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539 results for “disentangling”
Data from: Disentangling elevational richness: a multi-scale hierarchical Bayesian occupancy model of Colorado ant communities
Understanding the forces that shape the distribution of biodiversity across spatial scales is central in ecology and critical to effective conservation. To assess effects of possible richness drivers, we sampled ant communities on four elevational transects across two mountain ranges in Colorado, USA, with seven or eight sites on each transect and twenty repeatedly sampled pitfall trap pairs at each site each for a total of 90 days. With a multi-scale hierarchical Bayesian community occupancy model, we simultaneously evaluated the effects of temperature, productivity, area, habitat diversity, vegetation structure, and temperature variability on ant richness at two spatial scales, quantifying detection error and genus-level phylogenetic effects. We fit the model with data from one mountain range and tested predictive ability with data from the other mountain range. In total, we detected 105 ant species, and richness peaked at intermediate elevations on each transect. Species-specific thermal preferences drove richness at each elevation with marginal effects of site-scale productivity. Trap-scale richness was primarily influenced by elevation-scale variables along with a negative impact of canopy cover. Soil diversity had a marginal negative effect while daily temperature variation had a marginal positive effect. We detected no impact of area, land cover diversity, trap-scale productivity, or tree density. While phylogenetic relationships among genera had little influence, congeners tended to respond similarly. The hierarchical model, trained on data from the first mountain range, predicted the trends on the second mountain range better than multiple regression, reducing root mean squared error up to 65%. Compared to a more standard approach, this modeling framework better predicts patterns on a novel mountain range and provides a nuanced, detailed evaluation of ant communities at two spatial scales.
Disentangling the effects of methanogen community and environment on peatland greenhouse gas production by a reciprocal transplant experiment
<p>1. Northern peatlands consist of a mosaic of peatland types that vary spatially and temporally and differ in their methane (CH<sub>4</sub>) production. Microbial community composition and environment both potentially control the processes that release carbon from anoxic peat either as CH<sub>4</sub> or carbon dioxide (CO<sub>2</sub>), a less potent greenhouse gas than CH<sub>4</sub>. However, the respective roles of these controls remain unclear, which prevents incorporating microbes in the predictions of peatland CH<sub>4</sub> emissions.</p> <p>2. Here, a reciprocal transplant experiment was carried out to separate the influences of microbial community and environment in CH<sub>4</sub> and anaerobic CO<sub>2</sub> production. Peat from an acidic <i>Sphagnum</i> bog and a sedge fen with higher pH was enclosed in membrane bags with a pore size of 0.2 µm, preventing microbial colonization from the outside, and transplanted in the field for two months.</p> <p>3. Potential CH<sub>4</sub> production was primarily controlled by the environment. The conditions in the bog suppressed the initially higher activity of fen methanogens and reduced CH<sub>4</sub> production by 79%. Against expectations, the inhibition was not specific to acetate-using Methanotrichaceae. Reciprocal transplantation favoured Methanosarcinaceae and potentially methylotrophic methanogenesis in general. Bog methanogens, mostly hydrogenotrophic Methanoregulaceae, retained their community structure and activity in the fen with a slight increase (+37%) in CH<sub>4</sub> production.</p> <p>4. Anaerobic CO<sub>2</sub> production was controlled by both the microbial community and the environment. Transplantation led to increased CO<sub>2</sub> production in both bog (+50%) and fen peat (+57%) with distinct bacterial community, showing that the new environment directed more carbon to other anaerobic processes than methanogenesis. 5. Taken together, these results relate differences in CH<sub>4</sub> production of bogs and fens to ecophysiology of specific methanogen groups. The sensitiveness of fen methanogens to the acidic conditions in <i>Sphagnum</i> bogs can help explain the decrease of CH<sub>4</sub> emission in the typical boreal peatland succession from young fens to older bogs. Increase in anaerobic CO<sub>2</sub> vs. CH<sub>4</sub> production with transplantation shows that disturbances of boreal peatlands can activate poorly defined pathways of anaerobic decomposition.</p>
Data from: Disentangling evolutionary, environmental and morphological drivers of plant anatomical adaptations to drought and cold in Himalayan graminoids
Understanding what determine plants ability to survive drought and cold is crucial for predicting how plants may respond to ongoing climate change. Plant survival strategies are usually characterized by morphological and physiological adaptations, while their underlying anatomical settings are largely unknown. Woody angiosperms and herbaceous dicots have repeatedly evolved small water transporting conduits and large storage parenchyma tissues at colder or drier places to cope with freezing- and drought-induced damages. However, whether these adaptations are also valid for graminoids remains unclear. Here we show that stem anatomical variations in grasses, sedges and rushes dominating in western Himalayan grasslands are driven by elevation and soil moisture via control over aboveground plant stature and belowground clonal growth, while phylogenetic constraints have only a weak effect. Phylogenetic comparative analyses controlling for confounding factors showed that the elevation-related cooling controls the conductive system through reduced vessel diameter and extended assimilatory and storage tissues with more chlorenchyma and less sclerenchyma around vessels. The soil moisture deficit, on the other hand, determines stabilization structures by promoting short-rhizomatous turf graminoids with hollow stems, thicker epidermis and deep adventitious roots in dry steppes and semi-deserts. Saline wetlands and moist alpine pastures promote long-rhizomatous short-stature plants with lower need for mechanical support (absence of hollow stem) and exposure to high evaporative forcing (thinner epidermis). Observed trends of decreasing vessel sizes and lignification rate with elevation supports the existing knowledge that narrower vessels and extensive parenchyma assist plants to grow in cold environments by avoiding freezing-induced cavitation. Our results bring novel information on ecological drivers influencing the evolution of anatomical adaptations in high mountain graminoids. Distinct grassland types, covering elevations from 2650 to 6150 m, harbor unrelated species with different evolutionary histories that have converged towards similar anatomical structures.
Disentangling drivers of small mammal diversity in a highly fragmented forest system
<p class="Standard">The Atlantic Forest is the second most diverse forest system in South America and only a fraction of its original distribution remains. In this study, we aim to use robust datasets of small mammals along the entire forest system to disentangle the main drivers for diversity along this gradient. More specifically we aim to disentangle if deforestation (recent), biogeographical variables, including 19 bioclimatic variables (historic), or historical trapping bias best describe patterns of taxonomic, functional, and phylogenetic diversities using small mammal assembles, from northeastern Brazil to eastern Paraguay. For that, we applied regression tree analyses to determine what environmental variables best describe each of the dimensions of diversity. Additionally, we implemented polynomial regression to test non-linear relationships between biodiversity metrics and patch size. We found that patterns of overall taxonomic, functional and phylogenetic diversities; rodent taxonomic diversity; and marsupial functional diversity were better explained by temperature variables. Meanwhile, marsupial taxonomic and phylogenetic diversities; and rodent functional and phylogenetic diversities were best explained by precipitation variables. Furthermore, patch area, trapping, and latitude were never the best descriptors for any of the diversity dimensions. Although all dimensions of biodiversity are correlated, they have unique information and should be considered individually to better understand biodiversity and inform conservation strategies. We found that fragmentation is impactful at a local scale and becomes less important at a biogeographical scale. Therefore, climatic variables drove biogeographical faunal patterns for all clades, probably reflecting important historical assembly process at large spatial scales.</p>
Disentangling the assembly mechanisms of ant cuticular bacterial communities of two Amazonian ant species sharing a common arboreal nest
<p>Bacteria living on the cuticle of ants are generally studied for their protective role against pathogens, especially in the clade of fungus-growing ants. However, little is known of the diversity of cuticular bacteria in other ant host species, as well as of the mechanisms leading to the composition of these communities. Here, we used 16S rRNA gene amplicon sequencing to study the influence of host species, species interactions, and the pool of bacteria from the environment on the assembly of cuticular bacterial communities on two phylogenetically distant Amazonian ant species that frequently nest together inside the roots system of epiphytic plant<i>s</i>, <i>Camponotus femoratus</i> and <i>Crematogaster levior</i>. Our results show that 1) the vast majority of the bacterial community on the cuticle is shared with the nest, suggesting that most bacteria on the cuticle are acquired through environmental acquisition, 2) 5.2% and 2.0% OTUs are respectively specific to <i>Camponotus femoratus</i> and <i>Crematogaster levior</i>, likely representing their respective core cuticular bacterial community, and 3) 3.6% of OTUs are shared between the two ant species. Additionally, mass spectrometry metabolomics analysis of metabolites on the cuticle of ants, which excludes the detection of cuticular hydrocarbons produced by the host, were conducted to evaluate correlations among bacterial OTUs and m/z ion mass. Although some positive and negative correlations are found, the cuticular chemical composition was weakly species specific which supports that cuticular bacterial communities are prominently environmentally acquired. Overall, our results suggest that the environment is the dominant source of bacteria found on the cuticle of ants.</p>
Disentangling the mechanisms underpinning disturbance-mediated invasion data
<p><span>Disturbances can play a major role in biological invasions: by destroying biomass, they alter habitat and resource abundances. Previous field studies suggest that disturbance-mediated invader success is a consequence of resource influxes, but the importance of other potential covarying causes, notably the opening up of habitats, have yet to be directly tested. Using experimental populations of the bacterium <i>Pseudomonas fluorescens </i>we determined the relative importance of disturbance-mediated habitat opening and resource influxes, plus any interaction between them, for invader success of two ecologically distinct morphotypes. Resource addition increased invasibility, while habitat opening had little impact or interacted with resource addition. Both invaders behaved similarly, despite occupying different ecological niches in the microcosms. Treatment also affected the composition of the resident population, which further affected invader success. Our results provide experimental support for the observation that resource input is a key mechanism through which disturbance increases invasibility. </span></p>
Data from: Disentangling competitive versus climatic drivers of tropical forest mortality
1. Tropical forest mortality is controlled by biotic and abiotic processes, but how these processes interact to determine forest structure is not well understood. Using long-term demography data from permanent forest plots at the Paracou Tropical Forest Research Station in French Guiana, we analyzed the relative influence of competition and climate on tree mortality. We found that self-thinning is evident at the stand level, and is associated with clumped mortality at smaller scales (< 2 m) and regular spacing of living trees at intermediate (2.5-7.5 m) scales. A competition index based on spatial clustering of dead trees was used to build predictive mortality models, which also accounted for climate interactions. 2. The model that most closely fitted observations included both the competition index and climatic variables, with climate-only and competition-only models performing worse than the full model. There was strong evidence for size-specific mortality, with highest mortality for small and very large trees, as well as sensitivity of trees to drought, especially when temperatures were high, and when soils were water saturated. The effect of the competition index was more complex than expected a priori: a higher CI index was associated with lower mortality odds, which we hypothesize is caused by gap-phase dynamics, but there was also evidence for competition-induced mortality at very high index values. 3. The strong signature of competition as a control over mortality at the stand and individual scales confirms that it plays a very important role in determining tropical forest structure. The complexity of the competition-mortality relationship and its interaction with climate indicates that a thorough consideration of the scale of analysis is needed when inferring the role of competition in tropical forests, but demonstrates that climate-only mortality models can be significantly improved by including competition effects, even when ignoring species-specific effects. 4. Synthesis Empirical models such as the one developed here can help constrain and improve process-based vegetation models, serving both as a benchmark and as a means to disentangle mortality processes. Tropical ecosystem dynamic models would benefit greatly from explicitly considering the role of competition in stand development and self-thinning while modeling demography, as well as its interaction with climate.
Data and code from: Disentangling the drivers of decadal body size decline in an insect population
<p>While climate warming is widely predicted to reduce body size of ectotherms, evidence for this trend is mixed. Body size depends not only on temperature but also on other factors, such as food quality and intraspecific competition. Because temperature trends or other long-term environmental factors may affect population size and food sources, attributing trends in average body size to temperature requires the separation of potentially confounding effects. We evaluated trends in the body size of the midge <em>Tanytarsus gracilentus</em> and potential drivers (water temperature, population size, and food quality) between 1977 and 2015 at Lake Mývatn, Iceland. Although temperatures increased at Mývatn over this period, there was only a slight (non-significant) decrease in midge adult body size, contrary to theoretical expectations. Using a state-space model including multiple predictors, body size was negatively associated with both water temperature and midge population abundance, and it was positively associated with <sup>13</sup>C enrichment of midges (an indicator of favorable food conditions). The magnitude of these effects were similar, such that simultaneous changes in temperature, abundance, and carbon stable isotopic signature could counteract each other in the long-term body size trend. Our results illustrate how multiple factors, all of which could be influenced by global change, interact to affect average ectotherm body size.</p>
Disentangling effects of climate and land use on biodiversity and ecosystem services – a multi-scale experimental design
<p>1. Climate and land-use change are key drivers of environmental degradation in the Anthropocene, but too little is known about their interactive effects on biodiversity and ecosystem services. Long-term data on biodiversity trends are currently lacking. Furthermore, previous ecological studies have rarely considered climate and land use in a joint design, did not achieve variable independence or lost statistical power by not covering the full range of environmental gradients.</p> <p>2. Here, we introduce a multi-scale space-for-time study design to disentangle effects of climate and land use on biodiversity and ecosystem services. The site selection approach coupled extensive GIS-based exploration and correlation heatmaps with a crossed and nested design covering regional, landscape and local scales. Its implementation in Bavaria (Germany) resulted in a set of study plots that maximize the potential range and independence of environmental variables at different spatial scales.</p> <p>3. Stratifying the state of Bavaria into five climate zones (reference period 1981–2010) and three prevailing land-use types, i.e. near-natural, agriculture and urban, resulted in 60 study regions (5.8x5.8 km quadrants) covering a mean annual temperature gradient of 5.6–9.8 °C and a spatial extent of ~310x310 km. Within these regions, we nested 180 study plots located in contrasting local land-use types, i.e. forests, grasslands, arable land or settlement (local climate gradient 4.5–10 °C). This approach achieved low correlations between climate and land use (proportional cover) at the regional and landscape scale with |r≤0.33| and |r≤0.29|, respectively. Furthermore, using correlation heatmaps for local plot selection reduced potentially confounding relationships between landscape composition and configuration for plots located in forests, arable land and settlements.</p> <p>4. The suggested design expands upon previous research in covering a significant range of environmental gradients and including a diversity of dominant land-use types at different scales within different climatic contexts. It allows independent assessment of the relative contribution of multi-scale climate and land use on biodiversity and ecosystem services. Understanding potential interdependencies among global change drivers is essential to develop effective restoration and mitigation strategies against biodiversity decline, especially in expectation of future climatic changes. Importantly, this study also provides a baseline for long-term ecological monitoring programs.</p>
Dataset to study "Disentangling ecosystem services perceptions from blue infrastructure around a rapidly expanding megacity"
<p>This dataset includes the raw data of a survey of 536 local residents along two rural-urban gradients around Bengaluru, India. The dataset sheet presents respondents' socio-demographic characteristics (village, village stratum, gender, age education, religion, length of residence, caste, occupation). It then displays Likert-scale answers, ranging from 1 ("not important" to 5 ("very important"), on agreement about the importance of water-filled and dry lakes (shown on photographs) for the provision of the respective ecosystem services and disservices, based on their livelihood needs and experiences. It then shows the answers to open questions on challenges and management options regarding lakes. The complete method is described in: Plieninger, T., Thapa, P., Bhaskar, D., Nagendra, H., Torralba, M., & Zoderer, B. M. (2022): Disentangling ecosystem services perceptions from blue infrastructure around a rapidly expanding megacity. Landscape and Urban Planning, in press.</p>
Data from: Towards a better ecological understanding of metacommunity stability: A multiscale framework to disentangle population variability and synchrony effects
<p>1. Despite great progress in our understanding of the mechanisms governing ecosystem stability in local communities, we still lack knowledge at a larger spatial scale. Studying the stability of metacommunities requires assessing the temporal stability and synchrony of populations across space and organizational levels. Previous attempts to disentangle these effects have provided limited ecological interpretations, and conceptual improvements are needed to identify the underlying ecological processes.</p> <p>2. We propose an extended framework aiming at disentangling simultaneously the relative effects of population stability and different types of synchronies on metacommunity stability. We adapted previous methods of decomposing stability into a new set of indices associated with clearer ecological hypotheses. Particularly, we provide synchrony indices that are not affected by statistical properties of the metacommunity but focus on species responses to environment, demography, and interactions. We applied this framework to a unique dataset describing the sorted biomass of individual plant populations, across 12 communities of a species-rich meadow, and for 16 years. The communities were sampled in different treatments of fertilization and dominant removal to evaluate the effect of environmental heterogeneity on stability.</p> <p>3. We found higher stability at a larger spatial scale, mainly due to statistical averaging (portfolio effect). The variability of individual populations was an important determinant of the stability of the whole metacommunity. Consistent with the hypothesis of a common response to environmental conditions, we found that the fluctuations of populations were mostly synchronized (within and between species) at a large spatial scale and tended to destabilize the metacommunity. On the other hand, opposite fluctuations (anti-synchrony) between populations occurred at the local scale, probably due to local species interactions.</p> <p>4. Synthesis Our framework appears as a powerful tool to test how ecological processes occurring simultaneously at different spatial and organizational scales affect the stability of metacommunities. This study advances our ecological understanding of the processes underlying the stability of species-rich environments. --</p>
Disentangling the impact of event- and annual-scale precipitation extremes on critical-zone hydrology in semiarid loess: A case study in apple tree plantation
<p>The dataset is the basic data of the author's paper ' Disentangling the impact of event-and annual-scale precipitation extremes on critical-zone hydrology in semiarid loess - a case study in apple tree plantation '. The main content of this paper is to study the hydrological effect of extreme precipitation on the critical area of semi-arid loess. Taking apple plantation as an example, the data set includes the soil moisture and soil temperature data monitored in the field and the apple tree transpiration data. The measured data are used to calibrate and verify the model used in this paper. The water vapor flux, apple tree evapotranspiration and soil leakage data of the simulated soil profile are also included to analyze the hydrological effect of extreme precipitation on the critical area of loess.</p>
Disentangling the interrelated abiotic and biotic pathways linking landscape composition and crop production
<p><span>Landscape composition and its related functional agrobiodiversity (FAB) was severely simplified during the last decades. As landscape composition is expected to influence the interrelated microclimate and arthropod community at different scales, this simplification might have led to a decline in multiple agro-ecosystem services, with potential impacts for the growth of crops with different demands from the environment. </span></p> <p><span>To study landscape-scale effects on multi-crop yield and herbivory in combination with its potential drivers, including functional arthropod community and microclimate, we used standardised 1 m² mini-gardens planted with ten different vegetable crops as phytometers. The gardens were installed at locations varying in surrounding landscape composition and </span><span>the vegetables were selected to have contrasting requirements in terms of growing conditions, pollination services, and susceptibility to pests. Monitoring of the mini-gardens was performed in 2018 and 2019 in Flanders (Belgium). </span></p> <p><span>We found no relationship between landscape composition in a 500 meter radius and crop yield. Considering possible mechanisms, we found that an increasing share of woody vegetation (> 3 m high) in the surrounding landscape is important to buffer the temperature and soil moisture variation in the mini-gardens. The share of agricultural land use and urban green (< 3 m high) is, respectively, positively and negatively related with the activity-density of natural enemies and pollinators. The growth of different crops responded differently to higher temperature ranges and we found no relation between natural enemies and herbivory. In conclusion, these abiotic and biotic pathways did not cause an overall relationship between landscape composition and yield.</span></p>
Data from: Disentangling direct from indirect effects of habitat disturbance on multiple components of biodiversity
<p><span>Human habitat disturbance affects both species diversity and intraspecific genetic diversity, leading to correlations between these two components of biodiversity</span><span> </span><span>(termed species - genetic diversity correlation, SGDC). However, whether</span><span> </span><span>SGDC predictions extend to host-associated communities, such as the intestinal parasite and gut microbial diversity, remains largely unexplored.</span><span> </span><span>Additionally, the role of dominant generalist species is often neglected despite their importance in shaping the environment experienced by other members of the ecological community, and their role as source, reservoir and vector of zoonotic diseases. New analytical approaches (e.g., structural equation modelling, SEM) can be used to assess SGDC relationships and distinguish among direct and indirect effects of habitat characteristics and disturbance on the various components of biodiversity</span><span>.</span></p> <p><span>With six concrete and biologically sound models in mind, we collected habitat characteristics of 22 study sites from four distinct landscapes located</span><span> </span><span>in central Panama. Each landscape differed in the degree of human disturbance and fragmentation measured by several quantitative variables, such as canopy cover, canopy height and understory density.</span><span> </span><span>In terms of biodiversity, we estimated on the one hand, 1) small mammal species diversity, and, on the other hand, 2) genome-wide diversity, 3) intestinal parasite diversity and 4) gut microbial heterogeneity of the most dominant generalist species (Tome's spiny rat, <em>Proechimys semispinosus</em>). We used</span><span> </span><span>SEMs to assess the links between habitat characteristics and biological diversity measures.</span></p> <p><span>The best supported SEM suggested that habitat characteristics directly and positively affect the richness of small mammals, the genetic diversity of <em>P. semispinosus</em> and its gut microbial heterogeneity. Habitat characteristics did not, however, directly impact intestinal parasite diversity.</span><span> </span><span>We</span><span> also </span><span>detected indirect, positive effects of habitat characteristics on both host-associated assemblages via small mammal richness. For microbes, this is likely linked to cross species transmission, particularly in shared and/or anthropogenically altered habitats, whereas host diversity mitigates parasite infections. The SEM revealed an additional indirect but negative effect on </span><span>intestinal</span><span> parasite diversity via host genetic diversity.</span></p> <p><span>Our study </span><span>showcases that habitat alterations not only affect species diversity and host genetic diversity in parallel, but also species diversity of host-associated assemblages. The impacts from </span><span>human disturbance are therefore expected to ripple through entire ecosystems with far reaching effects felt even by generalist species.</span></p>
Proccessed Data for the Pipelines of the Project "Multiomics and quantitative modelling disentangle diet, host, and microbiota contributions to the host metabolome"
<p><strong>Proccessed and Input Data for the Pipelines of the Project "Multiomics and quantitative modelling disentangle diet, host, and microbiota contributions to the host metabolome"</strong></p> <p>-----------------------------------------------------------------------------------------------------</p> <p>Contents:</p> <p>-----------------------------------------------------------------------------------------------------</p> <p>Folder /ProcessedData/metabolomics/ contains processed metabolomics data from the project:</p> <p>/metabolomics/metabolites_allions_combined_norm_intensity.csv - file containing normalized intensities of ions detected across tissues with six measurement methods.<br> /metabolomics/metabolites_allions_combined_formulas_with_metabolite_filters_spatial100clusters_with_mean.csv - file containing metabolite attribution to spatial clusters and mean intensity values across tissues and conditions.</p> <p>Other files are described in README_ProcessedData.md.</p> <p>-----------------------------------------------------------------------------------------------------</p> <p>Folder /ProcessedData/sequencing/ contains raw and normalized counts of metagenomics and metatransriptomics data mapped to bacterial genomes.</p> <p>Folder /ProccessedData/util/ contains files used for data preprocessing and attribution to chemical classes and pathways.</p> <p>Folder /ProcessedData/example_output/ contains example output of the pipelines:</p> <p>/output/model_results_SMOOTH_raw_2LIcoefHost1LIcoefbact_allions.csv - file containing estimated model parameters (intestinal flux and metabolic flux values) for the forward problem for metabolomics measurements in the GIT.<br> /output/model_results_SMOOTH_normbyabsmax_reciprocal_problem_allions.csv - file containing estimated model parameters for the reverse problem (metabolite intensities) for the parameters estimated with the forward problem.<br> /output/model_results_SMOOTH_normbyabsmax_2LIcoefHost1LIcoefbact_allions.csv - file containing estimated model parameters (intestinal flux and metabolic flux values) for the forward problem for metabolomics measurements in the GIT, normalized by absolute maximum value.<br> /output/model_results_SMOOTH_normbyabsmax_ONLYMETCOEF_2LIcoefHost1LIcoefbact_allions.csv - file containing estimated model parameters (only metabolic flux values) for the forward problem for metabolomics measurements in the GIT, normalized by absolute maximum value.<br> /output/table_hierarchical_clustering_groups.csv - file containing attribution of the annotated metabolites to groups according to hierarchical clustering of the normalized model parameters.<br> /output/cgo_clustergrams_of_model_coefficients.mat - matlab object containing clustergram of the normalized model parameters and manually derived sub-clustergrams corresponding to different largest parameter values.</p> <p>Description of other files is provided in the file README_ProcessedData.md.</p> <p>-----------------------------------------------------------------------------------------------------</p> <p>Folder /InputData/ contains HMDB and KEGG tables used for metabolite annotations and chemical group analysis.</p> <p>Folder InputData_KEGGreaction_path contains matlab files with metabolite-metabolite paths calculated from KEGG reaction-pair information (Each matrix contains a subset of paths). These files are used by the script workflow_extract_keggECpathes_for_SPpairs_final.m.</p> <p>Folder InputData_metabolomics_data contains raw metabolomics data from six methods (three LC columns: C08, C18 and HILIC, and positive and negative acquisition modes) and file tissue_weights.txt with tissue weight information used for normalization.</p> <p>Folder InputData_sequencing_data contains folders ballgown_DNA and ballgown_RNA with results of metagenomic and metatranscriptomic data analysis (raw counts, GetMM normalized counts, EdgeR and DeSeq2 analysis). </p> <p>Description of folders is provided in the file readme_InputData.md.</p> <p>-----------------------------------------------------------------------------------------------------</p>
Reciprocal bark exchange helps to disentangle tree species dependent bark and wood trait effects on invertebrate diversity
<p>1. Previous studies showed that bark cover at early-decay stage had profound control on the invertebrate assemblages of bark and wood, with possible consequence for the decomposition process. However, previous experimental designs could not disentangle how bark versus wood traits affect the invertebrate assemblage process in bark and/or wood separately because wood traits of different tree species may vary independently from bark traits. Furthermore, we do not know whether such tree species specific bark trait effects are still influential at mid-decay stage.</p> <p>2. To unravel whether and how bark and wood traits influence invertebrate communities in tree logs at mid-decay stage, we introduce reciprocal bark transplantation within pairs of different tree species as a new method. We applied this method to two pairs of phylogenetically contrasting species of gymnosperms (pair I: Araucaria araucana and Cryptomeria japonica, pair II: Picea abies and Thuja plicata) and another gymnosperm (Chamaecyparis lawsoniana) set as disturbance control to test for potential bark manipulation artefacts on invertebrate community composition.</p> <p>3. Our bark exchange experiment revealed that both bark and wood host abundant and divergent subsets of invertebrates on mid-decay logs of different tree species. We further documented that the invertebrate community composition was predominantly shaped by the traits of host tissue per se, while also being significantly but less strongly affected by the traits of the other tissue, i.e. the adjacent bark or wood. Our results indicated that bark trait effects faded with time and how long bark trait effects persist greatly depends on bark thickness.</p> <p>4. Synthesis. Our study suggests that maintaining deadwood heterogeneity related to variation between tree species, and to bark versus wood, is important for nursing a large biodiversity of invertebrates. Combined with bark removal methodology, our bark exchange method can be further extended to more decay stages and more forest biomes to track bark trait effects and bark induced priority effects on deadwood decomposition, and its associated invertebrate and microbial communities.</p>
Whole genome analyses disentangle reticulate evolution of primroses in a biodiversity hotspot
<p>1. Biodiversity hotspots<span>, such as the Caucasus mountains,</span> provide unprecedented opportunities for understanding the evolutionary processes that shape species diversity and richness. <span>Therefore, w</span>e investigate<span>d</span> the evolution of <em>Primula</em> sect. <em>Primula</em>, a clade with a high degree of endemism in the Caucasus.</p> <p>2. We performed phylogenetic and network analyses of whole-genome resequencing data from the entire nuclear genome, the entire chloroplast genome, and the entire heterostyly supergene. The different characteristics of the genomic partitions and the resulting phylogenetic incongruences enabled us to disentangle evolutionary histories resulting from tokogenetic versus cladogenetic processes. We provide the first phylogeny inferred from the heterostyly supergene <span>that includes</span> all species of <em>Primula</em> sect. <em>Primula</em>.</p> <p>3. Our results identified recurrent admixture at deep nodes between lineages in the Caucasus as the cause of non-monophyly in <em>Primula</em>. Biogeographic analyses support the "out-of-the-Caucasus" hypothesis, emphasizing the importance of this hotspot as a cradle for biodiversity.</p> <p>4. Our findings provide novel insights into causal processes of phylogenetic discordance, demonstrating that genome-wide analyses from partitions with contrasting genetic characteristics and broad geographic sampling are crucial for disentangling the diversification of species-rich clades in biodiversity hotspots.</p>
Data from: Disentangling the variability of symbiotic nitrogen fixation rate and the controlling factors
<p>Symbiotic nitrogen (N) fixation (SNF), replenishing bioavailable N for terrestrial ecosystems, exerts decisive roles in N cycling and gross primary production. Nevertheless, it remains unclear what determines the variability of SNF rate, which retards the accurate prediction for global N fixation in earth system models. This study synthesized 1230 isotopic observations to elucidate the governing factors underlying the variations of SNF rate. The SNF rates varied significantly from 3.69 to 12.54 g N m<sup>-2</sup> yr<sup>-1</sup> across host plant taxa. The traits of host plant (e.g., biomass characteristics and taxa) far outweighed soil properties and climatic factors in explaining the variations of SNF rate, accounting for 79.0% of total relative importance. Furthermore, annual SNF yield contributed to more than half of N uptake for host plants, which was consistent across different ecosystem types. This study highlights that the biotic factors, especially host plant traits (e.g., biomass characteristics and taxa), play overriding roles in determining SNF rate compared with soil properties. The suite of parameters for SNF lend support to improve N fixation module in earth system models that can provide more confidence in predicting bioavailable N changes in terrestrial ecosystems.</p>
Can ingredients based forecasting be learned? Disentangling a random forest's severe weather predictions
<p>Machine learning (ML)-based models have been rapidly integrated into forecast practices across the weather forecasting community in recent years. While ML tools introduce additional data to forecasting operations, there is a need for explainability to be available alongside the model output, such that the guidance can be transparent and trustworthy for the forecaster. This work makes use of the algorithm tree interpreter (TI) to disaggregate the contributions of meteorological features used in the Colorado State University Machine Learning Probabilities (CSU-MLP) system, a random forest-based ML tool that produces real-time probabilistic forecasts for severe weather using inputs from the Global Ensemble Forecast System v12. TI feature contributions are analyzed in time and space for CSU-MLP day-2 and 3 individual hazard (tornado, wind, and hail) forecasts and day-4 aggregate severe forecasts over a 2-yr period. For individual forecast periods, this work demonstrates that feature contributions derived from TI can be interpreted in an ingredients-based sense, effectively making the CSU-MLP probabilities physically interpretable. When investigated in an aggregate sense, TI illustrates that the CSU-MLP system's predictions use meteorological inputs in ways that are consistent with the spatiotemporal patterns seen in meteorological fields that pertain to severe storms climatology. This work concludes with a discussion on how these insights could be beneficial for model development, real-time forecast operations, and retrospective event analysis.</p>
Data from: Why are plant communities stable? Disentangling the role of dominance, asynchrony and averaging effect following realistic species loss scenario
<p>A growing number of studies have demonstrated that biodiversity is a strong and positive predictor of ecosystem temporal stability by simultaneously affecting multiple underlying mechanisms of stability <em>i.e.</em> dominance, asynchrony, and averaging effects. However, to date, no study has disentangled the relative role of these key mechanisms of stability in biodiversity experiments. We created a species richness gradient by mimicking a loss of rare species and assessed the role of species richness on community stability and, more importantly, quantified the relative role of three stabilizing mechanisms <em>i.e.</em> dominance (stabilization due to stable dominants compared to the rest of the species in the community), asynchrony (stabilization due to temporal asynchrony between species), and averaging effects (pure effect of diversity) on community stability across a species richness gradient. We found that extreme species loss negatively impacted community stability, but just three species were enough to stabilize biomass production to a level similar to highly diverse communities. However, the similar stability of communities resulted from differing contributions from each stability mechanism, depending on the community diversity. Since less abundant species were more temporally variable, species loss stabilized the populations of the remaining species. The loss of rare and subordinate species reduced the dominance and averaging effects, but increased the asynchrony effect. Hence, the asynchrony effect played a major role in the stability of species poor communities, while the averaging effect drove most of the stability of species rich communities. Overall, dominance played only a minor role, accounting for 5-15% of the stabilization, while asynchrony and averaging effects were dominating forces contributing to ~ 85-95% of the total stabilization.</p> <p><em>Synthesis</em>. This study highlights the importance of biodiversity and roles of dominant and rare species for long-term community stability and, for the first time, disentangles relative roles of dominance effect, asynchrony, and averaging effect on community stability in a real-world biodiversity experiment.</p>
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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.