Trophic compensation stabilizes marine primary producers exposed to artificial light at night

Artificial light at night (ALAN) is a widespread phenomenon along coastal areas. Despite in - creasing evidence of pervasive effects of ALAN on patterns of species distribution and abundance, the potential of this emerging threat to alter ecological processes in marine ecosystems has remained largely unexplored. Here, we show how exposure to white LED lighting, comparable to that experienced along local urbanized coasts, significantly enhanced the impact of grazing gastropods on epilithic microphytobenthos (MPB). ALAN increased both the photo-synthetic biomass of MPB and the grazing pressure of gastropods, such that consumers compensated for the positive effect of night lighting on primary producers. Our results indicate that trophic interactions can provide a stabilizing compensatory mechanism against ALAN effects in natural food webs

A Dose Relationship Between Brain Functional Connectivity and Cumulative Head Impact Exposure in Collegiate Water Polo Players.

A growing body of evidence suggests that chronic, sport-related head impact exposure can impair brain functional integration and brain structure and function. Evidence of a robust inverse relationship between the frequency and magnitude of repeated head impacts and disturbed brain network function is needed to strengthen an argument for causality. In pursuing such a relationship, we used cap-worn inertial sensors to measure the frequency and magnitude of head impacts sustained by eighteen intercollegiate water polo athletes monitored over a single season of play. Participants were evaluated before and after the season using computerized cognitive tests of inhibitory control and resting electroencephalography. Greater head impact exposure was associated with increased phase synchrony [r (16) > 0.626, p < 0.03 corrected], global efficiency [r (16) > 0.601, p < 0.04 corrected], and mean clustering coefficient [r (16) > 0.625, p < 0.03 corrected] in the functional networks formed by slow-wave (delta, theta) oscillations. Head impact exposure was not associated with changes in performance on the inhibitory control tasks. However, those with the greatest impact exposure showed an association between changes in resting-state connectivity and a dissociation between performance on the tasks after the season [r (16) = 0.481, p = 0.043] that could also be attributed to increased slow-wave synchrony [F (4, 135) = 113.546, p < 0.001]. Collectively, our results suggest that athletes sustaining the greatest head impact exposure exhibited changes in whole-brain functional connectivity that were associated with altered information processing and inhibitory control

Temporal clustering of extreme climate events drives a regime shift in rocky intertidal biofilms

Research on regime shifts has focused primarily on how changes in the intensity and duration of press disturbances precipitate natural systems into undesirable, alternative states. By contrast, the role of recurrent pulse perturbations, such as extreme climatic events, has been largely neglected, hindering our understanding of how historical processes regulate the onset of a regime shift. We performed field manipulations to evaluate whether combinations of extreme events of temperature and sediment deposition that differed in their degree of temporal clustering generated alternative states in rocky intertidal epilithic microphytobenthos (biofilms) on rocky shores. The likelihood of biofilms to shift from a vegetated to a bare state depended on the degree of temporal clustering of events, with biofilm biomass showing both states under a regime of non-clustered (60 d apart) perturbations while collapsing in the clustered (15 d apart) scenario. Our results indicate that time since the last perturbation can be an important predictor of collapse in systems exhibiting alternative states and that consideration of historical effects in studies of regime shifts may largely improve our understanding of ecosystem dynamics under climate change

Experimental evidence of spatial signatures of approaching regime shifts in macroalgal canopies

Developing early warning signals to predict regime shifts in ecosystems is a central issue in current ecological research. While there are many studies addressing temporal early warning indicators, research into spatial indicators is far behind, with field experiments even more rare. Here, we tested the performance of spatial early warning signals in an intertidal macroalgal system, where removal of algal canopies pushed the system toward a tipping point (corresponding to approximately 75% of canopy loss), marking the transition between a canopy- to a turf-dominated state. We performed a two-year experiment where spatial early warning indicators were assessed in transects where the canopy was differentially removed (from 0 to 100%). Unlike Moran correlation coefficient at lag-1, spatial variance, skewness, and spatial spectra at low frequency increased along the gradient of canopy degradation and dropped, or did not show any further increase beyond the transition point from a canopy- to a turf-dominated state (100% canopy removal). Our study provides direct evidence of the suitability of spatial early warning signals to anticipate regime shifts in natural ecosystems, emphasizing the importance of field experiments as a powerful tool to establish causal relationships between environmental stressors and early warning indicators

Hybrid datasets: integrating observations with experiments in the era of macroecology and big-data

Understanding how increasing human domination of the biosphere affects life on earth is a critical research challenge. This task is facilitated by the increasing availability of open-source data repositories, which allow ecologists to address scientific questions at unprecedented spatial and temporal scales. Large datasets are mostly observational, so they may have limited ability to uncover causal relations among variables. Experiments are better suited at attributing causation, but they are often limited in scope. We propose hybrid datasets, resulting from the integration of observational with experimental data, as an approach to leverage the scope and ability to attribute causality in ecological studies. We show how the analysis of hybrid datasets with emerging techniques in time series analysis (Convergent Cross Mapping) and macroecology (Joint Species Distribution Models) can generate novel insights into causal effects of abiotic and biotic processes that would be difficult to achieve otherwise. We illustrate these principles with two case-studies in marine ecosystems and discuss the potential to generalize across environments, species and ecological processes. If used wisely, the analysis of hybrid datasets may become the standard approach for research goals that seek causal explanations for large-scale ecological phenomena. This article is protected by copyright. All rights reserved

Ecological feedback mechanisms and variable disturbance regimes: the uncertain future of Mediterranean macroalgal forests

Loss of algal canopies can result in a shift towards a turf-dominated state, where variability in species life-history traits can determine new mechanisms of feedback, and influence the degraded system under variable regimes of disturbance. By focusing on rockpools dominated by Cystoseira brachycarpa, we tested the hypothesis that the alga Dictyopteris polypodioides could take advantage of extreme regimes of disturbance related to storms, and outcompete other turfs through a distinctive combination of life traits. Replacement of the canopy was initially driven by a mix of taxon-specific life-traits and resulting assemblages were susceptible to intense events of disturbance. Subsequently, D. polypodioides dominated removal quadrats, favored by density-dependent abilities to intercept more light and reach larger size than the rest of turf. These new positive feedbacks may contribute to maintain the modified state of the system and influence its ability to withstand extreme abiotic conditions

Validation of a bioanalytical method for the determination of synthetic and natural cannabinoids (New psychoactive substances) in oral fluid samples by means of hplc-ms/ms

New psychoactive substances (NPS) represent an important focus nowadays and are continually produced with minimal structural modifications in order to circumvent the law and increase the difficulty of identifying them. Moreover, since there are a high number of different compounds, it is arduous to develop analytical screening and/or confirmation methods that allow the identification and quantification of these compounds. The aim of this work is to develop and validate a bioanalytical method for detecting new synthetic drugs in biological samples, specifically oral fluid, using high-performance liquid chromatography coupled with mass spectrometry (HPLC-MS/MS) with minimal sample pretreatment. Oral fluid samples were simply centrifuged and denaturized with different rapid procedures before injection into the LC-MS/MS system. Calibration curves covered a linear concentration range from LOQ to 100 ng/mL. Validation parameters such as linearity, precision, accuracy, selectivity, matrix effect and thermal stability were evaluated and showed satisfactory results, in accordance with US Food & Drug Administration guidelines. The inter-day analytical bias and imprecision at two levels of quality control (QC) were within ±15% for most compounds. This method was able to identify and calculate the concentration of 10 NPS validated in this biological sample, even in the presence of matrix effect