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2,007 results for “ecological species”
Fig. 8 in Description of a new species and a new subspecies of Odontorrhina Burmeister, 1842 (Scarabaeidae, Cetoniinae), with ecological notes on the genus
Fig. 8. Aerial web (approximately 3 m long × 1.5 m high) of social spider Stegodyphus dumicola, capturing Odontorrhina maraisi sp. n. and other insect prey (Witwater, October 2010).
Figs 3, 4. Odontorrhina pubescens hantam ssp. n in Description of a new species and a new subspecies of Odontorrhina Burmeister, 1842 (Scarabaeidae, Cetoniinae), with ecological notes on the genus
Figs 3, 4. Odontorrhina pubescens hantam ssp. n.: (3) male dorsal (a) and ventral (b) side; (4) frontal (a) and side (b) view of male aedeagus.
Fig. 6 in Description of a new species and a new subspecies of Odontorrhina Burmeister, 1842 (Scarabaeidae, Cetoniinae), with ecological notes on the genus
Fig. 6. Known distribution of Odontorrhina species. O. maraisi sp. n. (*); O. p. pubescens (○); O. p. hantam ssp. n. (●); O. hispida (■); O. krigei (□).
Fig. 4 in New record and new species of Laubierpholoe Pettibone, 1992 (Annelida, Sigalionidae) from the soft bottom of submarine caves near Marseille (Mediterranean Sea) with discussion on phylogeny and ecology of the genus
Fig. 4. Laubierpholoe massiliana Zhadan sp. nov., SEM. A. ZMMSU WS16511, ventral view. B. ZMMSU WS16511, pharynx, dorso-anterior view. C. ZMMSU WS14001, parapodia of segments I-V, dorso-anterior view. D. Same, parapodia of segment III, anterior view. E. ZMMSU WS13977, bidentate neurochaetae. F–G. ZMMSU WS12292, tips of bidentate neurochaetae. Abbreviations: ne = neuropodium; no = notopodium; pa = palp; vbc = ventral buccal cirrus; vc = ventral cirrus. Arrows indicate papillae.
Fig. 2 in New record and new species of Laubierpholoe Pettibone, 1992 (Annelida, Sigalionidae) from the soft bottom of submarine caves near Marseille (Mediterranean Sea) with discussion on phylogeny and ecology of the genus
Fig. 2. Laubierpholoe massiliana Zhadan sp. nov., light microscopy. A–B. Living specimens from different samples. C. ZMMSU WS12418, paratype, general view with proboscis everted. D. ZMMSU WS16462, holotype, general view, proboscis everted. E. ZMMSU WS14001, paratype, general view. F–H. ZMMSU WS14001, paratype, compound microscope. F. General view. G. Anterior part, dark field. H. Right jaws.
Fig. 5 in New record and new species of Laubierpholoe Pettibone, 1992 (Annelida, Sigalionidae) from the soft bottom of submarine caves near Marseille (Mediterranean Sea) with discussion on phylogeny and ecology of the genus
Fig. 5. Laubierpholoe massiliana Zhadan sp. nov., line drawings. A. Anterior end, dorso-anterior view. B. Notochaeta and bidentate neurochaeta. C. Parapodium, anterior view. D. Jaw. Abbreviations: ah = anterior horns; dtc = dorsal tentacular cirrus; ma = median antenna; ne = neuropodium; no = notopodium; p = prostomium; pa = palp; vbc = ventral buccal cirrus; vc = ventral cirrus; vtc = ventral tentacular cirrus. Arrows indicate papillae.
Fig. 6. Bayesian phylogenetic tree obtained with the 18S rRNA and 28S in New record and new species of Laubierpholoe Pettibone, 1992 (Annelida, Sigalionidae) from the soft bottom of submarine caves near Marseille (Mediterranean Sea) with discussion on phylogeny and ecology of the genus
Fig. 6. Bayesian phylogenetic tree obtained with the 18S rRNA and 28S rRNA concatenated dataset showing position of Laubierpholoe massiliana Zhadan sp. nov. within Sigalionidae Kinberg, 1856. Posterior probabilities and bootstrap values are shown for each medium supported node.
Fig. 3 in New record and new species of Laubierpholoe Pettibone, 1992 (Annelida, Sigalionidae) from the soft bottom of submarine caves near Marseille (Mediterranean Sea) with discussion on phylogeny and ecology of the genus
Fig. 3. Laubierpholoe massiliana Zhadan sp. nov., SEM. A. ZMMSU WS12292, general view. B. ZMMSU WS14001, general view, elytra omitted. C. ZMMSU WS13977, elytra. D. ZMMSU WS14001, anterior end, dorsal view. E. Same, dorso-anterior view. F. ZMMSU WS16511, anterior end, dorso-anterior view, median antenna broken. G. ZMMSU WS16511, dorso-anterior view. Abbreviations: ah = anterior horns; dtc = dorsal tentacular cirrus; e = elytrophores; ma = median antenna; ne = neuropodium; no = notopodium; p = prostomium; pa = palp; ph = pharynx; vbc = ventral buccal cirrus; vtc = ventral tentacular cirrus. Arrows indicate papillae.
Figure 2 in Rhyacophila siparantum sp. nov. (Trichoptera: Rhyacophilidae), a new species of the R. philopotamoides species group from the Republic of Kosovo with molecular and ecological notes
Figure 2. Picture of the type locality of Rhyacophila siparantum sp. nov.: Bogë Stream, Rugovë Mountain, Kosovo.
Figure 4 in Rhyacophila siparantum sp. nov. (Trichoptera: Rhyacophilidae), a new species of the R. philopotamoides species group from the Republic of Kosovo with molecular and ecological notes
Figure 4. Lateral profile of segment X: A. Rhyacophila siparantum sp. nov. (Kosovo); B. Rhyacophila schmidinarica (Croatia); C. Rhyacophila hirticornis (Croatia).
Figure 3 in Rhyacophila siparantum sp. nov. (Trichoptera: Rhyacophilidae), a new species of the R. philopotamoides species group from the Republic of Kosovo with molecular and ecological notes
Figure 3. Lateral profile of: A. Rhyacophila schmidinarica (Croatia); B. Rhyacophila siparantum sp. nov. (Kosovo); C. Rhyacophila hirticornis (Croatia).
Figure 9 in Rhyacophila siparantum sp. nov. (Trichoptera: Rhyacophilidae), a new species of the R. philopotamoides species group from the Republic of Kosovo with molecular and ecological notes
Figure 9. Maximum likelihood phylogenetic tree based on the analysis of the COI sequences of Rhyacophila species. Numbers near nodes indicate maximum likelihood (ML) ultrafast bootstrap support values (BS), and Bayesian posterior probabilities (BPP). The result of morphological examination is shown by the first row of vertical bars where each color indicates a different species. The results of species delimitations are represented with the following vertical bars, from left to right, indicate the OTUs inferred by ABGD and mPTP. Terminal codes present BOLD ID, as in Table 1.
Figure 8. Segment X in Rhyacophila siparantum sp. nov. (Trichoptera: Rhyacophilidae), a new species of the R. philopotamoides species group from the Republic of Kosovo with molecular and ecological notes
Figure 8. Segment X and anal sclerites with apical band in ventrocaudal position (A); anal sclerites with apical band in dorsocaudal position (B).
Data for: A model of ecological abundance: Terrestrial species inventories
<p>Counts of species in ecological samples are important for two reasons: they tell us about community assembly processes and they form the basis of species diversity estimates. Previous models of count distributions are either complex, widely rejected, not grounded in population dynamics, or not able to predict high unevenness. I present a new one-parameter model assuming that individual counts track the geometric series. The series' governing parameter <em>p</em> is set to vary randomly among species. Communities differ only in the centering of the distribution of <em>p</em>. To find the probability distribution, a vector of evenly-spaced initial values called q is drawn from the range 0 to 1. Values are then scaled by (1) transforming each q into the odds <em>o</em> = <em>q</em>/(<em>1 – q</em>), (2) multiplying each o by a fitted parameter <em>m</em>, and (3) back-computing each <em>p</em> as <em>m o</em>/(<em>m o </em>+ <em>1</em>). This skews the values to match the centering of the actual counts. The distribution is consistent with a population dynamics model in which the number of offspring produced in each interval by each species is distributed geometrically, rising with the number of adults. Large-scale surveys of corals, fishes, butterflies, and trees are consistent with the distribution, as are local-scale inventories of trees and assorted vertebrate and insect groups. Each local survey is used to predict counts within biogeographically and taxonomically matched surveys. When only decisive differences are considered, the model's predictions outperform those of each rival in at least 86% of all pairwise comparisons. The new distribution's estimates haves no substantial sample size bias. Thus, it is preferable to other species diversity estimation methods in the frequent cases where it is a good fit to count data.</p>
Data from: An environmental habitat gradient and within-habitat segregation enable co-existence of ecologically similar bird species
<p>Niche theory predicts that ecologically similar species can co-exist through multidimensional niche partitioning. However, due to the challenges of accounting for both abiotic and biotic processes in ecological niche modelling, the underlying mechanisms that facilitate co-existence of competing species are poorly understood. In this study, we evaluated potential mechanisms underlying the co-existence of ecologically similar bird species in a biodiversity-rich transboundary montane forest in east-central Africa by computing niche overlap indices along an environmental elevation gradient, diet, forest strata, activity patterns, and within-habitat segregation across horizontal space. We found strong support for abiotic environmental habitat niche partitioning, with 55% of species pairs having separate elevation niches. For the remaining species pairs that exhibited similar elevation niches, we found that within-habitat segregation across horizontal space and to a lesser extent vertical forest strata provided the most likely mechanisms of species co-existence. Co-existence of ecologically similar species within a highly diverse montane forest was determined primarily by abiotic factors (e.g., environmental elevation gradient) that characterize the Grinnellian niche and secondarily by biotic factors (e.g., vertical and horizontal segregation within habitats) that describe the Eltonian niche. Thus, partitioning across multiple levels of spatial organization is a key mechanism of co-existence in diverse communities.</p>
Impact of forest disturbance on microarthropod communities depends on underlying ecological gradient and species traits
<p>Dataset and R scripts used in the publication "Impact of forest disturbance on microarthropod communities depends on underlying ecological gradient and species traits", PeerJ</p>
Data from: Species-specific ecological traits, phylogeny, and geography underpin vulnerability to population declines for North American birds
<p>Species declines and extinctions characterize the Anthropocene. Determining species vulnerability to decline, and where and how to mitigate threats, are paramount for effective conservation. We hypothesized that species with shared ecological traits also share threats, and therefore may experience similar population trends. Here, we used a Bayesian modeling framework to test whether phylogeny, geography, and 22 ecological traits predict regional population trends for 380 North American bird species. Groups like blackbirds, warblers, and shorebirds, as well as species occupying Bird Conservation Regions at more extreme latitudes in North America, exhibited negative population trends, while groups such as ducks, raptors, and waders, as well as species occupying more inland Bird Conservation Regions, exhibited positive trends. Specifically, we found that in addition to phylogeny and breeding geography, multiple ecological traits contributed to explaining variation in regional population trends for North American birds. Furthermore, we found that regional trends and the relative effects of migration distance, phylogeny, and geography differ between shorebirds, songbirds, and waterbirds. Our work provides evidence that multiple ecological traits correlate with North American bird population trends, but that the individual effects of these ecological traits in predicting population trends often vary between different groups of birds. Moreover, our results reinforce the notion that variation in avian population trends is controlled by more than phylogeny and geography, where closely-related species within one region can show unique population trends due to differences in their ecological traits. We recommend that regional conservation plans, i.e. one-size-fits-all plans, be implemented only for bird groups with population trends under strong phylogenetic or geographic controls. We underscore the need to develop species-specific research and management strategies for other groups, like songbirds, that exhibit high variation in their population trends and are influenced by multiple ecological traits.</p>
Linking the metabolic rate of individuals to species ecology and life history in key Arctic copepods
<p>This folder contains data and code for the manuscript "Linking the metabolic rate of individuals to species ecology <br> and life history in key Arctic copepods"</p> <p>The first script to run is the "rolling regression and adding covariates to MR data.R", this will read in all the<br> files with oxygen measurements, dry weight, and species and life stage information. The code will fit and predict <br> estimates for each individual, calculate O2 from calibration data, subtract background respiration, run the rolling regression,<br> and add the covariates DW, species and life stage to the metabolic rate data, and write the resulting data fame to a .txt file.</p> <p>The second script "lme4 Analysis and figures 5 6 7.R" will read in the data from the first script. <br> Here the AMR RMR and aerobic scope is estimated by Density Estimation via Model-Based Clustering. <br> The resulting data is fitted with a mixed model 'lmer'. <br> The remaining part of the script make the predictions that are presented in the text of the manuscript<br> and that are shown in figure 5, 6, and 7.</p> <p>Further information is annotated in the scripts</p>
Data, code, and supplementary materials for Pearman P. B., Broennimann, O., et al. Monitoring species genetic diversity in Europe varies greatly and overlooks potential climate change impacts. Nature Ecology & Evolution
<p>The repository contains several archives of digital materials that were used and/or produced in the analyses presented in Pearman, P. B. and Broennimann et al. Monitoring species genetic diversity in Europe varies greatly and overlooks potential climate change impacts. <strong>Nature Ecology & Evolution</strong>, likely 2023. These archives include (1) Supplementary Materials files ; (2) Data and code to generate country-level maps and plots; and (3) data and code to generate all maps of species and joint climate niche marginality, all in G-zipped tar archives. Readme files are available in each archive to guide running of the scripts and identification of objects in the Supplementary Materials. Please see the paper for all co-authors names, and the methods, the results obtained, and discussion of their implications.</p> <p>This work is dedicated to the memory of our friend and colleague Michael Bruford (1963-2023).</p>
Data from: Differential use of nest materials and niche space among avian species within a single ecological community
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.