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Metacommunity research can benefit from including context-dependency

Kolasa, J.; Hammond, M. P.; Yan, J.

2021-09-26 ecology
10.1101/2021.09.26.461405 bioRxiv
Show 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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