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<meta name="description" content="PhD Research Dashboard: Analyzing Climate Change Impacts on Coastal Ecosystems">
<meta name="keywords" content="climate change, coastal ecosystems, data visualization, PhD research, marine biology">
<meta name="author" content="PhD Researcher">
<title>Coastal Climate Research Dashboard</title>
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<span class="text-teal-400 font-bold text-xl">Coastal Research</span>
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<h1 class="text-4xl md:text-5xl font-bold mb-6 text-teal-400">Climate Change Impacts on Coastal Ecosystems</h1>
<p class="text-xl md:text-2xl text-gray-300 max-w-3xl mx-auto">
A PhD research project analyzing the effects of climate change on marine biodiversity, sea level rise, and coastal ecosystem health.
</p>
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Explore Data Visualizations
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<h2 class="text-3xl font-bold text-teal-400 mb-4">Interactive Data Visualizations</h2>
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Explore the key findings through interactive charts. Click on legend items to toggle data series.
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<!-- Sea Level Rise Chart -->
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<canvas id="seaLevelChart"></canvas>
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<p>Projected sea level rise based on satellite altimetry data and climate models.</p>
</div>
</div>
<!-- Species Diversity Chart -->
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<h3 class="text-xl font-semibold text-teal-300 mb-4">Species Diversity Across Coastal Regions</h3>
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<canvas id="speciesChart"></canvas>
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<p>Comparison of marine species diversity across five major coastal ecosystems.</p>
</div>
</div>
</div>
<!-- Temperature Anomalies vs Coral Bleaching Chart -->
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<h3 class="text-xl font-semibold text-teal-300 mb-4">Temperature Anomalies vs Coral Bleaching Events</h3>
<div class="chart-container">
<canvas id="bleachingChart"></canvas>
</div>
<div class="mt-4 text-sm text-gray-400">
<p>Relationship between ocean temperature anomalies and coral bleaching severity (2000-2023).</p>
</div>
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<h2 class="text-3xl font-bold text-teal-400 mb-4">Research Methodology</h2>
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Detailed explanation of the statistical models and data collection protocols.
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<!-- Markdown content will be rendered here by JavaScript -->
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<h2 class="text-3xl font-bold text-teal-400 mb-4">Publications</h2>
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Peer-reviewed research papers and conference presentations.
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<h3 class="text-xl font-semibold text-teal-300 mb-2">"Long-term impacts of sea level rise on coastal biodiversity"</h3>
<p class="text-gray-400 mb-2">Journal of Marine Ecology, 2023</p>
<p class="text-gray-300">This study examines the correlation between rising sea levels and changes in species distribution patterns across five coastal regions over a 25-year period.</p>
<a href="#" class="inline-block mt-3 text-teal-400 hover:text-teal-300">Read Full Paper →</a>
</div>
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<h3 class="text-xl font-semibold text-teal-300 mb-2">"ARIMA modeling of temperature anomalies in tropical coastal waters"</h3>
<p class="text-gray-400 mb-2">Climate Dynamics, 2022</p>
<p class="text-gray-300">Presents an autoregressive integrated moving average model for predicting ocean temperature anomalies and their ecological impacts.</p>
<a href="#" class="inline-block mt-3 text-teal-400 hover:text-teal-300">Read Full Paper →</a>
</div>
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<h3 class="text-xl font-semibold text-teal-300 mb-2">"Coral reef resilience under climate change scenarios"</h3>
<p class="text-gray-400 mb-2">Proceedings of the International Coral Reef Symposium, 2021</p>
<p class="text-gray-300">Analysis of coral bleaching events in relation to temperature anomalies and projections for future reef health under various climate scenarios.</p>
<a href="#" class="inline-block mt-3 text-teal-400 hover:text-teal-300">Read Full Paper →</a>
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For collaboration inquiries or additional information about this research.
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<script>
// Mobile menu toggle
document.getElementById('mobile-menu-button').addEventListener('click', function() {
const menu = document.getElementById('mobile-menu');
menu.classList.toggle('hidden');
});
// Sample data for charts
const seaLevelData = {
years: Array.from({length: 26}, (_, i) => 2000 + i),
levels: Array.from({length: 26}, (_, i) => {
const base = 50 + Math.random() * 10;
const trend = i * 1.5;
const variation = Math.sin(i / 3) * 2 + Math.random() * 1.5;
return base + trend + variation;
}),
projections: Array.from({length: 26}, (_, i) => {
if (i < 23) return null;
const base = 50 + Math.random() * 10;
const trend = i * 1.8;
const variation = Math.sin(i / 3) * 2 + Math.random() * 1.5;
return base + trend + variation;
})
};
const speciesData = {
regions: ['Great Barrier Reef', 'Gulf of Mexico', 'Mediterranean', 'Southeast Asia', 'Caribbean'],
diversity: [85, 72, 68, 91, 78],
change: [-12, -8, -5, -15, -10]
};
const bleachingData = {
anomalies: Array.from({length: 50}, () => Math.random() * 2.5),
bleaching: Array.from({length: 50}, (_, i) => {
const base = i < 25 ? Math.random() * 30 : 20 + Math.random() * 50;
return base * (1 + Math.random() * 0.3);
}),
years: Array.from({length: 50}, (_, i) => 2000 + Math.floor(i / 2))
};
// Initialize charts
document.addEventListener('DOMContentLoaded', function() {
// Sea Level Rise Chart
const seaLevelCtx = document.getElementById('seaLevelChart').getContext('2d');
const seaLevelChart = new Chart(seaLevelCtx, {
type: 'line',
data: {
labels: seaLevelData.years,
datasets: [
{
label: 'Observed Sea Level (mm)',
data: seaLevelData.levels,
borderColor: '#4fd1c5',
backgroundColor: 'rgba(79, 209, 197, 0.1)',
borderWidth: 2,
tension: 0.3,
fill: true
},
{
label: 'Projected Sea Level (mm)',
data: seaLevelData.projections,
borderColor: '#38b2ac',
backgroundColor: 'rgba(56, 178, 172, 0.1)',
borderWidth: 2,
borderDash: [5, 5],
tension: 0.3,
fill: true
}
]
},
options: {
responsive: true,
maintainAspectRatio: false,
plugins: {
legend: {
position: 'top',
labels: {
color: '#e2e8f0'
}
},
tooltip: {
mode: 'index',
intersect: false
}
},
scales: {
x: {
grid: {
color: 'rgba(74, 85, 104, 0.5)'
},
ticks: {
color: '#e2e8f0'
}
},
y: {
grid: {
color: 'rgba(74, 85, 104, 0.5)'
},
ticks: {
color: '#e2e8f0'
},
title: {
display: true,
text: 'Sea Level Change (mm)',
color: '#e2e8f0'
}
}
},
interaction: {
mode: 'nearest',
axis: 'x',
intersect: false
}
}
});
// Species Diversity Chart
const speciesCtx = document.getElementById('speciesChart').getContext('2d');
const speciesChart = new Chart(speciesCtx, {
type: 'bar',
data: {
labels: speciesData.regions,
datasets: [
{
label: 'Current Species Diversity Index',
data: speciesData.diversity,
backgroundColor: 'rgba(72, 187, 120, 0.7)',
borderColor: 'rgba(72, 187, 120, 1)',
borderWidth: 1
},
{
label: 'Change Since 2000 (%)',
data: speciesData.change,
backgroundColor: 'rgba(240, 101, 67, 0.7)',
borderColor: 'rgba(240, 101, 67, 1)',
borderWidth: 1,
type: 'line',
yAxisID: 'y1'
}
]
},
options: {
responsive: true,
maintainAspectRatio: false,
plugins: {
legend: {
position: 'top',
labels: {
color: '#e2e8f0'
}
}
},
scales: {
x: {
grid: {
color: 'rgba(74, 85, 104, 0.5)'
},
ticks: {
color: '#e2e8f0'
}
},
y: {
grid: {
color: 'rgba(74, 85, 104, 0.5)'
},
ticks: {
color: '#e2e8f0'
},
title: {
display: true,
text: 'Diversity Index',
color: '#e2e8f0'
}
},
y1: {
position: 'right',
grid: {
drawOnChartArea: false,
color: 'rgba(74, 85, 104, 0.5)'
},
ticks: {
color: '#e2e8f0'
},
title: {
display: true,
text: 'Change (%)',
color: '#e2e8f0'
}
}
}
}
});
// Bleaching Chart
const bleachingCtx = document.getElementById('bleachingChart').getContext('2d');
const bleachingChart = new Chart(bleachingCtx, {
type: 'scatter',
data: {
datasets: [{
label: 'Coral Bleaching Events',
data: bleachingData.anomalies.map((anomaly, i) => ({
x: anomaly,
y: bleachingData.bleaching[i],
r: 8,
year: bleachingData.years[i]
})),
backgroundColor: 'rgba(66, 153, 225, 0.7)',
borderColor: 'rgba(66, 153, 225, 1)',
borderWidth: 1
}]
},
options: {
responsive: true,
maintainAspectRatio: false,
plugins: {
legend: {
labels: {
color: '#e2e8f0'
}
},
tooltip: {
callbacks: {
label: function(context) {
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## Research Methodology Overview
This study employs a multi-disciplinary approach combining field observations, remote sensing data, and statistical modeling to analyze climate change impacts on coastal ecosystems.
### Data Collection
- **Sea Level Data**: Obtained from satellite altimetry (Jason-3, Sentinel-6) and tidal gauge stations
- **Biodiversity Surveys**: Conducted at 120 sites across five coastal regions (2015-2023)
- **Temperature Anomalies**: Calculated from NOAA's OISST dataset (1/4° resolution)
### Statistical Models
#### ARIMA for Time-Series Forecasting
We use AutoRegressive Integrated Moving Average (ARIMA) models to forecast sea level rise and temperature anomalies:
\`\`\`python
from statsmodels.tsa.arima.model import ARIMA
# Example ARIMA(1,1,1) model for sea level
model = ARIMA(sea_level_data, order=(1,1,1))
results = model.fit()
forecast = results.get_forecast(steps=36)
\`\`\`
Key parameters:
- p (autoregressive order): 1
- d (differencing order): 1
- q (moving average order): 1
#### Generalized Linear Models for Species Diversity
\`\`\`r
# GLM example in R
diversity_model <- glm(SpeciesCount ~ Temperature + Salinity + Year,
data = survey_data,
family = poisson(link = "log"))
\`\`\`
### Machine Learning Approaches
For coral bleaching prediction:
- Random Forest classifier (accuracy: 82%)
- XGBoost regression for severity estimation (R²: 0.76)
### Field Validation
All models are validated against:
1. Independent survey data
2. Historical records
3. Expert ecological assessments
`;
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