Nature Agriculture

The cyanogenic potential is measured as the amount of pre-cyanogenic compounds contained in the plant tissue . The cyanogenic capacity is measured as the amount of cyanide released by a given quantity of plant tissue over a unit of time . The enzymatic activity, which can be variable across species and genotypes, will determine how closely measurements of cyanogenic potential and cyanogenic capacity correspond . The interaction between cyanogenic plants and insect herbivores is complex and maybe be affected by several biotic and abiotic factors . As with other chemical defense mechanisms, specialist insect herbivores may have adaptations that protect them from cyanide produced by their host plant including metabolizing it for use of the nitrogen in protein synthesis or sequestering it for their own defense . Generalist herbivores may avoid cyanide intoxication by balancing their diet with cyanogenic and acyanogenic foods .As a defense mechanism, cyanogenesis can operate in two ways depending on the cyanogenic capacity of a given plant tissue: deterrence or intoxication . Cyanogenesis is not a universally effective deterrent and for some insects cyanide may even act as a phagostimulant . Cyanogenesis seems most effective as a deterrent when the cyanogenic capacity is high, release is rapid, and the insect herbivore is an opportunistic generalist rather than a well-adapted specialist . Below a certain threshold, dependent on the herbivore, square pots cyanogenesis is ineffective as a deterrent . Intoxication by cyanide consumption typically occurs when herbivores consume large amounts of plant material with lower cyanogenic capacity . In this sort of situation, cyanide may be released within the digestive track, causing lethal damage or inhibiting growth of the insect .

Plants with higher cyanogenic capacity may be rejected before an insect can consume a sufficient dose. There is variation in the susceptibility of Lima bean to damage by L. hesperus but this has only been catalogued within a small number of commercial cultivars. The first step of this study is to catalogue this variation within a more diverse panel of accessions. From this research, the University of California Davis Dry Bean Breeding program will be able to select better parents and introduce more diversity into the Lima Bean breeding pipeline. In addition to characterizing the variation in L. hesperus tolerance or resistance, understanding more about the possible mechanisms that contribute to this phenotype will help target selection in breeding. To do this a field study in which multiple varieties were vacuum sampled will be analyzed to demonstrate the choice of L. hesperus in the field when multiple varieties are present. It is unknown if cyanogenesis is an effective defense againstL. hesperus in Lima bean. In combination, these studies illustrate the extent of variation in L. hesperus resistance or tolerance phenotypes in Lima bean as well as determine if cyanogenesis is induced by L. hesperus presence and if there is a negative correlated between cyanide and L. hesperus population growth. The other block was a control not treated with insecticides. In 2019, UC 92 plots were vacuumed to in each block to verify that L. hesperus levels were lower in the insecticide treated plots. In 2021, the vacuum equipment was unavailable, so water traps were used to verify the difference in L. hesperus pressure between blocks. Both fields were drip irrigated and conventionally managed. Each variety was planted in a single row in eight plots of 4.5 meters . The plots were randomized within eight sub-blocks. Field notes on days to flowering, growth habit, seed color, and flower color were taken. Yield and 100-seed-weight measurements were conducted after harvest. Four ofthe lines were excluded from the analysis due to poor germination or photoperiod sensitivity.

In a small trial at the University of California Davis Student Organic Farm, nine Lima bean varieties were planted on June 1, 2017, at 38°32’32.5″N 121°46’01.3″W . The field was flood irrigated and organically managed. Every variety was planted in two plots, one of which was randomly assigned a location within each of two blocks. Each plot was 20 feet long and six 30-inch rows wide. Starting at the time of flowering, July 21, 2017, the middle two rows of every plot were vacuumed each week between 11am and 1pm. Samples for each plot were bagged and then frozen. Insects were then transferred to vials of ethanol and adult L. hesperus in the sample were counted and sexed. Adult L. hesperus are highly mobile and can readily fly between small plots. Nymph counts would therefore have been a better measurement to take. However, nymphs were not counted because many were crushed by the force of the vacuum or were two small to be accurately identified with the available expertise. The middle two rows of each plot were harvested measured for total yield and 100 seed weight. The variety UC Lee was removed from the study due to poor germination rates.Five cultivars of California-adapted Lima bean were selected for this study with the aim of representing the diversity of seed size, growth habit, cyanogenic capacity, and tolerance of L. hesperus . All the varieties had white seed coats as this is the market standard for dry Lima beans produced in California. Prior research found that there is not a correlation between seed coat color and cyanogenesis . Originally, one wild accession was included for comparison but due to photoperiod sensitivity and delayed phenology, it proved infeasible to collect samples from these plants in synchrony with the others.In four greenhouse plantings, plants of each variety were individually germinated from seed in azalea pots with approximately two liters of UC Agronomy potting soil mix. Each pot was placed in its own cage with drip line for water and fertilizer . Each cage was randomly assigned a position in the greenhouse. Three flowers and three young podsof each plant were collected one, two, and three weeks after flowering. Flowers were selected with white petals, indicating that the day of sampling was their first to open. Immature pods were approximately 2cm long . Additionally, succulent mature seed tissue was collected four weeks after flowering were sampled. Mature seed samples consisted of a slice of the bean from the opposite side of the hilum from the micropyle of approximately 200mg that would fit into a 96-well plate collection tube . All samples were frozen at -80°C and later analyzed for cyanogenic capacity using the Feigl-Anger paper assay . While some have critiqued this method for being only semiquantitative, it was selected based on the available resources and practicality for analyzing large numbers of samples .Half of the plants were randomly assigned to a treatment group which had adult L. hesperus added to their bug dorm one week after flowering. In the pilot study, 25 adult L. hesperus were added. The resulting level of herbivory was high and, as a result, the susceptible varieties, UC 92 and UC Lee, had insufficient flowers survive for sampling or pod development. In the subsequent rounds of the experiment a total of only 14 adult L. hesperus were added, square plant pot seven one-week-old adult males and seven one-week-old adult females. This level of herbivory preserved sufficient flowers for sampling and pod development on susceptible plants. The one-week-old adult insects were added after the week one flower and pod samples were collected so that those samples had no interaction with the L. hesperus. All cages had a low level of thrips infestation; however, the greenhouses were not treated with insecticide during the study. All L. hesperus introduced to cages in the experiment were one-week post emergence adults reared in a colony founded by individuals collected from Lima bean and alfalfa fields in the fall of 2019 and 2020 . The colony was maintained at 20°C and 12 h of photo period. Adults were held in 30.5cm cube collapsible cage with a bedding of shredded white printer paper, a water-soaked organic cotton round , hulled sunflower seeds, and fresh organic green beans supplied three times a week. The egg-laid beans were moved to rearing tubs where they emerged in approximately 7-10 days. Nymphs were supplied with a bedding of shredded white printer paper and green beans three times per week and moved to adult cages at the time of emergence.The pilot study, September 2019-December 2020 was conducted in a small greenhouse at the Orchard Park Greenhouse Facility at UC Davis and included only two plants of each variety.

The second round conducted in December 2019-March 2020 was conducted in the same greenhouse. In round two, six plants of each variety were planted and divided equally between the two treatment groups. The third round, March 2020-May 2020, was conducted in a neighboring greenhouse that had been enclosed with black plastic drapes to exclude all-natural light. Artificial lights lit the greenhouse in a 12-hour photo period. This was done in an attempt to include a photo period sensitive wild Lima bean accession in the study but even with this treatment, it was not possible to synchronize its flowering with that of the commercial cultivars. In round three, six plants of each variety were planted and divided equally between the two treatment groups. In the fourth round of the study, January 2021-April 2021, the experiment was planted in a neighboring greenhouse with natural light. In round four, eight plants of each variety were planted and divided equally between the two treatment groups. In each round of the experiment, an equal number of plants for each variety and treatment group were planted. However, due to poor germination, not every plant survived to participate in the study. Across the three plantings there were a total of 16 replicates of each variety divided between two treatment groups – so eight plants per treatment. In all rounds of the studies, cages were randomly assigned positions within the greenhouse using the Microsoft Excel random number generator function. All the flower and pod samples were frozen at -80°C for several months before they were processed with a colorimetric assay with Feigl-Anger paper . Defrosting samples were exposed to Feigl-Anger paper for 0-15 minutes, 15-30 minutes, 30-60 minutes, and 60-90 minutes after being removed from the freezer. The results of the assay were scanned and analyzed using the readplate2 plugin on ImageJ 1.52q . This semiquantitative method provided a measurement of the intensity of blue produced by the interaction of volatilized HCN and the chemical treatment of the Feigl-Anger paper. Since the volatilized HCN had to be synthesized from enzymatic activity in thawing sample tissues, a standard of KCN in NaOH solution, used in other studies, was not considered sufficiently comparable to use in estimating the quantities of cyanide released from tissues during each exposure window.To understand how well L. hesperus survive and reproduce on varieties of Lima bean, populations founded by adult L. hesperus added to cages in the cyanogenic response experiment were collected and analyzed after three weeks. The development of L. hesperus is temperature dependent but takes approximately 4 weeks at 20°C, with this being the approximate temperature of the greenhouses in which this experiment was conducted . Three weeks is therefore not enough time for eggs to be laid and the resulting offspring to develop into adults and so the adults collected were survivors of the initial introduction rather than newly developed adults. The number of surviving adults and nymphs were counted for each cage in the treatment group. In rounds three and four, the nymphal instars were identified to indicate the speed of development for L. hesperus on the various varieties of Lima bean. Analysis All statistical analysis was conducted in R version 4.2.1 . For the final analysis, only the 60–90-minute exposure window was used due to concerns that plate position may have affected the results of earlier windows since samples on the outside of the 96-well plate may have defrosted more quickly than samples in the interior of the 96-well plate . This design flaw was not apparent in the time trial since a smaller number of samples were used and so the thermal mass of the plate was lower. It has been noted as an important lesson in experimental uniformity. Prior to publication, a statistical model including plate position may be tested to analyze results from earlier exposure windows.

The disruption in stoichiometry of highly dosage-sensitive components of macromolecular complexes and pathways, across regulatory, signaling and metabolic networks, can negatively affect fitness or be lethal. Thus, partial to complete dominance of one subgenome over the other subgenome may help resolve genetic incompatibilities. Previous studies of ancient allopolyploids revealed that one subgenome may be dominantly expressed and over millions of years retain a significantly greater number of genes. Subgenome dominance has been observed in many allopolyploids, to varying amounts, but not in all allopolyploids nor in any autopolyploids . Thus, the underlying genetic and/or epigenetic mechanisms driving expression dominance remains poorly understood. Previous studies have shown that densities of transposable elements near genes are predictive of which subgenome is more highly expressed. However, if and how much genetic divergence of the diploid progenitors contributes to subgenome expression dominance has yet been evaluated in allopolyploids and especially in vertebrates. An additional whole genome duplication, termed TGD or 3 R, occurred in the teleosts fish lineage, estimated 225–350 million years ago, at the base of the largest and most diverse group of vertebrates. Some clades including Salmonidae, Cyprinidae and Corydoradinae have undergone their own, independent fourth rounds of polyploidization. Cyprinids, the carp family, Grow bag for blueberry plants contain roughly 600 polyploid species derived from potentially at least thirteen polyploidization events.

The family is delineated into eleven subfamilies, including Cyprininae that consists of eleven tribes, of which seven are largely composed of polyploids, Thus, cyprinids are an ideal model family for investigating subgenome evolution following multiple independent polyploid events within vertebrates. To date, to the best of our knowledge, subgenome-resolved assemblies of only three allopolyploid species from the Cyprinini tribe are publicly available, including the common carp, goldfish, and the hexaploid Prussian carp. Some evidence for subgenome expression dominance was uncovered from the analysis of both the common carp and goldfish genomes. However, no evidence for subgenome dominance at the transcriptome level was observed following the analysis of the hexaploid Prussian carp genome. Comparative genomic analysis of the Prussian carp revealed biased duplicate gene retention of certain genes towards one subgenome. This suggests that the genomes of cyprinine allopolyploid cyprinid fishes may exhibit subgenome dominance to varying levels. In this context, the role of transposable element differences, parental effects and/or genetic divergence of diploid progenitor species contributing to observed subgenome expression dominance remains poorly understood. Therefore, the evaluation of multiple independently derived cyprinine allopolyploids can provide valuable new insights into the underlying mechanisms of subgenome dominance. A robust phylogenomic framework for the subfamily Cyprininae is needed to phylogenetically localize polyploidy events and investigate the underlying genetic mechanisms contributing to subgenome dominance in allopolyploid fishes. However, the maternal and paternal diploid progenitors of known polyploids in this group remain largely unknown.

A recent study tried to address this point within this group using three single-copy nuclear loci, but the phylogenetic history of these three genes may not reflect the true history of species relationships within this subfamily. Phylogenomic analyses based on hundreds of orthologous markers from across the genome should reflect a more accurate evolutionary history of the species and more likely to reveal the diploid progenitors of allopolyploids. In the present study, we thus aim to resolve the phylogenetic relationships among several key Cyprininae species, uncover the polyploid origin of three allopolyploid species, identify the closest extant relatives of their diploid progenitors and investigate subgenome dominance and its genetic basis in the allopolyploids. To accomplish these goals, we assemble de novo high-quality reference genomes of twenty-one cyprinid fishes from across five subfamilies using PacBio HiFi long reads. Furthermore, we generate transcriptome data from several distinct organs to investigate subgenome expression dominance in three allotetraploids. Our study provides new insights into the evolutionary history of Cyprininae, including the identification of maternal and paternal diploid progenitor lineages of three independently formed allopolyploids, the genetic basis of subgenome dominance in these allopolyploids, and new large-scale genomic resources for the community as a foundation for future studies.Whole genomes of 21 cyprinid fishes were sequenced with PacBio CCS reads with an average of 32.34-fold coverage and Illumina paired-end 150 bp reads with an average 66.86- fold coverage, in total yielding 2.24 trillion base pairs of raw read data . These datasets were de novo assembled using Hifiasm, yielding high-quality genomes with an average contig N50 size of 23 Mb . The new assemblies ranged in size from 0.81 to 1.83 Gbp, similar to the estimated genome sizes obtained from k-mer analysis of Illumina reads .

A high percentage of Illumina reads aligned against the assembled contigs and high BUSCO scores , suggesting that the biggest proportion of the genomes was assembled . Previous phylogenetic work using three single-copy nuclear loci suggested that three species Procypris rabaudi , Spinibarbus sinensis and Luciobarbus capito are likely tetraploids. To generate chromosome-level genomes, high-throughput chromosome conformation capture reads, at ~100-fold coverage per haplotype, were obtained and scaffolded for each tetraploid with the ALLHiC algorithm. In total, 94.43%, 97.56% and 98.83% of all bases corresponding to S. sinensis, P. rabaudi and L. capito genomes were assigned to 50 pseudo-molecules after manual curation . Strong contact signals of the Hi-C data for all chromosomes of each genome suggest high quality of chromosome-level scaffolding . Homology-based and RNA sequence-based gene predictions were used to annotate all genomes after masking transposable elements , simple sequence repeats , and tandem repeats. The final annotated gene numbers for the three allopolyploids, P. rabaudi, L. capito and S. sinensis, were 45,857, 43,211 and 49,999 , respectively, which were comparable to those of two famous cyprinid fishes common carp and goldfish. The gene number of the rest eighteen species ranged from 23,658 to 32,381, which are similar to the 24,770 for Onychostoma macrolepis and 27,263 for grass carp. BUSCO analysis was conducted to evaluate the completeness of these annotations, which contain an average of 91.6% complete BUSCO gene sets .The overall TE content in the 21 sequenced species ranged from 40.87% to 59.18% . The most abundant repeat class of all species was DNA transposons , of which TC1/mariner, hAT, and CMC were the three top enriched superfamilies . Long terminal repeats account for an average of 11.09% of the genomes, which is higher than reported for zebrafish. Most of our sequenced fishes contained similar long interspersed nuclear element content with that of zebrafish but fewer short interspersed nuclear elements  than zebrafish .We also observed that the median age of DNA transposon families in our sequenced genomes were typically older than those of both LTR and LINE families , which was also found in the zebrafish.Multiple alignments of orthologous genes between each tetraploid and O. macrolepis successfully identified two subgenomes, each of which included 25 chromosomes . To assign each chromosome to a subgenome, a method similar to SubPhaser, a novel subgenome-phasing algorithm using subgenome-specific k-mers as markers, was applied. The allopolyploid origin of several previously determined allopolyploid plants as well as the common carp and African clawed frog Xenopus laevis was supported using this strategy. Therefore, the presence of repetitive kmers, blueberry grow bag which are exclusively or highly enriched towards one subgenome, were sought for each of the three polyploids. We confirmed that two distinct subgenomes, termed ‘subP’ and ‘subM’ , of each tetraploid could be determined based on a suite of 15-mers with unique distribution patterns along each homoeologous chromosome pair, supporting an allotetraploid origin of these three species . To further verify the polyploid origin , we adapted another strategy that involves analyzing TE types and abundances that has been successfully employed to confirm the polyploid history of the African clawed frog, blueberry, sterlet sturgeon, the goldfish and Prussian carp.

This approach is based on the hypothesis that relics of unique transposon types and abundances specific to the two parental species can be used as markers to partition each chromosome to a particular subgenome in an allopolyploid. Frequency analyses of TEs identified between 8 and 16 transposon types in each polyploid genome that were enriched differentially in the subP and subM . These results collectively support an allopolyploid origin for these three polyploid fishes.To estimate the divergence time of each subgenome, we established one-to-one ortholog gene sets from two putative diploid ancestors and the subP and subM genomes of three allotetraploids and calculated the pairwise synonymous substitutions . The divergence-time of diploid progenitors , served as the upper bound estimate of the polyploid event, and can be deduced based on the Ks age distributions of the orthologous pairs . We found that the two subgenomes of L. capito diverged approximately 7.5 to 13.9 million years ago , which is the most recent dateestimate among the allopolyploids examined in this study . In comparison, the divergence of the P. rabaudi subgenomes is estimated at ~15 to 28 Mya. This estimate is similar to the previous divergence times estimates of the subgenomes of common carp and goldfish. The results from our phylogenetic analyses further confirmed that P. rabaudi, common carp and goldfish likely share a common polyploid event, with subP and subM of each species in monophyletic clades . Lastly, the divergence of the subgenomes of S. sinensis was estimated at 10 to 18.6 Mya . Therefore, these three allopolyploid cases, with varying divergence estimates among subgenomes , provides a suitable framework to examine whether genetic divergence of the diploid progenitors contributes to subgenome expression dominance. Mitochondrial genomes are almost exclusively inherited from maternal progenitors, whereas nuclear protein-coding genes are biparentally inherited. Therefore, a comparison of the mtDNA phylogenetic tree and nuclear gene trees enables the identification of maternal and paternal diploid progenitors for allopolyploids. Our phylogenetic analyses using Triplophysa bleekeri or zebrafish as an outgroup provide strongly supported estimates for species relationships and the monophyly of Cyprininae . Furthermore, these analyses revealed three independent polyploidization events: one shared by P. rabaudi, common carp, and goldfish , one in S. sinensis and one in L. capito , consistent with a previous study. Based on the aforementioned phylogenetic analyses and the mitochondrial tree , the subP and subM of these five species denotes the paternal and maternal subgenome, respectively. These analyses also supported three independent allopolyploid origins. The maternal subM of common carp, goldfish and P. rabaudi is most closely related to Tribe Barbini or Acrossocheilini, and the paternal subP is most closely related to Tribe Labeonini. Similarly, a closely related species of Acrossocheilini could have served as the diploid progenitor of the S. sinensis subM, whereas its subP was the descendent of an ancestral fish much older than Smiliogastrini. The formation of L. capito was probably the result of hybridization of two diploid relatives from Barbini. To further confirm the above conclusion, phylogenetic analyses with the whole-genome alignment of 13 species, the fourfold degenerate sites in 1669 genes and CDS of 1669 individual genes were performed. The topologies of all these trees were congruent with each other . Meanwhile, we also observed the differences between overall consesnus species tree and individual gene trees , implying that these topological conflicts may be as a result of incomplete lineage sorting and introgression.Generally, there are four major evolutionary fates for duplicated genes derived from polyploidy events, including 1. duplicate gene retention due to dosage-balance constraints or selection favoring increased dosage of gene products, 2. gene loss or pseudogenization of one duplicate copy, 3. subfunctionalization, the partitioning of ancestral gene functions among the two duplicate gene copies and 4. neofunctionalization, the evolution of novel gene functions in one or both duplicate gene copies. To investigate the frequency of each fate among ohnologs, we analyzed the expression levels across six tissues for a set of positionally conserved syntenic ohnologs that were present in single copy in the genomes of two diploids and retained in duplicate in all three allotetraploid genomes. We identified 4884 to 5,345 gene pairs that had expression patterns consistent with duplicate retention due to dosage-selection, 226 to 348 due to non-functionalization, 9 to 14 due to subfunctionalization, and 223 to 420 dueto neofunctionalization . Examples of expression divergence consistent with subfunctionalization and neofunctionalization for each allotetraploid are shown in Supplementary Fig. 20. However, we should notice that the low level of subfunctionalization inferred could be due to the relatively small number of tissues examined.

All yields were recorded on a dry matter basis , adjusting plot weights by the average dry matter percentage.An experiment was established in April 2018 consisting of four replications laid out in a randomized complete block design. This trial was a large dormancy evaluation but included all populations in the yield trial described above except for the cycle one phenotypic selection population – NY1221. The trial was located in Davis, CA on a Yolo silty clay loam . Plants were sown in trays in the greenhouse 2 months prior to transplanting. Plots consisted of a single row of 25 plants spaced 30 cm apart with a 90cm gap between plots within rows and 60cm spacing between rows. Plants were harvested throughout the season when they reached the target maturity of bud to early flowering stage using a self-propelled forage harvester. Fertilizer was applied to maintain P and K at appropriate levels for high yielding perennial forages, with weeds, insects and other pests monitored and standard control measures applied if necessary. Plant height was measured 25 days after the final harvest in October in 2018 and 2019. Plant height was considered the distance from the soil surface to the tallest point of the plant at its natural height . A single measurement was taken from each plant and an was average height across all plants in the plot was determined.All analyses were performed using R statistical software . For the yield trial, grow bag gardening analysis of variance was conducted to estimate the effects of population, location, and harvest on forage yield.

Locations were analyzed independently followed by a multi-environment analysis. In addition to an overall annual yield analysis, the yield of individual harvests within location was conducted and across locations, harvests were analyzed by season, with spring , summer , and fall groups included. For the single location models, population, block, harvest, and population × block interaction were treated as fixed effects . For the multi-environment models, population, location, harvest within location, block within location, population × location interaction, and population × harvest within location were treated as fixed effects. Means and standard errors were calculated on a per harvest basis for each population using the emmeans package . Pairwise comparisons were conducted using the multcomp package . The significance threshold was set at 0.05 using the Tukey method for multiple comparisons.Forage yield differed among populations at each location and in the overall analysis . Forage yield also differed among populations for the different seasonal harvests at each location. The base population , phenotypic selection cycle one , genomic selection cycle one – high , and genomic selection cycle one – random were the top performing populations overall across both locations; the genomic selection cycle one – low and genomic selection cycle two populations were the poorest performing. These trends were also observed in the seasonal breakdown of harvests, with the exception of GSC1-L which performed well in the autumn harvests. In Ithaca, NY0847, GSC1-H, and GSC1-R had the highest yield per harvest over the four-year duration of the trial. GSC1-L had low yield in the spring harvests and overall. GSC2-H and GSC2-L were consistently the lowest yielding populations.

Although NY1221 was not significantly different to top performing varieties in the seasonal breakdown of harvests, the GSC1-H population had a significantly higher forage yield than NY1221 overall. In Tulelake, there was less separation between populations. NY0847 and GSC1-H yielded significantly more biomass than GSC1-L in spring, summer and overall; however GSC1-L outperformed GSC1-H in the fall. There was no significant difference between genomic selection and phenotypic selection in Tulelake.Fall height was relatively consistent among populations in the Davis experiment . The only significant difference was that GSC1-L had taller autumn regrowth than GSC2-H. A wide range of broad sense H2 was estimated for forage yield across all harvests . H2 for total annual forage dry matter yield over years was 0.93 at Ithaca and 0.57 at Tulelake. Overall H2 across all harvests and locations was 0.53.Dry matter yield is the most important trait for profitable alfalfa production, yet somewhat inexplicably, over the past 30 years, there has been no improvement in on-farm alfalfa yields in the USA . Genomic selection has been shown to increase the rate of genetic gain in many of the major crops grown in the United States, including alternatives to alfalfa, such as maize , in livestock rations . In this experiment, we evaluated and compared populations developed through traditional recurrent phenotypic selection and genomic selection to investigate whether genomic selection could be a viable option to address the lack of yield improvement in alfalfa. In this experiment heritability estimates for DMY are higher than have previously been reported , probably due to the use of ten replications within each location of the trial to obtain reliable estimates of forage yield in a densely sown sward. H2 estimates for Tulelake were lower than Ithaca, due in part to the inclusion of establishment year harvests .

Considering only the populations developed using the genomic prediction model, the GSC1- H population had higher yield than the GSC1-L population, with the population whose parents were chosen randomly falling intermediate between the others. Thus, the model had the ability to shift populations in the expected directions for biomass yield. Across all entries, the GSC1-H population was among the top yielding populations, and GSC1-L was among the lowest yielding. However, the genomic prediction model appeared to break down on the second cycle of selection, with both the high and low GSC2 populations performing poorly. This is concerning, as one of the major benefits of genomic selection is the potential ability to conduct multiple cycles of GS in the span of a phenotypic selection cycle. However, if the model breaks down after a single cycle, this benefit cannot be realized. Nevertheless, conducting a single cycle of GS in the space of a year is still considerably faster than a PS cycle. Approximately 9000 markers were used for the first cycle og genomic selection and fewer were used for the second cycle, which may explain some of the poor performance of the C2 populations; alternatively, the relative value of marker loci could have shifted following the first cycle, so that the model is simply not useful. In addition, there may have been an inadvertent shift in the dormancy of the C2 populations, which could contribute to lower total DMY. The base population and all populations developed through genomic selection were included in a separate trial investigating the autumn height of various alfalfa populations, a proxy for autumn dormancy. The GSC2-H population was significantly shorter than the GSC1-L population indicating selection for plants containing alleles for less fall growth. Future applications of genomic selection should include selection criteria to ensure fall dormancy remains unchanged during the selection process. This also shows a potential risk of genomic selection in a breeding program – the possibility for undesired shifts of non-target traits. Breeders should be aware of this when making selection decisions, and this result highlights the need to measure other traits of importance during the breeding process. The GS model was developed based solely on phenotypic information from plants grown in Ithaca, plastic grow bag and not surprisingly, the selected populations performed better relative to other entries in Ithaca than in Tulelake. This suggests that any potential gains derived from genomic selection require the inclusion of phenotypic information from the target environment. This observation has potentially significant implications for the viability of incorporating genomic selection into alfalfa breeding.

Already suffering from a paucity of breeders and breeding resources, expanding breeding trials to include more environments may not be possible for many breeding programs. Further investigation is required to determine the requisite number of environments that need to be evaluated in order for GS to work robustly. The lack of separation between the base population and populations selected for high yield, either by PS or GS, in the overall analysis provides some insight into what breeders have experienced over the past 30 years of alfalfa improvement. The selected populations have not increased yield in an experiment designed to replicate a commercial production environment. Notably, however, in Ithaca the GSC1-H population performed better than the PSC1 population that was selected through phenotypic evaluation, even though both relied on yield information from Ithaca in making selections or in developing the GS model. Regardless, the lack of DMY gain from the base population using either phenotypic or genomic selection remains a significant concern. Further improvements to the predictive model are possible and may yet result in real gains at the commercial production level. The GS populations evaluated in this experiment derived from a predictive model developed using clonally replicated space-plant yield. A poor correlation between individual space-plant yield and DMY of a densely planted sward is often obtained , so an alternative approach evaluating the DMY of families in densely planted small plots might be a better approach . These families can be bulk genotyped to obtain allele frequency marker data rather than individual genotyping calls . This method better captures commercial yield in the model so more accurate predictions can be made, aligns well with current the current breeding methods in alfalfa, and can be implemented alongside family-based recurrent selection. Genomic selection is still in its infancy in alfalfa; however, our data indicate there is the potential for greater genetic gain with GS than has been obtained with the use of phenotypic selection alone. Significantly more research is required to investigate alternative models and selection strategies across the wide range of environments in which alfalfa is grown. With the cost of genotyping decreasing, new high throughput technologies being developed, and a greater understanding of the alfalfa genome, the potential for GS to improve yield is quite high. The results of this work will be beneficial not only to alfalfa production but also will help guide decision making for breeding of other outcrossing perennial forages.Alfalfa is one of the most important perennial forage crops in the world. It is the third most valuable field crop in the United States in which California leads the nation for hay and seed production, generating in excess of $1B in 2022 . Its high yield and nutritional value are key drivers for California’s dairy industry, the state’s top valued agricultural commodity . In addition to its economic value and importance as a forage, alfalfa provides a host of beneficial ecosystem services. Its nitrogen fixing capabilities and perennial nature promote sustainable cropping systems and contribute to nutrient cycling . Alfalfa also plays a role as an important in sectary and habitat for native fauna . Cultivated alfalfa is predominantly derived from the subsp. sativa, an allogamous autotetraploid . Alfalfa breeding programs are based on recurrent phenotypic selection, with or without progeny testing . They are designed to increase the frequency of desirable alleles in a population while maintaining genetic variability for continued genetic improvement . Breeding goals in alfalfa are characteristic of those in other crops: increasing yield, enhancing forage quality, and improving tolerance to biotic and abiotic stresses . Simply inherited traits with high heritability have been greatly improved through traditional breeding methods; however, improvement in complex, quantitatively inherited traits have been less successful , most notably yield for which there has been little to no improvement over the last 30 years . Long breeding cycles , multiple harvests per year, limited breeding resources, inability to make gains in the harvest index, significant genotype by environment interaction , and selection based on vigor of spaced plants or short family rows are all factors contributing to the low rate of yield progress . Yield improvements in alfalfa in the past can be mainly attributed to improvement of ‘defensive’ traits i.e., improvements in pest and disease resistance . This helps alfalfa reach its yield potential, but it does not result in an increase in yield per se. To select on yield per se, selections could be based on yield data from the first full year of production before plant mortality becomes an influencing factor impacting yield, while persistence could be evaluated at the end of a multi-year trial. Marker-assisted selection is a modern tool that has great potential in addressing the lack of genetic gain in alfalfa yield . The availability of a large number of single nucleotide polymorphism markers, cost effective genotyping assays, and the recent availability of chromosome-scale, haplotype-phased genome assemblies facilitate the dissection of complex traits and provide a pathway for genetic improvement .

There is much variability within land types, even from parcel to parcel or land use categories such as single-family home, residential, high density residential, commercial and industrial. In areas which are highly hostile to bees, pollination is decreased, even among European honey bees, Urban landscape types: Classifications of different landscape cover types were done in somewhat coarse aggregates. For example, park vegetation, road edges, lawns, etc. This was a common choice among students who could quickly select green on maps via Photoshop . Alternatively, some students took the time to trace vegetation with Illustrator or In Design with similar results. Finally, some students also utilized ArcGIS land cover categorizations in GIS data using ArcGIS . Future studies could be done to compare each technique.Landscape design for bees is explored with help of student designers from California Polytechnic’s Landscape Architecture program . Students in both a studio and specialty interest course were given design tasks by author KC over two quarters. Their illustrations and work help to exemplify KC’s vision of designing bee habitat in a thorough ecological, but also provocative and engaging ways. KC’s design ideas for bees are rooted in scientific knowledge and aim to tackle bee pollinator conservation as a multiprong approach. Designs focus around the biological and ecological aspects of bees. The best designs look to celebrate what is unique or interesting about each focal bee. In addition to habitat creation, square black flower bucket wholesale maximization, and conservation, landscape designers can help to show how bees’ stories can be shared.

A seed library network has potential to provide opportunities for improved neighborhood pollinator habitat. Moreover, seed library patrons would be empowered to make positive changes within their vicinities with minimal physical labor and intrusion into private land spaces which are otherwise often inaccessible. Participation in seed library usage would be entirely voluntary for users. A network of seed libraries will act as a system of structural resiliency for urban pollinators. By using geographic analysis, mapping techniques could help to shed light into where seeds are being planted and also where important pollinator plants exist. With the help of citizen science data, areas of low pollinator plantings can be targeted for future landscape design for pollinators.Students were asked to show site visitors about special bees. Figure 1 shows how one student envisioned providing nesting habitat for Megachile bees in a sculptural way, conveying meaning to site visitors . This clever solution helps people to gain landscape literacy about these fascinating cavity nesting bees. Mutualism exists here, presenting opportunity for both bees and humans. Design mutualism is an opportunity for multiple species to benefit from a landscape change . In this case, bees benefit from habitat design for nesting and foraging, while people benefit from gaining landscape literacy about the pollination world around them. Another wonderful design focused on endangered Hylaeus bees in Hawaii. As it turns out the student lives on Oahu, the same island where the endangered Hylaeus species are found. By researching the foraging preferences and last sighting locations of these rare bees, a plan was made to help both conserve and celebrate these now rare bees. Interestingly, the possible conservation area overlapped with an already existing botanical arboretum.

Adding an installation to highlight the special traits of endangered Hylaeus appears to be an opportunity for public education. The student was able to research the face patterns of the local Hylaeus bees and designed an interactive walking tour which would appeal to a large age range of visitors. This project was serendipitous, and holds potential for implementation.Students were challenged to envision and demonstrate what a vegetated landscape looks like from a bee’s point of view, focusing on the valued elements. This project forces students to look at the landscape from their organism’s value system, which is an essential part of good ecological design. Figure 2 shows how Xylocopa favors some forage plants over others in this residential landscape. This student shows clearly which plants have ecological value to Xylocopa with the use of color, in contrast to the colorless portions of the image. This image is particularly good at transmitting meaning to human viewers, helping people to understand this organism’s preferences and landscape opportunities or limitations. Another intelligent “see like a bee” design solution shaped the ear pieces of glasses to look like tubular Megachile nests. The work was completed with an annotated design plan with callouts to highlight favorite foraging plants. The idea of ecologically based ‘bee glasses’ seems like an opportunity for helping capture the imagination of children and with educational presentations. There are many aspects of the bee’s biology, ecology and foraging preferences which could be highlighted and made possibly more memorable with the help of glasses props, for example.An aspect of bee biology which has potential for design is for bees which cavity nest above ground. It is possible for designers to create cavity nesting areas on any vertical surface. The form of these sorts of projects is limitless. One of the best student work’s shows a concept for spelling the desired nesting bee’s genus name . A design like this is fairly simple, yet demonstrates much more knowledge and information than a standard bee box from a standard retailer. Other students looked to maximize wall design space.

One student created a huge silhouette of Megachile and planned drilled holes of the correct diameter all over the entire surface. It is conceivable to imagine that design as both striking and memorable. Other students strove for more abstract geometric patterns, which though artistic in nature, were not effective at communicating as much information about the bees.Author KC has envisioned a new way to help achieve higher quality pollinator habitat in neighborhoods via the installation of free seed libraries. A prototype pollinator seed library was made from a repurposed windowed cabinet and painted to advertise its contents. Since pollinators are suffering from habitat fragmentation and degradation due to human land use activities. Habitat design is critical to solving these connectivity issues today. Improvements to habitat networks are on the forefront of research and design by urban and landscape ecologists. Seed libraries, a grass roots phenomenon, aid in accessibility for people to start their own seeds. These cabinets originated in effort to provide free resource availability and seem like an opportunity for growing pollinator habitat. Seed libraries are small outdoor cabinets which can be curated to a palette of the provider’s choice. The seeds contained within are available free to whoever accesses them. Seed library users are also encouraged to leave seeds for others as well. Seed libraries are a “spin-off” of the popular “Free Little Libraries” program for exchanging books. Cabinet-style libraries are hyper local in design scale, often with one every few blocks in a neighborhood. Designs are often creative, attractive and fun to elicit usage. Specializing seed libraries to help meet the needs of local pollinators has great mutual potential, both for humans, and also pollinators. So far, author KC’s “Free Pollinator Seed Library” has been extremely popular. Well over 800 hundred seed packets have already been exchanged in the months of its existence thus far.The reception of the Grover Beach, California surrounding neighbors and users has been extremely positive. Efforts have been made to create a ‘buzz’ online. Basic information about the project can be found at author KC’s personal website, plastic square flower bucket and it even has its own Facebook page, titled, “Free Pollinator Seed Libraries where author KC can post updates. However, the highest interest occurred by posting on the Nextdoor . Seventy-four people within the immediate neighborhood liked the post and twenty took the time to post comments, all with positive words about the project. Of the commenters, all were within a maximum 12.5 km  radius from the seed library. The average distance of a commenter to the seed library was 6.3 km and the median was 3.4 km and 2.1 mi. Commenters show which neighborhood area they are posting from, which are defined by local’s sense of geographic area, in this containing the following regions: Corbett Canyon, Edge of San Luis Obispo , Fair Oaks-Grand, Grover Heights, Horned Toad Trail, Huasna Valley and Huasna Corridor, Just Off The Pike, Lopez Drive, Oak Park Streets, Oceano, Ocean South, Old Oak Park, S. Oak Park and Trilogy. Most recently a Google Business listing was also made , which has further increased page views and visits. For example, in mid-January 2022 there have been over 1,100 visits to the Google page, which has increased exposure significantly. Therefore, the seed library captured the attention of people in the general geographic area as well as in the local neighborhood. There is a lot of enthusiasm among the neighborhood to help bees. Designing pollinator seed libraries seems to hold a great potential for making the largest positive changes in short amounts of time with limited budgets.

One of the most engaging potential design themes explores the contrasting nature of various bee genera. One student came up with a particularly interesting sculpture idea to celebrate two very different native bees. The student was keen enough to focus on the materials for each bee, wood for Xylocopa, and soil/ceramics for Andrena. The project shows two large bees of contrasting colors diving into the ground with their paths dynamically crossing. This work helps to demonstrate the various nesting substrates each bee would use. Furthermore, the student carefully imagined the body size and shape of each bee. . It would be an impressive sight to see this design implemented. Different bees could be chosen at geographically different places to highlight locally special bees. Other well thought out contrasting bee designs included, showcasing different bee nesting styles or foraging preferences. Some students juxtaposed different style nesters along a human walkway. Others used a human path to separate two very different foraging habitats on each side, for bees with extremely different foraging preferences. Overall, these themes have a lot of potential and should be explored more. Particularly, displaying uniqueness of bees and/or local adaptations seems like an excellent way to support local bee populations.Designing for bees over large areas of human dominated landscapes will require renovation of landscaping with little to no ecological value. Learning to maximize bee habitat with small planting areas is very important. When added together, these small snippets of micro-habitats contribute to pollinator habitat networks, which are essential for resilient landscapes. One of the best submitted images shows one student’s attempt to maximize bee habitat foraging area in their family home. This student wisely recommends more pollinator plantings on the ground level, but also imagines creating more foraging area by utilizing vertical wall space for habitat. Some students were bolder with their designs. They thought through how to maximize the area of foraging plants for bees, whether that was on the roof, walls, driveway, getting rid of grass or paving. Students were urged to think about a design they would like to look at every day, thus, in this way, it was easier for them to imagine if it was their own home or property. Since much of the human-built environment is already in existence, it is very important that we strive to update and augment the ecological functionality of such places for bees and other pollinators.Students tackled the bee habitat map categorization in a variety of ways, each producing effective graphics to demonstrate habitat patchiness of bees in human-dominated environments. Figure 4 shows an attempt at classifying landscape in Oakland, California from Bombus’ perspective. This is a somewhat typical classification of open space, park land, street and sidewalk vegetation. Looking at the landscape with spatial distances between habitat is essential to better understand how bee habitat fragmentation patterns play out for bees at a city-wide scale. Figure 4 was made quickly by using an extension of ArcMap within Illustrator , a more illustrative software. This method was quite quick and accurate, creating quite effective results. Other students tried to streamline the tracing task by utilizing Photoshop’s select by color tool which was perhaps the fastest method, but also lacking in accuracy. More mapping technique results are described below. Other mappers strove to add more detailed information, with varied categories for example, including: natural landscapes, parks, redwood tree dominated areas. This categorization scheme made more sense for the student working out of Mill Valley, California. Some students missed the opportunity to demonstrate human residential areas as possible habitat for native bees. The best projects, also show well the possible geographic connections between denoted patches.

Collected bee specimens were identified to genus both by author KC and with correspondence by bee expert Robbin Thorp , and additionally, in consultation with personnel and comparisons with collections at the UC Davis Bohart Museum . Plant identification was aided by correspondence with former UC Davis Arboretum Director of Horticulture, Ellen Zagory.Data collection was conducted weekly, but compiled into monthly data aggregations to minimize the possibility of sampling omission errors, such as variable detectability . Using this method, it was more likely that a greater magnitude of rarer associations were observed , which is advantageous for a study such as this, seeking to explore the relationships between bees and the plants they utilize. This data compilation method was selected after reviewing bee and other pollinator field research methods as well as much personal trial and error in field and personal correspondence with expert Robbin Thorp. From previous experience we determined that monthly walks produced significantly less association data than compiled weekly walks. Thus, we found that weekly data collection was best for observing ephemeral bee-to-flower foraging associations and monthly aggregations were most effective in understanding bee foraging and flower bloom times . A compiled monthly time step was primarily used for this study as it is a common standard protocol in both bee foraging and plant phenological records, flower harvest buckets such as field guides. As an example, Andrena was seen foraging in the Mary Wattis Brown garden on Ceanothus two weeks in a row.

This association was counted once for the month, not twice, when recording monthly association data. We determined two criteria for measuring a plant’s successful performance, including how many bee genera were attracted to a plant and also, the strength of a bee-to-plant association, with demonstrated repeat foraging events representing stronger associations. Additionally, we sought to determine forage plants utilized by bees which were not included in Table 1. Furthermore, we sought to determine characteristic trends among utilized forage plants, for example, whether they were native or not, and if not, what region of the world they originated from. The analyses were completed in MS Excel in an effort to identify plants missing from the current literature that hold potential for hosting bee foraging and, thus, provide habitat value.Initial investigation into potential pollinator plants revealed that 96 of the 134 of plant genera from Table 1 were included in the Arboretum’s plant collection maps. This indicated that the Arboretum’s records included many of the predictive plants for bees, allowing us to test the majority of the bee-to-plant associations from Table 1. We sought to evaluate to what degree the Arboretum geodatabase plant presence or absence was accurate. We were uncertain about the absolute accuracy of the Arboretum maps, as some new planting projects had taken place since the geodatabase had been completed. We were also interested in studying which weedy plants were used for pollination which were not included on the maps.We used two approaches to assess accuracy of the existing information foraging matrix. Model success is defined here as correct prediction of plants utilized by bees for foraging. First, we looked at how well Table 1 correctly predicted bee foraging overall in aggregate.

This relatively coarse method examines which plants, regardless of bee genus, were successfully both predicted and observed as floral resources. Next, a more precise investigation into the 1:1 association relationships between bees and their forage plants was performed. This statistical testing approach determines the accuracy to which the predictive Table 1 plants were utilized. The existing literature foraging matrix constructed in section 2.2 was validated by compiling field observations made in section 2.5 to determine its efficacy. There are three potential outcomes from this assessment: a correctly predicted presence , an omission error , and a commission error ; however, it should be noted that no correctly predicted absences are possible to assess in this study because the existing literature lists do not designate known absences . This makes traditional assessments of model accuracy using test statistics from a confusion matrix impossible, such as the Kappa statistic .Despite this limitation, it is possible to assess “sensitivity,” also known as the “true positive fraction” from the correctly predicted observations and the “omission rate,” or also known as the “false negative fraction”; these two measures are inversely related and sum to 1 . The third possible outcome is a metric of commission error which assesses the false positive rate. Each of these three metrics will be further described below. In the first case, if a known bee genus is observed in the field that is using a known plant genus this is considered a “correctly predicted” occurrence . For each bee genus this metric is calculated by dividing the count of literature plant genera correctly predicted by the count of all plant genera observed to be used in the Arboretum by that respective bee genus. This yields a “sensitivity score” or true positive fraction. In the second case, if a known bee genus is observed using a plant genus not on the literature list, this is an omission error. The omission rate is calculated by dividing the count of all additional plant genera observed to be used in the Arboretum by the count of all plant genera observed to be used in the Arboretum by that respective bee genus.

This yields an “omission score” or false negative fraction . It should be noted that the sensitivity and omission scores have the same denominator. In the third case, if a known bee genus is not observed to use a known plant genus that is present in the Arboretum, this is a commission error. In other words, the list predicts the bee genus to use the plant, but it is not observed. The commission rate in this study is calculated as a percentage by dividing the count of literature plant genera not observed to be used in the Arboretum by the count of all plant genera from the literature list in common with the Arboretum and multiplying by 100. There are 38 plant genera on the literature list that are not present in the Arboretum and therefore those plant genera are excluded from the error assessment. Finally, to assess the significance or model independence for each bee genus for all observations, a chi-square test was performed on each respective bee genus model result to assess observed versus expected values. This model independence test was conducted using CHISQ.TEST function in Microsoft 365 Excel. This test returns the probability of whether the model could attain the value of the chi-square statistic by chance alone under the assumption of independence. Values for p range from 0-1 and low values of the test statistic indicate independence. The degrees of freedom were calculated by subtracting 1 from the total number of columns used in each respective bee genus model.The completed presence-only bee-to-plant foraging matrix , derived from the literature, contains 23 bee genera and 134 plant genera. Of the 23 bee genera on listed on Table 1, 22 were observed in the Arboretum as well as five additional native bee genera that were not on the list. The only predicted native bee genus not observed in the Arboretum was Colletes, which had a singular association with just one plant genus, Solidago, round flower buckets which is found in Arboretum. In this case most likely either Colletes populations are too disjunct to access the floral resource or there are other lacking resource attributes which prohibited Colletes from using the Arboretum as habitat.The completed observed results of the bee-to-plant foraging matrix contains 27 observed bee genera and 297 observed forage plant genera. Table 2 differs from Table 1 in that results recorded the redundancy of the weekly foraging associations, demonstrating the relative strength of each bee-to-flower association throughout the year. A significant finding of this research is that more than three times the unique bee-to-plant foraging associations were observed than predicted . However, it is clear from Table 2 that plants varied considerably in terms of relative attraction . Appendix 2 shows a complete record of all bee genera predicted versus observed foraging.Observation data were summarized to show the annual pattern of association activity by garden . Bee foraging was well supported by the novel Arboretum plant communities. A full distribution of bee-to-plant associations by garden and month can be seen in Table 3.

Two gardens substantially out-performed all the rest: the Mary Wattis Brown native plant garden and the All-Stars in the Ruth Risdon Storer garden. The plants in each garden supported large numbers of bees, but there were notable differences in function over time. While native plant garden bee foraging peaked in May, the non-native garden peaked in August . Floral resource timing differences accommodate different seasons of bees, who also exhibit staggered emergence and activity months. Additionally, as plants in the native garden often desiccated and rested for the hottest summer months, many of the non-native plants continued to bloom, persisting to provide plentiful floral resources through the hottest months and even fall for summer and fall bees.We examined if Table 1 bee plants in the Arboretum’s map records correctly predicted foraging by bees. As stated in section 2.6, 96 of the 134 predicted plants were included in the Arboretum’s plant record maps. Of the 96 predicted matrix plants which were also in the plant maps 70 were actually used for forage. Wholistically, predicted foraging plant presence was highly correlated with a successful foraging utilization. Within the 84 of 96, or 87.5%, beeto-plant matrix association plants found in the Arboretum plant collections were foraged on by bees, thus, the success rate of the aggregate model indicated high correspondence. The majority of the plants stated to be in the Arboretum geodatabase maps were still present and also used by foraging bees. In total, 84 of the 134 predicted plants, were utilized by bees for foraging. In other words, though 70 predicted plants were also used for foraging and also confirmed on the maps, 14 additional predicted, but unmapped plants , were utilized for bee forage. The majority of Table 1 plants expected for bees were on the maps and 70 out of 84 plants used for forage . This high indication of map accuracy combined with the confirmation of bees foraging on the expected plant list seemed quite promising. Overall, it seemed the habitat relationship model, combined with existing habitat maps, were quite accurate to aid in making predictions in bee foraging habitat use as a whole . Meanwhile, bees were found to forage on many plants not predicted per the Table 1 matrix. Of the “unexpected novel” observed plants, 258 were on the Arboretum maps ,while only 39 forage plants were not on the maps. Interestingly, this is very similar to accuracy percentages of results above . This infers that map records were consistently accurate at providing foraging plant locations and subsequent pollinator association. While the bee-to-plant matrix is predictive of bee foraging the majority of the time, there are a variety of ways to analyze the matrix’s success. The Arboretum mapping accuracy omitted new or weedy plants and therefore some associations seen in Table 2. While these initial results above seem promising, when a more precise analysis is done below, it becomes clear that the individual bee genus models were not as predictive for foraging associations.We analyzed each bee genera by their predicted versus actual foraging data. Each bee genus was compared to the predicted plants it ought to have foraged on versus the observed data. The error analysis matrix and model independence tests presented in Table 4 show the results for each respective bee genus observed in the Arboretum. Error results are reported only for those bee genera listed in Table 1 . Table 4 breaks down the counts relevant to calculating the three aspects of error assessment for this study. The overall average true positive fraction for correctly predicting bee genera in the Arboretum was found to be 0.14 and likewise, the overall omission error rate, or false negative fraction, was found to be 0.86 . The overall average commission error rate for all bee genera was 47.8%, meaning that nearly half of the plant genera reported in the literature that bees are reported to use were not observed to be used in this study.

Such transmission is cited as an ecologically important way for plants to inherit beneficial microbes across generations and for seed associated pathogens to disperse . Vertical transmission has long been observed in grasses, which are hosts to clavicipitaceous fungal endophytes such as Epichloe . Vertical seed transmission has also been observed for non-clavicipitaceous endophytes in Setaria viridis , Triticum , Quercus , and other plants . Floral transmission of microbes into seeds has been studied extensively for pathogens such as Monilinia vaccinii-corymbosi in blueberry and Acidovorax citrulli in watermelon . However, flower-to-seed transmission has also been observed for commensal and beneficial bacteria, for example in Brassica napus . The microbial contributions of the vertical and floral transmission pathways are likely to vary based on a plant species’ pollination mode . Horizontal transmission is the acquisition of seed microbes from the environment, either prior to or after the maturation of the seed as it is still attached to the mother plant or as matured seed disperse and becomes colonized from sources such as air , water , animals , soil , and other seeds in storage . Seed dormancy and germination are likely to represent a very active period of such horizontal transmission, as soil microbes interact with seed exudates and pre-existing microorganisms on and within the seed .The meta community concept was formally described by Leibold et al. , who defined meta communities as sets of local communities that are interconnected by dispersal. This definition arose out of a need to better account for spatio-temporal scales in ecological studies , black plastic plant pots bulk and also included the impacts of dispersal and habitat heterogeneity on community patterns .

Since it was first described, meta community theory has adopted Vellend synthesis that community assembly and composition are driven by four categories of processes: abiotic and host filtering, species interactions, dispersal, and ecological drift . Categories 1 and 2 represent a deterministic or niche-based process of selection where differences in fitness between taxa, species, or guilds lead to differences in their abundances . Finally, drift is the stochastic fluctuation in species abundances, often due to chance birth, death, and migration events . Framing plant microbiomes as meta communities provides an integrated view of the drivers of their composition, function, and evolution, and of the impacts of these drivers on host health . Traditional meta community ecology states that filtering and species interactions occur at the local scale , while dispersal and drift occur at the regional scale . However, categorizing processes as “local” or “regional” is relative to the community that is being studied, and depends on the scales of interest and on defining the boundaries between a local community and a regional meta community. For plant microbiota, including those associated with seeds, the terms “local” and “regional” are contextual because microbes primarily behave at very small scales , although they can be affected by much larger scale factors . Furthermore, microbes can be ubiquitous across habitats at multiple scales, blurring the boundaries between patches of local communities in the landscape of interest . As we apply the first principles of meta community ecology to plant and seed microbiology below, we will therefore use three categories of spatial scale: macro- , meso- , and micro- scales.

Integrating the study of assembly processes across these three scales should give a more complete picture of how microbial communities are assembled, and how emergent community patterns occur at individual scales .Several studies have shown that seed microbial communities differ significantly across geographic locations, i.e., at the macroscale, for example in B. napus , Elymus nutans , Phelipanche ramosa and Pseudotsuga menziesii . For most of these studies, the abiotic factors that are important for structuring these seed microbial communities remain to be identified. However, we can assume that these factors are similar to the ones that drive macro-scale differences in the microbial communities on/in other parts of the plant. In communities associated with leaves, roots, and fruits, such factors include temperature , precipitation , humidity , and soil conditions . In a study of above ground microbial communities in Vitis vinifera, Bokulich et al. found that fungal communities of seeded fruit were associated with net precipitation, relative humidity, and temperature. During dormancy in the soil, the bacterial communities of Noccaea caerulescens seeds were correlated with soil pH and cation composition . Not much is known either about variation in seed microbial community as a function of abiotic factors at the meso-and microscales, although again, much can be learned from studies on other above ground plant tissues. At the meso-scale of an individual plant, microbial communities can vary with tissue location such as canopy height in trees. Unterseher et al. cultured fungi from leaves at different canopy heights in several tree species. They found that species richness was greater in the lower canopy. Harrison et al. went on to use next-generation sequencing in a survey of the needle fungi of Sequoia sempervirens at different height positions, and found that there were distinct communities present at each height across trees.

While they did not measure microclimate variables within the trees sampled, they suggested that the observed variation could be attributed to the amount of sunlight . At the micro-scale , factors such as exposure to ultraviolet radiation and water availability can also be important. Hayes et al. described variation in the bacterial communities and UV radiation along individual flower petals in two sunflower species. They found that while there was no significant difference in community composition along petals, there was variation in UV tolerance in association with source petal position . Another potentially important factor may be water availability, which has been shown to affect bacterial survival, growth, and movement on leaf surfaces . For many macro-scale studies, a major limitation is the use of location as a proxy for environmental conditions, which precludes linking variation in microbial communities to specific environmental factors. Because site effects are impacted by environmental, spatial, and temporal factors, it can be difficult to parse out how location and environment influence seed microbiota . Also, most of these studies do not explore if and how environmental conditions actually select for microbial traits and taxa. In vitro experiments suggest that there is potential for environmental filtering, as demonstrated by thermotolerance in fungal endophytes of desert plants , salt stress tolerance in fungal root endophytes , water stress tolerance in bacterial endophytes , and oxidative stress tolerance in the fungal endophyte Epichloë festucae . Similar characterization of seed microbial tolerance and survival when challenged with different environmental conditions could provide a more mechanistic understanding of abiotic filtering. Such studies would be particularly insightful at the micro-and meso-scales.Variation in plant microbial communities is often studied and interpreted as a result of plant genetics, which represents filtering through host selection. Studies at the macro-and meso-scales have revealed that plant genetics can significantly impact microbial community composition in different parts of the plant, although seeds are clearly underrepresented in the body of literature on this topic. Microbial community variation has been associated with specific genes in leaves and roots of various plants , an approach that has not yet been applied to seeds, as far as we know. Seed line has been weakly associated with microbial community variation in Zea mays and B. napus . Seed accessions of Oryza were also associated with variation in bacterial and fungal community composition, with significant compositional shifts between wild and domesticated accessions . In a study of the bacterial and fungal communities associated with grapes, Singh et al. found that host genotype had an impact particularly within individual sites, procona system whereas abiotic conditions better explained microbial community variation between sites. This is consistent with the notion that host effects are difficult to reveal without carefully controlling for environmental factors, which would suggest, by extension, that environmental factors may have a greater relative impact on seed microbiota than plant genotype. A recent study showed however that the fungal community composition of Quercus petraea internal seed tissue was largely influenced by the mother plant, with only weak significant environmental influences . Studying the roles of plant functional traits in seed microbiome assembly and dynamics provides the mechanistic framework to understand host filtering. Some of the clearest examples of these mechanisms come from the field of plant pathology, where plant traits can be used to predict disease outcomes . One obvious suite of traits to study are plant defenses. As agents of plant regeneration, seeds are one of the most defended plant organs, protected by both chemical and physical defenses .

Some of these defenses come from the mother plant, such as through innate floral defenses in angiosperms . Many studies on plant defense traits are obviously focused on protection against pests and pathogens , but can be extended to other members of the microbial community . A number of studies have been conducted to test how microbes interact with seeds at the micro-scale. Using microscopy, the microbial communities within seeds of Citrullus lanatus and Q. petraea were found to differ in abundance and composition depending on seed sub-structure. Since Q. petraea is a wind-pollinated species, the variation in seed sub-structure colonization observed by Fort et al. suggests physical filtering of microbes during vertical and horizontal transmission. Although few studies have explored the role of micromorphology of developing seeds in microbial community acquisition , there are plenty examples of such micro-scale studies come from work on the floral microbiome. Spinelli et al. used microscopy and fluorescent tagging to study the growth and movement of the bacteria Erwinia amylovora and Pantoea agglomerans on flowers of apple and pear . They found that the bacteria migrate from the stigma to the nectaries along a stylar groove in both species, indicating topographical effects on survival, population growth, and dispersal . Similarly, Steven et al. characterized at the high spatial resolution the floral bacterial communities on apple using next-generation sequencing and found that different flower parts were enriched with different bacterial families . It is intriguing to think that variation in microtopography on flowers and stigmas may contribute to host filtering during the process of flower-to-seed horizontal transmission of microorganisms.The role of species interactions in meta community dynamics is important, but often overlooked in meta community ecology studies . In plant microbiota research in general, much focus has been on pathogen antagonism interactions, for example with an eye toward applications in disease control . However, there is much interest and opportunity to better understand interactions between and among non-pathogens in plant and also seed microbial communities. As with traditional ecology studies, much of the work on species interactions in seed microbial communities focuses on competition and antagonism. For example, Raghavendra et al. inoculated Centaurea stoebe flowers with pairs of fungi and then cultured those fungi out of mature seeds. They always isolated the same single fungus from each pairing out of seeds across parent genotypes, and proposed that competition was the primary driver of selection . Fungi compete for space and resources in Q. petraea seeds , and have negative interactions with bacteria in Populus trichocarpa seeds . Similar competitive exclusion has been observed in floral stigma communities , and in dormant seeds within the soil . However, seed microbes can also coexist via niche partitioning and other interactions. For example, TorresCortés et al. looked at how transmission of several bacterial pathogens impacted the composition of Raphanus sativus seed microbiomes. They found that these pathogens did not alter the composition of the seed microbiome, suggesting that differences in resource usage lead to coexistence between taxa . A more complete understanding of the types and outcomes of microbial species interactions prior to and during seed development is desirable.As with filtering, microbial dispersal to seeds occurs at multiple nested spatial scales, with different mechanisms at play for each spatial scale. For example, at the micro-scale, dispersal from floral stigmas to seeds can be impacted by variation in the level of protection or nutrients that are available to microbial colonizers, which is closely tied to stigma surface topography. The presence of pollen may also be important, as it has been shown that germinating pollen can enhance the flower-to-seed transmission of pathogens and that some bacteria can even induce pollen germination .

To appropriately account for repeated measurements made over time, our analysis consisted of a linear mixed-effects model with binomial error, a random effect of block, and fixed effects of treatment , year , and symptom severity category . Next, we analyzed the rate at which PD reappeared in only severely pruned vines from category 3 in subsequent years using a survival analysis. Specifically, we used a Cox proportional hazards model with a fixed effect of plot .Accurate and time- or cost-efficient methods of diagnosing infected plants are important elements of a disease management program, both with respect to roguing to reduce pathogen spread , and the efficacy of pruning to clear plants of infection . Accurate diagnosis of PD in grapevines is complicated by quantitative and qualitative differences in symptoms among cultivars and other aspects of plant condition . Our results suggest that a well-trained observer can accurately diagnose PD based on visual symptoms, particularly for advanced cases of the disease. The small number of false positives in disease category 1 and 2 vines may have been due to misdiagnosis of other biotic or abiotic factors . Alternatively, false positives might indicate bacterial populations that are near the detection limit; conventional PCR has at least as low a detection threshold as other methods that rely on the presence of live bacterial cells . Regardless, although scouting based on visual symptoms clearly captured most cases of PD in the current study, some caution should be used when trying to diagnose early disease stages to ensure that vines are not needlessly removed. There is no cure for grapevines once infected with X. fastidiosa, plastic growers pots except for recovery that can occur in some overwintering vines .

The virulent nature of X. fastidiosa in grapevines, and the corresponding high mortality rate for early season infections, increases the potential value of any cultural practices that can cure vines of infection. Moreover, new vines replanted into established vineyards generally take longer to develop compared to vines planted in newly developed vineyards, potentially due to vine-to-vine competition for resources that limits growth of replacement vines. As a result, vines replanted in mature vineyards may never reach full productivity . Thus, management practices that speed the regeneration of healthy, fully developed, and productive vines may reduce the economic loss caused by PD . A multinomial logistic regression showed significant differences in the relative frequency of different grapevine growth outcomes between the two restoration methods . Chip-budded vines showed significantly lower frequency of strong growth and significantly higher frequencies of vines with developing growth and, especially, of no growth . Nearly 30% of chip-budded vines showed no growth in the following season, compared to 0% of vines on which established shoots were trained. These results indicate that training newly produced shoots from the remaining section of the scion was more likely to result in positive regrowth outcomes. As a result, of the two methods we evaluated, training of shoots that emerge from the scion of a severely pruned trunk is recommended for restoring growth. However, it is important to note that the current study did not estimate the amount of time required for severely pruned vines to return to full productivity. Moreover, the study did not include mature vines, in which growth responses may differ from young vines.

Additional studies may be needed to quantify vine yield, and perhaps fruit quality, in severely pruned vines over multiple seasons. The usefulness of pruning for disease management depends on its ability to clear plants of pathogen infection . A comparison of symptom prevalence among severely pruned and control vines from different disease severity categories showed significant effects of the number of years after pruning , pruning treatment , and initial disease symptom category . The analysis also showed significant interactions between year and treatment and between treatment and symptom category , a non-significant interaction between year and symptom category , and a marginally significant three-way interaction . Overall, more vines had symptoms in the second year compared to the first , and there was a higher prevalence of returning symptom in vines from higher initial disease categories . Severe pruning showed an apparent benefit to reducing symptoms of PD after the first year, but this effect weakened substantially by the second year, with no differences for category 1 or 3 vines, and a slightly lower disease prevalence for severely pruned category 2 vines . A survival analysis of severely pruned category 3 vines showed a significant difference in the rate of symptom return among plots . All vines in plots 1 to 3 had symptoms by autumn 2000, two years after pruning . In plots 4 and 5, more than 80% of vines showed symptoms after three years. Only plot 6 showed markedly lower disease prevalence; in plot 6, ~70% and 50% of severely pruned category 3 vines showed no symptoms after two and four years, respectively, versus ~36% of control vines overall, after two years. It is important to note that at the time of this study, disease pressure may not fully explain the return of symptoms in severely pruned vines.

Surveys conducted during the first two years of the study throughout the entirety of the six research blocks showed that the prevalence of PD in control vines actually declined slightly from the first to the second year , but not due to an increase in replanting efforts or vine death , Rather, this decline in prevalence likely reflects overwinter recovery of mild cases of the disease . Thus, the observed return of symptoms in most severely pruned vines does not appear to be explained by reinfection with X. fastidiosa after clearing of infection during the severe-pruning process. Our results indicate that the apparent effectiveness of severe pruning depended on the initial disease severity, and the effectiveness weakened over time. This suggests at least two constraints exist regarding the general utility of pruning as a PD management tool. First, severe pruning does not appear to be useful for mild cases of PD, as many of those same vines would recover from the infection over the winter . Second, there appears to be little value in pruning severely diseased vines; the high frequency of symptom return within a few years indicates that even severe pruning does not clear most vines of X. fastidiosa infection. That leaves a statistically significant window with respect to intermediate severity cases, which may benefit from severe pruning. The apparent benefit for this category of diseased vines would stem from infections that are not so localized that they are highly susceptible to natural recovery over the winter, but also not fully systemic such that the infection has developed below the pruning point . Reliable identification of this narrow class of diseased vines may require substantial experience with PD scouting, detailed record keeping, and an appreciation for variability in symptoms or infection dynamics based on grapevine cultivar and environmental conditions . Research in other bacterial plant pathosystems has evaluated the potential benefit of pruning and whether pruning extent is related to its effectiveness at clearing hosts of infection . A study of the citrus disease huanglongbing, blueberry in pot associated with infection by Candidatus Liberibacter spp., evaluated two levels of pruning severity, neither of which showed promise as a disease management tool . In this pathosystem, it is plausible that a very protracted incubation period may undermine the effectiveness of pruning, because by the time the first symptoms are visible, the infection may have already moved throughout much of the tree. Collectively, our results are more similar to a study of citrus variegated chlorosis . In this study, the presence of X. fastidiosa in plant tissues at different distances from symptomatic leaves was determined for varying levels of disease severity. X. fastidiosa was more widely distributed in trees with severe disease symptoms compared to those with early stage foliar symptoms. Although ColettaFilho et al. did not test whether pruning at various distances proximal to symptomatic leaves would eliminate X. fastidiosa infections, the current recommendation is to prune citrus material if early symptoms are present, and to not prune plants with severe disease symptoms . Citrus plant age is also an important consideration; Coletta-Filho and de Souza recommend that symptomatic citrus trees up to three-years-old be removed rather than pruned, whereas trees four-years-old or older should be pruned. We did not examine vine age as a factor in this study, but the biology of citrus and grape differ in terms of the overwinter recovery that can occur in grape and the apparently slower movement of X. fastidiosa in citrus compared to grape. Anecdotally, the two most mature plots in our study showed the most rapid return of disease, and the youngest plot showed the slowest return.

More studies of the effect of vine age are needed before concluding that interactive effects of plant age and pruning differ between the PD and citrus variegated chlorosis pathosystems.Most bee species are considered mass provisioners—i.e., they build a brood cell into which they pack a mixture of pollen and nectar, deposit an egg on the pollen provision, and seal off the brood cell while the offspring develops. This brood cell is left sealed until the fully developed bee emerges by breaking through the cell cap. While the mother bee creates the pollen provision for the developing bee, numerous other creatures may enter the brood cell. Organisms found in bee brood cells include—but are surely not limited to—nematodes, mites, springtails, bacteria, and fungi. The bee brood cell can therefore be considered a miniature ecosystem, and how the interactions occurring within these tiny ecosystems affect bee health is a fascinating question. High-throughput sequencing has allowed for detailed surveys of the diversity of the microbes that inhabit pollen provisions. Early next-generation sequencing surveys of pollen provisions suggested that many bacteria found in pollen provisions may be acquired from flowers. The observation that the same bacteria inhabit flowers, pollen provisions, and bee guts was subsequently verified. Further studies then linked foraging to microbial transmission, which is more apparent when characterizing a network of plants, multiple bee species, and bacteria than when studying a single population of bees. When looking at multiple populations of one species across habitats, pollen usage and fungi co-vary more than pollen usage and bacteria. The consensus arising from these studies is that flowers serve as transmission hubs for pollen-associated microbes, but the characteristics of pollen provisions may determine which microbes thrive there. The genomes of pollen-associated lactobacilli contain genes involved in osmotic stress tolerance, detoxification of metals and other toxicants, and pollen wall degradation. That these microbes exhibit genomic adaptations for rapid growth in nutrient-rich environments suggests that they likely ferment sugars found in pollen provisions and may exclude spoilage organisms, as their close relatives do in sourdough bread dough. Experimental evidence for a nutritional role of pollen-borne microbes is also mounting. Isotopic signatures of diet suggest that bee larvae from a diversity of bee species are not truly herbivores as one would expect, but instead exhibit omnivorous or even carnivorous traits. This finding suggests that bee larvae are consuming microbes in their pollen provisions. Feeding bee larvae different ratios of sterilized to normal pollen leads to differences in growth rates and survival, again suggesting that larvae consume pollen-borne microbes. Similarly, whether microbes were present or absent in pollen had a greater influence on larval development compared to whether the pollen was collected by con-specific or different bee species for larvae of the specialist blueberry pollinator Osmia ribifloris. Altogether, these studies are beginning to illustrate the importance of microbes in the pollen provisions of wild and solitary bees for larval health. One open question in the study of the microbiome of the pollination landscape is how diet breadth affects exposure to and acquisition of microbes. Across the bee phylogeny, there is a diversity of diet breadths, with some bees visiting a broad diversity of plant species and others visiting a limited number of plants , or even a single plant , with gradations in between these groups. As specialist bees visit fewer plants, they may acquire a distinct microbial community compared to generalist bees. Conversely, if specialists interact with the same plants as generalists do, both classes of bees may be exposed to the same microbes. The microhabitats of specialist and generalist bee pollen provisions may filter different microbes based on pollen and nectar chemistry, altering microbial composition as has been found with nectar microbial communities.

Similarly, it will be pertinent to explore the effects of heattolerant microbes like Acinetobacter on pollinator health and behaviour in the face of climate warming. Our results are a product of the microbe taxa we chose for our synthetic community and the plant species inoculated. However, our findings are likely generalisable to other bioregions, given the widespread geographic distributions of our focal microbes and the inclusion of both native and non-native plant species. Regardless, future research will benefit from incorporating additional plant and nectar traits and increasing replication within clades of plant taxa to clarify mechanisms influencing nectar microbe ecology.Drosophila suzukii Matsumura causes economic damage to susceptible small and stone fruit in North America, Asia, and Europe . Adult female flies oviposit in fruit and developing larvae render the high-value fresh fruit unmarketable and reduce processed fruit quality. Damage from D. suzukii in Western U.S.A. production areas may cause up to $500 million in annual losses assuming 30 % damage levels , and $207 million losses in Eastern U.S.A. production regions . Worldwide, the potential economic impacts due to D. suzukii damage are significant. In any integrated pest management system, it is important to use multiple strategies to manage key pests. For D. suzukii, some of these strategies include monitoring, fruit sampling, and direct control methods . For example, in Trento Province, Northern Italy, prior to the adoption of IPM, the potential losses to D. suzukii were about 13 % of the berry industry’s revenue, plastic planters bulk while after the implementation of an IPM strategy including mass trapping, field sanitation, and insecticide programs, the sum of losses and associated control costs decreased to about 7 % .

The ability to describe, forecast, and more effectively manage damaging pest populations can benefit producers, extension agents, and practitioners . Phenology models based on accumulation of heat units or degree days have become the standard method for determining when to treat crops for pests. These DD accumulation models can be used to predict important life history events based on pest development rates . With phenology models, a specific life stage of a pest, such as adults, can be targeted for management, maximizing efficacy of insecticides. DD phenology models tend to work best for pests with a high level of synchrony and few, non-overlapping generations . Previous data have shown that D. suzukii moves through generations rapidly, and has high reproductive levels and overlapping generations . This suggests that limited benefits are to be gained from a traditional DD phenology model. However, insect population models can also be helpful to predict impending damage of agriculturally and medically important insect pest populations . The major factors affecting population dynamics of D. suzukii include temperature, humidity , and the availability of essential food resources . Although DD phenology models may have limited application for a pest such as D. suzukii, accumulation of heat units can play an important role in predicting population dynamics. Temperature-dependent developmental, survival, and reproductive data are available for all life stages of D. suzukii . Recent D. suzukii modeling has used a combination of mean temperature and calendar-based matrices . The two published demographic models for D. suzukii include a discrete-time stage-specific Leslie matrix model, which did not estimate transition between different life stages for D. suzukii , and a physiologically based demographic model featuring distributed maturation time .

Asplen et al. used D. suzukii physiological data and included non-linear sub-models to capture temperature-dependent developmental rates and survivorship. Neither model takes into consideration winter survival, early-season reproductive potential, or host availability . However, attempts to model insect survival and fecundity using physiological time and matrices have been conducted successfully for other insects . Management strategies for D. suzukii include chemical , biological , and cultural controls. Additional control strategies may include genetic techniques such as RNAi biopesticides . Little information is available at the population level on the impact of insecticide sprays. Insecticides are typically targeted against specific life stages of D. suzukii and result in differential levels of mortality on the different life stages. Currently, calendar-based insecticide spray intervals are focused on preventing oviposition by D. suzukii , but their impacts on populations over a larger spatial scale are unknown. Organophosphate, pyrethroid, carbamate, spinosyn, and some diamide insecticides show efficacy against D. suzukii adults . Residual activity of currently available insecticides is between 5 and 10 days but can be shorter due to rainfall . There is increasing evidence that some insecticides that are active on adult D. suzukii, including spinosad family compounds, which, may also achieve control through mortality of egg and larval life stages . Biological control agents known to attack D. suzukii have been identified in areas of recent pest invasion . However, parasitoid success appears generally lower in these regions compared to levels observed in the indigenous range of the pest . In North America and Europe, specialist parasitoid species are absent.

Field studies indicate that natural populations of generalist species are not having a meaningful effect on populations of this pest; however, in the scope of an IPM program, a conservation biological control approach using these agents may contribute to an overall reduction in local D. suzukii populations . The complex of biological control agents for D. suzukii includes predators and pathogens ; however, parasitic hymenoptera have been the primary focus of current research. Numerous parasitoid species are known to attack frugivorous drosophilids and most attack larvae or pupae in decaying fruits on the ground . Recent studies in the U.S.A. and Europe found that most resident larval drosophila parasitoids were unable to develop on D. suzukii , but in Asia, several parasitoid species of Asobara, Ganaspis, and Leptopilina can attack and develop from larvae of D. suzukii . Collection trips to South Korea in 2013 and 2014 and China in 2013 yielded parasitoid species that readily attack D. suzukii larvae and pupae . Given the increasing availability of D. suzukii physiology data, the goal of this paper is to provide key insights into how physiological time can be utilized to integrate survival, development, and reproductive data from diverse environments. We demonstrate how physiological time is appropriate to describe population dynamics over the growing season. We also demonstrate how the physiological time concept breaks down during overwintering by examining how extreme temperatures cause mortality in non-acclimated D. suzukii at both high and low temperatures. D. suzukii enters reproductive diapause in November/ December in parts of the U.S.A. , and phenotypic changes among individuals in the population can affect winter survival . We focused on the latter portion of winter and spring to determine if DD accumulation could estimate female reproductive potential. Finally, we examined a cohort-level population model based on accumulation of DD utilizing daily high and low temperatures from different field sites to estimate DD for conditions within known thermal thresholds. These data were used to consider the impacts of current and possible future IPM with the cohort DD population model at the field level. Materials and methods The environmental factors described below illustrate the impacts of environmental conditions within and outside of known temperature thresholds of D. suzukii. Additionally, we describe the role of DD accumulation for estimating sexual maturity of reproductive flies collected during the late dormant period. During late winter and early spring, collection pot there is a transition from temperatures outside of thermal thresholds to conditions falling within thermal thresholds. The D. suzukii population model was used to demonstrate how management practices could affect populations on a relative scale.

We examined survival trends of D. suzukii populations under cold and warm temperature extremes outside the developmental and reproductive thresholds. Populations are expected to decrease substantially after exposure to extremes ; however, even after extended periods of unfavorable conditions and lack of suitable reproductive hosts, D. suzukii are known to respond to traps, indicating persistence of populations . We describe the impacts of such unfavorable conditions on population structure by plotting D. suzukii pupal and adult survival levels at extreme low and extreme high temperatures. Survival was fitted in this case with a Gompertz distribution over calendar days because no DD are accumulated at the extremes. Currently, we lack field data to illustrate the role of such environmental conditions on populations. We do not include these parameters in the model described below as this paper focuses on seasonal population fluctuation only.In this analysis, we examined how warming temperatures at the onset of the growing season affect female reproductive potential of field-collected D. suzukii. The goal was to determine if DD accumulation could be used to estimate reproductive potential of flies, and to determine whether laboratory-generated reproduction data are supported by field observations. Collections of females were conducted using established methods and the late dormant reproductive potential of D. suzukii females was classified by dissection of females under magnification to determine whether mature eggs were present and if they were in the ovaries or free in the abdomen . Collections from Seattle, Washington, U.S.A. were made from March 2011 to February 2012, and collections from Corvallis, Oregon, U.S.A. were made from April 2011 to June 2013 . Flies were collected using container traps baited with apple cider vinegar or yeast-sugar solution. Collections in Italy utilized container traps baited with 200 ml of the liquid bait Droskidrink , composed of 3 parts apple cider vinegar to 1 part red wine, with 4 g raw brown sugar dissolved into the mixture. In all sites, the total numbers of females dissected per location and date were used to calculate the percentage of females containing mature eggs. The percentage of females containing mature eggs was plotted over the midpoint for the time period in DD calculated from the daily high and low temperature using the single sine method. Temperature data originated from weather stations proximate to collection sites representing the regions where collections were made. In all regions, the relationship between accumulated DD and reproductive potential was determined with multiple regression .For the model runs, we used two of the temperature datasets originally from Wiman et al. . The first was from the 2013 growing season in Salem, Oregon, U.S.A. and the second from 2013 in Parlier, California, U.S.A. Mortality factors simulating management activities were applied to select life stages for the periods outlined below. Model runs started early in the season because the population structure during the beginning of the growing season was composed of mostly adults. This timing allows us to see how pesticides targeting adult or immature life stages perform in relative terms. For California, we assume that adults colonize blueberry fields to oviposit on ripening fruit on April 1. Whereas growers would likely apply insecticides more than one time per season, for simplicity, hypothetical insecticides were applied one time at the beginning of the season. Two insecticides with different effects on specific life stages were independently input into the model to compare population-level impacts. The two compounds represented active ingredients that control both adults and immature stages of D. suzukii at different levels . Insecticide A elicited an adult mortality factor of 95 % and an immature mortality factor of 5–100 %. Insecticide B caused 60 % adult mortality and 60–95 % mortality of immature stages. These mortality factors included a range of efficiency in order to simulate reduced residual activity over time. This technology has undergone major advances as a tool for pest management. Double-stranded RNA is administered to targeted insects by genetic modification of the crop, or synthesized in vitro and topically applied to host plants . Murphy et al. described a novel dsRNA delivery system in which researchers genetically engineered yeast to produce dsRNA that knocks down genes that are predicted to be critical for D. suzukii fitness. The yeast biopesticide, Insecticide C, was shown to decrease larval survivorship and to reduce adult locomotor activity and reproductive output. Using these findings, we applied realistic mortality levels as highlighted by Murphy et al. , assuming efficient delivery and persistence, in which D. suzukii egg production and egg viability was 63.2 % lower , and 22 % of the larvae were killed for a period of 7 days. The mortality factors for each class of toxicant were applied using weather data from Parlier, California, U.S.A. for 20–30 April 2013 using these treatment scenarios.

Among 1605 phylogenies analyzed , the lowest Smap values were for highly conserved CDSs such as ribosomal and cell division proteins. On the other hand, the highest Smap values found were ~0.5 belonging to CDSs encoding TonB-dependent receptor and the hypothetical protein PD0014 . Only 9 orthologous CDSs previously identified or predicted to be virulence and pathogenicity factors were among the 100 CDSs with Smap values greater than 0.44 with confidence >90% . These 9 CDSs include two related to adhesion , two related to polysaccharide hydrolysis , two related to polysaccharide synthesis and three that encode, respectively, quorum sensing response regulator , multidrug efflux pump and lipase/esterase . However, we reasoned that these medium Smap scores do not provide strong support to consider these CDSs as candidates to host specificity determinants.The enrichment of accessory genome with mobilome-associated CDSs prompted us to explore the full set of MGEs in X. fastidiosa strains. Using a combination of prediction tools, we identified a comprehensive set of sequences related to the MGEs in the 94 genome assemblies analyzed here. The content of MGEs varies considerably among the strains, ranging from 3.8% to 27.76% of the genome, with a mean value of 13.92% ± 5.77%. Among the strains with the higher MGE content are Dixon, U24D, 3124, Ann-1, MUL0034 and 9a5c . It is important to note that the strains whose genome assemblies are in contigs showed the lower percentages of MGE content than the strains with complete genomes, blueberry containers possibly due to a reduced efficiency of the programs to predict MGEs in fragmented genomes.

Overcoming this limitation will have to wait for the availability of complete versions of these genomes which, in most cases, requires resequencing with long-read technologies. X. fastidiosa genome assemblies harbor 11.6 ± 2.71 prophage-related regions. Among the complete genomes, the strains RH1 and LM10 of subspecies multiplex have the greatest number of prophage regions while those with the least prophage regions are the subspecies pauca strains Pr8x, Salento-2, De Donno . We found 5 intact, 2 incomplete, 1 questionable and 3 remnant prophages in 9a5c strain , and 4 intact, 5 incomplete, 3 questionable and 1 remnant prophages in Temecula1 strain . The genomes of X. fastidiosa also harbor on average 6.47 ± 2.57 genomic island regions. The strains U24D and 9a5c have the greatest number of genomic islands while the strains IVIA5235 and Bakersfield-11 have only 5 regions each. We found on average 6 ± 1.53 insertion sequences within certain prophages, genomic islands, chromosomes, or, occasionally, in plasmids.We performed a screening of the known immunity systems in X. fastidiosa to explore the strategies used by this bacterium to deal with their numerous MGEs . The screening of 94 X. fastidiosa genome assemblies detected only CDSs belonging to Restriction Modification , Toxin-Antitoxin , Cyclic-oligonucleotide-based antiphage signaling systems , Gabija and Wadjet systems. For each detected system, the CDS neighborhood was evaluated. The prediction of R-M systems showed that all strains possess at least one of the three main R-M system types previously reported for 9a5c and Temecula1 strains. The type II was usually found in multiple operons per genome, while the type III was observed in a single operon per genome. R-M type I and II were frequently found in all strains, and in most instances more than one subunit homolog was observed.

In contrast, R-M type III was mainly found among strains of subspecies pauca and fastidiosa. Curiously, the strains lacking R-M type III , have more homologs of the R-M type II subunit . The TA type II system was found mainly in the strains from the subspecies pauca from South America. This TA system is widely distributed among prokaryotes and has been confirmed to be involved in diverse biological processes including plasmid maintenance, phage inhibition, stress response, and others. The CBASS phage defense system is composed of an oligonucleotide cyclase, which generates signaling cyclic oligonucleotides in response to phage infection, and an effector that is activated by the cyclic oligonucleotides and promotes cell death. This system was found in strains from the subspecies pauca from Europe, and also in strains from the subspecies fastidiosa.The comparative analyses of 94 publicly available whole-genome sequence assemblies of X. fastidiosa strains revealed a pangenome comprising 4549 orthologous CDSs and a core genome of 954 CDSs . These values are somewhat different than previously reported because we have used different algorithms for genome annotation and clustering of orthologous CDSs as well as a larger number of genomes in the analyses. We found that the vast majority of the CDSs previously identified or predicted to be virulence and pathogenicity factors for X. fastidiosa belong either to the core or soft-core genomes. A core genome-scale phylogeny grouped the 94 X. fastidiosa strains in three major clades defined by strains from the subspecies fastidiosa , multiplex , and pauca consistent with previous k-mers based phylogeny of 72 X. fastidiosa strains as well as with phylogenetic reconstructions from 349 X. fastidiosa genomes. While several of the subclades sharing ST groups are congruent with country of origin of the strains, plant species from which strains were isolated are less congruent with these subclades. Although some strains isolated from Citrus, Olea, Vitis, and Morus group in separated subclades, other strains mainly isolated from Coffea, Prunus, and Nerium are distributed into the three distinct major clades .

It has been shown that citrus and coffee strains from subspecies pauca seem to be limited to their original hosts, despite crop proximity and the presence of insect vectors. In addition, there is experimental evidence of host specialization for certain X. fastidiosa strains. On the other hand, it is known that some strains can infect multiple hosts and that intersubspecific homologous recombination has been associated to X. fastidiosa adaptation to novel hosts. The factors that drive X. fastidiosa host-specificity or adaptation to new hosts have not been clearly elucidated despite recent evidence of a genetic basis to the host range of X. fastidiosa. Here we have explored the soft-core and core genomes for potential candidates related to this trait using comparative genomics, an approach that has been applied for some bacterial pathogens. Using a mapping metrics applied to phylogenetic trees for 1605 orthologous CDSs we found no CDS with Smap values that would provide strong support to point a CDS as candidate to host specificity determinant. The highest Smap values found were ~0.5, and among these CDSs only a few CDSs were related to virulence, including two related to adhesion , two related to polysaccharide hydrolysis , two related to polysaccharide synthesis and three encode, respectively, quorum sensing response regulator , multidrug efflux pump and lipase/esterase that present medium Smap scores. We call attention to CDS PD0815 related to LPS biosynthesis. It has been shown that O-antigen delays plant innate immune recognitionin grapevine and as such the heterogeneity of O-antigen composition may be related to X. fastidiosa host range. In summary, the approach we have used did not provide strong supporting evidence for CDSs that would contribute to X. fastidiosa host-specificity. It has been suggested that the X. fastidiosa pangenome is linked to host association and the presence/absence of a few genes in strains isolated specific plant genera have been correlated to host-specificity. However, at the present time some limitations for an experimental study of X. fastidiosa host-specificity should be considered such as prompt availability of sequenced isolates as well as the difficult genetic manipulation of some strains. Our comparative analyses revealed that the content of MGEs varies among X. fastidiosa strains and includes a considerable diversity of sequences related to prophages, GIs, ISs and plasmids with variable sizes . While several MGE sequences are conserved among X. fastidiosa strains some are unique MGEs, belonging to a single strain among the ones we analyzed here. The X. fastidiosa 94 genome assemblies harbor 11.6 ± 2.71 prophagerelated regions and 6.47 ± 2.57 genomic island regions.

A previous study reported 6 and 8 prophage-like elements respectively in genomes of 9a5c and Temecula1 strains, and a comparison of 72 X. fastidiosa genomes revealed an average of 9.5, 9.3 and 8.5 prophage regions, respectively, for strains from subsp. fastidiosa, multiplex and pauca. It remains to be investigated whether multiple prophage regions confer any fitness advantage to X. fastidiosa, as has been observed for Pseudomonas aeruginosa, best indoor plant pots where multiple prophage carriage seems to be beneficial during mixed bacterial infections. It is worth noting that inoviruses sequences are found in most of the analyzed strains and that they encode a Zot protein. Inoviruses have a relevant role in the structure in P. aeruginosa biofilm and have been reported to encode Zot in several Vibrio species. Zot protein seems to play a dual function as it is essential for inovirus morphogenesis and has also been reported to contribute for Vibrio cholerae pathogenesis. This toxin has been postulated as virulence factor for plant pathogens, including X. fastidiosa. Interestingly EB92-1, a proposed X. fastidiosa biocontrol strain, lacks both Zot homologous genes found in Temecula1 strain. Moreover, a X. fastidiosa Zot protein was shown to elicit cell death-like responses in the apoplast of some Nicotiana tabacum cultivars. Besides Zot, other prophage-encoded genes may play a role in the biology of X. fastidiosa as observed in other bacteria, where the so called “moron” loci have been related to virulence, stress resistance, phage resistance and host adaptation. More studies are necessary to understand the contribution of “moron” loci, such as Zot genes, as well as events of prophage induction to X. fastidiosa biology. There is experimental evidence X. fastidiosa releases phage particles but the impact of prophage induction in host colonization is unknown. To cope with the MGEs, bacteria have developed a diversity of immunity systems. The numerous immunity systems of some genomes protect the cell from a broad range of MGEs, and the MGEs themselves encode defense systems, which tend to be different across strains of a species. Although X. fastidiosa strains are devoid of most of these systems, R-M systems and one conserved cluster with genes of Gabija system were found widely distributed among the genome assemblies analyzed in this work. TA type II system and CBASS immunity systems were found only in some strains. It should be mentioned that the R-M systems have been reported to impact the stable acquisition of foreign plasmid DNA by X. fastidiosa. The low amount and diversity of immunity systems found in X. fastidiosa genomes, with the notable absence of important immune systems, especially CRISPR-Cas, gives a hint to understanding the high amount of MGEs found in this bacterial species. It seems that R-M, Gabija and CBASS systems are not enough to protect X. fastidiosa against phage acquisition. For instance, Temecula1, one of the most studied X. fastidiosa strains, carries 12 prophage regions, but only three immunity systems. This lower amount of immunity systems relative to high number of prophages differs from the positive correlation between the number of prophage and families of antiphage systems observed at species level. Therefore, we do not exclude the possibility that X. fastidiosa genomes might encode immunity systems yet to be discovered. The comprehensive comparative analyses of 94 whole-genome sequences from X. fastidiosa strains from diverse hosts and geographic regions contribute to a better understanding of the diversity of phylogenetically close genomes, explores candidates to host specificity determinants for this phytopathogen as well as greatly expands the knowledge of its mobile genetic elements content and of its immunity systems.The phylum Negarnaviricota, composed of viruses with negative-stranded RNA genome, includes species characterized by non-segmented or segmented genomes, the presence or absence of a membrane enveloping the capsid, and a diverse host range including plants and animals. Examples of nsRNA viruses associated with economically important diseases in plants are rose rosette virus , rice stripe virus, citrus psorosis virus, and blueberry mosaic associated virus. Historically, only a relatively small number of nsRNA viruses infecting plants as their primary host have been reported. Recently, however, more novel viruses infecting plants have been discovered around the world. In the last few years, the use of high throughput sequencing technology has allowed the identification and characterization of new nsRNA viruses in pistachio, citrus, watermelon , and apple. Interestingly, most of these novel nsRNA viruses were classified under the family Phenuiviridae . To date, there are fifteen recognized generaintegrating the family Phenuiviridae : Banyangvirus, Beidivirus, Goukovirus, Horwuvirus, Hudivirus, Hudovirus, Kabutovirus, Laulavirus, Mobuvirus, Phasivirus, Phlebovirus, Pidchovirus, Tenuivirus, Wenrivirus, and Wubeivirus. Except for members of the genus Tenuivirus that are plant-infecting viruses, the members of the other genera infect vertebrates, including humans, and arthropods.

Non-aborted carpels, and seed production as the counts of developed seeds vs. undeveloped seeds, both of which are structurally binomial variables. Relative to a binomial distribution, however, our data for both analyses were overdispersed which we corrected by including an individual-level random effect . We ran GLMMs with binomial-errors using the default logit link in the ‘lme4’ package for R . We assessed the relative contribution of the quantities of heterospecific and conspecific pollen on reproductive output and carpel abortion using a modelcomparison framework. In these models conspecific pollen and heterospecific pollen, as well as their interaction, are the fixed effects that we assess in different combinations. We specifically compared five mixed-effects models: full model including an interaction between the two fixed effects ; additive model ; amount of conspecific pollen only; amount of heterospecific pollen only; and a model including no fixed effects . For all analyses, we used AICc, Akaike’s Information Criterioncorrected for small sample size , to determine the best model. We reported all models within two ΔAICc points of the best model. We used the ‘AICcmodavg’ package in R for model selection. We excluded observations in which there was seed set with either zero stigmatic pollen recorded , blueberries in pots or zero proportion of conspecific pollen . We assume that these observations were due to loss of stigmatic pollen in the field between fertilization and stigma collection.

To understand the association between naturally deposited heterospecific pollen and seed production, we used a field approach linking stigmatic pollen deposition to seed set in the same individual carpels in wild plants. Heterospecific pollen deposition was highly variable on D. barbeyi stigmas in the field and while some degree of heterospecific pollen was found on most sampled flowers, it was typically present in low amounts . Neither heterospecific pollen nor conspecific pollen was a good predictor of carpel abortion in our sites. Conspecific pollen deposition was positively related to viable seed production, but we also found a significant negative interaction between heterospecific pollen and conspecific pollen. That is, with increasing heterospecific pollen, the positive relationship between conspecific pollen deposition and viable seed production in D. barberyi became weaker . We found that heterospecific pollen on D. barbeyi stigmas is widespread, highly variable, and typically occurs at relatively low levels. In terms of variability, heterospecific pollen represented anywhere from 0 to 97% of the grains present in a pollen load. The widespread nature of heterospecific pollen deposition is reflected by the fact that 85% of stigmas had some heterospecific pollen present. Still, most stigmas received only low levels of heterospecific pollen deposition . These results are broadly consistent with patterns reported in a comprehensive review of studies assessing the impact of heterospecific pollen transfer, including 77 species from 17 different sources . This review found that, although receipt of heterospecific pollen was variable, all species received at least some heterospecific pollen on their stigmas. Similarly, in a community-wide analysis of pollen transfer, Fang and Huang found that of the 57 plant species they surveyed, heterospecific pollen deposition was common but highly variable, representing 0-66% of the total pollen on stigmas.

The co-flowering plant community and pollinator behavior are just two of the factors that might influence variation in HP receipt between plants of the same species within and between sites. Variation in heterospecific pollen receipt within species or even within a population obviously has important implications for evolution of coping mechanisms and remains an area ripe for more research . A large proportion of carpels aborted in our study , yet contrary to our expectations we found that neither heterospecific pollen nor conspecific pollen was a good predictor of carpel abortion in D. barbeyi. Thus, it seems likely that resource limitation, rather than pollen limitation, drove carpel abortion in our system. Extrinsic factors such as weather conditions, flower phenology, herbivory, competition , and disease can lead to within plant variation in carpel abortion . Furthermore, intrinsic factors including architecture , plant size, developmental constraints or allocation strategies are also known to affect patterns of carpel abortion . In contrast to carpel abortion, both conspecific pollen and heterospecific pollen played a role in seed production in D. barberyi. As expected, conspecific pollen deposition on its own was positively related to viable seed production. Heterospecific pollen on its own did not affect seed set, but there was a significant negative heterospecific pollen × conspecific pollen interaction. In other words, with greater heterospecific pollen deposition, a fixed amount of conspecific pollen would result in lower seed set. Because this was a correlational study, we were not able to tease apart other factors that may have lead to a decrease in seed production such as diversity of heterospecific pollen.

To our knowledge, this is the first demonstration of an interaction between heterospecific pollen and conspecific pollen in their effects on plant reproduction. We hypothesized that we would find such an interaction as we expected that the negative effects of heterospecific pollen might occur only in the context of conspecific pollen. In a case comparing deposition of a small vs. a large heterospecific pollen load in stigmas with no conspecific pollen should yield the same result: zero seeds produced. Following the same logic, we would expect the impact of depositing a medium-sized load of heterospecific pollen on a stigma would differ in stigmas with just a few conspecific pollen grains versus a large conspecific pollen load . We are aware of only one previous assessment of the statistical interaction between stigmatic pollen load quantity and the proportion ofheterospecific pollen grains . This study found no evidence for a pollen quantity × proportion heterospecific pollen interaction, but the study design was oriented at a different objective and thus included just two heterospecific pollen load sizes, which corresponded to 28% and 16% of total pollen load proportions. Finally, we were not able to distinguish between self and outcrossed conspecific pollen in this study. Self pollen has been shown to intensify the negative impact of HP receipt in Mimulus guttatus and self pollen has been shown to produce fewer seeds in D. barbeyi . More studies examining how mixed mating plant species cope with HP receipt would be valuable, particularly in a field setting where plants may receive HP from a variety of plant species. Putting this result in the context of previous findings highlights that there has been a gulf between field studies and hand-pollination studies in greenhouse settings, a gulf that, if bridged, would improve our understanding of the effects of heterospecific pollen transfer in nature. Future work in hand-pollination studies should contribute to bridging the gap by integrating what we have learned from field studies so far. First, hand-pollination studies should be designed using parameters explicitly drawn from field studies, in terms of heterospecific and conspecific pollen amounts, and heterospecific pollen diversity, considering not only means but also variability. To date, most hand-pollination studies have used only one proportion of heterospecific pollen , and we are aware of only one hand-pollination study that specifically applied a full range of heterospecific pollen deposition. Second, the results from our field study, particularly our finding of a heterospecific pollen × conspecific pollen interaction in seed production, highlights the advantage of understanding this result mechanistically, via hand-pollination studies that vary the quantity of both conspecific pollen and heterospecific pollen factorially. Third, our finding that neither conspecific pollen nor heterospecific pollen was strongly linked to carpel abortion rates underscores that hand-pollination studies that control both pollen and resource limitation in a greenhouse setting could greatly improve our understanding of how these factors interact. Similarly, field studies on the effects of heterospecific pollen can look to hand-pollination experiments—with their typically more mechanistic focus—for inspiration. A critical first step is to increase the number of field studies that directly link pollen deposition and seed production within the same carpel . To our knowledge the work we present here was the first time that this approach has been applied to understanding the effects of heterospecific pollen, which should be repeated in a wide range of plant species with different mating systems .

Another particular need is for field studies that assess multiple sites. We continue to have a poor understanding of how plant genotype and environmental factors interact to shape the effects of heterospecific pollen, square plant pots and work along environmental gradients could be informative, especially in disentangling the relative effects of pollen vs. resource limitation in shaping seed set. Similarly, experimental approaches to assessing the relative effects of resource vs. pollen limitation in the context of heterospecific pollen deposition in field settings would also be a valuable research direction. Finally, hand-pollination and field approaches should be explicitly integrated by conducting more hand-pollination experiments in field settings. Our understanding of the impact of heterospecific pollen deposition is growing, but there is still much to learn about the way that co-flowering plants interact through pollinator sharing and how heterospecific pollen deposition impacts plant reproductive fitness. In a changing world where we can expect to see both increasing disruptions in pollination as well as the emergence of new interactions via introduced species and climate change, studies that unify both field studies and controlled hand pollination studies will allow us to better understand the implications of heterospecific pollen deposition for reproductive output in natural plant communities.Pollinator foraging behavior directly impacts plant reproductive output and ecosystem function through the transfer of pollen between plant individuals within a single foraging bout. If pollinators move between different plant species they can transfer heterospecific pollen, potentially reducing reproductive output . Given the functional significance of pollinator resource use, it is important to understand the factors driving pollinator foraging behavior. The plants that pollinators forage on is a function of a number of factors including innate and learned preference, morphological traits, as well as direct and indirect competition with other pollinators in the community . This study focuses on how competitive interactions between pollinators shape pollinator foraging behavior. Decades of research has demonstrated that interspecific competition can influence pollinator foraging behavior. In one example, Pimm et al. found that in the presence of a dominant competitor, two other hummingbird species spent more time at a less rewarding feeder. In contrast, without interspecific competition, all three hummingbird species visited a feeder with high sucrose concentrations. Brosi and Briggs found that after a release from interspecific competition, bumble bees decreased their floral fidelity . These changes in foraging behavior led to a significant decrease in reproductive output in a common alpine plant species. Fründ et al. provide another example in which pollinators’ flower preferences can be flexible, and depend on community context . In their system, as competition between pollinator species increased, the species reduced their niche overlap by shifting to new plant species, which resulted in increased plant reproduction. Thus, we know bees respond to competition and often do so strongly, but we do not know if bee species vary in their response to competition in complex assemblages of bee species or what traits are important in determining how they will respond. Trait based differences between species may reduce interspecific competition and maintain diversity within a community . Generally, we still have a poor understanding of which traits influence the outcome of competition and community structure but some animal traits such as body size or bill size/shape and plant traits related to resource acquisition, such as root depth , can limit competition thus encouraging species coexistence. Bumble bee communities provide an excellent system in which to empirically explore how trait differences drive foraging plasticity in response to interspecific competition, all within a community context. Bombus assemblages are often species-rich, and sympatric species typically have substantial overlap in their life history requirements . Furthermore, traits that affect resource acquisition and foraging efficiency can influence how species partition resources within a community . Tongue length is a trait that directly determines which resources a bumble bee can access and how resource selection varies among species . In general, long-tongued bumble bee foragers visit flowers with deep corollas and short-tongued bumble bees forage on shallow flowers . Still, bumble bees are known to be labile in their foraging patterns if more rewarding floral resources become available or the competitive landscape shifts .