Harnessing self-facilitation among ecosystem engineers for coastal ecosystem restoration

Activiteit: Academic presentationAcademic

Description

Ecosystem engineers – organisms that strongly modify their environment – are vital for the formation and stability of coastal landscapes. Clear examples are habitat-forming vegetation (e.g., seagrasses, salt marsh plants, dune grasses, mangroves) and reef-building organisms (e.g., corals, oysters, mussels) that attenuate wind or water flow, trap airborne or water-suspended particles, stabilize the sediment, and provide stable, spatially complex substrate. Over the last century, however, ecosystem engineers and the habitats they form have experienced massive human-induced declines. Although restoration is increasingly considered a vital tool to halt and reverse this coastal ecosystem degradation, its success is very limited (often less than 30%) and very costly compared to terrestrial restoration actions. Recent scientific advancements, however, demonstrate that by modifying transplants designs of habitat-forming engineering species from dispersed to clumped can amplify coastal restoration yields as it generates self-facilitation from emergent traits. These traits are not expressed by individuals or small clones, but emerge in clumped individuals or large clones. Moreover, follow-up studies show that by temporarily mimicking emergent traits such as sediment stabilization by dense root mats or flow attenuation by plant canopies or reef patches using crude biodegradable mimics, can ‘jump-start’ engineering species while using no or little donor material. Current work focuses on development of refined species-specific emergent trait-based mimics using industrial design-based conceptual approaches combined with 3D-printing techniques.
Periode20-sep.-2022
EvenementstitelNetherlands Annual Ecology Meeting 2022
EvenementstypeConference
Conferentienummer15
Organisator Netherlands Ecological Research Network (NERN)
LocatieLunteren, NetherlandsToon op kaart
Mate van erkenningNational