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1

Inglis, D. W. F., and T. W. Choularton. "Fine scale spatial variations in wet deposition." Atmospheric Research 55, no. 2 (October 2000): 139–57. http://dx.doi.org/10.1016/s0169-8095(00)00062-4.

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2

Plue, Jan, Geertrui Goyens, Marc Van Meirvenne, Kris Verheyen, and Martin Hermy. "Small-scale seed-bank patterns in a forest soil." Seed Science Research 20, no. 1 (November 2, 2009): 13–22. http://dx.doi.org/10.1017/s0960258509990201.

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AbstractThe forest seed bank has been demonstrated to vary spatially at scales from 2 to 10 m. To our knowledge, the fine-scale spatial structure, i.e. < 2 m, has not been studied before. This study aims to make a thorough investigation of fine-scale spatial structure. Soil samples (128) were collected from each of five 2.1 m × 2.1 m plots, using a combined systematic (64) and random design (64). This allowed investigation of the fine-scale spatial structure of individual species–plot combinations using indicator-variograms. Our results indicated that over half of all species recorded in a particular plot were spatially structured. Remarkably, the presence of spatial structure seemed independent of species frequency. Visualization of the spatial structure showed an irregular spatial pattern, i.e. seed clusters that were randomly distributed in space. Spatial dependence occurred over small distances, possibly suggesting that a significant proportion of seeds was deposited near the mother plant. We conclude by presenting the relevance and implications of small-scale spatial seed-bank patterning for seed-bank sampling.
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DICK, CHRISTOPHER W. "New interpretations of fine-scale spatial genetic structure." Molecular Ecology 17, no. 8 (March 19, 2008): 1873–74. http://dx.doi.org/10.1111/j.1365-294x.2008.03728.x.

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4

Brunett, B. A., J. M. Van Scyoc, N. R. Hilton, J. C. Lund, R. B. James, and T. E. Schlesinger. "Fine-scale spatial response of CdZnTe radiation detectors." IEEE Transactions on Nuclear Science 46, no. 3 (June 1999): 237–42. http://dx.doi.org/10.1109/23.775521.

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Hulleman, J., and A. H. J. Oomes. "Spatial Causality in Bilateral Symmetry Detection." Perception 26, no. 1_suppl (August 1997): 181. http://dx.doi.org/10.1068/v970179.

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We studied the influence of spatial scale on the detection of vertical and horizontal bilateral symmetry. The causality principle in scale - space theory states that increasing the spatial scale in a representation can only result in a decrease of structure. Consequently, a pattern can be random on the fine scale and symmetric on the coarse scale, never the reverse. Stimuli were bilaterally symmetric or random patterns, black-and-white on a grey background, with a circular aperture. The minimal scale was systematically varied and stimuli ranged from conventional noise patterns, through Dalmatian texture, to cow-like patterns. Observers had to judge whether a briefly presented pattern was ‘symmetric’ or ‘random’. Symmetric patterns resulted in a high accuracy (95%) with no influence of scale, and reaction times with a small linear decrease for increasing scale. Random patterns yielded an accuracy increasing from 70% at the smallest scale to 95% at the middle scales. Reaction times showed a similar pattern: largest at the smallest scales and decreasing to values equal to the symmetric condition at the middle scales. Results were similar for vertical and horizontal bilateral symmetry, though the effect for small scales in the random condition was more pronounced in the horizontal case. We conclude that bilateral symmetry is processed at multiple scales with coarse structures available slightly earlier than fine ones. The dramatic decrease of performance for fine-scale patterns is due to the causality effect; random patterns are judged as symmetric when the smallest scale information is not (yet) available.
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Carter, Neil H., Binoj K. Shrestha, Jhamak B. Karki, Narendra Man Babu Pradhan, and Jianguo Liu. "Coexistence between wildlife and humans at fine spatial scales." Proceedings of the National Academy of Sciences 109, no. 38 (September 4, 2012): 15360–65. http://dx.doi.org/10.1073/pnas.1210490109.

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Many wildlife species face imminent extinction because of human impacts, and therefore, a prevailing belief is that some wildlife species, particularly large carnivores and ungulates, cannot coexist with people at fine spatial scales (i.e., cannot regularly use the exact same point locations). This belief provides rationale for various conservation programs, such as resettling human communities outside protected areas. However, quantitative information on the capacity and mechanisms for wildlife to coexist with humans at fine spatial scales is scarce. Such information is vital, because the world is becoming increasingly crowded. Here, we provide empirical information about the capacity and mechanisms for tigers (a globally endangered species) to coexist with humans at fine spatial scales inside and outside Nepal’s Chitwan National Park, a flagship protected area for imperiled wildlife. Information obtained from field cameras in 2010 and 2011 indicated that human presence (i.e., people on foot and vehicles) was ubiquitous and abundant throughout the study site; however, tiger density was also high. Surprisingly, even at a fine spatial scale (i.e., camera locations), tigers spatially overlapped with people on foot and vehicles in both years. However, in both years, tigers offset their temporal activity patterns to be much less active during the day when human activity peaked. In addition to temporal displacement, tiger–human coexistence was likely enhanced by abundant tiger prey and low levels of tiger poaching. Incorporating fine-scale spatial and temporal activity patterns into conservation plans can help address a major global challenge—meeting human needs while sustaining wildlife.
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Pinel-Alloul, Bernadette, and Didier Pont. "Spatial distribution patterns in freshwater macrozooplankton: variation with scale." Canadian Journal of Zoology 69, no. 6 (June 1, 1991): 1557–70. http://dx.doi.org/10.1139/z91-219.

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The spatial heterogeneity of four macrozooplankton species (Skistodiaptomus oregonensis, Mesocyclops edax, Diaphanosoma brachyurum, and Daphnia sp.) was investigated over different scales, (fine and coarse scales: 2–40 m; lake-size scale: 10–380 m) in a small Canadian Shield lake. Values for the log s2: log [Formula: see text] relationships were established for the different scales and compared. Spatial analysis methods (space-constrained clustering analysis, spatial autocorrelation, and variogram modelling) were used for describing the surface distribution patterns observed on the whole-lake transect. The study demonstrated that spatial heterogeneity occurs on both the fine and coarse scales. Maximal spatial heterogeneity was observed on the vertical axis (depth) rather than on the horizontal axis. Macrozooplankton patchiness scales in Lake Cromwell correspond to whole-lake scale patterns for M. edax and D. brachyurum, and to fine-scale patterns for S. oregonensis and Daphnia spp. Our results confirm the general trend of interspecific variations in patch sizes of freshwater macrozooplankton. Distribution of the invertebrate predators Chaoborus spp. is inversely related to the large-scale gradient of D. brachyurum. Multiple regression analysis showed that several physical (water temperature, oxygen, wind direction) and biological (chlorophyll a) factors, in addition to mean population abundance, were correlated with macrozooplankton heterogeneity on the fine scale.
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8

Ciavarella, Constanze, and Neil M. Ferguson. "Deriving fine-scale models of human mobility from aggregated origin-destination flow data." PLOS Computational Biology 17, no. 2 (February 11, 2021): e1008588. http://dx.doi.org/10.1371/journal.pcbi.1008588.

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The spatial dynamics of epidemics are fundamentally affected by patterns of human mobility. Mobile phone call detail records (CDRs) are a rich source of mobility data, and allow semi-mechanistic models of movement to be parameterised even for resource-poor settings. While the gravity model typically reproduces human movement reasonably well at the administrative level spatial scale, past studies suggest that parameter estimates vary with the level of spatial discretisation at which models are fitted. Given that privacy concerns usually preclude public release of very fine-scale movement data, such variation would be problematic for individual-based simulations of epidemic spread parametrised at a fine spatial scale. We therefore present new methods to fit fine-scale mathematical mobility models (here we implement variants of the gravity and radiation models) to spatially aggregated movement data and investigate how model parameter estimates vary with spatial resolution. We use gridded population data at 1km resolution to derive population counts at different spatial scales (down to ∼ 5km grids) and implement mobility models at each scale. Parameters are estimated from administrative-level flow data between overnight locations in Kenya and Namibia derived from CDRs: where the model spatial resolution exceeds that of the mobility data, we compare the flow data between a particular origin and destination with the sum of all model flows between cells that lie within those particular origin and destination administrative units. Clear evidence of over-dispersion supports the use of negative binomial instead of Poisson likelihood for count data with high values. Radiation models use fewer parameters than the gravity model and better predict trips between overnight locations for both considered countries. Results show that estimates for some parameters change between countries and with spatial resolution and highlight how imperfect flow data and spatial population distribution can influence model fit.
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9

Ji, Q., S. Barr, P. James, and D. Fairbairn. "A GEOSPATIAL ANALYSIS FRAMEWORK FOR FINE SCALE URBAN INFRASTRUCTURE NETWORKS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4 (September 19, 2018): 291–96. http://dx.doi.org/10.5194/isprs-archives-xlii-4-291-2018.

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<p><strong>Abstract.</strong> Understanding the spatial connectivity of urban infrastructure networks that connect assets to buildings is important for the fine-scale spatial analysis and modelling of the resource flows within cities. However, rarely are spatially explicit representations of infrastructure networks available for such analysis. Further, an appropriate database system is the core of development of an infrastructure assets information and management platform, capable of handling the wide range of data for infrastructure system modelling and analysis. In this paper, we develop a geospatial simulation and analysis framework, which is capable of generating fine-scale urban infrastructure networks and storing the network instances in a hybrid database system for further modelling and analysis needs. We demonstrate the use of this platform by simulating the entire-city electricity distribution network for the city of Newcastle upon Tyne. Validation of the resulting network is performed using the network layout diagram from the local power company. The heuristically derived network was found to have a 91<span class="thinspace"></span>% spatial accuracy.</p>
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10

E., Santi, Tarantino C., Amici V., Bacaro G., Blonda P., Borselli L., Rossi M., Tozzi S., and Torri D. "Fine-scale spatial distribution of biomass using satellite images." Journal of Ecology and The Natural Environment 6, no. 2 (February 28, 2014): 75–86. http://dx.doi.org/10.5897/jene2013.0416.

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11

Paturel, J. E., and B. Chocat. "Analysis of the Rain Phenomenon at Fine Spatial Scale." Water Science and Technology 29, no. 1-2 (January 1, 1994): 31–37. http://dx.doi.org/10.2166/wst.1994.0648.

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Since 1984, the Urban Community of Lyon (CO.UR.LY.) has been setting up a network of rain gauges with a density of about 1 station per 20 km. This network is integrated in the French system of Experimental and Representative Basins. To get a better knowledge of the spatial distribution of the rainfall, a study was based on the establishment of I.D.F. relationships for each of these measuring stations. Since the study period extended only over 5 to 6 years, only return periods of 1 and 2 years were taken into account. The results show a high statistical heterogeneity of rain gauging data. These discrepancies may be due to sampling errors, to systematic measuring errors, to an excessively short observation period or to real spatial differences in rainfall. Each one of the causes of error was studied, and these 4 points all seem to play a more or less significant role in the differences observed between the stations. Thus there may be a spatial heterogeneity of the rainfall over the area of the CO.UR.LY. If confirmed, this observation may have very important consequences and may question risk assessment in urban hydrology.
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12

Nituch, Larissa A., James A. Schaefer, and Christine D. Maxwell. "Fine-Scale Spatial Organization Reflects Genetic Structure in Sheep." Ethology 114, no. 7 (July 2008): 711–17. http://dx.doi.org/10.1111/j.1439-0310.2008.01522.x.

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13

Smith, Claire L., A. Webb, G. J. Levermore, S. J. Lindley, and K. Beswick. "Fine-scale spatial temperature patterns across a UK conurbation." Climatic Change 109, no. 3-4 (February 8, 2011): 269–86. http://dx.doi.org/10.1007/s10584-011-0021-0.

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14

Zawierucha, Krzysztof, Jakub Buda, Diego Fontaneto, Roberto Ambrosini, Andrea Franzetti, Mariusz Wierzgoń, and Michał Bogdziewicz. "Fine-scale spatial heterogeneity of invertebrates within cryoconite holes." Aquatic Ecology 53, no. 2 (March 11, 2019): 179–90. http://dx.doi.org/10.1007/s10452-019-09681-9.

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15

Kranstauber, Bart, Willem Bouten, Hidde Leijnse, Berend-Christiaan Wijers, Liesbeth Verlinden, Judy Shamoun-Baranes, and Adriaan M. Dokter. "High-Resolution Spatial Distribution of Bird Movements Estimated from a Weather Radar Network." Remote Sensing 12, no. 4 (February 14, 2020): 635. http://dx.doi.org/10.3390/rs12040635.

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Weather radars provide detailed information on aerial movements of organisms. However, interpreting fine-scale radar imagery remains challenging because of changes in aerial sampling altitude with distance from the radar. Fine-scale radar imagery has primarily been used to assess mass exodus at sunset to study stopover habitat associations. Here, we present a method that enables a more intuitive integration of information across elevation scans projected in a two-dimensional spatial image of fine-scale radar reflectivity. We applied this method on nights of intense bird migration to demonstrate how the spatial distribution of migrants can be explored at finer spatial scales and across multiple radars during the higher flying en-route phase of migration. The resulting reflectivity maps enable explorative analysis of factors influencing their regional and fine-scale distribution. We illustrate the method’s application by generating time-series of composites of up to 20 radars, achieving a nearly complete spatial coverage of a large part of Northwest Europe. These visualizations are highly useful in interpreting regional-scale migration patterns and provide detailed information on bird movements in the landscape and aerial environment.
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16

Neatrour, Matthew A., Robert H. Jones, and Stephen W. Golladay. "Correlations between soil nutrient availability and fine-root biomass at two spatial scales in forested wetlands with contrasting hydrological regimes." Canadian Journal of Forest Research 35, no. 12 (December 1, 2005): 2934–41. http://dx.doi.org/10.1139/x05-217.

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We investigated the relationship between soil nutrients and fine-root biomass at broad (among ecosystem types) and fine (within a 20 m × 20 m plot) spatial scales in forested wetlands of the southeastern United States. We selected three replicates each of high-fertility floodplain swamps, low-fertility depressional swamps, and intermediate-fertility river swamp sloughs and measured soil nutrient availability (NO3-N, NH4-N, and PO4-P) and fine-root biomass. At one replicate of each wetland type, a dense network of sampling points was used to measure variability (variance and coefficient of variation) of soil nutrients and fine-root biomass. At the broad scale, fine-root biomass was lower in floodplain swamps than in either river swamp sloughs or depressional swamps. Also, multiple linear regression and Spearman's rank correlations indicated a negative relationship between soil nutrient availability and fine-root biomass. Fine-scale correlates between soil nutrient availability and fine-root biomass were generally weak. Fine-scale variability of NO3-N and NH4-N was greatest in the floodplain swamps, but nutrients were not spatially patchy at any of the sampled sites. We conclude that soil nutrient availability may control fine-root biomass at the broad scale, but it is unclear if the same is true at fine spatial scales.
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17

Doligez, Agnès, Claire Baril, and Hélène I. Joly. "Fine-Scale Spatial Genetic Structure with Nonuniform Distribution of Individuals." Genetics 148, no. 2 (February 1, 1998): 905–19. http://dx.doi.org/10.1093/genetics/148.2.905.

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Abstract This paper presents the first theoretical study of spatial genetic structure within nonuniformly distributed continuous plant populations. A novel individual-based model of isolation by distance was constructed to simulate genetic evolution within such populations. We found larger values of spatial genetic autocorrelations in highly clumped populations than in uniformly distributed populations. Most of this difference was caused by differences in mean dispersal distances, but aggregation probably also produced a slight increase in spatial genetic structure. Using an appropriate level of approximation of the continuous distribution of individuals in space, we assessed the potential effects of density, seed and pollen dispersal, generation overlapping, and overdominance selection at an independent locus, on fine-scale genetic structure, by varying them separately in a few particular cases with extreme clumping. When selfing was allowed, all these input variables influenced both aggregation and spatial genetic structure. Most variations in spatial genetic structure were closely linked to variations in clumping and/or local density. When selfing was not allowed, spatial genetic structure was lower in most cases.
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18

Hintzen, Niels T., Geert Aarts, and Adriaan D. Rijnsdorp. "Persistence in the fine-scale distribution and spatial aggregation of fishing." ICES Journal of Marine Science 76, no. 4 (December 6, 2018): 1072–82. http://dx.doi.org/10.1093/icesjms/fsy144.

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Abstract High-resolution vessel monitoring (VMS) data have led to detailed estimates of the distribution of fishing in both time and space. While several studies have documented large-scale changes in fishing distribution, fine-scale patterns are still poorly documented, despite VMS data allowing for such analyses. We apply a methodology that can explain and predict effort allocation at fine spatial scales; a scale relevant to assess impact on the benthic ecosystem. This study uses VMS data to quantify the stability of fishing grounds (i.e. aggregated fishing effort) at a microscale (tens of meters). The model links effort registered at a large scale (ICES rectangle; 1° longitude × 0.5° latitude, ˜3600 km2) to fine spatial trawling intensities at a local scale (i.e. scale matching gear width, here 24 m). For the first time in the literature, the method estimates the part of an ICES rectangle that is unfavourable or inaccessible for fisheries, which is shown to be highly stable over time and suggests higher proportions of inaccessible grounds for either extremely muddy or courser substrates. The study furthermore shows high stability in aggregation of fishing, where aggregation shows a positive relationship with depth heterogeneity and a negative relationship with year-on-year variability in fishing intensity.
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19

Yao, Demin. "Fine Scale Structure of the Local Lyapunov Exponent." Modern Physics Letters B 11, no. 16n17 (July 20, 1997): 707–12. http://dx.doi.org/10.1142/s0217984997000864.

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20

Jackson, Doug, Ash T. Zemenick, Brian Malloure, C. Alisha Quandt, and Timothy Y. James. "Fine-scale spatial genetic structure of a fungal parasite of coffee scale insects." Journal of Invertebrate Pathology 139 (September 2016): 34–41. http://dx.doi.org/10.1016/j.jip.2016.07.007.

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21

van den Berg, M. J., S. Vandenberghe, B. De Baets, and N. E. C. Verhoest. "Copula-based downscaling of spatial rainfall: a proof of concept." Hydrology and Earth System Sciences 15, no. 5 (May 11, 2011): 1445–57. http://dx.doi.org/10.5194/hess-15-1445-2011.

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Abstract. Fine-scale rainfall data is important for many hydrological applications. However, often the only data available is at a coarse scale. To bridge this gap in resolution, stochastic disaggregation methods can be used. Such methods generally assume that the distribution of the field is stationary, i.e. the distribution for the entire (fine-scale) field is the same as the distribution of a smaller region within the field. This assumption is generally incorrect and we provide a proof of concept of a method to estimate the distribution of a smaller region. In this method, a copula is used to construct a bivariate distribution describing the relation between the scales. This distribution is then used to estimate the distribution of the fine-scale rainfall within a single coarse-scale pixel, by conditioning on the coarse-scale rainfall depth.
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22

van den Berg, M. J., S. Vandenberghe, B. De Baets, and N. E. C. Verhoest. "Copula-based downscaling of spatial rainfall: a proof of concept." Hydrology and Earth System Sciences Discussions 8, no. 1 (January 13, 2011): 207–41. http://dx.doi.org/10.5194/hessd-8-207-2011.

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Abstract. Fine-scale rainfall data is important for many hydrological applications. However, often the only data available is at a coarse scale. To bridge this gap in resolution, stochastic disaggregation methods can be used. Such methods generally assume that the distribution of the field is stationary, i.e. the distribution for the entire (fine-scale) field is the same as the distribution of a smaller region within the field. This assumption is generally incorrect and we provide the proof of concept of a method to estimate the distribution of a smaller region. In this method, a copula is used to construct a bivariate distribution describing the relation between the scales. This distribution is then used to estimate the distribution of the fine-scale rainfall within a single coarse-scale pixel, by conditioning on the coarse-scale rainfall depth.
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23

Henry, L. A., J. Moreno Navas, and J. M. Roberts. "Multi-scale interactions between local hydrography, seabed topography, and community assembly on cold-water coral reefs." Biogeosciences Discussions 9, no. 12 (December 12, 2012): 17885–912. http://dx.doi.org/10.5194/bgd-9-17885-2012.

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Abstract. We investigated how the interactive effects of hydrography, topography and intrinsic community dynamics influence the assembly of species and functional traits across multiple spatial scales of a cold-water coral reef seascape. In a novel approach for these ecosystems, we use a spatially resolved complex three-dimensional flow model of hydrography to help explain assembly patterns. Forward selection of distance-based Moran's eigenvector mapping (dbMEM) variables identified two submodels of spatial scales at which communities are structured: broad-scale (across reef) and fine-scale (within reef). Canonical variance partitioning revealed broad-scale structures created mainly by variability in bathymetry and hydrography across reefs, which manifest as relatively narrow environmental niches for predators and scavenging detritivores. Fine-scale assembly was related more to processes that create spatially autocorrelated patches of fauna within a reef due to restricted dispersal in sessile fauna but social mating interactions and food supply in more mobile organisms. Our study implies that perturbations such as habitat fragmentation and altered hydrodynamic regimes have the potential to induce significant changes in the structure and function of cold-water coral reef ecosystems at spatial scales that span the entire seascape.
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Voytek, Bradley, Jason Samaha, Camarin E. Rolle, Zachery Greenberg, Navdeep Gill, Shai Porat, Tahim Kader, Sabahat Rahman, Rick Malzyner, and Adam Gazzaley. "Preparatory Encoding of the Fine Scale of Human Spatial Attention." Journal of Cognitive Neuroscience 29, no. 7 (July 2017): 1302–10. http://dx.doi.org/10.1162/jocn_a_01124.

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Our attentional focus is constantly shifting: In one moment, our attention may be intently concentrated on a specific spot, whereas in another moment we might spread our attention more broadly. Although much is known about the mechanisms by which we shift our visual attention from place to place, relatively little is known about how we shift the aperture of attention from more narrowly to more broadly focused. Here we introduce a novel attentional distribution task to examine the neural mechanisms underlying this process. In this task, participants are presented with an informative cue that indicates the location of an upcoming target. This cue can be perfectly predictive of the exact target location, or it can indicate—with varying degrees of certainty—approximately where the target might appear. This cue is followed by a preparatory period in which there is nothing on the screen except a central fixation cross. Using scalp EEG, we examined neural activity during this preparatory period. We find that, with decreasing certainty regarding the precise location of the impending target, participant RTs increased whereas target identification accuracy decreased. Additionally, the multivariate pattern of preparatory period visual cortical alpha (8–12 Hz) activity encoded attentional distribution. This alpha encoding was predictive of behavioral accuracy and RT nearly 1 sec later. These results offer insight into the neural mechanisms underlying how we use information to guide our attentional distribution and how that influences behavior.
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Shimatani, Kenichiro. "Point Processes for Fine-Scale Spatial Genetics and Molecular Ecology." Biometrical Journal 44, no. 3 (April 2002): 325. http://dx.doi.org/10.1002/1521-4036(200204)44:3<325::aid-bimj325>3.0.co;2-b.

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26

Meier, P. T. "Fine spatial scale phenotypic divergence in wood frogs (Lithobates sylvaticus)." Canadian Journal of Zoology 85, no. 8 (August 2007): 873–82. http://dx.doi.org/10.1139/z07-071.

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I studied local divergence in growth, a trait previously shown to be both phenotypically plastic and heritable, among wood frog (Lithobates sylvaticus (LeConte, 1825)) tadpoles inhabiting four ponds within a continuous woodland. Mark–recapture results revealed very low levels of migration among ponds as close as 35 m and no more than 185 m apart. Common garden experiments conducted at two temperatures revealed consistent year-to-year patterns of phenotypic divergence in tadpole growth performance among the four pond populations. The divergence in growth performance was conserved when controlling for parental effects via half-sibling experiments. Results of cross-transplant experiments suggest that the divergence in tadpole growth reflected either genetic drift or adaptation to local pond conditions. Taken together, the results suggest that divergence in growth performance among the tadpoles from the four ponds is the result of selection or genetic drift reinforced by low levels of gene flow among pond populations.
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Thompson, Patrick L., Forest Isbell, Michel Loreau, Mary I. O'Connor, and Andrew Gonzalez. "The strength of the biodiversity–ecosystem function relationship depends on spatial scale." Proceedings of the Royal Society B: Biological Sciences 285, no. 1880 (June 6, 2018): 20180038. http://dx.doi.org/10.1098/rspb.2018.0038.

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Our understanding of the relationship between biodiversity and ecosystem functioning (BEF) applies mainly to fine spatial scales. New research is required if we are to extend this knowledge to broader spatial scales that are relevant for conservation decisions. Here, we use simulations to examine conditions that generate scale dependence of the BEF relationship. We study scale by assessing how the BEF relationship (slope and R 2 ) changes when habitat patches are spatially aggregated. We find three ways for the BEF relationship to be scale-dependent: (i) variation among local patches in local (α) diversity, (ii) spatial variation in the local BEF relationship and (iii) incomplete compositional turnover in species composition among patches. The first two cause the slope of the BEF relationship to increase moderately with spatial scale, reflecting nonlinear averaging of spatial variation in diversity or the BEF relationship. The third mechanism results in much stronger scale dependence, with the BEF relationship increasing in the rising portion of the species area relationship, but then decreasing as it saturates. An analysis of data from the Cedar Creek grassland BEF experiment revealed a positive but saturating slope of the relationship with scale. Overall, our findings suggest that the BEF relationship is likely to be scale dependent.
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Cancellare, Imogene A., Elizabeth M. Kierepka, Jan Janecka, Byron Weckworth, Richard T. Kazmaier, and Rocky Ward. "Multiscale patterns of isolation by ecology and fine-scale population structure in Texas bobcats." PeerJ 9 (June 3, 2021): e11498. http://dx.doi.org/10.7717/peerj.11498.

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Patterns of spatial genetic variation can be generated by a variety of ecological processes, including individual preferences based on habitat. These ecological processes act at multiple spatial and temporal scales, generating scale-dependent effects on gene flow. In this study, we focused on bobcats (Lynx rufus), a highly mobile, generalist felid that exhibits ecological and behavioral plasticity, high abundance, and broad connectivity across much of their range. However, bobcats also show genetic differentiation along habitat breaks, a pattern typically observed in cases of isolation-by-ecology (IBE). The IBE observed in bobcats is hypothesized to occur due to habitat-biased dispersal, but it is unknown if this occurs at other habitat breaks across their range or at what spatial scale IBE becomes most apparent. Thus, we used a multiscale approach to examine isolation by ecology (IBE) patterns in bobcats (Lynx rufus) at both fine and broad spatial scales in western Texas. We genotyped 102 individuals at nine microsatellite loci and used partial redundancy analysis (pRDA) to test if a suite of landscape variables influenced genetic variation in bobcats. Bobcats exhibited a latitudinal cline in population structure with a spatial signature of male-biased dispersal, and no clear barriers to gene flow. Our pRDA tests revealed high genetic similarity in similar habitats, and results differed by spatial scale. At the fine spatial scale, herbaceous rangeland was an important influence on gene flow whereas mixed rangeland and agriculture were significant at the broad spatial scale. Taken together, our results suggests that complex interactions between spatial-use behavior and landscape heterogeneity can create non-random gene flow in highly mobile species like bobcats. Furthermore, our results add to the growing body of data highlighting the importance of multiscale study designs when assessing spatial genetic structure.
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29

Zhukov, Alexander, and Galina Gadorozhnaya. "Spatial Heterogeneity of Mechanical Impedance of Atypical Chernozem: The Ecological Approach." Ekológia (Bratislava) 35, no. 3 (September 1, 2016): 263–78. http://dx.doi.org/10.1515/eko-2016-0021.

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AbstractIn this research paper, the spatial heterogeneity of mechanical impedance of a typical chernozem was investigated. The distance between experimental points in the mechanical impedance space was explained by means of multidimensional scaling. Spearman’s rank correlation coefficients between dissimilarity indices and gradient separation with different data transformation methods revealed that the use of log-transformed data and Horn-Morisita distance was the most appropriate approach to reflect the relationship between the mechanical impedance of soil and ecological factors. A three dimensional variant of multidimensional scaling procedure was selected as the most appropriate decision. Environmental factors were estimated with the use of phytoindicator scales. Broad, medium and fine-scale components of spatial variation of mechanical impedance of soil were extracted using the principal coordinates of neighbour matrices method (PCNM). In the extracted dimensions, statistically significant phytoindicator scales were found to describe variability from 8 to 33%. Dimension 1 correlated with a thermal climate indicator value, a hygromorphs index, an abundance of steppe species and meadow species. Dimension 2 correlated with a continental climate indicator value, carbonate content in the soil and the soil trophicity index (capacity of the soil for plant nutrition). Dimension 3 correlated with acidity, humidity and cryoclimate indicator values. Variation partitioning results revealed that environmental factors and spatial variables explained 47.8% of the total variation of the dimensions. Purely environmental component explained 18.2% of total variation. The spatial component and spatially structured environmental fractions explained 43.6%. The broad-scale spatial component explained 26.4% of dimensional variation, medium-scale – 6.7% and fine-scale – 5.7%. As a result of regression analysis, the broad-scale spatially structured environmental fractions were found to be connected with variability of moisture and thermal climate indicator values. The medium-scale component was revealed to be connected with variability of moisture, thermal climate, total salt regime and aeration of soil indicator value. The fine-scale component was connected with carbonate content in the soil, acidity and humidity indicator values.
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30

Fisher, Martin. "Fine-scale distributions of tropical animal mounds: a revised statistical analysis." Journal of Tropical Ecology 9, no. 3 (August 1993): 339–48. http://dx.doi.org/10.1017/s0266467400007392.

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ABSTRACTDescriptions of the fine scale distribution of organisms have frequently been used to investigate various ecological phenomena. Unfortunately, the most widely used spatial analysis techniques are based on single index statistics, which convey only minimal information about the biological processes underlying the studied distributions. Such statistics cannot detect changes in pattern over different scales, and cannot identify some types of distribution. Additionally, both the use of such statistics on the distribution of individuals which have a non-negligible size, and the frequent failure to use an edge correction for points close to the boundaries of a sampled area, have led to the over-reporting of ‘spaced out’ (‘regular’) distributions. Using two spatial distributions recently analysed with a single index statistic (termite mounds, and earthmounds created by termites), I illustrate the benefits gained from using the spatial functions K(t), G(y) and F(x) to analyse both ‘point events’ and events which have a non-negligible size. These functions are considerably more informative about the nature of a spatial pattern and offer wide scope for the fitting of spatial models to biological distributions.
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31

Findlay, John M., and Iain D. Gilchrist. "Spatial Scale and Saccade Programming." Perception 26, no. 9 (September 1997): 1159–67. http://dx.doi.org/10.1068/p261159.

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The global effect in eye orienting occurs when saccades land at the ‘centre of gravity’ of a target stimulus configuration. Short-latency saccades are particularly prone to this effect whereas longer-latency saccades may show more influence of fine detail. Alternative explanations of these effects are considered and data are presented from an experiment in which the influence of different stimulus features on the global effect in a search task was examined. The effect shows a substantially different time course for target-distractor combinations differing in contrast polarity (black vs white) than for combinations differing in shape (circle vs square). It is concluded that the global effect cannot be explained either as a high-level strategic effect or as an effect of automatic fast processing of low-spatial-frequency information in early sensory channels. Instead it is suggested that the visual-spatial-integration characteristic of the global effect is an integral and unavoidable part of the process of selection of saccadic response.
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32

Gorospe, Kelvin D., and Stephen A. Karl. "Small-Scale Spatial Analysis ofIn SituSea Temperature throughout a Single Coral Patch Reef." Journal of Marine Biology 2011 (2011): 1–12. http://dx.doi.org/10.1155/2011/719580.

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Thermal stress can cause geographically widespread bleaching events, during which corals become decoupled from their symbiotic algae. Bleaching, however, also can occur on smaller, spatially patchy scales, with corals on the same reef exhibiting varying bleaching responses. Thus, to investigate fine spatial scale sea temperature variation, temperature loggers were deployed on a 4 m grid on a patch reef in Kāne'ohe Bay, Oahu, Hawai‘i to monitorin situ, benthic temperature every 50 minutes at 85 locations for two years. Temperature variation on the reef was characterized using several summary indices related to coral thermal stress. Results show that stable, biologically significant temperature variation indeed exists at small scales and that depth, relative water flow, and substrate cover and type were not significant drivers of this variation. Instead, finer spatial and temporal scale advection processes at the benthic boundary layer are likely responsible. The implications for coral ecology and conservation are discussed.
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Henry, L. A., J. Moreno Navas, and J. M. Roberts. "Multi-scale interactions between local hydrography, seabed topography, and community assembly on cold-water coral reefs." Biogeosciences 10, no. 4 (April 24, 2013): 2737–46. http://dx.doi.org/10.5194/bg-10-2737-2013.

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Abstract. We investigated how interactions between hydrography, topography and species ecology influence the assembly of species and functional traits across multiple spatial scales of a cold-water coral reef seascape. In a novel approach for these ecosystems, we used a spatially resolved complex three-dimensional flow model of hydrography to help explain assembly patterns. Forward-selection of distance-based Moran's eigenvector mapping (dbMEM) variables identified two submodels of spatial scales at which communities change: broad-scale (across reef) and fine-scale (within reef). Variance partitioning identified bathymetric and hydrographic gradients important in creating broad-scale assembly of species and traits. In contrast, fine-scale assembly was related more to processes that created spatially autocorrelated patches of fauna, such as philopatric recruitment in sessile fauna, and social interactions and food supply in scavenging detritivores and mobile predators. Our study shows how habitat modification of reef connectivity and hydrography by bottom fishing and renewable energy installations could alter the structure and function of an entire cold-water coral reef seascape.
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34

Griffin, Michael T., James Dean Edwards Jr., and Thomas R. Allen. "Coastal Impervious Cover and Watershed Scale." International Journal of Applied Geospatial Research 7, no. 1 (January 2016): 45–62. http://dx.doi.org/10.4018/ijagr.2016010104.

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Environmental planners seek techniques that will enable them to analyze impervious cover to develop sound management plans for coastal regions. The spatial scale in which impervious cover has traditionally been widely analyzed is mismatched to the fine-scale resolution needed for local environmental management. This study examines impervious cover in New Hanover County, North Carolina using LiDAR derived subwatersheds and United States Geological Survey (USGS) 14-digit hydrologic unit watersheds to evaluate potential scale-dependency of impervious cover estimates. Spatial analysis of impervious cover across multi-scale watersheds indicates that fine scale subwatersheds exhibit patterns not revealed with coarser watersheds. Spatial and cartographic analyses suggest that localized impervious development and its expansion in first-order drainages originating in coastal lagoon watersheds is more appropriately analyzed using fine-scale, LiDAR-derived watersheds. Results stress the importance of using scale in watershed management and hydrogeomorphic context to aid planners when making decisions involving impervious cover.
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35

Xu, Julie Y. "The Effect of Host’s Dispersal Ability on Fine-Scale Spatial Differentiation." IU Journal of Undergraduate Research 1, no. 1 (June 1, 2015): 38. http://dx.doi.org/10.14434/iujur.v1i1.13516.

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Gene flow of a parasite is commonly contingent upon its most motile host’s dispersal rate. High gene flow can reduce local differentiation and potentially the rate of adaptation to local hosts (Blasco-Costa, Waters, & Poulin, 2011; Louhi, Karvonen, Rellstab, & Jokela, 2010). We investigated fine-scale spatial differentiation in a parasitic trematode (Microphallus sp.), which alternates between two hosts: a relatively sedentary invertebrate, a freshwater snail (Potamopyrgus antipodarum), and a highly motile vertebrate, a duck (Hechinger, 2012). In 2014, adult snails were sampled from 13 different sites around a New Zealand lake to determine the distribution of infection. Juvenile snails were also collected from these sites for experimental manipulation. Finally, parasite eggs were collected by sampling duck feces from a northern and southern site on the lake. Juvenile snails from each site were exposed to parasites from either the northern or southern source. The infection status of field-collected adults and experimental juveniles was determined by dissection. Given the close proximity between sites and the duck host’s strong dispersal ability, we predicted low spatial variation in infectivity of the two parasite sources. The results, however, indicate significant spatial variation in both host resistance and parasite infectivity. Though infection rates across host sites were significantly correlated, the two sources differed significantly in their infectivity to hosts from different sites. This result suggests that the two parasite sources are adapted to infect different hosts, indicating genetic differentiation of the parasite. In addition, the frequency of infection and resistance of the freshwater snail differed significantly between sites within close proximity to one another. Detection of strong variation indicates that dispersal of the vertebrate host does not prevent fine-scale spatial differentiation in this host-parasite system. Further studies are needed to investigate the forces that maintain the extensive spatial variation in disease observed.
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36

Amend, Anthony, Sterling Keeley, and Matteo Garbelotto. "Forest age correlates with fine-scale spatial structure of Matsutake mycorrhizas." Mycological Research 113, no. 5 (May 2009): 541–51. http://dx.doi.org/10.1016/j.mycres.2009.01.005.

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37

Chomitz, Kenneth M., and Timothy S. Thomas. "Determinants of Land Use in Amazônia: A Fine‐Scale Spatial Analysis." American Journal of Agricultural Economics 85, no. 4 (November 2003): 1016–28. http://dx.doi.org/10.1111/1467-8276.00504.

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38

Barluenga, M., F. Austerlitz, J. A. Elzinga, S. Teixeira, J. Goudet, and G. Bernasconi. "Fine-scale spatial genetic structure and gene dispersal in Silene latifolia." Heredity 106, no. 1 (April 14, 2010): 13–24. http://dx.doi.org/10.1038/hdy.2010.38.

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39

OLSON, M. S., A. V. GRAF, and K. R. NILES. "Fine scale spatial structuring of sex and mitochondria in Silene vulgaris." Journal of Evolutionary Biology 19, no. 4 (July 2006): 1190–201. http://dx.doi.org/10.1111/j.1420-9101.2006.01103.x.

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40

Han, Dongrui, Xiaohuan Yang, Hongyan Cai, Xinliang Xu, Zhi Qiao, Chuanzhou Cheng, Nan Dong, Dong Huang, and Andi Liu. "Modelling spatial distribution of fine-scale populations based on residential properties." International Journal of Remote Sensing 40, no. 14 (February 17, 2019): 5287–300. http://dx.doi.org/10.1080/01431161.2019.1579387.

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41

HE, JIAN, XIAOYI LI, DANDAN GAO, PENG ZHU, ZHENGFENG WANG, ZHANGMING WANG, WANHUI YE, and HONGLIN CAO. "Topographic effects on fine-scale spatial genetic structure inCastanopsis chinensisHance (Fagaceae)." Plant Species Biology 28, no. 1 (March 27, 2012): 87–93. http://dx.doi.org/10.1111/j.1442-1984.2011.00365.x.

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42

Wang, Guiming, Wei Liu, Yanni Wang, Xinrong Wan, and Wenqin Zhong. "Restricted dispersal determines fine-scale spatial genetic structure of Mongolian gerbils." Current Zoology 63, no. 6 (July 14, 2017): 687–91. http://dx.doi.org/10.1093/cz/zox044.

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43

smith, jeff, Joan E. Strassmann, and David C. Queller. "Fine-scale spatial ecology drives kin selection relatedness among cooperating amoebae." Evolution 70, no. 4 (March 31, 2016): 848–59. http://dx.doi.org/10.1111/evo.12895.

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44

Xing, Yang, Peter Brimblecombe, and Zhi Ning. "Fine-scale spatial structure of air pollutant concentrations along bus routes." Science of The Total Environment 658 (March 2019): 1–7. http://dx.doi.org/10.1016/j.scitotenv.2018.12.001.

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45

NUSSEY, D. H., D. W. COLTMAN, T. COULSON, L. E. B. KRUUK, A. DONALD, S. J. MORRIS, T. H. CLUTTON-BROCK, and J. PEMBERTON. "Rapidly declining fine-scale spatial genetic structure in female red deer." Molecular Ecology 14, no. 11 (October 2005): 3395–405. http://dx.doi.org/10.1111/j.1365-294x.2005.02692.x.

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46

Smith, Steven E., Tulio Arredondo, Martín Aguiar, Elisabeth Huber-Sannwald, Angel Alpuche, Armando Aguado, Oscar A. Grageda, Kandres Halbrook, and Cecilia Bottini. "Fine-Scale Spatial Genetic Structure in Perennial Grasses in Three Environments." Rangeland Ecology & Management 62, no. 4 (July 2009): 356–63. http://dx.doi.org/10.2111/08-159.1.

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47

Crawford, Joanne C., Amy Dechen Quinn, David M. Williams, Brent A. Rudolph, Kim T. Scribner, and William F. Porter. "Fine-scale spatial genetic structure of deer in a suburban landscape." Journal of Wildlife Management 82, no. 3 (January 14, 2018): 596–607. http://dx.doi.org/10.1002/jwmg.21417.

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48

De Iorio, Maria, and Claudio J. Verzilli. "A spatial probit model for fine-scale mapping of disease genes." Genetic Epidemiology 31, no. 3 (April 2007): 252–60. http://dx.doi.org/10.1002/gepi.20206.

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49

Ray, J., S. A. McKenna, B. van Bloemen Waanders, and Y. M. Marzouk. "Bayesian reconstruction of binary media with unresolved fine-scale spatial structures." Advances in Water Resources 44 (August 2012): 1–19. http://dx.doi.org/10.1016/j.advwatres.2012.04.009.

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50

Kerckhoffs, Jules, Meng Wang, Kees Meliefste, Ebba Malmqvist, Paul Fischer, Nicole A. H. Janssen, Rob Beelen, and Gerard Hoek. "A national fine spatial scale land-use regression model for ozone." Environmental Research 140 (July 2015): 440–48. http://dx.doi.org/10.1016/j.envres.2015.04.014.

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