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1,855 results for “Framework”
Data from: Below-ground causes and consequences of woodland shrub invasions: a novel paired-point framework reveals new insights
1. Confirming the impacts of invasive plants is essential for prioritizing management efforts, but is challenging, especially if impacts occur below ground and over long periods as hypothesized for woodland shrub invasions. 2. For this reason, we developed a novel "paired-point" framework capable of detecting the below-ground impacts of slow-growing invasive plants from short-term datasets in an investigation into the below-ground consequences of European buckthorn Rhamnus cathartica L. (hereafter buckthorn) invasions into Chicago-area woodlands. We measured differences between the members of 97 pairs of buckthorn-invaded and buckthorn-free points in ten below-ground response variables (RVs) that buckthorn is hypothesized to alter (listed below). We then modelled these differences (ΔRVs) in response to the severity of the invasion found at each invaded point. A relationship (linear or non-linear) between a ΔRV and severity, i.e. slope ≠ 0, suggests a buckthorn-induced change. An intercept (value of ΔRV where severity = 0) different from zero suggests a pre-existing difference. 3. Relating differences to an invasion gradient rather than simply noting their presence provided evidence that the higher levels of moisture, pH, total C, total N, NH4+-N, and Ca2+ in invaded soils pre-date and possibly promote invasion (particularly Ca2+), and that neither earthworm biomass nor soil C:N ratios are associated with buckthorn invasion, all of which suggest buckthorn to be less of a "driver" of below-ground change than hypothesized. We did, however, find evidence that buckthorn establishes in areas having greater leaf-litter mass and higher rates of decomposition, and then proceeds to accelerate decomposition further and to alter spring soil NO3--N levels. 4. Synthesis and applications. Our findings suggest that decisions regarding regional buckthorn management should be less driven by concerns about buckthorn's below-ground impacts, and that greater consideration of how variation in below-ground factors relates to invader establishment is needed, rather than simply assuming this variation to be invader-induced. This latter consideration can help to design better-targeted monitoring programs, limiting the further spread of woodland invaders. These insights illustrate the utility of the paired-point framework both for investigating below-ground causes and consequences of slow-growing invasive plants and for guiding the management of these invasions.
Data from: Necrobiome framework for bridging decomposition ecology of autotrophically and heterotrophically derived organic matter
Decomposition contributes to global ecosystem function by contributing to nutrient recycling, energy flow and limiting biomass accumulation. The decomposer organisms influencing this process form diverse, complex, and highly dynamic communities that often specialize on different plant or animal resources. Despite performing the same net role, there is a need to conceptually synthesize information on the structure and function of decomposer communities across the spectrum of dead plant and animal resources. A lack of synthesis has limited cross-disciplinary learning and research in important areas of ecosystem and community ecology. Here we expound on the 'necrobiome' concept and develop a framework describing the decomposer communities and their interactions associated with plant and animal resource types within multiple ecosystems. We outline the biotic structure and ecological functions of the necrobiome, along with how the necrobiome fits into a broader landscape and ecosystem context. The expanded necrobiome model provides a set of perspectives on decomposer communities across resource types, and conceptually unifies plant and animal decomposer communities into the same framework, while acknowledging key differences in processes and mechanisms. This framework is intended to raise awareness among researchers, and advance the construction of explicit, mechanistic hypotheses that further our understanding of decomposer community contributions to biodiversity, the structure and function of ecosystems and global nutrient recycling and energy flow.
Data from: An integrated framework to identify wildlife populations under threat from climate change
Climate change is a major threat to global biodiversity that will produce a range of new selection pressures. Understanding species responses to climate change requires an interdisciplinary perspective, combining ecological, molecular and environmental approaches. We propose an applied integrated framework to identify populations under threat from climate change based on their extent of exposure, inherent sensitivity due to adaptive and neutral genetic variation and range shift potential. We consider intraspecific vulnerability and population-level responses, an important but often neglected conservation research priority. We demonstrate how this framework can be applied to vertebrates with limited dispersal abilities using empirical data for the bat Plecotus austriacus. We use ecological niche modelling and environmental dissimilarity analysis to locate areas at high risk of exposure to future changes. Combining outlier tests with genotype-environment association analysis we identify potential climate-adaptive SNPs in our genomic dataset and differences in the frequency of adaptive and neutral variation between populations. We assess landscape connectivity and show that changing environmental suitability may limit the future movement of individuals, thus affecting both the ability of populations to shift their distribution to climatically suitable areas and the probability of evolutionary rescue through the spread of adaptive genetic variation among populations. Therefore a better understanding of movement ecology and landscape connectivity is needed for predicting population persistence under climate change. Our study highlights the importance of incorporating genomic data to determine sensitivity, adaptive potential and range shift potential, instead of relying solely on exposure to guide species vulnerability assessments and conservation planning.
Data from: How can we get close to zero?: the potential contribution of biomedical prevention and the investment framework towards an effective response to HIV
Background: In 2011 an Investment Framework was proposed that described how the scale-up of key HIV interventions could dramatically reduce new HIV infections and deaths in low and middle income countries by 2015. This framework included ambitious coverage goals for prevention and treatment services resulting in a reduction of new HIV infections by more than half. However, it also estimated a leveling in the number of new infections at about 1 million annually after 2015. Methods: We modeled how the response to AIDS can be further expanded by scaling up antiretroviral treatment (ART) within the framework provided by the 2013 WHO treatment guidelines. We further explored the potential contributions of new prevention technologies: 'Test and Treat', pre-exposure prophylaxis and an HIV vaccine. Findings: Immediate aggressive scale up of existing approaches including the 2013 WHO guidelines could reduce new infections by 80%. A 'Test and Treat' approach could further reduce new infections. This could be further enhanced by a future highly effective pre-exposure prophylaxis and an HIV vaccine, so that a combination of all four approaches could reduce new infections to as low as 80,000 per year by 2050 and annual AIDS deaths to 260,000. Interpretation: In a set of ambitious scenarios, we find that immediate implementation of the 2013 WHO antiretroviral therapy guidelines could reduce new HIV infections by 80%. Further reductions may be achieved by moving to a 'Test and Treat' approach, and eventually by adding a highly effective pre-exposure prophylaxis and an HIV vaccine, if they become available.
Data from: Towards a predictive framework for biocrust mediation of plant performance: a meta-analysis
Understanding the importance of biotic interactions in driving the distribution and abundance of species is a central goal of plant ecology. Early vascular plants likely colonized land occupied by biocrusts — photoautotrophic, surface-dwelling soil communities comprised of cyanobacteria, bryophytes, lichens, and fungi — suggesting biotic interactions between biocrusts and plants may have been at play for some 2,000 million years. Today, biocrusts coexist with plants in dryland ecosystems worldwide, and have been shown to both facilitate or inhibit plant species performance depending on ecological context. Yet, the factors that drive the direction and magnitude of these effects remain largely unknown. We conducted a meta-analysis of plant responses to biocrusts using a global dataset encompassing 1,004 studies from six continents. Our meta-analysis revealed there is no simple positive or negative effect of biocrusts on plants. Rather, plant responses differ by biocrust composition and plant species traits and vary across plant ontogeny. Moss-dominated biocrusts facilitated, while lichen-dominated biocrusts inhibited overall plant performance. Plant responses also varied among plant functional groups: C4 grasses received greater benefits from biocrusts compared to C3 grasses, and plants without N-fixing symbionts responded more positively to biocrusts than plants with N-fixing symbionts. Biocrusts decreased germination but facilitated growth of non-native plant species. Our results suggest that interspecific variation in plant responses to biocrusts, contingent on biocrust type, plant traits, and ontogeny can have strong impacts on plant species performance. These findings have important implications for understanding plant community assembly processes and ecosystem responses to global change.
Data from: A conceptual framework for clutch size evolution in songbirds
Causes of evolved differences in clutch size among songbird species remain debated. I propose a new conceptual framework that integrates aspects of traditional life history theory, while including novel elements, to explain evolution of clutch size among songbirds. I review evidence that selection by nest predation on length of time that offspring develop in the nest creates a gradient in offspring characteristics at nest-leaving (fledging), including flight mobility, spatial dispersion, and self-feeding rate. I postulate that this gradient has consequences for offspring mortality rates and parental energy expenditure per offspring. These consequences then determine how reproductive effort is partitioned among offspring, while reproductive effort evolves from age-specific mortality effects. Using data from a long-term site in Arizona, as well as from the literature, I provide support for hypothesized relationships. Nestling development period consistently explains fledgling mortality, energy expenditure per offspring, and clutch size while accounting for reproductive effort (i.e., total energy expenditure) to thereby support the framework. Tests in this paper are not definitive, but they document previously unrecognized relationships and address diverse traits (developmental strategies, parental care strategies, energy requirements per offspring, evolution of reproductive effort, clutch size) that justify further investigations of hypotheses proposed here.
Data from: Linking functional diversity and ecosystem processes: a framework for using functional diversity metrics to predict the ecosystem impact of functionally unique species
1.Functional diversity (FD) metrics are widely used to assess invasion ecosystem impacts, but we have limited theory to predict how FD should respond to invasion. A key challenge to effectively using FD metrics is the complexity of conceptualizing alterations to multi-dimensional trait space, making it difficult to select a priori the most appropriate metric for specific ecological questions. 2.Here, we provide expectations on how invasion should change four commonly used FD metrics—functional richness (FRic), evenness (FEve), divergence (FDiv), and dispersion (FDis)—and then test these expectations in a lab decomposition experiment. We simulate invasion of a forest by understory plants by adding leaf litter from 18 natives and nonnatives to a representative canopy tree litter mixture to test changes in FD and decomposition. 3.All four metrics changed predictably with invasion. Species that were more functionally unique or when added at greater proportions had larger impacts on FD. Overall, FRic, FEve, and FDiv were poor choices for understanding impacts of nonnative species. FDis was the only metric that both changed predictably with addition of understory litter and correlated intuitively with changes in carbon mineralization. Furthermore, ranking species based upon how much they changed FDis of the litter mixture provided a fair assessment of which species had the largest impact on decomposition. As such, functional dispersion may be a key tool for predicting a priori which nonnatives will have the greatest impact on ecosystem processes. 4.Synthesis: We highlight the need to assess the suitability of each FD metric for the specific ecological question at hand. Our work reveals the pitfalls of considering multiple metrics or randomly choosing a single metric without suitability assessments. At the same time, it suggests a framework for metric assessment that should help lead to selection of a metric or metrics that provide robust a priori insights into how invasion by nonnative species can impact ecosystem processes.
Data from: Implementing an evolutionary framework for understanding genetic relationships of phenotypically defined insect biotypes in the invasive soybean aphid (Aphis glycines)
Adaptive evolution of pest insects in response to the introduction of resistant cultivars is well documented and commonly results in virulent (i.e. capable of feeding upon resistant cultivars) insect populations being labeled as distinct biotypes. Phenotypically defined, biotypes frequently remain evolutionarily indistinct, resulting in ineffective application of virulence control measures and shorter durability of resistant cultivars. Here we utilize an evolutionary framework to discern the genetic relationship between biotypes of the soybean aphid (Aphis glycines, Matsumura). The soybean aphid is invasive in North America, and is among the most destructive pests of commercial soybean on the continent. Attempts to breed host-plant resistant soybean have been hampered by the emergence of virulent aphid biotypes that are unaffected by the plant's resistance mechanism(s). Comparative population genetic analysis of virulent and avirulent (i.e. unable to feed on resistant cultivars) biotypes found populations to be genetically indistinguishable across biotype and geographic distance, with high rates of inter-population immigration and admixture. The lack of genetic distinction between biotypes coupled with elevated genotypic diversity within all populations suggested virulence has a non-genetic based or includes a gene complex that is widely distributed throughout soybean aphid populations, which undergo regular dispersal and unimpeded sexual recombination.
Data from: Evaluating population receptive field estimation frameworks in terms of robustness and reproducibility
Within vision research retinotopic mapping and the more general receptive field estimation approach constitute not only an active field of research in itself but also underlie a plethora of interesting applications. This necessitates not only good estimation of population receptive fields (pRFs) but also that these receptive fields are consistent across time rather than dynamically changing. It is therefore of interest to maximize the accuracy with which population receptive fields can be estimated in a functional magnetic resonance imaging (fMRI) setting. This, in turn, requires an adequate estimation framework providing the data for population receptive field mapping. More specifically, adequate decisions with regard to stimulus choice and mode of presentation need to be made. Additionally, it needs to be evaluated whether the stimulation protocol should entail mean luminance periods and whether it is advantageous to average the blood oxygenation level dependent (BOLD) signal across stimulus cycles or not. By systematically studying the effects of these decisions on pRF estimates in an empirical as well as simulation setting we come to the conclusion that a bar stimulus presented at random positions and interspersed with mean luminance periods is generally most favorable. Finally, using this optimal estimation framework we furthermore tested the assumption of temporal consistency of population receptive fields. We show that the estimation of pRFs from two temporally separated sessions leads to highly similar pRF parameters.
Data from: Assemblage Accumulation Curves: A framework for resolving species accumulation in biological communities using chloroplast genome sequences
The timing and tempo of the processes involved in community assembly are of substantial concern to community ecologists and conservation managers. The fossil record is a valuable source of data for studying past changes in community composition, but it is not always detailed enough to allow the process of community assembly to be resolved at regional or site scales while tracing the trajectories of known species with associated known traits. We present a three‐step framework for studying present‐day species accumulation through time: DNA sampling from multiple individuals from multiple species within a community; estimates of coalescence times for each species using molecular dating methods; and plotting the accumulation of present‐day species through time using the inferred population ages. Our approach is illustrated using whole chloroplast genomes from plants from three rainforest communities in eastern Australia. Expected times to coalescence for multiple species in each community were inferred from pooled high‐throughput sequence libraries. Local assemblage accumulation curves for each community were constructed. We also explored the variation in assemblage accumulation curves of species with different functional traits. Models of equilibrium species richness informed our null hypothesis and largely explained the shape of the assemblage accumulation curves and indicated that the complexities of the accumulation process should be explored with additional parameters, for example allowing species classes with different extinction rates. The assemblage accumulation curves for the study sites showed evidence of recent population expansions within each of the communities. This signal of recent accumulation is consistent with the increase in suitable rainforest habitat that followed the Last Glacial Maximum. Our method of constructing assemblage accumulation curves provides a simple approach for visualizing species‐accumulation data. It can be used to test hypotheses such as the relative survival potential of species‐specific ecological attributes. Although our example used single‐nucleotide polymorphisms derived from whole‐chloroplast sequencing, this framework can be applied to mitochondrial genomes and to communities of other organisms.
Data from: A metabarcoding framework for facilitated survey of endolithic phototrophs with tufA
Background: In spite of their ecological importance as primary producers and microbioeroders of marine calcium carbonate (CaCO3) substrata, endolithic phototrophs spanning both prokaryotic (the cyanobacteria) and eukaryotic algae lack established molecular resources for their facilitated survey with high throughput sequencing. Here, the development of a metabarcoding framework for the elongation factor EF-Ttu (tufA) was tested on four Illumina-sequenced marine CaCO3 microfloras for the characterization of their endolithic phototrophs, especially the abundant bioeroding Ostreobium spp. (Ulvophyceae). The framework consists of novel tufA degenerate primers and a comprehensive database enabling Operational Taxonomic Unit (OTU) identification at multiple taxonomic ranks with percent identity thresholds determined herein. Results: The newly established tufA database comprises 4057 non-redundant sequences (from 1339 eukaryotic and prokaryotic phototrophs, and 2718 prokaryotic heterotrophs) including 27 classes in 10 phyla of phototrophic diversity summarized from data mining on GenBank®, our barcoding of >150 clones produced from coral reef microfloras, and >300 eukaryotic phototrophs (>230 Ulvophyceae including >100 'Ostreobium' spp., and >70 Florideophyceae, Phaeophyceae and miscellaneous taxa). Illumina metabarcoding with the newly designed primers resulted in 802 robust OTUs including 618 phototrophs and 184 heterotrophs (77 and 23 % of OTUs, respectively). Phototrophic OTUs belonged to 14 classes of phototrophs found in seven phyla, and represented ~98 % of all reads. The phylogenetic profiles of coral reef microfloras showed few OTUs in large abundance (proportion of reads) for the Chlorophyta (Ulvophyceae, i.e. Ostreobium and Phaeophila), the Rhodophyta (Florideophyceae) and Haptophyta (Coccolithophyceae), and a large diversity (richness) of OTUs in lower abundance for the Cyanophyta (Cyanophyceae) and the Ochrophyta (the diatoms, 'Bacillariophyta'). The bioerosive 'Ostreobium' spp. represented four families in a large clade of subordinal divergence, i.e. the Ostreobidineae, and a fifth, phylogenetically remote family in the suborder Halimedineae (provisionally assigned as the 'Pseudostreobiaceae'). Together they harbor 85–95 delimited cryptic species of endolithic microsiphons. Conclusions: The novel degenerate primers allowed for amplification of endolithic phototrophs across a wide phylogenetic breadth as well as their recovery in very large proportions of reads (overall 98 %) and diversity (overall 77 % of OTUs). The established companion tufA database and determined identity thresholds allow for OTU identification at multiple taxonomic ranks to facilitate the monitoring of phototrophic assemblages via metabarcoding, especially endolithic communities rich in bioeroding Ulvophyceae, such as those harboring 'Ostreobium' spp., Phaeophila spp. and associated algal diversity.
Data from: A new integrative framework for large-scale assessments of biodiversity and community dynamics, using littoral gastropods and crabs of British Columbia, Canada
Improving our understanding of species responses to environmental changes is an important contribution ecologists can make to facilitate effective management decisions. Novel synthetic approaches to assessing biodiversity and ecosystem integrity are needed, ideally including all species living in a community and the dynamics defining their ecological relationships. Here we present and apply an integrative approach that links high-throughput, multi-character taxonomy with community ecology. The overall purpose is to enable the coupling of biodiversity assessments with investigations into the nature of ecological interactions in a community-level data set. We collected 1,195 gastropods and crabs in British Columbia. First, the General mixed Yule-coalescent (GMYC) and the Poisson Tree Processes (PTP) methods for proposing primary species-hypotheses based on cox1 sequences were evaluated against an integrative taxonomic framework. We then used data on the geographic distribution of delineated species to test species co-occurrence patterns for non-randomness using community-wide and pairwise approaches. Results showed that PTP generally outperformed GMYC and thus constitutes a more effective option for producing species-hypotheses in community-level datasets. Non-random species co-occurrence patterns indicative of ecological relationships or habitat preferences were observed for grazer gastropods, whereas assemblages of opportunistic omnivorous gastropods and crabs appeared influenced by random processes. Species-pair associations were consistent with current ecological knowledge, thus suggesting that applying community assembly within a large taxonomical framework constitutes a valuable tool for assessing ecological interactions. Combining phylogenetic, morphological and co-occurrence data enabled an integrated view of communities, providing both a conceptual and pragmatic framework for biodiversity assessments and investigations into community dynamics.
Data from: Markov-modulated Poisson processes as a new framework for analyzing capture-recapture data
1.Opportunistic capture-recapture data consists of observations over non-constant time-intervals and so fails to satisfy the basic assumptions of traditional capture-recapture models. Analyzing opportunistic capture-recapture data is often done by discretizing time-intervals or summarizing data, but without taking into account the continuous-time process of the state and/or the capture. 2.To deal with non-constant time-intervals, continuous-time closed capture-recapture models have been proposed by Yip et al. (1996), Hwang & Chao (2002), Schofield et al. (2017) for estimating population size. More recently, a continuous-time Cormack-Jolly-Seber model has been proposed by Fouchet et al. (2016) to reduce bias in survival rates, and a two-state process has been proposed by Choquet et al. (2017) to estimate reproduction rates and survival rates of young within a season. 3.The aim of the current study is to demonstrate how an approach based on a Markov-modulated Poisson process (MMPP) (Freed & Shepp, 1982) allows, in a similar way to a multistate model, to model opportunistic data using several states. To this end, several multistate models were rewritten as MMPP models, showing, the potential for this approach to address the ecological questions as multistate models, but using an extended data framework. In particular, it is a useful framework for dealing with data that has unordered levels of uncertainty. 4.The methods were illustrated using simulations and analysis of data on the Alpine ibex (Capraibex).
Data from: From randomness to traplining: a framework for the study of routine movement behavior
Memory allows many animals to benefit from the spatial predictability of their environment by revisiting known profitable places. Travel route optimization or resource acquisition constraints usually lead to repeated sequences of visits, which may have major evolutionary and ecological implications. However, the study of this behavior has been impaired by a lack of concepts and methodologies. We here formally define routine movement behavior, provide an index that quantifies the degree of repetitiveness in movement sequences in terms of minimal conditional entropy, and design a flexible procedure that detects the specific subsequences that are repeated. We demonstrate our framework using computer simulations and real-world movement data of black-tailed deer (Odocoileus hemionus) introduced into a novel environment. The simulation example showed that our methods can suitably reveal the increase in the level of routine movement behavior during home range (HR) establishment. Black-tailed deer did not show such an increase, suggesting that HR establishment occurred very fast. In both examples, our procedure determining the subsequences that are repeated provides a precise visualization of routine movements. Our approach solves limitations in the study of routine movement behavior and thus opens promising perspectives for the study of the linkages between cognition, foraging strategies, and environments. Although we developed it to study routine movement behavior, it can be applied to any type of behavioral sequence and should thus be of interest to a broad range of behavioral ecologists.
Data from: Inferring longitudinal hierarchies: framework and methods for studying the dynamics of dominance
1. Social inequality is a consistent feature of animal societies, often manifesting as dominance hierarchies, in which each individual is characterized by a dominance rank denoting its place in the network of competitive relationships among group‐members. Most studies treat dominance hierarchies as static entities despite their true longitudinal, and sometimes highly dynamic, nature. 2. To guide study of the dynamics of dominance, we propose the concept of a longitudinal hierarchy: the characterization of a single, latent hierarchy and it's dynamics over time. Longitudinal hierarchies describe the hierarchy position (r) and dynamics (∆) associated with each individual as a property of its interaction data, the periods into which these data are divided based on a period delineation rule (p), and the method chosen to infer the hierarchy. Hierarchy dynamics result from both active (∆a) and passive (∆p) processes. Methods that infer longitudinal hierarchies should optimize accuracy of rank dynamics as well as of the rank orders themselves, but no studies have yet evaluated the accuracy with which different methods infer hierarchy dynamics. 3. We modify three popular ranking approaches to make them better suited for inferring longitudinal hierarchies. Our three 'informed' methods assign ranks that are informed by data from the prior period rather than calculating ranks de novo in each observation period, and use prior knowledge of dominance correlates to inform placement of new individuals in the hierarchy. These methods are provided in an R package. 4. Using both a simulated dataset and a long‐term empirical dataset from a species with two distinct sex‐based dominance structures, we compare the performance of these methods and their unmodified counterparts. We show that choice of method has dramatic impacts on inference of hierarchy dynamics via differences in estimates of ∆a. Methods that calculate ranks de novo in each period overestimate hierarchy dynamics, but incorporation of prior information leads to more accurately inferred ∆a. Of the modified methods, Informed MatReorder infers the most conservative estimates of hierarchy dynamics and Informed Elo infers the most dynamic hierarchies. 5. This work provides crucially needed conceptual framing and methodological validation for studying social dominance and its dynamics.
Data from: Plant population success across urban ecosystems – a framework to inform biodiversity conservation in cities
1. In a rapidly urbanising world, the ability of plant species to survive and build self-sustaining populations in urban environments is increasingly important for biodiversity conservation. Yet the contribution of cities to biodiversity conservation remains unclear because ecologists have studied biodiversity patterns, largely without considering the population establishment of plants and the ways in which different kinds of urban ecosystems harbour native and endangered plant species. These limitations can mislead conservation policies for cities. 2. To better-understand how urban ecosystems can contribute to biodiversity conservation, we propose a framework that links the population status (casual or established) of plant species with ecosystem novelty and highlights barriers to population establishment in different types of urban ecosystems, from natural remnants to novel ecosystems. 3. To quantify the relative importance of natural remnants vs. human-shaped ecosystems for the conservation of self-sustaining urban plant populations we re-analyse a unique dataset from a metropolitan region in Europe with information on the population status of 1199 plant species. 4. Results demonstrate that urban ecosystems harbour many established native and endangered species although a considerable share (37%) of species of conservation concern are confined to natural remnants. In hybrid and immature novel ecosystems, high species numbers reflect many species with only casual populations. The role of novel ecosystems as habitats for native and endangered plant species increases as novel ecosystems mature. 5. Synthesis and applications. General information about plant species richness in urban environments may mislead conservation policies as different kinds of urban ecosystems can play different roles in harbouring species of conservation concern. Moreover, presence-absence data can mask establishment failures of species. This proposed framework helps to distinguish between casual and established populations of plant species, and highlights barriers to population persistence in urban ecosystems; reflecting different land uses and land use histories over time. Revealing the role of natural remnants vs. hybrid vs. novel ecosystems as habitats for species of conservation concern illustrates opportunities for biodiversity conservation in all urban ecosystems and can support setting priorities for conservation.
An actor-model framework for visual sensory encoding
<pre>This folder contains the dataset used in the article 'An actor-model framework for visual sensory encoding'. </pre> <pre>There are three main folders 'models' contains the trained neural network for the different experiments.<br>The code to load the model and generate the figures in the article is available<br>in https://github.com/lne-lab/actor-retina<br>or at https://doi.org/10.5281/zenodo.10519578 'spikes_data' contains the data used to train the neural network.<br>This can be used to train a network from scratch. 'Van_Hateren_image' contains the image dataset used in the experiments.<br><br>UPDATE (2025-08-22)<br>'stimulus' contains the stimulus used as input to train the forward and actor models.</pre>
Online Companion: A Preference Informed Energy Sharing Framework for a Centralized Energy Community
<p>This manuscript serves as an electronic companion to [1]. We present the complementary input data, including prosumers target demand, PV power generation, and electricity market prices.</p><p> </p><p> </p>
Understanding the Relation Between Performance and Energy-Efficiency in Object-Relational Mapping Frameworks
Open the record for dataset details and reuse information.
Supplementary data as part of the article "Mechanism of Benzene Hydroxylation on Tri-Iron Oxo-Centered Cluster-Based Metal-Organic Frameworks" (https://doi.org/10.1021/acs.jpcc.3c06423)
<p>Cartesian coordinates in the *.XYZ format for all the structures optimized at the M06-L/def2-TZVP in the reactivity study as part of the article "Mechanism of Benzene Hydroxylation on Tri-Iron Oxo-Centered 2 Cluster-Based Metal-Organic Frameworks" (https://doi.org/10.1021/acs.jpcc.3c06423)</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.