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Topic Editors

Department of Life Sciences, University of Trieste, Via L. Giorgieri, 4, 34127 Trieste, Italy
Dr. Cristiana Guerranti
Department of Life Science, University of Trieste, Via L. Giorgieri, 10, 34127 Trieste, Italy
Dr. Manuela Piccardo
Department of Life Sciences, University of Trieste, Via L. Giorgieri, 10, 34127 Trieste, Italy

Conservation and Management of Marine Ecosystems

Abstract submission deadline
closed (31 August 2024)
Manuscript submission deadline
closed (31 October 2024)
Viewed by
25691

Topic Information

Dear Colleagues,

Marine ecosystems are the largest of Earth's aquatic ecosystems and exist in waters that have a high salt content. These systems contrast with freshwater ecosystems, which have a lower salt content. The conservation and management of marine ecosystems are very important. Marine ecosystem conservation is all about the protection and preservation of seas and oceans, which is known as conservation of marine resources. It focuses on restricting the damages caused by humans to marine ecosystems. Restoring damaged marine resources plays a vital role in marine ecosystem conservation. Marine ecosystem management seeks to manage marine resources in ways that protect ecosystem health while providing the ecosystem services needed by people.

Papers focusing on these aspects of conservation and management of marine ecosystems are welcome.

Prof. Dr. Monia Renzi
Dr. Cristiana Guerranti
Dr. Manuela Piccardo
Topic Editors

Keywords

  • marine ecosystems
  • environmental levels
  • ocean conservation
  • conservation
  • management

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Journal of Marine Science and Engineering
jmse
2.7 4.4 2013 16.9 Days CHF 2600
Oceans
oceans
1.5 3.1 2020 32.2 Days CHF 1600
Remote Sensing
remotesensing
4.2 8.3 2009 24.7 Days CHF 2700
Sustainability
sustainability
3.3 6.8 2009 20 Days CHF 2400
Water
water
3.0 5.8 2009 16.5 Days CHF 2600

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Published Papers (14 papers)

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14 pages, 1754 KiB  
Article
Ecosystem Structure and Function in the Sea Area of Zhongjieshan Islands Based on Ecopath Model
by Yao Qu, Zhongming Wang, Yongdong Zhou, Jun Liang, Kaida Xu, Yazhou Zhang, Zhenhua Li, Qian Dai, Qiuhong Zhang and Yongsheng Jiang
J. Mar. Sci. Eng. 2024, 12(11), 2086; https://doi.org/10.3390/jmse12112086 - 18 Nov 2024
Abstract
Based on the field survey and reference data of the sea area of the Zhongjieshan Islands from 2021 to 2022, the Ecopath model was used to analyze the energy flow structure of the marine ecosystem of the sea area of the Zhongjieshan Islands; [...] Read more.
Based on the field survey and reference data of the sea area of the Zhongjieshan Islands from 2021 to 2022, the Ecopath model was used to analyze the energy flow structure of the marine ecosystem of the sea area of the Zhongjieshan Islands; the energy structure of the marine ecosystem was divided into 21 functional groups, and its nutrient structure, energy flow, and total system characteristics were analyzed. The results show that the credibility of the model is 0.414, which is at a medium level. The trophic level of each functional group of the ecosystem in the sea area of Zhongjieshan Islands was 1–3.48, the energy flow structure of the system was mainly concentrated in the first five grades, and the trophic level was relatively simple, with the average energy transfer efficiency of the system being 8.11%, the energy flow range being 2.81–13.04%, the energy transfer efficiency of the primary producers of the system being 7.25%, and the energy conversion efficiency of the system debris being 9.12%. The total system throughput was 2125.96 t·km−2; The analysis of the overall characteristics of the ecosystem showed that the system connectance index and the system omnivory index were 0.45 and 0.24, respectively, while the Finn’s cycling index was 8.24, the Finn’s mean path length of the system was 2.72, and the total primary production/total respiration was 1.71. In this study, the marine ecosystem model of the sea area of the Zhongjieshan Islands was studied to understand the trophic structure and ecosystem status of the sea area, which is conducive to the sustainable utilization and scientific management of fishery resources in the sea area. Full article
(This article belongs to the Topic Conservation and Management of Marine Ecosystems)
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Figure 1
<p>Station diagram of surveys in sea area of Zhongjieshan Islands. Notes: Stations H1–H10 are in the Special Marine Protected Area of the Zhongjieshan Islands. Stations W1–W8 are in the outer waters of the protected area.</p>
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<p>PREBAL pre-test trend chart of the sea area of the Zhongjieshan Islands.</p>
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<p>Energy flow between trophic levels of the marine ecosystem in the sea area of Zhongjieshan Islands. P: Primary producer; D: Detritus; TL: Trophic level; TST: Ratio of each integrated nutrient level to the tolal system flow; TE: Transfer efficiency.</p>
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<p>Ecopath flow diagram in the sea area of Zhongjieshan Islands.</p>
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<p>Mixed trophic impact analysis of functional groups in the Ecopath model of the ecosystem in the sea area of Zhongjieshan Islands.</p>
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16 pages, 10303 KiB  
Article
Deep Learning-Based Automatic Estimation of Live Coral Cover from Underwater Video for Coral Reef Health Monitoring
by Zechen Li, Shuqi Zhao, Yuxian Lu, Cheng Song, Rongyong Huang and Kefu Yu
J. Mar. Sci. Eng. 2024, 12(11), 1980; https://doi.org/10.3390/jmse12111980 - 2 Nov 2024
Viewed by 624
Abstract
Coral reefs are vital to marine biodiversity but are increasingly threatened by global climate change and human activities, leading to significant declines in live coral cover (LCC). Monitoring LCC is crucial for assessing the health of coral reef ecosystems and understanding their degradation [...] Read more.
Coral reefs are vital to marine biodiversity but are increasingly threatened by global climate change and human activities, leading to significant declines in live coral cover (LCC). Monitoring LCC is crucial for assessing the health of coral reef ecosystems and understanding their degradation and recovery. Traditional methods for estimating LCC, such as the manual interpretation of underwater survey videos, are labor-intensive and time-consuming, limiting their scalability for large-scale ecological monitoring. To overcome these challenges, this study introduces an innovative deep learning-based approach that utilizes semantic segmentation to automatically interpret LCC from underwater videos. That is, we enhanced PSPNet for live coral segmentation by incorporating channel and spatial attention mechanisms, along with pixel shuffle modules. Experimental results demonstrated that the proposed model achieved a mean Intersection over Union (mIoU) of 89.51% and a mean Pixel Accuracy (mPA) of 94.47%, showcasing superior accuracy in estimating LCC compared to traditional methods. Moreover, comparisons indicated that the proposed model aligns more closely with manual interpretations than other models, with an mean absolute error of 4.17%, compared to 5.89% for the original PSPNet, 6.03% for Deeplab v3+, 7.12% for U-Net, and 6.45% for HRNet, suggesting higher precision in LCC estimation. By automating the estimation of LCC, this deep learning-based approach can greatly enhance efficiency, thereby contributing significantly to global conservation efforts by enabling more scalable and efficient monitoring and management of coral reef ecosystems. Full article
(This article belongs to the Topic Conservation and Management of Marine Ecosystems)
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Figure 1
<p>Labeling of coral datasets. The coral species include (<b>a</b>). <span class="html-italic">Symphyllia nobilis</span>, (<b>b</b>). <span class="html-italic">Pavona decussata</span>, (<b>c</b>). <span class="html-italic">Pavona duerdeni</span>, (<b>d</b>). <span class="html-italic">Stylophora pistillata</span>, (<b>e</b>). <span class="html-italic">Montipora cactus</span> Bernard, (<b>f</b>). <span class="html-italic">Goniastrea aspera</span>, (<b>g</b>). <span class="html-italic">Acropora austera</span>, and (<b>h</b>). <span class="html-italic">Montipora foliosa</span>.</p>
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<p>Two images with different Laplacian variances: (<b>a</b>) showing a Laplacian variance of 95.29; (<b>b</b>) showing a Laplacian variance of 328.61.</p>
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<p>(<b>a</b>–<b>l</b>) are key frame images taken from the transect at distances between 3 and 90 m.</p>
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<p>The flow chart of coral image segmentation method.</p>
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<p>Architecture of ours: the Convolutional Block Attention Module.</p>
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<p>Pixel Shuffle diagram illustration.</p>
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<p>The images in panels (<b>a</b>–<b>d</b>) represent the transect survey, while the corresponding masks in panels (<b>e</b>–<b>h</b>) highlight the coral count and detected coral regions. The green box represents the coral.</p>
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<p>The P (PSPNet), D (Deeplab v3+), U (U-Net), H (HRNet), and O (Ours) models represent the interpretation results of coral images, respectively.</p>
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<p>Absolute error for different models.</p>
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<p>Live coral cover interpretation results from different models.</p>
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15 pages, 1835 KiB  
Article
Inventory of Shallow-Water Fouling Invertebrates of Long Island, New York
by Ezra Roesch, Jack H. Rosencrans, Kent A. Hatch and Robert W. Thacker
Oceans 2024, 5(4), 825-839; https://doi.org/10.3390/oceans5040047 - 1 Nov 2024
Viewed by 722
Abstract
Invasive marine invertebrates are increasingly recognized as a potential disturbance to coastal ecosystems. We sought to better document the taxonomic composition of subtidal communities around Long Island to obtain a baseline that can be used to monitor current and future invasions of non-indigenous [...] Read more.
Invasive marine invertebrates are increasingly recognized as a potential disturbance to coastal ecosystems. We sought to better document the taxonomic composition of subtidal communities around Long Island to obtain a baseline that can be used to monitor current and future invasions of non-indigenous species. We placed settlement blocks at 18 sites along the coast of Long Island, New York, for three months. After recovering blocks at 12 sites, we analyzed the taxonomic composition of fouling communities on the blocks. We observed 64 invertebrate and 3 algal taxa, with large variation in taxon richness among sites. Multivariate analyses revealed that although taxon composition was significantly dissimilar between north and south shores, variation in dissimilarity did not differ significantly between shores. The high variability in taxon composition observed among sites indicates that additional research is needed to expand our knowledge of invertebrate diversity in the waters surrounding Long Island. Adding more sites and replicate blocks within sites could improve future sampling designs. This research will benefit continuing efforts to monitor, manage, and prevent the establishment of marine invasive species. Full article
(This article belongs to the Topic Conservation and Management of Marine Ecosystems)
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<p>Sites where settlement blocks were placed. Closed circles indicate sites where no settlement plates were collected either because the plates or the entire block were lost. Open circles represent sites where at least one settlement plate was collected. Site names are as follows: A = Kings Point; B = Silver Point; C = East Island; D = Point Lookout; E = Lloyd Harbor; F = Sore Thumb, Gilgo State Park; G = Crane Neck; H = Smith Point; I = Wildwood; J = Cupsogue Beach; K = Reeves Beach; L = Shinnecock Inlet; M = Bailie Beach; N = W. Scott Cameron Beach; O = Horton Point; P = Hog Creek Point; Q = Orient Point; R = Montauk Point. GPS coordinates for each location are provided in <a href="#oceans-05-00047-t001" class="html-table">Table 1</a>.</p>
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<p>Diagram of cement block and Petri dish settlement plates. Blocks were placed at subtidal depths such that the settlement plates remained submerged throughout the tidal cycle.</p>
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<p>The median number of taxa found per settlement plate at each location. Bold lines indicate the median values, while boxes delimit the second and third quartiles, and lines indicate the maximum and minimum values. Locations with a single bar indicate that only one plate could be analyzed at that location.</p>
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<p>The median number of taxa found per site on north and south shores of Long Island. Bold lines indicate the median values among sites, while boxes delimit the second and third quartiles, and lines indicate the maximum and minimum values.</p>
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<p>Rarefaction curves describing the accumulation of unique taxa across sites on the north (dark gray) and south (light gray) shores of Long Island, as well as on both shores combined (black).</p>
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<p>Non-metric multidimensional scaling plot comparing each settlement plate’s taxonomic dissimilarity as measured by the Jaccard index (stress = 0.198, non-metric fit <span class="html-italic">R</span><sup>2</sup> = 0.97). Open circles represent sites on the north shore of Long Island, while filled circles represent sites on the south shore. Plate angle is not indicated since it was not found to be a significant factor (<span class="html-italic">p</span> = 0.804).</p>
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<p>Number of cryptogenic, indigenous, non-indigenous, and unresolved taxa at each location. The relative abundances of these categories were not significantly different among locations (chi-square = 19.12, df = 33, <span class="html-italic">p</span> = 0.974).</p>
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13 pages, 7781 KiB  
Article
Operational Mapping of Submarine Groundwater Discharge into Coral Reefs: Application to West Hawai‘i Island
by Gregory P. Asner, Nicholas R. Vaughn and Joseph Heckler
Oceans 2024, 5(3), 547-559; https://doi.org/10.3390/oceans5030031 - 5 Aug 2024
Viewed by 1282
Abstract
Submarine groundwater discharge (SGD) is a recognized contributor to the hydrological and biogeochemical functioning of coral reef ecosystems located along coastlines. However, the distribution, size, and thermal properties of SGD remain poorly understood at most land–reef margins. We developed, deployed, and demonstrated an [...] Read more.
Submarine groundwater discharge (SGD) is a recognized contributor to the hydrological and biogeochemical functioning of coral reef ecosystems located along coastlines. However, the distribution, size, and thermal properties of SGD remain poorly understood at most land–reef margins. We developed, deployed, and demonstrated an operational method for airborne detection and mapping of SGD using the 200 km coastline of western Hawai‘i Island as a testing and analysis environment. Airborne high spatial resolution (1 m) thermal imaging produced relative sea surface temperature (SST) maps that aligned geospatially with boat-based transects of SGD presence–absence. Boat-based SST anomaly measurements were highly correlated with airborne SST anomaly measurements (R2 = 0.85; RMSE = 0.04 °C). Resulting maps of the relative difference in SST inside and outside of SGD plumes, called delta-SST, revealed 749 SGD plumes in 200 km of coastline, with nearly half of the SGD plumes smaller than 0.1 ha in size. Only 9% of SGD plumes were ≥1 ha in size, and just 1% were larger than 10 ha. Our findings indicate that small SGD is omnipresent in the nearshore environment. Furthermore, we found that the infrequent, large SGD plumes (>10 ha) displayed the weakest delta-SST values, suggesting that large discharge plumes are not likely to provide cooling refugia to warming coral reefs. Our operational approach can be applied frequently over time to generate SGD information relative to terrestrial substrate, topography, and pollutants. This operational approach will yield new insights into the role that land-to-reef interactions have on the composition and condition of coral reefs along coastlines. Full article
(This article belongs to the Topic Conservation and Management of Marine Ecosystems)
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<p>Map of the west Hawai‘i Island study area. The eight flight coverage regions along the mapped coastline are shown in different colors. Inset shows the location of Hawai‘i Island west of the continental United States. Red box in upper right corner indicates locations of Hawai‘i Island globally. White arrow indicates true north.</p>
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<p>Example image mosaics of sea surface temperature (<b>a</b>) before and (<b>b</b>) after flight line temperature offset computations for improved blending of flight line temperatures. Background imagery provided by Google Earth™. White arrow indicates true north.</p>
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<p>Demonstration of the standardizing effect of conversion from raw surface temperature maps (<b>a</b>) to relative temperature maps (<b>b</b>). The latter were used to visually outline SGD plumes across the state. Background imagery provided by Google Earth™. White arrow indicates true north.</p>
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<p>Distribution of field validation sites (<span class="html-italic">n</span> = 52) at (<b>a</b>) region, (<b>b</b>) cluster, and (<b>c</b>) SGD plume scales. Panel (<b>c</b>) also shows seven of the mapped SGD plumes in red, with boat-based transects shown as sequential dots. Values in panel (<b>a</b>) indicate number of SGD plumes in each sub-region.</p>
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<p>Spatial density of submarine groundwater discharge (SGD) sites along the west Hawai‘i Island coastline. Refer to <a href="#oceans-05-00031-f001" class="html-fig">Figure 1</a> for geographic context. Due to the rare occurrence of very large SGD plumes, the density maps were calculated by the number and size of discharge sites in specific size classes of ≤1 ha and &gt;1 ha per linear coastline distance of one km.</p>
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<p>Frequency distribution of submarine groundwater discharge (SGD) plumes along the west Hawai‘i coastline.</p>
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<p>Frequency distribution of remotely sensed delta-SST in each submarine groundwater discharge (SGD) plume. Delta-SST was calculated as the difference in sea surface temperature inside relative to outside of each mapped SGD plume (see Methods).</p>
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<p>(<b>a</b>) Example boat transect into submarine groundwater discharge (SGD) plume (in red) at Honokōhau Harbor. (<b>b</b>) Transect results corresponding to panel (<b>a</b>). Dots in both panels indicate each sea surface temperature (SST) measurement.</p>
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<p>Relationship between boat-based estimates of delta-SST inside and outside of each SGD plume and those derived from airborne thermal imaging (n = 47). Open circles indicate each SGD site and dashed line indicates quadratic fit line.</p>
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<p>Relationship between remotely sensed submarine groundwater discharge (SGD) plume area and delta-SST values. Open circles indicate each SGD site.</p>
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16 pages, 3021 KiB  
Article
Elucidating Temporal Patterns in Coral Health and Assemblage Structure in Papahānaumokuākea
by Atsuko Fukunaga, Kailey H. Pascoe, Randall K. Kosaki and John H. R. Burns
J. Mar. Sci. Eng. 2024, 12(8), 1267; https://doi.org/10.3390/jmse12081267 - 28 Jul 2024
Viewed by 923
Abstract
Coral reefs worldwide are under increasing levels of pressure due to global and local stressors. Long-term monitoring of coral reefs through repeated observations at fixed survey sites allows scientists to assess temporal patterns in coral-reef communities and plays important roles in informing managers [...] Read more.
Coral reefs worldwide are under increasing levels of pressure due to global and local stressors. Long-term monitoring of coral reefs through repeated observations at fixed survey sites allows scientists to assess temporal patterns in coral-reef communities and plays important roles in informing managers of the state of the ecosystems. Here, we describe coral assemblages in Papahānaumokuākea, the largest contiguous fully protected marine conservation area in the United States, using long-term monitoring data collected from 20 permanent (fixed) sites at three islands/atolls, Lalo, Kapou and Manawai, between 2014 and 2021. Significant temporal shifts in coral colony composition were detected at some of the monitoring sites, which were attributed to the impact of a mass coral bleaching event in 2014 and Hurricane Walaka in 2018. In particular, the bleaching affected multiple sites at Kapou and one site at Manawai where coral assemblages shifted from the Montipora dilatata/flabellata/turgescens complex to M. capitata dominance; despite being the dominant species at multiple monitoring sites prior to the bleaching, the M. dilatata/flabellata/turgescens complex has not been recorded at any of our monitoring sites in recent years. Coral conditions, such as bleaching, predation, subacute tissue loss, Porites pigmentation response and trematodiasis, did not show differences in the occurrence among the three islands/atolls once the site and temporal variabilities, as well as environmental covariates for bleaching, were considered. Coral genera, however, exhibited different sensitivities to these conditions. These findings highlight the importance of continuing coral reef monitoring at the species level, covering a broad range of coral assemblage compositions and habitat types in Papahānaumokuākea. Full article
(This article belongs to the Topic Conservation and Management of Marine Ecosystems)
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<p>Map of the Hawaiian Archipelago (<b>bottom right</b>) and the locations of Manawai, Lalo, Kapou, and aerial imagery of Manawai (<b>top left</b>), Lalo (<b>top right</b>) and Kapou (<b>bottom left</b>) showing the 20 permanent monitoring sites.</p>
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<p>Hierarchical clustering with Type 1 SIMPROF test identifying the grouping structure of coral assemblages at Lalo. Dotted red branches show internally homogeneous structures. Square-root transformed percent coral colony compositions (red gradient ranging from 0 to 10) are shown for all coral species that were identified to characterize the grouping structure using SIMPER analyses, including those for Kapou and Manawai. Those specific to Lalo are mark by “*”. Species abbreviations are ACYT—<span class="html-italic">Acropora cytherea</span>, COCE—<span class="html-italic">Cyphastrea ocellina</span>, FSCU—<span class="html-italic">Lobactis scutaria</span>, MCAP—<span class="html-italic">Montipora capitata</span>, MFLA—<span class="html-italic">Montipora dilatata/flabellata/turgescens</span> complex, MINC—<span class="html-italic">Montipora incrassate</span>, MPAT—<span class="html-italic">Montipora patula</span>, PBRI—<span class="html-italic">Porites brighami</span>, PCOM—<span class="html-italic">Porites compressa</span>, PDAM—<span class="html-italic">Pocillopora damicornis</span>, PLIC—<span class="html-italic">Porites lichen</span>, PLIG—<span class="html-italic">Pocillopora ligulata</span>, PLOB—<span class="html-italic">Porites lobata</span>, PMEA—<span class="html-italic">Pocillopora meandrina</span> and PSTE—<span class="html-italic">Psammocora stellata</span>.</p>
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<p>Hierarchical clustering with Type 1 SIMPROF test identifying the grouping structure of coral assemblages at Kapou. Dotted red branches show internally homogeneous structures. Square-root transformed percent coral colony compositions are shown for all coral species that were identified to characterize the grouping structure using SIMPER analyses, including those for Lalo and Manawai. Ones specific to Kapou are mark by “*”. See <a href="#jmse-12-01267-f002" class="html-fig">Figure 2</a> for species abbreviations.</p>
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<p>Hierarchical clustering with Type 1 SIMPROF test identifying the grouping structure of coral assemblages at Manawai. Dotted red branches show internally homogeneous structures. Square-root transformed percent coral colony compositions are shown for all coral species that were identified to characterize the grouping structure using SIMPER analyses, including those for Lalo and Kapou. Ones specific to Manawai are mark by “*”. See <a href="#jmse-12-01267-f002" class="html-fig">Figure 2</a> for species abbreviations.</p>
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<p>Plots showing the percentage of coral colonies exhibiting bleaching, predation, subacute tissue loss, <span class="html-italic">Porites</span> pigmentation response or trematodiasis at each region (island/atoll) each year. The percentage values were calculated for each site within each region. Note that the sites that were surveyed each year varied (see <a href="#jmse-12-01267-t001" class="html-table">Table 1</a>). In Manawai, there was only one site (PHR tc26) surveyed in 2014, and no surveys were done in 2021.</p>
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<p>Interval plot (<b>a</b>) showing the estimated coefficients for the final bleaching occurrence model selected based on LOO-CV and conditional effect plots for (<b>b</b>) the interaction between standardized sea surface temperature and standardized wind speed and (<b>c</b>) the interaction between standardized sea surface temperature and standardized chlorophyll <span class="html-italic">a</span> concentration. The interval plot shows the median estimates (circles) and 50 and 95 percentiles (thick and thin lines) of the coefficients including standardized sea surface temperature (sst), standardized surface wind speed (wind), standardized chlorophyll <span class="html-italic">a</span> concentration (chlorophyll), their interactions and the fixed factor of genus. For the fixed factor of genus, <span class="html-italic">Porites</span> was treated as the reference factor level. The standardized sea surface temperature of 0 corresponds to 26.42 °C with 1 unit of change corresponding to a difference in 1.41 °C (see Methods).</p>
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<p>Interval plot showing the estimated coefficients for the final models based on LOO-CV for (<b>a</b>) predation and (<b>b</b>) subacute tissue loss. For the fixed effects of genus, <span class="html-italic">Porites</span> was treated as the reference factor level.</p>
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<p>Interval plot showing the estimated coefficients for the final models based on LOO-CV for (<b>a</b>) <span class="html-italic">Porites</span> pigmentation response and (<b>b</b>) trematodiasis.</p>
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18 pages, 13360 KiB  
Article
Identification of Suitable Mangrove Distribution Areas and Estimation of Carbon Stocks for Mangrove Protection and Restoration Action Plan in China
by Bingbin Feng, Yancheng Tao, Xiansheng Xie, Yingying Qin, Baoqing Hu, Renming Jia, Lianghao Pan, Wenai Liu and Weiguo Jiang
J. Mar. Sci. Eng. 2024, 12(3), 445; https://doi.org/10.3390/jmse12030445 - 1 Mar 2024
Cited by 1 | Viewed by 2839
Abstract
Mangrove forests are significant blue carbon pools on the Earth with strong carbon sequestration capacity and play an important role in combating climate change. To improve the capacity of regional carbon sinks, China has implemented a Special Action Plan for Mangrove Protection and [...] Read more.
Mangrove forests are significant blue carbon pools on the Earth with strong carbon sequestration capacity and play an important role in combating climate change. To improve the capacity of regional carbon sinks, China has implemented a Special Action Plan for Mangrove Protection and Restoration (2020–2025). In this context, based on the MaxEnt model, this study analyzed the important environmental factors affecting the distribution of mangrove forests, combined with the planning objectives and carbon density parameters of different regions; assessed the habitat suitability areas of China’s mangrove forests; and predicted their future carbon stock potential. The results showed the following: (1) Elevation was the most important factor affecting the overall distribution of mangrove forests in China, and the optimal elevation of mangrove distribution was 0.52 m. (2) The most suitable areas of mangrove forests in China were mainly distributed in Hainan, Guangxi, and Guangdong, which had great potential for carbon stock. Danzhou Bay and Hongpai Harbor in Hainan, Lianzhou Bay in Guangxi, and the Huangmao Sea in Guangdong are potential areas for habitat suitability but are not yet under high levels of protection. (3) Achieving the goals of this action plan was expected to increase carbon stocks by 4.13 Tg C. Other suitable areas not included in this plan could still increase carbon stocks by 7.99 Tg C in the long term. The study could provide a scientific basis for siting mangrove restoration areas and developing efficient management policies. Full article
(This article belongs to the Topic Conservation and Management of Marine Ecosystems)
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<p>Distribution of mangroves in China.</p>
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<p>Research framework.</p>
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<p>The performance results of the MaxEnt model. (<b>a</b>) AUC values for the model; (<b>b</b>) test sample omission rate versus predicted omission rate.</p>
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<p>Jacknife results of regularized training gain for mangroves. Dark blue stripes indicate independent test results of each variable, light green stripes indicate test results excluding the variable, and red stripes indicate test results including all variables.</p>
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<p>Response relationships between mangrove habitat suitability and major environmental factors. (<b>a</b>) Elevation. (<b>b</b>) Precipitation of Coldest Quarter. (<b>c</b>) Max Temperature of Warmest Month. (<b>d</b>) Temperature Annual Range. (<b>e</b>) Precipitation of Wettest Quarter. (<b>f</b>) Annual Precipitation.</p>
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<p>Distributions of suitable mangrove habitats in China.</p>
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<p>Priority areas for mangrove protection and restoration in China. (<b>a</b>) Southern Guangxi. (<b>b</b>) Central Guangdong. (<b>c</b>) Northern and western Hainan. (<b>d</b>) Western Guangdong.</p>
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<p>Recommended sites for mangrove creation and restoration actions in South China.</p>
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<p>Recommended sites for mangrove creation and restoration actions in Eastern China.</p>
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<p>Spatial regional carbon stock changes induced by mangrove restoration and conservation actions in Chinese provinces.</p>
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62 pages, 34100 KiB  
Article
Stronger Hurricanes and Climate Change in the Caribbean Sea: Threats to the Sustainability of Endangered Coral Species
by Edwin A. Hernández-Delgado, Pedro Alejandro-Camis, Gerardo Cabrera-Beauchamp, Jaime S. Fonseca-Miranda, Nicolás X. Gómez-Andújar, Pedro Gómez, Roger Guzmán-Rodríguez, Iván Olivo-Maldonado and Samuel E. Suleimán-Ramos
Sustainability 2024, 16(4), 1506; https://doi.org/10.3390/su16041506 - 9 Feb 2024
Cited by 2 | Viewed by 3493
Abstract
An increasing sea surface temperature as a result of climate change has led to a higher frequency and strengthening of hurricanes across the northeastern Caribbean in recent decades, with increasing risks of impacts to endangered corals and to the sustainability of coral reefs. [...] Read more.
An increasing sea surface temperature as a result of climate change has led to a higher frequency and strengthening of hurricanes across the northeastern Caribbean in recent decades, with increasing risks of impacts to endangered corals and to the sustainability of coral reefs. Category five Hurricanes Irma and María during 2017 caused unprecedented damage to coral reef ecosystems across northeastern Puerto Rico, including mechanical destruction, localized sediment bedload (horizontal sediment transport and abrasion), and burial by hurricane-generated rubble fields. Hurricanes inflicted significant site-, depth-, and life history trait-specific impacts to endangered corals, with substantial and widespread mechanical damage to branching species, moderate mechanical damage to foliose species, and moderate to high localized damage to small-sized encrusting and massive morphotypes due to sediment bedload and burial by rubble. There was a mean 35% decline in Acropora palmata live cover, 79% in A. cervicornis, 12% in Orbicella annularis, 7% in O. faveolata, 12% in O. franksi, and 96% in Dendrogyra cylindrus. Hurricane disturbances resulted in a major regime shift favoring dominance by macroalgae, algal turf, and cyanobacteria. Recovery from coral recruitment or fragment reattachment in A. palmata was significantly higher on more distant coral reefs, but there was none for massive endangered species. Stronger hurricanes under projected climate change may represent a major threat to the conservation of endangered coral species and reef sustainability which will require enhancing coral propagation and restoration strategies, and the integration of adaptive, ecosystem-based management approaches. Recommendations are discussed to enhance redundancy, rapid restoration responses, and conservation-oriented strategies. Full article
(This article belongs to the Topic Conservation and Management of Marine Ecosystems)
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Figure 1

Figure 1
<p>Storm trajectories within a radius of 300 km or less of northeastern Puerto Rico between 1851 and 2022 (Source: <a href="https://coast.noaa.gov/hurricanes/#map=4/32/-80" target="_blank">https://coast.noaa.gov/hurricanes/#map=4/32/-80</a> (accessed on 1 December 2023)).</p>
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<p>Study sites across northeastern Puerto Rico. Northeast Reserves System Habitat Focus Area (NER-HFA) within Arrecifes La Cordillera Natural Reserve (ALCNR): ICA, AUD, RAT, PLM; Culebra Island within Canal Luis Peña Natural Reserve (CLPNR): PCR, BTA, PTC; Culebra outside CLPNR: DAK, CAR, AMA, GRO, COS, CRE, CON, CBT. For acronyms, see <a href="#sustainability-16-01506-t001" class="html-table">Table 1</a>. Aerial image source: Google Earth Pro v.7.3.6.9345. Tracks of category five hurricanes Irma and María are shown in <a href="#app1-sustainability-16-01506" class="html-app">Figures S1 and S2</a>.</p>
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<p>Increase in storm frequency and magnitude across the northeastern Caribbean for the period of 1981 to 2022.</p>
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<p>Temporal variation in global climate-related environmental variables: (<b>A</b>) atmospheric CO<sub>2</sub> concentration (ppm); (<b>B</b>) annual increments in atmospheric CO<sub>2</sub> concentration (ppm); (<b>C</b>) land–ocean temperature anomaly (°C); (<b>D</b>) Ocean heat content (×10<sup>22</sup> joules); (<b>E</b>) Thermosteric component of sea level change (mm); (<b>F</b>) North Atlantic Oscillation Index. Data are annual means for the period of 1981 to 2022. Black = regression line; blue = 95% confidence interval bands; red = prediction bands.</p>
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<p>Temporal variation in the frequency and intensity of storms passing within a radius of 300 km off northeastern PR measured at the nearest point of each storm to the island: (1) Mean wind speed (kt); (2) Maximum wind speed (kt), (3) Minimum pressure (mb); (4) Total storm frequency per decade; and (5) Major hurricane frequency per decade. Data source: <a href="https://coast.noaa.gov/hurricanes/#map=4/32/-80" target="_blank">https://coast.noaa.gov/hurricanes/#map=4/32/-80</a> (accessed on 1 December 2023).</p>
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<p>Box plot diagram of spatio-temporal variation in <span class="html-italic">Acropora palmata</span> population parameters before and after Hurricanes Irma and María: (<b>a</b>) Colony surface area (m<sup>2</sup>); (<b>b</b>) Log10 Colony volume (m<sup>3</sup>); (<b>c</b>) Colony height (cm); (<b>d</b>) Percent live cover. Each box plot is composed of a box and two whiskers. The box encloses the middle half of the data. The box is bisected by a line at the value for the median. The vertical lines at the top and the bottom of the box are the whiskers, and they indicate the range of “typical” data values. Whiskers always end at the value of an actual data point and cannot be longer than 1½ times the size of the box. Extreme values are displayed as “◦” for possible outliers and for probable outliers. Possible outliers are values that are outside the box boundaries by more than 1.5 times the size of the box. Probable outliers are values that are outside the box boundaries by more than 3 times the size of the box.</p>
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<p>Spatio-temporal variation in <span class="html-italic">Acropora palmata</span> population parameters before and after Hurricanes: (<b>a</b>) Proportion of fragmented colonies; (<b>b</b>) Proportion of recruit crusts.</p>
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<p>Box plot diagram of spatio-temporal variation in percent coral live cover before and after Hurricanes Irma and María: (<b>a</b>) PCR = Playa Carlos Rosario; (<b>b</b>) DAK = Cayo Dákity; (<b>c</b>) CAR = Punta Carenero; (<b>d</b>) AMA = Arrecife Amarillo; (<b>e</b>) GRO = Bajo Grouper; (<b>f</b>) COS= Arrecife Los Corchos-South; (<b>g</b>) CRE = Arrecife Cabezas Crespas; (<b>h</b>) CON = Arrecife Los Corchos-North; (<b>i</b>) CBT = Culebrita Island; (<b>j</b>) Palominos Island. 0 = Before hurricanes; 1 = After hurricanes; I = &lt;5 m; II = 5–10 m; III = 10–15 m.</p>
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<p>Box plot diagram of spatio-temporal variation in percent coral live cover before and after Hurricanes Irma and María: (<b>a</b>) PCR = Playa Carlos Rosario; (<b>b</b>) DAK = Cayo Dákity; (<b>c</b>) CAR = Punta Carenero; (<b>d</b>) AMA = Arrecife Amarillo; (<b>e</b>) GRO = Bajo Grouper; (<b>f</b>) COS= Arrecife Los Corchos-South; (<b>g</b>) CRE = Arrecife Cabezas Crespas; (<b>h</b>) CON = Arrecife Los Corchos-North; (<b>i</b>) CBT = Culebrita Island; (<b>j</b>) Palominos Island. 0 = Before hurricanes; 1 = After hurricanes; I = &lt;5 m; II = 5–10 m; III = 10–15 m.</p>
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<p>Box plot diagram of spatio-temporal variation in percent macroalgal cover before and after Hurricanes Irma and María: (<b>a</b>) PCR = Playa Carlos Rosario; (<b>b</b>) DAK = Cayo Dákity; (<b>c</b>) CAR = Punta Carenero; (<b>d</b>) AMA = Arrecife Amarillo; (<b>e</b>) GRO = Bajo Grouper; (<b>f</b>) Arrecife Los Corchos-South; (<b>g</b>) CRE = Arrecife Cabezas Crespas; (<b>h</b>) CON = Arrecife Los Corchos-North; (<b>i</b>) CBT = Culebrita Island; (<b>j</b>) Palominos Island. 0 = Before hurricanes; 1 = After hurricanes; I = &lt;5 m; II = 5–10 m; III = 10–15 m.</p>
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<p>Box plot diagram of spatio-temporal variation in percent macroalgal cover before and after Hurricanes Irma and María: (<b>a</b>) PCR = Playa Carlos Rosario; (<b>b</b>) DAK = Cayo Dákity; (<b>c</b>) CAR = Punta Carenero; (<b>d</b>) AMA = Arrecife Amarillo; (<b>e</b>) GRO = Bajo Grouper; (<b>f</b>) Arrecife Los Corchos-South; (<b>g</b>) CRE = Arrecife Cabezas Crespas; (<b>h</b>) CON = Arrecife Los Corchos-North; (<b>i</b>) CBT = Culebrita Island; (<b>j</b>) Palominos Island. 0 = Before hurricanes; 1 = After hurricanes; I = &lt;5 m; II = 5–10 m; III = 10–15 m.</p>
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<p>Principal coordinates ordination (PCO) showing trajectories of benthic community structure across sites, before and after Hurricanes Irma and María. 0 (dark blue) = before, 1 (aquamarine) = after. Vectors shown are based on a Spearman rank correlation &gt; 0.70. This solution explains 60.1% of the observed spatio-temporal variation. <span class="html-italic">Acer</span> = <span class="html-italic">Acropora cervicornis</span>; <span class="html-italic">Ppor</span> = <span class="html-italic">Porites porites</span>; <span class="html-italic">Pfur</span> = <span class="html-italic">P. furcata</span>; <span class="html-italic">Aaga</span> = <span class="html-italic">Agaricia agaricites</span>; <span class="html-italic">Dlab</span> = <span class="html-italic">Diploria labyrinthiformis</span>; <span class="html-italic">Oann</span> = <span class="html-italic">Orbicella annularis</span>; <span class="html-italic">Ofav</span> = <span class="html-italic">O. faveolata</span>; <span class="html-italic">Ofra</span> = <span class="html-italic">O. franksi</span>; <span class="html-italic">Mac</span> = <span class="html-italic">Macrocalgae</span>; <span class="html-italic">CCA</span> = <span class="html-italic">Crustose coralline algae</span>; <span class="html-italic">Cya</span> = <span class="html-italic">Cyanobacteria</span>.</p>
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<p>Spatio-temporal variation in coral biodiversity before and after Hurricanes Irma and María: (<b>a</b>) Species richness (S); (<b>b</b>) Species diversity index (H’<sub>c</sub>); (<b>c</b>) Evenness (J’<sub>c</sub>).</p>
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<p>Spatio-temporal variation in coral biodiversity before and after Hurricanes Irma and María: (<b>a</b>) Species richness (S); (<b>b</b>) Species diversity index (H’<sub>c</sub>); (<b>c</b>) Evenness (J’<sub>c</sub>).</p>
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<p>Example of a demolished shallow (&lt;3 m) mixed stand of Elkhorn coral (<span class="html-italic">Acropora palmata</span>) and Staghorn coral (<span class="html-italic">Acropora cervicornis</span>) due to strong wave action during Hurricanes Irma and María. Note nearly total mortality of <span class="html-italic">A. cervicornis</span> and the substantial partial colony mortality in <span class="html-italic">A. palmata</span>. The end result of such massive reef destruction was a permanent flattening effect which severely decimated shallow reef’s role as a fish nursery ground and as a natural buffer of wave energy and runup.</p>
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<p>Example of a demolished deeper (8 m) patch of Staghorn coral (<span class="html-italic">Acropora cervicornis</span>) due to strong wave action during Hurricanes Irma and María. Note also the massive sand shift from shallow reef zones displaced to deeper reef sections and covering extensive areas of reef slopes. The end result of such massive reef destruction is a permanent flattening effect which severely decimated essential fish habitats, impairing natural reef recovery ability.</p>
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<p>Example of a demolished shallow (&lt;3 m) stand of Elkhorn coral (<span class="html-italic">Acropora palmata</span>) due to strong wave action during Hurricanes Irma and María. Pounding waves caused the massive destruction of <span class="html-italic">A. palmata</span>. Lose fragments piled up and suffocated numerous other fragments that remained below. Regular wave action also moved fragments causing further abrasion and fragment mortality.</p>
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<p>Example of a formerly demolished mixed stand of Finger coral (<span class="html-italic">Porites porites</span>) and Elkhorn coral (<span class="html-italic">Acropora palmata</span>) across a shallow reef front near Ensenada Honda Bay currently dominated by extensive stands of Fire coral (<span class="html-italic">Millepora complanata</span>). According to local older fishers, this shallow reef was mechanically impacted in 1979 by category 4 Hurricanes David and Frederick (1979). This is evidence of how much stochastic disturbances such as hurricanes can inflict major physical damage, shifting benthic community structure beyond natural recover, and permanently reshaping shallow reefs composition and ecological functions.</p>
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<p>Example of the nearly total devastation of a Staghorn (<span class="html-italic">Acropora cervicornis</span>) thicket following Hurricanes Irma and Maria. Waves in excess of 10 m height caused extensive destruction of windward shallow reef’s framework, resulting in a mechanical collapse and in permanent reef flattening.</p>
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<p>The collapsed structure of Staghorn coral (<span class="html-italic">Acropora cervicornis</span>) patches resulted in major reef flattening, affecting reef fish and demersal invertebrate communities due to the immediate loss of diverse microhabitats.</p>
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<p>Partial view of a rubble field formed following Hurricanes Irma and María that killed every coral colony across thousands of square meters of reef slope bottom at Grouper Reef (GRO). Rubble fields are formed after extensive mechanical destruction of shallower coral reef segments. Debris was deposited on backreefs and forereef slopes, causing immediate extensive coral mortality by burial and a permanent reef flattening effect. This image shows partially buried sea fan (<span class="html-italic">Gorgonia ventalina</span>) colonies.</p>
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<p>Detailed view of a recently formed rubble field that suffocated thousands of coral colonies following Hurricanes Irma and Maria in Culebra Island. The major concern with such formations is that rubble fields are a novel, mobile substrate, capable of producing long-term extensive damage to adjacent reef bottoms during subsequent disturbances such as future winter swells, tropical storms, or hurricanes. Moving substrates can kill any potential sexual coral recruit by flipping over.</p>
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<p>Example of a dislodged head of Columnar star coral (<span class="html-italic">Orbicella annularis</span>). This colony was temporarily overturned, which was already causing coral bleaching. The coral was also being subjected to significant macroalgal overgrowth by <span class="html-italic">Acrosymphyton caribaeum</span>.</p>
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<p>Example of a partially buried and suffocated colony of Massive star coral (<span class="html-italic">Orbicella franksi</span>) under a recently formed rubble field during Hurricanes Irma and María. Note extensive bleaching and partial tissue mortality. Note also that most of the rubble was formed by demolished colonies of Finger corals (<span class="html-italic">Porites</span> spp.), which were rapidly dead by abrasion and suffocation.</p>
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<p>Example of a partially dead colony of Massive star coral (<span class="html-italic">Orbicella franksi</span>) dislodged by wave action, and then suffocated under a recently formed rubble field during Hurricanes Irma and María.</p>
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<p>Dislodged colony of Brain coral (<span class="html-italic">Pseudodiploria strigosa</span>). Dislodgment and overturning of coral heads under strong wave action often results in severe bleaching and eventual partial or total mortality.</p>
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<p>Example of projectile impacts on soft corals. Massive impacts by dislodged rubble from adjacent reef areas can be devastating and lethal for octocorals. This is an example of such impacts. Note the nearly entire extirpation of the soft coral community from this reef following Hurricanes Irma and Maria.</p>
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<p>Large colony of Elkhorn coral (<span class="html-italic">Acropora palmata</span>) showing blunt (and already healing) branches fragmented during Hurricanes Irma and Maria. Such blunt large coral colonies were commonly found across numerous shallow reefs across northeastern Puerto Rico.</p>
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<p>Recently killed colony of the Mustard hill coral (<span class="html-italic">Porites astreoides</span>) due to severe abrasion and suffocation by projectiles from moving rubble.</p>
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<p>Unprecedented devastation from Hurricanes Irma and Maria. Extensive segments of spur and groove systems on offshore windward coral reefs were mechanically pulverized by wave action. Rubble produced by such massive destruction dispersed through adjacent grooves, clogging sand channels among spurs. These deposits may become future projectiles during strong storm events and heavy winter swells.</p>
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<p>Unprecedented devastation from Hurricanes Irma and Maria. Extensive segments of spur and groove systems on offshore windward coral reefs dominated by Finger coral (<span class="html-italic">Porites porites</span>) were mechanically pulverized by wave action, resulting in the physical disintegration of the substrate and in extensive reef flattening. Rubble produced by such massive destruction dispersed through adjacent grooves.</p>
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<p>Rubble from the unprecedented destruction of adjacent reef spurs suffocated extensive zones of deeper reef terraces and slopes, sometimes at depths reaching 10–15 m after rubble spillover and burial.</p>
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<p>Example of a rubble field formed across a sandy reef groove system at a depth of 8–12 m. Deeper reef spur and grooves and forereef terraces were affected by spillover and burial by rubble displaced by wave action from shallower zones.</p>
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<p>Example of a rubble field formed across a sandy reef groove system at a depth of 8–10 m. The substrate of some groove channels was elevated from 1 to 2 m due to the heavy sand shift and sediment or rubble deposition. This resulted in a stochastic reduction of benthic spatial heterogeneity.</p>
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<p>Deeper reef slopes were also severely suffocated by moving hurricane-generated debris, causing further damage to corals, and a permanent loss of benthic spatial heterogeneity.</p>
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<p>Partial suffocation and bleaching in a partially buried head of brain coral (<span class="html-italic">Colpophyllia natans</span>).</p>
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<p>Partial bleaching and burial in a dislodged colony of Laminar star coral (<span class="html-italic">Orbicella faveolata</span>).</p>
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<p>Partially bleached and killed fragment of Elkhorn coral (<span class="html-italic">Acropora palmata</span>). Numerous fragments of this species died by abrasive effects of projectiles during the hurricane or suffocation by moving debris.</p>
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<p>Example of extremely turbid conditions of inner reefs at Ensenada Honda Bay, Culebra. Poor water transparency across coral reefs persisted for a period of more than two months after Hurricane María caused by blooming phytoplankton and resuspended silt following hurricanes and major turbid runoff impacts.</p>
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<p>Example of massive reef destruction, in combination with very high turbidity across inner reefs at Ensenada Honda Bay, Culebra.</p>
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<p>Example of massive reef destruction and rubble field formation, in combination with very high turbidity across inner reefs at Ensenada Honda Bay, Culebra.</p>
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<p>Example of a major macroalgal bloom and phytoplankton bloom across one of the outer reefs at Ensenada Honda Bay. Such blooms are common after major hurricanes, heavy rainfall, and sediment-laden, nutrient-loaded runoff events.</p>
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<p>Example of a partially fragmented patch of Finger coral (<span class="html-italic">Porites porites</span>) in a coral reef at the entrance of Ensenada Honda Bay. Natural recovery ability of such moderate impacts can be significantly compromised due to chronic, extremely poor water quality.</p>
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<p>Example of a major macroalgal bloom and phytoplankton bloom across one of the outer reefs at Ensenada Honda Bay. In this case, the reef is 100% covered by invasive Red encrusting algae (<span class="html-italic">Ramicrusta textilis</span>), intermingled with brown unpalatable macroalgae <span class="html-italic">Lobophora variegata</span> and <span class="html-italic">Dictyota</span> spp.</p>
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<p>Example of a shallow reef segment at Cayo Quebrado being also impacted by a massive lens of turbid freshwater. Freshwater lenses following heavy rainfall, runoff, and groundwater seepage can be a significant source of stress and of partial coral colony mortality across shallow, semi-protected backreef zones.</p>
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<p>Example of a partially killed colony of Laminar star coral (<span class="html-italic">Orbicella faveolata</span>) after exposure to a freshwater lens following Hurricanes Irma and Maria.</p>
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<p>Example of a partially killed colony of Brain coral (<span class="html-italic">Pseudodiploria strigosa</span>) impacted by Black band disease (BBD) after exposure to a freshwater lens following Hurricanes Irma and Maria.</p>
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<p>Example of a partially killed colony of a Sea fan (<span class="html-italic">Gorgonia flabellum</span>) after exposure to a freshwater lens following Hurricanes Irma and Maria.</p>
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<p>Example of a partially bleached and killed colony of a mat zoanthid (<span class="html-italic">Palythoa caribbaorum</span>) after exposure to a freshwater lens following Hurricanes Irma and Maria.</p>
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<p>Example of a displaced pile of rubble from old hurricanes (e.g., David and Frederick, 1979) that was relocated in another segment of the Outer Bay Reef at the entrance of Ensenada Honda. Rubble pile displacement also impacted adjacent non-impacted reef segments by becoming lethal projectiles during hurricane-generated waves, resulting in burial of corals. Stabilizing such rubble fields is a paramount management priority to restore shallow reef zones.</p>
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<p>Example of a reef bottom largely impacted by a major macroalgal bloom following hurricane impacts, dominated by three red macroalgal species: <span class="html-italic">Liagora</span> spp., <span class="html-italic">Acrosymphyton caribaeum</span>, and <span class="html-italic">Trichogloeopsis pedicellata</span>. These species tend to occur in deeper habitats, but heavy algal and sediment resuspension due to strong wave action and bottom swells, in combination with heavy nutrient loading from major turbid runoff following heavy rainfall and flooding, resulted in major algal blooms, further impacting remnant surviving coral assemblages.</p>
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<p>Example of mechanical impacts to reef framework: Dislodgement of a shallower head dominated by Columnar star coral (<span class="html-italic">Orbicella annularis</span>) at Cayo Dákity. This piece of the reef framework fell from an approximate depth of 5 m down to 12 m.</p>
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<p>Example of mechanical impacts to reef framework: Dislodgement of another shallower head dominated by Columnar star coral (<span class="html-italic">Orbicella annularis</span>) at Cayo Dákity (background). This piece of the reef framework felt from an approximate depth of 6 m down to 12 m. Note the presence of another dislodged colony of <span class="html-italic">O. annularis</span> in the foreground that appears to have been also dislodged by a previous hurricane.</p>
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<p>Example of mechanical impacts to reef framework: Dislodgement and overturning of a large head of Laminar star coral (<span class="html-italic">Orbicella faveolata</span>) and of Sea fan (<span class="html-italic">Gorgonia flabellum</span>) from 5 to 10 m.</p>
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<p>Impact by strong wave action over very shallow rubble fields: Waves rolling action may prevent cementation by crustose coralline algae and sponges, maintaining shifting rubble as moving projectiles. This can result into a continuing problem of abrasion and suffocation over adjacent remnant corals, also affecting successful coral’s sexual larval recruitment, affecting reef’s natural regeneration ability. It can also permanently impair shallow reef’s role in wave energy and runup attenuation, and as fish nursery grounds. Therefore, this is a form of a carry-over hurricane impact effect which is still poorly understood, but which may extend to very long-term scales (years to decades, at least).</p>
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16 pages, 9775 KiB  
Article
Land Use/Land Cover Changes in a Mediterranean Summer Tourism Destination in Turkey
by Ismail Cinar, Zeynep R. Ardahanlıoğlu and Süleyman Toy
Sustainability 2024, 16(4), 1480; https://doi.org/10.3390/su16041480 - 9 Feb 2024
Viewed by 1248
Abstract
Tourism contributes to national and local economies especially in the Mediterranean and Aegean coasts of Turkey including the study area, Fethiye-Göcek, Muğla in southwest Turkey. The study evaluates land use/land cover (LULC) changes driven by tourism development as a case considering the past [...] Read more.
Tourism contributes to national and local economies especially in the Mediterranean and Aegean coasts of Turkey including the study area, Fethiye-Göcek, Muğla in southwest Turkey. The study evaluates land use/land cover (LULC) changes driven by tourism development as a case considering the past (1995–2020) and future environmental impacts on the area. High-resolution remote sensing and some socio-economic data were employed to monitor the situation and causes of LULC changes using Normalised Difference Vegetation Index (NDVI) and Land Surface Temperature (LST). The results show a decrease in the size of water surface, forest and maquis lands due to tourism development together with an increase in urban fabrics and bare lands due to urbanisation and forest fires. A significant positive correlation was detected between the urbanisation rate, population size and built-up area as well as air temperature and LST. Rapid and unplanned tourism development boosted investments for infrastructure and facilities and thus increased the demands for lands. Such lands were mostly gained by filling the sea or transforming agricultural and greenhouse areas, forest and maquis-covered lands. The unplanned development of tourism and urban areas caused serious hazards to the natural and cultural areas which threaten the sustainability of tourism. Planning suggestions are proposed to decision makers like coordination works for sustainable and responsible tourism development. Full article
(This article belongs to the Topic Conservation and Management of Marine Ecosystems)
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Figure 1
<p>Location map of the study area in Turkey.</p>
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<p>LST flowchart for ArcGIS.</p>
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<p>Comparing the spatial distribution of the changes in LULC between 1995, 2003 [<a href="#B63-sustainability-16-01480" class="html-bibr">63</a>] and 2020.</p>
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<p>Spatial distribution of LST in the study years.</p>
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<p>Linear regression model for LST and LULC.</p>
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<p>Spatial distribution of NDVI in the study years.</p>
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<p>The relationship between NDVI and LST in the study area and study period.</p>
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10 pages, 8386 KiB  
Article
Artificial Reef Deployment Reduces Diving Pressure from Natural Reefs—The Case of Introductory Dives in Eilat, Red Sea
by Nadav Shashar, Asa Oren, Re’em Neri, Omer Waizman, Natalie Chernihovsky and Jenny Tynyakov
Oceans 2024, 5(1), 71-80; https://doi.org/10.3390/oceans5010005 - 7 Feb 2024
Viewed by 2862
Abstract
Artificial reefs have been suggested as alternative dive sites to mitigate human pressure on natural reefs. Despite the conceptual appeal of artificial reefs, there is a paucity of empirical evidence regarding their effectiveness in achieving this objective. Here, we report that a small [...] Read more.
Artificial reefs have been suggested as alternative dive sites to mitigate human pressure on natural reefs. Despite the conceptual appeal of artificial reefs, there is a paucity of empirical evidence regarding their effectiveness in achieving this objective. Here, we report that a small artificial reef deployed adjacent to a local coral marine protected area caused a shift in the routes taken by introductory dives and nearly eliminated their visitations to the natural fringing reef within the MPA. This behavioral shift among divers persisted for more than a decade following the AR deployment. These findings underscore the efficacy of well-designed and appropriately located artificial reefs as valuable instruments in the conservation of coral reefs. Full article
(This article belongs to the Topic Conservation and Management of Marine Ecosystems)
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Graphical abstract

Graphical abstract
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<p>(<b>A</b>) Location of the artificial reef. (<b>B</b>–<b>D</b>) Artificial reef just after deployment. Photos by Ziggy Livnat. (<b>B</b>) North side of the AR; (<b>C</b>) east side of the AR; (<b>D</b>) south side of the AR. The AR is composed of 6 units (<b>C</b>), each with 2 m on its side, depth, and height.</p>
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<p>Introductory dives gathered around the 4 × 4 × 4 m large artificial reef. Left—8 instructor and guest pairs. Photographed by AO on 15 October 2019. Right—4 pairs. Photographed by JT on 5 October 2023.</p>
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<p>(<b>Left</b>): introductory dive routes prior to the deployment of an AR (prior to 2006). (<b>Right</b>): routes following the deployment of the AR (after 2018). NRB—the northern border and fence of the local natural MPA, which is fenced from land. Arrows indicate places of entry to the water used by divers. Two coral outcrops are located in the area (named outcrops 5 and 6 due to their depth), and an area rich with garden eels, <span class="html-italic">Gorgasia sillneri</span>, is located further north of the AR (GE). Note the drop in visitation to the natural fringing reef, which is part of the fenced nature reserve, that occurred following AR deployment.</p>
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18 pages, 3607 KiB  
Article
Assessing the Fishing Impact on the Marine Ecosystem of Guishan Island in the Northeastern Waters of Taiwan Using Ecopath and Ecosim
by Chien-Pang Chin, Kuan-Yu Su and Kwang-Ming Liu
J. Mar. Sci. Eng. 2023, 11(12), 2368; https://doi.org/10.3390/jmse11122368 - 15 Dec 2023
Viewed by 1316
Abstract
The northeastern waters of Guishan Island constitute one of the crucial fishing grounds for coastal trawl fishery in Taiwan and have been exploited for many decades. To construct the marine ecosystem and to examine the interactions among trophic levels of fisheries resources in [...] Read more.
The northeastern waters of Guishan Island constitute one of the crucial fishing grounds for coastal trawl fishery in Taiwan and have been exploited for many decades. To construct the marine ecosystem and to examine the interactions among trophic levels of fisheries resources in the waters of Guishan Island, historical catch, catch composition, biological information, fishing effort, environmental data such as sea surface temperature, salinity, and nutrients were analyzed using Ecopath with Ecosim. The results indicated that the longline and drift net fisheries have a very minor incidental catch of cetaceans, with a fishing mortality (F) of 0.01 year−1 and an exploitation rate (E) of 0.03. The F and E were 0.308 year−1 and 0.617 for small skates and rays, and were 0.261 year−1 and 0.580, respectively, for small sharks. The F and E of the dolphinfish, Coryphaena hippurus, an important pelagic species, were 0.411 year−1 and 0.245, respectively. Fisheries had negative impact on major commercial species except the dolphinfish and the oil fish, Lepidocybium spp., which benefited from the reduction of their predators or competitors. The keystone species of the Guishan Island marine ecosystem is phytoplankton, which has the lowest trophic level and great biomass, and is an important energy source of the ecosystem. The influences of zooplankton and anchovy rank as second and third, respectively, with regard to the keystone species in the ecosystem due to their great biomass. Regarding the biomass of less abundant species, carangids had the highest influence followed by hairtail due to their feeding habits. The results of simulations using Ecosim indicated that the hairtail, small sharks, skates and rays, mackerels, and marine eels will benefit if fishing efforts are reduced by 30%. On the other hand, the biomass of phytoplankton, zooplankton, demersal benthivores, and shrimps will decrease due to the increase in the biomass of their predators. Full article
(This article belongs to the Topic Conservation and Management of Marine Ecosystems)
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<p>Study area of Guishan Island waters, northeastern Taiwan.</p>
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<p>The flow diagram of the food web derived from the marine ecosystem model of the Guishan Island, northeastern Taiwan.</p>
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<p>The trophic and fishery impacts on species/functional group derived from the marine ecosystem model of the Guishan Island. Larger size of circles indicates larger impact.</p>
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<p>The 30-year trend of relative biomass of species/functional group in the marine ecosystem of the Guishan Island derived from simulations of 30% deduction in fishing effort.</p>
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<p>The changes in relative biomass of species/functional groups in the marine ecosystem of the Guishan Island derived from simulations of 30% deduction in fishing effort.</p>
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19 pages, 11393 KiB  
Review
Development Trends, Current Hotspots, and Research Frontiers of Oyster Reefs: A Bibliometric Analysis Based on CiteSpace
by Jie Cheng, Duian Lu, Li Sun, Wei Mo, Mengnan Shen, Ming Li, Chenyang Li, Ming Zhang, Jun Cheng, Degang Wang and Yonghua Tan
Water 2023, 15(20), 3619; https://doi.org/10.3390/w15203619 - 16 Oct 2023
Cited by 1 | Viewed by 2244
Abstract
The ocean is the largest reservoir on Earth. With the scarcity of water resources, the destruction of the benign cycle of the marine ecosystem would seriously impact people’s quality of life and health. Oyster reefs, the world’s most endangered marine ecosystems, have been [...] Read more.
The ocean is the largest reservoir on Earth. With the scarcity of water resources, the destruction of the benign cycle of the marine ecosystem would seriously impact people’s quality of life and health. Oyster reefs, the world’s most endangered marine ecosystems, have been recognized as a global issue due to their numerous essential ecological functions and provision of various ecosystem services. As a result, interest in oyster reef research has been steadily increasing worldwide in recent decades. The goal of this study is to assess the knowledge structure, development trends, research hotspots, and frontier predictions of the global oyster reef research field. Based on 1051 articles selected from the Web of Science Core Collection from 1981 to 2022, this paper conducted a visual analysis of oyster reef ecosystems conservation, restoration, and management. Specifically, it examined research output characteristics, research cooperation networks, highly cited papers and core journals, and keywords. Results indicate a steady rise in research interest in oyster reefs over the past 40 years, with notable acceleration after 2014. Authoritative experts and high-impact organizations were also identified. This paper outlines habitat conservation and restoration, ecosystem services, and the impacts of climate change as the primary research hotspots and frontiers. This paper provides valuable guidance for scholars and regulators concerned about oyster reef conservation to conduct research on oyster reefs. Full article
(This article belongs to the Topic Conservation and Management of Marine Ecosystems)
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<p>The annual number of published articles on oyster reefs extracted from the WoS Core Collection database.</p>
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<p>Contributions of various countries worldwide in the production of articles on oyster reefs. The subjects began in 1981, and the evolution until 2022 is shown from left to right.</p>
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<p>The network map of institutions for oyster reef research.</p>
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<p>The network map of authors for scientific research on oyster reefs.</p>
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<p>Dual-map overlays of oyster reefs research.</p>
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<p>Journal co-citation network.</p>
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<p>A schematic representation of network analysis of keywords appeared in scientific documents published on oyster reefs.</p>
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<p>Visualization of keywords timeline analysis.</p>
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<p>Top 30 keywords with the strongest citation bursts.</p>
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14 pages, 23469 KiB  
Technical Note
Exploring New Frontiers in Coral Nurseries: Leveraging 3D Printing Technology to Benefit Coral Growth and Survival
by Ofer Berman, Natalie Levy, Haim Parnas, Oren Levy and Ezri Tarazi
J. Mar. Sci. Eng. 2023, 11(9), 1695; https://doi.org/10.3390/jmse11091695 - 28 Aug 2023
Cited by 5 | Viewed by 2723
Abstract
Coral nurseries and associated techniques are the most common and widespread reef restoration methods worldwide. Due to the rapid decline of coral reefs, coral nurseries need to be eco-friendlier and adapted for effective upscaling to support large restoration projects. We suggest new design [...] Read more.
Coral nurseries and associated techniques are the most common and widespread reef restoration methods worldwide. Due to the rapid decline of coral reefs, coral nurseries need to be eco-friendlier and adapted for effective upscaling to support large restoration projects. We suggest new design and fabrication processes associated with coral gardening and transplantation with 3D printing technology to offer a beneficial solution for growing coral fragments in on-land and underwater nurseries. We describe multiple combinations of building nurseries through the integration of biomimetic substrates and novel solutions for attaching coral fragments. Our methods are supported with supplemental testing of two hybrid substrate designs and coral mounting structures, building upon previous studies in the Gulf of Eilat/Aqaba (GoE/A), Red Sea. We identified and quantified marine invertebrates colonizing the surfaces of our substrates with environmental DNA (eDNA) by targeting the mitochondrial COI gene. We evaluated our coral fragments with and without our mounting structures to obtain an indication of total protein as a proxy for tissue health. We demonstrate the ability to design hybrid nurseries with custom mounting structures using biomimetic substrates, such as large ceramic artificial reefs, or with an interlocking mesh for holding numerous fragments to maximize out-planting efforts. We propose several methods for both land and underwater nurseries catered to various restoration initiatives for cost-effective up-scaling to meet the demands of global reef restoration. Full article
(This article belongs to the Topic Conservation and Management of Marine Ecosystems)
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<p>Biomimetic settlement tile adapted with mounting structure. (<b>A</b>) The square ceramic tile after bisque firing, and the initial design of the mounting structure custom-made to fit specific holes in the tiles. (<b>B</b>) Custom mounting structure with coral skeleton; the flexible mounting structures are printed with bottom and top overhangs which help to secure it to the tile. (<b>C</b>) The square tile submerged with the planted fragments (not all attached with the mounting structure). (<b>D</b>) Conceptualization of a horizontal floating coral nursery composed of square ceramic tiles and custom mounting structures.</p>
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<p>Complex 3DP settlement tile configurations with mounting structure. (<b>A</b>) The round 3DP ceramic tile after bisque firing, with second-version universal mounting structures, exhibiting a more advanced design. Mounting structures are anchored to the holes in the tiles. (<b>B</b>) Underwater testing of the design of the mounting structure to attach coral fragments (in the Northern Red Sea, 2023). (<b>C</b>) Testing different infill patterns of the round tiles with fragments (without inserts) underwater (in the Maldives, 2022). (<b>D</b>) Conceptualization of a vertical floating coral nursery made up of round ceramic tiles and universal mounting structures.</p>
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<p>Proof of concept of coral nursery mesh design consisting of universal mounting structures. (<b>A</b>) First-generation design of the universal mounting structure, 3DP modular nylon housing, and a 3DP jig to die-cut the inner wall to release the bristles. (<b>B</b>) Overview of the flexible nursery prototype, which in a 100 m<math display="inline"><semantics> <msup> <mrow/> <mn>2</mn> </msup> </semantics></math> floating nursery that could contain up to 90,000 fragments. (<b>C</b>) Close-up of a coral skeleton secured to the meshed mounting structure. (<b>D</b>) Testing the prototype underwater with live coral fragments. The design of the mesh mounting structures can wrap around existing artificial structures such as concrete columns or piers, turning them into a nursery.</p>
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<p>Total number of sequences of phyla found on parametric square tiles. Phyla were detected from eDNA present only on tiles at two study sites in the GoE/A after quality control. Pictures represent the organisms from each phyla to show habitat partitioning on tiles (adapted with permission from Ref. [<a href="#B17-jmse-11-01695" class="html-bibr">17</a>]; Science of The Total Environment; Elsevier; 2023).</p>
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<p>Total protein content from the tissues of three branching corals. Baseline corals represent the fragments before they were attached to substrates (tiles). The substrate treatment is the 6 months after they were mounted to tiles. Asterisks represent the level of <span class="html-italic">p</span>-value significance: <span class="html-italic">p</span> &lt; 0.01 (*) and <span class="html-italic">p</span> &lt; 0.001 (**). Dots represent replicates.</p>
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<p>Visualization of a benthic organism succession on a ceramic reef with planted fragments (adapted with permission from Ref. [<a href="#B6-jmse-11-01695" class="html-bibr">6</a>]; Science of The Total Environment; Elsevier; 2022). (<b>A</b>) Newly deployed biomimetic AR with fragments. (<b>B</b>) Projection of a six-month- to one-year-old AR with growing fragments, with a gradual accumulation of marine invertebrates, microorganisms, and algae. (<b>C</b>) Fully covered coral reef ecobiome growing on the AR with larger and diverse coral fragments.</p>
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18 pages, 2051 KiB  
Article
Heavy Metal Content in Macroalgae as a Tool for Environmental Quality Assessment: The Eastern Gulf of Finland Case Study
by Yulia I. Gubelit, Tatiana D. Shigaeva, Valentina A. Kudryavtseva and Nadezhda A. Berezina
J. Mar. Sci. Eng. 2023, 11(9), 1640; https://doi.org/10.3390/jmse11091640 - 23 Aug 2023
Cited by 3 | Viewed by 1318
Abstract
Macroalgae are widely used for bioindication and assessment; however, in the case of pollutants of different origin, it is still unclear which contaminants in thalli can be regarded as indicative because too many factors influence the ability of algae to uptake them. The [...] Read more.
Macroalgae are widely used for bioindication and assessment; however, in the case of pollutants of different origin, it is still unclear which contaminants in thalli can be regarded as indicative because too many factors influence the ability of algae to uptake them. The present study is a part of an international HAZLESS project and was conducted in the eastern Gulf of Finland (GoF). The main goal of our study was the application of metal concentrations in macroalgae as a tool for environmental quality assessment. To achieve this goal, we calculated the threshold metal concentrations in macroalgae (Cladophora glomerata) and compared our obtained values with actual concentrations. We found significant Spearman correlations in May between metals in sediments and pore water (−0.73 for Zn, −0.62 for Cd, 0.85 for Pb) and also between metals in algae and metals in pore water (1 for Cu and Cd, 0.98 for Zn and Pb). In July, Pb in algae were significantly correlated with Pb in pore water (0.88). The application of the calculated environmental quality standard (EQSMPC) for macroalgae has shown moderate pollution by Cu and Pb in the coastal zone of the eastern GoF. This was confirmed by an assessment based on the comparisons of metal concentrations in water with Environmental Quality Standards for water (EQSw). However, differences in the bioaccumulation factor and EQSMPC between May and July have shown that it is necessary to compare samples taken during the same period every year for adequate results in long-term monitoring. Considering the sensitivity of accumulating processes to the surrounding environment, we believe that in the case of habitats with diverse conditions, even for the same species of algae, threshold values should be calculated and used individually for every habitat. Our results have shown that this approach can be widely used for an assessment of environmental quality via metal concentrations in opportunistic macroalgae and can be recommended for further use. Full article
(This article belongs to the Topic Conservation and Management of Marine Ecosystems)
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<p>Schematic map of the eastern Gulf of Finland. Sampling sites are marked by numbers.</p>
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<p>Metal distribution in the water on study sites of the EGoF in May 2019. <span style="color:red">*</span>—significantly higher; *—significantly lower.</p>
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<p>Metal distribution in the water on study sites of the EGoF in July 2019. <span style="color:#C00000">*</span>—significantly higher.</p>
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<p>Metal distribution in sediments on study sites of the EGoF in May 2019. <span style="color:#C00000">*</span>—significantly higher.</p>
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<p>Metal content in biomass of <span class="html-italic">Cladophora glomerata</span> in May 2019. <span style="color:#C00000">*</span>—significantly higher.</p>
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<p>Metal content in algal biomass in July 2019. <span style="color:#C00000">*</span>—significantly higher.</p>
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<p>Principal component and classification analysis for main hydrochemical parameters (Eh, Temperature, pH in sediments (pHsed), water pH (pHw), salinity) and metal distribution in sediments (Me), water (Me1), pore water (Me2), and algae (Me3) in May 2019.</p>
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<p>Principal component and classification analysis for main hydrochemical parameters (Eh, Temperature, water pH (pH), salinity) and metal distribution in water (Me1), pore water (Me2), and algae (Me3) in July 2019.</p>
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19 pages, 2879 KiB  
Article
Estimate of Cetacean and Shark Depredations in the Small-Scale Longline Fishery in the Southeastern Waters of Taiwan
by Kwang-Ming Liu, Kuan-Yu Su and Chien-Pang Chin
J. Mar. Sci. Eng. 2023, 11(6), 1233; https://doi.org/10.3390/jmse11061233 - 15 Jun 2023
Viewed by 1510
Abstract
Cetacean and shark depredations in a small-scale longline fishery in the southeastern Taiwan waters were estimated based on interviews of 21 fishermen and logbooks of 12 sampling vessels, including 649 operations (681,310 hooks) from October 2009 to December 2010. Cetacean depredations were more [...] Read more.
Cetacean and shark depredations in a small-scale longline fishery in the southeastern Taiwan waters were estimated based on interviews of 21 fishermen and logbooks of 12 sampling vessels, including 649 operations (681,310 hooks) from October 2009 to December 2010. Cetacean depredations were more serious than shark depredations, with damage rates of 19.26% and 11.56%, respectively. The depredation rates in number and weight from cetaceans were estimated to be 2.21% and 3.23%, respectively, and were significantly higher than those from sharks, which were estimated to be 0.51% and 0.47%, respectively. The depredation indices from cetacean and shark were estimated to be 0.93 and 0.22 per 1000 hooks, respectively. The dolphinfish and yellowfin tuna were the top two species depredated by cetaceans and sharks. The annual economic loss of the small-scale longline fishery due to cetacean and shark depredations was estimated to be USD 441.9 thousand and USD 58.8 thousand, respectively, which corresponded to 4.5% and 0.6% of the total sales of the longline fishery at Hsinkang fishing port, southeastern Taiwan. The catch in number of dolphinfish and the operation depth were significant factors that affected cetacean depredations. Full article
(This article belongs to the Topic Conservation and Management of Marine Ecosystems)
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<p>The fishing area and fishing efforts of the small-scale tuna longline sampling vessels in this study.</p>
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<p>The percentage of species-specific catch in number (<b>a</b>) and catch in weight (<b>b</b>) of sampling vessels.</p>
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<p>The species-specific catch in number from March to September (<b>a</b>) and from October to February (<b>b</b>), and the catch in weight from March to September (<b>c</b>) and from October to February (<b>d</b>) of sampling vessels in different fishing seasons. The left side of the <span class="html-italic">Y</span>-axis is for dolphinfish, and the right side is for other species.</p>
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<p>A catch depredated by cetacean (<b>a</b>) and shark (<b>b</b>).</p>
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<p>The depredation rate in number (DRN) of cetaceans (<b>a</b>) and sharks (<b>b</b>), and depredation index (DI) of cetaceans (<b>c</b>) and sharks (<b>d</b>) by 0.25° × 0.25° grid.</p>
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<p>The percentage of species-specific production (<b>a</b>) and value (thousand USD) (<b>b</b>) at Hsinkang fishing port.</p>
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<p>Species-specific economic loss due to depredations from cetaceans (<b>a</b>) and sharks (<b>b</b>) of the sampling vessels.</p>
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