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2,045 results for “Plan S”
PA 2017 ACS Congressional Districting Plans via SFSR
<p>11,206 Congressional redistricting plans for Pennsylvania, using the 2017 American Community Survery (ACS) census data, and</p> <p>assuming 17 districts. All generated with an implementation of the SFSR algorithm, originated by the author.</p>
Five States with SFSR, 1000 plans each: PA, MI, WI, NC, AZ
<p>1000 Congressional redistricting plans each for five states: AZ, PA, NC, MI, WI. Using 2018 American Community Survey (ACS) data.</p> <p>Produced by the Seed-Fill-Shift-Repair (SFSR) algorithm.</p>
Data from: Evaluating the potential for bird-habitat models to support biodiversity-friendly urban planning
<ol> <li>Urban expansion poses a major threat to wildlife populations. Biodiversity-friendly urban landscapes could deliver benefits for both wildlife and people, by incorporating conservation and ecosystem services objectives. Well-designed urban developments could also soften the ecological impacts of urbanisation. However, delivering urban landscapes that integrate biodiversity requirements effectively remains challenging.</li> <li>Ecological models, designed to predict wildlife population responses to alternative urban designs, could prove effective in supporting the creation of biodiversity-friendly urban landscapes. Here, we combine national-scale bird abundance data with high resolution, spatially explicit habitat data to characterise relationships between bird densities and urban landscape form in Britain. From these analyses and cross-validation, we evaluate the potential for well-parameterised, species-specific models to be used to predict bird densities in novel or modified urban areas.</li> <li>Our analyses indicate that responses of bird abundance to urban habitat are species-specific and complex, with few variables consistently affecting a large proportion of species. However, contiguous areas of greenspace within urban sites are preferential for accommodating breeding birds, compared to a more fragmented arrangement of multiple, small greenspace patches. In combination, the bird-habitat relationships identified could successfully predict observed variation in abundance for most bird species considered.</li> <li>Further evaluation of habitat descriptor variables, spatial scales of species' habitat use and analytical modelling approaches may be needed to improve the predictive ability of bird-habitat models for certain species, particularly waterbirds and those observed less frequently in urban areas.</li> <li> <i>Synthesis and applications.</i> We modelled breeding bird abundance in built-up areas with respect to the characteristics and contexts of urban environments. While most variables were important for multiple species, responses overall were species-specific, so simple assemblage metrics, like diversity, will not describe the variation in bird communities well. However, the results illustrate the potential of an evidence-based, spatially explicit evaluation of urban development impacts on biodiversity, by predicting the consequences for bird numbers. Subject to verification of predictive ability, practitioners can apply the models to compare, for example, land-sparing and sharing within developments, or to quantify the biodiversity requirements for effective offsetting. This would be facilitated by incorporation into an online tool allowing user-determined input scenarios.</li> </ol>
Literature on Cloud Capacity Planning
<p>This release captures the state-of-the-art (as of 2020) in cloud capacity planning literature and provides a set of complementary scripts to analyze this literature. The dataset which is central to this release (<code>publications.yaml</code>) maps 57 cloud capacity planning approaches as published in literature to the taxonomy on cloud capacity planning which the authors of this release have proposed. The approaches were gathered with a systematic literature survey process, aggregating multiple common sources and executing a set of automated and manual filtering steps.</p> <p><strong>Taxonomy</strong></p> <p>The taxonomy and the process used to derive it is described in detail in the MSc Thesis of Georgios Andreadis at Delft University of Technology (to be published end of August 2020), on cloud capacity planning. We describe the taxonomy here to provide context to the raw data.</p> <p>The taxonomy divides the process underlying capacity planning systems into the following categories:</p> <ol> <li>System Model <ul> <li>Workloads</li> <li>Resources</li> <li>Model Inputs</li> </ul> </li> <li>Forecast Model <ul> <li>Modeling Strategy</li> <li>Model Structure</li> </ul> </li> <li>Decision Support <ul> <li>Role</li> <li>Type of Advice</li> <li>Advice Method</li> </ul> </li> </ol> <p>For each of these categories, the taxonomy prescribes a set of possible <em>classes</em> (possible instantiations of the category). We list these for each category, below, preceded by its abbrevation as appearing in the dataset:</p> <ol> <li>System Model <ul> <li>Workloads <ul> <li><code>VM</code>: Virtual Machines</li> <li><code>DB</code>: Databases</li> <li><code>S</code>: Streaming Workloads</li> <li><code>BD</code>: Big Data Frameworks</li> <li><code>WS</code>: Web Service</li> <li><code>B</code>: Batch Jobs</li> </ul> </li> <li>Resources <ul> <li><code>C</code>: Compute Hardware</li> <li><code>S</code>: Storage Hardware</li> <li><code>N</code>: Network Hardware</li> <li><code>E</code>: Energy Hardware (Storage and Supply)</li> <li><code>H</code>: Heat Control Hardware</li> <li><code>V</code>: Virtualized Resources (VM, containers, etc.)</li> </ul> </li> <li>Model Inputs <ul> <li><code>H</code>: Historical Data</li> <li><code>RS</code>: Resource Specifications</li> <li><code>B</code>: (Micro)Benchmarks or Systematic Performance Tests</li> <li><code>S</code>: SLAs</li> <li><code>P</code>: Pricing Data</li> <li><code>LC</code>: Lease Contracts</li> <li><code>HP</code>: Human Personnel-related Factors</li> </ul> </li> </ul> </li> <li>Forecast Model <ul> <li>Modeling Strategy <ul> <li><code>A</code>: Analytical</li> <li><code>S</code>: Simulation</li> <li><code>E</code>: Real-world Experimentation</li> </ul> </li> <li>Model Structure <ul> <li><code>U</code>: Unconditional Extrapolation</li> <li><code>W</code>: What-if Scenarios</li> </ul> </li> </ul> </li> <li>Decision Support <ul> <li>Role <ul> <li><code>F</code>: Forecast</li> <li><code>A</code>: Adaptation Advice</li> </ul> </li> <li>Type of Advice <ul> <li><code>N</code>: Number of Resources</li> <li><code>T</code>: Type of Resources</li> <li><code>L</code>: Locality of Resources</li> </ul> </li> <li>Advice Method <ul> <li><code>H</code>: Heuristic</li> <li><code>R</code>: Regression</li> <li><code>L</code>: Local Search</li> <li><code>SS</code>: Stochastic Search</li> <li><code>SP</code>: Stochastic Programming</li> <li><code>NN</code>: Neural Network</li> <li><code>GT</code>: Game Theory</li> <li><code>GA</code>: Genetic Algorithm</li> <li><code>NLP</code>: (Non)Linear Programming</li> </ul> </li> </ul> </li> </ol> <p><strong>File Structure</strong></p> <p>This release is structured as follows:</p> <ul> <li><code>publications.yaml</code>: This is the dataset of mappings of publications to the taxonomy. Each item in the array represents a publication, with a set of true-false classifications per category for each class. <ul> <li>The <code>id</code> field of each publication identifies the publication (first-author and publication year).</li> <li>The <code>summary</code> field of each publication summarizes the publication in a short sentence.</li> <li>The <code>classification</code> field contains a set of true-false classifications per category for each class.</li> <li>The <code>notes</code> field is an optional field containing any additional notes kept by the author of this dataset on their classification, in the case where doubts arose during the classification process.</li> </ul> </li> <li><code>taxonomy.py</code>: Script which parses the YAML dataset into different CSV views per category, to facilitate meta-analysis. Also prints out a full (long-table) representation of the mappings.</li> <li><code>taxonomy_analysis.py</code>: Jupyter notebook which contains several meta-analysis processing steps, including trend, cluster, and correlation analysis.</li> <li><code>README.md</code>: A file containing this description.</li> </ul>
Types of planning systems and effects on construction material volumes: An explanatory analysis in Europe
<p>The primary aim of this study is to assess the effect of the spatial governance and planning on the utilization of construction materials, based on a panel of 35 European countries between 1995 and 2017. Additionally, the influence of core socio-economic characteristics, namely the GDP per capita, urbanization, and economic structure is assessed as well.</p> <p>https://doi.org/10.1016/j.landusepol.2021.105682</p>
Randomized control trial of SMS for postpartum behaviors and family planning in Kiambu County, Kenya
<p><strong>Background </strong></p> <p>It is estimated that one third of maternal deaths in Kenya in 2014 could have been prevented by more timely care-seeking. Mobile health interventions are increasingly being recognized as tools for the delivery of health education and promotion. Many maternal deaths occur in the first few weeks after delivery and mothers who are given adequate care in the postpartum period have better health outcomes. Kiambu County, Kenya has a high level of literacy and phone ownership amongst mothers delivering in public hospitals and was chosen as a site for a postpartum short message service intervention. </p> <p><strong>Methods </strong></p> <p>Women were recruited after delivery and randomized to receive a package of mobile messages or standard of care only. Messages covered danger signs, general postpartum topics, and family planning. Endline phone surveys were conducted at 8 weeks postpartum to assess knowledge, care seeking behavior and family planning uptake. Analysis was conducted using Stata and is presented in odds ratios. </p> <p><strong>Results </strong></p> <p>Women who received the danger sign messages were 1.6 times more likely to be able to list at least 1 danger sign and 3.51 times more likely to seek treatment if they experienced postpartum danger signs. There was no significant difference in routine postpartum care seeking or care seeking behaviors concerning newborns. Women who received family planning messages were 1.85 times more likely to uptake family planning services compared to controls and 2.1 times more likely to choose a longacting method.</p> <p><strong>Conclusions </strong></p> <p>Simple, low-cost mobile interventions can support women in the early postpartum period when the information is targeted to particular points in the postpartum continuum. Additional research is needed to understand the interplay between healthcare providers and mobile health interventions. Health policy makers should consider direct mobile interventions for women as an option for supporting positive maternal health outcomes in certain populations.</p>
Learning to plan with uncertain topological maps: Dataset
<p>Dataset for training and evaluation of neural path planning algorithms, for the paper "Learning to Plan with Uncertain Topological Maps"</p> <p><a href="https://arxiv.org/abs/2007.05270">https://arxiv.org/abs/2007.05270</a></p>
WikiHow Planning recipes Dataset: Code companion for KEPS 2020
<p>This is the dataset as used by the paper "Planning Domain Generation from Natural Language Step-by-Step Instructions", published in KEPS 2020.</p>
Data from: The value of time-series data for conservation planning
<ol> <li>Protected areas (PAs) are increasingly being used worldwide for the conservation and management of wildlife. Systematic conservation planning (SCP) aims at ensuring biodiversity persistence while minimizing the threats faced by the species and/or the economic costs related to protection. To account for spatio-temporal interactions between species and human threats, conservation planning for mobile wildlife requires time-series data derived from monitoring of species and human threats, a process that is costly and technically challenging. Therefore, assessments of the monitoring period needed to ensure sufficient data input in the design of efficient, adequate and representative networks of PAs are crucial.</li> <li>We demonstrated the value of time-series data in conservation planning by implementing SCP and data from different monitoring periods to identify priority conservation areas for highly mobile marine megafauna accounting for their main threat: commercial fishing. Two analyses of ten reserve-design scenarios each, replicated as many times as the data composing each scenario permitted were run in Marxan. The best solutions of the planning scenarios were statistically compared using the Cohen`s Kappa test. We also assessed differences in spatial similarity among and within scenarios using the Wilcoxon non-parametric test and a non-metric multidimensional scaling analysis. Finally, we compared the necessary cost and the area selected for each scenario.</li> <li>Our study highlights the importance of time-series ecological and socioeconomic data for the robust selection of priority conservation areas. The results revealed different thresholds of the minimum temporal data required to design efficient networks of PAs for highly mobile species, demonstrating that the incorporation of data covering longer periods to the scenarios produce a more robust selection of priority conservation areas. Conservation plans using data covering less than three years were missing important priority areas.</li> <li> <i>Synthesis and applications. </i>We provide a method for estimating the minimum number of years of monitoring required to design efficient networks of protected areas that ensure the persistence of highly mobile species such as cetaceans and seabirds. This method can be used within an adaptive management framework to evaluate whether a network of PAs performs as planned, and to test whether management strategies should be altered or adjusted in response to local and global changes.</li> </ol>
Conservation planning across realms: enhancing connectivity for multi-realm species
<p>Connectivity plays a key role in biodiversity conservation as it sustains ecological processes important for the maintenance of populations such as migrations. Connectivity is especially relevant for species that rely on different realms during their life cycle or use different realms daily or seasonally (multi-realm species). However, effort to address conservation across multiple realms have focused on identifying priority areas for conservation in a single realm (mostly marine) accounting for threats propagating from other realms or single species needs. Here, we demonstrate how to identify priority areas for conservation across three different realms (freshwater-terrestrial, estuary and marine) for multiple species, including some multi-realm species, that inhabit or move across the three realms. We use the whole Tagus River Basin, its estuary and nearby marine area as a case study. We compared the allocation of priority areas and spatial connectivity achieved under three scenarios: no-connectivity, within-realm and cross-realm connectivity scenarios. There were some differences in the spatial allocation of priority areas across scenarios. The most remarkable difference laid on the connectivity achieved under each scenario, which experienced a 3-fold increase when considering connectivity across realms, compared to solutions that considered only connectivity within each realm independently. This improvement in connectivity was especially marked for some of the species that occur across the three realms. There were, however, trade-offs between this improvement in connectivity: i) an increase in the number of planning units selected, especially in the estuary, the realm that links the other two; and ii) a decline in connectivity achieved within the freshwater—terrestrial and marine realms. Synthesis and applications: Addressing connectivity across realms deserves especial attention when planning for conservation of multi-realm species to ensure adequacy of conservation recommendations to respond to the needs of these species. Given the potential trade-offs between enhanced cross-realm connectivity and total area needed or internal within-realm connectivity, consideration of cross-realm connectivity must be cautiously evaluated and integrated in multi-realm conservation plans.</p>
Predictive genetic plan for a captive population of the Chinese goral (Naemorhedus griseus) and prescriptive action for ex situ and in situ conservation management in Thailand
<p>Captive breeding programs for endangered species can increase population numbers for eventual reintroduction to the wild. Captive populations are typically small and isolated, which results in inbreeding and reduction of genetic variability, and may lead to an increased risk of extinction. The Omkoi Wildlife Breeding Center maintains the only Thai captive Chinese goral (<i>Naemorhedus griseus</i>) population, and has plans to reintroduce individuals into natural isolated populations. Genetic variability was assessed within the captive population using microsatellite data. Although no bottleneck was observed, genetic variability was low (allelic richness = 7.091 ± 0.756, <i>H</i><sub>e</sub> = 0.455 ± 0.219; <i>H</i><sub>e</sub> < <i>H</i><sub>o</sub>) and 11 microsatellite loci were informative that likely reflect inbreeding. Estimates of small effective population size and limited numbers of founders, combined with wild-born individuals within subpopulations, tend to cause reduction of genetic variability over time in captive programs. This leads to low reproductive fitness and limited ability to adapt to environmental change, thereby increasing the risk of extinction. Management of captive populations as evolutionarily significant units with diverse genetic backgrounds offers an effective strategy for population recovery. Relocation of individuals among subpopulations, or introduction of newly captured wild individuals into the captive program will help to ensure the future security of Chinese goral. Implications for future conservation actions for the species are discussed herein.</p>
Combining seascape connectivity with cumulative impact assessment in support of ecosystem-based marine spatial planning
<p>1. Cumulative impact assessment (CIA) is a promising approach to guide marine spatial planning (MSP) and management. One limitation of CIA is the neglect of seascape connectivity, which may spread the impact of localised pressures to ambient areas, e.g. through lost dispersal and recruitment of organisms.</p> <p>2. We here, for the first time, incorporate seascape connectivity into a traditional CIA model using a connectivity matrix, exemplified by dispersal of propagules estimated through biophysical modelling. Two <i>connectivity impacts</i>are identified: the <i>source impact</i> represents downstream areas losing recruits because of reduced larval dispersal from sites affected by the pressure, and the <i>sink impact</i> represents loss of recruits originating from upstream areas prevented from settlement in the site affected by the local pressure.</p> <p>3. By including seascape connectivity into the Swedish MSP-guiding CIA tool Symphony we demonstrate how to practically account for remote effects of local environmental impact. Our example on blue mussel shows how reducing mussel fitness in a given area may have impacts on mussels far from the acting pressures. Overall, results indicate that connectivity impact for blue mussels plays a minor role in most areas, less than 10% of the ordinary cumulative impact. However, in some smaller areas, e.g. on offshore banks and the Danish Straits, seascape connectivity may increase ordinary cumulative impact with 20-30%. In an example of scenario-based CIA analyses of MSP projections, we demonstrate how impacts of particular management actions, e.g. shipping rerouting and wind power developments, can be tracked far from the original area of influence.</p> <p>4. Depending on the dispersal ability of ecosystem components, a local pressure may impact a considerable area through seascape connectivity, transgressing management units and national borders. Although the mean connectivity impact may be modest for a single ecosystem component, the consideration of seascape connectivity across multiple ecosystem components may significantly alter the mapping of cumulative impact and the assessment of different MSP scenarios.</p> <p>5. Synthesis and applications.<span><span><span><span><span><span><span><span><span><span><span> Our extension of Cumulative Impact Assessment offers a new method for mapping and practically integrating seascape connectivity with ecosystem-based MSP and other spatial instruments for policy making, such as marine protected areas.</span></span></span></span></span></span></span></span></span></span></span></p>
Bibliometric assessment of marine spatial planning publications (2003-2019)
<p>Dataset of marine spatial planning (MSP) publications for the period 2003 - 2019.</p>
A Conceptual Model Framework for Analyzing, Simulating, Planning and Controlling of Supply-Demand Matching of Ecosystem Services in Agricultural Landscapes
<p>The video gives an explanation of our conceptual approach for the investigation of the adaptation of societal demands for ecosystem services in agricultural landscapes.</p>
Combining conservation status and species distribution models for planning assisted colonisation under climate change
<p>Effects of climate change are particularly important in the Mediterranean Biodiversity hotspot where rising temperatures and drought are negatively affecting several plant taxa, including endemic species. Assisted Colonisation (AC) represents a useful tool for reducing the effect of climate change on endemic plant species threatened by climate change.</p> <p>We combined SDMs for 188 taxa endemic to Italy with the IUCN red listing range loss threshold under criterion A (30%) to define: a) the number of AC (measured as 2×2 km grid cells that should be occupied by new populations, that is grid cells = new populations) required to fully compensate for predicted range loss and to halt the decline below the 30% of range loss; b) The number of cells necessary to compensate for range loss was calculated as the number of currently occupied cells lost under future climate due to unsuitable conditions. We used two Representative Concentration Pathways, +2.6 and +8.5 W/m2, optimistic and pessimistic scenarios, respectively. Availability of suitable areas for AC was also assessed within the current species distribution and within protected areas.</p> <p>Under the optimistic scenario, no taxa would lose more than 30% of their range and AC would not be required. Under the pessimistic scenario, roughly 90% of taxa showed a cell loss higher than 30%. Eight taxa were predicted to lose >95% of their range. For these species, AC was required from 13 to 16 new populations (= 13 to 16 grid cells) per taxon to cap the range loss at 30%. For currently VU or EN species, an average number of 32 to 35 AC attempts would be necessary to fully compensate for their range loss under a pessimistic scenario. Suitable recipient sites within protected areas falling in their projected range were identified, allowing for short-distance AC.</p> <p>Synthesis. Combining SDMs and red listing thresholds under Criterion A has enabled the strategic planning of multiple-species AC minimising the effort in terms of new populations to be created and maximising the conservation benefit in terms of range loss compensation.</p>
Using genomic information for management planning of an endangered perennial, Viola uliginosa
Species occupying habitats subjected to frequent natural and/or anthropogenic changes are a challenge for conservation management. We studied one such species, Viola uliginosa, an endangered perennial wetland species typically inhabiting sporadically flooded meadows alongside rivers/lakes. In order to estimate genomic diversity, population structure and history, we sampled five sites in Finland, three in Estonia, and one each in Slovenia, Belarus, and Poland using genomic SNP data with double-digest restriction site associated DNA sequencing (ddRAD-seq). We found monophyletic populations, high levels of inbreeding (mean population FSNP = 0.407 – 0.945), low effective population sizes (Ne = 0.8 – 50.9), indications of past demographic expansion and rare long-distance dispersal. Our results are important in implementing conservation strategies for Viola uliginosa, which should include founding of seed banks, ex situ cultivations, and re-introductions with individuals of proper origin, combined with continuous population monitoring and habitat management.
A novel body plan alters diversification of body shape and genitalia in live-bearing fish
<p>Major evolutionary innovations can greatly influence subsequent evolution. While many major transitions occurred in the deep past, male live-bearing fishes (family Poeciliidae) more recently evolved a novel body plan. This group possesses a three-region axial skeleton, with one region—the ano-urogenital region—representing a unique body region accommodating male genitalic structures (gonopodial complex). Here we evaluate several hypotheses for the evolution of diversity in this region and examine its role in the evolution of male body shape. Examining <i>Gambusia</i> fishes, we tested <i>a priori</i> predictions for 1) joint influence of gonopodial-complex traits on mating performance, 2) correlated evolution of gonopodial-complex traits at macro- and microevolutionary scales, and 3) predator-driven evolution of gonopodial-complex traits in a post-Pleistocene radiation of Bahamas mosquitofish. We found the length of the sperm-transfer organ (gonopodium) and its placement along the body (gonopodial anterior transposition) jointly influenced mating success, with correlational selection favoring particular trait combinations. Despite these two traits functionally interacting during mating, we found no evidence for their correlated evolution at macro- or microevolutionary scales. In contrast, we did uncover correlated evolution of modified vertebral hemal spines (part of the novel body region) and gonopodial anterior transposition at both evolutionary scales, matching predictions of developmental connections between these components. Developmental linkages in the ano-urogenital region apparently play key roles in evolutionary trajectories, but multiple selective agents likely act on gonopodium length and cause less predictable evolution. Within Bahamas mosquitofish, evolution of hemal-spine morphology and gonopodial anterior transposition across predation regimes was quite predictable, with populations evolving under high predation risk showing more modified hemal spines with greater modifications and a more anteriorly positioned gonopodium. These changes in the ano-urogenital vertebral region have facilitated adaptive divergence in swimming abilities and body shape between predation regimes. Gonopodium surface area, but not length, evolved as predicted in Bahamas mosquitofish, consistent with a previously suggested tradeoff between natural and sexual selection on gonopodium size. These results provide insight into how restructured body plans offer novel evolutionary solutions. Here, a novel body region—originally evolved to aid sperm transfer—was apparently co-opted to alter whole-organism performance, facilitating phenotypic diversification.</p>
Time-Plan Optimization with Genetic Algorithm for Regain of Energy from Train Tracks
<p>Dataset using for Time-Plan Optimization with Genetic Algorithm for Regain of Energy from Train Tracks</p>
Data from: Catchment zoning for freshwater conservation: refining plans to enhance action on the ground
1. Recent advances in freshwater conservation planning allow addressing some of the specific needs of these systems. These include spatial connectivity or propagation of threats along stream networks, essential to ensure the maintenance of ecosystem processes and the biodiversity they sustain. However, these peculiarities make conservation recommendations difficult to implement as they often require considering large areas that cannot be managed under conventional conservation schemes (e.g. strict protection). 2. To facilitate the implementation of conservation in freshwater systems, a multizoning approach with different management zones subject to different management regimes was proposed. So far, this approach has only been used in post hoc exercises where zones were allocated using expert criteria. This might undermine the cost-effectiveness of conservation recommendations, because both the allocation and extent of these zones have never been optimized using the principles of systematic planning. 3. Here, we demonstrate how to create a catchment multizone plan by using a commonly applied tool in marine and terrestrial realms. We first test the capability of Marxan with Zones to address problems in rivers by using a simulated example and then apply the findings to a real case in the Daly River catchment, northern Australia. We also demonstrate how to address common conservation planning issues, such as accounting for threats or species-specific connectivity needs in this multizone framework, and evaluate their effects on the spatial distribution and extent of different zones. 4. We found that by prioritizing the allocation of zones subject to different management regimes, we could minimize the total area in need of strict conservation by a twofold factor. This reduction can be further reduced (threefold) when considering species' connectivity needs. The integration of threats helped reduce the average threats of areas selected by a twofold factor. 5. Synthesis and applications. Catchment zoning can help refine conservation recommendations and enhance cost-effectiveness by prescribing different management regimes informed by ecological needs or distribution of threats. Reliable information on these factors is a key to ensure soundness of planning. Freely available software can be used to implement the approach we demonstrate here.
Data from: Postglacial range expansion shaped the spatial genetic structure in a marine habitat-forming species: implications for conservation plans in the Eastern Adriatic Sea
Aim: Understanding how historical and contemporary processes shaped and maintain spatial patterns of genetic diversity is a major goal for conservation biologists. Here, we characterized the pattern of neutral genetic diversity and we inferred underlying processes in the habitat-forming octocoral Paramuricea clavata in the Adriatic Sea, a peculiar phylogeographic region of the Mediterranean Sea. Location: Eastern coast of the Adriatic Sea. Methods: We genotyped seven microsatellites in 454 individuals of P. clavata from 13 populations recolonized after the last glacial maximum (LGM). We estimated the levels of contemporary connectivity and genetic drift and we reconstructed the demographic history of these populations. Results: The pattern of spatial genetic structure resulted from the combination of hierarchical genetic clusters and isolation by distance (IBD). A significant decrease in genetic diversity and an increase of the frequencies of individual alleles likely due to allele surfing from the south to the north of the area were observed as expected after a postglacial sequential recolonization. Based on maximum likelihood analyses, the foundation of these populations was not linked to dramatic change in population size. Main conclusion: Oceanographic barriers to gene flow combined to the restricted dispersal of P. clavata likely maintain the hierarchical structure and the IBD pattern. We suggest that the latitudinal genetic gradient results from a northward 'serial founder events' recolonization. By integrating patterns and processes, we bridge the gap between the evolutionary and the conservation biology of P. clavata, providing management guidelines, which will benefit the associated coralligenous biodiversity.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.