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67 results for “macroinvertebrate communities”
Zooplankton and macroinvertebrate size spectra, biomass, and community composition; and harvest of bigmouth buffalo and common carp in six shallow lakes in Iowa, USA (2018-2020)
This data product contains biological data collected within six shallow lakes in Iowa, USA between 2018 - 2020, where four lakes were undergoing targeted removals of common carp (Cyprinus carpio) and bigmouth buffalo (Ictiobus cyprinellus). Parts of these data were a portion of Albright et al. 2022 (https://doi.org/10.6073/pasta/1d3797fd573208bae6f78963479445a0), however the data herein include additional survey data from the Ambient Lake Monitoring network instituted through Iowa State University and the Iowa Department of Natural Resources (https://www.iowadnr.gov/environmental-protection/water-quality/water-monitoring/ambient-lake-monitoring#ambient-lake-monitoring-sampling-plan). Data are packaged and formatted specifically for size spectra analysis and compositional analysis.
Lake Mendota, Wisconsin, USA, (Non-Dreissenid) Benthic Macroinvertebrate Abundance, Biomass, and Community Composition 2016-2018
We sampled the zoobenthos (macroinvertebrates of the benthos) of Lake Mendota from 2016-2018 to track impacts of invasive zebra mussels (Dreissena polymorpha) which were discovered in Lake Mendota in 2015 and grew exponentially to densities greater than 10,000 m-2 in shallow, rocky habitat by 2018. The data presented here exclude all zebra mussels, which are archived in a separate datset. We sampled along three transects inherited from Karatayev et al. (2013) at five different depths (1, 3, 5, 8, and 10 m) twice a summer (June and August) from 2016-2018. These data also contain some samples opportunistically taken from deeper depths along these transects that do not follow the routine sampling structure. A pared-down version of this routine sampling continued from 2019 onward but is not included here. This dataset complements zebra mussel and phytobenthos data collected according to the same routine sampling structure, for which data is also archived with EDI.
Summer water chemistry; sediment phosphorus fluxes and sorption capacity; sedimentation and sediment resuspension dynamics; water column thermal structure; and zooplankton, macroinvertebrate, and macrophyte communities in eight shallow lakes in northwest Iowa, USA (2018-2020)
The primary aim of this data product is to characterize change in water chemistry, sediment-water interactions, and biological communities in shallow, eutrophic lakes undergoing a fishery biomanipulation. We studied eight glacial lakes located in northwest Iowa, USA, from 2018 to 2020 during the summer season (May to September). A subset of these lakes (n = 4; Center, Five Island, North Twin, and Silver Lakes) were part of a fishery biomanipulation in which the Iowa Department of Natural Resources (IDNR) incentivized commercial harvest of common carp (Cyprinus carpio) and bigmouth buffalo (Ictiobus cyprinellus). Harvests occurred in Center and Five Island Lakes during 2018-2019 and in North Twin and Silver Lakes during 2019-2020. Between 73 and 373 kg fish biomass per ha were removed each year. The other study lakes (n = 4; Blue, South Twin, Storm, and Swan Lakes) remained unmanipulated during the study period. Over the course of the biomanipulation, we quantified a suite of physical, chemical, and biological parameters across the study lakes. High frequency aquatic sensors were used to measure water column thermal structure, dissolved oxygen concentrations, and algal pigments. Manual water chemistry sampling further quantified suspended solids, total phosphorus and nitrogen, soluble reactive phosphorus, nitrate, and water clarity. We measured flux rates of phosphorus between bottom sediments and the overlying water using ex situ sediment core incubations under both oxic and anoxic conditions. We further quantified sediment phosphorus sorption capacity using equilibrium phosphorus concentration assays. Tiered sediment traps were used to measure sedimentation rates as well as sediment resuspension in bottom waters. We also measured change in zooplankton, macroinvertebrate, and macrophyte community composition and abundance. These data will be used to better understand the mechanisms of internal phosphorus loading in shallow lakes and the ecosystem effects of fisherie
Stream Subsurface Flowpaths and Macroinvertebrate Communities at Harvard Forest 2004
Headwater streams and wetlands with a combination of surface and subsurface flows are common features of many upland-forested watersheds. Unlike headwater stream reaches with continuous surface flow, the hydrology and ecology of subsurface stream reaches are poorly studied and not factored into existing wetland legislation. We assessed subsurface habitats and associated biota in a 435-m reach of a first-order, intermittent stream draining a riparian zone dominated by eastern hemlock (Tsuga canadensis) in north central Massachusetts. Stream flow was found only in subsurface flowpaths beneath large boulders and surface root mats over approximately 70% of the total stream length at summer base flow. Temperature, specific conductivity, dissolved oxygen, and dissolved organic carbon concentrations of subsurface water were similar to surface water. Macroinvertebrates were found in subsurface habitats but at a lower abundance and richness per unit area compared to surface habitats. Collectors such as Chironomidae, Polycentropodidae, and Ephemerellidae were generally the most abundant families in both surface and subsurface habitats. Our findings indicate that in some glaciated watersheds, intermittent streams with no visual evidence of surface flow may contain subsurface flowpaths with water chemistry and biota comparable to coupled perennial surface flow reaches. The prevalence and importance of subsurface habitats in some headwater streams may warrant review or revision of existing state and local regulatory definitions of intermittent and headwater streams.
Summer water chemistry, high frequency sensors, zooplankton and benthic macroinvertebrate community composition, periphyton, fish, and macrophyte biomass, along with lake metabolism and greenhouse gas dynamics in six experimental ponds in central Iowa, USA (2020)
This data product contains physical, chemical, and biological data ranging from the minute to daily to weekly scale in six artificial ponds (400 square meter surface area, 2m depth) in central Iowa (USA) 2020. Ponds were paired into three sets of treatment and reference with treatment ponds receiving two nutrient pulses designed to increase ambient phosphorus concentrations ~ 3 - 5%. Nitrogen and phosphorus were added as NH4NO3 and H3PO4, respectively, at a 24:1 molar ratio. The first nutrient pulse occurred on Julian day of year (DOY) 176 corresponding to a 3% increase and the second nutrient pulse occurred on DOY 211 to a 5% increase. Each treatment-reference set had a different food web structure established ranging between low, intermediate, and high complexity based on trophic connectivity and food chain length. Added to this data package is a document titled "2020 Iowa State University Horticultural Farm Experimental Ponds Nutrient Addition Experiment". For experimental set up, context, and a summary table of the data tables archived herein with available variables please review this document. It is added to aid in successful interpretation and to increase ease-of-use. Please email Tyler Butts (tyler.james.butts@gmail.com) for any and all questions regarding context or use of this dataset!
A unified dataset of co-located sewage pollution, periphyton, and benthic macroinvertebrate community and food web structure from Lake Baikal (Siberia)
Sewage released from lakeside development can introduce nutrients and micropollutants that can restructure aquatic ecosystems. Lake Baikal, the world's most ancient, biodiverse, and voluminous lake, has been experiencing localized sewage pollution from lakeside settlements. Increasing filamentous algal abundance suggests benthic communities are responding to this localized pollution. We surveyed 40-km of Lake Baikal's southwestern shoreline 19-23 August 2015 for sewage indicators, including pharmaceuticals, personal care products, and microplastics with co-located periphyton, macroinvertebrate, stable isotope, and fatty acid sampling. Unique identifiers corresponding to sampling locations are retained throughout all data files to facilitate interoperability among the dataset's 150+ variables. The data are structured in a tidy format (a tabular arrangement familiar to limnologists) to encourage future reuse. For Lake Baikal studies, these data can support continued monitoring and research efforts. For global studies of lakes, these data can help characterize sewage prevalence and ecological consequences of anthropogenic disturbance across spatial scales.
Spatiotemporal Assessment and Composition of Benthic Macroinvertebrate Communities in the Bermejo River Basin in the Ecuadorian Amazonia
The information includes biotic and ecological index data of benthic macroinvertebrates collected in the Ecuadorian Amazon Region. The biotic indexes are taxonomic abundance, richness, evenness, diversity, and dominance. The ecological indexes refer to the ecological water quality as determined by pollution-tolerant macroinvertebrates. The datasets also include physicochemical parameters for water quality determination. The dataset has been completed,; however, it may be updated if new information is generated.
Community structure of aquatic vertebrates and macroinvertebrates in relation to hydrologic variables in the Shark River Slough, Everglades National Park, Florida USA: Ongoing since 2012
The purpose of this project is to characterize the community structure of aquatic fauna (macroinvertebrates and fishes) and floating mats (including periphyton) across the heterogenous landscape of the NE Shark River Slough in Everglades NP. The community structure (abundance, biomass, and species composition) of floating mat, emergent vascular plants, fishes, and macroinvertebrates, and the spatial distribution of the latter in relation to hydrology, are among the key performance measures targeted for monitoring. The aim of our study is to provide a baseline characterization of these parameters so that the impact of future management activities (e.g., Modified Water Deliveries and Comprehensive Everglades Restoration Plan) can be assessed. The study area is sampled during the late wet season (September through November) to capture data when all sites are innundated with water and aquatic animal standing stocks are typically at their maximum. We document landscape-scale patterns in the NE Shark River Slough from this comprehensive sampling.
Diversity and composition of macroinvertebrate communities in a rare inland salt marsh
<p>Inland salt marshes are rare habitats in the Great Lakes region of North America, formed on salt deposits from the Silurian period. These patchy habitats are abiotically stressful for the freshwater invertebrates that live there, and provide an opportunity to study the relationship between stress and diversity. We used morphological and COI metabarcoding data to assess changes in diversity and composition across both space (a transect from the salt seep to an adjacent freshwater area) and time (three sampling seasons). Richness was significantly lower at the seep site with both datatypes, while metabarcoding data additionally showed reduced richness at the freshwater transect end, consistent with a pattern where intermediate levels of stress show higher diversity. We found complementary, rather than redundant, patterns of community composition using the two datatypes: not all taxa were equally sequenced with the metabarcoding protocol. We identified taxa that are abundant at the salt seep of the marsh, including biting midges (<i>Culicoides</i>) and ostracods (<i>Heterocypris</i>). We conclude that (as found in other studies) molecular and morphological work should be used in tandem to identify the biodiversity in this rare habitat. Additionally, salinity may be a driver of community membership in this system, though further ecological research is needed to rule out alternate hypotheses.</p>
Climate warming shifts riverine macroinvertebrate communities to be more sensitive to chemical pollutants
<p>Freshwaters are highly threatened ecosystems that are vulnerable to chemical pollution and climate change. Freshwater taxa vary in their sensitivity to chemicals and changes in species composition can potentially affect the sensitivity of assemblages to chemical exposure. Here we explore the potential consequences of future climate change on the composition and sensitivity of freshwater macroinvertebrate assemblages to chemical stressors using the UK as a case study.</p> <p>Macroinvertebrate assemblages under end of century (2080-2100) and baseline (1980-2000) climate conditions were predicted for 608 UK sites for four climate scenarios corresponding to mean temperature changes of 1.28°C to 3.78°C. Freshwater macroinvertebrate toxicity data were collated for 19 chemicals and the hierarchical Species Sensitivity Distribution (hSSD) model was used to predict the sensitivity of untested taxa using relatedness within a Bayesian approach. All four future climate scenarios resulted in shifts in assemblage composition, with increases in the prevalence of molluscan, crustacean and annelid species, and towards increasing insect taxa of Odonata, Chironomidae, and Baetidae species. In contrast decreases in were projected for Plecoptera, Ephemeroptera (except for Baetidae) and Coleoptera species.</p> <p>Shifts in taxonomic composition were associated with changes in the percentage of species at risk from chemical exposure. For the 3.78°C climate scenario, 76% of all assemblages became more sensitive to chemicals and for 18 of the 19 chemicals, the percentage of species at risk increased. Climate warming-induced increases in sensitivity were greatest for assemblages exposed to metals and were dependent on baseline assemblage composition, which varied spatially.</p> <p>Climate warming is predicted to result in changes in the use, environmental exposure and toxicity of chemicals. Here we show that, even in the absence of these climate-chemical interactions, shifts in species composition due to climate warming will increase chemical risk and that the impact of chemical pollution on freshwater macroinvertebrate biodiversity may double or quadruple by the end of the 21st century.</p>
Fig. 1 in Spatio-Temporal Variations Of Macroinvertebrate Community In The Tisza River (Ne Hungary)
Fig. 1. Cross-section of the Tisza riverbed between Tiszamogyorós and Lónya at low water level. Abbreviations: 1 = main flow (right bank), 2 = mid-bed (at half distance between the right and the left
Fig. 3 in Spatio-Temporal Variations Of Macroinvertebrate Community In The Tisza River (Ne Hungary)
Fig. 3. Classification of samples from the cross-section of River Tisza between Lónya and Tiszamogyorós by dates. All taxa were taken into consideration with chironomids identified to family level. Groups are as follows: 1: March, 2: April, 3: June, 4: July, 5: September, 6: November
Fig. 2 in Spatio-Temporal Variations Of Macroinvertebrate Community In The Tisza River (Ne Hungary)
Fig. 2. Classification of sampling sites along the cross-section of River Tisza between Lónya and Tiszamogyorós. All taxa were taken into consideration with chironomids identified to species level. Groups are as follows: 1: left bank, 2: mid-bed, 3. main flow
Figure 6 in Macroinvertebrate communities along the Velika Morava River
Figure 6. Hierarchical classification of the sampling sites (a) and months (b) according to the relative abundance of macroinvertebrate taxa, using Noy-Meir clustering from generalized Euclidean distances. The sampling sites are coded as follows: 1 – VM1, 2 –VM2, 3 – VM3, 4 – VM4, and 5 – VM5. The months are coded as follows: 1 – July, 2 – August, 3 – October, and 4 – November.
Figure 8 in Macroinvertebrate communities along the Velika Morava River
Figure 8. CCA triplot (75 taxa, 14 samples, and 6 environmental factors) displaying 56% variance (first CCA axis, 31.4%; second CCA axis, 24.1%) in the WA (weighted averages) of taxa and species with respect to the environmental variables. Down-weighting of rare species was performed, and the WA algorithm was applied. The names of the taxa and species are abbreviated as follows: Hep fus – Kageronia fuscogrisea, Hep sp. – Heptagenia sp., Pot lut – Potamanthus luteus, Eph ign – Ephemerella ignita, Bae rho – Baetis rhodani, Hyd sp – Hydropsyche sp., etc. (full list of abbreviations is provided in the Appendix). The environmental factors are coded as follows: pH (pH), WTemp (water temperature), NH4 (ammonium ion), Organic N (organic nitrogen), TOC (total organic carbon), and Orthoph (orthophosphate). The samples are coded as in the Table (for example, 1- VM1_7, 2 – VM3_7, etc.).
Figure 4 in Macroinvertebrate communities along the Velika Morava River
Figure 4. The Shannon–Wiener index: spatial (a) and monthly (b) aspects (mean, maximal, and minimal values).
Figure 3 in Macroinvertebrate communities along the Velika Morava River
Figure 3. Relative abundance of the main taxonomic groups regarding sampling sites (a) and months (b).
Figure 7 in Temporal variability of the macroinvertebrate community associated with Eichhornia azurea (Swarts) Kunth (Pontederiaceae) in a lake marginal to a tropical river
Figure 7. NMDS diagram of macroinvertebrates in the sampled periods. (A) NMDS: structure; (B) NMDS: composition.
Figure 1 in Temporal variability of the macroinvertebrate community associated with Eichhornia azurea (Swarts) Kunth (Pontederiaceae) in a lake marginal to a tropical river
Figure 1. Study site and sampling stations (P1, P2, and P2) in Barbosa Lake (the circle shows the connection site between the lake and the river).
Figure 4 in Temporal variability of the macroinvertebrate community associated with Eichhornia azurea (Swarts) Kunth (Pontederiaceae) in a lake marginal to a tropical river
Figure 4. Means and standard deviations of root biomass of E. azurea (g.DW–1) in Barbosa Lake during the study period.
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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