Dataset title: Mangrove Leaf Litter Carbon and Nutrients from the Shark River Slough, Everglades National Park (FCE), South Florida, USA, January 2019 - ongoing Dataset ID: doi:10.6073/pasta/6218d6f516e1c865984ebd485eb31b69 Dataset Creator Name: Dr. John Kominoski Organization: Florida Coastal Everglades LTER Address: Florida International University 11200 SW 8th Street, OE 148 Miami, FL 33199 Email: jkominos@fiu.edu Name: Dr. Edward Castañeda-Moya Organization: Florida Coastal Everglades LTER Address: Florida International University 11200 SW 8th Street, OE 148 Miami, FL 33199 Email: edwardcm@gmail.com Name: Caitlin Reisa Organization: Florida Coastal Everglades LTER Address: Florida International University 11200 SW 8th Street, OE 148 Miami, FL 33199 Email: creisa@fiu.edu Metadata Provider Organization: Florida Coastal Everglades LTER Address: Florida International University 11200 SW 8th Street, OE 148 , Email: fcelter@fiu.edu URL: https://fcelter.fiu.edu Dataset Abstract Mangrove litterfall dynamics have been monitored in all Shark River sites (SRS-4, SRS-5, SRS-6) since January 2001 using the same collection method stated in Castañeda-Moya et al. 2013 (metadata: knb-lter-fce.1195) and Danielson et al. 2017. Briefly, litterfall was collected monthly at all sites (10 baskets per site) using permanent 0.25 m2 wooden baskets supported approximately 1.3 m above the soil surface and lined with 1 mm mesh screening. Litterfall from each basket was sorted, dried, and weighed by leaf species, reproductive parts by species, and woody material. Leaf litter data from different years (2019, 2020, 2021, 2023) were selected for each site to identify species-specific foliar carbon and nutrient (N and P) content. Monthly leaf litter samples were analyzed separately by species for all years after grinding with a Wiley Mill to pass through a 40-µm mesh screen. Total leaf litter C and N contents were determined with a Carlo-Erba NA-1500 elemental analyzer (Fisons Instruments Inc., Danvers, MA, USA). Total leaf litter P was extracted using an acid-digest (HCl) extraction, and concentrations of SRP were determined by spectrophotometric analysis (Methods 365.4 and 365.2, USA EPA 1983). Litterfall data collection is ongoing every year since 2001, while C and nutrients analyses are performed every other year after 2021. See also Shark River mangrove litterfall data (knb-lter-fce.1195) on the FCE LTER website's data catalog or in the EDI repository (https://portal.edirepository.org/nis/mapbrowse?scope=knb-lter-fce&identifier=1195). References: Castañeda-Moya, E., Twilley, R. R., & Rivera-Monroy, V. H. (2013). Allocation of biomass and net primary productivity of mangrove forests along environmental gradients in the Florida Coastal Everglades, USA. Forest Ecology and Management, 307, 226-241. Danielson, T.M., V.H. Rivera-Monroy, E. Castaneda-Moya, H. Briceno, R. Travieso, B.D. Marx, E. Gaiser, and L.M. Farfan. 2017. Assessment of Everglades mangrove forest resilience: Implications for above-ground net primary productivity and carbon dynamics. Forest Ecology and Management 404: 115-125. EPA. 1983. Methods for chemical analysis of water and wastes. Methods 365.4 and 365.2, USA EPA 1983. Office of Research and Development, Washington, DC 20460. Geographic Coverage Bounding Coordinates Geographic description: SRS4 West bounding coordinate: -80.96431016 East bounding coordinate: -80.96431016 North bounding coordinate: 25.40976421 South bounding coordinate: 25.40976421 Geographic description: SRS5 West bounding coordinate: -81.03234716 East bounding coordinate: -81.03234716 North bounding coordinate: 25.37702258 South bounding coordinate: 25.37702258 Geographic description: SRS6 West bounding coordinate: -81.07794623 East bounding coordinate: -81.07794623 North bounding coordinate: 25.36462994 South bounding coordinate: 25.36462994 Temporal Coverage Start Date: 2019 End Date: 2023 Data Table Entity Name: FCE1266_SRS_Mangrove_Leaf_Litter_C_Nutrients Entity Description: Carbon and nutrient (N and P) content of mangrove leaf litter in Shark River Slough Object Name: FCE1266_SRS_Mangrove_Leaf_Litter_C_Nutrients.csv Data Format Number of Header Lines: 1 Attribute Orientation: column Field Delimiter: , Number of Records: Attributes Attribute Name: SITENAME Attribute Label: SITENAME Attribute Definition: Study sites Storage Type: string Measurement Scale: SRS4= FCE LTER Shark River Slough site 4 SRS5= FCE LTER Shark River Slough site 5 SRS6= FCE LTER Shark River Slough site 6 Missing Value Code: Attribute Name: Year Attribute Label: Year Attribute Definition: Year of data collection Storage Type: dateTime Measurement Scale: Missing Value Code: Attribute Name: Month Attribute Label: Month Attribute Definition: Month of data collection Storage Type: float Measurement Scale: Units: dimensionless Number Type: integer Missing Value Code: Attribute Name: Season Attribute Label: Season Attribute Definition: Seasonality - Dry and Wet seasons Storage Type: string Measurement Scale: Dry= December-May Wet= June-November Missing Value Code: Attribute Name: Mangrove_species Attribute Label: Mangrove_species Attribute Definition: Mangrove species Storage Type: string Measurement Scale: A. germinans= Avicennia germinans C. erectus= Conocarpus erectus L. racemosa= Laguncularia racemosa R. mangle= Rhizophora mangle Missing Value Code: Attribute Name: Total_C_leaf_litter Attribute Label: Total_C_leaf_litter Attribute Definition: Total C content in mangrove leaf litter Storage Type: float Measurement Scale: Units: milligramPerGram Precision: .01 Number Type: real Missing Value Code: -9999.00 (Value will never be recorded) Attribute Name: Total_N_leaf_litter Attribute Label: Total_N_leaf_litter Attribute Definition: Total N content in mangrove leaf litter Storage Type: float Measurement Scale: Units: milligramPerGram Precision: .01 Number Type: real Missing Value Code: -9999.00 (Value will never be recorded) Attribute Name: Total_P_leaf_litter Attribute Label: Total_P_leaf_litter Attribute Definition: Total P content in mangrove leaf litter Storage Type: float Measurement Scale: Units: milligramPerGram Precision: .001 Number Type: real Missing Value Code: -9999.000 (Value will never be recorded) Methods Method Step Description Litterfall samples were collected monthly at all sites (10 baskets per site) using permanent 0.25 m2 wooden baskets supported approximately 1.3 m above the soil surface and lined with 1 mm mesh screening. Litterfall from each basket was sorted, dried, and weighed by leaf species, reproductive parts by species, and woody material. Leaf litter data from different years (2019, 2020, 2021, 2023) were selected for each site to identify species-specific foliar carbon and nutrient (N and P) content. Monthly leaf litter samples were analyzed separately by species for all years after grinding with a Wiley Mill to pass through a 40-µm mesh screen. Total leaf litter C and N contents were determined with a Carlo-Erba NA-1500 elemental analyzer (Fisons Instruments Inc., Danvers, MA, USA). Total leaf litter P was extracted using an acid-digest (HCl) extraction, and concentrations of SRP were determined by spectrophotometric analysis (Methods 365.4 and 365.2, USA EPA 1983). References: EPA. 1983. Methods for chemical analysis of water and wastes. Methods 365.4 and 365.2, USA EPA 1983. Office of Research and Development, Washington, DC 20460. Method Step Description Quality Control: Dataset QA/QC performed during analysis of samples; SRP concentrations with 5% between lab replicates were redone; data is graphed to check for outliers. Distribution Online distribution: https://pasta.lternet.edu/package/data/eml/knb-lter-fce/1266/2/6e1766151ba84a2f73261e98d5a40842 Intellectual Rights This information is released under the Creative Commons license - Attribution - CC BY (https://creativecommons.org/licenses/by/4.0/). The consumer of these data ("Data User" herein) is required to cite it appropriately in any publication that results from its use. The Data User should realize that these data may be actively used by others for ongoing research and that coordination may be necessary to prevent duplicate publication. The Data User is urged to contact the authors of these data if any questions about methodology or results occur. Where appropriate, the Data User is encouraged to consider collaboration or co-authorship with the authors. The Data User should realize that misinterpretation of data may occur if used out of context of the original study. While substantial efforts are made to ensure the accuracy of data and associated documentation, complete accuracy of data sets cannot be guaranteed. All data are made available "as is." The Data User should be aware, however, that data are updated periodically and it is the responsibility of the Data User to check for new versions of the data. The data authors and the repository where these data were obtained shall not be liable for damages resulting from any use or misinterpretation of the data. Thank you. Dataset Keywords FCE LTER LTER Florida Coastal Everglades LTER Shark River Slough ecological research foliar carbon foliar nutrients mangrove Leaf Litter litterfall mangroves long term monitoring plant growth wetlands primary production primary production Maintenance knb-lter-fce.1226.2: Updated data through 2023; updated metadata (including addition of QUDT unit annotations); renamed data file from ‘SRS_Mangrove_Leaf_Litter_C_Nutrients.csv’ to ‘FCE1266_SRS_Mangrove_Leaf_Litter_C_Nutrients.csv" Dataset Contact Name: Dr. John Kominoski Organization: Florida Coastal Everglades LTER Address: Florida International University 11200 SW 8th Street, OE 148 Miami, FL 33199 Email: jkominos@fiu.edu Name: Dr. Edward Castañeda-Moya Organization: Florida Coastal Everglades LTER Address: Florida International University 11200 SW 8th Street, OE 148 Miami, FL 33199 Email: Edward.Castaneda@miamidade.gov Position: Information Manager Organization: Florida Coastal Everglades LTER Address: Florida International University, 11200 SW 8th Street, OE 148 Miami, FL 33199 USA Email: fcelter@fiu.edu URL: https://fcelter.fiu.edu Project permits EVER-2017-SCI-0054 EVER-2019-SCI-0055 EVER-2022-SCI-0029 EVER-2023-SCI-0011