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23 results for “dimensions of diversity”
Tree mortality in Forest and Biodiversity 2: a tree diversity experiment to understand the consequences of multiple dimensions of diversity and composition for long-term ecosystem function and resilience
The Forest and Biodiversity (FAB2) experiment uses native tree species in varying levels of species richness, phylogenetic diversity, and functional diversity planted in 100 m2 and 400 m2 plots at 1 m spacing, appropriate for testing long-term ecosystem consequences. FAB2 was designed and established in conjunction with a prior experiment (FAB1) in which the same set of twelve species was planted in 16 m2 plots at 0.5 m spacing. Both are adjacent to the BioDIV prairie-grassland diversity experiment, enabling comparative investigations of diversity and ecosystem function relationships between experimental grasslands and forests at different planting densities and plot sizes. This data package examines mortality in the first six years of the experiment.
FAB2_sapling_volume_2021-2022 in Forest and Biodiversity 2: a tree diversity experiment to understand the consequences of multiple dimensions of diversity and composition for long-term ecosystem function and resilience
The Forest and Biodiversity (FAB2) experiment uses native tree species in varying levels of species richness, phylogenetic diversity, and functional diversity planted in 100 m2 and 400 m2 plots at 1 m spacing, appropriate for testing long-term ecosystem consequences. FAB2 was designed and established in conjunction with a prior experiment (FAB1) in which the same set of twelve species was planted in 16 m2 plots at 0.5 m spacing. Both are adjacent to the BioDIV prairie-grassland diversity experiment, enabling comparative investigations of diversity and ecosystem function relationships between experimental grasslands and forests at different planting densities and plot sizes. This data package examines mortality in the first six years of the experiment.
fab2_allometry_2016-2022 in Forest and Biodiversity 2: a tree diversity experiment to understand the consequences of multiple dimensions of diversity and composition for long-term ecosystem function and resilience
The Forest and Biodiversity (FAB2) experiment uses native tree species in varying levels of species richness, phylogenetic diversity, and functional diversity planted in 100 m2 and 400 m2 plots at 1 m spacing, appropriate for testing long-term ecosystem consequences. FAB2 was designed and established in conjunction with a prior experiment (FAB1) in which the same set of twelve species was planted in 16 m2 plots at 0.5 m spacing. Both are adjacent to the BioDIV prairie-grassland diversity experiment, enabling comparative investigations of diversity and ecosystem function relationships between experimental grasslands and forests at different planting densities and plot sizes. This data package examines mortality in the first six years of the experiment.
Connecting the multiple dimensions of global soil fungal diversity
<p>How the multiple facets of soil fungal diversity vary worldwide remains virtually unknown, hindering the management of this essential species-rich group. By sequencing high-resolution DNA markers in over 4000 topsoil samples from natural and human-altered ecosystems across all continents, we illustrate the distributions and drivers of different levels of taxonomic and phylogenetic diversity of fungi and their ecological groups. We show the impact of precipitation and temperature interactions on fungal local species richness (alpha diversity) across different climates. Our findings reveal how temperature drives fungal compositional turnover (beta diversity) and phylogenetic diversity, linking them with regional species richness (gamma diversity). Our work integrates fungi into the principles of global biodiversity distribution and presents detailed maps for biodiversity conservation and modeling of global ecological processes.</p> <p><strong>### Data overview</strong></p> <p>These datasets contain comprehensive estimates of alpha, beta, and gamma diversity. The data are provided in two formats: TIFF (Tagged Image File Format) and GeoPackage formats, which are commonly used to store geospatially-referenced data.</p> <p><strong>Alpha Diversity</strong>:</p> <ul> <li>`<em>Alpha_S_</em>*` files: These files contain estimates of alpha diversity (local species diversity) for each grid cell of a raster file.</li> <li>`<em>Alpha_AOA_</em>*` files: These files outline the 'Area of Applicability' for the alpha diversity estimates.</li> <li>`<em>Alpha_Uncertainty_</em>*` files: These files contain data related to the uncertainty of the alpha diversity predictions. Uncertainty here represents the range or degree of error associated with the diversity estimates.</li> <li> `<em>Alpha_Hotspots_and_ProtectedAreas</em>` contains information on fungal diversity hotspots and their area under protection (based on IUCN classification). 'Hotspots' are areas with exceptionally high alpha diversity.</li> </ul> <p><strong>Beta Diversity</strong>:</p> <ul> <li>`<em>Beta_</em>*` files: These files include results of beta diversity analyses: maps of global compositional dissimilarity among soil fungal communities and maps of compositional turnover rate.</li> </ul> <p><strong>Other files</strong>:</p> <ul> <li>`<em>EcM_and_AM_GlobalDistribution</em>`: the global distribution of areas with high richness of ectomycorrhizal and arbuscular mycorrhizal fungi.</li> <li>`<em>Ecoregions_Alpha,Beta,Gamma_Diversities</em>`: estimates of alpha, beta, and gamma diversity at the level of ecoregion cf. Tedersoo et al., 2022 (DOI:10.1111/gcb.16398).</li> </ul> <p> </p> <p><strong>### Data description</strong></p> <p>Alpha diversity, which is a measure of local species richness (number of Operational Taxonomic Unit (OTU) representing distinct taxa, roughly corresponding to species level). Alpha diversity is represented by the residuals from a model adjusting for sequencing depth, with zero equating to the average OTU richness in the training data set.</p> <p><br> `<strong>Alpha_S_AllFungi_Consensus.tif</strong>`: This file provides consensus estimates for total fungal alpha diversity.<br> Within the file, there are two types of consensus estimates:</p> <ul> <li> <em>AvgW</em> - weighted consensus estimates for alpha diversity. The weighting takes into account both the area of applicability and the goodness-of-fit for the model used to generate the estimates.</li> <li> <em>Avg</em> - non-weighted consensus estimates for alpha diversity. Unlike <em>AvgW</em>, these estimates give equal weight to all models regardless of their goodness-of-fit or area of applicability.</li> </ul> <p><br> `<strong>Alpha_AOA_*</strong>`: Files containing Area of Applicability information:</p> <ul> <li> A raster value of '1' represents areas that are outside the Area of Applicability</li> <li> A raster value of '2' denotes areas that are inside the Area of Applicability</li> </ul> <p><br> In the files containing prediction uncertainties (`<strong>Alpha_Uncertainty_*</strong>`), two types of data are presented to quantify the amount of uncertainty in model predictions, each represented by a different band:</p> <ul> <li>The SD band represents the standard deviation of predictions based on different folds of cross-validation. A larger standard deviation indicates greater variability in the predictions.</li> <li>The IQR band represents the interquartile range (the difference between the upper and lower quartiles) of predictions. The wider the IQR, the greater variability in the predictions.</li> </ul> <p><br> `<strong>Alpha_Hotspots_and_ProtectedAreas.tif</strong>`: This file provides information on regions of exceptionally high species richness, referred to as 'hotspots', along with information about protected areas. Hotspots are identified as the top 2.5% quantiles of the richest grid cells on the map in terms of OTU richness.</p> <ul> <li><em>IUCN_1_4</em> - terrestrial protected areas that fall into categories I-IV, as classified by the International Union for Conservation of Nature (IUCN). These categories typically represent areas with high levels of protection, often prohibiting extractive and destructive activities to preserve biodiversity.</li> <li><em>IUCN_all</em> - all terrestrial protected areas as recorded in the World Database on Protected Areas (WDPA) database v.1.6. It includes a wider range of protected areas beyond the categories I-IV.</li> <li><em>All_Avg</em> - Hotspots of total fungal alpha diversity, based on the consensus map</li> <li><em>GSM_All</em> - Hotspots of total fungal alpha diversity, based on the GSMc dataset</li> <li><em>GSM_EcM</em> - Hotspots of ectomycorrhizal alpha diversity</li> <li><em>GSM_AM</em> - Hotspots of arbuscular mycorrhizal alpha diversity</li> <li><em>GSM_AgarNM</em> - Hotspots of non-EcM Agaricomycetes alpha diversity</li> <li><em>GSM_Mold</em> - Hotspots of mold alpha diversity</li> <li><em>GSM_Pathog</em> - Hotspots of opportunistic human parasitic fungal alpha diversity</li> <li><em>GSM_OHP</em> - Hotspots of putative pathogenic fungal alpha diversity</li> <li><em>GSM_Unicel</em> - Hotspots of unicellular, non-yeast fungal alpha diversity</li> <li><em>GSM_Yeast</em> - Hotspots of yeast alpha diversity</li> <li><em>GSMc_PD</em> - Hotspots of phylogenetic alpha diversity</li> <li><em>GSM_PDst</em> - Hotspots of phylogenetic dispersion</li> </ul> <p><br> `<strong>EcM_and_AM_GlobalDistribution.tif</strong>`: To illustrate the worldwide distribution of ectomycorrhizal (EcM) and arbuscular mycorrhizal (AM) fungi, we have categorized their richness into three distinct groups with low (1), medium (2), and high (3) alpha diversity. These categories have been encoded in the raster file using a bitcode system. Specifically, a value of '9' indicates that both EcM and AM fungal communities have low alpha diversity, while a value of '27' signifies that both groups of fungi are OTU-rich To assist with interpretation, a color legend has been provided in a separate QML style file (`<strong>EcM_and_AM_GlobalDistribution.qml</strong>`). This should be automatically recognized by geographic information system software, such as QGIS, to aid in visual analysis.</p> <p><br> `<strong>Beta_Taxonomic_AllFungi.tif</strong>` and `<strong>Beta_Phylogenetic_AllFungi.tif</strong>`: These files quantify the degree of difference in OTU composition of fungal communities. The measurements are based on the Generalized Dissimilarity Modelling (GDM) framework, as described by Mokany et al., 2022 (DOI:10.1111/geb.13459). Each file provides a different perspective on beta diversity: taxonomic (which is the change in species composition between different locations), and phylogenetic (the change in phylogenetic lineage composition between different locations). Each of these raster files contains three bands, with each band representing a scaled axis from a Principal Component Analysis (PCA) of the GDM-transformed environmental predictors.</p> <p><br> `<strong>Beta_LocalTurnover.tif</strong>`: This file contains estimates of local turnover in fungal communities composition estimated as the median expected compositional dissimilarity (taxonomic or phylogenetic) between each location and its closest neighbors within a 150 km radius. In addition, interquartile range (IQR) of dissimilarities is also provided.</p> <p> </p> <p>`<strong>Ecoregions_Alpha,Beta,Gamma_Diversities.gpkg</strong>`: Median alpha, beta, and gamma diversity estimates within ecoregions.</p> <ul> <li><em>Ecoregion</em> - Ecoregion name (cf. Tedersoo et al., 2022, DOI:10.1111/gcb.16398)</li> <li><em>area</em> - Ecoregion area, m<sup>2</sup></li> <li><em>Alpha_S_AllFungi_Consensus</em> - Richness of all fungi (S'<sub>tot</sub>), consensus map</li> <li><em>Alpha_S_AllFungi_GSMc</em> - Richness of all fungi (S'<sub>GSMc</sub>), based on GSMc dataset</li> <li><em>Alpha_S_EcM_GSMc</em> - Richness of ectomycorrhizal fungi (S'<sub>ecm</sub>)</li> <li><em>Alpha_S_AM_GSMc</em> - Richness of arbuscular mycorrhizal fungi (S'<sub>am</sub>)</li> <li><em>Alpha_S_NMA_GSMc</em> - Richness of non-EcM Agaricomycetes (S'<sub>nma</sub>)</li> <li><em>Alpha_S_Mold_GSMc</em> - Richness of molds (S'<sub>mold</sub>)</li> <li><em>Alpha_S_OHP_GSMc</em> - Richness of opportunistic human parasitic fungi (S'<sub>ohp</sub>)</li> <li><em>Alpha_S_Path_GSMc</em> - Richness of putative pathogenic fungi (S'<sub>path</sub>)</li> <li><em>Alpha_S_Ucel_GSMc</em> - Richness of unicellular, non-yeast fungi (S'<sub>ucel</sub>)</li> <li><em>Alpha_S_Yeast_GSMc</em> - Richness of yeasts (S'<sub>yeast</sub>)</li> <li><em>Alpha_SESPD_GSMc</em> - Phylogenetic dispersion of fungal communities (SES<sub>PD</sub>)</li> <li><em>Beta_Taxonomic_Median</em> - Median taxonomic dissimilarity of fungal communities (Simpson's index)</li> <li><em>Beta_Taxonomic_IQR</em> - Interquartile range of taxonomic dissimilarities of fungal communities</li> <li><em>Beta_Phylogenetic_Median</em> - Median phylogenetic dissimilarity of fungal communities</li> <li><em>Beta_Phylogenetic_IQR</em> - Interquartile range of phylogenetic dissimilarities of fungal communities</li> <li><em>Gamma_AllFungi</em> - Gamma diversity (regional species richness) for all fungi (G<sub>tot</sub>)</li> <li><em>Gamma_EcM</em> - Gamma diversity of ectomycorrhizal fungi (G<sub>ecm</sub>)</li> <li><em>Gamma_AM</em> - Gamma diversity of arbuscular mycorrhizal fungi (G<sub>am</sub>)</li> <li><em>Gamma_NMA</em> - Gamma diversity of non-EcM Agaricomycetes (G<sub>nma</sub>)</li> <li><em>Gamma_Mold</em> - Gamma diversity of molds (G<sub>mold</sub>)</li> <li><em>Gamma_Path</em> - Gamma diversity of opportunistic human parasitic fungi (G<sub>ohp</sub>)</li> <li><em>Gamma_OHP</em> - Gamma diversity of putative pathogenic fungi (G<sub>path</sub>)</li> <li><em>Gamma_Ucel</em> - Gamma diversity of unicellular, non-yeast fungi (G<sub>ucel</sub>)</li> <li><em>Gamma_Yeast</em> - Gamma diversity of yeasts (G<sub>yeast</sub>)</li> </ul> <p> </p> <p><strong>### Source code</strong></p> <p>The code used for data analysis and visualization of the main results of the study are available at GitHub:</p> <p><a href="https://github.com/Mycology-Microbiology-Center/Global_fungal_diversity">https://github.com/Mycology-Microbiology-Center/Global_fungal_diversity</a></p> <p> </p>
Multiple dimensions of phylogenetic diversity are needed to explain the complex aboveground-belowground diversity relationships
<p>The complex relationship between aboveground and belowground diversity and whether they act as surrogates for one another remains unresolved. Increasing evidence suggests that investigating phylogenetic diversity could provide valuable insights into the interplay between plants and soil microbes, but the proliferation of phylogenetic diversity metrics has hindered comparative studies and the identification of general patterns. To overcome this challenge, we implemented a multi-dimensional framework that classifies phylogenetic diversity metrics into three dimensions: richness, divergence, and regularity, each of which captures different ecological aspects of species differences. Then we applied this framework to investigate the relationship between above and belowground diversity in a subtropical forest in Eastern China. We found that phylogenetic diversity of plant and soil microbes, including bacteria and fungi, were more strongly correlated at the richness and regularity dimension compared with divergence dimension. Further analyses revealed that these observed correlation patterns can be attributed to the influence of soil total phosphorus content, which is the limiting factor of plant and microbial phylogenetic diversity at richness and regularity dimensions. Together, our study demonstrated the necessity of using a multi-dimensional approach to advance our understanding of the complex relationships between plant and soil microbial biodiversity.</p>
Multiple dimensions of phylogenetic diversity are needed to explain the complex aboveground-belowground diversity relationships
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Multiple dimensions of dietary diversity in large mammalian herbivores
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Shade-growing practices lessen the impact of coffee plantations on multiple dimensions of ant diversity
<p>1. Land use management influence changes in biodiversity beyond the targeted species. Management practices in coffee plantations have shifted from coffee growing below accompanying (shade) trees, to intensified monocultures in which coffee grows fully exposed to the sun. Anthropogenic disturbance causes changes in species composition relative to adjacent natural patches and reduces their biotic heterogeneity. Here, we assessed the impact of coffee plantation management practices on the taxonomical, phylogenetic, and functional composition of ant communities, an ecologically dominant group and crucial biological pest controller in these agroecosystems. We hypothesized that shade-grown coffee plantations would harbor ant communities similar to those of nearby forest patches, but dissimilar to those of intensified monocultures.</p> <p>2. We surveyed ant diversity in eight shade-grown coffee farms, eight intensive coffee monocultures and eight forest patches. We used a combination of active and passive sampling methods over two field campaigns spanning six months.</p> <p>3. Our results support our hypothesis for all diversity dimensions. Additionally, ant communities in intensified monocultures were taxonomically and functionally, but not phylogenetically, more homogeneous than those found in forest patches and shade-grown plantations.</p> <p>4. Synthesis and applications. Our findings support the idea that practices in shade-grown plantations buffer the impoverishment of multiple diversity dimensions after forest conversion. By assessing and integrating multiple biodiversity dimensions into management strategies, farmers and interested parties can minimize future biodiversity and ecosystem service loss.</p>
Data from: Multiple dimensions of bird beta diversity support that mountains are higher in the tropics
<p><b>Aim</b> We examine latitudinal effects of breeding bird taxonomic, phylogenetic and functional β-diversity (Tβ, Pβ and Fβ, respectively) along elevational gradients to test predictions derived from Janzen's (1967) classic ideas that tropical mountains represent stronger dispersal barriers than temperate mountains.</p> <p><b>Location</b> Global</p> <p><b>Taxon</b> Birds</p> <p><b>Methods</b> Using a global dataset from 46 mountains, we examine latitudinal patterns of Tβ, Pβ, and Fβ, and their components: β <sub>rich</sub> and β <sub>repl</sub>. For each mountain and each dimension of diversity we calculated (a) total β-diversity, (b) the steepness of distance decay patterns, and (c) within-mountain variability in pairwise β-diversity and regressed each one of these response variables against absolute latitude. We predicted that tropical montane biotas would have (1) overall higher Tβ, Pβ, and Fβ, (2) faster distance decay patterns and (3) higher within-mountain variability in pairwise β-diversity. Furthermore, we expected the richness component β <sub>rich</sub> to be more important in temperate mountains, and the replacement component β <sub>repl</sub> in tropical mountains.</p> <p><b>Results</b> Latitude had a negative effect on total β-diversity for all dimensions of diversity. Similarly, metrics of Tβ and Pβ mostly agree with our expectations, whereas Fβ showed contrasting results with steeper distance decay curves and higher within-mountain variability in temperate mountains. Overall, β <sub>rich</sub> was a more important component at high elevations in the tropics and across elevations in temperate mountains, and β <sub>repl </sub>more important in tropical low and mid-elevations.</p> <p><b>Main Conclusions</b> Our findings are consistent with tropical mountain assemblages containing species with narrow elevational distributions, low dispersal ability and potentially high allopatric speciation, resulting in high β-diversity across elevations. Contrasting results for Fβ indicate high niche packing in tropical assemblages, with most changes in functional diversity among assemblages involving species redundant in trait space. --</p>
Shade-growing practices lessen the impact of coffee plantations on multiple dimensions of ant diversity
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Structural and compositional dimensions of phytochemical diversity in the genus Piper reflect distinct ecological modes of action
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From the leaf to the community: distinct dimensions of phytochemical diversity shape plant-insect interactions within and among individual plants
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Data from: Multiple dimensions of bird beta diversity support that mountains are higher in the tropics
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Niche differentiation along multiple functional-trait dimensions contributes to high local diversity of Euphorbiaceae in a tropical tree assemblage
<p><span>Understanding the mechanisms that drive community assembly in species-rich tropical forest remains a fundamental challenge in ecology. Here, we integrated multivariate functional trait dimensions, phylogeny, and metabolomics to test fundamental predictions concerning the role of differentiation with respect to abiotic and biotic niche axes in the maintenance of high local diversity of woody plants in the Euphorbiaceae.</span></p> <p><span>We measured 40 functional traits related to resource acquisition, photosynthetic capacity, hydraulic efficiency, and secondary-metabolite profiles generated using untargeted metabolomics in all 26 Euphorbiaceae species in a 20-ha forest dynamics plot in tropical southwestern China. We examined the correlation structure of 40 traits using a trait networking approach. We coupled these traits with variation in soil nutrients, light environment, soil water content and herbivore pressure within the plot to assess niche differentiation in space. We compared phylogenetic signal among </span><span>multivariate trait dimensions and secondary metabolites to assess niche differentiation in evolutionary time.</span></p> <p><span>Network analysis revealed that a small number of traits with high network centrality reflected variation in ecological strategy among the Euphorbiaceae. Using these high-centrality traits, we observed significant functional turnover along environmental gradients defined by light, soil moisture, soil nutrients and leaf herbivory, respectively. Most resource utilization traits showed significant phylogenetic signal, whereas almost all defensive traits lacked phylogenetic signal, including species similarity with respect to plant secondary metabolites.</span></p> <p><span>Synthesis</span><span>.</span><span> </span><span>Our results suggest that resource-utilization traits and the habitat associations play a significant role in the </span><span>niche segregation</span><span> of co-occurring woody plants in the Euphorbiaceae. Secondary metabolites, however, may enhance diversity at a finer spatial scale by allowing closely related species with similar functional traits to partition biotic niche space within shared habitats in tropical</span><span> rainforest.</span></p>
Niche differentiation along multiple functional-trait dimensions contributes to high local diversity of Euphorbiaceae in a tropical tree assemblage
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Net N mineralization:Dimensions of Biodiversity - Genetic, Phylogenetic, Functional, and Remotely Sensed Diversity
Novel remote sensing methods for monitoring the Earth's biodiversity will be applied to experimental manipulations of plant diversity - allowing scientists to examine the linkages between plant biodiversity, soil microbe diversity and ecosystem function at multiple scales of spatial resolution. Specifically, we propose to link remotely sensed optical diversity to plant functional, phylogenetic and genotypic diversity aboveground and to net primary production (NPP), and soil properties and microbial processes belowground, as a basis for predicting ecosystem processes with remote sensing. Our central hypothesis is that i) biodiversity (genotypic, functional and phylogenetic diversity) at one trophic level (plants) drives genetic and functional diversity in other trophic levels (soil microbes) with consequences for ecosystem function and ii) that such diversity can be detected remotely at multiple scales of spatial resolution. We propose to test this hypotheses within the long-term prairie biodiversity experiment (e120 Big Bio), the newly established Forest and Biodiversity (e271 FAB 1) experiment, and the Biodiversity of Willows and Poplars (e277 BiWaP) experiment. We will measure optical properties of these plots at the leaf level, 1 m above the plant canopy and from aircraft. Leaf level sampling and percent cover estimates will be non-destructive. Biomass sampling in Big Bio will follow standard protocol for the long-term experiment. Biomass estimates in FAB and BiWaP will use non-destructive methods. Below ground sampling in BigBio will be taken within the clip strip for biomass harvest. The proposed research involves researchers at the University of Minnesota, the University of Alberta, the University of Nebraska Lincoln, the University of Wisconsin, and Appalachian State University.
Root biomass:Dimensions of Biodiversity - Genetic, Phylogenetic, Functional, and Remotely Sensed Diversity
Novel remote sensing methods for monitoring the Earth's biodiversity will be applied to experimental manipulations of plant diversity - allowing scientists to examine the linkages between plant biodiversity, soil microbe diversity and ecosystem function at multiple scales of spatial resolution. Specifically, we propose to link remotely sensed optical diversity to plant functional, phylogenetic and genotypic diversity aboveground and to net primary production (NPP), and soil properties and microbial processes belowground, as a basis for predicting ecosystem processes with remote sensing. Our central hypothesis is that i) biodiversity (genotypic, functional and phylogenetic diversity) at one trophic level (plants) drives genetic and functional diversity in other trophic levels (soil microbes) with consequences for ecosystem function and ii) that such diversity can be detected remotely at multiple scales of spatial resolution. We propose to test this hypotheses within the long-term prairie biodiversity experiment (e120 Big Bio), the newly established Forest and Biodiversity (e271 FAB 1) experiment, and the Biodiversity of Willows and Poplars (e277 BiWaP) experiment. We will measure optical properties of these plots at the leaf level, 1 m above the plant canopy and from aircraft. Leaf level sampling and percent cover estimates will be non-destructive. Biomass sampling in Big Bio will follow standard protocol for the long-term experiment. Biomass estimates in FAB and BiWaP will use non-destructive methods. Below ground sampling in BigBio will be taken within the clip strip for biomass harvest. The proposed research involves researchers at the University of Minnesota, the University of Alberta, the University of Nebraska Lincoln, the University of Wisconsin, and Appalachian State University.
Soil percent carbon and nitrogen:Dimensions of Biodiversity - Genetic, Phylogenetic, Functional, and Remotely Sensed Diversity
Novel remote sensing methods for monitoring the Earth's biodiversity will be applied to experimental manipulations of plant diversity - allowing scientists to examine the linkages between plant biodiversity, soil microbe diversity and ecosystem function at multiple scales of spatial resolution. Specifically, we propose to link remotely sensed optical diversity to plant functional, phylogenetic and genotypic diversity aboveground and to net primary production (NPP), and soil properties and microbial processes belowground, as a basis for predicting ecosystem processes with remote sensing. Our central hypothesis is that i) biodiversity (genotypic, functional and phylogenetic diversity) at one trophic level (plants) drives genetic and functional diversity in other trophic levels (soil microbes) with consequences for ecosystem function and ii) that such diversity can be detected remotely at multiple scales of spatial resolution. We propose to test this hypotheses within the long-term prairie biodiversity experiment (e120 Big Bio), the newly established Forest and Biodiversity (e271 FAB 1) experiment, and the Biodiversity of Willows and Poplars (e277 BiWaP) experiment. We will measure optical properties of these plots at the leaf level, 1 m above the plant canopy and from aircraft. Leaf level sampling and percent cover estimates will be non-destructive. Biomass sampling in Big Bio will follow standard protocol for the long-term experiment. Biomass estimates in FAB and BiWaP will use non-destructive methods. Below ground sampling in BigBio will be taken within the clip strip for biomass harvest. The proposed research involves researchers at the University of Minnesota, the University of Alberta, the University of Nebraska Lincoln, the University of Wisconsin, and Appalachian State University.
Soil pH:Dimensions of Biodiversity - Genetic, Phylogenetic, Functional, and Remotely Sensed Diversity
Novel remote sensing methods for monitoring the Earth's biodiversity will be applied to experimental manipulations of plant diversity - allowing scientists to examine the linkages between plant biodiversity, soil microbe diversity and ecosystem function at multiple scales of spatial resolution. Specifically, we propose to link remotely sensed optical diversity to plant functional, phylogenetic and genotypic diversity aboveground and to net primary production (NPP), and soil properties and microbial processes belowground, as a basis for predicting ecosystem processes with remote sensing. Our central hypothesis is that i) biodiversity (genotypic, functional and phylogenetic diversity) at one trophic level (plants) drives genetic and functional diversity in other trophic levels (soil microbes) with consequences for ecosystem function and ii) that such diversity can be detected remotely at multiple scales of spatial resolution. We propose to test this hypotheses within the long-term prairie biodiversity experiment (e120 Big Bio), the newly established Forest and Biodiversity (e271 FAB 1) experiment, and the Biodiversity of Willows and Poplars (e277 BiWaP) experiment. We will measure optical properties of these plots at the leaf level, 1 m above the plant canopy and from aircraft. Leaf level sampling and percent cover estimates will be non-destructive. Biomass sampling in Big Bio will follow standard protocol for the long-term experiment. Biomass estimates in FAB and BiWaP will use non-destructive methods. Below ground sampling in BigBio will be taken within the clip strip for biomass harvest. The proposed research involves researchers at the University of Minnesota, the University of Alberta, the University of Nebraska Lincoln, the University of Wisconsin, and Appalachian State University.
Soil microbial respiration rate:Dimensions of Biodiversity - Genetic, Phylogenetic, Functional, and Remotely Sensed Diversity
Novel remote sensing methods for monitoring the Earth's biodiversity will be applied to experimental manipulations of plant diversity - allowing scientists to examine the linkages between plant biodiversity, soil microbe diversity and ecosystem function at multiple scales of spatial resolution. Specifically, we propose to link remotely sensed optical diversity to plant functional, phylogenetic and genotypic diversity aboveground and to net primary production (NPP), and soil properties and microbial processes belowground, as a basis for predicting ecosystem processes with remote sensing. Our central hypothesis is that i) biodiversity (genotypic, functional and phylogenetic diversity) at one trophic level (plants) drives genetic and functional diversity in other trophic levels (soil microbes) with consequences for ecosystem function and ii) that such diversity can be detected remotely at multiple scales of spatial resolution. We propose to test this hypotheses within the long-term prairie biodiversity experiment (e120 Big Bio), the newly established Forest and Biodiversity (e271 FAB 1) experiment, and the Biodiversity of Willows and Poplars (e277 BiWaP) experiment. We will measure optical properties of these plots at the leaf level, 1 m above the plant canopy and from aircraft. Leaf level sampling and percent cover estimates will be non-destructive. Biomass sampling in Big Bio will follow standard protocol for the long-term experiment. Biomass estimates in FAB and BiWaP will use non-destructive methods. Below ground sampling in BigBio will be taken within the clip strip for biomass harvest. The proposed research involves researchers at the University of Minnesota, the University of Alberta, the University of Nebraska Lincoln, the University of Wisconsin, and Appalachian State University.
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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.