DOI: 10.5061/dryad.zs7h44jhb
title: Climate warming shifts riverine macroinvertebrate communities to be more sensitive to chemical pollutants

description: Freshwaters are highly threatened ecosystems that are vulnerable to
 chemical pollution and climate change. Freshwater taxa vary in their
 sensitivity to chemicals and changes in species composition can
 potentially affect the sensitivity of assemblages to chemical exposure.
 Here we explore the potential consequences of future climate change on the
 composition and sensitivity of freshwater macroinvertebrate assemblages to
 chemical stressors using the UK as a case study. Macroinvertebrate
 assemblages under end of century (2080-2100) and baseline (1980-2000)
 climate conditions were predicted for 608 UK sites for four climate
 scenarios corresponding to mean temperature changes of 1.28°C to 3.78°C.
 Freshwater macroinvertebrate toxicity data were collated for 19 chemicals
 and the hierarchical Species Sensitivity Distribution (hSSD) model was
 used to predict the sensitivity of untested taxa using relatedness within
 a Bayesian approach. All four future climate scenarios resulted in shifts
 in assemblage composition, with increases in the prevalence of molluscan,
 crustacean and annelid species, and towards increasing insect taxa of
 Odonata, Chironomidae, and Baetidae species. In contrast decreases in were
 projected for Plecoptera, Ephemeroptera (except for Baetidae) and
 Coleoptera species. Shifts in taxonomic composition were associated with
 changes in the percentage of species at risk from chemical exposure. For
 the 3.78°C climate scenario, 76% of all assemblages became more sensitive
 to chemicals and for 18 of the 19 chemicals, the percentage of species at
 risk increased. Climate warming-induced increases in sensitivity were
 greatest for assemblages exposed to metals and were dependent on baseline
 assemblage composition, which varied spatially. Climate warming is
 predicted to result in changes in the use, environmental exposure and
 toxicity of chemicals. Here we show that, even in the absence of these
 climate-chemical interactions, shifts in species composition due to
 climate warming will increase chemical risk and that the impact of
 chemical pollution on freshwater macroinvertebrate biodiversity may double
 or quadruple by the end of the 21st century.
description: # Climate warming shifts riverine macroinvertebrate communities to be more
 sensitive to chemical pollutants Access these data on
 https://doi.org/10.5061/dryad.zs7h44jhb Software/code available at
 https://doi.org/10.5281/zenodo.10811583 Tom Sinclair1, Peter Craig2 and
 Lorraine Maltby1 1 Department of Biosciences, University of Sheffield,
 Alfred Denny Building, Western Bank, Sheffield, S10 2TN, United Kingdom 2
 Department of Mathematical Sciences, Durham University, Upper Mountjoy
 Campus, Stockton Road, Durham DH1 3LE, United Kingdom This work was
 supported by the award of a NERC (Natural Environment Research Council)
 studentship to TMS (1945243) via the ACCE (Adapting to the Challenges of a
 Changing Environment) Doctoral Training Programme. NERC is a section of
 the UKRI (United Kingdom Research and Innovation). ## Data file structure
 Missing values in data are denoted by NA. The files have been broken down
 to the step in pipeline they are produced and used ### UKCP18:
 #### temp\_change\_25km\_rcp26\_2090.csv ####
 temp\_change\_25km\_rcp45\_2090.csv ####
 temp\_change\_25km\_rcp60\_2090.csv ####
 temp\_change\_25km\_rcp85\_2090.csv All of the UKCP18 output files follow
 the same format for each of the climate scenarios of RCP2.6, RCP4.5,
 RCP6.0 and RCP8.5 as reflected in the file titles. Where a value for the
 site could not be determined due to the scale of the UKCP18 data a value
 of 9.96920996838687E+36 was inputted as copied from MetOffice (2019) site
 - RICT site reference code temp - change in daily average air temperature
 in oC between the baseline (1981-2000) and the future (2080–2099) temp_max
 - change in daily maximum air temperature in oC between the baseline
 (1981-2000) and the future (2080–2099) temp_max - change in daily minumum
 air temperature in oC between the baseline (1981-2000) and the future
 (2080–2099) temp_max - change in daily range of air temperature in oC
 between the baseline (1981-2000) and the future (2080–2099), a negative
 value indicates a decrease in the range compared to the baseline ###
 RICT: #### jaccard pairwise.csv Jaccard similarity of the
 taxonomy present between pairs of sites scenario - the site when under the
 baseline (base) or a future (fute_rcpXX, where XX refers to the scenario
 number of RCP2.6, RCP4.5, RCP6.0 and RCP8.5) scenario site_A - RICT site
 reference code site_B - RICT site reference code site A is being compared
 to jaccard - Jaccard similarity between site A and site B #### jaccard
 similarity.csv Jaccard similarity for the taxonomy of a site temporally
 between the baseline and each of the four future scenarios (RCP2.6,
 RCP4.5, RCP6.0 and RCP8.5) site - RICT site reference code prop_base_rcp26
 - Jaccard index for taxonomy calcualted between the site under baseline
 and future RCP2.6 prop_base_rcp45 - Jaccard index for taxonomy calcualted
 between the site under baseline and future RCP4.5 prop_base_rcp60 -
 Jaccard index for taxonomy calcualted between the site under baseline and
 future RCP6.0 prop_base_rcp85 - Jaccard index for taxonomy calcualted
 between the site under baseline and future RCP8.5 ####
 NMDA\_site\_scores.csv A list of the calculated NMDS scores based on the
 taxonomy present for each site and scenario combination NMDS1 - the NMDS1
 axis score NMDS2 - the NMDS2 axis score site_scenario - the RICT site code
 and scenario for which the taxonomy has been used to calculate NMDS values
 site - just the site from site_scenario, RICT site reference code scenario
 - just the scenario from site_scenario, the baseline (base) or a future
 (rcpXX, where XX refers to the scenario number of RCP2.6, RCP4.5, RCP6.0
 and RCP8.5) scenario #### NMDS\_taxa\_scores.csv A list of the average
 NMDS axis scores for each taxa across all the sites where that taxa is
 present taxa - the taxonomic name of the taxa NMDS1 - the NMDS1 axis score
 NMDS2 - the NMDS2 axis score #### site\_sprn\_0-4.csv A list of RICT sites
 and their predicted taxa when run through RICT under baseline conditions
 and for each future scenario and selected by a 40% occurence rate cut-off
 as according to site - the RICT site code taxa - the taxonomic name of the
 taxa predicted by RICT scenario - the site when under the baseline (base)
 or a future (fute_rcpXX, where XX refers to the scenario number of RCP2.6,
 RCP4.5, RCP6.0 and RCP8.5) scenario ####
 site\_sprn\_0-4\_25km\_taxonomy.csv The Linnean taxonomic ranking for all
 the taxa predicted by RICT Kingdom - kingdom of the taxa Phylum_division -
 phylum of the taxa Subphylum - taxonomic level between phylum and class;
 above superclass Subphylum - taxonomic level between phylum and class;
 below subphylum Class - class of the taxa Order - order of the taxa Family
 - family of the taxa Genus - genus of the taxa Latin - species exclusing
 the genus of the taxa taxa_change_sites.csv A presence absence list for
 each site and taxa combination as predicted by RICT for each climate
 scenario site - the RICT site code taxa - the taxonomic name of the taxa
 predicted by RICT base - presence or absence of the taxa at that site
 under the baseline scenario fute_rcp26 - presence or absence of the taxa
 at that site under the future RCP2.6 scenario fute_rcp45 - presence or
 absence of the taxa at that site under the future RCP4.5 scenario
 fute_rcp60 - presence or absence of the taxa at that site under the future
 RCP6.0 scenario fute_rcp8.5 - presence or absence of the taxa at that site
 under the future RCP8.5 scenario #### taxa\_change\_sites\_long.csv A
 presence absence list for each site and taxa combination as predicted by
 RICT for each climate scenario in long format which also includes some
 higher taxonomic rankings, whether that taxa is gained or lost compared to
 the baseline and some clade groupings used for plotting and data analysis
 site - the RICT site code taxa - the taxonomic name of the taxa predicted
 by RICT phylum - phylum of the taxa class - class of the taxa order -
 order of the taxa scenario - the site when under a future (fute_rcpXX,
 where XX refers to the scenario number of RCP2.6, RCP4.5, RCP6.0 and
 RCP8.5) scenario presence - a binary 1 or 0 refering to the presence (1)
 or absence (0) of a taxa at that site and scenario combination change - A
 gain (Gain), loss (Loss) or no change (NA) in the presence of that taxa at
 that site for that scenario when compared to the baseline clade -
 taxonomic grouping used for plotting and data analysis
 taxa_change_sites_matrix.csv The complete presence absence matrix used to
 fit the NMDS for taxa and the corresponding site and scenario combination
 site_scenario - the RICT site code and scenario for which the taxonomy has
 been used to calculate NMDS values, the scenario is either a baseline
 (base) or a future (rcpXX, where XX refers to the scenario number of
 RCP2.6, RCP4.5, RCP6.0 and RCP8.5) scenario all other column names refer
 to each of the taxa predicted by RICT (full taxonomy listed in
 site_sprn_0-4_25km_taxonomy.csv) ### hSSD: #### tax\_merged.csv
 The Linnean taxonomic ranking for all the taxa predicted by RICT or
 present within the toxicity datasets Kingdom - kingdom of the taxa
 Phylum_division - phylum of the taxa Subphylum - taxonomic level between
 phylum and class; above superclass Subphylum - taxonomic level between
 phylum and class; below subphylum Class - class of the taxa Order - order
 of the taxa Family - family of the taxa Genus - genus of the taxa Latin -
 species exclusing the genus of the taxa #### r2\_sig.csv R squared values
 for the leave one out test for each of the 19 chemicals considered and
 whether the R squared value was significantly different from 0 chem -
 chemical abbreviation, the following chemicals (followed by addreviation
 used in file name) are included: azinphos-methyl,AZM carbofuran,CBF
 carbaryl,CBL cadmium,Cd copper, Cu DDT,DDT deltamethrin,DTM diazinon,DZN
 endosulfan,EDS fenitrothion,FNT lead,Pb lindane,LIN malathion,MLT
 methoxychlor,MXC nickel,Ni parathion-ethyl,PAE parathion-methyl,PAM
 pentachlorophenol,PCP zinc, Zn model - the version of the hSSD model
 database used for predictions r2 - R squared value comparing the predicted
 against actual toxicity values for each taxa with sensitivity data for
 every chemical n - number of taxa with sensitivity data for that chemical
 t -the t-value of the test to assess significance of the R squared
 compared to 0 crit - the critical t-value for a dataset of size name sig -
 whether the chemical dataset is significantly (sig) or not (not sig)
 different from 0 #### PAF\_RICT\_25km\_all\_chems.csv The list of
 proportion affect fraction (PAF) for every site and scenario combination
 site - the RICT site code HC5 - the calculated hazardous concentration
 affecting 5% of taxa for this site and scenario lower - the 95% lower
 confidence interval for the calculated hazardous concentration affecting
 5% of taxa for this site and scenario HC5_50th - the 50th percentile for
 the calculated hazardous concentration affecting 5% of taxa for this site
 and scenario upper - the 95% upper confidence interval for the calculated
 hazardous concentration affecting 5% of taxa for this site and scenario
 PAF - the proportion affect fraction of taxa when exposed to the hazardous
 concentration of the baseline for that site chem - chemical abbreviation,
 the following chemicals (followed by addreviation used) are included:
 azinphos-methyl,AZM carbofuran,CBF carbaryl,CBL cadmium,Cd copper, Cu
 DDT,DDT deltamethrin,DTM diazinon,DZN endosulfan,EDS fenitrothion,FNT
 lead,Pb lindane,LIN malathion,MLT methoxychlor,MXC nickel,Ni
 parathion-ethyl,PAE parathion-methyl,PAM pentachlorophenol,PCP zinc, Zn
 scenario - the site when under a future (rcpXX, where XX refers to the
 scenario number of RCP2.6, RCP4.5, RCP6.0 and RCP8.5) scenario change -
 direction of change compared to baseline (i.e. PAF &gt; or &lt; 0.05) moa
 - mode of action if known moa2 - mode of action (alternative) if known
 type - the type of chemical; either insecticide, metal or biocide temp -
 the average temperature change in oC associated with that future scenario
 ### tox\_data.zip A zip folder containing the toxicity data for
 the 25 chemicals for which toxicity data was finalised. All files have the
 same format : latin - the latin species name (genus and species) for the
 taxa tested lconc - the log10 sensitivity of the species to that chemical
 in ug/L The following chemicals (followed by addreviation used in file
 name) are included: azinphos-methyl,AZM benzamine,BNZ carbofuran,CBF
 carbaryl,CBL cadmium,Cd copper, Cu DDT,DDT deltamethrin,DTM diazinon,DZN
 endrin,EDR endosulfan,EDS fluoranthene,FLN fenitrothion,FNT lead,Pb
 lindane,LIN malathion,MLT methoxychlor,MXC nickel,Ni nonyl-phenol,NPH
 parathion-ethyl,PAE parathion-methyl,PAM pentachlorophenol,PCP phenol,PHN
 zinc, Zn ### 01\_ukcp18.zip ### 02\_RICT.zip ###
 03\_hSSD.zip Results were gained from running three R projects in
 sequence, ukcp18, RICT and hSSD. These have been uploaded here numerically
 as 01, 02 and 03 respectively for the R scripts and input files necessary
 to reproduce the results. The R scripts in each zip file are also
 numerically ordered by the order in which they should be run. The output
 files used in the analysis and reporting of this manuscript have been
 uploaded below the zip files. By running the input and R zip files for
 each project in order, the full set of results can be reobtained. Note
 that as the Bayesian MCMC sample runs are random, repeated results may
 differ slightly from those in the manuscript. ## Access Information Data
 were adapted or derived from the following sources: UKCP18 - Met Office.
 (2019). Met Office Hadley Centre (2019): UKCP local projections on a 5 km
 grid over the UK for 1980–2080.
 https://catalogue.ceda.ac.uk/uuid/e304987739e RICT - Environment Agency
 (EA), NIEA, NRW, and SEPA. (2021). River Invertebrate Classification Tool
 (RICT). Freshwater Biology Association.
 https://www.fba.org.uk/FBA/Public/Discover-and-Learn/Projects/RIVPACS_Landing.aspx available at: https://www.fba.org.uk/rivpacs-and-rict/river-invertebrate-classification-tool hSSD model - Craig, P. S. (2013). Exploring novel ways of using species sensitivity distributions to establish PNECs for industrial chemicals: Final report to project steering group 3 April 2013. Technical report. http://dro.dur.ac.uk/13383/ Taxonomy - Chamberlain, S. A., & Szöcs, E. (2013). Taxize: Taxonomic search and retrieval in R [version 2; peer review: 3 approved]. F1000Research, 2, 191. https://doi.org/10.12688/f1000research.2-191.v2 Schoch, C. L., Ciufo, S., Domrachev, M., Hotton, C. L., Kannan, S., Khovanskaya, R., & Leipe, D. (2020). NCBI taxonomy: A comprehensive update on curation resources and tools. Database. https://doi.org/10.1093/database/baaa062 Research Domain: 1.6 Biological sciences