Revisiting the effect of PCR replication and sequencing depth on biodiversity metrics in environmental DNA metabarcoding.

Environmental DNA (eDNA) metabarcoding is an increasingly popular tool for measuring and cataloguing biodiversity. Because the environments and substrates in which DNA is preserved differ considerably, eDNA research often requires bespoke approaches to generating eDNA data. Here, we explore how two experimental choices in eDNA study design-the number of PCR replicates and the depth of sequencing of PCR replicates-influence the composition and consistency of taxa recovered from eDNA extracts. We perform 24 PCR replicates from each of six soil samples using two of the most common metabarcodes for Fungi and Viridiplantae (ITS1 and ITS2), and sequence each replicate to an average depth of ~84,000 reads. We find that PCR replicates are broadly consistent in composition and relative abundance of dominant taxa, but that low abundance taxa are often unique to one or a few PCR replicates. Taxa observed in one out of 24 PCR replicates make up 21-29% of the total taxa detected. We also observe that sequencing depth or rarefaction influences alpha diversity and beta diversity estimates. Read sampling depth influences local contribution to beta diversity, placement in ordinations, and beta dispersion in ordinations. Our results suggest that, because common taxa drive some alpha diversity estimates, few PCR replicates and low read sampling depths may be sufficient for many biological applications of eDNA metabarcoding. However, because rare taxa are recovered stochastically, eDNA metabarcoding may never fully recover the true amplifiable alpha diversity in an eDNA extract. Rare taxa drive PCR replicate outliers of alpha and beta diversity and lead to dispersion differences at different read sampling depths. We conclude that researchers should consider the complexity and unevenness of a community when choosing analytical approaches, read sampling depths, and filtering thresholds to arrive at stable estimates.

Anti-racist interventions to transform ecology, evolution and conservation biology departments.

Racial and ethnic discrimination persist in science, technology, engineering and mathematics fields, including ecology, evolution and conservation biology (EECB) and related disciplines. Marginalization and oppression as a result of institutional and structural racism continue to create barriers to inclusion for Black people, Indigenous people and people of colour (BIPOC), and remnants of historic racist policies and pseudoscientific theories continue to plague these fields. Many academic EECB departments seek concrete ways to improve the climate and implement anti-racist policies in their teaching, training and research activities. We present a toolkit of evidence-based interventions for academic EECB departments to foster anti-racism in three areas: in the classroom; within research laboratories; and department wide. To spark restorative discussion and action in these areas, we summarize EECB's racist and ethnocentric histories, as well as current systemic problems that marginalize non-white groups. Finally, we present ways that EECB departments can collectively address shortcomings in equity and inclusion by implementing anti-racism, and provide a positive model for other departments and disciplines.

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

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.

Integrating archaeology and ancient DNA analysis to address invasive species colonization in the Gulf of Alaska.

The intentional and unintentional movement of plants and animals by humans has transformed ecosystems and landscapes globally. Assessing when and how a species was introduced are central to managing these transformed landscapes, particularly in island environments. In the Gulf of Alaska, there is considerable interest in the history of mammal introductions and rehabilitating Gulf of Alaska island environments by eradicating mammals classified as invasive species. The Arctic ground squirrel (Urocitellus parryii) is of concern because it affects vegetation and seabirds on Gulf of Alaska islands. This animal is assumed to have been introduced by historic settlers; however, ground squirrel remains in the prehistoric archaeological record of Chirikof Island, Alaska, challenge this timeline and suggest they colonized the islands long ago. We used 3 lines of evidence to address this problem: direct radiocarbon dating of archaeological squirrel remains; evidence of prehistoric human use of squirrels; and ancient DNA analysis of dated squirrel remains. Chirikof squirrels dated to at least 2000 years ago, and cut marks on squirrel bones suggested prehistoric use by people. Ancient squirrels also shared a mitochondrial haplotype with modern Chirikof squirrels. These results suggest that squirrels have been on Chirikof longer than previously assumed and that the current population of squirrels is closely related to the ancient population. Thus, it appears ground squirrels are not a recent, human-mediated introduction and may have colonized the island via a natural dispersal event or an ancient human translocation.