orchamp

orchamp monitors biodiversity and ecosystem functions across elevational gradients in the French Alps and Pyrenees using botanical surveys, environmental DNA (eDNA), remote sensing, and video and acoustic sensors, and applies data integration, statistical analyses, visualization, and AI-based processing to assess impacts of climate change, land-use change, and pollution.

Key Features:

• Geographic focus: Monitoring centered on natural elevational gradients in the French Alps and Pyrenees.
• Botanical surveys: Traditional field sampling for vegetation and community composition assessments.
• Environmental DNA (eDNA): Molecular detection of species presence without direct observation.
• Remote sensing: Large-scale environmental monitoring using airborne or satellite data.
• Video and acoustic sensors: Continuous monitoring of wildlife activity and behavior.
• Data integration: Combining diverse data sources into a cohesive analytical framework.
• Statistical analyses: Application of robust statistical methods to interpret complex datasets.
• Visualization tools: Creation of graphical representations to display data trends.
• AI-based processing: Automated data processing and predictive modeling for forecasting impacts.

Scientific Applications:

• Biodiversity monitoring: Tracking species presence and community changes across elevational gradients.
• Ecosystem function assessment: Investigating responses of ecosystem services to environmental pressures.
• Impact assessment: Evaluating effects of climate change, land-use change, and pollution on biodiversity.
• Species detection and mapping: Using eDNA, video, and acoustic data to detect and map species distributions.
• Landscape-scale monitoring: Employing remote sensing to observe large-scale environmental change.
• Forecasting: Using AI-based analyses to predict future biodiversity and ecosystem responses.

Methodology:

Data integration, statistical analyses, visualization tools, and AI-based processing are applied to synthesize and analyze the diverse datasets generated by botanical surveys, eDNA sampling, remote sensing, and video and acoustic sensors.