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129 results for “Biodiversity change”
Data from: Proportional mixture of two rarefaction/extrapolation curves to forecast biodiversity changes under landscape transformation
Progressive habitat transformation causes global changes in landscape biodiversity patterns, but can be hard to quantify. Rarefaction/extrapolation approaches can quantify within‐habitat biodiversity, but may not be useful for cases in which one habitat type is progressively transformed into another habitat type. To quantify biodiversity patterns in such transformed landscapes, we use Hill numbers to analyse individual‐based species abundance data or replicated, sample‐based incidence data. Given biodiversity data from two distinct habitat types, when a specified proportion of original habitat is transformed, our approach utilises a proportional mixture of two within‐habitat rarefaction/extrapolation curves to analytically predict biodiversity changes, with bootstrap confidence intervals to assess sampling uncertainty. We also derive analytic formulas for assessing species composition (i.e. the numbers of shared and unique species) for any mixture of the two habitat types. Our analytical and numerical analyses revealed that species unique to each habitat type are the most important determinants of landscape biodiversity patterns.
Data from: How do different aspects of biodiversity change through time? A case study on an Australian bird community
The study of ecological communities through time can reveal fundamental ecological processes and is key to understanding how natural and human pressures will affect biodiversity. Most studies of ecological communities through time consider only one or a few summary measures (e.g. species richness, total abundance), which might neglect important aspects of community structure or function. We studied temporal variation in several measures of species diversity, size diversity, and species composition in an intensively sampled bird community to determine whether different biodiversity measures change synchronously. We used a novel function regression model, which supports the study of diversity measures that are distributions (e.g. species abundance distributions) alongside measures that are scalar values (e.g. species richness). Most diversity measures changed predictably within years, but inter-annual changes in size diversity and species composition were not reflected in species diversity. Within and among years, there was considerable variation in distributional measures that was not captured in scalar measures. Predictable variation within years probably was related to seasonal variation in weather patterns or food availability, but variation in size diversity among years probably resulted from stochastic changes in species composition. These results suggest that species and size diversity may be decoupled, and that inferences on scalar diversity measures might not reflect fundamental changes to community structure or function. Our method supports the inclusion of size-based measures and distributional measures in ecological analyses, and broader uptake of our approach is likely to provide new insight into the processes structuring ecological communities, and inform the links between structure and function in ecological communities.
Selected data sets for Marsh et al. 2024 'Tropical forest clearance impacts biodiversity and function whereas logging changes structure'
<p>Data sets used in the for the manuscript <strong>Marsh<em> </em>et<em> </em>al. 2024 'Tropical forest clearance impacts biodiversity and function whereas logging changes structure'</strong>. The DOIs that link to all other data sets used in the publication are available in Tables S2-5 of the supplementary information. The z-score standardised data, and outputs of RMarkdown documents outline all the steps in the processing and analysis of the data are available at https://zenodo.org/uploads/13161799.</p> <p> </p> <p>This repository contains data used for:</p> <h3><strong><em>Mean canopy height</em></strong></h3> <p>Canopy height and vertical profiles of forest structure were compiled using airborne remote sensing with LiDAR collected by NERC’s Airborne Research Facility (ARF) in November 2014, using a Leica ALS50-II LiDAR. A Beer-Lambert approximation was used to convert point clouds to plant area density (PAD) distributions, a similar measure to leaf-area index, but where methods do not distinguish between leaves and branches or trunks. LiDAR measurements for the carbon plots were converted to rasters with 0.5 × 0.5 m cell size. Plots were rotated to a North-South axis if necessary</p> <h3><br><em><strong>Spectral diversity</strong></em></h3> <p>Spectral measurements were made on five leaves attached to tree branches used to measure leaf chemical traits. Leaves were randomly selected but we avoided damaged and young plant material to avoid potential confounding factors. Reflectance spectra (350–2500 nm) were acquired using a FieldSpec 4, produced by Analytical Spectral Devices (ASD, Boulder, Colorado, USA). The spectroradiometer's contact probe was mounted on a clamp and firmly pushed down onto the sample against a black background so that no extraneous light was included in the measurement. Spectral measurements were taken halfway between the petiole and leaf tip, and between the main vein and the leaf edge, with the abaxial surface pointing towards the probe. The readings were calibrated against a Spectralon white reference panel every five samples. Leaf reflectance measured at 430 nm, 660 nm, 1450, 1980 nm and 2350 nm align closely with absorption features for pigments, water content, proteins and cellulose. Spectral diversity calculated from these absorption features can provide an integrated measure of the functional trait variability within plant communities and may be used as a proxy for functional diversity.</p> <p> </p> <h3><em><strong>Liana abundance</strong></em></h3> <p>Percentage liana cover for large canopy and emergent trees. The four quadrants of the canopy were scored as 0 (no lianas), 1 (1-20%), 2 (20-40%), 3 (40-60%), 4 (60-80%) and 5 (80-100%).</p> <p> </p> <h3><em><strong>Leaf-area index<br></strong></em></h3> <p>Leaf area index (LAI) for carbon plots was derived from hemispherical photos (Sigma 8mm SRL fish eye lens and Canon EOS 600D digital camera, mounted on a tripod at 1 m height). Between 5-27 photos were taken over time in each subplot. Images were processed with Hemisfer® software (www.wsl.ch/dienstleistungen/produkte/software/hemisfer/index_EN). LAI was calculated with the method by Thimonier et <em>al</em>. (2010) <em>European Journal of Forest Research</em> 129, 543–562 (2010), with a canopy clumping correction applied from Chen & Cihlar (1995) <em>IEEE Transactions on Geoscience and Remote Sensing</em> 33, 777–787.</p> <p> </p> <h2>Funding</h2> <p>Analyses were carried out, and data were collected, as part of the BALI (Biodiversity And Land-use Impacts on tropical ecosystem function) using the following funding:</p> <ul> <li>NERC's Human Modified Tropical Forests research programme (grant number NE/K016377/1 awarded to the BALI consortium)</li> <li>MHN was supported by a PhD scholarship from the Conselho Nacional de Pesquisa e Desenvolvimento (CNPq, grant No. 201516/2014-4) from Brazil</li> </ul>
Supplementary material 1 from: Fernandez D, Millán A, Rizzo V, Comas J, Lleopard E, Pastor J, Pallarés S, Abellán P, Spada M, Bilton DT, Ribera I (2018) The CAVEheAT project: climate change, thermal niche and conservation of subterranean biodiversity. ARPHA Conference Abstracts 1: e30105. https://doi.org/10.3897/aca.1.e30105
The CAVEheATproject: climate change, thermal niche and conservation of subterranean biodiversity
Data from: How do different aspects of biodiversity change through time? A case study on an Australian bird community
Open the record for dataset details and reuse information.
Data from: Proportional mixture of two rarefaction/extrapolation curves to forecast biodiversity changes under landscape transformation
Open the record for dataset details and reuse information.
Fig. 5 in How might sea level change affect arthropod biodiversity in anchialine caves: a comparison of Remipedia and Atyidae taxa (Arthropoda: Altocrustacea)
Fig. 5 Scatterplot of the distances of cave openings from the current coastline and the coastline 18,000 years ago during the last glacial maximum. Analysis limited to caves in regions where both remipedes and atyid shrimp co-occur (Table 2). Box in the lower corner of (a) is enlarged to show finer scale remipede distributions in (b). Regressions. (a) Shrimp: y = 0.2376x+10.0617, r 2 =0.4297; Neither: y =0.2610x +9.0827, r 2 = 0.4568. (b) Remipede: y =- 0.3130x+0.3040, r 2 =0.6379
Fig. 2 in How might sea level change affect arthropod biodiversity in anchialine caves: a comparison of Remipedia and Atyidae taxa (Arthropoda: Altocrustacea)
Fig. 2 Atyid species richness in (a) the Yucatan Peninsula, (b) the Caribbean, (c) southern Europe, (d) Australia, and (e) global species richness. Species richness by cave correlates with the size of white circles. For (e), only the caves with the highest richness in the region are shown. The present-day coastlines are outlined in black, and the
Nutrient enrichment changes species composition, taxonomic and functional diversity in a global biodiversity hotspot
<p>This data set was presented in the article "Nutrient enrichment changes species composition, taxonomic and functional diversity in a global biodiversity hotspot", by Castro and collaborators. </p><p>We collected plant traits from a Brazilian savanna known as Cerrado. </p>
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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.