Many studies have attempted to predict whether coastal marshes will be able to keep up with future acceleration of sea-level rise by estimating marsh accretion rates. However, there are few studies focussing on the long-term effects of herbivores on vegetation structure and subsequent effects on marsh accretion. Deposition of fine-grained, mineral sediment during tidal inundations, together with organic matter accumulation from the local vegetation, positively affects accretion rates of marsh surfaces. Tall vegetation can enhance sediment deposition by reducing current flow and wave action. Herbivores shorten vegetation height and this could potentially reduce sediment deposition. This study estimated the effects of herbivores on 1) vegetation height, 2) sediment deposition and 3) resulting marsh accretion after long-term (at least 16 years) herbivore exclusion of both small (i.e. hare and goose) and large grazers (i.e. cattle) for marshes of different ages. Our results firstly showed that both small and large herbivores can have a major impact on vegetation height. Secondly, grazing processes did not affect sediment deposition. Finally, trampling by large grazers affected marsh accretion rates by compacting the soil. In many European marshes, grazing is used as a tool in nature management as well as for agricultural purposes. Thus, we propose that soil compaction by large grazers should be taken in account when estimating the ability of coastal systems to cope with an accelerating sea-level rise. (C) 2013 Elsevier Ltd. All rights reserved.
", "keywords": ["marsh succession", "0106 biological sciences", "Surface elevation change", "Sea-level rise", "FLOW", "Sedimentation rate", "SEA-LEVEL RISE", "SURFACE ELEVATION", "01 natural sciences", "BROWN HARES", "Herbivory", "14. Life underwater", "Marsh succession", "Biology", "Global change", "VEGETATION SUCCESSION", "global change", "COASTAL WETLANDS", "0105 earth and related environmental sciences", "2. Zero hunger", "sedimentation rate", "herbivory", "GEESE", "sea-level rise", "15. Life on land", "PRODUCTIVITY GRADIENT", "surface elevation change", "NORTH-SEA", "13. Climate action", "TIDAL MARSH"]}, "links": [{"href": "https://doi.org/10.1016/j.ecss.2013.08.021"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Estuarine%2C%20Coastal%20and%20Shelf%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.ecss.2013.08.021", "name": "item", "description": "10.1016/j.ecss.2013.08.021", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.ecss.2013.08.021"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-11-01T00:00:00Z"}}, {"id": "10.1016/j.catena.2017.08.005", "type": "Feature", "geometry": null, "properties": {"license": "Closed Access", "updated": "2026-06-26T16:17:09Z", "type": "Journal Article", "created": "2017-08-11", "title": "Soil Greenhouse Gas Fluxes In Tropical Mangrove Forests And In Land Uses On Deforested Mangrove Lands", "description": "Mangrove forests are important carbon sinks in the tropics, yet tropical mangrove deforestation and land use conversion still persists. Reporting of greenhouse gas (GHG) emissions from natural and anthropogenic sources in wetlands are important in regional and national emissions inventories. However, very few studies have been conducted to measure on the GHG fluxes in coastal wetlands, particularly in mangrove forest and non-forest land uses in deforested mangroves. We investigated the soil fluxes of CO2, CH4 and N2O in mangrove forest and non-forest land uses on deforested mangrove areas (i.e. abandoned aquaculture ponds, coconut plantations, abandoned salt ponds, and cleared mangroves) in the coasts of Honda Bay, Philippines. Results showed that the emissions of CO2 and CH4 were higher by 2.6 and 6.6 times in mangrove forests (110 and 0.6 kg CO2e ha \u2212 1 day \u2212 1, respectively) while N2O emissions were lower by 34 times compared to the average of non-forest land uses (1.3 kg CO2e ha \u2212 1 day \u2212 1). CH4 and N2O emissions accounted for 0.59% and 0.04% of the total emissions in mangrove forest as compared to 0.23% and 3.07% for non-forest land uses, respectively. Site-scale soil GHG flux distribution could be mapped with 75% to 83% accuracy using Ordinary Kriging. Unlike mangroves that can offset all GHG emissions through CO2 uptake from photosynthesis, the non-forest land uses cannot offset their emissions on-site as they are usually devoid of vegetation. Our results could be utilised in higher tier national GHG inventories, to refine regional and global estimates of GHG emissions in mangrove wetlands, and improve policy on coastal wetlands conservation.", "keywords": ["coastal wetlands", "580", "soil greenhouse gas fluxes", "570", "Philippines", "15. Life on land", "01 natural sciences", "6. Clean water", "12. Responsible consumption", "13. Climate action", "non-forest land uses in deforested mangrove lands", "11. Sustainability", "geostatistics", "14. Life underwater", "mangrove forest", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.catena.2017.08.005"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/CATENA", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.catena.2017.08.005", "name": "item", "description": "10.1016/j.catena.2017.08.005", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.catena.2017.08.005"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-12-01T00:00:00Z"}}, {"id": "10.1016/j.ecss.2013.10.026", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:17:19Z", "type": "Journal Article", "created": "2013-11-01", "title": "Does Livestock Grazing Affect Sediment Deposition And Accretion Rates In Salt Marshes?", "description": "Accretion rates, defined as the vertical growth of salt marshes measured in mm per year, may be influenced by grazing livestock in two ways: directly, by increasing soil compaction through trampling, and indirectly, by reducing aboveground biomass and thus decreasing sediment deposition rates measured in g/m(2) per year. Although accretion rates and the resulting surface elevation change largely determine the resilience of salt marshes to sea-level rise (SLR), the effect of livestock grazing on accretion rates has been little studied. Therefore, this study aimed to investigate the effect of livestock grazing on salt-marsh accretion rates. We hypothesise that accretion will be lower in grazed compared to ungrazed salt marshes. In four study sites along the mainland coast of the Wadden Sea (in the south-eastern North Sea), accretion rates, sediment deposition rates, and soil compaction of grazed and ungrazed marshes were analysed using the Cs-137 radionuclide dating method. Accretion rates were on average 11.6 mm yr(-1) during recent decades and thus higher than current and projected rates of SLR. Neither accretion nor sediment deposition rates were significantly different between grazing treatments. Meanwhile, soil compaction was clearly affected by grazing with significantly higher dry bulk density on grazed compared to ungrazed parts. Based on these results, we conclude that other factors influence whether grazing has an effect on accretion and sediment deposition rates and that the effect of grazing on marsh growth does not follow a direct causal chain. It may have a great importance when interacting with other biotic and abiotic processes on the marsh. Crown Copyright (C) 2013 Published by Elsevier Ltd. All rights reserved.
", "keywords": ["0106 biological sciences", "F800 - Physical geographical sciences", "550", "137Cs", "geochronology", "SEA-LEVEL RISE", "SURFACE ELEVATION", "01 natural sciences", "630", "Wadden Sea", "inundation", "CS-137", "F820 Geomorphology", "(CS)-C-137", "compaction", "NITROGEN MINERALIZATION", "COASTAL WETLANDS", "0105 earth and related environmental sciences", "land use management", "WADDEN SEA", "15. Life on land", "NORTH-SEA", "13. Climate action", "C180 - Ecology", "TIDAL MARSH", "VEGETATION", "C180 Ecology", "dating", "SW NETHERLANDS"]}, "links": [{"href": "https://doi.org/10.1016/j.ecss.2013.10.026"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Estuarine%2C%20Coastal%20and%20Shelf%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.ecss.2013.10.026", "name": "item", "description": "10.1016/j.ecss.2013.10.026", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.ecss.2013.10.026"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-12-01T00:00:00Z"}}, {"id": "10.3354/meps11447", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:23:08Z", "type": "Journal Article", "created": "2015-08-06", "title": "Ecosystem Engineering By Large Grazers Enhances Carbon Stocks In A Tidal Salt Marsh", "description": "Grazers can have a large impact on ecosystem processes and are known to change vegetation composition. However, knowledge of how the long-term presence of grazers affects soil carbon sequestration is limited. In this study, we estimated total accumulated organic carbon in soils of a back-barrier salt marsh and determined how this is affected by long-term grazing by both small and large grazers in relation to age of the ecosystem. In young marshes, where small grazers predominate, hare and geese have a limited effect on total accumulated organic carbon. In older, mature marshes, where large grazers predominate, cattle substantially enhanced carbon content in the marsh soil. We ascribe this to a shift in biomass distribution in the local vegetation towards the roots in combination with trampling effects on the soil chemistry. These large grazers thus act as ecosystem engineers: their known effect on soil compaction (based on a previous study) enhances anoxic conditions in the marsh soil, thereby reducing the oxygen available for organic carbon decomposition by the local microbial community. This study showed that the indirect effects of grazing can significantly enhance soil carbon storage through changing soil abiotic conditions. This process should be taken into account when estimating the role of ecosystems in reducing carbon dioxide concentration in the atmosphere. Ultimately, we propose a testable conceptual framework that includes 3 pathways by which grazers can alter carbon storage: (1) through above-ground biomass removal, (2) through alteration of biomass distribution towards the roots and/or (3) by changing soil abiotic conditions that affect decomposition.
", "keywords": ["Carbon sequestration", "0106 biological sciences", "IMPACT", "SEA-LEVEL RISE", "01 natural sciences", "Coastal wetland", "Climate change", "Biology", "Soil compaction", "Succession", "VEGETATION SUCCESSION", "0105 earth and related environmental sciences", "2. Zero hunger", "CLIMATE-CHANGE", "WETLAND SOILS", "WADDEN SEA", "15. Life on land", "PRODUCTIVITY GRADIENT", "6. Clean water", "Chemistry", "Grazing", "ORGANIC-MATTER", "NORTH-SEA", "REDOX OSCILLATION", "13. Climate action", "Redox potential"]}, "links": [{"href": "https://doi.org/10.3354/meps11447"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Marine%20Ecology%20Progress%20Series", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3354/meps11447", "name": "item", "description": "10.3354/meps11447", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3354/meps11447"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-10-14T00:00:00Z"}}, {"id": "10.25338/B8P92J", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-26T16:23:00Z", "type": "Dataset", "created": "2023-07-13", "title": "Spatio-temporal dynamics of insect communities in constructed and natural tidal marshes with distinct landscape positions", "description": "unspecified| | | | | | | | | ------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------- | ------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- | ------- | ------------------------------------------------------ | | This readme file was generated on 2023-07-05 by Emily Fromenthal | | | | | | | | | | | | | | | | GENERAL INFORMATION | | | | | | | | | | | | | | | | Title of Dataset: Beyond the Marsh: Tidal Marsh Landscape Position Influences Insect Community Structure | | | | | | | | | | | | | | | | Author/Principal Investigator Information | | | | | | | | Name: Emily Fromenthal | | | | | | | | Institution: University of Alabama | | | | | | | | Email:[efromenthal@crimson.ua.edu](mailto:efromenthal@crimson.ua.edu) | | | | | | | | Author/Associate or Co-investigator Information | | | | | | | | Name: Shelby Rinehart | | | | | | | | ORCID:0000-0001-9820-1350 | | | | | | | | Institution: University of Alabama & Drexel University | | | | | | | | Email: [srinehart@ucdavis.edu](mailto:srinehart@ucdavis.edu) OR [sarinehart@ua.edu](mailto:sarinehart@ua.edu) | | | | | | | | Author/Associate or Co-investigator Information | | | | | | | | Name: Jacob M Dybiec | | | | | | | | Institution: University of Alabama | | | | | | | | Email: [jmdybiec@crimson.ua.edu](mailto:jmdybiec@crimson.ua.edu) | | | | | | | | Author/Associate or Co-investigator Information | | | | | | | | Name: Julia A Cherry | | | | | | | | Institution: University of Alabama | | | | | | | | Email: [cherr002@ua.edu](mailto:cherr002@ua.edu) | | | | | | | | | | | | | | | | Date of data collection: 2021-04 through 2021-10 | | | | | | | | | | | | | | | | Geographic location of data collection: West Fowl River | Coden | Alabama | USA | | | | | CON-1: 30.368 N | -88.152 W | | | | | | | CON-2: 30.367 N | -88.151 W | | | | | | | NAT: 30.368 N | -88.160 W | | | | | | | | | | | | | | | Information about funding sources that supported the collection of the data: | | | | | | | | The Society of Wetland Scientists | | | | | | | | University of Alabama | Department of Biological Sciences | | | | | | | | | | | | | | | | | | | | | | | SHARING/ACCESS INFORMATION | | | | | | | | | | | | | | | | Licenses/restrictions placed on the data: None | | | | | | | | | | | | | | | | Links to publications that cite or use the data: Please see the publication associated with these data in XXXXXXXX (doi: XXXXXX) | | | | | | | | | | | | | | | | Recommended citation for this dataset: | | | | | | | | | | | | | | | | Fromenthal | E | S. Rinehart | J.M. Dybiec | and J.A Cherry. Beyond the Marsh: Tidal Marsh Landscape Position Influences Insect Community Structure. Dryad | Dataset | [https://doi.org/XXXXXXXXX](https://doi.org/XXXXXXXXX) | | | | | | | | | | | | | | | | | | DATA & FILE OVERVIEW | | | | | | | | | | | | | | | | File List: | | | | | | | | Taxa- count data for each insect taxon observed at study sites | | | | | | | | Biodiversity- total individuals | taxa richness | and Shannon-Weiner diversity (H') indeces for each quadrat | | | | | | FloralCounts- total count | average count | standard deviation | and variance of Juncus roemerianus inflorescences | | | | | Herbivory- percent area of herbivory damage on J. roemerianus shoots collected from each quadrat in each marsh. | | | | | | | | | | | | | | | | METHODOLOGICAL INFORMATION | | | | | | | | | | | | | | | | Description of methods used for collection/generation of data: See the publication associated with these data in XXXXXXXX (doi: XXXXXX) for details on methods. | | | | | | | | | | | | | | | | Methods for processing the data: See the publication associated with these data in XXXXXXXX (doi: XXXXXX) for details on methods. | | | | | | | | | | | | | | | | Instrument- or software-specific information needed to interpret the data: Microsoft Excel | | | | | | | | | | | | | | | | Environmental/experimental conditions: CON-1 and CON-2 are two constructed tidal marshes hydrologically connected via canal to the West Fowl River in Mobile County | Alabama. NAT is a reference marsh directly connected to the West Fowl River. All marshes are located in a sub-tropical estuary along the northern Gulf fo Mexico. | | | | | | | | | | | | | | | Describe any quality-assurance procedures performed on the data: | | | | | | | | General QA/QC done by all co-authors. | | | | | | | | | | | | | | | | People involved with sample collection | processing | analysis | and/or submission: | | | | | Emily Fromenthal was involved in sample collection | processing | analysis | and submission. | | | | | Shelby Rinehart was involved in sample collection | analysis | and submission. | | | | | | Jacob M Dybiec was involved in sample collection and analysis. | | | | | | | | Julia A Cherry was involved in analysis and submission. | | | | | | | | | | | | | | | | DATA-SPECIFIC INFORMATION FOR: Taxa | | | | | | | | Number of variables: 86 | | | | | | | | Number of cases/rows: 146 | | | | | | | | Missing data codes: No data missing. | | | | | | | | Specialized formats or other abbreviations used: N/A. | | | | | | | | | | | | | | | | Variable List: | | | | | | | | Marsh-indicates the marsh (CON1 | CON2 | or NAT) that data was collected from | | | | | | Month- month that data was collected | | | | | | | | Method- method used to collect data (Pan | Net | Light | FC) | | | | | Quadrat- indicates the replicate quadrat (i.e. | CON1-1 | CON1-2 | etc.) that data was collected from | | | | | Variables E-CH (5-86) represent counts of indiviual taxa identified to the lowest possible taxa (family | in most cases). | | | | | | | | | | | | | | | DATA-SPECIFIC INFORMATION FOR: Biodiversity | | | | | | | | Number of variables: 5 | | | | | | | | Number of cases/rows: 12 | | | | | | | | | | | | | | | | Missing data codes: No missing data. | | | | | | | | Specialized formats or other abbreviations used: | | | | | | | | H'- Shannon-Wiener diversity index; calculated using the formula H^'= - _(i=1)^Rp _i ln p _i | | | | | | | | | | | | | | | | Variable List: | | | | | | | | Marsh- indicates the marsh (CON1 | CON2 | or NAT) that data was collected from | | | | | | Quadrat- indicates the replicate quadrat (i.e. | CON1-1 | CON1-2 | etc.) that data was collected from | | | | | Total Individuals- total count of individual insects per quadrat across all sampling strategies. | | | | | | | | Taxa Richness- number of unique taxa identified per quadrat across all sampling stratagies. | | | | | | | | H'- Shannon-Wiener diversity calculated for each quadrat across all sampling stratagies. | | | | | | | | | | | | | | | | DATA-SPECIFIC INFORMATION FOR: FloralCounts | | | | | | | | Number of variables: 4 | | | | | | | | Number of cases/rows: 37 | | | | | | | | | | | | | | | | Missing data codes: No missing data. | | | | | | | | Specialized formats or other abbreviations used: None | | | | | | | | | | | | | | | | Variable List: | | | | | | | | Marsh- indicates the marsh (CON1 | CON2 | or NAT) that data was collected from | | | | | | Quadrat- indicates the replicate quadrat (i.e. | CON1-1 | CON1-2 | etc.) that data was collected from | | | | | Replicate- inducates which sub-sample from each quadrat is associated with each observation | | | | | | | | Floral count- the number of flowering J. roemerianus shoots in each observation. | | | | | | | | | | | | | | | | DATA-SPECIFIC INFORMATION FOR: Herbivory | | | | | | | | Number of variables: 7 | | | | | | | | Number of cases/rows: 12 | | | | | | | | | | | | | | | | Missing data codes: No missing data. | | | | | | | | Specialized formats or other abbreviations used: N/A | | | | | | | | | | | | | | | | Variable List: | | | | | | | | Quadrat- indicates the replicate quadrat (i.e. | CON1-1 | CON1-2 | etc.) that data was collected from. | | | | | Marsh- notes which tidal wetland site the sample was collected from. | | | | | | | | Herbivory (sq inch)- area of insect herbivory damage/scars in square inches | | | | | | | | Herbivory (cm2)- area of insect herbivory damage/scars per cm2 | | | | | | | | Total area (sq inch)- total size (area) of J. roemerianus shoots in square inches | | | | | | | | Total area (cm2)- total size (area) of of J. roemerianus shoots in cm2. | | | | | | | | % Herbivory- the percent area of J. roemerianus shoots with insect herbivory damage | | | | | | |", "keywords": ["coastal wetlands", "Gulf of Mexico", "Restoration ecology", "insect ecology", "Seasonal variations", "Spatial and landscape ecology", "FOS: Natural sciences", "Species diversity"], "contacts": [{"organization": "Rinehart, Shelby, Fromenthal, Emily, Dybiec, Jacob, Cherry, Julia,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.25338/B8P92J"}, {"rel": "self", "type": "application/geo+json", "title": "10.25338/B8P92J", "name": "item", "description": "10.25338/B8P92J", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.25338/B8P92J"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-04-26T00:00:00Z"}}, {"id": "10.5061/dryad.3bk3j9kt3", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-06-26T16:24:00Z", "type": "Dataset", "created": "2024-03-31", "title": "Data from: Burrowing crab effects on the properties and functions of coastal soft sediments", "description": "unspecified# Data from: Burrowing crab effects on the properties and functions of coastal soft sediments [https://doi.org/10.5061/dryad.3bk3j9kt3](https://doi.org/10.5061/dryad.3bk3j9kt3) Effect size calculations (including means, sample sizes, and standard deviation) of crab burrowing effects (i.e., high density vs low density) on the properties, nutrient stocks, and functions of coastal sediments. Data comes from studies conducted across Africa, Asia, Australia, North America, and South America. ## Description of the data and file structure **File list:** 1. Rinehart_et_al.202X_Effectsizes CSV file containing the Hedges d effect size calculations (including the raw means, sample sizes, and standard deviations) for each extracted comparison/study from all 59 manuscripts. Additional extracted data (e.g., crab taxa, experimental conditions, habitat, burrow density) are also included for each comparison/study. 2. Rinehart_et_al.202X_Publicationbias CSV file containing the pooled standard deviation and the Hedges d effect size calculation for each comparison/study. This datafile was used to conduct analyses of publication bias for a resulting systematic meta-analysis. **Data-specific information for:** (1) Rinehart_et_al.202X_Effectsizes **Number of variables:** 47 **Number of cases/rows:** 1423 Variable List:\u00a0 1. id: the unique code assigned to each data row. 2. reference: author, year, and journal for each data source. 3. pub_year: year of reference publication. One in preparation study was included in the dataset (Rinehart et al. 20XX), it's publication year is denoted as 20XX. 4. paper id: the unique code assigned to each manuscript included in the dataset. 5. continent: the continent where the data was collected. 6. country: the country where the data was collected. 7. state: the state (united states only) where the data was collected. 8. estuary: the name of the estuary where the data was collected. 9. latitude_dd: the latitude associated with the data collected in decimal degrees (dd). 10. longitude_dd: the longitude associated with the data collected in decimal degrees (dd). 11. ecosystem: the type of ecosystem (e.g., salt marsh, mangrove forest, tidal flat) associated with the collected data. 12. vegetation: categorical variable noting the presence (vegetated) or absence (not unvegetated) of any vegetation. 13. ecosystem_type: categorical variable noting if the ecosystem was restored, created, or natural. 14. relative_salinity: categorical variable noting the relative salinity in the ecosystem where the data was collected. 15. tidal_amplitude_m: the tidal amplitude (in meters) in the ecosystem where the data was collected. 16. tidal_cycle: categorical variable noting the type of tidal cycle (e.g., diurnal) in the ecosystem where the data was collected. 17. soil_type: categorical variable noting the soil type (e.g., sand) in the ecosystem where the data was collected. 18. elevation_m: the elevation (in meters) of the ecosystem where the data was collected. 19. study_duration_d: the length of time (in days) that the study ran (applies mainly to manipulative studies). 20. study_timing: the seasons or months during which the study was run. 21. dominant_plant_genus: the genus of the dominant plant present in the ecosystem where the data was collected. 22. dominant_plant_species: the species of the dominant plant present in the ecosystem where the data was collected. 23. dominant_plant_functional_group: categorical variable noting the functional group (e.g., grass) of the dominant plant species in the ecosystem where the data was collected. 24. crab_genus: the genus of the dominant burrowing crab used in the study. Studies with mixed crab communities are denoted with by 'mixed'. 25. crab_species: the species of the dominant burrowing crab used in the study. Studies with mixed crab communities are denoted with by 'mixed'. 26. crab_diet: categorical variable noting the main feeding strategy (e.g., herbivore, detritivore) used by the dominant crab species. 27. crab_superfamily: the superfamily of the dominant burrowing crab used in the study. Studies with mixed crab communities are denoted with by 'mixed'. 28. mean_burrow_diameter_high_crab_treatment_mm: the mean burrow diameter in the study's high crab treatment in mm. 29. mean_burrow_diameter_low_crab_treatment_mm: the mean burrow diameter in the study's low crab treatment in mm. 30. mean_burrow_depth_cm: the mean burrow depth in cm reported by the study. 31. burrow_density_high_crab_m^2: the mean crab burrow density per meter-squared reported in the study's high crab treatment. 32. burrow_density_low_crab_m^2: the mean crab burrow density per meter-squared reported in the study's low crab treatment. 33. experiment_type: categorical variable noting if the study used observational or manipulative methodologies. 34. experiment_setting: categorical variable noting if the study was conducted in a laboratory or field setting. Laboratory studies also include outdoor mesocosm studies. 35. field_location: categorical variable noting where studies conducted in the field placed their study relative to the shoreline. Specifically, we noted if studied sampled in the ecosystem interior (far from shoreline) or at the ecosystem edge (adjacent to the shoreline). 36. soil_depth_cm: the depth, in cm, within the soil profile from which the sediment samples were collected. 37. soil_characteristic_measured: categorical variable identifying the specific sediment property, nutrient stock, or function that was quantified by the study. 38. soil_characteristic_units: the original units used to quantify the soil characteristic within the study. 39. mean_low_crab: the mean value of the soil characteristic measured in the low crab treatment within the study. 40. sd_low_crab: the standard deviation of the soil characteristic measured in the low crab treatment within the study. 41. n_low_crab: the sample size of the soil characteristic measured in the low crab treatment within the study. 42. mean_high_crab: the mean value of the soil characteristic measured in the high crab treatment within the study. 43. sd_high_crab: the standard deviation of the soil characteristic measured in the high crab treatment within the study. 44. n_high_crab: the sample size of the soil characteristic measured in the high crab treatment within the study. 45. crab_density: categorical variable noting if the study documented relative burrowing crab density within their study using burrow density (burrow) or counts of individuals (individuals). 46. hedges_d: the hedges d effect size calculated for the effects of burrowing crabs on the measured sediment characteristic. Hedges d values were calculated in OpenMee software (see code/software below). Positive effect sizes indicate that burrowing crabs increased the value of the sediment measurement, while negative effect sized indicate that burrowing crabs decreased the value of the sediment measurement. 47. hedges_d_var: the variation of the hedges d effect size calculated for the effects of burrowing crabs on the measured sediment characteristic. Hedges d variation values were calculated in OpenMee software (see code/software below). **Missing data codes:** na Data-specific information for: (2) Rinehart_et_al.202X_Publicationbias ***Number of variables:*** 22 ***Number of cases/rows:*** 1423 Variable List:\u00a0 1. id: the unique code assigned to each data row. 2. reference: author, year, and journal for each data source. 3. pub_year: year of reference publication. One in preparation study was included in the dataset (Rinehart et al. 20XX), it's publication year is denoted as 20XX. 4. paper id: the unique code assigned to each manuscript included in the dataset. 5. ecosystem: the type of ecosystem (e.g., salt marsh, mangrove forest, tidal flat) associated with the collected data. 6. vegetation: categorical variable noting the presence (vegetated) or absence (not unvegetated) of any vegetation. 7. crab_superfamily: the superfamily of the dominant burrowing crab used in the study. Studies with mixed crab communities are denoted with by 'mixed'. 8. burrow_density_high_crab_m^2: the mean crab burrow density per meter-squared reported in the study's high crab treatment. 9. experiment_type: categorical variable noting if the study used observational or manipulative methodologies. 10. experiment_setting: categorical variable noting if the study was conducted in a laboratory or field setting. Laboratory studies also include outdoor mesocosm studies. 11. soil_characteristic_measured: categorical variable identifying the specific sediment property, nutrient stock, or function that was quantified by the study. 12. soil_characteristic_units: the original units used to quantify the soil characteristic within the study. 13. mean_low_crab: the mean value of the soil characteristic measured in the low crab treatment within the study. 14. sd_low_crab: the standard deviation of the soil characteristic measured in the low crab treatment within the study. 15. n_low_crab: the sample size of the soil characteristic measured in the low crab treatment within the study. 16. mean_high_crab: the mean value of the soil characteristic measured in the high crab treatment within the study. 17. sd_high_crab: the standard deviation of the soil characteristic measured in the high crab treatment within the study. 18. n_high_crab: the sample size of the soil characteristic measured in the high crab treatment within the study. 19. pooled_sd: the pooled standard deviation of the high and low crab treatments for each study. 20. crab_density: categorical variable noting if the study documented relative burrowing crab density within their study using burrow density (burrow) or counts of individuals (individuals). 21. hedges_d: the hedges d effect size calculated for the effects of burrowing crabs on the measured sediment characteristic. Hedges d values were calculated in OpenMee software (see code/software below). Positive effect sizes indicate that burrowing crabs increased the value of the sediment measurement, while negative effect sized indicate that burrowing crabs decreased the value of the sediment measurement. 22. hedges_d_var: the variation of the hedges d effect size calculated for the effects of burrowing crabs on the measured sediment characteristic. Hedges d variation values were calculated in OpenMee software (see code/software below). **Missing data codes:** na ## Sharing/Access information All data are included in the provided datafiles. ## Code/Software Hedges\u2019 *d* (hereafter, *d*) effect sizes were calculated using meta-analysis using OpenMEE software (Build date: 26 July 2016; Wallace et al. 2017). Wallace, B. C., M. J. Lajeunesse, G. Dietz, I. J. Dahabreh, T. A. Trikalinos, C. H. Schmid, and J. Gurevitch. 2017. OpenMEE: Intuitive, open-source software for meta-analysis in ecology and evolutionary biology. 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