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Barabás G. Parameter Sensitivity of Transient Community Dynamics. Am Nat 2024; 203:473-489. [PMID: 38489777 DOI: 10.1086/728764] [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] [Indexed: 03/17/2024]
Abstract
AbstractTransient dynamics have always intrigued ecologists, but current rapid environmental change (inducing transients even in previously undisturbed systems) has highlighted their importance more than ever. Here, I introduce a method for analyzing the sensitivity of transient ecological dynamics to parameter perturbations. The question the method answers is: how would the community dynamics have unfolded for some time horizon had the parameters been slightly different? I apply the method to three empirically parameterized models: competition between native forbs and exotic grasses in California, a host-parasitoid system, and an experimental chemostat predator-prey model. These applications showcase the ecological insights one can gain from models using transient sensitivity analysis. First, one can find parameters and their combinations whose perturbations disproportionately affect a system. Second, one can identify particular windows of time during which the predicted deviation from the unperturbed trajectories is especially large and utilize this information for management purposes. Third, there is an inverse relationship between transient and long-term sensitivities whenever the interacting populations are ecologically similar; paradoxically, the smaller the immediate response of the system, the more extreme its long-term response will be.
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2
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Vollert SA, Drovandi C, Adams MP. Unlocking ensemble ecosystem modelling for large and complex networks. PLoS Comput Biol 2024; 20:e1011976. [PMID: 38483981 DOI: 10.1371/journal.pcbi.1011976] [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: 07/24/2023] [Revised: 03/26/2024] [Accepted: 03/07/2024] [Indexed: 03/27/2024] Open
Abstract
The potential effects of conservation actions on threatened species can be predicted using ensemble ecosystem models by forecasting populations with and without intervention. These model ensembles commonly assume stable coexistence of species in the absence of available data. However, existing ensemble-generation methods become computationally inefficient as the size of the ecosystem network increases, preventing larger networks from being studied. We present a novel sequential Monte Carlo sampling approach for ensemble generation that is orders of magnitude faster than existing approaches. We demonstrate that the methods produce equivalent parameter inferences, model predictions, and tightly constrained parameter combinations using a novel sensitivity analysis method. For one case study, we demonstrate a speed-up from 108 days to 6 hours, while maintaining equivalent ensembles. Additionally, we demonstrate how to identify the parameter combinations that strongly drive feasibility and stability, drawing ecological insight from the ensembles. Now, for the first time, larger and more realistic networks can be practically simulated and analysed.
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Affiliation(s)
- Sarah A Vollert
- Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Christopher Drovandi
- Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Matthew P Adams
- Centre for Data Science, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
- School of Chemical Engineering, The University of Queensland, St Lucia, Australia
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3
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Bodini A, Pereira D, Scotti M. The decline of kilkas, sturgeons and seals in the Caspian Sea: The potential of qualitative loop analysis for the cumulative assessment of multiple drivers of stress. MARINE POLLUTION BULLETIN 2024; 200:116091. [PMID: 38335632 DOI: 10.1016/j.marpolbul.2024.116091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 01/22/2024] [Accepted: 01/27/2024] [Indexed: 02/12/2024]
Abstract
Multiple stressors often act concomitantly on ecosystems but detection of species responses follows the "single species-single driver" strategy, and cumulative impacts are seldom considered. During 1990-2010, multiple perturbations in the Caspian Sea, led to the decline of kilka, sturgeon and Caspian seal populations. Specific causes for their collapse were identified but a cumulative assessment has never been carried out. Using loop analysis, a qualitative modelling technique suitable in poor-data contexts, we show how multiple drivers can be combined to assess their cumulative impact. We confirm that the decline of kilka, sturgeon and Caspian seal populations is compatible with a net effect of the concomitant perturbations. Kilkas collapse was certainly due to the outburst of M. leidyi and overfishing. In addition, the excess nutrient might have conspired to reduce these populations. The interplay between concurrent drivers produces trade-offs between opposite effects and ecosystem management must face this challenge.
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Affiliation(s)
- Antonio Bodini
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy.
| | - Daniel Pereira
- Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy; UMR PACEA 5199, University of Bordeaux, France
| | - Marco Scotti
- GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany; Institute of Biosciences and Bioresources, National Research Council of Italy, 50019 Sesto Fiorentino, (Firenze), Italy
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4
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Eichenwald AJ, Fefferman NH, Reed JM. Potential extinction cascades in a desert ecosystem: Linking food web interactions to community viability. Ecol Evol 2024; 14:e10930. [PMID: 38362165 PMCID: PMC10867880 DOI: 10.1002/ece3.10930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 11/27/2023] [Accepted: 12/05/2023] [Indexed: 02/17/2024] Open
Abstract
Desert communities are threatened with species loss due to climate change, and their resistance to such losses is unknown. We constructed a food web of the Mojave Desert terrestrial community (300 nodes, 4080 edges) to empirically examine the potential cascading effects of bird extinctions on this desert network, compared to losses of mammals and lizards. We focused on birds because they are already disappearing from the Mojave, and their relative thermal vulnerabilities are known. We quantified bottom-up secondary extinctions and evaluated the relative resistance of the community to losses of each vertebrate group. The impact of random bird species loss was relatively low compared to the consequences of mammal (causing the greatest number of cascading losses) or reptile loss, and birds were relatively less likely to be in trophic positions that could drive top-down effects in apparent competition and tri-tropic cascade motifs. An avian extinction cascade with year-long resident birds caused more secondary extinctions than the cascade involving all bird species for randomized ordered extinctions. Notably, we also found that relatively high interconnectivity among avian species has formed a subweb, enhancing network resistance to bird losses.
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Affiliation(s)
| | - Nina H. Fefferman
- Department of Ecology and Evolutionary BiologyUniversity of TennesseeKnoxvilleTennesseeUSA
| | - J. Michael Reed
- Department of BiologyTufts UniversityMedfordMassachusettsUSA
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Cosme M, Thomas C, Gaucherel C. On the History of Ecosystem Dynamical Modeling: The Rise and Promises of Qualitative Models. ENTROPY (BASEL, SWITZERLAND) 2023; 25:1526. [PMID: 37998218 PMCID: PMC10670156 DOI: 10.3390/e25111526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Revised: 10/25/2023] [Accepted: 10/25/2023] [Indexed: 11/25/2023]
Abstract
Ecosystem modeling is a complex and multidisciplinary modeling problem which emerged in the 1950s. It takes advantage of the computational turn in sciences to better understand anthropogenic impacts and improve ecosystem management. For that purpose, ecosystem simulation models based on difference or differential equations were built. These models were relevant for studying dynamical phenomena and still are. However, they face important limitations in data-poor situations. As a response, several formal and non-formal qualitative dynamical modeling approaches were independently developed to overcome some limitations of the existing methods. Qualitative approaches allow studying qualitative dynamics as relevant abstractions of those provided by quantitative models (e.g., response to press perturbations). Each modeling framework can be viewed as a different assemblage of properties (e.g., determinism, stochasticity or synchronous update of variable values) designed to satisfy some scientific objectives. Based on four stated objectives commonly found in complex environmental sciences ((1) grasping qualitative dynamics, (2) making as few assumptions as possible about parameter values, (3) being explanatory and (4) being predictive), our objectives were guided by the wish to model complex and multidisciplinary issues commonly found in ecosystem modeling. We then discussed the relevance of existing modeling approaches and proposed the ecological discrete-event networks (EDEN) modeling framework for this purpose. The EDEN models propose a qualitative, discrete-event, partially synchronous and possibilistic view of ecosystem dynamics. We discussed each of these properties through ecological examples and existing analysis techniques for such models and showed how relevant they are for environmental science studies.
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Affiliation(s)
- Maximilien Cosme
- UMR AMAP, INRAE, University of Montpellier (Faculté des Sciences), IRD, CIRAD, CNRS, 34398 Montpellier, France
- UMR DECOD, Institut Agro Rennes-Angers (Campus Rennes), 65 rue de Saint-Brieuc, 35042 Rennes, France
| | - Colin Thomas
- IBISC, University of Evry, 91025 Evry, France (C.G.)
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6
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Patonai K, Fábián VA. Comparison of three modelling frameworks for aquatic ecosystems: practical aspects and applicability. COMMUNITY ECOL 2022. [DOI: 10.1007/s42974-022-00117-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
AbstractFreshwater ecosystems are under multiple stressors and it is crucial to find methods to better describe, manage, and sustain aquatic ecosystems. Ecosystem modelling has become an important tool in integrating trophic relationships into food webs, assessing important nodes using network analysis, and making predictions via simulations. Fortunately, several modelling techniques exist, but the question is which approach is relevant and applicable when? In this study, we compare three modelling frameworks (Ecopath, Loop Analysis in R, STELLA software) using a case study of a small aquatic network (8 nodes). The choice of framework depends on the research question and data availability. We approach this topic from a methodological aspect by describing the data requirements and by comparing the applicability and limitations of each modelling approach. Each modelling framework has its specific focus, but some functionalities and outcomes can be compared. The predictions of Loop Analysis as compared to Ecopath’s Mixed Trophic Impact plot are in good agreement at the top and bottom trophic levels, but the middle trophic levels are less similar. This suggests that further comparisons are needed of networks of varying resolution and size. Generally, when data are limiting, Loop Analysis can provide qualitative predictions, while the other two methods provide quantitative results, yet rely on more data.
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7
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Daugaard U, Munch SB, Inauen D, Pennekamp F, Petchey OL. Forecasting in the face of ecological complexity: Number and strength of species interactions determine forecast skill in ecological communities. Ecol Lett 2022; 25:1974-1985. [PMID: 35831269 PMCID: PMC9540476 DOI: 10.1111/ele.14070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 06/12/2022] [Accepted: 06/17/2022] [Indexed: 11/28/2022]
Abstract
The potential for forecasting the dynamics of ecological systems is currently unclear, with contrasting opinions regarding its feasibility due to ecological complexity. To investigate forecast skill within and across systems, we monitored a microbial system exposed to either constant or fluctuating temperatures in a 5-month-long laboratory experiment. We tested how forecasting of species abundances depends on the number and strength of interactions and on model size (number of predictors). We also tested how greater system complexity (i.e. the fluctuating temperatures) impacted these relations. We found that the more interactions a species had, the weaker these interactions were and the better its abundance was predicted. Forecast skill increased with model size. Greater system complexity decreased forecast skill for three out of eight species. These insights into how abundance prediction depends on the connectedness of the species within the system and on overall system complexity could improve species forecasting and monitoring.
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Affiliation(s)
- Uriah Daugaard
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
| | - Stephan B Munch
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, California, USA
| | - David Inauen
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
| | - Frank Pennekamp
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
| | - Owen L Petchey
- Department of Evolutionary Biology and Environmental Studies, University of Zurich, Zurich, Switzerland
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8
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Baumgartner MT, Bianco Faria LD. The sensitivity of complex dynamic food webs to the loss of top omnivores. J Theor Biol 2022; 538:111027. [DOI: 10.1016/j.jtbi.2022.111027] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 01/10/2022] [Accepted: 01/14/2022] [Indexed: 12/12/2022]
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9
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Srivastava DS, Coristine L, Angert AL, Bontrager M, Amundrud SL, Williams JL, Yeung ACY, Zwaan DR, Thompson PL, Aitken SN, Sunday JM, O'Connor MI, Whitton J, Brown NEM, MacLeod CD, Parfrey LW, Bernhardt JR, Carrillo J, Harley CDG, Martone PT, Freeman BG, Tseng M, Donner SD. Wildcards in climate change biology. ECOL MONOGR 2021. [DOI: 10.1002/ecm.1471] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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10
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Cortez MH, Duffy MA. The Context-Dependent Effects of Host Competence, Competition, and Pathogen Transmission Mode on Disease Prevalence. Am Nat 2021; 198:179-194. [PMID: 34260871 DOI: 10.1086/715110] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
AbstractBiodiversity in communities is changing globally, including the gain and loss of host species in host-pathogen communities. Increased host diversity can cause infection prevalence in a focal host to increase (amplification) or decrease (dilution). However, it is unclear what general rules govern the context-dependent effects, in part because theories for pathogens with different transmission modes have developed largely independently. Using a two-host model, we explore how the pathogen transmission mode and characteristics of a second host (disease competence and competitive ability) influence disease prevalence in a focal host. Our work shows how the theories for pathogens with environmental transmission, density-dependent direct transmission, and frequency-dependent direct transmission can be unified. Our work also identifies general rules about how host and pathogen characteristics affect amplification/dilution. For example, higher-competence hosts promote amplification, unless they are strong interspecific competitors; strong interspecific competitors promote dilution, unless they are large sources of new infections; and dilution occurs under frequency-dependent direct transmission more than density-dependent direct transmission, unless interspecific host competition is sufficiently strong. Our work helps explain how the characteristics of the pathogen and a second host affect disease prevalence in a focal host.
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11
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Mertens D, Boege K, Kessler A, Koricheva J, Thaler JS, Whiteman NK, Poelman EH. Predictability of Biotic Stress Structures Plant Defence Evolution. Trends Ecol Evol 2021; 36:444-456. [PMID: 33468354 DOI: 10.1016/j.tree.2020.12.009] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2020] [Revised: 12/11/2020] [Accepted: 12/17/2020] [Indexed: 12/16/2022]
Abstract
To achieve ecological and reproductive success, plants need to mitigate a multitude of stressors. The stressors encountered by plants are highly dynamic but typically vary predictably due to seasonality or correlations among stressors. As plants face physiological and ecological constraints in responses to stress, it can be beneficial for plants to evolve the ability to incorporate predictable patterns of stress in their life histories. Here, we discuss how plants predict adverse conditions, which plant strategies integrate predictability of biotic stress, and how such strategies can evolve. We propose that plants commonly optimise responses to correlated sequences or combinations of herbivores and pathogens, and that the predictability of these patterns is a key factor governing plant strategies in dynamic environments.
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Affiliation(s)
- Daan Mertens
- Laboratory of Entomology, Wageningen University and Research, P.O. Box 16, 6700 AA, Wageningen, The Netherlands.
| | - Karina Boege
- Instituto de Ecología, Universidad Nacional Autónoma de México, Ciudad Universitaria, Apartado Postal 70-275, Coyoacán, C.P. 04510, Ciudad de México, Mexico
| | - André Kessler
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY 14853, USA
| | - Julia Koricheva
- Department of Biological Sciences, Royal Holloway University of London, Egham, Surrey TW20 0EX, UK
| | | | - Noah K Whiteman
- Department of Integrative Biology, University of California-Berkeley, Berkeley, CA 94720, USA
| | - Erik H Poelman
- Laboratory of Entomology, Wageningen University and Research, P.O. Box 16, 6700 AA, Wageningen, The Netherlands.
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12
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Coupling ecological network analysis with high-throughput sequencing-based surveys: Lessons from the next-generation biomonitoring project. ADV ECOL RES 2021. [DOI: 10.1016/bs.aecr.2021.10.007] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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13
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Cortez MH, Duffy MA. Comparing the Indirect Effects between Exploiters in Predator-Prey and Host-Pathogen Systems. Am Nat 2020; 196:E144-E159. [PMID: 33211567 DOI: 10.1086/711345] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
AbstractIn multipredator and multipathogen systems, exploiters interact indirectly via shared victim species. Interspecific prey competition and the degree of predator specialization are known to influence whether predators have competitive (i.e., (-,-)) or noncompetitive (i.e., (-,+) or (+,+)) indirect interactions. Much less is known about the population-level indirect interactions between pathogens that infect the same populations of host species. In this study, we use two-predator-two-prey and two-host-two-pathogen models to compare the indirect effects between predators with the indirect effects between pathogens. We focus on how the indirect interactions between pathogens are affected by the competitive abilities of susceptible and infected hosts, whether the pathogens are specialists or generalists, and the transmission pathway (direct vs. environmental transmission). In many cases, indirect effects between pathogens and predators follow similar patterns, for example, more positive indirect effects with increased interspecific competition between victim species. However, the indirect effects between pathogens can qualitatively differ, for example, more negative indirect effects with increased interspecific host competition. These contrasting patterns show that an important mechanistic difference between predatory and parasitic interactions (specifically, whether interactions are immediately lethal) can have important population-level effects on the indirect interactions between exploiters.
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14
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How intra-stage and inter-stage competition affect overcompensation in density and hydra effects in single-species, stage-structured models. THEOR ECOL-NETH 2020. [DOI: 10.1007/s12080-020-00488-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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15
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Kang HY, Kim C, Kim D, Lee YJ, Park HJ, Kundu GK, Kim YK, Bibi R, Jang J, Lee KH, Kim HW, Yun SG, Kim H, Kang CK. Identifying patterns in the multitrophic community and food-web structure of a low-turbidity temperate estuarine bay. Sci Rep 2020; 10:16637. [PMID: 33024163 PMCID: PMC7538895 DOI: 10.1038/s41598-020-73628-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2020] [Accepted: 09/21/2020] [Indexed: 11/08/2022] Open
Abstract
Food web dynamics outline the ecosystem processes that regulate community structure. Challenges in the approaches used to capture topological descriptions of food webs arise due to the difficulties in collecting extensive empirical data with temporal and spatial variations in community structure and predator-prey interactions. Here, we use a Kohonen self-organizing map algorithm (as a measure of community pattern) and stable isotope-mixing models (as a measure of trophic interaction) to identify food web patterns across a low-turbidity water channel of a temperate estuarine-coastal continuum. We find a spatial difference in the patterns of community compositions between the estuarine and deep-bay channels and a seasonal difference in the plankton pattern but less in the macrobenthos and nekton communities. Dietary mixing models of co-occurring dominant taxa reveal site-specific but unchanging food web topologies and the prominent role of phytoplankton in the trophic base of pelagic and prevalent-detrital benthic pathways. Our approach provides realistic frameworks for linking key nodes from producers to predators in trophic networks.
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Affiliation(s)
- Hee Yoon Kang
- School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Gwangju, 61005, Republic of Korea
| | - Changseong Kim
- School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Gwangju, 61005, Republic of Korea
| | - Dongyoung Kim
- School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Gwangju, 61005, Republic of Korea
| | - Young-Jae Lee
- School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Gwangju, 61005, Republic of Korea
| | - Hyun Je Park
- Department of Marine Bioscience, Gangneung-Wonju National University, Gangneung, 25457, Republic of Korea
| | - Goutam K Kundu
- School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Gwangju, 61005, Republic of Korea
| | - Young Kyun Kim
- School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Gwangju, 61005, Republic of Korea
| | - Riaz Bibi
- School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Gwangju, 61005, Republic of Korea
| | - Jaebin Jang
- School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Gwangju, 61005, Republic of Korea
| | - Kwang-Hun Lee
- School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Gwangju, 61005, Republic of Korea
| | - Hyun-Woo Kim
- Department of Marine Biology, Pukyong National University, Busan, 48513, Republic of Korea
| | - Sung-Gyu Yun
- Department of Science Education, Daegu University, Gyeongsan, 38453, Republic of Korea
| | - Heeyong Kim
- South Sea Fisheries Research Institute, National Institute of Fisheries Science, Yeosu, 59780, Republic of Korea
| | - Chang-Keun Kang
- School of Earth Sciences and Environmental Engineering, Gwangju Institute of Science and Technology, Gwangju, 61005, Republic of Korea.
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16
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Weiskopf SR, Rubenstein MA, Crozier LG, Gaichas S, Griffis R, Halofsky JE, Hyde KJW, Morelli TL, Morisette JT, Muñoz RC, Pershing AJ, Peterson DL, Poudel R, Staudinger MD, Sutton-Grier AE, Thompson L, Vose J, Weltzin JF, Whyte KP. Climate change effects on biodiversity, ecosystems, ecosystem services, and natural resource management in the United States. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 733:137782. [PMID: 32209235 DOI: 10.1016/j.scitotenv.2020.137782] [Citation(s) in RCA: 114] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 02/28/2020] [Accepted: 03/05/2020] [Indexed: 05/22/2023]
Abstract
Climate change is a pervasive and growing global threat to biodiversity and ecosystems. Here, we present the most up-to-date assessment of climate change impacts on biodiversity, ecosystems, and ecosystem services in the U.S. and implications for natural resource management. We draw from the 4th National Climate Assessment to summarize observed and projected changes to ecosystems and biodiversity, explore linkages to important ecosystem services, and discuss associated challenges and opportunities for natural resource management. We find that species are responding to climate change through changes in morphology and behavior, phenology, and geographic range shifts, and these changes are mediated by plastic and evolutionary responses. Responses by species and populations, combined with direct effects of climate change on ecosystems (including more extreme events), are resulting in widespread changes in productivity, species interactions, vulnerability to biological invasions, and other emergent properties. Collectively, these impacts alter the benefits and services that natural ecosystems can provide to society. Although not all impacts are negative, even positive changes can require costly societal adjustments. Natural resource managers need proactive, flexible adaptation strategies that consider historical and future outlooks to minimize costs over the long term. Many organizations are beginning to explore these approaches, but implementation is not yet prevalent or systematic across the nation.
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Affiliation(s)
- Sarah R Weiskopf
- U.S. Geological Survey National Climate Adaptation Science Center, Reston, VA, USA.
| | | | - Lisa G Crozier
- NOAA Northwest Fisheries Science Center, Seattle, WA, USA
| | - Sarah Gaichas
- NOAA Northeast Fisheries Science Center, Woods Hole, MA, USA
| | - Roger Griffis
- NOAA National Marine Fisheries Service, Silver Spring, MD, USA
| | - Jessica E Halofsky
- University of Washington, School of Environmental and Forest Sciences, Seattle, WA, USA
| | | | - Toni Lyn Morelli
- U.S. Geological Survey Northeast Climate Adaptation Science Center, Amherst, MA, USA
| | - Jeffrey T Morisette
- U.S. Department of the Interior, National Invasive Species Council Secretariat, Fort Collins, CO, USA
| | - Roldan C Muñoz
- NOAA Southeast Fisheries Science Center, Beaufort, NC, USA
| | | | - David L Peterson
- University of Washington, School of Environmental and Forest Sciences, Seattle, WA, USA
| | | | - Michelle D Staudinger
- U.S. Geological Survey Northeast Climate Adaptation Science Center, Amherst, MA, USA
| | - Ariana E Sutton-Grier
- University of Maryland Earth System Science Interdisciplinary Center, College Park, MD, USA
| | - Laura Thompson
- U.S. Geological Survey National Climate Adaptation Science Center, Reston, VA, USA
| | - James Vose
- U.S. Forest Service Southern Research Station, Raleigh, NC, USA
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Abstract
Observational studies have not yet shown that environmental variables can explain pervasive nonlinear patterns of species abundance, because those patterns could result from (indirect) interactions with other species (e.g., competition), and models only estimate direct responses. The experiments that could extract these indirect effects at regional to continental scales are not feasible. Here, a biophysical approach quantifies environment- species interactions (ESI) that govern community change from field data. Just as species interactions depend on population abundances, so too do the effects of environment, as when drought is amplified by competition. By embedding dynamic ESI within framework that admits data gathered on different scales, we quantify responses that are induced indirectly through other species, including probabilistic uncertainty in parameters, model specification, and data. Simulation demonstrates that ESI are needed for accurate interpretation. Analysis demonstrates how nonlinear responses arise even when their direct responses to environment are linear. Applications to experimental lakes and the Breeding Bird Survey (BBS) yield contrasting estimates of ESI. In closed lakes, interactions involving phytoplankton and their zooplankton grazers play a large role. By contrast, ESI are weak in BBS, as expected where year-to-year movement degrades the link between local population growth and species interactions. In both cases, nonlinear responses to environmental gradients are induced by interactions between species. Stability analysis indicates stability in the closed-system lakes and instability in BBS. The probabilistic framework has direct application to conservation planning that must weigh risk assessments for entire habitats and communities against competing interests.
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18
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Coblentz KE, DeLong JP. Predator‐dependent functional responses alter the coexistence and indirect effects among prey that share a predator. OIKOS 2020. [DOI: 10.1111/oik.07309] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Kyle E. Coblentz
- School of Biological Sciences, Univ. of Nebraska – Lincoln 402 Manter Hall Lincoln NE 68588 USA
| | - John P. DeLong
- School of Biological Sciences, Univ. of Nebraska – Lincoln 402 Manter Hall Lincoln NE 68588 USA
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19
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Pires MM, O'Donnell JL, Burkle LA, Díaz‐Castelazo C, Hembry DH, Yeakel JD, Newman EA, Medeiros LP, Aguiar MAM, Guimarães PR. The indirect paths to cascading effects of extinctions in mutualistic networks. Ecology 2020; 101:e03080. [DOI: 10.1002/ecy.3080] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2019] [Revised: 04/07/2020] [Accepted: 04/14/2020] [Indexed: 12/14/2022]
Affiliation(s)
- Mathias M. Pires
- Departamento de Biologia Animal Instituto de Biologia Universidade Estadual de Campinas Campinas 13.083-862 São Paulo Brazil
| | - James L. O'Donnell
- School of Marine and Environmental Affairs University of Washington Seattle WA 98105 Washington USA
| | - Laura A. Burkle
- Department of Ecology Montana State University Bozeman MT 59717 Montana USA
| | - Cecilia Díaz‐Castelazo
- Red de Interacciones Multitróficas Instituto de Ecología, A.C. Xalapa VER 11 351 Veracruz México
| | - David H. Hembry
- Department of Entomology Cornell University Ithaca NY 14853 New York USA
- Department of Ecology and Evolutionary Biology University of Arizona Tucson AZ 85721 Arizona USA
| | - Justin D. Yeakel
- School of Natural Sciences University of California Merced CA 95343 California USA
| | - Erica A. Newman
- Department of Ecology and Evolutionary Biology University of Arizona Tucson AZ 85721 Arizona USA
| | - Lucas P. Medeiros
- Department of Civil and Environmental Engineering MIT Cambridge MA 02142 Massachusetts USA
| | - Marcus A. M. Aguiar
- Instituto de Física “Gleb Wataghin” Universidade Estadual de Campinas Campinas 13083-859 São Paulo Brazil
| | - Paulo R. Guimarães
- Departamento de Ecologia Instituto de Biociências Universidade de São Paulo São Paulo 05508-090 Brazil
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20
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Adams MP, Sisson SA, Helmstedt KJ, Baker CM, Holden MH, Plein M, Holloway J, Mengersen KL, McDonald-Madden E. Informing management decisions for ecological networks, using dynamic models calibrated to noisy time-series data. Ecol Lett 2020; 23:607-619. [PMID: 31989772 DOI: 10.1111/ele.13465] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2019] [Revised: 06/13/2019] [Accepted: 12/27/2019] [Indexed: 12/25/2022]
Abstract
Well-intentioned environmental management can backfire, causing unforeseen damage. To avoid this, managers and ecologists seek accurate predictions of the ecosystem-wide impacts of interventions, given small and imprecise datasets, which is an incredibly difficult task. We generated and analysed thousands of ecosystem population time series to investigate whether fitted models can aid decision-makers to select interventions. Using these time-series data (sparse and noisy datasets drawn from deterministic Lotka-Volterra systems with two to nine species, of known network structure), dynamic model forecasts of whether a species' future population will be positively or negatively affected by rapid eradication of another species were correct > 70% of the time. Although 70% correct classifications is only slightly better than an uninformative prediction (50%), this classification accuracy can be feasibly improved by increasing monitoring accuracy and frequency. Our findings suggest that models may not need to produce well-constrained predictions before they can inform decisions that improve environmental outcomes.
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Affiliation(s)
- Matthew P Adams
- School of Earth and Environmental Sciences, The University of Queensland, St Lucia, Qld, 4072, Australia.,Centre for Biodiversity and Conservation Science, The University of Queensland, St Lucia, Qld, 4072, Australia.,ARC Centre of Excellence for Mathematical and Statistical Frontiers, The University of Queensland, St Lucia, Qld, 4072, Australia
| | - Scott A Sisson
- School of Mathematics and Statistics, The University of New South Wales, Sydney, NSW, 2052, Australia
| | - Kate J Helmstedt
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Qld, 4001, Australia.,ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, Brisbane, Qld, 4001, Australia
| | - Christopher M Baker
- Centre for Biodiversity and Conservation Science, The University of Queensland, St Lucia, Qld, 4072, Australia.,School of Mathematical Sciences, Queensland University of Technology, Brisbane, Qld, 4001, Australia.,School of Biological Sciences, The University of Queensland, St Lucia, Qld, 4072, Australia.,CSIRO Ecosystem Sciences, Ecosciences Precinct, Dutton Park, Qld, 4102, Australia.,Centre of Excellence for Environmental Decisions, The University of Queensland, St Lucia, Qld, 4072, Australia
| | - Matthew H Holden
- Centre for Biodiversity and Conservation Science, The University of Queensland, St Lucia, Qld, 4072, Australia.,School of Biological Sciences, The University of Queensland, St Lucia, Qld, 4072, Australia.,Centre of Excellence for Environmental Decisions, The University of Queensland, St Lucia, Qld, 4072, Australia.,Centre for Applications in Natural Resource Mathematics, School of Mathematics and Physics, The University of Queensland, St Lucia, Qld, 4072, Australia
| | - Michaela Plein
- School of Earth and Environmental Sciences, The University of Queensland, St Lucia, Qld, 4072, Australia.,Centre for Biodiversity and Conservation Science, The University of Queensland, St Lucia, Qld, 4072, Australia.,Administration de la Nature et des Forêts, 6, rue de la Gare, 6731, Grevenmacher, Luxembourg
| | - Jacinta Holloway
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Qld, 4001, Australia.,ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, Brisbane, Qld, 4001, Australia
| | - Kerrie L Mengersen
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, Qld, 4001, Australia.,ARC Centre of Excellence for Mathematical and Statistical Frontiers, Queensland University of Technology, Brisbane, Qld, 4001, Australia
| | - Eve McDonald-Madden
- School of Earth and Environmental Sciences, The University of Queensland, St Lucia, Qld, 4072, Australia.,Centre for Biodiversity and Conservation Science, The University of Queensland, St Lucia, Qld, 4072, Australia.,Centre of Excellence for Environmental Decisions, The University of Queensland, St Lucia, Qld, 4072, Australia
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21
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Lever JJ, van de Leemput IA, Weinans E, Quax R, Dakos V, van Nes EH, Bascompte J, Scheffer M. Foreseeing the future of mutualistic communities beyond collapse. Ecol Lett 2020; 23:2-15. [PMID: 31707763 PMCID: PMC6916369 DOI: 10.1111/ele.13401] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2019] [Revised: 06/20/2019] [Accepted: 09/14/2019] [Indexed: 02/02/2023]
Abstract
Changing conditions may lead to sudden shifts in the state of ecosystems when critical thresholds are passed. Some well-studied drivers of such transitions lead to predictable outcomes such as a turbid lake or a degraded landscape. Many ecosystems are, however, complex systems of many interacting species. While detecting upcoming transitions in such systems is challenging, predicting what comes after a critical transition is terra incognita altogether. The problem is that complex ecosystems may shift to many different, alternative states. Whether an impending transition has minor, positive or catastrophic effects is thus unclear. Some systems may, however, behave more predictably than others. The dynamics of mutualistic communities can be expected to be relatively simple, because delayed negative feedbacks leading to oscillatory or other complex dynamics are weak. Here, we address the question of whether this relative simplicity allows us to foresee a community's future state. As a case study, we use a model of a bipartite mutualistic network and show that a network's post-transition state is indicated by the way in which a system recovers from minor disturbances. Similar results obtained with a unipartite model of facilitation suggest that our results are of relevance to a wide range of mutualistic systems.
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Affiliation(s)
- J. Jelle Lever
- Department of Evolutionary Biology and Environmental StudiesUniversity of ZurichWinterthurerstrasse 190CH‐8057ZurichSwitzerland
- Department of Aquatic Ecology and Water Quality ManagementWageningen UniversityP.O. Box 47NL‐6700 AAWageningenThe Netherlands
| | - Ingrid A. van de Leemput
- Department of Aquatic Ecology and Water Quality ManagementWageningen UniversityP.O. Box 47NL‐6700 AAWageningenThe Netherlands
| | - Els Weinans
- Department of Aquatic Ecology and Water Quality ManagementWageningen UniversityP.O. Box 47NL‐6700 AAWageningenThe Netherlands
| | - Rick Quax
- Computational Science LabUniversity of AmsterdamNL‐1098 XHAmsterdamThe Netherlands
- Institute of Advanced StudiesUniversity of Amsterdam1012 GCAmsterdamThe Netherlands
| | - Vasilis Dakos
- Institut des Sciences de l'Evolution de Montpellier (ISEM)BioDICée TeamCNRSUniversité de MontpellierMontpellierFrance
| | - Egbert H. van Nes
- Department of Aquatic Ecology and Water Quality ManagementWageningen UniversityP.O. Box 47NL‐6700 AAWageningenThe Netherlands
| | - Jordi Bascompte
- Department of Evolutionary Biology and Environmental StudiesUniversity of ZurichWinterthurerstrasse 190CH‐8057ZurichSwitzerland
| | - Marten Scheffer
- Department of Aquatic Ecology and Water Quality ManagementWageningen UniversityP.O. Box 47NL‐6700 AAWageningenThe Netherlands
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22
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Terry JCD, Bonsall MB, Morris RJ. Identifying important interaction modifications in ecological systems. OIKOS 2019. [DOI: 10.1111/oik.06353] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
| | - Michael B. Bonsall
- Dept of Zoology, Univ. of Oxford Oxford OX1 3PS UK
- St. Peter's College Oxford UK
| | - Rebecca J. Morris
- Dept of Zoology, Univ. of Oxford Oxford OX1 3PS UK
- School of Biological Sciences, Univ. Of Southampton Southampton UK
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23
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Kristensen NP, Chisholm RA, McDonald‐Madden E. Dealing with high uncertainty in qualitative network models using Boolean analysis. Methods Ecol Evol 2019. [DOI: 10.1111/2041-210x.13179] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Nadiah P. Kristensen
- ARC Centre of Excellence for Environmental Decisions The University of Queensland St Lucia Qld Australia
- Department of Biological Sciences National University of Singapore Singapore Singapore
| | - Ryan A. Chisholm
- Department of Biological Sciences National University of Singapore Singapore Singapore
| | - Eve McDonald‐Madden
- ARC Centre of Excellence for Environmental Decisions The University of Queensland St Lucia Qld Australia
- School of Geography, Planning and Environmental Management the University of Queensland St. Lucia Qld Australia
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24
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Doizy A, Barter E, Memmott J, Varnham K, Gross T. Impact of cyber-invasive species on a large ecological network. Sci Rep 2018; 8:13245. [PMID: 30185798 PMCID: PMC6125364 DOI: 10.1038/s41598-018-31423-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2018] [Accepted: 08/02/2018] [Indexed: 11/20/2022] Open
Abstract
As impacts of introduced species cascade through trophic levels, they can cause indirect and counter-intuitive effects. To investigate the impact of invasive species at the network scale, we use a generalized food web model, capable of propagating changes through networks with a series of ecologically realistic criteria. Using data from a small British offshore island, we quantify the impacts of four virtual invasive species (an insectivore, a herbivore, a carnivore and an omnivore whose diet is based on a rat) and explore which clusters of species react in similar ways. We find that the predictions for the impacts of invasive species are ecologically plausible, even in large networks. Species in the same taxonomic group are similarly impacted by a virtual invasive species. However, interesting differences within a given taxonomic group can occur. The results suggest that some native species may be at risk from a wider range of invasives than previously believed. The implications of these results for ecologists and land managers are discussed.
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Affiliation(s)
- Anna Doizy
- Université Paris-Sud, 91400 Orsay, France and AgroParisTech, 75005, Paris, France.
| | - Edmund Barter
- Queen's Building, University Walk, Bristol, BS8 1TR, UK
| | - Jane Memmott
- School of Biological Sciences, Life Sciences Building, Tyndall Avenue, Bristol, BS8 1TQ, UK
| | - Karen Varnham
- Royal Society for the Protection of Birds, The Lodge, Beds, Sandy, SG19 2DL, UK
| | - Thilo Gross
- Merchant Venturers Building, Woodland Road, Bristol, BS8 1UB, UK
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25
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Effects of Climate Change on Grassland Biodiversity and Productivity: The Need for a Diversity of Models. AGRONOMY-BASEL 2018. [DOI: 10.3390/agronomy8020014] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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26
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Biomonitoring for the 21st Century: Integrating Next-Generation Sequencing Into Ecological Network Analysis. ADV ECOL RES 2018. [DOI: 10.1016/bs.aecr.2017.12.001] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
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27
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Giordano G, Altafini C. Qualitative and quantitative responses to press perturbations in ecological networks. Sci Rep 2017; 7:11378. [PMID: 28900208 PMCID: PMC5596000 DOI: 10.1038/s41598-017-11221-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2017] [Accepted: 08/21/2017] [Indexed: 11/09/2022] Open
Abstract
Predicting the sign of press perturbation responses in ecological networks is challenging, due to the poor knowledge of the strength of the direct interactions among the species, and to the entangled coexistence of direct and indirect effects. We show in this paper that, for a class of networks that includes mutualistic and monotone networks, the sign of press perturbation responses can be qualitatively determined based only on the sign pattern of the community matrix, without any knowledge of parameter values. For other classes of networks, we show that a semi-qualitative approach yields sufficient conditions for community matrices with a given sign pattern to exhibit mutualistic responses to press perturbations; quantitative conditions can be provided as well for community matrices that are eventually nonnegative. We also present a computational test that can be applied to any class of networks so as to check whether the sign of the responses to press perturbations is constant in spite of parameter variations.
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Affiliation(s)
- Giulia Giordano
- Department of Automatic Control and LCCC Linnaeus Center, Lund University, Box 118, SE-221 00, Lund, Sweden
| | - Claudio Altafini
- Division of Automatic Control, Department of Electrical Engineering, Linköping University, SE-58183, Linköping, Sweden.
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28
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Exact probabilities for the indeterminacy of complex networks as perceived through press perturbations. J Math Biol 2017; 76:877-909. [PMID: 28735343 DOI: 10.1007/s00285-017-1163-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Revised: 07/13/2017] [Indexed: 10/19/2022]
Abstract
We consider the goal of predicting how complex networks respond to chronic (press) perturbations when characterizations of their network topology and interaction strengths are associated with uncertainty. Our primary result is the derivation of exact formulas for the expected number and probability of qualitatively incorrect predictions about a system's responses under uncertainties drawn form arbitrary distributions of error. Additional indices provide new tools for identifying which links in a network are most qualitatively and quantitatively sensitive to error, and for determining the volume of errors within which predictions will remain qualitatively determinate (i.e. sign insensitive). Together with recent advances in the empirical characterization of uncertainty in networks, these tools bridge a way towards probabilistic predictions of network dynamics.
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29
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Tunney TD, Carpenter SR, Vander Zanden MJ. The consistency of a species’ response to press perturbations with high food web uncertainty. Ecology 2017; 98:1859-1868. [DOI: 10.1002/ecy.1853] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2017] [Accepted: 02/07/2017] [Indexed: 11/10/2022]
Affiliation(s)
- Tyler D. Tunney
- Center for Limnology; University of Wisconsin-Madison; 680 North Park Street Madison Wisconsin 53706 USA
| | - Stephen R. Carpenter
- Center for Limnology; University of Wisconsin-Madison; 680 North Park Street Madison Wisconsin 53706 USA
| | - M. Jake Vander Zanden
- Center for Limnology; University of Wisconsin-Madison; 680 North Park Street Madison Wisconsin 53706 USA
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30
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Bayesian characterization of uncertainty in species interaction strengths. Oecologia 2017; 184:327-339. [DOI: 10.1007/s00442-017-3867-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2016] [Accepted: 04/05/2017] [Indexed: 10/19/2022]
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31
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Spatial complexity enhances predictability in food webs. Sci Rep 2017; 7:43440. [PMID: 28240306 PMCID: PMC5327493 DOI: 10.1038/srep43440] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2016] [Accepted: 01/23/2017] [Indexed: 11/19/2022] Open
Abstract
The prediction of an ecosystem’s response to an environmental disturbance or the artificial control of ecosystems is a challenging task in ecology. Ecological theory predicts that disturbances frequently result in unexpected responses between interacting species due to the many indirect interactions within a complex community. However, such indeterminacy appears to be unusual in nature. Here using a meta-community food web, I show that spatiality is key to resolving this disparity. A moderate level of spatial coupling strength between habitats due to species migration increases the possibility of expected responses to press perturbation or predictability. Moreover, predictability increases with increasing spatial complexity, as measured by the number of local food webs and their connectivity. A meta-community network can attenuate the propagation of disturbances through indirect pathways due to species emigration to other habitats, thereby preserving the expected effect on the interacting species. These results suggest that the isolation of communities due to habitat destruction decreases the predictability of communities, thereby complicating the control of ecosystems.
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32
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33
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Wootton KL, Stouffer DB. Species' traits and food‐web complexity interactively affect a food web's response to press disturbance. Ecosphere 2016. [DOI: 10.1002/ecs2.1518] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Affiliation(s)
- K. L. Wootton
- Centre for Integrative EcologySchool of Biological SciencesUniversity of Canterbury Private Bag 4800 8140 Christchurch New Zealand
| | - D. B. Stouffer
- Centre for Integrative EcologySchool of Biological SciencesUniversity of Canterbury Private Bag 4800 8140 Christchurch New Zealand
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34
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Novak M, Yeakel JD, Noble AE, Doak DF, Emmerson M, Estes JA, Jacob U, Tinker MT, Wootton JT. Characterizing Species Interactions to Understand Press Perturbations: What Is the Community Matrix? ANNUAL REVIEW OF ECOLOGY EVOLUTION AND SYSTEMATICS 2016. [DOI: 10.1146/annurev-ecolsys-032416-010215] [Citation(s) in RCA: 72] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The community matrix is among ecology's most important mathematical abstractions, formally encapsulating the interconnected network of effects that species have on one another's populations. Despite its importance, the term “community matrix” has been applied to multiple types of matrices that have differing interpretations. This has hindered the application of theory for understanding community structure and perturbation responses. Here, we clarify the correspondence and distinctions among the Interaction matrix, the Alpha matrix, and the Jacobian matrix, terms that are frequently used interchangeably as well as synonymously with the term “community matrix.” We illustrate how these matrices correspond to different ways of characterizing interaction strengths, how they permit insights regarding different types of press perturbations, and how these are related by a simple scaling relationship. Connections to additional interaction strength characterizations encapsulated by the Beta matrix, the Gamma matrix, and the Removal matrix are also discussed. Our synthesis highlights the empirical challenges that remain in using these tools to understand actual communities.
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Affiliation(s)
- Mark Novak
- Department of Integrative Biology, Oregon State University, Corvallis, Oregon 97331
| | - Justin D. Yeakel
- School of Natural Sciences, University of California, Merced, California 95343
- Santa Fe Institute, Santa Fe, New Mexico 87501
| | - Andrew E. Noble
- Department of Environmental Science and Policy, University of California, Davis, California 95616
| | - Daniel F. Doak
- Department of Environmental Studies, University of Colorado, Boulder, Colorado 80309
| | - Mark Emmerson
- School of Biological Sciences, Queen's University Belfast, Belfast BT7 1NN, Northern Ireland, United Kingdom
| | - James A. Estes
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, California 95060
| | - Ute Jacob
- Department of Biology, University of Hamburg, D-22767 Hamburg, Germany
| | - M. Timothy Tinker
- Western Ecological Research Center, US Geological Survey, Santa Cruz, California 95060
| | - J. Timothy Wootton
- Department of Ecology and Evolution, University of Chicago, Chicago, Illinois 60637
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35
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Neutel AM, Thorne MAS. Beyond connectedness: why pairwise metrics cannot capture community stability. Ecol Evol 2016; 6:7199-7206. [PMID: 28725392 PMCID: PMC5513267 DOI: 10.1002/ece3.2461] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2016] [Revised: 07/29/2016] [Accepted: 08/04/2016] [Indexed: 11/17/2022] Open
Abstract
The connectedness of species in a trophic web has long been a key structural characteristic for both theoreticians and empiricists in their understanding of community stability. In the past decades, there has been a shift from focussing on determining the number of interactions to taking into account their relative strengths. The question is: How do the strengths of the interactions determine the stability of a community? Recently, a metric has been proposed which compares the stability of observed communities in terms of the strength of three‐ and two‐link feedback loops (cycles of interaction strengths). However, it has also been suggested that we do not need to go beyond the pairwise structure of interactions to capture stability. Here, we directly compare the performance of the feedback and pairwise metrics. Using observed food‐web structures, we show that the pairwise metric does not work as a comparator of stability and is many orders of magnitude away from the actual stability values. We argue that metrics based on pairwise‐strength information cannot capture the complex organization of strong and weak links in a community, which is essential for system stability.
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36
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Frost CM, Peralta G, Rand TA, Didham RK, Varsani A, Tylianakis JM. Apparent competition drives community-wide parasitism rates and changes in host abundance across ecosystem boundaries. Nat Commun 2016; 7:12644. [PMID: 27577948 PMCID: PMC5013663 DOI: 10.1038/ncomms12644] [Citation(s) in RCA: 42] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2016] [Accepted: 07/19/2016] [Indexed: 11/21/2022] Open
Abstract
Species have strong indirect effects on others, and predicting these effects is a central challenge in ecology. Prey species sharing an enemy (predator or parasitoid) can be linked by apparent competition, but it is unknown whether this process is strong enough to be a community-wide structuring mechanism that could be used to predict future states of diverse food webs. Whether species abundances are spatially coupled by enemy movement across different habitats is also untested. Here, using a field experiment, we show that predicted apparent competitive effects between species, mediated via shared parasitoids, can significantly explain future parasitism rates and herbivore abundances. These predictions are successful even across edges between natural and managed forests, following experimental reduction of herbivore densities by aerial spraying of insecticide over 20 hectares. This result shows that trophic indirect effects propagate across networks and habitats in important, predictable ways, with implications for landscape planning, invasion biology and biological control. Species sharing a common enemy such as a parasitoid or predator can indirectly affect one another. Here, Frost et al. use quantitative food-web data from communities of caterpillar hosts to show experimentally that apparent competition is important in predicting food-web structure across habitats.
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Affiliation(s)
- Carol M Frost
- Centre for Integrative Ecology, School of Biological Sciences, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand
| | - Guadalupe Peralta
- Centre for Integrative Ecology, School of Biological Sciences, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand
| | - Tatyana A Rand
- USDA-ARS Northern Plains Agricultural Research Laboratory, Sidney, Montana 59270, USA
| | - Raphael K Didham
- School of Animal Biology, The University of Western Australia, 35 Stirling Highway, Crawley Western Australia 6009, Australia.,CSIRO Land &Water, Centre for Environment and Life Sciences, Underwood Ave, Floreat Western Australia 6014, Australia
| | - Arvind Varsani
- Centre for Integrative Ecology, School of Biological Sciences, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand.,Biomolecular Interaction Centre, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand.,Structural Biology Research Unit, Department of Clinical Laboratory Sciences, University of Cape Town, Observatory, Cape Town 7700, South Africa.,Department of Plant Pathology and Emerging Pathogens Institute, University of Florida, Gainesville, Florida 32611, USA
| | - Jason M Tylianakis
- Centre for Integrative Ecology, School of Biological Sciences, University of Canterbury, Private Bag 4800, Christchurch 8140, New Zealand.,Department of Life Sciences, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot, Berkshire SL5 7PY, UK
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37
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Iles AC, Novak M. Complexity Increases Predictability in Allometrically Constrained Food Webs. Am Nat 2016; 188:87-98. [DOI: 10.1086/686730] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
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38
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Barabás G, Allesina S. Predicting global community properties from uncertain estimates of interaction strengths. J R Soc Interface 2016; 12:20150218. [PMID: 26246417 DOI: 10.1098/rsif.2015.0218] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The community matrix measures the direct effect of species on each other in an ecological community. It can be used to determine whether a system is stable (returns to equilibrium after small perturbations of the population abundances), reactive (perturbations are initially amplified before damping out), and to determine the response of any individual species to perturbations of environmental parameters. However, several studies show that small errors in estimating the entries of the community matrix translate into large errors in predicting individual species responses. Here, we ask whether there are properties of complex communities one can still predict using only a crude, order-of-magnitude estimate of the community matrix entries. Using empirical data, randomly generated community matrices, and those generated by the Allometric Trophic Network model, we show that the stability and reactivity properties of systems can be predicted with good accuracy. We also provide theoretical insight into when and why our crude approximations are expected to yield an accurate description of communities. Our results indicate that even rough estimates of interaction strengths can be useful for assessing global properties of large systems.
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Affiliation(s)
- György Barabás
- Department of Ecology and Evolution, University of Chicago, 1101 E 57th Street, Chicago, IL 60637, USA
| | - Stefano Allesina
- Department of Ecology and Evolution, University of Chicago, 1101 E 57th Street, Chicago, IL 60637, USA Computational Institute, University of Chicago, 1101 E 57th Street, Chicago, IL 60637, USA
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39
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Burman CJ, Aphane M, Delobelle P. Reducing the overall HIV-burden in South Africa: is 'reviving ABC' an appropriate fit for a complex, adaptive epidemiological HIV landscape? AJAR-AFRICAN JOURNAL OF AIDS RESEARCH 2016; 14:13-28. [PMID: 25920980 DOI: 10.2989/16085906.2015.1016988] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
This article questions the recommendations to 'revive ABC (abstain, be faithful, condomise)' as a mechanism to 'educate' people in South Africa about HIV prevention as the South African National HIV Prevalence, Incidence and Behaviour Survey, 2012, suggests. We argue that ABC was designed as a response to a particular context which has now radically changed. In South Africa the contemporary context reflects the mass roll-out of antiretroviral treatment; significant bio-medical knowledge gains; a generalised population affected by HIV that has made sense of and embodied those diverse experiences; and a government committed to confronting the epidemic. We suggest that the situation can now be plausibly conceptualised as a complex, adaptive epidemiological landscape that could benefit from an expansion of the existing, 'descriptive' prevention paradigm towards strategies that focus on the dynamics of transmission. We argue for this shift by proposing a theoretical framework based on complexity theory and pattern management. We interrogate one educational prevention heuristic that emphasises the importance of risk-reduction through the lens of transmission, called A-3B-4C-T. We argue that this type of approach provides expansive opportunities for people to engage with the epidemic in contextualised, innovative ways that supersede the opportunities afforded by ABC. We then suggest that framing the prevention imperative through the lens of 'dynamic prevention' at scale opens more immediate opportunities, as well as developing a future-oriented mind-set, than the 'descriptive prevention' parameters can facilitate. The parameters of the 'descriptive prevention' paradigm, that maintain - and partially reinforce - the presence of ABC, do not have the flexibility required to develop the armamentarium of tools required to contribute to the management of a complex epidemiological landscape. Uncritically adhering to both the 'descriptive paradigm', and ABC, represents an historically dislocated form of prevention - with restrictive options for reducing the overall burden of HIV-related challenges in South Africa.
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Affiliation(s)
- Christopher J Burman
- a The Rural Development and Innovation Hub , University of Limpopo , Turfloop Campus, Polokwane , South Africa
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Suweis S, Grilli J, Banavar JR, Allesina S, Maritan A. Effect of localization on the stability of mutualistic ecological networks. Nat Commun 2015; 6:10179. [PMID: 26674106 PMCID: PMC4703855 DOI: 10.1038/ncomms10179] [Citation(s) in RCA: 58] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2015] [Accepted: 11/12/2015] [Indexed: 11/10/2022] Open
Abstract
The relationships between the core–periphery architecture of the species interaction network and the mechanisms ensuring the stability in mutualistic ecological communities are still unclear. In particular, most studies have focused their attention on asymptotic resilience or persistence, neglecting how perturbations propagate through the system. Here we develop a theoretical framework to evaluate the relationship between the architecture of the interaction networks and the impact of perturbations by studying localization, a measure describing the ability of the perturbation to propagate through the network. We show that mutualistic ecological communities are localized, and localization reduces perturbation propagation and attenuates its impact on species abundance. Localization depends on the topology of the interaction networks, and it positively correlates with the variance of the weighted degree distribution, a signature of the network topological heterogeneity. Our results provide a different perspective on the interplay between the architecture of interaction networks in mutualistic communities and their stability. The architecture of ecological interaction networks affects community dynamics. Here, Suweis et al. show that mutualistic networks are characterized by a high degree of localization, and that localization reduces perturbation propagation and attenuates its impact on species abundances.
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Affiliation(s)
- Samir Suweis
- Department of Physics and Astronomy, University of Padua, Consorzio Nazionale Interuniversitario per le Scienze Fisiche della Materia and Istituto Nazionale di Fisica Nucleare, 35131 Padova, Italy
| | - Jacopo Grilli
- Department of Ecology and Evolution, University of Chicago, 1101 East 57th Street, Chicago, Illinois 60637, USA
| | - Jayanth R Banavar
- Department of Physics, University of Maryland, College Park, Maryland 20742, USA
| | - Stefano Allesina
- Department of Ecology and Evolution, University of Chicago, 1101 East 57th Street, Chicago, Illinois 60637, USA
| | - Amos Maritan
- Department of Physics and Astronomy, University of Padua, Consorzio Nazionale Interuniversitario per le Scienze Fisiche della Materia and Istituto Nazionale di Fisica Nucleare, 35131 Padova, Italy
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Abrams PA, Cortez MH. Is competition needed for ecological character displacement? Does displacement decrease competition? Evolution 2015; 69:3039-53. [PMID: 26548922 PMCID: PMC5063131 DOI: 10.1111/evo.12816] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2015] [Revised: 10/27/2015] [Accepted: 10/29/2015] [Indexed: 11/29/2022]
Abstract
Interspecific competition for resources is generally considered to be the selective force driving ecological character displacement, and displacement is assumed to reduce competition. Skeptics of the prevalence of character displacement often cite lack of evidence of competition. The present article uses a simple model to examine whether competition is needed for character displacement and whether displacement reduces competition. It treats systems with competing resources, and considers cases when only one consumer evolves. It quantifies competition using several different measures. The analysis shows that selection for divergence of consumers occurs regardless of the level of between-resource competition or whether the indirect interaction between the consumers is competition (-,-), mutualism (+,+), or contramensalism (+,-). Also, divergent evolution always decreases the equilibrium population size of the evolving consumer. Whether divergence of one consumer reduces or increases the impact of a subsequent perturbation of the other consumer depends on the parameters and the method chosen for measuring competition. Divergence in mutualistic interactions may reduce beneficial effects of subsequent increases in the other consumer's population. The evolutionary response is driven by an increase in the relative abundance of the resource the consumer catches more rapidly. Such an increase can occur under several types of interaction.
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Affiliation(s)
- Peter A Abrams
- Department of Ecology & Evolutionary Biology, University of Toronto:, 25 Harbord St., Toronto, Ontario, M5S 3G5, Canada.
| | - Michael H Cortez
- Department of Mathematics and Statistics, Utah State University, Logan, Utah, 84322
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Abrams PA, Cortez MH. The many potential indirect interactions between predators that share competing prey. ECOL MONOGR 2015. [DOI: 10.1890/14-2025.1] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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Petchey OL, Pontarp M, Massie TM, Kéfi S, Ozgul A, Weilenmann M, Palamara GM, Altermatt F, Matthews B, Levine JM, Childs DZ, McGill BJ, Schaepman ME, Schmid B, Spaak P, Beckerman AP, Pennekamp F, Pearse IS, Vasseur D. The ecological forecast horizon, and examples of its uses and determinants. Ecol Lett 2015; 18:597-611. [PMID: 25960188 PMCID: PMC4676300 DOI: 10.1111/ele.12443] [Citation(s) in RCA: 143] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2015] [Accepted: 03/27/2015] [Indexed: 12/28/2022]
Abstract
Forecasts of ecological dynamics in changing environments are increasingly important, and are available for a plethora of variables, such as species abundance and distribution, community structure and ecosystem processes. There is, however, a general absence of knowledge about how far into the future, or other dimensions (space, temperature, phylogenetic distance), useful ecological forecasts can be made, and about how features of ecological systems relate to these distances. The ecological forecast horizon is the dimensional distance for which useful forecasts can be made. Five case studies illustrate the influence of various sources of uncertainty (e.g. parameter uncertainty, environmental variation, demographic stochasticity and evolution), level of ecological organisation (e.g. population or community), and organismal properties (e.g. body size or number of trophic links) on temporal, spatial and phylogenetic forecast horizons. Insights from these case studies demonstrate that the ecological forecast horizon is a flexible and powerful tool for researching and communicating ecological predictability. It also has potential for motivating and guiding agenda setting for ecological forecasting research and development.
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Affiliation(s)
- Owen L Petchey
- Institute of Evolutionary Biology and Environmental Studies, University of ZurichWinterthurerstrasse 190, CH-8057, Zurich, Switzerland
- Department of Aquatic Ecology, Eawag: Swiss Federal Institute of Aquatic Science and TechnologyÜberlandstrasse 133, 8600 Dübendorf, Switzerland
| | - Mikael Pontarp
- Institute of Evolutionary Biology and Environmental Studies, University of ZurichWinterthurerstrasse 190, CH-8057, Zurich, Switzerland
- Department of Ecology and Environmental Science, Umeå UniversitySE- 901 87 Umeå, Sweden
| | - Thomas M Massie
- Institute of Evolutionary Biology and Environmental Studies, University of ZurichWinterthurerstrasse 190, CH-8057, Zurich, Switzerland
| | - Sonia Kéfi
- Institut des Sciences de l’Evolution, Université de Montpellier, CNRS, IRD, EPHE, CC065Place Eugène Bataillon, 34095, Montpellier Cedex 05, France
| | - Arpat Ozgul
- Institute of Evolutionary Biology and Environmental Studies, University of ZurichWinterthurerstrasse 190, CH-8057, Zurich, Switzerland
| | - Maja Weilenmann
- Institute of Evolutionary Biology and Environmental Studies, University of ZurichWinterthurerstrasse 190, CH-8057, Zurich, Switzerland
| | - Gian Marco Palamara
- Institute of Evolutionary Biology and Environmental Studies, University of ZurichWinterthurerstrasse 190, CH-8057, Zurich, Switzerland
| | - Florian Altermatt
- Institute of Evolutionary Biology and Environmental Studies, University of ZurichWinterthurerstrasse 190, CH-8057, Zurich, Switzerland
- Department of Aquatic Ecology, Eawag: Swiss Federal Institute of Aquatic Science and TechnologyÜberlandstrasse 133, 8600 Dübendorf, Switzerland
| | - Blake Matthews
- Department of Aquatic Ecology, Center for Ecology, Evolution, and Biogeochemistry, Eawag: Swiss Federal Institute of Aquatic Science and TechnologyKastanienbaum, Seestrasse 79, 6047 Luzern, Switzerland
| | - Jonathan M Levine
- Institute of Integrative Biology, ETH ZurichUniversitätstrasse 16, 8092, Zurich, Switzerland
| | - Dylan Z Childs
- Animal and Plant Sciences, Sheffield UniversitySheffield, Western Bank. S10 2TN South Yorkshire, UK
| | - Brian J McGill
- School of Biology and Ecology and Mitchel Center for Sustainability Solutions, University of MaineOrono, 5751 Murray Hall, ME 04469, USA
| | - Michael E Schaepman
- University of Zurich, Department of Geography, Remote Sensing LaboratoriesWinterthurerstrasse 190, CH-8057 Zurich, Switzerland
| | - Bernhard Schmid
- Institute of Evolutionary Biology and Environmental Studies, University of ZurichWinterthurerstrasse 190, CH-8057, Zurich, Switzerland
| | - Piet Spaak
- Department of Aquatic Ecology, Eawag: Swiss Federal Institute of Aquatic Science and TechnologyÜberlandstrasse 133, 8600 Dübendorf, Switzerland
- Institute of Integrative Biology, ETH ZurichUniversitätstrasse 16, 8092, Zurich, Switzerland
| | - Andrew P Beckerman
- Animal and Plant Sciences, Sheffield UniversitySheffield, Western Bank. S10 2TN South Yorkshire, UK
| | - Frank Pennekamp
- Institute of Evolutionary Biology and Environmental Studies, University of ZurichWinterthurerstrasse 190, CH-8057, Zurich, Switzerland
| | - Ian S Pearse
- The Illinois Natural History SurveyChampaign, 1816 South Oak Street, MC 652, IL 61820, USA
| | - David Vasseur
- Institute of Evolutionary Biology and Environmental Studies, University of ZurichWinterthurerstrasse 190, CH-8057, Zurich, Switzerland
- Department of Aquatic Ecology, Eawag: Swiss Federal Institute of Aquatic Science and TechnologyÜberlandstrasse 133, 8600 Dübendorf, Switzerland
- Department of Ecology and Environmental Science, Umeå UniversitySE- 901 87 Umeå, Sweden
- Institut des Sciences de l’Evolution, Université de Montpellier, CNRS, IRD, EPHE, CC065Place Eugène Bataillon, 34095, Montpellier Cedex 05, France
- Department of Aquatic Ecology, Center for Ecology, Evolution, and Biogeochemistry, Eawag: Swiss Federal Institute of Aquatic Science and TechnologyKastanienbaum, Seestrasse 79, 6047 Luzern, Switzerland
- Institute of Integrative Biology, ETH ZurichUniversitätstrasse 16, 8092, Zurich, Switzerland
- Animal and Plant Sciences, Sheffield UniversitySheffield, Western Bank. S10 2TN South Yorkshire, UK
- School of Biology and Ecology and Mitchel Center for Sustainability Solutions, University of MaineOrono, 5751 Murray Hall, ME 04469, USA
- University of Zurich, Department of Geography, Remote Sensing LaboratoriesWinterthurerstrasse 190, CH-8057 Zurich, Switzerland
- The Illinois Natural History SurveyChampaign, 1816 South Oak Street, MC 652, IL 61820, USA
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Lurgi M, Montoya D, Montoya JM. The effects of space and diversity of interaction types on the stability of complex ecological networks. THEOR ECOL-NETH 2015. [DOI: 10.1007/s12080-015-0264-x] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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Mumby PJ, van Woesik R. Consequences of ecological, evolutionary and biogeochemical uncertainty for coral reef responses to climatic stress. Curr Biol 2015; 24:R413-23. [PMID: 24845674 DOI: 10.1016/j.cub.2014.04.029] [Citation(s) in RCA: 39] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Coral reefs are highly sensitive to the stress associated with greenhouse gas emissions, in particular ocean warming and acidification. While experiments show negative responses of most reef organisms to ocean warming, some autotrophs benefit from ocean acidification. Yet, we are uncertain of the response of coral reefs as systems. We begin by reviewing sources of uncertainty and complexity including the translation of physiological effects into demographic processes, indirect ecological interactions among species, the ability of coral reefs to modify their own chemistry, adaptation and trans-generational plasticity. We then incorporate these uncertainties into two simple qualitative models of a coral reef system under climate change. Some sources of uncertainty are far more problematic than others. Climate change is predicted to have an unambiguous negative effect on corals that is robust to several sources of uncertainty but sensitive to the degree of biogeochemical coupling between benthos and seawater. Macroalgal, zoanthid, and herbivorous fish populations are generally predicted to increase, but the ambiguity (confidence) of such predictions are sensitive to the source of uncertainty. For example, reversing the effect of climate-related stress on macroalgae from being positive to negative had no influence on system behaviour. By contrast, the system was highly sensitive to a change in the stress upon herbivorous fishes. Minor changes in competitive interactions had profound impacts on system behaviour, implying that the outcomes of mesocosm studies could be highly sensitive to the choice of taxa. We use our analysis to identify new hypotheses and suggest that the effects of climatic stress on coral reefs provide an exceptional opportunity to test emerging theories of ecological inheritance.
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Affiliation(s)
- Peter J Mumby
- Marine Spatial Ecology Lab & ARC Centre of Excellence for Coral Reef Studies, School of Biological Sciences, University of Queensland, St Lucia, Qld 4072, Australia.
| | - Robert van Woesik
- Department of Biological Sciences, Florida Institute of Technology, 150 West University Blvd, Melbourne, Florida, 32901, USA
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Palamara GM, Childs DZ, Clements CF, Petchey OL, Plebani M, Smith MJ. Inferring the temperature dependence of population parameters: the effects of experimental design and inference algorithm. Ecol Evol 2014; 4:4736-50. [PMID: 25558365 PMCID: PMC4278823 DOI: 10.1002/ece3.1309] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2014] [Revised: 09/25/2014] [Accepted: 10/01/2014] [Indexed: 11/22/2022] Open
Abstract
Understanding and quantifying the temperature dependence of population parameters, such as intrinsic growth rate and carrying capacity, is critical for predicting the ecological responses to environmental change. Many studies provide empirical estimates of such temperature dependencies, but a thorough investigation of the methods used to infer them has not been performed yet. We created artificial population time series using a stochastic logistic model parameterized with the Arrhenius equation, so that activation energy drives the temperature dependence of population parameters. We simulated different experimental designs and used different inference methods, varying the likelihood functions and other aspects of the parameter estimation methods. Finally, we applied the best performing inference methods to real data for the species Paramecium caudatum. The relative error of the estimates of activation energy varied between 5% and 30%. The fraction of habitat sampled played the most important role in determining the relative error; sampling at least 1% of the habitat kept it below 50%. We found that methods that simultaneously use all time series data (direct methods) and methods that estimate population parameters separately for each temperature (indirect methods) are complementary. Indirect methods provide a clearer insight into the shape of the functional form describing the temperature dependence of population parameters; direct methods enable a more accurate estimation of the parameters of such functional forms. Using both methods, we found that growth rate and carrying capacity of Paramecium caudatum scale with temperature according to different activation energies. Our study shows how careful choice of experimental design and inference methods can increase the accuracy of the inferred relationships between temperature and population parameters. The comparison of estimation methods provided here can increase the accuracy of model predictions, with important implications in understanding and predicting the effects of temperature on the dynamics of populations.
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Affiliation(s)
- Gian Marco Palamara
- Department of Evolutionary Biology and Environmental Studies, University of Zurich Wintherthurerstrase 190, CH-8057, Zurich, Switzerland ; Computational Science Laboratory, Microsoft Research Cambridge, CB1 2FB, UK
| | - Dylan Z Childs
- Department of Animal and Plant Sciences, University of Sheffield Sheffield, S10 2TN, UK
| | - Christopher F Clements
- Department of Evolutionary Biology and Environmental Studies, University of Zurich Wintherthurerstrase 190, CH-8057, Zurich, Switzerland
| | - Owen L Petchey
- Department of Evolutionary Biology and Environmental Studies, University of Zurich Wintherthurerstrase 190, CH-8057, Zurich, Switzerland
| | - Marco Plebani
- Department of Evolutionary Biology and Environmental Studies, University of Zurich Wintherthurerstrase 190, CH-8057, Zurich, Switzerland
| | - Matthew J Smith
- Computational Science Laboratory, Microsoft Research Cambridge, CB1 2FB, UK
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47
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Burns TP, Rose KA, Brenkert AL. Quantifying direct and indirect effects of perturbations using model ecosystems. Ecol Modell 2014. [DOI: 10.1016/j.ecolmodel.2013.12.017] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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48
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Barabás G, Pásztor L, Meszéna G, Ostling A. Sensitivity analysis of coexistence in ecological communities: theory and application. Ecol Lett 2014; 17:1479-94. [DOI: 10.1111/ele.12350] [Citation(s) in RCA: 37] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2014] [Revised: 04/18/2014] [Accepted: 08/01/2014] [Indexed: 11/29/2022]
Affiliation(s)
- György Barabás
- Department of Ecology and Evolution; University of Chicago; 1101 E 57th St Chicago IL 60637 USA
| | - Liz Pásztor
- Department of Genetics; Eötvös Loránd University; Pázmány Péter sétány 1C H-1117 Budapest Hungary
| | - Géza Meszéna
- Department of Biological Physics; Eötvös Loránd University; Pázmány Péter sétány 1A H-1117 Budapest Hungary
| | - Annette Ostling
- Department of Ecology and Evolutionary Biology; University of Michigan; 830 North University Ann Arbor MI 48109-1048 USA
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Abstract
The dynamics of ecosystem collapse are fundamental to determining how and why biological communities change through time, as well as the potential effects of extinctions on ecosystems. Here, we integrate depictions of mammals from Egyptian antiquity with direct lines of paleontological and archeological evidence to infer local extinctions and community dynamics over a 6,000-y span. The unprecedented temporal resolution of this dataset enables examination of how the tandem effects of human population growth and climate change can disrupt mammalian communities. We show that the extinctions of mammals in Egypt were nonrandom and that destabilizing changes in community composition coincided with abrupt aridification events and the attendant collapses of some complex societies. We also show that the roles of species in a community can change over time and that persistence is predicted by measures of species sensitivity, a function of local dynamic stability. To our knowledge, our study is the first high-resolution analysis of the ecological impacts of environmental change on predator-prey networks over millennial timescales and sheds light on the historical events that have shaped modern animal communities.
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50
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Kimbro DL, Byers JE, Grabowski JH, Hughes AR, Piehler MF. The biogeography of trophic cascades on US oyster reefs. Ecol Lett 2014; 17:845-54. [PMID: 24796892 DOI: 10.1111/ele.12293] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2014] [Revised: 03/18/2014] [Accepted: 04/11/2014] [Indexed: 11/27/2022]
Abstract
Predators can indirectly benefit prey populations by suppressing mid-trophic level consumers, but often the strength and outcome of trophic cascades are uncertain. We manipulated oyster reef communities to test the generality of potential causal factors across a 1000-km region. Densities of oyster consumers were weakly influenced by predators at all sites. In contrast, consumer foraging behaviour in the presence of predators varied considerably, and these behavioural effects altered the trophic cascade across space. Variability in the behavioural cascade was linked to regional gradients in oyster recruitment to and sediment accumulation on reefs. Specifically, asynchronous gradients in these factors influenced whether the benefits of suppressed consumer foraging on oyster recruits exceeded costs of sediment accumulation resulting from decreased consumer activity. Thus, although predation on consumers remains consistent, predator influences on behaviour do not; rather, they interact with environmental gradients to cause biogeographic variability in the net strength of trophic cascades.
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Affiliation(s)
- David L Kimbro
- Marine Science Center, Department of Marine and Environmental Sciences, Northeastern University, 430 Nahant Road, Nahant, MA, 01908, USA
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