225 research outputs found
Teaching Critical Thinking in Statistics for Natural Resource Education
Graduate education in natural resource fields requires high level critical thinking in specialized areas of interest to the student. This challenge is typically embraced by graduate students who are excited to be learning in the areas of their choice. Most graduate programs in natural resources require students to take a course in statistics or data analysis and natural resources research relies heavily on these tools. But many students have limited experience with quantitative science and that experience may not have been recent. This poses a challenge when teaching courses in statistics. In this presentation I will outline the challenges to teaching and the barriers to learning that can be present for some students in natural resources. I will suggest some approaches to teaching statistics that have been successful in the classroom and outline how different kinds of learning activities can be used together to improve student learning of statistics
Spatial Patterns in Forest Understories: Relationships to Overstory Thinning Intensity and Understory Plant Diversity
Amount, spatial distribution, and species composition of understory plant communities have been shown to respond to changes in overstory structure. While response of the amount and composition of understory vegetation to thinning has been investigated in several ecosystems, spatial distributions have received less attention. We investigated spatial statistical techniques to examine associations of patch size of clonal shrubs and annual ruderals as they relate to overstory conditions after thinnings. We assessed the interpretation of empirical semivariograms in describing spatial pattern and whether semivariogram parameters can be useful when comparing impacts of different thinning regimes. We simulated vegetation patterns to test the ability of empirical semivariograms to describe patch sizes and suggest a nonparametric semivariogram range parameter as a metric of patch size. We applied results from the simulations to data from a long-term thinning study, in which intensity and spatial patterns of thinnings varied. We used range parameters from semivariograms of percent cover to compare response of patch sizes among thinning treatments and life forms. Initial results indicated that empirical semivariograms quantified both patch sizes and distance between patches. Nonparametric semivariogram estimates of patch size showed differences among thinning treatments, suggesting that spatial patterns of overstory conditions are influencing spatial distributions of understory vegetation. Patches of selected clonal shrubs were smallest in the treatment with spatially variable thinnings. Overall patch size of clonal shrubs was less strongly associated with thinning treatments than patch size of annual ruderals, likely reflecting differences in mobility between species that mainly regenerate by sprouting versus seeds. We conclude that spatial pattern of understory vegetation is responsive to thinning treatments and empirical semivariograms can provide useful information for developing silvicultural prescriptions
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Diagnostic tools for overdispersion in generalized linear models
Data in the form of counts or proportions often exhibit more
variability than that predicted by a Poisson or binomial
distribution. Many different models have been proposed to account
for extra-Poisson or extra-binomial variation. A simple model
includes a single heterogeneity factor (dispersion parameter) in the
variance. Other models that allow the dispersion parameter to vary
between groups or according to a continuous covariate also exist but
require a more complicated analysis. This thesis is concerned with
(1) understanding the consequences of using an oversimplified model
for overdispersion, (2) presenting diagnostic tools for detecting the
dependence of overdispersion on covariates in regression settings for
counts and proportions and (3) presenting diagnostic tools for
distinguishing between some commonly used models for overdispersed
data.
The double exponential family of distributions is used as a
foundation for this work. A double binomial or double Poisson
density is constructed from a binomial or Poisson density and an
additional dispersion parameter. This provides a completely
parametric framework for modeling overdispersed counts and
proportions.
The first issue above is addressed by exploring the properties
of maximum likelihood estimates obtained from incorrectly specified
likelihoods. The diagnostic tools are based on a score test in the
double exponential family. An attractive feature of this test is
that it can be computed from the components of the deviance in the
standard generalized linear model fit. A graphical display is
suggested by the score test. For the normal linear model, which is a
special case of the double exponential family, the diagnostics reduce
to those for heteroscedasticity presented by Cook and Weisberg
(1983)
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Multi-scale spatial controls of understory vegetation in Douglas-fir–western hemlock forests of western Oregon, USA
Forest understory vegetation is influenced by broad-scale variation in climate, intermediate-scale variation in topography, disturbance and neighborhood interactions. However, little is known about how these multi-scale controls interact to influence observed spatial patterns. We examined relationships between the aggregated cover of understory plant species (%C[subscript U]) and multi-scale controls using a large-scale experiment including treatments of low (LS), moderate (MS) and variable (VS) disturbance severity replicated in second-growth Douglas-fir (Pseudotsuga meziesii)–western hemlock (Tsuga heterophylla) forests spanning climate and topographic gradients. We developed hierarchical models using a multi-step selection process, assessing changes residual spatial autocorrelation associated with progressively broader spatial scales of influence and interaction. To examine the role of plant traits in mediating multi-scale controls, we contrasted effects for early- (%C[subscript ES]) and late-seral (%C[subscript LS]) species cover. At neighborhood scales, decreases in %C[subscript U] with overstory density were accelerated with increases in the relative importance of hemlock in the overstory in the in all but the LS treatment. At intermediate scales, %C[subscript U] was lower in areas with higher potential radiation in undisturbed control treatments but that trend was reversed in the harvested, disturbed areas. When separated, effects of multi-scale controls differed between %C[subscript ES] and %C[subscript LS]. Rates of increases in %C[subscript ES] with reductions in density increased with disturbance severity and decreased with increases in %C[subscript LS]. At broader scales, %C[subscript ES] increased with climatic moisture deficit where potential radiation was high, and %C[subscript LS] low. Similarly to %C[subscript U], %C[subscript LS] was related to a three-way interaction between overstory density, disturbance and hemlock abundance. %C[subscript LS] declined with increases in climatic moisture deficit where overstory density and the relative abundance of hemlock was high, and decreased with local increases in %C[subscript ES]. Multi-scale controls explained a portion of the observed spatial autocorrelation for %C[subscript ES] but not %C[subscript LS], suggesting the spatial patterning of %C[subscript LS] is related primarily to unmeasured processes. Results show how understory responses to overstory density and disturbance severity vary across the landscape with moisture and potential radiation, at fine scales with neighborhood structure, and with species traits. Hence, understory responses to climate change likely depend on overstory composition and structure, disturbance and species traits
The betaine content of sweat from adolescent females
<p>Abstract</p> <p>Background</p> <p>This study was developed to establish whether betaine was present in the sweat of females and to determine any correlations with other sweat components.</p> <p>Methods</p> <p>Sweat patches were placed on eight trained adolescent Highland dancers (age = 13.6 ± 2.3 yr), who then participated in a dance class for 2 hours. Patches were removed, and the sweat recovered via centrifugation. The sweat was subsequently analyzed for betaine, choline, sodium, potassium, chloride, lactate, glucose, urea and ammonia.</p> <p>Results</p> <p>Betaine was present in the sweat of all subjects (232 ± 84 μmol·L<sup>-1</sup>), which is higher than typically found in plasma. The concentration of several sweat components were correlated, in particular betaine with most other measured components.</p> <p>Conclusion</p> <p>Betaine, an osmoprotectant and methyl donor, is a component of sweat that may be lost from the body in significant amounts.</p
A Trap-Door Mechanism for Zinc Acquisition by Streptococcus pneumoniae AdcA.
Zinc is an essential element in all domains of life. Nonetheless, how prokaryotes achieve selective acquisition of zinc from the extracellular environment remains poorly understood. Here, we elucidate a novel mechanism for zinc-binding in AdcA, a solute-binding protein of Streptococcus pneumoniae. Crystal structure analyses reveal the two-domain organization of the protein and show that only the N-terminal domain (AdcAN) is necessary for zinc import. Zinc binding induces only minor changes in the global protein conformation of AdcA and stabilizes a highly mobile loop within the AdcAN domain. This loop region, which is conserved in zinc-specific solute-binding proteins, facilitates closure of the AdcAN binding site and is crucial for zinc acquisition. Collectively, these findings elucidate the structural and functional basis of selective zinc uptake in prokaryotes.
IMPORTANCE Zinc is an essential nutrient for the virulence of bacterial pathogens such as Streptococcus pneumoniae. Many Gram-positive bacteria use a two-domain lipoprotein for zinc acquisition, but how this class of metal-recruiting proteins acquire zinc and interact with the uptake machinery has remained poorly defined. We report the first structure of a two-domain lipoprotein, AdcA from S. pneumoniae, and use computational, spectroscopic, and microbiological approaches to provide new insights into the functional basis of zinc recruitment. Our findings reveal that AdcA employs a novel mechanism for zinc binding that we have termed the “trap-door” mechanism, and we show how the static metal-binding site of the protein, which confers its selectivity for zinc ions, is combined with a dynamic surface element to facilitate zinc recruitment and import into the bacterium. Together, these findings expand our understanding of how bacteria acquire zinc from the environment and provide a foundation for inhibiting this process, through antimicrobial targeting of the dynamic structural elements to block bacterial zinc scavenging
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Multiomics modeling of the immunome, transcriptome, microbiome, proteome and metabolome adaptations during human pregnancy.
MotivationMultiple biological clocks govern a healthy pregnancy. These biological mechanisms produce immunologic, metabolomic, proteomic, genomic and microbiomic adaptations during the course of pregnancy. Modeling the chronology of these adaptations during full-term pregnancy provides the frameworks for future studies examining deviations implicated in pregnancy-related pathologies including preterm birth and preeclampsia.ResultsWe performed a multiomics analysis of 51 samples from 17 pregnant women, delivering at term. The datasets included measurements from the immunome, transcriptome, microbiome, proteome and metabolome of samples obtained simultaneously from the same patients. Multivariate predictive modeling using the Elastic Net (EN) algorithm was used to measure the ability of each dataset to predict gestational age. Using stacked generalization, these datasets were combined into a single model. This model not only significantly increased predictive power by combining all datasets, but also revealed novel interactions between different biological modalities. Future work includes expansion of the cohort to preterm-enriched populations and in vivo analysis of immune-modulating interventions based on the mechanisms identified.Availability and implementationDatasets and scripts for reproduction of results are available through: https://nalab.stanford.edu/multiomics-pregnancy/.Supplementary informationSupplementary data are available at Bioinformatics online
The betaine content of sweat from adolescent females
Abstract Background This study was developed to establish whether betaine was present in the sweat of females and to determine any correlations with other sweat components. Methods Sweat patches were placed on eight trained adolescent Highland dancers (age = 13.6 ± 2.3 yr), who then participated in a dance class for 2 hours. Patches were removed, and the sweat recovered via centrifugation. The sweat was subsequently analyzed for betaine, choline, sodium, potassium, chloride, lactate, glucose, urea and ammonia. Results Betaine was present in the sweat of all subjects (232 ± 84 μmol·L-1), which is higher than typically found in plasma. The concentration of several sweat components were correlated, in particular betaine with most other measured components. Conclusion Betaine, an osmoprotectant and methyl donor, is a component of sweat that may be lost from the body in significant amounts
Systemic Immunologic Consequences of Chronic Periodontitis
Chronic periodontitis (ChP) is a prevalent inflammatory disease affecting 46% of the US population. ChP produces a profound local inflammatory response to dysbiotic oral microbiota that leads to destruction of alveolar bone and tooth loss. ChP is also associated with systemic illnesses, including cardiovascular diseases, malignancies, and adverse pregnancy outcomes. However, the mechanisms underlying these adverse health outcomes are poorly understood. In this prospective cohort study, we used a highly multiplex mass cytometry immunoassay to perform an in-depth analysis of the systemic consequences of ChP in patients before (n = 28) and after (n = 16) periodontal treatment. A high-dimensional analysis of intracellular signaling networks revealed immune system–wide dysfunctions differentiating patients with ChP from healthy controls. Notably, we observed exaggerated proinflammatory responses to Porphyromonas gingivalis–derived lipopolysaccharide in circulating neutrophils and monocytes from patients with ChP. Simultaneously, natural killer cell responses to inflammatory cytokines were attenuated. Importantly, the immune alterations associated with ChP were no longer detectable 3 wk after periodontal treatment. Our findings demarcate systemic and cell-specific immune dysfunctions in patients with ChP, which can be temporarily reversed by the local treatment of ChP. Future studies in larger cohorts are needed to test the boundaries of generalizability of our results
Expression of specific inflammasome gene modules stratifies older individuals into two extreme clinical and immunological states
Low-grade, chronic inflammation has been associated with many diseases of aging, but the mechanisms responsible for producing this inflammation remain unclear. Inflammasomes can drive chronic inflammation in the context of an infectious disease or cellular stress, and they trigger the maturation of interleukin-1β (IL-1β). Here we find that the expression of specific inflammasome gene modules stratifies older individuals into two extremes: those with constitutive expression of IL-1β, nucleotide metabolism dysfunction, elevated oxidative stress, high rates of hypertension and arterial stiffness; and those without constitutive expression of IL-1β, who lack these characteristics. Adenine and N4-acetylcytidine, nucleotide-derived metabolites that are detectable in the blood of the former group, prime and activate the NLRC4 inflammasome, induce the production of IL-1β, activate platelets and neutrophils and elevate blood pressure in mice. In individuals over 85 years of age, the elevated expression of inflammasome gene modules was associated with all-cause mortality. Thus, targeting inflammasome components may ameliorate chronic inflammation and various other age-associated conditions
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