RIVPACS database documentation. Final report

With the advent of the EU Water Framework Directive the concept of the 'reference condition' has become explicit within the legislative framework of the European Union. Reference condition has been established as a quality standard against which assessments of biological degradation must be compared. It is therefore essential that Member States can demonstrate that the biological datasets used to define their reference conditions meet the criteria of the WFD. The RIVPACS reference site dataset is therefore central to the definition of reference conditions for macroinvertebrates in streams and rivers in the United Kingdom. Objectives of research: • To establish the ownership of the RIVPACS reference site dataset • To liaise with all stakeholders of the dataset to establish unhindered access to the RIVPACS reference site dataset for the UK agencies (in perpetuity) • To deliver the RIVPACS reference site dataset to the UK agencies and to the public domain in a readily accessible database together will its accompanying physicochemical variables (both existing and newly collated as part of this project), historical and current anthropogenic stress data, and a range of calculated biotic indices. Key findings and recommendations: Ownership of the RIVPACS dataset resides with no single organization and several different organizations consider that they own different portions of the dataset. Formal permissions to release the dataset into the public domain have been obtained from all twelve extant organizations that have been identified as having funded various phases of RIVPACS research. In addition, CEH/NERC has also agreed to release the RIVPACS dataset to the public domain. Terms and conditions relating to the end use of the RIVPACS dataset have now been established. The RIVPACS database has been assembled in Microsoft® Access and can now be downloaded from the CEH web site. This report details the terms and conditions that apply to all end users of the database and it documents the tables given in the database, their structure and the origin of their data. A separate Pressure Data Analysis report describes the screening of the RIVPACS sites in terms of the current and emerging definitions of reference condition

SNIFFER WFD119: Enhancement of the River Invertebrate Classification Tool (RICT)

EXECUTIVE SUMMARY Project funders/partners: Environment Agency (EA), Northern Ireland Environment Agency (NIEA), Scotland & Northern Ireland Forum for Environmental Research (SNIFFER), Scottish Environment Protection Agency (SEPA) Background to research The Regulatory Agencies in the UK (the Environment Agency; Scottish Environment Protection Agency; and the Northern Ireland Environment Agency) now use the River Invertebrate Classification Tool (RICT) to classify the ecological quality of rivers for Water Framework Directive compliance monitoring. RICT incorporates RIVPACS IV predictive models and is a highly capable tool written in a modern software programming language. While RICT classifies waters for general degradation and organic pollution stress, producing assessments of status class and uncertainty, WFD compliance monitoring also requires the UK Agencies to assess the impacts of a wide range of pressures including hydromorphological and acidification stresses. Some of these pressures alter the predictor variables that current RIVPACS models use to derive predicted biotic indices. This project has sought to broaden the scope of RICT by developing one or more RIVPACS model(s) that do not use predictor variables that are affected by these stressors, but instead use alternative GIS based variables that are wholly independent of these pressures. This project has also included a review of the wide range of biotic indices now available in RICT, identifying published sources, examining index performance, and where necessary making recommendations on further needs for index testing and development. Objectives of research •To remove and derive alternative predictive variables that are not affected by stressors, with particular emphasis on hydrological/acidification metric predictors. •To construct one or more new RIVPACS model(s) using stressor independent variables. •Review WFD reporting indices notably AWIC(species), LIFE (species), PSI & WHPT. Key findings and recommendations : Predictor variables and intellectual property rights : An extensive suite of new variables have been derived by GIS for the RIVPACS reference sites that have been shown to act as stressor-independent predictor variables. These include measures of stream order, solid and drift geology, and a range of upstream catchment characteristics (e.g. catchment area, mean altitude of upstream catchment, and catchment aspect). It is recommended that decisions are reached on which of the newly derived model(s) are implemented in RICT so that IPR issues for the relevant datasets can be quickly resolved and the datasets licensed. It is also recommended that licensing is sought for a point and click system (where the dataset cannot be reverse engineered) that is capable of calculating any of the time-invariant RIVPACS environmental predictor variables used by any of the newly derived (and existing) RIVPACS models, and for any potential users. New stressor-independent RIVPACS models : Using the existing predictor variables, together with new ones derived for their properties of stressor-independence, initial step-wise forward selection discriminant models suggested a range of 36 possible models that merited further testing. Following further testing, the following models are recommended for assessing watercourses affected by flow/hydromorphological and/or acidity stress: • For flow/hydromorphological stressors that may have modified width, depth and/or substrate in GB, it is suggested that a new ‘RIVPACS IV – Hydromorphology Independent’ model (Model 24) is used (this does not use the predictor variables width, depth and substratum, but includes a suite of new stressor-independent variables). • For acidity related stressors in GB, it is suggested that a new ‘RIVPACS IV – Alkalinity Independent’ model (Model 35) is used (this does not use the predictor variable alkalinity, but includes new stressor-independent variables). • For flow/hydromorphological stressors and acidity related stressors in GB, it is suggested that a new ‘RIVPACS IV – Hydromorphology & Alkalinity Independent’ model (Model 13) is used (this does not use the predictor variables width, depth, substratum and alkalinity, but includes a suite of new stressor-independent variables). • Reduced availability of appropriate GIS tools at this time has meant that no new models have been developed for Northern Ireland. Discriminant functions and end group means have now been calculated to enable any of these models to be easily implemented in the RICT software. Biotic indices : The RIVPACS models in RICT can now produce expected values for a wide range of biotic indices addressing a variety of stressors. These indices will support the use of RICT as a primary tool for WFD classification and reporting of the quality of UK streams and rivers. There are however a number of outstanding issues with indices that need to be addressed: • There is a need to develop a biotic index for assessing metal pollution. • WFD EQR banding schemes are required for many of the indices to report what is considered an acceptable degree of stress (High-Good) and what is not (Moderate, Poor or Bad). • A comprehensive objective testing process needs to be undertaken on the indices in RICT using UK-wide, large-scale, independent test datasets to quantify their index-stressor relationships and their associated uncertainty, for example following the approach to acidity index testing in Murphy et al., (in review) or organic/general degradation indices in Banks & McFarland (2010). • Following objective testing, the UK Agencies should make efforts to address any index under-performance issues that have been identified, and where necessary new work should be commissioned to modify existing indices, or develop new ones where required so that indices for all stress types meet certain minimum performance criteria. • Testing needs to be done to examine index-stressor relationships with both observed index scores and RIVPACS observed/expected ratios. Work should also be done to compare the existing RIVPACS IV and the new stressor-independent models (developed in this project) as alternative sources of the expected index values for these tests. • Consideration should be given to assessing the extent to which chemical and biological monitoring points co-occur. Site-matched (rather than reach-matched) chemical and biological monitoring points would i) generate the substantial training datasets needed to refine or develop new indices and ii) generate the independent datasets for testing

Rediscovery of the critically endangered ‘scarce yellow sally stonefly’ Isogenus nubecula in United Kingdom after a 22 year period of absence.

The critically endangered ‘scarce yellow sally stonefly’ Isogenus nubecula (Newman, 1833) (Plecoptera: Perlodidae) was rediscovered in the United Kingdom (UK) in 2017. This rediscovery comes after a 22-year period of absence despite numerous surveys since its last record in 1995. This species is one of the rarest stoneflies in the UK and Europe and its rediscovery is of international significance, being the westernmost point in Europe where the species is found, with the next nearest populations occurring in Austria and western Hungary, Slovakia, and central Sweden. The species is classed as pRDB2 (vulnerable), however is not listed in the British Red Data Book despite only being present (as far as records detail) in one river, the River Dee in North Wales, UK. Only fourteen individuals were caught and the need for conservation of this rare stonefly is therefore of paramount importance. We have made recommendations for the need to increase survey effort using environmental DNA (eDNA) techniques in order to fully understand the species range in this river and those in the surrounding area. The DNA sequence of I. nubecula has been uploaded on GenBank for further genetic studies. Captive rearing could also be explored with possible reintroductions to sites within its former UK range

First detection of a highly invasive freshwater amphipod (Crangonyx floridanus) in the United Kingdom

The freshwater gammarid, Crangonyx floridanus, originates from North America but has invaded and subsequently spread rapidly throughout Japan. We provide here the first genetic and microscopic evidence that C. floridanus has now also reached the United Kingdom. We found this species in two locations separated by more than 200 km (Lake Windermere in the North of the UK and Smestow Brook, West Midlands). The current distribution of C. floridanus is currently unknown, however, both sites are well connected to other river and canal systems. Therefore, the chance of further spread is high. Genetic analyses of C. floridanus indicate that British inland waters are colonised by the same lineage, which invaded Japan. We recommend further work to assess the distribution of this species and its impact on the local fauna and flora

Anglers’ Riverfly Monitoring Initiative (ARMI): A UK-wide citizen science project for water quality assessment

The Anglers’ Riverfly Monitoring Initiative (ARMI) is a UK-wide citizen science project focused on river water quality assessment. There are currently >2000 ARMI volunteers monitoring >1600 sites that are organized into 35 regional hubs across the UK. ARMI is effective in the early detection of water pollution and complements the routine monitoring undertaken by the UK statutory environment agencies. ARMI volunteers are trained to take standardized 3-min kick-samples of freshwater invertebrates from a river site, and use these samples to produce an ARMI score based on the abundance of key pollution-sensitive taxa. ARMI scores and standard invertebrate monitoring metrics are closely correlated. Each sampling site has a ‘trigger level’ score set by the national regulatory authority—e.g., the Environment Agency (EA) in England. If the ARMI score falls below this trigger level, the regulatory authority is notified and agency officers investigate the cause of the low score. This process has resulted in many reports of pollution incidents that otherwise may have gone undiscovered but were instead rapidly detected and neutralized. In some cases, investigations resulted in fines being levied against those responsible. ARMI data have also proved useful in assessing the effectiveness of river restoration schemes. Here, we demonstrate the effectiveness of the ARMI as a structured citizen science program in enhancing the environmental protection of rivers. We also show that the ARMI program complements the work of statutory authorities and describe how it promotes community engagement with river environments.© 2019 by The Society for Freshwater Science. The attached file is the published pdf (embargo period has expired)

River Invertebrate Classification Tool

Background to research The Regulatory Agencies in the UK (the Environment Agency; Scottish Environment Protection Agency; and the Environment & Heritage Service) currently use RIVPACS III+ software to classify the ecological quality of rivers. However, because RIVPACS III+ pre-dates the WFD, there has been a requirement to ensure that the RIVPACS reference sites are fully WFD compliant, to add new biotic indices to the RIVPACS models, and to improve the robustness of the RIVPACS software to fully meet the needs of the Agencies in their delivery of WFD monitoring. These issues have been addressed in this project and have led to the development of new RIVPACS IV predictive models that will be programmed into a new River Invertebrate Classification Tool being built by SEPA. This new system will be based on a modern software programming language, be compatible with the agencies’ computer systems and include the ability to predict new biological indices, produce biological status assessments based on these new indices and be able to estimate the errors involved in using these new indices. Because access to the new system will be essential for the UK Agencies to be able to implementation the WFD, the new tool will be readily and freely available to anyone who might seek to use it. Objectives of research • The overall objective of the project was to produce a new set of RIVPACS predictive models for use within a new River Invertebrate Classification Tool that will be used to classify the ecological status of rivers for Water Framework Directive compliance monitoring • The new RIVPACS models constructed with this project required considerably enhanced functionality compared to RIVPACS III+ to properly address the monitoring requirements of the UK Agencies in their implementation of the Water Framework Directive. Key findings and recommendations This project has produced new RIVPACS IV models with considerably enhanced functionality compared to RIVPACS III+. These models incorporate: • A full revision of the taxonomic framework of RIVPACS to bring the taxonomy up-to-date and enable compatiability across the revised Miatland, Furse code and National Biodiversity Network taxon coding systems used across the UK Agencies and beyond • Predictions that fully satisfy the WFD definition of ‘reference condition’ by adjusting predictions for certain stream types and by removal of sites that were not in reference condition when sampled • Allocation of actual abundance values to family level records in the RIVPACS reference data set. Lack of actual abundance data, especially at family level, has affected all versions of RIVPACS and has constrained the types of biotic indices that RIVPACS can predict • Extension to the suite of biotic indices so that the new system can predict a wider range of reference state “expected” index values. This enables full WFD quality reporting capabilities as well as providing the system with the general functionality to predict a much wider range of indices e.g. intercalibration indices (e.g. ICMi), stress-specific indices, and ecological and functional trait indices • Extension of the uncertainty/errors module to estimate and assess uncertainty in (i) assignment to status class and (ii) comparison of samples for temporal change in quality and status. This needs to be done for a wider range of biotic indices (including those incorporating abundance data) These new RIVPACS IV models can be used by the UK Agencies across Great Britain and Northern Ireland in their WFD compliance monitoring. All of the algorithms, variables and data necessary to build these models have been provided to SEPA for programming into a new River Invertebrate Classification Tool that will be disseminated made free of charge to all interested user