DOI: 10.5061/dryad.p5hqbzm1b
title: A globally influential area-condition metric is a poor proxy for invertebrate biodiversity

description: There is increasing demand for standardised, easy-to-use metrics to assess
 progress towards achieving biodiversity targets and the effectiveness of
 ecological compensation schemes. Biodiversity metrics based on combining
 habitat area and habitat condition scores are proliferating rapidly, but
 there is limited evidence on how they relate to ecological outcomes. Here,
 we test the relationship between the statutory biodiversity metric used
 for Biodiversity Net Gain (BNG) in England — and as the basis for new
 biodiversity credit systems around the world — and invertebrate richness,
 abundance, and community composition. We find that the combined
 area-condition BNG metric does not capture the value of arable farmland
 and grassland sites for invertebrate biodiversity: invertebrate
 communities were highly variable across sites that had the same type and
 condition under the BNG metric. We found no reliable relationship between
 scores under the metric and either invertebrate abundance or species
 richness, with the risk of the metric undervaluing sites of high
 invertebrate value. Our results highlight the need to incorporate factors
 beyond habitat type and condition into site evaluations, and to complement
 metric use with species-based surveys. This dataset contains the
 invertebrate abundance and richness data collected and used in the
 analysis of this paper.
description: # A globally influential area-condition metric is a poor proxy for
 invertebrate biodiversity Dataset DOI:
 [10.5061/dryad.p5hqbzm1b](10.5061/dryad.p5hqbzm1b) ## Description of the
 data and file structure The data was collected across a range of parcels
 within different sites using pitfall traps. Pitfall traps were used to
 sample ground invertebrate abundance and species richness. In year 1
 (2022), just carabid species richness was analysed. In year 2 (2023) DNA
 metabarcoding was used to look at total ground invertebrate species
 richness. Invertebrate richness and abundance was analysed against
 England's statutory biodiversity metric scoring
 (distinctiveness*condition scoring).  ## Files and variables ### File:
 JAPPL-2025-00285-Data_v2.xlsx ### **Description:** Datasheets used in the
 R code for analysis. ### Sheets #### **Sheet 1: Y1 data:** Data on ground
 invertebrate abundance and richness for analysis from year 1 (2022).
 Includes distinctiveness*condition scoring values from the statutory
 biodiversity metric for each parcel. **Variables: Parcel_ID**: unique
 identifier for each habitat parcel (this is consistent throughout all
 sheets), **Site:** identifies which landholding each habitat parcel
 belongs to, **Habitat type:** UK Habitat Classification type (UKHab) of
 the habitat parcel, **Distinctiveness:** habitat distinctiveness as
 determined by England Statutory Biodiversity Metric, **Condition:**
 habitat condition measured in the field as determined by England Statutory
 Biodiversity Metric, **Distinctiveness.Condition:** values for
 distinctiveness and condition multiplied together,
 **All.Invert.Abundance:** total invertebrate abundance values for each
 habitat parcel, **Carabid.abundance:** carabid beetle abundance values for
 each habitat parcel, **Spider.abundance:** spider abundance values for
 each habitat parcel, **Rarefied.Richness:** rarefied species richness
 values for each habitat parcel, All following columns denote the abundance
 of each carabid species listed in the column name, which were used to
 generate species richness values. #### **Sheet 2: Y2 Abundance and raw
 richness:** Data on ground invertebrate abundance and raw species richness
 values for analysis from year 2 (2023). Includes distinctiveness*condition
 scoring values from the statutory biodiversity metric for each parcel.
 **Variables: Parcel_ID**: unique identifier for each habitat parcel (this
 is consistent throughout all sheets), **Site:** identifies which
 landholding each habitat parcel belongs to, **Replicate:** refers to which
 sampling period data was taken from (1= May, 2=June, 3= August,
 Total=summed 3 replicates), **Habitat type:** UK Habitat Classification
 type (UKHab) of the habitat parcel, **Distinctiveness:** habitat
 distinctiveness as determined by England Statutory Biodiversity Metric,
 **Condition:** habitat condition measured in the field as determined by
 England Statutory Biodiversity Metric,** Num.Pitfalls**: number of pitfall
 traps summed together for the total values, **Distinctiveness.Condition:**
 values for distinctiveness and condition multiplied together,
 **All.Invert.Abundance_y2:** total invertebrate abundance values for each
 habitat parcel, **Carabid.abundance_y2:** carabid beetle abundance values
 for each habitat parcel, **Spider.abundance_y2:** spider abundance values
 for each habitat parcel, **Spider.Richness, Carabid.Richness,
 Rove.Richness, Collembola.Richness, Gastropod.Richness, and
 Hemiptera.Richness** all refer to the raw species richness value for the
 summed replicates for each habitat parcel. #### Sheet 3: Y2 Metabarcoding
 target OTUs: Operational Taxonomic Unit (OTU) data for target taxa from
 year 2 (2023) **Variables:** **Sequence**: genetic sequence used to make
 species ID, **Kingdom, Phylum, Class, Order, Family, Genus, and Species**
 columns refer to the taxonomy of the identified species. **Further
 columns** list the presence of this sequence in each sample. Column name
 denotes the habitat parcel name (e.g., 1_2) and the month in which the
 sample was collected (May June or August) #### Sheet 4: Y2 species
 occurrence: Species-level identifications derived from OTUs from year 2
 (2023). **Variables:** This spreadsheet is formatted so that it runs the
 code for species richness rarefaction in iNEXT. The first row is the
 samples, with each sample being a unique habitat parcel (same ID structure
 as above). The second row is the number of pitfall traps in each habitat
 parcel. Each row after that corresponds to a species and how many of the
 replicates it appeared in (1,2,3). #### **Sheet 5: Y2 rarefied species
 richness:** The outcome of the species richness rarefaction code.
 **Variables:** **Parcel_ID:** unique habitat parcel identifier, **t:**
 number of pitfall traps at which diversity estimate is calculated at,
 **Method:** rarefaction or extrapolation, **Order.q:** specifies the type
 of diversity being estimated, in this case, q=0 means that species
 richness is being calculated. **SC:** sampling coverage,
 **Rarefied.richness:** the rarefied species richness value, **qD.LCL:**
 lower confidence limit of the species richness value, **qD:UCL:** upper
 confidence limit. All other variables as defined in sheet 2. #### Sheet 6:
 Y2 rarefied OTUs: Rarefied OTU values from year 2 (2023). Variables: as
 above but using Operational Taxonomic Unit (OTU) richness rather than
 species richness.  #### Sheet 7: Y2 family OTUs: Family-level OTU data
 used for Non-metric multidimensional scaling (NMDS) analysis from year 2
 (2023).  **Variables: Samples:** denotes the unique parcel identifier,
 **Replicate:** 1,2,3 to denote whether sample was collected in May, June,
 or August. Each subsequent column represents a taxonomic family and how
 many OTUs from that family were present in that sample. Within the sheets
 NA is used to denote missing data (e.g., due to interference with
 samples), or for values which aren't relevant to particular entries.
 "0" is used to denote zero. #### Sheet 8: Variables NMDS:
 Variables appended to the 3-dimensional NMDS plots. Variables are named as
 in sheet 2. 
 
 ### File: JAPPL-2025-00285_supplementary_data.csv **Description:** Data
 used for the supplementary bayesian analysis **Variables: May.Parcel.ID,
 June.Parcel.ID, August.Parcel.ID:** parcel IDs for each 2023 replicate,
 **May.Invert.Abundance, June.Invert.Abundance, Aug.Invert.Abundance:**
 invertebrate abundance totals for the 3 replicates in 2023,
 **May.Distinctiveness.Condition, June.Distinctiveness.Condition,
 Aug.Distinctiveness.Condition**: Distinctiveness multiplied by Condition
 scores as determined using England's Statutory Biodiversity Metric,
 **May.Site, June.Site, Aug.Site:** Landholding which each habitat parcel
 is contained within, **SR.Parcel.ID:** unique parcel ID for rarefied
 species richness analysis, **Site.SR:** landholding each SR.Parcel is
 contained within, **Rarefied.richness.y2:** rarefied species richness
 values from 2023 iNEXT analysis,
 **SR.distinctiveness.condtion:** Distinctiveness multiplied by Condition
 scores as determined using England's Statutory Biodiversity Metric.
 **Parcel.ID.y1**: habitat parcel IDs for 2022 data, **Site.y1**:
 landholdings with 2022 habitat parcels are contained within,
 **Invert.abundance.y1**: invertebrate abundance values from 2022,
 **Rarefied.richness.y1:** Rarefied species richness value from year 1,
 **Distinctiveness.condtion.y1**: Distinctiveness multiplied by Condition
 scores as determined using England's Statutory Biodiversity Metric.
 ## Code/software Data is stored in a .xlsx file. Data analysis was
 conducted in R, using the following packages:  library(dplyr)
 library(ggplot2) library(iNEXT) library(MASS) library(vegan)
 library(tidyverse) library(lme4) library(scatterplot3d) library(DHARMa)
 library(simr) library(brms)