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Gaudin M, Eveillard D, Chaffron S. Ecological associations distribution modelling of marine plankton at a global scale. Philos Trans R Soc Lond B Biol Sci 2024; 379:20230169. [PMID: 39034696 PMCID: PMC11293856 DOI: 10.1098/rstb.2023.0169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 03/21/2024] [Accepted: 03/21/2024] [Indexed: 07/23/2024] Open
Abstract
Marine plankton communities form intricate networks of interacting organisms at the base of the food chain, and play a central role in regulating ocean biogeochemical cycles and climate. However, predicting plankton community shifts in response to climate change remains challenging. While species distribution models are valuable tools for predicting changes in species biogeography under climate change scenarios, they generally overlook the key role of biotic interactions, which can significantly shape ecological processes and ecosystem responses. Here, we introduce a novel statistical framework, association distribution modelling (ADM), designed to model and predict ecological associations distribution in space and time. Applied on a Tara Oceans genome-resolved metagenomics dataset, the present-day biogeography of ADM-inferred marine plankton associations revealed four major biogeographic biomes organized along a latitudinal gradient. We predicted the evolution of these biome-specific communities in response to a climate change scenario, highlighting differential responses to environmental change. Finally, we explored the functional potential of impacted plankton communities, focusing on carbon fixation, outlining the predicted evolution of its geographical distribution and implications for ecosystem function.This article is part of the theme issue 'Connected interactions: enriching food web research by spatial and social interactions'.
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Affiliation(s)
- Marinna Gaudin
- Nantes Université, École Centrale Nantes, CNRS, LS2N, UMR 6004, Nantes44000, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara Oceans GOSEE, Paris75016, France
| | - Damien Eveillard
- Nantes Université, École Centrale Nantes, CNRS, LS2N, UMR 6004, Nantes44000, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara Oceans GOSEE, Paris75016, France
| | - Samuel Chaffron
- Nantes Université, École Centrale Nantes, CNRS, LS2N, UMR 6004, Nantes44000, France
- Research Federation for the Study of Global Ocean Systems Ecology and Evolution, FR2022/Tara Oceans GOSEE, Paris75016, France
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2
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Rocchini D, Tordoni E, Marchetto E, Marcantonio M, Barbosa AM, Bazzichetto M, Beierkuhnlein C, Castelnuovo E, Gatti RC, Chiarucci A, Chieffallo L, Da Re D, Di Musciano M, Foody GM, Gabor L, Garzon-Lopez CX, Guisan A, Hattab T, Hortal J, Kunin WE, Jordán F, Lenoir J, Mirri S, Moudrý V, Naimi B, Nowosad J, Sabatini FM, Schweiger AH, Šímová P, Tessarolo G, Zannini P, Malavasi M. A quixotic view of spatial bias in modelling the distribution of species and their diversity. NPJ BIODIVERSITY 2023; 2:10. [PMID: 39242713 PMCID: PMC11332097 DOI: 10.1038/s44185-023-00014-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 03/23/2023] [Indexed: 09/09/2024]
Abstract
Ecological processes are often spatially and temporally structured, potentially leading to autocorrelation either in environmental variables or species distribution data. Because of that, spatially-biased in-situ samples or predictors might affect the outcomes of ecological models used to infer the geographic distribution of species and diversity. There is a vast heterogeneity of methods and approaches to assess and measure spatial bias; this paper aims at addressing the spatial component of data-driven biases in species distribution modelling, and to propose potential solutions to explicitly test and account for them. Our major goal is not to propose methods to remove spatial bias from the modelling procedure, which would be impossible without proper knowledge of all the processes generating it, but rather to propose alternatives to explore and handle it. In particular, we propose and describe three main strategies that may provide a fair account of spatial bias, namely: (i) how to represent spatial bias; (ii) how to simulate null models based on virtual species for testing biogeographical and species distribution hypotheses; and (iii) how to make use of spatial bias - in particular related to sampling effort - as a leverage instead of a hindrance in species distribution modelling. We link these strategies with good practice in accounting for spatial bias in species distribution modelling.
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Affiliation(s)
- Duccio Rocchini
- BIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126, Bologna, Italy.
- Czech University of Life Sciences Prague, Faculty of Environmental Sciences, Department of Spatial Sciences, Kamýcka 129, Praha - Suchdol, 16500, Czech Republic.
| | - Enrico Tordoni
- Department of Botany, Institute of Ecology and Earth Science, University of Tartu, J. Liivi 2, 50409, Tartu, Estonia
| | - Elisa Marchetto
- BIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126, Bologna, Italy
| | - Matteo Marcantonio
- Evolutionary Ecology and Genetics Group, Earth and Life Institute, UCLouvain, 1348, Louvain-la-Neuve, Belgium
| | - A Márcia Barbosa
- CICGE (Centro de Investigação em Ciências Geo-Espaciais), Universidade do Porto, Porto, Portugal
| | - Manuele Bazzichetto
- Czech University of Life Sciences Prague, Faculty of Environmental Sciences, Department of Spatial Sciences, Kamýcka 129, Praha - Suchdol, 16500, Czech Republic
| | - Carl Beierkuhnlein
- Biogeography, BayCEER, University of Bayreuth, Universitaetsstraße 30, 95440, Bayreuth, Germany
| | - Elisa Castelnuovo
- BIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126, Bologna, Italy
| | - Roberto Cazzolla Gatti
- BIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126, Bologna, Italy
| | - Alessandro Chiarucci
- BIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126, Bologna, Italy
| | - Ludovico Chieffallo
- BIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126, Bologna, Italy
| | - Daniele Da Re
- Georges Lemaître Center for Earth and Climate Research, Earth and Life Institute, UCLouvain, Louvain-la-Neuve, Belgium
| | - Michele Di Musciano
- BIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126, Bologna, Italy
- Department of Life, Health and Environmental Sciences, University of L'Aquila, Piazzale Salvatore Tommasi 1, 67100, L'Aquila, Italy
| | - Giles M Foody
- School of Geography, University of Nottingham, Nottingham, UK
| | - Lukas Gabor
- Dept of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA
- Center for Biodiversity and Global Change, Yale University, New Haven, CT, USA
| | - Carol X Garzon-Lopez
- Knowledge Infrastructures, Campus Fryslan University of Groningen, Leeuwarden, The Netherlands
| | - Antoine Guisan
- Department of Ecology and Evolution, University of Lausanne, 1015, Lausanne, Switzerland
- Institute of Earth Surface Dynamics, University of Lausanne, 1015, Lausanne, Switzerland
| | - Tarek Hattab
- MARBEC, Univ Montpellier, CNRS, Ifremer, IRD, Sète, France
| | - Joaquin Hortal
- Department of Biogeography and Global Change, Museo Nacional de Ciencias Naturales (MNCN-CSIC), Madrid, Spain
| | | | | | - Jonathan Lenoir
- UMR CNRS 7058 "Ecologie et Dynamique des Systèmes Anthropisés" (EDYSAN), Université de Picardie Jules Verne, 1 Rue des Louvels, 80000, Amiens, France
| | - Silvia Mirri
- Department of Computer Science and Engineering, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126, Bologna, Italy
| | - Vítězslav Moudrý
- Czech University of Life Sciences Prague, Faculty of Environmental Sciences, Department of Spatial Sciences, Kamýcka 129, Praha - Suchdol, 16500, Czech Republic
| | - Babak Naimi
- Rui Nabeiro Biodiversity Chair, MED Institute, University of Évora, Évora, Portugal
| | - Jakub Nowosad
- Institute of Geoecology and Geoinformation, Adam Mickiewicz University, Krygowskiego 10, 61-680, Poznan, Poland
| | - Francesco Maria Sabatini
- BIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126, Bologna, Italy
- Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Prague - Suchdol, Czech Republic
| | - Andreas H Schweiger
- Department of Plant Ecology, Institute of Landscape and Plant Ecology, University of Hohenheim, Stuttgart, Germany
| | - Petra Šímová
- Czech University of Life Sciences Prague, Faculty of Environmental Sciences, Department of Spatial Sciences, Kamýcka 129, Praha - Suchdol, 16500, Czech Republic
| | | | - Piero Zannini
- BIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum University of Bologna, via Irnerio 42, 40126, Bologna, Italy
| | - Marco Malavasi
- University of Sassari, Department of Chemistry, Physics, Mathematics and Natural Sciences, Sassari, Italy
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Giezendanner J, Pasetto D, Perez-Saez J, Cerrato C, Viterbi R, Terzago S, Palazzi E, Rinaldo A. Earth and field observations underpin metapopulation dynamics in complex landscapes: Near-term study on carabids. Proc Natl Acad Sci U S A 2020; 117:12877-12884. [PMID: 32461358 PMCID: PMC7293626 DOI: 10.1073/pnas.1919580117] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Understanding risks to biodiversity requires predictions of the spatial distribution of species adapting to changing ecosystems and, to that end, Earth observations integrating field surveys prove essential as they provide key numbers for assessing landscape-wide biodiversity scenarios. Here, we develop, and apply to a relevant case study, a method suited to merge Earth/field observations with spatially explicit stochastic metapopulation models to study the near-term ecological dynamics of target species in complex terrains. Our framework incorporates the use of species distribution models for a reasoned estimation of the initial presence of the target species and accounts for imperfect and incomplete detection of the species presence in the study area. It also uses a metapopulation fitness function derived from Earth observation data subsuming the ecological niche of the target species. This framework is applied to contrast occupancy of two species of carabids (Pterostichus flavofemoratus, Carabus depressus) observed in the context of a large ecological monitoring program carried out within the Gran Paradiso National Park (GPNP, Italy). Results suggest that the proposed framework may indeed exploit the hallmarks of spatially explicit ecological approaches and of remote Earth observations. The model reproduces well the observed in situ data. Moreover, it projects in the near term the two species' presence both in space and in time, highlighting the features of the metapopulation dynamics of colonization and extinction, and their expected trends within verifiable timeframes.
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Affiliation(s)
- Jonathan Giezendanner
- Laboratory of Ecohydrology, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Damiano Pasetto
- Laboratory of Ecohydrology, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | - Javier Perez-Saez
- Laboratory of Ecohydrology, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland
| | | | | | - Silvia Terzago
- National Research Council (CNR), Institute of Atmospheric Sciences and Climate, 10133 Torino, Italy
| | - Elisa Palazzi
- National Research Council (CNR), Institute of Atmospheric Sciences and Climate, 10133 Torino, Italy
| | - Andrea Rinaldo
- Laboratory of Ecohydrology, École Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland;
- Dipartimento di Ingegneria Civile Edile e Ambientale (DICEA), Università di Padova, 35131 Padova, Italy
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Mateo RG, Mokany K, Guisan A. Biodiversity Models: What If Unsaturation Is the Rule? Trends Ecol Evol 2017; 32:556-566. [PMID: 28610851 PMCID: PMC5516772 DOI: 10.1016/j.tree.2017.05.003] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2016] [Revised: 05/10/2017] [Accepted: 05/12/2017] [Indexed: 11/26/2022]
Abstract
Improving biodiversity predictions is essential if we are to meet the challenges posed by global change. As knowledge is key to feed models, we need to evaluate how debated theory can affect models. An important ongoing debate is whether environmental constraints limit the number of species that can coexist in a community (saturation), with recent findings suggesting that species richness in many communities might be unsaturated. Here, we propose that biodiversity models could address this issue by accounting for a duality: considering communities as unsaturated but where species composition is constrained by different scale-dependent biodiversity drivers. We identify a variety of promising advances for incorporating this duality into commonly applied biodiversity modelling approaches and improving their spatial predictions. The majority of biodiversity modelling approaches do not explicitly address the question of saturation. Theoretical and methodological implications of saturation or unsaturation in biodiversity modelling. Addressing saturation or unsaturation is vital to produce more reliable conservation strategies. Integrative community modelling frameworks may be the way forward.
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Affiliation(s)
- Rubén G Mateo
- Department of Ecology and Evolution, University of Lausanne, Biophore, CH-1015, Lausanne, Switzerland; ETSI de Montes, Forestal y del Medio Natural, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, 28040, Madrid, Spain.
| | | | - Antoine Guisan
- Department of Ecology and Evolution, University of Lausanne, Biophore, CH-1015, Lausanne, Switzerland; Institute of Earth Science Dynamics, University of Lausanne, Geopolis, CH-1015 Lausanne, Switzerland
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