@article{01JE8WPJYQFQRRVVB14WJAX1B3,
  abstract     = {{Interactions among plants are changing across the globe resulting from a multitude of changes in the environment. Obtaining accurate predictions of plant species' range dynamics requires us to account for plant-plant interactions, but this remains challenging using the existing species distribution modelling (SDM) techniques. Advanced SDM techniques facilitate the integration of plant species interactions based on species-to-species associations. However, for uncharted environmental conditions in which the formerly derived species' correlations potentially no longer hold, a more process-based alternative is expected to become increasingly relevant. We first review the most common SDM techniques that integrate plant-plant interactions and then present the concept for a novel map product: a spatial plant-plant interaction index (PII) depicting the link between a focal species' performance and the trait signature of the interacting vegetation. The latest developments in remote sensing and the increasing availability of vegetation plot data facilitate PII mapping based on vegetation trait-environment relationships. Synthesis: PII mapping holds the potential to advance next-generation biogeographical analyses as it can serve as a pivotal missing covariate layer necessary for the integration of plant-plant interactions into SDM applications. This data product adds flexibility to the ecologists' toolbox to analyse species range shifts and the formation of novel communities as a response to multiple environmental changes. Concept summary and flowchart of data to calculate a Plant-plant Interaction Index (PII) map Here, the PII is mapped for the forest herb Geum urbanum based on the realized impact of the competitive generalist herb Urtica dioica, while accounting for the effects of ambient plant interaction with other resident herb species. This PII map product may be integrated into SDMs to account for biotic interaction (competition) effects brought about by Urtica on the habitat suitability of Geum. Knowing the link between Geum performance and the percentage cover of Urtica, it is for instance possible to assess the impacts of changes in tree cover density on the percentage cover of Urtica, and how this affects the PII, to ultimately analyse to what extent these biotic changes propagate up to biogeographical range shifts of Geum. This way, PII mapping is a powerful and flexible tool that effectively leverages the strengths of both experimental research and correlative SDMs.image}},
  author       = {{Sanczuk, Pieter and Landuyt, Dries and De Lombaerde, Emiel and Lenoir, Jonathan and Lorer, Eline and Luoto, Miska and Van Meerbeek, Koenraad and Zellweger, Florian and De Frenne, Pieter}},
  issn         = {{0022-0477}},
  journal      = {{JOURNAL OF ECOLOGY}},
  keywords     = {{biogeography,competition,environmental change,experimental macroecology,plant-plant interactions,spatial model,species distribution model,vegetation survey,BIOTIC INTERACTIONS,DISTRIBUTION MODELS,CLIMATE-CHANGE,COMPETITIVE INTERACTIONS,FUNCTIONAL TRAITS,DISTRIBUTIONS,DRIVEN,ASSOCIATIONS,FACILITATION,METAANALYSIS}},
  language     = {{eng}},
  number       = {{12}},
  pages        = {{2698--2714}},
  title        = {{Embracing plant-plant interactions : rethinking predictions of species range shifts}},
  url          = {{http://doi.org/10.1111/1365-2745.14415}},
  volume       = {{112}},
  year         = {{2024}},
}

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