Environmental DNA (eDNA) metabarcoding is a promising method to monitor species and community diversity that is rapid, affordable and non‐invasive. The longstanding needs of the eDNA community are modular informatics tools, comprehensive and customizable reference databases, flexibility across high‐throughput sequencing platforms, fast multilocus metabarcode processing and accurate taxonomic assignment. Improvements in bioinformatics tools make addressing each of these demands within a single toolkit a reality. The new modular metabarcode sequence toolkit Anacapa ( https://github.com/limey-bean/Anacapa/) addresses the above needs, allowing users to build comprehensive reference databases and assign taxonomy to raw multilocus metabarcode sequence data. A novel aspect of Anacapa is its database building module, “Creating Reference libraries Using eXisting tools” (CRUX), which generates comprehensive reference databases for specific user‐defined metabarcoding loci. The Quality Control and ASV Parsing module sorts and processes multiple metabarcoding loci and processes merged, unmerged and unpaired reads maximizing recovered diversity. DADA2 then detects amplicon sequence variants (ASVs) and the Anacapa Classifier module aligns these ASVs to CRUX‐generated reference databases using Bowtie2. Lastly, taxonomy is assigned to ASVs with confidence scores using a Bayesian Lowest Common Ancestor (BLCA) method. The Anacapa Toolkit also includes an r package, ranacapa, for automated results exploration through standard biodiversity statistical analysis. Benchmarking tests verify that the Anacapa Toolkit effectively and efficiently generates comprehensive reference databases that capture taxonomic diversity, and can assign taxonomy to both MiSeq and HiSeq‐length sequence data. We demonstrate the value of the Anacapa Toolkit in assigning taxonomy to seawater eDNA samples collected in southern California. The Anacapa Toolkit improves the functionality of eDNA and streamlines biodiversity assessment and management by generating metabarcode specific databases, processing multilocus data, retaining a larger proportion of sequencing reads and expanding non‐traditional eDNA targets. All the components of the Anacapa Toolkit are open and available in a virtual container to ease installation.

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.

A Biodiversity Composition Map of California Derived from Environmental DNA 33 Metabarcoding and Earth Observation 34Abstract 35 Unique ecosystems globally are under threat from ongoing anthropogenic environmental 36 change. Effective conservation management requires more thorough biodiversity surveys that 37can reveal system-level patterns and that can be applied rapidly across space and time. We offer 38 a way to use environmental DNA, community science and remote sensing together as methods to 39 reduce the discrepancy between the magnitude of change and historical approaches to measure it. 40Taking advantages of modern ecological models, we integrate environmental DNA and Earth 41 observations to evaluate regional biodiversity patterns for a snapshot of time, and provide critical 42 community-level characterization. We collected 278 samples in Spring 2017 from coastal, shrub 43 and lowland forest sites in California, a large-scale biodiversity hotspot. We applied gradient 44 forest to model 915 family occurrences and community composition together with environmental 45 variables and multi-scalar habitat classifications to produce a statewide biodiversity-based map. 46 16,118 taxonomic entries recovered were associated with environmental variables to test their 47 predictive strength on alpha, beta, and zeta diversity. Local habitat classification was diagnostic 48 of community composition, illuminating a characteristic of biodiversity hotspots. Using gradient 49 forest models, environmental variables predicted 35% of the variance in eDNA patterns at the 50 family level, with elevation, sand percentage, and greenness (NDVI32) as the top predictors. 51This predictive power was higher than we found in published literature at global scale. In 52 addition to this indication of substantial environmental filtering, we also found a positive 53 relationship between environmentally predicted families and their numbers of biotic interactions. 54In aggregate, these analyses showed that strong eDNA community-environment correlation is a 55 4 general characteristic of temperate ecosystems, and may explain why communities easily 56 destabilize under disturbances. Our study provides the first example of integrating citizen science 57 based eDNA with biodiversity mapping across the tree of life, with promises to produce large 58 scale, high resolution assessments that promote a more comprehensive and predictive 59 understanding of the factors that influence biodiversity and enhance its maintenance. 60