A global agenda for advancing freshwater biodiversity research.

Global freshwater biodiversity is declining dramatically, and meeting the challenges of this crisis requires bold goals and the mobilisation of substantial resources. While the reasons are varied, investments in both research and conservation of freshwater biodiversity lag far behind those in the terrestrial and marine realms. Inspired by a global consultation, we identify 15 pressing priority needs, grouped into five research areas, in an effort to support informed stewardship of freshwater biodiversity. The proposed agenda aims to advance freshwater biodiversity research globally as a critical step in improving coordinated actions towards its sustainable management and conservation.

Plant Metabolic Network 15: A resource of genome-wide metabolism databases for 126 plants and algae.

To understand and engineer plant metabolism, we need a comprehensive and accurate annotation of all metabolic information across plant species. As a step towards this goal, we generated genome-scale metabolic pathway databases of 126 algal and plant genomes, ranging from model organisms to crops to medicinal plants (https://plantcyc.org). Of these, 104 have not been reported before. We systematically evaluated the quality of the databases, which revealed that our semi-automated validation pipeline dramatically improves the quality. We then compared the metabolic content across the 126 organisms using multiple correspondence analysis and found that Brassicaceae, Poaceae, and Chlorophyta appeared as metabolically distinct groups. To demonstrate the utility of this resource, we used recently published sorghum transcriptomics data to discover previously unreported trends of metabolism underlying drought tolerance. We also used single-cell transcriptomics data from the Arabidopsis root to infer cell type-specific metabolic pathways. This work shows the quality and quantity of our resource and demonstrates its wide-ranging utility in integrating metabolism with other areas of plant biology.

Reduction of taxonomic bias in diatom species data.

Inconsistency in taxonomic identification and analyst bias impede the effective use of diatom data in regional and national stream and lake surveys. In this study, we evaluated the effect of existing protocols and a revised protocol on the precision of diatom species counts. The revised protocol adjusts five elements of sample preparation, taxon identification and enumeration, and quality control (QC) samples. We used six independent datasets to assess the effect of the adjustments on analytical outcomes. The first dataset was produced by five analysts from three laboratories following a standard protocol (Charles et al. 2002). The remaining datasets were produced by 2-3 analysts in 1-3 laboratories following a revised protocol. The revised protocol included the following modifications: 1) use of Battarbee settling chambers to prepare coverslips, 2) development of coordinated pre-count voucher floras based on morphological operational taxonomic units (mOTUs), 3) random assignment of samples to analysts, 4) post-count identification and documentation of taxa, and 5) increased QC samples. The revised protocol reduced taxonomic bias, as measured by reduction in analyst signal, and improved similarity among QC samples. Reduced taxonomic bias improves the performance of biological assessments, facilitates transparency across studies, and refines estimates of diatom species distributions.

Genome-Wide Association and Prediction of Traits Related to Salt Tolerance in Autotetraploid Alfalfa (Medicago sativa L.).

Soil salinity is a growing problem in world production agriculture. Continued improvement in crop salt tolerance will require the implementation of innovative breeding strategies such as marker-assisted selection (MAS) and genomic selection (GS). Genetic analyses for yield and vigor traits under salt stress in alfalfa breeding populations with three different phenotypic datasets was assessed. Genotype-by-sequencing (GBS) developed markers with allele dosage and phenotypic data were analyzed by genome-wide association studies (GWAS) and GS using different models. GWAS identified 27 single nucleotide polymorphism (SNP) markers associated with salt tolerance. Mapping SNPs markers against the Medicago truncatula reference genome revealed several putative candidate genes based on their roles in response to salt stress. Additionally, eight GS models were used to estimate breeding values of the training population under salt stress. Highest prediction accuracies and root mean square errors were used to determine the best prediction model. The machine learning methods (support vector machine and random forest) performance best with the prediction accuracy of 0.793 for yield. The marker loci and candidate genes identified, along with optimized GS prediction models, were shown to be useful in improvement of alfalfa with enhanced salt tolerance. DNA markers and the outcome of the GS will be made available to the alfalfa breeding community in efforts to accelerate genetic gains, in the development of biotic stress tolerant and more productive modern-day alfalfa cultivars.

Landscape heterogeneity strengthens the relationship between ß-diversity and ecosystem function.

Consensus has emerged in the literature that increased biodiversity enhances the capacity of ecosystems to perform multiple functions. However, most biodiversity/ecosystem function studies focus on a single ecosystem, or on landscapes of homogenous ecosystems. Here, we investigate how increased landscape-level environmental dissimilarity may affect the relationship between different metrics of diversity (α, ß, or γ) and ecosystem function. We produced a suite of simulated landscapes, each of which contained four experimental outdoor aquatic mesocosms. Differences in temperature and nutrient conditions of the mesocosms allowed us to simulate landscapes containing a range of within-landscape environmental heterogeneities. We found that the variation in ecosystem functions was primarily controlled by environmental conditions, with diversity metrics accounting for a smaller (but significant) amount of variation in function. When landscapes were more homogeneous, α, ß, and γ diversity was not associated with differences in primary production, and only γ was associated with changes in decomposition. In these homogeneous landscapes, differences in these two ecosystem functions were most strongly related to nutrient and temperature conditions in the ecosystems. However, as landscape-level environmental dissimilarity increased, the relationship between α, ß, or γ and ecosystem functions strengthened, with ß being a greater predictor of variation in decomposition at the highest levels of environmental dissimilarity than α or γ. We propose that when all ecosystems in a landscape have similar environmental conditions, species sorting is likely to generate a single community composition that is well suited to those environmental conditions, ß is low, and the efficiency of diversity-ecosystem function couplings is similar across communities. Under this low ß, the effect of abiotic conditions on ecosystem function will be most apparent. However, when environmental conditions vary among ecosystems, species sorting pressures are different among ecosystems, producing different communities among locations in a landscape. These conditions lead to stronger relationships between ß and the magnitude of ecosystem functions. Our results illustrate that abiotic conditions and the homogeneity of communities influence ecosystem function expressed at the landscape scale.

Thermal and hydrologic responses to climate change predict marked alterations in boreal stream invertebrate assemblages.

Air temperature at the northernmost latitudes is predicted to increase steeply and precipitation to become more variable by the end of the 21st century, resulting in altered thermal and hydrological regimes. We applied five climate scenarios to predict the future (2070-2100) benthic macroinvertebrate assemblages at 239 near-pristine sites across Finland (ca. 1200 km latitudinal span). We used a multitaxon distribution model with air temperature and modeled daily flow as predictors. As expected, projected air temperature increased the most in northernmost Finland. Predicted taxonomic richness also increased the most in northern Finland, congruent with the predicted northwards shift of many species' distributions. Compositional changes were predicted to be high even without changes in richness, suggesting that species replacement may be the main mechanism causing climate-induced changes in macroinvertebrate assemblages. Northern streams were predicted to lose much of the seasonality of their flow regimes, causing potentially marked changes in stream benthic assemblages. Sites with the highest loss of seasonality were predicted to support future assemblages that deviate most in compositional similarity from the present-day assemblages. Macroinvertebrate assemblages were also predicted to change more in headwaters than in larger streams, as headwaters were particularly sensitive to changes in flow patterns. Our results emphasize the importance of focusing protection and mitigation on headwater streams with high-flow seasonality because of their vulnerability to climate change.

Global synthesis of the temperature sensitivity of leaf litter breakdown in streams and rivers.

Streams and rivers are important conduits of terrestrially derived carbon (C) to atmospheric and marine reservoirs. Leaf litter breakdown rates are expected to increase as water temperatures rise in response to climate change. The magnitude of increase in breakdown rates is uncertain, given differences in litter quality and microbial and detritivore community responses to temperature, factors that can influence the apparent temperature sensitivity of breakdown and the relative proportion of C lost to the atmosphere vs. stored or transported downstream. Here, we synthesized 1025 records of litter breakdown in streams and rivers to quantify its temperature sensitivity, as measured by the activation energy (Ea , in eV). Temperature sensitivity of litter breakdown varied among twelve plant genera for which Ea could be calculated. Higher values of Ea were correlated with lower-quality litter, but these correlations were influenced by a single, N-fixing genus (Alnus). Ea values converged when genera were classified into three breakdown rate categories, potentially due to continual water availability in streams and rivers modulating the influence of leaf chemistry on breakdown. Across all data representing 85 plant genera, the Ea was 0.34 ± 0.04 eV, or approximately half the value (0.65 eV) predicted by metabolic theory. Our results indicate that average breakdown rates may increase by 5-21% with a 1-4 °C rise in water temperature, rather than a 10-45% increase expected, according to metabolic theory. Differential warming of tropical and temperate biomes could result in a similar proportional increase in breakdown rates, despite variation in Ea values for these regions (0.75 ± 0.13 eV and 0.27 ± 0.05 eV, respectively). The relative proportions of gaseous C loss and organic matter transport downstream should not change with rising temperature given that Ea values for breakdown mediated by microbes alone and microbes plus detritivores were similar at the global scale.

Understanding temporal variability across trophic levels and spatial scales in freshwater ecosystems.

A tenet of ecology is that temporal variability in ecological structure and processes tends to decrease with increasing spatial scales (from locales to regions) and levels of biological organization (from populations to communities). However, patterns in temporal variability across trophic levels and the mechanisms that produce them remain poorly understood. Here we analyzed the abundance time series of spatially structured communities (i.e., metacommunities) spanning basal resources to top predators from 355 freshwater sites across three continents. Specifically, we used a hierarchical partitioning method to disentangle the propagation of temporal variability in abundance across spatial scales and trophic levels. We then used structural equation modeling to determine if the strength and direction of relationships between temporal variability, synchrony, biodiversity, and environmental and spatial settings depended on trophic level and spatial scale. We found that temporal variability in abundance decreased from producers to tertiary consumers but did so mainly at the local scale. Species population synchrony within sites increased with trophic level, whereas synchrony among communities decreased. At the local scale, temporal variability in precipitation and species diversity were associated with population variability (linear partial coefficient, ß = 0.23) and population synchrony (ß = -0.39) similarly across trophic levels, respectively. At the regional scale, community synchrony was not related to climatic or spatial predictors, but the strength of relationships between metacommunity variability and community synchrony decreased systematically from top predators (ß = 0.73) to secondary consumers (ß = 0.54), to primary consumers (ß = 0.30) to producers (ß = 0). Our results suggest that mobile predators may often stabilize metacommunities by buffering variability that originates at the base of food webs. This finding illustrates that the trophic structure of metacommunities, which integrates variation in organismal body size and its correlates, should be considered when investigating ecological stability in natural systems. More broadly, our work advances the notion that temporal stability is an emergent property of ecosystems that may be threatened in complex ways by biodiversity loss and habitat fragmentation.

Indicators of the effects of climate change on freshwater ecosystems.

Freshwater ecosystems, including lakes, streams, and wetlands, are responsive to climate change and other natural and anthropogenic stresses. These ecosystems are frequently hydrologically and ecologically connected with one another and their surrounding landscapes, thereby integrating changes throughout their watersheds. The responses of any given freshwater ecosystem to climate change depend on the magnitude of climate forcing, interactions with other anthropogenic and natural changes, and the characteristics of the ecosystem itself. Therefore, the magnitude and manner in which freshwater ecosystems respond to climate change is difficult to predict a priori. We present a conceptual model to elucidate how freshwater ecosystems are altered by climate change. We identify eleven indicators that describe the response of freshwater ecosystems to climate change, discuss their potential value and limitations, and describe supporting measurements. Indicators are organized in three inter-related categories: hydrologic, water quality, and ecosystem structure and function. The indicators are supported by data sets with a wide range of temporal and spatial coverage, and they inform important scientific and management needs. Together, these indicators improve the understanding and management of the effects of climate change on freshwater ecosystems.

The application of metacommunity theory to the management of riverine ecosystems.

River managers strive to use the best available science to sustain biodiversity and ecosystem function. To achieve this goal requires consideration of processes at different scales. Metacommunity theory describes how multiple species from different communities potentially interact with local-scale environmental drivers to influence population dynamics and community structure. However, this body of knowledge has only rarely been used to inform management practices for river ecosystems. In this paper, we present a conceptual model outlining how the metacommunity processes of local niche sorting and dispersal can influence the outcomes of management interventions and provide a series of specific recommendations for applying these ideas as well as research needs. In all cases, we identify situations where traditional approaches to riverine management could be enhanced by incorporating an understanding of metacommunity dynamics. A common theme is developing guidelines for assessing the metacommunity context of a site or region, evaluating how that context may affect the desired outcome, and incorporating that understanding into the planning process and methods used. To maximize the effectiveness of management activities, scientists and resource managers should update the toolbox of approaches to riverine management to reflect theoretical advances in metacommunity ecology.

Increased male reproductive success in Ts65Dn "Down syndrome" mice.

The Ts65Dn mouse is trisomic for orthologs of about half the genes on Hsa21. A number of phenotypes in these trisomic mice parallel those in humans with trisomy 21 (Down syndrome), including cognitive deficits due to hippocampal malfunction that are sufficiently similar to human that "therapies" developed in Ts65Dn mice are making their way to human clinical trials. However, the impact of the model is limited by availability. Ts65Dn cannot be completely inbred and males are generally considered to be sterile. Females have few, small litters and they exhibit poor care of offspring, frequently abandoning entire litters. Here we report identification and selective breeding of rare fertile males from two working colonies of Ts65Dn mice. Trisomic offspring can be propagated by natural matings or by in vitro fertilization (IVF) to produce large cohorts of closely related siblings. The use of a robust euploid strain as recipients of fertilized embryos in IVF or as the female in natural matings greatly improves husbandry. Extra zygotes cultured to the blastocyst stage were used to create trisomic and euploid embryonic stem (ES) cells from littermates. We developed parameters for cryopreserving sperm from Ts65Dn males and used it to produce trisomic offspring by IVF. Use of cryopreserved sperm provides additional flexibility in the choice of oocyte donors from different genetic backgrounds, facilitating rapid production of complex crosses. This approach greatly increases the power of this important trisomic model to interrogate modifying effects of trisomic or disomic genes that contribute to trisomic phenotypes.

Genome-enabled discovery of anthraquinone biosynthesis in Senna tora.

Senna tora is a widely used medicinal plant. Its health benefits have been attributed to the large quantity of anthraquinones, but how they are made in plants remains a mystery. To identify the genes responsible for plant anthraquinone biosynthesis, we reveal the genome sequence of S. tora at the chromosome level with 526 Mb (96%) assembled into 13 chromosomes. Comparison among related plant species shows that a chalcone synthase-like (CHS-L) gene family has lineage-specifically and rapidly expanded in S. tora. Combining genomics, transcriptomics, metabolomics, and biochemistry, we identify a CHS-L gene contributing to the biosynthesis of anthraquinones. The S. tora reference genome will accelerate the discovery of biologically active anthraquinone biosynthesis pathways in medicinal plants.

Genetic Loci Associated with Salt Tolerance in Advanced Breeding Populations of Tetraploid Alfalfa Using Genome-Wide Association Studies.

Many agricultural lands in the western United States consist of soil with high concentrations of salt, which is detrimental to alfalfa ( L.) growth and production, especially in the region where water resource is limited. Developing alfalfa varieties with salt tolerance is imperative for sustainable production under increasing soil salinity. In the present study, we used advanced alfalfa breeding populations and evaluated five traits related to salt tolerance including biomass dry weight (DW) and fresh weight (FW), plant height (PH), leaf relative water content (RWC), and stomatal conductance (SC) under control and salt stress. Stress susceptibility index (SSI) of each trait and single-nucleotide polymorphism (SNP) markers generated by genotyping-by-sequencing (GBS) were used for genome-wide association studies (GWAS) to identify loci associated with salt tolerance. A total of 53 significant SNPs associated with salt tolerance were identified and they were located at 49 loci through eight chromosomes. A Basic Local Alignment Search Tool (BLAST) search of the regions surrounding the SNPs revealed 21 putative candidate genes associated with salt tolerance. The genetic architecture for traits related to salt tolerance characterized in this report could help in understanding the genetic mechanism by which salt stress affects plant growth and production in alfalfa. The markers and candidate genes identified in the present study would be useful for marker-assisted selection (MAS) in breeding salt-tolerant alfalfa after validation of the markers.

Reintroduction of freshwater macroinvertebrates: challenges and opportunities.

Species reintroductions - the translocation of individuals to areas in which a species has been extirpated with the aim of re-establishing a self-sustaining population - have become a widespread practice in conservation biology. Reintroduction projects have tended to focus on terrestrial vertebrates and, to a lesser extent, fishes. Much less effort has been devoted to the reintroduction of invertebrates into restored freshwater habitats. Yet, reintroductions may improve restoration outcomes in regions where impoverished regional species pools limit the self-recolonisation of restored freshwaters. We review the available literature on macroinvertebrate reintroductions, focusing on identifying the intrinsic and extrinsic factors that determine their success or failure. Our study reveals that freshwater macroinvertebrate reintroductions remain rare, are often published in the grey literature and, of the attempts made, approximately one-third fail. We identify life-cycle complexity and remaining stressors as the two factors most likely to affect reintroduction success, illustrating the unique challenges of freshwater macroinvertebrate reintroductions. Consideration of these factors by managers during the planning process and proper documentation - even if a project fails - may increase the likelihood of successful outcomes in future reintroduction attempts of freshwater macroinvertebrates.

Predicting current and future background ion concentrations in German surface water under climate change.

Salinization of surface waters is a global environmental issue that can pose a regional risk to freshwater organisms, potentially leading to high environmental and economic costs. Global environmental change including climate and land use change can increase the transport of ions into surface waters. We fit both multiple linear regression (LR) and random forest (RF) models on a large spatial dataset to predict Ca2+ (266 sites), Mg2+ (266 sites), and [Formula: see text] (357 sites) ion concentrations as well as electrical conductivity (EC-a proxy for total dissolved solids with 410 sites) in German running water bodies. Predictions in both types of models were driven by the major factors controlling salinity including geologic and soil properties, climate, vegetation and topography. The predictive power of the two types of models was very similar, with RF explaining 71-76% of the spatial variation in ion concentrations and LR explaining 70-75% of the variance. Mean squared errors for predictions were all smaller than 0.06. The factors most strongly associated with stream ion concentrations varied among models but rock chemistry and climate were the most dominant. The RF model was subsequently used to forecast the changes in EC that were likely to occur for the period of 2070 to 2100 in response to just climate change-i.e. no additional effects of other anthropogenic activities. The future forecasting shows approximately 10% and 15% increases in mean EC for representative concentration pathways 2.6 and 8.5 (RCP2.6 and RCP8.5) scenarios, respectively.This article is part of the theme issue 'Salt in freshwaters: causes, ecological consequences and future prospects'.

Effects of sample standardization on mean species detectabilities and estimates of relative differences in species richness among assemblages.

Ecological surveys provide the basic information needed to estimate differences in species richness among assemblages. Comparable estimates of the differences in richness between assemblages require equal mean species detectabilities across assemblages. However, mean species detectabilities are often unknown, typically low, and potentially different from one assemblage to another. As a result, inferences regarding differences in species richness among assemblages can be biased. We evaluated how well three methods used to produce comparable estimates of species richness achieved equal mean species detectabilities across diverse assemblages: rarefaction, statistical estimators, and standardization of sampling effort on mean taxonomic similarity among replicate samples (MRS). We used simulated assemblages to mimic a wide range of species-occurrence distributions and species richness to compare the performance of these three methods. Inferences regarding differences in species richness based on rarefaction were highly biased when richness estimates were compared among assemblages with distinctly different species-occurrence distributions. Statistical estimators only marginally reduced this bias. Standardization on MRS yielded the most comparable estimates of differences in species richness. These findings have important implications for our understanding of species-richness patterns, inferences drawn from biological monitoring data, and planning for biodiversity conservation.

An eFP browser for visualizing strawberry fruit and flower transcriptomes.

Wild strawberry Fragaria vesca is emerging as an important model system for the cultivated strawberry due to its diploid genome and availability of extensive transcriptome data and a range of molecular genetic tools. Being able to better utilize these tools, especially the transcriptome data, will greatly facilitate research progress in strawberry and other Rosaceae fruit crops. The electronic fluorescent pictograph (eFP) software is a useful and popular tool to display transcriptome data visually, and is widely used in other model organisms including Arabidopsis and mouse. Here we applied eFP to display wild strawberry RNA sequencing (RNA-seq) data from 42 different tissues and stages, including various flower and fruit developmental stages. In addition, we generated eight additional RNA-seq data sets to represent tissues from ripening-stage receptacle fruit from yellow-colored and red-colored wild strawberry varieties. Differential gene expression analysis between these eight data sets provides additional information for understanding fruit-quality traits. Together, this work greatly facilitates the utility of the extensive transcriptome data for investigating strawberry flower and fruit development as well as fruit-quality traits.

Quantifying biological integrity by taxonomic completeness: its utility in regional and global assessments.

Water resources managers and conservation biologists need reliable, quantitative, and directly comparable methods for assessing the biological integrity of the world's aquatic ecosystems. Large-scale assessments are constrained by the lack of consistency in the indicators used to assess biological integrity and our current inability to translate between indicators. In theory, assessments based on estimates of taxonomic completeness, i.e., the proportion of expected taxa that were observed (observed/expected, O/E) are directly comparable to one another and should therefore allow regionally and globally consistent summaries of the biological integrity of freshwater ecosystems. However, we know little about the true comparability of O/E assessments derived from different data sets or how well O/E assessments perform relative to other indicators in use. I compared the performance (precision, bias, and sensitivity to stressors) of O/E assessments based on five different data sets with the performance of the indicators previously applied to these data (three multimetric indices, a biotic index, and a hybrid method used by the state of Maine). Analyses were based on data collected from U.S. stream ecosystems in North Carolina, the Mid-Atlantic Highlands, Maine, and Ohio. O/E assessments resulted in very similar estimates of mean regional conditions compared with most other indicators once these indicators' values were standardized relative to reference-site means. However, other indicators tended to be biased estimators of O/E, a consequence of differences in their response to natural environmental gradients and sensitivity to stressors. These results imply that, in some cases, it may be possible to compare assessments derived from different indicators by standardizing their values (a statistical approach to data harmonization). In situations where it is difficult to standardize or otherwise harmonize two or more indicators, O/E values can easily be derived from existing raw sample data. With some caveats, O/E should provide more directly comparable assessments of biological integrity across regions than is possible by harmonizing values of a mix of indicators.

Predictive models attribute effects on fish assemblages to toxicity and habitat alteration.

Biological assessments should both estimate the condition of a biological resource (magnitude of alteration) and provide environmental managers with a diagnosis of the potential causes of impairment. Although methods of quantifying condition are well developed, identifying and proportionately attributing impairment to probable causes remain problematic. Furthermore, analyses of both condition and cause have often been difficult to communicate. We developed an approach that (1) links fish, habitat, and chemistry data collected from hundreds of sites in Ohio (USA) streams, (2) assesses the biological condition at each site, (3) attributes impairment to multiple probable causes, and (4) provides the results of the analyses in simple-to-interpret pie charts. The data set was managed using a geographic information system. Biological condition was assessed using a RIVPACS (river invertebrate prediction and classification system)-like predictive model. The model provided probabilities of capture for 117 fish species based on the geographic location of sites and local habitat descriptors. Impaired biological condition was defined as the proportion of those native species predicted to occur at a site that were observed. The potential toxic effects of exposure to mixtures of contaminants were estimated using species sensitivity distributions and mixture toxicity principles. Generalized linear regression models described species abundance as a function of habitat characteristics. Statistically linking biological condition, habitat characteristics including mixture risks, and species abundance allowed us to evaluate the losses of species with environmental conditions. Results were mapped as simple effect and probable-cause pie charts (EPC pie diagrams), with pie sizes corresponding to magnitude of local impairment, and slice sizes to the relative probable contributions of different stressors. The types of models we used have been successfully applied in ecology and ecotoxicology, but they have not previously been used in concert to quantify impairment and its likely causes. Although data limitations constrained our ability to examine complex interactions between stressors and species, the direct relationships we detected likely represent conservative estimates of stressor contributions to local impairment. Future refinements of the general approach and specific methods described here should yield even more promising results.

Setting expectations for the ecological condition of streams: the concept of reference condition.

An important component of the biological assessment of stream condition is an evaluation of the direct or indirect effects of human activities or disturbances. The concept of a "reference condition" is increasingly used to describe the standard or benchmark against which current condition is compared. Many individual nations, and the European Union as a whole, have codified the concept of reference condition in legislation aimed at protecting and improving the ecological condition of streams. However, the phrase "reference condition" has many meanings in a variety of contexts. One of the primary purposes of this paper is to bring some consistency to the use of the term. We argue the need for a "reference condition" term that is reserved for referring to the "naturalness" of the biota (structure and function) and that naturalness implies the absence of significant human disturbance or alteration. To avoid the confusion that arises when alternative definitions of reference condition are used, we propose that the original concept of reference condition be preserved in this modified form of the term: "reference condition for biological integrity," or RC(BI). We further urge that these specific terms be used to refer to the concepts and methods used in individual bioassessments to characterize the expected condition to which current conditions are compared: "minimally disturbed condition" (MDC); "historical condition" (HC); "least disturbed condition" (LDC); and "best attainable condition" (BAC). We argue that each of these concepts can be narrowly defined, and each implies specific methods for estimating expectations. We also describe current methods by which these expectations are estimated including: the reference-site approach (condition at minimally or least-disturbed sites); best professional judgment; interpretation of historical condition; extrapolation of empirical models; and evaluation of ambient distributions. Because different assumptions about what constitutes reference condition will have important effects on the final classification of streams into condition classes, we urge that bioassessments be consistent in describing the definitions and methods used to set expectations.