Exploring ecological patterns with structural equation modeling and Bayesian analysis

Daqu and environmental microbiota regulate fatty acid biosynthesis via driving the core microbiota in soy sauce aroma type liquor fermentation

Fatty acids are considered as important compounds for the aroma and taste of Chinese liquor. Revealing the core microbiota related with fatty acid biosynthesis and how they are influenced are essential to control fatty acids in spontaneous Chinese liquor fermentation. Herein, we identified the core microbiota related with fatty acid biosynthesis based on their microbial abundance, abundance and expression level of genes related with fatty acid biosynthesis, using high-throughput amplicon sequencing, metagenomic and metatranscriptomic analysis, respectively. Acetilactobacillus, Kroppenstedtia, Saccharomyces, Paecilomyces and Pichia were identified as the core microbiota (the criteria for identifying core microbiota: average relative abundance ≥1 %, average abundance of related genes >400 fragments per kilobase of transcript per million fragments mapped [FPKM], and expression level of related genes >1000 FPKM) related with fatty acid biosynthesis. SourceTracker analysis showed that Daqu mainly provided Kroppenstedtia (34.01 %) and Acetilactobacillus (3.31 %). Ground mainly provided Pichia (47.47 %), Saccharomyces (16.17 %) and Paecilomyces (8.55 %). Structural equation model revealed that Daqu and environmental microbiota drove the core microbiota (P < 0.05), and the core microbiota drove the biosynthesis of fatty acids (P < 0.05). This work revealed the important role of Daqu and environmental microbiota in fatty acid biosynthesis in liquor fermentation. It would benefit controlling fatty acids in liquor fermentation, and improving the liquor quality.

Dung removal increases under higher dung beetle functional diversity regardless of grazing intensification

Dung removal by macrofauna such as dung beetles is an important process for nutrient cycling in pasturelands. Intensification of farming practices generally reduces species and functional diversity of terrestrial invertebrates, which may negatively affect ecosystem services. Here, we investigate the effects of cattle-grazing intensification on dung removal by dung beetles in field experiments replicated in 38 pastures around the world. Within each study site, we measured dung removal in pastures managed with low- and high-intensity regimes to assess between-regime differences in dung beetle diversity and dung removal, whilst also considering climate and regional variations. The impacts of intensification were heterogeneous, either diminishing or increasing dung beetle species richness, functional diversity, and dung removal rates. The effects of beetle diversity on dung removal were more variable across sites than within sites. Dung removal increased with species richness across sites, while functional diversity consistently enhanced dung removal within sites, independently of cattle grazing intensity or climate. Our findings indicate that, despite intensified cattle stocking rates, ecosystem services related to decomposition and nutrient cycling can be maintained when a functionally diverse dung beetle community inhabits the human-modified landscape.

Temporal patterns of algae in different urban lakes and their correlations with environmental variables in Xi'an, China

Urban lakes were critical in aquatic ecology environments, but how environmental factors affected the distribution and change characteristics of algal communities in urban lakes of Xi'an city was not clearly. Here, we investigated the algal community structure of six urban lakes in Xi'an and evaluated the effects of water quality parameters on algae. The results indicated that the significant differences on physicochemical parameters existed in different urban lakes. The maximum concentration of total phosphorus in urban lakes was (0.18 ± 0.01) mg/L and there was a phenomenon of phosphorus limitation. In addition, 51 genera of algae were identified and Chlorella sp. was the dominant algal species, which was affiliated with Chlorophyta. Network analysis elucidated that each lake had a unique algal community network and the positive correlation was dominant in the interaction between algae species, illustrating that mature microbial communities existed or occupied similar niches. Redundancy analysis illustrated that environmental factors explained 47.35% variance of algal species-water quality correlation collectively, indicating that water quality conditions had a significant influence on the temporal variations of algae. Structural equation model further verified that algal community structure was directly or indirectly regulated by different water quality conditions. Our study shows that temporal patterns of algal communities can reveal the dynamics and interactions of different urban ecosystem types, providing a theoretical basis for assessing eutrophication levels and for water quality management.

Explore variations of DOM components in different landcover areas of riparian zone by EEM-PARAFAC and partial least squares structural equation model

Dissolved organic matter (DOM) plays key roles in species-distribution of contaminants and the biogeochemical cycle of carbon in ecosystems. Riparian zone is the representative of water-land ecotone and controls the DOM exchange between water and land. However, the variance of DOM in different landcover areas of an urban river riparian zone is unknown. In this study, fluorescence excitation-emission matrix (EEM) spectroscopy coupled with parallel factor analysis (PARAFAC) and partial least squares structural equation model (PLS-SEM) was applied to character dissolved organic matter (DOM) fractions in four types of landcover riparian areas (natural forest, artificial forest, semi-natural grassland, and cropland) of Puhe River and trace latent factors. Soil samples were collected at 0-20 cm, 20-40 cm, 40-60 cm, and 60-80 cm. The results showed that soil DOM components and humification varied between forests with grassland and cropland samples, and soil humification was obviously higher in the forest samples than that in the grassland and cropland samples. In the natural and artificial forest soils, the humic/fulvic-like were the dominant fractions of DOM, whose variations were smaller than the protein-like with soil depths. However, the tyrosine-like was the representative component in the grassland and cropland soils, whose variation was smaller than the humus substances. According to the PLS-SEM, the DOM components and humification were affected by soil physiochemical properties and DOM sources. The humification in the forest soils had a positive correlation with tryptophan-like, which derived from blended source of the autochthonous and terrigenous. Nevertheless, a positive correlation was observed between humification and humus substances, which could derive from microbial degradation of tyrosine-like, in the grassland and cropland soils. Moreover, the soil physiochemical properties were negatively related to DOM components in all soil samples, which could affect indirectly soil humification. Therefore, EEM combined with PARAFAC and PLS-SEM might be an effective method to investigate DOM fractions and trace the latent factors in different landcover areas of the riparian zone.

Effects of detection limits on spatial modeling of water quality in lakes

Identifying sources and fate of nutrients and pollutants in lake waters is often difficult when key analytes (e.g., dissolved phosphate) are frequently below analytical detection limits (non-detects). One way of dealing with this problem in water quality data is to replace non-detects with "fill-in" values using imputation methods (IMs). While their performance for estimating descriptive statistics (e.g., mean and variance) has been evaluated comprehensively for many environmental variables, whether IMs can reconstruct spatial patterns using long-term water quality data with non-detects under different magnitudes of spatial variation remains under-studied. We developed an integrative framework, combining numerical simulations with univariate and multivariate approaches, to compare performance of nine IMs in recovering spatial patterns of water quality data with different degrees of spatial heterogeneity. We applied this framework to a 12-year water quality dataset sampled from the nearshore region of Lake Ontario near Pickering and Ajax to show the usefulness of IMs in estimating water quality spatial variation. Firstly, in the simplest modeling scenario, we found that most IMs reproduced spatial patterns of univariate data well with ≤30 % non-detects in the dataset. Secondly, when spatial patterns were heterogeneous (e.g., when weak water mixing in nearshore regions limited nutrient transport from input sources to offshore regions), most IMs also performed well by recovering spatial variation in multivariate data with ≤80 % non-detects. Thirdly, when spatial distributions were homogeneous (e.g., when strong water mixing increased transport of nutrients from input sources to other lake areas), only weighted quantile sum regression (WQSR) performed well in reconstructing spatial multivariate data trends with ≤10 % non-detects. Our study highlighted that IMs (especially WQSR) are useful for reconstructing spatial trends of water quality in large lakes. However, potential interactions between spatial heterogeneity and non-detect frequency must be considered when selecting an appropriate IM procedure to accurately model spatial patterns in water quality.

Network analysis to evaluate complexities in relationships among fermentation variables measured within continuous culture experiments

The objective of this study was to leverage a frequentist (ELN) and Bayesian learning (BLN) network analyses to summarize quantitative associations among variables measured in 4 previously published dual-flow continuous culture fermentation experiments. Experiments were originally designed to evaluate effects of nitrate, defaunation, yeast, and/or physiological shifts associated with pH or solids passage rates on rumen conditions. Measurements from these experiments that were used as nodes within the networks included concentrations of individual volatile fatty acids, mM and nitrate, NO3-,%; outflows of non-ammonia nitrogen (NAN, g/d), bacterial N (BN, g/d), residual N (RN, g/d), and ammonia N (NH3-N, mg/dL); degradability of neutral detergent fiber (NDFd, %) and degradability of organic matter (OMd, %); dry matter intake (DMI, kg/d); urea in buffer (%); fluid passage rate (FF, L/d); total protozoa count (PZ, cells/mL); and methane production (CH4, mmol/d). A frequentist network (ELN) derived using a graphical LASSO (least absolute shrinkage and selection operator) technique with tuning parameters selected by Extended Bayesian Information Criteria (EBIC) and a BLN were constructed from these data. The illustrated associations in the ELN were unidirectional yet assisted in identifying prominent relationships within the rumen that were largely consistent with current understanding of fermentation mechanisms. Another advantage of the ELN approach was that it focused on understanding the role of individual nodes within the network. Such understanding may be critical in exploring candidates for biomarkers, indicator variables, model targets, or other measurement-focused explorations. As an example, acetate was highly central in the network suggesting it may be a strong candidate as a rumen biomarker. Alternatively, the major advantage of the BLN was its unique ability to imply causal directionality in relationships. Because the BLN identified directional, cascading relationships, this analytics approach was uniquely suited to exploring the edges within the network as a strategy to direct future work researching mechanisms of fermentation. For example, in the BLN acetate responded to treatment conditions such as the source of N used and the quantity of substrate provided, while acetate drove changes in the protozoal populations, non-NH3-N and residual N flows. In conclusion, the analyses exhibit complementary strengths in supporting inference on the connectedness and directionality of quantitative associations among fermentation variables that may be useful in driving future studies.

Disentangling direct and indirect effects of extreme events on coastal wetland communities

One of the primary ways in which climate change will impact coastal freshwater wetlands is through changes in the frequency, intensity, timing and distribution of extreme weather events. Disentangling the direct and indirect mechanisms of population- and community-level responses to extreme events is vital to predicting how species composition of coastal wetlands will change under future conditions. We extended static structural equation modelling approaches to incorporate system dynamics in a multi-year multispecies occupancy model to quantify the effects of extreme weather events on a coastal freshwater wetland system. We used data from an 8-year study (2009-2016) on St. Marks National Wildlife Refuge in Florida, USA, to quantify species-specific and community-level changes in amphibian and fish occupancy associated with two flooding events in 2012 and 2013. We examine how physical changes to the landscape, including potential changes in salinity and increased wetland connectivity, may have contributed to or exacerbated the effects of these extreme weather events on the biota of isolated coastal wetlands. We provide evidence that the primary effects of flooding on the amphibian community were through indirect mechanisms via changes in the composition of the sympatric fish community that may have had lethal (i.e. through direct predation) or non-lethal (i.e. through direct or indirect competitive interactions) effects. In addition, we have shown that amphibian species differed in their sensitivity to direct flooding effects and indirect changes in the fish community and wetland-specific conductance, which led to variable responses across the community. These effects led to the overall decline in amphibian species richness from 2009 to 2016, suggesting that wetland-breeding amphibian communities on St. Marks National Wildlife Refuge may not be resilient to predicted changes in coastal disturbance regimes because of climate change. Understanding both direct and indirect effects, as well as species interactions, is important for predicting the effects of a changing climate on individual species, communities and ecosystems.

Modelling and predicting population of core fungi through processing parameters in spontaneous starter (Daqu) fermentation

Traditional fermented foods are usually produced by spontaneous fermentation with multiple microorganisms. Environmental factors play important roles in microbial succession. However, it is still unclear how the processing parameters regulate the microbiota during fermentation. Here, we reveal the effects of processing parameters on the core microbiota in spontaneous fermentation of Chinese liquor starter. Rhizopus, Pichia, Wickerhamomyces, Saccharomycopsis, Aspergillus and Saccharomyces were identified as core microbiota using amplicon sequencing and metaproteomics analysis. Fermentation moisture gradually decreased from 34.8% to 14.2%, and fermentation temperature varied between 17.0 °C and 35.3 °C during the fermentation. Mantel test showed that fermentation moisture (P < 0.001) and fermentation temperature (P < 0.05) significantly affected the core microbiota. Moreover, structural equation modelling analysis indicated that fermentation moisture (P < 0.001) and fermentation temperature (P < 0.001) were respectively influenced by the processing parameters, room humidity and room temperature. The succession of Rhizopus, Pichia, Wickerhamomyces, Saccharomycopsis and Aspergillus were significantly affected by room humidity (P < 0.05), and the succession of Saccharomyces was significantly affected by room temperature (P < 0.001). Further, models were constructed to predict the population of core microbiota by room humidity and room temperature, using Gaussian process regression and linear regression (P < 0.05). This work would be beneficial for regulating microorganisms via controlling processing parameters in spontaneous food fermentations.

Equity and determinants in universal health coverage indicators in Iraq, 2000-2030: a national and subnational study

Background

Equity is one of three dimensions of universal health coverage (UHC). However, Iraq has had capital-focused health services and successive conflicts and political turmoil have hampered health services around the country. Iraq has embarked on a new reconstruction process since 2018 and it could be time to aim for equitable healthcare access to realise UHC. We aimed to examine inequality and determinants associated with Iraq’s progress towards UHC targets.

Methods

We assessed the progress toward UHC in the context of equity using six nationally representative population-based household surveys in Iraq in 2000–2018. We included 14 health service indicators and two financial risk protection indicators in our UHC progress assessment. Bayesian hierarchical regression model was used to estimate the trend, projection, and determinant analyses. Slope and relative index of inequality were used to assess wealth-based inequality.

Results

In the national-level health service indicators, inequality indices decreased substantially from 2000 to 2030. However, the wide inequalities are projected to remain in DTP3, measles, full immunisations, and antenatal care in 2030. The pro-rich inequality gap in catastrophic health expenditure increased significantly in all governorates except Sulaimaniya from 2007 to 2012. The higher increases in pro-rich inequality were found in Missan, Karbala, Erbil, and Diala. Mothers’ higher education and more antenatal care visits were possible factors for increased coverage of health service indicators. The higher number of children and elderly population in the households were potential risk factors for an increased risk of catastrophic and impoverishing health payment in Iraq.

Conclusions

To reduce inequality in Iraq, urgent health-system reform is needed, with consideration for vulnerable households having female-heads, less educated mothers, and more children and/or elderly people. Considering varying inequity between and within governorates in Iraq, reconstruction of primary healthcare across the country and cross-sectoral targeted interventions for women should be prioritised.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12939-021-01532-0.

A protocol for modelling generalised biological responses using latent variables in structural equation models

In this paper, we consider the problem of how to quantitatively characterise the degree to which a study object exhibits a generalised response. By generalised response, we mean a multivariate response where numerous individual properties change in concerted fashion due to some internal integration. In latent variable structural equation modelling (LVSEM), we would typically approach this situation using a latent variable to represent a general property of interest (e.g. performance) and multiple observed indicator variables that reflect the specific features associated with that general property. While ecologists have used LVSEM in a number of cases, there is substantial potential for its wider application. One obstacle is that LV models can be complex and easily over-specified, degrading their value as a means of generalisation. It can also be challenging to diagnose causes of misspecification and understand which model modifications are sensible. In this paper, we present a protocol, consisting of a series of questions, designed to guide the researchers through the evaluation process. These questions address: (1) theoretical development, (2) data requirements, (3) whether responses to perturbation are general, (4) unique reactions by individual measures and (5) how far generality can be extended. For this illustration, we reference a recent study considering the potential consequences of maintaining biodiversity as part of agricultural management on the overall quality of grapes used for wine-making. We extend our presentation to include the complexities that occur when there are multiple species with unique reactions.

Afforestation suppresses Oncomelania hupensis snail density through influencing algae in beaches of the Dongting Lake

BACKGROUND

Oncomelania snails serve as the sole intermediate host for Schistosoma japonicum, one of the most important neglected tropical diseases in the world. Afforestation suppression of the Oncomelania hupensis snail has been a long-term effective national strategy to decrease snail density in China. Many previous studies have made clear that vegetation (biotic factors) and soil (abiotic factors) were the basic requirements for snail survival on beaches. Moreover, a lot of research on snail control has been focused on the specific influencing environmental factors for snail survival, such as the vegetation community structure, species composition, diversity index, and the physical and chemical properties of the soil. Most of the existing research has studied the influence of a single factor on snail population density. Conversely, there have been only a few studies focused on the food sources and food composition of the snails. The current research situation on snail control has indicated that the mechanisms underlying ecological snail control have not been systematically characterized. The question of whether biotic or abiotic factors were more important in influencing snail survival remains unclear. Afforestation on beaches has significantly suppressed snail density in China so far. In this study, we proposed that the reduction of snail density was not affected by a single factor but by the interactions of multiple related factors introduced by afforestation. Moreover, different biotic and abiotic factors have significantly different effects on snail control. Therefore the goal of this study was to evaluate the relative importance and interactions of related biotic and abiotic factors on snail density. Methods: Four major vegetation communities: Sedge, Reed, Artificial poplar (3 years of age) and Artificial poplar (5 years of age), on the beaches of the Yangtze River in China were selected for vegetation and snail surveys, as well as for soil sampling. Structural Equation Model (SEM) analysis was used to assess the interactions of biotic and abiotic factors in the context of snail ecology. The soil properties were considered as abiotic factors, while algae of Chlorophyta, Cyanophyta and Bacillariophyta phyla were considered to be biotic factors. In the path analysis, the total effect between the variables was the sum of the direct and indirect effects.

RESULTS

The snail density had significant correlations with soil properties, such as water content, bulk density, capillary porosity and pH value, as well as with all three types of soil algae, Chlorophyta, Cyanophyta, and Bacillariophyta. Snail density had a direct negative relationship with capillary porosity and soil bulk density, an indirect negative relationship with soil pH value and an indirect positive relationship with soil water content via soil algae. Meanwhile, as an important food source for the snail, the Chlorophyta, Cyanophyta and Bacillariophyta algae had a significant positive correlation with snail density. High soil pH had a negative impact on Chlorophyta, Bacillariophyta, while soil water content had a positive impact on Chlorophyta, and soil bulk density had a negative impact on Cyanophyta. In addition, the soil pH value and soil bulk density both had negative correlations with soil water content.

CONCLUSION

Afforestation of the beach environment can significantly reduce the snail population density by altering ecological factors. Soil algae (biological factors) might be the key element that drives ecological snail control. As important habitat determinants, the impact of the properties of the soil (non-biological factors) on the snail population was largely mediated through soil algae.

Biogeographic distribution patterns of algal community in different urban lakes in China: Insights into the dynamics and co-existence

Urban lake ecosystems are significant for social development, but currently we know little about the geographical distribution of algal community in urban lakes at a large-scale. In this study, we investigated the algal community structure in different areas of urban lakes in China and evaluated the influence of water quality parameters and geographical location on the algal community. The results showed that obvious differences in water quality and algal communities were observed among urban lakes in different geographical areas. Chlorophyta was the dominant phylum, followed by cyanobacteria in all areas. The network analysis indicated that algal community composition in urban lakes of the western and southern area showed more variations than the eastern and northern areas, respectively. Redundancy analysis and structural equation model revealed that nutrients and pH were dominant environmental factors that affected the algal community, and they showed higher influence than that of iron, manganese and COD _Mn concentration. Importantly, algal community and density exhibited longitude and latitude relationship. In general, these results provided an ecological insight into large-scale geographical distributions of algal community in urban lakes, thereby having potential applications for management of the lakes.

Using Bayesian hierarchical modelling to capture cyanobacteria dynamics in Northern European lakes

Cyanobacteria blooms in lakes and reservoirs currently threaten water security and affect the ecosystem services provided by these freshwater ecosystems, such as drinking water and recreational use. Climate change is expected to further exacerbate the situation in the future because of higher temperatures, extended droughts and nutrient enrichment, due to urbanisation and intensified agriculture. Nutrients are considered critical for the deterioration of water quality in lakes and reservoirs and responsible for the widespread increase in cyanobacterial blooms. We model the response of cyanobacteria abundance to variations in lake Total Phosphorus (TP) and Total Nitrogen (TN) concentrations, using a data set from 822 Northern European lakes. We divide lakes in ten groups based on their physico-chemical characteristics, following a modified lake typology defined for the Water Framework Directive (WFD). This classification is used in a Bayesian hierarchical linear model which employs a probabilistic approach, transforming uncertainty into probability thresholds. The hierarchical model is used to calculate probabilities of cyanobacterial concentrations exceeding risk levels for human health associated with the use of lakes for recreational activities, as defined by the World Health Organization (WHO). Different TN and TP concentration combinations result in variable probabilities to exceed pre-set thresholds. Our objective is to support lake managers in estimating acceptable nutrient concentrations and allow them to identify actions that would achieve compliance of cyanobacterial abundance risk levels with a given confidence level.

Biodiversity breakpoints along stress gradients in estuaries and associated shifts in ecosystem interactions

Denitrification in coastal sediments can provide resilience to eutrophication in estuarine ecosystems, but this key ecosystem function is impacted directly and indirectly by increasing stressors. The erosion and loading of fine sediments from land, resulting in sedimentation and elevated sediment muddiness, presents a significant threat to coastal ecosystems worldwide. Impacts on biodiversity with increasing sediment mud content are relatively well understood, but corresponding impacts on denitrification are uncharacterised. Soft sediment ecosystems have a network of interrelated biotic and abiotic ecosystem components that contribute to microbial nitrogen cycling, but these components (especially biodiversity measures) and their relationships with ecosystem functions are sensitive to stress. With a large dataset spanning broad environmental gradients this study uses interaction network analysis to present a mechanistic view of the ecological interactions that contribute to microbial nitrogen cycling, showing significant changes above and below a stressor (mud) threshold. Our models demonstrate that positive biodiversity effects become more critical with a higher level of sedimentation stress, and show that effective ecosystem management for resilience requires different action under different scenarios.

When can we declare a success? A Bayesian framework to assess the recovery rate of impaired freshwater ecosystems

Evaluating the degree of improvement of an impaired freshwater ecosystem resembles the statistical null-hypothesis testing through which the prevailing conditions are compared against a reference state. The pillars of this process involve the robust delineation of what constitutes an achievable reference state; the establishment of threshold values for key environmental variables that act as proxies of the degree of system impairment; and the development of an iterative decision-making process that takes advantage of monitoring data to assess the system-restoration progress and revisit management actions accordingly. Drawing the dichotomy between impaired and non-impaired conditions is a challenging exercise that is surrounded by considerable uncertainty stemming from the variability that natural systems display over time and space, the presence of ecosystem feedback loops (e.g., internal loading) that actively influence the degree of recovery, and our knowledge gaps about biogeochemical processes directly connected to the environmental problem at hand. In this context, we reappraise the idea of probabilistic water quality criteria, whereby the compliance rule stipulates that no more than a stated number of pre-specified water quality extremes should occur within a given number of samples collected over a compliance assessment domain. Our case study is the Bay of Quinte, Ontario, Canada; an embayment lying on the northeastern end of Lake Ontario with a long history of eutrophication problems. Our study explicitly accounts for the covariance among multiple water quality variables and illustrates how we can assess the degree of improvement for a given number of violations of environmental goals and samples collected from the system. The present framework offers a robust way to impartially characterize the degree of restoration success and minimize the influence of the conflicting perspectives among decision makers/stakeholders and conscious (or unconscious) biases pertaining to water quality management.

Factors influencing community participation in the management of household electronic waste in West Surabaya, Indonesia

The objective of the study was to determine the factors that influence community participation in the management of electronic waste. A survey of community willingness to participate in the management of electronic waste was conducted using questionnaires. Survey locations covered western areas of the city of Surabaya, Indonesia, where 238 respondents were selected proportionally from high-, medium-, and low-income groups during 2014. The group was divided by land and building taxes, which represents the socio-economic conditions of the community. Processing and statistical data analysis were performed with structural equation modeling. Results showed that one factor influencing the willingness of communities to manage e-waste was behavior, while factors influencing the willingness of communities to pay more included behavior, attitudes, and knowledge. Strategies to increase community participation can be applied through education and community assistance, the provision of recycling facilities, and applied regulations about e-waste management and extended producer responsibility.

Evaluating the mechanisms of the impacts of key factors on soil soluble organic nitrogen concentrations in subtropical mountain ecosystems

Soil soluble organic nitrogen (SON) concentrations in terrestrial ecosystems were influenced differently and substantially by both biotic and abiotic factors. This study aimed to ascertain the mechanisms of the impact of the key factors on the SON concentrations of subtropical mountain ecosystems in southeastern China using an integrative approach, which combined a field plot survey, gray relational analysis and structure equation modeling. The results showed that the soil organic matter, clay content, protease activity and bacterial biomass were the key factors controlling the dynamics of the SON concentrations in subtropical mountain ecosystems. Protease activity, by catalyzing the degradation of complex organic nitrogen to SON, had the highest direct influence on the SON concentrations among all of the impact factors with direct impact effect of 0.44. Organic matter, which serves as a primary source of SON and can increase soil protease activity and bacterial biomass, contributed the most significantly to the SON concentrations in both direct and indirect pathways with total impact effects of 0.87. Clay, by adsorbing SON and affecting organic matter accumulation and protease activity, also had important direct or indirect influences on the SON concentrations with total impact effects of 0.48. The impact of the bacterial biomass on the SON concentrations was likely to be concealed by accompanying nitrogen-degrading enzyme activity with total impact effects of 0.22. Thus, the organic matter, clay content and protease activity exerted greater total impact effects on the SON concentrations compared with the bacterial biomass. Protease activity and organic matter had a greater positive direct impact on the SON concentrations compared with the bacterial biomass and clay content, while organic matter also had greater positive indirect impacts on the SON concentrations than did the clay content. This study's results could help to elucidate the differential mechanism of SON dynamics among various terrestrial ecosystems.

Co-contamination of antibiotics and metals in peri-urban agricultural soils and source identification

To identify the dominant sources of contamination in peri-urban land, this study investigated the concentrations and distributions of antibiotics and metals in agricultural soil of this area. An index of landscape development intensity (LDI) was used to characterize the distribution of human disturbance-related land use. The results showed that total antibiotic concentration in the soil reached 395.55 μg/kg and that chlortetracycline was the predominant antibiotic compound, with a relatively high mean concentration of 30.62 μg/kg. In soils, the mean concentrations of Cu, Zn, and Pb were 38.41, 127.88, and 56.61 mg/kg and those of Al, Fe, and K were 83.73, 24.17, and 23.42 g/kg, respectively. A redundancy analysis showed that the landscape pattern in a 300-m buffer zone can well explain the variation in the concentrations of antibiotics and metals (24%, p < 0.05). The LDI in the 300-m buffer zone significantly correlated with the concentrations of total antibiotics and total amounts of Cu and Zn in the soil, suggesting that the risk of soil contamination increases with the intensity of anthropogenic activities. A structural equation modeling analysis indicated that Al, Cu, and Zn could significantly aggravate accumulation of tetracycline antibiotics in the soil, whereas there were only significantly direct paths from Cu to ciprofloxacin and norfloxacin. Overall, the results showed that aggravated co-contamination of antibiotics and metals occurs in agricultural soil under intensive human disturbance.

Exploring the influence of meteorological conditions on the performance of a waste stabilization pond at high altitude with structural equation modeling

Algal photosynthesis plays a key role in the removal mechanisms of waste stabilization ponds (WSPs), which is indicated in the variations of three parameters, dissolved oxygen, pH, and chlorophyll a. These variations can be considerably affected by extreme climatic conditions at high altitude. To investigate these effects, three sampling campaigns were conducted in a high-altitude WSP in Cuenca (Ecuador). From the collected data, the first application of structure equation modeling (SEM) on a pond system was fitted to analyze the influence of high-altitude characteristics on pond performance, especially on the three indicators. Noticeably, air temperature appeared as the highest influencing factors as low temperature at high altitude can greatly decrease the growth rate of microorganisms. Strong wind and large diurnal variations of temperature, 7-20 °C, enhanced flow efficiency by improving mixing inside the ponds. Intense solar radiation brought both advantages and disadvantages as it boosted oxygen level during the day but promoted algal overgrowth causing oxygen depletion during the night. From these findings, the authors proposed insightful recommendations for future design, monitoring, and operation of high-altitude WSPs. Moreover, we also recommended SEM to pond engineers as an effective tool for better simulation of such complex systems like WSPs.

Distribution and availability of cadmium in profile and aggregates of a paddy soil with 30-year fertilization and its impact on Cd accumulation in rice plant

The research was conducted to investigate the accumulation, distribution and availability of Cd in paddy soil and their relation to Cd in rice plants under 30-year fertilization regimes. Six treatments were involved in the study: control without fertilization (CK), chemical fertilizer (NPK), high nitrogen chemical fertilizer (HN), rice straw incorporation (ST), low and high dosage of manure fertilizer (LM and HM). Total and DTPA extractable concentration of Cd (T-Cd and DTPA-Cd) in bulk soils (20 cm topsoil), profiles (0-60 cm) and aggregates (>2, 1-2, 0.5-1, 0.25-0.5, 0.053-0.25 and < 0.053 mm) were investigated. The Cd concentration in relevant rice plant (roots, stems, leaves, husks and grains) were also analyzed. Manure fertilizers caused T-Cd accumulation in bulk soil with a significant increase of 36.2% in LM and 81.2% in HM. Similar impacts of manure fertilizers were observed in DTPA-Cd in the bulk soil. Further, the HM generated a further accumulation in deeper soil layers, presenting a remarkable increase of T-Cd (28.3%-225%) in 10-40 cm and DTPA-Cd (116%-158%) in 10-30 cm profiles. Moreover, the continuous application of manure fertilizers enhanced the availability of Cd in all aggregate size classes with an increase of 17.3%-87.8% in DTPA-Cd. Organic fertilizers (LM, HM and ST) heightened the content of Cd (38.0%-152%) in all parts of rice plant. The accumulation of Cd in rice plants was directly affected by fertilization regimes and Cd availability in the 10-20 cm soil layers and 0.25-0.5 mm aggregates. In conclusion, long-term application of manures resulted in increasing availability of Cd in aggregates and in topsoil and subsoil layers, which accordingly enhanced the accumulation of Cd in rice plants.

Landscape variation influences trophic cascades in dengue vector food webs

The epidemiology of vector-borne diseases is governed by a structured array of correlative and causative factors, including landscape (for example, rural versus urban), abiotic (for example, weather), and biotic (for example, food web) factors. Studies of mosquito-borne diseases rarely address these multiple factors at large spatial scales, which limits insights into how human alterations of landscapes and food webs alter mosquito abundance. We used structural equation modeling to identify the relative magnitude and direction of landscape, abiotic, and food web factors on Aedes larvae and adults across 70 sites in northern Thailand. Food web factors were modeled as mosquito-predator trophic cascades. Landscape context affected mosquito-predator communities in aquatic and terrestrial environments via cascading food web interactions. Several mosquito predators within these food webs showed potential as biocontrol agents in mosquito population control, but their potentials for control were landscape-dependent. In terrestrial food webs, the habitat-sensitive tokay gecko structured mosquito-predator communities, indicating that a conservation approach to vector control could be a useful addition to existing control efforts.

The counter-balance between ammonia absorption and the stimulation of volatilization by periphyton in shallow aquatic systems

Ammonia (NH₃) volatilization is one of the main pathways of nitrogen (N). The aim of this work was to investigate the determinants of NH₃ volatilization, and characterize how the overlying water, sediment, and periphyton interact to regulate the rates of NH₃ volatilization in shallow aquatic systems. Two types of structural equation modeling (SEM) methods ('elements' and 'components' models) were evaluated to examine the complex multivariate response of NH₃ volatilization. The N components and the pH in the 'elements' models exerted significant and positive effects on NH₃ volatilization. The water column accounted for the greatest variation of NH₃ volatilization in a favorable pH environment and high NH₄⁺-N concentrations according to the 'components' models. Although periphyton biofilm prohibited the direct flow of NH₃ gas, this was counter-balanced by its indirect stimulation effects that positively affected the NH₄⁺-N and DOC concentrations and the pH in both the overlying water and the sediment.

Roads to ruin: conservation threats to a sentinel species across an urban gradient

Urbanization poses a global challenge to species conservation. This is primarily understood in terms of physical habitat loss, as agricultural and forested lands are replaced with urban infrastructure. However, aquatic habitats are also chemically degraded by urban development, often in the form of toxic stormwater runoff. Here we assess threats of urbanization to coho salmon throughout developed areas of the Puget Sound Basin in Washington, USA. Puget Sound coho are a sentinel species for freshwater communities and also a species of concern under the U.S. Endangered Species Act. Previous studies have demonstrated that stormwater runoff is unusually lethal to adult coho that return to spawn each year in urban watersheds. To further explore the relationship between land use and recurrent coho die-offs, we measured mortality rates in field surveys of 51 spawning sites across an urban gradient. We then used spatial analyses to measure landscape attributes (land use and land cover, human population density, roadways, traffic intensity, etc.) and climatic variables (annual summer and fall precipitation) associated with each site. Structural equation modeling revealed a latent urbanization gradient that was associated with road density and traffic intensity, among other variables, and positively related to coho mortality. Across years within sites, mortality increased with summer and fall precipitation, but the effect of rainfall was strongest in the least developed areas and was essentially neutral in the most urbanized streams. We used the best-supported structural equation model to generate a predictive mortality risk map for the entire Puget Sound Basin. This map indicates an ongoing and widespread loss of spawners across much of the Puget Sound population segment, particularly within the major regional north-south corridor for transportation and development. Our findings identify current and future urbanization-related threats to wild coho, and show where green infrastructure and similar clean water strategies could prove most useful for promoting species conservation and recovery.

Structural Equation Model of Total Phosphorus Loads in the Red River of the North Basin, USA and Canada

Attribution of the causes of trends in nutrient loading is often limited to correlation, qualitative reasoning, or references to the work of others. This paper represents efforts to improve causal attribution of water-quality changes. The Red River of the North basin provides a regional test case because of international interest in the reduction of total phosphorus loads and the availability of long-term total phosphorus data and ancillary geospatial data with the potential to explain changes in water quality over time. The objectives of the study are to investigate structural equation modeling methods for application to water-quality problems and to test causal hypotheses related to the drivers of total phosphorus loads over the period 1970 to 2012. Multiple working hypotheses that explain total phosphorus loads and methods for estimating missing ancillary data were developed, and water-quality related challenges to structural equation modeling (including skewed data and scaling issues) were addressed. The model indicates that increased precipitation in season 1 (November-February) or season 2 (March-June) would increase total phosphorus loads in the basin. The effect of agricultural practices on total phosphorus loads was significant, although the effect is about one-third of the effect of season 1 precipitation. The structural equation model representing loads at six sites in the basin shows that climate and agricultural practices explain almost 60% of the annual total phosphorus load in the Red River of the North basin. The modeling process and the unexplained variance highlight the need for better ancillary long-term data for causal assessments.

Integrative analysis of the Lake Simcoe watershed (Ontario, Canada) as a socio-ecological system

Striving for long-term sustainability in catchments dominated by human activities requires development of interdisciplinary research methods to account for the interplay between environmental concerns and socio-economic pressures. In this study, we present an integrative analysis of the Lake Simcoe watershed, Ontario, Canada, as viewed from the perspective of a socio-ecological system. Key features of our analysis are (i) the equally weighted consideration of environmental attributes with socioeconomic priorities and (ii) the identification of the minimal number of key socio-hydrological variables that should be included in a parsimonious watershed management framework, aiming to establish linkages between urbanization trends and nutrient export. Drawing parallels with the concept of Hydrological Response Units, we used Self-Organizing Mapping to delineate spatial organizations with similar socio-economic and environmental attributes, also referred to as Socio-Environmental Management Units (SEMUs). Our analysis provides evidence of two SEMUs with contrasting features, the "undisturbed" and "anthropogenically-influenced", within the Lake Simcoe watershed. The "undisturbed" cluster occupies approximately half of the Lake Simcoe catchment (45%) and is characterized by low landscape diversity and low average population density <0.4 humans ha^-1. By contrast, the socio-environmental functional properties of the "anthropogenically-influenced" cluster highlight the likelihood of a stability loss in the long-run, as inferred from the distinct signature of urbanization activities on the tributary nutrient export, and the loss of subwatershed sensitivity to natural mechanisms that may ameliorate the degradation patterns. Our study also examines how the SEMU concept can augment the contemporary integrated watershed management practices and provides directions in order to promote environmental programs for lake conservation and to increase public awareness and engagement in stewardship initiatives.

A Bayesian network approach to determine environmental factors controlling Karenia selliformis occurrences and blooms in the Gulf of Gabès, Tunisia

A Bayesian Network modeling framework is introduced to explore the effect of physical and meteorological factors on the dinoflagellate red tide forming Karenia selliformis in various sampling sites of the national phytoplankton monitoring program. The proposed models took into account the physical environment effects (salinity, temperature and tide amplitude), meteorological constraints (evaporation, air temperature, insolation, rainfall, atmospheric pressure and humidity), sampling months and sites on both Karenia selliformis occurrences and blooms. The models produced plausible results and enabled the identification of the factors that directly impacted on the species occurrences and concentration levels. The sampling sites dominated the species occurrences. The models show that the relationship between salinity and Karenia selliformis is more apparent when the species concentrations are focused on and that the bloom occurrences can be predicted based on salinity. Concentrations up to 10⁵ cells L^-1 were recorded when salinity exceeded 42.5 and dominated the shallow and weak water renewal areas.

Bacterioplankton community responses to key environmental variables in plateau freshwater lake ecosystems: A structural equation modeling and change point analysis

Elevated environmental pressures negatively affect the bacterial community structure. However, little knowledge about the nonlinear responses of spatially related environmental variable across multiple plateau lake ecosystems on bacterioplankton communities has been gathered. Here, we used 454 pyrosequencing of 16S rRNA genes to study the associations of bacterial communities in terms of environmental characteristics as well as the potentially ecological threshold-inducing shifts of the bacterial community structure along the key environmental variables based on hypothesized structural equation models and the SEGMENTED method in 21 plateau lakes. Our results showed that water transparency was the major driving force and that total nitrogen was more significant than total phosphorus in determining the taxon composition of the bacterioplankton community. Significant community threshold estimates for bacterioplankton were observed at 7.36 for pH and 25.6% for the percentage of the agricultural area, while the remarkable change point of the cyanobacteria community structure responding to pH was at 7.74. Furthermore, the findings indicated that increasing nutrient loads can induce a distinct shift in dominance from Proteobacteria to Cyanobacteria, as well as a sharp decrease and adjacent increase when crossing the change point for Actinobacteria and Bacteroidetes along the gradient of the agricultural area.

The phosphorus release pathways and their mechanisms driven by organic carbon and nitrogen in sediments of eutrophic shallow lakes

To reveal phosphorus (P) release pathways from sediment and their mechanisms induced by organic matter enrichment, 116 sampling sites (including surface water and sediment) in 29 shallow lakes with different eutrophic degrees in Wuhan city, China, were investigated from July 2011 to November 2011. Empirical relationship and structural equation model indicated that the decomposition of total organic matter (TOM), including proteins (PRT), carbo-hydrates (CHO) and lipids (especially PRT) mediated by extracellular enzymes, accelerated the formation of anaerobic status. On the other hand, coupled nitrification-denitrification caused by ammonium (NH₄⁺-N) accumulation due to PRT decomposition further aggravated anaerobic status and nitrate removal in terms of the increase of dehydrogenase activity (DHA). As a consequence, ferric iron was reduced to ferrous iron and soluble reactive phosphorus (SRP) was released from iron-bound phosphorus (Fe(OOH)~P) in sediments. In addition, extracellular alkaline phosphatase can be induced by organic carbon and nitrogen on condition that the input of nitrogen (N) and carbon (C) exceeded by far that of P. Taken together, enrichment of N and C can result in P release through the formation of anaerobic status and alkaline phosphatase production. Hence, we indicated that a close coupling existed among C, N and P cycles.

Underappreciated problems of low replication in ecological field studies

The cost and difficulty of manipulative field studies makes low statistical power a pervasive issue throughout most ecological subdisciplines. Ecologists are already aware that small sample sizes increase the probability of committing Type II errors. In this article, we address a relatively unknown problem with low power: underpowered studies must overestimate small effect sizes in order to achieve statistical significance. First, we describe how low replication coupled with weak effect sizes leads to Type M errors, or exaggerated effect sizes. We then conduct a meta-analysis to determine the average statistical power and Type M error rate for manipulative field experiments that address important questions related to global change; global warming, biodiversity loss, and drought. Finally, we provide recommendations for avoiding Type M errors and constraining estimates of effect size from underpowered studies.

The trophic responses of two different rodent-vector-plague systems to climate change

Plague, the causative agent of three devastating pandemics in history, is currently a re-emerging disease, probably due to climate change and other anthropogenic changes. Without understanding the response of plague systems to anthropogenic or climate changes in their trophic web, it is unfeasible to effectively predict years with high risks of plague outbreak, hampering our ability for effective prevention and control of the disease. Here, by using surveillance data, we apply structural equation modelling to reveal the drivers of plague prevalence in two very different rodent systems: those of the solitary Daurian ground squirrel and the social Mongolian gerbil. We show that plague prevalence in the Daurian ground squirrel is not detectably related to its trophic web, and that therefore surveillance efforts should focus on detecting plague directly in this ecosystem. On the other hand, plague in the Mongolian gerbil is strongly embedded in a complex, yet understandable trophic web of climate, vegetation, and rodent and flea densities, making the ecosystem suitable for more sophisticated low-cost surveillance practices, such as remote sensing. As for the trophic webs of the two rodent species, we find that increased vegetation is positively associated with higher temperatures and precipitation for both ecosystems. We furthermore find a positive association between vegetation and ground squirrel density, yet a negative association between vegetation and gerbil density. Our study thus shows how past surveillance records can be used to design and improve existing plague prevention and control measures, by tailoring them to individual plague foci. Such measures are indeed highly needed under present conditions with prevailing climate change.

Modeling phytoplankton community in reservoirs. A comparison between taxonomic and functional groups-based models

In this paper we address the formulation of two mechanistic water quality models that differ in the way the phytoplankton community is described. We carry out parameter estimation subject to differential-algebraic constraints and validation for each model and comparison between models performance. The first approach aggregates phytoplankton species based on their phylogenetic characteristics (Taxonomic group model) and the second one, on their morpho-functional properties following Reynolds' classification (Functional group model). The latter approach takes into account tolerance and sensitivity to environmental conditions. The constrained parameter estimation problems are formulated within an equation oriented framework, with a maximum likelihood objective function. The study site is Paso de las Piedras Reservoir (Argentina), which supplies water for consumption for 450,000 population. Numerical results show that phytoplankton morpho-functional groups more closely represent each species growth requirements within the group. Each model performance is quantitatively assessed by three diagnostic measures. Parameter estimation results for seasonal dynamics of the phytoplankton community and main biogeochemical variables for a one-year time horizon are presented and compared for both models, showing the functional group model enhanced performance. Finally, we explore increasing nutrient loading scenarios and predict their effect on phytoplankton dynamics throughout a one-year time horizon.

Determining the probability of cyanobacterial blooms: the application of Bayesian networks in multiple lake systems

A Bayesian network model was developed to assess the combined influence of nutrient conditions and climate on the occurrence of cyanobacterial blooms within lakes of diverse hydrology and nutrient supply. Physicochemical, biological, and meteorological observations were collated from 20 lakes located at different latitudes and characterized by a range of sizes and trophic states. Using these data, we built a Bayesian network to (1) analyze the sensitivity of cyanobacterial bloom development to different environmental factors and (2) determine the probability that cyanobacterial blooms would occur. Blooms were classified in three categories of hazard (low, moderate, and high) based on cell abundances. The most important factors determining cyanobacterial bloom occurrence were water temperature, nutrient availability, and the ratio of mixing depth to euphotic depth. The probability of cyanobacterial blooms was evaluated under different combinations of total phosphorus and water temperature. The Bayesian network was then applied to quantify the probability of blooms under a future climate warming scenario. The probability of the "high hazardous" category of cyanobacterial blooms increased 5% in response to either an increase in water temperature of 0.8°C (initial water temperature above 24°C) or an increase in total phosphorus from 0.01 mg/L to 0.02 mg/L. Mesotrophic lakes were particularly vulnerable to warming. Reducing nutrient concentrations counteracts the increased cyanobacterial risk associated with higher temperatures.

Mercury cycling in aquatic ecosystems and trophic state-related variables--implications from structural equation modeling

Structural equation modeling (SEM) provides a framework that can more properly handle complex variable interactions inherent in mercury cycling and its bioaccumulation compared to more traditional regression-based methods. SEM was applied to regional data sets for three different types of aquatic ecosystems within Florida, USA--lakes, streams, and the Everglades--to evaluate the underlying nature (i.e., indirect and direct) of the relationships between fish mercury concentrations and trophic state related variables such as nutrients, dissolved organic carbon (DOC), sulfate, and alkalinity. The modeling results indicated some differences in key variable relationships--for example, the effect of nutrients on fish mercury in lakes and streams was uniformly negative through direct and indirect pathways consistent with biodilution or eutrophication-associated effects on food web structure. Somewhat surprisingly, however, was that total phosphorus did not serve as a meaningful variable in the Everglades model, apparently because its effects were masked or secondary to the effects of DOC. What is perhaps a more important result were two key similarities across the three systems. First, the modeling clearly indicates that the dominant influence on fish tissue mercury concentrations in all three systems is related to variations in the methylmercury signal. Second, the modeling demonstrated that the effect of DOC on fish mercury concentrations was exerted through multiple and antagonistic pathways, including facilitated transport of total mercury and methylmercury, enhanced rates of methylation, and limitations imposed on bioavailability. Indeed, while the individual DOC pathways in the models were all highly significant (generally p<0.001), the net effect of DOC in each model was greatly reduced or insignificant. These results can help explain contradictory results obtained previously by other researchers in other systems, and illustrate the importance of SEM as a modeling tool when studying systems with complex interactions such as the aquatic mercury cycle.

Abiotic and biotic controls on local spatial distribution and performance of Boechera stricta

This study investigates the relative influence of biotic and abiotic factors on community dynamics using an integrated approach and highlights the influence of space on genotypic and phenotypic traits in plant community structure. We examined the relative influence of topography, environment, spatial distance, and intra- and interspecific interactions on spatial distribution and performance of Boechera stricta (rockcress), a close perennial relative of model plant Arabidopsis. First, using Bayesian kriging, we mapped the topography and environmental gradients and explored the spatial distribution of naturally occurring rockcress plants and two neighbors, Taraxacum officinale (dandelion) and Solidago missouriensis (goldenrod) found in close proximity within a typical diverse meadow community across topographic and environmental gradients. We then evaluated direct and indirect relationships among variables using Mantel path analysis and developed a network displaying abiotic and biotic interactions in this community. We found significant spatial autocorrelation among rockcress individuals, either because of common microhabitats as displayed by high density of individuals at lower elevation and high soil moisture area, or limited dispersal as shown by significant spatial autocorrelation of naturally occurring inbred lines, or a combination of both. Goldenrod and dandelion density around rockcress does not show any direct relationship with rockcress fecundity, possibly due to spatial segregation of resources. However, dandelion density around rockcress shows an indirect negative influence on rockcress fecundity via herbivory, indicating interspecific competition. Overall, we suggest that common microhabitat preference and limited dispersal are the main drivers for spatial distribution. However, intra-specific interactions and insect herbivory are the main drivers of rockcress performance in the meadow community.

A model to determine the lake nutrient standards for drinking water sources in Yunnan-Guizhou Plateau Ecoregion, China

Lake eutrophication (LE) has become an increasingly severe environmental problem recently. However, there has been no nutrient standard established for LE control in many developing countries such as China. This study proposes a structural equation model to assist in the establishment of a lake nutrient standard for drinking water sources in Yunnan-Guizhou Plateau Ecoregion (Yungui Ecoregion), China. The modeling results indicate that the most predictive indicator for designated use-attainment is total phosphorus (TP) (total effect = -0.43), and chlorophyll a (Chl-a) is recommended as the second important indicator (total effect = -0.41). The model is further used for estimating the probability of use-attainment associated with lake water as a drinking water source and various levels of candidate criteria (based on the reference conditions and the current environmental quality standards for surface water). It is found that these candidate criteria cannot satisfy the designated 100% use-attainment. To achieve the short-term target (85% attainment of the designated use), TP and Chl-a values ought to be less than 0.02 mg/L and 1.4 microg/L, respectively. When used as a long-term target (90% or greater attainment of the designated use), the TP and Chl-a values are suggested to be less than 0.018 mg/L and 1 microg/L, respectively.

Plant production and alternate prey channels impact the abundance of top predators

While numerous studies have examined the effects of increased primary production on higher trophic levels, most studies have focused primarily on the grazing food web and have not considered the importance of alternate prey channels. This has happened despite the fact that fertilization not only increases grazing herbivore abundance, but other types of consumers such as detritivores that serve as alternate prey for generalist predators. Alternate prey channels can sustain generalist predators at times when prey abundance in the grazing food web is low, thus increasing predator densities and the potential for trophic cascades. Using arthropod data from a fertilization experiment, we constructed a hierarchical Bayesian model to examine the direct and indirect effects of plant production and alternate prey channels on predators in a salt marsh. We found that increased plant production positively affected the density of top predators via effects on lower trophic level herbivores and mesopredators. Additionally, while the abundance of algivores and detritivores positively affected mesopredators and top predators, respectively, the effects of alternate prey were relatively weak. Because previous studies in the same system have found that mesopredators and top predators rely on alternate prey such as algivores and detritivores, future studies should examine whether fertilization shifts patterns of prey use by predators from alternate channels to the grazing channel. Finally, the hierarchical Bayesian model used in this study provided a useful method for exploring trophic relationships in the salt marsh food web, especially where causal relationships among trophic groups were unknown.

Environmental influence on coastal phytoplankton and zooplankton diversity: a multivariate statistical model analysis

In a marine ecosystem, the diversity of phytoplankton can influence the diversity of zooplankton, or vice versa, and both can be affected by the environmental factors. In this study, we used principal component analysis (PCA) to identify the major sources of influence on the coastal water near an industrial park, following by construction of structural equation model (SEM) to determine the direct and indirect effect of the factors on phytoplankton and zooplankton diversity. PCA results indicated that the coastal area was mainly affected by riverine discharge (represented by high PC factor loadings of transparency and turbidity) and seasonal change (represented by temperature). SEM further suggested that both riverine discharge and seasonal influences can directly affect phytoplankton diversity, but indirectly affected zooplankton diversity via changes in phytoplankton. Using PCA to determine the sources of influence followed by construction of SEM allowed us to understand the relative importance of the environmental factors, direct or indirect, on phytoplankton and zooplankton diversity. When environmental changes occur, a new SEM could be constructed using the same category of physical and biological data and then compared to the current model to verify whether the environmental changes were the cause of alterations in planktonic communities in the area.