Museum specimens reveal loss of pollen host plants as key factor driving wild bee decline in The Netherlands

Evidence for declining populations of both wild and managed bees has raised concern about a potential global pollination crisis. Strategies to mitigate bee loss generally aim to enhance floral resources. However, we do not really know whether loss of preferred floral resources is the key driver of bee decline because accurate assessment of host plant preferences is difficult, particularly for species that have become rare. Here we examine whether population trends of wild bees in The Netherlands can be explained by trends in host plants, and how this relates to other factors such as climate change. We determined host plant preference of bee species using pollen loads on specimens in entomological collections that were collected before the onset of their decline, and used atlas data to quantify population trends of bee species and their host plants. We show that decline of preferred host plant species was one of two main factors associated with bee decline. Bee body size, the other main factor, was negatively related to population trend, which, because larger bee species have larger pollen requirements than smaller species, may also point toward food limitation as a key factor driving wild bee loss. Diet breadth and other potential factors such as length of flight period or climate change sensitivity were not important in explaining twentieth century bee population trends. These results highlight the species-specific nature of wild bee decline and indicate that mitigation strategies will only be effective if they target the specific host plants of declining species.Pollinating insects such as bees play an essential role in the pollination of wild plants (1) and crops (2). However, reported population declines in both wild and managed bees (3–5) have raised concerns about loss of pollination services and triggered interest in identifying the underlying causes for bee decline (6). Land use change and agricultural intensification are major drivers of biodiversity loss in general (7, 8) and are considered the most important environmental drivers of loss of wild bee diversity in particular (6, 9). It is generally believed that these drivers affect bees, which depend on floral resources in both their larval and adult life stages, through repercussions on the availability of floral resources in contemporary anthropogenic landscapes (9–11), but, so far, scientific evidence that loss of floral resources is driving bee decline is lacking. Nevertheless, current strategies to mitigate bee decline focus primarily on enhancing floral resources (12). To prioritize and develop effective mitigation strategies, it is essential to identify the mechanisms underlying bee population trends and assess whether these are mediated by floral resources.Although bees as a group are declining, individual species show more variable responses, with some species declining sharply while others remain stable or even increase under current land use change and agricultural intensification (3, 4, 13). These differential responses can be used to disentangle the effects of floral resource availability from those of other potential factors affecting bee population trends. The proportion of the floral resources in contemporary anthropogenic landscapes that can be used for forage by a bee species depends on its diet breadth and host plant preference, and it may be expected that species that have declined have a narrower diet breadth and prefer host plants that have declined (14, 15). However, diet breadth and host plant preference of bee species is difficult to assess. Presently observed host plant use does not necessarily reflect actual preference, as preferred host plants may have gone locally extinct and bees that have declined may have become restricted in their food choice in their remaining habitats (15). In addition, if host plant use is measured for more individuals of abundant, widespread species than for rare ones, an apparent link between diet breadth and population trend may simply arise as a sampling artifact (16). Furthermore, the relationship between host plant use and population trend may be confounded by species’ rarity prior to the onset of major environmental changes (17), as rarity in itself increases susceptibility to stochastic events (18) and has been shown to be one of the most important factors predicting population decline in various taxa (19–21). Surprisingly, to our knowledge, none of the studies that have so far examined the relationship between diet breadth and/or host plant preference and bee population trends have taken species’ initial rarity into account (e.g., refs. 3, 4, 15, and 22). Other factors, such as body size (4, 23), phenology (4, 22), and sensitivity to climate change (4, 24, 25) may be associated with bee decline as well, and, to date, the relative importance of diet breadth and pollen host plant preference in explaining bee population trends remains unclear.Here we solve this problem by analyzing historical pollen preferences of wild bees (15). Bees are generally more selective in their choice of food plants when foraging for pollen (source of protein and minerals for both larvae and adults) than nectar (source of energy) (26, 27). Distributional changes in plant species from which pollen is collected therefore probably exerts a larger influence on bee populations than changes in nectar plants. We investigate whether and to what extent loss of preferred floral resources drives bee population trends in The Netherlands, one of the most human-modified and intensively farmed countries in the world. Over the course of the twentieth century, agriculture has intensified in The Netherlands (Fig. S1) and the area of seminatural habitat preferred by bees has diminished to only one-fifth of the area at the beginning of the twentieth century (Fig. S2). More than half of the bee species are currently on the national Red List (28). As such, this country is a particularly suitable study area to identify critical factors associated with bee population decline.We assessed pollen host plant use of bee species independently from their population trends by analyzing pollen loads on the bodies of bee specimens that were collected before 1950 (15), before the onset of agricultural intensification in The Netherlands. Altogether, our analysis included trend and trait data of 57 bee species in 10 genera and 4 subfamilies (Table S1). We calculated population trend indices for bee species and their host plants (period 1902–1949 vs. 1975–1999) using extensive national species distribution datasets (13, 29). Linear mixed models, with bee subfamily as a random factor to account for phylogeny, and a multimodel inference approach were used to examine the relationship between bee population trends and pollen host plant use, simultaneously taking into account differences in species’ rarity before the onset of agricultural intensification and other factors that have been proposed to explain bee population trends.     

Validation of cephalic index measurements in scaphocephaly

Introduction

The cephalic index (CI) of the head can be measured manually using a caliper, the original technique, but it is also possible to determine it using skull X-ray, 2DCT and 3DCT images, 3D photo and with help of plagiocephalometry (PCM).

Patients and methods

In this study, the manual caliper determination is statistically compared with other measuring methods for scaphocephaly patients (n?=?39).

Results

The CI mean differences for the most representative data are sequentially 3.74, 2.16, 1.09 and 0.97 for the 2DCT, PCM, 3D photo and 3DCT techniques. The CI 2DCT values show a significant difference (p?<?0.01) in reference to CI manually, while the other techniques show a p?>?0.05.

Conclusion

The conclusions are that significantly different results are achieved when using 2DCT relative to the manual caliper determination. No significant difference is observed between the 3D techniques and the manual method.     

Accelerated sequence divergence of conserved genomic elements in Drosophila melanogaster

Recent genomic sequencing of 10 additional Drosophila genomes provides a rich resource for comparative genomics analyses aimed at understanding the similarities and differences between species and between Drosophila and mammals. Using a phylogenetic approach, we identified 64 genomic elements that have been highly conserved over most of the Drosophila tree, but that have experienced a recent burst of evolution along the Drosophila melanogaster lineage. Compared to similarly defined elements in humans, these regions of rapid lineage-specific evolution in Drosophila differ dramatically in location, mechanism of evolution, and functional properties of associated genes. Notably, the majority reside in protein-coding regions and primarily result from rapid adaptive synonymous site evolution. In fact, adaptive evolution appears to be driving substitutions to unpreferred codons. Our analysis also highlights interesting noncoding genomic regions, such as regulatory regions in the gene gooseberry-neuro and a putative novel miRNA.     

Analytical derivation of elasticity in breast phantoms for deformation tracking

Purpose

Patient-specific biomedical modeling of the breast is of interest for medical applications such as image registration, image guided procedures and the alignment for biopsy or surgery purposes. The computation of elastic properties is essential to simulate deformations in a realistic way. This study presents an innovative analytical method to compute the elastic modulus and evaluate the elasticity of a breast using magnetic resonance (MRI) images of breast phantoms.

Methods

An analytical method for elasticity computation was developed and subsequently validated on a series of geometric shapes, and on four physical breast phantoms that are supported by a planar frame. This method can compute the elasticity of a shape directly from a set of MRI scans. For comparison, elasticity values were also computed numerically using two different simulation software packages.

Results

Application of the different methods on the geometric shapes shows that the analytically derived elongation differs from simulated elongation by less than 9% for cylindrical shapes, and up to 18% for other shapes that are also substantially vertically supported by a planar base. For the four physical breast phantoms, the analytically derived elasticity differs from numeric elasticity by 18% on average, which is in accordance with the difference in elongation estimation for the geometric shapes. The analytic method has shown to be multiple orders of magnitude faster than the numerical methods.

Conclusion

It can be concluded that the analytical elasticity computation method has good potential to supplement or replace numerical elasticity simulations in gravity-induced deformations, for shapes that are substantially supported by a planar base perpendicular to the gravitational field. The error is manageable, while the calculation procedure takes less than one second as opposed to multiple minutes with numerical methods. The results will be used in the MRI and Ultrasound Robotic Assisted Biopsy (MURAB) project.

     

Targeted discovery of novel human exons by comparative genomics

A complete and accurate set of human protein-coding gene annotations is perhaps the single most important resource for genomic research after the human-genome sequence itself, yet the major gene catalogs remain incomplete and imperfect. Here we describe a genome-wide effort, carried out as part of the Mammalian Gene Collection (MGC) project, to identify human genes not yet in the gene catalogs. Our approach was to produce gene predictions by algorithms that rely on comparative sequence data but do not require direct cDNA evidence, then to test predicted novel genes by RT-PCR. We have identified 734 novel gene fragments (NGFs) containing 2188 exons with, at most, weak prior cDNA support. These NGFs correspond to an estimated 563 distinct genes, of which >160 are completely absent from the major gene catalogs, while hundreds of others represent significant extensions of known genes. The NGFs appear to be predominantly protein-coding genes rather than noncoding RNAs, unlike novel transcribed sequences identified by technologies such as tiling arrays and CAGE. They tend to be expressed at low levels and in a tissue-specific manner, and they are enriched for roles in motor activity, cell adhesion, connective tissue, and central nervous system development. Our results demonstrate that many important genes and gene fragments have been missed by traditional approaches to gene discovery but can be identified by their evolutionary signatures using comparative sequence data. However, they suggest that hundreds-not thousands-of protein-coding genes are completely missing from the current gene catalogs.     

Cognitive executive impairment and dopaminergic deficits in de novo Parkinson's disease

Cognitive impairment in Parkinson's disease (PD) is common and does directly impact patients' everyday functioning. However, the underlying mechanisms of early cognitive decline are not known. This study explored the association between striatal dopaminergic deficits and cognitive impairment within a large cohort of early, drug‐naïve PD patients and tested the hypothesis that executive dysfunction in PD is associated with striatal dopaminergic depletion. A cross‐sectional multicenter cohort of 339 PD patients and 158 healthy controls from the Parkinson's Progression Markers Initiative study was analyzed. Each individual underwent cerebral single‐photon emission CT (SPECT) and a standardized neuropsychological assessment with tests of memory as well as visuospatial and executive function. SPECT imaging was performed with [¹²³I]FP‐CIT, and specific binding ratios in left and right putamen and caudate nucleus were calculated. The association between specific binding ratios, cognitive domain scores, and age was analyzed using Pearson's correlations, partial correlation, and conditional process analysis. A small, but significant, positive association between total striatal dopamine transporter binding and the attention/executive domain was found (r = 0.141; P = 0.009) in PD, but this was not significant after adjusting for age. However, in a moderated mediation model, we found that cognitive executive differences between controls and patients with PD were mediated by an age‐moderated striatal dopaminergic deficit. Our findings support the hypothesis that nigrostriatal dopaminergic deficit is associated with executive impairment, but not to memory or visuospatial impairment, in early PD. © 2014 International Parkinson and Movement Disorder Society     

Phylogenomics of primates and their ancestral populations

Genome assemblies are now available for nine primate species, and large-scale sequencing projects are underway or approved for six others. An explicitly evolutionary and phylogenetic approach to comparative genomics, called phylogenomics, will be essential in unlocking the valuable information about evolutionary history and genomic function that is contained within these genomes. However, most phylogenomic analyses so far have ignored the effects of variation in ancestral populations on patterns of sequence divergence. These effects can be pronounced in the primates, owing to large ancestral effective population sizes relative to the intervals between speciation events. In particular, local genealogies can vary considerably across loci, which can produce biases and diminished power in many phylogenomic analyses of interest, including phylogeny reconstruction, the identification of functional elements, and the detection of natural selection. At the same time, this variation in genealogies can be exploited to gain insight into the nature of ancestral populations. In this Perspective, I explore this area of intersection between phylogenetics and population genetics, and its implications for primate phylogenomics. I begin by “lifting the hood” on the conventional tree-like representation of the phylogenetic relationships between species, to expose the population-genetic processes that operate along its branches. Next, I briefly review an emerging literature that makes use of the complex relationships among coalescence, recombination, and speciation to produce inferences about evolutionary histories, ancestral populations, and natural selection. Finally, I discuss remaining challenges and future prospects at this nexus of phylogenetics, population genetics, and genomics.The genome sequence of “Susie,” a female Sumatran orangutan from the Gladys Porter Zoo in Brownsville, Texas, will soon be published (Orangutan Genome Sequencing and Analysis Consortium, in prep.), bringing the total number of sequenced primate species to four (human, chimpanzee, rhesus macaque, and orangutan). Preliminary genome assemblies, with various levels of sequencing coverage, are also available for the gorilla, marmoset, bushbaby, mouse lemur, and tarsier genomes, and work is underway to sequence the gibbon and baboon genomes. Moreover, four additional primate species have been approved for sequencing by the National Human Genome Research Institute (NHGRI) (Fig. 1; Open in a separate window^aOnly approved targets are listed. Proposals are pending for several others, including the owl monkey, Chinese rhesus macaque, pigtail macaque, and sooty mangabey. For the latest information, see http://www.genome.gov/10002154.^b(GA) Great Apes; (LA) Lesser Apes (Gibbons); (OWM) Old World Moneys; (NWM) New World Monkeys; (Pro) Prosimians.^cThe goal is a high-quality draft assembly in all cases except human (which is finished) and bonobo (which will be surveyed with fosmid-end sequencing).^d(BI/MIT) Broad Institute of MIT and Harvard University; (WUGSC) Washington University Genome Sequencing Center; (BCM-HGSC) Baylor College of Medicine Human Genome Sequencing Center; (TIGR/JTC) The Institute for Genomic Research/J. Craig Venter Institute; (WTSI) Wellcome Trust Sanger Institute. All projects are NHGRI-funded except Gorilla.^eRefinement in process.^fWith targeted BAC finishing.^gPreliminary draft assembly available.^hLow-coverage (2× Sanger sequencing coverage) assembly complete.Open in a separate windowFigure 1.Phylogeny of primates, showing species for which sequencing is complete, in process, or approved but pending. Three nonprimates—the flying lemur, treeshrew, and mouse—are shown as outgroups. (Cyn. macaque) Cynomolgous macaque, (Rhe. macaque) Rhesus macaque, (Sq. monkey) Squirrel monkey. An approximate time scale, based on estimated dates of divergence from Janecka et al. (2007) (dates >25 Mya), Goodman (1999) (dates 3–25 Mya), Caswell et al. (2008) (chimpanzee/bonobo), and Morales and Melnick (1998) (rhesus/cynomolgous macaque) is shown at the bottom of the figure. Note that the estimated numbers of years before the present reflect DNA sequence divergences and represent upper bounds on speciation times. Nodes are indicated by circles to emphasize that the phylogeny represents both ancestral and extant species, as well as their evolutionary relationships. Note that the prosimians do not form a proper clade but are paraphyletic.Among other things, these new genome sequences will help to identify the genetic basis of differences between primate species, including the genomic features that differentiate humans from other primates (Clark et al. 2003; Pollard et al. 2006b; Prabhakar et al. 2008), to identify and characterize functional sequences present in primates but not other mammals (Boffelli et al. 2003), and to catalog the genomic similarities and differences between humans and nonhuman primates widely used in biomedical research, such as the baboon and rhesus macaque (Rhesus Macaque Genome Sequencing and Analysis Consortium 2007). They will also help to clarify the molecular evolutionary context for human diseases such as AIDS, Alzheimer''s, cancer, and malaria (McConkey and Varki 2000; Rhesus Macaque Genome Sequencing and Analysis Consortium 2007; Degenhardt et al. 2009). In short, these new sequence data will put within reach the grand vision of comprehensive genomic resources for primates that was first articulated nearly a decade ago (McConkey and Varki 2000; Boffelli et al. 2003; Enard and Paabo 2004; Goodman et al. 2005).Perhaps the most informative approach available for comparative genomic analyses of multiple closely related species is to take an evolutionary and phylogenetic perspective—a technique that has been dubbed “phylogenomics” (Eisen and Fraser 2003; Murphy et al. 2004). By explicitly considering the phylogeny by which the species in question are related, phylogenomic methods not only capture the relationships among present-day genomes, but also reveal information about ancestral genomes, and about the lineages on which evolutionary changes have occurred. Moreover, phylogenomics opens up a two-way street between functional and evolutionary analyses, with evolutionary patterns providing information about the potential functions of genomic elements, and functional annotations allowing for richer and more realistic models of evolutionary dynamics. Phylogenomics has been applied widely in many groups of species, including mammals (e.g., Thomas et al. 2003; Rat Genome Sequencing Project Consortium 2004; The ENCODE Project Consortium 2007), yeasts (Cliften et al. 2003; Kellis et al. 2003), drosophilids (Clark et al. 2007; Stark et al. 2007), nematode worms (Stein et al. 2003), and various plants (Yu et al. 2002; Wang et al. 2008). It has already been used extensively within the primates (Boffelli et al. 2003; Rhesus Macaque Genome Sequencing and Analysis Consortium 2007) and is expected to be applied broadly as additional primate genomes become available.Nevertheless, there is an important—and, perhaps, underappreciated—challenge in applying phylogenomic methods to groups of closely related species such as the primates. Most phylogenomic methods inherit from phylogenetics the assumption that there is a single “correct” species phylogeny that holds across the genomes in question, and that present-day genomes have arisen by a stochastic process that operates along the branches of this phylogeny. This modeling approach ignores variation among individuals of the same species, implicitly assuming that it is negligible relative to variation across species. Within the primates, however, this assumption does not hold. Because species divergence times are short relative to ancestral population sizes, population genetic effects become significant, and variation in local genealogies across loci can be considerable. To take one prominent example, it has been estimated that the canonical ((human chimp) gorilla) species phylogeny holds across only about two-thirds of the genome, with the two alternative tree topologies occurring about one-third of the time, due to deep coalescences of ancestral lineages (Patterson et al. 2006; Hobolth et al. 2007; Burgess and Yang 2008). Population genetic effects, of course, are not limited to the primates—they also impact comparative genomics of other groups of interest, such as the drosophilids (e.g., Pollard et al. 2006a)—but my focus here will be on their implications in primate phylogenomics.In this article, I will examine the assumptions that underlie phylogenomic analyses from a population genetic point of view, and discuss their limitations within groups of species, such as the primates, that have experienced short intervals between ancestral speciation events relative to their population sizes. These limitations potentially have important consequences for inferences of rates and patterns of mutation, of positive or negative selection, and of the locations of functional elements. After introducing some basic concepts, I will review several pioneering papers from an emerging literature on “population-aware” phylogenomics, which not only consider interspecies comparisons in a more accurate and realistic way, but also shed light on modes of speciation, ancestral populations, and selective forces within the primates. Finally, I will discuss remaining challenges and future prospects at the intersection of phylogenetics and population genetics.