TY - UNPB
T1 - Detecting the most effective cleanup locations using network theory to reduce marine plastic debris: A case study in the Galapagos Marine Reserve
AU - Ypma, Stefanie Leonore
AU - Bohte, Quinten
AU - Forryan, Alexander
AU - Garabato, Alberto C. Naveira
AU - Donnelly, Andy
AU - Sebille, Erik van
PY - 2022/6/16
Y1 - 2022/6/16
N2 - The Galapagos Marine Reserve was established in 1986 to ensure protection of the islands' unique biodiversity. Unfortunately, the islands are polluted by marine plastic debris and the island authorities face the challenge to effectively remove plastic from its shorelines due to limited resources. To optimise efforts, we have identified the most effective cleanup locations on the Galapagos Islands using network theory. A network is constructed from a Lagrangian simulation describing the flow of macroplastic between the various islands within the Galapagos Marine Reserve, where the nodes represent locations along the coastline and the edges the likelihood for plastic to travel from one location and beach at another. We have found four network centralities that provide the best coastline ranking to optimise the cleanup effort based on various impact metrics. In particular locations with a high retention rate are favourable for cleanup. The results indicate that using the most effective centrality for finding cleanup locations is a good strategy for heavily polluted regions if the distribution of marine plastic debris on the coastlines is unknown and limited cleanup resources are available.
AB - The Galapagos Marine Reserve was established in 1986 to ensure protection of the islands' unique biodiversity. Unfortunately, the islands are polluted by marine plastic debris and the island authorities face the challenge to effectively remove plastic from its shorelines due to limited resources. To optimise efforts, we have identified the most effective cleanup locations on the Galapagos Islands using network theory. A network is constructed from a Lagrangian simulation describing the flow of macroplastic between the various islands within the Galapagos Marine Reserve, where the nodes represent locations along the coastline and the edges the likelihood for plastic to travel from one location and beach at another. We have found four network centralities that provide the best coastline ranking to optimise the cleanup effort based on various impact metrics. In particular locations with a high retention rate are favourable for cleanup. The results indicate that using the most effective centrality for finding cleanup locations is a good strategy for heavily polluted regions if the distribution of marine plastic debris on the coastlines is unknown and limited cleanup resources are available.
U2 - 10.5194/egusphere-2022-426
DO - 10.5194/egusphere-2022-426
M3 - Preprint
SP - 1
EP - 22
BT - Detecting the most effective cleanup locations using network theory to reduce marine plastic debris: A case study in the Galapagos Marine Reserve
PB - EGU
ER -