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212 results for “Conserved regions”
FIGURE 5 in Bryofloristic diversity and conservation value of a protected area in the Brazilian semi-arid region
FIGURE 5. Unweighted group pairwise average (UPGMA). The average distance between all group members shows that areas within the same landscapes generally tend to have similar sets of species. Number differentiates landscapes; CF—Closed Forest; OF—Open Forest. Areas in dark gray had collections recorded during the dry season; in marine water, rainy season. Correlation Coefficient = 0.67—indicates moderate correlation.
FIGURE 5 in Evaluating the occurrence and conservation statuses of Sri Lankan Orchids (Orchidaceae): Observations on newly recorded species and undocumented regions
FIGURE 5. (A). Habenaria pterocarpa (B). Ipsea speciosa (C). Liparis elliptica (D). Liparis brachyglottis (E). Podochilus warnagalensis (F). Zeuxine reginasilvae.
FIGURE 4 in Evaluating the occurrence and conservation statuses of Sri Lankan Orchids (Orchidaceae): Observations on newly recorded species and undocumented regions
FIGURE 4. (A). Acanthephippium bicolor (B). Aerangis hologlottis (C). Anoectochilus regalis (D). Arundina minor (E). Didymoplexis pallens (F). Habenaria dolichostachya.
Data from: Population genetic structure and connectivity of deep-sea stony corals (Order Scleractinia) in the New Zealand region: implications for the conservation and management of Vulnerable Marine Ecosystems
Deep-sea stony corals, which can be fragile, long-lived, late to mature and habitat-forming, are defined as vulnerable marine ecosystem indicator taxa. Under United Nations resolutions these corals require protection from human disturbance such as fishing. To better understand the vulnerability of stony corals (Goniocorella dumosa, Madrepora oculata, Solenosmilia variabilis) to disturbance within the New Zealand region, and to guide marine protected area design, genetic structure and connectivity were determined using microsatellite loci and DNA sequencing. Analyses compared population genetic differentiation between two biogeographic provinces, amongst three sub-regions (north-central-south), and amongst geomorphic features. Extensive population genetic differentiation was revealed by microsatellite variation, whilst DNA sequencing revealed very little differentiation. For G. dumosa, genetic differentiation existed amongst regions and geomorphic features, but not between provinces. For M. oculata, only a north-central-south regional structure was observed. For S. variabilis, genetic differentiation was observed between provinces, amongst regions and amongst geomorphic features. Populations on the Kermadec Ridge were genetically different from Chatham Rise populations in all three species. A significant isolation-by-depth pattern was observed for both marker types in G. dumosa, and also in ITS of M. oculata. An isolation-by-distance pattern was revealed for microsatellite variation in S. variabilis. Medium to high levels of self-recruitment were detected in all geomorphic populations, and rates and routes of genetic connectivity were species-specific. These patterns of population genetic structure and connectivity at a range of spatial scales indicate that flexible spatial management approaches are required for the conservation of deep-sea corals around New Zealand.
Non-protected areas demanding equitable conservation strategies as of protected areas in Central Himalayan region
<p><span>The present study aims to explore the mammalian diversity of Darjeeling district using camera traps along with questionnaire survey in protected area (PA) and non- protected area (Non-PA). We also attempted to understand the influence of habitat variables on mammalian species richness using the generalized linear mixed models (GLMM). A total of 30 mammal species were recorded of which 21 species were detected through camera trapping with the most abundant records of barking deer (<i>Muntiacus muntjak</i>) and least of the elusive Chinese pangolin (<i>Manis pentadactyla</i>) and red panda (<i>Ailurus fulgens</i>). Additionally, melanistic forms of four mammals were also recorded. The mammalian species richness, their capture rate and naïve occupancy did not differ significantly among the PA and Non-PA. The GLMM revealed that the proportions of oak and bamboo in the forest, percentage canopy cover and camera trap operational days (<i>w</i>AICc = 0.145, <i>w</i>BIC = 0.603) were significant predictors of species richness in the study. We suggest Non-PA forest of Darjeeling should be given equal conservation importance as to the PA. Landscape based conservation planning will be imperative for achieving long term conservation goals in the study area. </span></p>
FIGURE 1 in Genetic structure of Ipomoea imperati (Convolvulaceae) in the Mediterranean region and implications for its conservation
FIGURE 1. Geographical distribution of chloroplast haplotypes. Further locality details are provided in Table 1.
FIGURE 3 in Genetic structure of Ipomoea imperati (Convolvulaceae) in the Mediterranean region and implications for its conservation
FIGURE 3. Single most parsimonious (MP) tree /Maximum Clade Credibility (MCC) tree for ITS sequences of the organisms in study. Topology of the MP tree is identical to that of MCC tree from the Bayesian analyses (see text for details). Numbers below branches are, left to right, bootstrap percentages (Felsenstein 1985) out of 1000 replicates, the clade decay index (Bremer 1994) computed out of trees up to 10 steps longer and the posterior probability of the maximum clade credibility tree (branches with p.p. <0.5 were collapsed, with the exception of the Israel/Honduras/Valencia clade, which was present in the MP tree). Estimated divergence times are provided above nodes. Nodes numbers refer to Table 3.
FIGURE 2 in Genetic structure of Ipomoea imperati (Convolvulaceae) in the Mediterranean region and implications for its conservation
FIGURE 2. Median-joining network for plastid DNA haplotypes in Mediterranean, Mexican and Honduran samples of Ipomoea imperati. Haplotypes are represented by the circles, the size of each being proportional to the observed frequency of each haplotype. Median vectors are labelled mv1 and mv2; these represent possible unsampled or extinct haplotypes. Information on the geographic locations where each haplotype is found is provided in Table 1.
Supplementary data for "Novel mutation/s in the conserved region of EPSPS imparts herbicide resistance in pigeonpea"
<p><strong>Figure S1. </strong>The picture represents the binding positions of different ligands in the binding pocket of w-CcEPSPS. A. GPJ B. PEP, C. S3P, D. PEP, and S3P together, and E. GPJ and PEP together. The structural diagram and the ligand interaction clearly shows the ligand’s individual binding site in A, B, and C and the binding of the two substrates ie., PEP and S3P in the same catalytic pocket with different binding site whereas PEP and GPJ share the same binding site in the catalytic site of CcEPSPS enzyme in the E. GPJ; Glyphosate, PEP; Phosphoenol pyruvate, S3P; Shikimate-3-phosphate.</p> <p><strong>Figure S2. </strong>Ramachandran plot representing the CcEPSPS protein structure, with each residue, plotted with their respective coordinates ie., phi and psi angles. The density of the points suggests the most prevalent secondary structure and CcEPSPS show dense right-handed ɑ helices followed by 𝛽 sheet secondary structure. The points lying in between the favorable region are defined as secondary structure areas for random coils.</p> <p><strong>Figure S3. </strong>Domain search based on Simple Modular Architecture Research Tool (SMART) (http://smart.embl.de/) revealed that the EPSPS proteins from A. pigeonpea, B. <em>Vibrio cholerae </em>and C. <em>Colwellia psychrerythraea </em>contain basic EPSP synthase domain. The Interaction network developed utilizing the STRING protein-protein database (https://string-db.org/) for D. pigeonpea, E. <em>Vibrio cholerae </em>and F. <em>Colwellia psychrerythraea </em>EPSPS proteins revealed the metabolically important EPSPS enzyme.</p> <p> </p>
Water charge and conservation of natural areas: An ex-ante assessment of a policy proposal for the Mantiqueira region, Brazil
<p>Economic model calibrated from a multiregional input-output table coupled to a water accounting system (hybrid-MRIO) focused on the Mantiqueira region, Brazil.</p>
Figure 2 in Endemic lineages of spiny frogs demonstrate the biogeographic importance and conservational needs of the Hindu Kush-Himalaya region
Figure 2. Minimum-spanning haplotype networks of Allopaa hazarensis generated for 16S and COI sequence data with the number of used sequences, detected haplotypes, and the level of nucleotide variability. Symbol sizes reflect haplotype frequencies, and a small black line between two haplotypes corresponds to one mutation step. Sequence-IDs are indicated for each haplotype (h1–h8). Map shows the localities from where the respective haplotypes originate.
Figure 3 in Endemic lineages of spiny frogs demonstrate the biogeographic importance and conservational needs of the Hindu Kush-Himalaya region
Figure 3. Distribution map for Allopaa hazarensis (A) and Chrysopaa sternosignata (B) derived from species distribution model (SDM) using MAXENT, including known records of the species (red = A. hazarensis, green = C. sternosignata). Photo credit: D. Jablonski.
Figure 1 in Endemic lineages of spiny frogs demonstrate the biogeographic importance and conservational needs of the Hindu Kush-Himalaya region
Figure 1. Bayesian inference (BI; left) and maximum likelihood tree (ML; right) based on concatenated mtDNA and nDNA sequence data (16S + COI + Rag1) of the tribe Paini. Numbers at branch nodes refer to posterior probabilities ≥ 0.9 (BI tree), as well as Felsenstein's bootstrap values ≥ 70% and transfer bootstrap expectation ≥ 0.9 (ML tree). Branches of Allopaa hazarensis are indicated red, while Chrysopaa sternosignata is highlighted green. Species names are followed by voucher number (if available). Coloured shaded boxes indicate subgroups of Nanorana and the new clade (in yellow) with so far unidentified specimens.
Water charge and conservation of natural areas: An ex-ante assessment of a policy proposal for the Mantiqueira region, Brazil
<p>Dataset and code: static interregional computable general equilibrium economic model (ICGE) for the Brazilian Mantiqueira region. ICGE model can be implemented in GEMPACK software.</p>
Data from: Seascape genetics and biophysical connectivity modelling support conservation of the seagrass Zostera marina in the Skagerrak-Kattegat region of the eastern North Sea
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Data from: Conservation phylogeography: does historical diversity contribute to regional vulnerability in European tree frogs (Hyla arborea)
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Data from: Regional genetic structure and environmental variables influence our conservation approach for feather heads (Ptilotus macrocephalus)
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Data from: Population genetic structure and connectivity of deep-sea stony corals (Order Scleractinia) in the New Zealand region: implications for the conservation and management of Vulnerable Marine Ecosystems
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Optimising nature conservation outcomes for a given region-wide level of food production
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Data from: Analysing biodiversity and conservation knowledge products to support regional environmental assessments
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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)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
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.