Spatial Variation In Composition Research Articles

Seasonal and spatial dynamics of the aquatic insect communities of an intermittent Mediterranean river

Although intermittent rivers are present in all climate regions, their biodiversity and ecosystem functions were largely overlooked in the past. Recently, considerable effort has been made to improve our understanding of these, however, many data gaps still remain. We conducted a study to improve knowledge of the community patterns and processes in intermittent rivers in the Dinaric Western Balkan ecoregion. We studied spatial and temporal variation of aquatic insect community composition and structure in the intermittent Krčić River over two seasons (June and December) in three river sections (spring, upper/middle and lower reaches), encompassing dominant microhabitats (phytal, boulders, cobbles, sand and xylal). Community was primarily composed of aquatic insects (92 % of the community) and seasonality was inferred as the most important factor determining its composition, diversity and abundance. This was also supported by the ecological trait information, i.e. trophic and dispersal-related community structure. The most diverse and abundant insect group were the under-investigated chironomids, thus, we discussed tolerance and intermittency indicator potential of some of these taxa. By providing new insights into temporal and spatial dynamics of aquatic insect communities, a major bioindicator component of the macroinvertebrate community used in water quality monitoring in intermittent rivers, our data support development of the intermittent river-specific and adequate management and monitoring procedures.

Spatial variation in taxonomic and functional composition of periphytic algae in lakes of Karelian Isthmus

Variation in species and functional structure of periphytic algae community in relation to chemical, physical, climatic and spatial factors was studied in 55 lakes of Karelian Isthmus. To assess factors driving functional structure, all algal species were divided into eight functional groups that differ in cell/colony morphology and attachment mode to the substrate. Variance partitioning analysis showed that environmental factors (chemical and climatic) prevailed over spatial variables in explaining variation in periphyton species structure. On the contrary, periphyton functional structure depended more on spatial variables than on environmental factors (chemical and physical). This suggests that dispersal processes which are dependent on landscape characteristics of the region and hydrological connectivity along individual river networks play a more significant role in spatial variation of functional composition of periphytic algae.

The Signature of Metasomatized Subcontinental Lithospheric Mantle in the Basaltic Magmatism of the Payenia Volcanic Province, Argentina

AbstractThe Payenia region of Argentina (34.5–38°S) is a large Pliocene‐Quaternary volcanic province of basaltic compositions in the Andean Cordillera foothills representing the northernmost extent of back‐arc volcanism in the Andean Southern Volcanic Zone (SVZ). Although the chemical diversity of the Payenia basalts has been characterized previously, the processes and sources responsible for such variation remain controversial. Here, we report new whole‐rock major and trace element concentrations, Sr‐, Nd‐, Hf‐, and Pb‐isotope ratios and high‐precision olivine oxygen‐isotope ratios in a suite of 35 alkaline basalts from Payenia. These lavas have major and trace elements that define a compositional range from arc‐influenced to intraplate signature. Variable crustal contamination and/or recent slab‐derived inputs inadequately account for elemental and isotopic systematics and spatial compositional variations of Payenia lavas. We present a simple forward model indicating that early metasomatism and subsequent melting of the metasomatized subcontinental lithospheric mantle (SCLM) has significantly contributed to the Payenia lava compositional range. Isotopic ingrowth calculations of radiogenic Sr, Nd, Hf, and Pb suggest that the SCLM metasomatism occurred at 50–150 Ma, consistent with the timing of the breakup of Gondwana and the development of the proto‐Pacific Andean arc. Variations in δ18Oolivine values from modeled melts indicate that the metasomatism and melting within the SCLM can fractionate oxygen isotopes even when the metasomatizing melt has MORB‐like δ18O values, providing a different explanation for the low‐δ18O signatures observed in continental arc settings.

Beta Diversity of Antarctic and Sub-Antarctic Benthic Communities Reveals a Major Role of Stochastic Assembly Processes

Community assembly is the result of both, deterministic and stochastic processes. The former encompasses niche-based local-scale mechanisms such as environmental filtering and biotic interactions; the latter includes ecological drift, probabilistic colonisation, and random extinctions. Using standardised sampling protocols, we show that the spatial variation in species composition (beta diversity) of shallow subtidal macrobenthic communities of sub-Antarctic (Strait of Magellan and Yendegaia Fjord [Beagle Channel]) and Antarctic (Fildes Bay [King George Island, West Antarctic Peninsula]) localities reflects a high contribution of stochastic processes to community assembly. Null model analyses indicated that random sampling from species pools of different sizes drove the observed among-locality differences in incidence- and abundance-based beta diversity. We analysed a normalised stochasticity ratio (NST), which delimits between more deterministic (<50%) and more stochastic (>50%) assembly. NST was notably larger than 50%, with mean values of 69.5% (95% CI = 69.2–69.8%), 62.5% (62.1–62.9%), and 72.8% (72.5–73.2%) in Strait of Magellan, Yendegaia Fjord, and Fildes Bay, respectively. Accordingly, environmental factors, such as depth, seawater temperature, salinity, and underwater light penetration, accounted for a small fraction of the spatial variation in community composition across the three localities. In this region, therefore, stochastic processes could have stronger effects on community assembly than deterministic niche-based factors. As anthropogenic biotic homogenisation continues apace, our study can give useful insights into the major ecological processes in Southern Ocean’ coastal marine communities.

Spatial and Annual Variation in Microbial Abundance, Community Composition, and Diversity Associated With Alpine Surface Snow.

Understanding microbial community dynamics in the alpine cryosphere is an important step toward assessing climate change impacts on these fragile ecosystems and meltwater-fed environments downstream. In this study, we analyzed microbial community composition, variation in community alpha and beta diversity, and the number of prokaryotic cells and virus-like particles (VLP) in seasonal snowpack from two consecutive years at three high altitude mountain summits along a longitudinal transect across the European Alps. Numbers of prokaryotic cells and VLP both ranged around 104 and 105 per mL of snow meltwater on average, with variation generally within one order of magnitude between sites and years. VLP-to-prokaryotic cell ratios spanned two orders of magnitude, with median values close to 1, and little variation between sites and years in the majority of cases. Estimates of microbial community alpha diversity inferred from Hill numbers revealed low contributions of common and abundant microbial taxa to the total taxon richness, and thus low community evenness. Similar to prokaryotic cell and VLP numbers, differences in alpha diversity between years and sites were generally relatively modest. In contrast, community composition displayed strong variation between sites and especially between years. Analyses of taxonomic and phylogenetic community composition showed that differences between sites within years were mainly characterized by changes in abundances of microbial taxa from similar phylogenetic clades, whereas shifts between years were due to significant phylogenetic turnover. Our findings on the spatiotemporal dynamics and magnitude of variation of microbial abundances, community diversity, and composition in surface snow may help define baseline levels to assess future impacts of climate change on the alpine cryosphere.

Geochemical and isotopical variations within the Campanian Comagmatic Province: implications on magma source composition

A spatial variation in chemical and isotopical composition is observed between the volcanoes belonging to the Campanian Comagmatic Province. At a given MgO content, magmas from volcanic islands (Procida and Ischia) are enriched in Ti, Na, depleted in La, Ba, Rb, Sr, Th, K contents, and shows lower LREE/HFSE (e.g., La/Nb = = 1-2), lower Sr-Pb isotopic ratios and higher Nd isotopic ratios with respect to magmas from volcanoes locat- ed inland (Campi Flegrei and Somma-Vesuvius). The observed compositional variations are explained involving two different mantle sources in the genesis of the magmas erupted in this region: a deeper asthenospheric man- tle source, from which the Tyrrhenian magmas also derived and a lithospheric mantle source enriched by slab- derived fluids. The contribution of the enriched-lithospheric mantle became more pronounced moving from the Tyrrhenian abyssal plain through the Italian Peninsula where it dominates, likely in response to the thickening of the lithosphere observed under the Peninsula

Spatiotemporal Distribution of Herbivorous Insects Along Always-Green Mountaintop Forest Islands

Insects make up the bulk of terrestrial diversity and about half of insect species are herbivores that have direct relationships with their host plants and are the basis of the entire food chain, on which wildlife and humanity depend. Some herbivorous insect traits, such as their spatio-temporal distribution, are especially relevant in the current scenario of global changes, which are more pronounced in high elevation areas, helping to improve the effectiveness of conservation actions. Here we evaluated the influence that different spatiotemporal scales have on three free-feeding herbivorous insect guilds (fluid-feeding, leaf-chewing, and xylophagous insects) in montane forest islands immersed in a grassland-dominated matrix (campo rupestre). We assessed whether species turnover or nestedness was the main component determining both spatial and temporal species composition variation (β-diversity) of the herbivorous insect community. We also checked the temporal effect on herbivorous insect guilds composition between vertical strata. We sampled herbivorous insects during two summers and two winters in 14 forest islands of different sizes and shapes in a natural mountainous fragment located in southeastern Brazil. A total of 6597 herbivorous insects representing 557 morphospecies were sampled, 290 of which were fluid-feeding, 147 leaf-chewing and 120 xylophagous insects. We found a main contribution of time scale in the organization of the herbivorous insect composition sampled in this study, mainly by turnover, with small differences among guilds. Additionally, we could see that climate determined the local variation of species, corroborating that we have a highly variable always-green system over space and time where the understory community varies less in comparison to the canopy community. Our findings suggest that long-term ecological research on herbivorous community structure in relation to climatic variation is a key element for future investigations, which can be decisive for the conservation of herbivorous insect communities. We also suggest that the effects of anthropogenic pressures must be monitored in this system, since these forest islands may serve as warming refuges in a fragmented landscape holding an invaluable diversity of species that, without these old-growth forest reservoirs, would be doomed to disappear.

Tree species diversity mapping using UAS-based digital aerial photogrammetry point clouds and multispectral imageries in a subtropical forest invaded by moso bamboo (Phyllostachys edulis)

Moso bamboo (Phyllostachys edulis) tends to invade any surrounding forest areas due to its aggressive characteristics (fast growth and clonal reproduction), where it changes the species composition and canopy structure of the forests, and has negative effects on forest diversity and ecosystem functions. Unmanned aerial system (UAS)-based remote sensing has the capacity to provide high-resolution, continuous spatial data that can be used to detect forest invasion dynamics. In this study, UAS-based RGB and multispectral image data and digital aerial photogrammetric point cloud (PPC) were acquired and used to detect areas of bamboo invasion in a subtropical forest of Southern China. First, a point cloud segmentation (PCS) method was applied for individual tree detection (ITD) using photogrammetric point clouds (PPCs). A random forest (RF) classifier was used to perform tree species classification based on PPC metrics, vegetation indices, and texture metrics. Finally, based on the results of the ITD and tree species classification, alpha-diversity (i.e., the species richness (S), Shannon-Wiener (H’), Simpson (D), and Pielou’s evenness index(J)) and the spatial variation in species composition along the altitude gradient (beta-diversity) in the invaded forests were assessed. Results demonstrated that PCS worked well for tree detection in invaded forests (F1-score = 80.63%), and the overall accuracy of tree species classification was 75.69%, with a kappa accuracy of 73.76%. The forest diversity analysis showed that all alpha-diversity values were generally predicted well (R2 = 0.84–0.91, RMSE = 0.05–0.84). The diversity showed a decreasing tendency with increasing bamboo invasion, and the predominantly broad-leaved invaded forests had higher diversity than the predominantly coniferous invaded forests. The human intervention had a significant impact on bamboo invasion. The ANOVA of the dispersion of the dissimilarities along the elevation gradient showed significant differences in abundance-weighted similarity among the altitude classes (ANOVA of the Bray-Curtis dissimilarity, F4,40 = 6.453, P = 0.0004***; ANOVA of the Jaccard dissimilarity, F4,40 = 5.20, P = 0.0017**). This study indicated the potential benefits of using UAS- based remote sensing data to identify tree species and predict forest diversity in bamboo-invaded forests. Our results suggested that tree species diversity can be directly estimated using individual tree detection results based on PPC data instead of modelling the relationship between field-measured indices and remote sensing data-derived metrics, and revealed the influence of human intervention on bamboo invasion.

Complex relationships between beta diversity and dispersal in meta‐community models

Dispersal is one of the most important drivers of community assembly. Understanding how dispersal impacts spatial variations in community composition (beta diversity) is crucial for predicting biodiversity change during the Anthropocene. Classic theories and a large amount of empirical evidence have led to a common belief that increasing dispersal rate should lead to regional community homogenization (lower beta diversity). However, recent empirical studies show that increasing dispersal can also lead to regional community divergence when interacting with other processes such as disturbance and priority effect. The underappreciation of the complex relationship between beta diversity and dispersal might impede our ability to make accurate ecological forecasts. To address this concern, I examine the beta diversity–dispersal relationship through extinction and colonization dynamics in meta‐community models. I find that a wide range of beta diversity–dispersal relationships (e.g. negative, positive, hump‐shaped) can be generated by changes in species‐level occurrence probabilities when meta‐population dispersal (rather than mainland–island dispersal), disturbance and strong biotic interactions are at play. Specifically, reducing the variance of species‐level occurrence probabilities leads to community divergence and increasing the mean occurrence probability leads to community homogenization; a positive or hump‐shaped beta diversity–dispersal relationship emerges when the effect of the decreasing variance is stronger than the effect of increasing mean. These findings highlight the intrinsic constraint of occupancy stochasticity on beta diversity changes and echo the call for more realistic manipulations of stochastic dispersal and a detailed understanding of the interaction networks to test various beta diversity–dispersal relationships in future empirical studies.

Assemblage reorganization of South African dragonflies due to climate change

AbstractAimClimate change is expected to cause large shifts in species assemblages such as dragonflies and damselflies (Insecta: Odonata). Here, we assess the influence of environmental drivers of turnover on Odonata assemblages. Secondly, we map the predicted spatial variation in species composition, first as a gradient of assemblage similarity, and then as discrete bioregions delineating major areas of odonate endemism. Finally, we map the magnitude of expected change in species turnover in response to climate change under two emission scenarios.LocationSouth Africa.MethodsWe used a spatial database comprising of 164 species of odonates and 20 covariates, to explore changes in compositional turnover using generalized dissimilarity models. Bioregions were compiled through various clustering techniques.ResultsPresent‐day odonate bioregions correspond to climatic zones and are clearly separated by transitional zones with rapid spatial turnover. Present odonate bioregions are projected to undergo extensive reorganization by 2050 and 2070. Temporal turnover in species composition is expected to reach up to 80% in the large arid interior and 64% along the coast. Half of all South Africa's protected areas are likely to experience climate induced changes to dragonfly bioregions in the near future.Main conclusionsSpecies assemblages are rapidly changing. This work highlights future shifts in climate will result in complex and nonlinear responses in Odonata communities. With ongoing climate change, current odonate bioregions are predicted to expand while others will contract considerably in size within the next 30 years. The current demarcated protected areas may be inadequate to protect dragonflies as climates change. Odonata can be used to track forefronts of climate change, which will likely affect a larger array of taxa as well.

Analysis of pollen across the surface sediments of Lake Imbradas, Lithuania

AbstractIn conventional pollen analysis, usually one sediment core per basin is analyzed to reconstruct past environmental conditions. This approach does not consider spatial heterogeneity of pollen assemblages, and assumes that one analyzed location is representative of the whole basin. To improve the spatial resolution of fossil pollen studies, further knowledge of the factors influencing variations in pollen assemblages throughout a basin is needed. We examined the spatial heterogeneity of pollen assemblages from 45 lacustrine surface samples from a lake with relatively simple hydrology and compared this dense network of surface pollen samples with the Lithuanian State Forest Service arboreal vegetation database. Calculations of pollen productivity at different locations across the lake revealed variations in the behavior of a pollen-vegetation relationship model in different parts of the basin. Our findings suggest that the model underestimated pollen contributions from the lakeshore vegetation. We demonstrate that detailed investigations of surface pollen as a step prior to fossil pollen investigations can provide useful insights, including understanding the influence of sedimentation rate on modelling results and spatial variations in pollen composition, thus providing guidance for site selection for fossil pollen studies.

Polychaete (Annelida) Diversity Patterns in Southern Gulf of Mexico: The Influence of Spatial Structure and Environmental Variables

A comprehensive database was built to examine the spatial diversity patterns of polychaete species from the continental shelf in Southern Gulf of Mexico. Using Cluster and nMDS analysis we found the composition of polychaete species to be different between the terrigenous and carbonate regions of the Gulf. To test the relative importance of spatial and environmental components in the polychaetae community structure in the Southern Gulf of Mexico, we examined the spatial relationships between polychaetae assemblages and environmental variables over broad geographical scales. A distance-based redundancy analysis (dbRDA) and variation partitioning was used to quantify the relative importance of these explanatory variables on the spatial variations of species richness and composition. Variation partitioning is an important tool to investigate the importance of spatial structure to species distribution in communities, but it has not yet been used in marine ecosystems. The significance level of spatial and environmental components to the distribution of polychaete species showed that the combined effect of spatial processes and sediment characteristics explained a higher percentage of variance than those parameters could alone.

Revealing floristic variation and map uncertainties for different plant groups in western Amazonia

AbstractQuestionsUnderstanding spatial variation in floristic composition is crucial to quantify the extent, patchiness and connectivity of distinct habitats and their spatial relationships. Broad‐scale variation in floristic composition and the degree of uniqueness of different regions remains poorly mapped and understood in several areas across the globe. We here aim to map vegetation heterogeneity in Amazonia.LocationMiddle Juruá river region, Amazonas State, Brazil.MethodsWe mapped four plant groups by applying machine learning to scale up locally observed community composition and using environmental and remotely sensed variables as predictors, which were obtained as GIS layers. To quantify how reliable our predictions were, we made an assessment of model transferability and spatial applicability. We also compared our floristic composition map to the official Brazilian national‐level vegetation classification.ResultsThe overall performance of our floristic models was high for all four plant groups, especially ferns, and the predictions were found to be spatially congruent and highly transferable in space. For some areas, the models were assessed not to be applicable, as the field sampling did not cover the spectral or environmental characteristics of those regions. Our maps show extensive habitat heterogeneity across the region. When compared to the Brazilian vegetation classification, floristic composition was relatively homogeneous within dense forests, while floristic heterogeneity in rainforests classified as open was high.ConclusionOur maps provide geoecological characterization of the regions and can be used to test biogeographical hypotheses, develop species distribution models and, ultimately, aid science‐based conservation and land‐use planning.

The ectomycorrhizal fungal communities react differently to climatic, edaphic and spatial variables depending on their host species

AbstractAimEctomycorrhizal (ECM) fungal community structures can vary across sites at a regional scale (>1,000 km), affected by abiotic and biotic environments, dispersal abilities of the fungi, or ecological drift, even among forests of the same host tree species. The spatial patterns of such variation may differ among associated host species and their growth environments, but our knowledge about this remains limited. In the present study, we aimed to investigate whether the ECM fungal community structures (i.e. species richness and species composition) at the regional scale and their driving factors vary across hosts.LocationJapan.TaxonECM fungi associated with Fagus crenata and Castanopsis sieboldii.MethodsUsing DNA metabarcoding of fine roots, the ECM fungal communities of 15 Fagus crenata forests across their distribution range were characterised. The resultant community structure of ECM fungi, as well as the relative effects of edaphic, climatic and spatial factors on community composition were compared with those of 12 Castanopsis sieboldii forests investigated in a previous study.ResultsECM fungal community composition differed between the two Fagaceae hosts. The spatial pattern of ECM fungal community composition also differed between hosts. Specifically, the spatial variation in community composition across sites was smaller in F. crenata forests than in C. sieboldii forests. The spatial pattern of ECM fungal communities of F. crenata forests was explained by climatic and edaphic factors, while that of C. sieboldii forests was explained by spatial and edaphic factors.Main conclusionsOn a regional scale in Japan, the spatial pattern of ECM fungal communities and its driving factors varied between two Fagaceae host species. Our results provide an example that the difference in associated host leads to the difference in environmental response among ECM fungal communities.

A new joint species distribution model for faster and more accurate inference of species associations from big community data

Abstract Joint species distribution models (JSDMs) explain spatial variation in community composition by contributions of the environment, biotic associations and possibly spatially structured residual covariance. They show great promise as a general analytical framework for community ecology and macroecology, but current JSDMs, even when approximated by latent variables, scale poorly on large datasets, limiting their usefulness for currently emerging big (e.g. metabarcoding and metagenomics) community datasets. Here, we present a novel, more scalable JSDM (sjSDM) that circumvents the need to use latent variables by using a Monte Carlo integration of the joint JSDM likelihood together with flexible elastic net regularization on all model components. We implemented sjSDM in PyTorch, a modern machine learning framework, which allows making use of both CPU and GPU calculations. Using simulated communities with known species–species associations and different number of species and sites, we compare sjSDM with state‐of‐the‐art JSDM implementations to determine computational runtimes and accuracy of the inferred species–species and species–environment associations. We find that sjSDM is orders of magnitude faster than existing JSDM algorithms (even when run on the CPU) and can be scaled to very large datasets. Despite the dramatically improved speed, sjSDM produces more accurate estimates of species association structures than alternative JSDM implementations. We demonstrate the applicability of sjSDM to big community data using eDNA case study with thousands of fungi operational taxonomic units (OTU). Our sjSDM approach makes the analysis of JSDMs to large community datasets with hundreds or thousands of species possible, substantially extending the applicability of JSDMs in ecology. We provide our method in an R package to facilitate its applicability for practical data analysis.

Characterizing Sources and Composition of Chromophoric Dissolved Organic Matter in a Key Drinking Water Reservoir Lake Tianmu

Lake Tianmu is an important source of drinking water, and its water quality can influence ecosystem service functions. Unraveling the sources and composition of chromophoric dissolved organic matter (CDOM) that can affect water treatment processes is necessary to maintain water supply safety and ecosystem service functioning of Lake Tianmu. Samples were collected monthly in 2017 and analyzed for CDOM absorbance and fluorescent spectra using parallel factor analysis (PARAFAC) to investigate the spatial and temporal variations of CDOM sources and composition in Lake Tianmu. PARAFAC results showed that CDOM in Lake Tianmu was mainly composed of a microbial humic-like component C1 (44.2%±9.8%), followed by a tryptophan-like component C2 (29.2%±4.3%), tyrosine-like component C3 (17.2%±13.1%), and terrestrial humic-like component, C4 was the lowest (9.4%±2.4%). The CDOM abundance a(254) and fluorescence intensities of C1 and C2 were significantly higher in the river mouths than in the downstream lake regions, whereas the spectral slope S275-295 was significantly lower in the river mouths (t-test, P<0.05), indicating that allochthonous inputs cause an elevated degree of humification and relative increase in the molecular weight of CDOM in the inflowing river mouths. Seasonal differences in CDOM composition were mainly ascribed to the a(254) and fluorescence intensities of C1, C2, and C4 being significantly higher in the summer and autumn than in the winter and spring (t-test, P<0.05). Our results showed that the influences of different seasons on CDOM composition comprise differences in rainfall and runoff input, as well as water temperature, thermal stratification, phytoplankton biomass, and mineralization of CDOM by light and microbes.

Intrinsic and growth-mediated cell and matrix specialization during murine meniscus tissue assembly.

The incredible mechanical strength and durability of mature fibrous tissues and their extremely limited turnover and regenerative capacity underscores the importance of proper matrix assembly during early postnatal growth. In tissues with composite extracellular matrix (ECM) structures, such as the adult knee meniscus, fibrous (Collagen-I rich), and cartilaginous (Collagen-II, proteoglycan-rich) matrix components are regionally segregated to the outer and inner portions of the tissue, respectively. While this spatial variation in composition is appreciated to be functionally important for resisting complex mechanical loads associated with gait, the establishment of these specialized zones is poorly understood. To address this issue, the following study tracked the growth of the murine meniscus from its embryonic formation through its first month of growth, encompassing the critical time-window during which animals begin to ambulate and weight bear. Using histological analysis, region specific high-throughput qPCR, and Col-1, and Col-2 fluorescent reporter mice, we found that matrix and cellular features defining specific tissue zones were already present at birth, before continuous weight-bearing had occurred. These differences in meniscus zones were further refined with postnatal growth and maturation, resulting in specialization of mature tissue regions. Taken together, this work establishes a detailed timeline of the concurrent spatiotemporal changes that occur at both the cellular and matrix level throughout meniscus maturation. The findings of this study provide a framework for investigating the reciprocal feedback between cells and their evolving microenvironments during assembly of a mechanically robust fibrocartilage tissue, thus providing insight into mechanisms of tissue degeneration and effective regenerative strategies.

Taxonomic, Temporal, and Spatial Variations in Zooplankton Fatty Acid Composition in Puget Sound, WA, USA

Fatty acid (FA) content and composition of zooplankton in Puget Sound, Washington (USA) was studied to investigate the nutritional quality of diverse zooplankton prey for juvenile salmon (Oncorhynchus spp.) in terms of their essential fatty acid (EFA) content. The study focus was on eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA), and arachidonic acid (ARA) as these are key FA needed to maintain growth and development of juvenile fish. The different zooplankton taxa varied in their FA composition. Much of the variation in FA composition was driven by 18:1ω9 (a biomarker of carnivory), ARA, DHA, and FA characteristic of diatoms, which are linked to zooplankton diet sources. Gammarid and hyperiid amphipods contained the highest amount of EFA, particularly the gammarid amphipod Cyphocaris challengeri, while shrimp and copepods had much lower EFA content. Crab larvae, which are important prey for juvenile salmon in Puget Sound, had intermediate EPA + DHA content and the lowest DHA/EPA ratio, and were rich in diatom biomarkers. Temporal and spatial trends in zooplankton lipids were less apparent than the taxonomic differences, although the EFA content increased from spring to summer in Cancridae zoeae and the amphipod C. challengeri. These results on taxon-specific EFA content provide baseline information on the nutritional quality of zooplankton that can be applied in food web models. Combining zooplankton fatty acid data (quality) with taxon-specific zooplankton biomass data (quantity) enables development of new, sensitive indicators of juvenile fish production to help assess recent declines in salmon production in the Pacific Northwest and predict future adult returns.

Enhancement of Magnetoelectric Effect in Compositionally Graded Ferroelectric/Ferromagnetic Pb(1−x)SrxTiO3/CoFe2O4 Nanocomposites

In this study, phase-field model is developed for ferroelectric/ferromagnetic nanocomposites, in which ferroelectric composition is spatially varied along the thickness of ferroelectric layers. The developed phase field model is applied to investigate the effect of composition gradient on magnetoelectric response of the multilayer nanocomposite. Stripe domain structures are observed in both ferroelectric and ferromagnetic layers, however the sizes of magnetic domains are larger than that of polarization ones. Particularly, the size of polarization domains and geometry of domain walls are altered according to the gradient of ferroelectric composition. The obtained results suggest that the larger the composition gradient is, the higher the magnetoelectric effect becomes. The enhancement of magnetoelectric effect is attributed to the concentration of energy in ferroelectric layer, which originates from the spatial variation of ferroelectric composition.

Assessing changes in stream macroinvertebrate communities across ecological gradients using morphological versus DNA metabarcoding approaches

Freshwater macroinvertebrates provide valuable indicators for biomonitoring ecosystem change in relation to natural and anthropogenic drivers. DNA metabarcoding is an efficient approach for estimating such indicators, but its results may differ from morphotaxonomic approaches traditionally used in biomonitoring. Here we test the hypothesis that despite differences in the number and identity of taxa recorded, both approaches may retrieve comparable patterns of community change, and detect similar ecological gradients influencing such changes. We compared results obtained with morphological identification at family level of macroinvertebrates collected at 80 streams under a Water Framework Directive biomonitoring program in Portugal, with results obtained with metabarcoding from the ethanol preserving the bulk samples, using either single (COI-M19BR2, 16S-Inse01, 18S-Euka02) or multiple markers. Metabarcoding recorded less families and different communities compared to morphotaxonomy, but community sensitivities to disturbance estimated with the IASPT index were more similar across approaches. Spatial variation in local community metrics and the factors influencing such variation were significantly correlated between morphotaxonomy and metabarcoding. After reducing random noise in the dissimilarity matrices, the spatial variation in community composition was also significantly correlated across methods. A dominant gradient of community change was consistently retrieved, and all methods identified a largely similar set of anthropogenic stressors strongly influencing such gradient. Overall, results confirm our initial hypothesis, suggesting that morphotaxonomy and metabarcoding can estimate consistent spatial patterns of community variation and their main drivers. These results are encouraging for macroinvertebrate biomonitoring using metabarcoding approaches, suggesting that they can be intercalibrated with morphotaxonomic approaches to recover equivalent spatial and temporal gradients of ecological change.