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1,868 results for “Spatial Data”
Data from: Revised time scales of RNA virus evolution based on spatial information
The time scales of pathogen evolution are of major concern in the context of public and veterinary health, epidemiology and evolutionary biology. Dating the emergence of a pathogen often relies on estimates of evolutionary rates derived from nucleotide sequence data. For many viruses, this has yielded estimates of evolutionary origins only a few hundred years in the past. Here we demonstrate through the incorporation of geographic information from virus sampling that evolutionary age estimates of two European hantaviruses are severely underestimated because of pervasive mutational saturation of nucleotide sequences. We detected very strong relationships between spatial distance and genetic divergence for both Puumala and Tula hantavirus – irrespective whether nucleotide or derived amino acid sequences were analyzed. Extrapolations from these relationships dated the emergence of these viruses most conservatively to at least 3,700 and 2,500 years ago, respectively. Our minimum estimates for the age of these hantaviruses are ten to a hundred times older than results from current non-spatial methods and in much better accordance with the biogeography of these viruses and their respective hosts. Spatial information can thus provide valuable insights on the deeper time scales of pathogen evolution and improve our understanding of disease emergence.
Data from: Sharpening coarse-to-fine stereo vision by perceptual learning: asymmetric transfer across the spatial frequency spectrum
Neurons in the early visual cortex are finely tuned to different low-level visual features, forming a multi-channel system analysing the visual image formed on the retina in a parallel manner. However, little is known about the potential 'cross-talk' among these channels. Here, we systematically investigated whether stereoacuity, over a large range of target spatial frequencies, can be enhanced by perceptual learning. Using narrow-band visual stimuli, we found that practice with coarse (low spatial frequency) targets substantially improves performance, and that the improvement spreads from coarse to fine (high spatial frequency) three-dimensional perception, generalizing broadly across untrained spatial frequencies and orientations. Notably, we observed an asymmetric transfer of learning across the spatial frequency spectrum. The bandwidth of transfer was broader when training was at a high spatial frequency than at a low spatial frequency. Stereoacuity training is most beneficial when trained with fine targets. This broad transfer of stereoacuity learning contrasts with the highly specific learning reported for other basic visual functions. We also revealed strategies to boost learning outcomes 'beyond-the-plateau'. Our investigations contribute to understanding the functional properties of the network subserving stereovision. The ability to generalize may provide a key principle for restoring impaired binocular vision in clinical situations.
Data from: Changes in spatial variance during a grassland to shrubland state transition
State transitions are changes in ecosystem structure and self-reinforcing feedbacks that are initiated when an exogenous driver variable crosses a threshold. Reversing state transitions is difficult and costly. While some state transitions are relatively rapid, many take years to decades. Outside of theoretical models, very little is known about slower state transitions and how they unfold in time and space. We quantified changes in spatial variance as a mesic grassland ecosystem shifts to a shrub-dominated state, using long-term experiments and simulations that maintain grasslands with annual fires or initiate a state transition to shrub dominance by decreasing fire frequency. In the experiments, the susceptibility to state transitions varied substantially in space. In the less frequent fire treatment, some plots became shrub-dominated around year 20 and grass extirpations began in year 25, but a third of the plots were still grass-dominated in year 37. Variable rates of state transition resulted in increasing spatial variance of grass cover over time, whereas shrub cover variance decreased. In the annually burned treatment, grasses remained dominant and the spatial variance of grass cover declined. In a separate experiment, less frequent fires were maintained for 23 years and then switched to annual fires. The switch to annual fires occurred shortly after grass variance started to increase and a majority of these plots quickly returned to a grass dominated state. In simulations, spatial variance remained low and average grass cover was high under frequent fires. If fire frequency decreased below a threshold, the ecosystem transitioned to shrubland, with a transient increase in the spatial variance of grass cover during the transition between states. Synthesis. Spatial variability in the rate and susceptibility to state transitions is indicative of a system with a patchy spatial structure, high spatial heterogeneity and low connectivity between patches. Increases in spatial variance can serve as an indication that some patches have begun a state transition and that management interventions are needed to avoid widespread transitions. This is one of the first empirical examples where altering management after an increase in spatial variance prevented state transitions.
Data from: Fractal measures of spatial pattern as a heuristic for return rate in vegetative systems
Measurement of population persistence is a long-standing problem in ecology; in particular, whether it is possible to gain insights into persistence without long time-series. Fractal measurements of spatial patterns, such as the Korcak exponent or boundary dimension, have been proposed as indicators of the persistence of underlying dynamics. Here we explore under what conditions a predictive relationship between fractal measures and persistence exists. We combine theoretical arguments with an aerial snapshot and time series from a long-term study of seagrass. For this form of vegetative growth, we find that the expected relationship between the Korcak exponent and persistence is evident at survey sites where the population return rate can be measured. This highlights a limitation of the use of power-law patch-size distributions and other indicators based on spatial snapshots. Moreover, our numeric simulations show that for a single species and a range of environmental conditions that the Korcak–persistence relationship provides a link between temporal dynamics and spatial pattern; however, this relationship is specific to demographic factors, so we cannot use this methodology to compare between species.
Data from: Online spatial normalization for real-time fMRI
Real-time functional magnetic resonance imaging (rtfMRI) is a recently emerged technique that demands fast data processing within a single repetition time (TR), such as a TR of 2 seconds. Data preprocessing in rtfMRI has rarely involved spatial normalization, which can not be accomplished in a short time period. However, spatial normalization may be critical for accurate functional localization in a stereotactic space and is an essential procedure for some emerging applications of rtfMRI. In this study, we introduced an online spatial normalization method that adopts a novel affine registration (AFR) procedure based on principal axes registration (PA) and Gauss-Newton optimization (GN) using the self-adaptive β parameter, termed PA-GN(β) AFR and nonlinear registration (NLR) based on discrete cosine transform (DCT). In AFR, PA provides an appropriate initial estimate of GN to induce the rapid convergence of GN. In addition, the β parameter, which relies on the change rate of cost function, is employed to self-adaptively adjust the iteration step of GN. The accuracy and performance of PA-GN(β) AFR were confirmed using both simulation and real data and compared with the traditional AFR. The appropriate cutoff frequency of the DCT basis function in NLR was determined to balance the accuracy and calculation load of the online spatial normalization. Finally, the validity of the online spatial normalization method was further demonstrated by brain activation in the rtfMRI data.
Data from: The challenges that spatial context present for synthesizing community ecology across scales
Accurately characterizing spatial patterns on landscapes is necessary to understand the processes that generate biodiversity, a problem that has applications in ecological theory, conservation planning, ecosystem restoration, and ecosystem management. However, the measurement of biodiversity patterns and the ecological and evolutionary processes that underlie those patterns is highly dependent on the study unit size, boundary placement, and number of observations. These issues, together known as the modifiable areal unit problem, are well known in geography. These factors limit the degree to which results from different metacommunity and macro-ecological studies can be compared to draw new inferences, and yet these types of comparisons are widespread in community ecology. Using aquatic community datasets, we demonstrate that spatial context drives analytical results when landscapes are sub-divided. Next, we present a framework for using resampling and neighborhood smoothing to standardize datasets to allow for inferential comparisons. We then provide examples for how addressing these issues enhances our ability to understand the processes shaping ecological communities at landscape scales and allows for informative meta-analytical synthesis. We conclude by calling for greater recognition of issues derived from the modifiable areal unit problem in community ecology, discuss implications of the problem for interpreting the existing literature, and identify tools and approaches for future research.
Data from: Spatial-temporal variability and related factors of soil organic carbon in Henan province
Spatial variability and influence factors are important to evaluate soil organic carbon(SOC) and the carbon pool in large areas. In the present study, sampling was conducted from May to November 2011 in Henan province, a typical agricultural region of central China, to study the effects of soil properties and anthropogenic factors on SOC variability in cropland. Physicochemical properties of soil samples were analyzed, which were collected at 280 sites from the surface layer (at a depth of 0–20 cm), and related data about the sampling sites were also collected from the Second State Soil Survey of China (SSSSC), conducted in 1981. The main results were as follows: 1) Increasing trends in soil organic carbon density (SOCD) and soil organic carbon pool (SOCP) were obvious from 1981 to 2011, and we conclude that cropland presents great carbon sequestration potential for the future. Carbon pool ability varied with soil properties: the order of fixed carbon amount in different soil types was found to be Inceptisols > Luvisols > Semi-hydromorphic soil > Anthrosols, and the average SOCP increased significantly from 1981 to 2011. 2) Soil bulk density, pH and returning straw are the key influence factors for SOCD in the past 30 years. 3) Although random factors (returning straw) only explain 29.1% of SOCD variability, the factor should be paid more attention, because application of returning strawwas the most dominant anthropogenic factors, which can be used to improve cropland productivity and carbon sink capacity within a short period if they are properly managed in the future.
Data from: Morphological variability in propagules of a desert annual as a function of rainfall patterns at different temporal and spatial scales
1.Organisms living in highly variable environments have to display integrated strategies to deal with both systematic and random variation occurring at different temporal and spatial scales. Two predictions were tested by analysing geographic-scale patterns of seed size and seed retention (serotiny) in Chorizanthe rigida, a strict winter desert annual that delays seed dispersal and releases propagules after rainfall events: (a) Adaptation to systematic environmental cues occurs by means of changes in morphology, and (b) within-individual variation in seed size allows a differential response to rainfall cues: while some seeds germinate rapidly others are retained for future rainfall events. 2.We quantified morphological variation and performed germination experiments on C. rigida propagules (involucres + achenes) from six populations distributed throughout the Mojave and Sonoran deserts covering: (a) a systematic, west-to-east, winter-to-bi-seasonal (summer and winter) precipitation gradient, and (b) a winter-rain unpredictability gradient inferred from long-term climatic data. 3.The propagule retention structure (i.e., base area of the pedicel) of C. rigida individuals experiencing bi-seasonal rainfall are double the size of those that have evolved under a strict winter rainfall regime, showing that populations living in bi-seasonal environments have higher seed retention which allows them to avoid releasing seeds to a summer rainfall cue. 4.Within-individual variance of propagule size varied significantly between populations and was correlated with winter rainfall variability in each site. 5.Germination varied as a function of propagule size; smaller seeds germinated more readily than larger seeds. Increased variability in propagule size might result in a more variable germination response. 6.Under common experimental conditions germination varied significantly among sites and was negatively correlated with mean winter effective precipitation, suggesting that propagules from populations in drier sites have lower germination moisture thresholds. 7.Synthesis. C. rigida propagules have larger bases in deserts with biseasonal rainfall, which allows them to avoid seed release during summer rainfall cues, and display within-individual seed variance associated to rainfall unpredictability, a trait often interpreted as a bet-hedging strategy. Our study provides empirical evidence of an integrated strategy that allows to cope with both random and systematic rainfall variation.
Data from: Spatial patterns and interspecific associations among trees at different stand development stages in the natural secondary forests on the Loess Plateau, China
Quercus wutaishansea populations on the Loess Plateau are currently becoming more dominant in natural secondary forests, whereas Pinus tabulaeformis is declining. In the present paper, the diameter class (instead of age) was used to classify the different growth stages as juvenile, subadult, or adult, and the univariate function g(r) was used to analyze the dynamic changes in spatial patterns and interspecific associations in three 1‐ha tree permanent plots on the Loess Plateau, NW China. Our results suggested that the niche breadth changed with the development stage. The diameter distribution curve was consistent with the inverted "J" type, indicating that natural regeneration was common in all three plots. There was a close relationship between the spatial pattern and scale, which showed significant aggregation at small distances, and became more random as distance increased, but in the Pinus + Quercus mixed forests, the whole species were aggregated at distances up to 50 m. The degree of spatial clumping decreased from juvenile to subadult and from subadult to adult. The spatial pattern also differed at different growth stages, likely due to strong intraspecific competition. Associations among different growth stages were positively correlated at small scales. Our study is important to the understanding of the development of the Q. wutaishansea forests; thus, the spatial dynamic change features should be received greater attention when planning forest management and developing restoration strategies on the Loess Plateau.
Data from: A new method for reconstructing brain morphology: applying the brain-neurocranial spatial relationship in an extant lungfish to a fossil endocast
Lungfish first appeared in the geological record over 410 million years ago and are the closest living group of fish to the tetrapods. Palaeoneurological investigations into the group show that unlike numerous other fishes—but more similar to those in tetrapods—lungfish appear to have had a close fit between the brain and the cranial cavity that housed it. As such, researchers can use the endocast of fossil taxa (an internal cast of the cranial cavity) both as a source of morphological data but also to aid in developing functional and phylogenetic implications about the group. Using fossil endocast data from a three-dimensional-preserved Late Devonian lungfish from the Gogo Formation, Rhinodipterus, and the brain-neurocranial relationship in the extant Australian lungfish, Neoceratodus, we herein present the first virtually reconstructed brain of a fossil lungfish. Computed tomographic data and a newly developed 'brain-warping' method are used in conjunction with our own distance map software tool to both analyse and present the data. The brain reconstruction is adequate, but we envisage that its accuracy and wider application in other taxonomic groups will grow with increasing availability of tomographic datasets.
Data from: Spatial and temporal patterns of nest distribution influences sexual selection in a marine fish
In many species, the natural distribution of material resources important for reproduction can profoundly impact reproductive success among individuals and, hence, the opportunity and intensity of sexual selection. Here, we report on a field-based experiment investigating the effects of nest aggregation on sexual selection in a fish, the sand goby (Pomatoschistus minutus). We found that the distribution of potential nests (sparse versus aggregated nest treatments) affected patterns of nest colonization and reproductive success. Specifically, in the treatment with aggregated nesting resources, a greater proportion of nests remained unoccupied by sand goby males. Although the size of nesting males did not differ between treatments, eggs accumulated more rapidly when nests were sparsely distributed. We found that the opportunity for selection decreased over time with the accumulation of eggs in the nests in both the aggregated and sparse treatments. Moreover, the effect of male size on reproductive success was influenced by an interaction between nest distribution and time, with the selection gradient being highest right after nest colonization when nests were aggregated, while the opposite pattern was observed in the sparse nest treatment. Such findings highlight the vital role that environmental and social factors can play in determining the importance of male phenotypic traits (in this case, male size). More broadly, our results also underscore how the natural distribution of resources, both in space and time, can impact the strength of sexual selection acting on wild animal populations.
Data from: Quantifying the effects of migration and mutation on adaptation and demography in spatially heterogeneous environments
How do mutation and gene flow influence population persistence, niche expansion, and local adaptation in spatially heterogeneous environments? In this article, we analyse a demographic and evolutionary model of adaptation to an environment containing two habitats in equal frequencies, and we bridge the gap between different theoretical frameworks. Qualitatively, our model yields four qualitative types of outcomes: (i) global extinction of the population (ii) adaptation to one habitat only, but also adaptation to both habitats with (iii) specialized phenotypes, or (iv) with generalized phenotypes; and we determine the conditions under which each equilibrium is reached. We derive new analytical approximations for the local densities and the distributions of traits in each habitat under a migration--selection--mutation balance, compute the equilibrium values of the means, variances and asymmetries of the local distributions of phenotypes, and contrast the effects of migration and mutation on the evolutionary outcome. We then check our analytical results by solving our model numerically, and also assess their robustness in the presence of demographic stochasticity. While increased migration results in a decrease in local adaptation, mutation in our model does not influence the values of the local mean traits. Yet, both migration and mutation can have dramatic effects on population size and even lead to metapopulation extinction when selection is strong. Niche expansion, the ability for the population to adapt to both habitats, can also be prevented by small migration rates and a reduced evolutionary potential characterised by rare mutation events of small effects; but niche expansion is otherwise the most likely outcome. Although our results are derived under the assumption of clonal reproduction, we finally show and discuss the links between our model and previous quantitative genetics models.
Data from: Detecting spatial genetic signatures of local adaptation in heterogeneous landscapes
The spatial structure of the environment (e.g., the configuration of habitat patches) may play an important role in determining the strength of local adaptation. However, previous studies of habitat heterogeneity and local adaptation have largely been limited to simple landscapes, which poorly represent the multi-scale habitat structure common in nature. Here, we use simulations to pursue two goals: (1) we explore how landscape heterogeneity, dispersal ability, and selection affect the strength of local adaptation, and (2) we evaluate the performance of several genotype-environment association (GEA) methods for detecting loci involved in local adaptation. We found that the strength of local adaptation increased in spatially aggregated selection regimes, but remained strong in patchy landscapes when selection was moderate to strong. Weak selection resulted in weak local adaptation that was relatively unaffected by landscape heterogeneity. In general, the power of detection methods closely reflected levels of local adaptation. False positive rates (FPRs), however, showed distinct differences across GEA methods based on levels of population structure. The univariate GEA approach had high FPRs (up to 55%) under limited dispersal scenarios, due to strong isolation by distance. By contrast, multivariate, ordination-based methods had uniformly low FPRs (0-2%), suggesting these approaches can effectively control for population structure. Specifically, constrained ordinations had the best balance of high detection and low FPRs, and will be a useful addition to the GEA toolkit. Our results provide both theoretical and practical insights into the conditions that shape local adaptation and how these conditions impact our ability to detect selection.
Data from: Analysing small insect glands with UV-LDI MS: high-resolution spatial analysis reveals the chemical composition and use of the osmeterium secretion in Themira superba (Sepsidae: Diptera)
For many insect species, pheromones are important communication tools, but chemical analysis and experimental study can be technically challenging because they require the detection and handling of complex chemicals in small quantities. One drawback of traditional mass spectrometry methods such as gas chromatography mass spectrometry is that whole-body extractions from one to several hundred individuals are required, with the consequence that intra- and interindividual differences cannot be detected. Here, we used the recently introduced UV-LDI MS (ultraviolet laser desorption/ionization mass spectrometry) to profile the 'osmeterium' of the sepsid fly Themira superba that is located on the edge of the hind tibia of males. Based on analyses of individual legs, we established that the gland produced a secretion that consisted of oxygenated hydrocarbons and putative isoprenoids. The secretion was first detected 24 h after eclosion, and its transfer to the wings of females during mating was demonstrated using UV-LDI MS. We then tested whether the secretion had an anti-aphrodisiac function, but experimental transfer of the secretion to virgin females did not affect mating success or copulation duration. Throughout the study, UV-LDI MS proved invaluable, because it allowed tracking the natural and experimental transfer of small quantities of pheromones to specific body parts of small flies.
Data from: Spatial heterogeneity in the strength of plant-herbivore interactions under predation risk: the tale of bison foraging in wolf country
Spatial heterogeneity in the strength of trophic interactions is a fundamental property of food web spatial dynamics. The feeding effort of herbivores should reflect adaptive decisions that only become rewarding when foraging gains exceed 1) the metabolic costs, 2) the missed opportunity costs of not foraging elsewhere, and 3) the foraging costs of anti-predator behaviour. Two aspects of these costs remain largely unexplored: the link between the strength of plant-herbivore interactions and the spatial scale of food-quality assessment, and the predator-prey spatial game. We modeled the foraging effort of free-ranging plains bison (Bison bison bison) in winter, within a mosaic of discrete meadows. Spatial patterns of bison herbivory were largely driven by a search for high net energy gains and, to a lesser degree, by the spatial game with grey wolves (Canis lupus). Bison decreased local feeding effort with increasing metabolic and missed opportunity costs. Bison herbivory was most consistent with a broad-scale assessment of food patch quality, i.e., bison grazed more intensively in patches with a low missed opportunity cost relative to other patches available in the landscape. Bison and wolves had a higher probability of using the same meadows than expected randomly. This co-occurrence indicates wolves are ahead in the spatial game they play with bison. Wolves influenced bison foraging at fine scale, as bison tended to consume less biomass at each feeding station when in meadows where the risk of a wolf's arrival was relatively high. Also, bison left more high-quality vegetation in large than small meadows. This behavior does not maximize their energy intake rate, but is consistent with bison playing a shell game with wolves. Our assessment of bison foraging in a natural setting clarifies the complex nature of plant-herbivore interactions under predation risk, and reveals how spatial patterns in herbivory emerge from multi-scale landscape heterogeneity.
Data from: Dispersal influences genetic and acoustic spatial structure for both males and females in a tropical songbird
1. Animals exhibit diverse dispersal strategies, including sex-biased dispersal, a phenomenon common in vertebrates. Dispersal influences the genetic structure of populations as well as geographic variation in phenotypic traits. Patterns of spatial genetic structure and geographic variation may vary between the sexes whenever males and females exhibit different dispersal behaviours. 2. Here, we examine dispersal, spatial genetic structure, and spatial acoustic structure in Rufous-and-white Wrens, a year-round resident tropical bird. Both sexes sing in this species, allowing us to compare acoustic variation between males and females, and examine the relationship between dispersal and song sharing for both sexes. 3. Using a long-term dataset collected over an 11-year period, we used banding data and molecular genetic analyses to quantify natal and breeding dispersal distance in Rufous-and-white Wrens. We quantified song-sharing and examined whether sharing varied with dispersal distance, for both males and females. 4. Observational data and molecular genetic analyses indicate that dispersal is female-biased. Females dispersed farther from natal territories than males, and more often between breeding territories than males. Furthermore, females showed no significant spatial genetic structure, consistent with expectations, whereas males showed significant spatial genetic structure. Overall, natal dispersal appears to have more influence than breeding dispersal on spatial genetic structure and spatial acoustic structure, given that the majority of breeding dispersal events resulted in individuals moving only short distances. 5. Song sharing between pairs of same-sex animals decreases with the distance between their territories for both males and females, although males exhibited significantly greater song-sharing than females. 6. Lastly, we measured the relationship between natal dispersal distance and song sharing. We found that sons shared fewer songs with their fathers the farther they dispersed from their natal territories, but that song sharing between daughters and mothers was not significantly correlated with natal dispersal distance. 7. Our results reveal cultural differences between the sexes, suggesting a relationship between culture and sex-biased dispersal
Data from: Optimizing the spatial planning of prescribed burns to achieve multiple objectives in a fire-dependent ecosystem.
1. There is potential for negative consequences for the ecological integrity of fire-dependent ecosystems as a result of inappropriate fire regimes. This can occur when asset (property) protection is prioritised over conservation objectives in burn programs. 2. Optimisation of fire management for multiple objectives is rarely undertaken. Here, we use integer linear programming to identify burn scheduling solutions that will cost-effectively achieve asset protection and conservation objectives. 3. An approach to burn scheduling that favours a risk-averse asset protection strategy results in poor conservation outcomes. Conversely, a conservation-focused approach achieves only modest asset protection benefits. However, when formulated as a multi-objective problem, good conservation outcomes can be realised with only a small reduction in potential benefits for asset protection. 4. A conservation-focused approach resulted in substantially more heterogeneity in burns at multiple spatial scales and a marked reduction in mean time since fire among all forest patches relative to an asset protection scenario. This increase in heterogeneity improves ecological integrity, while the resulting reduction in fuel load is beneficial for asset protection. 5. Synthesis and applications. Mathematical optimisation is a powerful framework for informing fire management that improves the prioritisation and scheduling of controlled burns to efficiently achieve management objectives. By quantifying the trade-offs that exist between the two competing objectives of conservation and asset protection we demonstrate that compromise solutions can be identified that achieve good outcomes for both objectives. In a transparent and equitable manner, we show that conservation value may be improved within a fire-dependent ecosystem with only modest concession to asset protection performance. Explicitly evaluating trade-offs among competing objectives enables managers to identify potentially undesirable outcomes, and facilitate development of preferred solutions. Heterogeneous burning under the auspices of conservation also has the potential to reduce overall fuel loads within the ecosystem and thus its value for asset protection is likely underappreciated.
Data from: Crop-to-wild gene flow and spatial genetic structure in the closest wild relatives of the cultivated apple
Crop-to-wild gene flow have important evolutionary and ecological consequences and require careful consideration in conservation programs for wild genetic resources of potential use in breeding programs and in assessments of the risk of transgene escape into natural ecosystems. Using 26 microsatellites and a set of 1181 trees, we investigated the extent of introgression from the cultivated apple, Malus domestica, to its three closest wild relatives, M. sylvestris in Europe, M. orientalis in the Caucasus and M. sieversii in Central Asia. We found footprints of introgression from M. domestica to M. orientalis (3.2% of hybrids), M. sieversii (14.8%) and M. sylvestris (36.7%). Malus sieversii and M. orientalis presented weak but significant genetic structures across their geographic range. Malus orientalis displayed genetic differentiation with three differentiated populations in Turkey, Armenia and Russia. Malus sieversii consisted of a main population spread over Central Asia and a smaller population in the Tian Shan Mountains. The low Sp values suggest high dispersal capacities for the wild apple relatives. High potential for crop-to-wild gene flow in apples needs to be considered in the implementation of in situ and ex situ actions for the conservation of wild apple genetic resources potentially useful to plant breeding.
Data from: Spatial and temporal genetic structure at the fourth trophic level in a fragmented landscape
A fragmented habitat becomes increasingly fragmented for species at higher trophic levels, such as parasitoids. To persist, these species are expected to possess life-history traits, such as high dispersal, that facilitate their ability to use resources that become scarce in fragmented landscapes. If a specialized parasitoid disperses widely to take advantage of a sparse host, then the parasitoid population should have lower genetic structure than the host. We investigated the temporal and spatial genetic structure of a hyperparasitoid (fourth trophic level) in a fragmented landscape over 50 × 70 km, using microsatellite markers, and compared it with the known structures of its host parasitoid, and the butterfly host which lives as a classic metapopulation. We found that population genetic structure decreases with increasing trophic level. The hyperparasitoid has fewer genetic clusters (K = 4), than its host parasitoid (K = 15), which in turn is less structured than the host butterfly (K = 27). The genetic structure of the hyperparasitoid also shows temporal variation, with genetic differentiation increasing due to reduction of the population size, which reduces the effective population size. Overall, our study confirms the idea that specialized species must be dispersive to use a fragmented host resource, but that this adaptation has limits.
Data from: A spatial theory for characterizing predator–multiprey interactions in heterogeneous landscapes
Trophic interactions in multiprey systems can be largely determined by prey distributions. Yet, classic predator–prey models assume spatially homogeneous interactions between predators and prey. We developed a spatially informed theory that predicts how habitat heterogeneity alters the landscape-scale distribution of mortality risk of prey from predation, and hence the nature of predator interactions in multiprey systems. The theoretical model is a spatially explicit, multiprey functional response in which species-specific advection–diffusion models account for the response of individual prey to habitat edges. The model demonstrates that distinct responses of alternative prey species can alter the consequences of conspecific aggregation, from increasing safety to increasing predation risk. Observations of threatened boreal caribou, moose and grey wolf interacting over 378 181 km2 of human-managed boreal forest support this principle. This empirically supported theory demonstrates how distinct responses of apparent competitors to landscape heterogeneity, including to human disturbances, can reverse density dependence in fitness correlates.
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.