Identifying high risk seafloor areas to bottom trawling in Aotearoa New Zealand to support marine spatial management DOI Creative Commons

Benjamin Hall,

Matthew Bennion, Orlando Lam‐Gordillo

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 3, 2025

Abstract Seafloor species play important ecological roles within marine ecosystems, yet many are vulnerable to the impacts of bottom fishing. Despite known vulnerability seafloor taxa, destructive fishing remains prevalent in parts world given demand for wild-caught seafood. Species Distribution Models (SDMs) increasingly used estimate distribution taxa and possible risk interactions with gears, but most approaches have a limited number taxa. In this study, spatial predictions distributions 207 invertebrate New Zealand waters were combined comprehensive database functional traits related trawling predict areas high vulnerability. addition, estimates redundancy calculated combined, these elucidated ‘high risk’ that covered 182,087 km2 (9.5%) study area. The current Marine Management Areas (MMAs) highly fished zones revealed MMAs protect 50% (91,000 km2), less than 1% is areas. This leaves predicted 90,937 (49%) outside protection, some close potentially priority future management. Identifying showcases previously areas, as well highlighting management action. Using different sets approach could also be assess other anthropogenic impacts, improving ecosystem-based by ensuring protection functions at globally significant scales.

Language: Английский

Identifying high risk seafloor areas to bottom trawling in Aotearoa New Zealand to support marine spatial management DOI Creative Commons

Benjamin Hall,

Matthew Bennion, Orlando Lam‐Gordillo

et al.

Research Square (Research Square), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 3, 2025

Abstract Seafloor species play important ecological roles within marine ecosystems, yet many are vulnerable to the impacts of bottom fishing. Despite known vulnerability seafloor taxa, destructive fishing remains prevalent in parts world given demand for wild-caught seafood. Species Distribution Models (SDMs) increasingly used estimate distribution taxa and possible risk interactions with gears, but most approaches have a limited number taxa. In this study, spatial predictions distributions 207 invertebrate New Zealand waters were combined comprehensive database functional traits related trawling predict areas high vulnerability. addition, estimates redundancy calculated combined, these elucidated ‘high risk’ that covered 182,087 km2 (9.5%) study area. The current Marine Management Areas (MMAs) highly fished zones revealed MMAs protect 50% (91,000 km2), less than 1% is areas. This leaves predicted 90,937 (49%) outside protection, some close potentially priority future management. Identifying showcases previously areas, as well highlighting management action. Using different sets approach could also be assess other anthropogenic impacts, improving ecosystem-based by ensuring protection functions at globally significant scales.

Language: Английский

Citations

0