Find research datasets worth reusing

Spatial scaling properties of coral reef benthic communities

The spatial structure of ecological communities on tropical coral reefs across seascapes and geographies have historically been poorly understood. Here we addressed this for the first time using spatially expansive and thematically resolved benthic community data collected around five uninhabited central Pacific oceanic islands, spanning 6° latitude and 17° longitude. Using towed-diver digital image surveys over ~140 linear km of shallow (8 – 20 m depth) tropical reef, we highlight the autocorrelated nature of coral reef seascapes. Benthic functional groups and hard coral morphologies displayed significant spatial clustering (positive autocorrelation) up to kilometre-scales around all islands, in some instances dominating entire sections of coastline. The scale and strength of these autocorrelation patterns showed differences across geographies, but patterns were more similar between islands in closer proximity and of a similar size. For example, crustose coralline algae (CCA) were clustered up to scales of 0.3 km at neighbouring Howland and Baker Islands and macroalgae were spatially clustered at scales up to ~3 km at both neighbouring Kingman Reef and Palmyra Atoll. Of all the functional groups, macroalgae had the highest levels of spatial clustering across geographies at the finest resolution of our data (100 m). There were several cases where the upper scale at which benthic community members showed evidence of spatial clustering correlated highly with the upper scales at which concurrent gradients in physical environmental drivers were spatially clustered. These correlations were stronger for surface wave energy than subsurface temperature (regardless of benthic group) and turf algae and CCA had the closest alignments in scale with wave energy across functional groups and geographies. Our findings suggest such physical drivers not only limit or promote the abundance of various benthic competitors on coral reefs, but also play a key role in governing their spatial scaling properties across seascapes.

opencc-zeroSep 2020View details →

The scale and dynamics of COVID-19 epidemics across Europe

The number of COVID-19 deaths reported from European countries has varied more than 100-fold. In terms of coronavirus transmission, the relatively low death rates in some countries could be due to low intrinsic (e.g. low population density) or imposed contact rates (e.g. non-pharmaceutical interventions) among individuals, or because fewer people were exposed or susceptible to infection (e.g. smaller populations). Here we develop a flexible empirical model (skew-logistic) to distinguish among these possibilities. We find that countries reporting fewer deaths did not generally have intrinsically lower rates of transmission and epidemic growth, and flatter epidemic curves. Rather, countries with fewer deaths locked down earlier, had shorter epidemics that peaked sooner, and smaller populations. Consequently, as lockdowns are eased we expect, and are starting to see, a resurgence of COVID-19 across Europe.

opencc-zeroDec 2016View details →

Data from: Robust inference on large-scale species habitat use with interview data: the status of jaguars outside protected areas in Central America

Evaluating range-wide habitat use by a target species requires information on species occurrence over broad geographic regions, a process made difficult by species rarity, large spatiotemporal sampling domains, and imperfect detection. We address these challenges in an assessment of habitat use for jaguars (Panthera onca) outside protected areas in Central America. Occurrence records were acquired within 12 putative corridors using interviews with knowledgeable corridor residents. We developed a Bayesian hierarchical occupancy model to gain robust inference, allowing for heterogeneity introduced in the sampling process over space and time, using records of jaguar occurrence prone to false positives and false negatives. Probability of false detection of jaguars increased with the number of interviews conducted per unit (from 5.42% to 7.74% given <4 and ≥4 observers per unit). True probability of detection (mean=0.58) increased with the number of days interviewees spent in a survey unit per year. Failing to account for false positives biased predicted habitat use high (˜1.8x), especially where occurrence records were sparse. Probability of site use by jaguars increased with greater forest cover, prey richness, and distance from human settlements, and decreased with greater agricultural cover, elevation, and distance from protected areas. Site use probabilities averaged 0.15-0.97 by corridor, providing relatively fine-scale resolution of predicted jaguar occurrence consistent with known patterns of jaguar gene flow across Central America. Model validation, accounting for both false positives and negatives in the observation process, indicated moderate correspondence between model-predicted observations and actual observations for withheld data (0.65, 95% CRI 0.59–0.71), with sensitivity and specificity rates of 0.69 (0.61 – 0.77) and 0.59 (0.50 – 0.68), respectively. These results demonstrate that reliable predictions can be achieved despite the complexity of large-scale, interview-based analyses of species occurrence. Synthesis and applications. Our Bayesian hierarchical occupancy model accommodated heterogeneity caused by typical sampling inequities and idiosyncrasies associated with interview data, yielding robust estimates of jaguar habitat use. Our approach is applicable to any wide-ranging and readily identifiable species and has particular utility for rare species in human-dominated landscapes where traditional survey techniques (e.g., camera traps) may be impractical.

Data from: Allometric scaling of eDNA production in stream-dwelling brook trout (Salvelinus fontinalis) inferred from population size structure

Environmental DNA (eDNA) concentration exhibits a positive correlation with organism abundance in nature, but modelling this relationship could be substantially improved by incorporating the biology of eDNA production. A recent model (Yates et al. 2020) extended models of physiological allometric scaling to eDNA production, hypothesizing that brook trout eDNA production scales non-linearly with mass as a power-function with scaling coefficients < 1 in lakes. To validate this hypothesis, we re-analysed data from Wilcox et al. (2016) that examined the correlation between eDNA concentration and brook trout abundance in streams. We found that allometrically scaled mass (ASM) (e.g. ∑(individual mass0.36) best described patterns of eDNA concentration across streams (r2 = 0.43). ASM exhibited substantially improved model fit relative to biomass (r2 = 0.31, ∆AIC = 5.19), indicating that eDNA production did not scale linearly with biomass. However, the explanatory power of ASM was comparable to density (r2 = 0.40, ∆AIC = 1.25). Additionally, the optimal scaling coefficient estimated from the data (0.36) was substantially lower than that found in Yates et al. (2020) (0.72). Discrepancies between datasets could be attributable to ecological differences between study habitats (streams vs lakes) or due to the exclusion of juveniles (i.e. individuals < 75 mm) that can be abundant in stream environments. Nevertheless, this study adds to the growing body of literature demonstrating that individual eDNA production does not scale linearly with biomass.

opencc-zeroSep 2020View details →

Support for a relationship between demography and modeled habitat suitability is scale dependent for the Purple Martin, Progne subis

1. Species distribution models (SDMs) estimate habitat suitability for species in geographic space. They are extensively used in conservation under the assumption that there is a positive relationship between habitat suitability and species success and stability. 2. Given the difficulties in obtaining demographic data across a species' range, this assumption is rarely tested. Here we provide a range-wide test of this relationship for the eastern subspecies of purple martin (Progne subis subis). 3. We build a well-supported SDM for the breeding range of the purple martin, and pair it with an unparalleled demographic dataset of nest success and local and regional abundance data for the species to test the proposed link between habitat suitability and fecundity and demography. 4. We find a positive relationship between regional abundance and habitat suitability but no relationship between local abundance or fecundity and habitat suitability. 5. Our data suggest that local success is driven largely by biotic and stochastic factors and raise the possibility that purple martins are experiencing a time lag in their distribution. More broadly our results call for caution in how we interpret SDMs and do not support the assumption that areas of high habitat suitability are the best areas for species persistence.

opencc-zeroSep 2020View details →

Small scale variability in soil moisture drives infection of vulnerable juniper populations by invasive forest pathogen

The oomycete plant pathogen, Phytophthora austrocedri, is an aggressive killer of cypress trees causing severe mortality of Chilean cedar (Austrocedrus chilensis) in Argentina since the 1940s and now common juniper (Juniperus communis s.l.) in the UK. Rapid mortality of key UK juniper populations was first observed in the early 2000s; the causal agent of mortality was confirmed as P. austrocedri in 2012 and the pathogen has now been widely detected - but is not ubiquitous - in juniper populations across Scotland and England. Although juniper has a broad distribution across the northern hemisphere, the UK incidence of P. austrocedri remains the only confirmed infection of juniper populations globally. Juniper is an important species for biodiversity, so it is imperative to understand the abiotic and biotic drivers of emergent P. austrocedri infection to inform detection, containment and conservation strategies to manage juniper populations across the full extent of its range. As management of UK juniper populations is primarily conducted at a local level, we investigated field scale drivers of disease – in three, geographically separate populations with different infection histories. Variation in the proportion of juniper showing symptoms - discoloured or dead foliage – was measured using stratified sampling across along key environmental gradients within each 100-hectare population, including juniper density identified from aerial imagery. Potential predictors of infection included altitude, slope, distance to nearest watercourse, soil moisture (mean percentage volumetric water content), area of red deer browsing damage and area of commonly associated vascular plant species. We assessed support in the data for alternative models explaining the spatial distribution of P. austrocedri symptoms using full subset covariate selection and Deviance Information Criteria (DIC). Despite differences in environmental gradients and infection histories between populations, area of juniper symptomatic for P. austrocedri increased with waterlogging, increasing with soil moisture in sites where soils had higher peat or clay contents, and decreasing with proximity to watercourses where sites had shallower, sandier soils. These results are consistent with key drivers identified at both local and landscape scale in Chilean cedar. Our approach enables identification of site-specific disease management strategies including prioritisation of inspections in microsites with high soil moisture and promoting conservation measures such as creation of sites for natural regeneration in drier microsites to minimise pathogen spread and maximise the resilience of existing juniper populations.

opencc-by-4.0Aug 2020View details →

Age-dependent modulation of bone metabolism in zebrafish scales as new model of male osteoporosis in lower vertebrates

After middle age, in human bone, the resorption usually exceeds formation resulting in bone loss and increased risk of fractures in the aged population. Only few in vivo models in higher vertebrates are available for pathogenic and therapeutic studies about bone aging. Among these, male Danio rerio (zebrafish) can be successfully used as low vertebrate model to study degenerative alterations that affect the skeleton during aging, reducing the role of sex hormones.In this paper, we investigated the early bone aging mechanisms in male zebrafish (3, 6, 9 months old) scales evaluating the physiological changes and the effects of prednisolone, a pro-osteoporotic drug.The results evidentiated an age-dependent reduction of the mineralization rate in the fish scales, as highlighted by growing circle measurements. Indeed, the osteoblastic ALP activity at the matrix deposition site was found progressively downregulated.The higher TRAP activity was found in 63% of 9-month-old fish scales associated with resorption lacunae along the scale border. Gene expression analysis evidentiated that an increase of the tnfrsf1b (homolog of human rank) in aging scales may be responsible for resorption stimulation.Interestingly, prednisolone inhibited the physiological growth of the scale and induced in aged scales a more significant bone resorption compared with untreated fish (3.8% vs 1.02%). Bone markers analysis shown a significant reduction of ALP/TRAP ratio due to a prednisolone-dependent stimulation of tnfsf11 (homolog of human rankl) in scales of older fish.The results evidentiated for the first time the presence of a senile male osteoporosis in lower vertebrate. This new model could be helpful to identify the early mechanisms of bone aging and new therapeutic strategies to prevent age-related bone alterations in humans.

Acoustic indices perform better when applied at ecologically meaningful time and frequency scales

Abstract: 1. Acoustic indices are increasingly employed in the analysis of soundscapes to ascertain biodiversity value. However, conflicting results and lack of consensus on best practices for their usage has hindered their application in conservation and land-use management contexts. Here we propose that the sensitivity of acoustic indices to ecological change and fidelity of acoustic indices to ecological communities are severely impacted by signal masking. Signal masking can occur when acoustic responses sensitive to the effect being monitored are masked by less sensitive acoustic groups, or target taxa sonification is masked by non-target noise. We argue that by calculating acoustic indices at ecologically appropriate time and frequency bins, masking effects can be reduced and the efficacy of indices increased. 2. We test this on a large acoustic dataset collected in Eastern Amazonia spanning a disturbance gradient including undisturbed, logged, burned, logged-and-burned, and secondary forests. We calculated values for two acoustic indices: the Acoustic Complexity Index and the Bioacoustic Index, across the entire frequency spectrum (0-22.1 kHz), and four narrower subsets of the frequency spectrum; at dawn, day, dusk and night. 3. We show that signal masking has a large impact on the sensitivity of acoustic indices to forest disturbance classes. Calculating acoustic indices at a range of narrower time-frequency bins substantially increases the classification accuracy of forest classes by random forest models. Furthermore, signal masking led to highly misleading correlations, including spurious inverse correlations, between biodiversity indicator metrics and acoustic index values compared to correlations derived from manual sampling of the audio data. 4. Consequently, we recommend that acoustic indices are calculated either at a range of time and frequency bins, or at a single narrow bin, predetermined by a priori ecological understanding of the soundscape.

Diurnal timing of nonmigratory movement by birds: the importance of foraging spatial scales

Timing of activity can reveal an organism's efforts to optimize foraging either by minimizing energy loss through passive movement or by maximizing energetic gain through foraging. Here, we assess whether signals of either of these strategies are detectable in the timing of activity of daily, local movements by birds. We compare the similarities of timing of movement activity among species using six temporal variables: start of activity relative to sunrise, end of activity relative to sunset, relative speed at midday, number of movement bouts, bout duration, and proportion of active daytime hours. We test for the influence of flight mode and foraging habitat on the timing of movement activity across avian guilds. We used 64570 days of GPS movement data collected between 2002 and 2019 for local (non-migratory) movements of 991 birds from 49 species, representing 14 orders. Dissimilarity among daily activity patterns was best explained by flight mode. Terrestrial soaring birds began activity later and stopped activity earlier than pelagic soaring or flapping birds. Broad-scale foraging habitat explained less of the clustering patterns because of divergent timing of active periods of pelagic surface and diving foragers. Among pelagic birds, surface foragers were active throughout the day while diving foragers matched their active hours more closely to daylight hours. Pelagic surface foragers also had the greatest daily foraging distances, which was consistent with their daytime activity patterns. This study demonstrates that flight mode and foraging habitat influence temporal patterns of daily movement activity of birds.

opencc-by-4.0Oct 2020View details →

Application Deployment using Containers with Auto-scaling for Microservices in Cloud Environment

This dataset release supports the results presented in the paper "Application Deployment using Containers with Auto-scaling for Microservices in Cloud Environment" by S. N. Srirama, M. Adhikari, and S. Paul, accepted in Journal of Network and Computer Applications, ISSN: 1084-8045, vol. 160, pp. 1-20, 2020. Elsevier. When referring to the dataset please cite the paper above.

opencc-by-4.0Mar 2020View details →

ToxicoDB: an integrated database to mine and visualize large-scale toxicogenomic datasets (TGGATEs human dataset)

This data was generated by Igarashi Y, Nakatsu N, Yamashita T, Ono A, Ohno Y, Urushidani T, Yamada H. Open TG-GATEs: a large-scale toxicogenomics database. Nucleic Acids Res [Internet]. 2015 Jan;43(Database issue):D921–7. Available from: http://dx.doi.org/10.1093/nar/gku955 PMCID: PMC4384023. The data have been curated and analyzed using our open-source R package, ToxicoGx (<a href="http://bioconductor.org/packages/devel/bioc/html/ToxicoGx.html">http://bioconductor.org/packages/devel/bioc/html/ToxicoGx.html</a>), and are available publicly in the ToxicoDB web application (<a href="http://www.toxicodb.ca">www.toxicodb.ca</a>).

Scale-dependent drivers of the phylogenetic structure and similarity of tree communities in northwestern Amazonia

1. The extent to which historical dispersal, environmental features and geographic barriers shape the phylogenetic structure and turnover of tree communities in northwestern Amazonia at multiple spatial scales remains poorly understood. 2. We used 85 floristically standardized 0.1-ha plots (DBH ³ 2.5 cm) distributed in three subregions of northwestern (NW) Amazonia across three main habitat types (floodplain, swamp, terra firme forests), to hypothesize that: i) historical dispersal overcome geographical barriers, which meant low local phylogenetic relatedness and low phylogenetic turnover. ii) Geographical barriers triggered dispersal limitation, causing high local and subregional phylogenetic clustering and high regional phylogenetic turnover. iii) Edaphic properties and flooding were negatively associated to stem size and determined the tree phylogenetic structure and turnover at local and regional scales in Amazon forests. 3. We found that the extent to which environmental or evolutionary features shaped the phylogenetic structure and phylogenetic similarity of tree communities in NW Amazonia was scale dependent. Specifically, we show that the relative importance of environmental factors increases as spatial scale and species pool decreases. Further, we find that these results are generally robust for both adult and juvenile trees. Synthesis: Our analysis at the regional (NW Amazon) scale lends support to the idea of Amazonian forests as a large metacommunity primarily structured by historical dispersal at large spatial scales with an increasing importance of environmental factors at finer spatial scales. The convergence of ancestral lineages across habitat types may have been due to the relatively recent formation of geographical barriers that promoted local isolation and allopatric speciation.

opencc-zeroNov 2020View details →

Genome reduction is associated with bacterial pathogenicity across different scales of temporal and ecological divergence - between species core gene alignments

Emerging bacterial pathogens threaten global health and food security, and so it is important to ask whether these transitions to pathogenicity have any common features. We present a systematic study of the claim that pathogenicity is associated with genome reduction and gene loss. We compare broad-scale patterns across all bacteria, with detailed analyses of Streptococcus suis, an emerging zoonotic pathogen of pigs, which has undergone multiple transitions between disease and carriage forms. We find that pathogenicity is consistently associated with reduced genome size across three scales of divergence (between species within genera, and between and within genetic clusters of S. suis). While genome reduction is also found in mutualist and commensal bacterial endosymbionts, genome reduction in pathogens cannot be solely attributed to the features of their ecology that they share with these species, i.e. host restriction or intracellularity. Moreover, other typical correlates of genome reduction in endosymbionts (reduced metabolic capacity, reduced GC content, and the transient expansion of non-functional elements) are not consistently observed in pathogens. Together, our results indicate that genome reduction is a predictive marker of pathogenicity in bacteria.

opencc-zeroNov 2020View details →

Supplementary material 1 from: Antoł A, Kozłowski J (2020) Scaling of organ masses in mammals and birds: phylogenetic signal and implications for metabolic rate scaling. ZooKeys 982: 149-159. https://doi.org/10.3897/zookeys.982.55639

Figures S1–S5. Additional graphs with result analysis and phylogenetical trees used in data analysis

opencc-by-4.0Oct 2020View details →

Comparability of Raman Spectroscopic Configurations: A Large Scale Cross-Laboratory Study

Slightly processed raw data for the paper 'Comparability of Raman Spectroscopic Configurations:  A Large Scale Cross-Laboratory Study' <ul> <li>The processing include a spike removal to allow an interpolation to a common wavenumber axis.</li> <li>Always three files belong to each other: wavenumber axis file (wx_XYZ), spectral intensity file (spec_XYZ) and metadata file (meta_XYZ). The ‘XYZ’ refers to the samples measured (see the publication and its SI for details).</li> </ul>

opencc-by-4.0Jun 2020View details →

Chang'E-4 rover spectra revealing micro-scale surface thermophysical properties of the Moon

Dataset of the article 'Chang’E-4 rover spectra revealing micro-scale surface thermophysical properties of the Moon'

opencc-zeroNov 2020View details →

Multi-scale habitat assessment of pronghorn migration routes

We studied the habitat selection of pronghorn (Antilocapra americana) during seasonal migration; an important period in an animal's annual cycle associated with broad-scale movements. We further decompose our understanding of migration habitat itself as the product of both broad- and fine-scale behavioral decisions and take a multi-scale approach to assess pronghorn spring and fall migration across the transboundary Northern Sagebrush Steppe region. We used a hierarchical habitat selection framework to assess a suite of natural and anthropogenic features that have been shown to influence selection patterns of pronghorn at both broad (migratory neighborhood) and fine (migratory pathway) scales. We then combined single-scale predictions into a scale-integrated step selection function (ISSF) map to assess its effectiveness in predicting migration route habitat. During spring, pronghorn selected for native grasslands, areas of high forage productivity (NDVI), and avoided human activity (i.e., roads and oil and natural gas wells). During fall, pronghorn selected for native grasslands, larger streams and rivers, and avoided roads. We detected avoidance of paved roads, unpaved roads, and wells at broad spatial scales, but no response to these features at fine scales. In other words, migratory pronghorn responded more strongly to anthropogenic features when selecting a broad neighborhood through which to migrate than when selecting individual steps along their migratory pathway. Our results demonstrate that scales of migratory route selection are hierarchically nested within each other from broader (second-order) to finer scales (third-order). In addition, we found other variables during particular migratory periods (i.e., native grasslands in spring) were selected for across scales indicating their importance for pronghorn. The mapping of ungulate migration habitat is a topic of high conservation relevance. In some applications, corridors are mapped according to telemetry location data from a sample of animals, with the assumption that the sample adequately represents habitat for the entire population. Our use of multi-scale modelling to predict resource selection during migration shows promise and may offer another relevant alternative for use in future conservation planning and land management decisions where telemetry-based sampling is unavailable or incomplete.

opencc-by-4.0Oct 2019View details →

Benefit-cost analysis of adaptation objectives to coastal flooding at the global scale

This dataset presents results of benefit-cost analyses of different adaptation objectives using grey infrastructure to coastal flooding at the global scale.  The four adaptation objectives are: (1) ‘Protection constant’, which keeps protection levels in the future the same as current protection levels; (2) ‘Absolute risk constant’, which calculates future protection standards when the absolute value for expected annual damage is kept the same as current;  (3) ‘Relative risk constant’, which calculates future protection standards when expected annual damage as a percentage of GDP is kept the same as current; and (4) ‘Optimize’, which calculates future protection standards by maximizing net present value. The results for each adaptation objective include future protection standards, change in risk relative to GDP, benefit-cost ratio and net present value for various RCP-SSP combinations for sub-national regions.

opencc-by-4.0Nov 2020View details →

Dataset for scaling of the 2d orders coupled to the Ising Model

This is the data and some example analysis scripts used for the article "Phase transitions in $2$d orders coupled to the Ising model"