Journal Article

Landscape analyses using eDNA metabarcoding and Earth observation predict community biodiversity in California

Turba, Rachel, Rutledge, Kelsi, Fox, Emma A., Harrigan, Ryan J., Pentcheff, N. Dean, Garcia-Vedrenne, Ana E., Ruiz-Ramos, Dannise V., Schweizer, Teia M., Wetzer, Regina, Helman, Sarah K., Gold, Zack, Moore, Tiara N., Shapiro, Beth, Shirazi, Sabrina, Schneider, Fabian D., Lin, Meixi, Curd, Emily E., Wayne, Robert K., Ramos, Miroslava N. Munguia, Meyer, Rachel S., McTavish, Emily Jane, Osborne, Melisa G., Mejia, Maura Palacios, Dawson, Michael N., Marwayana, Onny, Simons, Ariel Levi

2021

Overview

Ecosystems globally are under threat from ongoing anthropogenic environmental change. Effective conservation management requires more thorough biodiversity surveys that can reveal system-level patterns and that can be applied rapidly across space and time. Using modern ecological models and community science, we integrate environmental DNA and Earth observations to produce a time snapshot of regional biodiversity patterns and provide multi-scalar community-level characterization. We collected 278 samples in spring 2017 from coastal, shrub, and lowland forest sites in California, a complex ecosystem and biodiversity hotspot. We recovered 16,118 taxonomic entries from eDNA analyses and compiled associated traditional observations and environmental data to assess how well they predicted alpha, beta, and zeta diversity. We found that local habitat classification was diagnostic of community composition and distinct communities and organisms in different kingdoms are predicted by different environmental variables. Nonetheless, gradient forest models of 915 families recovered by eDNA analysis and using BIOCLIM variables, Sentinel-2 satellite data, human impact, and topographical features as predictors, explained 35% of the variance in community turnover. Elevation, sand percentage, and photosynthetic activities (NDVI32) were the top predictors. In addition to this signal of environmental filtering, we found a positive relationship between environmentally predicted families and their numbers of biotic interactions, suggesting environmental change could have a disproportionate effect on community networks. Together, these analyses show that coupling eDNA with environmental predictors including remote sensing data has capacity to test proposed Essential Biodiversity Variables and create new landscape biodiversity baselines that span the tree of life.

• Publisher: John Wiley and Sons, Inc,Ecological Society of America
• Subject: anthropogenic activities / Anthropogenic factors / beta diversity / Biodiversity / Biodiversity hot spots / biomonitoring / California / citizen science / Community composition / community ecology / Community involvement / community structure / DNA barcoding / DNA Barcoding, Taxonomic / DNA, Environmental / ecological modeling / Ecological models / Ecosystem / ecosystems / Elevation / Environmental changes / Environmental DNA / Environmental management / Environmental Monitoring / gradient forest / habitats / Human impact / Human influences / Landscape / landscapes / lowland forests / Photosynthesis / Remote sensing / sand / shrubs / space and time / spring / variance / Wildlife conservation / zeta diversity