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1,445 results for “Distances”
Small mammals reduce distance-dependence and increase seed predation risk in tropical rainforest fragments
Seed predation and reduced predation risk with distance from conspecific trees are important influences on tree regeneration in tropical forests. Shifts in animal communities, such as an increase in rodents and other small mammals due to forest fragmentation, could alter patterns of seed predation and affect tree regeneration and community dynamics in forest fragments. We performed a field experiment on four native rainforest tree species in the Western Ghats, India, to test whether fragmentation increases seed predation by mammals and alters the distance-dependence of seed predation. We monitored seed predation within open and mammal-exclosure plots, near and far from the canopies of conspecific trees, in contiguous and fragmented forests. Seed predation of Cullenia exarillata, Ormosia travancorica, and Syzygium rubicundum was markedly higher in forest fragments, and more so within open plots than exclosures, while the predominantly insect-predated Acronychia pedunculata experienced similar predation in contiguous forests and fragments. Seed predation of C. exarillata and S. rubicundum was unrelated to distance from conspecific trees in open plots in both contiguous forests and fragments, in contrast to exclosures that showed marked near versus far differences in seed predation. Our findings suggest that by increasing overall seed predation risk and imposing similar seed predation risk near and far from adults variably across the tree species, small mammals could alter processes that shape tree diversity and species composition in fragmented tropical rainforests.
Data for: "Dynamic species distribution modeling reveals the pivotal role of human-mediated long-distance dispersal in plant invasion"
<p>All the data needed to reproduce the results and Figures of our article:</p> <p>Botella, C., Bonnet, P., Hui, C., Joly, A., & Richardson, D. M. (2022). Dynamic Species Distribution Modeling Reveals the Pivotal Role of Human-Mediated Long-Distance Dispersal in Plant Invasion. <em>Biology</em>, <em>11</em>(9), 1293. <a href="https://doi.org/10.3390/biology11091293">https://doi.org/10.3390/biology11091293</a></p> <p>Please, find the R scripts and guidelines to reproduce our results on the article's Github repository :</p> <p><a href="https://github.com/ChrisBotella/plectranthus_barbatus/tree/main">https://github.com/ChrisBotella/plectranthus_barbatus/tree/main</a></p>
Comparing climatic suitability and niche distances to explain populations responses to extreme climatic events
<p><span>Habitat suitability calculated from Species Distribution Models (SDMs) has been used to assess population performance, but empirical studies have provided weak or inconclusive support to this approach. Novel approaches measuring population distances to niche centroid and margin in environmental space have been recently proposed to explain population performance, particularly when populations experience exceptional environmental conditions that may place them outside of the species niche. Here, we use data of co-occurring species' decay, gathered after an extreme drought event occurring in the SE of the Iberian Peninsula which highly affected rich semiarid shrubland communities, to compare the relationship between population decay (mortality and remaining green canopy) and (1) distances between populations' location and species niche margin and centroid in the environmental space, and (2) climatic suitability estimated from frequently used SDMs (here MaxEnt) considering both the extreme climatic episode and the average reference climatic period before this. We found that both SDMs-derived suitability and distances to species niche properly predict populations performance when considering the reference climatic period; but climatic suitability failed to predict performance considering the extreme climate period. In addition, while distance to niche margins accurately predict both mortality and remaining green canopy responses, centroid distances failed to explain mortality, suggesting that indexes containing information about the position to niche margin (inside or outside) are better to predict binary responses. We conclude that the location of populations in the environmental space is consistent with performance responses to extreme drought. Niche distances appear to be a more efficient approach than the use of climate suitability indices derived from more frequently used SDMs to explain population performance when dealing with environmental conditions that are located outside the species environmental niche. The use of this alternative metrics may be particularly useful when designing</span><span> conservation measures to mitigate impacts of shifting environmental conditions.</span></p>
Neutral processes related to regional bee commonness and dispersal distances are important predictors of plant-pollinator networks along gradients of climate and landscape conditions
<p>Understanding how niche-based and neutral processes contribute to the spatial variation in plant-pollinator interactions is central to designing effective pollination conservation schemes. Such schemes are needed to reverse declines of wild bees and other pollinating insects and to promote pollination services to wild and cultivated plants. We used data on wild bee interactions with plants belonging to the four tribes Loteae, Trifolieae, Anthemideae, and either spring- or summer-flowering Cichorieae, sampled systematically along a 682km latitudinal gradient to build models that allowed us to (a) predict occurrences of pairwise bee-flower interactions across 115 sampling locations, and (b) estimate the contribution of variables hypothesized to be related to niche-based assembly structuring processes (viz. annual mean temperature, landscape diversity, bee sociality, bee phenology, and flower preferences of bees) and neutral processes (viz. regional commonness and dispersal distance to conspecifics). While neutral processes were important predictors of plant-pollinator distributions, niche-based processes were reflected in the contrasting distributions of solitary bee and bumble bees along the temperature gradient, and in the influence of bee flower preferences on the distribution of bee species across plant types. In particular, bee flower preferences separated bees into three main groups, albeit with some overlap: visitors to spring-flowering Cichorieae; visitors to Anthemideae and summer-flowering Cichorieae; and visitors to Trifolieae and Loteae. Our findings suggest that both neutral and niche-based processes are significant contributors to the spatial distribution of plant-pollinator interactions so that conservation actions in our region should be directed towards areas: near high concentrations of known occurrences of regionally rare bees; in mild climatic conditions; and that are surrounded by heterogeneous landscapes. Given the observed niche-based differences, the proportion of functionally distinct plants in flower-mixes could be chosen to target bee species, or guilds, of conservation concern.</p>
Text-fig. 5. Mastixiopsis nyssoides KIRCHH. a, b, g–n: Organic preservation. a, b: Lignitic, unpermineralized, early Eocene Dorset Pipe clays at Arne, V. 40762. a: Ventral view (original illustration from pl. 18, fig. 1 of Chandler 1962). b: Transverse fracture, somewhat distorted by compression. c–f: Pyrite permineralization. c: Ventral view, V. 22963(1) from Sheppey, originally listed as Mastixia cantiensis. d: Lateral view, V. 22969 from Sheppey (identified as Mastixia grandis by Reid and Chandler 1933: pl. 25, fig. 8). e: Equatorial transverse physical section from (c). f: Equatorial transverse physical section from (d). g: Detail of pericarp from (e), showing endocarp formed of dense fibrous tissue, surrounded by mesocarp of anticlinally oriented larger cells. h: Detail of pericarp from (f). i–n: Type material from Eocene of Riestadt, Germany, MNB. i: Ventral view. j, k: Ventral and apical views of holotype. l: View of the transversely fractured surface from (j) showing horseshoe shaped locule. m: Equatorial transverse physical cut of the specimen in (i); note yellow resin cavity (arrow). n: Scanning electron microscopy of pericarp from (l) with locule lining at lower edge of image. Note dense endocarp tissue composed of small cells (fibres and sclereids), extending about 3/5 of distance to periphery, surrounded by mesocarp of larger, anticlinally oriented cells. Scale bars 1 cm in (a–f), (i–k), 1 mm in (g), 2 mm in (h), 3 mm in (l), m, 250 Μm in (n). Bar in (d) applies also to (c). Bar in (l) also applies to (m). Bar in (i) also applies to (j) and (k). in Mastixioid Fruits (Cornales) From The Early Eocene London Clay Flora: Morphology, Anatomy And Nomenclatural Revision
Text-fig. 5. Mastixiopsis nyssoides KIRCHH. a, b, g–n: Organic preservation. a, b: Lignitic, unpermineralized, early Eocene Dorset Pipe clays at Arne, V. 40762. a: Ventral view (original illustration from pl. 18, fig. 1 of Chandler 1962). b: Transverse fracture, somewhat distorted by compression. c–f: Pyrite permineralization. c: Ventral view, V. 22963(1) from Sheppey, originally listed as Mastixia cantiensis. d: Lateral view, V. 22969 from Sheppey (identified as Mastixia grandis by Reid and Chandler 1933: pl. 25, fig. 8). e: Equatorial transverse physical section from (c). f: Equatorial transverse physical section from (d). g: Detail of pericarp from (e), showing endocarp formed of dense fibrous tissue, surrounded by mesocarp of anticlinally oriented larger cells. h: Detail of pericarp from (f). i–n: Type material from Eocene of Riestadt, Germany, MNB. i: Ventral view. j, k: Ventral and apical views of holotype. l: View of the transversely fractured surface from (j) showing horseshoe shaped locule. m: Equatorial transverse physical cut of the specimen in (i); note yellow resin cavity (arrow). n: Scanning electron microscopy of pericarp from (l) with locule lining at lower edge of image. Note dense endocarp tissue composed of small cells (fibres and sclereids), extending about 3/5 of distance to periphery, surrounded by mesocarp of larger, anticlinally oriented cells. Scale bars 1 cm in (a–f), (i–k), 1 mm in (g), 2 mm in (h), 3 mm in (l), m, 250 Μm in (n). Bar in (d) applies also to (c). Bar in (l) also applies to (m). Bar in (i) also applies to (j) and (k).
Distance estimation in the Goldfish (Carassius auratus)
<p>Neurophysiological advances have given us exciting insights into the systems responsible for spatial mapping in mammals. However, we are still lacking information on the evolution of these systems and whether the underlying mechanisms identified are universal across phyla, or specific to the species studied. Here we address these questions by exploring whether a species that is evolutionarily distant from mammals can perform a task central to mammalian spatial mapping – distance estimation. We developed a behavioural paradigm allowing us to test whether goldfish (<em>Carassius</em> <em>auratus</em>) can estimate distance and explored the behavioural mechanisms that underpin this ability. Fish were trained to swim a set distance within a narrow tank covered with striped pattern. After changing the background pattern, we found that goldfish use the spatial frequency of their visual environment to estimate distance; doubling the spatial frequency of the background pattern resulted in a large overestimation of the swimming distance. These results provide robust evidence that goldfish can accurately estimate distance, and show that they use local optic flow to do so. These results provide a compelling basis to utilise goldfish as a model system to interrogate the evolution of the mechanisms that underpin spatial cognition, from brain to behaviour.</p>
Data and codes from "Daniel et al. What can optimized cost distances based on genetic distances offer? A simulation study on the use and misuse of ResistanceGA"
<p><span>Data and codes used for </span><span>“Daniel et al. What can optimized cost distances based on genetic distances offer? A simulation study on the use and misuse of ResistanceGA”</span></p>
Data - Teaching and Learning of Introduction to Software Engineering Experimentation to Distance-Learning Students: a Quasi-Experiment
<p>Data from a quasi-experiment on "Teaching and Learning of Introduction to Software Engineering Experimentation to Distance-Learning Students: a Quasi-Experiment"</p> <p> </p> <p>Funded by Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) 311503/2022-5</p>
Road distances and trip duration matrix for Brazilian municipalities
<p>This dataset presents a matrix with road distance and travel duration estimates for all the trips combination among the Brazilian municipalities. More details about the methodology are available <a href="https://rfsaldanha.github.io/data-projects/brazil_road_distances.html" target="_blank" rel="noopener">here</a>.</p> <p>This version was generated considering the road network at the OSRM project on May 2024.</p> <p><strong>Variable dictionary</strong></p> <ul> <li>orig: Code of the municipality of origin (IBGE 7-digits) </li> <li>dest: Code of the municipality of destiny (IBGE 7-digits) </li> <li>dist: Road distance of the shortest route, in meters</li> <li>dur: Travel time estimation, in minutes.</li> </ul> <p><strong>Files</strong></p> <ul> <li>dist_brasil.rds : R serialized object</li> <li>dist_brasil.parquet : Parquet format</li> <li>dist_brasil.zip : Compressed CSV file. Semi-colon ( ; ) field delimiter and point ( . ) as decimal separator</li> </ul>
Figure 4 in Effects of Palmer Amaranth (Amoronthus polmeri) Establishment Time and Distance from the Crop Row on Biological and Phenological Characteristics of the Weed: Implications on Soybean Yield
Figure 4. Effects of the interaction of weed establishment time and distance from the crop row on Amoronthus polmeri dry weight before soybean harvest. Vertical bars represent ± standard error of the mean (SE2014 = 1.27; SE2015 = 0.74) from the analysis for comparisons between weed establishment times with sample size n = 72. WAE, weeks after soybean emergence.
Figure 3 in Effects of Palmer Amaranth (Amoronthus polmeri) Establishment Time and Distance from the Crop Row on Biological and Phenological Characteristics of the Weed: Implications on Soybean Yield
Figure 3. Effects of the interaction of weed establishment time and distance from the crop on Amoronthus polmeri plant height at harvest. Vertical bars represent ± standard error of the mean (SE2014 = 4.68; SE2015 = 3.14) from the analysis for comparisons between weed establishment times with sample size n = 72. WAE, weeks after soybean emergence.
Figure 7 in Effects of Palmer Amaranth (Amoronthus polmeri) Establishment Time and Distance from the Crop Row on Biological and Phenological Characteristics of the Weed: Implications on Soybean Yield
Figure 7. Relationship between ground cover and extinction coefficient for each sampling date (n = 12 plots) throughout the 2014 growing season. WAE, weeks after soybean emergence.
Figure 2 in Effects of Palmer Amaranth (Amoronthus polmeri) Establishment Time and Distance from the Crop Row on Biological and Phenological Characteristics of the Weed: Implications on Soybean Yield
Figure 2. Soybean and Amoronthus polmeri (AMAPA) height (averaged across distance from the crop) at 0, 1, 2, 4, 6, and 8 wk after soybean emergence (WAE) (i.e., AMAPA-0, AMAPA-1, AMAPA-2, AMAPA-4, AMAPA-6, and AMAPA-8, respectively). Vertical bars represent ± standard error of the mean from the analysis for comparisons within each sampling date (i.e., n = 12 for 0 WAE, 24 for 1 WAE, etc.).
Figure 9 in Effects of Palmer Amaranth (Amoronthus polmeri) Establishment Time and Distance from the Crop Row on Biological and Phenological Characteristics of the Weed: Implications on Soybean Yield
Figure 9. Effects of weed establishment time on soybean yield averaged across Amoronthus polmeri distances from the crop row. Dashed lines indicate the confidence intervals at 95% confidence level (sample size n = 72). WAE, weeks after soybean emergence.
Figure 10 in Effects of Palmer Amaranth (Amoronthus polmeri) Establishment Time and Distance from the Crop Row on Biological and Phenological Characteristics of the Weed: Implications on Soybean Yield
Figure 10. Effects of Amoronthus polmeri distance from the soybean row on crop yield averaged across A. polmeri establishment times. Vertical bars represent ± standard error of the mean (SE2014 = 337.45; SE2015 = 207.14) from the analysis for comparisons between A. polmeri distances from the crop with sample size n = 72.
Figure 6 in Effects of Palmer Amaranth (Amoronthus polmeri) Establishment Time and Distance from the Crop Row on Biological and Phenological Characteristics of the Weed: Implications on Soybean Yield
Figure 6. Effects of weed establishment time on Amoronthus polmeri (AMAPA) flowering (averaged across distance from the crop) at various sampling occasions for 0, 1, 2, 4, 6, and 8 wk after soybean emergence (WAE) (i.e., AMAPA-0, AMAPA-1, AMAPA-2, AMAPA-4, AMAPA-6, and AMAPA-8 respectively) in 2014 and 2015. Vertical bars represent ± standard error of the mean (i.e., flowering of the entire A. polmeri population was evaluated at each sampling occasion) from the analysis for comparisons within each sampling date (i.e., n = 12 plots for 0 WAE, 24 plots for 1 WAE, 36 plots for 2 WAE, etc.).
Figure 5 in Effects of Palmer Amaranth (Amoronthus polmeri) Establishment Time and Distance from the Crop Row on Biological and Phenological Characteristics of the Weed: Implications on Soybean Yield
Figure 5. Effects of the interaction of weed establishment time and distance from the crop row on Amoronthus polmeri seed production before soybean harvest. Vertical bars represent ± standard error of the mean (SE2014 = 2,530.27; SE2015 = 1,008.30) from the analysis for comparisons between weed establishment times with sample size n = 72. WAE, weeks after soybean emergence.
Figure 8 in Effects of Palmer Amaranth (Amoronthus polmeri) Establishment Time and Distance from the Crop Row on Biological and Phenological Characteristics of the Weed: Implications on Soybean Yield
Figure 8. Relationship between ground cover and extinction coefficient for each sampling date (n = 12 plots) throughout the 2015 growing season. WAE, weeks after soybean emergence
Figure 2. Jump distance versus the maximum horizontal velocity component for 13 in Jumping Performance in Flightless Hawaiian Grasshopper Moths (Xyloryctidae: Thyrocopa spp.)
Figure 2. Jump distance versus the maximum horizontal velocity component for 13 total jumps of male T. apatela. The regression is given by: y = 1.01 x + 16.39, r2=0.57, P<0.004.
SI Figure 3: Compositional difference among eukaryotic microinvertebrate external and internal microbiomes, using Bray Curtis distance matrix visualized with a NMDS ordination. Circles indicate each community and stars centroid location of each microbiome type. Communities do not cluster by animal, microbiome type, mat type, or stream. in External and internal microbiomes of Antarctic nematodes are distinct, but more similar to each other than the surrounding environment
SI Figure 3: Compositional difference among eukaryotic microinvertebrate external and internal microbiomes, using Bray Curtis distance matrix visualized with a NMDS ordination. Circles indicate each community and stars centroid location of each microbiome type. Communities do not cluster by animal, microbiome type, mat type, or stream.
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