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226 results for “habitat fragmentation”
Tree and habitat structure data from rainforest fragments and coffee plantations in the Anamalai Hills, Western Ghats, India
<p><strong>TITLE</strong></p><p><strong>Tree and habitat structure data from rainforest fragments and coffee plantations in the Anamalai Hills, Western Ghats, India</strong><br> </p><p><strong>DESCRIPTION</strong></p><p>This dataset contains point-centred quarter (PCQ) data on trees and habitat structure measurements data from rainforest fragments and some coffee plantations in the Valparai Plateau and Anamalai Tiger Reserve, Tamil Nadu, India. The data were gathered to quantity habitat parameters for bird and small carnivorous mamm community studies. Data were gathered mainly by T. R. Shankar Raman and Divya Mudappa (2000 to 2003), Hari Sridhar (2005), and Akshay Surendra (2019).</p><p><strong>Publications</strong></p><p>Specific portions of the dataset have been used in the following publications:</p><ul><li>Mudappa, D. 2001. <a href="https://hdl.handle.net/10603/101890">Ecology of the brown palm civet <i>Paradoxurus jerdoni</i> in the tropical rainforests of the Western Ghats, India</a>. Ph. D. thesis, Bharathiar University, Coimbatore. https://hdl.handle.net/10603/101890</li><li>Raman, T. R. S. 2001. <a href="https://archive.org/details/raman-2001-ph-d-thesis-iisc">Community ecology and conservation of mid-elevation tropical rainforest bird communities in the southern Western Ghats, India</a>. PhD thesis, Indian Institute of Science, Bangalore. https://archive.org/details/raman-2001-ph-d-thesis-iisc</li><li>Raman, T.R.S. 2006. <a href="https://doi.org/10.1007/s10531-005-2352-5">Effects of Habitat Structure and Adjacent Habitats on Birds in Tropical Rainforest Fragments and Shaded Plantations in the Western Ghats, India</a>. <i>Biodiversity and Conservation</i> 15: 1577–1607. https://doi.org/10.1007/s10531-005-2352-5</li><li>Sridhar, H., & Sankar, K. 2008. <a href="https://doi.org/10.1017/S0266467408004823">Effects of habitat degradation on mixed-species bird flocks in Indian rain forests</a>. <i>Journal of Tropical Ecology</i> 24: 135-147. https://doi.org/10.1017/S0266467408004823</li><li>Surendra, A. & Raman, T. R. S. 2022. <a href="https://doi.org/10.1101/2022.10.22.513365">Forest bird decline and community change over 19 years in long-isolated South Asian tropical rainforest fragments</a>. Preprint. <i>BioRxiv</i> 2022.10.22.513365. https://doi.org/10.1101/2022.10.22.513365<br> </li></ul><p>A related dataset is the following:<br>Raman, T. R. S. (2020). Data from: Effects of Habitat Structure and Adjacent Habitats on Birds in Tropical Rainforest Fragments and Shaded Plantations in the Western Ghats, India. <i>Dryad Dataset.</i> https://doi.org/10.5061/dryad.4mw6m907q<br> </p><p><strong>Curation and corrections</strong></p><p>Data were collated, curated, and corrected before this upload. Besides addition of new columns, explanations of metadata, and other corrections included few related to canopy measurements, effective girth of multi-stem trees, and species identification.</p><p><strong>Acknowledgements</strong></p><p>We are grateful to P. Jeganathan and P. R. Shankar for assistance with data collection in 2000. Others who assisted with field research, and funding agencies related to the specific studies, are acknowledged in the above publications. The data compilation and publication was carried out as part of a grant from Fondation Franklinia to NCF.</p><p><br><strong>CONTACTS</strong><br> </p><p>CONTACT #1<br>1. Name: T. R. Shankar Raman<br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: trsr@ncf-india.org<br>5. ORCID: https://orcid.org/0000-0002-1347-3953</p><p>CONTACT #2<br>1. Name: Divya Mudappa<br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: divya@ncf-india.org<br>5. ORCID: https://orcid.org/0000-0001-9708-4826</p><p>CONTACT #3<br>1. Name: Hari Sridhar<br>2. Work Address: Wildlife Institute of India, Post Bag #18, Chandrabani, Dehradun – 248001, Uttarakhand, India; Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: harisridhar1982@gmail.com<br>5. ORCID: https://orcid.org/0000-0003-3286-0120</p><p>CONTACT #4<br>1. Name: Akshay Surendra<br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India; School of the Environment, Yale University, New Haven, CT – 06511, USA; New York Botanical Garden, 2900 Southern Blvd, Bronx, NY 10458<br>3. Work Phone: +91 821 2515601<br>4. Email address: akshaysurendra1@gmail.com<br>5. ORCID: https://orcid.org/0000-0003-2719-7432<br> </p><p><br><strong>GEOGRAPHIC COVERAGE</strong></p><p>1. Location/Study Area: Valparai Plateau, Tamil Nadu, India; Anamalai Tiger Reserve, Tamil Nadu, India</p><p>2. GPS coordinates: Valparai Plateau (10°15'- 10°22'N, 76°52' - 76°59'E); Anamalai Tiger Reserve (10°12' - 10°35'N, 76°49' - 77°24'E)</p><p><br><strong>TEMPORAL COVERAGE</strong></p><p>1. Begins: 2000-01-01 (Year, Month, Day)<br>2. Ends: 2019-12-31 (Year, Month, Day)</p><p><br><strong>METHODS</strong></p><p>Methods involved are described in the publications listed above. The vegetation sampling methods are briefly described below.</p><p>PCQ data: Trees ≥30cm girth at breast height (gbh, at 1.3 m) were sampled in replicate point-centred quarter (PCQ) points in each of the sites (fragments or coffee plantations).</p><p>All trees in the PCQ plots were identified to species, or in a few cases to genus, using available field guides. Using a tape measure, distance from plot centre to the middle of the bole and GBH were recorded for each tree. At each of the PCQ plots, circular plots were laid to enumerate shrubs and cut trees and record presence or absence of lianas, cane, Lantana etc as described in the metadata. Canopy and leaf litter variables were measured at replicate points, spaced 25 to 50 m apart, in each site. Elevation readings were also taken at these points using an altimeter or handheld GPS. Canopy height was measured using a rangefinder. Percentage canopy cover was measured using a spherical densiometer at each of the 25 points in each site. Vertical stratification was assessed by noting presence or absence of foliage in the following height intervals (in metres): 0–1, 1–2, 2–4, 4–8, 8–16, 16–24, 24–32, and > 32, directly above and in a 0.5 m radius around each point. Leaf litter depth on the forest floor was measured using a calibrated wooden probe at each point. Where ground vegetation and litter were disturbed along trails, the samples were taken away from trails in the forest floor.</p><p><br><strong>FILES INCLUDED</strong><br>Besides the 00_README.txt file that contains this metadata, the dataset includes the following 7 files, whose details and contents are explained below. (Wherever used in the various files, NA implies not available.)<br> </p><p><strong>01) sites.csv -- Details of study sites</strong><br>verbatimLocality: Name of locality as originally used<br>Fragment: Name of rainforest fragment or coffee plantation<br>decimalLongitude: Longitude in decimal degrees North (WGS 84 datum)<br>decimalLatitude: Latitude in decimal degrees East (WGS 84 datum)<br>habitat: Habitat type as mature tropical rainforest, tropical rainforest fragment, or coffee plantation<br>Description: Description of the place<br> </p><p><strong>02) allpcqdata.csv -- Tree data from point-centred quarter (PCQ) surveys</strong><br>Year: Year of survey for bird and vegetation study<br>verbatimLocality: Name of locality as originally used<br>Fragment: Name of rainforest fragment or coffee plantation<br>Point_name: Name ID of point-centred quarter (PCQ) point as used within a survey year<br>pointID: Unique ID of point-centred quarter (PCQ) point including year of survey<br>Tree_no: Tree number ID given to the four trees in each PCQ plot (T1 to T4)<br>verbatimIdentification: Scientific name of tree species as originally written or identified<br>scientificName: Scientific name as currently identified under updated taxonomy<br>nativeAlien: Category indicating whether species is native or alien to the region/country<br>kingdom: Taxonomic Kingdom<br>phylum: Taxonomic Phylum<br>Distance_eff: Distance in metres from centre of PCQ plot to centre of tree trunk<br>Girth_eff: Girth in centimetres (cm) at breast height (1.3 m) of the tree after correction (using appropriate formula) in the case of multi-stemmed individuals<br>locationRemarks: Code for site name as originally used<br>SpCode: Species code as originally used during data entry<br>TreeHeight: Tree height in metres (only available in 2019 survey)<br>identificationRemarks: Notes related to identification if available<br>occurrenceRemarks: Notes related to multi-stemmed individuals (girths in cm) if available and note on one possibly errorneous girth<br> </p><p><strong>03) pcqlocations.csv -- Locations of sample PCQ points</strong><br>pointID: Unique ID of point-centred quarter (PCQ) point including year of survey<br>note: Site name code<br>decimalLatitude: Latitude in decimal degrees East (WGS 84 datum)<br>decimalLongitude: Longitude in decimal degrees North (WGS 84 datum)<br>coordinateUncertaintyInMeters: Approximate uncertainty of the location in metres<br> </p><p><strong>04) allhabitat.csv -- Data on habitat structure variables</strong><br>Year: Year of survey for bird and vegetation study<br>verbatimLocality: Name of locality as originally used<br>Fragment: Name of rainforest fragment or coffee plantation<br>Point: ID of replicate survey point within the Fragment<br>0-1m: Presence (1) or absence (0) of foliage within 0.5 m of point in the vertical band 0-1 m above ground<br>1-2m: Presence (1) or absence (0) of foliage within 0.5 m of point in the vertical band 1-2 m above ground<br>2-4m: Presence (1) or absence (0) of foliage within 0.5 m of point in the vertical band 2-4 m above ground<br>4-8m: Presence (1) or absence (0) of foliage within 0.5 m of point in the vertical band 4-8 m above ground<br>8-16m: Presence (1) or absence (0) of foliage within 0.5 m of point in the vertical band 8-16 m above ground<br>16-24m: Presence (1) or absence (0) of foliage within 0.5 m of point in the vertical band 16-24 m above ground<br>24-32m: Presence (1) or absence (0) of foliage within 0.5 m of point in the vertical band 24-32 m above ground<br>over32m: Presence (1) or absence (0) of foliage within 0.5 m of point in the vertical band greater than 32 m above ground<br>VertStrata: Number of vertical strata with foliage (sum of preceding 8 columns)<br>CanopyHeight: Canopy height in metres<br>CanopyOpenness: Canopy openness in percentage as measured using a spherical densiometer<br>CanopyCover: Canopy cover (closure) in percentage as measured using a spherical densiometer<br>CanopyOverlap: Canopy overlap rank: 0-open sky above; 1-branches above barely touching; 2-overlapping branches above, sky visible; 3-overlapping branches, sky not visible<br>UC: Canopy overlap rank as above, for understorey vegetation only<br>MC: Canopy overlap rank as above, for the midstorey only<br>CC: Canopy overlap rank as above, for the upper canopy only<br>Altitude: Altitude above sea leavel in metres, measued from hand-held altimeter or GPS device<br>RfShrub: Number of shrubs (woody stems at least 1 m in height, GBH < 30 cm) within 2 m radius of point<br>Coffee: Number of coffee bushes (woody stems at least 1 m in height, GBH < 30 cm) within 2 m radius of point<br>Maesopsis: Number of alien Maesopsis eminii stems (woody stems at least 1 m in height, GBH < 30 cm) within 2 m radius of point<br>Strobilanthes: Number of Strobilanthes shrubs (woody stems at least 1 m in height, GBH < 30 cm) within 2 m radius of point<br>TotalShrub: Total number of shrubs within 2 m radius of point<br>Liana: Presence (1) or absence (0) of woody lianas within 5 m radius of point<br>Cane: Presence (1) or absence (0) of cane (Calamus sp.) within 2 m radius of point<br>Lantana: Presence (1) or absence (0) of Lantana camara shrubs within 2 m radius of point<br>Bamboo: Presence (1) or absence (0) of bamboo culms within 2 m radius of point<br>LeafLitter: Depth of leaf litter in cm (to 0.5 cm accuracy) measured using a calibrated wooden probe<br>CutTrees: Number of cut trees within 5 m radius of point<br> </p><p><strong>05) gbifnames.csv -- Results of GBIF name matching tool</strong><br>sno: Serial number<br>verbatimScientificName: Scientific name of tree species as originally written or identified<br>scientificName: Scientific name after matching with Global Biodiversity Information Facility (GBIF) database to lowest taxonomic level<br>sciNameWithAuthor: Scientific name with author as provided by GBIF name matching tool<br>key: GBIF key as provided by GBIF name matching tool<br>matchType: Type of match as provided by GBIF name matching tool<br>confidence: Confidence as provided by GBIF name matching tool<br>status: Status as accepted name or synonym as provided by GBIF name matching tool<br>rank: Taxonomic rank as provided by GBIF name matching tool<br>kingdom: Kingdom as provided by GBIF name matching tool<br>phylum: Phylum as provided by GBIF name matching tool<br>class: Class as provided by GBIF name matching tool<br>order: Order as provided by GBIF name matching tool<br>family: Family as provided by GBIF name matching tool<br>genus: Genus as provided by GBIF name matching tool<br>species: Species as provided by GBIF name matching tool<br>canonicalName: Canonical name as provided by GBIF name matching tool<br>authorship: Author of name as provided by GBIF name matching tool<br> </p><p><strong>06) plots2000.csv -- Data from 5 m radius circular plots in select sites</strong><br>verbatimLocality: Name of locality as originally used<br>Fragment: Name of rainforest fragment or coffee plantation<br>PlotID: ID of 5 m radius plot<br>Treeno: Serial number of tree in the plot<br>verbatimIdentification: Scientific name of tree species as originally written or identified<br>scientificName: Scientific name as currently identified under updated taxonomy<br>Girth_eff: Girth in centimetres (cm) at breast height (1.3 m) of the tree after correction (using appropriate formula) in the case of multi-stemmed individuals<br>nativeAlien: Category indicating whether species is native or alien to the region/country<br>kingdom: Kingdom as provided by GBIF name matching tool<br>phylum: Phylum as provided by GBIF name matching tool<br>occurrenceRemarks: Notes related to multi-stemmed individuals (girths in cm) if available and identification</p><p> </p><p><strong>07) anampcqs4gbif.rmd -- Text file with code in the R statistical and programming language</strong> </p><p>This R code was used for converting data in this Zenodo dataset into Darwin Core occurrence dataset for upload to the Global Biodiversity Information Facility (GBIF, https://www.gbif.org). The published dataset can now be accessed at: https://doi.org/10.15468/cmsveh</p><p> </p><p><strong>Changes in Version 2</strong></p><p>In sites.csv, changed habitat from "Rainforest" to "Tropical rainforest fragment" for Puthuthottam</p><p>Added the anampcqs4gbif.rmd file with R code</p>
Data and Code for "Why are generalists the 'winners' of habitat loss? Unveiling the process underlying specialist-generalist replacements in fragmented landscapes"
<p><span>Data and R-based workflow for the study "Why are generalists the ‘winners’ of habitat loss? Unveiling the process underlying specialist-generalist replacements in fragmented landscapes".</span></p>
Habitat fragmentation mite data, South Carolina, 2018
These csv files contain mite abundance and richness data, fungal abundance data, and leaf characteristics used in the paper "The impact of habitat fragmentation on domatia-dwelling mites and a mite-plant-fungus tritrophic interaction" published in Landscape Ecology in 2022. The project was conducted at the Savannah River Site, near Aiken, South Carolina, United States during the summer of 2018. The goal of the project was to assess the impacts of landscape-level habitat fragmentation on communities of mites and fungi on leaf surfaces growing on Quercus nigra oak trees within landscape patches. To investigate this, we counted and morphotyped mites found on leaves taken from oaks located in habitat patches manipulated to have different edge-to-area ratios and connectivity statuses. We also manipulated mite access to domatia on oak leaves using a tar treatment, and assessed whether mite exclusion and landscape fragmentation variables influenced levels of fungal hyphae on oak leaves. We found a significant positive effect of patch edge proximity on mite abundance and richness, as well as fungal hyphae abundance, indicating that landscape-level habitat fragmentation can impact microscopic foliar communities.
Seed dispersal data for Warneke et al "Habitat fragmentation alters the distance of abiotic seed dispersal through edge effects and direction of dispersal"
This csv file contains seed dispersal data for five species (Carphephorus bellidifolius, Aristida beyrichiana, Liatris squarrulosa, Sorghastrum secundum, and Anthenantia villosa). Data were collected at the Savannah River Site, near Aiken, South Carolina, United States. Data were collected between November 17, 2009, to January 22, 2010 and were collected using the methods outlined in this document.
Fig. 2 in Autumn habitat selection of the harvest mouse (Micromys minutus Pallas, 1771) in a rural and fragmented landscape
Fig. 2. Map representing the study area and the different habitat types present in it. The Caricteum acutiformis patch in the North is the main tall sedge meadow, where most of the study was conducted. The transects (red lines) shown on this map were the ones used for trapping (i.e., for the Capture, Mark and Release event).
Fig. 7 in Autumn habitat selection of the harvest mouse (Micromys minutus Pallas, 1771) in a rural and fragmented landscape
Fig. 7. Relocations of the four male individuals M1, M2, M3 and M4. M1 was tracked from the 19th to the 21th of September 2017. M2 was tracked from the 06th to the 10th of October 2017. M3 was tracked from the 15th to the 19th of October 2017. M4 was tracked from the 15th to the 17th of October 2017.
Data and modeling results for publication: Landscape genetics indicate recently increased habitat fragmentation in African forest-associated chafers
<ul> <li>DNA sequences: <em>cox1</em> and ITS1 alignments</li> <li>spatial records (in hypervolume archive)</li> <li>spatial principal component 1-3 used for <em>hypervolume</em> models (in hypervolume archive)</li> <li>Present and past species distribution models (SDMs): <ul> <li><em>biomod2</em> ensemble SDMs <ul> <li>Present</li> <li>Holocene Altithermal</li> <li>Last Glacial Maximum</li> </ul> </li> <li><em>biomod2</em> SDMs for single PMIP3 models <ul> <li>Present</li> <li>Holocene Altithermal</li> <li>Last Glacial Maximum</li> </ul> </li> <li><em>hypervolume</em> SDMs</li> </ul> </li> <li>landscape connectivity models <ul> <li>circuitscape (for F0, F1, and F2)</li> <li>least cost corridors and paths (for F0, F1, and F2)</li> </ul> </li> </ul>
Overcoming confusion and stigma in habitat fragmentation research - supplementary data and R code
<p>Data and code necessary to produce results and figures for the manuscript:</p> <p>Riva, Koper and Fahrig (2024). "Overcoming confusion and stigma in habitat fragmentation research". Biol Rev. Accepted conditional on minor revisions. </p>
Stable species and interactions in plant-pollinator networks deviate from core position in fragmented habitats
<p><span>S</span><span>pecies</span><span> and their interactions are more dynamic over time and space</span> <span>in</span><span> fragmented habitats </span><span>than</span><span> in continuous habitats</span><span>.</span> <span>In fragmented habitats,</span><span> the</span> <span>low </span><span>nestedness</span> <span>of </span><span>mutualistic</span><span> networks may be related to the</span> <span>position</span><span> change</span> <span>of stable (high persistence over time/space) species and interactions in </span><span>the</span><span> network</span><span>s.</span><span> Previous studies</span> <span>have shown that </span><span>s</span><span>table species </span><span>and</span><span> interactions tend to </span><span>be in</span><span> the core position </span><span>of</span> <span>mutualistic</span><span> networks</span><span>. </span><span>H</span><span>owever</span><span>, </span><span>in fragmented habitats</span><span>, </span><span>it remains unknown whether </span><span>stable species or interactions still </span><span>tend to </span><span>be in</span><span> the core position.</span><span> </span><span>To address this gap,</span> <span>here</span><span> we evaluated </span><span>the correlation between the position of proximity to the network core and the temporal/spatial stability of </span><span>species and interactions</span><span>, </span><span>using</span> <span>the </span><span>observation of 42 plant-pollinator networks conducted in a fragmented island landscape over 3 years</span><span>.</span> <span>We showed that temporally/spatially </span><span>stable </span><span>species </span><span>and</span><span> interactions </span><span>deviated from the network core</span><span> to varying degrees</span><span>. Temporally stable plants</span><span> were</span> <span>most likely to deviate from the network core, followed by</span> <span>pollinators and</span> <span>interactions</span><span>, while only </span><span>spatially stable </span><span>pollinators</span><span> tend to </span><span>deviate from the network core</span><span>. </span><span>When unstable species (</span><span>present in few time/space points</span><span>, </span><span>typically specialists) and interactions occupy the network core,</span> <span>they cannot interact with most species in the network </span><span>as</span><span> generalists</span> <span>do</span><span>, </span><span>result</span><span>ing</span> <span>in</span> <span>the</span> <span>decrease of network nestedness. Therefore, from the perspective of</span><span> position and stability,</span><span> s</span><span>table species and interactions </span><span>deviate from the network core</span> <span>in</span> <span>fragmented habitats</span><span>, which </span><span>is an important reason for</span><span> the</span><span> decrease of</span><span> nestedness in </span><span>mutualistic</span><span> networks</span><span>.</span><span> </span><span>Our study</span><span> suggests that protecting</span> <span>plants that</span><span> occupy the core in large plant-pollinator networks is </span><span>essential for</span> <span>maintaining the network persistence in fragmented habitats.</span></p>
Source code and data from: Foraging personalities modify effects of habitat fragmentation on biodiversity
<p><span>Habitat loss undeniably poses a substantial threat to biodiversity, but whether fragmentation per se drives the loss of species is still widely debated. While negative consequences from fragmentation are often anticipated, many empirical studies report positive effects. However, the intrinsic mechanisms governing species' persistence in fragmented landscapes are not yet understood. In this study, we investigated consistent personality-dependent differences in foraging behavior among individuals as a possible mechanism underlying the discrepancy of reported fragmentation effects. </span><span>We </span><span>devised a mechanistic individual-based model simulating the home range behavior of a competitive small mammal community based on the availability of a shared resource. Thereby, an individual's risk-taking behavior dictates its foraging decisions at risky habitat edges, an inherent property of fragmentation per se. Our simulations show that differences in risk-taking while foraging are potentially a further mechanism contributing to reconciling the fragmentation debate. The first scenario considering risk-seeking communities showed a neutral response towards fragmentation, while the second scenario featuring risk-avoiding communities confirmed the negative effects of fragmentation. Notably, the third scenario, simulating behaviorally diverse communities including risk-avoiding and risk-seeking individuals, demonstrated a positive influence of fragmentation on biodiversity. Intraspecific differences in behavior could also enhance the temporal species coexistence (coviability) of communities threatened by an ongoing habitat loss. Our study highlights the importance of recognizing the behavioral composition of populations and communities for estimating fragmentation effects, because differences in risk-taking can influence the coping abilities of animal communities in light of fragmentation.</span></p>
Dataset belonging to Fragmented micro-growth habitats present opportunities for alternative competitive outcomes
<p>This Dataset contains the raw data, processed data and script/code underlying the results and figures presented in the manuscript "Fragmented micro-growth habitats present opportunities for alternative competitive outcomes", (deposited at BioRXiv 10.1101/2024.01.26.577336)</p> <p>by: Maxime Batsch<sup>1</sup>, Isaline Guex<sup>2</sup>, Helena Todorov<sup>1</sup>, Clara M. Heiman<sup>1</sup>, Jordan Vacheron<sup>1</sup>, Julia A. Vorholt<sup>3</sup>, Christoph Keel<sup>1</sup>, and Jan Roelof van der Meer<sup>1*</sup></p> <p>1) Department of Fundamental Microbiology, University of Lausanne, CH-1015 Lausanne, Switzerland</p> <p>2) Department of Mathematics, University of Fribourg, CH-1700 Fribourg, Switzerland</p> <p>3) Institute for Microbiology, Swiss Federal Institute of Technology (ETH Zürich), CH-8049 Zürich, Switzerland</p> <p>The raw data consists of microscopy droplet/cell image data, 96-well plate reader data, and flow cytometry cell counts.<br>Processed data are organised by Figure in the manuscript and/or the Supplementary figures belonging to the manuscript. Figure folders contain the main output, the input data, the code and scripts to produce the output from the input, and relevant statistical tests.</p>
Data archive for 'Convolutional neural networks facilitate river barrier detection and evidence severe habitat fragmentation in the Mekong River biodiversity hotspot'
<p>This repository contains the code and databases used in the paper 'Convolutional neural networks facilitate river barrier detection and evidence severe habitat fragmentation in the Mekong River biodiversity hotspot'. </p> <p>The 'Mekong River Barrier Database (MRBD)' folder contains the basin-scale barrier database developed in this study. This database contains more than 13,000 unique barriers, which were identified by using the convolutional neural networks-based object detection method from Google Earth’s satellite imagery.</p> <p>The 'FCOS' folder contains the barrier detection model (FCOS ResNext-101-FPN), trained for detecting river barriers from remotely sensed images within the MMDetection framework. The 'FCOS_x101_v2' folder contains the enhanced FCOS model.</p> <p>The 'R_script' folder contains R files used in the paper. Coordinate.R was used to extract coordinates from bounding boxes in each TIF image. CAFI.R was used to calculate the CAFI index in each sub-catchment.</p> <p>The 'Barrier image training set' folder contains over 10,000 river barrier satellite images and their associated JSON files, forming the 'training, validation, and test datasets' used during the model training process. This dataset is made available to the user community in raw, in the hope that others will contribute to its future development, thereby enhancing its use and utility.</p> <p>For more information on the MMDetection framework, refer to the following GitHub repository: <a href="https://github.com/open-mmlab/mmdetection">https://github.com/open-mmlab/mmdetection</a></p>
Fig. 7 in A comparative exploration of the inquiline and prey species of Nepenthes rafflesiana pitchers in contiguous and fragmented habitat patches in Singapore
Fig. 7. Box and whisker (a, d) and scatter (b, c) plots showing the relationships between the inquiline species richness of individual pitchers and pitcher type (a), pitcher size (b), canopy cover (c), and location (within or outside of the CCNR; d). The plots show that inquiline species richness was higher in lower than upper pitchers (a), and pitcher size (b) and canopy cover (c) had weak positive effects on inquiline species richness, but there was no significant difference in inquiline species richness between pitchers outside of and within the Central Catchment Nature Reserve (CCNR) (d). In (a) and (d), boxes represent interquartile ranges, whiskers represent maxima and minima, and points represent outliers. In (b) and (c), points (green = lower, beige = upper pitchers) represent the species richness of individual pitchers, and lines represent the model predictions of the second (b; ΔAICc = 1.94) and third (c; ΔAICc = 1.99) best models for lower (green) and upper (beige) pitchers.
Fig. 11 in A comparative exploration of the inquiline and prey species of Nepenthes rafflesiana pitchers in contiguous and fragmented habitat patches in Singapore
Fig. 11. Scanning electron microscope (SEM) photographs exemplifying morphological differences in the chelicerae of Nepenthes histiostomatid mites: (a) Creutzeria sp., (b) Zwickia sp., (c) Nepenthacarus sp. Scale bar = 10 micrometres. (Photographs by: Norman J. Fashing).
Fig. 3 in A comparative exploration of the inquiline and prey species of Nepenthes rafflesiana pitchers in contiguous and fragmented habitat patches in Singapore
Fig. 3. Two-dimensional NMDS plot of the plant communities co-occurring with Nepenthes rafflesiana in plots located within (brown points) and outside (pink points) of the CCNR (a), and box and whisker plot comparing the log-transformed floristic species richness of these locations (b). Plant communities differed significantly in composition (a; pseudo-F1,11 = 3.80, p-value <0.001) and species richness (b; T11 = 4.74, p-value = 0.001). Each point in the NMDS plot (a) represents the plant communities of a single plot. Colours are translucent, so that overlapping points may be distinguished. Points which are located closer to each other in the NMDS plot share more similar plant communities. Texts represent plant species centroids, with font sizes proportional to the number of plots in which each was found (species which were found in two or less plots are not displayed). A species is more likely to occur in a plot if the plot's point is located close to the species' centroid. Bold lines in the box and whisker plot represent median log-transformed species richness, boxes represent interquartile ranges, whiskers represent maxima/minima and points represent outliers.
Fig. 6 in A comparative exploration of the inquiline and prey species of Nepenthes rafflesiana pitchers in contiguous and fragmented habitat patches in Singapore
Fig. 6. Box and whisker plots show that inquiline taxa were found in different abundances across the different forest types, with several species being confined to the old secondary forests within the Central Catchment Nature Reserve (CCNR). Bold horizontal lines represent median log-transformed number of each inquiline taxon in pitchers from each forest type (denoted by colours); boxes represent interquartile range; whiskers represent maximum values. Taxon names are abbreviated as done in the previous figure; rare inquiline taxa which were present in only one sample are not displayed.
Fig. 2 in A comparative exploration of the inquiline and prey species of Nepenthes rafflesiana pitchers in contiguous and fragmented habitat patches in Singapore
Fig. 2. Habitat types in which Nepenthes rafflesiana plants were found in this study: (a) coastal cliffs; (b) adinandra belukar; (c) old secondary forests (in this case, a tree fall gap within an old secondary forest). Nepenthes rafflesiana plants are indicated by an arrow in panels a and c. Coastal cliffs (a) and adinandra belukar (b) type habitats were mainly found outside the Central Catchment Nature Reserve (CCNR), while old secondary forests type habitats were only found within the CCNR. Despite their different locations, plant communities in which N. rafflesiana were found in coastal cliff habitats (a) and typical adinandra belukar habitats (b) were compositionally highly similar and may both be classified as adinandra belukar type plant communities. (Photographs by: Lam Weng Ngai).
Fig. 1 in A comparative exploration of the inquiline and prey species of Nepenthes rafflesiana pitchers in contiguous and fragmented habitat patches in Singapore
Fig. 1. Nepenthes rafflesiana lower (a) and upper (b) pitchers in situ; location of the Central Catchment Nature Reserve (CCNR) in Singapore (c). Data sources for (c): Singapore Public Data (https://data.gov.sg); Global Administrative Areas Database version 3.6 (https:// gadm.org/data.html). (Photographs by: Lam Weng Ngai).
Fig. 5 in A comparative exploration of the inquiline and prey species of Nepenthes rafflesiana pitchers in contiguous and fragmented habitat patches in Singapore
Fig. 5. Sample-size- (a) and coverage-based (b) rarefaction curves of inquiline species richness from pitchers collected outside of (pink lines) and within (brown lines) the Central Catchment Nature Reserve (CCNR). Lines represent the interpolated (continuous) and extrapolated (dashed) species richness of each forest type, as a function of the number of individuals sampled within it (a) and the estimated sample coverage (b); shaded regions represent the 95% confidence intervals of these estimates; points represent the observed species richness (these are omitted from panel b to prevent the obscuring of other details in the figure).
Fig. 4 in A comparative exploration of the inquiline and prey species of Nepenthes rafflesiana pitchers in contiguous and fragmented habitat patches in Singapore
Fig. 4. Two-dimensional NMDS plot of the pitcher inquiline communities of the sampled Nepenthes rafflesiana pitchers. Each point represents an inquiline community from an individual pitcher, with its colour denoting the location in which it was found (within [brown] or outside [pink] the Central Catchment Nature Reserve [CCNR]), and its shape denoting its pitcher type (triangles denote upper, and circles, lower, pitchers). Texts represent inquiline species centroids, with font sizes proportional to the number of pitchers in which each was found. A species is more likely to occur in a pitcher if the pitcher's point is located close to the species' centroid. Taxon name abbreviations: Dasy = Dasyhelea spp.; Phor = Phoridae; Ar.giv = Armigeres giveni; Ar.kuc = Ar. cf. kuchingensis; Cx.bre = Culex brevipalpus complex; Cx.cur = Cx. curtipalpis; Tp.tnx = Tripteroides tenax; Lest = Lestodiplosis sp.; Nsyr = Nepenthosyrphus sp. raff; Creu = Creutzeria spp.; M2.sp1 = Histiostomatidae genus 1 sp. 1; Naca = Nepenthacarus spp.; Zwic = Zwickia spp.; Nema = nematodes.
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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.