Methanogenesis has traditionally been assumed to occur only in anoxic environments, yet there is mounting, albeit indirect, evidence of methane (CH 4 ) production in oxic marine and freshwaters. Here we present the first direct, ecosystem-scale demonstration of methanogenesis in oxic lake waters. This methanogenesis appears to be driven by acetoclastic production, and is closely linked to algal dynamics. We show that oxic water methanogenesis is a significant component of the overall CH 4 budget in a small, shallow lake, and provide evidence that this pathway may be the main CH 4 source in large, deep lakes and open oceans. Our results challenge the current global understanding of aquatic CH 4 dynamics, and suggest a hitherto unestablished link between pelagic CH 4 emissions and surface-water primary production. This link may be particularly sensitive to widespread and increasing human influences on aquatic ecosystem primary productivity.

The use of eDNA to detect the presence/absence of rare or invasive species is well documented and its use in biodiversity monitoring is expanding. Preliminary laboratory research has also shown a positive correlation between the concentration of species‐specific eDNA particles and the density/biomass of a species in a given environment. However, the extent to which these results can be extended to natural environments has yet to be formally quantified. We collated data from experiments that examined the correlation between eDNA and two metrics of abundance (biomass and density) and, using mixed‐effects meta‐analysis, quantified the strength of that correlation across laboratory and natural environments. We found that eDNA particle concentration was more strongly correlated with abundance in laboratory environments compared to natural environments, accounting for approximately 82% and 57% of the observed variation in abundance, respectively. We found some evidence of potential publication bias that may have impacted the estimation of the correlation in natural environments; after smaller studies were removed from the dataset, eDNA particle concentration accounted for approximately 50% of the observed variation in abundance in natural environments. No effect of abundance metric was found on the strength of correlation between eDNA particle concentration and abundance. Despite a weaker general correlation in natural environments, eDNA concentration often still explained substantial variation in abundance. eDNA research is still an emergent field of study; with only moderate improvements in technology or technique, it could represent a powerful new tool for quantifying abundance.

Organism abundance is a critical parameter in ecology, but its estimation is often challenging.Approaches utilizing eDNA to indirectly estimate abundance have recently generated substantial interest. However, preliminary correlations observed between eDNA concentration and abundance in nature are typically moderate in strength with significant unexplained variation.Here we apply a novel approach to integrate allometric scaling coefficients into models of eDNA concentration and organism abundance. We hypothesize that eDNA particle production scales non-linearly with mass, with scaling coefficients < 1. Wild populations often exhibit substantial variation in individual body size distributions; we therefore predict that the distribution of mass across individuals within a population will influence population-level eDNA production rates. To test our hypothesis, we collected standardized body size distribution and mark-recapture abundance data using whole-lake experiments involving nine populations of brook trout. We correlated eDNA concentration with three metrics of abundance: density (individuals/ha), biomass (kg/ha), and allometrically scaled mass (ASM) (∑(individual mass 0.73 )/ha). Density and biomass were both significantly positively correlated with eDNA concentration (adj. R 2 = 0.59 and 0.63, respectively), but ASM exhibited improved model fit (adj. R 2 = 0.78). We also demonstrate how estimates of ASM derived from eDNA samples in 'unknown' systems can be converted to biomass or density estimates with additional size structure data. Future experiments should empirically validate allometric scaling coefficients for eDNA production, particularly where substantial intraspecific size distribution variation exists. Incorporating allometric scaling may improve predictive models to the extent that eDNA concentration may become a reliable

An experiment in >1000 river and riparian sites found spatial patterns and controls of carbon processing at the global scale.

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