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At least 1,189 records · Page 66

A gene-editing/complementation strategy for tissue-specific lignin reduction while preserving biomass yield

Lignification of secondary cell walls is a major factor conferring recalcitrance of lignocellulosic biomass to deconstruction for fuels and chemicals. Genetic modification can reduce lignin content and enhance saccharification efficiency, but usually at the cost of moderate-to-severe growth penalties. We have developed a method, using a single DNA construct that uses CRISPR–Cas9 gene editing to knock-out expression of an endogenous gene of lignin monomer biosynthesis while at the same time expressing a modified version of the gene’s open reading frame that escapes cutting by the Cas9 system and complements the introduced mutation in a tissue-specific manner. Expressing the complementing open reading frame in vessels allows for the regeneration of Arabidopsis plants with reduced lignin, wild-type biomass yield, and up to fourfold enhancement of cell wall sugar yield per plant. The above phenotypes are seen in both homozygous and bi-allelic heterozygous T1 lines, and are stable over at least four generations. The method provides a rapid approach for generating reduced lignin trees or crops with one single transformation event, and, paired with a range of tissue-specific promoters, provides a general strategy for optimizing loss-of-function traits that are associated with growth penalties. This method should be applicable to any plant species in which transformation and gene editing are feasible and validated vessel-specific promoters are available.

59 BASIC BIOLOGICAL SCIENCES↗

Small and mighty: adaptation of superphylum Patescibacteria to groundwater environment drives their genome simplicity

The newly defined superphylum Patescibacteria such as Parcubacteria (OD1) and Microgenomates (OP11) has been found to be prevalent in groundwater, sediment, lake, and other aquifer environments. Recently increasing attention has been paid to this diverse superphylum including > 20 candidate phyla (a large part of the candidate phylum radiation, CPR) because it refreshed our view of the tree of life. However, adaptive traits contributing to its prevalence are still not well known. Results Here, we investigated the genomic features and metabolic pathways of Patescibacteria in groundwater through genome-resolved metagenomics analysis of >600 Gbp sequence data. We observed that, while the members of Patescibacteria have reduced genomes (~ 1 Mbp) exclusively, functions essential to growth and reproduction such as genetic information processing were retained. Surprisingly, they have sharply reduced redundant and nonessential functions, including specific metabolic activities and stress response systems. The Patescibacteria have ultra-small cells and simplified membrane structures, including flagellar assembly, transporters, and two-component systems. Despite the lack of CRISPR viral defense, the bacteria may evade predation through deletion of common membrane phage receptors and other alternative strategies, which may explain the low representation of prophage proteins in their genomes and lack of CRISPR. By establishing the linkages between bacterial features and the groundwater environmental conditions, our results provide important insights into the functions and evolution of this CPR group.

59 BASIC BIOLOGICAL SCIENCES↗

Metagenomic insights into the taxonomy, function, and dysbiosis of prokaryotic communities in octocorals

Background. In octocorals (Cnidaria Octocorallia), the functional relationship between host health and its symbiotic consortium has yet to be determined. Here, we employed comparative metagenomics to uncover the distinct functional and phylogenetic features of the microbiomes of healthy Eunicella gazella, Eunicella verrucosa, and Leptogorgia sarmentosa tissues, in contrast with the microbiomes found in seawater and sediments. We further explored how the octocoral microbiome shifts to a pathobiome state in E. gazella. Results. Multivariate analyses based on 16S rRNA genes, Clusters of Orthologous Groups of proteins (COGs), Protein families (Pfams), and secondary metabolite-biosynthetic gene clusters annotated from 20 Illumina-sequenced metagenomes each revealed separate clustering of the prokaryotic communities of healthy tissue samples of the three octocoral species from those of necrotic E. gazella tissue and surrounding environments. While the healthy octocoral microbiome was distinguished by so-far uncultivated Endozoicomonadaceae, Oceanospirillales, and Alteromonadales phylotypes in all host species, a pronounced increase of Flavobacteriaceae and Alphaproteobacteria, originating from seawater, was observed in necrotic E. gazella tissue. Increased abundances of eukaryotic-like proteins, exonucleases, restriction endonucleases, CRISPR/Cas proteins, and genes encoding for heat-shock proteins, inorganic ion transport, and iron storage distinguished the prokaryotic communities of healthy octocoral tissue regardless of the host species. An increase of arginase and nitric oxide reductase genes, observed in necrotic E. gazella tissues, suggests the existence of a mechanism for suppression of nitrite oxide production by which octocoral pathogens may overcome the host’s immune system. Conclusions. This is the first study to employ primer-less, shotgun metagenome sequencing to unveil the taxonomic, functional, and secondary metabolism features of prokaryotic communities in octocorals. Our analyses reveal that the octocoral microbiome is distinct from those of the environmental surroundings, is host genus (but not species) specific, and undergoes large, complex structural changes in the transition to the dysbiotic state. Host-symbiont recognition, abiotic-stress response, micronutrient acquisition, and an antiviral defense arsenal comprising multiple restriction endonucleases, CRISPR/Cas systems, and phage lysogenization regulators are signatures of prokaryotic communities in octocorals. We argue that these features collectively contribute to the stabilization of symbiosis in the octocoral holobiont and constitute beneficial traits that can guide future studies on coral reef conservation and microbiome therapy.

59 BASIC BIOLOGICAL SCIENCES↗

Microbial colonization and persistence in deep fractured shales is guided by metabolic exchanges and viral predation

Background: Microbial colonization of subsurface shales following hydraulic fracturing offers the opportunity to study coupled biotic and abiotic factors that impact microbial persistence in engineered deep subsurface ecosystems. Shale formations underly much of the continental USA and display geographically distinct gradients in temperature and salinity. Complementing studies performed in eastern USA shales that contain brine-like fluids, here we coupled metagenomic and metabolomic approaches to develop the first genome-level insights into ecosystem colonization and microbial community interactions in a lower-salinity, but high-temperature western USA shale formation. Results: We collected materials used during the hydraulic fracturing process (i.e., chemicals, drill muds) paired with temporal sampling of water produced from three different hydraulically fractured wells in the STACK (Sooner Trend Anadarko Basin, Canadian and Kingfisher) shale play in OK, USA. Relative to other shale formations, our metagenomic and metabolomic analyses revealed an expanded taxonomic and metabolic diversity of microorganisms that colonize and persist in fractured shales. Importantly, temporal sampling across all three hydraulic fracturing wells traced the degradation of complex polymers from the hydraulic fracturing process to the production and consumption of organic acids that support sulfate- and thiosulfate-reducing bacteria. Furthermore, we identified 5587 viral genomes and linked many of these to the dominant, colonizing microorganisms, demonstrating the key role that viral predation plays in community dynamics within this closed, engineered system. Lastly, top-side audit sampling of different source materials enabled genome-resolved source tracking, revealing the likely sources of many key colonizing and persisting taxa in these ecosystems. Conclusions: These findings highlight the importance of resource utilization and resistance to viral predation as key traits that enable specific microbial taxa to persist across fractured shale ecosystems. We also demonstrate the importance of materials used in the hydraulic fracturing process as both a source of persisting shale microorganisms and organic substrates that likely aid in sustaining the microbial community. Moreover, we showed that different physicochemical conditions (i.e., salinity, temperature) can influence the composition and functional potential of persisting microbial communities in shale ecosystems. Together, these results expand our knowledge of microbial life in deep subsurface shales and have important ramifications for management and treatment of microbial biomass in hydraulically fractured wells.

59 BASIC BIOLOGICAL SCIENCES↗

HT-SIP: a semi-automated stable isotope probing pipeline identifies cross-kingdom interactions in the hyphosphere of arbuscular mycorrhizal fungi

Abstract Background Linking the identity of wild microbes with their ecophysiological traits and environmental functions is a key ambition for microbial ecologists. Of many techniques that strive for this goal, Stable-isotope probing—SIP—remains among the most comprehensive for studying whole microbial communities in situ. In DNA-SIP, actively growing microorganisms that take up an isotopically heavy substrate build heavier DNA, which can be partitioned by density into multiple fractions and sequenced. However, SIP is relatively low throughput and requires significant hands-on labor. We designed and tested a semi-automated, high-throughput SIP (HT-SIP) pipeline to support well-replicated, temporally resolved amplicon and metagenomics experiments. We applied this pipeline to a soil microhabitat with significant ecological importance—the hyphosphere zone surrounding arbuscular mycorrhizal fungal (AMF) hyphae. AMF form symbiotic relationships with most plant species and play key roles in terrestrial nutrient and carbon cycling. Results Our HT-SIP pipeline for fractionation, cleanup, and nucleic acid quantification of density gradients requires one-sixth of the hands-on labor compared to manual SIP and allows 16 samples to be processed simultaneously. Automated density fractionation increased the reproducibility of SIP gradients compared to manual fractionation, and we show adding a non-ionic detergent to the gradient buffer improved SIP DNA recovery. We applied HT-SIP to 13 C-AMF hyphosphere DNA from a 13 CO 2 plant labeling study and created metagenome-assembled genomes (MAGs) using high-resolution SIP metagenomics (14 metagenomes per gradient). SIP confirmed the AMF Rhizophagus intraradices and associated MAGs were highly enriched (10–33 atom% 13 C), even though the soils’ overall enrichment was low (1.8 atom% 13 C). We assembled 212 13 C-hyphosphere MAGs; the hyphosphere taxa that assimilated the most AMF-derived 13 C were from the phyla Myxococcota, Fibrobacterota, Verrucomicrobiota, and the ammonia-oxidizing archaeon genus Nitrososphaera . Conclusions Our semi-automated HT-SIP approach decreases operator time and improves reproducibility by targeting the most labor-intensive steps of SIP—fraction collection and cleanup. We illustrate this approach in a unique and understudied soil microhabitat—generating MAGs of actively growing microbes living in the AMF hyphosphere (without plant roots). The MAGs’ phylogenetic composition and gene content suggest predation, decomposition, and ammonia oxidation may be key processes in hyphosphere nutrient cycling.

59 BASIC BIOLOGICAL SCIENCES↗

The ancestral environment of teosinte populations shapes their root microbiome

Summary Background The composition of the root microbiome affects the host’s growth, with variation in the host genome associated with microbiome variation. However, it is not known whether this intra-specific variation of root microbiomes is a consequence of plants performing targeted manipulations of them to adapt to their local environment or varying passively with other traits. To explore the relationship between the genome, environment and microbiome, we sampled seeds from teosinte populations across its native range in Mexico. We then grew teosinte accessions alongside two modern maize lines in a common garden experiment. Metabarcoding was performed using universal bacterial and fungal primers to profile their root microbiomes. Results The root microbiome varied between the two modern maize lines and the teosinte accessions. We further found that variation of the teosinte genome, the ancestral environment (temperature/elevation) and root microbiome were all correlated. Multiple microbial groups significantly varied in relative abundance with temperature/elevation, with an increased abundance of bacteria associated with cold tolerance found in teosinte accessions taken from high elevations. Conclusions Our results suggest that variation in the root microbiome is pre-conditioned by the genome for the local environment (i.e. non-random). Ultimately, these claims would be strengthened by confirming that these differences in the root microbiome impact host phenotype, for example, by confirming that the root microbiomes of high-elevation teosinte populations enhance cold tolerance.

Genetics & Heredity↗

Ponderosa pine hydraulic stress predicts more extreme wildfire behavior under future conditions in Bandelier National Monument, New Mexico

Background Live fuel moisture contributes to wildfire spread and reflects plant stress and physiological traits. The anticipated change in live fuel moisture under future conditions is likely non-linear, owing to physiological plant thresholds in water hydraulics. We constructed a mechanistic model of live fuel moisture’s response to water stress to understand the impact of future climate on live fuel moisture. We first gathered data on plant physiology and live fuel moisture for Pinus ponderosa at Bandelier National Monument, NM, USA, and modeled their relationship. We then parameterized a mechanistic plant hydrodynamics model (FATES-HYDRO) to simulate changes in plant stress and a statistical model to simulate the resulting impact on live fuel moisture. We then simulated FATES-HYDRO under future climate anomalies (SSP2-4.5 and SSP5-8.5: 2080–2100) to understand the change in plant stress and estimate its impact on live fuel moisture. Results We found that the number of days below crucial thresholds of live fuel moisture (100% and 79%) increased from contemporary levels (< 100%: 72 days, < 79%: 1.4 days) under SSP2-4.5 (< 100%: 185 days, < 79%: 10.2 day) and increased exponentially under SSP5-8.5 (< 100%: 215 days, < 79%: 65 days). We found that gross primary productivity decreased under both future climate scenarios (contemporary: 336 g C m −2 , SSP2-4.5: 203 g C m −2 , SSP5-8.5: 243 g C m −2 ); however, spring productivity increased under SSP5-8.5, potentially altering fuel loading. We additionally see a potentially lethal loss of conductivity in hydraulic P. ponderosa under SSP5-8.5. Conclusions The overall increase in plant water stress (as represented by loss of hydraulic conductivity and leaf water potential) and lower live fuel moisture appear to be driven by reduced precipitation during late summer monsoons typical of the region, extending the fire season later in the year. We predict increasing variability in the P. ponderosa wildfire regime under both climate projections driven by changing productivity, rising mortality, and an overall decrease in live fuel moisture.

54 ENVIRONMENTAL SCIENCES↗

Identification, characterization, and structure of a tRNA splicing enzyme RNA 5′-OH kinase from the pathogenic fungi Mucorales

Fungal Trl1 is an essential tRNA splicing enzyme composed of C-terminal cyclic phosphodiesterase and central polynucleotide kinase end-healing domains that convert the 2′,3′-cyclic-PO 4 and 5′-OH ends of tRNA exons into the 3′-OH,2′-PO 4 and 5′-PO 4 termini required for sealing by an N-terminal ATP-dependent ligase domain. Trifunctional Trl1 enzymes are present in most human fungal pathogens and are untapped targets for antifungal drug discovery. Mucorales species, deemed high-priority human pathogens by WHO, elaborate a noncanonical tRNA splicing apparatus in which a stand-alone monofunctional RNA ligase enzyme joins 3′-OH,2′-PO 4 and 5′-PO 4 termini. Here we identify a stand-aloneMucor circinelloidespolynucleotide kinase (MciKIN) and affirm its biological activity in tRNA splicing by genetic complementation in yeast. Recombinant MciKIN catalyzes magnesium-dependent phosphorylation of 5′-OH RNA and DNA ends in vitro. MciKIN displays a strong preference for GTP as the phosphate donor in the kinase reaction, a trait shared with the stand-alone RNA kinase homologs from Mucorales speciesRhizopus azygosporus(RazKIN) andLichtheimia corymbifera(LcoKIN) and with the kinase domains of fungal Trl1 enzymes. We report a 1.65 Å crystal structure of RazKIN in complex with GDP•Mg 2+ that illuminates the basis for guanosine nucleotide specificity.

Biochemistry & Molecular Biology↗

Improving precision and accuracy of genetic mapping with genotyping-by-sequencing data in outcrossing species

This dataset contains all data and supplementary materials from "Improving precision and accuracy of genetic mapping with genotyping-by-sequencing data in outcrossing species". An Excel file a list of all QTLs and linkage group length (in cM) obtained with two different SNP-calling methods (Tassel-Uneak and Tassel-GBS), genetic map-construction method (linkage-only and reference order-corrected) and depth filters (12x, 20x, 30x and 40x) for genetic mapping of 18 biomass yield traits in a biparental Miscanthus sinensis population using RAD-Seq SNPs is provided as "Supplementary file 1". A Perl script with the code for filtering VCF and HapMap-formatted data files is provided as “Supplementary file 2”. Phenotype data used for QTL mapping is provided as “Supplementary File 3”. A Perl script with the code for the simulation study is provided as “Supplementary file 4”.

GenotypingSimulator↗

Data for Characterization of the Ghd8 Flowering Time Gene in a Mini-Core Collection of Miscanthus sinensis

The optimal flowering time for bioenergy crop miscanthus is essential for environmental adaptability and biomass accumulation. However, little is known about how genes controlling flowering in other grasses contribute to flowering regulation in miscanthus. Here, we report on the sequence characterization and gene expression of Miscanthus sinensisGhd8 , a transcription factor encoding a HAP3/NF-YB DNA-binding domain, which has been identified as a major quantitative trait locus in rice, with pleiotropic effects on grain yield, heading date and plant height. In M. sinensis , we identified two homoeologous loci, MsiGhd8A located on chromosome 13 and MsiGhd8B on chromosome 7, with one on each of this paleo-allotetraploid species’ subgenomes. A total of 46 alleles and 28 predicted protein sequence types were identified in 12 wild-collected accessions. Several variants of MsiGhd8 showed a geographic and latitudinal distribution. Quantitative real-time PCR revealed that MsiGhd8 expressed under both long days and short days, and MsiGhd8B showed a significantly higher expression than MsiGhd8A . The comparison between flowering time and gene expression indicated that MsiGhd8B affected flowering time in response to day length for some accessions. This study provides insight into the conserved function of Ghd8 in the Poaceae, and is an important initial step in elucidating the flowering regulatory network of Miscanthus.

Feedstock Production↗

UAV remote sensing imagery - Miscanthus trials 2020 - Energy Farm - UIUC

Aerial imagery utilized as input in the manuscript "Deep convolutional neural networks exploit high spatial and temporal resolution aerial imagery to predict key traits in miscanthus" . Data was collected over M. Sacchariflorus and Sinensis breeding trials at the Energy Farm, UIUC in 2020. Flights were performed using a DJI M600 mounted with a Micasense Rededge multispectral sensor at 20 m altitude around solar noon. Imagery is available as tif file by field trial and date (10). The post-processing of raw images into orthophoto was performed in Agisoft Metashape software. Each crop surface model and multispectral orthophoto was stacked into an unique raster stack by date and uploaded here. Each raster stack includes 6 layers in the following order: Layer 1 = crop surface model, Layer 2 = Blue, Layer 3 = Green, Layer 4 = Red, Layer 5 = Rededge, and Layer 6 = NIR multispectral bands. Msa raster stacks were resampled to 1.67 cm spatial resolution and Msi raster stacks were resampled to 1.41 cm spatial resolution to ease their integration into further analysis. 'MMDDYYYY' is the date of data collection, 'MSA' is M. Sacchariflorus trial, 'MSI' is Miscanthus Sinensis trial, 'CSM' is crop surface model layer, and 'MULTSP' are the five multispectral bands.

bioenergy↗

Data from Bioenergy Sorghum Maintains Photosynthetic Capacity in Elevated Ozone Concentrations

Elevated tropospheric ozone concentration (O3) significantly reduces photosynthesis and productivity in several C4 crops including maize, switchgrass and sugarcane. However, it is unknown how O3 affects plant growth, development and productivity in sorghum ( Sorghum bicolor L.), an emerging C4 bioenergy crop. Here, we investigated the effects of elevated O3 on photosynthesis, biomass and nutrient composition of a number of sorghum genotypes over two seasons in the field using free-air concentration enrichment (FACE), and in growth chambers. We also tested if elevated O3 altered the relationship between stomatal conductance and environmental conditions using two common stomatal conductance models. Sorghum genotypes showed significant variability in plant functional traits, including photosynthetic capacity, leaf N content and specific leaf area, but responded similarly to O3. At the FACE experiment, elevated O3 did not alter net CO2 assimilation (A), stomatal conductance (gs), stomatal sensitivity to the environment, chlorophyll fluorescence and plant biomass, but led to reductions in the maximum carboxylation capacity of phosphoenolpyruvate and increased stomatal limitation to A in both years. These findings suggest that bioenergy sorghum is tolerant to O3 and could be used to enhance biomass productivity in O3 polluted regions.

Feedstock Production↗

Data for "High-resolution microCT reveals relationships between stomata and interior leaf anatomy in Sorghum"

Includes three different types of stacks, in two folders: "REC_RAW_STACKS.zip" contains: (1) Raw gray-scale reconstructed microCT x-ray scans, in the form of individual stacks per sample. "ML_STACKS.zip" contains: (2) Stacks that have been labeled using a machine-learning mask-RCNN pipeline identifying epidermis, mesophyll, airspace, vascular bundle, and background. (3) Stacks that have stomata locations labeled using a small point. The three types of stacks were used to calculate a variety of anatomical and physiological traits, using ImageJ Macros provided on Github: https://github.com/leakey-lab/microCT-Macros-Fischer. Young leaves from WT and transgenic Sorghum plants. CSV "microCT_REC2_META.csv" contains metadata, including sample/sub-sample labels.

3D↗

Data for Miscanthus giganteus Biolistic Transformation Using the Visible RUBY Red Marker Gene to Monitor Transformation Efficiency

Miscanthus × giganteus ( M × g ) is a high- yielding perennial C4 bioenergy crop, but genetic improvement by breeding is constrained by triploid sterility and clonal propagation. Improving genetic transformation methods for M × g would provide opportunities for advantageous trait introgression. Use of an easy to phenotype reporter gene is a promising strategy to improve transformation processes and efficiency. This study presents an efficient novel method for biolistic transformation of inflorescence- derived callus in M × g and demonstrates its efficacy using RUBY, a betalain-based noninvasive reporter that is visible throughout the transformation process. RUBY expression ( Zea mays codon optimized) was visible from callus stage through plantlet development into maturity. RUBY expressing independently transformed plants were confirmed by hygromycin phosphotransferase ELISA and by genomic PCR demonstrating that the RUBY phenotype is sufficient for screening transformants. The Zea mays codon optimized hygromycin selection marker was driven by previously established promoters for Miscanthus, ZmUBI and 2×35S, while the RUBY gene expression was controlled by a known Zea mays C4 promoter, Brachypodium UBI10, newly employed in Miscanthus. The construct containing the 2×35S promoter for hygromycin had a 15.1% transformation efficiency while the ZmUBI promoter had a 20.5% transformation efficiency. This study provides a novel, highly efficient protocol for successful biolistic transformation of M × g for stable expression. This study also demonstrates that RUBY expression can be used as a convenient and powerful monitor of transformation in ongoing and future work to engineer M × g into an improved bioproduct feedstock. **NOTE: in "TableS2_ProtocolComparison.csv", the data from row 665 to 971 should be removed.

Gene Editing↗

Similar photosynthetic, but different yield responses of C3 and C4 crops to elevated O3

This dataset contains leaf photosynthetic and biochemical traits, plant biomass, and yield in five C3 crops (chickpea, rice, snap bean, soybean, wheat) and four C4 crops (sorghum, maize, Miscanthus × giganteus, switchgrass) grown under ambient and elevated O3 concentration ([O3]) in the field at free-air O3 concentration enrichment (O3-FACE) facilities over the past 20 years.

C3 and C4 crops↗

Mucilage produced by aerial roots hosts diazotrophs that provide nitrogen in Sorghum bicolor

Sorghum ( Sorghum bicolor ) is an important food, feed, and fodder crop worldwide and is gaining popularity as an energy crop due to its high potential for biomass production. Some sorghum accessions develop many aerial roots and produce an abundant carbohydrate-rich mucilage after rain. This aerial root mucilage is similar to that observed in landraces of maize ( Zea mays ) from southern Mexico, which have been previously shown to host diazotrophs. In this study, we characterized the aerial root development of several sorghum accessions and the impact of humidity on this trait. We conducted a microbiome study of the aerial root mucilage of maize and sorghum and isolated numerous diazotrophs from field sorghum mucilage. We observed that the prevailing phyla in the mucilage were Pseudomonadota, Bacteroidota, and Bacillota. However, bacterial abundances varied based on the genotype and the location. Using acetylene reduction, 15 N 2 gas feeding, and 15 N isotope dilution assays, we confirmed that these sorghum accessions can acquire about 40% of their nitrogen from the atmosphere through these associations on aerial roots. Nitrogen fixation in sorghum aerial root mucilage offers a promising avenue to reduce reliance on synthetic fertilizers and promote sustainable agricultural practices for food, feed, fodder, and bioenergy production.

Venado, Rafael E.↗

Latent Dirichlet Allocation modeling of environmental microbiomes

Interactions between stressed organisms and their microbiome environments may provide new routes for understanding and controlling biological systems. However, microbiomes are a form of high-dimensional data, with thousands of taxa present in any given sample, which makes untangling the interaction between an organism and its microbial environment a challenge. Here we apply Latent Dirichlet Allocation (LDA), a technique for language modeling, which decomposes the microbial communities into a set of topics (non-mutually-exclusive sub-communities) that compactly represent the distribution of full communities. LDA provides a lens into the microbiome at broad and fine-grained taxonomic levels, which we show on two datasets. In the first dataset, from the literature, we show how LDA topics succinctly recapitulate many results from a previous study on diseased coral species. We then apply LDA to a new dataset of maize soil microbiomes under drought, and find a large number of significant associations between the microbiome topics and plant traits as well as associations between the microbiome and the experimental factors, e.g. watering level. This yields new information on the plant-microbial interactions in maize and shows that LDA technique is useful for studying the coupling between microbiomes and stressed organisms.

59 BASIC BIOLOGICAL SCIENCES↗

Identifying ecological and evolutionary research targets and risks in climate change studies to break barriers to broad inference

Understanding the responses of plants, microbes, and their interactions to long-term climate change is essential to identifying the traits, genes, and functions of organisms that maintain ecosystem stability and function of the biosphere. However, many studies investigating organismal responses to climate change are limited in their scope along several key ecological, evolutionary, and environmental axes, creating barriers to broader inference. Broad inference, or the ability to apply and validate findings across these axes, is a vital component of achieving climate preparedness in the future. Breaking barriers to broad inference requires accurate cross-ecosystem interpretability and the identification of reliable frameworks for how these responses will manifest. Current approaches have generated a valuable, yet sometimes contradictory or context dependent, understanding of responses to climate change factors from the organismal- to ecosystem-level. In this synthesis, we use plants, soil microbial communities, and their interactions as examples to identify five major barriers to broad inference and resultant target research areas. We also explain risks associated with disregarding these barriers to broad inference and potential approaches to overcoming them. Developing and funding experimental frameworks that integrate basic ecological and evolutionary principles and are designed to capture broad inference across levels of organization is necessary to further our understanding of climate change on large scales.

Love, Sarah J. (ORCID:0000000180787373)↗