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Fig. 1 in Natural-Licks Use By Orangutans And Conservation Of Their Habitats In Bornean Tropical Production Forest
Fig. 1. Location maps of Deramakot Forest Reserve in Sabah, Malaysian Borneo (D1 to D4: natural-licks).
FIGURE 10 in A new collared lizard (Tropidurus: Tropiduridae) endemic to the Western Bolivian Andes and its implications for seasonally dry tropical forests
FIGURE 10. Scatterplots of PC1 and PC2 generated by the principal component analyses and LD1 and LD2 generated by the linear discriminant analyses performed on meristic variables (scale counts). See table 7 for corresponding summary statistics. Figure color-coded following species labels in figure 11.
FIGURE 8 in A new collared lizard (Tropidurus: Tropiduridae) endemic to the Western Bolivian Andes and its implications for seasonally dry tropical forests
FIGURE 8. Boxplots showing variation in scale counts among Tropidurus chromatops, T. etheridgei, and T. azurduyae.
FIGURE 7 in A new collared lizard (Tropidurus: Tropiduridae) endemic to the Western Bolivian Andes and its implications for seasonally dry tropical forests
FIGURE 7. Scatterplots of PC1 and PC2 generated by the principal component analyses and LD1 and LD2 generated by the linear discriminant analyses performed on morphometric variables. See table 4 for corresponding summary statistics. Figure color-coded following species labels in figure 11.
FIGURE 6 in A new collared lizard (Tropidurus: Tropiduridae) endemic to the Western Bolivian Andes and its implications for seasonally dry tropical forests
FIGURE 6. Live specimens of Tropidurus chromatops Harvey and Gutberlet, 1998 from isolated granitic outcrops ~30 km W Florida, Santa Cruz, Bolivia (14° 36′ 17.28″ S, 61° 29′ 32.64″ W — WGS84 system; ~309 m). A, C, Adult female (MHNC-R 3003). B, D, Adult male (MHNC-R 3018).
FIGURE 5 in A new collared lizard (Tropidurus: Tropiduridae) endemic to the Western Bolivian Andes and its implications for seasonally dry tropical forests
FIGURE 5. Adult male of Tropidurus chromatops Harvey and Gutberlet, 1998 (MHNC-R 3018), illustrating the expanded lateral neck mite pockets and the colorful facial mask with touches of blue and cream, characteristic of the species.
FIGURE 4 in A new collared lizard (Tropidurus: Tropiduridae) endemic to the Western Bolivian Andes and its implications for seasonally dry tropical forests
FIGURE 4. Preserved holotype of Tropidurus azurduyae (adult male, MHNC-R 3011). A, Dorsal head. B, Ventral head. C, Lateral head. D, Ventral body. E, Lateral body. F, Dorsal body.
FIGURE 3 in A new collared lizard (Tropidurus: Tropiduridae) endemic to the Western Bolivian Andes and its implications for seasonally dry tropical forests
FIGURE 3. Live specimens of Tropidurus etheridgei Cei, 1982 and T. azurduyae. A, C, Adult male of T. etheridgei (AMNH-R 176273) from Orloff, Colonia 15, Filadelfia, Boquerón, Paraguay (22° 19′ 58.42″ S, 59° 55′ 00.02″ W — WGS84 system; ~136 m). B, D, Adult female of T. etheridgei (AMNH-R 176277) from Estancia Esmeraldas, Boquerón, Paraguay (20° 59′ 15.81″ S 61° 59′ 27.90″ W — WGS84 system; ~329 m). E, G, Adult female (allotype MHNC-R 3009) of T. azurduyae. F, H, Adult male (holotype MHNC-R 3011) of T. azurduyae.
FIGURE 1 in A new collared lizard (Tropidurus: Tropiduridae) endemic to the Western Bolivian Andes and its implications for seasonally dry tropical forests
FIGURE 1. Habitats visited in the Torotoro National Park, Potosí, Bolivia. A–D, Prepuna (18° 7′ 10.92″ S, 65° 48′ 30.24″ W — WGS84 system; ~2798 m). E–G, Inter-Andean dry valleys at the type locality of Tropidurus azurduyae (18° 5′ 54.24″ S, 65° 44′ 57.48″ W — WGS84 system; ~2264 m). H, Adult male of T. azurduyae, sighted (not collected) at the type locality of the species.
Fig. 5 in Long-term changes in avian relative abundances in relation to human disturbance in a tropical dry forest in central Myanmar
Fig. 5. Human detections along five, two-kilometre transects, one each in five habitats/subtypes (young dipterocarp forest, flooded dipterocarp forest, mixed deciduous forest, mature dipterocarp forest, and wetlands) per month in Chatthin Wildlife Sanctuary. Effort = number of habitat subtypes * total months sampled per year * 2 km, X-axis= year, Y-axis= human disturbance index (number of human detections per one unit of effort).
Fig. 1 in Long-term changes in avian relative abundances in relation to human disturbance in a tropical dry forest in central Myanmar
Fig. 1. Map of Chatthin Wildlife Sanctuary with land-cover changes; flooded dipterocarp forest (FL), mixed deciduous forest (MD) and young dipterocarp forest (YI) in Chatthin Wildlife Sanctuary between 1999 and 2020 and locations of bird survey points.
Fig 4 in Long-term changes in avian relative abundances in relation to human disturbance in a tropical dry forest in central Myanmar
Fig 4. Seasonal (y-axis) and long-term trends of abundances of six avian guilds in Chatthin Wildlife Sanctuary from 1999 to 2020. Redder = higher abundances, white/paler = lower abundances, and grey = no data.
Methane and Carbon Dioxide Production and Emission Pathways in the Belowground and Draining Water Bodies of a Tropical Peatland Plantation Forest
<p>This is the data repository for the second version (revised) of the manuscript "Methane and Carbon Dioxide Production and Emission Pathways in the Belowground and Draining Water Bodies of a Tropical Peatland Plantation Forest<strong>"</strong> submitted to Geophysical Research Letters on 10 January 2025.</p>
Data from: Using model analysis to unveil hidden patterns in tropical forest structures
<p>Data set of the article entitled: <strong>Using model analysis to unveil hidden patterns in tropical forest structures</strong></p> <p>This data set gives the following structural attributes for 133 forest plots at 9 sites in the tropics:</p> <ul> <li>tree density (ha<sup>-1</sup>)</li> <li>basal area (m<sup>2</sup> ha<sup>-1</sup>)</li> <li>mean diametere (cm)</li> <li>equivalent diameter (cm)</li> <li>density of trees in the dbh class 10-30 cm (ha<sup>-1</sup>)</li> <li>density of trees in the dbh class 30-60 cm (ha<sup>-1</sup>)</li> <li>density of trees with dbh ≥ 60 cm (ha<sup>-1</sup>)</li> <li>aboveground dry biomass (Mg ha<sup>-1</sup>)</li> <li>fraction of the biomass of trees with dbh ≥ 60 cm</li> <li>weighted mean wood density (g cm<sup>-3</sup>)</li> <li>density of trees in the dbh class 10-20 cm (ha<sup>-1</sup>)</li> <li>density of trees in the dbh class 20-30 cm (ha<sup>-1</sup>)</li> <li>density of trees in the dbh class 30-40 cm (ha<sup>-1</sup>)</li> <li>density of trees in the dbh class 40-50 cm (ha<sup>-1</sup>)</li> <li>density of trees in the dbh class 50-60 cm (ha<sup>-1</sup>)</li> <li>density of trees in the dbh class 60-70 cm (ha<sup>-1</sup>)</li> <li>density of trees in the dbh class 70-80 cm (ha<sup>-1</sup>)</li> <li>density of trees in the dbh class 80-90 cm (ha<sup>-1</sup>)</li> <li>density of trees in the dbh class 90-100 cm (ha<sup>-1</sup>)</li> <li>density of trees in the dbh class 100-110 cm (ha<sup>-1</sup>)</li> <li>density of trees in the dbh class 110-120 cm (ha<sup>-1</sup>)</li> <li>density of trees in the dbh class 120-130 cm (ha<sup>-1</sup>)</li> <li>density of trees with dbh ≥ 130 cm (ha<sup>-1</sup>)</li> </ul>
Data for: Trap type affects dung beetle taxonomic and functional diversity in Bornean tropical forests
<p>Dung beetle community composition data. Data was collected using either dung-baited pitfall traps or flight interception traps. Each row represents one trap, with the author/study information, name of study site, sampling period, trap type and habitat type. Dung beetle species and their abundances are listed. See "metadata" tab for more details.</p> <p>Paper abstract: Baited pitfall traps (BPTs) and flight intercept traps (FITs) are the most common methods employed for sampling dung beetle communities. These methods vary in their efficacy and are affected by factors such as the bait types used and the dispersal abilities of different dung beetle species. We present the first quantitative comparison of the taxonomic and functional diversity, and community composition of dung beetles caught in BPTs and FITs in Bornean tropical forests. We show that BPTs and FITs captured complementary communities with different functional traits, and that BPTs captured more functionally diverse communities. We therefore recommend using a combination of both baited BPTs and FITs for studies assessing the composition of dung beetles across habitat types. Our results also highlight that it is important to consider how trap type affects the trait composition of communities when relating dung beetle communities and functional traits to ecological functioning. We suggest modifications to FITs based on the design of harp traps to increase their effectiveness in capturing larger-bodied beetles.</p>
Acoustic lures increase tropical forest understorey bat captures
<p>Data used in the publication "Effectiveness of acoustic lures for increasing tropical forest understorey bat captures".</p>
Multi-taxa environmental DNA inventories reveal distinct taxonomic and functional diversity in urban tropical forest fragments
<p>Urban expansion and associated habitat transformation drives shifts in biodiversity, with declines in taxonomic and functional diversity. Forests fragments within urban landscapes offer a number of ecosystem services, and help to maintain biodiversity and ecosystem functions. Here, we focus on a tropical forest environment, and on the soil biota. Using eDNA metabarcoding, we compare forest fragments within the city of Cayenne, French Guiana, with a neighbouring continuous undisturbed forest. We wished to determine if urban forest fragments conserve high levels of alpha and beta diversity as well as similar functional composition for plants, soil animals, fungi and bacteria. We found that alpha diversity is similar across habitats for plants and fungi, lower in urban forests for metazoans and higher for bacteria. We also found that urban forests communities differ from undisturbed forests in their taxonomic composition, with urban forests exhibiting greater turnover between fragments potentially caused by ecological drift and limited dispersal. However, their functional composition exhibited limited differences, with an enrichment of palms, arbuscular mycorrhizal fungi and bacteria and a depletion of climber plants and termites. Thus, although urban forest fragments do shelter soil biodiversity that differs from native forests, the losses of soil functions may be relatively limited. This study demonstrates the strong potential of a multi-taxa eDNA approach for rapid inventories across taxonomic kingdoms, in particular for cryptic soil diversity. It also demonstrates the key role of urban forest fragments in conserving biodiversity and ecosystem function, and points to a need for more systematic monitoring of these areas in urban management plans.</p> <p>For each of the 16 samples per plot, 15 g of soil was used for eDNA analyses. Extracellular DNA was extracted as described previously (Zinger et al., 2016; 2019), where each soil sample is added to 15ml of saturated phosphate buffer (Na<sub>2</sub>HPO<sub>4</sub>; 0.12m; pH ≈8) in 50ml Falcon tubes. This is placed in an agitator for 15 minutes, before a 2ml aliquot of the soil/phosphate buffer mixture is pipetted into an Eppendorf tube and centrifuged for five minutes at 13000 rcf. 500μL of the resulting supernatant is then recovered and used for the next extraction steps that are carried out with a commercial kit for soil DNA (NucleoSpin® Soil; Macherey-Nagel, Düren, Germany), skipping the lysis step and following manufacturer’s instructions. The DNA extract was recovered in 100 μL and diluted 10 times before being used as PCR template.</p> <p> For each plot one DNA extraction negative control was performed adding up 17 extractions per plot. PCR amplifications were then conducted for four DNA molecular markers, with primers targeting either Viridiplantae (subsequently referred to as plants), Eukaryotes, Fungi or Bacteria (Table 1). For each marker, PCR amplification of samples occurred across 12 plates. Each PCR reaction was performed in a total volume of 20 μl and comprised 10 μl of AmpliTaq Gold Master Mix (Life Technologies, Carlsbad, CA, USA), 5.84 μl of Nuclease-Free Ambion Water (Thermo Fisher Scientific, Massachusetts, USA), 0.25 μM of each primer, 3.2 μg of BSA (Roche Diagnostic, Basel, Switzerland), and 2 μl of DNA template that was before 10-fold diluted to reduce the amounts of PCR inhibitors. Thermocycling conditions for each primer pair are indicated in Table 1. A negative extraction control per site and a negative PCR control per PCR plate were amplified and sequenced in parallel with the regular samples. Positive controls were also included and consisted of mock communities of plants and fungi DNA (no mock communities were built for bacteria or eukaryotes here), which were used to guide choices in our data curation process. Two PCR replicates were performed for each sample and control. Amplification was conducted using a double indexing system strategy (Binladen et al. 2007) using a system of 32 by 36 octamers with at least five differences between them located at the 5’ end of each primer (Coissac 2012). In doing so, each PCR product had a unique combination of tags for both forward and reverse primers, allowing for the retrieval of sequence data for each sample. Ten wells per PCR plate were left empty to act as sequencing controls (non-used tag combinations) for downstream data curation (see below). PCR products were pooled and sequencing libraries were constructed using the Illumina TruSeq NanoPCRFree kit following the supplier’s instructions (Illumina Inc., San Diego, California, USA), except that the ligation product was not PCR amplified to limit tag-jump biases (Taberlet et al 2018). The libraries were then sequenced on different Illumina platforms (San Diego, CA, USA) depending on the marker considered (Table S1), using the paired-end technology.</p> <p>Bioinformatic analyses were performed on the GenoToul bioinformatics platform (Toulouse, France), with the OBITOOLS package (Boyer et al. 2016). First, ‘illuminapairedend’ was used to assemble paired-end reads. This algorithm is based on an exact alignment algorithm that considers the quality scores at all positions during the assembly process. Subsequently, we used the ‘ngsfilter’ command to identify and remove the primers and tags on each read, and assign reads to their respective samples. This program was used with its default parameters tolerating two mismatches for each of the two primers and no mismatch for the tags. Following this, sequencing reads were dereplicated using the ‘obiuniq’ command. Sequences of low quality (containing Ns or with paired-end alignment scores below 50) were excluded using the ‘obigrep’ command. The same command was used to exclude sequences represented by only one read (singletons) as they are more likely to be molecular artefacts (Taberlet et al. 2018). Sequences outside of the preset range were also discarded (Table 1). To remove PCR/sequencing errors as well as intraspecific variability, we built OTUs (Operational Taxonomic Units) using the ‘sumaclust’ clustering algorithm (Mercier et al. 2013), which considers the most abundant sequence of each cluster as the cluster representative. OTUs were set at a sequence similarity threshold of 97% for eukaryotes, fungi and bacteria following the standards in microbial ecology, but this was lowered to 95% for plants since the eDNA target region is shorter (typically around 50 base pairs), where one mismatch inherently results in a lower percentage of similarity. To assign a taxon to plant and fungal OTUs, we built two reference sequence databases, one global, using the ecoPCR programme (Ficetola et al. 2010) and the plant / fungi specific markers on the European Molecular Biology Laboratory (EMBL; release 141), a second local, generated from specimens of fungi (Jaouen et al. 2019) and plants (see Zinger et al. 2019) collected in French Guiana. OTUs were then assigned a taxonomy, using OBITOOL’s ecotag programme (Boyer et al. 2016), which performs a global alignment of each OTU sequence (the query) against each reference. The reference taxon assigned to each OTU corresponds to the Last Common Ancestor of all the best-match sequences for the query. For taxonomic assignment of bacteria and eukaryote OTUs, the SILVA taxonomic database was used (version 1.3; Quast et al., 2012). Classification was performed by a local nucleotide BLAST search against the non-redundant version of the SILVA SSU Ref dataset (release 132; http://www.arb-silva.de) using blastn (version 2.2.30+; http://blast.ncbi.nlm.nih.gov/Blast.cgi) with standard settings (Camacho et al., 2009). Eukaryote derived metazoan OTUs were then further assigned a taxonomy for Phyla identified at the Arthropoda, Annelida and Nematoda level using reference sequence databases built as above for these groups using the ecoPCR programme on EMBL release 141.</p> <p>Datasets were subsequently filtered to remove contaminants as well as artefacts such as PCR chimeras and remaining sequencing errors, following Zinger et al. (2019) and using routines now implemented in the metabaR R package (Zinger et al 2020b), in R version 3.6.1 (R Development Core Team, 2013). The filtering process consisted of four steps: (i) a negative control-based filtering. OTUs whose maximum abundance was found in extraction/PCR negative controls were removed from the dataset, as they were likely to be reagent/aerosol contaminants, better amplified in the absence of competing DNA fragments as it is the case in biological samples. (ii) a reference-based filtering. OTUs which are too dissimilar from sequences available in reference databases are potential chimeras generated during sequencing and amplification. In this study, we chose to set similarity thresholds at 95% for plants, 80% for bacteria and eukaryotes and due to the marker being more polymorphic, 65% for fungi. For plants and fungi, the remaining assignment was then verified with the local database, to confirm if assigned taxa also occurred in the local dataset, with preference given to local assignment. In addition, we removed all taxa that are not targeted by the primer used. (iii) an abundance-based filtering. This procedure targets incorrect assignment of a few numbers of sequences corresponding to true OTUs occurring to the wrong sample, a phenomenon called “tag-switching” (Esling et al. 2015), “tag jumps” (Schnell et al. 2015) or “cross-talk” (Edgar 2018). It consists in setting OTUs abundances to 0 in samples where their abundance represents < 0.03% of the total OTU abundance in the entire dataset. (iv) Finally, we conducted a PCR-based filtering by considering any PCR reaction that yielded less than 100 reads for plants, 1000 reads for fungi, bacteria and eukaryotes as non-functional, and removed them from the dataset.</p> <p>Data provided consists of 4 x OTU tables for each of the markers used to target different components of the soil biota, with rows representing each OTU, and columns the features of the OTU within the dataset, namely their id code, the number of read counts in the analysed dataset, their similarity score against the taxonomic dataset used to identify them, and when possible, a functional group assignment used in the manuscript. Details of these can be found above and in the manuscript and supplementary information.</p> <p>For each of the four datasets, we also provide a .rds file, corresponding to the processed dataset used in manuscript preparation. This is in the format of a metabaR list which includes PCR, Sample, Read count and the seperately provided OTU datasets. To facilitate interpretation, please refer to Zinger, L., Lionnet, C., Benoiston, A.S., Donald, J., Mercier, C. and Boyer, F., 2021. metabaR: an R package for the evaluation and improvement of DNA metabarcoding data quality. Methods in Ecology and Evolution, 12(4), pp.586-592.</p> <p>For the fungal (ITS) data, we also provide : </p> <p>- the R1/R2 raw fastq files of the samples used in the paper + experimental controls</p> <p>- a tsv file containing the tag combinations corresponding to the samples/PCR replicates, to enable demultiplexing of data.</p> <p>- a csv file containing the description of each sample.</p>
Data from: Occupancy winners in tropical protected forests: a pantropical analysis
<p class="MsoNormal"><span>The structure of forest mammal communities appears surprisingly consistent across the continental tropics<span>, presumably due to convergent evolution in similar environments. W</span>hether such consistency extends to mammal occupancy, despite variation in species characteristics and context, remains unclear. Here we ask whether we can predict occupancy patterns and, if so, whether these relationships are consistent across biogeographic regions. Specifically, we assessed how mammal feeding guild, body mass and ecological specialization relate to occupancy in protected forests across the tropics. We used standardized camera-trap data (</span><span>1,002 camera-trap locations and 2-10 years of data)</span><span> and a hierarchical Bayesian occupancy model. We found that occupancy varied by regions, and </span><span>certain species characteristics</span><span> explained much of this variation. Herbivores consistently had the highest occupancy. However, only in the Neotropics did we detect a significant effect of body mass on occupancy: large mammals had lowest occupancy. Importantly, habitat specialists generally had higher occupancy than generalists, though this was reversed in the Indo-Malayan sites. We conclude that </span><span>habitat specialization is key for understanding variation in mammal occupancy across regions, and that habitat specialists often benefit more from protected areas, than do generalists. </span><span>The contrasting examples seen in the Indo-Malayan region likely reflect distinct anthropogenic pressures.</span></p>
Functional assembly of tropical montane tree islands in the Atlantic Forest is shaped by stress-tolerance, bamboo-presence and facilitation
<p><strong>Aims</strong>: Amidst the Campos de Altitude (Highland Grasslands) in the Brazilian Atlantic Forest, woody communities grow either clustered in tree islands or interspersed within the herbaceous matrix. The functional ecology, diversity and biotic processes shaping these plant communities are largely unstudied. We characterised the functional assembly and diversity of these tropical montane woody communities and investigated how they fit within Grime's CSR (C – competitor, S – stress-tolerant, R – ruderal) scheme, what functional trade-offs they exhibit and how traits and functional diversity vary in response to bamboo presence/absence.</p> <p><strong>Methods</strong>: To characterize the functional composition of the community, we sampled five leaf traits and wood density along transects covering the woody communities both inside tree islands and outside (i.e. isolated woody plants in the grasslands community) . Then, we used Mann Whitney test, t-test and variation partitioning to determine the effects of inside vs outside tree island and bamboo presence on community weighted means, woody species diversity and functional diversity.</p> <p><strong>Results</strong>: We found a general SC/S strategy with drought-related functional trade-offs. Woody plants in tree islands had more acquisitive traits than those within the grasslands. Trait variation was mostly taxonomically than spatially driven, and species composition varied between inside and outside tree islands. Leaf thickness, wood density and foliar water uptake were unrelated to CSR-strategies, suggesting independent trait dimensions and multiple drought-coping strategies within the predominant S-strategy. Islands with bamboo presence showed lower Simpson diversity, lower functional dispersion, lower foliar water uptake and greater leaf thickness than in tree islands without bamboo.</p> <p><strong>Conclusions</strong>: The observed functional assembly hints towards large-scale environmental abiotic filtering shaping stress-tolerant community strategy, and small-scale biotic interactions driving small-scale trait variation. We recommend experimental studies with fire, facilitation treatments, eco-physiological and recruitment traits to elucidate on tree island expansion and communities response to climate change.</p>
Fig. 2 in Croton sertanejus, a new species from Seasonally Dry Tropical Forest in Brazil, and redescription of C. echioides (Euphorbiaceae)
Fig. 2. Croton sertanejus Sodré & M.J.Silva sp. nov. A–B. Habit. C. Flowering branch showing ramifying in alternate branches. D. Inflorescence showing pistillate flowers and staminate buds. E. Pistillate flowers. F. Unisexual staminate inflorescence. G. Fruit. H–I. Fruit columella. J. Apex of columella with irregular and plane tips. K. Seed, dorsal side. L. Seed, ventral surface. A–F = Population from Oliveira dos Brejinhos, Bahia (R.C. Sodré et al. 3350, holotype; BOTU); G–L = K.N.C. Castro & J.B.A. Souza 471 (CEN). Photographs: R.C. Sodré.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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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.