Metacommunity framework and its core terms entanglement

  1. Jurek Kolasa
  2. Matthew P. Hammond
  3. Joyce Yan

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Abstract

The metacommunity framework links space and ecological processes but is vulnerable to complex entanglement among its integral components. Most ecological processes are context-dependent. However, when ecological theories show it, they may be seriously crippled unless they explicitly tackle it. Otherwise, findings emerging from accumulated cases will be of limited value and likely remain ambiguous or misleading. Specifically, interactions among the core terms of metacommunity theory interact in complex ways that we identify as entanglement. We employ four core dimensions to alleviate this issue and create a space where various studies converse and effectively complement each other irrespective of the case specifics. The dimensions encompass the metacommunity empirical domain: (1) inter-habitat differences, (2) species habitat specialization, (3) effective dispersal, and (4) species interactions (negative to positive). Then, we assess the entanglement effects by testing that (a) changing values in one dimension, with others constant, alters study conclusions , and (b) these effects increase and dominate when integral dimensions interact reciprocally . As a metric, we analyzed species diversity in a stochastic, agent-based, unified metacommunity model, UMM, where species move, select habitats, reproduce, and interact. In the simulations, each dimension has four or five levels spanning a broad spectrum of conditions. The exercise strongly supports both hypotheses. It also suggests that positive interactions, in contrast to the popular emphasis, promote biodiversity more than negative ones like competition or predation. The proposed integrated conceptual system can expand to include meta-ecosystems, habitat gradients, and other processes. Thus, it can offer a unified approach to spatial processes in ecology. Finally, by combining the four dimensions into one interactive system, we identify a rich array of lower-level hypotheses that inevitably emerge from this system. The hypotheses’ shared origin anchors individual studies in coherent structure to advance sound generalizations.

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  1. Version published to 10.1101/2021.09.26.461405v3 on bioRxiv
  2. Version published to 10.1101/2021.09.26.461405v2 on bioRxiv
  3. PeerRef

    Peer review report

    Reviewer: Bertrand Fournier Institution: Potsdam University email: bfourni@gmail.com

    General comments

    This paper investigates context-dependencies in metacommunities using a modelling approach. The authors present a new metacommunity model (the Unified Metacommunity Model) that includes habitat heterogeneity, dispersal, specialization, and species interactions. The authors use this model to illustrate two forms of context-dependency: directional and reciprocal context-dependency. They present several simulations that illustrate these two aspects. The authors also discussed the implications of their results for future research in metacommunity dynamics. I overall enjoyed reading this manuscript which I consider as an interesting contribution to the field of metacommunity ecology. I think that it has a clear structure and is well-written. The data, illustrations, and tables are of good quality. The cited literature is appropriate. Overall, the work and methods meet the expected scientific standards, but several precisions are needed to allow the replication of the study. The model created in this study presents interesting adaptations of existing concepts and is one of the main strength of this study. Another strength of this work is that it investigates a known weakness of metacommunity ecology (context-dependency) and ecology in general and discuss potential ways to tackle this problem. Overall, I think that the paper is of direct interest to scientists working in the field of metacommunity ecology and can be interesting for a broader audience in various fields of ecology including community assembly, biodiversity, and metapopulation. I did not identify major flaws, but I have a few suggestion for minor improvements. I think that addressing these concerns can further improve this work. See my comments below for further details.

    Section 1 – Serious concerns

    • Do you have any serious concerns about the manuscript such as fraud, plagiarism, unethical or unsafe practices? No

    • Have authors’ provided the necessary ethics approval (from authors’ institution or an ethics committee)? Yes

    Section 2 – Language quality

    • How would you rate the English language quality? High quality

    Section 3 – validity and reproducibility

    • Does the work cite relevant and sufficient literature? Yes
    • Is the study design appropriate and are the methods used valid? Yes
    • Are the methods documented and analysis provided so that the study can be replicated? No
    • Is the source data that underlies the result available so that the study can be replicated? not applicable
    • Is the statistical analysis and its interpretation appropriate? Yes
    • Is quality of the figures and tables satisfactory? Yes
    • Are the conclusions adequately supported by the results? Yes
    • Are there any objective errors or fundamental flaws that make the research invalid? Please describe these thoroughly. No

    Section 4 – Suggestions

    • Do you have any feedback or comments for the Author?

    Abstract:

    The use of abbreviation in the abstract is to me unnecessary and I encourage the authors to remove them (i.e. C-D). The mention of macro-variables got me confused. While it becomes clearer what those are later in the ms, I would suggest explicitly mentioning the four dimensions of the model (habitat heterogeneity, dispersal, specialization, and species interactions) in the abstract.

    Context-dependency in metacommunities:

    This section is nicely written. Please, consider providing a definition of directional and reciprocal context-dependency earlier in the text.

    Context-dependency in a model:

    This section clearly explains the functioning of the model and how it allows interactions among “macro-variables”. However, I would like to see more technical information because I don’t think that I would be able to replicate the same model with the information provided (either here or in the SupMat). I encourage the authors to add more detailed information about the functioning of the model (maybe as an additional document published at the same time as the models itself ...)

    Directional and reciprocal C-D:

    Nice section. I like the chosen examples for the two types of context-dependency.

    C-D in future metacommunity research:

    Also nicely written. Consider adding a few words about the implications of this work beyond the metacommunity framework.

    Fig. 3: Even with the explanation provided, I still struggle to understand the abbreviations (panels A-D).

    Fig. 4: Consider replacing the vector image by a raster image (png, jpeg...). While the quality is nice, it slows down the whole document.

    Fig. 4B: There is no legends for the R2 values (which values correspond to which line).

    Section 5 – Decision

    Verified with reservations: The content is scientifically sound, but has shortcomings that could be improved by further studies and/or minor revisions.

  4. PeerRef

    Peer review report

    Reviewer: Jinbao Liao Institution: Jiangxi Normal University. email: jinbaoliao@163.com

    Section 1 – Serious concerns

    • Do you have any serious concerns about the manuscript such as fraud, plagiarism, unethical or unsafe practices? No
    • Have authors’ provided the necessary ethics approval (from authors’ institution or an ethics committee)? not applicable

    Section 2 – Language quality

    • How would you rate the English language quality? Low to medium quality. I understand the content

    Section 3 – validity and reproducibility

    • Does the work cite relevant and sufficient literature? Yes
    • Is the study design appropriate and are the methods used valid? No
    • Are the methods documented and analysis provided so that the study can be replicated? No
    • Is the source data that underlies the result available so that the study can be replicated? Yes
    • Is the statistical analysis and its interpretation appropriate? Yes
    • Is quality of the figures and tables satisfactory? Yes
    • Are the conclusions adequately supported by the results? Yes
    • Are there any objective errors or fundamental flaws that make the research invalid? Please describe these thoroughly. No

    Section 4 – Suggestions

    • Do you have any feedback or comments for the Author?

    Three basic models are used to study complex systems: dynamical system modelling, agent-based model, and complex networks. Dynamical system modelling uses top-down modelling ideas (modelling with macroscopic variables; based on mean-field ideas). The agent-based model uses bottom-up modelling ideas (modelling with micro variables; based on individual simulation ideas). Complex networks lie between dynamical system modelling and agent-based model (each individual interacts with each other, and the interactions are linked into edges to form a complex network). The paper 'Metacommunity research can benefit from including context-dependency' uses the agent-based model framework (NetLogo).

    The agent-based model framework in this paper incorporates four dimensions: inter-habitat differences (heterogeneity), dispersal (dispersal rate on the probability of colonizing rather than general mobility), specialization (breadth of species response to collection of diverse habitats), species Interactions (competition, predation, mutualism, parasitism et al. mutualism, parasitism et al.), and these dimensions have been more or less extensively studied in the dynamical system framework and the complex network framework. Therefore, the authors should discuss in detail how agent-based model framework has advantages over the most common frameworks currently used for ecosystem modelling (dynamical systems, complex networks).

    For example, for the dynamical system framework, recent studies suggest incorporating six modules (such as species interactions, dispersal, demography, evolution, environment and physiology) into the model to predict biodiversity (Norberg et al., 2012, Nature Climate Change; Urban et al., 2016, Science). For the complex network framework, early theoretical studies explored the effects of multiple relationship types or dispersal on complex networks (Holland & Hastings, 2008, Nature; Mougi & Kondoh, 2012, Science; Allesina & Tang, 2012, Nature).

    Moreover, the idea of agent-based model is derived from the theory of complex adaptive systems (e.g., Kondoh, 2003, Science), and the core idea of this framework is that adaptability creates complexity. Many studies have focused on the evolution of dispersal strategies within single species (Cote et al., 2017, Ecography), while theoretical studies on the evolution of dispersal in meta-communities remain rare. For the dispersal dimension (a key dimension of this paper), do authors consider the evolution of dispersal strategies.

    Finally, after reading this ms, it is really unclear what the model is and how to simulate the model. Maybe you should describe it in details following the ODD protocol for describing individual-based models (Grimm et al. 2006).

    Section 5 – Decision

    Requires revisions: The manuscript contains objective errors that must be addressed

  5. Version published to 10.1101/2021.09.26.461405v1 on bioRxiv