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583 results for “plant distributions”
What are the most crucial soil variables for predicting the distribution of mountain plant species? a comprehensive study in the Swiss Alps
Aim: To investigate the potential of a large range of soil variables to improve topo-climatic models of plant species distributions in a temperate mountain region encompassing complex relief. Location: The western Swiss Alps. Methods: Fitting topo-climatic models for >60 plant species across >250 sites with and without added soil predictor variables (>30). Testing included: (i) which soil variables improve plant species distribution models; (ii) whether an optimal subset of soil variables can improve models for the majority of species and habitat types; and (iii) how much variation in plant species distributions soil variables alone explain. Results: Geochemical variables (i.e., CaO, pH and inorganic carbon) and a drainage indicator (i.e., bulk soil water content) improved the predictive abilities of the models across the large majority of alpine plant species. The improvement of the models after the addition of soil information varied strongly between plant species and habitat types, but a trade-off was found between the number of soil variables and the associated gain in model performance. Finally, across all species, one specific combination of soil variables–bulk soil water content + total phosphorus + <i>δ</i><sup>13</sup>C–outperformed the commonly used topo-climatic variables. Main conclusions: Several soil variables significantly increased the predictive power of plant species distribution models in the temperate mountain region. Geochemical and drainage variables proved most important.
Data from: The influence of geomorphic processes on plant distribution and abundance as reflected in plant tolerance curves
Ecologists describe plant distribution using direct gradient analysis, by which a tolerance curve of species abundance is described along an environmental gradient (any environmental variable that affects plant distribution). Soil moisture is generally the gradient in low relief areas that explains the most variation. Traditional direct gradient analyses have used terrain structure (i.e. transects up or down hillslopes) as a correlate to soil moisture. Here we use a numerical tectonic and geomorphic process-based landscape development model to create two landscapes with different geomorphic characteristics (i) to demonstrate the influence of geomorphic processes on soil moisture patterns and plant distribution and (ii) to evaluate the effectiveness of transects in describing moisture gradients and tolerance curves on landscapes dominated by creep or overland flow. We use a topographic index to approximate the distribution of soil moisture as it is determined by the shape of these different landscapes. Transects are placed on hillslopes in each model landscape and used to construct tolerance curves. Results show that transect methods that use the distance from the channel to the ridgeline as an approximation of soil moisture create variable tolerance curves for the same plant both within a single landscape and between different landscapes. The reason for these differences is that transects do not take into account the 3-dimensional landscape form that explains water movement. Landscapes have regions of convexity and flow path divergence and regions of concavity and flow path convergence which, along with hillslope length, determine contributing area. In addition, hillslope curvature results in varying capacities to retain water. However, when the topographic index is used instead of hillslope transect position, tolerance curves from the same and different landscapes reflect the differences the topographic structure has on soil moisture. We thus show that traditional methods of direct gradient analysis are not always adequate as they do not tend to consider that soil moisture depends on hillslope length, curvature, and slope. Furthermore, we show that within and between landscapes there are differences in spatial distributions of soil moisture that are reflections of the geomorphic processes that created them.
FIGURE 2. Eotetranychus herbicolus n in Two new plant feeding mites from Brachiaria ruziziensis in citrus groves in São Paulo, Brazil and new distribution records of other plant mites in Brazil
FIGURE 2. Eotetranychus herbicolus n.sp. Dorsal aspect of female.
FIGURE 3 in Phytodiversity, ecological attributes and phytogeographical distribution of plants in Arang Valley, District Bajaur, a remote area in the Northwest of Pakistan
FIGURE 3. Life form of the plant species
FIGURE 6 in Phytodiversity, ecological attributes and phytogeographical distribution of plants in Arang Valley, District Bajaur, a remote area in the Northwest of Pakistan
FIGURE 6. Flowering phenology of the flora
FIGURE 5 in Phytodiversity, ecological attributes and phytogeographical distribution of plants in Arang Valley, District Bajaur, a remote area in the Northwest of Pakistan
FIGURE 5. Floristic elements of Arang valley
FIGURE 4 in Phytodiversity, ecological attributes and phytogeographical distribution of plants in Arang Valley, District Bajaur, a remote area in the Northwest of Pakistan
FIGURE 4. Leaf size spectrum of the plant species
FIGURE 1 in Phytodiversity, ecological attributes and phytogeographical distribution of plants in Arang Valley, District Bajaur, a remote area in the Northwest of Pakistan
FIGURE 1. Map of the study area
FIGURE 2 in Phytodiversity, ecological attributes and phytogeographical distribution of plants in Arang Valley, District Bajaur, a remote area in the Northwest of Pakistan
FIGURE 2. Habit of the flora
Refugia during the last glacial period and the origin of the disjunct distribution of the insular plant Microtropis japonica (Celastraceae)
<p><span><b>Aim: </b>While many phylogeographical studies have focused on continental refugia, the function of islands as refugia has been long overlooked. In this study, we examined the biogeographic history of <i>Microtropis japonica </i>and its insular distribution to elucidate the hidden status of islands on the range expansion of plants.</span></p> <p><span><b>Location: </b>Two disjunct island areas of Japan (the Izu and Ryukyu Islands) and their adjacent areas (the Japanese mainlands Honshu and Kyushu, and Taiwan).</span></p> <p><span><b>Taxon: </b><i>Microtropis japonica </i>(Celastraceae).</span></p> <p><span><b>Methods: </b>Phylogeographic and population genetic analyses were performed using chloroplast DNA (cpDNA) and nuclear single-nucleotide polymorphism (SNP) data. In addition, ecological niche modeling of current suitable habitats and those during the last glacial maximum were conducted using occurrence and climate data.</span></p> <p><span><b>Results: </b>Both cpDNA and nuclear SNP data showed genetic differentiation between two disjunct regions (mainly the Izu and Ryukyu Islands). However, at the intra-regional level, the genetic structures revealed by different markers showed different geographic patterns. While cpDNA data indicated genetic differentiation within the Ryukyu Islands but not within the Izu Islands, nuclear SNP data indicated genetic differentiation within both island groups. Ecological niche modeling showed that both the Izu and Ryukyu Islands have continuously been potential distribution areas regardless of historical climate oscillations.</span></p> <p><span><b>Main conclusions: </b>Genetic data suggest that the current disjunct distribution pattern of <i>M. japonica</i> strongly reflects the refugia locations during the last glacial period and the subsequent range expansion. Ecological niche modeling revealed the importance of islands as refugia in the disjunct distribution of <i>M. japonica</i>.</span></p>
Supplementary material 1 from: Van De Walle R, Massol F, Vandegehuchte ML, Bonte D (2022) The distribution and impact of an invasive plant species (Senecio inaequidens) on a dune building engineer (Calamagrostis arenaria). NeoBiota 72: 1-23. https://doi.org/10.3897/neobiota.72.78511
Tables S1, S2, Figures S1, S2
Fig. 11 in Review of the fritillary species systematically close to Melitaea lutko Evans, 1932 (Lepidoptera: Nymphalidae) with analysis of their geographic distribution and interrelations with host plants
Fig. 11. Female genitalia (without the anal papillae, copulatory bursa, and anterior and posterior apophyses). A–C. Melitaea timandra timandra Coutsis & van Oorschot, 2014, S Turkmenistan, SaryYazy, alt. 300 m. D–I. M. timandra binaludica subsp. nov. D–F. Iran, Rezavi Khorassan Prov., Kuh-eBinalud Mts, Dorrud v. vicinity, alt. 2430 m. G–H. Iran, Mazandaran Prov., S macroslopes of Albors Mts, 80 km SE of Sari, 5 km NE of Foulad Mahhaleh v., E slopes of Sultan Kuh Mt., alt. 2000 m. I. Afghanistan, Bamian Prov., Band-e-Amir, alt. 3200 m.
Supplementary material 3 from: Sirbu C, Miu IV, Gavrilidis AA, Gradinaru SR, Niculae IM, Preda C, Oprea A, Urziceanu M, Camen-Comanescu P, Nagoda E, Sirbu IM, Memedemin D, Anastasiu P (2022) Distribution and pathways of introduction of invasive alien plant species in Romania. NeoBiota 75: 1-21. https://doi.org/10.3897/neobiota.75.84684
Appendix S3. Publications used to compile distribution of alien plant species in Romania.
Supplementary material 1 from: Sirbu C, Miu IV, Gavrilidis AA, Gradinaru SR, Niculae IM, Preda C, Oprea A, Urziceanu M, Camen-Comanescu P, Nagoda E, Sirbu IM, Memedemin D, Anastasiu P (2022) Distribution and pathways of introduction of invasive alien plant species in Romania. NeoBiota 75: 1-21. https://doi.org/10.3897/neobiota.75.84684
Appendix S1. List of invasive and potentially invasive alien plant species in Romania
Figure 3 from: Chadin I, Dalke I, Zakhozhiy I, Malyshev R, Madi E, Kuzivanova O, Kirillov D, Elsakov V (2017) Distribution of the invasive plant species Heracleum sosnowskyi Manden. in the Komi Republic (Russia). PhytoKeys 77: 71-80. https://doi.org/10.3897/phytokeys.77.11186
Figure 3 - The prediction map of Heracleum sosnowskyi habitats prepared with the species distribution model based on bioclaimatic predictors. The borders of Plot 2 within which the model prediction was made. The colour scale shows the probability Heracleum sosnowskyi presence.
Figure 2 from: Chadin I, Dalke I, Zakhozhiy I, Malyshev R, Madi E, Kuzivanova O, Kirillov D, Elsakov V (2017) Distribution of the invasive plant species Heracleum sosnowskyi Manden. in the Komi Republic (Russia). PhytoKeys 77: 71-80. https://doi.org/10.3897/phytokeys.77.11186
Figure 2 - The prediction map of Heracleum sosnowskyi habitats prepared with the species distribution model based on vegetation cover map, nearest road proximity map, proximity map to the borders of agricultural areas. The colour scale shows the probability Heracleum sosnowskyi presence.
Figure 1 from: Chadin I, Dalke I, Zakhozhiy I, Malyshev R, Madi E, Kuzivanova O, Kirillov D, Elsakov V (2017) Distribution of the invasive plant species Heracleum sosnowskyi Manden. in the Komi Republic (Russia). PhytoKeys 77: 71-80. https://doi.org/10.3897/phytokeys.77.11186
Figure 1 - Study area. Red points indicate occurrences of Heracleum sosnowskyi described in the data paper.
Supplementary material 2 from: Croce A, Nazzaro R (2017) An atlas of orchids distribution in the Campania region (Italy), a citizen science project for the most charming plant family. Italian Botanist 4: 15-32. https://doi.org/10.3897/ib.4.14916
Checklist of the taxa recorded in the database : Data type: Table
Figure 5 from: Croce A, Nazzaro R (2017) An atlas of orchids distribution in the Campania region (Italy), a citizen science project for the most charming plant family. Italian Botanist 4: 15-32. https://doi.org/10.3897/ib.4.14916
Figure 5 - Distribution of the observations over time, collected in research projects or by volunteer contributors.
Figure 4 from: Croce A, Nazzaro R (2017) An atlas of orchids distribution in the Campania region (Italy), a citizen science project for the most charming plant family. Italian Botanist 4: 15-32. https://doi.org/10.3897/ib.4.14916
Figure 4 - Richness of taxa based on field data (observations). The number includes hybrids. Coordinates are expressed in metres, UTM WGS84 33N. Province abbreviations: AV = Avellino, BN = Benevento, CE = Caserta, NA = Naples, SA = Salerno.
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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.