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53 results for “ecological methods”
Creating multi-themed ecological regions for macroscale ecology: Testing a flexible, repeatable, and accessible clustering method
This dataset was created for the following publication: Cheruvelil, K.S., S. Yuan, K.E. Webster, P.-N. Tan, J.-F. Lapierre, S.M. Collins, C.E. Fergus, C.E. Scott, E.N. Henry, P.A. Soranno, C.T. Filstrup, T. Wagner. Under review. Creating multi-themed ecological regions for macrosystems ecology: Testing a flexible, repeatable, and accessible clustering method. Submitted to Ecology and Evolution July 2016. This dataset includes lake total phosphorus (TP) and Secchi data from summer, epilimnetic water samples, as well as 52 geographic variables at the HU-12 scale; it is a subset of the larger LAGOS-NE database (Lake multi-scaled geospatial and temporal database, described in Soranno et al. 2015). LAGOS-NE compiles multiple, individual lake water chemistry datasets into an integrated database. We accessed LAGOSLIMNO version 1.054.1 for lake water chemistry data and LAGOSGEO version 1.03 for geographic data. In the LAGOSLIMNO database, lake water chemistry data were collected from individual state agency sampling and volunteer programs designed to monitor lake water quality. Water chemistry analyses follow standard lab methods. In the LAGOSGEO database geographic data were collected from national scale geographic information systems (GIS) data layers. The dataset is a subset of the following integrated databases: LAGOSLIMNO v.1.054.1 and LAGOSGEO v.1.03. For full documentation of these databases, please see the publication below: Soranno, P.A., E.G. Bissell, K.S. Cheruvelil, S.T. Christel, S.M. Collins, C.E. Fergus, C.T. Filstrup, J.F. Lapierre, N.R. Lottig, S.K. Oliver, C.E. Scott, N.J. Smith, S. Stopyak, S. Yuan, M.T. Bremigan, J.A. Downing, C. Gries, E.N. Henry, N.K. Skaff, E.H. Stanley, C.A. Stow, P.-N. Tan, T. Wagner, K.E. Webster. 2015. Building a multi-scaled geospatial temporal ecology database from disparate data sources: Fostering open science and data reuse. GigaScience 4:28 doi:10.1186/s13742-015-0067-4 .
Optimizing sampling across methods improves the power of ecological monitoring data
Transect-based monitoring has long been a valuable tool in ecosystem monitoring. These transects are often used to measure multiple ecosystem attributes. The line-point intercept (LPI), vegetation height, and canopy gap intercept methods comprise a set of core methods, which provide indicators of ecosystem condition. However, users struggle to design a sampling strategy that optimizes the ability to detect ecological change using transect-based methods. We assessed the sensitivity of these core methods on a one-hectare plot to transect length, number, and sampling interval to determine: 1) minimum sampling required to describe ecosystem characteristics and detect change for each method and 2) optimal transect length and number for all three methods to make recommendations for future analyses and monitoring efforts. We used data from 13 National Wind Erosion Research Network locations spanning the western US, which included 151 measurements over time across five biomes. We found that longer and increased numbers of transects were more important for reducing sampling error than increased sample intensity along transects. For all methods and indicators across plots, three 100-m transects reduced sampling error so that indicator estimates fall within an 95% confidence interval of +/- 5% for canopy gap intercept and LPI-total foliar cover, +/- 5 cm for height and +/- two species for LPI-species counts. For the same criteria at 80% confidence intervals, two 100-m transects are needed. Site-scale inference was strongly affected by sample design, consequently our understanding of ecological dynamics may be influenced by sampling decisions.
Text-fig. 9. Phylogenetic tree indicating the number of required character state changes (steps) under parsimony for various positions of Miranthus gen. nov. in a molecular based backbone tree (see material and methods for additional details). in Early Flowers Of Primuloid Ericales From The Late Cretaceous Of Portugal And Their Ecological And Phytogeographic Implications
Text-fig. 9. Phylogenetic tree indicating the number of required character state changes (steps) under parsimony for various positions of Miranthus gen. nov. in a molecular based backbone tree (see material and methods for additional details).
F I G U R E 3 in The future of fish-based ecological assessment of European rivers: from traditional EU Water Framework Directive compliant methods to eDNA metabarcoding-based approaches
F I G U R E 3 Comparison of trait-based metrics expressed in relative number of individuals computed from eDNA () and traditional electro-fishing (TEF;) samples in the five river stretches (RS), A, B, C, D and E. Trait categories: BEN, benthic; EUR, eurytopic; INS, insectivorous; OMN, omnivorous; PHY, phytophilic; POT, potamodromous; RHE, rheophilic; TOL, tolerant; PEL pelagic. Significance of the differences between eDNA and TEF metrics are shown: ns, not significant (P> 0.05)
F I G U R E 4 in The future of fish-based ecological assessment of European rivers: from traditional EU Water Framework Directive compliant methods to eDNA metabarcoding-based approaches
F I G U R E 4 Boxplots (, median value;, interquartile range;, full range;, outliers) showing the variability in the eDNAadapted fish index (six metrics) computed at three sites (Brangues, Rhins and Usses) where 10 eDNA water samples were collected once. At each site, the eDNA-based six-metric fish index was computed for each of the 45 possible pairs of samples
F I G U R E 2 in The future of fish-based ecological assessment of European rivers: from traditional EU Water Framework Directive compliant methods to eDNA metabarcoding-based approaches
F I G U R E 2 Comparison of trait-based metrics expressed in number of species computed from eDNA () and traditional electrofishing (TEF;) samples in the five river stretches (RS), A, B, C, D and E. Trait categories: BEN, benthic; EUR, eurytopic; INS, insectivorous; OMN, omnivorous; PHY, phytophilic; POT, potamodromous; RHE, rheophilic; TOL, tolerant; PEL pelagic. Significance of the differences between eDNA and TEF metrics are shown: P <0.05; P <0.01; ns, not significant (P> 0.05)
F I G U R E 1 in The future of fish-based ecological assessment of European rivers: from traditional EU Water Framework Directive compliant methods to eDNA metabarcoding-based approaches
F I G U R E 1 Sampling locations along river stretches (RS) A to E () of the main channel of the Rhône River, France, using both traditional electro-fishing (TEF) and eDNA., Sites sampled every 2 months (September 2015– August 2016);, sites where ten eDNA water samples (filtration capsules) were collected once;, sites located on the tributaries or the Rhône River itself sampled once for eDNA. The 10 metric fish index and the adapted six-metric fish index were computed at all sites with a black filled symbol within natural water bodies
The fungal ecology of the Brassington Formation (Middle Miocene) of Derbyshire, UK, and a new method for palaeoclimate reconstruction
<p>Köppen-Geiger climate class data used to reconstruct qualitative palaeoclimates. Two sheets in file. Sheet 1: Köppen-Geiger data used to reconstruct Middle Miocene Köppen-Geiger climate classes. Sheet 2: References supporting sheet 1.</p>
Supporting data for Guzzo et al. 2018, Methods in Ecology and Evolution, DOI: 10.1111/2041-210X.12993
<p>Supporting data for Guzzo et al. MEE, Field testing a novel high residence positioning system for monitoring the fine‐scale movements of aquatic organisms (DOI: 10.1111/2041-210X.12993)</p>
Combining epidemiological and ecological methods to quantify social effects on E. coli transmission
<p>Enteric microparasites like <i>Escherichia coli</i> utilize multiple transmission pathways to propagate within and between host populations. Characterizing the relative transmission risk attributable to host social relationships, and direct physical contact between individuals is paramount for understanding how microparasites like <i>E. coli </i>spread within affected communities and estimating colonization rates. To measure these effects, we carried out commensal <i>E. coli</i> transmission experiments in two cattle (<i>Bos taurus</i>) herds, wherein all individuals were equipped with real-time location tracking devices. Following transmission experiments in this model system, we derived temporally dynamic social and contact networks from location data. Estimated social affiliations, and dyadic contact frequencies during transmission experiments informed pairwise accelerated failure time models that we used to quantify effects of these sociobehavioral variables on weekly <i>E. coli</i> colonization risk in these populations. We found that sociobehavioral variables alone were ultimately poor predictors of <i>E. coli</i> colonization in feedlot cattle, but can have significant effects on colonization hazard rates (<i>p </i>≤ 0.05). We show, however, that observed effects were not consistent between similar populations. This work demonstrates that transmission experiments can be combined with real-time location data collection and processing procedures to create an effective framework for quantifying sociobehavioral effects on microparasite transmission.</p>
Quantifying animal social behaviour with ecological field methods
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Combining epidemiological and ecological methods to quantify social effects on E. coli transmission
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Integration of genomic and ecologic methods inform management of an undescribed, yet highly exploited, sardine species
<p>Assessing genetic diversity within species is key for conservation strategies in the context of human-induced biotic changes. This is important in marine systems where many species remain undescribed while being overfished, and conflicts between resource-users and conservation agencies are common. Combining niche modelling with population genomics can contribute to resolving those conflicts by identifying management units and understanding how past climatic cycles resulted in current patterns of genetic diversity. We addressed these issues on an undescribed but already overexploited species of sardine of the genus <em>Harengula</em>. We find that the species distribution is determined by salinity and depth, with a continuous distribution along the Brazilian mainland and two disconnected oceanic archipelagos. Genomic data indicates that such biogeographic barriers are associated with two divergent intraspecific lineages. Changes in habitat availability during the last glacial cycle led to different demographic histories among stocks. One coastal population experienced a 3.6-fold expansion, whereas an island-associated population contracted 3-fold, relative to the size of the ancestral population. Our results indicate that the island population should be managed separately from the coastal population, and that a Marine Protected Area covering part of the island population distribution can support the viability of this lineage.</p>
AngleCam publication data (Methods in Ecology and Evolution, MEE)
<p>These datasets were the basis for the study Kattenborn et al. 2022 published in Methods in Ecology and Evolution (MEE).</p> <p>The dataset includes:<br> - leaf_angle_reference_data: The image data with corresponding leaf angle distributions derived from visual interpretation. Note, that not for each image reference data exists. The corresponding scripts will only select data with available labels.<br> - leaf_angle_predictions_canopy_crane: The predictions obtained using AngleCam for the image time series recorded at the canopy crane. The raw image data amounts to several hundreds of gigabytes and can be obtained from the corresponding author.<br> - environmental_variables: The environmental variables recorded at the Leipzig Canopy Crane recorded in 2021 in 10 minute intervals. The folders lak1*, lak2* and lak3* correspond to consecutive periods (lak1 was recorded before lak2 and so forth). These predictions can be merged according to their time stamp.</p> <p>Questions can be addressed to Teja Kattenborn: https://rsc4earth.de/authors/tkattenborn/</p> <p>The trained models and further ressources are available under: </p> <pre>https://doi.org/10.5281/zenodo.6812085</pre>
Data supplementing the article "Avoiding quantification bias in metabarcoding: application of a cell biovolume correction factor in diatom molecular biomonitoring" V. Vasselon, A. Bouchez, F. Rimet, S. Jacquet, R. Trobajo, M. Corniquel, K. Tapolczai, I. Domaizon submitted to Methods in Ecology and Evolution journal
<p>These data supplement the article "Avoiding quantification bias in metabarcoding: application of a cell biovolume correction factor in diatom molecular biomonitoring" V. Vasselon, A. Bouchez, F. Rimet, S. Jacquet, R. Trobajo, M. Corniquel, K. Tapolczai, I. Domaizon submitted to Methods in Ecology and Evolution journal</p> <p>The directory contains the following files:</p> <p>1<strong>5 fastq files raw reads (5 mock communities, 3 replicates)</strong><strong>.rar </strong>- contains the 15 fastq files provided by the sequencing platform with demultiplexed DNA reads (raw data prior any bioinformatics treatments).</p> <p><strong>15 fastq files information.xlsx</strong> :</p> <p>- contains the information relative to the 15 fastq files corresponding to the PGM raw data of the 5 mock communities (sequenced with 3 replicates), including: the ID of the fastq files, the mock community name, the replicate number, the final sample Id and the number of raw reads per fastq file.</p> <p>- contains the information of the proportion of the 8 diatoms species (%) used to create the 5 mock communities (estimated from microscopy).</p>
Time series methods for cyclical ecological data
<p>Biodiversity monitoring has entered an era of `big data', exemplified by a near-continuous collection of sounds, images, chemical, and other signals from organisms in diverse ecosystems. Such data streams have the potential to help identify new threats, assess the effectiveness of conservation interventions, as well as generate new ecological insights. However, appropriate analytical methods are often still missing, particularly with respect to characterizing cyclical temporal patterns. Here, we present a framework for characterizing and analyzing ecological responses that represent nonstationary, complex temporal patterns and demonstrate the value of using Fourier transforms to decorrelate continuous data points. In our example, we use a framework based on three approaches (spectral analysis, magnitude squared coherence, and principal component analysis) to characterize differences in tropical forest soundscapes within and across sites and seasons in Gabon. By reconstructing the underlying, cyclic behavior of the soundscape for each site, we show how one can identify circadian patterns in acoustic activity. Soundscapes in the dry season had a complex diel cycle, requiring multiple harmonics to represent daily variation, whilst in the wet season there was less variance attributable to the daily cyclic patterns. Our framework can be applied to most continuous, or near-continuous ecological data collected at a fine temporal resolution, allowing ecologists to explore patterns of temporal autocorrelation at multiple levels for biologically meaningful trends. Such methods will become indispensable as biological big data are used to understand the impact of anthropogenic pressures on biodiversity and to inform efforts to mitigate them.</p>
Seasonal footprints on ecological time series and jumps in dynamic states of protein configurations from a nonlinear forecasting method characterization (DataSet)
<p>Data from the article: <br>"Seasonal footprints on ecological time series and jumps in dynamic states of protein configurations from a nonlinear forecasting method characterization", L. Reyes, K. Campos, G. D. Avendaño, L. González-Paz, A. Vivas, Y. J. Alvarado, and S. Flores.</p> <p>Data to be used with some implementation of the forecasting method of reference:<br>Sugihara G. and May R. M., Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series, <em>Nature</em> <strong>344</strong>, 734–741 (1990).</p>
R code and simulation output for Efford, M. G. & Boulanger, J. 2019. Fast evaluation of study designs for spatially explicit capture-recapture. Methods in Ecology and Evolution
<p>R code and simulation output for Efford, M. G. & Boulanger,<br> J. 2019. Fast evaluation of study designs for spatially explicit<br> capture-recapture. Methods in Ecology and Evolution In press.</p> <p>R code draws on previously published R packages 'secr' and 'secrdesign' available from CRAN:</p> <p><a href="https://CRAN.R-project.org/package=secr">https://CRAN.R-project.org/package=secr</a></p> <p><a href="https://CRAN.R-project.org/package=secrdesign">https://CRAN.R-project.org/package=secrdesign</a></p>
Use of geolocators for investigating breeding ecology of a rock crevice-nesting seabird: method validation and impact assessment
<p>1: Investigating ecology of marine animals, imposes a continuous challenge due to their temporal and/or spatial unavailability. Light-based geolocators (GLS) are animal-borne devices that provide relatively cheap and efficient method to track seabird movement and are commonly used to study migration. Here we explore the potential of GLS data to establish individual behaviour during the breeding period in a rock crevice-nesting seabird, the Little Auk, Alle alle. 2: By deploying GLS on 12 breeding pairs, we developed a methodological workflow to extract birds' behaviour from GLS data (nest attendance, colony attendance and foraging activity), and validated its accuracy using behaviour extracted from a well-established method based on video recordings. We also compared breeding outcome, as well as behavioural patterns of logged individuals with a control group treated similarly in all aspects except for the deployment of a logger, to assess short-term logger effects on fitness and behaviour. 3: We found a high accuracy of GLS-established behavioural patterns, especially during the incubation and early chick rearing period (when birds spend relatively long time in the nest). We observed no apparent effect of logger deployment on breeding outcome of logged pairs, but recorded some behavioural changes in logged individuals (longer incubation bouts and shorter foraging trips). 4: Our study provides a useful framework for establishing behavioural patterns (nest attendance and foraging) of a crevice-nesting seabird from GLS data (light and conductivity), especially during incubation and early chick rearing period. Given that GLS deployment does not seem to affect the breeding outcome of logged individuals but does affect fine-scale behaviour, our framework is likely to be applicable to a variety of crevice/burrow nesting seabirds, even though precautions should be taken to reduce deployment effect. Finally, because each species may have its own behavioural and ecological specificity, we recommend performing a pilot study before implementing the method in a new study system.</p>
Data from: Inferring the locomotor ecology of two of the oldest fossil squirrels: Influence of operationalisation, trait, body size, and machine learning method
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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.