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Landscape connectivity explains interaction network patterns at multiple scales
Author(s) -
Santos Micaela,
Cagnolo Luciano,
Roslin Tomas,
Marrero Hugo J.,
Vázquez Diego P.
Publication year - 2019
Publication title -
ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.144
H-Index - 294
eISSN - 1939-9170
pISSN - 0012-9658
DOI - 10.1002/ecy.2883
Subject(s) - metacommunity , guild , species richness , ecology , landscape connectivity , similarity (geometry) , herbivore , beta diversity , spatial ecology , metric (unit) , habitat , geography , computer science , biology , population , artificial intelligence , biological dispersal , demography , sociology , image (mathematics) , operations management , economics
Under a metacommunity framework, the spatial configuration of habitat fragments could determine local community structure. Yet, quantifying fragment connectivity is challenging, as it depends on multiple variables at several geographical scales. We assessed the extent to which fragment connectivity and area explain patterns in interaction structure among four herbivore guilds and their host plants in a metacommunity. We propose an integrative connectivity metric including geographic distance, neighboring fragment area and similarity in resource composition as an extension of Hanski's classic metric. We then used nonlinear models to assess whether fragment connectivity and area predicted link richness and similarity in link composition. We found that link richness was always negatively related to connectivity but at different geographic scales depending on the herbivore guild. In contrast, while link composition was also related to connectivity, the direction and strength of this relationship varied among herbivore guilds and type of link composition (qualitative or quantitative). Furthermore, focal fragment area was not an important determinant of interaction diversity in local communities. Our findings emphasize resource similarity as a novel dimension of fragment connectivity relevant in explaining interaction diversity patterns in natural trophic networks.