Wed, Aug 17, 2022: 2:00 PM-2:15 PM
515A
Background/Question/MethodsSelf-organized formation of spatial patterns is an intriguing process that has been observed and theoretically analyzed in a variety of different ecosystems, ranging from vegetation patterns in arid, savanna, or wetland systems to host-parasitoid systems. Although ecologists have been fascinated by this for decades, there is still surprisingly little known about how self-organized pattern formation affects key ecosystem properties such as biodiversity. In the presented work, we study a general ecosystem model where a diverse community of autotroph species consumes an abiotic nutrient and is exploited by a herbivore. The functional diversity of the autotrophs is modeled as the variance of a continuous distribution of a trait that affects both growth of the autotrophs and defense against the herbivore. A network of habitat patches, each hosting such a food web, is interconnected via dispersal, thereby forming a metacommunity on the regional scale. The basic mechanism by which the interplay of spatial interactions and local biomass and trait dynamics affects functional diversity is first studied in small metacommunities with an idealized spatial structure and subsequently extended to the ecologically more relevant case of complex spatial networks with a large number of habitat patches.
Results/ConclusionsOn isolated patches, diversity is always lost over time due to stabilizing selection, and the local communities settle on one of two alternative stable states that are characterized by a dominance of either defended or undefended species. In a metacommunity context, dispersal of the species and diffusion of the abiotic nutrients can destabilize these states, which leads to the emergence of complex spatio-temporal patterns in the species’ abundances and the nutrient concentrations. The associated spatial and temporal variation in resource availability and consumption pressure creates biomass-trait feedbacks that enhance the mean local functional diversity of the autotrophs by up to a factor of ten compared to scenarios without self-organized pattern formation. This establishes a novel mechanism for supporting (functional) diversity, which helps to maintain the ability of communities to adapt to potential future changes in biotic or abiotic environmental conditions. We further demonstrate that in large, complex networks of habitat patches a straight-forward mathematical analysis of the spatial network reveals which patches will be affected most by the self-organized pattern formation and that increasing connectance of the patch network can have both positive and negative effects on the level of maintained functional diversity.
Results/ConclusionsOn isolated patches, diversity is always lost over time due to stabilizing selection, and the local communities settle on one of two alternative stable states that are characterized by a dominance of either defended or undefended species. In a metacommunity context, dispersal of the species and diffusion of the abiotic nutrients can destabilize these states, which leads to the emergence of complex spatio-temporal patterns in the species’ abundances and the nutrient concentrations. The associated spatial and temporal variation in resource availability and consumption pressure creates biomass-trait feedbacks that enhance the mean local functional diversity of the autotrophs by up to a factor of ten compared to scenarios without self-organized pattern formation. This establishes a novel mechanism for supporting (functional) diversity, which helps to maintain the ability of communities to adapt to potential future changes in biotic or abiotic environmental conditions. We further demonstrate that in large, complex networks of habitat patches a straight-forward mathematical analysis of the spatial network reveals which patches will be affected most by the self-organized pattern formation and that increasing connectance of the patch network can have both positive and negative effects on the level of maintained functional diversity.