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942 results for “Scenarios”
Data from: Optimal mating of Pinus taeda L. under different scenarios using differential evolution algorithm
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Data from: Predicting range shifts of the giant pandas under future climate and land use scenarios
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GCAM Version 2 Reference Scenario with Water Constraints Downscaled with Demeter to 5-arcmin (Irrigated, Rain-fed)
<p>GCAM Version 2 Reference Scenario with Water Constraints Downscaled with Demeter to 5-arcmin resolution for year 2015 for irrigated and rain-fed GCAM crop breakout along with forest, urban, sparse, snow, shrub land classes. This run was generated for use by the `teleconnect` package (see <a href="https://github.com/IMMM-SFA/teleconnect">https://github.com/IMMM-SFA/teleconnect</a>). The following is the full README found in the zipped data resource:</p> <blockquote> <p>GCAM v5.2 to Demeter </p> <p>Title:<br> Demeter output for GCAM v5.2 with water constraints - Reference scenario</p> <p>Description:<br> Demeter run conducted using the base layer combining Mirca and Modis v6 type 5 to generate rain-fed and irrigated crops constrained to Modis crop area. GCAM projection split RockIceDesert into snow and sparse land classes.</p> <p>Building the Demeter base layer for use with GCAM allocated land classes and use types:<br> Described in the readme_gcam-reg32basin235_modis-v6-2010_mirca2000_5arcmin.pdf document the docs directory of this data archive.</p> <p>GCAM Version: https://github.com/JGCRI/gcam-core/tree/gcam-v5.2 ; https://doi.org/10.5281/zenodo.3528353 </p> <p>GCAM Reference:<br> Calvin, K., Patel, P., Clarke, L., Asrar, G., Bond-Lamberty, B., Cui, R. Y., Di Vittorio, A., Dorheim, K., Edmonds, J., Hartin, C., Hejazi, M., Horowitz, R., Iyer, G., Kyle, P., Kim, S., Link, R., McJeon, H., Smith, S. J., Snyder, A., Waldhoff, S., and Wise, M.: GCAM v5.1: representing the linkages between energy, water, land, climate, and economic systems, Geosci. Model Dev., 12, 677–698, https://doi.org/10.5194/gmd-12-677-2019, 2019.</p> <p>Demeter Reference:<br> Vernon, C.R., Le Page, Y., Chen, M., Huang, M., Calvin, K.V., Kraucunas, I.P. and Braun, C.J., 2018. Demeter – A Land Use and Land Cover Change Disaggregation Model. Journal of Open Research Software, 6(1), p.15. DOI: http://doi.org/10.5334/jors.208</p> <p>Run:<br> GCAM reference scenario with water constraints conducted by Sonny Kim (skim@pnnl.gov) originally retrieved from PNNL's Constance here: /pic/projects/GCAM/water_market/database_basexdbGCAM51WaterConstr. </p> <p>Contents:<br> teleconnect_agu2019<br> -- config_gcam5p1_watconstr_ref.ini (Demeter configuration file) <br> -- code (code to run Demeter pre-, run, and post-processing)<br> ---- README.txt (Description of run order and process for Demeter on Constance)<br> ---- demeter_preprocess.py (Python script to extract land data from the GCAM database and split RockIceDesert into snow and sparse)<br> ---- demeter_postprocessing.py (Python script to create fractional output of Demeter's native output in square kilometers)<br> ---- run_demeter.py (Python script to run Demeter)<br> ---- run_demeter_gcam5p1_watconstr_ref.sh (sbatch script to submit a Demeter run on Constance)<br> ---- run_postprocessing.sh (sbatch script to submit a post-processing run on Constance)<br> ---- run_preprocessing.sh (sbatch script to submit a pre-processing run on Constance)<br> ---- slurm-11504861.out (Slurm output from Demeter run)<br> -- GCAM <br> ---- database_basexdbGCAM51WaterConstr (GCAM output database)<br> -- inputs (input files used by Demeter) <br> ---- allocation <br> ------ gcam_regbasin_modis_v6_type5_mirca_5arcmin_constraint_alloc.csv (weighting of constraints)<br> ------ gcam_regbasin_modis_v6_type5_mirca_5arcmin_observed_alloc.csv (reclassification table for observed land classes to Demeter final land classes)<br> ------ gcam_regbasin_modis_v6_type5_mirca_5arcmin_order_alloc.csv (processing order for land classes)<br> ------ gcam_regbasin_modis_v6_type5_mirca_5arcmin_projected_alloc.csv (reclassification table for GCAM land classes to Demeter final land classes)<br> ------ gcam_regbasin_modis_v6_type5_mirca_5arcmin_transition_alloc.csv (transition order for land classes)<br> ---- constraints<br> ------ 000_nutrientavail_hswd_5arcmin.csv (nutrient availability constraint weighted by grid cell)<br> ------ 001_soilquality_hswd_5arcmin.csv (soil quality constraint weighted by grid cell)<br> ---- observed<br> ------ gcam_reg32_basin235_modis_v6_2010_mirca_2000_5arcmin_sqdeg_wgs84_11Jul2019.csv (Demeter base layer)<br> ---- projected<br> ------gcam_5p1_watconst_reference.csv (output from demeter_preprocess.py from GCAM output)<br> ------gcam_5p1_watconst_reference_split.csv (output from demeter_preprocess.py from GCAM output with RockIceDesert split into snow and sparse land classes)<br> ---- reference (see https://github.com/IMMM-SFA/demeter)<br> ------ aezcoord.csv<br> ------ countrycoord.csv<br> ------ gcam_basin_lookup.csv<br> ------ gcam_regions_32.csv<br> ------ limits.csv<br> ------ query_land_reg32_basin235_gcam5p0.xml (land allocatio query)<br> ------ regioncoord.csv<br> -- for_teleconnect<br> ---- usa_demeter.csv (file used by the `teleconnect model` containing only 5-arcmin grid cells that are in GCAM region 1 (USA))<br> -- outputs (output files from Demeter run)<br> ---- ref_watconstr_2019-11-07_07h20m46s (output Demeter run directory)<br> ------ log_files (log file directory)<br> -------- logfile_ref_watconstr_2019-11-07_07h20m46s.log (log file from Demeter run)<br> ------ spatial_landcover_tabular<br> -------- landcover_2015_fraction.csv (fraction of land cover per grid cell per land class for 2015) <br> -------- landcover_2015_sqkm.csv (square kilometers of land cover per grid cell per land class for 2015) <br> -------- landcover_2015_timestep.csv (square kilometers of land cover per grid cell per land class for 2015) <br> -- docs <br> ---- readme_gcam-reg32basin235_modis-v6-2010_mirca2000_5arcmin.pdf (creation of the Demeter base layer)</p> </blockquote>
Brainport, Automated valet parking, pickup scenario with DLR vehicle
<p><strong>Scenario description</strong>:</p> <p>The AD-vehicle receives parking command message (AutoPilot.VehicleCommand) containing the destination pickup spot and the free obstacle route and drives from the parking spot and parks to the destination pickup spot.During the collection process the vehicle send two type of messages (AutoPilot.PositionEstimate and AutoPilot.VehicleAVPStatus)</p> <p><strong>Session description</strong>:</p> <p>The pickup scenario with DLR vehicle. DLR vehicle parks autonomously from the parking spot to the destination pickup spot at the parking area on DLR test site in Brunswick.</p> <p><strong>Datasets descriptions</strong>:</p> <p><strong>AUTOPILOT_BrainPort_AutomatedValetParking_DriverVehicleInteraction</strong>: Data extracted from the CAN of the vehicle</p> <p>Dataset Description This dataset contains e.g. throttlestatus, clutchstatus, brakestatus, brakeforce, wipersstatus, steeringwheel for the vehicle</p> <p><strong>AUTOPILOT_BrainPort_AutomatedValetParking_DroneAvpCommand</strong>: Data sent from drone</p> <p>Dataset Description This dataset contains route information for a vehicle to a designated parking spot</p> <p><strong>AUTOPILOT_BrainPort_AutomatedValetParking_EnvironmentSensorsAbsolute</strong>: Data extracted from the vehicle environment sensors</p> <p>Dataset Description This dataset contains information about detected object, with absolute coordinates</p> <p><strong>AUTOPILOT_BrainPort_AutomatedValetParking_EnvironmentSensorsRelative</strong>: Data extracted from the vehicle environment sensors</p> <p>Dataset Description This dataset contains information about detected object, with relative coordinates</p> <p><strong>AUTOPILOT_BrainPort_AutomatedValetParking_IotVehicleMessage</strong>: Data sent between all devices, vehicles and services</p> <p>Dataset Description Each sensor data submission is a Message. A Message has an Envelope, a Path, and optionally (but likely) Path Events and optionally Path Media. The envelope bears fundamental information about the individual sender (the vehicle) but not to a level that owner of the vehicle can be identified or different messages can be identified that originate from a single vehicle.</p> <p><strong>AUTOPILOT_BrainPort_AutomatedValetParking_ParkingSpotDetection</strong>: Data sent from drone to parkingService</p> <p>Dataset Description This dataset contains informaton about detected parking spots</p> <p><strong>AUTOPILOT_BrainPort_AutomatedValetParking_PositioningSystem</strong>: Data from GPS on the vehicle</p> <p>Dataset Description This dataset contains speed, longitude, latitude, heading from the GPS</p> <p><strong>AUTOPILOT_BrainPort_AutomatedValetParking_PositioningSystemResampled</strong>: Data from GPS on the vehicle</p> <p>Dataset Description This dataset contains speed,longitude,latitude,heading from the GPS, resampled to 100 milliseconds</p> <p><strong>AUTOPILOT_BrainPort_AutomatedValetParking_Vehicle</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>Dataset Description This dataset contains a.o temperature and battery state of the vehicles</p> <p><strong>AUTOPILOT_BrainPort_AutomatedValetParking_VehicleAvpCommand</strong>: Data sent from ParkingService to vehicle</p> <p>Dataset Description This dataset contains route to parkingspot, and some other environmental information</p> <p><strong>AUTOPILOT_BrainPort_AutomatedValetParking_VehicleAvpStatus</strong>: Data sent from vehicle to ParkingService</p> <p>Dataset Description This dataset contains information about the current status and parkingstatus of the vehicle</p> <p><strong>AUTOPILOT_BrainPort_AutomatedValetParking_VehicleDynamics</strong>: Data from the CAN and sensors about the state of the vehicle</p> <p>Dataset Description This dataset contains a.o accelerations and speedlimit of the vehicle, as observed from the CAN and the external sensors</p>
Seed traits determine species responses to fire under varying soil heating scenarios
<p>1) Many plant species in fire-prone environments maintain persistence through fire via soil seedbanks. However, seeds stored within the soil are at risk of mortality from elevated soil temperatures during fire. Seeds may be protected from fire-temperature impacts by burial, however those buried too deeply may germinate but fail to emerge. Thus, successful post-fire seed regeneration is contingent upon a trade-off between burial depth and survival through fire.</p> <p>2) We examined the relationships between seedling emergence behaviour, seed survival, and soil temperatures during fire in 13 native and four non-native woodland species in southwestern Australia. We assessed total seedling emergence per depth, maximum seedling emergence depth and seedling emergence speed from seeds planted at seven depths (0, 1, 2, 3, 4, 5, 7 10 cm). Soil temperatures were quantified using distributed temperature sensing in optic fibre (DTS), measured continuously between 1 and 10 cm in depth (temperatures were subsequently categorised into 1 cm increments for analysis) during five experimental fires in beds with fine fuels manipulated between 8–20 t ha<sup>-1</sup>. Using seed survival and emergence success relative to soil temperatures, , we determined vulnerability of seedling emergence relative to soil temperatures generated by combustion of fuel quantities typically observed in woodlands.</p> <p>3) Maximum depth of emergence varied between species from 2 to >10 cm, with a positive linear correlation to seed mass. Maximum soil temperatures from the two highest fuel masses exceeded seed lethal thresholds (T<sub>50</sub> - representing temperatures lethal to 50% of seeds) of at least five species. Lethal temperatures exceeded at all potential emergence depths for all three grass species, and all four non-native species studied. Of the remaining 10 species, temperatures did not exceed the lethal thresholds under any of the fuel mass levels tested. We found no relationship between lethal temperature thresholds and maximum emergence depth.</p> <p>4) Our data demonstrate that seeds exhibit variation in their response to soil heating and capacity to emerge from depth, with three distinct functional responses amongst our study species, which enable persistence through, and recruitment following, fire. Such variation in species attributes and fuel mass may lead to heterogeneity (within fires) or divergent trajectories (among fires) in community response under changed fire regime.</p>
Scenario Input files for "The Domestic and International Implications of Future Climate for U.S. Agriculture in GCAM"
<p>The GCAM scenario input files needed for the experiments described in the paper "The Domestic and International Implications of Future Climate for U.S. Agriculture in GCAM".</p>
Data from: Weighing homoplasy against alternative scenarios with the help of macroevolutionary modeling: a case study on limb bones of fossorial sciuromorph rodents
Homoplasy is a strong indicator of a phenotypic trait's adaptive significance when it can be linked to a similar function. We assessed homoplasy in functionally relevant scapular and femoral traits of Marmotini and Xerini, two sciuromorph rodent clades that independently acquired a fossorial lifestyle from an arboreal ancestor. We studied 125 species in the scapular dataset and 123 species in the femoral dataset. Pairwise evolutionary model comparison was used to evaluate whether homoplasy of trait optima is more likely than other plausible scenarios. The most likely trend of trait evolution among all traits was assessed via likelihood scoring of all considered models. The homoplasy hypothesis could never be confirmed as the single most likely model. Regarding likelihood scoring, scapular traits most frequently did not differ among Marmotini, Xerini, and arboreal species. For the majority of femoral traits, results indicate that Marmotini, but not Xerini, evolved away from the ancestral arboreal condition. We conclude on the basis of the scapular results that the forelimbs of fossorial and arboreal sciuromorphs share mostly similar functional demands, whereas the results on the femur indicate that the hind limb morphology is less constraint, perhaps depending on the specific fossorial habitat.
Robustness of a meta‐network to alternative habitat loss scenarios
<p>Studying how habitat loss affects the tolerance of ecological networks to species extinction (i.e. their robustness) is key for our understanding of the influence of human activities on natural ecosystems. With networks typically occurring as local interaction networks interconnected in space (a meta-network), we may ask how the loss of specific habitat fragments affects the overall robustness of the meta-network. To address this question, for an empirical meta-network of plants, herbivores and natural enemies we simulated the removal of habitat fragments in increasing and decreasing order of area, age and connectivity for plant extinction and the secondary extinction of herbivores, natural enemies and their interactions. Meta-network robustness was characterized as the area under the curve of remnant species or interactions at the end of a fragment removal sequence. To pinpoint the effects of fragment area, age and connectivity, respectively, we compared the observed robustness for each removal scenario against that of a random sequence. The meta-network was more robust to the loss of old (i.e. long-fragmented), large, connected fragments than of young (i.e. recently fragmented), small, isolated fragments. Thus, young, small, isolated fragments may be particularly important to the conservation of species and interactions, while contrary to our expectations larger, more connected fragments contribute little to meta-network robustness. Our findings highlight the importance of young, small, isolated fragments as sources of species and interactions unique to the regional level. These effects may largely result from an unpaid extinction debt, in which case these fragments are likely to lose species over time. Yet, there may also be more long-lasting effects from cultivated lands (e.g. water, fertilizers and restricted cattle grazing) and network complexity in small, isolated fragments. Such fragments may sustain important biological diversity in fragmented landscapes, but maintaining their conservation value may depend on adequate restoration strategies.</p>
Evaluating spatially explicit sharing-sparing scenarios for multiple environmental outcomes
<p>1. Understanding how to allocate land for the sustainable delivery of multiple, competing objectives is a major societal challenge. The land sharing-sparing framework presents a heuristic for understanding the trade-off between food production and biodiversity conservation by comparing region-wide land use scenarios which are equivalent in terms of overall food production.</p> <p>2. Here, for two contrasting regions of lowland England (The Fens and Salisbury Plain), we use empirical data and predictive models to compare a suite of spatially explicit scenarios reflecting the full range of the sharing-sparing continuum, including mixed scenarios which combine elements of both sharing and sparing. We evaluate a range of outcomes (bird populations, global warming potential (GWP), nitrogen and phosphorus pollution and outdoor recreation), in order to identify approaches to regional land use planning with the potential to deliver multiple societal benefits.</p> <p>3. Land-sharing scenarios (which reduce the dominance of productive agricultural land in farmed areas and the area of larger unfarmed areas) result in negative outcomes, particularly for birds and GWP. In contrast, many land-sparing scenarios (including mixed scenarios which increase the area of lower-yield farmland alongside larger unfarmed areas) resulted in improvements in all or most outcomes, although for recreation and nutrient export differences between scenarios were modest.</p> <p>4. Importantly, environmental outcomes also depended on the spatial arrangement of spared land, the types of natural or semi-natural habitat promoted on spared land, whether some lower-yield farmland is delivered alongside larger unfarmed areas, and the overall region-wide food production target.</p> <p>5. <i>Policy implications</i>. Our study suggests that land-sparing strategies which increase the area of natural and seminatural areas can improve environmental outcomes, despite the costs associated with high-yield agriculture. However, high-yield agriculture should not compromise future production or ecosystem services on spared land, and explicit policies such as certification or payments for ecosystem services are required to link sustainable high-yield production to habitat conservation. Our study also highlights the importance of mitigating projected increases in food <a>demand.</a></p>
Supplementary material for: "On the selection of time-varying scenarios of wind and ocean waves: methodologies and applications in the North Tyrrhenian Sea"
<p>All the routines to perform the clustering of the hindcast data have been developed in Matlab.<br> The code Case_study.m allows to reproduce the examples outlined in chapter 3.2, Figs. 15-16 of the manuscript:</p> <p>"On the selection of time-varying scenarios of wind and ocean waves: methodologies and applications in the North Tyrrhenian Sea"</p> <p>Submitted to "Ocean Modelling" - Elsevier, and currently is available online.</p> <p>The code needs to be fed with the data stored into the "hind_param.mat" and "clusters.mat" files, attached to this repo.<br> Please note that the wave parameters stored into "hind_param.mat" cannot be employed for commercial purposes.<br> In case they are meant to be used for research, reference has to be made to:</p> <p>- Mentaschi, L., Besio, G., Cassola, F., & Mazzino, A. (2013).<br> Developing and validating a forecast/hindcast system for the Mediterranean Sea.<br> Journal of Coastal Research, 65(sp2), 1551-1556.</p> <p>- Mentaschi, L., Besio, G., Cassola, F., & Mazzino, A. (2015).<br> Performance evaluation of Wavewatch III in the Mediterranean Sea.<br> Ocean Modelling, 90, 82-94.</p> <p>For further inquires about the hindcast data, please contact meteocean@dicca.unige.it.</p> <p>Finally, results of the sensitivity analysis of CE and W2 with respect to varying number of clusters are stored into the<br> zip files "CE.zip" and "W2.zip", respectively (Figs. from 2 to 8 of the submitted manuscript).<br> Each *dat file refers to a particular set of the data inital conditions (see manuscript), and it is labeled as follows:<br> "*_[FIRST YEAR OF TRAINING]_[LAST YEAR OF TRAINING]_[FIRST YEAR OF VALIDATION]_[LAST YEAR OF VALIDATION]_<br> [TOTAL NUMBER OF TIME STEPS]_[TIME SHIFT BETWEEN SUCCESSIVE SCENARIOS]_*_[INITIAL TIME RESOLUTION]_*_<br> [VARIABLES EMPLOYED].dat"</p> <p>For further information, please contact Giulia Cremonini at:<br> giulia.cremonini@edu.unige.it</p>
Dynamic evolution and scenario simulation of habitat quality under the impact of land-use change in the Huaihe River Economic Belt, China
<p>1. Land-use data</p> <p>Meaning of the value in the layers:<br> 11: Paddy field <br> 12: Dry land<br> 21: Forestland<br> 22: Shrubland<br> 23: Sparse woodland<br> 24: Other woodland<br> 31: High coverage grassland<br> 32: Medium coverage grassland<br> 33: Low coverage grassland<br> 41: River canal<br> 42: Lake<br> 43: Reservoir and pond<br> 44: Permanent glacial snow<br> 45: Coastal mud flat <br> 46: Inland tidal flat<br> 51: Urban land<br> 52: Rural residential land<br> 53: Industrial and traffic land<br> 61: Dene<br> 62: Gobi Desert<br> 63: Saline and alkaline land<br> 64: Marshland<br> 65: Bare land<br> 66: Bare rock<br> 67: Other unused land</p> <p>2. GDP data (Meaning of the value in the layer: yuan/km<sup>2</sup>)</p> <p>3. Population density data (Meaning of the value in the layer: person/km<sup>2</sup>)</p> <p>4. Meteorological data</p> <p>temperature data (unit: ℃)</p> <p>perception data(unit:mm)</p> <p>5. Terrain data including elevation, slope and aspect</p> <p>6. Vector data including railways, highways, national roads, provincial roads and county roads</p>
WindNODE_ABW single scenario results data
<p>These notebooks are created based on the model results of <a href="https://windnode-abw.readthedocs.io">WindNODE_ABW</a> which are available <a href="https://doi.org/10.5281/zenodo.4288942">here</a>.</p>
Hotspots of species loss do not vary across future climate scenarios in a drought-prone river basin
<p><b>Aim</b>: Climate change is expected to alter the distributions of species around the world, but estimates of species' outcomes vary widely among competing climate scenarios. Where should conservation resources be directed to maximize expected conservation benefits given future climate uncertainty? Here, we explore this question by quantifying variation in fish species' distributions across future climate scenarios.</p> <p><b>Location</b>: Red River basin, south-central United States.</p> <p><b>Methods</b>: We modeled historical and future stream fish distributions using a suite of environmental covariates derived from high-resolution hydrologic and climatic modeling of the basin. We quantified variation in outcomes for individual species across climate scenarios and across space, and identified hotspots of species loss by summing changes in probability of occurrence across species.</p> <p><b>Results</b>: Under all climate scenarios, we find that the distribution of most fish species in the Red River Basin will contract by 2050. However, the variability across climate scenarios was more than 10 times higher for some species than for others. Despite this uncertainty in outcomes for individual species, hotspots of species loss tended to occur in the same portions of the basin across all climate scenarios. We also find that the most common species are projected to experience the greatest range contractions, underscoring the need for directing conservation resources towards both common and rare species</p> <p><b>Main conclusions</b>: Our results suggest that while it may be difficult to predict which species will be most impacted by climate change, it may nevertheless be possible to identify spatial priorities for climate mitigation actions that are robust to future climate uncertainty. These findings are likely to be generalizable to other ecosystems around the world where future climate conditions follow prevailing historical patterns of key environmental covariates.</p>
PM10 scenarios in Northern Italy
<p>The dataset contains PM10 grided concentrations for Northern Italy in the reference year 2010 obtained with the chemical transport models CAMx and FARM for different emissive scenarios.</p>
Integrating stakeholders' perspectives and spatial modelling to develop scenarios of future land use and land cover change in northern Tanzania
<p>Rapid rates of land use and land cover change (LULCC) in eastern Africa and limited instances of genuinely equal partnerships involving scientists, communities and decision makers challenge the development of robust pathways toward future environmental and socioeconomic sustainability. We use a participatory modelling tool, Kesho, to assess the biophysical, socioeconomic, cultural and governance factors that influenced past (1959-1999) and present (2000-2018) LULCC in northern Tanzania and to simulate four scenarios of land cover change to the year 2030. Simulations of the scenarios used spatial modelling to integrate stakeholders' perceptions of future environmental change with social and environmental data on recent trends in LULCC. From stakeholders' perspectives, between 1959 and 2018, LULCC was influenced by climate variability, availability of natural resources, agriculture expansion, urbanization, tourism growth, and legislation governing land access and natural resource management. Among other socio-environmental-political LULCC drivers, the stakeholders envisioned that from 2018 to 2030 LULCC will largely be influenced by land health, natural and economic capital, and political will in implementing land use plans and policies. The projected scenarios suggest that by 2030 agricultural land will have expanded by 8-20% under different scenarios and herbaceous vegetation and forest land cover will be reduced by 2.5-5% and 10-19% respectively. Stakeholder discussions further identified desirable futures in 2030 as those with improved infrastructure, restored degraded landscapes, effective wildlife conservation, and better farming techniques. The undesirable futures in 2030 were those characterized by land degradation, poverty, and cultural loss. Insights from our work identify the implications of future LULCC scenarios on wildlife and cultural conservation and in meeting the Sustainable Development Goals (SDGs) and targets by 2030. The Kesho approach capitalizes on knowledge exchanges among diverse stakeholders, and in the process promotes social learning, provides a sense of ownership of outputs generated, democratizes scientific understanding, and improves the quality and relevance of the outputs.</p>
Data for ED2 fire scenarios
<p>The folder consists of inputs data necessary to run ED2 model for fire scenarios</p>
Data from: Phylogeography and population differentiation in the Psittacanthus calyculatus (Loranthaceae) mistletoe: a complex scenario of climate-volcanism interaction along the Trans-Mexican Volcanic Belt
Aim The formation of the Trans-Mexican Volcanic Belt (TMVB) played an important role in driving inter- and intraspecific diversification at high elevations. However, Pleistocene climate changes and ecological factors might also contribute to plant genetic structuring along the volcanic belt. Here, we analysed phylogeographic patterns of the parrot-mistletoe Psittacanthus calyculatus to determine the relative contribution of these different factors. Location Trans-Mexican Volcanic Belt Methods Using nuclear and chloroplast DNA sequence data for 370 individuals, we investigate the genetic differentiation of 35 populations across the species range. We conducted phylogenetic, population and spatial genetic analyses of P. calyculatus sequences along with ecological niche modelling and Bayesian inference methods to gain insight into the structuring of genetic variation of these populations. Results Our analyses revealed population structure with three genetic groups corresponding to individuals from Oaxaca and those from the central-eastern and western TMVB regions. A significant genetic signal of demographic expansion, an east-to-west expansion predicted by species distribution modelling, and approximate Bayesian computation analyses strongly supported a scenario of habitat isolation and invasion of TMVB by P. calyculatus during the late-Pleistocene. Main conclusions The genetic differentiation of P. calyculatus may be explained by the combined effects of (i) geographical isolation linked to the effects of the glacial/interglacial cycles and environmental factors, driving genetic differentiation from congeners into more xeric vegetation and (ii) the invasion of TMVB from east to west, suggesting a role for both colonization and glacial/interglacial cycles models.
Data from: Model-based comparisons of phylogeographic scenarios resolve the intraspecific divergence of cactophilic Drosophila mojavensis
The cactophilic fly Drosophila mojavensis exhibits considerable intraspecific genetic structure across allopatric geographic regions and shows associations with different host cactus species across its range. The divergence between these populations has been studied for more than 60 years, yet their exact historical relationships have not been resolved. We analysed sequence data from 15 intronic X-linked loci across populations from Baja California, mainland Sonora-Arizona and Mojave Desert regions under an isolation-with-migration model to assess multiple scenarios of divergence. We also compared the results with a pre-existing sequence dataset of 8 autosomal loci. We derived a population tree with Baja California placed at its base and link their isolation to Pleistocene climatic oscillations. Our estimates suggest the Baja California population diverged from an ancestral Mojave Desert/mainland Sonora-Arizona group around 230-270 Kya, while the split between the Mojave Desert and mainland Sonora-Arizona populations occurred one glacial cycle later, 117-135 Kya years ago. Although we found these three populations to be effectively allopatric, model ranking could not rule out the possibility of a low-level of gene flow between two of them. Finally, the Mojave Desert population showed a small effective population size, consistent with a historical population bottleneck. We show that model-based inference from multiple loci can provide accurate information on the historical relationships of closely related groups allowing us to set into historical context a classic system of incipient ecological speciation.
Data from: Genetic diversity, population structure and migration scenarios of the marsupial "Monito del Monte" in south-central Chile.
In this study, we quantified the three pivotal genetic processes (i.e., genetic diversity, spatial genetic structuring and migration) necessary for a better biological understanding and management of the singular "living-fossil" and near-threatened mouse opossum marsupial Dromiciops gliroides, the "Monito del Monte", in south-central Chile. We used 11 microsatellite loci to genotype 47 individuals distributed on the mainland and northern Chiloé Island. Allelic richness, observed and expected heterozygosity, inbreeding coefficient and levels of genetic differentiation were estimated. The genetic structure was assessed based on Bayesian clustering methods. In addition, potential migration scenarios were evaluated based on a coalescent theory framework and Bayesian approach to parameter estimations. Microsatellites revealed moderate to high levels of genetic diversity across sampled localities. Moreover, such molecular markers suggested that at least two consistent genetic clusters could be identified along the D. gliroides distribution ("Northern" and "Southern" cluster). However, general levels of genetic differentiation observed among localities and between the two genetic clusters were relatively low. Migration analyses showed that the most likely routes of migration of D. gliroides occurred a) from the Southern cluster to the Northern cluster and b) from the Mainland to Chiloé Island. Our results could represent critical information for future conservation programs and for a recent proposal about the taxonomic status of this unique mouse opossum marsupial.
Data from: Scale-dependent responses of pollination and seed dispersal mutualisms in a habitat transformation scenario
Transformed habitats are the result of deliberate replacement of native species by an exotic monoculture, involving changes in biotic and abiotic conditions. Despite this, transformed habitats are becoming more common and constitute a major biodiversity change driver, little is known about the scale-dependent responses of plant-animal mutualisms. Aiming to test the multi-scale responses of pollination and seed dispersal in a habitat transformation scenario, we examined a gradient of native and transformed habitats at three spatial scales (0-50, 50-100, and 100-250 m), focused on a highly-specialized mutualistic system composed of a hemiparasitic mistletoe (Tristerix corymbosus) that is almost exclusively pollinated by a hummingbird (Sephanoides sephaniodes) and dispersed by an arboreal marsupial (Dromiciops gliroides). Even though mistletoes were found along the gradient, they were more abundant and more densely aggregated when the transformed habitat was dominant. Disperser and pollinator activity also increased as the transformed habitat become dominant, at the scale of 0-50 m and 50-100 m, respectively. Furthermore, crop size and disperser activity co-varied at broad and intermediate scales, whereas recruitment co-varied at intermediate and fine scales. Moreover, disperser activity and the number of seedlings were spatially associated, stressing D. gliroides' role in the recruitment of the mistletoe. Synthesis: This highly specialized mutualistic system seems to be responding positively to the habitat structure modifications associated with Eucalyptus plantations. However, the actual costs (e.g., reduced gene flow, increased herbivory) in these transformed habitats are yet to be assessed.
ScienceDex guides
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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.