Genetic monitoring can help public agencies implement environmental laws

In the face of increasing threats to biodiversity, the advancement of methods for surveying biological communities is a major priority for ecologists. Recent advances in molecular biological technologies have made it possible to detect and sequence DNA from environmental samples (environmental DNA or eDNA); however, eDNA techniques have not yet seen widespread adoption as a routine method for biological surveillance primarily due to gaps in our understanding of the dynamics of eDNA in space and time. In order to identify the effective spatial scale of this approach in a dynamic marine environment, we collected marine surface water samples from transects ranging from the intertidal zone to four kilometers from shore. Using PCR primers that target a diverse assemblage of metazoans, we amplified a region of mitochondrial 16S rDNA from the samples and sequenced the products on an Illumina platform in order to detect communities and quantify their spatial patterns using a variety of statistical tools. We find evidence for multiple, discrete eDNA communities in this habitat, and show that these communities decrease in similarity as they become further apart. Offshore communities tend to be richer but less even than those inshore, though diversity was not spatially autocorrelated. Taxon-specific relative abundance coincided with our expectations of spatial distribution in taxa lacking a microscopic, pelagic life-history stage, though most of the taxa detected do not meet these criteria. Finally, we use carefully replicated laboratory procedures to show that laboratory treatments were remarkably similar in most cases, while allowing us to detect a faulty replicate, emphasizing the importance of replication to metabarcoding studies. While there is much work to be done before eDNA techniques can be confidently deployed as a standard method for ecological monitoring, this study serves as a first analysis of diversity at the fine spatial scales relevant to marine ecologists and confirms the promise of eDNA in dynamic environments.

Massively parallel sequencing is rapidly emerging as an efficient way to quantify biodiversity at all levels, from genetic variation and expression to ecological community assemblage. However, the number of reads produced per sequencing run far exceeds the number required per sample for many applications, compelling researchers to sequence multiple samples per run in order to maximize efficiency. For studies that include a PCR step, this can be accomplished using primers that include an index sequence allowing sample origin to be determined after sequencing. The use of indexed primers assumes they behave no differently than standard primers; however, we found that indexed primers cause substantial template sequence-specific bias, resulting in radically different profiles of the same environmental sample. Likely the outcome of differential amplification efficiency due to primer-template mismatch, two indexed primer sets spuriously change the inferred sequence abundance from the same DNA extraction by up to 77.1%. We demonstrate that a double PCR approach alleviates these effects in applications where indexed primers are necessary.

Environmental DNA (eDNA), genetic material recovered from an environmental medium such as soil, water, or feces, reflects the membership of the ecological community present in the sampled environment. As such, eDNA is a potentially rich source of data for basic ecology, conservation, and management, because it offers the prospect of quantitatively reconstructing whole ecological communities from easily obtained samples. However, like all sampling methods, eDNA sequencing is subject to methodological limitations that can generate biased descriptions of ecological communities. Here, we demonstrate parallels between eDNA sampling and traditional sampling techniques, and use these parallels to offer a statistical structure for framing the challenges faced by eDNA and for illuminating the gaps in our current knowledge. Although the current state of knowledge on some of these steps precludes a full estimate of biomass for each taxon in a sampled eDNA community, we provide a map that illustrates potential methods for bridging these gaps. Additionally, we use an original data set to estimate the relative abundances of taxon-specific template DNA prior to PCR, given the abundance of DNA sequences recovered post-PCR-and-sequencing, a critical step in the chain of eDNA inference. While we focus on the use of eDNA samples to determine the relative abundance of taxa within a community, our approach also applies to single-taxon applications (including applications using qPCR), studies of diversity, and studies focused on occurrence. By grounding inferences about eDNA community composition in a rigorous statistical framework, and by making these inferences explicit, we hope to improve the inferential potential for the emerging field of community-level eDNA analysis.

19Many fundamental properties of ecological systems and interactions are tied to body size, and a 20 related metric, the metabolic rate distribution, both within and across species. A previously 21proposed Maximum Entropy Theory of Ecology (METE) predicts numerous interrelated 22 macroecological patterns, including spatial distributions of individuals within species, abundance 23 distributions across species, species area relationships, and distributions of metabolic rates of all 24 individuals within a community. Extensive tests of METE's macroecological predictions 25 generally support the theory, but two related predictions have not been evaluated against full 26 community census data: the distribution of metabolic rates of individuals within species as a 27 function of the abundance of the species, and the distribution of average individual metabolic 28 rates across species. We test the metabolic predictions of METE for herbaceous plants in a 29 subalpine meadow and show that while this theory realistically predicts the distribution of 30 individual metabolic rates across the entire community, the within and across species predictions 31 generally fail. We also test the energy-equivalence type prediction that arises as a consequence 32 of the prediction for the distribution of average individual metabolic rates across species. We 33 suggest several possible explanations for the empirical deviations from theory, and distinguish 34 between the expected deviations caused by ecological disturbance and those deviations that 35 might be corrected within the theory. 36 37 Key words 38 metabolism, macroecology, scaling laws, Maximum Entropy Theory of Ecology, METE, 39 information entropy, energy equivalence 40 41 Erica A. Newman et al., 3 Introduction 42