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5,805 results for “Data model”
Data from: Modelling the probability of microhabitat formation on trees using cross-sectional data
1. Context: Tree-related microhabitats (TreMs), such as trunk cavities, peeled bark, cracks or sporophores of lignicolous fungi, are essential to support forest biodiversity because they are used as substrate, foraging, roosting or breeding places by bryophytes, fungi, invertebrates and vertebrates. Biodiversity conservation requires the continuous presence of TreMs in a forest. However, little is known about their dynamics. Moreover, we usually have only cross-sectional TreM data (observations of many trees at a single time), making it difficult to estimate TreM formation rates. 2. Method: This study adapted the methods of survival and reliability analysis to model the rate of TreM formation per unit of diameter increment as a function of tree diameter at breast height (DBH). We tested three variants of this model: the TreM formation rate independent of, proportional to or increasing non-linearly with DBH. We calculated the likelihood of the models, considering cross-sectional observations either of TreM presence/absence or TreM number on trees of different sizes. We calibrated the models in six sub-natural montane forests dominated by European beech (Fagus sylvatica) and silver fir (Abies alba) – in the French Pyrenees. Assuming an annual DBH increment value, the annual formation rate of TreMs was predicted both at the level of the tree and at the level of the forest stand. 3. Results: This method provided a coherent framework to model the probability that a TreM forms on a tree during a unit growth step and produces realistic predictions of TreM accumulation on trees. TreM formation accelerated as trees grew for A. alba but not for F. sylvatica. The TreM formation rate was twice as fast on F. sylvatica as on A. alba. We estimated a formation of 0.82–1.28 TreMs/ha per year and 0.5–0.9 TreM bearing trees/ha per year in the sub-natural forests studied. 4. Synthesis and applications: This method makes rigorous modelling of the formation of TreMs possible during the growth of trees and forest stands. The quantitative evaluation of TreM fluxes will help to design forest biodiversity conservation strategies favouring the development and temporal continuity of TreMs.
Data from: Modeling effects of climate change and phase shifts on detrital production of a kelp bed
The exchange of energy and nutrients between ecosystems (i.e., resource subsidies) plays a central role in ecological dynamics over a range of spatial and temporal scales. Little attention has been paid to the role of anthropogenic impacts on natural systems in altering the magnitude, timing, and quality of resource subsidies. Kelp ecosystems are highly productive on a local scale and export over 80% of kelp primary production as detritus, subsidizing consumers across broad spatial scales. Here, we generate a model of detrital production from a kelp bed in Nova Scotia to hindcast trends in detrital production based on temperature and wave height recorded in the study region from 1976 to 2009, and to project changes in detrital production that may result from future climate change. Historical and projected increases in temperature and wave height led to higher rates of detrital production through increased blade breakage and kelp dislodgment from the substratum, but this reduced kelp biomass and led to a decline in detrital production in the long term. We also used the model to demonstrate that the phase shift from a highly productive kelp bed to a low-productivity barrens, driven by the grazing activity of sea urchins, reduces kelp detrital production by several orders of magnitude, an effect that would be exacerbated by projected increases in temperature and wave action. These results indicate that climate-mediated changes in ecological dynamics operating on local scales may alter the magnitude of resource subsidies to adjacent ecosystems, affecting ecological dynamics on regional scales.
Data from: Self-cannulation for haemodialysis: patient attributes, clinical correlates and self-cannulation predilection models
Background and objectives: With emerging evidence in support of home haemodialysis (HHD), patient factors which determine uptake of the modality need to be better understood. Self-cannulation (SC) is a major step towards enabling self-care 'in-centre' and home HD and remains the foremost barrier to its uptake. Human factors governing this aspect of HD practice are poorly understood. The aim of this study is to better understand self-cannulation preferences and factors which define them in end stage renal disease (ESRD). Design: In this multicentre study, 508 of 535 patients from predialysis (Group A: n=222), in-centre (Group B: n= 213), and home HD (Group C: n= 100) responded to a questionnaire with 3 self-cannulation questions. Simultaneously, data on clinical, cognitive and psychosocial variables were ascertained. The primary outcome measure was 'perceived ability to self-cannulate AV access'. Predictive models were developed using logistic regression analysis. Results: 36.6% of predialysis patients (A) and 29.1% of the 'in-centre' haemodialysis patients (B) felt able to consider SC for HD. Technical-skills related apprehension was highest in Group B (14.4%) patients. Response to routine venepuncture and the types of SC concerns were significant predictors of perceived ability to self-cannulate. There was no significant difference in concern for pain across the groups. In multivariable regression analysis, age, education level, 3MS score, hypoalbuminemia in Groups B & C and additionally, attitude to routine phlebotomy and the nature of specific concern for self-cannulation in Groups A, B and C, are significant predictors of SC preference. The unadjusted c-statistics of models 1 (derived from Group A and validated on A) and 2 (derived from B+C and validated on B), are 0.76(95% CI 0.69, 0.83) and 0.80 (95% CI 0.74, 0.87) respectively. Conclusions: There is high prevalence of perceived ability to self-cannulate. Modifiable SC concerns exist in ESRD. The use of predictive models to objectively define and target education and training strategies could potentially impact on HD self-management and future uptake of home HD.
Data from: Correlation between genetic diversity and environmental suitability: taking uncertainty from ecological niche models into account
The hindcast of shifts in the geographical ranges of species as estimated by ecological niche modelling (ENM) has been coupled with phylogeographical patterns, allowing the inference of past processes that drove population differentiation and genetic variability. However, more recently, some studies have suggested that maps of environmental suitability estimated by ENM may be correlated to species' abundance, raising the possibility of using environmental suitability to infer processes related to population demographic dynamics and genetic variability. In both cases, one of the main problems is that there is a wide variation in ENM development methods and climatic models. In this study, we analyse the relationship between heterozygosity (He) and environmental suitability from multiple ENMs for 25 population estimates for Dipteryx alata, a widely distributed, endemic tree species of the Cerrado region of central Brazil. We propose a new approach for generating a statistical distribution of correlations under randomly generated ENM. The confidence intervals from these distributions indicate how model selection with different properties affects the ability to detect a correlation of interest (e.g. the correlation between He and suitability). Additionally, our approach allows us to explore which particular ensemble of ENMs produces the better result for finding an association between environmental suitability and He. Caution is necessary when choosing a method or a climatic data set for modelling geographical distributions, but the new approach proposed here provides a conservative way to evaluate the ability of ensembles to detect patterns of interest.
Data from: Taming the wild: resolving the gene pools of non-model Arabidopsis lineages
Background: Wild relatives in the genus Arabidopsis are recognized as useful model systems to study traits and evolutionary processes in outcrossing species, which are often difficult or even impossible to investigate in the selfing and annual Arabidopsis thaliana. However, Arabidopsis as a genus is littered with sub-species and ecotypes which make realizing the potential of these non-model Arabidopsis lineages problematic. There are relatively few evolutionary studies which comprehensively characterize the gene pools across all of the Arabidopsis supra-groups and hypothesized evolutionary lineages and none include sampling at a world-wide scale. Here we explore the gene pools of these various taxa using various molecular markers and cytological analyses. Results: Based on ITS, microsatellite, chloroplast and nuclear DNA content data we demonstrate the presence of three major evolutionary groups broadly characterized as A. lyrata group, A. halleri group and A. arenosa group. All are composed of further species and sub-species forming larger aggregates. Depending on the resolution of the marker, a few closely related taxa such as A. pedemontana, A. cebennensis and A. croatica are also clearly distinct evolutionary lineages. ITS sequences and a population-based screen based on microsatellites were highly concordant. The major gene pools identified by ITS sequences were also significantly differentiated by their homoploid nuclear DNA content estimated by flow cytometry. The chloroplast genome provided less resolution than the nuclear data, and it remains unclear whether the extensive haplotype sharing apparent between taxa results from gene flow or incomplete lineage sorting in this relatively young group of species with Pleistocene origins. Conclusions: Our study provides a comprehensive overview of the genetic variation within and among the various taxa of the genus Arabidopsis. The resolved gene pools and evolutionary lineages will set the framework for future comparative studies on genetic diversity. Extensive population-based phylogeographic studies will also be required, however, in particular for A. arenosa and their affiliated taxa and cytotypes.
Data from: Impact of model violations on the inference of species boundaries under the multispecies coalescent
The use of genetic data for identifying species-level lineages across the tree of life has received increasing attention in the field of systematics over the past decade. The multispecies coalescent model provides a framework for understanding the process of lineage divergence, and has become widely adopted for delimiting species. However, because these studies lack an explicit assessment of model fit, in many cases, the accuracy of the inferred species boundaries are unknown. This is concerning given the large amount of empirical data and theory that highlight the complexity of the speciation process. Here, we seek to fill this gap by using simulation to characterize the sensitivity of inference under the multispecies coalescent to several violations of model assumptions thought to be common in empirical data. We also assess the fit of the multispecies coalescent model to empirical data in the context of species delimitation. Our results show substantial variation in model fit across datasets. Posterior predictive tests find the poorest model performance in datasets that were hypothesized to be impacted by model violations. We also show that while the inferences assuming the multispecies coalescent are robust to minor model violations, such inferences can be biased under some biologically plausible scenarios. Taken together, these results suggest that researchers can identify individual datasets in which species delimitation under the multispecies coalescent is likely to be problematic, thereby highlighting the cases where additional lines of evidence to identify species boundaries are particularly important to collect. Our study supports a growing body of work highlighting the importance of model checking in phylogenetics, and the usefulness of tailoring tests of model fit to assess the reliability of particular inferences.
Data from: Importance of antecedent environmental conditions in modeling species distributions
Although species distributions can change in an unexpectedly short period of time, most species distribution models (SDMs) use only long-term averaged environmental conditions to explain species distributions. We aimed to demonstrate the importance of incorporating antecedent environmental conditions into SDMs in comparison to long-term averaged environmental conditions. We modeled the presence/absence of 18 fish species captured across 108 sampling events along a 50-km length of the Sagami River in Japan throughout the 1990s (one to four times per site at 45 sites). We constructed and compared the two types of SDMs: (1) a conventional model that uses only long-term averaged (10-year) environmental conditions; and (2) a proposed model that incorporates environmental conditions 2 years prior to a sampling event (antecedent conditions) together with long-term averages linked to life-history stages. These models both included geomorphological, hydrological, and sampling conditions as predictors. A random forest algorithm was applied for modeling and quantifying the relative importance of the predictors. For seven species, antecedent hydrological conditions were more important than the long-term averaged hydrological conditions. Furthermore, the distributions of two species with low prevalence could not be predicted using long-term averaged hydrological conditions but only using antecedent hydrological conditions. In conclusion, incorporating antecedent environmental factors linked with life-history stages at appropriate time scales can better explain changes in species distribution through time.
Data from: Correction of location errors for presence-only species distribution models
1. Species distribution models (SDMs) for presence-only data depend on accurate and precise measurements of geographic and environmental covariates that influence presence and abundance of the species. Some data sets, however, may contain both systematic and random errors in the recorded location of the species. Environmental covariates at the recorded location may differ from those at the true location and result in biased parameter estimates and predictions from SDMs. 2. Regression calibration is a well-developed statistical method that can be used to correct the bias in estimated coefficients and predictions from SDMs when the recorded geographic location differ from the true location for some, but not all locations. We expand the application of regression calibration methods to SDMs and provide illustrative examples using simulated data and opportunistic records of whooping cranes (Grus americana). 3. We found we were able to successfully correct the bias in our SDM parameters estimated from simulated data and opportunistic records of whooping cranes using regression calibration. 4. When modeling species distributions with data that have geographic location errors, we recommend researchers consider the effect of location errors. Correcting for location errors requires that at least a portion of the data have locations recorded without error. Bias correction can result in an increase in variance; this increase in variance should be considered when evaluating the utility of bias correction.
Data from: Modelling of ships as a source of underwater noise
In this paper, a methodology is presented for modelling underwater noise emissions from ships based on realistic vessel activity in the Baltic Sea region. This paper combines the Wittekind noise source model with the Ship Traffic Emission Assessment Model (STEAM) in order to produce regular updates for underwater noise from ships. This approach allows the construction of noise source maps, but requires parameters which are not commonly available from commercial ship technical databases. For this reason, alternative methods were necessary to fill in the required information. Most of the parameters needed contain information that is available during the STEAM model runs, but features describing propeller cavitation are not easily recovered for the world fleet. Baltic Sea ship activity data were used to generate noise source maps for commercial shipping. Container ships were recognized as the most significant source of underwater noise, and the significant potential for an increase in their contribution to future noise emissions was identified.
Data from: A low-threshold potassium current enhances sparseness and reliability in a model of avian auditory cortex
Birdsong is a complex vocal communication signal, and like humans, birds need to discriminate between similar sequences of sound with different meanings. The caudal mesopallium (CM) is a cortical-level auditory area implicated in song discrimination. CM neurons respond sparsely to conspecific song and are tolerant of production variability. Intracellular recordings in CM have identified a diversity of intrinsic membrane dynamics, which could contribute to the emergence of these higher-order functional properties. We investigated this hypothesis using a novel linear-dynamical cascade model that incorporated detailed biophysical dynamics to simulate auditory responses to birdsong. Neuron models that included a low-threshold potassium current present in a subset of CM neurons showed increased selectivity and coding efficiency relative to models without this current. These results demonstrate the impact of intrinsic dynamics on sensory coding and the importance of including the biophysical characteristics of neural populations in simulation studies.
Data from: Testing the validity of functional response models using molecular gut content analysis for prey choice in soil predators
Analysis of predator - prey interactions is a core concept of animal ecology, explaining structure and dynamics of animal food webs. Measuring the functional response, i.e. the intake rate of a consumer as a function of prey density, is a powerful method to predict the strength of trophic links and assess motives of prey choice, particularly in arthropod communities. However, due to their reductionist set-up, functional responses, which are based on laboratory feeding experiments, may not display field conditions, possibly leading to skewed results. Here, we tested the validity of functional responses of centipede predators and their prey by comparing them with empirical gut content data from field-collected predators. Our predator - prey system included lithobiid and geophilomorph centipedes, abundant and widespread predators of forest soils and their soil-dwelling prey. First, we calculated the body size-dependent functional responses of centipedes using a published functional response model in which we included natural prey abundances and animal body masses. This allowed us to calculate relative proportions of specific prey taxa in the centipede diet. In a second step, we screened field-collected centipedes for DNA of eight abundant soil-living prey taxa and estimated their body size-dependent proportion of feeding events. We subsequently compared empirical data for each of the eight prey taxa, on proportional feeding events with functional response-derived data on prey proportions expected in the gut, showing that both approaches significantly correlate in five out of eight predator - prey links for lithobiid centipedes but only in one case for geophilomorph centipedes. Our findings suggest that purely allometric functional response models, which are based on predator-prey body size ratios are too simple to explain predator - prey interactions in a complex system such as soil. We therefore stress that specific prey traits, such as defence mechanisms, must be considered for accurate predictions.
Data from: Linkage into care among newly diagnosed HIV-positive individuals tested through outreach and facility-based HIV testing models in Mbeya, Tanzania: a prospective mixed-method cohort study
Objective: Linkage to care is the bridge between HIV testing and HIV treatment, care and support. In Tanzania, mobile testing aims to address historically low testing rates. Linkage to care was reported at 14% in 2009 and 28% in 2014. The study compares linkage to care of HIV-positive individuals tested at mobile/outreach versus public health facility-based services within the first 6 months of HIV diagnosis. Setting: Rural communities in four districts of Mbeya Region, Tanzania. Participants: A total of 1012 newly diagnosed HIV-positive adults from 16 testing facilities were enrolled into a two-armed cohort and followed for 6 months between August 2014 and July 2015. 840 (83%) participants completed the study. Main outcome: measures We compared the ratios and time variance in linkage to care using the Kaplan-Meier estimator and Log rank tests. Cox proportional hazards regression models to evaluate factors associated with time variance in linkage. Results: At the end of 6 months, 78% of all respondents had linked into care, with differences across testing models. 84% (CI 81% to 87%, n=512) of individuals tested at facility-based site were linked to care compared to 69% (CI 65% to 74%, n=281) of individuals tested at mobile/outreach. The median time to linkage was 1 day (IQR: 1–7.5) for facility-based site and 6 days (IQR: 3–11) for mobile/outreach sites. Participants tested at facility-based site were 78% more likely to link than those tested at mobile/outreach when other variables were controlled (AHR=1.78; 95% CI 1.52 to 2.07). HIV status disclosure to family/relatives was significantly associated with linkage to care (AHR=2.64; 95% CI 2.05 to 3.39). Conclusions: Linkage to care after testing HIV positive in rural Tanzania has increased markedly since 2014, across testing models. Individuals tested at facility-based sites linked in significantly higher proportion and modestly sooner than mobile/outreach tested individuals. Mobile/outreach testing models bring HIV testing services closer to people. Strategies to improve linkage from mobile/outreach models are needed.
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: Model-based analysis supports interglacial refugia over long-dispersal events in the diversification of two South American cactus species
Pilosocereus machrisii and P. aurisetus are cactus species within the P. aurisetus complex, a group of eight cacti that are restricted to rocky habitats within the Neotropical savannas of eastern South America. Previous studies have suggested that diversification within this complex was driven by distributional fragmentation, isolation leading to allopatric differentiation, and secondary contact among divergent lineages. These events have been associated with Quaternary climatic cycles, leading to the hypothesis that the xerophytic vegetation patches which presently harbor these populations operate as refugia during the current interglacial. However, owing to limitations of the standard phylogeographic approaches used in these studies, this hypothesis was not explicitly tested. Here we use Approximate Bayesian Computation to refine the previous inferences and test the role of different events in the diversification of two species within P. aurisetus group. We used molecular data from chloroplast DNA and simple sequence repeats loci of P. machrisii and P. aurisetus, the two species with broadest distribution in the complex, in order to test if the diversification in each species was driven mostly by vicariance or by long-dispersal events. We found that both species were affected primarily by vicariance, with a refuge model as the most likely scenario for P. aurisetus and a soft vicariance scenario most probable for P. machrisii. These results emphasize the importance of distributional fragmentation in these species, and add support to the hypothesis of long-term isolation in interglacial refugia previously proposed for the P. aurisetus species complex diversification.
Data from: Which traits do observers use to distinguish Batesian mimics from their models?
Batesian mimicry, in which a harmless mimic resembles a more aversive model, can encompass a wide range of morphological traits, but the resemblance is never perfect. Previous studies have used abstract "prey" designs to show that differences in certain traits may not be relevant to mimicry if they are not perceived or recognized by a predator. Here, we extend these results by examining how human "predators" respond to realistic variation in traits of aposematic wasps and their hoverfly mimics. We measured the ability of humans to discriminate between images of wasps and hoverflies in which only certain traits were visible, to determine the contributions of those traits to discrimination decisions. We found that shape is a particularly useful and easily learnt trait for separating the 2 taxa. Subjects did not successfully discriminate on the basis of abdominal patterns, despite those containing useful information. Color similarity between wasps and hoverflies is relatively high in comparison with other traits, suggesting that selection has acted more strongly on color. Our findings demonstrate the importance of consideration of natural variation in the traits of prey and their salience to predators for understanding the evolution of prey defenses.
Data from: A dynamic state model of migratory behavior and physiology to assess the consequences of environmental variation and anthropogenic disturbance on marine vertebrates
Integrating behavior and physiology is critical to formulating new hypotheses on the evolution of animal life-history strategies. Migratory capital breeders acquire most of the energy they need to sustain migration, gestation and lactation before parturition. Therefore, when predicting the impact of environmental variation on such species, a mechanistic understanding of the physiology of their migratory behavior is required. Using baleen whales as a model system, we developed a dynamic state variable model that captures the interplay among behavioral decisions, energy, reproductive needs and the environment. We applied the framework to blue whales (Balaenoptera musculus) in the Eastern North Pacific Ocean, and explored the effects of environmental and anthropogenic perturbations on female reproductive success. We demonstrate the emergence of migration to track prey resources, enabling us to quantify the trade-offs among capital breeding, body condition, and metabolic expenses. We predict that periodic climatic oscillations affect reproductive success less than unprecedented environmental changes do. The effect of localized, acute anthropogenic impacts depended on whales' behavioral response to the disturbance; chronic, but weaker, disturbances had little effect on reproductive success. Because we link behavior and vital rates by modeling individuals' energetic budgets, we provide a general framework to investigate the ecology of migration and assess the population consequences of disturbance, while identifying critical knowledge gaps.
Data from: Ecological niche modeling for a cultivated plant species: a case study on taro (Colocasia esculenta) in Hawai'i
Under the threat of ongoing and projected climate change, communities in the Pacific Islands face challenges of adapting culture and lifestyle to accommodate a changing landscape. Few models can effectively predict how biocultural livelihoods might be impacted. Here, we examine how environmental and anthropogenic factors influence an ecological niche model (ENM) for the realized niche of cultivated taro (Colocasia esculenta) in Hawai'i. We created and tuned two sets of ENMs: one using only environmental variables, and one using both environmental and cultural characteristics of Hawa'i. These models were projected under two different Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathways (RCPs) for 2070. Models were selected and evaluated using average omission rate and area under the receiver operating characteristic curve (AUC). We compared optimal model predictions by comparing the percentage of taro plots predicted present and measured ENM overlap using Schoener's D-statistic. The model including only environmental variables consisted of 19 Worldclim bioclimatic variables, in addition to slope, altitude, distance to perennial streams, soil evaporation, and soil moisture. The optimal model with environmental variables plus anthropogenic features also included a road density variable (which we assumed as a proxy for urbanization) and a variable indicating agricultural lands of importance to the State of Hawai'i. The model including anthropogenic features performed better than the environment-only model based on omission rate, AUC, and review of spatial projections. The two models also differed in spatial projections for taro under anticipated future climate change. Our results demonstrate how ENMs including anthropogenic features can predict which areas might be best suited to plant cultivated species in the future, and how these areas could change under various climate projections. These predictions might inform biocultural conservation priorities and initiatives. In addition, we discuss the incongruences that arise when traditional ENM theory is applied to species whose distribution has been significantly impacted by human intervention, particularly at a local scale relevant to biocultural conservation initiatives.
Data from: A statistical skull geometry model for children 0-3 years old
Head injury is the leading cause of fatality and long-term disability for children. Pediatric heads change rapidly in both size and shape during growth, especially for children under 3 years old (YO). To accurately assess the head injury risks for children, it is necessary to understand the geometry of the pediatric head and how morphologic features influence injury causation within the 0–3 YO population. In this study, head CT scans from fifty-six 0–3 YO children were used to develop a statistical model of pediatric skull geometry. Geometric features important for injury prediction, including skull size and shape, skull thickness and suture width, along with their variations among the sample population, were quantified through a series of image and statistical analyses. The size and shape of the pediatric skull change significantly with age and head circumference. The skull thickness and suture width vary with age, head circumference and location, which will have important effects on skull stiffness and injury prediction. The statistical geometry model developed in this study can provide a geometrical basis for future development of child anthropomorphic test devices and pediatric head finite element models.
Data from: Bunching up the background betters bias in species distribution models
Sets of presence records used to model species' distributions typically consist of observations collected opportunistically rather than systematically. As a result, sampling probability is geographically uneven, which may confound the model's characterization of the species' distribution. Modelers frequently address sampling bias by manipulating training data: either subsampling presence data or creating a similar spatial bias in non-presence background data. We tested a new method, which we call "background thickening," in the latter category. Background thickening entails concentrating background locations around presence locations in proportion to presence location density. We compared background thickening to two established sampling bias correction methods — target group background selection and presence thinning — using simulated data and data from a case study. In the case study, background thickening and presence thinning performed similarly well, both producing better model discrimination than target group background selection, and better model calibration than models without correction. In the simulation, background thickening performed better than presence thinning when the number of simulated presence locations was low, and vice versa. We discuss drawbacks to target group background selection, why background thickening and presence thinning are conservative but robust sampling bias correction methods, and why background thickening is better than presence thinning for small sample sizes. Particularly, background thickening is advantageous for treating sampling bias when data are scarce because it avoids discarding presence records.
Data from: Clock model makes a large difference to age estimates of long-stemmed clades with no internal calibration: a test using Australian grasstrees
Background: Estimating divergence times in phylogenies using a molecular clock depends on accurate modeling of nucleotide substitution rates in DNA sequences. Rate heterogeneity among lineages is likely to affect estimates, especially in lineages with long stems and short crowns ("broom" clades) and no internal calibration. We evaluate the performance of the random local clocks model (RLC) and the more routinely employed uncorrelated lognormal relaxed clock model (UCLN) in situations in which a significant rate shift occurs on the stem branch of a broom clade. We compare the results of simulations to empirical results from analyses of a real rate-heterogeneous taxon – Australian grass trees (Xanthorrhoea) – whose substitution rate is slower than in its sister groups, as determined by relative rate tests. Results: In the simulated datasets, the RLC model performed much better than UCLN: RLC correctly estimated the age of the crown node of slow-rate broom clades, whereas UCLN estimates were consistently too young. Similarly, in the Xanthorrhoea dataset, UCLN returned significantly younger crown ages than RLC (mean estimates respectively 3-6 Ma versus 25-35 Ma). In both real and simulated datasets, Bayes Factor tests strongly favored the RLC model over the UCLN model. Conclusions: The choice of an unsuitable molecular clock model can strongly bias divergence time estimates. In particular, for data predicted to have more rate variation among than within clades, dating with RLC is much more likely to be accurate than with UCLN. The choice of clocks should be informed by the biology of the study group (e.g., life-form) or assessed with relative rate tests and post-hoc model comparisons.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.