Temporal scale of environmental correlations affects ecological synchrony.

Population densities of a species measured in different locations are often correlated over time, a phenomenon referred to as synchrony. Synchrony results from dispersal of individuals among locations and spatially correlated environmental variation, among other causes. Synchrony is often measured by a correlation coefficient. However, synchrony can vary with timescale. We demonstrate theoretically and experimentally that the timescale-specificity of environmental correlation affects the overall magnitude and timescale-specificity of synchrony, and that these effects are modified by population dispersal. Our laboratory experiments linked populations of flour beetles by changes in habitat size and dispersal. Linear filter theory, applied to a metapopulation model for the experimental system, predicted the observed timescale-specific effects. The timescales at which environmental covariation occurs can affect the population dynamics of species in fragmented habitats.

Expanding success in the isolation of abundant marine bacteria after reduction in grazing and viral pressure and increase in nutrient availability.

Isolation of microorganisms is a useful approach to gathering knowledge about their genomic properties, physiology, and ecology, in addition to allowing the characterization of novel taxa. We performed an extensive isolation effort on samples from seawater manipulation experiments that were carried out during the four astronomical seasons in a coastal site of the northwest Mediterranean to evaluate the impact of grazing, viral mortality, resource competition reduction, and light presence/absence on bacterioplankton growth. Isolates were retrieved using two growth media, and their full 16S rRNA gene was sequenced to assess their identity and calculate their culturability across seasons and experimental conditions. A total of 1,643 isolates were obtained, mainly affiliated to the classes Gammaproteobacteria (44%), Alphaproteobacteria (26%), and Bacteroidia (17%). Isolates pertaining to class Gammaproteobacteria were the most abundant in all experiments, while Bacteroidia were preferentially enriched in the treatments with reduced grazing. Sixty-one isolates had a similarity below 97% to cultured taxa and are thus putatively novel. Comparison of isolate sequences with 16S rRNA gene amplicon sequences from the same samples showed that the percentage of reads corresponding to isolates was 21.4% within the whole data set, with dramatic increases in the summer virus-reduced (71%) and diluted (47%) treatments. In fact, we were able to isolate the top 10 abundant taxa in several experiments and from the whole data set. We also show that top-down and bottom-up controls differentially affect taxa in terms of culturability. Our results indicate that culturing marine bacteria using agar plates can be successful in certain ecological situations. IMPORTANCE Bottom-up and top-down controls greatly influence marine microbial community composition and dynamics, which in turn have effects on their culturability. We isolated a high amount of heterotrophic bacterial strains from experiments where seawater environmental conditions had been manipulated and found that decreasing grazing and viral pressure as well as rising nutrient availability are key factors increasing the success in culturing marine bacteria. Our data hint at factors influencing culturability and underpin bacterial cultures as a powerful way to discover new taxa.

Chemistry Matters: High Leaf Litter Consumption Does Not Represent a Direct Increase in Shredders' Biomass.

Changes in riparian vegetation can alter the input and quality of leaf litter in aquatic ecosystems, but the effects of these changes on litter fragmentation by invertebrate shredder communities in tropical streams remain poorly studied. The caddisfly genus Phylloicus Müller, 1880 (Trichoptera: Calamoceratidae) is highly abundant in Neotropical streams, representing a great part of shredder biomass, which uses the allochthonous litter as a food resource and for case-building. We investigated leaf consumption by Phylloicus sp. under different leaf conditioning (leached and unleached) and plant species (Eucalyptus grandis, Erythrina falcata, and Inga uruguensis). The effects of leaf conditioning and plant species were measured using microcosm treatments, with one free Phylloicus sp. larva per 2-l microcosm, and a decomposition control to correct for microbial decomposition. Our study suggests that phosphorus and caloric values of leaf litter are more important than leaf hardness and nitrogen in driving leaf consumption by Phylloicus sp. On the one hand, higher consumption was observed in treatment with unleached leaves than in leached leaf treatment due to higher nutrient concentration and caloric values on unleached leaves. On the other hand, Phylloicus sp. larvae preferred leached leaves for case building over unleached leaves, as leached leaves are less prone to the activity of the decomposing community, thus lowering the need for constant case renewal. Finally, high litter consumption is not necessarily converted into biomass by Phylloicus sp. larvae. In this sense, Phylloicus sp. larvae showed selectivity for resources with high caloric content for consumption and low caloric content for case-building.

The Impact of Anti-Inflammatory Drugs on the Prokaryotic Community Composition and Selected Bacterial Strains Based on Microcosm Experiments.

Non-steroidal anti-inflammatory drugs (NSAIDs) are increasingly recognized as potential environmental contaminants that may induce toxicity in aquatic ecosystems. This 3-week microcosm experiment explores the acute impacts of NSAIDs, including diclofenac (DCF), ibuprofen (IBU), and acetylsalicylic acid (ASA), on bacterial communities using a wide range of these substances (200-6000 ppm). The results showed that the NSAID-treated microcosms had higher cell count values than control samples, though the diversity of microbial communities decreased. The isolated heterotrophic bacteria mostly belonged to Proteobacteria, particularly Klebsiella. Next-generation sequencing (NGS) revealed that NSAIDs altered the structure of the bacterial community composition, with the proportion of Proteobacteria aligning with the selective cultivation results. Bacteria had higher resistance to IBU/ASA than to DCF. In DCF-treated microcosms, there has been a high reduction of the number of Bacteroidetes, whereas in the microcosms treated with IBU/ASA, they have remained abundant. The numbers of Patescibacteria and Actinobacteria have decreased across all NSAID-treated microcosms. Verrucomicrobia and Planctomycetes have tolerated all NSAIDs, even DCF. Cyanobacteria have also demonstrated tolerance to IBU/ASA treatment in the microcosms. The archaeal community structure was also impacted by the NSAID treatments, with Thaumarchaeota abundant in all microcosms, especially DCF-treated microcosms, while Nanoarchaeota is more typical of IBU/ASA-treated microcosms with lower NSAID concentrations. These results indicate that the presence of NSAIDs in aquatic environments could lead to changes in the composition of microbial communities.

Differences in initial abundances reveal divergent dynamic structures in Gause's predator-prey experiments.

Improved understanding of complex dynamics has revealed insights across many facets of ecology, and has enabled improved forecasts and management of future ecosystem states. However, an enduring challenge in forecasting complex dynamics remains the differentiation between complexity and stochasticity, that is, to determine whether declines in predictability are caused by stochasticity, nonlinearity, or chaos. Here, we show how to quantify the relative contributions of these factors to prediction error using Georgii Gause's iconic predator-prey microcosm experiments, which, critically, include experimental replicates that differ from one another only in initial abundances. We show that these differences in initial abundances interact with stochasticity, nonlinearity, and chaos in unique ways, allowing us to identify the impacts of these factors on prediction error. Our results suggest that jointly analyzing replicate time series across multiple, distinct starting points may be necessary for understanding and predicting the wide range of potential dynamic types in complex ecological systems.

Changes in element availability induced by sterilization in heavy metal contaminated substrates: A comprehensive study.

Microbiome analyses of soils and microcosm experiments depend on conditions that include sterilization in order to perform experimental manipulation of microbial communities. Still, they should represent conditions close to nature. When using metal contaminated soils, sterilization methods might alter metal availability. Here, four typical metal contaminated substrates were analyzed, representing different contamination histories and soil types. They included two very poor substrates, as they are often found at metal contaminated sites. The low contents in organic carbon and nitrogen as well as two substrates with slightly higher nutrient availability were used to perform a comprehesive study for element availability changes induced by sterilization. Autoclaving, dry heat or gamma raγ sterilization were applied and compared to a non-treated control. The sterile substrates were analyzed using sequential extraction to account for different associations of the elements. Metals forming specific (hydro)oxide layers were specifically analyzed since they in turn may also impact other metals or ions. In addition, (heavy) metals and (micro)nutrients were analyzed for changes in speciation. The effects of autoclaving (wet heat) was found acceptable, while γ-ray irradiation did show unexpected changes in metal associations, especially for one substrate. Dry heat changed metal availability to the highest degree.

TiO2 nanoparticles for the remediation of eutrophic shallow freshwater systems: Efficiency and impacts on aquatic biota under a microcosm experiment.

The application of nanomaterials (NMs) in the remediation of eutrophic waters, particularly in the control of internal loading of nutrients, has been started, but limited investigations evaluated the effectiveness of these new treatment approaches and of their potential impacts on species from shallow freshwater lakes. The present work investigated, under a microcosm experiment, the application of a TiO2 nanomaterial both for reducing nutrient (mainly phosphorus and nitrogen forms) desorption and release from sediments (preventive treatment-PT) and for eliminating algal blooms (remediation treatment-RT). Furthermore, we also intended to assess the potential impacts of nano-TiO2 application on key freshwater species. The results showed the effectiveness of nano-TiO2 in controlling the release of phosphates from surface sediment and the subsequent reduction of total phosphorus in the water column. A reduction in total nitrogen was also observed. Such changes in nutrient dynamics contributed to a progressive inhibition of development of algae after the application of the NM in PT microcosms. Concerning the ability of nano-TiO2 to interact with algal cells, this interaction has likely occurred, mainly in RT, enhancing the formation of aggregates and their rapid settlement, thus reducing the algal bloom. Both treatments caused deleterious effects on freshwater species. In PT, Daphnia magna and Lemna minor showed a significant inhibition of several endpoints. Conversely, no inhibitory effect on the growth of Chironomus riparius was recorded. In opposite, C. riparius was the most affected species in RT microcosms. Such difference was probably caused by the formation of larger TiO2-algae aggregates in RT, under a high algal density, that rapidly settled in the sediment, becoming less available for pelagic species. In summary, despite the effectiveness of both treatments in controlling internal nutrient loading and in the mitigating algal bloom episodes, their negative effects on biota have to be seriously taken into account.

Can the algicidal material Ca-aminoclay be harmful when applied to a natural ecosystem? An assessment using microcosms.

We assessed the ability of an artificial clay (Ca-aminoclay) to suppress harmful algal bloom species (HABs) such as Cochlodinium polykrikoides and Chattonella marina and investigated the ecological responses in the closed and open microcosm systems. The Ca-aminoclay induced rapidly and selectively cell lysis in the HABs. However, applying Ca-aminoclay could cause adverse impacts in terms of biological and environmental changes. The bacterioplankton abundance increased and then, the abundances of heterotrophic nanoflagellates and ciliates increased rapidly. Extremely poor environmental conditions such as increase in nutrients and development of anoxic conditions were sustained continuously in a closed system, while the environmental conditions in open systems deteriorated before recovering to the initial conditions. We evaluated the potential for the occurrence of a bloom of another phytoplankton after HABs had been controlled using the Ca-aminoclay. The Ca-aminoclay controlled blooms of Chattonella marina in mixed cell cultures containing a Tetraselmis chui. However, T. chui increased over time and then bloomed. Therefore, caution should be taken when considering the direct application of Ca-aminoclay in natural environments even though it offers the rapid removal of HABs.

Inferring the temperature dependence of population parameters: the effects of experimental design and inference algorithm.

Understanding and quantifying the temperature dependence of population parameters, such as intrinsic growth rate and carrying capacity, is critical for predicting the ecological responses to environmental change. Many studies provide empirical estimates of such temperature dependencies, but a thorough investigation of the methods used to infer them has not been performed yet. We created artificial population time series using a stochastic logistic model parameterized with the Arrhenius equation, so that activation energy drives the temperature dependence of population parameters. We simulated different experimental designs and used different inference methods, varying the likelihood functions and other aspects of the parameter estimation methods. Finally, we applied the best performing inference methods to real data for the species Paramecium caudatum. The relative error of the estimates of activation energy varied between 5% and 30%. The fraction of habitat sampled played the most important role in determining the relative error; sampling at least 1% of the habitat kept it below 50%. We found that methods that simultaneously use all time series data (direct methods) and methods that estimate population parameters separately for each temperature (indirect methods) are complementary. Indirect methods provide a clearer insight into the shape of the functional form describing the temperature dependence of population parameters; direct methods enable a more accurate estimation of the parameters of such functional forms. Using both methods, we found that growth rate and carrying capacity of Paramecium caudatum scale with temperature according to different activation energies. Our study shows how careful choice of experimental design and inference methods can increase the accuracy of the inferred relationships between temperature and population parameters. The comparison of estimation methods provided here can increase the accuracy of model predictions, with important implications in understanding and predicting the effects of temperature on the dynamics of populations.