transects generated in ArcGIS corresponded well with slope values of those taken at the corresponding field locations, represented by black circles (Figure 5) While there was a vertical offset in the data the transect with the lowest slope from the field data also had the lowest slope using the TBDEM This vertical offset ranged from −0.2 m to 0.1 m at points along the transects with the TBDEM on average 0.01 m higher than the field measurements The difference in slope between the field data and TBDEM altered the percent rise of the transects between 0.7 and 1.1% rise Using this slope quantification method, we have created an estuary-wide dataset of slope values across marsh-forest boundaries in the Chesapeake Bay coastal-plain. Interestingly, less than 3% of transects cross boundaries with a slope value considered favorable for forest to marsh conversion. The majority of these transects are located on the Virginia portion of the Delmarva peninsula (region 10 on Figure 5) where salt marsh gently slopes upward for kilometers into wide expanses of coastal forest Given the key role of slope in controlling marsh migration rates this has significant implications for directing conservation efforts throughout the Chesapeake Bay coastal plain It is not uncommon in our dataset to see transects with unexpectedly high slopes across the marsh-forest boundary where the forest abuts farmland on the opposite side berms were likely built to protect the farmland from inundation and this artificially higher land provided favorable conditions for forest growth As these features were put in by the individual landowners and they are often difficult to identify from aerial imagery A dataset of berms and other built barriers would be invaluable to an assessment of migration potential this method offers the first step at identifying these structures for future work assessing barriers to marsh migration in the region Simple estimates of marsh migration rates throughout Chesapeake Bay can be calculated using the median slope (4.0%) from this dataset and modern sea level rise rates in Chesapeake Bay of 4–10 mm/yr (Ezer and Corlett, 2012) This predicts that salt marsh will transgress inland at rates of 0.1–0.25 m/yr Given the wide variation of slope values discussed above these rates will range significantly throughout the coastal plain Migration rates have the potential to reach meters per year on the Delmarva peninsula while no migration may occur where natural or man-made barriers exist inland Our ultimate goal with the establishment of this method is to encourage analysis of marsh migration on an estuary-scale using slope data alongside other factors to assess marsh migration potential We extracted maximum storm inundation depth (meters) and duration of storm inundation (hours) at the midpoint of each slope transect from the ADCIRC datasets. Then these data were assessed in combination with the slope dataset to assign migration likelihood at each location. The values in all three datasets were divided into 5 categories, which were assigned a score of 0–4 corresponding to values that reflect an increase in migration likelihood (Table 2) with 0 being little to no influence on migration and 4 a large increase in migration likelihood A score of 0 reflects the lowest likelihood of marsh migration while a score of 4 represents the highest likelihood based on these three factors we further subdivided the 1–20% category (steep upland slope) into two bins A number of small-scale berms built by homeowners to protect their land from inundation were detected by our slope quantification method (Results); these structures range in slope from about 5 to 20% While not all transects with a slope between 5 and 20% cross berms this category acknowledges a reduction in migration potential as the slope increases past 5% regardless of if a manmade barrier exists or not Scores for all three variables at each point were added together and averaged for a final score of marsh migration potential that ranged from 0 to 4 This example stands as one application of the method described to determine slopes across the marsh-forest boundary and how it might be used in ongoing research Marsh migration potential in the Chesapeake Bay We have identified several additional data layers worth examining for more in-depth future marsh transgression potential indexes: • Salinity: Modeling systems capable of nowcasting and forecasting salinity levels for individual estuaries would further inform inundation data • Sea level rise: The National Oceanic and Atmospheric Administration (NOAA) has released global and regional sea level rise predictions for multiple probabilistic ranges which can be examined locally for estuary-specific studies (Sweet et al., 2017) • Storm inundation: The ADCIRC Prediction System developed at the University of North Carolina at Chapel Hill has high resolution inundation data for historic storm events that impacted the Atlantic Coast. Additionally, the North Atlantic Coastal Comprehensive Study (NACCS) by the U. S. Army Corp of Engineers, has produced over 1,000 model runs of synthetic tropical cyclones in the North Atlantic (Nadal-Caraballo et al., 2015) inundation duration and frequency can be obtained from both datasets to further inform migration potential further assessment of how these variables impact geospatial patterns of marsh migration and if there are certain threshold levels (for example Such work would also benefit from additional studies measuring marsh migration rates across the Chesapeake Bay coastal-plain to further corroborate our results Our method would be well suited to quantify slope across land use type boundaries to add to these probability assessments such as land cover/land use data from more recent imagery or an updated TBDEM the methodology is easily replicable to update the marsh-forest boundary or the slope values land managers interested in buying forested areas for conservation efforts can incorporate this method to determine the most likely area for marsh migration inland Those interested in marsh migration in the previous century could use historical photographs or topographic sheets to identify the marsh-forest boundary and assign slope data from older elevation datasets Other major estuaries where marsh migration studies are underway (e.g. Narragansett Bay) can supplement their research efforts with this method the slope quantification method is not restricted to use at the marsh-forest boundary; this method can be applied to marsh boundaries with other upland environments such as agricultural lands this slope quantification method and the published dataset are the first of its kind and provide critical information on marsh survival to a rapidly growing field of study We recognize that the number of ground-truthed transects available for our accuracy assessment represents only three locations out of over 200,000 transects in our dataset We acknowledge that this method is not a substitute for the accuracy of field measurements as it is limited by the precision and accuracy of the input datasets this method does provide a reasonable and consistent estimate of slopes across an area too extensive for field work and establishes a starting point for more targeted studies of high interest locations the reproducible workflow presented in this study can be applied more locally allowing for utilization of higher resolution datasets and application of numerous field measurements for verification purposes Our goal is to have this method and its future applications better inform land managers and others interested in conservation to ensure coastal salt marshes continue to provide essential ecosystems services in the coming decades and JC designed the overall study; GM and ZD developed and applied the geospatial methods AA developed the oceanographic model analysis GM analyzed the results with aid from all authors JC collected and provided field data for accuracy assessment of results GM wrote the manuscript with feedback from all authors All authors provided critical feedback and helped shape the research Funding for this study was provided by the United States Geological Survey’s Coastal/Marine Hazards and Resources Program and Ecosystems Mission Area The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest 1https://tidesandcurrents.noaa.gov/sltrends/regionalcomparison.html?region=USNA Upslope Development of a Tidal Marsh as a Function of Upland Land Use PubMed Abstract | CrossRef Full Text | Google Scholar The Value of Estuarine and Coastal Ecosystem Services CrossRef Full Text | Google Scholar Beven, J., and Cobb, H. (2004). Tropical Cyclone Report: Hurricane Isabel. Available at: https://www.nhc.noaa.gov/data/tcr/AL132003_Isabel.pdf (Accessed Jun 23 Google Scholar Brinson, M. M., Christian, R. R., and Blum, L. K. (1995). Multiple States in the Sea-Level Induced Transition from Terrestrial Forest to Estuary. Estuaries 18, 648–659. Available at: https://www.jstor.org/stable/1352383 CrossRef Full Text | Google Scholar Historical Changes in the Vegetated Area of Salt Marshes CrossRef Full Text | Google Scholar Chesapeake Conservancy (2018a). Land Cover Data Project 2013/2014. Available at: https://chesapeakeconservancy.org/conservation-innovation-center/high-resolution-data/land-cover-data-project/ (Accessed September 5 Google Scholar Chesapeake Conservancy (2018b). Land Use Data Project 2013/2014. Available at: https://chesapeakeconservancy.org/conservation-innovation-center/high-resolution-data/land-use-data-project/ (Accessed September 6 Google Scholar Cowardin, L. M., Carter, V., Golet, F. C., and LaRoe, E. T. (1979). Classification of Wetlands and Deepwater Habitats of the United States. Washington, DC: Fish and Wildlife ServiceAvailable at: https://www.nrc.gov/docs/ML1801/ML18019A904.pdf Google Scholar Danielson, J., and Tyler, D. (2016). Topobathymetric Model for Chesapeake Bay Region - District of Columbia, States of Delaware. Maryland: Pennsylvania, and Virginia, 1859 to 2015. Available at: https://topotools.cr.usgs.gov/topobathy_viewer/dwndata.htm (Accessed January 29 Google Scholar Spatial Variability of Late Holocene and 20th Century Sea-Level Rise along the Atlantic Coast of the United States CrossRef Full Text | Google Scholar Barriers to and Opportunities for Landward Migration of Coastal Wetlands with Sea-Level Rise CrossRef Full Text | Google Scholar Is Sea Level Rise Accelerating in the Chesapeake Bay A Demonstration of a Novel New Approach for Analyzing Sea Level Data CrossRef Full Text | Google Scholar Sea Level Rise and the Dynamics of the Marsh-Upland Boundary CrossRef Full Text | Google Scholar Federal Geographic Data Committee (2013) Classification of Wetlands and Deepwater Habitats Forest Resistance to Sea-Level Rise Prevents Landward Migration of Tidal Marsh CrossRef Full Text | Google Scholar Rapid Land Cover Change in a Submerging Coastal County CrossRef Full Text | Google Scholar Digital Shoreline Analysis System (DSAS) Version 5.0 User Guide doi:10.3133/ofr2018117910.3133/ofr20181179 CrossRef Full Text | Google Scholar Modeling the Impact of Tidal Inundation on Submerging Coastal Landscapes of the Chesapeake Bay CrossRef Full Text | Google Scholar Modeling of Sea-Level Rise and Deforestation in Submerging Coastal Ultisols of Chesapeake Bay CrossRef Full Text | Google Scholar IPCC (2013). “Climate Change 2013: The Physical Science Basis” in Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change editors. T. F. Stocker, D. Qin, G.-K. Plattner, M. Tignor, S. K. Allen, J. Boschunget al. (Cambridge, United Kingdom: Cambridge University Press), 1535. Available at: https://www.ipcc.ch/report/ar5/wg1/ Google Scholar Sea-level Rise and Storm Surges Structure Coastal Forests into Persistence and Regeneration Niches PubMed Abstract | CrossRef Full Text | Google Scholar Sea-level Driven Land Conversion and the Formation of Ghost Forests CrossRef Full Text | Google Scholar Dynamics of an Estuarine Forest and its Response to Rising Sea Level CrossRef Full Text | Google Scholar Sea Level Driven Marsh Expansion in a Coupled Model of Marsh Erosion and Migration CrossRef Full Text | Google Scholar High-resolution Records of the Response of Coastal Wetland Systems to Long-Term and Short-Term Sea-Level Variability CrossRef Full Text | Google Scholar Climate Change Impacts in the United States: The Third National Climate Assessment CrossRef Full Text Wave Attenuation over Coastal Salt Marshes under Storm Surge Conditions CrossRef Full Text | Google Scholar Slope values across marsh-forest boundary in Chesapeake Bay region CrossRef Full Text Responses of Coastal Wetlands to Rising Sea Level doi:10.1890/0012-9658(2002)083[2869:rocwtr]2.0.co;2 CrossRef Full Text | Google Scholar Nadal-Caraballo, N. C., Melby, J. A., Gonzalez, V. M., and Cox, A. T. (2015). Coastal Storm Hazards from Virginia to Maine. Available at: https://apps.dtic.mil/dtic/tr/fulltext/u2/a627157.pdf (Accessed November 25 Google Scholar The Value of Coastal Wetlands for Flood Damage Reduction in the Northeastern United States PubMed Abstract | CrossRef Full Text | Google Scholar Pallai, C., and Wesson, K. (2017). Chesapeake Bay Program Partnership High-Resolution Land Cover Classification Accuracy Assessment Methodology. Available at: https://chesapeakeconservancy.org/wp-content/uploads/2017/01/Chesapeake_Conservancy_Accuracy_Assessment_Methodology.pdf (Accessed June 23 Google Scholar Pendleton, E. A., Williams, S. J., and Thieler, E. R. (2004). Coastal Vulnerability Assessment of Assateague Island National Seashore (ASIS) to Sea-Level Rise. Available at: https://pubs.usgs.gov/of/2004/1020/html/rank.htm (June 23 CrossRef Full Text | Google Scholar Perry, J. E., Barnard, T. A., Bradshaw, J. G., Friedrichs, C. T., Havens, K. J., Mason, P. A., et al. (2001). Creating Tidal Salt Marshes in the Chesapeake Bay. 170–191. Available at: https://www.jstor.org/stable/25736172 (Accessed October 17 Google Scholar Expansion of Tidal Marsh in Response to Sea-Level Rise: Gulf Coast of Florida CrossRef Full Text | Google Scholar Reed, D. J. (2002). Sea-level Rise and Coastal Marsh Sustainability: Geological and Ecological Factors in the Mississippi Delta Plain. Geomorphology 48, 233–243. Available at: www.elsevier.com/locate/geomorph CrossRef Full Text | Google Scholar Hotspot of Accelerated Sea-Level Rise on the Atlantic Coast of North America CrossRef Full Text | Google Scholar Sea-level Driven Acceleration in Coastal Forest Retreat CrossRef Full Text | Google Scholar Massive Upland to Wetland Conversion Compensated for Historical Marsh Loss in Chesapeake Bay CrossRef Full Text | Google Scholar The Role of Phragmites Australis in Mediating Inland Salt Marsh Migration in a Mid-Atlantic Estuary PubMed Abstract | CrossRef Full Text | Google Scholar Sweet, W. V., Kopp, R. E., Weaver, C. P., Obeysekera, J., Horton, R. M., Thieler, E. R., et al. (2017). Global and Regional Sea Level Rise Scenarios for the United States. Available at: https://tidesandcurrents.noaa.gov/publications/techrpt83_Global_and_Regional_SLR_Scenarios_for_the_US_final.pdf (Accessed August 10 CrossRef Full Text | Google Scholar Assessing Coastal Squeeze of Tidal Wetlands CrossRef Full Text | Google Scholar U. S. Fish and Wildlife Service (2018). National Wetlands Inventory: Wetlands Mapper. U.S. Department of the Interior, Fish and Wildlife Service. Washington, D.C. Available at: https://www.fws.gov/wetlands/ (Accessed September 20 Google Scholar Williams, K., Ewel, K. C., Stumpf, R. P., Putz, F. E., Workman, T. W., Williams, K., et al. (1999). Sea-Level Rise and Coastal Forest Retreat on the West Coast of Florida. United States. Ecology 80, 2045–2063. Available at: https://www.jstor.org/stable/176677 CrossRef Full Text | Google Scholar Ganju NK and Carr JA (2021) Quantifying Slopes as a Driver of Forest to Marsh Conversion Using Geospatial Techniques: Application to Chesapeake Bay Coastal-Plain Received: 12 October 2020; Accepted: 22 April 2021;Published: 17 May 2021 Copyright © 2021 Molino, Defne, Aretxabaleta, Ganju and Carr. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use distribution or reproduction in other forums is permitted provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited in accordance with accepted academic practice distribution or reproduction is permitted which does not comply with these terms *Correspondence: Grace D. Molino, Z2Rtb2xpbm9Admltcy5lZHU= †Present address: Virginia Institute of Marine Science Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher 94% of researchers rate our articles as excellent or goodLearn more about the work of our research integrity team to safeguard the quality of each article we publish FALMOUTH — The town election on May 17 will include contested races for Select Board and School Committee and ballot questions asking voters to OK spending $10 million to build a new fire station and $25 million to overhaul the sewage treatment plant Voters will also be asked to go on record against plans by the owners of Pilgrim Nuclear Power Plant to dump millions of gallons of radioactive water into Cape Cod Bay.  three candidates are running for two open seats: incumbent Douglas Brown six candidates are running for three seats: incumbent Melissa Keefe Town Clerk: Incumbent Michael Palmer will run uncontested.  Library Trustee: Incumbent Kathryn Elder and Mary Fran Buckley will run uncontested for two open seats.  Planning Board: Incumbents Patricia Kerfoot and Paul Dreyer will run uncontested for two open seats.  Town meeting members (Precinct 1): Nine candidates will run for nine open positions: Alfredo Aretxabaleta Aretxabaleta is the only non-incumbent.  Town meeting members (Precinct 2): 11 candidates will run for nine open positions: Charles Rader Town meeting members (Precinct 3): Eight candidates will run for nine open positions: Anthony Fusaro Town meeting members (Precinct 4): Nine candidates will run for nine open positions: Robert Baker Town meeting members (Precinct 5): 11 candidates will run for nine open positions: Janet Azarovitz Oshman and Brown are non-incumbents.  Town meeting members (Precinct 6): Nine candidates will run for nine open positions: James Morse Town meeting members (Precinct 7): Six candidates will run for nine open positions: Richard Bradley Town meeting members (Precinct 8): 12 candidates will run for nine open positions: John Barkley Town meeting members (Precinct 9): Eight candidates will run for nine open positions: David DuBois any empty precinct seats are filled first by write-in candidates The Falmouth ballot questions Question 1: This question is a Proposition 2 ½ debt exclusion to pay for designing and building a new fire station on Sandwich Road Voters approved borrowing $10 million for the station at the April 4 town meeting.  Question 2: Voters asked to approve another Proposition 2 ½ debt exclusion to pay for improvements to sewage treatment plant at Blacksmith Shop Road. Voters approved borrowing $24 million for the improvements at the April 4 town meeting.  Question 3: This question would ask the Select Board to communicate with state officials to work against any plans to dump radioactive water in Cape Cod Bay by Holtec Decommissioning International Holtec is the company in charge of the decommissioning of Pilgrim Nuclear Power Station.  Question 4: Voters asked to approve a charter amendment proposed at the Nov Article 2 would be amended to support the town’s current method of considering the capital improvement budget at the fall town meeting and the operating budget at spring town meeting Question 5: This question would approve a charter amendment proposed at the Nov.15 Article 2 would be amended to consolidate information about the town moderator’s responsibilities.  Question 6: This question would approve a charter amendment passed at the Nov. 15 Article III and Article VII would be amended to clarify the Select Board’s ability to appoint governmental bodies Question 7: This question would approve a charter amendment passed at the Nov Article 7 would be amended to clarify the Select Board’s sole responsibility of determining the size of governmental bodies.  Question 8: This question would approve a charter amendment passed at the Nov Article 7 would be amended to make sure that the town manager prepares a capital improvement plan consistent with the strategic plan and the local comprehensive plan.  Polls will be open 7 a.m. to 8 p.m Precinct 1: Town Hall, 59 Town Hall Square  Precinct 3: Falmouth High School Gymnasium, 874 Gifford St Anthony's Lodge Building,167 East Falmouth Highway Precinct 6: Falmouth High School Gymnasium Precinct 7: Waquoit Congregational Church Hall Precinct 8: Navigator Club, 55 Ashumet Road Precinct 9: Jewish Congregational Community Center, 7 Hatchville Road Completed ballots can be returned by mail with pre-paid envelopes received with the ballot OR placed in the town hall drop box located in front of town hall Asad Jung can be reached at ajung@capecodonline.com Ertzaintzak droga kontrolen kanpaina berezia jarri du martxan euskal errepideetan Neurria aste osoan zehar egongo da indarrean eta droga kontsumoaren gorakada eteten saiatzeko abiaraziko da azken urtean droga kontsumoak gora egin du aurten 238 euskal gidarik emaitza positiboak eman dituzte droga kontroletan eta datu horri iazko emaitza positiboa eman zuten 571 gidariren kopurua gehitu behar zaio Ertzaintzako Trafiko Alorreko adituen ustez datu kezkagarri horiei beste faktore batzuk gehitu behar zaizkie asteburuetan drogak kontsumitzea nabarmen areagotu izana eta substantzia ugari aldi berean kontsumitzearen fenomenoa egun hauetan errepideetan drogen kontrol zehatzak ugaritzearen helburua gidari arriskutsuak detektatzea da gazteak fenomeno horren arriskuaz kontzientziatzea Ertzaintzak txistu laginak erabiltzen ditu legez kanpoko substantziak antzemateko Laginak hodi xurgatzaile baten bidez jasotzen dira Gailuek detektatzen dituzten bost substantzietako edozeinetan (kokaina anfetaminak eta metanfetaminak) emaitza positiboa emate hutsak 500 euroko administrazio isuna eta gidabaimenean sei puntu kentzea dakar estupefaziente eta substantzia psikotropikoen kasuan hauek kontsumitu ondoren sei eta hamabi ordu geroago ere detekta daitezkeela faktore ezberdinek eragin dezakete organismo bakoitzak droga ezabatzeko behar duen denboran baita kontroletan detekta daitezkeen denbora tartean ere; faktore horien artean daude Debagoieneko albiste nabarmenenak eta azken ordukoak Whatsapp edo Telegram bidez jaso gura dituzu WHATSAPP: Bidali ALTA 688 69 00 07 telefono zenbakira –Whatsapp bidez– TELEGRAM: Batu zaitez @GoienaAlbisteak kanalera Zure posta elektronikoan asteburuko albiste nabarmenekin osatutako mezua jasoko duzu. Harpidetu zaitez debalde hemen.