Ambitious global targets for mangrove and seagrass recovery

Buelow, Christina; Connolly, Rod M.; Turschwell, Mischa P.; Adame, Maria Fernanda; Ahmadia, Gabby N.; Andradi-Brown, Dominic A.; Bunting, Peter; Canty, Steven W. J.; Dunic, Jillian C.; Friess, Daniel A.; Lee, Joe; Lovelock, Catherine E.; McClure, Eva C.; Pearson, Ryan M.; Sievers, Michael; Sousa, Ana I.; Worthington, Thomas A.; Brown, Christopher J.

doi:10.1016/j.cub.2022.02.013

Cited by 33 publications

(20 citation statements)

References 59 publications

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“…Achieving ambitious conservation and restoration targets for seagrasses and other habitat-forming macrophytes will require the rapid identification of suitable habitat at a spatial scale and resolution relevant for regional decision-makers and restoration projects. Aggressive protection is necessary, but is likely not sufficient to ensure global recovery of seagrass ecosystems (Buelow et al, 2022). Recovery of seagrass ecosystems will require a portfolio of target conservation and restoration work.…”

Section: Discussionmentioning

confidence: 99%

“…Economic value of services provided by seagrasses, kelp beds, and mangroves, such as coastal protection, nutrient cycling, fisheries production, recreational opportunities, and carbon sequestration, range from $100s − $100,000s USD ha -1 yr -1 (Barbier et al, 2011;Dewsbury et al, 2016;Himes-Cornell et al, 2018;Eger et al, 2021). Consequently, there is strong motivation behind ambitious calls for habitat protection and restoration (van Katwijk et al, 2016;Eger et al, 2020;Buelow et al, 2022). These strong ecological and economic rationales for protection, however, are juxtaposed with a lack of fine-scale data on the distribution and extent of these important ecosystems at regional scales, which hinders the application and success of conservation planning and targeted habitat rehabilitation programs.…”

Section: Introductionmentioning

confidence: 99%

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Fine-scale ensemble species distribution modeling of eelgrass (Zostera marina) to inform nearshore conservation planning and habitat management

O’Brien

Wong²,

Stanley³

2022

Front. Mar. Sci.

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Baseline data on the distribution and extent of biogenic habitat-forming species at a high spatial resolution are essential to inform habitat management strategies, preserve ecosystem integrity, and achieve effective conservation objectives in the nearshore. Model-based approaches to map suitable habitat for these species are a key tool to address this need, filling in gaps where observations are otherwise unavailable and remote sensing methods are limited by turbid waters or cannot be applied at scale. We developed a high resolution (35 m) ensemble species distribution model to predict the distribution of eelgrass (Zostera marina) along the Atlantic coast of Nova Scotia, Canada where the observational coverage of eelgrass occurrence is sparse and nearshore waters are optically complex. Our ensemble model was derived as a performance-weighted average prediction of 7 different modeling methods fit to 6 physical predictors (substrate type, depth, wave exposure, slope, and two bathymetric position indices) and evaluated with a 5-fold spatially-blocked cross-validation procedure. The ensemble model showed moderate predictive performance (Area Under the Receiver-Operating Characteristic Curve (AUC) = 0.803 ± 0.061, True Skill Statistic (TSS) = 0.531 ± 0.100; mean ± SD), high sensitivity (92.0 ± 4.5), and offered some improvement over individual models. Substrate type, depth, and relative wave exposure were the most influential predictors associated with eelgrass occurrence, where the highest probabilities were associated with sandy and sandy-mud sediments, depths ranging 0 m – 4 m, and low to intermediate wave exposure. Within our study region, we predicted a total extent of suitable eelgrass habitat of 38,130 ha. We found suitable habitat was particularly extensive within the long narrow inlets and extensive shallow flats of the South Shore, Eastern Shore, and Bras d’Or Lakes. We also identified substantial overlap of eelgrass habitat with previously identified Ecologically and Biologically Significant Areas that guide regional conservation planning while also highlighting areas of greater prediction uncertainty arising from disagreement among modeling methods. By offering improved sensitivity and insights into the fine-scale regional distribution of a habitat-forming species with associated uncertainties, our ensemble-based modeling approach provides improved support to numerous nearshore applications including conservation planning and restoration, marine spatial and emergency response planning, environmental impact assessments, and fish habitat protection.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Fine-scale ensemble species distribution modeling of eelgrass (Zostera marina) to inform nearshore conservation planning and habitat management

O’Brien

Wong²,

Stanley³

2022

Front. Mar. Sci.

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“…Gains in mangrove extent provide the opposite by supporting carbon accumulation and storage, attracting flora and fauna and protecting coastlines against storm impacts and erosion. Protection of mangroves is critical, while the restoration of mangroves has been demonstrated to provide significant ecosystem services benefits over short time periods [4] and is important for reversing at least some of the recent declines in mangrove extent [11].…”

Section: Introductionmentioning

confidence: 99%

Global Mangrove Extent Change 1996–2020: Global Mangrove Watch Version 3.0

Rosenqvist²,

et al. 2022

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Mangroves are a globally important ecosystem that provides a wide range of ecosystem system services, such as carbon capture and storage, coastal protection and fisheries enhancement. Mangroves have significantly reduced in global extent over the last 50 years, primarily as a result of deforestation caused by the expansion of agriculture and aquaculture in coastal environments. However, a limited number of studies have attempted to estimate changes in global mangrove extent, particularly into the 1990s, despite much of the loss in mangrove extent occurring pre-2000. This study has used L-band Synthetic Aperture Radar (SAR) global mosaic datasets from the Japan Aerospace Exploration Agency (JAXA) for 11 epochs from 1996 to 2020 to develop a long-term time-series of global mangrove extent and change. The study used a map-to-image approach to change detection where the baseline map (GMW v2.5) was updated using thresholding and a contextual mangrove change mask. This approach was applied between all image-date pairs producing 10 maps for each epoch, which were summarised to produce the global mangrove time-series. The resulting mangrove extent maps had an estimated accuracy of 87.4% (95th conf. int.: 86.2–88.6%), although the accuracies of the individual gain and loss change classes were lower at 58.1% (52.4–63.9%) and 60.6% (56.1–64.8%), respectively. Sources of error included misregistration in the SAR mosaic datasets, which could only be partially corrected for, but also confusion in fragmented areas of mangroves, such as around aquaculture ponds. Overall, 152,604 km2 (133,996–176,910) of mangroves were identified for 1996, with this decreasing by −5245 km2 (−13,587–1444) resulting in a total extent of 147,359 km2 (127,925–168,895) in 2020, and representing an estimated loss of 3.4% over the 24-year time period. The Global Mangrove Watch Version 3.0 represents the most comprehensive record of global mangrove change achieved to date and is expected to support a wide range of activities, including the ongoing monitoring of the global coastal environment, defining and assessments of progress toward conservation targets, protected area planning and risk assessments of mangrove ecosystems worldwide.

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“…Targets for restoration influence government and institutional policies and activities [ 11 ]. There are numerous international targets for restoration relevant to mangroves and other coastal wetlands.…”

Section: Introductionmentioning

confidence: 99%

“…If achieved, this would reach approximately half of the Aichi Target 15 of restoring 15% of mangrove area and would be on a trajectory of approximately 1% increase in global mangrove area per year. Recent modelling analyses indicate that this level of restoration is likely achievable by 2050 [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Tackling the mangrove restoration challenge

Lovelock

Barbier²,

Duarte³

2022

PLoS Biol

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Mangroves have been converted and degraded for decades. Rates of loss have declined over the past decades, but achieving resilient coastlines requires both conservation and restoration. Here, we outline the challenges for the global restoration of mangroves and what actions could enhance restoration. Ambitious global targets for mangrove restoration, if successful, could deliver global benefits of carbon sequestration, fisheries production, biodiversity, and coastal protection. However, large-scale mangrove planting efforts have often failed, and smaller projects may not deliver landscape-scale benefits, even though they are more suited to community management. Solutions to achieving global targets include reducing risks of large projects and increasing the uptake and effectiveness of smaller projects. Sustainable mangrove restoration requires investment in capacity building in communities and institutions, and mechanisms to match restoration opportunities with prospective supporters and investors. Global reporting standards will support adaptive management and help fully understand and monitor the benefits of mangrove restoration.

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Ambitious global targets for mangrove and seagrass recovery

Cited by 33 publications

References 59 publications

Fine-scale ensemble species distribution modeling of eelgrass (Zostera marina) to inform nearshore conservation planning and habitat management

Fine-scale ensemble species distribution modeling of eelgrass (Zostera marina) to inform nearshore conservation planning and habitat management

Global Mangrove Extent Change 1996–2020: Global Mangrove Watch Version 3.0

Tackling the mangrove restoration challenge

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