eprintid: 10107823
rev_number: 16
eprint_status: archive
userid: 608
dir: disk0/10/10/78/23
datestamp: 2021-09-01 15:52:15
lastmod: 2021-10-08 21:58:10
status_changed: 2021-09-01 15:52:15
type: working_paper
metadata_visibility: show
creators_name: Benjamin, B
creators_name: Drew, P
creators_name: Georgina, M
creators_name: Murrell, D
title: Ecological theory predicts ecosystem stressor interactions in freshwater communities, but highlights the strengths and weaknesses of the additive null model
ispublished: pub
divisions: UCL
divisions: B02
divisions: C08
divisions: D09
divisions: F99
keywords: Meta-analysis, Freshwater, Synergy, Multiple Factors, Lotka-Volterra, Ecological Surprise, Multiple Stressors, Theoretical Ecology, Sampling Variation, Food chain
note: This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions.
abstract: Understanding and predicting how multiple co-occurring environmental stressors combine to affect biodiversity and ecosystem services is an on-going grand challenge for ecology. So far progress has been made through accumulating large numbers of smaller-scale individual studies that are then investigated by meta-analyses to look for general patterns. In particular there has been an interest in checking for so-called ecological surprises where stressors interact in a synergistic manner. Recent reviews suggest that such synergisms do not dominate, but few other generalities have emerged. This lack of general prediction and understanding may be due in part to a dearth of ecological theory that can generate clear hypotheses and predictions to tested against empirical data. Here we close this gap by analysing food web models based upon classical ecological theory and comparing their predictions to a large (546 interactions) dataset for the effects of pairs of stressors on freshwater communities, using trophic- and population-level metrics of abundance, density, and biomass as responses. We find excellent overall agreement between the stochastic version of our models and the experimental data, and both conclude additive stressor interactions are the most frequent, but that meta-analyses report antagonistic summary interaction classes. Additionally, we show that the statistical tests used to classify the interactions are very sensitive to sampling variation. It is therefore likely that current weak sampling and low sample sizes are masking many non-additive stressor interactions, which our theory predicts to dominate when sampling variation is removed. This leads us to suspect ecological surprises may be more common than currently reported. Our results highlight the value of developing theory in tandem with empirical tests, and the need to examine the robustness of statistical machinery, especially the widely-used null models, before we can draw strong conclusions about how environmental drivers combine.
date: 2020-08-10
publisher: BioRxiv
official_url: https://doi.org/10.1101/2020.08.10.243972
oa_status: green
full_text_type: pub
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1807930
doi: 10.1101/2020.08.10.243972
lyricists_name: Murrell, David
lyricists_id: DJMUR72
actors_name: Murrell, David
actors_id: DJMUR72
actors_role: owner
full_text_status: public
place_of_pub: Cold Spring Harbor, NY, USA
pages: 39
citation:        Benjamin, B;    Drew, P;    Georgina, M;    Murrell, D;      (2020)    Ecological theory predicts ecosystem stressor interactions in freshwater communities, but highlights the strengths and weaknesses of the additive null model.                    BioRxiv: Cold Spring Harbor, NY, USA.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10107823/1/2020.08.10.243972v1.full-1.pdf