Quantifying temporal variability and spatial heterogeneity in rainfall recharge thresholds in a montane karst environment

Abstract Background The possible relationship between temporal variability of electrocardiographic spatial heterogeneity of repolarisation and the risk of sudden cardiac death (SCD) in patients with coronary artery disease (CAD) is not completely understood. Purpose To investigate the prognostic value of temporal variability of T-wave spatial heterogeneity in SCD in patients with CAD. Methods The Innovation to reduce Cardiovascular Complications of Diabetes at the Intersection (ARTEMIS) study population consisted of 1,946 patients with angiographically verified CAD. T-wave morphology dispersion (TMD), which estimates the average angle between all reconstruction vector pairs in T-wave loop based on leads I-II and V2-V6, was analysed on beat-to-beat basis from 10 minutes period of the baseline electrocardiographic recording in 1,678 study subjects. The temporal variability of TMD was evaluated by standard deviation of TMD (TMD-SD). Results After on average of 7.4±2.0 years of follow-up, a total of 47 of the 1,678 study subjects (2.8%) had experienced SCD or were resuscitated from sudden cardiac arrest (SCA). TMD-SD was significantly higher in patients who had experienced SCD/SCA compared with those who remained alive (3.64±2.57 vs. 2.65±2.54, p<0.01, respectively), but did not differ significantly between the patients who had experienced non-sudden cardiac death (n=40, 2.4%) and those who remained alive (2.98±2.43 vs. 2.67±2.55, p=0.45, respectively) or between the patients who succumbed to non-cardiac death (n=88, 5,2%) and those who stayed alive (2.74±2.44 vs. 2.67±2.55, p=0.81). After adjustments with relevant clinical risk indicators of SCD/SCA, such as left ventricular ejection fraction, diabetes, left bundle branch block and Canadian Cardiac Society class, TMD-SD still predicted SCD/SCA (HR 1.113, 95% CIs 1.028–1.206, p<0.01). The discrimination and reclassification accuracy increased significantly (p=0.02, p=0.033) and the C-index increased from 0.733 to 0.741 when TMD-SD was added to the clinical risk model of SCD/SCA. The Kaplan-Meier survival curves show proportional probabilities of event-free survival for different modes of death for patients classified according to the optimised TMD-SD cut-off point (Figure). Figure 1 Conclusions Temporal variability of electrocardiographic spatial heterogeneity of repolarisation represented by TMD-SD independently predicts long-term risk of SCD/SCA in patients with CAD. Acknowledgement/Funding Sigrid Juselius Foundation and Finnish Foundation for Cardiovascular Research

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Effects of Spatial Variability and Relic DNA Removal on the Detection of Temporal Dynamics in Soil Microbial Communities

mBio ◽

10.1128/mbio.02776-19 ◽

2020 ◽

Vol 11 (1) ◽

Cited By ~ 4

Author(s):

Paul Carini ◽

Manuel Delgado-Baquerizo ◽

Eve-Lyn S. Hinckley ◽

Hannah Holland‐Moritz ◽

Tess E. Brewer ◽

...

Keyword(s):

Microbial Community ◽

Spatial Variability ◽

Spatial Heterogeneity ◽

Microbial Communities ◽

Temporal Variability ◽

Temporal Dynamics ◽

Microbial Community Composition ◽

Soil Microbial Communities ◽

Environmental Preferences ◽

Soil Microbial

ABSTRACT Few studies have comprehensively investigated the temporal variability in soil microbial communities despite widespread recognition that the belowground environment is dynamic. In part, this stems from the challenges associated with the high degree of spatial heterogeneity in soil microbial communities and because the presence of relic DNA (DNA from dead cells or secreted extracellular DNA) may dampen temporal signals. Here, we disentangle the relationships among spatial, temporal, and relic DNA effects on prokaryotic and fungal communities in soils collected from contrasting hillslopes in Colorado, USA. We intensively sampled plots on each hillslope over 6 months to discriminate between temporal variability, intraplot spatial heterogeneity, and relic DNA effects on the soil prokaryotic and fungal communities. We show that the intraplot spatial variability in microbial community composition was strong and independent of relic DNA effects and that these spatial patterns persisted throughout the study. When controlling for intraplot spatial variability, we identified significant temporal variability in both plots over the 6-month study. These microbial communities were more dissimilar over time after relic DNA was removed, suggesting that relic DNA hinders the detection of important temporal dynamics in belowground microbial communities. We identified microbial taxa that exhibited shared temporal responses and show that these responses were often predictable from temporal changes in soil conditions. Our findings highlight approaches that can be used to better characterize temporal shifts in soil microbial communities, information that is critical for predicting the environmental preferences of individual soil microbial taxa and identifying linkages between soil microbial community composition and belowground processes. IMPORTANCE Nearly all microbial communities are dynamic in time. Understanding how temporal dynamics in microbial community structure affect soil biogeochemistry and fertility are key to being able to predict the responses of the soil microbiome to environmental perturbations. Here, we explain the effects of soil spatial structure and relic DNA on the determination of microbial community fluctuations over time. We found that intensive spatial sampling was required to identify temporal effects in microbial communities because of the high degree of spatial heterogeneity in soil and that DNA from nonliving sources masks important temporal patterns. We identified groups of microbes with shared temporal responses and show that these patterns were predictable from changes in soil characteristics. These results provide insight into the environmental preferences and temporal relationships between individual microbial taxa and highlight the importance of considering relic DNA when trying to detect temporal dynamics in belowground communities.

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Spatial heterogeneity and temporal variability

Ecology ◽

10.1201/9781482294354-16 ◽

2003 ◽

pp. 192-216

Keyword(s):

Spatial Heterogeneity ◽

Temporal Variability

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Using an advanced robotic chamber system to detect spatio-temporal short-term responses in measured CO2 exchange to soil manipulation and N fertilization

10.5194/egusphere-egu21-1256 ◽

2021 ◽

Author(s):

Mathias Hoffmann ◽

Shrijana Vaidya ◽

Marten Schmidt ◽

Norbert Bonk ◽

Peter Rakowski ◽

...

Keyword(s):

Spatial Heterogeneity ◽

Temporal Variability ◽

Agricultural Practices ◽

N Fertilization ◽

Soil Types ◽

Small Scale ◽

Chamber System ◽

Short Term ◽

Flux Dynamics ◽

Spatio Temporal

Improved agricultural practices sequestering additional atmospheric C within the soil are considered as one of the potential solution for mitigating global climate change. However, agricultural used landscapes are complex and their capacity to sequester additional atmospheric C differs substantially in time and space. Hence, accurate and precise information on the complex spatio-temporal CO2 flux pattern is needed to evaluate the effects/benefits of new agricultural practices aiming towards increasing soil organic carbon.To date, different approaches are used to measure and quantify CO2 flux dynamics of agricultural landscapes, such as e.g. eddy covariance, as well as manual and automatic chamber systems. However, all these methods fail to some extend in either accounting for small scale spatial heterogeneity (e.g., eddy covariance and automatic chambers) or short-term temporal variability (e.g., manual chambers). Although, automatic chambers are in principle capable to detect small-scale spatial differences of CO2 flux dynamics in a sufficient temporal resolution, these systems are usually limited to only a few spatial repetitions which is not sufficient to represent small scale soil heterogeneity such as present within the widespread hummocky ground moraine landscape of NE-Germany.To overcome these challenges, we developed a novel robotic chamber system. This system was used to detect small-scale spatial heterogeneity and short-term temporal variability of CO2 flux dynamics in a full factorial experimental setup for a range of three different soil types, two N fertilization forms (2; mineral vs. organic) and two soil manipulation status, representing two different tillage practices. Here, we present measured CO2 flux dynamics and cumulative emissions for the 3 repetitions of the 12 randomized treatments (36 subplots) directly following soil manipulation and N fertilization during summer 2020. Our results show distinct differences between the three measured soil types as well as a clear response of all three soil types to conducted soil manipulation, yielding in significantly lower ecosystem respiration (Reco) and net ecosystem exchange (NEE) for manipulated vs. non-manipulated subplots. No clear difference, however, was obtained in case of N fertilization.

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Unraveling the effects of spatial variability and relic DNA on the temporal dynamics of soil microbial communities

10.1101/402438 ◽

2018 ◽

Cited By ~ 3

Author(s):

Paul Carini ◽

Manuel Delgado-Baquerizo ◽

Eve-Lyn S. Hinckley ◽

Hannah Holland-Moritz ◽

Tess E Brewer ◽

...

Keyword(s):

Microbial Community ◽

Spatial Variability ◽

Spatial Heterogeneity ◽

Microbial Communities ◽

Temporal Variability ◽

Temporal Dynamics ◽

Microbial Community Composition ◽

Soil Microbial Communities ◽

Soil Microbial ◽

Over Time

AbstractFew studies have comprehensively investigated the temporal variability in soil microbial communities despite widespread recognition that the belowground environment is dynamic. In part, this stems from the challenges associated with the high degree of spatial heterogeneity in soil microbial communities and because the presence of relic DNA (DNA from non-living cells) may dampen temporal signals. Here we disentangle the relationships among spatial, temporal, and relic DNA effects on bacterial, archaeal, and fungal communities in soils collected from contrasting hillslopes in Colorado, USA. We intensively sampled plots on each hillslope over six months to discriminate between temporal variability, intra-plot spatial heterogeneity, and relic DNA effects on the soil prokaryotic and fungal communities. We show that the intra-plot spatial variability in microbial community composition was strong and independent of relic DNA effects with these spatial patterns persisting throughout the study. When controlling for intra-plot spatial variability, we identified significant temporal variability in both plots over the six-month study. These microbial communities were more dissimilar over time after relic DNA was removed, suggesting that relic DNA hinders the detection of important temporal dynamics in belowground microbial communities. We identified microbial taxa that exhibited shared temporal responses and show these responses were often predictable from temporal changes in soil conditions. Our findings highlight approaches that can be used to better characterize temporal shifts in soil microbial communities, information that is critical for predicting the environmental preferences of individual soil microbial taxa and identifying linkages between soil microbial community composition and belowground processes.ImportanceNearly all microbial communities are dynamic in time. Understanding how temporal dynamics in microbial community structure affect soil biogeochemistry and fertility are key to being able to predict the responses of the soil microbiome to environmental perturbations. Here we explain the effects of soil spatial structure and relic DNA on the determination of microbial community fluctuations over time. We found that intensive spatial sampling is required to identify temporal effects in microbial communities because of the high degree of spatial heterogeneity in soil and that DNA from non-living microbial cells masks important temporal patterns. We identified groups of microbes that display correlated behavior over time and show that these patterns are predictable from soil characteristics. These results provide insight into the environmental preferences and temporal relationships between individual microbial taxa and highlight the importance of considering relic DNA when trying to detect temporal dynamics in belowground communities.

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