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470 results for “spatial pattern”
Short-Tandem-Repeat (STR) marker set for Eurasian lynx for article: Genetic analysis indicates spatial-dependent patterns of sex-biased dispersal in Eurasian lynx in Finland
<p>Conservation and management of large carnivores requires knowledge of female and male dispersal. Such information is crucial to evaluate the population's status and thus management actions. This knowledge is challenging to obtain, often incomplete and contradictory at times. The size of the target population and the methods applied can bias the results. Also, population history and biological or environmental influences can affect dispersal on different scales within a study area. We have genotyped Eurasian lynx (180 males and 102 females, collected 2003-2017) continuously distributed in southern Finland (~23,000 km<sup>2</sup>) using 21 short tandem repeats (STR) loci and compared statistical genetic tests to infer local and sex-specific dispersal patterns within and across genetic clusters as well as geographic regions. We tested for sex-specific substructure with individual-based Bayesian assignment tests and spatial autocorrelation analyses. Differences between the sexes in genetic differentiation, relatedness, inbreeding, and diversity were analysed using population-based AMOVA, F-statistics, and assignment indices. Our results showed two different genetic clusters that were spatially structured for females but admixed for males. Similarly, spatial autocorrelation and relatedness was significantly higher in females than males. However, we found weaker sex-specific patterns for the Eurasian lynx when the data were separated in three geographical regions than when divided in the two genetic clusters. Overall, our results suggest male-biased dispersal and female philopatry for the Eurasian lynx in Southern Finland. The female genetic structuring increased from west to east within our study area. In addition, detection of male-biased dispersal was dependent on analytical methods utilized, on whether subtle underlying genetic structuring was considered or not, and the choice of population delineation. Conclusively, we suggest using multiple genetic approaches to study sex-biased dispersal in a continuously distributed species in which population delineation is difficult.</p>
Data from: Scale‐dependent spatial patterns in benthic communities around a tropical island seascape
Understanding and predicting patterns of spatial organization across ecological communities is central to the field of landscape ecology, and a similar line of inquiry has begun to evolve sub‐tidally among seascape ecologists. Much of our current understanding of the processes driving marine community patterns, particularly in the tropics, has come from small‐scale, spatially‐discrete data that are often not representative of the broader seascape. Here we expand the spatial extent of seascape ecology studies and combine spatially‐expansive in situ digital imagery, oceanographic measurements, spatial statistics, and predictive modeling to test whether predictable patterns emerge between coral reef benthic competitors across scales in response to intra‐island gradients in physical drivers. We do this around the entire circumference of a remote, uninhabited island in the central Pacific (Jarvis Island) that lacks the confounding effects of direct human impacts. We show, for the first time, that competing benthic groups demonstrate predictable scaling patterns of organization, with positive autocorrelation in the cover of each group at scales < ~1 km. Moreover, we show how gradients in subsurface temperature and surface wave power drive spatially‐abrupt transition points in group dominance, explaining 48 – 84% of the overall variation in benthic cover around the island. Along the western coast, we documented ten times more sub‐surface cooling‐hours than any other part of the coastline, with events typically resulting in a drop of 1 – 4°C over a period of < 5 hr. These high frequency temperature fluctuations are indicative of upwelling induced by internal waves and here result in localized nitrogen enrichment (NO2 + NO3) that promotes hard coral dominance around 44% of the island's perimeter. Our findings show that, in the absence of confounding direct human impacts, the spatial organization of coral reef benthic competitors are predictable and somewhat bounded across the seascape by concurrent gradients in physical drivers.
Data from: Repeatable patterns of small-scale spatial variation in intertidal mussel beds and their implications for responses to climate change
The interaction of ocean conditions and weather with small-scale physical features of a habitat can have profound effects on the experiences of individual organisms. On topographically complex shorelines, and particularly within dense aggregations of organisms such as mussel beds, a mosaic of environmental conditions can develop, and the resulting variation in conditions within the aggregation could drastically alter the performance of neighboring individuals. Using a suite of sensors mounted to individual Mytilus californianus mussels over two summer field deployments, we have characterized the temperature variation and valve gaping behavior differences found at two spatial scales: within a group separated by centimeters, and between groups of mussels located at the upper and lower extents of the natural mussel zone separated by meters. While temperature conditions near the lower edge of the mussel bed were generally more benign, temperature extremes were similar at both heights in the bed, and variation in body temperature among neighbors increased as the daily mean temperature increased. These patterns were similar across years despite a 3.8°C difference in mean air and seawater temperatures between years. Gaping behavior was also highly variable among individuals, though that variability diminished at the high end of the mussel bed where the total time mussels spent submerged was much more constrained. These data indicate that an individual mussel's physiological status and past history can be drastically different than those of its nearby neighbors, complicating our ability to characterize representative conditions within a habitat. These observations also provide for the possibility that the impacts of future climate change will be highly specific to certain individuals based on their relative exposure or protection within the mosaic. To address such possibilities, future work must examine the correlation between genotypic and physiological traits that determine performance and individuals' unique experiences in their disparate micro-environments.
Data from: A new digital method of data collection for spatial point pattern analysis in grassland communities
<p>A major objective of plant ecology research is to determine the underlying processes responsible for the observed spatial distribution patterns of plant species. Plants can be approximated as points in space for this purpose, and thus, spatial point pattern analysis has become increasingly popular in ecological research. The basic piece of data for point pattern analysis is a point location of an ecological object in some study region. Therefore, point pattern analysis can only be performed if data can be collected. However, due to the lack of a convenient sampling method, a few previous studies have used point pattern analysis to examine the spatial patterns of grassland species. This is unfortunate because being able to explore point patterns in grassland systems has widespread implications for population dynamics, community-level patterns and ecological processes. In this study, we develop a new method to measure individual coordinates of species in grassland communities. This method records plant growing positions via digital picture samples that have been sub-blocked within a geographical information system (GIS). Here, we tested out the new method by measuring the individual coordinates of <i>Stipa</i><i> grandis</i> in grazed and ungrazed <i>S. grandis</i> communities in a temperate steppe ecosystem in China. Furthermore, we analyzed the pattern of <i>S. grandis</i> by using the pair correlation function <i>g</i>(<i>r</i>) with both a homogeneous Poisson process and a heterogeneous Poisson process. Our results showed that individuals of <i>S. grandis</i> were overdispersed according to the homogeneous Poisson process at 0-0.16 m in the ungrazed community, while they were clustered at 0.19 m according to the homogeneous and heterogeneous Poisson processes in the grazed community. These results suggest that competitive interactions dominated the ungrazed community, while facilitative interactions dominated the grazed community. In sum, we successfully executed a new sampling method, using digital photography and a Geographical Information System, to collect experimental data on the spatial point patterns for the populations in this grassland community.</p>
Data from: The role of climate, water and biotic interactions in shaping biodiversity patterns in arid environments across spatial scales
Aim: Desert ecosystems, with their harsh environmental conditions, hold the key to understanding the responses of biodiversity to climate change. As desert community structure is influenced by processes acting at different spatial scales, studies combining multiple scales are essential for understanding the conservation requirements of desert biota. We investigated the role of environmental variables and biotic interactions in shaping broad and fine-scale patterns of diversity and distribution of bats in arid environments to understand how the expansion of nondesert species can affect the long-term conservation of desert biodiversity. Location: Levant, Eastern Mediterranean. Methods: We combine species distribution modelling and niche overlap statistics with a statistical model selection approach to integrate interspecific interactions into broadscale distribution models and fine-scale analysis of ecological requirements. We focus on competition between desert bats and mesic species that recently expanded their distribution into arid environment following anthropogenic land-use changes. Results: We show that both climate and water availability limit bat distributions and diversity across spatial scales. The broadscale distribution of bats was determined by proximity to water and high temperatures, although the latter did not affect the distribution of mesic species. At the fine-scale, high levels of bat activity and diversity were associated with increased water availability and warmer periods. Desert species were strongly associated with warmer and drier desert types. Range and niche overlap were high among potential competitors, but coexistence was facilitated through fine-scale spatial partitioning of water resources. Main conclusions: Adaptations to drier and warmer conditions allow desert-obligate species to prevail in more arid environments. However, this competitive advantage may disappear as anthropogenic activities encroach further into desert habitats. We conclude that reduced water availability in arid environments under future climate change projections pose a major threat to desert wildlife because it can affect survival and reproductive success and may increase competition over remaining water resources.
Data from: Assessing spatial patterns of soil erosion in a high‐latitude rangeland
<p>High‐latitude areas are experiencing rapid change: we therefore need a better understanding of the processes controlling soil erosion in these environments. We used a spatiotemporal approach to investigate soil erosion in Svalbarðstunga, Iceland (66° N, 15° W), a degraded rangeland. We used three complementary datasets: 1) high‐resolution UAV imagery collected from 12 sites (total area ~0.75 km<sup>2</sup>); 2) historical imagery of the same sites; and 3) a simple, spatially‐explicit cellular automata model. Sites were located along a gradient of increasing altitude and distance from the sea, and varied in erosion severity (5–47% eroded). We found that there was no simple relationship between location along the environmental gradient and the spatial characteristics of erosion. Patch‐size frequency distributions lacked a characteristic scale of variation, but followed a power‐law distribution on five of the 12 sites. Present total eroded area is poorly related to current, site‐scale levels of environmental stress, but the number of small erosion patches did reflect site‐level stress. Small (< 25 m<sup>2</sup>) erosion patches clustered near large patches. The model results suggested that the large‐scale patterns observed likely arise from strong, local interactions, which mean that erosion spreads from degraded areas. Our findings suggest that contemporary erosion patterns reflect historical stresses, as well as current environmental conditions. The importance of abiotic processes to the growth of large erosion patches and their relative insensitivity to current environmental conditions makes it likely that the total eroded area will continue to increase, despite a warming climate and reducing levels of grazing pressure.</p>
Data from a flexible framework to assess patterns and drivers of beta diversity across spatial scales
<p><span>The patterns and underlying ecological (e.g., environmental filtering) and </span><span>historical</span><span> (e.g., priority effects) drivers of beta diversity are scale-dependent but generally difficult to distinguish</span> <span>and rarely explored with a sufficiently broad range of spatial scales. We propose a general scale-explicit framework to assess and contrast the patterns and drivers of beta diversity across hierarchical spatial scales ranging from within fine-scale ecoregion-scale to among broad-scale ecoregion-scale. By applying this framework to aquatic macroinvertebrate datasets, we show that beta diversity generally increases with spatial extent.</span> <span>With an increasing spatial extent, beta diversity shifts from being more influenced by environmental filtering to being more influenced by recent historical factors (i.e., past beta diversity). Such recent historical effects may result from past environmental variation rather than priority effects.</span><span> We also found that the small-scale and large-scale environmental drivers act differently on beta diversity across spatial extents. Our research reveals a complex spatial-scale dependence in beta diversity patterns and their drivers and provides a more holistic understanding of beta diversity dynamics. Our framework represents a flexible way to unravel the internal structure of beta diversity across scales by partitioning of entire beta diversity variation into scale-specific differences and may have broad application in community ecology, landscape planning and biodiversity conservation.</span></p>
Data from: Contrasting patterns of female house mouse spatial organisation among outbreaking and stable populations
<p>The size and distribution of home ranges reflects how individuals within a population use, defend, and share space and resources, and may thus be an important predictor of population-level dynamics. In eruptive species like the house mouse in Australian grain growing regions, contrasting space use between stable and outbreaking populations allows us to test predictions regarding social or life history strategies that may contribute to an outbreak. In this study we use spatially explicit capture-recapture models to compare home range overlap (as a proxy for territoriality) in female mice from populations showing different outbreak trajectories. We found that female space use in spring varied between outbreaking and stable populations. Our analysis indicated greater home range overlap in populations with stable trajectories compared to those that would later experience an outbreak, suggesting females in these stable populations may have had greater potential for cooperative group formation as indicated by shared space use. We discuss the results with respect to intrinsic factors, such as kin structure, with potential implications for better predicting mouse outbreaks at a microgeographic scale.</p>
Spatial patterns and effects of invasive plants on soil microbial activity and diversity along river corridors - raw data
<p>Dataset for the study</p> <p><strong><span>Spatial patterns and effects of invasive plants on soil microbial activity and diversity along river corridors</span></strong></p> <ol> <li>environmental variables of the research plots</li> <li>vascular plant species composition of the research plots</li> <li>mcirobial activity on the research plots</li> <li>CLPP profiles of the research plots</li> </ol>
Dataset on Spatial Analysis and Clustering of Deforestation in the Amazon Biome: Spatio-Temporal Patterns and Priority Areas
<p>The dataset was developed with the aim of facilitating the development of a methodology to identify and evaluate deforestation patterns and trends in the Amazon. This innovative method combines deforestation alerts from the Real-Time Deforestation Detection System (DETER) with detailed information on various land categories, including environmental protection areas, settlements, rural properties, undesignated public forests, indigenous lands, and conservation units. The integration of this robust data allowed for the precise identification of areas at risk of deforestation, significantly strengthening monitoring and control activities aimed at combating deforestation in the Amazon region.</p> <p> </p> <p><strong>Spatial resolution</strong></p> <p>The data are available with a spatial resolution of 25 x 25 km (625 km²) and cover the Amazon biome.</p> <p> </p> <p><strong>Temporal resolution </strong></p> <p>Period of observed data: 2017 and 2021</p> <p> </p> <p><strong>Coordinate reference system</strong> </p> <p>Geographic Coordinate System with Datum SIRGAS 2000 (EPSG:5880)</p> <p> </p> <p><strong>Data format</strong></p> <p>Data is provided as Shapefile.</p> <p> </p> <p><strong>Dataset usage</strong> </p> <p>It is free to use, but please make sure to cite the repository and our paper properly if you use this dataset.</p> <p> </p> <p><strong>Publication & further information</strong></p> <p>For additional scenario information, please contact Francisco Gilney Silva Bezerra (franciscogilney@gmail.com).</p>
Spatial distribution of naming patterns in Russian law firms through text embeddings: data and code
<p>Data and code for a paper about spatial analysis of law firms naming in Russia. See also the attached paper's DOI and URL as well as the link to the GitHub repository.</p>
Fine-scale spatial patterns of wildlife disease are common and understudied
<p>1. All parasites are heterogeneous in space, yet little is known about the prevalence and scale of this spatial variation, particularly in wild animal systems. To address this question, we sought to identify and examine spatial dependence of wildlife disease across a wide range of systems.</p> <p>2. Conducting a broad literature search, we collated 31 such datasets featuring 89 replicates and 71 unique host-parasite combinations, only 51% of which had previously been used to test spatial hypotheses. We analysed these datasets for spatial dependence within a standardised modelling framework using Bayesian linear models, and we then meta-analysed the results to identify generalised determinants of the scale and magnitude of spatial autocorrelation.</p> <p>3. We detected spatial autocorrelation in 48/89 model replicates (54%) across 21/31 datasets (68%), spread across parasites of all groups. Even some very small study areas (under 0.01km2) exhibited substantial spatial variation.</p> <p>4. Despite the common manifestation of spatial variation, our meta-analysis was unable to identify host-, parasite-, or sampling-level determinants of this heterogeneity across systems. Parasites of all transmission modes had easily detectable spatial patterns, implying that structured contact networks and susceptibility effects are potentially as important in spatially structuring disease as are environmental drivers of transmission efficiency.</p> <p>5. Our findings demonstrate that fine-scale spatial patterns of infection manifest frequently and across a range of wild animal systems, and many studies are able to investigate them – whether or not the original aim of the study was to examine spatially varying processes. Given the widespread nature of these findings, studies should more frequently record and analyse spatial data, facilitating development and testing of spatial hypotheses in disease ecology. Ultimately, this may pave the way for an a priori predictive framework for spatial variation in novel host-parasite systems.</p>
Data from: The effects of human-altered habitat spatial pattern on frugivory and seed dispersal: a global meta-analysis
<p>Seed dispersal by frugivorous animals is important for plant mobility, regeneration, and persistence. Human-caused landscape change is thought to disrupt seed dispersal, but evidence is scarce. We performed a comprehensive meta-analysis on the effects of habitat spatial pattern on frugivory and seed dispersal. We found 233 effects from 71 studies. At a patch or local scale, altered habitat spatial pattern was measured as declining patch size, increasing patch isolation, or habitat edge (vs. interior). At a landscape scale it was measured as declining amount of habitat, increasing mean patch isolation, increasing number of patches, or increasing habitat edge in the landscape.</p> <p>We found overall negative effects of altered habitat spatial pattern on: (i) the quantity of frugivory or seed dispersal, (ii) the number of species involved in a plant-frugivore interaction, and (iii) seed dispersal distance. Moderator variable analysis was only possible for the first of these. It revealed negative responses of the quantity of frugivory or seed dispersal to habitat loss at both the local scale (declining patch size), and the landscape scale (declining habitat amount), but little evidence for a response to habitat edge at either scale. In addition, altered habitat spatial pattern reduced the quantity of frugivory or seed dispersal more strongly in temperate than tropical areas. Finally, the few-recorded effects of landscape-scale fragmentation per se (increasing patch density or edge density) on the quantity of frugivory or seed dispersal were mixed and weak. Our meta-analysis reinforces the notion that habitat loss is a major threat to frugivory and seed dispersal by animals, and reveals an insufficiency of studies of the effects of habitat fragmentation per se. Thus, based on the current literature, we conclude that maintaining and increasing habitat amount is vital for maintaining seed dispersal by frugivorous animals.</p>
Data for: Modeling of spatial pattern and influencing factors of cultivated land quality based on spatial-temporal big data (PONE-D-21-21084R1)
<p>The quality of cultivated land determines the production capacity of cultivated land and the level of regional development, and also directly affects the food security and ecological safety of the country. This paper starts from the perspective of spatial pattern of cultivated land quality and uses spatial autocorrelation analysis to study the spatial aggregation characteristics and differences of cultivated land quality in Henan Province at the county level scale, and also uses bivariate spatial autocorrelation to analyze the influence of neighboring influences on the quality of cultivated land in the target area. The spatial autoregressive model was used to further analyze the driving factors affecting the quality of cultivated land, and the influence of cultivated land area index was coupled in the process of rating analysis, which was finally used as a basis to propose more precise measures for the protection of cultivated land zoning. The results show that: (1) The quality of cultivated land in Henan Province has a strong spatial correlation (global Moran's I≈0.710) and shows an obvious aggregation pattern in spatial distribution; positive correlation types (high-high and low-low) are concentrated in north-central and western mountainous areas of Henan Province, respectively; negative correlation types are discrete. The negative correlation types are distributed in a discrete manner. (2) The bivariate spatial autocorrelation results show that Slope (Moran's I≈-0.505), Irrigation guarantee rate (IGR, 0.354), Urbanization rate (-0.255), Total agricultural machinery power (TAMP, 0.331) and Pesticide use (0.214) are the main influencing factors. (3) According to the absolute values of the regression coefficients, it can be seen that the magnitude of the influence of different factors on the quality of cultivated land is: Slope (0.089) >IGR (0.025) > Urbanization rate (0.002) > TAMP (0.001) > Pesticide use (1.96e-006). (4) Based on the spatial pattern presented by the spatial autocorrelation results, we proposed corresponding protection zoning measures to provide more scientific reference decisions and technical support for the implementation of refined cultivated land management in Henan Province. </p>
Data from: Trait hierarchies are stronger than trait dissimilarities in structuring spatial co-occurrence patterns of common tree species in a subtropical forest
<p>1. The dissimilarity and hierarchy of trait values that characterize niche and fitness differences, respectively, have been increasingly applied to infer mechanisms driving community assembly and to explain species co-occurrence patterns. Here, we predict that limiting similarity should result in the spatial segregation of functionally similar species, while functionally similar species will be more likely to co-occur either due to environmental filtering or competitive exclusion of inferior competitors (hereafter hierarchical competition).</p> <p>2. We used a fully mapped 50-ha subtropical forest plot in southern China to explore how pairwise spatial associations between saplings and between adult trees were influenced by trait dissimilarity and hierarchy in order to gain insight into assembly mechanisms. We assessed pairwise spatial associations using two summary statistics of spatial point patterns at different spatial scales and compared the effects of trait dissimilarity and trait hierarchy of different functional traits on the interspecific spatial associations. These comparisons allow us to disentangle the effects of limiting similarity, environmental filtering and hierarchical competition on species co-occurrence.</p> <p>3. We found that trait dissimilarity was generally negatively related with interspecific spatial associations for both saplings and adult trees across spatial scales, meaning that species with similar trait values were more likely to co-occur and thus supporting environmental filtering or hierarchical competition. We further found that trait hierarchy outweighed trait dissimilarity in structuring pairwise spatial associations, suggesting that hierarchical competition played a more important role in structuring our forest community than environmental filtering across life stages.</p> <p>4. This study employed a novel method, by offering the integration of pairwise spatial association and trait dissimilarity as well as trait hierarchy, to disentangle the relative importance of multiple assembly mechanisms in structuring co-occurrence patterns, especially the mechanisms of environmental filtering and hierarchical competition, which lead to indistinguishable co-occurrence patterns. This study also reinforced the importance of trait hierarchy rather than trait dissimilarity in driving neighborhood competition.</p>
Fig. 5 in Spatial Patterns Of Bird Communities Of The Lower Dnieper Sands During The Breeding Season: Differentiation Factors
Fig. 5. The bird abundance ratio in the separate groups of samples.
Using deep convolutional neural networks to forecast spatial patterns of Amazonian deforestation: supporting data and outputs
<p class="MsoNormal"><strong>1. </strong>Tropical forests are subject to diverse deforestation pressures while their conservation is essential to achieve global climate goals. Predicting the location of deforestation is challenging due to the complexity of the natural and human systems involved but accurate and timely forecasts could enable effective planning and on-the-ground enforcement practices to curb deforestation rates. New computer vision technologies based on deep learning can be applied to the increasing volume of Earth observation data to generate novel insights and make predictions with unprecedented accuracy.</p> <p class="MsoNormal"><strong>2. </strong>Here, we demonstrate the ability of deep convolutional neural networks (CNNs) to learn spatiotemporal patterns of deforestation from a limited set of freely available global data layers, including multispectral satellite imagery, the Hansen maps of annual forest change (2001-2020) and the ALOS PALSAR digital surface model, to forecast deforestation (2021). We designed four model architectures, based on 2D CNNs, 3D CNNs, and Convolutional Long Short-Term Memory (ConvLSTM) Recurrent Neural Networks (RNNs), to produce spatial maps that indicate the risk to each forested pixel (~30 m) in the landscape of becoming deforested within the next year. They were trained and tested on data from two ~80,000 km<sup>2</sup> tropical forest regions in the Southern Peruvian Amazon.</p> <p class="MsoNormal"><strong>3.</strong><strong> </strong><span>The networks could predict the location of future forest loss to a high degree of accuracy (F</span><sub>1 </sub><span>= 0.58-0.71). Our best performing model (3D CNN) had the highest pixel-wise accuracy (F</span><sub>1 </sub><span>= 0.71) when validated on 2020 forest loss (2014-2019 training). Visual interpretation of the mapped forecasts indicated that the network could automatically discern the drivers of forest loss from the input data. For example, pixels around new access routes (e.g. roads) were assigned high risk whereas this was not the case for recent, concentrated natural loss events (e.g. remote landslides).</span></p> <p class="MsoNormal"><strong>4.</strong><strong> </strong>CNNs can harness limited time-series data to predict near-future deforestation patterns, an important step in harnessing the growing volume of satellite remote sensing data to curb global deforestation. The modelling framework can be readily applied to any tropical forest location and used by governments and conservation organisations to prevent deforestation and plan protected areas.</p>
Spatial phylogenetic and phenotypic patterns reveal ontogenetic shifts in ecological processes of plant community assembly
The analysis of spatial phylogenetic and phenotypic structure of plant communities provides insight into the underlying processes and interactions governing their assembly, and how these may change during plant ontogeny. We used point pattern analysis to find out if saplings and adult plants are surrounded by phylogenetically and phenotypically more similar or dissimilar neighbours than expected by chance, and whether these associations change from the sapling to the adult stage. To this end, we combined information on the phylogenetic structure and eight phenotypic traits of 15 woody plant species in two Mediterranean mixed forests of southeastern Spain. At the community level, we found that the sapling bank at both sites did not show phylogenetic or phenotypic spatial patterns, but adults showed phylogenetic clustering (i.e., heterospecific neighbours were more similar than expected). At the species level, we found frequently repulsive patterns in the sapling bank of less abundant species (i.e., heterospecific sapling or adult neighbours were more dissimilar than expected) in both, phylogenetic and phenotypic analyses. For the adult stage, we found phylogenetic attraction (i.e., more similar neighbours) in just one species and phenotypic clustering in four species. The processes driving the assembly of the communities of saplings and adults leave detectable signals in the spatial phylogenetic and phenotypic structure of our two forest communities. Our findings reinforce the existence of ontogenetic shifts in the mechanisms involved in plant community assembly. Facilitation between phylogenetically distant and phenotypically divergent species favours the recruitment of less abundant species. However, processes acting later in the ontogeny ameliorate the competition between close relatives and determine the spatial structure of adult plants. Nevertheless, the role of phenotype in shaping adult-adult interactions was context- and trait-dependent. The use of spatial point pattern analysis allowed a nuanced interpretation of the phylogenetic and phenotypic structures of the plant community.
Spatial patterning of Artemisia tridentata neighborhoods and relative crowding
<p>Plants reflect resource use in their spatial patterning. Competition for limited resources—such as available soil water in a dryland ecosystem—drives establishment, growth, and mortality, resulting in shifts of spatial arrangement over time. We characterized the spatial patterning of two big sagebrush (<em>Artemisia tridentata</em> subspecies <em>wyomingensis</em>) communities in the upper Green River Basin of Wyoming, USA. We mapped big sagebrush canopies in two, 100-square meter sites and calculated plant neighborhoods as the area closer to a target plant than to any other plant. We assumed that neighborhoods were areas in which the target plant dominates resource use. We found that plant neighborhoods had strong, positive correlations with plant size, indicating that larger neighborhoods may access more belowground resources. We also found that the relationships between experienced crowding, i.e. Crowding Index (CI) by an average neighbor, and neighborhood size, were consistently negative regardless of calculation method. We also found that the residuals of a regression of target plant biomass and neighborhood area were strongly related to the CI calculated via all methods. This means that plants with smaller neighborhoods than expected also experience the greatest crowding by an average neighbor. These results are consistent with negative density dependence and show that greater static crowding predicts smaller neighborhoods in two, undisturbed, intermediate-successional big sagebrush communities. In the future, similar studies of spatial patterning that include interspecific plant-plant interactions will be useful for understanding the relationship between spatial patterning and negative density dependence.</p>
Establishment of mountain birch (Betula pubescens ssp. tortuosa) on a glacial outwash plain: spatial patterns and decadal processes
<p><span>Most of the Earth's surface has now been modified by humans. In many countries, natural and semi-natural ecosystems mostly occur as islands, isolated by land converted to agriculture and a variety of other land-uses. In this fragmented state, long-distance dispersal may be the only option for species to adapt their ranges in response to changing climate. The order of arrival of species may leave a lasting imprint on community assembly. Although mostly studied at and above the species level, such priority effects also apply at the intraspecific level. We suggest that this may be particularly important in subarctic and arctic ecosystems. </span>Mountain birch (Betula pubescens ssp. tortuosa) is characterised by great intraspecific variation. We explored spatio-temporal patterns of the first two mountain birch generations on a homogeneous, early successional glacial outwash plain in SE Iceland that was the recipient of spatially extensive long-distance dispersal ca. 30 years ago. We evaluated the decadal progress of the young population by remeasuring in 2018, tree density and growth form, plant size, and reproductive effort on 30 transects (150 m2) established in 2008 at four sites on the plain and two adjacent sites ca. 10 km away. All measured variables showed positive increases, but contrary to our predictions of converging dynamics among sites, they had significantly diverged. Thus, two of the sites (only 500 m apart) could not be distinguished in 2008 but by 2018, one of them had much faster growth rates than the other, a higher growth form index reflecting more upright tree stature, greater reproductive effort, and much greater second-generation seedling recruitment. We discuss two hypotheses that may explain the diverging dynamics, site-scale environmental heterogeneity and legacies of intraspecific priority effects. </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.