Spatial connectivity in a large river system: resolving the sources and fate of dissolved organic matter

Large rivers are generally heterogeneous and productive systems that receive important inputs of dissolved organic matter (DOM) from terrestrial and in situ sources. Thus, they are likely to play a significant role in the biogeochemical cycling of the DOM flowing to the oceans. The asymmetric spatial gradient driven by directional flow and environmental heterogeneity contributes to the fate of DOM flowing downstream. Yet, the relative effects of spatial connectivity and environmental heterogeneity on DOM dynamics are poorly understood. For example, since environmental variables show spatial heterogeneity, the variation explained by environmental and spatial variables may be redundant. We used the St. Lawrence River (SLR) as a representative large river to resolve the unique influences of environmental heterogeneity and spatial connectivity on DOM dynamics. We used three-dimensional fluorescence matrices combined with parallel factor analysis (PARAFAC) to characterize the DOM pool in the SLR. Seven fluorophores were modeled, of which two were identified to be of terrestrial origin and three from algal exudates. We measured a set of environmental variables that are known to drive the fate of DOM in aquatic systems. Additionally, we used asymmetric eigenvector map (AEM) modeling to take spatial connectivity into account. The combination of spatial and environmental models explained 85% of the DOM variation. We show that spatial connectivity is an important driver of DOM dynamics, as a large fraction of environmental heterogeneity was attributable to the asymmetric spatial gradient. Along the longitudinal axis, we noted a rapid increase in dissolved organic carbon (DOC), mostly controlled by terrestrial input of DOM originating from the tributaries. Variance partitioning demonstrated that freshly produced protein-like DOM was found to be the preferential substrate for heterotrophic bacteria undergoing rapid proliferation, while humic-like DOM was more correlated to the diffuse attenuation coefficient of UVA radiation.     

Effect of citric acid and EDTA on chromium and nickel uptake and translocation by Datura innoxia

EDTA and citric acid were tested to solubilize metals and enhance their uptake by Datura innoxia, chosen because of its ability to accumulate and tolerate metals. Two application modes were used on an industrial soil contaminated mainly by Cr and Ni. The results showed that citric acid was the most effective at increasing the uptake of Cr and EDTA for Ni. These results are consistent with the effectiveness of both chelants in solubilizing metals from the soil. The translocation factor (TF) of Ni was 1.6- and 6.7-fold higher than the control, respectively, for one and two applications of 1mmolkg(-1) EDTA. After two applications of 5 and 10mmolkg(-1) citric acid, the TF of Cr increased 2- and 3.5-fold relative to the control. Whatever the concentration, the application of EDTA modified the plant physiology significantly. For citric acid this was only observed with the highest dose (10mmolkg(-1)).     

Exposure assessment of French women and their newborns to tetrabromobisphenol-A: occurrence measurements in maternal adipose tissue, serum, breast milk and cord serum

A French monitoring study was initiated to evaluate the exposure of fetus and newborn to brominated flame retardants (BFR). A previously developed multi-residue analytical method was used for measuring the main classes of BFR (tetrabromobisphenol-A, and tri- to decabomodiphenyl ethers) in various human biological matrices. Analyzed samples (maternal and cord serum, adipose tissue and breast milk) were collected from 93 volunteer women during caesarean deliveries. TBBPA was detected in 44% of the analyzed breast milk samples, at levels varying from 0.06 to 37.34 ng g(-1) lipid weight, but was not detected in adipose tissue. This compound was also detected in 30% of the analyzed serum samples, with similar average values in maternal and cord serum (154 pg g(-1) fresh weight versus 199 pg g(-1) fresh weight, respectively). The interpretation of the collected data permitted the demonstration of (1) a significant exposure to TBBPA both for mothers and fetuses and (2) a possible risk of overexposure of newborns through breastfeeding.     

Testing hypotheses in evolutionary ecology with imperfect detection: capture-recapture structural equation modeling

Studying evolutionary mechanisms in natural populations often requires testing multifactorial scenarios of causality involving direct and indirect relationships among individual and environmental variables. It is also essential to account for the imperfect detection of individuals to provide unbiased demographic parameter estimates. To cope with these issues, we developed a new approach combining structural equation models with capture-recapture models (CR-SEM) that allows the investigation of competing hypotheses about individual and environmental variability observed in demographic parameters. We employ Markov chain Monte Carlo sampling in a Bayesian framework to (1) estimate model parameters, (2) implement a model selection procedure to evaluate competing hypotheses about causal mechanisms, and (3) assess the fit of models to data using posterior predictive checks. We illustrate the value of our approach using two case studies on wild bird populations. We first show that CR-SEM can be useful to quantify the action of selection on a set of phenotypic traits with an analysis of selection gradients on morphological traits in Common Blackbirds (Turdus merula). In a second case study on Blue Tits (Cyanistes caeruleus), we illustrate the use of CR-SEM to study evolutionary trade-offs in the wild, while accounting for varying environmental conditions.     

Meta-ecosystem engineering: nutrient fluxes reveal intraspecific and interspecific feedbacks in fragmented mussel beds

Ecologists still have to elucidate the complex feedback interactions operating among biodiversity and ecosystem processes in engineered systems. To address this, a field experiment was conducted to mimic natural mussel bed meta-ecosystems (Mytilus spp.) of the lower St. Lawrence Estuary (Quebec, Canada) and partition the effects of their biotic and abiotic properties and spatial structure on ecosystem processes and community dynamics of associated macro-invertebrates. We found positive intraspecific feedbacks between mussels and their recruits, and negative interspecific feedbacks between mussels and their associated ecosystem. These feedbacks were associated with mussel bed ecosystem processes (fluxes of ammonium and oxygen). In addition, we showed that proximity between mussel patches increased within-patch nutrient fluxes. Our study revealed the potential for meta-ecosystem engineering to drive feedback interactions between community and ecosystem functioning in marine fragmented systems. It also shows the relevance of meta-ecosystem theories as a conceptual framework to elucidate biotic and abiotic processes controlling ecosystem and community structure. Such framework could contribute to ecosystem-based management of spatially structured systems such as reserve networks and fragmented ecosystems.     

Species distribution modelling: Does one size fit all? A phytogeographic analysis of Salix in Ontario

Empirical models for predicting the distribution of organisms from environmental data have often focused on principles of ecological niche theory. However, even at large scales, there is little agreement over how to represent the dimensions of a species’ niche. The performance of such models is greatly affected by the nature of species distributional and environmental data. Regional scale distribution models were developed for 30 willow species in Ontario to examine (i) the predictive ability of logistic regression analysis, and (ii) the effects of using different distributional and environmental data sets. Two original measures of model accuracy and over-prediction were employed and evaluated using independent data. Models based on unique combinations of monthly climate data predicted distributions most accurately for all species. Models based on a fixed set of variables, while generating the highest average probabilities of occurrence for certain species with limited ranges, resulted in the greatest under- and over-estimates of willow distributions. Comparisons of models demonstrated climatic patterns among willows of differing habit and habitat. The distribution of dwarf willow species, present only in the Ontario arctic, followed gradients of summer maximum temperatures. The distribution of the tree species in the southerly portions of the province followed gradients of fall and winter minimum temperatures. Regardless of distributional and environmental data input, no algorithm maximized model performance for all species. Individual species models require individual approaches; i.e., the variable selection technique, the set of environmental factors used as predictors, and the nature of species distributional data must be carefully matched to the intended application. An understanding of evolutionary processes enhances the meaningful interpretation of individual species models. Unless sampling bias and species prevalence can be accounted for, models based on collection point data are best used to guide field surveys. While inferred range data may be better suited to determine potential ecological niches, overestimation of species prevalence and environmental tolerance must be recognized. A combination of available distributional data types is recommended to best determine species niches, an important step in developing conservation strategies.     

Modelling radiative balance in a row-crop canopy: Row-soil surface net radiation partition

Row crops like vineyards undergo various and significant manipulations of training system and cultural practices, which strongly influence the quality of products. Variations of water vapour fluxes from the soil surface and the leaves in the row volume are closely linked to the ratio of energy available to each compartment. A physically realistic model of available energy partition between the rows and the soil surface is therefore a key factor towards optimization of such systems, and must be included in canopy models. A number of available models were not directly validated. The purpose of the study was therefore to design a model of net radiation partition and check it directly.The model of net radiation partition between rows (Rnv), considered as a whole, and intervening soil surface (Rns) of a row-crop canopy was developed from physically realistic yet simple assumptions:

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global solar (short wave) radiation partition was calculated by a previously validated geometric model;

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long-wave radiative fluxes between the soil surface, the rows and the atmosphere were calculated from the corresponding view factors, which only depended on canopy geometry;

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atmospheric radiation was estimated by a simple empirical relation based on air temperature as the only input variable;

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air temperature in the vicinity of leaves replaced leaf surface temperatures as a more convenient input variable, with little loss of information.

The input variables were incoming direct and diffuse solar radiation, soil surface mean temperature and air temperature near the leaves. The main parameters were soil and leaf albedos, row porosity and dimensions.A direct validation of the model was attempted by measuring net radiation above the canopy and at five positions above the soil surface in a vineyard of the Bordeaux area. The reliability of soil surface net radiation measurements was estimated by thorough error propagation analysis. When found significant, errors were corrected and finally soil surface net radiation data were corrected only for delay in direct downward solar radiation striking net radiometers, because canopy was discontinuous and height of net radiometers was not negligible compared to canopy height.In these conditions, model calculations were in agreement with measurements, although the model slightly underestimated Rns and therefore overestimated Rnv. As the mean error was about 20 W m⁻², and therefore compatible with instrument accuracy, the results were considered satisfactory.This available energy partition model is able to estimate radiative balance in various canopy systems and in various thermal environment conditions, leading to easier simulations of energy balance and water fluxes. It could therefore be a useful tool for optimizing row-crop canopies, taking fully into account any kind of present or future thermal environment.