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122 results for “ecological approach”
The data used for the paper "Adapting a multiscale approach to assess the compositional diversity of landscapes" (Landscape Ecology)
<p>The data consists of a single SimpleFeatures (sf) object with 267,813 rows, i.e. hexagons covering Hungary, and 89 variables. The following variables are contained by the data (Table 1.).</p> <table> <caption>Table 1. Main attributes of the variables. For explanation of the vegetation type codes implied in the table by "XX", see the Supplementary Material S2 of Konrád et al. 2023.</caption> <thead> <tr> <th scope="col">Variable</th> <th scope="col">Description</th> </tr> </thead> <tbody> <tr> <td>id</td> <td>unique id of hexagons</td> </tr> <tr> <td>Bakony</td> <td>logical mask for subsetting the landscape Bakony</td> </tr> <tr> <td>Baranya</td> <td>logical mask for subsetting the landscape Baranya Hills</td> </tr> <tr> <td>ExternalSomogy</td> <td>logical mask for subsetting the landscape External Somogy</td> </tr> <tr> <td>HunGreatPlain</td> <td>logical mask for subsetting the landscape Hungarian Great Plain</td> </tr> <tr> <td>KorosMarosInterfluve</td> <td>logical mask for subsetting the landscape Körös-Maros Interfluve</td> </tr> <tr> <td>Mezofold</td> <td>logical mask for subsetting the landscape Mezőföld & Velence Hills</td> </tr> <tr> <td>NorthernHunMountains</td> <td>logical mask for subsetting the landscape Northern Hungarian Mountains</td> </tr> <tr> <td>Orseg</td> <td>logical mask for subsetting the landscape Őrség</td> </tr> <tr> <td>SouthernBukk</td> <td>logical mask for subsetting the landscape Southern Bükk</td> </tr> <tr> <td>binarized_potential_XX</td> <td>binarized potential vegetation data of the XX vegetation type</td> </tr> <tr> <td>binarized_actual_XX</td> <td> <p>binarized potential vegetation data of the XX vegetation type</p> </td> </tr> </tbody> </table> <p> </p> <p><strong>References</strong><br> Konrád KD, Bede-Fazekas Á, Bartha S, Somodi I (2023) Adapting a multiscale approach to assess the compositional diversity of landscapes. <em>Landscape Ecology.</em></p> <p> </p>
Data from: Genomic, ecological, and morphological approaches to investigating species limits: a case study in modern taxonomy from Tropical Eastern Pacific surgeonfishes
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An innovative approach combining metabarcoding and ecological interaction networks for selecting candidate biological control agents
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An ecological network approach to assessing the site suitability of photovoltaic power stations
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Data from: A new null model approach to quantify performance and significance for ecological niche models of species distributions
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The evolutionary ecology of primate hair coloration: a phylogenetic approach
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Behaviour across time and space–how large scale ‘trait-based’ approaches can shape behavioural ecology
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Codes: A new approach to interspecific synchrony in population ecology using tail association
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Dataset for: An optimisation approach for designing wildlife corridors with ecological and spatial considerations
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Data from: Assessing niche conservatism using a multiproxy approach: dietary ecology of extinct and extant spotted hyenas
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Data from: Comparisons of quantitative approaches for assessing microglial morphology reveal inconsistencies, ecological fallacy, and a need for standardization
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Ecological patterns of root nodule diversity in cultivated and wild rooibos populations: a community prediction approach
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Data for Characterizing the spatial signal of environmental DNA in river systems using a community ecology approach
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Diversity patterns along ecological succession in tropical dry forests: A multi-taxonomic approach
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A machine learning approach to integrating genetic and ecological data in tsetse flies (Glossina pallidipes) for spatially explicit vector control planning
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Data from: Comparing traditional and Bayesian approaches to ecological meta-analysis
<p>1. Despite the wide application of meta-analysis in ecology, some of the traditional methods used for meta-analysis may not perform well given the type of data characteristic of ecological meta-analyses.</p> <p>2. We reviewed published meta-analyses on the ecological impacts of global climate change, evaluating the number of replicates used in the primary studies (ni) and the number of studies or records (k) that were aggregated to calculate a mean effect size. We used the results of the review in a simulation experiment to assess the performance of conventional frequentist and Bayesian meta-analysis methods for estimating a mean effect size and its uncertainty interval.</p> <p>3. Our literature review showed that ni and k were highly variable, distributions were right-skewed, and were generally small (median ni =5, median k=44). Our simulations show that the choice of method for calculating uncertainty intervals was critical for obtaining appropriate coverage (close to the nominal value of 0.95). When k was low (<40), 95% coverage was achieved by a confidence interval based on the t-distribution that uses an adjusted standard error (the Hartung-Knapp-Sidik-Jonkman, HKSJ), or by a Bayesian credible interval, whereas bootstrap or z-distribution confidence intervals had lower coverage. Despite the importance of the method to calculate the uncertainty interval, 39% of the meta-analyses reviewed did not report the method used, and of the 61% that did, 94% used a potentially problematic method, which may be a consequence of software defaults.</p> <p>4. In general, for a simple random-effects meta-analysis, the performance of the best frequentist and Bayesian methods were similar for the same combinations of factors (k and mean replication), though the Bayesian approaches had higher than nominal (>95%) coverage for the mean effect when k was very low (k<15). Our literature review suggests that many meta-analyses that used z-distribution or bootstrapping confidence intervals may have over-estimated the statistical significance of their results when the number of studies was low; more appropriate methods need to be adopted in ecological meta-analyses.</p>
Data from: Reconstructing long-term human impacts on plant communities: an ecological approach based on lake sediment DNA
Paleoenvironmental studies are essential to understand biodiversity changes over long timescales and to assess the relative importance of anthropogenic and environmental factors. Sedimentary ancient DNA (sedaDNA) is an emerging tool in the field of paleoecology and has proven to be a complementary approach to the use of pollen and macroremains for investigating past community changes. SedaDNA-based reconstructions of ancient environments often rely on indicator taxa or expert knowledge, but quantitative ecological analyses might provide more objective information. Here, we analysed sedaDNA to investigate plant community trajectories in the catchment of a high-elevation lake in the Alps over the last 6400 years. We combined data on past and present plant species assemblages along with sedimentological and geochemical records to assess the relative impact of human activities through pastoralism, and abiotic factors (temperature and soil evolution). Over the last 6400 years, we identified significant variation in plant communities, mostly related to soil evolution and pastoral activities. An abrupt vegetational change corresponding to the establishment of an agropastoral landscape was detected during the Late Holocene, approximately 4500 years ago, with the replacement of mountain forests and tall-herb communities by heathlands and grazed lands. Our results highlight the importance of anthropogenic activities in mountain areas for the long-term evolution of local plant assemblages. SedaDNA data, associated with other paleoenvironmental proxies and present plant assemblages, appear to be a relevant tool for reconstruction of plant cover history. Their integration, in conjunction with classical tools, offers interesting perspectives for a better understanding of long-term ecosystem dynamics under the influence of human-induced and environmental drivers.
Data from: From pristine forests to high-altitude pastures: an ecological approach to prehistoric human impact on vegetation and landscapes in the western Italian Alps
1. This paper addresses the origin and development of the oldest prehistoric pasture in the timberline ecotone known so far in the Alps and its relation to anthropogenic pressure and natural climate change. 2. Paleoecological and geochemical techniques were applied on the Crotte Basse mire stratigraphy (2365 m asl, western Italy) to describe changes in vegetation composition, forest biomass, land use and fertilization between ca. 6400 - 1800 yrs cal BP. 3. Subalpine forests dominated by Pinus cembra occurred at very high-altitude up to ca. 5600 yrs cal BP, when a sharp contraction of woody vegetation took place. This major vegetation shift is matched by increasing charcoal input and markers of pastoral/grazing activities (pollen, dung spores, and forms of phosphorus) in the sediment sequence in this small basin. 4. Major phases of landscape change detected in our multiproxy record chronologically match intervals of cumulative probability density of 14C ages from nearby archaeological sites, suggesting that human activity was the factor leading to massive landscape change from the onset of the Copper Age (ca. 5600 yrs cal BP). The change may have been reinforced by climate variability in the period 5700 - 5300 years cal BP. 5. Sensitivity of woody species to fires was statistically explored (Appendix S3 in Supporting Information), revealing negative reactions of Pinus cembra and Betula to frequent fire episodes and positive reactions of Alnus viridis and Juniperus. Fire episodes do not affect Larix dynamics. 6. Synthesis: Mt. Fallère provides some of the oldest and consistent evidence so far available in the Alps for major anthropogenic pressure at the upper forest limit. As far back as 5600 cal years BP, high-elevation forest ecosystems were permanently disrupted and the alpine pastures were created. Palaeoecological data enable a clear distinction between a random and sporadic use of the alpine space, typical for Mesolithic and Neolithic societies, and an organized seasonal exploitation of natural resources, starting from the Copper Age onwards. The chronological comparison of independent climate proxies, paleoecological information and pollen-based temperature reconstructions sheds light on the relationships between climate and humans since prehistoric times.
Data from: Examining the full effects of landscape heterogeneity on spatial genetic variation: a multiple matrix regression approach for quantifying geographic and ecological isolation
Understanding the effects of landscape heterogeneity on spatial genetic variation is a primary goal of landscape genetics. Ecological and geographic variables can contribute to genetic structure through geographic isolation, in which geographic barriers and distances restrict gene flow, and ecological isolation, in which gene flow among populations inhabiting different environments is limited by selection against dispersers moving between them. Although methods have been developed to study geographic isolation in detail, ecological isolation has received much less attention, partly because disentangling the effects of these mechanisms is inherently difficult. Here, I describe a novel approach for quantifying the effects of geographic and ecological isolation using multiple matrix regression with randomization. I explored the parameter space over which this method is effective using a series of individual-based simulations and found that it accurately describes the effects of geographic and ecological isolation over a wide range of conditions. I also applied this method to a set of real-world datasets to show that ecological isolation is an often overlooked but important contributor to patterns of spatial genetic variation and to demonstrate how this analysis can provide new insights into how landscapes contribute to the evolution of genetic variation in nature.
Data from: Parallel tagged next-generation sequencing on pooled samples – a new approach for population genetics in ecology and conservation
Next-generation sequencing (NGS) on pooled samples has already been broadly applied in human medical diagnostics and plant and animal breeding. However, thus far it has been only sparingly employed in ecology and conservation, where it may serve as a useful diagnostic tool for rapid assessment of species genetic diversity and structure at the population level. Here we undertake a comprehensive evaluation of the accuracy, practicality and limitations of parallel tagged amplicon NGS on pooled population samples for estimating species population diversity and structure. We obtained 16S and Cyt b data from 20 populations of Leiopelma hochstetteri, a frog species of conservation concern in New Zealand, using two approaches – parallel tagged NGS on pooled population samples and individual Sanger sequenced samples. Data from each approach were then used to estimate two standard population genetic parameters, nucleotide diversity (π) and population differentiation (FST), that enable population genetic inference in a species conservation context. We found a positive correlation between our two approaches for population genetic estimates, showing that the pooled population NGS approach is a reliable, rapid and appropriate method for population genetic inference in an ecological and conservation context. Our experimental design also allowed us to identify both the strengths and weaknesses of the pooled population NGS approach and outline some guidelines and suggestions that might be considered when planning future projects.
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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.
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
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.