Data Collection Requirements
Before using the SAVS tool: Gather comprehensive climate projections and natural history data for your target species and region. This preparation is essential for accurate vulnerability assessment.
Climate Change Scenarios
Required Climate Data (applies to all questions)
- Precipitation Changes: Total annual and seasonal precipitation projections
- Temperature Changes: Average temperatures (day and night), maximum summer temperatures, minimum winter temperatures
- Snow and Frost: Changes to snowpack duration and amount, number of frost days
- Extreme Events: Projected drought duration and frequency, flooding potential and timing
- Disturbances: Changes in frequency, severity, extent, or timing of:
- Fire disturbances
- Extreme weather events (storms, heat waves)
Natural History Data by Category
Habitat Data (Questions H1-H7)
- Habitat Types: Breeding and non-breeding habitats, vegetation type associations (H1, H2)
- Habitat Components: Specific components required for breeding and survival (H3, H4)
- Habitat Quality: Features associated with improved breeding success or survival (H5)
- Dispersal: Dispersal ability and sex-biased dispersal patterns (H6)
- Migration: Migration habits and requirements (H7)
- Climate Projections: Vegetation-specific climate projections including disturbance processes
Physiology Data (Questions PS1-PS6)
- Physiological Thresholds: Threshold or sensitivity to moisture or temperature extremes (Alternative: species range relative to area under assessment) (PS1)
- Sex Determination: Sex ratio/temperature relationships (some reptiles) (PS2)
- Weather Exposure: Potential exposure of species to extreme weather conditions, known cases of mortality or failed reproduction related to weather events (PS3)
- Activity Limitations: Climate or weather-mediated limitations to active periods (PS4)
- Metabolic Type: Endothermic or ectothermic classification (PS6)
- Life History Flexibility: Variable life history strategies, ability to postpone reproductive output (PS5)
Phenology Data (Questions PH1-PH4)
- Environmental Cues: Temperature or moisture variables used as cues for life activities (PH1)
- Critical Events: Events that need to be timed to coincide with reproduction/survival (insect emergence, etc.) (PH2)
- Cue-Resource Proximity: Proximity (temporal and geographical) of cues, activities, and essential resources (PH3)
- Breeding Frequency: Number of breeding attempts per year (PH4)
Biotic Interactions Data (Questions I1-I5)
- Food Resources: Identify primary food resources and expected changes to resources (I1)
- Predation: Identify primary predators and expected changes to predator populations (I2)
- Symbiosis: Identify symbionts and expected changes to symbiont populations (I3)
- Disease: Identify significant pathogen entities, disease risk factors, and expected changes to these issues (I4)
- Competition: Identify major competitors and expected changes to competitor populations (I5)
Data Collection Checklist
Before Starting Your Assessment:
- ✓ Define Target Region: Clearly define the geographic boundaries for your assessment
- ✓ Select Time Period: Choose appropriate time horizon for climate projections (typically 2050s or 2080s)
- ✓ Gather Climate Data: Collect all required climate change projections for your region
- ✓ Literature Review: Conduct comprehensive review of species natural history
- ✓ Expert Consultation: Identify and consult with species experts if needed
- ✓ Assess Data Quality: Evaluate confidence level in available information for uncertainty scoring
Data Sources and Tips
Climate Data Sources
- National Climate Services: NOAA, Environment Canada, Met Office, etc.
- Regional Climate Models: Downscaled projections for your study area
- Climate Portals: Climate Explorer, Climate Wizard, regional climate portals
- Scientific Literature: Published climate impact studies for your region
Natural History Data Sources
- Scientific Literature: Peer-reviewed papers on species ecology and life history
- Species Accounts: Comprehensive species accounts (e.g., Birds of North America)
- Field Guides: Regional field guides with ecological information
- Government Reports: Species status reports and recovery plans
- Expert Knowledge: Local biologists, researchers, and wildlife managers
- Museum Records: Specimen data and associated ecological information
- Citizen Science: eBird, iNaturalist, and other observation databases
Important Considerations
- Data Quality: Always note the quality and reliability of your data sources - this will inform your uncertainty scoring
- Geographic Scale: Ensure climate and species data match your assessment scale
- Temporal Alignment: Use climate projections that align with your assessment timeframe
- Knowledge Gaps: Document areas where information is limited - these may warrant further research
- Expert Validation: Consider having species experts review your data compilation
Common Challenges and Solutions
Limited Climate Data
Challenge: Detailed climate projections may not be available for your specific study area.
Solutions:
- Use data from nearest weather stations or grid cells
- Consult regional climate assessments
- Use broader regional trends as proxies
- Document uncertainty in your assessment
Sparse Natural History Data
Challenge: Limited published information on species ecology.
Solutions:
- Use data from closely related species
- Consult local experts and field biologists
- Use general ecological principles for the species' taxonomic group
- Mark high uncertainty for questions with limited data
Conflicting Information
Challenge: Different sources provide contradictory information.
Solutions:
- Prioritize peer-reviewed sources over grey literature
- Consider regional variation in species traits
- Use most recent and geographically relevant data
- Mark as "conflicting" in uncertainty assessment
Ready to Begin?
Once you've gathered the necessary data, you're ready to use the SAVS assessment tool. Remember that this assessment is only as good as the data that informs it - invest time in thorough data collection for the most reliable results.