Spatially explicit predictions of food web structure from regional-level data.
Philos Trans R Soc Lond B Biol Sci
; 379(1909): 20230166, 2024 Sep 09.
Article
en En
| MEDLINE
| ID: mdl-39034704
ABSTRACT
Knowledge about how ecological networks vary across global scales is currently limited given the complexity of acquiring repeated spatial data for species interactions. Yet, recent developments in metawebs highlight efficient ways to first document possible interactions within regional species pools. Downscaling metawebs towards local network predictions is a promising approach to using the current data to investigate the variation of networks across space. However, issues remain in how to represent the spatial variability and uncertainty of species interactions, especially for large-scale food webs. Here, we present a probabilistic framework to downscale a metaweb based on the Canadian mammal metaweb and species occurrences from global databases. We investigated how our approach can be used to represent the variability of networks and communities between ecoregions in Canada. Species richness and interactions followed a similar latitudinal gradient across ecoregions but simultaneously identified contrasting diversity hotspots. Network motifs revealed additional areas of variation in network structure compared with species richness and number of links. Our method offers the potential to bring global predictions down to a more actionable local scale, and increases the diversity of ecological networks that can be projected in space. This article is part of the theme issue 'Connected interactions enriching food web research by spatial and social interactions'.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Cadena Alimentaria
/
Biodiversidad
Límite:
Animals
País/Región como asunto:
America do norte
Idioma:
En
Revista:
Philos Trans R Soc Lond B Biol Sci
Año:
2024
Tipo del documento:
Article
País de afiliación:
Canadá
Pais de publicación:
Reino Unido