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Fig. 6 in Areas of endemism in Thailand: has historical partitioning between seasonally dry lowland and aseasonal moist mountain forests shaped biodiversity in Southeast Asia?

Fig. 6. Relationship between elevation and geographical range of Hybos spp. in Thailand. The number of 1° grids in which a species was recorded is plotted against the median elevation of all records. Line fitted by linear regression in PAST (r2=0.1026).

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Fig. 5 in Areas of endemism in Thailand: has historical partitioning between seasonally dry lowland and aseasonal moist mountain forests shaped biodiversity in Southeast Asia?

Fig. 5. EZPAE down-weighted against homoplasy, using altitudinally zoned mountain ranges as OGU, 'characters' made additive. Strict consensus tree of two equally parsimonious trees (CI = 0.716, RI = 0.534) produced by maximum parsimony analysis with weighted 'characters' and TBR branch swapping in TNT. Symmetrical resampling support is given under the nodes. Alphabetic codes of termini correspond with mountain ranges as abbreviated in Fig. 3; the suffixes 'low' & 'high' refer to low (<1,250m) and high (>1,250m) elevation sample data.

opencc-by-4.0Dec 2014View details →
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Fig. 4 in Areas of endemism in Thailand: has historical partitioning between seasonally dry lowland and aseasonal moist mountain forests shaped biodiversity in Southeast Asia?

Fig. 4. EZPAE down-weighted against homoplasy, using altitudinally zoned mountain ranges as OGU, 'characters' made non-additive. Strict consensus tree of four equally parsimonious trees (CI = 0.674, 0.580) produced by maximum parsimony analysis with weighted 'characters' and TBR branch swapping in TNT. Symmetrical resampling support is given under the nodes. Alphabetic codes of termini correspond with mountain ranges as abbreviated in Fig. 3; the suffixes 'low' & 'high' refer to low (<1,250m) and high (>1,250m) sample data.

opencc-by-4.0Dec 2014View details →
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Fig. 2. PAE using 1 in Areas of endemism in Thailand: has historical partitioning between seasonally dry lowland and aseasonal moist mountain forests shaped biodiversity in Southeast Asia?

Fig. 2. PAE using 1° grids as OGU. Strict consensus tree of 760 equally parsimonious trees (CI = 0.501, RI = 0.557) produced by maximum parsimony analysis with unweighted 'characters' and TBR branch swapping in TNT. Symmetrical resampling support is given under the nodes (see Fig 1A for explanation of alphabetic codes).

opencc-by-4.0Dec 2014View details →
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Fig. 3 in Areas of endemism in Thailand: has historical partitioning between seasonally dry lowland and aseasonal moist mountain forests shaped biodiversity in Southeast Asia?

Fig. 3. PAE using mountain ranges as OGU. Strict consensus tree of nine equally parsimonious trees (CI = 0.745, RI = 0.722) produced by maximum parsimony analysis with weighted 'characters' and implicit enumeration in TNT. Symmetrical resampling support is given under the nodes. Abbreviations. – CM, Cardamom Mountains; DK, Dong Paya Yen – Khao Yai Forest Complex; DL, Daen Lao Range; LP, Luang Prabang Range; NST, Nakhon Si Thammarat Range; PM, Petchabun Mountains; PR, Phuket Range; PPR, Phu Pan Range; TH, Tenasserim Hills; TT, Thanon Thongchai Range. Grid-B and Grid-L refer to 1° grids (B and L in Fig. 1A) that were not assigned to any mountain range.

opencc-by-4.0Dec 2014View details →
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Fig. 1 in Areas of endemism in Thailand: has historical partitioning between seasonally dry lowland and aseasonal moist mountain forests shaped biodiversity in Southeast Asia?

Fig. 1. Maps of Thailand showing: A, Grid of 1° of latitude and longitude denoted by single-letters A–W. Mountain ranges are indicated by two- or three letter codes (CD, DK, DL, LP, NST, PM, PPR, PR, TH & TT) and the grids that comprise each range are colour-coded. Grids B and L were not assigned to any mountain range; B, Species richness (number of species) of Hybos present in 1° grids; C, reciprocal weighted endemicity of Hybos spp. calculated for 1° grids.

opencc-by-4.0Dec 2014View details →
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Fig. 6 in A new species of Chirixalus Boulenger, 1893 (Anura: Rhacophoridae) from the lowland forests of Java

Fig. 6. Oscillogram and spectrogram of Chirixalus pantaiselatan, new species, MZB. Amph 30547, long call (A), and short call (B). The samples of advertisement calls are available at https://doi.org/10.6084/m9.figshare.14554179

opencc-by-4.0Jul 2021View details →
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Fig. 5 in A new species of Chirixalus Boulenger, 1893 (Anura: Rhacophoridae) from the lowland forests of Java

Fig. 5. Chirixalus pantaiselatan, new species, MZB. Amph 30547 in night-time (A) and MZB. Amph 30548 in the daytime (B), uncollected Chiromantis trilaksonoi (C), and Feihyla vittiger, MZB. Amph 27238 (D). C & D photographed by Farits Alhadi.

opencc-by-4.0Jul 2021View details →
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Fig. 4 in A new species of Chirixalus Boulenger, 1893 (Anura: Rhacophoridae) from the lowland forests of Java

Fig. 4. Ventral of right foot (A) and right hand (B) views of the holotype Chirixalus pantaiselatan, new species, MZB. Amph MZB. Amph 30547. Scales = 5 mm.

opencc-by-4.0Jul 2021View details →
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Fig. 3 in A new species of Chirixalus Boulenger, 1893 (Anura: Rhacophoridae) from the lowland forests of Java

Fig. 3. Dorsal (A) and ventral (B) views of the holotype Chirixalus pantaiselatan, new species, MZB. Amph 30547. Scale = 5 mm.

opencc-by-4.0Jul 2021View details →
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Fig. 2 in A new species of Chirixalus Boulenger, 1893 (Anura: Rhacophoridae) from the lowland forests of Java

Fig. 2. The plot of the first two principal components with 95% confidence of ellipses within two populations of adult male Chirixalus trilaksonoi (violet) and Chirixalus sp. (blue) based on the size-corrected morphometric variables (loading scores of the characters, see appendix 5).

opencc-by-4.0Jul 2021View details →
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Fig. 1 in A new species of Chirixalus Boulenger, 1893 (Anura: Rhacophoridae) from the lowland forests of Java

Fig. 1. Phylogenetic tree (A) Maximum likelihood (ML), (B) Bayesian Inference (BI) from ~483 bp of 16S rRNA mtDNA of Chirixalus spp., values above or below nodes indicate the Maximum Likelihood Bootstrap Proportion (MLBP) and Bayesian Posterior Probability (BPP) with the current distribution map of Chirixalus sp. (open diamond) and Chirixalus trilaksonoi (open circle). The distribution map was generated based on voucher material stored at the Museum Zooloogicum Bogoriense and sightings recorded from the ARK project on iNaturalist. Living specimen of Chirixalus trilaksonoi photographed by Wahyu Trilaksono.

opencc-by-4.0Jul 2021View details →
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Fig. 31. Tropical lowland evergreen rain forest along the Sungai Sadaunta, 700 m in A Systematic Review Of Sulawesi Bunomys (Muridae, Murinae) With The Description Of Two New Species

Fig. 31. Tropical lowland evergreen rain forest along the Sungai Sadaunta, 700 m (in 1976). Examples of Bunomys chrysocomus were caught amid the rocks in the foreground, deep within the forest, and occasionally on trunks and branches spanning the stream. Similar dense streamside forest and bridging trunks and limbs from old treefalls characterize much of the habitat along the Sungai Sadaunta where B. chrysocomus as well as B. karokophilus, n. sp., were encountered (see Natural History in account of B. chrysocomus).

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Fig. 29. Tropical lowland evergreen rain forest along the Sungai Sadaunta, 750–850 m in A Systematic Review Of Sulawesi Bunomys (Muridae, Murinae) With The Description Of Two New Species

Fig. 29. Tropical lowland evergreen rain forest along the Sungai Sadaunta, 750–850 m (in 1974). Typical forest composition on terraces just above the stream: dense undergrowth of shrubs and tree saplings, woody vines looping through the understory. Beneath the dense cover, the ground is wet, the air cool. Most Bunomys chrysocomus were trapped in this kind of stream terrace habitat, either on the ground beneath the shrubs, alongside decomposing, moss-covered trunks and limbs lying on the terrace, or among moss-covered rocks. Bunomys karokophilus, n. sp., was encountered in similar habitat.

opencc-by-4.0Dec 2014View details →
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Fig. 97 in The Mammals Of Paracou, French Guiana: A Neotropical Lowland Rainforest Fauna Part 2. Nonvolant Species

Fig. 97. Results of biogeographic analyses of 12 nonvolant rainforest mammal faunas (see table 55 for geographic coordinates and other locality information). Solid and broken contours enclosing various groups were drawn following the same conventions explained in the caption to figure 96. The raw (presence/absence) data on which both clustering and PAE were based are tabulated in appendix 2.

opencc-by-4.0Jun 2001View details →
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Fig. 95 in The Mammals Of Paracou, French Guiana: A Neotropical Lowland Rainforest Fauna Part 2. Nonvolant Species

Fig. 95. Distribution of lowland rainforest on the Central and South American mainland (see Voss and Emmons, 1996, for references). Major habitat discontinuities delimit four distinct regions: (1) the Andes and the Serranía de Perijá separate trans­Andean rainforests to the west from Venezuelan coastal rainforests and Amazonian rainforests to the east; (2) the Llanos and the lower Orinoco separate Venezuelan coastal rainforests to the north and west from Amazonia to the south and east; (3) an arid diagonal of xeromorphic biomes (Caatinga, Cerrado, Chaco) separates Amazonia to the northwest from the Atlantic rainforests (Mata Atlantica) to the southeast. The location of our inventory site at Paracou is indicated by the arrow.

opencc-by-4.0Jun 2001View details →
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Fig. 94 in The Mammals Of Paracou, French Guiana: A Neotropical Lowland Rainforest Fauna Part 2. Nonvolant Species

Fig. 94. Percent faunal similarity (Jaccard's coefficient of faunal similarity Χ 100) plotted against airline distance for all 45 pairwise comparisons among ten nonvolant rainforest mammal inventories (tables 62, 63).

opencc-by-4.0Jun 2001View details →
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Fig. 89 in The Mammals Of Paracou, French Guiana: A Neotropical Lowland Rainforest Fauna Part 2. Nonvolant Species

Fig. 89. Analysis of faunal similarity among nonvolant mammal inventories from 12 Neotropical rainforest localities. Faunal similarity was quantified between each pair of localities (i, j) by Jaccard's coefficient, Jij = Cij/Tij, where Cij is the number of species common to both faunas and Tij is the total number of species in both faunas combined (Tij = Ni + Nj — Cij). Localities were clustered by the unweighted pair­group method using arithmetic averages (Sneath and Sokal, 1973) for comparability with other recent biogeographic analyses of Neotropical vertebrates (e.g., da Silva and Sites, 1995). The bottom scale shows the clustering level in units of percent faunal similarity (J Χ 100). No historical or other causal interpretation is implied by these results, nor do we assume that a hierarchical model is necessarily appropriate except as a convenient summary graphic.

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Fig. 93 in The Mammals Of Paracou, French Guiana: A Neotropical Lowland Rainforest Fauna Part 2. Nonvolant Species

Fig. 93. Percent faunal similarity (Jaccard's coefficient of faunal similarity Χ 100) plotted against airline distance for all 45 pairwise comparisons among ten rainforest bat inventories (tables 62, 63).

opencc-by-4.0Jun 2001View details →
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Fig. 91 in The Mammals Of Paracou, French Guiana: A Neotropical Lowland Rainforest Fauna Part 2. Nonvolant Species

Fig. 91. Species accumulation for all mammals at Paracou, where we recorded 128 species in the course of 202 field days from 1991 to 1994. ''Minimum known diversity'' (142 species) includes additional records obtained from interviews, together with specimens previously collected in our study area by other investigators.

opencc-by-4.0Jun 2001View details →

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Allen Brain Atlas

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Annotated Behaviour and Observability Dataset (ABODe)

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behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
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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.

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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.

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behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
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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.

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neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record

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