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Asymmetric Biotic Interactions Cannot Be Inferred Without Accounting for Priority Effects

Francisca Powell‐Romero Orcid Logo, Konstans Wells Orcid Logo, Nicholas J. Clark Orcid Logo

Ecology Letters, Volume: 27, Issue: 9

Swansea University Author: Konstans Wells Orcid Logo

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DOI (Published version): 10.1111/ele.14509

Abstract

Understanding biotic interactions is a crucial goal in community ecology and species distribution modelling, and large strides have been made towards improving multivariate computational methods with the aim of quantifying biotic interactions and improving predictions of species occurrence. Yet, whi...

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Published in: Ecology Letters
ISSN: 1461-023X 1461-0248
Published: Wiley 2024
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URI: https://cronfa.swan.ac.uk/Record/cronfa67897
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spelling v2 67897 2024-10-02 Asymmetric Biotic Interactions Cannot Be Inferred Without Accounting for Priority Effects d18166c31e89833c55ef0f2cbb551243 0000-0003-0377-2463 Konstans Wells Konstans Wells true false 2024-10-02 BGPS Understanding biotic interactions is a crucial goal in community ecology and species distribution modelling, and large strides have been made towards improving multivariate computational methods with the aim of quantifying biotic interactions and improving predictions of species occurrence. Yet, while considerable attention has been given to computational approaches and the interpretation of these quantitative tools, the importance of sampling design to reveal these biotic interactions has received little consideration. This study explores the influential role of priority effects, that is, the order of habitat colonisation, in shaping our ability to detect biotic interactions. Using a simple set of simulations, we demonstrate that commonly used cross-sectional co-occurrence data alone cannot be used to make reliable inferences on asymmetric biotic interactions, even if they perform well in predicting the occurrence of species. We then show how sampling designs that consider priority effects can recover the asymmetric effects that are lost when priority effects are ignored. Based on these findings, we urge for caution when drawing inferences on biotic interactions from cross-sectional binary co-occurrence data, and provide guidance on sampling designs that may provide the necessary data to tackle this longstanding challenge. Journal Article Ecology Letters 27 9 Wiley 1461-023X 1461-0248 asymmetric interactions, biotic interactions, community ecology, priority effects, species interactions 1 9 2024 2024-09-01 10.1111/ele.14509 PERSPECTIVE COLLEGE NANME Biosciences Geography and Physics School COLLEGE CODE BGPS Swansea University Another institution paid the OA fee Royal Society: RGS\R2\222152, Australian Research Council: DE210101439 2024-11-04T14:32:02.4671611 2024-10-02T20:08:15.0479691 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Biosciences Francisca Powell‐Romero 0000-0001-9800-3100 1 Konstans Wells 0000-0003-0377-2463 2 Nicholas J. Clark 0000-0001-7131-3301 3 67897__31522__4ad148bb3b484cec8562c05b1c3acbb5.pdf Powell-Romero_etal_2024_EcolLett.pdf 2024-10-02T20:15:44.5246881 Output 7776198 application/pdf Version of Record true © 2024 The Author(s). This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License. true eng http://creativecommons.org/licenses/by-nc/4.0/ 282 Francisca Powell-Romero 0000-0001-9800-3100 francisca.powell@uq.net.au true https://zenodo.org/records/13363723 false 283 true https://zenodo.org/records/13363723 false
title Asymmetric Biotic Interactions Cannot Be Inferred Without Accounting for Priority Effects
spellingShingle Asymmetric Biotic Interactions Cannot Be Inferred Without Accounting for Priority Effects
Konstans Wells
title_short Asymmetric Biotic Interactions Cannot Be Inferred Without Accounting for Priority Effects
title_full Asymmetric Biotic Interactions Cannot Be Inferred Without Accounting for Priority Effects
title_fullStr Asymmetric Biotic Interactions Cannot Be Inferred Without Accounting for Priority Effects
title_full_unstemmed Asymmetric Biotic Interactions Cannot Be Inferred Without Accounting for Priority Effects
title_sort Asymmetric Biotic Interactions Cannot Be Inferred Without Accounting for Priority Effects
author_id_str_mv d18166c31e89833c55ef0f2cbb551243
author_id_fullname_str_mv d18166c31e89833c55ef0f2cbb551243_***_Konstans Wells
author Konstans Wells
author2 Francisca Powell‐Romero
Konstans Wells
Nicholas J. Clark
format Journal article
container_title Ecology Letters
container_volume 27
container_issue 9
publishDate 2024
institution Swansea University
issn 1461-023X
1461-0248
doi_str_mv 10.1111/ele.14509
publisher Wiley
college_str Faculty of Science and Engineering
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hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Biosciences, Geography and Physics - Biosciences{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Biosciences
document_store_str 1
active_str 0
description Understanding biotic interactions is a crucial goal in community ecology and species distribution modelling, and large strides have been made towards improving multivariate computational methods with the aim of quantifying biotic interactions and improving predictions of species occurrence. Yet, while considerable attention has been given to computational approaches and the interpretation of these quantitative tools, the importance of sampling design to reveal these biotic interactions has received little consideration. This study explores the influential role of priority effects, that is, the order of habitat colonisation, in shaping our ability to detect biotic interactions. Using a simple set of simulations, we demonstrate that commonly used cross-sectional co-occurrence data alone cannot be used to make reliable inferences on asymmetric biotic interactions, even if they perform well in predicting the occurrence of species. We then show how sampling designs that consider priority effects can recover the asymmetric effects that are lost when priority effects are ignored. Based on these findings, we urge for caution when drawing inferences on biotic interactions from cross-sectional binary co-occurrence data, and provide guidance on sampling designs that may provide the necessary data to tackle this longstanding challenge.
published_date 2024-09-01T14:32:00Z
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score 11.035634

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