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Bozzuto C, Ives AR. Predictability of ecological and evolutionary dynamics in a changing world. Proc Biol Sci 2024; 291:20240980. [PMID: 38981521 DOI: 10.1098/rspb.2024.0980] [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: 11/06/2023] [Accepted: 06/07/2024] [Indexed: 07/11/2024] Open
Abstract
Ecological and evolutionary predictions are being increasingly employed to inform decision-makers confronted with intensifying pressures on biodiversity. For these efforts to effectively guide conservation actions, knowing the limit of predictability is pivotal. In this study, we provide realistic expectations for the enterprise of predicting changes in ecological and evolutionary observations through time. We begin with an intuitive explanation of predictability (the extent to which predictions are possible) employing an easy-to-use metric, predictive power PP(t). To illustrate the challenge of forecasting, we then show that among insects, birds, fishes and mammals, (i) 50% of the populations are predictable at most 1 year in advance and (ii) the median 1-year-ahead predictive power corresponds to a prediction R 2 of only 20%. Predictability is not an immutable property of ecological systems. For example, different harvesting strategies can impact the predictability of exploited populations to varying degrees. Moreover, incorporating explanatory variables, accounting for time trends and considering multivariate time series can enhance predictability. To effectively address the challenge of biodiversity loss, researchers and practitioners must be aware of the information within the available data that can be used for prediction and explore efficient ways to leverage this knowledge for environmental stewardship.
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Affiliation(s)
- Claudio Bozzuto
- Wildlife Analysis GmbH, Oetlisbergstrasse 38 , 8053 Zurich, Switzerland
| | - Anthony R Ives
- Department of Integrative Biology, University of Wisconsin-Madison , Madison, WI 53706, USA
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2
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Zhao Q, Van den Brink PJ, Xu C, Wang S, Clark AT, Karakoç C, Sugihara G, Widdicombe CE, Atkinson A, Matsuzaki SIS, Shinohara R, He S, Wang YXG, De Laender F. Relationships of temperature and biodiversity with stability of natural aquatic food webs. Nat Commun 2023; 14:3507. [PMID: 37316479 DOI: 10.1038/s41467-023-38977-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 05/22/2023] [Indexed: 06/16/2023] Open
Abstract
Temperature and biodiversity changes occur in concert, but their joint effects on ecological stability of natural food webs are unknown. Here, we assess these relationships in 19 planktonic food webs. We estimate stability as structural stability (using the volume contraction rate) and temporal stability (using the temporal variation of species abundances). Warmer temperatures were associated with lower structural and temporal stability, while biodiversity had no consistent effects on either stability property. While species richness was associated with lower structural stability and higher temporal stability, Simpson diversity was associated with higher temporal stability. The responses of structural stability were linked to disproportionate contributions from two trophic groups (predators and consumers), while the responses of temporal stability were linked both to synchrony of all species within the food web and distinctive contributions from three trophic groups (predators, consumers, and producers). Our results suggest that, in natural ecosystems, warmer temperatures can erode ecosystem stability, while biodiversity changes may not have consistent effects.
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Affiliation(s)
- Qinghua Zhao
- Aquatic Ecology and Water Quality Management Group, Wageningen University & Research, P.O. Box 47, 6700 AA, Wageningen, The Netherlands.
- Research Unit of Environmental and Evolutionary Biology (URBE), University of Namur, Namur, Belgium.
- Institute of Complex Systems (naXys), University of Namur, Namur, Belgium.
- Institute of Life, Earth and the Environment (ILEE), University of Namur, Namur, Belgium.
| | - Paul J Van den Brink
- Aquatic Ecology and Water Quality Management Group, Wageningen University & Research, P.O. Box 47, 6700 AA, Wageningen, The Netherlands
- Wageningen Environmental Research, P.O. Box 47, 6700 AA, Wageningen, The Netherlands
| | - Chi Xu
- School of Life Sciences, Nanjing University, Nanjing, 210023, China
| | - Shaopeng Wang
- Institute of Ecology, College of Urban and Environmental Science, and Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, 100871, Beijing, China
| | - Adam T Clark
- Institute of Biology, University of Graz, Holteigasse 6, 8010, Graz, Austria
| | - Canan Karakoç
- Department of Biology, Indiana University, 1001 East Third Street, Bloomington, IN, 47405, USA
| | - George Sugihara
- Scripps Institution of Oceanography, University of California-San Diego, La Jolla, CA, USA
| | | | - Angus Atkinson
- Plymouth Marine Laboratory, Prospect Place, The Hoe, Plymouth, PL13DH, UK
| | | | | | - Shuiqing He
- Wildlife Ecology and Conservation Group, Wageningen University & Research, Wageningen, The Netherlands
| | - Yingying X G Wang
- Department of Biological and Environmental Science, University of Jyväskylä, FI-40014, Jyväskylä, Finland
| | - Frederik De Laender
- Research Unit of Environmental and Evolutionary Biology (URBE), University of Namur, Namur, Belgium
- Institute of Complex Systems (naXys), University of Namur, Namur, Belgium
- Institute of Life, Earth and the Environment (ILEE), University of Namur, Namur, Belgium
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3
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Munch SB, Rogers TL, Sugihara G. Recent developments in empirical dynamic modelling. Methods Ecol Evol 2023. [DOI: 10.1111/2041-210x.13983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Affiliation(s)
- Stephan B. Munch
- Southwest Fisheries Science Center, National Marine Fisheries Service National Oceanic and Atmospheric Administration Santa Cruz California USA
- Department of Applied Mathematics University of California Santa Cruz California USA
| | - Tanya L. Rogers
- Southwest Fisheries Science Center, National Marine Fisheries Service National Oceanic and Atmospheric Administration Santa Cruz California USA
| | - George Sugihara
- Scripps Institution of Oceanography University of California San Diego La Jolla California USA
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Medeiros LP, Allesina S, Dakos V, Sugihara G, Saavedra S. Ranking species based on sensitivity to perturbations under non-equilibrium community dynamics. Ecol Lett 2023; 26:170-183. [PMID: 36318189 PMCID: PMC10092288 DOI: 10.1111/ele.14131] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 09/20/2022] [Accepted: 09/27/2022] [Indexed: 11/06/2022]
Abstract
Managing ecological communities requires fast detection of species that are sensitive to perturbations. Yet, the focus on recovery to equilibrium has prevented us from assessing species responses to perturbations when abundances fluctuate over time. Here, we introduce two data-driven approaches (expected sensitivity and eigenvector rankings) based on the time-varying Jacobian matrix to rank species over time according to their sensitivity to perturbations on abundances. Using several population dynamics models, we demonstrate that we can infer these rankings from time-series data to predict the order of species sensitivities. We find that the most sensitive species are not always the ones with the most rapidly changing or lowest abundance, which are typical criteria used to monitor populations. Finally, using two empirical time series, we show that sensitive species tend to be harder to forecast. Our results suggest that incorporating information on species interactions can improve how we manage communities out of equilibrium.
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Affiliation(s)
- Lucas P Medeiros
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Massachusetts, Cambridge, USA.,Institute of Marine Sciences, University of California Santa Cruz, California, Santa Cruz, USA
| | - Stefano Allesina
- Department of Ecology & Evolution, University of Chicago, Illinois, Chicago, USA.,Northwestern Institute on Complex Systems, Northwestern University, Illinois, Evanston, USA
| | - Vasilis Dakos
- Institut des Sciences de l'Evolution de Montpellier, Université de Montpellier, Montpellier, France
| | - George Sugihara
- Scripps Institution of Oceanography, University of California San Diego, California, La Jolla, USA
| | - Serguei Saavedra
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Massachusetts, Cambridge, USA
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5
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Medeiros LP, Song C, Saavedra S. Merging dynamical and structural indicators to measure resilience in multispecies systems. J Anim Ecol 2021; 90:2027-2040. [PMID: 33448053 DOI: 10.1111/1365-2656.13421] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 12/09/2020] [Indexed: 11/30/2022]
Abstract
Resilience is broadly understood as the ability of an ecological system to resist and recover from perturbations acting on species abundances and on the system's structure. However, one of the main problems in assessing resilience is to understand the extent to which measures of recovery and resistance provide complementary information about a system. While recovery from abundance perturbations has a strong tradition under the analysis of dynamical stability, it is unclear whether this same formalism can be used to measure resistance to structural perturbations (e.g. perturbations to model parameters). Here, we provide a framework grounded on dynamical and structural stability in Lotka-Volterra systems to link recovery from small perturbations on species abundances (i.e. dynamical indicators) with resistance to parameter perturbations of any magnitude (i.e. structural indicators). We use theoretical and experimental multispecies systems to show that the faster the recovery from abundance perturbations, the higher the resistance to parameter perturbations. We first use theoretical systems to show that the return rate along the slowest direction after a small random abundance perturbation (what we call full recovery) is negatively correlated with the largest random parameter perturbation that a system can withstand before losing any species (what we call full resistance). We also show that the return rate along the second fastest direction after a small random abundance perturbation (what we call partial recovery) is negatively correlated with the largest random parameter perturbation that a system can withstand before at most one species survives (what we call partial resistance). Then, we use a dataset of experimental microbial systems to confirm our theoretical expectations and to demonstrate that full and partial components of resilience are complementary. Our findings reveal that we can obtain the same level of information about resilience by measuring either a dynamical (i.e. recovery) or a structural (i.e. resistance) indicator. Irrespective of the chosen indicator (dynamical or structural), our results show that we can obtain additional information by separating the indicator into its full and partial components. We believe these results can motivate new theoretical approaches and empirical analyses to increase our understanding about risk in ecological systems.
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Affiliation(s)
- Lucas P Medeiros
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Chuliang Song
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.,Department of Biology, Quebec Centre for Biodiversity Science, McGill University, Montreal, Quebec, Canada.,Department of Ecology and Evolutionary Biology, University of Toronto, Toronto, Ontario, Canada
| | - Serguei Saavedra
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
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