Using MODIS data for mapping of water types within river plumes in the Great Barrier Reef, Australia: Towards the production of river plume risk maps for reef and seagrass ecosystems

Petus, Caroline; Silva, Eduardo Teixeira da; Devlin, Michelle; Wenger, Amelia S.; Álvarez‐Romero, Jorge G.

doi:10.1016/j.jenvman.2013.11.050

Cited by 39 publications

(62 citation statements)

References 60 publications

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“…These results indicate that the SWIM algorithm tended to converge to a solution more often for LI than the other two regions. We hypothesize that this is either because: (i) the spectral IOP models within SWIM are well suited to this region, and/or (ii) the LI region is not subject to frequent river flood plume events for extended periods that disperse sediment plumes and/or highly attenuating water [Petus et al, 2014] that may cause product failure.…”

Section: Lizard Island Regionmentioning

confidence: 99%

A semianalytical ocean color inversion algorithm with explicit water column depth and substrate reflectance parameterization

et al. 2015

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A semianalytical ocean color inversion algorithm was developed for improving retrievals of inherent optical properties (IOPs) in optically shallow waters. In clear, geometrically shallow waters, light reflected off the seafloor can contribute to the water-leaving radiance signal. This can have a confounding effect on ocean color algorithms developed for optically deep waters, leading to an overestimation of IOPs. The algorithm described here, the Shallow Water Inversion Model (SWIM), uses pre-existing knowledge of bathymetry and benthic substrate brightness to account for optically shallow effects. SWIM was incorporated into the NASA Ocean Biology Processing Group's L2GEN code and tested in waters of the Great Barrier Reef, Australia, using the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua time series (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013). SWIM-derived values of the total non-water absorption coefficient at 443 nm, a t (443), the particulate backscattering coefficient at 443 nm, b bp (443), and the diffuse attenuation coefficient at 488 nm, K d (488), were compared with values derived using the Generalized Inherent Optical Properties algorithm (GIOP) and the Quasi-Analytical Algorithm (QAA). The results indicated that in clear, optically shallow waters SWIM-derived values of a t (443), b bp (443), and K d (443) were realistically lower than values derived using GIOP and QAA, in agreement with radiative transfer modeling. This signified that the benthic reflectance correction was performing as expected. However, in more optically complex waters, SWIM had difficulty converging to a solution, a likely consequence of internal IOP parameterizations. Whilst a comprehensive study of the SWIM algorithm's behavior was conducted, further work is needed to validate the algorithm using in situ data.

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Section: Lizard Island Regionmentioning

confidence: 99%

A semianalytical ocean color inversion algorithm with explicit water column depth and substrate reflectance parameterization

et al. 2015

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“…They represent a gradient from the inshore to the offshore boundaries of river plumes. Each plume water type is associated with characteristic optical properties, light levels and colours, as well as different concentrations and proportions of land-sourced contaminants (e.g., [11][12][13][14][15][16]). Table 1 gives examples of remote sensing monitoring products developed through the GBR Marine Monitoring Program (MMP) to improve our understanding of the relationships between coastal water quality in river plumes and its effects on marine ecosystems [15].…”

Section: Introductionmentioning

confidence: 99%

“…River plume maps have thus been used as an interpretative tool for understanding changes in seagrass meadow health [18] and, in a case study in Cleveland Bay (north Queensland), the decline in seagrass meadow area and cover was positively linked to a high occurrence of primary plume water masses mapped through Moderate Resolution Imaging Spectroradiometer (MODIS) imagery [19]. There is, however, a need to improve these remote sensing monitoring products and incorporate them into unique Risk Assessment Frameworks focusing on the GBR-wide scale and incorporating the potential of cumulative impacts from multiple contaminants in river plume waters [13,16]. The assessment of risk in this study is defined as "the methods by which the likely adverse effect of combined contaminants on ecosystems is estimated with a known degree of certainty using scientific methodology" [20].…”

Section: Introductionmentioning

confidence: 99%

“…C: River plume risk maps (In progress: [16], this study) Product aiming to evaluate the risk of GBR ecosystems from river plume exposure through the use of established risk management approaches (magnitudeˆlikelihood)…”

Section: Introductionmentioning

confidence: 99%

“…A simple risk framework has been recently proposed to generate maps of potential risk of seagrass and coral reef ecosystems in the GBR to river plumes using MODIS imagery ( [16], Table 1C and Figure 2). This framework (hereafter Satellite Risk Framework) was based on a "magnitudeˆlikelihood" approach that assumed there would be increased adverse biological responses from GBR seagrass and coral ecosystems if contaminant concentrations and frequency of exposure to river plumes were increased.…”

Section: Introductionmentioning

confidence: 99%

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Estimating the Exposure of Coral Reefs and Seagrass Meadows to Land-Sourced Contaminants in River Flood Plumes of the Great Barrier Reef: Validating a Simple Satellite Risk Framework with Environmental Data

et al. 2016

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River runoff and associated flood plumes (hereafter river plumes) are a major source of land-sourced contaminants to the marine environment, and are a significant threat to coastal and marine ecosystems worldwide. Remote sensing monitoring products have been developed to map the spatial extent, composition and frequency of occurrence of river plumes in the Great Barrier Reef (GBR), Australia. There is, however, a need to incorporate these monitoring products into Risk Assessment Frameworks as management decision tools. A simple Satellite Risk Framework has been recently proposed to generate maps of potential risk to seagrass and coral reef ecosystems in the GBR focusing on the Austral tropical wet season. This framework was based on a "magnitudeˆlikelihood" risk management approach and GBR plume water types mapped from satellite imagery. The GBR plume water types (so called "Primary" for the inshore plume waters, "Secondary" for the midshelf-plume waters and "Tertiary" for the offshore plume waters) represent distinct concentrations and combinations of land-sourced and marine contaminants. The current study aimed to test and refine the methods of the Satellite Risk Framework. It compared predicted pollutant concentrations in plume water types (multi-annual average from 2005-2014) to published ecological thresholds, and combined this information with similarly long-term measures of seagrass and coral ecosystem health. The Satellite Risk Framework and newly-introduced multi-annual risk scores were successful in demonstrating where water conditions were, on average, correlated to adverse biological responses. Seagrass meadow abundance (multi-annual change in % cover) was negatively correlated to the multi-annual risk score at the site level (R 2 = 0.47, p < 0.05). Relationships between multi-annual risk scores and multi-annual changes in proportional macroalgae cover (as an index for coral reef health) were more complex (R 2 = 0.04, p > 0.05), though reefs incurring higher risk scores showed relatively higher proportional macroalgae cover. Multi-annual risk score thresholds associated with loss of seagrass cover were defined, with lower risk scores (ď0.2) associated with a gain or little loss in seagrass cover (gain/´12%), medium risk scores (0.2-0.4) associated with moderate loss (´12/´30%) and higher risk scores (>0.4) with the greatest loss in cover (>´30%). These thresholds were used to generate an intermediate river plume risk map specifically for seagrass meadows of the GBR. An intermediate river plume risk map for coral reefs was also developed by considering a multi-annual risk score threshold of 0.2-above which a higher proportion of macroalgae within the algal communities can be expected. These findings contribute to a long-term and adaptive approach to set relevant risk framework and thresholds for adverse biological responses in the GBR. The ecological thresholds and risk scores used in this study will be refined and validated through ongoing monitoring and assessment. As uncertainties are red...

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Assessing the ability of adaptive designs to capture trends in hard coral cover

2023

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Coral reefs have become one of the most vulnerable ecosystems worldwide due to rising environmental and anthropogenic pressures. Methods from experimental design can be used to furnish our ability to monitor such ecosystems efficiently. Recently, adaptive design approaches have been proposed for monitoring coral reefs; however, questions have surfaced around the ability of such approaches to capture trends over time. The aim of this study was to develop an approach to assess trends in hard coral cover and evaluate the effectiveness of adaptive designs for estimating such trends in coral reef communities within a region of the Great Barrier Reef. Our approach was couched within a Bayesian design and inference framework such that uncertainty was captured rigorously and so that information from accumulating data can be incorporated straightforwardly to inform future data collection. The designs found under this approach were compared to historical non‐adaptive designs which surveyed all locations over time. Through this comparison, we show that adaptive designs can maintain trends over time with little to no loss in information, even when sampling effort is substantially reduced. Accordingly, this research serves to further promote adaptive design methods for efficiently and effectively sampling in ecological monitoring.

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Using MODIS data for mapping of water types within river plumes in the Great Barrier Reef, Australia: Towards the production of river plume risk maps for reef and seagrass ecosystems

Cited by 39 publications

References 60 publications

A semianalytical ocean color inversion algorithm with explicit water column depth and substrate reflectance parameterization

A semianalytical ocean color inversion algorithm with explicit water column depth and substrate reflectance parameterization

Estimating the Exposure of Coral Reefs and Seagrass Meadows to Land-Sourced Contaminants in River Flood Plumes of the Great Barrier Reef: Validating a Simple Satellite Risk Framework with Environmental Data

Assessing the ability of adaptive designs to capture trends in hard coral cover

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