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Tempo-spatial evolution of seed plant endemism in Taiwan island

Aim: In Taiwan island, dispersal through recent land-bridge and oversea after the appearance of proto-Taiwan (<6.5 Ma) is responsible for its biodiversity assembly. While radiations have also been widely reported in mountain systems. So, the tempo-spatial route to the floral hotspot was determined through a meta-analysis of evolution of endemic plants. Location: Taiwan island and adjacent Asian regions. Taxon: Seed plants. Methods: Published dated phylogenies were compiled, and the stem ages were considered as origin times. Ancestral range shift pattern and/or distribution of sister lineage/species were used to determine the speciation mode, in situ origin or dispersal. The distributions of sister taxa were assigned to ten different biogeographical regions. Histograms quantifying the number of different origin mode events within 0.5 Ma bins were constructed. Possibility of long-distance dispersal (LDD) was evaluated. Results: The 125 sampled endemic plants originated between the late Eocene and late Pleistocene, with 111 species (88.8%) originating after the emergence of proto-Taiwan and 14 species (11.2%) before. Spatially, in situ speciation contributed more to the formation of endemism than dispersal (56.8% vs 43.2%). The mean ages of in situ origin species (1.83 Ma) are significantly younger than that of dispersal (6.34 Ma). The main regions from which dispersal occurred were south-central (n=29) and southeast China (n=28) (referred to as south China), followed by Japan (n=14). High ratio (60.8%) of LDD ability is found. Main conclusions: Spatially, recent land-bridge and oversea dispersal from the adjacent flora of Asia is supported and southwest and southeast China are the most important sources. In situ speciation that may be correlated with mountain uplift, monsoon intensification and Pleistocene climatic fluctuations exert greater contributions. Temporally, floral endemism is predominantly origin after the emergence of proto-Taiwan. Additional investigations with more sophisticated sampling and genetic data are needed in the future.

A biorefinery model for the production of oil and biomethane using castor plants

This study investigated the effects of two nitrogen fertilization levels on seed and oil yield, and the biomethane production from castor husks residue. A biological pretreatment using two white rot fungi was adopted to reduce the lignin content of capsule husks and enhance biomethane production. The study aimed to highlight the potential of castor plants as energy crops using a biorefinery approach to produce biodiesel from the oil and biomethane from the residual biomass in order to reduce agricultural waste.

Data from: Host plant height explains the effect of nitrogen enrichment on arbuscular mycorrhizal fungal communities

Nitrogen (N) enrichment is widely known to affect the root-associated arbuscular mycorrhizal fungal (AMF) community in different ways, for example, via altering soil properties and/or shifting host plant functional traits. However, empirical knowledge of their relative importance is still lacking. Using a long-term N addition experiment, we measured the AMF community taxonomic and phylogenetic diversity at the single plant species (roots of 15 plant species) and plant community (mixed roots) levels. We also measured four functional traits of 35 common plant species along the N addition gradient. We found divergent responses of AMF diversity to N addition for host plants with different innate heights (i.e., plant natural height under unfertilized treatment). Furthermore, our data showed that species-specific responses of AMF diversity to N addition were negatively related to the change in maximum plant height. When scaling up to the community level, N addition affected AMF diversity mainly by increasing the maximum plant height, rather than altering soil properties. Our results highlight that plant height drives the AMF community dynamics under nitrogen enrichment at both species and community levels, thus providing important implications for understanding the response of AMF diversity to anthropogenic nitrogen deposition.

Taxonomic and functional biogeographies of soil bacterial communities across the Tibet plateau are better explained by abiotic conditions than distance and plant community composition

The processes governing soil bacteria biogeography are still not fully understood. It remains unknown how the importance of environmental filtering and dispersal differs between bacterial taxonomic and functional biogeography, and whether their importance is scale-dependent. We sampled soils across the Tibet plateau, with distances among plots ranging from 20 m to 1,550 km. Taxonomic composition of bacterial community was characterized by 16S amplicon sequencing and functional community composition by qPCR targeting 9 functional groups involved in N dynamics. Factors representing climate, soil, and plant community were measured to assess different facets of environmental dissimilarity. Both bacterial taxonomic and functional dissimilarities were more related to abiotic dissimilarity than biotic (vegetation) dissimilarity or distance. Taxonomic dissimilarity was mostly explained by differences in soil pH and mean annual temperature (MAT), while functional dissimilarity was linked to differences in soil N and P availabilities and N:P ratio. Soil pH and MAT remained the main determinants of taxonomic dissimilarity across spatial scales. In contrast, the explanatory variables of N-related functional dissimilarity varied across the scales, with soil moisture and organic matter having the highest role across short distances (<~330 km), and available P, N:P ratio and distance being important over long distances (>~660 km). Our results demonstrate how biodiversity dimension (taxonomic versus functional aspects) and spatial scale influence the factors driving soil bacterial biogeography.

Plant water limitation and its impact on the oviposition preferences of the monarch butterfly, Danaus plexippus (Lepidoptera: Nymphalidae)

Intensifying drought conditions across the western United States due to global climate change are altering plant-insect interactions. Specialist herbivores must find their host plants within a matrix of nonhosts, and thus often rely upon specific plant secondary chemistry for host location and oviposition cues. Climate-induced alterations to plant chemistry could thus affect female selection of larval food-plants. Here, we investigated whether host-plant water limitation influenced oviposition preference in a threatened invertebrate: the monarch butterfly (Danaus plexippus). We found that females deposited more eggs on reduced-water than on well-watered narrowleaf milkweed plants (Asclepias fascicularis), but we could not attribute this change to any specific change in plant chemistry. Specialist herbivores, such as the monarch butterfly, which are tightly linked to specific plant cues, may experience a shift in preferences under global-change conditions. Understanding oviposition preferences will be important to directing ongoing habitat restoration activities for this declining insect.

Predicting plant species climate preferences on the basis of mechanistic traits

Improved estimation of climate niches is critical, given climate change. Plant adaptation to climate depends on their physiological traits and their distributions, yet traits are rarely used to inform the estimation of species climate niches, and the power of a trait-based approach has been controversial, given the many ecological factors and methodological issues that may result in decoupling of species' traits from their native climate. For 107 species across six ecosystems of California, we tested the hypothesis that mechanistic leaf and wood traits can robustly predict the mean of diverse species' climate distributions, when combining methodological improvements from previous studies, including standard trait measurements and sampling plants growing together at few sites. Further, we introduce an approach to quantify species' trait-climate mismatch. We demonstrate a strong power to predict species' mean climate from traits. As hypothesized, the prediction of species' mean climate is stronger (and mismatch lower) when traits are sampled for individuals closer to species' mean climates. Improved resolution of species' climate niches based on mechanistic traits can importantly inform conservation of vulnerable species under the threat of climatic shifts in upcoming decades.

Data from "Tissue and toxin-specific divergent evolution in plant defense"

Files and code necessary to replicate the results from the manuscript are described as follows: Syrfampop.sas --> SAS code to conduct the analyses. HPLC_asyr.csv --> contains the cardenolide data of root, leaf and seed tissue from each individual plant belonging to multiple families of each of the two populations (main analysis in SAS code). chemmantelcorr.csv --> contains the correlation matrices between cardenolides within a given tissue (permutation test in SAS code) SS.csv --> contains the sums of squares matrices of cardenolide concentrations at the population and family levels for each tissue and whole plant after the MANOVA in the SAS code (used for the R code in Martin et al. (2008)). ehdbp.vcf --> Description of SNP data used for this study. ehdbp.arp --> SNP data in Arlequin format ready for FST analysis.

Data and Code supplement to: Effects of intraspecific variation in a native species´ phenology on its coexistence with non-native plants

Data and code to generate the results of the paper published at Oikos "Effects of intraspecific variation in a native species´ phenology on its coexistence with non-native plants".  Both R files can be independently run, and datasets include the raw data to generate the interaction coefficients according Lasthenia phenology or simulations to investigate the effect of intraspecific trait variation of Lasthenia population abundances.

Performance and preference of four above- and below-ground invertebrate and generalist herbivores on regionally and locally rare plant species

<ol> <li>Rare plant species are suggested to be less resistant to herbivores than common species. Their lower apparency and the fact that they often live in isolated populations, resulting in fewer herbivore encounters, might have led to the evolution of reduced defences. Moreover, their frequently lower levels of genetic diversity compared with common species could negatively affect their resistance against enemies. However, the hypothesis that plant resistance depends on plant regional and local rarity, independently of habitat and competitive and growth strategy, lacks evidence.</li> <li>To test this hypothesis, we assessed the performance and preference of one belowground and three aboveground generalist invertebrate herbivores from different taxonomic groups as indicators of plant resistance. Herbivores were fed a total of 62 regionally and locally rare and common plant species from Switzerland. We accounted for differences in a plant's growth and competitive strategy and habitat resource availability.</li> <li>We found that regionally and locally rare and common plant species did not generally differ in their resistance to most generalist herbivores. However, one herbivore species even performed better and preferred locally and regionally common plant species over rarer ones, indicating that common species are not more resistant, but tend to be less resistant. We also found that all herbivore species consistently performed better on competitive and large plant species, although different herbivore species generally preferred and performed better on different plant species. The latter indicates that the use of generalist herbivores as indicators of plant-resistance levels can be misleading.</li> <li> Synthesis: Our results show that rare plant species are not inherently less resistant than common ones to herbivores. Instead, our results suggest that the ability of plants to allocate resources away from defence towards enhancing their competitive ability might have allowed plants to tolerate herbivory, and to become locally and regionally common.</li> </ol>

Puke or poop? Comparison of regurgitate and faecal samples to infer alpine grasshopper (Paprides nitidus Hutton) diet in experimental plant communities

Characterising plant-herbivore interactions is important to understanding the processes that influence community structure and ecosystem functioning. Traditional methods used to identify plant-herbivore interactions are being superseded by non-destructive molecular approaches that can infer interactions with greater resolution and accuracy from environmental DNA (e.g., faeces and regurgitate). However, few studies have compared the use of different types of samples and whether they provide similar or contrasting information about species' diet. Here we compared the success of DNA amplification and host plant species identification using restriction fragment length polymorphism (RFLP) of faecal and regurgitate samples collected from alpine grasshoppers Paprides nitidus Hutton during a grassland community mesocosm experiment. We found that DNA amplification success was 23% and 86% higher for faecal than regurgitate samples from female and male grasshoppers, respectively, whereas successful host plant identification using RFLP was 9% higher for regurgitate than faecal samples. The mean number of host plant species identified per sample (1.40) did not differ between sample types or grasshopper sexes. Of the 136 paired faecal-regurgitate samples, just 41% and 74% produced exactly or partially matching host plant identifications, respectively, indicating that different sample types provided complementary information about herbivore diet. Some plant species were more likely to be identified from faecal samples than expected by chance, and this identification bias skewed towards greater representation in faecal samples for plant species with higher investment in leaf tissue. We conclude that multiple sample types may be required to fully characterise an invertebrate herbivore species' diet.

Designing a Synthetic Microbial Community through Genome Metabolic Modeling to enhance Plant-Microbe Interaction

Supplementary data 1 - Reconstructed  genome-scale metabolic networks from MAGs and Hosts Supplementary data 2 - Plant growth-promoting traits among members of the minimal community   Manipulating the rhizosphere microbial community through beneficial microorganism inoculation has gained interest in improving crop productivity and stress resistance. Synthetic microbial communities, known as SynCom, mimic natural microbial compositions while reducing the number of components. However, achieving this goal requires a comprehensive understanding of natural microbial communities and a careful selection of compatible microorganisms with colonization traits, which still pose challenges. In this study, we employed an in-silico approach using genome metabolic modeling to design a synthetic microbial community aimed at improving the yield of important crop plants. We used a targeted approach to select a minimal community (MinCom) encompassing essential compounds for microbial metabolism and compounds relevant to plant interactions. This resulted in a reduction of the initial community size by approximately 4.5-fold. Notably, the MinCom retained crucial genes associated with essential plant growth-promoting traits, such as iron acquisition, EPS production, potassium solubilization, nitrogen fixation, GABA production, and IAA-related tryptophan metabolism. Furthermore, our selection process for the SymCom, based on a comprehensive understanding of microbe-microbe-plant interactions, yielded a set of six hub species that displayed notable taxonomic novelty, including members of the Eremiobacterota and Verrucomicrobiota phyla. Our study contributes to the growing body of research on synthetic microbial communities and their potential to enhance agricultural practices. The insights gained from our in-silico approach and the selection of hub species pave the way for further investigations into the development of tailored microbial communities that can optimize crop productivity and improve stress resilience in agricultural systems.

Data for Torppa et al. 2023 'Soil compaction effects on arbuscular mycorrhizal symbiosis in wheat depend on host plant variety'

The dataset consists of the data that supports the findings of the article 'Soil compaction effects on arbuscular mycorrhizal symbiosis in wheat depend on host plant variety’ written by Torppa et al. and published in Plant and Soil in 2023. The data consists of arbuscular mycorrhizal colonization, fatty acid and community data, as well as soil and crop nutrient and yield data.

Suppl. File S1 - OGM plants approved by CTNBio until 2023 in Brazil

Suppl. File S1 - OGM plants approved by CTNBio until 2023 in Brazil.

Data for: The relative impact of parental and current environment on plant transcriptomes depends on type of stress and genotype

Through developmental plasticity, an individual organism integrates influences from its immediate environment with those due to the environment of its parents. While both effects on phenotypes are well documented, their relative impact has been little studied in natural systems, especially at the level of gene expression. We examined this issue in four genotypes of the annual plant Persicaria maculosa by varying two key resources light and soil moisture in both generations. Transcriptomic analyses showed that the relative effects of parent and offspring environment on gene expression (i.e., the number of differentially expressed transcripts, DETs) varied both for the two types of resource stress and among genotypes. For light, immediate environment induced more DETs than parental environment for all genotypes (although the precise proportion of parental versus immediate DETs varied among genotypes). By contrast, the relative effect of soil moisture varied dramatically among genotypes, from 8-fold more DETs due to parental than immediate conditions to 10-fold fewer. These findings provide evidence at the transcriptome level that the relative impacts of parental and immediate environment on the developing organism may depend on the environmental factor and vary strongly among genotypes, providing potential for the interplay of these developmental influences to evolve.

Data from: Distribution, drivers, and restoration priorities of plant invasions in India

Biological invasions threaten biodiversity and human wellbeing, with developing tropical countries being more vulnerable. Despite the urgency to reduce impacts of invasions, management interventions are constrained by unavailability of timely information on invasive species occurrence, potential drivers, and restoration priorities. Generating this information at biogeographic scales can be costly, unless integrated with multi-objective biodiversity monitoring. Invasive plant monitoring is integrated with India's national-scale tiger population assessment, wherein natural areas are sampled at 25 km2 scale to inventory plants. In 2018, a total of 158,979 plots were sampled covering ~358,550 km2. We used 206,393 locations of high concern invasive plants to model their distribution using socio-ecological covariates and identify potential drivers of invasions. Considering the invasion magnitude and financial constraints in management, we further identified priority restorations sites at national-scale to maximize biodiversity outcomes. High-concern invasive plants were recorded from ~254,880 km2 (72% sampled area) and modelled to invade in total ~750,905 km2 (66%) Indian natural systems. While open and deciduous ecosystems were the highest invaded by woody plants, areas with extreme climate and less anthropic pressure were least invaded. Since managing invasions across their range seemed futile due to costly (~13.5 billion USD for one-time management) and ineffective strategies, restoration priority was assigned to least invaded areas (11% protected areas, 23% multi-use) to maximize biodiversity returns. Synthesis and applications: India implemented national-scale invasive plant monitoring by integrating it with the umbrella project on tiger assessment. Embarking on this big data, we show that two-thirds of India's natural areas are under multiple plant invasions, owing to the legacy of anthropogenic modifications. Our study offers a restoration priority model, empowering policymakers to devise adaptive strategies for restoring invaded biomes and maximizing biodiversity returns.

opencc-zeroSep 2023View details →

Data from: Different effects of fire age and fire recurrence on grass and woody plant chemistry in Kafue National Park, Zambia

In savannas, fire and herbivores are important drivers of natural ecosystem processes. Fire is also used intensively for management purposes. However, reported fire effects differ between studies. Reasons for these differences are still poorly understood. Here, we investigated the effects of fire on leaf chemistry of grasses and woody plants in the savanna of the Busanga Flood Plain, Zambia, in relation to the time elapsed between plant sampling and the last fire (fire age) and the frequency of fires during the last 16 years (fire recurrence). We analyzed leaves for their nitrogen, carbon and fiber concentrations, and estimated their metabolizable energy content, reflecting feed quality for browsers and grazers. Grasses and woody plants differed in all chemical components and showed different responses to fire. Grass quality was higher at sites burnt in the year of sample collection than at sites burnt only in previous years, but did not change under different fire recurrences. Leaves of woody plants did not differ in relation to fire age but their quality increased with increasing fire recurrence. In woody plants, the carbon content responded to the interaction between fire age and fire recurrence, indicating changes in carbon allocation in response to fire. Thus, burning increased feed quality for grazers and browsers but on different temporal scales. The scale effects may contribute to the differences in resource allocation described by different studies. They merit more attention in management decisions as well as in future studies on fire effects in savanna systems.

opencc-zeroSep 2023View details →

Environment differentially affects the functional and phylogenetic structures of plant communities in a dry evergreen Afromontane tropical forest

Testing how local environmental conditions influence plant community assembly is important to understand the underlying mechanisms that promote and/or maintain biodiversity. Functional traits are used to find the broad spectrum of resource use strategies that plants use to respond to environmental variation. The patterns and drivers of plant community assembly through the lens of traits and phylogeny, however, remain to be studied in a uniquely biodiversity rich but poorly known fragmented dry Afromontane forest of Ethiopia. Here, we combined trait and community phylogenetic data from thirty sampling plots of 20 × 20 m size to determine the functional and phylogenetic structures and their drivers in a fragmented, human-dominated dry evergreen Afromontane forest. We found phylogenetic and functional clustering of plants in which the effect of environment was found to be trait specific. A weak phylogenetic signal for traits was detected suggesting that species resource use strategies may not be inferred using species phylogenetic distance. Additionally, we found functional traits to be weak in predicting species abundance distribution. Overall, while this study shows a non-random community assembly pattern, it also highlights the importance of deterministic processes being trait specific.

opencc-zeroMay 2023View details →

Balancing Authority Hourly Generation Of Installed Plant Capacities in CONUS

This dataset contains the hourly generation time series for each Balancing Authority representing the installed capacity in each month from 2007 through 2020. The time series is aggregated from plant-level generation of plants that exist in the Energy Information Administration (EIA) database as of 2020. The time series are simulated actual generation meaning that the installed capacities have been applied to the hourly capacity factor profiles in <a href="https://doi.org/10.5281/zenodo.7901614">Bracken et al. 2023</a>. These historical generation time series reflect the actual monthly installed capacity at each plant; the EIA 860 and EIA 860m databases were mined to identify months of first operation, retirement, and extended periods of maintenance or non-operation. These databases were also used to create time series of Balancing Authority (BA) level hourly generation to reflect the actual monthly installed capacity. The BA-level time series tracks the BA membership of each power plant in each month; the time series reflects the monthly inventory and hourly production in each BA. For more information please refer to Campbell et al. 2023, Dynamically Downscaled Power Production for All EIA Wind and Solar Power Plants, in prep, and to the code repository at <a href="https://github.com/GODEEEP/godeeep-eia-power">https://github.com/GODEEEP/godeeep-eia-power</a>. The dataset contains three types of files: Monthly Plant-Level Inventory - The monthly plant-level inventory (<code>all_years_860m.csv</code>) contains the identification codes for each generator (including the <code>plant_code_unique</code> identifier to link with the solar and wind profiles in Bracken et al. 2023), the capacity in that month, the balancing authority that plant operated for in that month, the resource type (<code>solar</code> or <code>wind</code>), the month and year, and whether the nameplate capacity in that month needs to be scale to account for aggregation of very large wind power plants (i.e., more than 300 turbines). BA-level Hourly Generation - The BA-level hourly generation files (<code>solar_BA_generation.csv</code> and <code>wind_BA_generation.csv</code>) contain hourly generation at the BA level for each BA in the 2020 EIA 860 database. The first column contains a time stamp and each column header is the name of the BA as it exists in the EIA 860 database (e.g., ISO New England is ISNE, CAISO is CISO). The time series spans 2007 through 2020. The time series begin in 2007, as this aligns with the first year of publication of the EIA 923 monthly plant-level generation dataset and with the first year of available BA-level self-reported generation.  The purpose of the temporal baseline alignment is for validation of the time series, discussed in Campbell et al. 2023. Validation metrics in this paper are provided at the BA-level. Plant-level Hourly Generation - The plant-level hourly generation files (<code>solar_plant_generation.csv</code> and <code>wind_plant_generation.csv</code>) contain hourly generation at the generator level for each power plant that exists in the EIA 860 database in 2020. The files are organized with an hourly timestamp for each row and a unique generator id for each column. The generator id is a concatenation of the EIA Plant ID and the EIA Generator ID with an underscore separating the strings. The plant-level hourly generation time series are intended to be aggregated to the BA-level. These plant-level time series are provided to the user to allow for re-aggregation for bespoke regional analyses.   Known Issues <ul> <li>The following wind power plants (identifier <code>plant_code_unique</code>) have a cf greater than 1 and were scaled to 0.885 <ul> <li>['2024', '2024_1', '2024_3', '2024_4', '7855', '7855_1', '7927', '7927_1', '7927_2', '7965', '7965_1', '7974', '7974_1', '52162', '52163', '54300', '54793', '54793_2', '55741', '55944', '55995_1', '56577', '57214', '57257', '57258', '57258_1', '57594', '57721', '57721_1', '58105', '58112', '58113', '58113_1', '59328', '59329', '59330', '59331', '61677', '61677_1', '61677_2', '62442', '64130']</li> </ul> </li> </ul>   Changelog <ul> <li>v1.1.0 - Updates the basis for plant-level inventory from the EIA860 monthly reports (considered preliminary) to the EIA860 annual reports (considered complete and final).</li> </ul>   This research was supported by the Grid Operations, Decarbonization, Environmental and Energy Equity Platform (GODEEEP) Investment, under the Laboratory Directed Research and Development (LDRD) Program at Pacific Northwest National Laboratory (PNNL). PNNL is a multi-program national laboratory operated for the U.S. Department of Energy (DOE) by Battelle Memorial Institute under Contract No. DE-AC05-76RL01830.

opencc-zeroSep 2023View details →

Tackling local ecological homogeneity: Finding intraspecific trait variability in local populations of Mediterranean plants

Local homogeneity, in ecology, is the often undisclosed assumption that variability within populations is negligible or mostly distributed evenly. In large areas, this can lead to the aggregation of different populations without regard for their unique needs and characteristics, such as drought sensitivity and functional traits distributions. Here we discuss whether this assumption can be justified, and we hypothesize that discerning the source of variation between plasticity and adaptation could be a feasible approach to formulate an informed decision. We test this hypothesis on plants, resorting to a common garden experiment to determine the source of variation of several plant functional traits at a local scale (~60 Km) of three wild species: Quercus ilex, Pistacia lentiscus and Cistus salviifolius. Individuals of each species were sourced from three key sites chosen along a local aridity gradient. Our approach led to the rejection of the local homogeneity assumption for Q. ilex and C. salviifolius at this scale due to the adaptive divergence observed among neighbouring populations. This case study provides evidence that addressing local homogeneity can highlight diverging populations in a relatively simple way. We conclude that gathering empirical evidence on intraspecific variability is a feasible approach that can provide researchers with solid bases to decide whether to adopt the local homogeneity assumption or not.