Spatiotemporal ecological filtering for metabarcoding (Apidae)

Knowledge graph centered on Spatiotemporal ecological filtering for metabarcoding (Apidae) with 37 nodes and 121 connections. Top connected: Bombus, Bombus terrestris, Bombus appositus, Bombus impatiens, B. appositus.

Method synopsis

A three-step approach that combines regional occurrence data, species distribution modeling, and phenological filtering to create targeted candidate species lists for improved metabarcoding accuracy.

Synthesized from method descriptions across 1 paper using this protocol.

Procedure as described in the canonical source

Steps below were extracted from the paper that introduces this protocol — Improving plant DNA metabarcoding accuracy with ecological filters and Angiosperms353: Field and pollen microscopy validation (2025), Applications in Plant Sciences. Implementations in other papers (listed below) may differ.

1. Generate regional plant taxa list
   Query the Botanical Information and Ecology Network (BIEN) database to identify plant species observed within the Southern Rockies ecoregion. Create a bounding box around the Gunnison County Level 3 ecoregion where the study site is located.
   Quantities: 1295 candidate plant species initially identifiedDuration: Not specifiedConditions: Not applicable
   Equipment: BIEN database, Geographic Information Systems software
2. Create species distribution models
   Construct SDMs using four commonly implemented algorithms: random forest, boosted regression trees, generalized linear models, and generalized additive models. Use 26 environmental variables at 30-m resolution. Remove highly collinear predictors using linear regression models. Evaluate accuracy using standard protocols.
   Quantities: 26 environmental variables, 4 SDM algorithms, 426 species after filteringDuration: Not specifiedConditions: 30-m resolution environmental data
   Equipment: R software, sdm R package
3. Apply temporal filtering
   Identify species with flowering phenologies overlapping pollen load collection dates using Weibull estimates of phenological parameters. Use herbarium records to estimate flowering periods, requiring more than 10 herbarium records per species. Calculate initiation, peak, and cessation dates for flowering.

Typical Equipment

• BIEN database
• R software
• sdm R package

Output Measurements

• candidate species lists
• spatial suitability scores
• flowering probability estimates

Papers Using This Protocol (1)

Species Studied With This Protocol