Relationship between peak VO₂ and performance on the Rockport fitness walking test of adolescent males with mental retardation

Graduation date: 199

Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude

Predicting the impacts of multiple stressors is important for informing ecosystem management but is impeded by a lack of a general framework for predicting whether stressors interact synergistically, additively or antagonistically. Here, we use process-based models to study how interactions generalise across three levels of biological organisation (physiological, population and consumer-resource) for a two-stressor experiment on a seagrass model system. We found that the same underlying processes could result in synergistic, additive or antagonistic interactions, with interaction type depending on initial conditions, experiment duration, stressor dynamics and consumer presence. Our results help explain why meta-analyses of multiple stressor experimental results have struggled to identify predictors of consistently non-additive interactions in the natural environment. Experiments run over extended temporal scales, with treatments across gradients of stressor magnitude, are needed to identify the processes that underpin how stressors interact and provide useful predictions to management

Coverage of endangered species in environmental risk assessments at EFSA

The EFSA performs environmental risk assessment (ERA) for single potential stressors such as plantprotection products, genetically modified organisms and feed additives, and for invasive alien speciesthat are harmful to plant health. This ERA focusses primarily on the use or spread of such potentialstressors in an agricultural context, but also considers the impact on the wider environment. It isimportant to realise that the above potential stressors in most cases contribute a minor proportion ofthe total integrated pressure that ecosystems experience. The World Wildlife Fund listed the relativeattribution of threats contributing to the declines in animal populations as follows: 37% fromexploitation (fishing, hunting, etc.), 31% habitat degradation and change, 13% from habitat loss, 7%from climate change, and only 5% from invasive species, 4% from pollution and 2% from disease. Inthis scientific opinion, the Scientific Committee gathered scientific knowledge on the extent of coverageof endangered species in current ERA schemes that fall under the remit of EFSA. The legal basis andthe relevant ecological and biological features used to classify a species as endangered areinvestigated. The characteristics that determine vulnerability of endangered species are reviewed.Whether endangered species are more at risk from exposure to potential stressors than other non-target species is discussed, but specific protection goals for endangered species are not given. Due toa lack of effect and exposure data for the vast majority of endangered species, the reliability of usingdata from other species is a key issue for their ERA. This issue and other uncertainties are discussedwhen reviewing the coverage of endangered species in current ERA schemes. Potential tools, such aspopulation and landscape modelling and trait-based approaches, for extending the coverage ofendangered species in current ERA schemes, are explored and reported

Preparing GIS data for analysis of stream monitoring data: The R package openSTARS.

Stream monitoring data provides insights into the biological, chemical and physical status of running waters. Additionally, it can be used to identify drivers of chemical or ecological water quality, to inform related management actions, and to forecast future conditions under land use and global change scenarios. Measurements from sites along the same stream may not be statistically independent, and the R package SSN provides a way to describe spatial autocorrelation when modelling relationships between measured variables and potential drivers. However, SSN requires the user to provide the stream network and sampling locations in a certain format. Likewise, other applications require catchment delineation and intersection of different spatial data. We developed the R package openSTARS that provides the functionality to derive stream networks from a digital elevation model, delineate stream catchments and intersect them with land use or other GIS data as potential predictors. Additionally, locations for model predictions can be generated automatically along the stream network. We present an example workflow of all data preparation steps. In a case study using data from water monitoring sites in Southern Germany, the resulting stream network and derived site characteristics matched those constructed using STARS, an ArcGIS custom toolbox. An advantage of openSTARS is that it relies on free and open-source GRASS GIS and R functions, unlike the original STARS toolbox which depends on proprietary ArcGIS. openSTARS also comes without a graphical user interface, to enhance reproducibility and reusability of the workflow, thereby harmonizing and simplifying the data pre-processing prior to statistical modelling. Overall, openSTARS facilitates the use of spatial regression and other applications on stream networks and contributes to reproducible science with applications in hydrology, environmental sciences and ecology

Recovery of aquatic and terrestrial populations in the context of European pesticide risk assessment

In the present review, we compiled and evaluated the available information supporting the assessment of population and community recovery after pesticide application. This information is crucial for the environmental risk assessment of pesticides. We reviewed more than 3900 manuscripts on those organism groups relevant or likely to become relevant for the risk assessment procedures in Europe, i.e. aquatic invertebrates, algae, aquatic plants, fish, aquatic microbes, amphibians, as well as birds and mammals, non-target terrestrial arthropods including honeybees, non-arthropod invertebrates, terrestrial microbes, non-target terrestrial plants, nematodes, and reptiles. Finally, 106 aquatic and 76 terrestrial studies met our selection criteria and were evaluated in detail. We extracted the following general conclusions: (1) Internal recovery depends strongly on reproduction capacity. For aquatic invertebrates recovery was generally observed within a maximum of five generation times. (2) In cases where recovery occurred within one generation, migration from uncontaminated areas was identified as the main pathway for aquatic and terrestrial invertebrates, in particular for insect species with the ability for aerial re-colonization. (3) Community composition in general did not recover within the study duration in the majority of cases. (4) The ecological context, including factors such as food resources, habitat quality and re-colonization potential, is a crucial factor for recovery from pesticide effects. (5) Indirect effects acting through food chain processes, including predation and competition, are highly relevant for increasing the magnitude of effect and for prolonging recovery time. Based on our findings, we recommend defining realistic scenarios for risk assessment regarding exposure, taxa considered, environmental conditions and ecological context. In addition to experimental studies, field monitoring was shown to yield valuable information to identify relevant taxa, long-term effects and the conditions for recovery, and should therefore be considered to validate approaches of risk assessment. Likewise, ecological modelling was found to be a valuable tool for assessing recovery. Finally, both study design and interpretation of results still often suffer from missing ecological information or from neglect of the available knowledge. Hence, a more rigorous utilization of existing knowledge (e.g. from general disturbance ecology) and the generation of systematic ecological knowledge on the various factors influencing recovery are needed.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Modeling Macroinvertebrate Community Dynamics in Stream Mesocosms Contaminated with a Pesticide

Modeling community dynamics of aquatic invertebrates is an important but challenging task, in particular in ecotoxicological risk assessment. Systematic parameter estimation and rigorous assessment of model uncertainty are often lacking in such applications. We applied the mechanistic food web model Streambugs to investigate the temporal development of the macroinvertebrate community in an ecotoxicological mesocosm experiment with pulsed contaminations with the insecticide thiacloprid. We used Bayesian inference to estimate parameters and their uncertainty. Approx. 85% of all experimental observations lie within the 90% uncertainty intervals indicating reasonably good fits of the calibrated model. However, a validation with independent data was not possible due to lacking data. Investigation of vital rates and limiting factors in the model yielded insights into recovery dynamics. Inclusion of the emergence process and sub-lethal effects turned out to be potentially relevant model extensions. Measurements of food source dynamics, individual body size (classes), and additional knowledge on sub-lethal effects would support more accurate modeling. This application of a process-based, ecotoxicological community model with uncertainty assessment by Bayesian inference increased our process understanding of toxicant effects in macroinvertebrate communities and helped identifying potential improvements in model structure and experimental design

Mapping water quality-related ecosystem services: concepts and applications for nitrogen retention and pesticide risk reduction

One of the challenges of using the ecosystem service (ES) framework in the context of planning and decision support is the question of how to map these services in an appropriate way. For water quality-related ESs, this implies a movement from the display of classical water quality indicators towards the mapping of the service itself. We explore the potential of mapping such water quality-related ESs based on three case studies focusing on different aspects of these services: (1) a European case study on pesticides, (2) a multi-scale German case study on nitrogen retention and (3) a more local case study on nitrogen retention in the Elbe floodplain (Lödderitzer Forst). All these studies show a high spatial variation of the results that can be depicted in maps of ES supply. This allows an identification of areas in which nitrogen retention is highest or which areas face the highest ecological risk due to pesticides. The multi-scale case study shows how the level of detail of the results varies with model resolution-a hierarchical approach to environmental and river basin management seems useful, because it allows the planners to determine scale-specific environmental problems and implement specific measures for the different planning levels.JRC.H.1-Water Resource