The global fish and invertebrate abundance value of mangroves dataset

  • Philine Zu Ermgassen (Creator)
  • Thomas A. Worthington (Creator)
  • Jonathan r. Gair (Creator)
  • Emma Garnett (Creator)
  • Nibedita Mukherjee (Creator)
  • Kate Longley-wood (Creator)
  • Ivan Nagelkerken (Creator)
  • Kátya Abrantes (Creator)
  • Octavio Aburto-Oropeza (Creator)
  • Alejandro Acosta (Creator)
  • Ana Rd.R. Araujo (Creator)
  • Ronald Baker (Creator)
  • Adam Barnett (Creator)
  • Christine M. Beitl (Creator)
  • Rayna Benzeev (Creator)
  • Justin Brookes (Creator)
  • Gustavo A. Castellanos-galindo (Creator)
  • Ving Ching Chong (Creator)
  • Rod M. Connolly (Creator)
  • Marília Cunha-lignon (Creator)
  • Farid Dahdouh-guebas (Creator)
  • Karen Diele (Creator)
  • Patrick G. Dwyer (Creator)
  • Daniel A. Friess (Creator)
  • Thomas Grove (Creator)
  • M. Enamul Hoq (Creator)
  • Chantal Huijbers (Creator)
  • Neil Hutchinson (Creator)
  • Andrew F. Johnson (Creator)
  • Ross Johnson (Creator)
  • Jon Knight (Creator)
  • Uwe Krumme (Creator)
  • Baraka Kuguru (Creator)
  • Shing Yip Lee (Creator)
  • Aaron Savio Lobo (Creator)
  • Blandina R. Lugendo (Creator)
  • Jan-olaf Meynecke (Creator)
  • Cosmas Nzaka Munga (Creator)
  • Andrew D. Olds (Creator)
  • Cara L. Parrett (Creator)
  • Borja G. Reguero (Creator)
  • Patrik Rönnbäck (Creator)
  • Anna Safryghin (Creator)
  • Marcus Sheaves (Creator)
  • Matthew D. Taylor (Creator)
  • Jocemar Tomasino Mendonça (Creator)
  • Matthias Wolff (Creator)
  • Nathan Waltham (Creator)
  • Mark D. Spalding (Creator)

Dataset

Description

This dataset is the species and species group predictions of the density of 37 commercially important fish and invertebrates that are known to extensively use mangroves. All methods are provided in detail in the accompanying bioRxiv preprint, zu Ermgassen et al. (2024) The global fish and invertebrate abundance value of mangroves Description of files Mangrove_commercial_fauna_density_data_references.csv: this is the raw data used to create the linear model using generalized least squares relating the fish density values to the covariate data R Scripts & Data This folder contain several R scripts and data files to used calculate the values in zu Ermgassen et al. (2024) The global fish and invertebrate abundance value of mangroves. Species Predictions* all_sp_fit_fn.csv: the mean predicted species density for 37 commercially important fish and invertebrates for a grid with a spatial resolution of 1 km2. all_sp_fit_fn_lower.csv: the lower (1.96 * standard error of the model fit) predicted species density for 37 commercially important fish and invertebrates for a grid with a spatial resolution of 1 km2. all_sp_fit_fn_upper.csv: the upper (1.96 * standard error of the model fit) predicted species density for 37 commercially important fish and invertebrates for a grid with a spatial resolution of 1 km2. Species Name Contractions.csv: file with key to name contractions in above datasets Shapfiles: spatial representations of the above datasets based on the 1km2 grid Species Group Predictions all_sp_fit_fn_total.csv: the mean, lower and upper (1.96 * standard error of the model fit) predicted species density for 37 commercially important fish and invertebrates for a grid with a spatial resolution of 1 km2, with species summed into finfishes (n = 29), crabs (n = 4), bivalves (n = 1), and prawns (n = 3). Shapfiles: spatial representations of the above dataset based on the 1km2 grid * N.B. data labeled Neosarmatium meinerti in the above files has been corrected to Neosarmatium africanum

Data Citation

zu Ermgassen, P. S. E., Worthington, T. A., Gair, J. R., Garnett, E., Mukherjee, N., Longley-Wood, K., Nagelkerken, I., Abrantes, K., Aburto-Oropeza, O., Acosta, A., Araujo, A. R. d R., Baker, R., Barnett, A., Beitl, C., Benzeev, R., Brookes, J., Castellanos-Galindo, G. A., Ching Chong, V., Connolly, R. M., … Spalding, M. D. (2024). The global fish and invertebrate abundance value of mangroves dataset [Data set]. Zenodo. https://doi.org/10.5281/zenodo.11097214
Date made available1 May 2024
PublisherZenodo

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