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Hederström V, Ekroos J, Friberg M, Krausl T, Opedal ØH, Persson AS, Petrén H, Quan Y, Smith HG, Clough Y. Pollinator-mediated effects of landscape-scale land use on grassland plant community composition and ecosystem functioning - seven hypotheses. Biol Rev Camb Philos Soc 2024; 99:675-698. [PMID: 38118437 DOI: 10.1111/brv.13040] [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: 11/29/2022] [Revised: 12/05/2023] [Accepted: 12/07/2023] [Indexed: 12/22/2023]
Abstract
Environmental change is disrupting mutualisms between organisms worldwide. Reported declines in insect populations and changes in pollinator community compositions in response to land use and other environmental drivers have put the spotlight on the need to conserve pollinators. While this is often motivated by their role in supporting crop yields, the role of pollinators for reproduction and resulting taxonomic and functional assembly in wild plant communities has received less attention. Recent findings suggest that observed and experimental gradients in pollinator availability can affect plant community composition, but we know little about when such shifts are to be expected, or the impact they have on ecosystem functioning. Correlations between plant traits related to pollination and plant traits related to other important ecosystem functions, such as productivity, nitrogen uptake or palatability to herbivores, lead us to expect non-random shifts in ecosystem functioning in response to changes in pollinator communities. At the same time, ecological and evolutionary processes may counteract these effects of pollinator declines, limiting changes in plant community composition, and in ecosystem functioning. Despite calls to investigate community- and ecosystem-level impacts of reduced pollination, the study of pollinator effects on plants has largely been confined to impacts on plant individuals or single-species populations. With this review we aim to break new ground by bringing together aspects of landscape ecology, ecological and evolutionary plant-insect interactions, and biodiversity-ecosystem functioning research, to generate new ideas and hypotheses about the ecosystem-level consequences of pollinator declines in response to land-use change, using grasslands as a focal system. Based on an integrated set of seven hypotheses, we call for more research investigating the putative pollinator-mediated links between landscape-scale land use and ecosystem functioning. In particular, future research should use combinations of experimental and observational approaches to assess the effects of changes in pollinator communities over multiple years and across species on plant communities and on trait distributions both within and among species.
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Affiliation(s)
- Veronica Hederström
- Centre for Environmental and Climate Science, Lund University, Sölvegatan 37, Lund, 223 62, Sweden
| | - Johan Ekroos
- Centre for Environmental and Climate Science, Lund University, Sölvegatan 37, Lund, 223 62, Sweden
| | - Magne Friberg
- Department of Biology, Lund University, Sölvegatan 37, Lund, 223 62, Sweden
| | - Theresia Krausl
- Centre for Environmental and Climate Science, Lund University, Sölvegatan 37, Lund, 223 62, Sweden
| | - Øystein H Opedal
- Department of Biology, Lund University, Sölvegatan 37, Lund, 223 62, Sweden
| | - Anna S Persson
- Centre for Environmental and Climate Science, Lund University, Sölvegatan 37, Lund, 223 62, Sweden
| | - Hampus Petrén
- Department of Biology, Lund University, Sölvegatan 37, Lund, 223 62, Sweden
| | - Yuanyuan Quan
- Centre for Environmental and Climate Science, Lund University, Sölvegatan 37, Lund, 223 62, Sweden
| | - Henrik G Smith
- Centre for Environmental and Climate Science, Lund University, Sölvegatan 37, Lund, 223 62, Sweden
- Department of Biology, Lund University, Sölvegatan 37, Lund, 223 62, Sweden
| | - Yann Clough
- Centre for Environmental and Climate Science, Lund University, Sölvegatan 37, Lund, 223 62, Sweden
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Domínguez-Garcia V, Molina FP, Godoy O, Bartomeus I. Interaction network structure explains species' temporal persistence in empirical plant-pollinator communities. Nat Ecol Evol 2024; 8:423-429. [PMID: 38302580 DOI: 10.1038/s41559-023-02314-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 12/14/2023] [Indexed: 02/03/2024]
Abstract
Despite clear evidence that some pollinator populations are declining, our ability to predict pollinator communities prone to collapse or species at risk of local extinction is remarkably poor. Here, we develop a model grounded in the structuralist approach that allows us to draw sound predictions regarding the temporal persistence of species in mutualistic networks. Using high-resolution data from a six-year study following 12 independent plant-pollinator communities, we confirm that pollinator species with more persistent populations in the field are theoretically predicted to tolerate a larger range of environmental changes. Persistent communities are not necessarily more diverse, but are generally located in larger habitat patches, and present a distinctive combination of generalist and specialist species resulting in a more nested structure, as predicted by previous theoretical work. Hence, pollinator interactions directly inform about their ability to persist, opening the door to use theoretically informed models to predict species' fate within the ongoing global change.
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Affiliation(s)
| | | | - Oscar Godoy
- Departamento de Biología, Instituto Universitario de Ciencias del Mar (INMAR), Universidad de Cádiz, Puerto Real, Spain
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Long C, Deng J, Nguyen J, Liu YY, Alm EJ, Solé R, Saavedra S. Structured community transitions explain the switching capacity of microbial systems. Proc Natl Acad Sci U S A 2024; 121:e2312521121. [PMID: 38285940 PMCID: PMC10861894 DOI: 10.1073/pnas.2312521121] [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: 07/24/2023] [Accepted: 12/29/2023] [Indexed: 01/31/2024] Open
Abstract
Microbial systems appear to exhibit a relatively high switching capacity of moving back and forth among few dominant communities (taxon memberships). While this switching behavior has been mainly attributed to random environmental factors, it remains unclear the extent to which internal community dynamics affect the switching capacity of microbial systems. Here, we integrate ecological theory and empirical data to demonstrate that structured community transitions increase the dependency of future communities on the current taxon membership, enhancing the switching capacity of microbial systems. Following a structuralist approach, we propose that each community is feasible within a unique domain in environmental parameter space. Then, structured transitions between any two communities can happen with probability proportional to the size of their feasibility domains and inversely proportional to their distance in environmental parameter space-which can be treated as a special case of the gravity model. We detect two broad classes of systems with structured transitions: one class where switching capacity is high across a wide range of community sizes and another class where switching capacity is high only inside a narrow size range. We corroborate our theory using temporal data of gut and oral microbiota (belonging to class 1) as well as vaginal and ocean microbiota (belonging to class 2). These results reveal that the topology of feasibility domains in environmental parameter space is a relevant property to understand the changing behavior of microbial systems. This knowledge can be potentially used to understand the relevant community size at which internal dynamics can be operating in microbial systems.
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Affiliation(s)
- Chengyi Long
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA02139
| | - Jie Deng
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA02139
| | - Jen Nguyen
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA02139
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA02139
| | - Yang-Yu Liu
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA02115
- Center for Artificial Intelligence and Modeling, The Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Champaign, IL61801
| | - Eric J. Alm
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA02139
- Center for Microbiome Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA02139
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA02139
| | - Ricard Solé
- Complex Systems Lab, Universitat Pompeu Fabra, Barcelona08003, Spain
- Institució Catalana de Recerca i Estudis Avançats, Barcelona08010, Spain
- Institute of Evolutionary Biology, Spanish National Research Council (CSIC)-Universitat Pompeu Fabra, Barcelona08003, Spain
- Santa Fe Institute, Santa Fe, NM87501
| | - Serguei Saavedra
- Institució Catalana de Recerca i Estudis Avançats, Barcelona08010, Spain
- Santa Fe Institute, Santa Fe, NM87501
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Deng J, Taylor W, Levin SA, Saavedra S. On the limits to invasion prediction using coexistence outcomes. J Theor Biol 2024; 577:111674. [PMID: 38008157 DOI: 10.1016/j.jtbi.2023.111674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 11/01/2023] [Accepted: 11/14/2023] [Indexed: 11/28/2023]
Abstract
The dynamics of ecological communities in nature are typically characterized by probabilistic processes involving invasion dynamics. Because of technical challenges, however, the majority of theoretical and experimental studies have focused on coexistence dynamics. Therefore, it has become central to understand the extent to which coexistence outcomes can be used to predict analogous invasion outcomes relevant to systems in nature. Here, we study the limits to this predictability under a geometric and probabilistic Lotka-Volterra framework. We show that while individual survival probability in coexistence dynamics can be fairly closely translated into invader colonization probability in invasion dynamics, the translation is less precise between community persistence and community augmentation, and worse between exclusion probability and replacement probability. These results provide a guiding and testable theoretical framework regarding the translatability of outcomes between coexistence and invasion outcomes when communities are represented by Lotka-Volterra dynamics under environmental uncertainty.
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Affiliation(s)
- Jie Deng
- Department of Civil and Environmental Engineering, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139, USA.
| | - Washington Taylor
- Center for Theoretical Physics, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139, USA
| | - Simon A Levin
- Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA; High Meadows Environmental Institute, Princeton University, Princeton, NJ 08544, USA
| | - Serguei Saavedra
- Department of Civil and Environmental Engineering, MIT, 77 Massachusetts Avenue, Cambridge, MA 02139, USA; Santa Fe Institute, 1399 Hyde Park Rd, Santa Fe, NM 87501, USA
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Allen-Perkins A, García-Callejas D, Bartomeus I, Godoy O. Structural asymmetry in biotic interactions as a tool to understand and predict ecological persistence. Ecol Lett 2023; 26:1647-1662. [PMID: 37515408 DOI: 10.1111/ele.14291] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 06/29/2023] [Accepted: 07/05/2023] [Indexed: 07/30/2023]
Abstract
A universal feature of ecological systems is that species do not interact with others with the same sign and strength. Yet, the consequences of this asymmetry in biotic interactions for the short- and long-term persistence of individual species and entire communities remains unclear. Here, we develop a set of metrics to evaluate how asymmetric interactions among species translate to asymmetries in their individual vulnerability to extinction under changing environmental conditions. These metrics, which solve previous limitations of how to independently quantify the size from the shape of the so-called feasibility domain, provide rigorous advances to understand simultaneously why some species and communities present more opportunities to persist than others. We further demonstrate that our shape-related metrics are useful to predict short-term changes in species' relative abundances during 7 years in a Mediterranean grassland. Our approach is designed to be applied to any ecological system regardless of the number of species and type of interactions. With it, we show that is possible to obtain both mechanistic and predictive information on ecological persistence for individual species and entire communities, paving the way for a stronger integration of theoretical and empirical research.
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Affiliation(s)
- Alfonso Allen-Perkins
- Departamento de Ingeniería Eléctrica, Electrónica, Automática y Física Aplicada, ETSIDI, Technical University of Madrid, Madrid, Spain
| | - David García-Callejas
- School of Biological Sciences, University of Canterbury, Christchurch, New Zealand
- Landcare Research, Lincoln, New Zealand
| | | | - Oscar Godoy
- Departamento de Biología, Instituto Universitario de Ciencias del Mar (INMAR), Universidad de Cádiz, Puerto Real, Spain
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