DOI: 10.5061/dryad.1g1jwsv5z
title: Data from: Functional diversity shapes the stability of reef fish biomass under global change

description: Understanding how environmental and human pressures impact the temporal
 stability of fish community biomass on shallow reefs is essential for
 effective conservation and management. These pressures influence community
 stability directly, by affecting species stability and asynchrony in
 species’ fluctuations. However, their effects may also indirectly depend
 on the functional traits of the species composing the community, which
 remains poorly understood. Here, we examine both direct and indirect,
 trait-mediated effects of environmental variability and human impacts on
 species biomass stability and asynchrony in 215 Australian shallow reefs.
 These communities span a 10-degree sea surface temperature (SST) gradient
 and have been monitored over 14 years. Our results indicate higher
 asynchrony in tropical reefs due to higher trait diversity and trait
 redundancy and higher species stability in temperate communities due to
 higher mean trophic level. Human impacts, through its negative effects on
 species stability and trait diversity, was the main destabilising factor
 of fish community biomass. Temporal change in SST destabilised species
 biomass while increasing mean trophic level in fish communities. Overall,
 our findings show that a comprehensive analysis of the multiple facets of
 functional diversity is crucial to better understand the long-term
 stability of marine ecosystems under global change.
description: We quantitatively evaluate the direct and indirect effects of
 environmental and human pressures on the temporal stability of fish
 community biomass. We use an extensive shallow reef monitoring dataset
 that spans the entire Australian continent during a sea warming period
 punctuated by multiple extreme marine heatwaves (2008-2021) with
 observable impacts on fish populations. We focus on 215 fish communities
 on shallow rocky and coral reefs distributed across Australia, along a
 spatial gradient of mean sea surface temperature (hereafter mean SST) that
 ranges from 13.9 to 25.4 °C (mean = 19.3 <strong>±</strong>
 3.1 °C; Supplementary Figure 1). For each community, we characterise two
 aspects of climate change that capture (<em>i</em>) the linear
 trend in sea surface temperature through time (hereafter SST change) [32]
 and (<em>ii</em>) the temporal variability in SST caused by
 increasingly frequent marine heatwaves (hereafter
 CV<sub>SST</sub>). We also consider the temporal variability
 in marine primary productivity, measured by chlorophyll a content
 (hereafter CV<sub>Chlorophyll</sub>), as it can directly
 influence the stability of fish communities. We assess the intensity of
 human pressures using human gravity that integrates both reef
 accessibility and human population density, providing a relevant proxy of
 the intensity of multiple human activities on shallow reef ecosystems. We
 estimate four facets of functional diversity (i.e. CWMs, trait diversity,
 trait redundancy and trait distinctiveness) using four fish functional
 traits; species maximum length, growth coefficient, trophic level and
 maximum depth, which relate to both fish species responses to abiotic
 conditions (e.g. deepening) and fish species contributions to ecosystem
 functioning (e.g. food web).
description: # Functional diversity shapes the stability of reef fish biomass under
 global change
 [https://doi.org/10.5061/dryad.1g1jwsv5z](https://doi.org/10.5061/dryad.1g1jwsv5z) ## Description of the data and file structure We used raw data, which are freely available. URLs are given in Supplementary Table 3, which accompanies our submitted manuscript. The R code used for data processing and analysis is given in this Dryad folder. ### Files and variables #### File: final\_data.rds **Description:** This is the processed data used in our analysis. It contains site attributes, fish biodiversity facets and abiotic variables. Missing values are NA. More specifically, the 39columns correspond to: * site_code : name of the site (i.e., fish community) as in Edgar et al. (2023) * Longitude of the site * Latitude of the site * mean \_ annual_biomass: averaged of annual total fish biomass across the 14 years of survey (unit: g) for each site. For each community, we summed the annual biomass of each species to get annual total fish biomass. Then we averaged across years. Because not all sites underwent monitoring throughout the 14-year period, we extrapolated data for missing year. The process is detailled in the Materials and Methods section of the related paper. * sd annual biomass: standard deviation of annual total fish biomass for each site (unit: g) * mean raw annual biomass: averaged of annual total fish biomass across the 14 years of survey (unit: g) for each site before filling in missing annual data - see details in Materials and Methods * sd raw data : standard deviation of annual total raw fish biomass (unit: g) * cv biomass: coefficient of variation of annual total fish biomass. It is computed as the ratio between the sd and the mean of annual fish biomass (unitless) * cv biomass raw: coefficient of variation of raw annual fish biomass (unitless) * cv sp biomass: average coefficient of variation of annual species biomass. For each species in the community, we compute the coefficient of variation of its annual biomass across the 14 years. Then, we averaged the coefficient of variations of all species presented in the community (unitless). * cv sp raw biomass: same as cv sp biomass but with raw biomass data (unitless)- see Materials and Methods for details. * synchrony: quantifies the covariation between the fluctuation of annual species biomass. See De Mazancourt & Loreau (2008) for details (unitless) * synchrony raw : same as synchrony but based on raw annual biomass data (unitless) * n: number of year with biomass information. varies between 7 and 14 * richness: number of fish species in each community (site) * td1: taxonomic diversity of order 1 that is, exponential of shanon index (unitless) (not used in this study) * fd1: functional diversity of order 1 (unitless) - see Materials and Methods for details * fr1: functional richness (unitless) (not used in this study) * cwm_trophic level: Community Weighted Mean value of fish trophic level (unitless) - see Materials and Methods for details * cwm_length: - Community Weighted Mean value of fish length (unit: cm) - see Materials and Methods for details * cwm_depth: - Community Weighted Mean value of fish maximum depth (unit:m) - see Materials and Methods for details * cwm_grate: - Community Weighted Mean value of fish growth rate (unit:cm per year) - see Materials and Methods for details * n_distinct; number of functionally distinct species - see Materials and Methods for details * cool; warm and tropical: We classified each fish in three biogeographic groups (i.e. cool, tropical or warm; extracted from Edgar et al., 2023). Then for each community, we computed the summed of species relative biomass in each biogeographic group (respectively the column cool, warm and tropical) (unit: %) * high, low and medium: We classified each fish species in three classes of trophic level (low, medium and high) by splitting the distribution of the trophic level of fish species into three classes of equal effective. Then, we computed for each communities the sum of the relative biomass of species in the low, medium and high trophic level groups (i.e. dominance of low/medium/high trophic level) (unit: %) * mean sst: mean sea surface temperature (unit: °C) across the 14 years of survey * change sst: we quantify temporal changes in SST using linear models with ‘annual SST’ and ‘year’ as dependent and independent variables, respectively. We use the coefficient of regression of ‘year’ to quantify the annual rate of change in SST (unit: °C per year) * sd sst: standard deviation of the annual sea surface temperature across the 14 years of survey (unit: °C) * cv sst: coefficient of variation (i.e., sd/mean) of annual sea surface temperature across the 14 years of survey (unitless) * mean_chloro : mean chlorophyll content across the 14 years of survey (unit %), see Materials and methods for details * sd chloro: standard deviation of annual chlorophyll content across the 14 years of survey (unit %), see Materials and methods for details * cv chloro: coefficient of variation (sd/mean) of annual chlorophyll content * mean depth: mean site depth (unit: m) - see Materials and methods for details * max depth: maximal site depth (unit: m) - see Materials and methods for details * gravity: an index of human impact on shallow reef ecosystems - see Materials and methods for details ## Code/software We use R version 4.0.0 to process and analyse our data. URLs of the R packages that we used are given in the supplementary table 3 of our submitted manuscript. The script to process and analyse the data is organised in order to make the workflow easily interpretable.