Development and application of quantitative methods for ecosystem services

Ecosystem services are benefits that people receive from the environment. Despite recent exponential increases in ecosystem service research, the ecosystem service framework has made little impact on policy and land management decisions, especially in the United States. Two of the main limitations for a lack of ecosystem service considerations in both policy and land management decisions are a need for more advanced quantification methods and the lack of engagement of key stakeholders who are responsible for making land management decisions. This research seeks to address these two limitations by testing and improving quantification methods of ecosystem services and by evaluating agricultural managers\u27 understanding and perceptions of ecosystem services. The main objectives of this research were to (1) test an existing ecosystem service evaluation method in the Upper Mississippi River Basin under current conditions and future climate change, (2) improve understanding of influences of aquatic genetic resource provisioning using the SWAT model, (3) improve quantification methods for climate regulation ecosystem services using the DayCent model; and (4) evaluate Indiana agricultural producers\u27 and conservationists\u27 perceptions of ecosystem services in order to identify the best ways to improve inclusion of the ecosystem service considerations in making agricultural management decisions. For the first objective, previously developed quantification methods for freshwater provision, food provision, erosion regulation, and flood regulation were applied to a large 2-digit HUC watershed in the U.S. (the Upper Mississippi River Basin). The results show that these methods were able to capture tradeoffs between existing ecosystem services, specifically freshwater provision and food provision, in this watershed. Climate change and variability may have considerable impact on ecosystem services in this river basin. For the second objective of this research a Soil and Water Assessment Tool (SWAT) model was developed to evaluate the possible drivers of an observed change in fish regime the Wabash River that occurred around the 1990\u27s. The results indicated that changing agricultural practices combined with increasing precipitation may have influenced the observed fish regime change. This link between agricultural management decisions and an historical fish regime change in the Wabash River can improve understanding of the link between management decisions and aquatic genetic resource provisioning. The third objective of this research applied a multi-objective genetic algorithm optimization tool (AMALGAM) to improve the performance of the DayCent model and then proposed a quantification method for climate regulation using DayCent. Although the DayCent calibration method was able to improve the performance of the model at the calibration plots for both yield and N2O flux, the N2O flux simulation of the validation plots were not improved due to the influence of two plots with high N2O emissions. This work suggests that although a multi-objective function can be used to calibrate DayCent, the method may work best within a treatment, even if the plots are all at the same location. The climate regulation index that was developed under Objective 3 was able to capture the ability of a local, terrestrial ecosystem to regulate climate. For the last objective, surveys were conducted of Indiana farmers and conservationists, and interviews were held with Indiana farmers. The results indicated that Indiana farmers and conservationists understand ecosystem services, even if they do not use the terminology. It also shows that the existing conservation framework can be utilized to implement ecosystem service based management. By understanding the perceptions of these key stakeholders, the ecosystem service framework can be better implemented in developing management and policy strategies

Dynamics of Trophoblast Differentiation in Peri-Implantation–Stage Human Embryos

Single-cell RNA sequencing of cells from cultured human blastocysts has enabled us to define the transcriptomic landscape of placental trophoblast (TB) that surrounds the epiblast and associated embryonic tissues during the enigmatic day 8 (D8) to D12 peri-implantation period before the villous placenta forms. We analyzed the transcriptomes of 3 early placental cell types, cytoTB (CTB), syncytioTB (STB), and migratoryTB (MTB), picked manually from cultured embryos dissociated with trypsin and were able to follow sublineages that emerged from proliferating CTB at the periphery of the conceptus. A unique form of CTB with some features of STB was detectable at D8, while mature STB was at its zenith at D10. A form of MTB with a mixed MTB/CTB phenotype arose around D10. By D12, STB generation was in decline, CTB had entered a new phase of proliferation, and mature MTB cells had begun to move from the main body of the conceptus. Notably, the MTB transcriptome at D12 indicated enrichment of transcripts associated with IFN signaling, migration, and invasion and upregulation of HLA-C, HLA-E, and HLA-G. The STB, which is distinct from the STB of later villous STB, had a phenotype consistent with intense protein export and placental hormone production, as well as migration and invasion. The studies show that TB associated with human embryos is in rapid developmental flux during periimplantation period when it must invade, signal robustly to the mother to ensure that the pregnancy continues, and make first contact with the maternal immune system

Public perceptions about risk and protective factors for cognitive health and impairment: a review of the literature

ABSTRACT Background: Preventing and/or delaying cognitive impairment is a public health priority. To increase awareness of and participation in behaviors that may help maintain cognitive function or reduce risk of impairment, we need to understand public perceptions about risk and protective factors. Methods: We conducted a scoping review of studies examining the public's perceptions about risk and protective factors related to cognitive health and impairment published since the 2007 National Public Health Road Map to Maintaining Cognitive Health . Results: A search of five databases yielded 1,115 documents published between June 2007 and December 2013. Initial review of abstracts identified 90 potentially eligible studies. After full-article review, 30 met inclusion criteria; four additional articles identified in reference lists also met inclusion criteria. Of the 34, 16 studies addressed Alzheimer's disease (AD) specifically, 15 dementia broadly, 5 mild to moderate cognitive impairment, and 8 normal functioning, with some content overlap. Across studies, respondents reported genetics ( n = 14 studies), older age ( n = 8), stress ( n = 7), brain/head injury ( n = 6), and mental illness/brain disease ( n = 6) as perceived risk factors for AD and dementia. Protective factors most commonly identified for maintaining cognitive health were intellectual/mental stimulation ( n = 13), physical activity ( n = 12), healthy diet ( n = 10), and social/leisure activities ( n = 10). Conclusions: Studies identified genetics and older age as key perceived risk factors more so than behaviors such as smoking. Individuals perceived that numerous lifestyle factors (e.g. intellectual stimulation, physical activity) could protect against cognitive impairment, AD, and/or dementia. Results can inform national and international education efforts about AD and other dementias

Evaluating the effectiveness and cost-effectiveness of Dementia Care Mapping™ to enable person-centred care for people with dementia and their carers (DCM-EPIC) in care homes: study protocol for a randomised controlled trial

Background Up to 90 % of people living with dementia in care homes experience one or more behaviours that staff may describe as challenging to support (BSC). Of these agitation is the most common and difficult to manage. The presence of agitation is associated with fewer visits from relatives, poorer quality of life and social isolation. It is recommended that agitation is treated through psychosocial interventions. Dementia Care Mapping™ (DCM™) is an established, widely used observational tool and practice development cycle, for ensuring a systematic approach to providing person-centred care. There is a body of practice-based literature and experience to suggests that DCM™ is potentially effective but limited robust evidence for its effectiveness, and no examination of its cost-effectiveness, as a UK health care intervention. Therefore, a definitive randomised controlled trial (RCT) of DCM™ in the UK is urgently needed. Methods/design A pragmatic, multi-centre, cluster-randomised controlled trial of Dementia Care Mapping (DCM™) plus Usual Care (UC) versus UC alone, where UC is the normal care delivered within the care home following a minimum level of dementia awareness training. The trial will take place in residential, nursing and dementia-specialist care homes across West Yorkshire, Oxfordshire and London, with residents with dementia. A random sample of 50 care homes will be selected within which a minimum of 750 residents will be registered. Care homes will be randomised in an allocation ratio of 3:2 to receive either intervention or control. Outcome measures will be obtained at 6 and 16 months following randomisation. The primary outcome is agitation as measured by the Cohen-Mansfield Agitation Inventory, at 16 months post randomisation. Key secondary outcomes are other BSC and quality of life. There will be an integral cost-effectiveness analysis and a process evaluation. Discussion The protocol was refined following a pilot of trial procedures. Changes include replacement of a questionnaire, whose wording caused some residents distress, to an adapted version specifically designed for use in care homes, a change to the randomisation stratification factors, adaption in how the staff measures are collected to encourage greater compliance, and additional reminders to intervention homes of when mapping cycles are due, via text message. Trial registration Current Controlled Trials ISRCTN82288852. Registered on 16 January 2014. Full protocol version and date: v7.1: 18 December 2015

Imputation of Exome Sequence Variants into Population- Based Samples and Blood-Cell-Trait-Associated Loci in African Americans: NHLBI GO Exome Sequencing Project

Researchers have successfully applied exome sequencing to discover causal variants in selected individuals with familial, highly penetrant disorders. We demonstrate the utility of exome sequencing followed by imputation for discovering low-frequency variants associated with complex quantitative traits. We performed exome sequencing in a reference panel of 761 African Americans and then imputed newly discovered variants into a larger sample of more than 13,000 African Americans for association testing with the blood cell traits hemoglobin, hematocrit, white blood count, and platelet count. First, we illustrate the feasibility of our approach by demonstrating genome-wide-significant associations for variants that are not covered by conventional genotyping arrays; for example, one such association is that between higher platelet count and an MPL c.117G>T (p.Lys39Asn) variant encoding a p.Lys39Asn amino acid substitution of the thrombpoietin receptor gene (p = 1.5 × 10−11). Second, we identified an association between missense variants of LCT and higher white blood count (p = 4 × 10−13). Third, we identified low-frequency coding variants that might account for allelic heterogeneity at several known blood cell-associated loci: MPL c.754T>C (p.Tyr252His) was associated with higher platelet count; CD36 c.975T>G (p.Tyr325∗) was associated with lower platelet count; and several missense variants at the α-globin gene locus were associated with lower hemoglobin. By identifying low-frequency missense variants associated with blood cell traits not previously reported by genome-wide association studies, we establish that exome sequencing followed by imputation is a powerful approach to dissecting complex, genetically heterogeneous traits in large population-based studies

Haze in Pluto's atmosphere: Results from SOFIA and ground-based observations of the 2015 June 29 Pluto occultation

On UT 29 June 2015, the occultation by Pluto of a bright star (r′ = 11.9) was observed from the Stratospheric Observatory for Infrared Astronomy (SOFIA) and several ground-based stations in New Zealand and Australia. Pre-event astrometry allowed for an in-flight update to the SOFIA team with the result that SOFIA was deep within the central flash zone (~22 km from center). Analysis of the combined data leads to the result that Pluto's middle atmosphere is essentially unchanged from 2011 and 2013 (Person et al. 2013; Bosh et al. 2015); there has been no significant expansion or contraction of the atmosphere. Additionally, our multi-wavelength observations allow us to conclude that a haze component in the atmosphere is required to reproduce the light curves obtained. This haze scenario has implications for understanding the photochemistry of Pluto's atmosphere

A Variational Bayes Discrete Mixture Test for Rare Variant Association

Recently, many statistical methods have been proposed to test for associations between rare genetic variants and complex traits. Most of these methods test for association by aggregating genetic variations within a predefined region, such as a gene. Although there is evidence that “aggregate” tests are more powerful than the single marker test, these tests generally ignore neutral variants and therefore are unable to identify specific variants driving the association with phenotype. We propose a novel aggregate rare-variant test that explicitly models a fraction of variants as neutral, tests associations at the gene-level, and infers the rare-variants driving the association. Simulations show that in the practical scenario where there are many variants within a given region of the genome with only a fraction causal our approach has greater power compared to other popular tests such as the Sequence Kernel Association Test (SKAT), the Weighted Sum Statistic (WSS), and the collapsing method of Morris and Zeggini (MZ). Our algorithm leverages a fast variational Bayes approximate inference methodology to scale to exome-wide analyses, a significant computational advantage over exact inference model selection methodologies. To demonstrate the efficacy of our methodology we test for associations between von Willebrand Factor (VWF) levels and VWF missense rare-variants imputed from the National Heart, Lung, and Blood Institute’s Exome Sequencing project into 2,487 African Americans within the VWF gene. Our method suggests that a relatively small fraction (~10%) of the imputed rare missense variants within VWF are strongly associated with lower VWF levels in African Americans

Development of a quantification method for ecosystem services

Ecosystem services are benefits that people receive from their environment. The ecosystem service concept takes a holistic approach to viewing how humans interact and depend on their environment. Although the concept has been gaining in popularity, it has yet to play a major role in any water management policy. We propose that one reason for this lack of adoption is that the current method for quantifying ecosystem services are inadequate and have many limitations. The purpose of this project was to create quantitative methods for evaluating watershed scale ecosystem services. Outputs from the Soil and Water Assessment Tool (SWAT) were used to develop quantitative methods to evaluate six ecosystem services: Fresh Water Provision, Food Provision, Fuel Provision, Genetic Resource Provision, Erosion Regulation and Flood Regulation. These six ecosystem services were evaluated in Wildcat Creek Watershed in Central Indiana. Results show that over the study period (1995-2009), all ecosystem services except Food and Fuel Provisioning have been diminished