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    Reply to: Do not downplay biodiversity loss

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    Reply to: Emphasizing declining populations in the Living Planet Report

    Department of Biology, McGill University, Montreal, Quebec, CanadaBrian Leung & Anna L. HargreavesBieler School of Environment, McGill University, Montreal, Quebec, CanadaBrian LeungDepartment of Biological Sciences, Simon Fraser University, Burnaby, British Columbia, CanadaDan A. GreenbergSchool of Biology and Ecology and Mitchell Center for Sustainability Solutions, University of Maine, Orono, ME, USABrian McGillCentre for Biological Diversity, University of St Andrews, St Andrews, UKMaria DornelasIndicators and Assessments Unit, Institute of Zoology, Zoological Society of London, London, UKRobin FreemanB.L. wrote the response. A.C.H. and D.A.G. helped with writing, editing and discussing ideas. B.M. and M.D. discussed ideas with some editing. R.F. contributed discussions to the original manuscript2. More

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    Reply to: The Living Planet Index does not measure abundance

    Department of Biology, McGill University, Montreal, Quebec, CanadaBrian Leung & Anna L. HargreavesBieler School of Environment, McGill University, Montreal, Quebec, CanadaBrian LeungDepartment of Biological Sciences, Simon Fraser University, Burnaby, British Columbia, CanadaDan A. GreenbergSchool of Biology and Ecology and Mitchell Center for Sustainability Solutions, University of Maine, Orono, ME, USABrian McGillCentre for Biological Diversity, University of St Andrews, St Andrews, UKMaria DornelasIndicators and Assessments Unit, Institute of Zoology, Zoological Society of London, London, UKRobin FreemanB.L. wrote the response. A.L.H. and D.A.G. helped with writing, editing and discussing ideas. B.M., M.D. and R.F. discussed ideas and did some editing. More

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    Reply to: Shifting baselines and biodiversity success stories

    Cite this articleLeung, B., Hargreaves, A.L., Greenberg, D.A. et al. Reply to: Shifting baselines and biodiversity success stories.
    Nature 601, E19 (2022). https://doi.org/10.1038/s41586-021-03749-zDownload citationPublished: 26 January 2022Issue Date: 27 January 2022DOI: https://doi.org/10.1038/s41586-021-03749-zShare this articleAnyone you share the following link with will be able to read this content:Get shareable linkSorry, a shareable link is not currently available for this article.Copy to clipboard
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    Do not downplay biodiversity loss

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    DNA metabarcoding suggests dietary niche partitioning in the Adriatic European hake

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    Rare and localized events stabilize microbial community composition and patterns of spatial self-organization in a fluctuating environment

    Effects of environmental fluctuations on co-culture composition and intermixingWe first tested the effects of fluctuations between anoxic (inducing a mutualistic interaction) and oxic (inducing a competitive interaction) conditions on co-culture composition (quantified as the ratio of consumer-to-producer at the expansion edge) and interspecific mixing (quantified as the number of interspecific boundaries divided by the colony circumference). We expected that, over a series of anoxic/oxic transitions, the ratio of consumer-to-producer at the expansion edge and the degree of intermixing would both decrease (Fig. 1d). To test this, we performed range expansions where we transitioned the environment between anoxic and oxic conditions. While we performed the experiments with defined anoxic and oxic incubation times, our main prediction (i.e., that repeated transitions between anoxic and oxic conditions can induce irreversible pattern transitions that alter co-culture composition and functioning) is independent of the time spent under either of those conditions as far as cells can adjust their metabolism to the new environment (Fig. 1d).As expected, the ratio of consumer-to-producer and the intermixing index both decreased over the series of anoxic/oxic transitions (Fig. 2a, b). The changes in these quantities appear to have two distinct dynamic phases; a first phase with a relatively steep decay and a second phase with a shallower decay. We therefore modeled their dynamics using a two-phase linear regression model [53,54,55]. During the first phase, the ratio of consumer-to-producer decreased significantly more rapidly at pH 7.5 (r2 = 0.90, p = 2 × 10−9, coeff = −0.0374, 95% CI = [−0.038, −0.0368]) than at 6.5 (r2 = 0.94, p = 1 × 10−7, coeff = −0.0103, 95% CI = [−0.0108, −0.0097]) (Fig. 2a). We observed consistent results for the intermixing index, where it also decreased significantly more rapidly at pH 7.5 (r2 = 0.90, p = 2 × 10−9, coeff = −0.0289, 95% CI = [−0.0295, −0.0284]) than at 6.5 (r2 = 0.93, p = 9 × 10−8, coeff = −0.01, 95% CI = [−0.0109, −0.0098]) (Fig. 2b). During the second phase, the change in the ratio of consumer-to-producer did not significantly differ between pH 7.5 (r2 = 0.90, p = 2 × 10−9, coeff = 0.0008, 95% CI = [0.0002, 0.0014]) and 6.5 (r2 = 0.94, p = 1 × 10−7, coeff = 0.0003, 95% CI = [−0.0002, 0.0008]) (Fig. 2a). However, we observed that the decrease in the intermixing index was significantly different between pH 7.5 (r2 = 0.94, p = 2 × 10−9, coeff = 0.0018, 95% CI = [0.0013, 0.0024]) and 6.5 (r2 = 0.94, p = 8 × 10−8, coeff = −0.0019, 95% CI = [−0.0025, −0.0013]). Overall, the final ratio of consumer-to-producer is lower at pH 7.5 (mean = 0.0163, SD = 0.01) than at 6.5 (mean = 0.052, SD = 0.02) (two-sample two-sided t-test; p = 0.03, n = 4) (Fig. 2). Consistently, the final intermixing index is also lower at pH 7.5 (mean = 0.0039, SD = 0.0032) than at 6.5 (mean = 0.0107, SD = 0.0049) (two-sample two-sided t-test; p = 0.05, n = 4) (Fig. 2b).Fig. 2: Dynamics of co-culture composition and intermixing during repeated anoxic/oxic transitions.a Co-culture composition measured as the ratio of consumer-to-producer. b Intermixing between the consumer and producer measured as the intermixing index, where N is the number of interspecific boundaries between the two strains. Experiments were performed at pH 6.5 (strong mutualistic interaction) (magenta data points) or pH 7.5 (weak mutualistic interaction) (cyan data points). Each data point is for an independent replicate (n = 4). The solid black lines are the two-phase linear regression models for pH 6.5, while the dashed black lines are the two-phase linear regression models for pH 7.5. Images of the final expansions after 350 h of incubation at c pH 6.5 and d pH 7.5. The scale bars are 1000 μm.Full size imageThe results described above yielded two important outcomes. First, the modeled two-phase linear regression of the ratio of consumer-to-producer and the intermixing index both depended on the strength of the mutualistic interaction, where the initial rate of decay was faster at pH 7.5 than at 6.5 (Fig. 2a, b). Thus, as the strength of the interdependency increases, the decay in the ratio and the intermixing index slows. Second, at pH 6.5 we never observed the complete loss of the consumer from the expansion edge (i.e., neither the ratio of consumer-to-producer nor the intermixing index reached zero) (Fig. 2a, b), which is counter to our initial expectation (Fig. 1d).We further performed controls under continuous oxic and continuous anoxic conditions (Supplementary Fig. S5). The ratio of consumer-to-producer and the intermixing indices both significantly differed between continuous oxic and continuous anoxic conditions regardless of the pH (two-sample two-sided t-tests; p  More

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    Wildland fire smoke alters the composition, diversity, and potential atmospheric function of microbial life in the aerobiome

    Fire conditions and particulate and bioaerosol emissionsFire radiative power values estimated from satellite imagery ranged from 6 to 259 MW over three days of burning [19]. Smoke sampled above combusting vegetation contained high concentrations of PM10 (mean ± s.e. 928.4 ± 140.6 µg m−3; Fig. 1). Microbial cells are a component of total bioaerosols, and their abundance can correlate with PM in ambient conditions [24] as well as in wildland fire smoke [6]. However, we observed that only the concentration of viable cells (and not total cells) correlated with PM2.5 and PM10 values (r2 = 0.80, and 0.81, respectively; p  More