DOI: 10.5061/dryad.0zpc86788
title: Data from: Inferring community assembly processes from mangrove species–area relationships

description: The increasing species–area relationship (SAR) is a nearly universal
 ecological law. But recent theory has predicted that in systems with low
 large-scale diversity the law should be violated and the SAR should be
 nearly flat at intermediate scales, with species richness roughly constant
 at some value typically greater than one. We tested this prediction using
 a global dataset of mangrove trees—a species-poor group. We used a
 published global dataset of mangrove tree distributions to construct an
 SAR spanning local to global scales. We found that over a large range of
 scales (≈10^-4 to 10^6 km^2) the SAR was close to flat, in stark contrast
 to a classical power-law SAR, which would predict roughly a 300-fold
 change in species richness over these scales. Importantly, species
 richness was not simply equal to the minimum value of one or the maximum
 value of global mangrove richness over these scales, either of which
 possibilities would be reconcilable with the classical theory, but instead
 was maintained at an average value of between two and three species. Our
 theoretical interpretation of the results is that there are two to three
 stabilising niches (i.e., niches that would allow two to three species to
 stably coexist without substantial immigration) for mangrove trees in
 typical coastal settings and that immigrant propagule diversity is in most
 cases too low (because of low mangrove tree metacommunity diversity) for
 there to be more species than niches. Only at scales greater than ≈10^6
 km^2 is the diversity of immigrants typically sufficient to yield more
 species than niches. We speculate that in other systems, local niche
 diversity may be similarly low but that the nearly flat SAR phase is
 hidden by immigration from diverse source pools.
description: We based our dataset on a recently compiled large field-based
 dataset on mangrove forest structure and biomass (Rovai et al. 2021, Rovai
 2023). In its raw form, the dataset is a compilation of summary data for
 3,497 mangrove plots distributed globally across 67 countries, synthesised
 from approximately 500 different sources (both published and unpublished).
 We removed 1,433 plots for which mangrove species identities and species
 richness were not available, leaving 2,064 plots. A total of 54 mangrove
 and mangrove-associated tree taxa were represented at these plots (i.e.,
 roughly 74% of the global total). Our goal was to
 construct SARs that are, as far as possible, based on accurate taxonomy,
 based on true mangrove tree species, and representative of natural
 conditions without anthropogenic influence. To this end we performed
 several data curation steps. We updated the name of <em>Avicennia
 lanata</em> to <em>Avicennia rumphiana</em>. We removed
 from the dataset species that are not considered true mangroves and we
 merged synonymous taxa (as per the World Register of Marine Species). This
 resulted in the purging of three species considered mangrove associates
 (<em>Cerbera odollam</em>, <em>Intsia bijuga</em>,
 and <em>Pterocarpus officinalis</em>) and the merger of five
 taxa with synonymous taxa (<em>Avicennia africana</em> was
 absorbed into <em>Avicennia germinans</em>;
 <em>Bruguiera decandra</em> into <em>Ceriops
 decandra</em>; <em>Excoecaria ovalis</em> into
 <em>Excoecaria agallocha</em>; <em>Rhizophora
 brevistyla</em> into <em>Rhizophora harrisonii</em>; and
 <em>Xylocarpus mekongensis</em> into <em>Xylocarpus
 moluccensis</em>). After these changes, the number of species in our
 dataset was reduced to 46. In addition, the dataset contained errors in
 which the wrong mangrove species was recorded in a small number of plots.
 This was determined by checking for distributional outliers against known
 mangrove distribution patterns by biogeographical region (Spalding, 2010).
 There were 20 plots with such errors (Supplemental Information S1). These
 errors were corrected to account for likely misidentifications where
 possible, but two plots with particularly dubious occurrences
 (<em>Laguncularia racemosa</em> in a plot in the Philippines
 and <em>Avicennia marina</em> in a plot in Venezuela) were
 deleted. We removed from the database a further seven
 mangrove plots that had no remaining species after deletions. Plots
 containing only introduced mangrove species were also removed from the
 dataset. There were ten such plots, all in Hawaii. Our final dataset thus
 comprised 2,045 plots. Rovai, A. S. 2023. Mangrove
 forest structure dataset associated to Rovai et al. 2021 in GEB. figshare:
 https://doi.org/10.6084/m9.figshare.13570601.v1 Rovai, A. S., R. R. Twilley, E. Castañeda-Moya, S. R. Midway, D. A. Friess, C. C. Trettin, J. J. Bukoski, A. E. L. Stovall, P. R. Pagliosa, A. L. Fonseca, R. A. Mackenzie, A. Aslan, S. D. Sasmito, M. Sillanpää, T. G. Cole, J. Purbopuspito, M. W. Warren, D. Murdiyarso, W. Mofu, S. Sharma, P. H. Tinh, and P. Riul. 2021. Macroecological patterns of forest structure and allometric scaling in mangrove forests. Global Ecology and Biogeography <strong>30</strong>:1000-1013.
description: # Inferring community assembly processes from mangrove species–area
 relationships
 [https://doi.org/10.5061/dryad.0zpc86788](https://doi.org/10.5061/dryad.0zpc86788) ## Description of the data and file structure The data were existing published data comprising mangrove species diversity data from sites around the world. See the following references: Rovai, A. S. 2023. Mangrove forest structure dataset associated to Rovai et al. 2021 in GEB. figshare: [https://doi.org/10.6084/m9.figshare.13570601.v1](https://doi.org/10.6084/m9.figshare.13570601.v1) Rovai, A. S., R. R. Twilley, E. Castañeda-Moya, S. R. Midway, D. A. Friess, C. C. Trettin, J. J. Bukoski, A. E. L. Stovall, P. R. Pagliosa, A. L. Fonseca, R. A. Mackenzie, A. Aslan, S. D. Sasmito, M. Sillanpää, T. G. Cole, J. Purbopuspito, M. W. Warren, D. Murdiyarso, W. Mofu, S. Sharma, P. H. Tinh, and P. Riul. 2021. Macroecological patterns of forest structure and allometric scaling in mangrove forests. Global Ecology and Biogeography **30**:1000-1013. ### Files and variables #### File: mangrove\_data\_Oikos.csv **Description:** This is the data file containing mangrove species occurrences for 2045 sites around the world. ##### Variables * References: This variable lists the references from which the data in the current row were obtained. * Country_Name: This is the name of the country in which the site is located. * lonDD: This is the longitude of the site (in decimal degree) * latDD: This is the latitude of the site (in decimal degree) * biogeo: This is the biogeographic region, either "iwp" (Indo-West Pacific) or "aep" (Atlantic-East Pacific). * PlotSize_sqm: This is the area of the site in square metres (blank values indicate no information on area available). * TotalNumSpp: This is the total number of species at the site. * \: Each of these columns corresponds to a mangrove tree species, and the data comprise binary values indicating presence (1) or absence (0) of a species at a site. ## Code/software The .csv file can be opened in a text browser (e.g., Windows Notepad or MacOS TextEdit) or a spreadsheet programme (e.g., Microsoft Excel or MacOS Numbers). The code files can be opened in R. The main file is "compile_and_fit_mangrove_SAR_for_Oikos.R". The other file, "fit_mangrove_SAR_for_Oikos.R", is sourced by the main file. ## Access information Other publicly accessible locations of the data: * A complete version of the original database can be found at [https://doi.org/10.6084/m9.figshare.13570601.v1](https://doi.org/10.6084/m9.figshare.13570601.v1) Data was derived from the following sources: * The above-linked database.