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107 results for “Landscape complexity”
Navigating the complex policy landscape for carbon farming in The Netherlands and the EU -- Open Research Europe Extended Data-- Tables 1-6, Figures 1-2
<p>This is extended data for the article entitle 'Navigating the complex policy landscape for carbon farming in The Netherlands and the EU' submitted to Open Research Europe by Eise Spijker. </p>
The energy landscape for R-loop formation by the CRISPR-Cas Cascade complex - Minimal Dataset
<p>Minimal Dataset for "The energy landscape for R-loop formation by the CRISPR-Cas Cascade complex", published at <a href="https://www.nature.com/nsmb/">NSMB</a>.</p>
Data accompanying manuscript: 'Antarctic subglacial topography mapped from space reveals complex mesoscale landscape dynamics'
<p>This upload contains the data which accompanies the manuscript: 'Antarctic subglacial topography mapped from space reveals complex mesoscale landscape dynamics'.</p> <p><strong>Metrics calculated for each of the 4269 50 km by 50 km regions</strong></p> <table> <tbody> <tr> <td>Filename (IFPA)</td> <td>Filename (Bedmachine)</td> <td>Filename (Bedmap3)</td> <td>Description</td> </tr> <tr> <td>x_ifpa.nc<br>y_ifpa.nc</td> <td> </td> <td> </td> <td>X and Y coordinates</td> </tr> <tr> <td>mean_ifpa.nc or ifpa_mean.nc</td> <td>bedmach_mean.nc</td> <td> </td> <td>Mean elevation (m)</td> </tr> <tr> <td> <p>ifpa_count.nc<br>ifpa_count_max_20.nc<br>ifpa_count_max_100.nc<br>ifpa_count_max_250.nc</p> </td> <td>bedmach_count.nc<br>bedmach_count_max_20.nc<br>bedmach_count_max_100.nc<br>bedmach_count_max_250.nc</td> <td> </td> <td> <p>The number of hills with a 50 m prominence within a 5 km neighbourhood <br>(or 20 m, 100 m, 250 m respectively)</p> </td> </tr> <tr> <td>ifpa_b1_5km.nc<br>ifpa_b1_thickness.nc</td> <td>bedmach_b1_5km.nc<br>bedmach_b1_thickness.nc</td> <td> </td> <td>The fourier fractal dimension for wavelengths greater than 5 km or the ice thickness respectively</td> </tr> <tr> <td>ifpa_std_deslope.nc<br>i_std_l.nc</td> <td>bedmach_std_deslope.nc<br>b_std_l.nc</td> <td> </td> <td>The standard deviation:<br>- with the best fit slope removed<br>- of some long wavelength components of the fourier spectrum</td> </tr> <tr> <td>ifpa_wav_max_power.nc</td> <td>bedmach_wav_max_power.nc</td> <td> </td> <td>The wavelength in the Fourier spectrum with the maximum power</td> </tr> <tr> <td>ifpa_rms_slope.nc<br>i_rms_slope_h.nc</td> <td>bedmach_rms_slope.nc<br>b_rms_slope_h.nc</td> <td> </td> <td>The RMS slope of:<br>- the bed elevation<br>- some short wavelength components of the fourier spectrum</td> </tr> <tr> <td>ifpa_rms_curvature.nc</td> <td>bedmach_rms_curvature.nc</td> <td> </td> <td>The RMS curvature of the bed elevation</td> </tr> <tr> <td> </td> <td>source.nc</td> <td> </td> <td>The method used to calculate the bed topography (Bedmachine only)</td> </tr> <tr> <td> </td> <td> </td> <td>mean_nearest.nc</td> <td>The mean distance from each IFPA grid point to the nearest Bedmap3 data point</td> </tr> <tr> <td> </td> <td> </td> <td>bedmap3_count.nc</td> <td>The number of Bedmap3 data points within the region</td> </tr> </tbody> </table> <p> </p> <p><strong>Datasets required for plotting</strong></p> <table> <tbody> <tr> <td>Filename</td> <td>Description</td> </tr> <tr> <td>Groundingline_Antarctica_v2.shp</td> <td>Antarctic grounding line </td> </tr> <tr> <td>ECR_features.shp</td> <td>Outline of significant features within the example regions chosen</td> </tr> <tr> <td>IFPA_bed.nc</td> <td>OLD VERSION of IFPA bed topography map for Antarctica</td> </tr> <tr> <td> <p>IFPA_bed_C50.nc</p> </td> <td>IFPA bed topography map for Antarctica (without radar correction)</td> </tr> </tbody> </table> <p><strong>To plot the figures, you will either require the following datasets: </strong></p> <table> <tbody> <tr> <td>Filename</td> <td>Description</td> </tr> <tr> <td>IFPA_figures_data.zip</td> <td>Additionally data to plot figures 1,6,8 and 9 </td> </tr> <tr> <td> <p>HA_data.csv<br>HB_data.csv<br>RSB_data.csv</p> </td> <td>For Highland A, Highland B and Recovery Subglacial Basin<br>IFPA (radar corrected), IFPA (not radar corrected), Bedmachine v3, and ice-penetrating radar profiles</td> </tr> <tr> <td> <p>HA_data_ifpa.csv<br>HB_data_ifpa.csv<br>RSB_data_ifpa.csv</p> </td> <td> <p>For Highland A, Highland B and Recovery Subglacial Basin<br>IFPA (radar corrected) map for the region crossed by the ice-penetrating radar profile</p> </td> </tr> </tbody> </table> <p><strong>or, the figures can be regenerated using the following datasets, which are available at the listed DOIs</strong></p> <table> <tbody> <tr> <td>Filename</td> <td>Description</td> <td>Reference</td> <td>DOI</td> </tr> <tr> <td>GaplessREMA100.nc</td> <td>Gapless REMA Antarctica dataset at 100m resolution</td> <td>Dong et al. (2022)</td> <td>10.1016/j.isprsjprs.2022.01.024</td> </tr> <tr> <td>BedMachineAntarctica-v3.nc</td> <td>MEaSURES BedMachine Antarctica bed topography map version 3</td> <td>Morlighem et al. (2020)</td> <td>10.5067/FPSU0V1MWUB6</td> </tr> <tr> <td>antarctica_ice_velocity_450m_v2.nc</td> <td>ITSLIVE Antarctic velocity map</td> <td>Gardner et al. (2019)</td> <td>10.5067/6II6VW8LLWJ7</td> </tr> <tr> <td>antarctic_ice_vel_phase.nc</td> <td>MEaSURES Antarctic velocity map</td> <td>Mouginot et al. (2019)</td> <td>10.5067/PZ3NJ5RXRH10</td> </tr> <tr> <td>UTIG_2010_ICECAP_AIR_BM3.csv</td> <td>Bed elevation from airborne radar from the UTIG Icecap survey</td> <td>Wright et al. (2012)</td> <td>10.1029/2011JF002066</td> </tr> <tr> <td>BAS_2012_ICEGRAV_AIR_BM3.csv</td> <td>Bed elevation from airborne radar from the BAS Icegrav survey</td> <td>Forsberg et al. (2018)</td> <td>10.1144/SP461.17</td> </tr> </tbody> </table> <p><strong> </strong></p>
Dataset for article: Co-evolutionary landscape at the interface and non-interface regions of protein-protein interaction complexes
<p>Proteins involved in interactions throughout the course of evolution tend to co-evolve and compensatory changes may occur in interacting proteins to maintain or refine such interactions. However, certain residue pair alterations may prove to be detrimental for functional interactions. Hence, determining co-evolutionary pairings that could be structurally or functionally relevant for maintaining the conservation of an inter-protein interaction is important. Inter-protein co-evolution analysis in several complexes utilizing multiple existing methodologies suggested that co-evolutionary pairings can occur in spatially proximal and distant regions in inter-protein interactions. Subsequently, the Co-Var (<b>Co</b>rrelated <b>Var</b>iation) method based on mutual information and Bhattacharyya coefficient was developed, validated, and found to perform relatively better than CAPS and EV-complex. Interestingly, while applying the Co-Var measure and EV-complex program on a set of protein-protein interaction complexes, co-evolutionary pairings were obtained in interface and non-interface regions in protein complexes. The Co-Var approach involves determining high degree co-evolutionary pairings that include multiple co-evolutionary connections between particular co-evolved residue positions in one protein with multiple residue positions in the binding partner. Detailed analyses of high degree co-evolutionary pairings in protein-protein complexes involved in cancer metastasis suggested that most of the residue positions forming such co-evolutionary connections mainly occurred within functional domains of constituent proteins and substitution mutations were also common among these positions. The physiological relevance of these predictions suggests that Co-Var can predict residues that could be crucial for preserving functional protein-protein interactions. Finally, <b>Co-Var </b>web server (<a href="http://www.hpppi.iicb.res.in/ishi/covar/index.html">http://www.hpppi.iicb.res.in/ishi/covar/index.html</a>) that implements this methodology identifies co-evolutionary pairings in intra and inter-protein interactions.</p>
Extended ensemble molecular dynamics study of ammonia–cellulose I complex crystal models: free-energy landscape and atomistic pictures of ammonia diffusion in the crystalline phase.
<p>The data deposited here accompany the manuscript "Extended ensemble molecular dynamics study of ammonia–cellulose I complex crystal models: free-energy landscape and atomistic pictures of ammonia diffusion in the crystalline phase" and include the molecular dynamics trajectories and the AMBER topology (parm) files. Detailed file contents are summarized in the README file.</p>
Navigating the Complex Solid Form Landscape of the Quercetin Flavonoid Molecule
<p>Data related to the paper published in Crystal Growth & Design, with doi:https://doi.org/10.1021/acs.cgd.3c00584.</p> <p>Quercetin, a naturally occurring bioflavonoid substance widely used in the nutraceutical and food industries, exists in various solid forms that can have different physicochemical properties, thus impacting this compound’s performance in various applications. In this work, we will clarify the complex solid-form landscape of this molecule. Two elusive isostructural solvates of quercetin were obtained from ethanol and methanol. The obtained crystals were characterized experimentally, but the crystallographic structure could not be solved due to their high instability. Nevertheless, the desolvated structure resulting from a high-temperature treatment (or prolonged storage at ambient conditions) of both these two labile crystals was characterized and solved via powder X-ray diffraction and solid-state nuclear magnetic resonance (SSNMR). This anhydrous crystal structure was compared with another anhydrous quercetin form obtained in our previous work, indicating that, at least, two different anhydrous polymorphs of quercetin exist. Navigating the solid-form landscape of quercetin is essential to ensure accurate control of the functional properties of food, nutraceutical, or pharmaceutical products containing crystal forms of this substance.</p>
Tracking small animals in complex landscapes: a comparison of localisation workflows for automated radio telemetry systems
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Dataset for article: Co-evolutionary landscape at the interface and non-interface regions of protein-protein interaction complexes
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Local adaptation across a complex bioclimatic landscape in two montane bumble bee species
<p>Understanding evolutionary responses to variation in temperature and precipitation across species ranges is of fundamental interest given ongoing climate change. The importance of temperature and precipitation for multiple aspects of bumble bee (<i>Bombus</i>) biology, combined with large geographic ranges that expose populations to diverse environmental pressures, make these insects well-suited for studying local adaptation. We analyzed genome-wide sequence data from two widespread bumble bees, <i>Bombus vosnesenskii </i>and <i>Bombus vancouverensis</i>, using multiple Environmental Association Analysis methods to investigate climate adaptation across latitude and altitude. The strongest signatures of selection were observed in <i>B. </i><i>vancouverensis</i>, but despite unique responses between species for most loci, we detected several shared responses. Genes relating to neural and neuromuscular function and ion transport are especially evident with respect to temperature variables, while genes relating to cuticle formation, tracheal and respiratory system development, and homeostasis were associated with precipitation variables. Our data thus suggest that adaptive responses for tolerating abiotic variation are likely to be complex, but that several parallels among species can emerge even for these complex traits and landscapes. Results provide the framework for future work into mechanisms of thermal and desiccation tolerance in bumble bees and a set of genomic targets that might be monitored for future conservation efforts.</p>
Complex landscapes stabilize farm bird communities and their expected ecosystem services
<p>1. Birds play many roles within agroecosystems including as consumers of crops and pests, carriers of pathogens, and beloved icons. Birds are also rapidly declining across North America, in part due to agricultural intensification. Thus, it is imperative to identify how to manage agroecosystems to best support birds for multi-functional outcomes (e.g., crop production and conservation). Both the average amounts of services/disservices provided and their temporal stability are important for effective farm planning.</p> <p>2. Here, we conducted point-count surveys for four years across 106 locations on 27 diversified farms in Washington and Oregon, USA. We classified birds as ecosystem service or disservice providers using indices spanning supporting, regulating, provisioning, and cultural services/disservices. We then examined service/disservice index pairwise correlations and assessed the relative importance of local, farm, and landscape complexity on the average and temporal stability of avian service/disservice provider indices.</p> <p>3. Generally, service provider indices (production benefitting birds, grower appreciation, and conservation scores) were positively correlated with each other. Foodborne pathogen risk, grower disapproval, and identity/iconic value indices were also positively correlated with each other. However, the crop damaging bird index generally had low correlations with other indices.</p> <p>4. Farms that implemented more conservation-friendly management practices generally had higher average service provider indices, but farm management did not impact disservice provider indices, except for grower disapproval. Average disservice provider indices were lower on farms in complex landscapes.</p> <p>5. Local vertical vegetation complexity tended to increase the temporal stability of service provider indices but did not affect the disservice provider indices. Greater landscape complexity was generally associated with increased temporal stability of service and disservice provider indices. Increased landscape complexity may stabilize bird communities by increasing bird community evenness, which in turn, positively predicted temporal stability of all service/disservice provider indices.</p> <p>6. <i>Policy implications</i>: Our results suggest that farmers can effectively manage their farms to harness ecosystem services from birds through farm diversification. Disservices provided by birds, however, appear to be most negatively impacted by landscape-level complexity. Thus, greater incentives for farmers to increase seminatural cover at the landscape-scale are likely necessary to achieve multifunctional outcomes for conservation and agriculture.</p>
Highland forest's environmental complexity drives landscape genomics and connectivity of the rodent Peromyscus melanotis
<p>We evaluate how the environmental complexity of La Malinche volcano influences patterns of genomic variation in <em>Peromyscus melanotis</em>, across two mountain slopes and global and regional geographic scales.Using reduced representation genomic sequencing we estimated population genetic diversity, subdivisions and migration rates. Remote sensing data and drone image processing were used to characterize landscape variables. We evaluated their effect on connectivity, based on a landscape analyses framework, using resistance surfaces, circuit theory and omnidirectional connectivity. Our findings showed how the forest environmental complexity across different geographic scales drives dispersal, genomic structure and connectivity patterns in this rodent, where dirt roads and disturbed areas limit its connectivity, while exhibiting higher connectivity at the highest elevations where the forest is less disturbed. Notably, that our 3D variable of tree height was significant demonstrates the utility in incorporating 3D vegetation structure variables into landscape genetic analyses.</p>
Weed communities are more diverse, but not more abundant, in dense and complex bocage landscapes
<p>1. Bocage landscapes are characterized by a network of hedgerows that delimits arable fields. Such landscapes provide many ecosystem services, including biodiversity conservation, but their effects on weed communities remain largely unknown. Bocage landscapes could affect weed communities through two main processes: plant spillover from hedgerows and increased environmental heterogeneity in arable fields. These bocage effects are also likely to vary between farming systems (conventional vs organic), due to differences in management practices.</p> <p>2. We sampled weed communities more than 20 m from field margins in 74 arable fields (37 per farming system). Fields were located along two independent landscape gradients of total length of hedgerows (with or without a shrub layer) and organic farming cover, in Brittany (France). We analysed the effect of 'bocage' (i.e., the density and complexity of hedgerow networks) and farming systems at field and landscape scales on species and functional diversity of weed communities. Further, we used fidelity to non-crop habitats and Ellenberg indicator values to assess the 'plant spillover' and 'environmental heterogeneity' hypotheses, respectively.</p> <p>3. Weed communities were more diverse and more abundant in organic farming systems. In addition, weed communities were more diverse, but not more abundant, in denser and more complex bocage landscapes. 'Bocage' increased species diversity of weeds, but also community-weighted variance of specific leaf area, plant height and seed mass. Positive effects of 'bocage' on weed diversity were driven by increased environmental heterogeneity rather than spillover of transient species from hedgerows. 'Bocage' effects were independent of farming systems at field and landscape scales.</p> <p>4. Synthesis and applications. Maintaining diverse weed communities is key to agroecological weed management and biodiversity conservation in agricultural landscapes. Farmers are often concerned that hedgerows harbour competitive plants spreading into field edges, thereby increasing weed pressure. However, our study shows that dense and complex bocage landscapes promote weed diversity in field cores, most likely by increasing environmental heterogeneity. Thus, bocage landscapes could actually enhance ecosystem services provided by weed communities and reduce weed-crop competition.</p>
Data from: Tracking shifts in forest structural complexity through space and time in human-modified tropical landscapes
<p>Habitat structural complexity is an emergent property of ecosystems that directly shapes their biodiversity, functioning and resilience to disturbance. Yet despite its importance, we continue to lack consensus on how best to define structural complexity, nor do we have a generalised approach to measure habitat complexity across ecosystems. To bridge this gap, here we adapt a geometric framework developed to quantify the surface complexity of coral reefs and apply it to the canopies of tropical rainforests. Using high-resolution, repeat-acquisition airborne laser scanning data collected over 450 km2 of human-modified tropical landscapes in Borneo, we generated 3D canopy height models of forests at varying stages of recovery from logging. We then tested whether the geometric framework of habitat complexity – which characterises 3D surfaces according to their height range, rugosity and fractal dimension – was able to detect how both human and natural disturbances drive variation in canopy structure through space and time across these landscapes. We found that together, these three metrics of surface complexity captured major differences in canopy 3D structure between highly-degraded, selectively logged and old-growth forests. Moreover, the three metrics were able to track distinct temporal patterns of structural recovery following logging and wind disturbance. However, in the process we also uncovered several important conceptual and methodological limitations with the geometric framework of habitat complexity. We found that fractal dimension was highly sensitive to small variations in data inputs and was ecologically counteractive (e.g., higher fractal dimension in oil palms than old-growth forests), while rugosity and height range were tightly correlated (r=0.75) due to their strong dependency on maximum tree height. Our results suggest that forest structural complexity cannot be summarised using these three descriptors alone, as they overlook key features of canopy vertical and horizontal structure that arise from the way trees fill 3D space.</p> <p> </p> <p> </p>
Complex urban environments provide Apis mellifera with a richer plant forage than suburban and more rural landscapes
<p>Growth in the global development of cities, and increasing public interest in beekeeping, has led to rises in the numbers of urban apiaries. Towns and cities can provide an excellent diet for managed bees, with a diverse range of nectar and pollen available throughout a long flowering season and are often more ecologically diverse than the surrounding rural environments. Accessible urban honeybee hives are a valuable research resource to gain insights into the diet and ecology of wild pollinators in urban settings. We used DNA metabarcoding of the rbcL and ITS2 gene regions to characterise the pollen community in Apis mellifera honey, inferring the floral diet, from 14 hives across an urban gradient around Greater Manchester, UK. We found that the proportion of urban land around a hive is significantly associated with an increase in the diversity of plants foraged, and that invasive and non-native plants appear to play a critical role in the sustenance of urban bees, alongside native plant species. The proportion of improved grassland, typical of suburban lawns and livestock farms, is significantly associated with decreases in the diversity of plant pollen found in honey samples. These findings are relevant to urban landscape developers motivated to encourage biodiversity and bee persistence, in line with global bio-food security agendas.</p>
Inconsistent responses of carabid beetles and spiders to land-use intensity and landscape complexity in Northwestern Europe
<p>Reconciling biodiversity conservation with agricultural production requires a better understanding of how key ecosystem service providing species respond to agricultural intensification. Carabid beetles and spiders represent two widespread guilds providing biocontrol services. Here we surveyed carabid beetles and spiders in 66 winter wheat fields in four Northwestern European countries and analyzed how the activity density and diversity of carabid beetles and spiders were related to crop yield (proxy for land-use intensity), percentage cropland (proxy for landscape complexity) and soil organic carbon content, and whether these patterns differed between dominant and non-dominant species. Less than 17% of carabid or spider species were classified as dominant, which accounted for more than 90% of individuals respectively. We found that carabids and spiders were generally related to different aspects of agricultural intensification. Carabid species richness was positively related with crop yield and evenness was negatively related to crop cover. The activity density of non-dominant carabids was positively related with soil organic carbon content. Meanwhile, spider species richness and non-dominant spider species richness and activity density were all negatively related to percentage cropland. Our results show that practices targeted to enhance one functionally important guild may not promote another key guild, which helps explain why conservation measures to enhance natural enemies generally do not ultimately enhance pest regulation. Dominant and non-dominant species of both guilds showed mostly similar responses suggesting that management practices to enhance service provisioning by a certain guild can also enhance the overall diversity of that particular guild.</p>
Data from: Exploring the hidden landscape of female preferences for complex signals
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Complex urban environments provide Apis mellifera with a richer plant forage than suburban and more rural landscapes
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Inconsistent responses of carabid beetles and spiders to land-use intensity and landscape complexity in Northwestern Europe
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Local adaptation across a complex bioclimatic landscape in two montane bumble bee species
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Data from: Phylogeography of the highly dispersible landscape-dominant woody species complex, Metrosideros, in Hawaii
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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.