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348 results for “seagrass”
Seagrass and tiger shark data
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Data from: Are macroalgal blooms necessarily bad? Nutrient impacts on seagrass in upwelling-influenced estuaries
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First field-based evidence that the seagrass-lucinid mutualism can mitigate sulfide stress in seagrasses
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Data from: Low-canopy seagrass beds still provide important coastal protection services
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Data from: The thin(ning) green line? Investigating changes in Kenya’s seagrass coverage
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Data from: Latitudinal variation in seagrass herbivory: global patterns and explanatory mechanisms
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Data from: Population structure and gene flow of the tropical seagrass, Syringodium filiforme, in the Florida Keys and subtropical Atlantic region
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Data from: Consensus forecasting of intertidal seagrass habitat in the Wadden Sea
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Data from: Spatiotemporal variability in the structure of seagrass meadows and associated macrofaunal assemblages in southwest England (UK): using citizen science to benchmark ecological pattern
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Data from: Seagrass on the brink: decline of threatened seagrass Posidonia australis continues following protection
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Experimental evidence root-associated microbes mediate seagrass response to environmental stress
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Data from: Biogeographical scenarios modulate seagrass resistance to small-scale perturbations
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Data from: Should we sync? Seascape-level genetic and ecological factors determine seagrass flowering patterns
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Data from: Tampa Bay (Florida, USA): documenting seagrass recovery since the 1980’s and reviewing the benefits
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Data from: Phylogeographic differentiation versus transcriptomic adaptation to warm temperatures in Zostera marina, a globally important seagrass
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Data from: Comparison of macro-molluscan assemblages in a protected and a non-protected tropical seagrass ecosystem
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Data from: Beyond a single patch: local and regional processes explain diversity patterns in a seagrass epifaunal metacommunity
<p>Ecological communities are jointly structured by dispersal, density-independent responses to environmental conditions and density-dependent biotic interactions. Metacommunity ecology provides a framework for understanding how these processes combine to determine community seagrass meadows along the British Columbia coast, we tested the hypothesis that eelgrass (<i>Zostera marina</i> L.) epifaunal invertebrate assemblages are influenced by local environmental conditions, but that high dispersal rates at larger spatial scales dampen effects of environmental differences. We used hierarchical joint species distribution modelling to understand the contribution of environmental conditions, spatial distance between meadows, and species co-occurrences to epifaunal invertebrate abundance and distribution across the region. We found that patterns of taxonomic compositional similarity among meadows were inconsistent with dispersal limitation, and meadows in the same region were often no more similar to each other than meadows over 1000 km away. Abiotic environmental conditions (temperature, dissolved oxygen) explained a small fraction of variation in taxonomic abundances patterns across the region. We found novel co-occurrence patterns among taxa that could not be explained by shared responses to environmental gradients, suggesting the possibility that interspecific interactions influence seagrass invertebrate abundance and distribution. Our results suggest that biodiversity and ecosystem functions provided by seagrass meadows reflect ecological processes occurring both within meadows and across seascapes, and that management of eelgrass habitat for biodiversity may be most effective when both local and regional processes are considered.</p>
Methane emission and sulfide levels increase in tropical seagrass sediments during temperature stress: a mesocosm experiment
<p>Climate change-induced ocean warming is expected to greatly affect carbon dynamics and sequestration in vegetated shallow waters, especially in the upper subtidal where water temperatures may fluctuate considerably and can reach high levels at low tides. This might alter the greenhouse gas balance and significantly reduce the carbon sink potential of tropical seagrass meadows. In order to assess such consequences, we simulated temperature stress during low tide exposures by subjecting seagrass plants (<i>Thalassia hemprichii</i>) and associated sediments to elevated midday temperature spikes (31, 35, 37, 40 and 45ºC) for seven consecutive days in an outdoor mesocosm setup. During the experiment, methane release from the sediment surface was estimated using gas chromatography. Sulfide concentration in the sediment pore water was determined spectrophotometrically, and the plant's photosynthetic capacity as Electron Transport Rate (ETR) and maximum quantum yield (Fv/Fm) was assessed using pulse-amplitude modulated (PAM) fluorometry. The highest temperature treatments (40 and 45ºC) had a clear positive effect on methane emission and the level of sulfide in the sediment and, at the same time, clear negative effects on the photosynthetic performance of seagrass plants. The effects observed by temperature stress were immediate (within hours) and seen in all response variables, including ETR, Fv/Fm, methane emission and sulfide levels. In addition, both the methane emission and the size of the sulfide pool were already negatively correlated to changes in the photosynthetic rate (ETR) during the first day, and with time, the correlations became stronger. These findings show that increased temperature will reduce primary productivity and increase methane and sulfide levels. Future increases in the frequency and severity of extreme temperature events could hence reduce the climate mitigation capacity of tropical seagrass meadows by reducing CO<sub>2</sub> sequestration, increase damage from sulfide toxicity, and induce the release of larger amounts of methane.</p>
Data from: Analysing the dynamics and relative influence of variables affecting ecosystem responses using functional PCA and boosted trees: a seagrass case study
1. Understanding the relative influence of variables on ecosystem responses and the dynamics of their effect is necessary for effective ecosystem monitoring and management. Also known as causal pathways anlaysis, we develop an approach using functional Principal Components Analysis (fPCA) and machine learning within a scenario analysis framework. 2. fPCA is used to identify most influential variables for correlated, non-homogenoeus and non-linear time series data characteristic of complex ecosystems. Hierarchical clustering of fPCA scores reveals groups of more homogeneous scenarios and similarly influential variables. The resultant subset of variables helps to overcome model identifiability problems when analysing time-lagged effects using Boosted Regression Trees (BRT). 3. We use simulated data generated by a Dynamic Bayesian Network (DBN) of ecological windows for seagrass ecosystems given dredging stressors; 3024 scenarios with 75 state variables are analysed. The BRT demonstrated a high level of fit ((R^2≈0.97,MSE≈0.16), supporting the validity of influential variables identified by fPCA. Influential variables identified included genus, location type, light, growth and seed. Six consecutive months of positive growth and adequate light were important for predicting states of high or moderate population. 4. Compared to traditional scenario analysis and sensitivity analysis approaches, our approach simultaneously enabled capture of n-way interactions while accounting for time correlations. Although some variables and their dynamics agreed with existing knowledge, new variables and/or time lags of their effects were identified, corresponding to opportunities for further investigation as well as informing monitoring and management. Although our method was demonstrated on state variables with DBN simulated data, it is equally applicable to general time series data.
Data from: Range-edge genetic diversity: locally poor extant southern patches maintain a regionally diverse hotspot in the seagrass Zostera marina
Refugial populations at the rear edge are predicted to contain higher genetic diversity than those resulting from expansion, such as in post-glacial recolonizations. However, peripheral populations are also predicted to have decreased diversity compared to the center of a species' distribution. We aim to test these predictions by comparing genetic diversity in populations at the limits of distribution of the seagrass Zostera marina, with populations in the species' previously described central diversity 'hotspot'. Zostera marina populations show decreased allelic richness, heterozygosity and genotypic richness in both the 'rear' edge and the 'leading' edge compared to the diversity 'hotspot' in the North Sea / Baltic region. However, when populations are pooled, genetic diversity at the southern range is as high as in the North Sea / Baltic region while the 'leading edge' remains low in genetic diversity. The decreased genetic diversity in these Southern Iberia populations compared to more central populations is possibly the effect of drift due to small effective population size, as a result of reduced habitat, low sexual reproduction and low gene flow. However, when considering the whole southern edge of distribution rather than per population, diversity is as high as in the central 'hotspot' in the North Sea / Baltic region. We conclude that diversity patterns assessed per population can mask the real regional richness that is typical of rear edge populations, which have played a key role in the species biogeographic history and as marginal diversity hotspots have very high conservation value.
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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.