Philippa Kaur

Annual grains, domesticated from wild species, have dominated agriculture since the Neolithic. A new study reports how turning to high-yield perennial rice crops could maintain key ecosystem functions while supporting livelihoods.The past several decades have seen modest but growing investments in the development of perennial grain crops, including perennial counterparts of wheat, rice and sorghum suitable for the USA, China, Europe and Africa. One technique involves domesticating wild perennial species through continual selection of desirable traits over multiple generations3. A recently developed perennial grain currently grown for niche markets in the USA, Kernza, was domesticated from Thinopyrum intermedium, a wild relative of wheat. While yields of Kernza remain low compared with those of annual wheat, they are increasing. As with the development of perennial rice, plant breeders can also cross perennial species with domesticated annual relatives to produce perennial hybrids with desirable traits derived from the annual parent3. More

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Bacterial strains, primers, and growth conditionsBacterial strains, plasmids, and primers used in this study are shown in Supplementary Table S1. Escherichia coli strains carrying plasmids used in conjugation experiments were grown at 37 °C in LB medium. S. fredii CCBAU25509 (SF2) and its derivatives were grown at 28 °C in TY medium (5 g tryptone, 3 g yeast extract, 0.6 g CaCl2 per liter). To screen and purify conjugants or obtain pure cultures of bacteria, antibiotics were supplemented as required at the following concentrations (μg/mL): for E. coli, gentamicin (Gen), 30; and kanamycin (Km), 100; for Sinorhizobium strains, trimethoprim (Tmp), 10; nalidixic acid (Na), 30; and kanamycin (Km), 100. To screen sacB mutants from SF2 derivatives, firstly SF2 tolerance of 8%-30% sucrose in the TY medium was measured by the growth curve using Bioscreen C (Oy Growth Curves Ab Ltd, Raisio, Finland), and then the TY medium containing 10% sucrose was chosen as the selection medium.Construction of S. fredii derivatives harboring xenogeneic PsacB-sacB
The multipartite genome of SF2 consists of a chromosome (Ch, GC% = 62.6%), a chromid (pB, GC% = 62%) [31], and a symbiosis plasmid (pA, GC% = 59%) [26]. Within each replicon, an insertion position, with GC% of its 10 kb flanking region being the same as the replicon average, was chosen for subsequent experiments (Fig. 1A). The suicide plasmid pJQ200SK carries the wild-type sacB gene (characterized by its low GC content of 38.8%; 1422 bp) and its promoter region PsacB (GC% = 36.1%, 446 bp) from Bacillus subtilis subsp. subtilis str. 168 [32]. A Km-resistant cassette from pBBR1MCS-2 [33] was amplified and assembled with a linearized pJQ200SK lacking the Gm-resistant cassette using a seamless cloning kit (Taihe Biotechnology, Beijing, China) as described previously [34]. This generated pJQ-L carrying the wild-type low GC% sacB (38.8%; 1422 bp; L-GC). The sacB gene with medium (54.6%; M-GC) or high GC (61.6%; H-GC) content in its synonymous codons was synthesized (Fig. S1), and used to replace the wild-type low GC% sacB gene of pJQ-L to generate pJQ-M and pJQ-H. This was also performed using the seamless cloning method as described above with the linearized pJQ-L lacking the wild-type sacB. Three genomic segments of SF2 (pA:330682-331687, pB:702541-703493, Ch:674057-675207) were individually cloned into each of pJQ-L, pJQ-M, and pJQ-H at the SmaI site using the seamless cloning method, which allowed subsequent integration of xenogeneic cassettes into three replicons. This generated nine plasmids (pJQ-L_pA, pJQ-L_pB, pJQ-L_Ch; pJQ-M_pA, pJQ-M_pB, pJQ-M_Ch; pJQ-H_pA, pJQ-H_pB, pJQ-H_Ch), which were transformed into E. coli DH5α and verified by Sanger sequencing before conjugation into rhizobia via triparental mating with helper plasmid pRK2013 [35]. This generated nine SF2 derivatives individually carrying a xenogeneic cassette in a replicon (Fig. 1A). The correct insertion of the xenogeneic cassette was checked by PCR.Fig. 1: Screening mutations in xenogeneic sacB of different GC content.A The xenogeneic cassettes harboring sacB of L-GC, M-GC, or H-GC were individually inserted into the symbiosis plasmid (pA; GC% = 59%), chromid (pB; GC% = 62%), or chromosome (Ch; GC% = 62.6%) of Sinorhizobium fredii CCBAU25509. Gene IDs surrounding each insertion position are shown. GC% of the three sacB versions were 38.8% (L-GC, the wild-type version from Bacillus subtilis subsp. subtilis str. 168), 54.6% (M-GC, synthesized), and 61.6% (H-GC, synthesized). The wild-type PsacB (GC% = 36.1%, 446 bp) of B. subtilis 168 was cloned together with each of the three versions of sacB. The number of A, T, C, or G in the 1422 bp sacB gene is indicated. B Growth curves in TY medium. C Levansucrase enzyme activity assay of crude proteins collected at OD600 = 1.2 in TY medium. Different letters indicate significant difference (Average ± SEM; ANOVA followed by Duncan’s test, alpha = 0.05). D Growth curves in TY medium supplemented with 10% sucrose. E Schematic view of culturing, mutant screening, and mutation identification in this work. sacB, levansucrase gene; km, kanamycin resistance gene.Full size imageThe xenogeneic silencer MucR prefers low GC% DNA targets [29, 30], and its potential role in niche differentiation for IS community members was tested. SF2 has two mucR copies, and the in-frame deletion mutant ΔmucR1R2 was constructed by using an allelic exchange strategy: upstream and downstream ~500 bp flanking regions of mucR1 or mucR2 were amplified and assembled with the linearized allelic exchange vector pJQ200SK. The pJQ200SK derivative used to delete mucR1 was linearized and then cloned seamlessly with the sequence coding MucR1 and C-terminal fused FLAG-tag. The resultant plasmid was conjugated into SF2 to generate SF2MucR1FLAG. The xenogeneic cassettes carrying plasmids (pJQ-L_pA, pJQ-M_pA, pJQ-H_pA) were then inserted into the same position of pA in ΔmucR1R2 and SF2MucR1FLAG, and verified by PCR.Mutant screening and calculation of mutation frequencyTo screen sacB mutants from SF2 derivatives, single colonies of S. fredii derivatives were inoculated and grown to an OD600 = 0.2, 0.6, 1.2, and 2.0, and dilutions were applied to plates with and without 10% sucrose respectively. The number of colonies on the 10% sucrose TY plates was recorded as “A” at the dilution of 10−a, and the number of colonies on the sucrose-free TY plates was recorded as “B” at the dilution of 10−b. The total mutation frequency was then calculated by (A·10-a)/(B·10-b). Independent colonies on the 10% sucrose TY plates were further purified on the same medium plates, and the full length of PsacB-sacB fragment was amplified by colony PCR. Gene loss, SNPs or short InDels, or large insertion mutations were identified by electrophoresis analysis of PCR products. Representative clones with large insertion mutations were selected for Sanger sequencing. Three independent experiments were performed for all test strains.Enzyme activity assay for levansucraseTo evaluate the function of xenogeneic sacB in SF2 derivatives, sucrose was dissolved in the buffer solution (0.1 M CH3COONa, pH 5.5), and the total protein extract of bacteria was added (calibrated to the same concentration) to make the final concentration of sucrose 1%, and the reaction system was incubated at 28°C for 12 h. After adding the color development solution (3,5-dinitrosalicylic acid 6.3 g, sodium hydroxide 21.0 g, potassium sodium tartrate 182.0 g, phenol 5.0 g, sodium metabisulfite 5.0 g in 1000 mL water; BOXBIO, Beijing, China), the enzyme was inactivated at 95 °C for 5 min, and the absorbance value at 540 nm was measured to calculate the glucose content. Determination of the release of glucose and fructose from sucrose allowed calculation of the total activity of the levansucrase. One unit (U) of enzyme is defined as the amount of enzyme required for producing 1 µmol glucose per min in reaction buffer. The specific activity of levansucrase hydrolysis activity is the activity units per mg of protein (U/mg).5′RACETo determine the transcription start site of the sacB gene, a 5′RACE experiment was performed with the 5′RACE kit (Sangon, Beijing, China) for Rapid Amplification of cDNA Ends using three gene-specific primers (Table S1) that anneal to the known region and an adapter primer that targets the 5′ end. Products generated by 5′RACE were subcloned into the TOPO-TA vector and individual colonies were sequenced.RNA extraction and RT-qPCRTo determine transcriptional levels of the major active ISs in SF2 and its ΔmucR1R2 mutant, strains were grown in 50 mL TY liquid medium to an OD600 of 1.2. A bacterial total RNA Kit (Zomanbio, Beijing, China) was used for total RNA extraction. cDNA was synthesized using FastKing-RT SuperMix (TIANGEN, Beijing, China). qPCR was performed by using QuantStudio 6 Flex and 2× RealStar Green Mixture (Genstar, Beijing, China). The primer pairs used are listed in Table S1. The 16S rRNA gene was used as an internal reference to normalize the expression level. Three independent biological replicates were performed.ChIP-qPCRTo test the potential recruitment of MucR in the xenogeneic PsacB-sacB region, three SF2 derivative strains harboring sacB of different GC% in the pA replicon and MucR1-FLAG (Table S1; MucR1-FLAG: L-GC, MucR1-FLAG: M-GC, MucR1-FLAG: H-GC) were cultured until the OD600 had reached 1.2. Formaldehyde was added into the TY medium to a final concentration of 1%, which was then incubated at 28 °C for 15 min. To stop crosslinking, glycine was added to a final concentration of 0.1 M. The cross-linked samples were harvested (5000 × g, 5 min, 4 °C) and washed twice with cold phosphate-buffered saline (PBS). After the pellets were ground into fine powder in liquid nitrogen, the samples were resuspended in buffer containing 1% SDS and 1 mM phenylmethanesulfonyl fluoride, and lysed by sonication using a sonicator (Q800R3, QSonica). Chromatin immunoprecipitation (ChIP) was performed using the ChIP assay kit (Beyotime, Shanghai, China) according to the manufacturer’s recommendations. The supernatant was collected and chromatin was immunoprecipitated with Anti-FLAG M2 antibody (Sigma). Input control and DNA obtained from the immunoprecipitation were amplified by PCR using primers listed in Table S1. The recruitment level of FLAG-tagged MucR1 in multiple regions within the PsacB-sacB fragment inserted by ISs at high frequency was detected by ChIP-qPCR.Crosslinking and western blotting assayTo test the ability of MucR1 to form homodimer in SF2 derivatives carrying sacB in pA, rhizobial cells (SF2MucR1FLAG, MucR1-FLAG: L-GC, MucR1-FLAG: M-GC, and MucR1-FLAG: H-GC) were cultured in 50 mL TY medium to an OD600 of 1.2. Formaldehyde was added at a final concentration of 1% in the culture which was then shaken at 28 °C, 100 rpm for 15 min to allow crosslinking. The crosslinking reaction was terminated by adding a final concentration of 100 mM glycine (28 °C, 100 rpm, 5 min). 1 mL of the above solution was centrifuged (5000 × g, 4 °C, 1 min), resuspended in 50 µL SDS loading buffer to a uniform cell density, and then boiled for 10 minutes for lysis. Next, lysates were separated on 12% SDS-PAGE and transferred to a nitrocellulose membrane. For immunodetection of individual proteins, the method described previously was used [30]. Briefly, mouse monoclonal Anti-FLAG M2 antibody (Sigma), HRP (horseradish peroxidase) conjugated goat Anti-mouse IgG (Abcam), and eECL Western blot kit (CWBIO, Beijing, China) were used, and chemiluminescence signals were visualized using Fusion FX6 (Vilber) and Evolution-Capt Edge software.Protein purificationTo purify MucR1 protein, E. coli BL21(DE3) carrying His6-SUMO-tagged MucR1 in the pET30a [29] was cultured in 500 mL LB medium until OD600 reached 0.8. The procedure described previously was used [30]. IPTG was then added to the culture to a final concentration of 0.6 mM and switched to 18 °C at 150 rpm for 12 h. Cells were harvested by centrifugation (5000 × g, 5 min, 4 °C) and resuspended in 30 mL of lysis buffer (25 mM Tris, pH 8.0, 250 mM NaCl, 10 mM imidazole) supplemented with 0.1 mg/mL DNase I, 0.4 mg/mL of lysozyme, and protease inhibitor mixture (Roche). After 30 min incubation and 120 sonication cycles (300 W, 10 s on, 10 s off), lysates were removed by centrifugation (18,000 × g, 4 °C, 30 min) and filtration through a 0.22 μm membrane. The supernatant was loaded onto Ni-Agarose Resin (CWBIO, Beijing, China) pre-washed using lysis buffer, washed 3 times with wash buffer (lysis buffer containing 20 mM imidazole), and then eluted by lysis buffer containing imidazole gradient (100, 200, 300 mM imidazole). The purified proteins were finally concentrated by ultrafiltration and redissolved in storage buffer (25 mM Tris, pH 8.0, 250 mM NaCl, 10% glycerol) prior to use or storage at −80 °C.DNA bridging assayTo determine if MucR1 can form DNA-MucR1-DNA complex with various regions of xenogeneic PsacB-sacB fragment, a DNA bridging assay described earlier [30, 36] was performed with modifications. DNA probes were prepared by annealing of synthesized complementary strands (PsacB −90~−24) or by PCR amplification (PsacB −90~+3, sacB +710~+802, sacB +908~+1007) using 5′-biotin-labeled or 5′-Cy5 primers (Table S1). In each bridging assay, 100 μL of hydrophilic streptavidin magnetic beads (NEB) were washed twice with 500 μL of PBS and then resuspended in 500 μL of coupling buffer (20 mM Tris-HCl, pH 7.4, 1 mM EDTA, 500 mM NaCl). Then, the suspension was supplied with 10 pmol of biotin-labeled DNA and incubated with the beads for 30 min at room temperature with gentle rotation. The resulting beads were washed twice with 500 μL of incubation buffer (20 mM Tris, pH 7.4, 150 mM NaCl, 1 mM dithiothreitol, 5% glycerol (vol/vol), 0.05% Tween 20) and resuspended after the addition of 10 pmol Cy5-labeled DNA and 10 μL HRV 3C protease to a final volume of 500 μL. The HRV 3C protease was used herein to remove SUMO. A twofold serial dilution of the protein sample was added to each 50 μL aliquot of bead suspension, and supplemented with incubation buffer to 60 μL final volume. After 30 minutes of incubation with gentle rotation at room temperature, the mixture was placed on a magnetic stand for 5 minutes. The supernatant was collected and labeled as Sample A. The beads were mixed with 60 μL of elution buffer (incubation buffer with 0.1% SDS and 20 μg/mL biotin) and incubated in a boiling water bath for 10 min. The eluted samples were labeled as Sample B. Cy5 fluorescence signals of Sample A and B were detected by a Microscale Thermophoresis Monolith NT.115 system (NanoTemper). The Cy5 fluorescence signal of the Sample A from the treatment without MucR1 was defined as 100% input signal.Statistical analysesAnalysis of variance (ANOVA) followed by Duncan’s test, Student’s t-test, and Fisher’s exact test were performed using GraphPad Prism 8. The closest homolog of individual active ISs and their family identification were determined using ISfinder [37]. Target sequence logos of ISs were generated by multiple sequence alignments of insertion sites within xenogeneic PsacB-sacB or genomic background using the program WebLogo [38].Although the fundamental niche, not constrained by biological interactions, cannot be determined by observation [15], the realized niche, representing a proportion of the fundamental niche where organisms actually live under abiotic and biotic interactions, can be estimated by correlative approaches [15, 39]. In order to address the influence of intracellular variables on biased IS insertions into nine common gardens, the within outlying mean index analysis developed for niche differentiation analysis was carried out using the R package “subniche” [40, 41]. The intracellular environmental gradients were determined by Principal Component Analysis (PCA) based on variables as follows: GC% of different sacB versions, replicon GC%, the number of each IS in the corresponding replicon where sacB is inserted, available insertion sites of ISs in different sacB versions, and levansucrase activity of strains carrying different sacB versions. Within this multidimensional Euclidean space (environmental space), mean positions in realized (sub)niches and parameters of each IS were obtained for the whole data set (realized niches in environmental space defined by nine common gardens) or various subsets (realized subniches in sub-environmental spaces identified by the hierarchical clustering analysis with the ward.D method based on the Euclidean distance matrix) [41]. Two and three subsets rather than four and more subsets were statistically analyzable. By comparing to the overall average habitat conditions (G) or the average subset habitat conditions (GK) of the spatial domain, ISs selecting for a less common habitat were indicated by their significantly higher niche marginality values compared to the simulated values, based on a Monte Carlo test with 1,000 permutations, under the hypothesis that each IS is indifferent to its intracellular environment [40]. More

Data acquisition and preparationStructured datasetsWe used structured North American Breeding Bird Survey (BBS) data, which is conducted annually over  > 2500 routes across the United States and Canada11,12 during the peak of the breeding season (May and June). BBS routes were approximately 40 km long with 50 stops spaced 0.8 km apart. At each stop a 3-min point count was conducted, where all species seen or heard were recorded12. We downloaded the entire dataset, 1966–2019, to identify each observer’s first year and account for differences in survey experience. We created a binary variable for the observers’ first year, with 1 indicating the first year they provided data, and 0 indicating all subsequent years. We then subset the data to years 2010–2019 to align with available community science data. We zero-filled BBS data by adding zeros for each species on routes in which birds were not detected in each year.Semi-structured datasetWe used the eBird Basic Dataset as a semi-structured dataset. We used checklists within the US and Canada during June and July from 2010 to 2019. Data were filtered to impose structure on the observation process and minimize effects of unequal spatial and temporal sampling using the auk package in program R24,25,56,59,60. Data were filtered to only include complete checklists where observers recorded counts of all species detected to reduce effects of preferential species reporting61. We also filtered data based on observer effort to only include checklists  More

Selection of environmental-biotic events to be studiedIn global warming events associated with mass extinctions, the current environmental changes are similar to those recorded during the end-Ordovician, end-Guadalupian, and end-Permian mass extinctions. Therefore, I analyzed global surface temperature anomalies, mercury pollution concentrations, and deforestation percentages in these three mass extinctions and in the current crisis. The asteroid impact at the K–Pg boundary and nuclear war cause the formation of stratospheric soot aerosols distributed globally, thus inducing sunlight reductions and global cooling (impact winter and nuclear winter). I also analyzed stratospheric soot aerosols as a possible cause of future extinctions.Most likely case and worst caseThe most likely case corresponds to the reduction of CO2 emissions resulting from human conduct, the protection of forests, and the introduction of anti-pollution measures in the future under the Paris Agreement on Climate change and Sustainable Development Goals (SDGs). The worst case corresponds to the scenario in which humans fail to stop increasing global surface temperatures, pollution, and deforestation until 2100–2200 CE.I use the average of the RCP4.5 and RCP6.0 cases in the Intergovernmental Panel on Climate Change (IPCC)8 as the most likely case of GHG emissions, representing the middle of the four potential GHG emissions cases (RCP2.6, 4.5, 6.0, and 8.5) in Fifth Assessment Report of the IPCC8, approximately corresponding to the middle of SSP2-4.5 and SSP3-7.0 in Sixth Assessment Report of the IPCC9. The timing of decreased global GHG emissions is 2060–2080 CE. Therefore, I use the average GHG emissions and global surface temperature anomalies of the RCP4.5 and RCP6.0 cases as the most likely values and those of the RCP8.5 case as the worst-case scenario, marked by stopping GHG emissions from 2090 to 2100 CE8,9, as this case corresponds to the highest GHG emissions8,9.Surface temperature anomaly, environment, and extinction magnitude dataData on surface temperature anomalies and extinction percentages are from Kaiho4. Changes in industrial GHG emissions and global surface temperature anomalies are sourced from the Fifth and Sixth Assessment Report of the IPCC8,9.Pollution can be represented by mercury concentrations measured in sedimentary rocks recording mass extinctions8 and in recent sediments deposited in seas and lakes25,26 because mercury is toxic to plants and animals and because its sources include volcanic eruptions, meteorite impacts, and the combustion of fossil fuels10,33, which are common sources of pollutants, and because it can be commonly measured from sedimentary rocks recording mass extinctions33. The mercury concentration is related to the CO2 emission amount during global warming because of the common sources of mercury and CO2 (volcanism and fossil fuel combustion influencing global warming). Thus, the future mercury concentrations are estimated based on the CO2 emission amounts estimated by the IPCC8,9. Since mercury and the other pollutants mainly come from oil, coal, and vegetation33, the amount of mercury released should change in parallel with industrial CO2 emissions because there is a good correlation between mercury and CO2 emissions11.Deforestation occurs by the expansion of agricultural areas and urban areas, which are strongly related to human populations13,28. Thus, future deforestation percentages are estimated based on estimated future population data27 (Supplementary Table S2). The severity of deforestation in each event is expressed by the occupancy % of the deforested area in the pre-event forest area in (i) the Permian–Triassic transition marked by the largest mass extinction based on plant fossil records24 and (ii) 2005–2015 CE as a representative of the Anthropocene epoch12,13,28 based on the actual forest area relative to the pre-agriculture phase before 4000 BP. Deforestation is related to the human population because agriculture and urbanization have caused deforestation13,28. I estimate the past and future deforestation percentage using human population data in the past and future21 based on the parallel growth of the human population and deforestation13,28.Amount of stratospheric soot was calculated using a method of Kaiho and Oshima34 (Supplementary Table S1). I obtained global surface temperature anomaly caused by stratospheric soot using Fig. 5 of Kaiho and Oshima34.I then use those data to estimate the future extinction magnitude based on the assumption that the Earth and contemporary life at the time of each crisis are more or less mutually comparable throughout time and to the present day.I estimate the magnitude of the species animal extinction crisis between 2000 and 2500 CE using Figs. 1, 2 and Supplementary Tables S1 and S2 in each cause under the most likely case and worst case under three nuclear war scenarios (zero, minor, and major; Fig. 2d)15 in the PETM and mass extinction cases, respectively (Supplementary Tables S3, S4; Fig. 3). Finally, I estimate the magnitude of current animal extinction crisis by the four causes as an average of the species extinction magnitude by the four causes in Fig. 3. I use two different contribution rates of temperature anomalies, pollution, deforestation, and stratospheric soot by nuclear wars, 1:0.2:0.1:1 for marine animals and 1:0.5:1:1 for terrestrial tetrapods (different contribution case considering lower influence of pollution and deforestation to marine animals rather than terrestrial animals) and 1:1:1:1 for marine animals and 1:1:1:1 for terrestrial tetrapods (equal contribution case considering high influence of pollution and deforestation to marine animals via rain and soil erosion) (Supplementary Tables S5–S9). These contribution rates are estimated as end-members to show ranges of animal species extinction magnitude (%). More

Madhusudan Katti says ecology would benefit from including perspectives from all of Earth’s inhabitants.Credit: Marc Hall

Decolonizing science

Science is steeped in injustice and exploitation. Scientific insights from marginalized people have been erased, natural history specimens have been taken without consent and genetics data have been manipulated to back eugenics movements. Without acknowledgement and redress of this legacy, many people from minority ethnic groups have little trust in science and certainly don’t feel welcome in academia — an ongoing barrier to the levels of diversity that many universities claim to pursue.
In the next of a short series of articles about decolonizing the biosciences, Madhusudan Katti suggests five shifts that ecologists need to make to unravel the effects of colonization on their field. Katti, an evolutionary ecologist at North Carolina State University in Raleigh, would also like to see stronger inclusion of uncredentialed experts and Indigenous communities in research.

Last year, my colleagues and I wrote a paper highlighting five shifts that would help to decolonize ecology (C. H. Trisos et al. Nature Ecol. Evol. 5, 1205–1212; 2021). Ecologists need to improve how they incorporate varied perspectives, approaches and interpretations from the diverse peoples inhabiting Earth’s natural environments. The five shifts are: the individual need to decolonize one’s mind; understand the history of colonization and how it shaped Western ecology; facilitate access to and dissemination of data; recognize diverse scientific expertise; and establish inclusive research groups. Although it can be difficult to make reforms given how resistant institutions are to change, we are optimistic because we have received invitations to speak on these issues. People are ready for these conversations.
Decolonizing science toolkit
My colleagues and I developed a workshop around the five shifts. We have conducted the workshop at my institution, and at the annual conference of the Society for Integrative and Comparative Biology. For each of the shifts, I have participants brainstorm and write down challenges and solutions that might lead to progress in these areas for their own research departments or institutions. We address them, shuffle groups and suggest policy changes and future action.Some organizations are already moving forward with some low-hanging fruit, such as making data and published results more accessible. However, open-access publishing models put an even greater burden of publication costs on authors and perpetuate inequalities, because early-career researchers and those in the global south often can’t afford them.The most contentious area tends to be the reluctance of academia to accept non-credentialed expertise such as traditional knowledge. Universities are in the business of giving out credentials in the form of degrees. If academia no longer requires a PhD, that can be a challenge to that model. There are also few, if any, incentives or rewards to spend time working towards decolonizing academia, even though it takes time and effort away from furthering individual careers.As an Indian American, I would like to see institutions expand antiracism conversations rather than introduce new checklists of things to do. For example, at annual meetings, it would be great to see scientific societies make more connections with the Indigenous communities where we work and invite them to share their perspectives.
This interview has been edited for length and clarity. More

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Changes of straw degradation characteristics at different culture stagesCorn straw degradation ratioCorn straw weight loss in M44 at F1 reached 35.90% at 15 ℃ for 21 days, which was greater than that at F5, F8, and F11 by 2.33%, 3.01%, and 3.35%, respectively. There were no significant differences between F8 and F11(Fig. 1).Figure 1Corn straw degradation ratio was measured at different culture stages. The same small letter means there was no significant difference, and different small letters indicate significant differences at p  More