Simulated Host-Parasite Networks for Sampling and Taxonomic Bias Analysis

Simulated host-parasite communities created for a 2022 ecology study. The data includes full communities and resampled versions affected by varying levels of host sampling completeness and parasite taxonomic resolution. The dataset was authored by Cristina Llopis‐Belenguer and colleagues.

Use Cases

• Assess the sensitivity of network metrics to incomplete host sampling based on simulated sampling completeness levels.
• Evaluate the impact of taxonomic uncertainty on ecological network structure based on simulated parasite resolution levels.
• Benchmark network analysis methods against controlled, simulated ecological communities.
• Study the interaction effects of sampling completeness and taxonomic resolution on network properties.

Strengths

• Data is structured for a controlled study on two specific bias sources: host sampling completeness and parasite taxonomic resolution.
• Simulated communities allow for systematic testing across defined gradients, from 90% to 10% for both completeness and resolution.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data is simulated, not observed from a real ecosystem, limiting direct ecological inference.

Provenance

Source

ETH Zurich

Collection Method

Simulated for a published research study.