VOL. 33 · NO. 4 | December 2014
 
IN THIS ISSUE

Articles (25)
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Articles
33(4), (14 July 2014) https://doi.org/10.1086/677900
KEYWORDS: benthic macroinvertebrates, large rivers, Nutrient addition, water quality, food resources, trophic ecology, NMDS, BACI
33(4), (14 July 2014) https://doi.org/10.1086/677883
KEYWORDS: Nutrient addition, phosphorus, nitrogen, TN:TP ratio, water quality, chlorophyll accrual, periphyton, river restoration
33(4), (11 December 2014) https://doi.org/10.1086/678516
KEYWORDS: benthic algae, resilience, resistance, disturbance, storm flow, flood, spate, tropics, filamentous algae
33(4), (7 July 2014) https://doi.org/10.1086/677767
KEYWORDS: whole-stream metabolism, primary production, respiration, two-stage ditch, floodplain, time series analysis
33(4), (19 September 2014) https://doi.org/10.1086/678673
KEYWORDS: pollution abatement, macroinvertebrates, taxonomic metrics, trait-based approach, null model, wastewater treatment plant
33(4), (3 September 2014) https://doi.org/10.1086/678048
KEYWORDS: abundance patterns, disturbance, Eutrophication, resilience, weed cutting, Aquatic plants, macrophyte, COIA analyses
33(4), (3 July 2014) https://doi.org/10.1086/677806
KEYWORDS: Glossosoma intermedium, consumer-driven nutrient recycling, stoichiometry, lotic ecosystem, caddisfly, Driftless Area
33(4), (19 September 2014) https://doi.org/10.1086/678693
KEYWORDS: consumer-driven nutrient recycling, ecological stoichiometry, streams, excretion, egestion, selective feeding
33(4), (29 September 2014) https://doi.org/10.1086/678700
KEYWORDS: tundra lakes, benthic invertebrate communities, sediment chemistry, permafrost thaw, climate change
33(4), (27 August 2014) https://doi.org/10.1086/678049
KEYWORDS: Rarity, habitat, Classification tree, climate change, Plecoptera, Beloneuria jamesae, Alabama
33(4), (11 July 2014) https://doi.org/10.1086/677815
KEYWORDS: life history, growth rate, von Bertalanffy, Hyriidae, Unionoida, Unionida, Australia
33(4), (12 September 2014) https://doi.org/10.1086/678492
KEYWORDS: biogeography, bioclimatic envelope models, climate change, freshwater, river
33(4), (14 July 2014) https://doi.org/10.1086/677898
KEYWORDS: benthic macroinvertebrates, predictor interactions, boosted regression trees, variable aggregation, multimetric index, streams, Ohio
33(4), (14 August 2014) https://doi.org/10.1086/678228
KEYWORDS: Lake Ontario, fish habitat classification, Nearshore, fish communities, land cover, Great Lakes
33(4), (11 August 2014) https://doi.org/10.1086/678128
KEYWORDS: eDNA, kicknet sampling, lotic systems, cytochrome oxidase I, water quality assessment, EPT, Amphipoda
33(4), (18 April 2014) https://doi.org/10.1086/678465
KEYWORDS: stressor—response, nutrients, Chlorophyll, classification
33(4), (5 September 2014) https://doi.org/10.1086/678483
KEYWORDS: poly-ether-sulfone membranes, Ammonium, Rhizon Soil Moisture Samplers, sampling porewater, interstitial concentration gradients
33(4), (6 October 2014) https://doi.org/10.1086/678771
KEYWORDS: bioassessment, reference condition approach, AUSRIVAS, predictive models, BEAST, simpacts
33(4), (2 October 2014) https://doi.org/10.1086/678946
KEYWORDS: reference condition approach, AUSRIVAS, simulated impairment, bioassessment, predictive modeling, macroinvertebrates
33(4), (3 October 2014) https://doi.org/10.1086/678948
KEYWORDS: reference condition approach, CABIN, BEAST, simulated disturbance, Type 1 error, Type 2 error, bioassessment, predictive modeling
33(4), (7 October 2014) https://doi.org/10.1086/678947
KEYWORDS: reference condition approach, BEAST, AUSRIVAS, CABIN, simulated impairment, bioassessment, predictive modeling, tiered DFA
33(4), (25 September 2014) https://doi.org/10.1086/678702
KEYWORDS: reference condition, benthic macroinvertebrates, Assessment by Nearest Neighbour, redundancy analysis, simulated impact
33(4), (15 September 2014) https://doi.org/10.1086/678701
KEYWORDS: predictive model, limiting factor, bioassessment, freshwater, macroinvertebrate
33(4), (3 October 2014) https://doi.org/10.1086/678949
KEYWORDS: reference condition model, macroinvertebrate, Bayesian hierarchical model, random effects model, principal components analysis, R, OpenBUGS
33(4), (15 September 2014) https://doi.org/10.1086/678768
KEYWORDS: support vector machines, artificial neural networks, K-Nearest Neighbor, reference condition approach, bioassessment, streams, invertebrates
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