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1,071 results for “Mangroves”
Volatile compounds of five mangrove species and parts
<p><span>Mangrove plants contain a variety of secondary metabolites, which are important for their survival and adaptation to the coastal environment, as well as for producing bioactive compounds. To reveal differences in mangrove volatile</span><span>s</span><span>, </span><span>a </span><span>GC-MS </span><span>method</span><span> was </span><span>built</span> <span>up</span> <span>and</span><span> used to analyze and identify five mangrove species' leaf, root, and stem. </span><span>The relative content and type of volatile compounds were counted and compared, and their pathway enrichment analysis was p</span><span>erformed. The results showed that 5</span><span>32 compounds were detected in the l</span><span>eaf, root, and stem parts of five mangrove species, which </span><span>were</span><span> grouped into 18 classes including alcohols, aldehydes, alkaloids, alkanes, etc. The number of compounds found was from 41 to 86 in each part of five mangrove species, <em>A</em>. <em>corniculatum</em> leaves and <em>A</em>. <em>marina</em> roots contained a maximum of 86 compounds. 247 compounds were found in <em>A</em>. <em>corniculatum</em>, 245 in <em>K</em>. <em>candel</em>, and 240 in <em>A</em>. <em>marina</em>. Roots, stems, and leaves each had 399, 342, and 339 compounds. There were 40 unique compounds in <em>A</em>. <em>corniculatum</em> leaves, and 39 in <em>A</em>. <em>corniculatum</em> stems.</span> <span>71 common compounds occurring in more than two species or organ parts were analyzed by PLS-DA model. Compared w</span><span>it</span><span>h the contents and compositions of their compounds, <em>A</em>. <em>ilicifolius</em> and <em>B</em>. <em>gymnorrhiza</em> differed significantly from the other species</span><span>, </span><span>while the leaves differed significantly from the other parts. </span><span>Unique compounds and common compounds were found to have a significant difference in composition and concentration between species and parts based on the results of one-way analysis of variance, principal component analysis, and hierarchical clustering analysis. </span><span>VIP screening and pathway enrichment analysis were performed </span><span>on</span><span> 17 common compounds closely related to mangrove tree species or parts</span><span>, and </span><span>these compounds </span><span>were involved in metabolic pathways of C10 isoprenoids, C15 isoprenoids, fatty alcohols, etc. These findings might help in the development of genetic varieties and medicinal utilization of mangrove plants.</span></p>
Coexisting mangrove-coral habitat use by reef fishes in the Caribbean
<p>We conducted visual fish surveys in coexisting mangrove-coral (CMC) habitats in Panama to analyze the effect of coral presence in mangrove habitats on the fish assemblage. Our study revealed that CMC habitats harbor distinct fish assemblages compared to mangrove habitats without coral, with greater species richness and increased herbivore abundance.</p>
Global Mangrove Watch: Monthly Alerts of Mangrove Loss for Africa 2019--2022
<p>This results from a prototype change alert system (Bunting et al., 2023) that has been developed to identify mangrove losses on a monthly basis. Implemented on the Microsoft Planetary Computer, the Global Mangrove Watch v3.0 mangrove baseline extent map (<a href="https://doi.org/10.3390/rs14153657">Bunting et al., 2022</a>) for 2018 was refined and used to define the mangrove extent mask under which potential losses would be identified. The study period was 2018-2022 due to the availability of the Copernicus Sentinel-2 imagery used for the study. The alert system is based on optimised NDVI thresholds used to identify mangrove losses and a temporal scoring system used to filter false positives. The alert system was found to have an estimated overall accuracy of 92.1 %, with the alert commission and omission estimated to be 10.4 % and 20.6 %, respectively. The alert system is presently limited to Africa, where significant losses were identified in the study period, with 90 % of the loss alerts identified in Nigeria, Guinea-Bissau, Madagascar, Mozambique and Guinea. The drivers of those losses vary, with West Africa primarily driven by economic activities such as agricultural conversion and infrastructure development. At the same time, East Africa is dominated by climatic drivers, primarily storm frequency and intensity. Production of the monthly loss alerts for Africa will be continued as part of the wider Global Mangrove Watch project, and the spatial coverage is expected to be expanded over the coming months and years. Future updates of the mangrove loss alerts will be via the Global Mangrove Watch portal: <a href="https://www.globalmangrovewatch.org">https://www.globalmangrovewatch.org</a></p>
Exploring spatiotemporal dynamics of flower visitor association pattern on two Avicennia mangroves: A network approach
<p>All the data sets used in the analyses of this study are provided here along with the <strong>R-Script.</strong><br> The datasets for foraging behaviour and Generalized linear mixed models will be provided upon request to the first or corresponding author of this article.</p> <p><strong>Please note that, in this R-script, we have shown the codes only for one dataset of respective analyses.</strong><br> <strong>PLEASE NOTE: In this R-script, there are two minor mistakes, as follows:<br> 1) Line no. 46<br> Present code: </strong><strong>nulls <- nullmodel(I_S.network, N=1000, method=3) ##(3=Vaznull) ## file name mistake<br> Correct code: nulls <- nullmodel(AO_Site, N=1000, method=3) ##(3=Vaznull)</strong></p> <p><strong>2) Line no. 55<br> Present code: AO_Site_V<-AM_Site[,-1] ##Omitting individual coloumn(species) ## file name mistake<br> Correct code: AO_Site_V<-AO_Site[,-1] ##Omitting individual coloumn(species)</strong></p> <ul> <li><strong>Description of the data set</strong></li> </ul> <p>Data explorers the plant-flower visitor network with spatiotemporal approaches. Here, AM denotes <em>Avicennia marina </em>and AO denotes <em>Avicennia officinalis. </em>For the overall site-visitor network (combining all years and all time frames) datasets are AO_Site and AM_Site.</p> <p>For the overall visiting time-visitor network (combining all years and all sites) the datasets are AO_Time and AM_Time</p> <p>For the site-visitor networks on the yearly scale, the datasets are AO_2016, AO_2017, AO_2018, AM_2016, AM_2017 and AM_2018.</p> <p>For the site-specific visiting time-visitor networks the datasets are AO_Satjelia, AO_Bali, AO_Sagar, AO_Bakkhali, AM_Satjelia, AM_Bali, AM_Sagar and AM_Bakkhali.</p>
Extremely stochastic connectivity of island mangroves
Studies of mangrove population connectivity have focused primarily on global to regional scales and have suggested potential for long-distance connectivity, with archipelagos serving as stepping stones for trans-oceanic dispersal. However, the contribution of propagule dispersal to connectivity is still largely unknown, especially at local-scale. Identifying fine-scale propagule dispersal patterns unique to individual island systems is important to understand their contribution to global species distributions, and to select appropriate sizes and locations for mangrove conservation in archipelagos. Using population genetic methods and a release-recapture method employing GPS drifting buoys, we investigated the spatiotemporal scale of propagule dispersal of Rhizophora stylosa, one of the widely distributed mangrove species in the Indo-West Pacific. This study sought to quantify intra- and inter-island connectivity and to assess their contributions to oceanic scale dispersal of R. stylosa from the Ryukyu Archipelago, which spans over 545 km in southwestern Japan. Using 7 microsatellite markers, we tested 354 samples collected from 16 fringing populations on 4 islands. We identified 3 genetic populations, indicating distinct genetic structures comprising 3 distinguishable bioregions (genetic clusters). The western end of the archipelago receives relatively frequent migration (m &gt; 0.1), but is genetically isolated from other sites. Based on genetic migration rates, we found that the central area of the archipelago serves as a stepping stone for southwestward, but not northeastward dispersal. On the other hand, with in-situ drifting buoys, we did not confirm prevailing dispersal directionality within the archipelago, instead confirming local eddies. Some buoys trapped in those eddies demonstrated potential for successful beaching from another island. A large portion of buoys were carried predominantly northeastward by the Kuroshio Current and drifted away from the coastal areas into the Pacific, contrary to local migrations. We found that the spatiotemporal scale of propagule dispersal is limited by the distance between islands (&lt; 200km), propagule viability duration, and fecundity. Over all, recruitment does not occur frequently enough to unify the genetic structure in the archipelago, and the Ryukyu Archipelago is isolated in the center of the global mangrove distribution.
Dataset : Global mangrove root production and its controls
<p>This Dataset include root production reported in individual mangrove root production studies published until the 23 March 2022.</p> <p>Alongside of this data, it reports associated environmental data and metadata.</p> <p>For full methodology report to the methodology section of the article: "Global mangrove root production, its controls and roles in the blue carbon budget of mangroves" by Arnaud et al. 2023 (Global Change Biology).</p>
APPENDIX 1 in Vittaliana mangrovei Devadatha, Nikita, A.Baghela & V.V.Sarma, gen. nov, sp. nov. (Phaeosphaeriaceae), from mangroves near Pondicherry (India), based on morphology and multigene phylogeny
APPENDIX 1. — Complementary authorship for cited taxa
FIG. 1 in Vittaliana mangrovei Devadatha, Nikita, A.Baghela & V.V.Sarma, gen. nov, sp. nov. (Phaeosphaeriaceae), from mangroves near Pondicherry (India), based on morphology and multigene phylogeny
FIG. 1. — Continuation.
APPENDIX 1 in Vittaliana mangrovei Devadatha, Nikita, A.Baghela & V.V.Sarma, gen. nov, sp. nov. (Phaeosphaeriaceae), from mangroves near Pondicherry (India), based on morphology and multigene phylogeny
APPENDIX 1. — Continuation.
Large-scale changes in macrobenthic biodiversity driven by mangrove afforestation
<ol> <li><span>Large-scale anthropogenic mangroves have been constructed in coastal regions worldwide, but our understanding of their ecological effects is limited. In particular, the question of whether and how anthropogenic mangroves influence biodiversity patterns remains elusive.</span></li> <li><span>Here, we investigated the influence of large-scale anthropogenic mangroves on biodiversity patterns of mangrove macrobenthos. Specifically, we measure and seek to explain differences in species richness, abundance, assemblage composition, and distance-decay effect before and after the construction of anthropogenic mangroves.</span></li> <li><span>We surveyed assemblages of gastropod, bivalve and crab species over a wide latitudinal extent (24–28°N) in subtropical China. For each, we calculated species richness, abundance, assemblage composition, and distance-decay relationship before and after the construction of anthropogenic mangroves.</span></li> <li> <span>After the large-scale anthropogenic mangroves, we found species richness of gastropods, bivalves and crabs increased by 23.81%, 100% and 20%,</span> <span>respectively. The distance-decay effects of gastropods and bivalves decreased by 25% and 91.43%, while that of crabs remained virtually unchanged, indicating that large-scale monospecific planting changed spatial processes of macrobenthos (e.g., dispersal limitation). With mangrove plantation, compositional similarity of crab and bivalve assemblages increased by 28.57% and 38.46%, suggesting that large-scale monospecific planting exacerbates biotic homogenization. Altogether, these results indicate that large-scale anthropogenic habitats increase the diversity of mangrove macrobenthos and change taxonomic compositions by reducing distance-decay effects.</span> </li> <li> <em><span>Synthesis and applications</span></em><span>. We emphasize that afforestation of coastal wetlands can drive major changes in benthonic communities. Monitoring and assessing the ecological effects of the anthropogenic habitats for the presence of functional faunas will be important in determining the future coastal restoration and maintaining economic aquaculture. Quantifying those effects in terms of regional biodiversity composition enables management decisions about habitat restoration to be based upon macro-evidence rather than wishful thinking or untested intuition even or a one-sided local perspective.</span> </li> </ol>
Figure 3 in Biology of the oribatid mite Acrotritia clavata (Märkel, 1964) from the mangrove ecosystems of North Kerala, India
Figure 3. Acrotritia clavata (lateral view). A. Larva, B. Protonymph, C. Deutonymph, D. Tritonymph.
Fig. 8. A in Small carnivores (Mammalia: Carnivora) in the Wonorejo Mangroves, Jawa Timur, Indonesia: habitat use and activity patterns
Fig. 8. A, domestic cat on a dyke on 15 November 2018; B, activity pattern of the domestic cat.
Fig. 1 in Small carnivores (Mammalia: Carnivora) in the Wonorejo Mangroves, Jawa Timur, Indonesia: habitat use and activity patterns
Fig. 1. Map of the study area in Wonorejo Mangroves east of Surabaya, Jawa Timur, Indonesia.
Geographic distributions of mangrove gastropods
<p>Knowledge of the biogeography of marine taxa has lagged significantly behind terrestrial ecosystems. A hotspot of marine biodiversity associated with coral reefs is known in the Coral Triangle of the Indo-West Pacific, but until now there was little data with which to evaluate broad patterns of species richness in the coastal fauna of ecosystems other than coral reefs. This data is critically needed for fauna with low functional redundancy like that of mangroves, that are vulnerable to habitat loss and rising sea levels. Here we show that the diversity of mangrove fauna is characterized by two distinct hotspots in the Indo-West Pacific, associated with two habitat types: fringe mangroves in the Coral Triangle, and riverine mangroves in the Strait of Malacca, between the west coast of Peninsular Malaysia and Sumatra. This finding, based on a family of slugs of which the systematics has been completely revised, illustrates an unexpected biogeographic pattern that emerged only after this taxon was studied intensively. Most organisms that live in the mangrove forests of Southeast Asia remain poorly known both taxonomically and ecologically, and the hotspot of diversity of onchidiid slugs in the riverine mangroves of the Strait of Malacca indicates that further biodiversity studies are needed to support effective conservation of mangrove biodiversity.</p>
Impacts of hurricanes and disease on Diadema antillarum in shallow water reef and mangrove locations in St John, USVI
<p>Number of Diadema antillarum per 10x2 m2 transect at 9 reef sites and 3 mangrove sites in St John USVI from 2017-2023</p>
Data from: Hindcast-validated species distribution models reveal future vulnerabilities of mangroves and salt marsh species
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Data from: Divergence of vessel diameter explains interspecific variation in hydraulic safety to salinity in the Sundarbans mangrove ecosystem
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Data from: Hurricanes overcome migration lag and shape intraspecific genetic variation beyond a poleward mangrove range limit
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Satellite and LiDAR imagery for canopy height and NDVI estimation for mangroves in Puerto Rico
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A high-quality genome assembly and annotation of the gray mangrove, Avicennia marina
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.