Identifying the impact of toxicity on stream macroinvertebrate communities in a multi-stressor context based on national ecological and ecotoxicological monitoring databases.

In situ bioassays are used to measure the harmful effects induced by mixtures of toxic chemicals in watercourses. In France, national-scale biomonitoring data are available including invertebrate surveys and in-field chemical toxicity measures with caged gammarids to assess environmental toxicity of mixtures of chemicals. The main objective of our study is to present a proof-of-concept approach identifying possible links between in-field chemical toxicity, stressors and the ecological status. We used two active biomonitoring databases comprising lethal toxicity (222 in situ measures of gammarid mortality) and sublethal toxicity (101 in situ measures of feeding inhibition). We measured the ecological status of each active biomonitoring site using the I2M2 metric (macroinvertebrate-based multimetric index), accounted for known stressors of nutrients and organic matter, hydromorphology and chemical toxicity. We observed a negative relationship between stressors (hydromorphology, nutrients and organic matter, and chemical toxicity) and the good ecological status. This relationship was aggravated in watercourses where toxicity indicators were degraded. We validated this hypothesis for instance with nutrients and organic matter like nitrates or hydromorphological conditions like percentage of vegetation on banks. Future international assesments concerning the role of in-field toxic pollution on the ecological status in a multi-stressor context are now possible via the current methodology.

A metric-based analysis on the effects of riparian and catchment landuse on macroinvertebrates.

Woody riparian vegetation along rivers and streams provides multiple functions beneficial for aquatic macroinvertebrate communities. They retain fine sediments, nutrients and pesticides, improve channel hydromorphology, control water temperature and primary production through shading and provide leaves, twigs and large wood. In a recent conceptual model (Feld et al., 2018), woody riparian functions were considered either independent from large-scale landuse stressors (e.g. shading, input of organic matter), or dependent on landuse at larger spatial scales (e.g. fine sediment, nutrient and pesticide retention). We tested this concept using high-resolution data on woody riparian vegetation cover and empirical data from 1017 macroinvertebrate sampling sites in German lowland and mountain streams. Macroinvertebrate metrics indicative for individual functions were used as response variables in structural equation models (SEM), representing the hierarchical structure between the different considered stressors at different spatial scales: catchment, upstream riparian, local riparian and local landuse cover along with hydromorphology and water quality. The analysis only partly confirmed the conceptual model: Biotic integrity and water quality were strongly related to large-scale stressors as expected (absolute total effect 0.345-0.541), but against expectations, fine sediments retention, considered scale-dependent in the conceptual model, was poorly explained by large-scale stressors (absolute total effect 0.027-0.231). While most functions considered independent from large-scale landuse were partly explained by riparian landuse cover (absolute total effect 0.023-0.091) they also were nonetheless affected by catchment landuse cover (absolute total effect 0.017-0.390). While many empirical case studies at smaller spatial scales clearly document the positive effects of restoring woody riparian vegetation, our results suggest that most effects of riparian landuse cover are possibly superimposed by larger-scale stressors. This does not negate localized effects of woody riparian vegetation but helps contextualize limitations to successful restoration measures targeting the macroinvertebrate community.

Quantification of multi-scale links of anthropogenic pressures with PAH and PCB bioavailable contamination in French freshwaters.

Aquatic ecosystems are exposed to multiple environmental pressures including chemical contamination. Polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) are persistent organic pollutants (POPs) known as preoccupying substances for the environment. Active biomonitoring (ABM) is a surveillance method for polluted aquatic ecosystems measuring bioavailable contamination. In this work, the aim was to quantify the total links between environmental pressures and bioavailable contamination (for PAHs and PCBs) at the French national scale. Based on 245 sites experimented by ABM from 2017 to 2019, environmental pressures (anthropogenic pressures and environmental parameters) were defined (point source landfill density, point source urban density, point source industry density, point source road density, nonpoint source industry density, nonpoint source road density, nonpoint source urban density, nutrients and organic matter, slope, dams, straightness, coarse sediment, summer precipitation, hydrographic network density and watershed size) and characterized by one or a combination of measures called stressor indicators. The links between environmental pressures and bioavailable POPs contamination (ABM measure) at a large spatial scale were defined and quantified via structural equation modeling. Point source urban density, nutrients and organic matter, summer precipitation, straightness and point source industry density are correlated positively with PAH bioavailable contamination. In contrast, nonpoint source urban density, nonpoint source industry density, nonpoint source road density and watershed size are positively correlated with PCB bioavailable contamination. The dominant pressures linked to PAHs and PCBs were different, respectively local and large-scale pressures were linked to PAH bioavailable contamination, and only large-scale pressures were linked to PCB bioavailable contamination.

ARPEGES: A Bayesian Belief Network to Assess the Risk of Pesticide Contamination for the River Network of France.

Pesticides are priority concerns in aquatic risk assessment due to their widespread use, ongoing development of new molecules, and potential effects from short- and long-term exposures to aquatic life. Water quality assessments are also challenged by contrasting pesticide behaviors (e.g., mobility, half-life time, solubility) in different environmental contexts. Furthermore, monitoring networks are not well adapted to the pesticide media transfer dynamics and therefore fail at providing a reliable assessment of pesticides. We present here a Bayesian belief network that was developed in a cooperative process between researchers specializing in Bayesian modeling, soil sciences, agronomy, and diffuse pollutants to provide a tool for stakeholders to assess surface water contamination by pesticides. It integrates knowledge on dominant transfer pathways according to basin physical context and climate for different pesticides properties, such as half-life duration and affinity to organic C, to develop an assessment of risks of contamination for every watershed in France. The resulting model, ARPEGES (Analyse de Risque PEsticide pour la Gestion des Eaux de Surface; trans. Risk analysis of contamination by pesticides for surface water management), was developed in R. A user-friendly R interface was built to enable stakeholders to not only obtain ARPEGES' results, but also freely use it to test management scenarios. Though it is applicable to any chemical, its results are illustrated for S-Metolachlor, a pesticide that was widely used on cereals crops worldwide. In addition to providing contamination potential, ARPEGES also provides a way to diagnose its main explaining factors, enabling stakeholders to focus efforts in the most potentially affected basins, but also on the most probable cause of contamination. In this context, the Bayesian belief network allowed us to use information at different scales (i.e., regional contexts for climate, pedology at the basin scale, pesticide use at the municipality scale) to provide an expert assessment of the processes driving pesticide contamination of streams and the associated uncertainties. Integr Environ Assess Manag 2021;17:188-201. © 2020 SETAC.

How to quantify the links between bioavailable contamination in watercourses and pressures of anthropogenic land cover, contamination sources and hydromorphology at multiple scales?

Active biomonitoring permits the quantification of biological exposure to chemicals through measurements of bioavailable concentrations in biota and biological markers of toxicity in organisms. It enables respective comparison of the levels of contamination between sites and sampling campaigns. Caged gammarids are recently proposed as relevant probes for measuring bioavailable contamination in freshwater systems. The purpose of the present study was to develop a multi-pressure and multiscale approach, considering metallic contamination levels (from data based on active biomonitoring) as a response to pressures (combination of individual stressors). These pressures were anthropogenic land cover, industry density, wastewater treatment plant density, pressures on stream hydromorphological functioning, riverside vegetation and bioavailability factors. A dataset combining active biomonitoring and potentially related pressures was established at the French national scale, with 196 samplings from 2009 to 2016. The links between pressures and metallic contamination were defined and modelled via structural equation modeling (more specifically partial least squares - path modeling). The model enabled the understanding of the respective influences of pressures on metallic bioconcentration in caged sentinel organisms. Beyond validating the local influence of industries and wastewater treatment plants on metallic contamination, this model showed a complementary effect of driving forces of anthropogenic land cover (leading to human activities). It also quantified a significant influence of pressures on stream hydromorphological functioning, presence of vegetation and physico-chemical parameters on metal bioconcentration. This hierarchical multi-pressure approach could serve as a concept on how pressures and contamination (assessed by active biomonitoring) can be connected. Its future application will enable better understanding of environmental pressures leading to contamination in freshwater ecosystems.

Lack of definition of mathematical terms in ecology: The case of the sigmoid class of functions in macro-ecology.

Defining mathematical terms and objects is a constant issue in ecology; often definitions are absent, erroneous, or imprecise. Through a bibliographic prospection, we show that this problem appears in macro-ecology (biogeography and community ecology) where the lack of definition for the sigmoid class of functions results in difficulties of interpretation and communication. In order to solve this problem and to help harmonize papers that use sigmoid functions in ecology, herein we propose a comprehensive definition of these mathematical objects. In addition, to facilitate their use, we classified the functions often used in the ecological literature, specifying the constraints on the parameters for the function to be defined and the curve shape to be sigmoidal. Finally, we interpreted the different properties of the functions induced by the definition through ecological hypotheses in order to support and explain the interest of such functions in ecology and more precisely in biogeography.

Multisubstance Indicators Based on Caged Gammarus Bioaccumulation Reveal the Influence of Chemical Contamination on Stream Macroinvertebrate Abundances across France.

Most anthropogenic stressors affecting freshwater systems are qualitatively known. However, the quantitative assessment of contaminant exposure and effects to aquatic communities is still difficult, limiting the understanding of consequences on aquatic ecosystem functioning and the implementation of effective management plans. Here, multisubstance indicators based on caged gammarid bioaccumulated contamination data are proposed (for metals and persistent organic pollutants, POPs) to map the bioavailable contamination level of freshwater ecosystems at a large spatial scale. We assessed the ability of these indicators to highlight the relationships between chemical exposure gradients and alteration in the abundance of macroinvertebrate populations on a data set of 218 watercourses distributed throughout France. We identified spatial regional heterogeneities in the levels of bioavailable contamination of metals (18 compounds) and POPs (43 compounds). Besides this, a degradation of Gammaridae, Ephemeridae, and Hydrobiidae densities with increasing levels of metal contamination are identified relative to Baetidae, Chironomidae, and Hydropsychidae. We show here that active biomonitoring allows the establishment of multisubstance indicators of bioavailable contamination, which reliably quantify chemical exposure gradients in freshwater ecosystems. Our ability to identify species-specific responses to chemical exposure gradients demonstrates the promising possibility to further decipher the effects of chemical contamination on macroinvertebrate assemblages through this type of indicator.

At what scale and extent environmental gradients and climatic changes influence stream invertebrate communities?

In a context of increasing landscape modifications and climatic changes, scale hierarchy becomes an ever more crucial issue to integrate in the analysis of drivers and stressors of biological communities, especially in river networks. To cope with this issue, we developed (i) spatial hierarchical models of functional diversity of stream invertebrate communities to assess the relative influence of local- vs. regional-scale factors in structuring community assembly, and (ii) analysis of metacommunity elements to determine the ecological processes behind the structuring. The spatial structuring of benthic invertebrate communities was investigated over 568 sites in South-eastern France. Community structure was mainly driven by the altitudinal gradient and spring flow variation at broad scales, with functional diversity gradually decreasing with elevation and being maximized at intermediate levels of flow variability. According to the 'elements of metacommunity structure' analysis, the prevailing influence of the altitudinal gradient was also supported by a Clementsian structuration of invertebrate communities. Conversely, the influence of observed climatic changes in temperature and rainfall was weak and observed only at fine scales. As a result, natural environmental filters were stronger drivers of the functional diversity of communities than human-induced stressors (e.g. water pollution and hydromorphological alterations). More broadly, our results suggest that management needs to embrace the possibilities of gathering high spatial and taxonomical resolution data when analysing and predicting flow variation and climate change effects in order to preserve and restore functionally diverse communities. Moreover, to develop environmental flow schemes or restoration and climate change adaptation strategies for freshwater communities, local and regional processes need to be addressed simultaneously; equally responsible as drivers of community diversity.

Metapopulation modelling of riparian tree species persistence in river networks under climate change.

Floodplain landscapes are highly fragmented by river regulation resulting in habitat degradation and flood regime perturbation, posing risks to population persistence. Climate change is expected to pose supplementary risks in this context of fragmented landscapes, and especially for river systems adaptation management programs are developed. The association of habitat quality and quantity with the landscape dynamics and resilience to human-induced disturbances is still poorly understood in the context of species survival and colonization processes, but essential to prioritize conservation and restoration actions. We present a modelling approach that elucidates network connectivity and landscape dynamics in spatial and temporal context to identify vital corridors and conservation priorities in the Loire river and its tributaries. Alteration of flooding and flow regimes is believed to be critical to population dynamics in river ecosystems. Still, little is known of critical levels of alteration both spatially and temporally. We applied metapopulation modelling approaches for a dispersal-limited tree species, white elm; and a recruitment-limited tree species, black poplar. In different model steps the connectivity and natural dynamics of the river landscape are confronted with physical alterations (dams/dykes) to species survival and then future scenarios for climatic changes and potential adaptation measures are entered in the model and translated in population persistence over the river basin. For the two tree species we highlighted crucial network zones in relation to habitat quality and connectivity. Where the human impact model already shows currently restricted metapopulation development, climate change is projected to aggravate this persistence perspective substantially. For both species a significant drawback to the basin population is observed, with 1/3 for elm and » for poplar after 25 years already. But proposed adaptation measures prove effective to even bring metapopulation strength and persistence up to a level above the current level.

Unravelling river system impairments in stream networks with an integrated risk approach.

Rivers are complex systems for which it is hard to make reliable assessments of causes and responses to impairments. We present a holistic risk-based framework for river ecosystem assessment integrating all potential intervening processes and functions. Risk approaches allow us to deal with uncertainty both in the construction of indicators for magnitude of stressors and in the inference of environmental processes and their impairment. Yet, here we go further than simply replacing uncertainty by a risk factor. We introduce a more accurate and rigorous notion of risk with a transcription of uncertainty in causal relationships in probability distributions for the magnitude of impairment and the weight of different descriptors, with an associated confidence in the diagnostic. We discuss how Bayesian belief networks and Bayesian hierarchical inference allow us to deal with this risk concept to predict impairments and potential recovery of river ecosystems. We developed a comprehensive approach for river ecosystem assessment, which offers an appealing tool to facilitate diagnosis of the likely causes of impairment and predict future conditions. The ability of the risk approaches to integrate multi-scale quantitative and qualitative descriptors in the identification of multiple stressor sources and pathways in the stream network, and their impairment of specific processes and structures is illustrated for the national-level risk analysis for hydromorphology and pesticide pollution. Not only does the risk-based framework provide a more complete picture of environmental impairments, but it also offers a comprehensive, user-friendly tool to instruct the decision process.

The spatial distribution of Mustelidae in France.

We estimated the spatial distribution of 6 Mustelidae species in France using the data collected by the French national hunting and wildlife agency under the "small carnivorous species logbooks" program. The 1500 national wildlife protection officers working for this agency spend 80% of their working time traveling in the spatial area in which they have authority. During their travels, they occasionally detect dead or living small and medium size carnivorous animals. Between 2002 and 2005, each car operated by this agency was equipped with a logbook in which officers recorded information about the detected animals (species, location, dead or alive, date). Thus, more than 30000 dead or living animals were detected during the study period. Because a large number of detected animals in a region could have been the result of a high sampling pressure there, we modeled the number of detected animals as a function of the sampling effort to allow for unbiased estimation of the species density. For dead animals -- mostly roadkill -- we supposed that the effort in a given region was proportional to the distance traveled by the officers. For living animals, we had no way to measure the sampling effort. We demonstrated that it was possible to use the whole dataset (dead and living animals) to estimate the following: (i) the relative density -- i.e., the density multiplied by an unknown constant -- of each species of interest across the different French agricultural regions, (ii) the sampling effort for living animals for each region, and (iii) the relative detection probability for various species of interest.