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Environmental heterogeneity promotes spatial resilience of phototrophic biofilms in streambeds.

ABSTRACT: The loss of environmental heterogeneity threatens biodiversity and ecosystem functioning. It is therefore important to understand the relationship between environmental heterogeneity and spatial resilience as the capacity of ecological communities embedded in a landscape matrix to reorganize following disturbance. We experimented with phototrophic biofilms colonizing streambed landscapes differing in spatial heterogeneity and exposed to flow-induced disturbance. We show how streambed roughness and related features promote growth-related trait diversity and the recovery of biofilms towards carrying capacity (CC) and spatial resilience. At the scale of streambed landscapes, roughness and exposure to water flow promoted biofilm CC and growth trait diversity. Structural equation modelling identified roughness, post-disturbance biomass and a 'neighbourhood effect' to drive biofilm CC. Our findings suggest that the environment selecting for adaptive capacities prior to disturbance (that is, memory effects) and biofilm connectivity into spatial networks (that is, mobile links) contribute to the spatial resilience of biofilms in streambed landscapes. These findings are critical given the key functions biofilms fulfil in streams, now increasingly experiencing shifts in sedimentary and hydrological regimes.

SUBMITTER: Dzubakova K

PROVIDER: S-EPMC6227859 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Environmental heterogeneity promotes spatial resilience of phototrophic biofilms in streambeds.

Dzubakova Katharine K Peter Hannes H Bertuzzo Enrico E Juez Carmelo C Franca Mário J MJ Rinaldo Andrea A Battin Tom J TJ

Biology letters 20181010 10

The loss of environmental heterogeneity threatens biodiversity and ecosystem functioning. It is therefore important to understand the relationship between environmental heterogeneity and spatial resilience as the capacity of ecological communities embedded in a landscape matrix to reorganize following disturbance. We experimented with phototrophic biofilms colonizing streambed landscapes differing in spatial heterogeneity and exposed to flow-induced disturbance. We show how streambed roughness a ...[more]

PMID: 30305460

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Project description:Phototrophic biofilms are exposed to multiple stressors that can affect them both directly and indirectly. By modifying either the composition of the community or the physiology of the microorganisms, press stressors may indirectly impact the ability of the biofilms to cope with disturbances. Extracellular polymeric substances (EPS) produced by the biofilm are known to play an important role in its resilience to various stresses. The aim of this study was to decipher to what extent slight modifications of environmental conditions could alter the resilience of phototrophic biofilm EPS to a realistic sequential disturbance (4-day copper exposure followed by a 14-day dry period). By using very simplified biofilms with a single algal strain, we focused solely on physiological effects. The biofilms, composed by the non-axenic strains of a green alga (Uronema confervicolum) or a diatom (Nitzschia palea) were grown in artificial channels in six different conditions of light intensity, temperature and phosphorous concentration. EPS quantity (total organic carbon) and quality (ratio protein/polysaccharide, PN/PS) were measured before and at the end of the disturbance, and after a 14-day rewetting period. The diatom biofilm accumulated more biomass at the highest temperature, with lower EPS content and lower PN/PS ratio while green alga biofilm accumulated more biomass at the highest light condition with lower EPS content and lower PN/PS ratio. Temperature, light intensity, and P concentration significantly modified the resistance and/or recovery of EPS quality and quantity, differently for the two biofilms. An increase in light intensity, which had effect neither on the diatom biofilm growth nor on EPS production before disturbance, increased the resistance of EPS quantity and the resilience of EPS quality. These results emphasize the importance of considering the modulation of community resilience ability by environmental conditions, which remains scarce in the literature.

Project description:BackgroundIn the context of environmentally influenced communicable diseases, proximity to environmental sources results in spatial heterogeneity of risk, which is sometimes difficult to measure in the field. Most prevention trials use randomization to achieve comparability between groups, thus failing to account for heterogeneity. This study aimed to determine under what conditions spatial heterogeneity biases the results of randomized prevention trials, and to compare different approaches to modeling this heterogeneity.MethodsUsing the example of a malaria prevention trial, simulations were performed to quantify the impact of spatial heterogeneity and to compare different models. Simulated scenarios combined variation in baseline risk, a continuous protective factor (age), a non-related factor (sex), and a binary protective factor (preventive treatment). Simulated spatial heterogeneity scenarios combined variation in breeding site density and effect, location, and population density. The performances of the following five statistical models were assessed: a non-spatial Cox Proportional Hazard (Cox-PH) model and four models accounting for spatial heterogeneity-i.e., a Data-Generating Model, a Generalized Additive Model (GAM), and two Stochastic Partial Differential Equation (SPDE) models, one modeling survival time and the other the number of events. Using a Bayesian approach, we estimated the SPDE models with an Integrated Nested Laplace Approximation algorithm. For each factor (age, sex, treatment), model performances were assessed by quantifying parameter estimation biases, mean square errors, confidence interval coverage rates (CRs), and significance rates. The four models were applied to data from a malaria transmission blocking vaccine candidate.ResultsThe level of baseline risk did not affect our estimates. However, with a high breeding site density and a strong breeding site effect, the Cox-PH and GAM models underestimated the age and treatment effects (but not the sex effect) with a low CR. When population density was low, the Cox-SPDE model slightly overestimated the effect of related factors (age, treatment). The two SPDE models corrected the impact of spatial heterogeneity, thus providing the best estimates.ConclusionOur results show that when spatial heterogeneity is important but not measured, randomization alone cannot achieve comparability between groups. In such cases, prevention trials should model spatial heterogeneity with an adapted method.Trial registrationThe dataset used for the application example was extracted from Vaccine Trial #NCT02334462 ( ClinicalTrials.gov registry).

Dataset Information

Environmental heterogeneity promotes spatial resilience of phototrophic biofilms in streambeds.

Publications

Environmental heterogeneity promotes spatial resilience of phototrophic biofilms in streambeds.

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