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3,583 results for “elevations”
Data from: Nitrogen niche partitioning between tropical legumes and grasses conditionally weakens under elevated CO2
<p>Plant community biodiversity can be maintained, at least partially, by shifts in species interactions between facilitation and competition for resources as environmental conditions change. These interactions also drive ecosystem functioning, including productivity, and can promote over-yielding- an ecosystem service prioritized in agro-ecosystems, such as pastures, that occurs when multiple species together are more productive than the component species alone. Importantly, species interactions that can result in over-yielding may shift in response to rising CO<sub>2</sub> concentrations and changes in resource availability, and the consequences these shifts have on production is uncertain especially in the context of tropical mixed-species grasslands.</p> <p>We examined the relative performance of two species pairs of tropical pasture grasses and legumes growing in monoculture and mixtures in a glasshouse experiment manipulating CO<sub>2</sub>. We investigated how over-yielding can arise from nitrogen (N) niche partitioning and biotic facilitation using stable isotopes to differentiate soil N from biological N fixation (BNF) within N acquisition into aboveground biomass for these two-species mixtures.</p> <p>We found that N niche partitioning in species-level use of soil N vs. BNF drove species interactions in mixtures. Importantly partitioning and overyielding were generally reduced under elevated CO<sub>2</sub>. However, this finding was mixture-dependent based on biomass of dominant species in mixtures and the strength of selection effects for the dominant species.</p> <p>This study demonstrates that rising atmospheric CO<sub>2</sub> may alter niche partitioning between co-occurring species, with negative implications for the over-yielding benefits predicted for legume-grass mixtures in working landscapes with tropical species. Furthermore, these changes in inter-species interactions may have consequences for grassland composition that are not yet considered in larger-scale projections for impacts of climate change and species distributions. </p>
PERDAW (Plan, and Elevation Representations of Doors And Windows)
<p>The Perdaw dataset comprises 28,800 images depicting doors and windows, initially created as digital 3D objects and projected onto plan (top view) and elevation (front/back view). Twenty 3D objects were designed, including 10 doors and 10 windows.</p>
The Highs and Lows of Grazing: Effects of Ungulates and Elevation on Grassland and Sagebrush Steppe Vegetation Composition in Yellowstone National Park
<p>Yellowstone National Park’s Northern Range is emblematic for the wolves, bison and elk that inhabit its grassland and sagebrush-steppe habitats. Their interactions and populations have been the focus of considerable conservation debate. Recent changes in ungulate populations provide an opportunity to examine their influence on the vegetation communities. We conducted expansive vegetation surveys along an elevation gradient and at exclosure sites where ungulates were unable to graze. We collected a large database (n = 620 quadrats), which we analyzed using classic community ecology approaches. We found that non-native species have higher abundances at low elevations, and that grazing by ungulates reduces beta diversity and native cover, while promoting non-native cover. The magnitude of these changes are greater in bison-dominated than elk-dominated areas of Yellowstone, suggesting that bison may be overgrazing. These results provide valuable insights into major factors shaping vegetation communities, while also contextualizing management practices in a world-renowned ecosystem.</p> <p> </p> <p>Please respect licensing, and contact the corresponding author for permission to use this dataset in any research or publications. </p>
Data from: Enhanced woody biomass production in a mature temperate forest under elevated CO2
<p>This data set reports tree growth and net primary productivity in response to experimentally elevated atmospheric CO<sub>2</sub> concentration in the free-air CO<sub>2</sub> enrichment (FACE) of the Birmingham Institute of Forest Research (BIFoR FACE). Data ae reported for a pre-treatment period (2010-2016) and from the onset of CO<sub>2</sub> treatment (2017-2023). The BIFoR FACE experiment is located in central England (52.801°N, 2.301°W, 107 m above sea level) within a deciduous forest dominated by 180-year old <em>Quercus robur</em> L. trees, which represent 92% of the forest's basal area. There are six experimental arrays of approximately 30 m diameter. Tree ring analysis was used to determine growth patterns within the arrays prior to the onset of CO<sub>2</sub> treatment. The trees in three of the arrays have been exposed to elevated CO<sub>2</sub> (ambient concentration + 150 ppm) during the growing seasons since 2017. Tree diameter was measured with manual dendrometers, and dry mass of oak trees was calculated using an allometric equation determined by terrestrial laser scan of the trees within the arrays. Dry matter production of understory species and coarse roots was calculated using allometric equations from the literature. Leaf production was calculated from mass of leaf litter collected in litter baskets. Fine-root production was measured in ingrowth cores and scaled to 1-meter depth based on fine-root biomass in deep cores. Exudation rates were scaled up to a full growing season and total fine-root mass.</p>
Data from the journal article "Individual versus combined effects of warming, elevated CO2 and drought on grassland water uptake and fine root traits"
<p>This data file contains all data used in the aforementioned article (DOI: 10.1111/pce.15274). The data was obtained in a long-term multifactor global-change experiment (‘ClimGrass’) in a managed (three cuts, fertilized) C3 grassland near the central European Alps in Styria, Austria (47°29′44.6″N, 14°5′54.6″E). Grassland plots were exposed to six treatments: (i) ambient conditions (control; n = 8); (ii) drought (n = 4); (iii) warming (n = 3); (iv) elevated CO2 (n = 3), (v) future conditions (warming and elevated CO2; n = 3); and (vi) drought in future conditions (warming, elevated CO2 and drought; n = 4). The experiment was conducted during the growing seasons of 2017, 2019, and 2020. The aim was to determine how warming, elevated CO2 and drought individually and interactively affected root water uptake (RWU, calculated from soil water dynamics) as well as the corresponding mass and key traits (specific root length (SRL); specific root area (SRA); mean diameter) of newly produced fine roots (extracted using ingrowth cores) and biomass allocation (fine-root-to-shoot production ratios; R/S ratios). Treatment effects on RWU were studied across varying conditions of soil water content (SWC) and vapour pressure deficit (VPD), referred to as dryness conditions. Fine root characteristics were compared to the maximum hourly in-situ RWU observed. </p> <p>The following data is contained in this file (processed as described in the journal article and, importantly, in the supplementary information):<br>- data_SWC: SWC and precipitation, used to calculate RWU (resolution: hourly; figures: 1)<br>- data_RWU_daily: RWU for the main rooting horizon, fractions of total RWU across depth (resolution: daily; figures: 1, 2, 3)<br>- data_RWU_hourly: RWU for the main rooting horizon, SWC, VPD (resolution: hourly; figures: 1, 4, 5)<br>- data_FineRoots: Mass, traits (SRL, SRA, diameter) and maximum hourly RWU of newly produced fine roots across depth, R/S ratios (resolution: three samplings per growing season; figures: 6, 7)</p> <p>The metadata.xlsx file summarizes the contents of these datasets, including units and descriptions of the variables.</p> <p>Note below: the name of the project funded by the Austrian Academy of Sciences is ClimGrassHydro.</p>
NVIDIA AI Elevating Gaming to Photorealistic Levels
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Datasets and scripts for the publication "Insights into Defect Cluster Formation in Non-Stoichiometric Wustite (Fe1-xO) at Elevated Temperatures: Accurate force field from Deep Learning"
<div> <div> <div> <div> <p><strong>All the datasets and scripts for the publication"Insights into Defect Cluster Formation in Non-Stoichiometric Wustite (Fe<sub>1-x</sub>O) at Elevated Temperatures: Accurate force field from Deep Learning".</strong></p> <p>This database contains high-fidelity datasets for non-stoichiometric wüstite (Fe₁₋ₓO), including atomic coordinates, energies, and forces generated through ab initio molecular dynamics (AIMD) and refined using Deep Potential (DP) training. The dataset encompasses bulk phases, vacancy structures, and surface orientations, enabling accurate modeling of defect clusters and thermodynamic properties. It supports machine-learning force field development, offering insights into defect formation and large-scale simulations of Fe₁₋ₓO systems at elevated temperatures.</p> </div> </div> </div> </div> <div> <p>Description of the File Structure of Fe1-xO_DeepMD_Code_Datasets_Analysis.zip:</p> <p>1. `<code>init</code>` Folder <br>This folder contains the foundational datasets and inputs used for training and developing the machine-learning force field for Fe₁₋ₓO. </p> <blockquote> <p>1.1 `<code>01.train_data</code>` Subfolder <br>This folder organizes data related to the initial training of the Deep Potential (DP) model. <br>- `<code>dpmd_dataset</code>`: Processed dataset ready for DeepMD training, containing atomic configurations, forces, and energies.<br>- `<code>dpmd_rawfiles</code>`: Raw files from ab initio molecular dynamics (AIMD) simulations, serving as the source for generating training datasets.</p> <p>1.2 `<code>02.develop_data</code>` Subfolder<br>Contains `<code>.vasp</code>` files representing structural data used to develop and refine the force field. The structures include bulk, vacancy, and surface configurations of Fe₁₋ₓO. <br>- Files labeled `<code>bulk</code>` represent bulk Fe₁₋ₓO systems with varying lattice constants. <br>- Files labeled `<code>defect</code>` represent Fe and O vacancy structures (single and double vacancies). <br>- Files labeled `<code>surface</code>` represent Fe₁₋ₓO surface structures in various crystallographic orientations. <br><br></p> </blockquote> <p>2. `<code>run</code>` Folder<br>This folder contains files and logs generated during iterative training and testing of the DP force field, as well as subfolders for each iteration of the training process. </p> <blockquote> <p>2.1 Iteration Folders (`<code>iter.000000</code>` to `<code>iter.000024</code>`):<br>Each folder represents an iteration in the iterative refinement of the DP model, with three subfolders: <br>- `<code>00.train</code>`: Contains training data and outputs for the DP model during the current iteration. <br>- `<code>01.model_devi</code>`: Tracks deviations between DP predictions and ab initio results, guiding dataset selection for the next iteration. <br>- `<code>02.fp</code>`: Stores first-principles (FP) results from CP2K used to improve DP model accuracy. </p> <p>2.2 Other Key Files: <br>- `<code>cp2k.input</code>`: Input file for CP2K, used for performing ab initio calculations on configurations during the iterative process. <br>- `<code>dpdispatcher.log</code>`: Log file tracking the progress of data dispatching and task execution. <br>- `<code>dpgen.log</code>`: Log file recording operations of DPGEN during dataset generation and force field development. <br>- `<code>dpgen_nohup.sh</code>`: Script for running DPGEN in the background. <br>- `<code>machine_slurm_cp2k.json</code>`: Configuration file specifying computing resources for CP2K simulations in a cluster environment. <br>- `<code>param_cp2k.json</code>`: Parameter file for CP2K calculations, defining simulation settings. <br>- `<code>record.dpgen</code>`: Record of iterative processes, including input parameters and outputs for each stage.</p> </blockquote> <p>This organized structure ensures a systematic approach to dataset preparation, model training, and iterative refinement for developing accurate machine-learning potentials for Fe₁₋ₓO.</p> <p>graph-compress.0330.pb is the final compressed DeepMD potential parameters.</p> </div>
Shuttle Radar Topography Mission digital elevation models, data points, radiocarbon dates, and geochemical data for the Rub' al Khali Desert
Open the record for dataset details and reuse information.
Morphological trait matching in plant–Hymenoptera and plant–Diptera mutualisms across an elevational gradient
<p>Morphological trait-matching and species abundance are thought to be the main factors affecting the frequency and strength of mutualistic interactions. However, the relative importance of trait-matching and species abundance in shaping species interactions across environmental gradients remains poorly understood, especially for plant–insect mutualisms involving generalist species.</p> <p>Here, we characterised variation in species and trait composition and the relative importance of trait-matching and species abundance in shaping plant–Hymenoptera and plant–Diptera mutualisms in four meadows across an elevational gradient (2,725–3,910 m) in Yulong Snow Mountain, Southwest China. We also evaluated the effects of morphological traits of flower visitors and plant composition on their foraging specialisation (d' and normalised degree).</p> <p>There was a high degree of dissimilarity in the composition of Hymenoptera and Diptera visitors and their visited plants between communities. This variation was mainly driven by the spatial replacement of species. Both for plant–Hymenoptera and plant–Diptera networks, trait-matching between nectar tube depth and proboscis length was a stronger predictor of the interactions between temporally co-occurring plants and flower visitors than species abundance. Fourth-corner analyses revealed statistically significant trait-matching between nectar tube depth and proboscis length in plant–Hymenoptera networks at all sites, suggesting that Hymenoptera consistently foraged on plant species with nectar tube depths matching their proboscis lengths. By contrast, significant trait-matching in plant–Diptera networks was only observed at the two lower elevation sites. The species-level specialisation d' of flower visitors increased significantly as the proboscis length and the difference in nectar tube depth between the plant community and the plants visited by flower visitors increased.</p> <p>Our results highlight that the importance of trait-matching in shaping pairwise interactions and niche partitioning depends on the specific features (e.g. species composition and trait availability) of the plant-pollinator system. For specialised plant-Hymenoptera systems, trait-matching is an important determinant of species interactions, whereas for generalist plant-Diptera systems, trait-matching is relatively unimportant.</p>
Phylogenetic α- and β-diversities jointly reveal leaf-litter ant community assembly mechanisms along a tropical elevational gradient
<p>This study was conducted along the eastern slope of the Cofre de Perote mountain, in Veracruz, Mexico. This region is located at the junction of the Trans-Mexican volcanic belt and the Sierra Madre Oriental. We selected eight study sites spanning an elevational gradient of 3500 meters of altitude. Regardless of the geographical distance, all sites were systematically separated with an elevational difference of 500 meters on average between each other. We placed our study sites at the following elevations above sea level: 30-50 m, 610-670 m, 900-1010 m, 1470-1650 m, 2020-2230 m, 2470-2600 m, 3070-3160 m and 3480-3540 m, however, for simplicity, we will refer to each site as discrete units (i.e. 0, 600, 1000, 1500, 2100, 2500, 3100, 3500 m).</p> <p>Sampling sites were old-growth forests characterized by no obvious forest use and highly dominance of mature forests, except in the case of the lowest site (i.e., La Mancha), where most of its original vegetation has been transformed. To overcome the effect of perturbation in the studied patterns, we sampled La Mancha in a secondary forest with up to 30 years of regeneration. All sampling sites were closed-canopy forests in which a leaf-litter layer could be guaranteed. During the rainy season (July-September) of 2018 one 300-m transversal transect was located at each one of the eight study locations where we established 10 equidistantly sampling points (i.e., 30 meters between each other). Two independent 1-m2 samples were taken perpendicularly to each sampling point: one 10 meters on the right side and the other 10 meters from the left side. This procedure was repeated in a second transect placed during the dry season (March-May) of 2019 to increase community characterization as well as reduce any seasonality effect on our diversity patterns. Transects within an elevational site were separated at least 1 km away from each other. Thus, we obtained 320 m<sup>2</sup> leaf-litter samples characterized the whole mountain (8 study sites x 20 m<sup>2 </sup>per transect x 2 transects = 320 m<sup>2</sup>). In each 1-m<sup>2</sup> quadrat, we collected the leaf litter inside and sifted it through a coarse mesh screen of 1-cm grid size to remove the largest fragments and concentrate the fine litter. The concentrated fine litter from each sample was suspended in independent mini-Winkler sacks for 3 days in the laboratory. Falling arthropods were collected into a container with 95% ethanol. Ant workers were removed from each container for identification. When possible, specimens were identified at the species level. If not, we assigned a morphospecies number.</p> <p> </p> <p><strong>Phylogenetic tree constructions</strong></p> <p>Ideally, one would use a complete, species-level phylogeny of all ant species present in your study area to calculate phylogenetic diversity, yet our current understanding of ant relationships is still limited. As an alternative, we built a genus-level phylogeny based on the tree by Moreau & Bell, (2013), but using the phylogenetic relationships and divergence times within Myrmicinae from Ward et al. (2015). This phylogeny was then pruned to keep only a single species per genus to generate a genus-level phylogeny. To maximize taxonomic coverage, we replaced genera that were missing from those studies by closely-related lineages that were not present in our dataset using other phylogenetic studies (Borowiec, 2016; Lapolla et al., 2010; Schmidt & Shattuck, 2014). We then used the list of species (Supporting Information Table S1) in our dataset to simulate a species-level phylogeny in which the relationships within genera were obtained from a Yule (pure-birth) process using the <em>genus.to.species.tree</em> function in the “phytools” package (Revell, 2012). A total of 1000 simulated trees were obtained to account for phylogenetic uncertainty [see Arnan et al. (2018) and Divieso et al. (2020) for similar approach]. Additionally, we constructed a maximum clade credibility tree (hereafter MCC tree) which was used to summarize the uncertainty of the 1000 simulated trees. The MCC tree was constructed from the sample of the 1000 trees with the <em>maxCladeCred</em> function incorporated in the “ape” package (Paradis et al., 2019). Both the 1000 hypothetical trees and the MCC tree were used in downstream analyses (Supporting Information Fig. 1).</p>
Influence of elevation on bioregionalisation: A case study of the Sino-Himalayan flora
<p><b>Aim: </b>Elevation is an important factor that influences bioregionalisation in mountainous areas, but its effects are not well known. Taking the Sino-Himalayan flora as a case, we aimed to test the effect of elevation on bioregionalisation and provide a regionalisation scheme of the Sino-Himalayan flora.</p> <p><span class="fontstyle0"><strong>Location:</strong> </span><span class="fontstyle2">The Sino-Himalaya (East Himalaya, the Hengduan Mountains and the Yunnan Plateau in China).</span></p> <p><b>Taxon: </b>Angiosperms.</p> <p><b>Methods: </b>We compiled distribution data and elevation ranges of angiosperms in the Sino-Himalaya and adjacent areas and reconstructed a species-level phylogenetic tree of 19,313 angiosperm species. The area was divided into 398 grid cells, each 1 × 1°. Nine datasets of different elevation ranges were then used to delineate the flora of the Sino-Himalaya and adjacent areas using the phylogenetic dissimilarity approach.</p> <p><b>Results: </b>A comparison of nine regionalisation schemes of the Sino-Himalayan flora based on different elevation range datasets revealed that more than half of grid cells were allocated to more than one subregion. Most of these grid cells were located in areas with a wide range of elevation and/or at the boundaries between subregions. After revising the subregion allocations of eight shifting grid cells, we generated a phylogeny- and elevation-based regionalisation scheme of three regions, comprising eight subregions, for the Sino-Himalayan flora.</p> <p><b>Main conclusions:</b> By integrating phylogenetic and elevational information, the Sino-Himalaya can be divided into three floristic regions: the Yunnan Plateau region, the Hengduan Mountains region, and the East Himalaya region. Our study provides novel insights into the regionalisation of the flora and highlights the importance of incorporating elevation data in the bioregionalisation of areas with a broad elevational range.</p>
Elevated atmospheric CO2 changes defence allocation in wheat but herbivore resistance persists
<p>Predicting how plants allocate to different anti-herbivore defences in response to elevated carbon dioxide (CO<sub>2</sub>) concentrations is important for understanding future patterns of crop susceptibility to herbivory. Theories of defence allocation, especially in the context of environmental change, largely overlook the role of silicon (Si), despite it being the major anti-herbivore defence in the Poaceae. We demonstrated that elevated levels of atmospheric CO<sub>2</sub> (e[CO<sub>2</sub>]) promoted plant growth by 33% and caused wheat (<i>Triticum aestivum</i>) to switch from Si (–19%) to phenolic (+44%) defences. Despite the lower levels of Si under e[CO<sub>2</sub>], resistance to the global pest <i>Helicoverpa armigera</i> persisted; relative growth rates (RGR) were reduced by at least 33% on Si supplied plants, irrespective of CO<sub>2</sub> levels. RGR was negatively correlated with leaf Si concentrations. Mandible wear was c. 30% higher when feeding on Si supplemented plants compared to those feeding on plants with no Si supply. We conclude that higher carbon availability under e[CO<sub>2</sub>] reduces silicification and causes wheat to increase concentrations of phenolics. However, Si supply, at all levels, suppressed the growth of <i>H. armigera</i> under both CO<sub>2</sub> regimes, suggesting that shifts in defence allocation under future climate change may not compromise herbivore resistance in wheat.</p>
Habitat area and environmental filters determine avian richness along an elevation gradient in mountain peatlands
<p>Globally, relationships between avian richness and elevation in mountain ecosystems typically reflect one of four well-documented patterns, but the mechanisms responsible for these patterns are poorly understood. We investigated which pattern best described bird species richness in peatlands of the Upper Bow Basin of the Canadian Rocky Mountains (1300 to 2000 m a.s.l.) and used a model competition framework to investigate possible mechanisms. Avian richness displayed a plateauing (cubic) relationship in response to increasing elevation (AICc weight = 0.48). Log richness was significantly positively related to log peatland area (R<sup>2</sup> = 0.42, p = 0.001); however, once we accounted for the richness-area relationship (area was not related to elevation (R<sup>2</sup> = 0.13, p = 0.083)), the richness-elevation relationship was best described by a negative linear model rather than a cubic model (AICc weight = 0.69, R<sup>2</sup> = 0.39). Consequently, we reject the neutral model of the mid-domain effect and conclude that peatland area and one or more environmental filters are simultaneously driving relationships between avian richness and elevation in Rocky Mountain peatlands. Multi-causality likely explains why researchers in different geographies observe inconsistent patterns between richness and elevation: drivers and interactions among drivers may vary spatially. Importantly, Natural Subregion was a stronger predictor of avian species richness than elevation per se (AICc weight = 0.96), suggesting that the responsible environmental filter(s) is relatively homogenous within ecological land classes (e.g., primary productivity) rather than directly variable with elevation (e.g., temperature). The results also lend insight into priorities for future research on richness-elevation patterns in mountain birds.</p>
Fig. 4 in A New Species of Nannoscincus Günther (Squamata: Scincidae) from High Elevation Forest in Southern New Caledonia
Fig. 4. Map of New Caledonia showing location of Pic Ningua and adjacent Mont Çidoa,
Fig. 1 in A New Species of Nannoscincus Günther (Squamata: Scincidae) from High Elevation Forest in Southern New Caledonia
Fig. 1. Paratype of Nannoscincus garrulus n.sp. (AMS R163457).
Changes in community-weighted trait mean, functional diversity, soil chemical properties and temperature along an elevational gradient in Tenerife, Canary Islands
<p>This dataset comprises community-weighted trait means and functional diversity of leaf traits, chemical soil properties and temperature recorded in roadside (disturbed) and interior (less disturbed) plots, along an elevational gradient of 2,300 m in Tenerife, Canary Islands. The leaf traits measured were specific leaf area (SLA), nitrogen, nitrogen to phosphorus ratio, leaf dry matter content (LDMC) and carbon to phosphorus ratio. The soil chemical properties measured were pH, nitrogen, nitrogen to phosphorus ratio, carbon to phosphorus ratio, calcium, potassium, magnesium and cation exchange capacity. Also the scores of the three first axes derived from a PCA analysis including the soil chemical properties are included. The temperature variables consist of bioclimatic variables Bio10 (mean temperature of the warmest quarter) and Bio11 (mean temperature of the coldest quarter). This dataset has been used for the analysis presented in Ratier Backes et al. (2021).</p>
Thermal-metabolic phenotypes of the lizard Podarcis muralis differ across elevation, but converge in high elevation hypoxia
<p>In response to a warming climate, many montane species are shifting upslope to track the emergence of preferred temperatures. Characterizing patterns of variation in metabolic, physiological and thermal traits along an elevational gradient, and the plastic potential of these traits, is necessary to understand current and future responses to abiotic constraints at high elevations, including limited oxygen availability. We performed a transplant experiment with the upslope-colonizing common wall lizard (<em>Podarcis</em> <em>muralis</em>) in which we measured nine aspects of thermal physiology and aerobic capacity in lizards from replicate low- (400 m above sea level, ASL) and high-elevation (1700 m ASL) populations. We first measured traits at their elevation of origin and then transplanted half of each group to extreme high elevation (2900 m ASL; above the current elevational range limit of this species), where oxygen availability is reduced by ∼25% relative to sea level. After 3 weeks of acclimation, we again measured these traits in both the transplanted and control groups. The multivariate thermal–metabolic phenotypes of lizards originating from different elevations differed clearly when measured at the elevation of origin. For example, high-elevation lizards are more heat tolerant than their low-elevation counterparts (counter-gradient variation). Yet, these phenotypes converged after exposure to reduced oxygen availability at extreme high elevation, suggesting limited plastic responses under this novel constraint. Our results suggest that high-elevation populations are well suited to their oxygen environments, but that plasticity in the thermal–metabolic phenotype does not pre-adapt these populations to colonize more hypoxic environments at higher elevations.</p>
Ecological and evolutionary processes shape belowground springtail communities along an elevational gradient
<p> The data sets were analyzed during the current study. Data from: Ecological and evolutionary processes shape belowground springtail communities along an elevational gradient</p>
Lianas and trees exhibit divergent intrinsic water-use efficiency along elevational gradients in South American and African tropical forests
<p>Elevational gradients provide excellent opportunities to explore long-term morphological and physiological responses of plants to environmental change. We determined the difference in the elevational pattern of foliar carbon isotope composition (<i>δ</i><sup>13</sup>C) between lianas and trees, and assessed whether this difference arises from changes in photosynthesis or stomatal conductance. We also explored the pattern of nutrient limitations with the elevation of these two growth forms. We conducted inventories of lianas and trees using standardized techniques along elevational gradients in Ecuador and Rwanda. We determined the values of several foliar traits including <i>δ</i><sup>13</sup>C and chemical traits in dominant liana and tree species. We set up Bayesian linear mixed-effect models to quantify the effects of elevation and these two growth forms, and the difference of the effect of elevation between the two growth forms on each of the foliar traits. We found consistent growth form specific divergences in foliar<i> δ</i><sup>13</sup>C and carbon to nitrogen ratio (C:N) responses to elevation. While we noted a meaningful increase in foliar <i>δ</i><sup>13</sup>C and C:N with elevation for trees, lianas did not exhibit such a trend. Foliar <i>δ</i><sup>13</sup>C and C:N remained relatively constant for lianas along the transects. The physiological processes at the basis of foliar carbon isotope fractionation shift differently in lianas and trees along elevation. Lianas operate at relatively constant intrinsic water- and nitrogen- use efficiencies with elevation as opposed to trees. Altogether, the study suggests the existence of a functional divergence of water and nutrient use strategies between lianas and trees along tropical elevational transects.</p>
Tree-ring dataset of black pine (Pinus nigra) along an elevation gradient in the Cazorla Mountains (South of Spain)
<p>Tree-ring dataset in Heidelberg and Tucson formats of <em>Pinus nigra</em> samples from living trees in four sites along an elevation gradient in the Cazorla and Segura Mountains (South of Spain). There are two types of files: the ones that contain the mean curves per tree (file code contains "mc"), and the ones containing the measurements of each individual core (files coded as "sm", single measurements). These samples were researched within the scope of the NWO-funded project <em>Filling in the blanks in European dendrochronology</em>. The results were published in the following article:</p> <p>Domínguez-Delmás, M., Alejano-Monge, R., Wazny, T., García González, I<em>.</em>, 2013. Radial growth variations of black pine along an elevation gradient in the Cazorla Mountains (South of Spain) and their relevance for historical and environmental studies. <em>Eur J Forest Res</em> <strong>132, </strong>635–652. https://doi.org/10.1007/s10342-013-0700-7</p> <p>Refer to the article for further information.</p> <p> </p>
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