Species Richness Estimation
Estimate true species richness from sample data.
Overview
Observed species counts are almost always underestimates of true richness. FieldEco provides several estimators to predict actual species numbers from your samples.
Why Estimate Richness?
Problem: You observed 50 species, but how many are actually present?
Solution: Statistical estimators predict unobserved species based on:
- Rare species patterns
- Accumulation rates
- Sample coverage
Chao1 Estimator
Non-parametric estimator using singleton/doubleton counts.
Formula
S_Chao1 = S_obs + (f1² / 2f2)
Where:
- S_obs = observed species
- f1 = singletons (species with 1 individual)
- f2 = doubletons (species with 2 individuals)
When to Use
- Abundance data available
- Many rare species expected
- Moderate sample sizes
Interpretation
- Provides minimum estimate
- More singletons → more undetected species
- If f2 = 0, uses modified formula
Chao2 Estimator
For incidence (presence/absence) data across samples.
Formula
S_Chao2 = S_obs + (Q1² / 2Q2)
Where:
- Q1 = uniques (species in 1 sample only)
- Q2 = duplicates (species in 2 samples)
When to Use
- Multiple samples/plots
- Only presence/absence data
- Replicated sampling
Jackknife Estimators
Resampling-based approaches.
First-Order Jackknife
S_Jack1 = S_obs + f1(n-1)/n
Second-Order Jackknife
S_Jack2 = S_obs + [f1(2n-3)/n] - [f2(n-2)²/(n(n-1))]
Characteristics
- Less bias than Chao
- Higher variance
- More conservative estimates
Bootstrap Estimator
Uses resampling to estimate richness.
Characteristics
- Moderate bias
- Lower variance than Jackknife
- Good for moderate sample sizes
Species Accumulation Curves
Visualize sampling completeness.
What It Shows
- Species discovered vs. sampling effort
- Approaching asymptote = sampling complete
- Steep curve = more species to find
Interpretation
| Curve Shape | Meaning |
|---|---|
| Steep, rising | Many species remain |
| Leveling off | Approaching complete |
| Flat | Sampling likely complete |
Sample Coverage
Proportion of community sampled.
Coverage Definition
C = 1 - (f1 / n)
Where n = total individuals
Interpretation
| Coverage | Meaning |
|---|---|
| <50% | Inadequate sampling |
| 50-80% | Moderate coverage |
| >80% | Good coverage |
| >95% | Excellent coverage |
Using Analysis in FieldEco
Running Analysis
- Open completed survey(s)
- Tap Analysis
- Select Species Richness
- View estimators and curve
Results Include
- All estimator values
- Standard errors
- Accumulation curve
- Coverage estimate
Choosing an Estimator
| Data Type | Recommended |
|---|---|
| Abundance data | Chao1 |
| Presence/absence | Chao2 |
| Conservative estimate | Jackknife2 |
| Moderate approach | Bootstrap |
Best Practices
Sampling
- Use consistent effort
- Multiple samples improve estimates
- Record singletons carefully
Reporting
- Report observed AND estimated
- Include confidence intervals
- Note estimator used
- Describe sampling effort
Related Documentation
- Diversity Indices - Diversity metrics
- Checklist Survey - Data collection
- Quadrat Survey - Plot-based data