Data from: Ecosystem functioning during biodiversity loss and recovery
Data files
May 22, 2024 version files 104.02 KB
May 22, 2024 version files 104.01 KB
Abstract
Anthropogenic biodiversity loss can impair ecosystem functioning. Human activities are often managed with the aim of reversing biodiversity loss and its associated functional impacts. However, it is currently unknown whether biodiversity–ecosystem function (BEF) relationships observed during biodiversity recovery are the same as those observed during biodiversity loss. This will depend on how species extirpation and recolonisation sequences compare and how different species influence ecosystem functioning. Using data from a marine benthic invertebrate community, we modelled how bioturbation potential – a proxy for benthic ecosystem functioning – changes along biodiversity loss and recovery sequences governed by species’ sensitivity to physical disturbance and recolonisation capability, respectively. BEF relationships for biodiversity loss and recovery were largely the same despite species extirpation and recolonisation sequences being different. This held true irrespective of whether populations were assumed to exhibit compensatory responses as species were removed or added. These findings suggest that the functional consequences of local biodiversity loss can be reversed by alleviating its drivers, as different species present at comparable levels of species richness during biodiversity loss and recovery phases have similar functional effects. Empirically verifying and determining the generality of our model-based results are potential next steps for future research.
https://doi.org/10.5061/dryad.r7sqv9sm8
Benthic invertebrate community data (population abundance and biomass of species) were collected using a 0.1 square metre Day grab from an area of offshore mud within the Fladen Ground, northern North Sea. Sixty stations were sampled over six survey boxes in April 2015. Species were assigned biological trait information, obtained from published databases, denoting their effects on ecosystem functioning (via bioturbation), their sensitivity to physical disturbance, and their capacity to recolonise post-disturbance. These data were used to characterise an initial community and simulate the impact of biodiversity loss and recovery on benthic ecosystem functioning using a probabilistic model. Correlations between species sensitivity, recolonisation capability, and population bioturbation potential were inspected to help interpret the results.
Description of the data and file structure
Study area metadata are in the file:
Clare et al. Study area meta-data.xlsx
Variables:
Box - the survey boxes (A-F) from which benthic community samples were collected
Station - the sampling stations within each survey box. The letter denotes the box and the number denotes the station number (1-10 for each box)
Latitude - the latitude of the sampling stations in decimal degrees, using the World Geodetic System 1984 (WGS84)
Longitude - the longitude of the sampling stations in decimal degrees, using WGS84
Depth - the depth of the seabed at each sampling station, measured using a Conductivity-Temperature-Depth (CTD) probe at the time of benthic invertebrate community sampling
Gravel - the percent of the seabed sediment made up of gravel (> 2 mm diameter particles), based on a homogenised sediment sample collected from each station using a 0.1 square metre Day grab immediately prior to the same gear being used to sample the benthic invertebrate community
Sand - the percent of the seabed sediment made up of sand (0.063–2 mm diameter particles), based on the sampling method described above for gravel
Mud - the percent of the seabed sediment made up of mud (< 0.063 mm diameter particles), based on the sampling method described above for gravel
Date - the date (day/month/year) that benthic invertebrate community samples were collected from each station
Benthic invertebrate data used to characterize the initial community are in the file:
Clare et al. Abundance & Biomass data used to describe initial community.xlsx
This dataset contains 2 tabs: the first is a matrix of the population abundance (individuals per 0.1 square metre) of each species (or higher level taxon) at each sampling station and associated survey box; the second provides an analogous matrix for the population biomass (grams wet weight per 0.1 square metre) of each species.
Variables:
Box - the survey boxes (A-F) from which benthic community samples were collected
Station - the sampling stations within each survey box. The letter denotes the box and the number denotes the station number (1-10 for each box)
Taxa - the species (or higher level taxa) recorded across the 60 stations and six survey boxes during the survey used to describe the initial community
The initial community data used to simulate the effect of biodiversity loss and recovery on ecosystem functioning are in the file:
Clare et al. Data for simulations.csv
Variables:
Taxa - the species (or higher level taxa; hereafter referred to as species) recorded across the 60 stations and six survey boxes during the survey used to describe the initial community
Bavg - the average population biomass (grams wet weight per square metre) of each species in the initial community
Aavg - average population abundance (number of individuals per square metre) of each species in the initial community
Bind - the average body mass (grams wet weight per individual) of species in the initial community
Mi - the mobility mode of each species, obtained from Queirós et al. (2013) A bioturbation classification of European marine infaunal invertebrates. Ecology and Evolution 3, 3958-3985. This information is used to calculate the bioturbation potential at the individual, population, and community levels.
Ri - sediment reworking mode, obtained from Queirós et al. (2013) A bioturbation classification of European marine infaunal invertebrates. Ecology and Evolution 3, 3958-3985. This information is used to calculate the bioturbation potential at the individual, population, and community levels.
Sensitivity - the sensitivity of each species to physical disturbance, inferred from biological traits following the approach of Bolam et al. (2014) Sensitivity of macrobenthic secondary production to trawling in the English sector of the Greater North Sea: A biological trait approach. Journal of Sea Research 85, 162-177. Trait information was obtained from a trait database that can be obtained via Clare et al. (2022) Biological traits of marine benthic invertebrates in Northwest Europe. Scientific Data 9, 339.
Recolonisation.capability - the capability of each species to recolonise post-disturbance, inferred from biological traits following the approach of Bolam et al. (2014) Sensitivity of macrobenthic secondary production to trawling in the English sector of the Greater North Sea: A biological trait approach. Journal of Sea Research 85, 162-177. Trait information was obtained from a trait database that can be obtained via Clare et al. (2022) Biological traits of marine benthic invertebrates in Northwest Europe. Scientific Data 9, 339.
The data used to analyse correlations between species sensitivity, recolonisation capabiliy, and population bioturbation potential are in the file:
Clare et al. Data for correlations.csv
Variables:
Taxa - the species (or higher level taxa; hereafter referred to as species) recorded across the 60 stations and six survey boxes during the survey used to describe the initial community
Sensitivity - the sensitivity of each species to physical disturbance, inferred from biological traits following the approach of Bolam et al. (2014) Sensitivity of macrobenthic secondary production to trawling in the English sector of the Greater North Sea: A biological trait approach. Journal of Sea Research 85, 162-177. Trait information was obtained from a trait database that can be obtained via Clare et al. (2022) Biological traits of marine benthic invertebrates in Northwest Europe. Scientific Data 9, 339.
Recolonisation.capability - the capability of each species to recolonise post-disturbance, inferred from biological traits following the approach of Bolam et al. (2014) Sensitivity of macrobenthic secondary production to trawling in the English sector of the Greater North Sea: A biological trait approach. Journal of Sea Research 85, 162-177. Trait information was obtained from a trait database that can be obtained via Clare et al. (2022) Biological traits of marine benthic invertebrates in Northwest Europe. Scientific Data 9, 339.
Biomass - the average population biomass (grams wet weight per square metre) of each species in the initial community
BPi - the bioturbation potential of each species in the initial community at the individual level
Bpp - the bioturbation potential of each species in the initial community at the population level (i.e. BPi x population abundance (individuals per square metre))
log10.BPi - the individual bioturbation potential of each species in the initial community, transformed by log base 10
log10.Bpp - the population bioturbation potential of each species in the initial community, transformed by log base 10
Bpp.to.Biomass - the ratio of the population bioturbation potential of each species to its population biomass in the initial community
log10.Bpp.to.Biomass - the ratio of the population bioturbation potential of each species to its population biomass in the initial community, transformed by log base 10
Code/Software
The code used to run the model simulations is in the file:
Clare et al. BEF code - Simulations
The code used to fit trend lines to the simulated data is in the file:
Clare et al. BEF code - Plots & GAMs
The code used to analyse correlations between species sensitivity, recolonisation capability, and population bioturbation potential is in the file:
Clare et al. BEF code - Correlations between Sen, Rec & BPp
Benthic invertebrate community data (population abundance and biomass of species) were collected using a 0.1 square metre Day grab from an area of offshore mud within the Fladen Ground, northern North Sea. Sixty stations were sampled over six survey boxes in April 2015. Species were assigned biological trait information that reflects their effects on ecosystem functioning (via bioturbation), their sensitivity to physical disturbance, and their capacity to recolonise post-disturbance using published databases (Queirós et al. 2013; Clare et al. 2022). These data were used to characterise an initial community and simulate the impact of biodiversity loss and recovery on benthic ecosystem functioning using a probabilistic model (sensu Solan et al. 2004, 2012; Thomsen et al. 2017; Garcia et al., 2021). Correlations between species sensitivity, and recolonisation capability, and population bioturbation potential were inspected to help interpret the results. Detailed descriptions of data collection, processing, and analysis are provided in the main article linked to the accompanying datasets.
References:
Clare DS, Bolam SG, McIlwaine PSO, Garcia C, Murray JM, Eggleton JE. 2022. Biological traits of marine benthic invertebrates in Northwest Europe. Scientific Data 9, 339.
Garcia C, Solan M, Bolam SG, Sivyer D, Parker R, Godbold JA. 2021. Exploration of multiple post-extinction compensatory scenarios improves the likelihood of determining the most realistic ecosystem future. Environmental Research Communications 3, 045001.
Queirós AM, Birchenough SNR, Bremner J, Godbold JA, Parker RE, Romero-Ramirez A, Reiss H, Solan M, Somerfield PJ, van Colen C, van Hoey G, Widdicombe S. 2013. A bioturbation classification of European marine infaunal invertebrates. Ecology and Evolution 3, 3958 – 3985.
Solan M, Cardinale BJ, Downing AL, Engelhardt KA, Ruesink JL, Srivastava DS. 2004. Extinction and ecosystem function in the marine benthos. Science 306, 1177 – 1180.
Solan M, Scott F, Dulvy NK, Godbold JA, Parker R. 2012. Incorporating extinction risk and realistic biodiversity futures: implementation of trait-based extinction scenarios. In Marine Biodiversity and Ecosystem Functioning: frameworks, methodologies, and integration, ed. Solan, M., Aspden RJ, Patterson DM, pp. 127 – 148. Oxford University Press, Oxford, UK.
Thomsen MS, Garcia C, Bolam SG, Parker R, Godbold, JA, Solan M. 2017. Consequences of biodiversity loss diverge from expectation due to post-extinction compensatory responses. Scientific Reports 7, 43695.