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Summary 1.Community genetics studies frequently focus on individual communities associated with individual plant genotypes, but little is known about the genetically based relationships among taxonomically and spatially disparate communities. We integrate studies of a wide range of communities living on the same plant genotypes to understand how the ecological and evolutionary dynamics of one community may be constrained or modulated by its underlying genetic connections to another community. 2. We use pre-existing data sets collected from Populus angustifolia (narrowleaf cottonwood) growing in a common garden to test the hypothesis that the composition of pairs of distinct communities (e.g. endophytes, pathogens, lichens, arthropods, soil microbes) covary across tree genotypes, such that individual plant genotypes that support a unique composition of one community are more likely to support a unique composition of another community. We then evaluate the hypotheses that physical proximity, taxonomic similarity, time between sampling (time attenuation), and interacting foundation species within communities explain the strength of correlations. 3. Three main results emerged. First, Mantel tests between communities revealed moderate to strong (q = 0.25-0.85) community-genetic correlations in almost half of the comparisons; correlations among phyllosphere endophyte, pathogen and arthropod communities were the most robust. Secondly, physical proximity determined the strength of community-genetic correlations, supporting a physical proximity hypothesis. Thirdly, consistent with the interacting foundation species hypothesis, the most abundant species drove many of the stronger correlations. Other hypotheses were not supported. 4. Synthesis. The field of community genetics demonstrates that the structure of communities varies among plant genotypes; our results add to this field by showing that disparate communities covary among plant genotypes. Eco-evolutionary dynamics between plants and their associated organisms may therefore be mediated by the shared connections of different communities to plant genotype, indicating that the organization of biodiversity in this system is genetically based and non-neutral.

Labile carbon (C) input to soil can accelerate or slow the decomposition of soil organic matter, a phenomenon called priming. However, priming is difficult to predict, making its relationship with C input elusive. To assess this relationship, we added 13 C-glucose at five levels (8 to 1606 μg C g-1 soil week-1) to the soil from four different ecosystems for seven weeks. We observed a positive linear relationship between C input and priming in all soils: priming increased from negative or no priming at low C input to strong positive priming at high C input. However, the sensitivity of priming to C input varied among soils and between ways of expressing C input, and decreased with elevation. Positive substrate thresholds were detected in three soils (56 to 242

Leaf litter decomposition plays a major role in nutrient dynamics in forested streams. The chemical composition of litter affects its processing by microorganisms, which obtain nutrients from litter and from the water column. The balance of these fluxes is not well known, because they occur simultaneously and thus are difficult to quantify separately. Here, we examined C and N flow from streamwater and leaf litter to microbial biofilms during decomposition. We used isotopically enriched leaves ((13)C and (15)N) from two riparian foundation tree species: fast-decomposing Populus fremontii and slow-decomposing Populus angustifolia, which differed in their concentration of recalcitrant compounds. We adapted the isotope pool dilution method to estimate gross elemental fluxes into litter microbes. Three key findings emerged: litter type strongly affected biomass and stoichiometry of microbial assemblages growing on litter; the proportion of C and N in microorganisms derived from the streamwater, as opposed to the litter, did not differ between litter types, but increased throughout decomposition; gross immobilization of N from the streamwater was higher for P. fremontii compared to P. angustifolia, probably as a consequence of the higher microbial biomass on P. fremontii. In contrast, gross immobilization of C from the streamwater was higher for P. angustifolia, suggesting that dissolved organic C in streamwater was used as an additional energy source by microbial assemblages growing on slow-decomposing litter. These results indicate that biofilms on decomposing litter have specific element requirements driven by litter characteristics, which might have implications for whole-stream nutrient retention.

The complexity and natural variability of ecosystems present a challenge for reliable detection of change due to anthropogenic influences. This issue is exacerbated by necessary trade-offs that reduce the quality and resolution of survey data for assessments at large scales. The Peace–Athabasca Delta (PAD) is a large inland wetland complex in northern Alberta, Canada. Despite its geographic isolation, the PAD is threatened by encroachment of oil sands mining in the Athabasca watershed and hydroelectric dams in the Peace watershed. Methods capable of reliably detecting changes in ecosystem health are needed to evaluate and manage risks. Between 2011 and 2016, aquatic macroinvertebrates were sampled across a gradient of wetland flood frequency, applying both microscope-based morphological identification and DNA metabarcoding. By using multispecies occupancy models, we demonstrate that DNA metabarcoding detected a much broader range of taxa and more taxa per sample compared to traditional morphological identification and was essential to identifying significant responses to flood and thermal regimes. We show that family-level occupancy masks high variation among genera and quantify the bias of barcoding primers on the probability of detection in a natural community. Interestingly, patterns of community assembly were nearly random, suggesting a strong role of stochasticity in the dynamics of the metacommunity. This variability seriously compromises effective monitoring at local scales but also reflects resilience to hydrological and thermal variability. Nevertheless, simulations showed the greater efficiency of metabarcoding, particularly at a finer taxonomic resolution, provided the statistical power needed to detect change at the landscape scale.

Litter decomposition plays a key role in ecosystem nutrients cycling, yet, to date science is lacking a comprehensive understanding of the non-additive effect in mixing litter decomposition.In order to fill that gap, we compiled 69 individual studies for the purpose of performing two sub-meta-analyses on the non-additive effect.Our results show that a significantly synergistic effect occurs at global scale with the average increase by 2-4% in litter mixture decomposition; In particular, low-quality litter in mixture shows a significantly synergistic effect, while no significant change is observed with high-quality species. Additionally, the synergistic effect turns into the antagonistic effect when soil fauna is absent or litter decomposition enters into humus-near stage. In contrast to temperate and tropical areas, studies in frigid area also show a significantly antagonistic effect.Our meta-analysis provides a systematic evaluation of the non-additive effect in decomposition mixed litters, which is critical for understanding and improving the carbon forecasts and nutrient dynamics.

Classical biomonitoring techniques have focused primarily on measures linked to various biodiversity metrics and indicator species. Next-generation biomonitoring (NGB) describes a suite of tools and approaches that allow the examination of a broader spectrum of organizational levels-from genes to entire ecosystems. Here, we frame 10 key questions that we envisage will drive the field of NGB over the next decade. While Makiola et al. Questions for Next-Generation Biomonitoring not exhaustive, this list covers most of the key challenges facing NGB, and provides the basis of the next steps for research and implementation in this field. These questions have been grouped into current-and outlook-related categories, corresponding to the organization of this paper.

Environmental DNA (eDNA) metabarcoding is an increasingly popular method for rapid biodiversity assessment. As with any ecological survey, false negatives can arise during sampling and, if unaccounted for, lead to biased results and potentially misdiagnosed environmental assessments. We developed a multi-scale, multi-species occupancy model for the analysis of community biodiversity data resulting from eDNA metabarcoding; this model accounts for imperfect detection and additional sources of environmental and experimental variation. We present methods for model assessment and model comparison and demonstrate how these tools improve the inferential power of eDNA metabarcoding data using a case study in a coastal, marine environment. Using occupancy models to account for factors often overlooked in the analysis of eDNA metabarcoding data will dramatically improve ecological inference, sampling design, and methodologies, empowering practitioners with an approach to wield the high-resolution biodiversity data of next-generation sequencing platforms. OPEN ACCESS Citation: McClenaghan B, Compson ZG, Hajibabaei M (2020) Validating metabarcoding-based biodiversity assessments with multi-species occupancy models: A case study using coastal marine eDNA. PLoS ONE 15(3): e0224119. https://