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Predicting spatial patterns of soil bacteria under current and future environmental conditions.

ABSTRACT: Soil bacteria are largely missing from future biodiversity assessments hindering comprehensive forecasts of ecosystem changes. Soil bacterial communities are expected to be more strongly driven by pH and less by other edaphic and climatic factors. Thus, alkalinisation or acidification along with climate change may influence soil bacteria, with subsequent influences for example on nutrient cycling and vegetation. Future forecasts of soil bacteria are therefore needed. We applied species distribution modelling (SDM) to quantify the roles of environmental factors in governing spatial abundance distribution of soil bacterial OTUs and to predict how future changes in these factors may change bacterial communities in a temperate mountain area. Models indicated that factors related to soil (especially pH), climate and/or topography explain and predict part of the abundance distribution of most OTUs. This supports the expectations that microorganisms have specific environmental requirements (i.e., niches/envelopes) and that they should accordingly respond to environmental changes. Our predictions indicate a stronger role of pH over other predictors (e.g. climate) in governing distributions of bacteria, yet the predicted future changes in bacteria communities are smaller than their current variation across space. The extent of bacterial community change predictions varies as a function of elevation, but in general, deviations from neutral soil pH are expected to decrease abundances and diversity of bacteria. Our findings highlight the need to account for edaphic changes, along with climate changes, in future forecasts of soil bacteria.

SUBMITTER: Mod HK

PROVIDER: S-EPMC8397778 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundMutualistic interactions, which constitute some of the most advantageous interactions among fish species, are highly vulnerable to environmental changes. A key mutualistic interaction is the cleaning service rendered by the cleaner wrasse, Labroides dimidiatus, which involves intricate processes of social behaviour to remove ectoparasites from client fish and can be altered in near-future environmental conditions. Here, we evaluated the neuromolecular mechanisms behind the behavioural disruption of cleaning interactions in response to future environments. We subjected cleaner wrasses and surgeonfish (Acanthurus leucosternon, serving as clients) to elevated temperature (warming, 32 °C), increased levels of CO2 (high CO2, 1000 ppm), and a combined condition of elevated CO2 and temperature (warming and high CO2, 32 °C, and 1000 ppm) for 28 days.ResultsEach of these conditions resulted in behavioural disruptions concerning the motivation to interact and the quality of interaction (high CO2 - 80.7%, warming - 92.6%, warming and high CO2 - 79.5%, p < 0.001). Using transcriptomics of the fore-, mid-, and hindbrain, we discovered that most transcriptional reprogramming in both species under warming conditions occurred primarily in the hind- and forebrain. The associated functions under warming were linked to stress, heat shock proteins, hypoxia, and behaviour. In contrast, elevated CO2 exposure affected a range of functions associated with GABA, behaviour, visual perception, thyroid hormones and circadian rhythm. Interestingly, in the combined warming and high CO2 condition, we did not observe any expression changes of behaviour. However, we did find signs of endoplasmic reticulum stress and apoptosis, suggesting not only an additive effect of the environmental conditions but also a trade-off between physiological performance and behaviour in the cleaner wrasse.ConclusionsWe show that impending environmental shifts can affect the behaviour and molecular processes that sustain mutualistic interactions between L. dimidiatus and its clients, which could have a cascading effect on their adaptation potential and possibly cause large-scale impacts on coral reef ecosystems.

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Predicting spatial patterns of soil bacteria under current and future environmental conditions.

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