Find research datasets worth reusing

opencc-by-4.0Jan 2020View details →

Supplementary Information to: Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high–resolution visible channel: Evaluation of candidate approaches with MODIS observations

This repository contains the Python programmes and datasets used for the research described in the following paper: https://doi.org/10.5194/amt-2019-334 It has been prepared as supplementary information to the final paper. Note that the actual Cloud Property Retrieval (CPP) which would be required for full reproducability of the results cannot be made available by the authors, that the code included here is based on Python2, and that paths to the dataset have to be adapted in the code. The repository consists of three separate parts/directories: * method: Python routines for generating the cloud property retrieval   input based on the Meteosat and MODIS data * analysis: Python routines for analysing the different experiments   from the CPP outputs, producing the figures and calculating the   comparison statistics * datasets: the various input and output datasets used for the   analyses of the paper

openother-openFeb 2020View details →

Quantifying the Spatial Variability of a Snowstorm Using Differential Airborne Lidar

Dataset consists of a single folder that includes all data used for the publication entitled: Quantifying the Spatial Variability of a Snowstorm Using Differential Airborne Lidar. Within the folder is a README file that describes the data structure.

opencc-by-4.0Apr 2020View details →

Hydrate spatial distribution influence on the mechanical behavior hydrate-bearing sediment using computed tomography

This supporting information includes two Movie S1-2, illustrating the deformation evolution of the specimen # O-1 and specimen # O-2. Movie S1 is uploaded with file name Movie S1.gif. Detailed information includes the deformation evolution of the specimen # O-1. Movie S2 is uploaded with file name Movie S2. gif. Detailed information includes the deformation evolution of the specimen # O-2.

opencc-by-4.0Jul 2020View details →

SpaGE Spatial Gene Enhancement using scRNA-seq

Spatial transcriptomics and scRNA-seq datasets using for integration and prediction of spatially non-measured genes using SpaGE

opencc-zeroJan 2021View details →

Integrating stakeholders' perspectives and spatial modelling to develop scenarios of future land use and land cover change in northern Tanzania

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.

opencc-zeroDec 2014View details →

Data from: Using the Spatial Population Abundance Dynamics Engine for conservation management

1. An explicit spatial understanding of population dynamics is often critical for effective management of wild populations. Sophisticated approaches are available to simulate these dynamics, but are largely either spatially homogeneous or agent-based, and thus best suited to small spatial or temporal scales. These approaches also often ignore financial decisions crucial to choosing management approaches on the basis of cost-effectiveness. 2. We created a user-friendly and flexible modelling framework for simulating these population issues at large spatial scales – the Spatial Population Abundance Dynamics Engine (SPADE). SPADE is based on the STAR model (McMahon et al. 2010) and uses a reaction-diffusion approach to model population trajectories and a cost-benefit analysis technique to calculate optimal management strategies over long periods and across broad spatial scales. It expands on STAR by incorporating species interactions and multiple concurrent management strategies, and by allowing full user control of functional forms and parameters. 3. We used SPADE to simulate the eradication of feral domestic cats Felis catus on sub-Antarctic Marion Island (Bester et al. 2002) and compared modelled outputs to observed data. The parameters of the best-fitting model reflected the conditions of the management programme, and the model successfully simulated the observed movement of the cat population to the southern and eastern portion of the island under hunting pressure. We further demonstrated that none of the management strategies would likely have been successful within a reasonable timeframe if performed in isolation. 4. SPADE is applicable to a wide range of population management problems, and allows easy generation, modification and analysis of management scenarios. It is a useful tool for the planning, evaluation and optimisation of the management of wild populations, and can be used without specialised training.

opencc-zeroDec 2010View details →

Data from: Stay at home aphids: comparative spatial and seasonal metapopulation structure and dynamics of two specialist tansy aphid species studied using microsatellite markers

Two tansy-feeding aphids – Macrosiphoniella tanacetaria (MA) and Metopeurum fuscoviride (ME) – were studied at a small spatial scale in and around Jena (< 80 km2) using polymorphic microsatellite markers. Both species were found in ~ 60% of sites formerly known to harbour the aphids, although generally when they did occur, they occurred singly (MA ~ 50%; ME ~60%) and rarely together on the same plant at the same time (~10%) and then usually only in the early part of the growing season. This difference may be due to quasi-apparent competition effects elicited to ants farming ME aphids, and preferentially actively eliminating or disturbing MA aphids. In terms of population genetics, both aphids showed extreme genetic heterogeneity within a metapopulation structure, ME more than MA, i.e. higher FST values, ~ 0.4 vs. 0.15, respectively, and limited levels of interpopulation gene flow. Subpopulations often deviated from Hardy-Weinberg equilibrium and showed linkage disequilibria, as expected in animals with extended parthenogenetic reproduction, and had positive FIS values for most large samples, suggesting inbreeding, and possibly philopatry, certainly in ME. Hierarchical analysis (allele range and number per locus, analysis of molecular variance and FST) strongly suggested that the plant rather than site governs the level of genetic variation. Bayesian clustering analysis revealed that both species had heterogeneous historical genetic patterning, with K (number of subgroups) ranging from 3-7. Evidence is also provided from isolation by distance (IBD) and private allele analyses, that in MA, the presence of winged autumn males, absent in ME where males are wingless, influences comparative population genetic structuring, such that ME subpopulations are comparatively more inbred and genetically differentiated than MA subpopulations. Lastly, additional spatial arrangement (ALLELES-IN-SPACE) analysis showed that in both species, certain subpopulations were genetically isolated from the remainder, probably due to geographical barriers, including intervening buildings and woods. As such, the biology of these tansy aphids living in semi-natural habitats is very different from many pest aphid species examined within agro-ecosystems and infesting ephemeral crops, since the former seem much more reluctant to fly and hence show contrastingly much higher levels of interpopulation divergence, even at small spatial scales as here investigated. Indeed, the number of genotypic clusters found for tansy aphids found using Bayesian approaches is similar to that for the major pest the peach-potato aphid, Myzus persicae, globally.

opencc-zeroJun 2019View details →

Data from: Seasonality in spatial distribution: climate and land use have contrasting effects on the species richness of breeding and wintering birds

Aim: Many studies have examined large-scale distributions of various taxa and their drivers, emphasizing the importance of climate, topography, and land-use. Most studies have dealt with distributions over a single season or annually without considering seasonality. However, animal distributions and their drivers can differ among seasons because many animals migrate to suitable climates and areas with abundant prey resources. We aim to clarify seasonality in bird distributions and their drivers. Location: Japan. Methods: We examined the effects of climate (annual mean temperature, snow depth), topography (elevation), and land use (extent of surrounding habitat) on bird species richness, in the breeding and wintering seasons separately, using nationwide data (254 forest and 43 grassland sites, respectively). We separately analyzed the species richness of all species, residents, short-, and long-distance migrants in forests and grasslands. Results: In the breeding season, the annual mean temperature negatively affected all groups (except for forest and grassland residents), and the extent of surrounding habitat positively affected many groups. By contrast, in the wintering season, temperature positively affected all groups (except for forest residents), and the extent of surrounding habitat positively affected only grassland long-distance migrants. In both seasons, the species richness of forest and grassland residents was high in regions of moderate and high temperature, respectively. Moreover, snow depth negatively affected all forest groups in the wintering season. Mapping expected species richness suggested that regions with different climates served as habitats for different groups during different seasons. Main conclusions: All regions were important bird habitats depending on the season, reflecting the contrasting effects of temperature across seasons. In the breeding season, surrounding land-use was also an important driver. To understand the seasonal role that each region and environment plays in maintaining species/communities, a large-scale study considering both environmental seasonality and species distribution is needed.

opencc-zeroDec 2017View details →

Data from: Using satellite AIS to improve our understanding of shipping and fill gaps in ocean observation data to support marine spatial planning

1. A key stage underpinning marine spatial planning (MSP) involves mapping the spatial distribution of ecological processes and biological features, as well the social and economic interests of different user groups. One sector, merchant shipping (vessels that transport cargo or passengers), however, is often poorly represented in MSP due to a perceived lack of fine-scale spatially explicit data to support decision making processes. 2. Here, using the Republic of Congo as an example, we show how publicly accessible satellite derived Automatic Identification System (S-AIS) data can address gaps in ocean observation data for shipping at a national scale. We also demonstrate how fine-scale (0.05 km2 resolution) spatial data layers derived from S-AIS (intensity, occupancy) can be used to generate maps of vessel pressure to provide an indication of patterns of impact on the marine environment and potential for conflict with other ocean-user groups. 3. We reveal that passenger vessels, offshore service vessels, bulk carrier and cargo vessels and tankers account for 93.7% of all vessels and vessel traffic annually, and that these sectors operate in a combined area equivalent to 92% of Congo's exclusive economic zone(EEZ) – far exceeding the areas allocated for other user-groups (conservation, fisheries and petrochemicals). We also show that the shallow coastal waters and habitats of the continental shelf are subject to more persistent pressure associated with shipping; and that the potential for conflict among user groups is likely to be greater with fisheries, whose zones are subject to the highest vessel pressure scores than with conservation or petrochemical sectors. 4. Synthesis and applications. Shipping dominates ocean use, and so excluding this sector from decision making could lead to increased conflict among user groups, poor compliance and negative environmental impacts. This study demonstrates how Satellite derived Automatic Identification System data can provide a comprehensive mechanism to fill gaps in ocean observation data and visualise patterns of vessel behaviour and potential threats to better support marine spatial planning at national scales.13-Feb-2018

Data from: Examining disease prevalence for species of conservation concern using non-invasive spatial capture-recapture techniques

1. Non-invasive techniques have long been used to estimate wildlife population abundance and density. However, recent technological breakthroughs have facilitated non-invasive estimation of the proportion of animal populations with certain diseases. Giraffes Giraffa camelopardalisare increasingly becoming recognized as a species of conservation concern with decreasing population trajectories across their range in Africa. 2. Diseases may be an important component impacting giraffe population declines, and the emerging 'Giraffe Skin Disease' (GSD), characterized by the appearance of wrinkled skin and alopecic lesions on the limbs, neck, and chest of infected giraffe, may hinder movement causing increased susceptibility to predation. 3. We examined the prevalence of GSD in Tanzania's Ruaha National Park over a 4-month period in 2015, using photographic capture–recapture surveys via road-based transects. We divided the study area into five circuitous survey units, each approximately 100 km in length ($\bar x$ = 99.22 km, SD = 3.72), and surveyed for giraffes for four months. From these surveys, we developed a database of spatially-explicit giraffe photographs. 4. We processed these photos for individual identification and fitted spatial capture–recapture models to predict the spatial configuration of giraffe abundance and GSD prevalence within the study area. 5. Our results indicated that >86% of the giraffe population showed signs of GSD and that the disease was more prevalent in the northern and north-eastern portion of Ruaha National Park. 6. Synthesis and applications. Our research shows that data from non-invasive surveys can be used in spatial capture–recapture (SCR) models to estimate the proportion of a population affected by a visible disease. Researchers and conservationists can use SCR models to better examine the variation in parameters associated with these populations such as sex and age class, movement, and encounter rate, which may be linked to the prevalence of the disease, while incorporating broad spatial and temporal dimensions of the population in such areas. We discuss the implications of this research for conservation of threatened species with an emphasis on disease ecology and vulnerability to predations, and more broadly, for wildlife conservation.

Data from: Counting cats: spatially explicit population estimates of cheetah (Acinonyx jubatus) using unstructured sampling data

Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.22 ± 0.301 and 1.28 ± 0.322 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed 'hotspots' of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species.

Data from: Using camera trapping and hierarchical occupancy modelling to evaluate the spatial ecology of an African mammal community

Emerging conservation paradigms have shifted from single to multi-species approaches focused on sustaining biodiversity. Multi-species hierarchical occupancy modelling provides a method for assessing biodiversity while accounting for multiple sources of uncertainty. We analysed camera trapping data with multi-species models using a Bayesian approach to estimate the distributions of a terrestrial mammal community in northern Botswana and evaluate community, group, and species-specific responses to human disturbance and environmental variables. Groupings were based on two life-history traits: body size (small, medium, large and extra-large) and diet (carnivore, omnivore and herbivore). We photographed 44 species of mammals over 6607 trap nights. Camera station-specific estimates of species richness ranged from 8 to 27 unique species, and species had a mean occurrence probability of 0·32 (95% credible interval = 0·21–0·45). At the community level, our model revealed species richness was generally greatest in floodplains and grasslands and with increasing distances into protected wildlife areas. Variation among species' responses was explained in part by our species groupings. The positive influence of protected areas was strongest for extra-large species and herbivores, while medium-sized species actually increased in the non-protected areas. The positive effect of grassland/floodplain cover, alternatively, was strongest for large species and carnivores and weakest for small species and herbivores, suggesting herbivore diversity is promoted by habitat heterogeneity. Synthesis and applications. Our results highlight the importance of protected areas and grasslands in maintaining biodiversity in southern Africa. We demonstrate the utility of hierarchical Bayesian models for assessing community, group and individual species' responses to anthropogenic and environmental variables. This framework can be used to map areas of high conservation value and predict impacts of land-use change. Our approach is particularly applicable to the growing number of camera trap studies world-wide, and we suggest broader application globally will likely result in reduced costs, improved efficiency and increased knowledge of wildlife communities.

opencc-zeroDec 2012View details →

Data from: Optimizing the trade-off between spatial and genetic sampling efforts in patchy populations: towards a better assessment of functional connectivity using an individual-based sampling scheme

Genetic data are increasingly used in landscape ecology for the indirect assessment of functional connectivity, i.e. the permeability of landscape to movements of organisms. Among available tools, matrix correlation analyses (e.g. Mantel tests or mixed models) are commonly used to test for the relationship between pairwise genetic distances and movement costs incurred by dispersing individuals. When organisms are spatially clustered, a population-based sampling scheme (PSS) is usually performed, so that a large number of genotypes can be used to compute pairwise genetic distances on the basis of allelic frequencies. Because of financial constraints, this kind of sampling scheme implies a drastic reduction in the number of sampled aggregates, thereby reducing sampling coverage at the landscape level. We used matrix correlation analyses on simulated and empirical genetic datasets to investigate the efficiency of an individual-based sampling scheme (ISS) in detecting isolation-by-distance and isolation-by-barrier patterns. Provided that pseudo-replication issues are taken into account (e.g. through restricted permutations in Mantel tests), we showed that the use of inter-individual measures of genotypic dissimilarity may efficiently replace inter-population measures of genetic differentiation: the sampling of only three or four individuals per aggregate may be sufficient to efficiently detect specific genetic patterns in most situations. The ISS proved to be a promising methodological alternative to the more conventional PSS, offering much flexibility in the spatial design of sampling schemes and ensuring an optimal representativeness of landscape heterogeneity in data, with few aggregates left unsampled. Each strategy offering specific advantages, a combined use of both sampling schemes is discussed.

opencc-zeroDec 2018View details →

Data from: Use of classical bird census transects as spatial replicates for hierarchical modeling of an avian community

New monitoring programs are often designed with some form of temporal replication to deal with imperfect detection by means of occupancy models. However, classical bird census data from earlier times often lack temporal replication, precluding detection-corrected inferences about occupancy. Historical data have a key role in many ecological studies intended to document range shifts, and so need to be made comparable with present‐day data by accounting for detection probability. We analyze a classical bird census conducted in the region of Murcia (SE Spain) in 1991 and 1992 and propose a solution to estimating detection probability for such historical data when used in a community occupancy model: the spatial replication of subplots nested within larger plots allows estimation of detection probability. In our study, the basic sample units were 1‐km transects, which were considered spatial replicates in two aggregation schemes. We fit two Bayesian multispecies occupancy models, one for each aggregation scheme, and evaluated the linear and quadratic effect of forest cover and temperature, and a linear effect of precipitation on species occupancy probabilities. Using spatial rather than temporal replicates allowed us to obtain individual species occupancy probabilities and species richness accounting for imperfect detection. Species‐specific occupancy and community size decreased with increasing annual mean temperature. Both aggregation schemes yielded estimates of occupancy and detectability that were highly correlated for each species, so in the design of future surveys ecological reasons and cost‐effective sampling designs should be considered to select the most suitable aggregation scheme. In conclusion, the use of spatial replication may often allow historical survey data to be applied formally hierarchical occupancy models and be compared with modern‐day data of the species community to analyze global change process.

Data from: Uncovering spatial variation in acoustic environments using sound mapping

Animals select and use habitats based on environmental features relevant to their ecology and behavior. For animals that use acoustic communication, the sound environment itself may be a critical feature, yet acoustic characteristics are not commonly measured when describing habitats and as a result, how habitats vary acoustically over space and time is poorly known. Such considerations are timely, given worldwide increases in anthropogenic noise combined with rapidly accumulating evidence that noise hampers the ability of animals to detect and interpret natural sounds. Here, we used microphone arrays to record the sound environment in three terrestrial habitats (forest, prairie, and urban) under ambient conditions and during experimental noise introductions. We mapped sound pressure levels (SPLs) over spatial scales relevant to diverse taxa to explore spatial variation in acoustic habitats and to evaluate the number of microphones needed within arrays to capture this variation under both ambient and noisy conditions. Even at small spatial scales and over relatively short time spans, SPLs varied considerably, especially in forest and urban habitats, suggesting that quantifying and mapping acoustic features could improve habitat descriptions. Subset maps based on input from 4, 8, 12 and 16 microphones differed slightly (< 2 dBA/pixel) from those based on full arrays of 24 microphones under ambient conditions across habitats. Map differences were more pronounced with noise introductions, particularly in forests; maps made from only 4-microphones differed more (> 4 dBA/pixel) from full maps than the remaining subset maps, but maps with input from eight microphones resulted in smaller differences. Thus, acoustic environments varied over small spatial scales and variation could be mapped with input from 4–8 microphones. Mapping sound in different environments will improve understanding of acoustic environments and allow us to explore the influence of spatial variation in sound on animal ecology and behavior.

opencc-zeroDec 2016View details →

Data from: Spatial dynamics of habitat use informs reintroduction efforts in the presence of an invasive predator

1. Islands experience major impacts from introduced species, especially nocturnal predators. The Brown Treesnake (Boiga irregularis) extirpated almost the entire native avifauna on Guam shortly after introduction. Reintroductions from neighboring islands can restore bird communities but will take place in heavily managed units where snake populations can be controlled. Yet reintroductions often proceed without relevant biological information such as nocturnal habitat and space use when nocturnal predators are present. To guide efforts, we studied diurnal and nocturnal habitat and space use by the avian frugivore community on the nearby island of Saipan where the snake is absent. 2. Using radio telemetry and a Bayesian framework, we first compared data typically accessible to resource managers (diurnal home range [DHR] and habitat selection) and which often forms the basis of reintroduction plans. We contrast this with data on nocturnal habitat use that is often not available but relevant when nocturnal predation threat is high. 3. DHR size varied within and among species with Micronesian Starlings (Aplonis opaca) having DHRs at least 45 ha larger than other species. For all species, night roost locations were generally spatially clustered within a DHR and covered a smaller spatial extent. Two species had higher probabilities of roosting outside DHR boundaries but, when outside, roosts were often within 200 m of the DHR boundary. All species selected forested habitats during day and night, with some species choosing native forest over non-native habitat. 4. Synthesis and applications If individuals roosted randomly throughout DHR's, landscape-level suppression of B. irregularis might be the only viable option for reintroductions of some species. However, individuals of all species showed clustered roosting and high site fidelity. If site fidelity is common, then individuals that roost within fenced areas where snake populations are severely reduced or eliminated will experience high survivorship even if DHRs extend into surrounding unprotected matrix. There was large overlap in habitat selection during day and night indicating managed areas should be composed of native forest with non-native forests of secondary importance. In systems with nocturnal predators, understanding variability in diurnal and nocturnal habitat use could lead to better informed decisions.

opencc-by-4.0Mar 2024View details →

Experimental files for Spatial and temporal evolution of laser plasma produced using a double-stream gas puff target

Spatial and temporal evolution of laser plasma produced as a result of irradiation of an argon/helium gas puff target with short (1.3 ns) or long (6 ns) laser pulses generated with an Nd:YAG laser system was investigated. Imaging and spectral measurements of SXR emission from the plasma, created in the double-stream gas puff target, have been performed with the use of an x-ray streak camera. The experimental data.zip file contains the experimental data from an spectral and imaging systems coupled to an X-ray streak camera. Work supported by the National Science Centre, Poland, grant agreement no. 2020/39/B/ST2/00509

opencc-by-4.0Mar 2024View details →

Processed datasets used in Almet et al. (2024), "Inferring pattern-driving intercellular flows from single-cell and spatial transcriptomics"

These are the processed anndata objects used in Almet et al. (2024), "Inferring pattern-driving intercellular flows from single-cell and spatial transcriptomics". These datasets are stored as .h5ad files and are intended to be used with the <a href="https://scanpy.readthedocs.io/en/stable/api.html">Scanpy</a> package in Python. They contain all relevant cell type annotation, unnormalized and transformed gene expression counts, as well as the inferred intercellular fow networks inferred by FlowSig.

opencc-by-4.0Oct 2024View details →

Profiling the heterogeneity of colorectal cancer consensus molecular subtypes using spatial transcriptomics: fastq & bam files - Sample S5_Rec

You can find here the fastq and bam files related to the datasets used in the publication:  In this particular upload, you can find the fastq (version1) and bam (version2) files of the two replicates of sample S5_Rec (A121573) Valdeolivas, A., Amberg, B., Giroud, N. et al. Profiling the heterogeneity of colorectal cancer consensus molecular subtypes using spatial transcriptomics. npj Precis. Onc. 8, 10 (2024). https://doi.org/10.1038/s41698-023-00488-4