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153 results for “Non–native species”
Distribution of functionally distinct native and non-indigenous species within marine urban habitats
<p>This data file (.xls) is composed of 5 sheets:</p> <ol> <li>The “Taxon labels”: Taxon code, full name, authority and status/type (Abiotic, Unassigned, Native, Cryptogenic, Non-Indigenous Species)</li> <li>The “Trait labels”: Trait modality and labels and correspondences.</li> <li>The “Taxon-by-Trait matrix”: Fuzzy coded scores for each trait modality and taxon</li> <li>The “Taxon-by-sample matrix”: Abundance data of retained taxa in samples</li> <li>The “Sample labels and description”: Site and experimental factors (Habitat, Age, Experimental Unit, Replicate, nested within site) corresponding to each sample.</li> </ol> <p>Sheets 4 and 5 are extracted from a published dataset, which cannot be shared at this stage of revision without revealing the name of several of the manuscript authors. This is done in respect with the journal guidelines about data storage.</p>
Distribution of functionally distinct native and non-indigenous species within marine urban habitats
<p>This data file (.xls) is composed of 5 sheets:</p> <ol> <li>The “Taxon labels”: Taxon code, full name, authority and status/type (Abiotic, Unassigned, Native, Cryptogenic, Non-Indigenous Species)</li> <li>The “Trait labels”: Trait modality and labels and correspondences.</li> <li>The “Taxon-by-Trait matrix”: Fuzzy coded scores for each trait modality and taxon</li> <li>The “Taxon-by-sample matrix”: Abundance data of retained taxa in samples</li> <li>The “Sample labels and description”: Site and experimental factors (Habitat, Age, Experimental Unit, Replicate, nested within site) corresponding to each sample.</li> </ol> <p>Sheets 4 and 5 are extracted from a published dataset, which cannot be shared at this stage of revision without revealing the name of several of the manuscript authors. This is done in respect with the journal guidelines about data storage.</p>
Data from: Grazing by non-native ungulates negatively impacts vegetation important to a native species of concern
<p>Non-native grazers compete with native species across the globe. In the northwestern Great Basin of the western United States competition among livestock, feral horses, and Greater Sage-grouse has been the subject of numerous legal actions and management policies, yet spatially explicit temporal data documenting the details of this competition are lacking. We present a novel approach to studying the composition of the herbaceous understory across three study areas within the Great Basin with different historic and contemporary grazing regimes. We surveyed the landscape using distance sampling for livestock and horse feces as an index of use. In addition, we surveyed the herbaceous understory of random sites as well as sites chosen by female Greater Sage-grouse to nest and brood their chicks. We used a novel Bayesian hierarchical modeling framework to link vegetation metrics with the spatial-temporal distribution of horses and livestock while accounting for observation error. When livestock and feral horses were not present, we found that Greater Sage-grouse chose sites with higher percentages of perennial grasses and forbs to build their nests and brood their chicks compared to what was available to them. As livestock increased, we found evidence for decreases in the percentage of perennial grasses, forbs, cheatgrass (<em>Bromus tectorum</em>), and increases in the amount of bare ground. These effects were consistent at available sites and brood sites, however, we found less evidence for an impact of livestock at nest sites. As feral horses increased, we observed similar results at available sites, but at sites chosen by females to nest and brood their chicks, we observed increases in the amount of invasive cheatgrass as feral horses increased, which could reflect attempts by Greater Sage-grouse to compensate for reductions in protective cover. We present a noninvasive approach to assess space use that can be applied to other species. More importantly, we document that grazing by non-native ungulates impacts components of the plant community important to Greater Sage-grouse reproduction. We provide spatial-temporal maps of livestock and feral horse use to aid managers attempting to balance the needs of livestock producers, feral horses, Greater Sage-grouse, and ecosystem function.</p>
Figure 1 in Developing biosecurity plans for non-native species in marine dependent areas: the role of legislation, risk management and stakeholder engagement
Figure 1. Five-stage approach for risk assessment management of NNS in Shetland, adapted from the ecosystem-based risk management framework (Cormier et al. 2013).
Figure 1 in The value of regular monitoring and diverse sampling techniques to assess aquatic non-native species: a case study from Orkney
Figure 1. Locations of the monitoring sites. A: North of Orkney Mainland and northern isles, B: Scapa Flow and southern isles. For corresponding site names refer to Supplementary material Table S1.
Figure 3 in The value of regular monitoring and diverse sampling techniques to assess aquatic non-native species: a case study from Orkney
Figure 3. The total number of sites for which each non-native or cryptogenic species has been recorded for each sampling method for 2016 and 2017. NB: Only species recorded in these two years are reported in this figure. Abbreviations: Cm: Caprella mutica, As: Ascidiella scabra, Bh: Bonnemaisonia hamifera, Sj: Schizoporella japonica, Ce: Corella eumyota, Aa: Ascidiella aspersa, Cp: Colpomenia peregrina, Cf: Codium fragile ssp. fragile, Ti: Tricellaria inopinata, Ah: Asterocarpa humilis, Bs: Botryllus schlosseri, Bl: Botrylloides leachii, Mh: Melanothamnus harveyi, Bf: Bugulina fulva, Dj: Dasysiphonia japonica, Jm: Jassa marmorata, Mi: Monocorophium insidiosum, Ma: Monocorophium acherusicum, Cs: Ctenodrilus serratus, Tj: Telmatogeton japonicus, Pa: Potamopyrgus antipodarum, Cb: Crassicorophium bonellii, Dl: Diplosoma listerianum.
Figure 2 in The value of regular monitoring and diverse sampling techniques to assess aquatic non-native species: a case study from Orkney
Figure 2. The total number of non-native and cryptogenic species recorded at each monitoring location (2012–2017).
Fig. 3 in A newly established non-native praying mantis species, Liturgusa maya (Mantodea: Liturgusidae) in Florida, USA, and a key to Florida mantis genera
Fig. 3. Praying mantis genera in Florida: (A) Mantoida maya female (photograph by Cheryl Harleston (www.inaturalist.org, CC BY-NC-SA); (B) Brunneria borealis female (photograph by Gary L. Dearman); (C) Oligonicella scudderi female (photograph by Jennifer Thompson); (D) Thesprotia graminis female (photograph by Sturgis McKeever, Georgia Southern University (www.Bugwood.org, CC-BY-NC); (E) Gonatista grisea female (photograph by Scott D. Nelson); (F) Liturgusa maya female (photograph by Brian Fridie Jr.); (G) Stagmomantis carolina female (photograph by Wendy Garfinkel-Gold); (H) Stagmomantis floridensis female (photograph by Andrew Nisip).
Fig. 2 in A newly established non-native praying mantis species, Liturgusa maya (Mantodea: Liturgusidae) in Florida, USA, and a key to Florida mantis genera
Fig. 2. Liturgusa maya specimens were collected in and near Long Key Natural Area and Nature Center (red star on large map) in Davie, Florida. The inset map indicates the proximity of the 2 collection sites (adjacent red stars) to National Parks and Preserves. (Maps modified from www.freemapsonline.com and www.nps.gov).
Fig. 1 in A newly established non-native praying mantis species, Liturgusa maya (Mantodea: Liturgusidae) in Florida, USA, and a key to Florida mantis genera
Fig. 1. Habitus images of Liturgusa maya collected in Long Key Natural Area and Nature Center, Davie, Florida. (A) Adult female (scale = 1 cm); (B) ootheca produced by captive female (scale = 1 mm) (photographs by Rick Wherley).
FIGURE 6 in Adjustments in population and reproductive dynamics of native and non-native congeneric species during 26 years after invasion
FIGURE 6 | Stages of gonadal maturation at each age class for individuals of Serrasalmus marginatus (non-native; left) and S. maculatus (native; right) piranha species in the upper Paraná River floodplain, at each sampled time-period. The classification was based on Brown-Peterson et al. (2011). A. and B. 1986–1988: first time-period; C. and D. 2000–2002: second time-period; E. and F. 2010–2012: third timeperiod. CPUE values are fewer when compared to total CPUE values since individuals without standard length, sex and maturation stage were not considered in the estimation of age.
FIGURE 3 in Adjustments in population and reproductive dynamics of native and non-native congeneric species during 26 years after invasion
FIGURE 3 | Age frequencies of both non-native (left) and native species (right) for each sex and each sampled time-period in the upper Paraná River floodplain. A. and B. 1986–1988: first time-period; C. and D. 2000–2002: second time-period; E. and F. 2010–2012: third time-period. CPUE values are fewer when compared to total CPUE values since individuals without standard length and sex were not considered in the estimation of age.
FIGURE 1 in Adjustments in population and reproductive dynamics of native and non-native congeneric species during 26 years after invasion
FIGURE 1 | Map of the upper Paraná River floodplain showing its main tributaries. Sampling sites are marked: rivers and channels (circles), connected (squares), and isolated (triangles) floodplain lakes. Color of symbols are for Paraná (black), Ivinheima (white), and Baía (grey) rivers.
Linked collectors and determiners for: DNA analysis of a non-native lineage of Sinanodonta woodiana species complex (Bivalvia: Unionidae) from Middle Asia supports the Chinese origin of the European invaders.
Natural history specimen data linked to collectors and determiners held within, "DNA analysis of a non-native lineage of Sinanodonta woodiana species complex (Bivalvia: Unionidae) from Middle Asia supports the Chinese origin of the European invaders". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/86a42a54-2f47-458e-a443-13866e9e3191">https://bionomia.net/dataset/86a42a54-2f47-458e-a443-13866e9e3191</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/86a42a54-2f47-458e-a443-13866e9e3191">https://gbif.org/dataset/86a42a54-2f47-458e-a443-13866e9e3191</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Swiss Occurrence Records of Non-Native Species of Various Faunal Groups.
Natural history specimen data linked to collectors and determiners held within, "Swiss Occurrence Records of Non-Native Species of Various Faunal Groups". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/6167d892-cb27-47cf-97d2-7257572b45b9">https://bionomia.net/dataset/6167d892-cb27-47cf-97d2-7257572b45b9</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/6167d892-cb27-47cf-97d2-7257572b45b9">https://gbif.org/dataset/6167d892-cb27-47cf-97d2-7257572b45b9</a>. Formatted as a Frictionless Data package.
Fig. 6 in Spatio-temporal segregation and size distribution of fish assemblages as related to non-native species occurrence in the middle rio Doce Valley, MG, Brazil
Fig. 6. Least-square means and 95% confidence intervals from ANCOVA of the first three environmental factors from PCA. Different markers represent significantly different means as detected by planned contrasts with 5% significance level, first comparing lakes with any non-native species with those without them, and then comparing the two categories of lakes with non-natives (non-piscivores vs. piscivores).
Fig. 4 in Spatio-temporal segregation and size distribution of fish assemblages as related to non-native species occurrence in the middle rio Doce Valley, MG, Brazil
Fig. 4. Scatterplot of species body size (mean standard length) vs. a relative index of native affinity to lakes containing piscivorous invaders (the proportion of biomass of a given native species in lakes with piscivorous invaders). The estimated regression line is also presented (Y = 0.044*X - 0.279; R2 = 0.443; p = 0.007). Species codes: ast = Astyanax sp.; aus = Australoheros facetus; cyp = Cyphocharax gilbert; cre = Crenicichla lacustris; geo = Geophagus brasiliensis; gym = Gymnotus gr. carapo; hop = Hoplias malabaricus; lep = Leporinus steindachneri; lor = Loricariidae (unidentified species); lyc = Lycengraulis sp.; moe = Moenkhausia doceana; oli = Oligosarcus solitarius; pac = Pachyurus adspersus; pro = Prochilodus vimboides; tra = Trachelyopterus striatulus.
Fig. 5 in Spatio-temporal segregation and size distribution of fish assemblages as related to non-native species occurrence in the middle rio Doce Valley, MG, Brazil
Fig. 5. Least-square means and 95% confidence intervals from ANCOVA of mean individual size and temporal turnover as related to the three lake categories. Different markers represent significantly different means as detected by planned contrasts with 5% significance level, first comparing lakes with any non-native species with those without them, and then comparing the two categories of lakes with non-natives (non-piscivores vs. piscivores).
Fig. 2 in Spatio-temporal segregation and size distribution of fish assemblages as related to non-native species occurrence in the middle rio Doce Valley, MG, Brazil
Fig. 2. Alpha (mean) and beta richness. a) Comparison among the temporal and spatial components of richness. b) Species richness for each lake. The alpha (mean) and beta richness were taken along the temporal component. Lake codes: No = Nova; Ca = Capim; Fe = Ferrugem; Cr = Crentes; Po = Poço Redondo; Ro = Romoalda; Ti = Timburé; Ag = Águas Claras; Pa = Palmeirinha; Ar = Ariranha. "Natives" represents lakes without non-native species; "Non-piscivores" represents lakes with non-piscivorous non-native species; "Piscivores" represents lakes with invasive piscivorous species.
FIG. 4 in Terrestrial macro-arthropods of the sub-Antarctic islands of Possession (Crozet Archipelago) and Kerguelen: inventory of native and non-native species
FIG. 4. — Some indigeneous arthropod species: Diptera: A, Telmatogeton amphibius (Eaton, 1875); B, Amalopteryx maritima Eaton, 1875; Hymenoptera: C, Kleidotoma icarus (Quinlan, 1964); Coleoptera: D, Antarctotachinus crozetensis Enderlein, 1909; Hemiptera: E, Phthirocoris antarcticus Enderlein, 1904; Lepidoptera: F, Pringleophaga kerguelensis Enderlein, 1905. Photos: Bernard Chaubet.
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