Anthropogenic environmental changes, or ‘stressors’, increasingly threaten biodiversity and ecosystem functioning worldwide. Multiple-stressor research is a rapidly expanding field of science that seeks to understand and ultimately predict the interactions between stressors. Reviews and meta-analyses of the primary scientific literature have largely been specific to either freshwater, marine or terrestrial ecology, or ecotoxicology. In this cross-disciplinary study, we review the state of knowledge within and among these disciplines to highlight commonality and division in multiple-stressor research. Our review goes beyond a description of previous research by using quantitative bibliometric analysis to identify the division between disciplines and link previously disconnected research communities. Towards a unified research framework, we discuss the shared goal of increased realism through both ecological and temporal complexity, with the overarching aim of improving predictive power. In a rapidly changing world, advancing our understanding of the cumulative ecological impacts of multiple stressors is critical for biodiversity conservation and ecosystem management. Identifying and overcoming the barriers to interdisciplinary knowledge exchange is necessary in rising to this challenge. Division between ecosystem types and disciplines is largely a human creation. Species and stressors cross these borders and so should the scientists who study them.

• This is the pre-peer reviewed version of the article, which has been published in final form at: http://dx.doi.org/10.1002/rra.933

Biodiversity metrics are critical for assessment and monitoring of ecosystems threatened by anthropogenic stressors. Existing sorting and identification methods are too expensive and labour-intensive to be scaled up to meet management needs. Alternately, a high-throughput DNA sequencing approach could be used to determine biodiversity metrics from bulk environmental samples collected as part of a large-scale biomonitoring program. Here we show that both morphological and DNA sequence-based analyses are suitable for recovery of individual taxonomic richness, estimation of proportional abundance, and calculation of biodiversity metrics using a set of 24 benthic samples collected in the Peace-Athabasca Delta region of Canada. The high-throughput sequencing approach was able to recover all metrics with a higher degree of taxonomic resolution than morphological analysis. The reduced cost and increased capacity of DNA sequence-based approaches will finally allow environmental monitoring programs to operate at the geographical and temporal scale required by industrial and regulatory end-users.

Spatio‐temporal variability in river flow is a fundamental control on instream habitat structure and riverine ecosystem biodiversity and integrity. However, long‐term riverine ecological time‐series to test hypotheses about hydrology–ecology interactions in a broader temporal context are rare, and studies spanning multiple rivers are often limited in their temporal coverage to less than five years. To address this research gap, a unique spatio‐temporal hydroecological analysis was conducted of long‐term instream ecological responses (1990–2000) to river flow regime variability at 83 sites across England and Wales. The results demonstrate clear hydroecological associations at the national scale (all data). In addition, significant differences in ecological response are recorded between three ‘regions’ identified (RM1–3*) associated with characteristics of the flow regime. The effect of two major supra‐seasonal droughts (1990–1992 and 1996–1997) on inter‐annual (IA) variability of the LIFE scores is evident with both events showing a gradual decline before and recovery of LIFE scores after the low flow period. The instream community response to high magnitude flow regimes (1994 and 1995) is also apparent, although these associations are less striking. The results demonstrate classification of rivers into flow regime regions offers a way to help unravel complex hydroecological associations. The approach adopted herein could easily be adapted for other geographical locations, where datasets are available. Such work is imperative to understand flow regime–ecology interactions in a longer term, wider spatial context and so assess future hydroecological responses to climate change and anthropogenic modification of riverine ecosystems. Copyright © 2008 John Wiley & Sons, Ltd.

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• This is the pre-peer reviewed version of the article, which has been pub- Author for Correspondence:Wendy Monk, Canadian Rivers Institute, Department of Biology, Bag Service #45111, University of New Brunswick, Fredericton, New Brunswick, E3B 6E1, Canada. an 11-year macroinvertebrate community dataset (i.e. LIFE scores). The same 'best' models are produced using the PCA-based method and all 201 hydrological variables for two of the three river flow regime groups. However, weaker models are yielded by the PCA-based method for the remaining (flashy) river flow regime class and the whole data set (all 83 rivers). Thus, it is important to exercise caution when employing data reduction/ index redundancy approaches, as they may reject variables of ecological significance due to the assumption that the statistically dominant sources of hydrological variability are the principal drivers of, perhaps more subtle (sensitive), hydroecological associations.3 IntroductionThe ecological importance of river flow regime variability is increasingly well recognised (e.g., Clausen and Biggs, 1997;Wood and Armitage, 2004); and a wide range of potentially 'ecologically relevant' hydrological indices have been identified (e.g. Olden and Poff, 2003). However, such hydroecological analysis is limited by a general lack of paired longterm hydrological and ecological time-series (Wood et al., 2001; Jackson and Füreder, 2006). The search for 'ecologically relevant' hydrological indices has been driven by the need to quantify variability in ecological communities and/or individual populations that may be sensitive to natural hydrological changes or anthropogenic modifications (Richter et al., 1996). Some concerns have been raised regarding the large number of potential hydrological predictors available, since significant redundancy (multicollinearity) exists between many variables (Olden and Poff, 2003). Consequently, some guiding principles are required to aid researchers and water resource managers select the most 'ecologically relevant' hydrological variable(s).Olden and Poff (2003) proposed a method using principal components analysis (PCA) for assessing redundancy between hydrological variables and identifying those indices which account for most variation in river flow regimes using long-term flow records for 420 locations across the continental USA. They suggested that the variables identified by this method may form the basis of future hydroecological analysis. However, to date, their redundancy methodology and the resulting variables have not been widely tested in terms of ecological prediction.The aim of this short communication is to provide the first test of the PCA-based approach proposed by Olden and Poff (2003) in association with ecological data, and to compare its 4 effectiveness against regression models developed using 201 potentially 'ecologically relevant' hydrological variables identified in previous research. Data and methodsHydrological and ecological data were employed for 83 sites in England and Wales ( Figu...

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Widespread alteration of flow regimes requires guidelines for the protection of river ecosystems based on sound science. Preservation of the biodiversity within river ecosystems and sustaining natural ecological functions are key aspects of their management. However, the relationship between the biota and flow-related phenomena is poorly understood and, as a consequence, over-simplistic hydrologybased guidelines for river management have been adopted without establishing clear indicators of success. In the present paper, we aim to support the improvement of guidelines for flow (current velocity) management by developing a flow sensitivity index based on macroinvertebrates for Canadian rivers. Using benthic macroinvertebrate (BMI) samples collected by the Canadian Aquatic Biomonitoring Network (CABIN), current velocity preferences for the 55 most common invertebrate taxa across a range of reference and potential reference sites were derived. A Canadian Ecological Flow Index (CEFI) was developed based on these preferences. By testing the index against independent data, CEFI was found to respond mainly to changes in hydraulic conditions, and was minimally influenced by confounding factors (e.g. stream type, organic enrichment). The index was further validated using two independent data sets from the west and east of Canada, suggesting countrywide applicability of the method. In conclusion, we have developed a practical approach to evaluate relationships between hydrological regime and an important component of the river biota, permitting the development of an index which has good potential as an indicator for the effects of flow alteration. Moreover, we outline how the CEFI could be used as a tool for the development of holistic guidelines for the estimation of riverine flow needs.