Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
411
datasets available to search
ShareScore release 0.7.1
Dataset results
411 results for “spatial variation”
Using spatial capture-recapture methods to estimate long-term spatiotemporal variation of a wide-ranging marine species
Open the record for dataset details and reuse information.
Mimulus cardinalis plasticity analyses and R scripts for: Spatial variation in high temperature-regulated gene expression predicts evolution of plasticity with climate change in the scarlet monkeyflower
Open the record for dataset details and reuse information.
Detecting phylogenetic signal and adaptation in papionin cranial shape by decomposing variation at different spatial scales
Open the record for dataset details and reuse information.
Abiotic conditions shape spatial and temporal morphological variation in North American birds
Open the record for dataset details and reuse information.
Data from: Genetic and spatial variation in vegetative and floral traits across a hybrid zone
Open the record for dataset details and reuse information.
Spatial and temporal variation in the value of solar power across United States electricity markets
<p>This repository includes python scripts and input/output data associated with the following publication:</p> <p>[1] Brown, P.R.; O'Sullivan, F. "Spatial and temporal variation in the value of solar power across United States Electricity Markets". Renewable & Sustainable Energy Reviews 2019. <a href="https://doi.org/10.1016/j.rser.2019.109594">https://doi.org/10.1016/j.rser.2019.109594</a></p> <p>Please cite reference [1] for full documentation if the contents of this repository are used for subsequent work.</p> <p>Many of the scripts, data, and descriptive text in this repository are shared with the following publication:</p> <p>[2] Brown, P.R.; O'Sullivan, F. "Shaping photovoltaic array output to align with changing wholesale electricity price profiles". Applied Energy 2019, 256, 113734. <a href="https://doi.org/10.1016/j.apenergy.2019.113734">https://doi.org/10.1016/j.apenergy.2019.113734</a></p> <p>All code is in python 3 and relies on a number of dependencies that can be installed using pip or conda.</p> <p><strong>Contents</strong></p> <ul> <li>pvvm/*.py : Python module with functions for modeling PV generation and calculating PV energy revenue, capacity value, and emissions offset.</li> <li>notebooks/*.ipynb : Jupyter notebooks, including: <ul> <li>pvvm-vos-data.ipynb: Example scripts used to download and clean input LMP data, determine LMP node locations, assign nodes to capacity zones, download NSRDB input data, and reproduce some figures in [1]</li> <li>pvvm-example-generation.ipynb: Example scripts demonstrating the use of the PV generation model and a sensitivity analysis of PV generator assumptions</li> <li>pvvm-example-plots.ipynb: Example scripts demonstrating different plotting functions</li> <li>validate-pv-monthly-eia.ipynb: Scripts and plots for comparing modeled PV generation with monthly generation reported in EIA forms 860 and 923, as discussed in SI Note 3 of [1]</li> <li>validate-pv-hourly-pvdaq.ipynb: Scripts and plots for comparing modeled PV generation with hourly generation reported in NREL PVDAQ database, as discussed in SI Note 3 of [1]</li> <li>pvvm-energyvalue.ipynb: Scripts for calculating the wholesale energy market revenues of PV and reproducing some figures in [1]</li> <li>pvvm-capacityvalue.ipynb: Scripts for calculating the capacity credit and capacity revenues of PV and reproducing some figures in [1]</li> <li>pvvm-emissionsvalue.ipynb: Scripts for calculating the emissions offset of PV and reproducing some figures in [1]</li> <li>pvvm-breakeven.ipynb: Scripts for calculating the breakeven upfront cost and carbon price for PV and reproducing some figures in [1]</li> </ul> </li> <li>html/*.html : Static images of the above Jupyter notebooks for viewing without a python kernel</li> <li>data/lmp/*.gz : Day-ahead nodal locational marginal prices (LMPs) and marginal costs of energy (MCE), congestion (MCC), and losses (MCL) for CAISO, ERCOT, MISO, NYISO, and ISONE. <ul> <li>At the time of publication of this repository, permission had not been received from PJM to republish their LMP data. If permission is received in the future, a new version of this repository will be linked here with the complete dataset.</li> </ul> </li> <li>results/*.csv.gz : Simulation results associated with [1], including modeled energy revenue, capacity credit and revenue, emissions offsets, and breakeven costs for PV systems at all LMP nodes</li> </ul> <p><strong>Data notes</strong></p> <ul> <li>ISO LMP data are used with permission from the different ISOs. Adapting the MIT License (<a href="https://opensource.org/licenses/MIT">https://opensource.org/licenses/MIT</a>), "The data are provided 'as is', without warranty of any kind, express or implied, including but not limited to the warranties of merchantibility, fitness for a particular purpose and noninfringement. In no event shall the authors or sources be liable for any claim, damages or other liability, whether in an action of contract, tort or otherwise, arising from, out of or in connection with the data or other dealings with the data." Copyright and usage permissions for the LMP data are available on the ISO websites, linked below.</li> <li>ISO-specific notes on LMP data: <ul> <li>CAISO data from <a href="http://oasis.caiso.com/mrioasis/logon.do">http://oasis.caiso.com/mrioasis/logon.do</a> are used pursuant to the terms at <a href="http://www.caiso.com/Pages/PrivacyPolicy.aspx#TermsOfUse">http://www.caiso.com/Pages/PrivacyPolicy.aspx#TermsOfUse</a>.</li> <li>ERCOT data are from <a href="http://www.ercot.com/mktinfo/prices">http://www.ercot.com/mktinfo/prices</a>.</li> <li>MISO data are from <a href="https://www.misoenergy.org/markets-and-operations/real-time--market-data/market-reports/">https://www.misoenergy.org/markets-and-operations/real-time--market-data/market-reports/</a> and <a href="https://www.misoenergy.org/markets-and-operations/real-time--market-data/market-reports/market-report-archives/">https://www.misoenergy.org/markets-and-operations/real-time--market-data/market-reports/market-report-archives/</a>.</li> <li>PJM data were originally downloaded from <a href="https://www.pjm.com/markets-and-operations/energy/day-ahead/lmpda.aspx">https://www.pjm.com/markets-and-operations/energy/day-ahead/lmpda.aspx</a> and <a href="https://www.pjm.com/markets-and-operations/energy/real-time/lmp.aspx">https://www.pjm.com/markets-and-operations/energy/real-time/lmp.aspx</a>. At the time of this writing these data are currently hosted at <a href="https://dataminer2.pjm.com/feed/da_hrl_lmps">https://dataminer2.pjm.com/feed/da_hrl_lmps</a> and <a href="https://dataminer2.pjm.com/feed/rt_hrl_lmps">https://dataminer2.pjm.com/feed/rt_hrl_lmps</a>.</li> <li>NYISO data from <a href="http://mis.nyiso.com/public/">http://mis.nyiso.com/public/</a> are used subject to the disclaimer at <a href="https://www.nyiso.com/legal-notice">https://www.nyiso.com/legal-notice</a>.</li> <li>ISONE data are from <a href="https://www.iso-ne.com/isoexpress/web/reports/pricing/-/tree/lmps-da-hourly">https://www.iso-ne.com/isoexpress/web/reports/pricing/-/tree/lmps-da-hourly</a> and <a href="https://www.iso-ne.com/isoexpress/web/reports/pricing/-/tree/lmps-rt-hourly-final">https://www.iso-ne.com/isoexpress/web/reports/pricing/-/tree/lmps-rt-hourly-final</a>. The Material is provided on an "as is" basis. ISO New England Inc., to the fullest extent permitted by law, disclaims all warranties, either express or implied, statutory or otherwise, including but not limited to the implied warranties of merchantability, non-infringement of third parties' rights, and fitness for particular purpose. Without limiting the foregoing, ISO New England Inc. makes no representations or warranties about the accuracy, reliability, completeness, date, or timeliness of the Material. ISO New England Inc. shall have no liability to you, your employer or any other third party based on your use of or reliance on the Material.</li> </ul> </li> <li>Data workup: LMP data were downloaded directly from the ISOs using scripts similar to the pvvm.data.download_lmps() function (see below for caveats), then repackaged into single-node single-year files using the pvvm.data.nodalize() function. These single-node single-year files were then combined into the dataframes included in this repository, using the procedure shown in the pvvm-vos-data.ipynb notebook for MISO. We provide these yearly dataframes, rather than the long-form data, to minimize file size and number. These dataframes can be unpacked into the single-node files used in the analysis using the pvvm.data.copylmps() function.</li> </ul> <p><strong>Usage notes</strong></p> <ul> <li>Code is provided under the <a href="https://opensource.org/licenses/MIT">MIT License</a>, as specified in the pvvm/LICENSE file and at the top of each *.py file. </li> <li>Updates to the code, if any, will be posted in the non-static repository at <a href="https://github.com/patrickbrown4/pvvm_vos">https://github.com/patrickbrown4/pvvm_vos</a>. The code in the present repository has the following version-specific dependencies: <ul> <li>matplotlib: 3.0.3</li> <li>numpy: 1.16.2</li> <li>pandas: 0.24.2</li> <li>pvlib: 0.6.1</li> <li>scipy: 1.2.1</li> <li>tqdm: 4.31.1</li> </ul> </li> <li>To use the NSRDB download functions, you will need to modify the "settings.py" file to insert a valid NSRDB API key, which can be requested from <a href="https://developer.nrel.gov/signup/">https://developer.nrel.gov/signup/</a>. Locations can be specified by passing (latitude, longitude) floats to pvvm.data.downloadNSRDBfile(), or by passing a string googlemaps query to pvvm.io.queryNSRDBfile(). To use the googlemaps functionality, you will need to request a googlemaps API key (<a href="https://developers.google.com/maps/documentation/javascript/get-api-key">https://developers.google.com/maps/documentation/javascript/get-api-key</a>) and insert it in the "settings.py" file.</li> <li>Note that many of the ISO websites have changed in the time since the functions in the pvvm.data module were written and the LMP data used in the above papers were downloaded. As such, the pvvm.data.download_lmps() function no longer works for all ISOs and years. We provide this function to illustrate the general procedure used, and do not intend to maintain it or keep it up to date with the changing ISO websites. For up-to-date functions for accessing ISO data, the following repository (no connection to the present work) may be helpful: <a href="https://github.com/catalyst-cooperative/pudl">https://github.com/catalyst-cooperative/pudl</a>.</li> </ul> <p> </p>
Data from: Reproduction under light pollution: maladaptive response to spatial variation in artificial light in a glow-worm
<p>The amount of artificial light at night is growing worldwide, impacting the behaviour of nocturnal organisms. Yet, we know little about the consequences of these behavioural responses for individual fitness and population viability. We investigated if females of the common glow-worm <i>Lampyris noctiluca</i> – which glow in the night to attract males – mitigate negative effects of artificial light on mate attraction by adjusting the timing and location of glowing to spatial variation in light conditions. We found females do not move away from light when exposed to a gradient of artificial light, but delay or even refrain from glowing. Further, we demonstrate that this response is maladaptive, as our field study showed that staying still when exposed to artificial light from a simulated streetlight decreases mate attraction success, while moving only a short distance from the light source can markedly improve mate attraction. These results indicate that glow-worms are unable to respond to spatial variation in artificial light, which may be a factor in their global decline. Consequently, our results support the hypothesis that animals often lack adaptive behavioural responses to anthropogenic environmental changes and underlines the importance of considering behavioural responses when investigating effects of human activities on wildlife.</p>
Data from: Temporal variation in spatial genetic structure during population outbreaks: distinguishing among different potential drivers of spatial synchrony
Spatial synchrony is a common characteristic of spatio-temporal population dynamics across many taxa. While it is known that both dispersal and spatially autocorrelated environmental variation (i.e., the Moran effect) can synchronize populations, the relative contributions of each, and how they interact, is generally unknown. Distinguishing these mechanisms and their effects on synchrony can help us to better understand spatial population dynamics, design conservation and management strategies, and predict climate change impacts. Population genetic data can be used to tease apart these two processes as the spatio-temporal genetic patterns they create are expected to be different. A challenge, however, is that genetic data are often collected at a single point in time, which may introduce context-specific bias. Spatio-temporal sampling strategies can be used to reduce bias and to improve our characterization of the drivers of spatial synchrony. Using spatio-temporal analyses of genotypic data, our objective was to identify the relative support for these two mechanisms to the spatial synchrony in population dynamics of the irruptive forest insect pest, the spruce budworm (Choristoneura fumiferana), in Quebec (Canada). AMOVA, cluster analysis, isolation by distance and sPCA were used to characterize spatio-temporal genomic variation using 1370 SBW larvae sampled over four years (2012-2015) and genotyped at 3,562 SNP loci. We found evidence of overall weak spatial genetic structure that decreased from 2012 to 2015 and a genetic diversity homogenization among the sites. We also found genetic evidence of a long-distance dispersal event over > 140 km. These results indicate that dispersal is the key mechanism involved in driving population synchrony of the outbreak. Early intervention management strategies that aim to control source populations have the potential to be effective through limiting dispersal. However, the timing of such interventions relative to outbreak progression is likely to influence their probability of success.
Freshwater zooplankton metapopulations and metacommunities respond differently to environmental and spatial variation data files
<p>We used this data to examine how crustacean zooplankton and rotifer species’ metapopulation genetic structure and metacommunities respond to environmental and spatial variation both within and across four regions of boreal Canada (see Martin et al. in press, Freshwater zooplankton metapopulations and metacommunities respond differently to environmental and spatial variation, Ecology).</p> <p>Whole community zooplankton samples were collected from 113 lakes from four environmentally, geologically, and geographically distinct regions of Québec, Canada. Each lake was sampled once, and the bulk zooplankton samples were sequenced using metabarcoding targeting the cytochrome c oxidase subunit I (COI) mitochondrial gene region. Sequences were clustered to species based on 3% OTUs and within species-variation was captured based on ASVs. Read abundances were then normalized using rarefaction to the lowest library to accommodate differences in sequencing depth across sites. In addition 16 environmental variables plus two spatial variables were used to capture abiotic variation between lakes. The data files include the ASV sequences, OTU and taxonomic assignment, and site variables.</p>
Data from: Aragonite bias exhibits systematic spatial variation in the late Cretaceous Western Interior Seaway, North America
Preferential dissolution of the biogenic carbonate polymorph aragonite promotes preservational bias in shelly marine faunas. Whilst field studies have documented the impact of preferential aragonite dissolution on fossil molluscan diversity, its impact on regional and global biodiversity metrics is debated. Epicontinental seas are especially prone to conditions which both promote and inhibit preferential dissolution, which may result in spatially extensive zones with variable preservation. Here we present a multi-faceted evaluation of aragonite dissolution within the late Cretaceous Western Interior Seaway of North America. Occurrence data of molluscs from two time intervals (Cenomanian-Turonian boundary, early Campanian) are plotted on new high-resolution paleogeographies to assess aragonite preservation within the seaway. Fossil occurrences, diversity estimates and sampling probabilities for calcitic and aragonitic fauna were compared in zones defined by depth and distance from the seaway margins. Apparent range sizes, which could be influenced by differential preservation potential of aragonite between separate localities, were also compared. Our results are consistent with exacerbated aragonite dissolution within specific depth zones for both time slices, with aragonitic bivalves additionally showing a statistically significant decrease in range size compared to calcitic fauna within carbonate-dominated Cenomanian-Turonian strata. However, we are unable to conclusively show that aragonite dissolution impacted diversity estimates. Therefore, whilst aragonite dissolution is likely to have affected the preservation of fauna in specific localities, time averaging and instantaneous preservation events preserve regional biodiversity. Our results suggest that the spatial expression of taphonomic biases should be an important consideration for paleontologists working on paleobiogeographic problems.
Spatial variation in early-winter snow cover determines local dynamics in a network of alpine butterfly populations
<p>Snow cover is an extremely variable but critical component of alpine environments. We use long term population data on multiple small populations of the alpine butterfly <i>Parnassius smintheus</i>, combined with high-resolution satellite imagery of meadows, to show a strong link between fine-scale spatial and temporal variation in early-winter snow cover and annual change in butterfly population size, accounting for up to 80 percent of the variation in annual population change. Snow cover in early winter for each meadow is the best predictor of annual adult population change, despite being estimated for a relatively short time-window in late November. We identify a means by which subpopulation response to a local, short-term weather variable can be assessed over a large spatial extent, but also at a resolution relevant to the biology and local dynamics of this alpine species.</p>
Temporal and spatial variation in population structure among brooding sea stars in the genus Leptasterias
<p>Temporal genetic studies of low-dispersing organisms are rare. Marine invertebrates lacking a planktonic larval stage are expected to have lower dispersal, low gene flow, and a higher potential for local adaptation than organisms with planktonic dispersal. <i>Leptasterias</i> is a genus of brooding sea stars containing several cryptic species complexes. Population genetic methods were used to resolve patterns of fine-scale population structure in central California <i>Leptasterias</i> species using three loci from nuclear and mitochondrial genomes. Historic samples (collected between 1897 and 1998) were compared to contemporary samples (collected between 2008 and 2014) to delineate changes in species distributions in space and time. Phylogenetic analysis of contemporary samples confirmed the presence of a bay-localized clade and revealed an additional bay-localized and previously undescribed clade of <i>Leptasterias</i>. Analysis of contemporary and historic samples indicates two clades are experiencing a constriction in their southern range limit and suggests a decrease in clade-specific abundance at sites at which they were once prevalent. Historic sampling revealed a dramatically different distribution of diversity along the California coastline compared to contemporary sampling and illustrates the importance of temporal genetic sampling in phylogeographic studies. These samples were collected prior to significant impacts of Sea Star Wasting Disease (SSWD) and represent an in-depth analysis of genetic structure over 117 years prior to the SSWD-associated mass die-off of <i>Leptasterias</i>. </p>
Data from: Revisiting the functional response in habitat selection for large herbivores: a matter of spatial variation in resource distribution?
Most habitats are distributed heterogeneously in space, forcing animals to move according to both habitat characteristics and their needs for energy and safety. Animal space use should therefore vary according to habitat characteristics, a process known as the "functional response" in habitat selection. This response has often been tested vis-à-vis the proportion of a habitat category within areas available to individuals. Measuring sought-after resources in landscape where they are continuously distributed is a challenge and we posit here that both the mean availability of a resource and its spatial variation should be measured. Accordingly, we tested for a functional response in habitat selection according to these two descriptors of the resource available for a mountain herbivore. We hypothesized that selection should decrease with mean value of resources available and increase with its spatial variation. Based on GPS data from 50 chamois females and data on the actual foodscape (i.e. distribution of edible-only biomass in the landscape), we estimated individual selection ratio (during summer months) for biomass at the home range level, comparing edible biomass in individual home ranges and the mean and standard deviation of edible biomass in their available range. Chamois being a group-living species, available accessible ranges were shared by several individuals that formed socio-spatial groups (clusters) in the population. As expected, selection ratios increased with the standard deviation of edible resources in each cluster, but unlike our prediction, was unrelated to its mean. Selection of areas richer in resources hence did not fade away when more resources were available on average, a result that may be explained by the need for this capital breeder species to accumulate fat-reserve at a high rate during summer months. Low spatial variation could limit the selection of chamois, which highlights the importance of resource distribution in the process of habitat selection.
Data from: 10 years of life in compost: temporal and spatial variation of North German C. elegans populations
The nematode Caenorhabditis elegans is a central laboratory model system in almost all biological disciplines, yet its natural life history and population biology are largely unexplored. Such information is essential for in-depth understanding of the nematode's biology because its natural ecology provides the context, in which its traits and the underlying molecular mechanisms evolved. We characterized natural phenotypic and genetic variation among North German C. elegans isolates. We used the unique opportunity to compare samples collected 10 years apart from the same compost heap and additionally included recent samples for this and a second site, collected across a 1.5-year period. Our analysis revealed significant population genetic differentiation between locations, across the 10-year time period, but for only one location a trend across the shorter time frame. Significant variation was similarly found for phenotypic traits of likely importance in nature, such as choice behavior and population growth in the presence of pathogens or naturally associated bacteria. Phenotypic variation was significantly influenced by C. elegans genotype, time of isolation, and sampling site. The here studied C. elegans isolates may provide a valuable, genetically variable resource for future dissection of naturally relevant gene functions.
Data from: Examining the full effects of landscape heterogeneity on spatial genetic variation: a multiple matrix regression approach for quantifying geographic and ecological isolation
Understanding the effects of landscape heterogeneity on spatial genetic variation is a primary goal of landscape genetics. Ecological and geographic variables can contribute to genetic structure through geographic isolation, in which geographic barriers and distances restrict gene flow, and ecological isolation, in which gene flow among populations inhabiting different environments is limited by selection against dispersers moving between them. Although methods have been developed to study geographic isolation in detail, ecological isolation has received much less attention, partly because disentangling the effects of these mechanisms is inherently difficult. Here, I describe a novel approach for quantifying the effects of geographic and ecological isolation using multiple matrix regression with randomization. I explored the parameter space over which this method is effective using a series of individual-based simulations and found that it accurately describes the effects of geographic and ecological isolation over a wide range of conditions. I also applied this method to a set of real-world datasets to show that ecological isolation is an often overlooked but important contributor to patterns of spatial genetic variation and to demonstrate how this analysis can provide new insights into how landscapes contribute to the evolution of genetic variation in nature.
Data from: Spatial and temporal patterns of neutral and adaptive genetic variation in the endangered African wild dog (Lycaon pictus)
Deciphering patterns of genetic variation within a species is essential for understanding population structure, local adaptation and differences in diversity between populations. Whilst neutrally evolving genetic markers can be used to elucidate demographic processes and genetic structure, they are not subject to selection and therefore are not informative about patterns of adaptive variation. As such, assessments of pertinent adaptive loci, such as the immunity genes of the Major Histocompatibility Complex (MHC), are increasingly being incorporated into genetic studies. In this study we combined neutral (microsatellite, mtDNA) and adaptive (MHC class II DLA-DRB1 locus) markers to elucidate the factors influencing patterns of genetic variation in the African wild dog (Lycaon pictus); an endangered canid that has suffered extensive declines in distribution and abundance. Our genetic analyses found all extant wild dog populations to be relatively small (Ne < 30). Furthermore, through coalescent modelling, we detected a genetic signature of a recent and substantial demographic decline, which correlates with human expansion, but contrasts with findings in some other African mammals. We found strong structure of wild dog populations, indicating the negative influence of extensive habitat fragmentation and loss of gene flow between habitat patches. Across populations we found that the spatial and temporal structure of microsatellite and MHC diversity were correlated, and strongly influenced by demographic stability and population size, indicating the effects of genetic drift in these small populations. Despite this correlation, we detected signatures of selection at the MHC, implying that selection has not been completely overwhelmed by genetic drift.
Data from: Partitioning drivers of spatial genetic variation for a continuously-distributed population of boreal caribou: implications for management unit delineation
Isolation-by-distance (IBD) is a natural pattern not readily incorporated into theoretical models nor traditional metrics for differentiating populations, although clinal genetic differentiation can be characteristic of many wildlife species. Landscape features can also drive population structure additive to baseline IBD resulting in differentiation through isolation-by-resistance (IBR). We assessed the population genetic structure of boreal caribou across western Canada using non-spatial (STRUCTURE) and spatial (MEMGENE) clustering methods and investigated the relative contribution of IBD and IBR on genetic variation of 1221 boreal caribou multilocus genotypes across western Canada. We further introduced a novel approach to compare the partitioning of individuals into management units (MU) and assessed levels of genetic connectivity under different MU scenarios. STRUCTURE delineated five genetic clusters while MEMGENE identified finer-scale differentiation across the study area. IBD was significant and did not differ for males and females both across and among detected genetic clusters. MEMGENE landscape analysis further quantified the proportion of genetic variation contributed by IBD and IBR patterns, allowing for the relative importance of spatial drivers, including roads, water bodies and wildfires, to be assessed and incorporated into the characterization of population structure for the delineation of MUs. Local population units, as currently delineated in the boreal caribou recovery strategy, do not capture the genetic variation and connectivity of the ecotype across the study area. Here, we provide the tools to assess fine-scale spatial patterns of genetic variation, partition drivers of genetic variation and evaluate the best management options for maintaining genetic connectivity. Our approach is highly relevant to vagile wildlife species that are of management and conservation concern and demonstrate varying degrees of IBD and IBR with clinal spatial genetic structure that challenges the delineation of discrete population boundaries.
Data from: Spatial variation in bird pollination and its mitigating effects on the genetic diversity of pollen pools accepted by Camellia japonica trees within a population at a landscape level
Bird pollination can vary spatially in response to spatial fluctuations in flowering even within plant populations. In this study, we examined the hypothesis that the spatial variation in bird pollination may induce mitigating effects which maintains or increases genetic diversity of pollen pools at local sites with low flowering densities. To test this hypothesis, we analyzed the landscape-level genetic effects within a population of Camellia japonica on the pollen pools accepted by individuals in two reproductive years by using genotypes at eight microsatellite loci of 1323 seeds from 19 seed parents. Regression analyses using the quadratic models of correlated paternity between pollen pools against spatial distances between the seed-parent pairs revealed not only local pollination but also some amount of long-distance pollen dispersal. The genetic diversity of pollen pools accepted by seed parents tended to be negatively related to the densities of flowering individuals near the seed parents during winter (when the effective pollination of C. japonica is mediated mostly by Zosterops japonica). We show that the low density of flowering individuals may induce the expansion of the foraging areas of Z. japonica and consequently increase the genetic diversity of pollen pools. This spatial variation in bird pollination may induce the mitigating effects on the C. japonica population. The comparisons between the two study years indicate that the overall pattern of bird pollination and the genetic effects described here, including the mitigating effects, may be stable over time.
Spatial variation in diet-microbe associations across populations of a generalist North American carnivore
1. Generalist species, by definition, exhibit variation in niche attributes that promote survival in changing environments. Increasingly, phenotypes previously associated with a species, particularly those with wide or expanding ranges, are dissolving and compelling greater emphasis on population-level characteristics. 2. In the present study, we assessed spatial variation in diet characteristics, gut microbiome, and the association between these two ecological traits across populations of coyotes (Canis latrans). We highlight the influence of the carnivore community in shaping these relationships, as the coyote varied from being an apex predator to a subordinate, mesopredator across sampled populations. 3. We implemented a scat survey across three distinct coyote populations in Michigan, USA. We used carbon (δ13C) and nitrogen (δ15N) isotopic values to reflect consumption patterns and trophic level, respectively. Corresponding samples were also paired with 16S rRNA sequencing to describe the microbial community and correlate with isotopic values. 4. Though consumption patterns were comparable, we found spatial variation in trophic level among coyote populations. Specifically, δ15N was highest where coyotes were the apex predator and lowest where coyotes co-occurred with gray wolves (Canis lupus). 5. The gut microbial community exhibited marked spatial variation across populations with the lowest OTU diversity found where coyotes occurred at their lowest trophic level. Bacteriodes and Fusobacterium dominated the microbiome and were positively correlated across all populations. We found no correlation between δ13C and microbial community attributes. However, positive associations between δ15N and specific microbial genera increased as coyotes ascended trophic levels. 6. Coyotes provide a model for exploring implications of niche plasticity because they are a highly adaptable, wide-ranging omnivore. As coyotes continue to vary in trophic position and expand their geographic range, we might expect increased divergence within their microbial community, changes in physiology, and alterations in behavior. 05-May-2020
Data from: Influences of environmental and spatial factors on genetic and epigenetic variations in Rhododendron oldhamii (Ericaceae)
Test of the relationship of genetic and particularly epigenetic variation with geographic isolation and environment is important to reveal potential environmental drivers for selection. Rhododendron oldhamii is widespread but inhabits fragmented subtropical forest landscapes and populations across its range may exhibit different levels of genetic and epigenetic structuring correlated to their environmental conditions. Here, we investigated the genetic and epigenetic variations and their ecological correlates in R. oldhamii. Genetic and epigenetic variations were surveyed using amplified fragment length polymorphism (AFLP) and methylation-sensitive amplification polymorphism (MSAP), respectively. Using variation partitioning by redundant analysis (RDA), we examined the pure and spatially-structured environmental effects and pure spatial factors on genetic and epigenetic variations among individuals collected from 18 localities across R. oldhamii distribution range in Taiwan. We found that environments compared to geographic isolation among sites explained more genetic and epigenetic variations. Patchy distribution of the contemporary R. oldhamii populations was revealed by correlograms with patch size of approximately around 20-30 km based on the total genetic and epigenetic data. Spatial variables derived from the method of principal coordinates of neighbor matrices (PCNM), including PCNM3, PCNM5, PCNM7 and PCNM8 representing biotic processes, such as individual dispersal, were found to be important influencing potentially adaptive genetic and epigenetic variations. Annual mean temperature, annual precipitation, precipitation of the warmest quarter, aspect, slope and soil moisture were the most important environmental variables influencing potentially adaptive genetic and epigenetic variations, and could be particularly important for the evolution of local adaptation in R. oldhamii.
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.