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1. Reliance on ecosystem services instead of synthetic, non-renewable inputs is increasingly seen as key to achieving food security in an environmentally sustainable way. This process, known as ecological intensification, will depend in large part on enhancing below-ground biological interactions that facilitate resource use efficiency. Arbuscular mycorrhizas (AM), associations formed between the roots of most terrestrial plant species and a specialized group of soil fungi, provide valuable ecosystem services, but the full magnitude of these services may not be fully realized under conventional intensively managed annual agricultural systems. 2. Here, we use meta-analysis to assess how reducing soil disturbance and periods without roots in agricultural systems affect the formation of AM and the diversity and community composition of arbuscular mycorrhizal fungi (AMF). We compiled data from 54 field studies across five continents that measured effects of tillage and/or cover cropping on AMF colonization and/or communities and assessed effects of management and environmental factors on these responses. 3. Less intensive tillage and winter cover cropping similarly increased AMF colonization of summer annual cash crop roots by ~30%. The key variables influencing the change in AMF colonization were the type of cover crop or the type of alternative tillage, suggesting that farmers can optimize combinations of tillage and cover crops that most enhance AM formation, particularly with no-till systems and legume cover crops. 4. Richness of AMF taxa increased by 11% in low-intensity vs. conventional tillage regimes. Several studies showed changes in diversity and community composition of AMF with cover cropping, but these responses were not consistent. 5. Synthesis and applications. This meta-analysis indicates that less intensive tillage and cover cropping are both viable strategies for enhancing root colonization from indigenous arbuscular mycorrhizal fungi (AMF) across a wide range of soil types and cash crop species, and possibly also shifting AMF community structure, which could in turn increase biologically based resource use in agricultural systems.

Humans are intentionally exposed to gold nanoparticles (AuNPs) where they are used in variety of biomedical applications as imaging and drug delivery agents as well as diagnostic and therapeutic agents currently in clinic and in a variety of upcoming clinical trials. Consequently, it is critical that we gain a better understanding of how physiochemical properties such as size, shape, and surface chemistry drive cellular uptake and AuNP toxicity in vivo. Understanding and being able to manipulate these physiochemical properties will allow for the production of safer and more efficacious use of AuNPs in biomedical applications. Here, AuNPs of three sizes, 5 nm, 10 nm, and 20 nm, were coated with a lipid bilayer composed of sodium oleate, hydrogenated phosphatidylcholine, and hexanethiol. To understand how the physical features of AuNPs influence uptake through cellular membranes, sum frequency generation (SFG) was utilized to assess the interactions of the AuNPs with a biomimetic lipid monolayer composed of a deuterated phospholipid 1.2-dipalmitoyl-d62-sn-glycero-3-phosphocholine (dDPPC). SFG measurements showed that 5 nm and 10 nm AuNPs are able to phase into the lipid monolayer with very little energetic cost, whereas, the 20 nm AuNPs warped the membrane conforming it to the curvature of hybrid lipid-coated AuNPs. Toxicity of the AuNPs were assessed in vivo to determine how AuNP curvature and uptake influence cell health. In contrast, in vivo toxicity tested in embryonic zebrafish showed rapid toxicity of the 5 nm AuNPs, with significant 24 hpf mortality occurring at concentrations ≥20 mg/L, whereas the 10 nm and 20 nm AuNPs showed no significant mortality throughout the five-day experiment. By combining information from membrane models using SFG spectroscopy with in vivo toxicity studies, a better mechanistic understanding of how nanoparticles (NPs) interact with membranes is developed to understand how the physiochemical features of AuNPs drive nanoparticle-membrane interactions, cellular uptake, and toxicity.

The region adjacent to the River Plate is renowned for its fishing activity and abundant biodiversity. Both are closely linked to the significant local river flows responsible for fertilizing extensive marine areas. Among the several biological communities, micronekton deserves special attention as it serves as a vital trophic link between primary production and top predators in the ecosystem. Recognizing its importance, this study evaluates the spatio temporal variability of epipelagic micronekton biomass at the mouth of the River Plate. Numerical modeling outputs of micronekton functional groups were obtained from the Spatial Ecosystem and Population Dynamics Model (SEAPODYM), coupled with in situ environmental data (precipitation, wind direction, and intensity) from 2015 to 2019. The results revealed greater aggregations of epipelagic micronekton near the river mouth. There was a seasonal disparity in micronekton biomass in the zone influenced by river drainage, with higher biomass values observed during the summer and lower values during the winter. This seasonal difference was attributed to winds from the northeast and southeast quadrants, as the micronektonic plume is susceptible to their effects. However, precipitation data did not exhibit a significant correlation with in situ flow data nor with quantitative micronekton measurements. This discrepancy may be attributed to the positioning of the data collection stations relative to the dimensions of the mouth of the River Plate.

Blooms of Dinophysis acuminata occur every year in Galicia (northwest Spain), between spring and autumn. These blooms contaminate shellfish with lipophilic toxins and cause lengthy harvesting bans. They are often followed by short-lived blooms of Dinophysis acuta, associated with northward longshore transport, at the end of the upwelling season. During the summers of 1989 and 1990, dense blooms of D. acuta developed in situ, initially co-occurring with D. acuminata and later with the paralytic shellfish toxin-producer Gymnodinium catenatum. Unexplored data from three cruises carried out before, during, and following autumn blooms (13–14, 27–28 September and 11–12 October) in 1990 showed D. acuta distribution in shelf waters within the 50 m and 130 m isobaths, delimited by the upwelling front. A joint review of monitoring data from Galicia and Portugal provided a mesoscale view of anomalies in SST and other hydroclimatic factors associated with a northward displacement of the center of gravity of D. acuta populations. At the microscale, re-examination of the vertical segregation of cell maxima in the light of current knowledge, improved our understanding of niche differentiation between the two species of Dinophysis. Results here improve local transport models and forecast of Dinophysis events, the main cause of shellfish harvesting bans in the most important mussel production area in Europe.

Pelagic organisms inhabiting coastal upwelling regions face a high risk of advection away from the nearshore productive habitat, potentially leading to mortality. We explored how animals remain in a productive yet highly advective environment in the Northern California Current System using the cabled observatory system located off the Oregon coast. Acoustic scatterers consistent with swimbladder‐bearing fish were only present during the downwelling season as these animals avoided the cold waters associated with strong upwelling conditions in summer and fall. Fish responded to short‐term upwelling events by increasing the frequency of diel vertical migration. Throughout the study, their vertical positions corresponded to the depth of minimum cross‐shelf transport, providing a mechanism for retention. The observed behavioral response highlights the importance of studying ecological processes at short timescales and the abilities of pelagic organisms to control their horizontal distributions through fine‐tuned diel vertical migration in response to upwelling. Plain Language Summary Coastal upwelling regions are characterized by high nearshore productivity supported by wind‐driven nutrient supply. This high productivity cascades through the food web supporting high abundance of fish and providing feeding habitat for seabirds and marine mammals. Organisms living in the upwelling ecosystems constantly face challenges of being swept offshore into habitat with fewer food resources due to strong offshore‐moving currents near the surface. Studying how pelagic organisms remain in these nearshore productive waters despite the highly advective physical processes has been difficult. We used simultaneous observations of biological and physical properties to quantify how upwelling variability affects fish behavior and distributions in the Northern California Current System on the Oregon shelf throughout the year. Fish appeared at the nearshore study site during the downwelling season (fall—spring), avoiding cold waters associated with the summer upwelling season. Within the downwelling season, fish responded to short‐term upwelling events by conducting diel vertical migration more frequently during upwelling than downwelling conditions. Regardless of the upwelling strength, fish positioned themselves at the depth of minimum advection risk which aids in retention at the nearshore habitat. These observations highlight the survival strategies of animals in the environment where physical forcing exceeds their swimming capabilities. Key Points Acoustic scatterers responded to short‐term upwelling events outside of the summer upwelling season on the Oregon shelf Diel vertical migration occurred more frequently during upwelling than downwelling Acoustic scatterers positioned themselves at the depth of minimum cross‐shelf transport during both upwelling and downwelling

The Lüderitz upwelling cell and Orange River cone (LUCORC) area, a transboundary region between South Africa and Namibia, is considered to be an environmental barrier to transport of ichthyoplankton from the southern to the northern Benguela upwelling ecosystems. We use environmental data and modelling to assess the potential mechanisms responsible for this barrier: environmental data were extracted from the 1 × 1° World Ocean Atlas 2001 database and used to build maps of annual mean salinity, temperature, chlorophyll, dissolved oxygen and nutrient concentrations; outputs of a regional circulation model were used in an individual-based model to assess the transport of passive particles from the southern to the northern Benguela. The data show no clear environmental barrier at sea surface, but the model results suggest that particles released there would be largely transported offshore. The model also shows that particles released below the surface could be transported alongshore from the southern to the northern Benguela, but low subsurface temperatures would increase ichthyoplankton mortality and hence be a strong limiting factor to northward transport. We conclude that the combination of a surface hydrodynamic and a subsurface thermal barrier could limit the possibility for ichthyoplankton of epipelagic species to be transported from the southern to the northern Benguela, but that ichthyoplankton of mesopelagic species, having a wider tolerance to low temperatures, would be less affected.

Significance The conventional parametric approach to modeling relies on hypothesized equations to approximate mechanistic processes. Although there are known limitations in using an assumed set of equations, parametric models remain widely used to test for interactions, make predictions, and guide management decisions. Here, we show that these objectives are better addressed using an alternative equation-free approach, empirical dynamic modeling (EDM). Applied to Fraser River sockeye salmon, EDM models ( i ) recover the mechanistic relationship between the environment and population biology that fisheries models dismiss as insignificant, ( ii ) produce significantly better forecasts compared with contemporary fisheries models, and ( iii ) explicitly link control parameters (spawning abundance) and ecosystem objectives (future recruitment), producing models that are suitable for current management frameworks. It is well known that current equilibrium-based models fall short as predictive descriptions of natural ecosystems, and particularly of fisheries systems that exhibit nonlinear dynamics. For example, model parameters assumed to be fixed constants may actually vary in time, models may fit well to existing data but lack out-of-sample predictive skill, and key driving variables may be misidentified due to transient (mirage) correlations that are common in nonlinear systems. With these frailties, it is somewhat surprising that static equilibrium models continue to be widely used. Here, we examine empirical dynamic modeling (EDM) as an alternative to imposed model equations and that accommodates both nonequilibrium dynamics and nonlinearity. Using time series from nine stocks of sockeye salmon ( Oncorhynchus nerka ) from the Fraser River system in British Columbia, Canada, we perform, for the the first time to our knowledge, real-data comparison of contemporary fisheries models with equivalent EDM formulations that explicitly use spawning stock and environmental variables to forecast recruitment. We find that EDM models produce more accurate and precise forecasts, and unlike extensions of the classic Ricker spawner–recruit equation, they show significant improvements when environmental factors are included. Our analysis demonstrates the strategic utility of EDM for incorporating environmental influences into fisheries forecasts and, more generally, for providing insight into how environmental factors can operate in forecast models, thus paving the way for equation-free mechanistic forecasting to be applied in management contexts.

During the past few years, silver nanoparticles (AgNPs) became one of the most investigated and explored nanotechnology-derived nanostructures, given the fact that nanosilver-based materials proved to have interesting, challenging, and promising characteristics suitable for various biomedical applications. Among modern biomedical potential of AgNPs, tremendous interest is oriented toward the therapeutically enhanced personalized healthcare practice. AgNPs proved to have genuine features and impressive potential for the development of novel antimicrobial agents, drug-delivery formulations, detection and diagnosis platforms, biomaterial and medical device coatings, tissue restoration and regeneration materials, complex healthcare condition strategies, and performance-enhanced therapeutic alternatives. Given the impressive biomedical-related potential applications of AgNPs, impressive efforts were undertaken on understanding the intricate mechanisms of their biological interactions and possible toxic effects. Within this review, we focused on the latest data regarding the biomedical use of AgNP-based nanostructures, including aspects related to their potential toxicity, unique physiochemical properties, and biofunctional behaviors, discussing herein the intrinsic anti-inflammatory, antibacterial, antiviral, and antifungal activities of silver-based nanostructures.

Forecasting the response of ecological systems to environmental change is a critical challenge for sustainable management. The metabolic theory of ecology (MTE) posits scaling of biological rates with temperature, but it has had limited application to population dynamic forecasting. Here we use the temperature dependence of the MTE to constrain empirical dynamic modeling (EDM), an equation-free nonlinear machine learning approach for forecasting. By rescaling time with temperature and modeling dynamics on a “metabolic time step,” our method (MTE-EDM) improved forecast accuracy in 18 of 19 empirical ectotherm time series (by 19% on average), with the largest gains in more seasonal environments. MTE-EDM assumes that temperature affects only the rate, rather than the form, of population dynamics, and that interacting species have approximately similar temperature dependence. A review of laboratory studies suggests these assumptions are reasonable, at least approximately, though not for all ecological systems. Our approach highlights how to combine modern data-driven forecasting techniques with ecological theory and mechanistic understanding to predict the response of complex ecosystems to temperature variability and trends.