Non-invasive real-time genomic monitoring of the critically endangered kākāpō

Tree of life metabarcoding can serve as a biotic benchmark for shifting baselines in urbanized estuaries

Urbanization of estuaries drastically changed existing shorelines and bathymetric contours, in turn modifying habitat for marine foundational species that host critical biodiversity. And yet we lack approaches to characterize a significant fraction of the biota that inhabit these ecosystems on time scales that align with rates of urbanization. Environmental DNA (or eDNA) metabarcoding that combines multiple assays targeting a broad range of taxonomic groups can provide a solution, but we need to determine whether the biological communities it detects ally with different habitats in these changing aquatic environments. In this study, we tested whether tree of life metabarcoding (ToL-metabarcoding) data extracted from filtered seawater samples correlated with four known geomorphic habitat zones across a heavily urbanized estuary (Sydney Harbour, Australia). Using this method, we substantially expanded our knowledge on the composition and spatial distribution of marine biodiversity across the tree of life in Sydney Harbour, particularly for organisms where existing records are sparse. Excluding terrestrial DNA inputs, we identified significant effects of both distance from the mouth of Sydney Harbour and geomorphic zone on biological community structure in the ToL-metabarcoding dataset (entire community), as well as in each of the taxonomic subgroups that we considered (fish, macroinvertebrates, algae and aquatic plants, bacteria). This effect appeared to be driven by taxa as a collective versus a few individual taxa, with each taxon explaining no more than 0.62% of the variation between geomorphic zones. Similarly, taxonomic richness was significantly higher within geomorphic zones with large sample sizes, but also decreased by 1% with each additional kilometer from the estuary mouth, a result consistent with a reduction in tidal inputs and available habitat in upper catchments. Based on these results, we suggest that ToL-metabarcoding can be used to benchmark biological monitoring in other urbanized estuaries globally, and in Sydney Harbour at future time points based on detection of bioindicators across the tree of life. We also suggest that robust biotic snapshots can be archived following extensive curation of taxonomic assignments that incorporates ecological affinities, supported by records from relevant and regional biodiversity repositories.

Optimised PCR assays for detecting elusive waterfowl from environmental DNA

For many aquatic and semiaquatic mammal, amphibian and fish species, environmental DNA (eDNA) methods are employed to detect species distribution and to monitor their presence, but eDNA is much less employed for avian species. Here, we developed primers for the detection of true geese and swan species using eDNA and optimised a PCR protocol for eDNA. We selected taiga bean goose (Anser fabalis fabalis) as our focal (sub)species and sampled water from lakes, from which the presence of taiga bean goose was visually confirmed. To test, if taiga bean goose DNA could be detected among DNA of other goose species, we similarly sampled eDNA from a zoo pond housing several Anatidae species. We were able to detect taiga bean goose DNA in all but one of the tested lakes, including the zoo pond. The primers developed are not species-specific, but rather specific to the genus Anser, due to the close relatedness of Anser species, which prevented the development of species-specific primers and the use of, for example, quantitative PCR. We also developed eDNA primers for Branta species and Cygnus species and tested these primers using the same samples. Canada goose (B. canadensis) and barnacle goose (B. leucopsis) DNA were only detected in the zoo pond (in which they were present), as the sampled natural lakes fall outside the range of these species. We detected whooper swan (C. cygnus) DNA in three lakes and the zoo pond (in which the species was present). The eDNA method presented here provides a potential means to monitor elusive goose species and to study the co-occurrence of large waterfowl.

TICI: a taxon-independent community index for eDNA-based ecological health assessment

Global biodiversity is declining at an ever-increasing rate. Yet effective policies to mitigate or reverse these declines require ecosystem condition data that are rarely available. Morphology-based bioassessment methods are difficult to scale, limited in scope, suffer prohibitive costs, require skilled taxonomists, and can be applied inconsistently between practitioners. Environmental DNA (eDNA) metabarcoding offers a powerful, reproducible and scalable solution that can survey across the tree-of-life with relatively low cost and minimal expertise for sample collection. However, there remains a need to condense the complex, multidimensional community information into simple, interpretable metrics of ecological health for environmental management purposes. We developed a riverine taxon-independent community index (TICI) that objectively assigns indicator values to amplicon sequence variants (ASVs), and significantly improves the statistical power and utility of eDNA-based bioassessments. The TICI model training step uses the Chessman iterative learning algorithm to assign health indicator scores to a large number of ASVs that are commonly encountered across a wide geographic range. New sites can then be evaluated for ecological health by averaging the indicator value of the ASVs present at the site. We trained a TICI model on an eDNA dataset from 53 well-studied riverine monitoring sites across New Zealand, each sampled with a high level of biological replication (n = 16). Eight short-amplicon metabarcoding assays were used to generate data from a broad taxonomic range, including bacteria, microeukaryotes, fungi, plants, and animals. Site-specific TICI scores were strongly correlated with historical stream condition scores from macroinvertebrate assessments (macroinvertebrate community index or MCI; R2 = 0.82), and TICI variation between sample replicates was minimal (CV = 0.013). Taken together, this demonstrates the potential for taxon-independent eDNA analysis to provide a reliable, robust and low-cost assessment of ecological health that is accessible to environmental managers, decision makers, and the wider community.

How Can Genomics Help or Hinder Wildlife Conservation?

Genomic data are becoming increasingly affordable and easy to collect, and new tools for their analysis are appearing rapidly. Conservation biologists are interested in using this information to assist in management and planning but are typically limited financially and by the lack of genomic resources available for non-model taxa. It is therefore important to be aware of the pitfalls as well as the benefits of applying genomic approaches. Here, we highlight recent methods aimed at standardizing population assessments of genetic variation, inbreeding, and forms of genetic load and methods that help identify past and ongoing patterns of genetic interchange between populations, including those subjected to recent disturbance. We emphasize challenges in applying some of these methods and the need for adequate bioinformatic support. We also consider the promises and challenges of applying genomic approaches to understand adaptive changes in natural populations to predict their future adaptive capacity.

Nuclear environmental DNA resolves fine-scale population genetic structure in an aquatic habitat

There is considerable potential for nuclear genomic material in environmental DNA (eDNA) to inform us of population genetic structure within aquatic species. We tested if nuclear allelic composition data sourced from eDNA can resolve fine scale spatial genetic structure of the cichlid fish Astatotilapia calliptera in Lake Masoko, Tanzania. In this ∼35 m deep crater lake the species is diverging into two genetically distinguishable ecomorphs, separated by a thermo-oxycline at ∼15 m that divides biologically distinct water masses. We quantified population genetic structure along a depth transect using single nucleotide polymorphisms (SNPs) derived from genome sequencing of 530 individuals. This population genetic structure was reflected in a focal set of SNPs that were also reliably amplified from eDNA - with allele frequencies derived from eDNA reflecting those of fish within each depth zone. Thus, by targeting known genetic variation between populations within aquatic eDNA, we measured genetic structure within the focal species.