Connecting targets for catchment sediment loads to ecological outcomes for seagrass using multiple lines of evidence. (August 2021)

• Record Type: Journal Article
• Authors: Lambert, Victoria; Bainbridge, Zoe T.; Collier, Catherine; Lewis, Stephen E.; Adams, Matthew P.; Carter, Alex; Saunders, Megan I.; Brodie, Jon; Turner, Ryan D.R.; Rasheed, Michael A.; O'Brien, Katherine R.
• Is Part Of: Marine pollution bulletin. Volume 169(2021)
• Publication Date: 2021-08
• Subjects: Ecologically relevant targets -- Seagrass -- Catchment sediment -- Marine ecosystems; Marine pollution -- Periodicals; Marine Biology -- Periodicals; Water Pollution -- Periodicals; Mer -- Pollution -- Périodiques; Publications périodiques; Pollution des mers; Lutte antipollution; Electronic journals; 363.7394
• DOI: 10.1016/j.marpolbul.2021.112494
• Languages: English
• ISSNs: 0025-326X

Abstract

Abstract: Catchment impacts on downstream ecosystems are difficult to quantify, but important for setting management targets. Here we compared 12 years of monitoring data of seagrass area and biomass in Cleveland Bay, northeast Australia, with discharge and associated sediment loads from nearby rivers. Seagrass biomass and area exhibited different trajectories in response to river inputs. River discharge was a slightly better predictor of seagrass indicators than total suspended solid (TSS) loads, indicating that catchment effects on seagrass are not restricted to sediment. Linear relationships between Burdekin River TSS loads delivered over 1–4 years and seagrass condition in Cleveland Bay generated Ecologically Relevant Targets (ERT) for catchment sediment inputs. Our predicted ERTs were comparable to those previously estimated using mechanistic models. This study highlights the challenges of linking catchment inputs to condition of downstream ecosystems, and the importance of integrating a variety of metrics and approaches to increase confidence in ERTs. Highlights: Ecologically relevant targets (ERTs) are important for environmental management. ERTs are difficult to quantify and can be controversial. Here seagrass data and catchment inputs were used to derive ERTs. Our empirical ERTs agreed with those previously derived from mechanistic models. Using multiple indicators and modelling approaches increases confidence in ERTs.