The effects of non-native signal crayfish (Pacifastacus leniusculus) on fine sediment and sediment-biomonitoring

© 2017 The Authors The North American signal crayfish (Pacifastacus leniusculus) has invaded freshwater ecosystems across Europe. Recent studies suggest that predation of macroinvertebrates by signal crayfish can affect the performance of freshwater biomonitoring tools used to assess causes of ecological degradation. Given the reliance on biomonitoring globally, it is crucial that the potential influence of invasive species is better understood. Crayfish are also biogeomorphic agents, and therefore, the aim of this study was to investigate whether sediment-biomonitoring tool outputs changed following signal crayfish invasions, and whether these changes reflected post-invasion changes to deposited fine sediment, or changes to macroinvertebrate community compositions unrelated to fine sediment. A quasi-experimental study design was employed, utilising interrupted time series analysis of long-term environmental monitoring data and a hierarchical modelling approach. The analysis of all sites (n = 71) displayed a small, but statistically significant increase between pre- and post-invasion index scores for the Proportion of Sediment-sensitive Invertebrates (PSI) index biomonitoring tool (4.1, p <  0.001, 95%CI: 2.1, 6.2), which can range from 0 to 100, but no statistically significant difference was observed for the empirically-weighted PSI (0.4, p = 0.742, 95%CI: − 2.1, 2.9), or fine sediment (− 2.3, p = 0.227, 95%CI: − 6.0, 1.4). Subgroup analyses demonstrated changes in biomonitoring tool scores ranging from four to 10 percentage points. Importantly, these subgroup analyses showed relatively small changes to fine sediment, two of which were statistically significant, but these did not coincide with the expected responses from biomonitoring tools. The results suggest that sediment-biomonitoring may be influenced by signal crayfish invasions, but the effects appear to be context dependent, and perhaps not the result of biogeomorphic activities of crayfish. The low magnitude changes to biomonitoring scores are unlikely to result in an incorrect diagnosis of sediment pressure, particularly as these tools should be used alongside a suite of other pressure-specific indices

Ensemble evaluation of hydrological model hypotheses

It is demonstrated for the first time how model parameter, structural and data uncertainties can be accounted for explicitly and simultaneously within the Generalized Likelihood Uncertainty Estimation (GLUE) methodology. As an example application, 72 variants of a single soil moisture accounting store are tested as simplified hypotheses of runoff generation at six experimental grassland field-scale lysimeters through model rejection and a novel diagnostic scheme. The fields, designed as replicates, exhibit different hydrological behaviors which yield different model performances. For fields with low initial discharge levels at the beginning of events, the conceptual stores considered reach their limit of applicability. Conversely, one of the fields yielding more discharge than the others, but having larger data gaps, allows for greater flexibility in the choice of model structures. As a model learning exercise, the study points to a “leaking” of the fields not evident from previous field experiments. It is discussed how understanding observational uncertainties and incorporating these into model diagnostics can help appreciate the scale of model structural error

On the use of systematic reviews to inform environmental policies

AbstractEnvironmental research varies in its methodological quality, degree of bias, and relevance to policy questions. Using this heterogeneous, and sometimes polarised, research to inform environmental policies can be challenging. Policy-making in the healthcare field sometimes uses systematic reviews (SRs) to tackle these issues and present a comprehensive, policy-neutral, transparent and reproducible synthesis of the evidence. However, there is less familiarity with SRs in the environmental field. The aim of this article is to: (1) summarise the process of conducting SRs, using best practice methods from the healthcare field as an example, (2) explain the rationale behind each stage of conducting a SR, and (3) examine the prospects and challenges of using SRs to inform environmental policy. We conclude that existing SR protocols from healthcare can be, and have been, applied successfully to environmental research but some adaptations could improve the process. The literature search stage could be expedited by standardising the reporting and indexing of environmental studies, equivalent to that in the healthcare field. The consistency of the study appraisal stage of SRs could be augmented by refining the existing quality assessment tools used in the healthcare field, enhancing their ability to discriminate quality and risk of bias in non-randomised studies. Ultimately, the strength of evidence within SRs on environmental topics could be improved through more widespread use of randomised controlled trials as a research method, owing to their inherently lower risk of bias when conducted according to best practice

On the Use of Systematic Reviews to Inform Environmental Policies.” Environmental Science Policy 42: 6777

Environmental science Environmental policy a b s t r a c t Environmental research varies in its methodological quality, degree of bias, and relevance to policy questions. Using this heterogeneous, and sometimes polarised, research to inform environmental policies can be challenging. Policy-making in the healthcare field sometimes uses systematic reviews (SRs) to tackle these issues and present a comprehensive, policyneutral, transparent and reproducible synthesis of the evidence. However, there is less familiarity with SRs in the environmental field. The aim of this article is to: (1) summarise the process of conducting SRs, using best practice methods from the healthcare field as an example, (2) explain the rationale behind each stage of conducting a SR, and (3) examine the prospects and challenges of using SRs to inform environmental policy. We conclude that existing SR protocols from healthcare can be, and have been, applied successfully to environmental research but some adaptations could improve the process. The literature search stage could be expedited by standardising the reporting and indexing of environmental studies, equivalent to that in the healthcare field. The consistency of the study appraisal stage of SRs could be augmented by refining the existing quality assessment tools used in the healthcare field, enhancing their ability to discriminate quality and risk of bias in non-randomised studies. Ultimately, the strength of evidence within SRs on environmental topics could be improved through more widespread use of randomised controlled trials as a research method, owing to their inherently lower risk of bias when conducted according to best practice

I: Quality assessment tools for evidence from environmental science. Environmental Evidence 2014

Abstract Assessment of the quality of studies is a critical component of evidence syntheses such as systematic reviews (SRs) that are used to inform policy decisions. To reduce the potential for reviewer bias, and to ensure that the findings of SRs are transparent and reproducible, organisations such as the Cochrane Collaboration, the Campbell Collaboration, and the Collaboration for Environmental Evidence, recommend the use of formal quality assessment tools as opposed to informal expert judgment. However, there is a bewildering array of around 300 formal quality assessment tools that have been identified in the literature, and it has been demonstrated that the use of different tools for the assessment of the same studies can result in different estimates of quality, which can potentially reverse the conclusions of a SR. It is therefore important to consider carefully, the choice of quality assessment tool. We argue that quality assessment tools should: (1) have proven construct validity (i.e. the assessment criteria have demonstrable link with what they purport to measure), (2) facilitate inter-reviewer agreement, (3) be applicable across study designs, and (4) be quick and easy to use. Our aim was to examine current best practice for quality assessment in healthcare and investigate the extent to which these best practices could be useful for assessing the quality of environmental science studies. The feasibility of this transfer is demonstrated in a number of existing SRs on environmental topics. We propose that environmental practitioners should revise, test and adopt the best practice quality assessment tools used in healthcare as a recommended approach for application to environmental science. We provide pilot versions of quality assessment tools, modified from the best practice tools used in healthcare, for application on studies from environmental science

Evaluation of a fine sediment biomonitoring tool across a wide range of temperate rivers and streams

Journal ArticleThis is an open access article available at http://onlinelibrary.wiley.com/doi/10.1111/fwb.12429/epdfElevated levels of fine sediment (suspended and deposited) are a common cause of ecological degradation in freshwater ecosystems. However, it is time-consuming and expensive to monitor these parameters to support national and international water resource legislation. The Proportion of Sediment-sensitive Invertebrates (PSI) index is a biomonitoring tool that is designed to identify the degree of sedimentation in rivers and streams. Despite having a sound biological basis, until now, the PSI index has only been tested against observed fine sediment data in two catchments; other published applications of the PSI index have relied on inferred fine sediment values. In this study, we report the results of a comprehensive analysis of the performance of the PSI index across a wide range of reference condition temperate stream and river ecosystems, including 835 sites with data on deposited sediment and 451 sites with data on suspended solids (>12 500 data points measured between 1978 and 2002). The effect of taxonomic level and taxonomic resolution on the performance of the PSI index was also examined, as was the performance of the PSI index against other non-sediment-specific indices, including Average Score Per Taxon (ASPT), Lotic-invertebrate Index for Flow Evaluation (LIFE), Ephemeroptera, Plecoptera and Trichoptera (EPT) abundance, % EPT abundance, EPT richness and % EPT richness. The results of this study show that the PSI index was more correlated with fine sediment metrics than the other biological indices tested: rs = -0.64, (P < 0.01, n = 2502) for deposited sediment and rs = -0.50 (P < 0.01, n = 1353) for suspended solids. We highlight the optimal conditions for applying the PSI index, in its current form. Given the variability in the relationship between PSI and fine sediment metrics, we propose that the use of data from more objective, quantitative methods of measuring deposited fine sediment may help to enhance the performance of the model for future applications and advance understanding of fine sediment dynamics and the pressure-response relationship.NERCEnvironment Agenc

Developing an improved biomonitoring tool for fine sediment: Combining expert knowledge and empirical data

Journal ArticleThe Proportion of Sediment-sensitive Invertebrates (PSI) index is a biomonitoring tool that is designed to identify the degree of sedimentation in rivers and streams. Despite having a sound biological basis, the tool has been shown to have only a moderate correlation with fine sediment, which although comparable to other pressure specific indices, limits confidence in its application. The aim of this study was to investigate if the performance of the PSI index could be enhanced through the use of empirical data to supplement the expert knowledge and literature which were used to determine the original four fine sediment sensitivity ratings. The empirical data used, comprised observations of invertebrate abundance and percentage fine sediment, collected across a wide range of reference condition temperate stream and river ecosystems (model training dataset n = 2252). Species were assigned sensitivity weights within a range based on their previously determined sensitivity rating. Using a range of weights acknowledges the breadth of ecological niches that invertebrates occupy and also their differing potential as indicators. The optimum species-specific sensitivity weights were identified using non-linear optimisation, as those that resulted in the highest Spearman's rank correlation coefficient between the Empirically-weighted PSI (E-PSI) scores and deposited fine sediment in the model training dataset. The correlation between percentage fine sediment and E-PSI scores in the test dataset (n = 252) was eight percentage points higher than the correlation between percentage fine sediment and the original PSI scores (E-PSI rs = -0.74, p s = -0.66, p < 0.01). This study demonstrates the value of combining a sound biological basis with evidence from large empirical datasets, to test and enhance the performance of biomonitoring tools to increase confidence in their application.NERCEnvironment Agenc

The Effects of Run-of-River Hydroelectric Power Schemes on Fish Community Composition in Temperate Streams and Rivers

<div><p>The potential environmental impacts of large-scale storage hydroelectric power (HEP) schemes have been well-documented in the literature. In Europe, awareness of these potential impacts and limited opportunities for politically-acceptable medium- to large-scale schemes, have caused attention to focus on smaller-scale HEP schemes, particularly run-of-river (ROR) schemes, to contribute to meeting renewable energy targets. Run-of-river HEP schemes are often presumed to be less environmentally damaging than large-scale storage HEP schemes. However, there is currently a lack of peer-reviewed studies on their physical and ecological impact. The aim of this article was to investigate the effects of ROR HEP schemes on communities of fish in temperate streams and rivers, using a Before-After, Control-Impact (BACI) study design. The study makes use of routine environmental surveillance data collected as part of long-term national and international monitoring programmes at 23 systematically-selected ROR HEP schemes and 23 systematically-selected paired control sites. Six area-normalised metrics of fish community composition were analysed using a linear mixed effects model (number of species, number of fish, number of Atlantic salmon—<i>Salmo salar</i>, number of >1 year old Atlantic salmon, number of brown trout—<i>Salmo trutta</i>, and number of >1 year old brown trout). The analyses showed that there was a statistically significant effect (p<0.05) of ROR HEP construction and operation on the number of species. However, no statistically significant effects were detected on the other five metrics of community composition. The implications of these findings are discussed in this article and recommendations are made for best-practice study design for future fish community impact studies.</p></div