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67 results for “macroinvertebrate communities”
Figure 2 in Temporal variability of the macroinvertebrate community associated with Eichhornia azurea (Swarts) Kunth (Pontederiaceae) in a lake marginal to a tropical river
Figure 2. Scheme of an adult E. azurea individual showing the sampled root mass in sequential direction from the apical to the basal parts of the plant.
Fig. 5 in Can nesting waterbirds influence the community structure of macroinvertebrates in southern Brazilian intermittent wetlands?
Fig. 5. NMDS ordination diagram of (A) the composition of aQuatic macroinvertebrate communities in control and rookery wetlands in southern Brazil; (B) NMDS ordination diagram of the composition of aQuatic macroinvertebrate communities and sampling seasons. Red arrows indicate the water physicochemical variables significantly correlated (P <0.05) with the ordination, as detected by the envfit procedure. Abbreviation of water physicochemical variables: T (water temperature), MO (organic matter in the sediment), NTU (water turbidity); ORP (oXidation-reduction potential). TaXa abbreviation: Physa/Stenophysa (P.S), Thiaridae (Thr), Sepedon (Spd), Celina (Cln), Hidrophilus (Hdr), Dampfius (Dmp), Notonecta (Ntn), Lissorhoptrus (Lss), Belostoma (Bls), Oxyagrion (OXy), Tramea (Trm), Erythemis (Ery), Ochrotrichia (Och), Isotoma sp. (I), Oribatidae (Orb), Leptophlebia (Lpt), Eristalis (Ers), Amphizoa (Amp), Naucoris (Ncr), Delphacidae (D), Rhyacophila (Rhy), Mesovelia (Msv), Gerris (Grr), Ilybius (Ily), Hydrobiomorpha (Hyd), Berosus (Brs), Laccobius (Lcc), Derallus (Drl), Buenoa (Bun), Ambrysus (Amb), Neoplea (Npl), Perithemis (Prt). (C) projection of the water nutrients significantly correlated (P <0.05) with the ordination of aQuatic macroinvertebrate communities in the first sampling season (spring 2016), as detected by the envfit procedure (Ortoph, orthophosphate).
Fig 2 in Benthic macroinvertebrate communities in sites with native forest presence and absence in north Patagonia
Fig 2. Results of UPGMA for autumn (left) and winter (right) data of macroinvertebrates studied at Araucaria Region, Chile.
Fig 1 in Benthic macroinvertebrate communities in sites with native forest presence and absence in north Patagonia
Fig 1. Map with studied site in Araucania region, Chile (Mix-1, Mixed P1; Mix-2, Mixed P2; Co-1, CoigÜe P1; Co-2, CoigÜe P2; Co-3, CoigÜe P3).
Fig. 3 in Can nesting waterbirds influence the community structure of macroinvertebrates in southern Brazilian intermittent wetlands?
Fig. 3. Abundance of aQuatic macroinvertebrates in control and rookery wetlands in each sampling season, southern Brazil. Whiskers indicate upper and lower 95% confidence intervals (± standard error).
Fig. 1 in Can nesting waterbirds influence the community structure of macroinvertebrates in southern Brazilian intermittent wetlands?
Fig. 1. Map of the study area with the location of the studied wetlands in southern Brazil. Filled circles indicate the control wetlands (wetlands without the presence of nesting bird colonies). Filled stars indicate the rookery wetlands.
Fig. 4 in Can nesting waterbirds influence the community structure of macroinvertebrates in southern Brazilian intermittent wetlands?
Fig. 4. Relationships between the richness of aQuatic macroinvertebrate communities and water turbidity (A), total solids dissolved (B). Relationships between the abundance of aQuatic macroinvertebrates and nitrate (C) and organic phosphorus (D)(TDS, total dissolved solids).
Diversity and composition of macroinvertebrate communities in a rare inland salt marsh
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Climate warming shifts riverine macroinvertebrate communities to be more sensitive to chemical pollutants
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Macroinvertebrates communities from 14 lakes of the Canadian Rockies in summer and fall 2018.
Benthic macroinvertebrates communities from 8 samples stations per lake in 14 lakes (9 with fish, 4 fishless and one treated with rotenone) of the Canadian Rockies distributed along an elevation gradient. Sampling was done in 2018 for all lakes except Hidden Lake (treated with rotenone), which was sampled in 2018 and 2019. All lakes were sampled twice per year (mid-July and early September). The objective of this study was to assess the effect of rotenone application in Hidden lake during summer 2018 on macroinvertebrates communities.
Slow drawdown, fast recovery: Stream macroinvertebrate communities improve quickly after large dam decommissioning
<p>Dam removal is increasingly considered as a river restoration tool for impoundments that harm the environment or have exceeded their lifespan. However, few studies report the ecological consequences of large dam removal. We performed a multiple Before-After/Control-Impact (mBACI) study to investigate the consequences of the decommissioning of a large dam (42 m high) on instream habitat and invertebrate communities in a temperate, forested catchment of northern Spain. Before decommissioning, a lack of fine sediments and high concentrations of manganese and iron occurred below the dam but decreased downstream. Invertebrate taxa richness and diversity were reduced, and pollution-sensitive taxa were missing just below the dam. The drawdown of the reservoir, the first step towards its decommissioning, mobilized stored sediments causing frequent turbidity peaks downstream, which nevertheless, caused no detrimental effects on macroinvertebrate communities. One year after the drawdown, the communities downstream from the dam, as well as those in the newly formed stream in the area formerly impounded by the reservoir, became very similar to those in control reaches, showing a successful restoration project.</p> <p><em>Synthesis and applications: </em>Dam decommissioning helps restore instream habitats and facilitates the recovery of invertebrate communities in a very short time frame if there are nearby sources of potential colonizers. Slow drawdown reduces the transport of the sediments accumulated in the reservoir and their potential downstream impacts, even more if before drawdown the reservoir is kept full for years to promote the retention of sediments in marginal areas that will later be readily colonized by trees.</p>
Figure 2 in Macroinvertebrate communities along the Velika Morava River
Figure 2. Overall taxa richness at the sampling sites.
Figure 6 in Temporal variability of the macroinvertebrate community associated with Eichhornia azurea (Swarts) Kunth (Pontederiaceae) in a lake marginal to a tropical river
Figure 6. Box-plots of macroinvertebrates community richness (expressed in log values).
Soil Properties and Soil Macroinvertebrate Communities in Amazonian Anthropogenic Soils
<h3><strong>About</strong></h3> <p>This dataset is an update of the dataset 'A “Dirty” Footprint: Soil macrofauna biodiversity and fertility in Amazonian Dark Earths and adjacent soils' previously published in Dryad repository (https://doi.org/10.5061/dryad.3tx95x6cc). This dataset now include information on soil humification index, soil carbon related to different soil minerals and soil fatty acids characterization.</p> <h3><strong>Description</strong></h3> <p>Soils were sampled in Brazilian Amazonia in the municipalities of Iranduba-AM, Belterra-PA and Porto Velho-RO. In each region, paired sites with anthropogenic dark earths (ADE) and nearby reference (REF) non-anthropogenic soils were sampled under three different land-use systems: native secondary vegetation (<em>dense ombrophilous forest</em>) classified as old secondary forest when >20 years old, or young regeneration forest when <20 years old, and agricultural systems (maize in Iranduba, soybean in Belterra, and introduced pasture in Porto Velho).</p> <p>At each site, soil and litter macrofauna were collected using the Tropical Soil Biology and Fertility (TSBF) method (Anderson and Ingram, 1993) at five sampling points (soil monoliths 25x25 cm up to 30 cm depth) within a 1 ha plot, four at the corners and one on the center of a 60 x 60 m square, resulting in an “X” shaped sampling design. Each soil monolith was divided into surface litter and three 10 cm-thick soil layers (0-10, 10-20, 20-30 cm). Macroinvertebrates (animals with >2 mm body width) were manually hand-sorted and fixed in 92% ethanol. Earthworms, ants and termites were identified to species or genus level and other macroinvertebrates were sorted into morphospecies with higher taxonomic level assignations. Density (number of individuals) and biomass of the soil macrofauna surveyed using the TSBF method were extrapolated per square meter.</p> <p>For the earthworms, ants and termites (ecosystem engineers) additional samples were performed, especially in forest sites to better estimate species richness of these taxa. Earthworms were collected at four additional cardinal points of the grid at all sites, and hand-sorted from holes of similar dimensions as the TSBF monoliths. Termites were sampled in the forest sites only forests (except one of the REF young forests at Porto Velho), in five 20 m<sup>2</sup> (2 x 10 m) plots (close to the five main soil monoliths) by manually digging the soil and looking for termitaria in the soil, as well as in the litter and on trees using a modification of the transect method (Jones and Eggleton, 2000). Ants were sampled in 10 pitfall traps (300 ml plastic cups) set up as two 5-trap transects on the sides of each 1 ha plot, as well as in two traps to the side of each TSBF monolith (distant ~5 m) only in the forest systems of Iranduba and Belterra (not Porto Velho). Each cup was filled to a third of its volume with water, salt and detergent solution. Termites and ants were preserved in 80% ethanol and earthworms in 96% ethanol and the alcohol changed after cleaning the samples within 24 h. All the animals (earthworms, ants, termites) were identified to species level or morphospecies level (with genus assignations) by co-authors SWJ/MLCB (earthworms), AA (termites) and ACF/RMF (ants).</p> <p>Soil samples for chemical and particle size analysis were collected from each TSBF monolith after the soil fauna hand-sorting. Around 2 to 3 kg soil from each depth (0-10, 10-20, 20-30 cm) and the following soil properties were evaluated according to standard methodologies (Teixeira et al., 2017): pH (CaCl<sub>2</sub>); Ca<sup>2+</sup>, Mg<sup>2+</sup>, Al<sup>3+</sup> (KCl 1 mol L<sup>-1</sup>); K<sup>+</sup>, P, Fe, Zn, Mn, Cu and Ni (Mehlich-1); Pseudo-total contents of trace elements (Ba, Cd, Co, Cu, Ni, Pb, Se and ZN) were determined by acid digestion (HNO<sub>3</sub> + HCl); Fe (sulfuric extract); total nitrogen (TN) and carbon (TC) using an element analyzer (CNHS). Base saturation and cation exchange capacity (CEC) were calculated using standard formulae (Teixeira et al., 2017) and particle size fractions (% sand, silt, clay) were obtained following standard methodologies (Teixeira et al., 2017). Soil magnetic susceptibility (MS) and apparent electrical conductivity (EC<sub>a</sub>) (Siemens per meter – S m<sup>-1</sup>) were obtained using a KT-10 S/C magnetic susceptibility/conductivity meter (Terraplus) with 10 Hz of operating frequency.</p> <p>Soil macromorphology samples were taken close to the TSBF monolith (~2 m) using a 10 x 10 x 10 cm metal frame. The collected material was separated into different fractions including: living invertebrates, litter, roots, pebbles, pottery sherds, charcoal (biochar), non-aggregated/loose soil (NA), physical aggregates (PA), root-associated aggregates (RA), and fauna-produced aggregates (FA) using the methodology proposed by Velasquez et al. (2007).</p> <p>Laser-induced fluorescence spectroscopy analysis (LIFS) was performed on soil macroaggregate fraction (FA, PA, RA and NAS) from both YF and the pasture from Porto Velho to obtain the humification index of soil organic matter according to Milori et al. (2006).</p> <p>Were analysed fatty acids in soil macroaggregates (PA, RA and FA) from one site in Teotônio. The process involved extracting 2 g of each sample with a chloroform: methanol solution and a surrogate compound, 5α-cholestane. The extract was centrifuged, combined, and the solvent removed using a rotary evaporator and nitrogen. Extracts were stored at -20°C until analyzed by GC-MS. Samples were silylated, with excess silylating agent removed, followed by the addition of hexane and vortexing for GC-Q-MS analysis. The equipment used included an Agilent Technologies GC (7890B) and MS (5977A), with an autosampler and HP-5ms column. MassHunter and MSD ChemStation software facilitated analysis and quantification, respectively. Deconvolution and retention index calculations were performed using AMDIS software. Compounds were identified using NIST MS software, requiring at least three specific mass fragments per compound and a retention index deviation of less than 1.5%. Analyte intensities were normalized by dried soil sample weights and the internal standard.</p> <p>Soil samples from TSBF monoliths were fractionated by dry sieving into small (<500 µm) and large (>500 µm) aggregate size classes. These were further fractionated into sand-particulate organic matter (sand-MOP) (>53 µm), silt-organic matter associated with minerals (MOM) (53-2 µm), and clay-MOM (<2 µm). Total organic carbon and nitrogen in these fractions were measured using a Vario EL III elemental analyzer. Clay-MOM samples underwent a four-step sequential extraction with hydroxylamine, sodium dithionite, sodium pyrophosphate, and sodium hydroxide to determine carbon, silicon, iron, and aluminum contents associated with different soil components. For further details see Ramalho (2020).</p> <p>Soil bulk density and total porosity were determined using undisturbed core samples (0.05 m diameter, 0.05 m depth) collected at ~2 m from the TSBF samples following the method proposed by Teixeira et al. (2017).</p> <p>All data is provided in excel format, and includes 14 tabs in the data file: Metadata and legend, Site description, Soil chem, BD+POR, Macromorph, Seq_ext, Biomark, HLIF, Macro_den, Macro_bio, Morpho_TSBF, Add_worm, Add_ants, Add_termites. The Metadata and legend tab provides a detailed explanation for each variable included in each table, including the units used for each. The Site description tab include a brief description of the sites sampled. Soil chem, BD+POR, Macromorph, Seq_ext, Biomark and HLIF tables contain the data on soil chemical, physical, macromorphological, organic matter related to soil minerals, fatty acids and humidification index variables, respectively. The Macro_den and Macro_bio contain the data about density and biomass on all the soil invertebrate taxa found, respectively. The Morphosp_TSBF, Add_worm, Add_ants and Add_termites tables contain the invertebrate species/morphospecies occurrence in TBSF and extra samples for earthworms, ants and termites, respectively.</p> <h3><strong>References used in methods section</strong></h3> <p>Anderson, J.M., Ingram, J.S.I., 1993. Tropical Soil Biology and Fertility: A handbook of methods, 2 edition. ed. Oxford University Press, Oxford. https://doi.org/10.2307/2261129</p> <p>Jones, D.T., Eggleton, P., 2000. Sampling termite assemblages in tropical forests: testing a rapid biodiversity assessment protocol. Journal of Animal Ecology 37, 191–203. https://doi.org/10.1046/j.1365-2664.2000.00464.x</p> <p>Milori, D.M.B.P., Galeti, H.V.A., Martin-Neto, L., Dieckow, J., González-Pérez, M., Bayer, C., Salton, J., 2006. Organic Matter Study of Whole Soil Samples Using Laser-Induced Fluorescence Spectroscopy. Soil Science Society of America Journal. 70, 57. https://doi.org/10.2136/sssaj2004.0270</p> <p>Teixeira, P.C., Donagemma, G.K., Fontana, A., Teixeira, W.G., 2017. Manual de métodos de análise de solo, 3<sup>o</sup>. ed. Embrapa, Brasília.</p> <p>Ramalho. B., 2020. Caracterização das interações organo-mineral em Terra Preta de Índio. Thesis. Universidade Federal do Paraná. 113p.</p> <p>Velasquez, E., Pelosi, C., Brunet, D., Grimaldi, M., Martins, M., Rendeiro, A.C., Barrios, E., Lavelle, P., 2007. This ped is my ped: Visual separation and near infrared spectra allow determination of the origins of soil macroaggregates. Pedobiologia 51, 75–87. https://doi.org/10.1016/j.pedobi.2007.01.002</p> <h3><strong>Funding</strong></h3> <p>The study was supported by the Newton Fund and Fundação Araucária (grant Nos. 45166.460.32093.02022015, NE/N000323/1), Natural Environment Research Council (NERC) UK (grant No. NE/M017656/1), a European Union Horizon 2020 Marie-Curie fellowship to LC (MSCA-IF-2014-GF-660378) and another to DWGS (No. 796877), by CAPES scholarships to WCD, ACC, TF, RFS, AF, LM, HSN, TS, AM and RSM (PVE A115/2013), Araucaria Foundation scholarships to LB, AS, ACC and ES, Post-doctoral fellowships to DWGS (NERC grant NE/M017656/1) and ES (CNPq No. 150748/2014-0), PEER (Partnerships for Enhanced Engagement in Research Science Program) NAS/USAID award number AID-OAA-A-11-0001 - project 3-188 to RMF, and by CNPq grants, scholarships and fellowships to ACF, GGB, RF, SWJ, EGN and PL (Nos. <a>140260/2016-1</a>, 307486/2013-3, 302462/2016-3, <a>401824/2013-6</a>, 307179/2013-3, 400533/2014-6). We thank INPA, UFOPA, Embrapa Rondônia, Embrapa Amazônia Ocidental and Embrapa Amazônia Oriental and their staff for logistical support, and the farmers for access to and permission to sample on their properties. Sampling permit for Tapajós National Forest was granted by ICMBio.</p>
Unravelling the factors affecting taxonomic, phylogenetic and functional beta diversity of stream macroinvertebrate communities in the World's Third Pole
<p><span><strong>Aim</strong>: </span><span>Disentangling how</span><span> stochastic and deterministic processes contribute to variation in beta diversity is a common goal for ecologists and biogeographers. However, such studies are scarce in alpine streams, especially when different diversity facets are considered. Here, we combined different approaches to examine the drivers of taxonomic, phylogenetic and functional beta diversities and discussed how our results can inform community assembly and biodiversity conservation in Tibetan streams.</span></p> <p><span><strong>Location</strong>: </span><span>Tibet </span><span>Plateau</span></p> <p><span><strong>Taxon</strong>: </span><span>Macroinvertebrates</span></p> <p><span><strong>Methods</strong>: </span><span>We first partitioned multiple facets of beta diversity (B<sub>total</sub>) into species replacement (B<sub>repl</sub>) and richness difference (B<sub>rich</sub>) as well as local (LCBD) or species (SCBD) contributions. Then, we applied ordination methods to examine the relative importance of local, climatic and spatial factors on </span><span>B<sub>total</sub></span><span>, </span><span>B<sub>repl</sub></span><span> and </span><span>B<sub>rich</sub></span><span>, respectively. We explored community assembly rules using null models based on trait and phylogeny structure. </span></p> <p><span><strong>Results</strong>: </span><span>B<sub>total</sub></span><span> displayed high values and was primarily driven by B<sub>repl</sub>. Local, climatic and spatial factors were poor predictors of the different facets of beta diversity. Null models showed that the diversity metrics did not differ from those of null expectations, suggesting that most individual streams might be occupied by species that were merely random draws from the functional or phylogenetic pools available in this region. Partitioning beta diversity into LCBD and SCBD implied that the upper canyon streams were more unique than those at lower elevations and can be valuable for biodiversity conservation.</span></p> <p><span><strong>Main conclusions</strong>: </span><span>Analyzing multiple facets of beta diversity provide important insights into community assembly that cannot be acquired by focusing on taxonomic diversity only. Using a multi-faceted approach involving species, phylogenetic and trait data, our study not only sheds light on the assembly mechanisms of macroinvertebrate communities in alpine streams but also bring inspiration for biodiversity conservation in the 'World's Third Pole' that is highly sensitive to global change. </span></p>
Seasonal turnover in community composition of stream-associated macroinvertebrates inferred from freshwater environmental DNA metabarcoding
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Macroinvertebrate diversity, community structure, and dispersal in a regulated river are affected by tributary identity and confluence conditions
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Unravelling the factors affecting taxonomic, phylogenetic and functional beta diversity of stream macroinvertebrate communities in the World's Third Pole
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Slow drawdown, fast recovery: Stream macroinvertebrate communities improve quickly after large dam decommissioning
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Data from: Macroinvertebrate community responses to disturbance in a fragmented river with contrasting legacies of alteration
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