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Biotic Interactions Are an Unexpected Yet Critical Control on the Complexity of an Abiotically Driven Polar Ecosystem Biotic interactions are an unexpected yet critical control on the complexity of an abiotically driven polar ecosystem Lee, C. K., Laughlin, D. C., Bottos, E. M., Caruso, T., Joy, K., Barrett, J. E., Brabyn, L., Nielsen, U. N., Adams, B. J., Wall, D. H., Hopkins, D. W., Pointing, S. B., McDonald, I. R., Cowan, D. A., Banks, J. C., Stichbury, G. A., Jones, I., Zawar-Reza, P., Katurji, M., ... Cary, S. C. (2019). Biotic interactions are an unexpected yet critical control on the complexity of an abiotically driven polar ecosystem. Communications Biology, (2), [62]. https://doi.org/10.1038/s42003-018-0274-5 Published in: Communications Biology Document Version: Publisher's PDF, also known as Version of record Queen's University Belfast - Research Portal: Link to publication record in Queen's University Belfast Research Portal Publisher rights © 2019 The Authors. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. General rights Copyright for the publications made accessible via the Queen's University Belfast Research Portal is retained by the author(s) and / or other copyright owners and it is a condition of accessing these publications that users recognise and abide by the legal requirements associated with these rights. Take down policy The Research Portal is Queen's institutional repository that provides access to Queen's research output. Every effort has been made to ensure that content in the Research Portal does not infringe any person's rights, or applicable UK laws. If you discover content in the Research Portal that you believe breaches copyright or violates any law, please contact [email protected]. Download date:01. Oct. 2021 ARTICLE https://doi.org/10.1038/s42003-018-0274-5 OPEN Biotic interactions are an unexpected yet critical control on the complexity of an abiotically driven polar ecosystem Charles K. Lee et al.# 1234567890():,; Abiotic and biotic factors control ecosystem biodiversity, but their relative contributions remain unclear. The ultraoligotrophic ecosystem of the Antarctic Dry Valleys, a simple yet highly heterogeneous ecosystem, is a natural laboratory well-suited for resolving the abiotic and biotic controls of community structure. We undertook a multidisciplinary investigation to capture ecologically relevant biotic and abiotic attributes of more than 500 sites in the Dry Valleys, encompassing observed landscape heterogeneities across more than 200 km2. Using richness of autotrophic and heterotrophic taxa as a proxy for functional complexity, we linked measured variables in a parsimonious yet comprehensive structural equation model that explained significant variations in biological complexity and identified landscape-scale and fine-scale abiotic factors as the primary drivers of diversity. However, the inclusion of lin- kages among functional groups was essential for constructing the best-fitting model. Our findings support the notion that biotic interactions make crucial contributions even in an extremely simple ecosystem. Correspondence and requests for materials should be addressed to S.C.C. (email: [email protected]). #A full list of authors and their affiliations appears at the end of the paper. COMMUNICATIONS BIOLOGY | (2019) 2:62 | https://doi.org/10.1038/s42003-018-0274-5 | www.nature.com/commsbio 1 ARTICLE COMMUNICATIONS BIOLOGY | https://doi.org/10.1038/s42003-018-0274-5 nderstanding how ecosystems self-organize at landscape soils20,21,24–27. The extreme environmental conditions and lack of Uscales has long been a formidable challenge in ecology1,2 evidence for critical biotic interactions have made ecologists since the trophic complexity of most ecosystems obscures hypothesize that these ecosystems are fundamentally constrained the relative contributions of the biotic and abiotic factors reg- by abiotic factors and host some of the simplest trophic structures ulating biological diversity3–6. Given the fundamental effects of on Earth21,23,24,28,29 (Supplementary Figure 1). These unique biodiversity on ecosystem function7, a critical task is to resolve characteristics make the Dry Valleys a model system for resolving the relative importance of three sets of ecological factors that the roles of abiotic and biotic factors that shape community drive community structure: abiotic environmental filtering, dis- structure. persal limitation in space, and biotic interactions (e.g., competi- In this study, we analyzed data collected by the New Zealand tion, mutualism, and trophic relationships)2,8. Thorough and Terrestrial Antarctic Biocomplexity Survey (nzTABS, https:// spatially explicit descriptions of these ecosystem drivers are ictar.aq/nztabs-science/), which was initiated during the Inter- required for this task, but the complexity of most ecosystems national Polar Year 2007–2008. This project draws on a wide creates enormous logistical obstacles. range of international expertise to profile the biology, geochem- Biotic interactions, including those among higher eukaryotes istry, geology, and climate of the Dry Valleys, and has completed and those between higher eukaryotes and microorganisms, have a spatially and biologically comprehensive landscape-scale survey long been recognized as important drivers of ecosystem structure that aims to resolve the biotic and abiotic control of ecosystem and function6,9. However, attempts to capture biotic interactions complexity. We then used structural equation modelling (SEM) at the ecosystem level have often been restricted both by sampling to analyze the comprehensive collection of geological, geo- approaches and/or the expertise of individual investigators10, and graphical, geochemical, hydrological, and biological variables studies have largely focused on testing hypotheses associated with measured systematically across three Dry Valleys of Antarctica. pre-identified biotic interactions or ecosystem components6,11–15. Structural equation modelling (SEM), which is built on path A comprehensive investigation of abiotic and biotic interactions analysis and factor analysis, is one of the most useful statistical within an ecosystem therefore requires a sampling design that is approaches to disentangle numerous factors of influence30 and consistent across all major biological groups present. It also develop deeper causal understanding from observational data31. requires an explicitly interdisciplinary and comprehensive Users of SEM translate theoretical frameworks (informed by approach for data collection and analysis of both abiotic and knowledge of the ecosystem) into explicit multivariate hypoth- biotic variables. eses, and the SEM is used to evaluate whether the theory is For microorganisms (bacteria, archaea, and unicellular fungi), consistent with empirical data30,32. A robust SEM allows culture-independent characterization using molecular genetic researchers to quantitatively assess the relative importance of techniques is widely recognized as the most consistent and sen- ecological drivers32,33 and is thus well suited for predicting eco- sitive approach16, whereas conventional surveys remain the most system responses to global change1,33. reliable and practical approach for larger invertebrates and higher In addition to challenging climatic conditions and hyperar- animals and plants in terrestrial environments. For abiotic vari- idity21, biotic interactions in Dry Valley soils are thought to be ables and some major macroecological features (e.g., primary limited by very low biomass and patchy distribution of photo- productivity), geographic information system (GIS) has become trophic communities28. Temperature and biologically available an essential tool for collecting information across spatial scales. water have been proposed as the primary determinants of species The integration of GIS and remote sensing technologies (e.g., occurrence21,34, but the lack of studies explicitly addressing biotic satellites) can provide spatially explicit environmental informa- interactions in the Dry Valley ecosystems means that the role of tion for entire geographic regions17,18. Specifically, the availability biotic interactions is largely unknown (if present at all)28. of high-resolution data layers from sources such as the Landsat 7 Therefore, our primary hypothesis was that abiotic environmental and MODIS satellites facilitates complete and consistent filters are the major control on the biodiversity of this envir- descriptions of environmental conditions (e.g., surface tempera- onmentally extreme and simple terrestrial ecosystem, and the ture and snow coverage) at the landscape scale18,19. Using these structure of our SEM mostly reflected this notion. However, we descriptions in conjunction with information on bedrock geology found that linkages between different groups of biota and the
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