Bee foraging activity can also be affected by preferences for particular weather conditions , temperatures , or preferences for floral phenology leading to temporal complementarity. Interspecific interactions between bee species can also increase honey bee efficiency . In almonds, wild bee presence increases the likelihood that honey bees will move between different rows, which leads to higher pollen tube initiation and subsequent fruit set . Both niche complementarity and interspecific interactions likely underlie the positive relationship we detected between richness and seed set . In agreement with past findings , we detected an interactive effect between wild bee and honey bee visitation on sunflower seed set. We did not, however, detect any main effects of wild bee and honey bee visitation, despite strong evidence that wild bees positively increase seed set regardless of honey bee abundance . In order to evaluate the direct contribution of wild bees, other studies have estimated the contribution of wild and honey bee visitation to seed set separately . We were unable to do this because of our study design, which did not examine seed set from single bee visits. Nevertheless, this is the first sunflower seed set study to detect an interspecific interactive effect at the community-level rather than at the individual-level. However, despite the importance of these interactive effects on sunflower yield, company was the factor that most strongly influenced seed set. Although there was little variation in head size between sunflower companies , using company as a classification may mask other differences, such as genetic differences between varieties and variation in field management techniques. By pairing control and hedgerow sites by company, variety and landscape context, we sought to minimize these potential differences, and the few differences in management practice were noted between companies. It is hypothesized that the effectiveness of field-edge vegetation re-diversification is maximized in landscapes that retain a small percentage of natural areas that can facilitate recolonization of restored habitats . The added benefits of diversification efforts may be minimal in complex landscapes with high proportions of natural habitat since ecosystem service providers are often already supported.

Diversification efforts may not support ecosystem providers in highly intensified landscapes with no remaining natural habitat, big plastic pots either because there are no source areas to colonize the new habitats or because the new habitats alone cannot support populations of ecosystem service providers . Although the landscape where we conducted our study constitutes a “cleared” landscape, and we did not detect landscape effects, other studies in the same location have found that hedgerows increase wild bee abundance, richness and population persistence and promote rare and/or more specialized species . Nevertheless we did not find evidence that these biodiversity benefits translated into higher rates of pollination services in adjacent sunflower crop fields. Although both wild bee richness and abundance were important factors contributing to sunflower seed set, these contributions may be attributable to factors other than hedgerows. For example, wild bee visitors to sunflower were predominately sunflower specialists; the amount of sunflower maintained in the landscape over time could therefore influence sunflower pollinator populations more strongly than hedgerow plantings that do not contain floral resources suitable for the specialists’ dietary requirements , as we found was true in the independent dataset. While conservation and ecosystem service outcomes can be synergistic, win–win scenarios are challenging to achieve . Hedgerows augment pollinator populations, which can be important for achieving wild bee conservation goals ; however, they may not be a “silver bullet” strategy for increasing crop pollination. Both the scale of the re-diversification effort relative to the farming system and the adjacent crop type could limit the effectiveness of hedgerow plantings. Hedgerows occupy <1% of our study landscape and contain 175 times less area than a typical average crop field in our study area.

The intensity of bloom in hedgerows is also minimal in comparison to the hundreds of thousands of blooms in a single MFC field . Increasing the size of hedgerows relative to fields or introducing a suite of diversification techniques could increase the effectiveness of re-diversification efforts . Patch size may influence a habitat’s capacity to host different densities of pollinators . Alternately, the configuration of habitat could impact pollinator populations. For example, when Morandin and Winston examined the optimal spatial distribution of a MFC, canola , they found that both profits and pollination services would be maximized if a central field was left fallow or allowed to revert to semi-natural habitat. The size, configuration and quality of habitat may all interact to influence pollinator communities . The benefits of field-edge diversifications may also differ based on crop identity and landscape context . For example, sunflower has easily accessible florets that attract both generalist and specialist pollinators. However, in systems where flowers have specific requirements, such as highbush blueberry that requires buzz-pollination, the identity of pollinator species may be of more importance . Further, species-specific responses to habitat features may differ. Carvell et al. found bumble bees had differential responses to wildflower patch size and landscape heterogeneity, indicating that local and landscape habitat factors can also interact with one another, and with crop-specific attributes, to affect crop pollination. In a tropical region, Carvalheiro et al. found that wildflower plantings worked in concert with natural habitat to heighten mango production. There are a paucity of studies on the ecosystem service benefits from field-edge plantings, therefore the complex range of factors, including farming type, crop system, landscape context, and region , influencing their performance is still relatively unknown .Xylella fastidiosa is a Gram-negative bacterium in the Xanthomonadaceae family that colonizes the xylem vessels of its plant hosts and is exclusively vectored by xylem sapfeeding hemipteran insects. This bacterium causes several crop diseases, such as Pierce’s disease of grapevine, citrus variegated chlorosis, coffee leaf scorch, plum leaf scald, and olive quick decline syndrome.While X. fastidiosa has also been associated with diseases in many other plant species, the bacterium behaves as a commensal endophyte in a variety of its plant hosts. A range of pathogenicity and virulence factors has been identified in X. fastidiosa that potentially enable the bacterium to overcome host defenses and successfully establish itself in the xylem tissue. X. fastidiosa cells form biofilm-like structures that are crucial for successful acquisition and transmission by the insect vectors as well as for plant host colonization and pathogenesis. Progression of the disease symptoms is associated with X. fastidiosa systemic spread through the xylem vessel network which requires dispersal of bacterial cells from the biofilms as well as twitching motility and degradation of pit membranes by bacterial cell wall–degrading enzymes. Moreover, the severity of symptoms is exacerbated by host-derived xylem occlusions elicited by X. fastidiosa colonization of grapevine. Indeed, the symptoms caused by X. fastidiosa infection are suggestive of hydric stress and vary in intensity depending on pathogen genotype, plant host species/genotype, plant age, cultivation practices, and environmental conditions. Originally confined to the Americas, X. fastidiosa has spread to various plant species in a number of European countries, possibly through the importation of infected plant material.

Currently, most of X. fastidiosa strains are categorized in three major subspecies, fastidiosa, pauca and multiplex, which are presumed to have originated in Central America , South America and North America. Another two subspecies native to North America have also been proposed. Furthermore, X. fastidiosa strains can be classified into sequence types based on a multilocus sequence typing scheme with seven housekeeping genes. There is a loose association of X. fastidiosa subspecies or STs with host specificity, yet some strains can infect multiple hosts. Indeed, intersubspecific homologous recombination has been associated with X. fastidiosa adaptation to novel hosts. However, the mechanisms by which the distinct X. fastidiosa strains successfully colonize specific plant hosts remain unclear. X. fastidiosa lacks the Type III secretion system, growing berries in containers a membrane-embedded nanomachine typical of Gram-negative pathogens, which delivers effector proteins directly into host cells triggering or suppressing defense mechanisms, respectively in resistant or susceptible plants. Instead, X. fastidiosa type II secretion system seems to be a relevant delivery apparatus of its virulence proteins. It has been suggested that compatibility between xylem pit membrane carbohydrate composition and X. fastidiosa T2SS-secreted cell wall degrading enzymes is necessary for disease progression. Moreover, since X. fastidiosa lipopolysaccharide long chain O-antigen effectively delays plant innate immune recognition in grapevine, the heterogeneity of O-antigen composition may be among the mechanisms underlying X. fastidiosa host range. Comparative genomics studies of X. fastidiosa strains isolated from different plant hosts and from diverse geographical regions identified shared and exclusive genes among these strains, chromosome rearrangements, indels, single nucleotide polymorphisms as well as differences in their mobile genetic elements repertoire, such as plasmids, genomic islands and prophages. While some studies suggest that strains belonging to a phylogenetic group have similar pathogenicity mechanisms and strong selection, possibly driven by host adaptation, other studies identified differences in each subspecies, such as enriched molecular functions and distinct rates and events of recombination. The availability of new whole genome sequences of X. fastidiosa strains from diverse plant hosts and distinct geographical regions fosters up-to-date comparisons to be made. Here we present a thorough comparative analysis of 94 X. fastidiosa genomes with the goal of providing insights into host specificity determinants for this phytopathogen as well as expanding the knowledge of its MGE content and of its immunity systems.Nucleotide sequences of core genome orthologous CDSs were aligned using Clustal Omega v.1.2.1 with default parameters. Then, the sequences were concatenated and homologous recombination regions were masked using Gubbins v.3.1.6. The core genome phylogenetic tree was built with a maximum-likelihood method using IQ-TREE v.1.5.4 with a model predicted by ModelFinder and an ultrafast bootstrap of 1000 replicates. Phylogenetic trees for 1605 orthologous CDSs found in more than 80 strains including the soft-core and core genomes were built with a maximum-likelihood method using IQ-TREE v.1.5.4 with an ultra fast bootstrap of 1000 replicates. Information of plant host of origin for the strains was mapped to the conserved CDSs phylogenetic trees and a Score of mapping was estimated. The overall concept behind Smap was based on consenTRAIT, a metric that estimates the clade depth where organisms share a trait. The Smap for each phylogeny was estimated using a custom Python script that uses Phylo module to find clades in a tree and to calculate the proportion of each plant hostin each clade . The highest proportions of a given host is then retrieved and summed to obtain the Smap. We calculated Smap for both ML and bootstrap trees to get the average of Smap and the percentage of the trees with the same Smap to retrieve the confidence level. Smap values close to 1 indicate a strong relationship between specific hosts and the phylogenetic tree of an orthologous CDS while lowest values are found for highly conserved CDSs unrelated to specific hosts.Mobile Genetic Elements , such as prophages, genomic islands and insertion sequences were identified in the genome assemblies by a combination of prediction tools coupled with manual curation as previously described. Prophage regions were predicted with Virsorter2 and PHASTER. Inovirus_detector software accessed in 4 November 2021 was used for identification of prophages from the Inoviridae family. GI regions were defined using SeqWord Sniffer and GIPSy software, which was used to assign one or more categories related to GI potential function. GI regions overlapping to prophage regions were not considered. IS regions were predicted using the ISEScan software. Retrieved prophage, GI, and IS nucleotide sequences were compared to explore homology relationships using BLAST all-vs-all. Results of BLAST with an identity and coverage alignment higher than 50% and 80%, respectively, were filtered, analyzed and the resulting sequence similarity network was visualized with Cytoscape 3.8 software. Taxonomic classification of intact and incomplete prophages according to PHASTER output was performed with vContact2 and with PhaGCN.The relationship of the orthologous clusters of 1605 CDSs found in more than 80 strains with their respective plant host of origin was explored by mapping the host metadata to the individual phylogenies. A Score of mapping was estimated where Smap close to 1 indicates a strong relationship between the hosts and the phylogenetic tree of each orthologous CDS.