Spatial mechanisms promoting plant coexistence. the role of dispersal and competition

One of the great challenges in ecology is to explain how large numbers of plant species are able to coexist in natural communities. The role of spatial structure for maintaining plant coexistence has so far mainly been explored by theory. Spatial structure involves two main processes: dispersal and competition. Competitive interactions between plants occur over relatively small spatial scales. Spatially limited dispersal together with local interactions can result in individual neighbourhoods much different from mean population densities. Theory suggests that seed dispersal may contribute substantially to population dynamics and plant coexistence. However, additional processes affect the survival and fitness of established individuals, and the consequences of seed dispersal for local community dynamics are still under-explored. Individual-based models examine population dynamics by modelling survival and growth for each individual separately. As a consequence, assumptions have to be made about the distances over which neighbourhood interactions occur and how these attenuate with distance. Theory has shown that a competitively weaker species can invade a population of a superior species if the average distance at which conspecifics compete is longer than the average distance at which heterospecifics compete (heteromyopia). However, empirical knowledge on the spatial scales of competition lags behind, and heteromyopia has not been reported so far. Arbuscular mycorrhizal fungi (AMF) are symbiotic fungi that colonise the roots of most plant species and enhance their hosts' nutrient supply. Increasing evidence for host-specificity and the fact that AMF can connect the roots of many plant species suggest that they might be involved in the spatial scales of competiton. In my thesis I experimentally tested basic model assumptions and theoretical predictions on how dispersal and competition may contribute to maintain plant species coexistence. In a field experiment, I examined the consequences of seed dispersal distance for spatial pattern and local population dynamics of the perennial forb Prunella grandiflora. I found that only individuals in the vegetative but not in the reproductive stage responded to dispersal manipulation. Increasing dispersal distance lead to more vegetative individuals, and decreasing dispersal distance resulted in a more aggregated spatial distribution. In two target-neighbour competition experiments I tested for heteromyopia in co-occurring forbs from calcareous grasslands. I explored the spatial scales of intra- and interspecific competitive interactions, how these attenuate with distance and the role of AMF therein. Although the distances over which intra- and interspecific competition could be detected varied substantially, I found no evidence for hetereomyopia. AMF neither influenced the distances over which competition occurred nor how the strength of competition declined over distance. However, AMF reduced the effects of relative size differences between neighbouring plants. The intensity of competitive interactions was primarily determined by relative size differences between target and neighbour plants, irrespective of their con- or heterospecific status. However, a conspecific neighbour may be more important than a heterospecific neighbour but only as the neighbour becomes very large compared to the target individual (size-identity interaction). Finally, I also tested for within-population host-specificity of genetically different isolates of Glomus intraradices. The different AMF isolates altered plant biomass and differed in their efficiency to colonise plant roots. Interestingly, plant species differed substantially in their susceptibility to different functional differences between these isolates, and this seemed to be positively linked to the percentage root colonisation. The results of my thesis emphasise the importance of both dispersal and competition as spatial mechanisms promoting plant coexistence and point towards novel aspects of AMF in spatial plant ecology. I could confirm theory in that dispersal affects local population dynamics of natural plant communities - at least in the short run. From my target-neighbour experiments, I conclude that resource competition and AMF can be ruled out as potential mechanisms for heteromyopia. My results sugges

Are Invisible Hands Good Hands? Moral Hazard, Competition, and the Second-Best in Health Care Markets

The nature and normative properties of competition in health care markets have long been the subject of much debate. In this paper we consider what the optimal benchmark is in the presence of moral hazard effects on consumption due to health insurance. Intuitively, it seems that imperfect competition in the health care market may constrain this moral hazard by increasing prices. We show that this intuition cannot be correct if insurance markets are competitive. A competitive insurance market will always produce a contract that leaves consumers at least as well off under lower prices as under higher prices

Computational prediction and experimental validation of novel Hedgehog-responsive enhancers linked to genes of the Hedgehog pathway

Abstract Background The Hedgehog (Hh) signaling pathway, acting through three homologous transcription factors (GLI1, GLI2, GLI3) in vertebrates, plays multiple roles in embryonic organ development and adult tissue homeostasis. At the level of the genome, GLI factors bind to specific motifs in enhancers, some of which are hundreds of kilobases removed from the gene promoter. These enhancers integrate the Hh signal in a context-specific manner to control the spatiotemporal pattern of target gene expression. Importantly, a number of genes that encode Hh pathway molecules are themselves targets of Hh signaling, allowing pathway regulation by an intricate balance of feed-back activation and inhibition. However, surprisingly few of the critical enhancer elements that control these pathway target genes have been identified despite the fact that such elements are central determinants of Hh signaling activity. Recently, ChIP studies have been carried out in multiple tissue contexts using mouse models carrying FLAG-tagged GLI proteins (GLIFLAG). Using these datasets, we tested whether a meta-analysis of GLI binding sites, coupled with a machine learning approach, could reveal genomic features that could be used to empirically identify Hh-regulated enhancers linked to loci of the Hh signaling pathway. Results A meta-analysis of four existing GLIFLAG datasets revealed a library of GLI binding motifs that was substantially more restricted than the potential sites predicted by previous in vitro binding studies. A machine learning method (kmer-SVM) was then applied to these datasets and enriched k-mers were identified that, when applied to the mouse genome, predicted as many as 37,000 potential Hh enhancers. For functional analysis, we selected nine regions which were annotated to putative Hh pathway molecules and found that seven exhibited GLI-dependent activity, indicating that they are directly regulated by Hh signaling (78 % success rate). Conclusions The results suggest that Hh enhancer regions share common sequence features. The kmer-SVM machine learning approach identifies those features and can successfully predict functional Hh regulatory regions in genomic DNA surrounding Hh pathway molecules and likely, other Hh targets. Additionally, the library of enriched GLI binding motifs that we have identified may allow improved identification of functional GLI binding sites.http://deepblue.lib.umich.edu/bitstream/2027.42/134520/1/12861_2016_Article_106.pd

Cancer and non-cancer health effects from dietary toxic exposure for children and adults in California

BACKGROUND: In the absence of current cumulative dietary exposure assessments, this analysis was conducted to estimate exposure to multiple dietary contaminants for children, who are more vulnerable to toxic exposure than adults. METHODS: We estimated exposure to multiple food contaminants based on dietary data from preschool-age children (2–4 years, n=207), school-age children (5–7 years, n=157), parents of young children (n=446), and older adults (n=149). We compared exposure estimates for eleven toxic compounds (acrylamide, arsenic, lead, mercury, chlorpyrifos, permethrin, endosulfan, dieldrin, chlordane, DDE, and dioxin) based on self-reported food frequency data by age group. To determine if cancer and non-cancer benchmark levels were exceeded, chemical levels in food were derived from publicly available databases including the Total Diet Study. RESULTS: Cancer benchmark levels were exceeded by all children (100%) for arsenic, dieldrin, DDE, and dioxins. Non-cancer benchmarks were exceeded by >95% of preschool-age children for acrylamide and by 10% of preschool-age children for mercury. Preschool-age children had significantly higher estimated intakes of 6 of 11 compounds compared to school-age children (p<0.0001 to p=0.02). Based on self-reported dietary data, the greatest exposure to pesticides from foods included in this analysis were tomatoes, peaches, apples, peppers, grapes, lettuce, broccoli, strawberries, spinach, dairy, pears, green beans, and celery. CONCLUSIONS: Dietary strategies to reduce exposure to toxic compounds for which cancer and non-cancer benchmarks are exceeded by children vary by compound. These strategies include consuming organically produced dairy and selected fruits and vegetables to reduce pesticide intake, consuming less animal foods (meat, dairy, and fish) to reduce intake of persistent organic pollutants and metals, and consuming lower quantities of chips, cereal, crackers, and other processed carbohydrate foods to reduce acrylamide intake

Increasing atmospheric temperature implicates increasing risk for acute type A dissection in hypertensive patients

Background: Acute type A aortic dissection (AAAD) is a life-threatening condition with high mortality within 24 hours. We hypothesized if there is a correlation between seasonal weather changes and the occurrence of AAAD. The aim of the present study was to identify seasonal specific weather and patient characteristics predicting the occurrence of AAAD. Methods: This is a retrospective analysis of all consecutive patients of our department with AAAD between January 1st 2006 and December 31st 2016. The national meteorological department provided the data of temperature, humidity and air pressure during the study period. The occurrence of AAAD, preoperative neurological impairment and mortality were analyzed in correlation with the obtained daily weather data within the entire cohort and in patients with and without hypertension separately. Results: A total of 517 patients were included. Mean age was 63.4±13 years, 69.4% were male and 68.8% had documented hypertension. In-hospital mortality was 17.7%. In the whole cohort, the occurrence of AAAD was significantly increased in March, October, December (P=0.016). In hypertensive patients, the occurrence was increased 34% with rising temperature (0.1-9.6 °C, OR1.34, 95% CI: 1.06-1.69, P=0.015). There was no correlation between weather variables and preoperative neurological impairment or mortality. Conclusions: Our data suggests a relation between an increasing number of events of AAAD and certain months within our catchment area and a significantly increased occurrence with rising temperatures (independent from absolute temperature at time of the event) in hypertensive patients

Are Invisible Hands Good Hands? Moral Hazard, Competition, and the Second Best in Health Care Markets

The nature, and normative properties, of competition in health care markets has long been the subject of much debate. In particular, policymakers have exhibited a great deal of reservation toward competition in health care markets, as demonstrated by the plethora of regulations governing the health care sector. Currently, as consolidation rapidly occurs in health care markets, concern about reduced competition has arisen. This concern, however, cannot be properly evaluated without a normative standard. In this paper we consider what the optimal benchmark is in the presence of moral hazard effects on consumption due to health insurance. Moral hazard is widely recognized as one of the most important distortions in health care markets. Moral hazard due to health insurance leads to excess consumption, therefore it is not obvious that competition is second best optimal given this distortion. Intuitively, it seems that imperfect competition in the health care market may constrain this moral hazard by increasing prices. We show that this intuition cannot be correct if insurance markets are competitive. A competitive insurance market will always produce a contract that leaves consumers at least as well off under lower prices as under higher prices. Thus, imperfect competition in health care markets can not have efficiency enhancing effects if the only distortion is due to moral hazard.

A bestiary of non-linear functions for growth analysis

Plant growth is an essential ecological process, integrating across scales from physiology to community dynamics. Predicting the growth of plants is essential to understand a wide range of ecological issues, including competition, plant-herbivore interactions and ecosystem functioning.&#xd;&#xa;A challenge in modeling plant growth is that growth rates almost universally decrease with increasing size, for a variety of reasons. Traditional analyses of growth are hampered by the need to remain within the structures of linear models, which handle this slowing poorly. We demonstrate the implementation of a variety of non-linear models that are more appropriate for modeling plant growth than are the traditional, linear, models.&#xd;&#xa;Ecological inference is frequently based on growth rates, rather than model parameters. Traditional calculations of absolute and relative growth rates assume that they are invariant with respect to time or biomass, which is almost never valid. We advocate and demonstrate the calculation of function-derived growth rates, which highlight the time- and biomass-varying nature of growth. We further show how uncertainty in estimated parameter values can be propagated to express uncertainty in absolute and relative growth rates. &#xd;&#xa;The use of non-linear models and function-derived growth rates can facilitate testing novel hypotheses in population and community ecology. Even so, we acknowledge that fitting non-linear models can be tricky. To foster the spread of these methods, we make many recommendations for ecologists to follow when their hypotheses lead them into the subject of plant growth. &#xd;&#xa

Whole-genome sequence-informed MALDI-TOF MS diagnostics reveal importance of Klebsiella oxytoca group in invasive infections: a retrospective clinical study

Background: Klebsiella spp. are opportunistic pathogens which can cause severe infections, are often multi-drug resistant and are a common cause of hospital-acquired infections. Multiple new Klebsiella species have recently been described, yet their clinical impact and antibiotic resistance profiles are largely unknown. We aimed to explore Klebsiella group- and species-specific clinical impact, antimicrobial resistance (AMR) and virulence. Methods: We analysed whole-genome sequence data of a diverse selection of Klebsiella spp. isolates and identified resistance and virulence factors. Using the genomes of 3594 Klebsiella isolates, we predicted the masses of 56 ribosomal subunit proteins and identified species-specific marker masses. We then re-analysed over 22,000 Matrix- Assisted Laser Desorption Ionization - Time Of Flight (MALDI-TOF) mass spectra routinely acquired at eight healthcare institutions in four countries looking for these species-specific markers. Analyses of clinical and microbiological endpoints from a subset of 957 patients with infections from Klebsiella species were performed using generalized linear mixed-effects models. Results: Our comparative genomic analysis shows group- and species-specific trends in accessory genome composition. With the identified species-specific marker masses, eight Klebsiella species can be distinguished using MALDI-TOF MS. We identified K. pneumoniae (71.2%; n = 12,523), K. quasipneumoniae (3.3%; n = 575), K. variicola (9.8%; n = 1717), “K. quasivariicola” (0.3%; n = 52), K. oxytoca (8.2%; n = 1445), K. michiganensis (4.8%; n = 836), K. grimontii (2.4%; n = 425) and K. huaxensis (0.1%; n = 12). Isolates belonging to the K. oxytoca group, which includes the species K. oxytoca, K. michiganensis and K. grimontii, were less often resistant to 4th-generation cephalosporins than isolates of the K. pneumoniae group, which includes the species K. pneumoniae, K. quasipneumoniae, K. variicola and “K. quasivariicola” (odds ratio = 0.17, p \u3c 0.001, 95% confidence interval [0.09,0.28]). Within the K. pneumoniae group, isolates identified as K. pneumoniae were more often resistant to 4th-generation cephalosporins than K. variicola isolates (odds ratio = 2.61, p = 0.003, 95% confidence interval [1.38,5.06]). K. oxytoca group isolates were found to be more likely associated with invasive infection to primary sterile sites than K. pneumoniae group isolates (odds ratio = 2.39, p = 0.0044, 95% confidence interval [1.05,5.53]). Conclusions: Currently misdiagnosed Klebsiella spp. can be distinguished using a ribosomal marker-based approach for MALDI-TOF MS. Klebsiella groups and species differed in AMR profiles, and in their association with invasive infection, highlighting the importance for species identification to enable effective treatment options