Kew Internship Flashcards

Question

Explain: (Sandel et al., 2015) detected trait value biases in frequently measured against rarely measured species

Answer 1

"The first hypothesis questions whether a correlation exists between these traits and climatic conditions at the genus, bioregion and species level.

Answer 2

This tree was built using 260 targeted **low-copy nuclear genes **following Soto Gomez et al. (2019). HybPiper (Johnson et al. 2016) was used to assemble and extract the targeted genes, alignments were built and edited with MAFFT (Katoh & Standley 2013) and TRIMAL (Capella-Gutiérrez et al. 2009), respectively. Phylogenetic trees were built using a supermatrix approach in RAxML-NG (Kozlov et al. 2019) using the GTR+G molecular evolution model and 1000 bootstrap replicates. **Divergence times were estimated using treePL** (Smith & O’Meara 2012) by calibrating the stem node of D. sansibarensis at 22.5548 Ma (HPD: 15.5797-29.1444 Ma) following Viruel et al. (2016). Overall, the phylogenetic relationships are very well supported by the bootstrap values. The earliest diverged species appears to be D. sansibarensis. Then the MEYs clade can be divided in four main subclades: the subclade I including 4 species, the subclade II including 9 species, the subclade III including 16 species and the subclade IV including 4 species. D. arcuatinervis occupies a very distinct position in the phylogeny and cannot be attributed to any of those subclades. Finally, an accumulation curve of the number of lineages through time was produced

Answer 3

K-means clustering algorithm was used in conjunction with a dendrogram

Answer 4

A suitable platinum coating needs to be only half the thickness required for gold, resulting in less specimen distortion and giving superior peak-to-background ratio in X-ray analysis.

Answer 5

The Shapiro–Wilk test is essentially a goodness-of-fit test. That is, it examines how close the sample data fit to a normal distribution. It does this by ordering and standardizing the sample (standardizing refers to converting the data to a distribution with mean μ = 0 and standard deviation σ = 1 ).

Answer 6

The trait-specific lambda values were then used in a Phylogenetic Generalised Least Squares (PGLS) analysis to examine the relationships between the traits and climate variables while controlling for phylogenetic signal. PGLS models were fitted using the 'gls' function from the 'nlme' package (Pinheiro, Bates and R Core Team, 2023), with correlation structure specified as Pagel's lambda.

Answer 7

- acknowledge that there might be multiple models that could be used to describe our data - by weighting the average we can communicate how confident we are in each individual model’s view of the world. - model averaging usually reducing prediction errors beyond even above even the best individual component model

Answer 8

The sample size for each species was too small to build complex predictive models at the species level.

Answer 9

indicates the strength of the phylogenetic signal, with 0 signalling no phylogenetic signal and 1 indicating a Brownian Motion model.

Answer 10

Found across Africa and Madagascar atypical. It is often associated with watercourses and is likely to have green shoots and leaves year round in riverine forest (Wilkin, 2023). This may explain why D. sansibarensis shows a different InvPLSD trend to the other species in this region. D. sansibarensis individuals in areas with higher precipitation were found to increase pore length and decrease stomatal density.

Answer 11

Humid species, found exclusively in coastal regions in sub-clade I. Varies all 3 traits in response to climatic variables. Precipitation: Increase SLA and SD, PL decreased. Temp seasonality: increase PL, decrease SLA Temperature: reduce PL, increase SLA

Answer 12

Dry and Subclade III.

Answer 13

Dry and Sub-arid

Answer 14

Humid Region X Datapoints Trends

Answer 15

D. bemarivensis D. namorokensis D. bako D. maciba D. pteropoda D. sansibarensis

Answer 16

Proteiformis Madecassa Seriflora

Answer 17

Heteropoda Hexagona Seriflora

Answer 18

D. bemarivensis D. nako D. hombuka D. maciba D. sansibarensis

Answer 19

Seriflora - sub humid and humid Maciba, bemarivensis and sansibarensis - dry and subarid

Answer 20

Yes and No. Yes No - E.g. dry region. Habitat variety and sub climates

Answer 21

Dioscorea hombuka is unique because it is found in both the Sub-Arid and Sub-Humid regions, suggesting D. hombuka may change its growth rate and habit in response to varying temperature seasonality in different local climatic contexts

Answer 22

The creation of the highlands established empty ecological niches in a milder and more stable climate compared to the other regions which may explain why stomatal density, a more complex developmental trait, is only significantly correlated with climate in this region.

Answer 23

Models are fitted through repeated evaluation of the modified call extracted from the global.model. “Let the computer find out” is a poor strategy and usually reflects the fact that the researcher did not bother to think clearly about the problem of interest and its scientific setting (Burnham and Anderson,2002).

Answer 24

Similar observations in dwarf barley and wheat. Brassinosteroids affecting physiological reactions to drought e.g. antioxidant enzymes ascorbate peroxidase (HvAPX) and superoxide dismutase (HvSOD) was BR-dependent.

Answer 25

the ability of one genotype to adapt to different conditions

Answer 26

We use a simple elipse but not points are distributed equally in the space. Blonder produces smooth boundaries that can fit data either more loosely (Gaussian kernel density estimation) or more tightly (one-classification via support vector machine). Further, the algorithms can accept abundance-weighted data, and the resulting hypervolumes can be given a probabilistic interpretation and projected into geographic space. These new algorithms provide: (i) a more robust approach for delineating the shape and density of n-dimensional hypervolumes; (ii) more efficient performance on large and high-dimensional datasets; (iii) improved measures of functional diversity and environmental niche breadth

Answer 27

30 arc seconds (approximately 1 kilometer) ....

Answer 28

Microclimate - e.g. precipitation and temperature in that sq m in that year

Answer 29

Soil nutrient levels, particularly nitrogen and phosphorus, play a significant role in shaping these traits by enhancing photosynthetic capacity

Answer 30

Light availability introduces complexities associated with trade-offs between light interception and water-use efficiency

Answer 31

impacts microclimates, affecting trait variation

Answer 32

herbivory and interspecies competition, may influence resource allocation and trait plasticity (Gorne and Diaz, 2022)

Answer 33

CO2 variations around year.

Answer 34

Proof of Concept, small sample size - herbarium - traits vary within species, between species and bioregion - species level is most insightful - environment impacts these traits more than phylogeny

Answer 35

Type 1 Risk = low risk Type 2 Risk = high risk reasonability conservative

Answer 36

Independent Variable

Answer 37

conditions, resources, and interactions it needs

Answer 38

Physical Degradation: Loss of Water Content: - This dehydration may influence traits such as specific leaf area (SLA) leading to underestimations Limited Ecological Information: Herbarium specimens often lack detailed ecological information, such as precise location, soil type, and local environmental conditions. Without this information, it may be challenging to contextualize the observed leaf traits in relation to the ecological context. Sampling Bias: Herbarium collections may have been historically biased towards certain regions, habitats, or taxonomic groups. This bias can affect the representativeness of the sampled species and influence the generalizability of the findings. Inconsistencies in Data Recording: Variability in the methods used to collect and preserve herbarium specimens may introduce inconsistencies in the recorded data. These inconsistencies can impact the reliability and comparability of trait measurements across specimens.

Answer 39

Open-ended inquiry or interrogative statement prompting investigation. While not always directly testable, questions guide research and can lead to the formulation of hypotheses. Hypotheses. Specific, testable statement predicting the outcome of an experiment Designed to be tested through experimentation or data collection.

Answer 40

A clade (also known as a monophyletic group) is a group of organisms that includes a single ancestor and all of its descendents. Clades represent unbroken lines of evolutionary descent.

Answer 41

Address issues associated with collinearity, Dominance of a Few Variables: In the presence of highly correlated variables, the PCA may give more weight to those variables and emphasize their contributions disproportionately. This can lead to a situation where a few variables dominate the principal components, potentially obscuring the overall structure of the data. Unstable Component Loadings: Multicollinearity can result in unstable estimates of the component loadings. The loadings indicate the contribution of each variable to each principal component. When variables are highly correlated, small changes in the data can lead to large changes in the loadings, making them less reliable for interpretation. Reduced Interpretability: High multicollinearity can make it challenging to interpret the principal components accurately. Instead of representing distinct patterns in the data, the components may reflect the redundancy of information shared among correlated variables. Inflated Standard Errors: Multicollinearity inflates the standard errors of the estimated coefficients, making it difficult to assess the statistical significance of individual variables or components. This can lead to unreliable hypothesis testing and confidence interval estimates.

Answer 42

Intraindividual in 12

Answer 43

Scale bar refers to a phylogenetic distance of 0.05 nucleotide substitutions per site. Numbers on the branches indicate bootstrap percentage after 1000 replications in constructing the tree.

Answer 44

Variation in size and density of stomata may arise due to genetic factors and/or growth under different environmental conditions. A negative correlation has frequently been suggested between these two stomatal traits. This inverse relationship has been observed in plastic developmental responses to changes in environment and also during long-term evolutionary adaptation

Answer 45

Statistical Power (Power): The probability that a statistical test will correctly reject a false null hypothesis. It is the complement of Type II error (false negative rate) and is often denoted as 1−β, where β is the probability of a Type II error. - Type I Error (False Positive): Incorrectly rejecting a true null hypothesis. The probability of Type I error is denoted as α. - Type II Error (False Negative): Failing to reject a false null hypothesis

Answer 46

Long generation time. 1 year = 1 cotyledon Years till full individual

Answer 47

Lynn - mean estimate of values

Answer 48

A high risk of Type I error means rejecting the null hypothesis when it's actually true. It means concluding that results are statistically significant when, in reality, they came about purely by chance or because of unrelated factors. The risk of committing this error is the significance level (alpha or α) you choose.

Answer 49

A type II error is a statistical term used within the context of hypothesis testing that describes the error that occurs when one fails to reject a null hypothesis that is actually false. A type II error produces a false negative, also known as an error of omission.

Answer 50

probability value. strength of evidence against the null hypothesis, the smaller the p-value the stronger the evidence. The percentage accounts for random noise

Answer 51

Data is normally distributed Distributions have the same variance. Data are independent.

Answer 52

If strategy is to have longer living leaves, we want them to last as long as possible. We want thick tough leaves to protect from damage

Answer 53

Stem traits e.g. Xylem conductance

Answer 54

Few hypothesis: - increasing conductance = better temp regulation (cooling) - reduce nutritional demand (N+P) - reduced evaporative demand. Smaller stomata = more manipulative ability, ability to react to air points.

Answer 55

The independent variable is the cause. Its value is independent of other variables in your study. The dependent variable is the effect. Its value depends on changes in the independent variable. Independent - climate variable Effect - traits

Answer 56

Leaf stomata are well preserved on herbarium specimens and are especially poised for measurement. Standard specimen preparation protocol includes mounting specimens to sheets such that the adaxial side of some leaves and the abaxial side of other leaves are exposed for measurement. Parkhurst (1978) used specimens to assess which species have stomata on one or both sides of leaves, exploring the adaptive significance of this trait across phylogenies and environmental contexts. Similarly, a classic study by Woodward (1987) measured the stomatal density of seven woody species in Europe, reporting strong declines in stomatal numbers as a result of atmospheric CO2 increases, a phenomenon that has since been repeated across many studies. Of special interest are the historical specimens measured for stomatal traits, with findings of inverse correlations with CO2 levels similar to those found by Woodward (1987). These include specimens collected by Lewis and Clark in North America in the early 1800s (described above with leaf chemistry traits; Teece et al. 2002) and by Joseph Banks and David Solander during James Cook’s voyage to the South Pacific in 1769 (Large et al. 2017). The trait has even been used to reconstruct several millennia of CO2 levels from ancient Egypt to today using preserved olive leaves dating to 1327 BCE from King Tutankhamun’s tomb alongside a chronosequence of traditional herbarium specimens (Beerling and Chaloner 1993). More commonly, paleobotanists now routinely rely on both fossils and herbarium specimens, alongside living material, to assess the functional significance of stomatal density and index in reconstructions of paleoenvironments (Hu et al. 2019).

Answer 57

Potential collection biases and inherent data use limitations have long been recognized (Merrill 1916; Anderson and Turrill 1935; Fogg 1940; Fernald 1950), and recent analyses with digitized collections have shown that herbaria are indeed not random samples (Daru et al. 2018). These “biases” are often intentional, with field botanists and ecologists often interested in different types of questions and using different methods of surveying or collecting (Alba et al. 2021). While it is not possible to definitively know the motivation or sampling strategy of each collector, there are well-established approaches to addressing these potential biases (table 2). Many uses of specimens that are now mainstream (e.g., phenology) were undoubtedly met with skepticism that hindered the progress of methodological development before they became an accepted specimen use. Newly realized herbarium specimen uses push these limits, enabling new insight into old specimens.

Answer 58

Unknown microsite conditions of whole plant or plant parts (e.g., unclear whether sun or shade leaves collected): Ensure large sample size Woodson 1947 Use habitat information on labels Hanan-A. et al. 2016 Deliberate species selection (e.g., only open shaded habitat species; include species-level habitat affinities in analysis) Koski et al. 2020

Answer 59

Compare focal species with null control congenerics or ecological analogues Case et al. 2007; Flores-Moreno et al. 2015 Include ancillary data (e.g., historical climate records) in analysis Buswell et al. 2011 Compare responses in home and away ranges (in case of invasion studies) Buswell et al. 2011 Use specimens collected repeatedly from the same individual in botanical gardens Miller-Rushing et al. 2009 Conduct common-garden work with known germplasm accessions to link genotype to phenotype Exposito-Alonso et al. 2018 Extract genetic data from specimens to corroborate evolutionary shift Lamar and Partridge 2020

Answer 60

Limit analysis to only herbarium-derived traits or compare herbarium-derived and non-herbarium-derived trait measurements on proportional change (i.e., measurement precision robust, accuracy may differ) Many studies Experimentally simulate storage or preparation conditions to quantify potential effects Miller et al. 2020 Compare herbarium-derived traits with standard protocols and apply necessary correction factors Onstein et al. 2016; Perez et al. 2020

Answer 61

Robustness of the PC's increases with increasing sample size but not with the number of traits. Borkland 2019

Answer 62

C. Römermann et al. 2016 Looked at same leaf traits in summer green woody species. The results showed that all traits varied significantly throughout the year in a species-specific manner. We concluded that the seasonal timing of trait measurements is crucial. Most notably SLA and stomatal size were the most robust traits in terms of small intraspecific and large interspecific variation and showed largely consistent species rankings across seasons.

Answer 63

Stomatal size (S), as defined by guard cell length (L) and width (W).

Answer 64

Evergreen species may show less variation in SLA throughout the seasons compared to deciduous species. Evergreens can maintain leaves year-round, whereas deciduous species undergo seasonal leaf shedding.

Answer 65

Measures strength and direction of a linear correlation - R = 1: line passes through centre of all points perfectly - R2 = amount of variance shared by two variables - e.g. 93% variable of X is explained by Y, 7% explained by other factors - 2-tailed hypothesis Doesn't matter which variable on which axis

Answer 66

Random-samples Variables are continuous Data contains paired samples Independence of observations Variables are approximately normally distributed A linear associations exists Absence of outliers

Answer 67

Measures strength and direction of monotonic association between two ranked variables - rank variables than perform pearson correlation test - outputs coefficient value (Rs) and p value - null hypothesis = no correlation - p value smaller than 0.05 so reject null hypothesis

Answer 68

1) As one variable increases, the other variable never decreases 2) As one variable increases, the other variable never increases Can be linear

Answer 69

1) Random sample 2) Monotonic Association 3) Both variables are at least ordinal (not nominal) 4) Data contains paired samples 5) Independence of observations Don't need normal data e.g non-parametric

Answer 70

It is a herbaceous, climbing, tropical monocot that looks rather like a dicot, and is part of a lineage that is relatively closely related to the phylogenetically derived group containing the grasses. Therefore, it represents an important biological link between the eudicots and grasses--groups that contain all the model flowering plant species--and has the potential to fill gaps in our knowledge of plant biology and evolution. Yams also offer us the possibility to gain new insights into processes such as tuberization and sex determination, which cannot be studied in current model organisms.

Answer 71

Despite reticulate leaves - embryonic structure - vascular bundles - leaf venation - floral parts Embryonic Structure: - Yams, like other monocots, develop from seeds with a single cotyledon. Vascular Bundle Arrangement: - scattered vascular bundle pattern characteristic of monocots. Floral Parts: Yams conform to the monocot pattern with floral parts in threes. Dicots usually have floral parts in multiples of four or five. Root Development: Yams typically have fibrous root systems, consistent with monocot characteristics. In contrast to dicots often develop a taproot Secondary Growth: Yams, being monocots, generally do not exhibit secondary growth.

Answer 72

Large leaves from herbarium specimens Mature where possible

Answer 73

Dioscorea are randomly orientated and not distributed in cell lines

Answer 74

The Dioscorea genus of yams is a diverse and important group of plants, with many species found in Madagascar. In this study, we investigate the rapid radiation of Malagasy endemic yams and the role of biogeographic history and dispersal evolution in this process. We collected and analyzed molecular data from multiple species of yams, and used phylogenetic and biogeographic methods to reconstruct their evolutionary history. Our results suggest that the rapid radiation of Malagasy yams was driven by a combination of factors, including geological events, climate change, and the evolution of dispersal mechanisms. We also discuss the implications of our findings for the conservation of biodiversity in Madagascar.

Answer 75

identification of areas of likely species occurrence by learning a relationship between knownoccurrences and environmental variables (covariates). The ‘learning’ component of species-environmentrelationships can be accomplished by common machine learning algorithms, such as random forest or MaximumEntropy (MaxEnt). The output of our model is a % estimate of the likelihood of each pixel in ourcalibration area being a presence. This percentage is calculated by counting the number of different decision trees that decided a pixel was either a presence or an absence.

Answer 76

Non-conductive ones like biological samples, insulating polymers, or certain minerals, can build up a charge when exposed to the electron beam in the SEM. This charge can lead to distorted images and affect the quality of the data. Coating the specimen with a thin layer of conductive material, such as gold or platinum, helps dissipate the charge, enabling better imaging. Conductive coatings provide a uniform surface that reflects electrons back into the detector, enhancing the signal and providing sharper images with better contrast. We can achieve this by applying a thin metal coating, localizing the response from the sample, and improving the contrast and the yield of secondary electrons. Coating a sample will also reduce localized heating, reducing beam damage. Charging-induced damage can occur in non-conductive samples due to the accumulation of electrons on the sample surface. Coating helps to prevent this damage by providing a conductive path for charge dissipation. Coatings reduce the charge of the sample, making it easier to analyze. When the sample is coated, the electrons are removed from the top of the sample, and the sample is grounded, meaning that charge accumulates, forming a potential on top of the sample. If the sample is not coated, that charge accumulates, potentially resulting in negative charging, positive charging or even traveling charge. The accumulation of charge is related to microscope operating conditions, and charge effects may vary between microscope models, including edge charging, line by line charging, area charging or residual charging

Answer 77

Bootstrapping statistics is a form of hypothesis testing that involves resampling a single data set to create a multitude of simulated samples. Those samples are used to calculate standard errors, confidence intervals and for hypothesis testing. This approach allows you to generate a more accurate sample from a smaller data set than the traditional method. the proportion of bootstrap replicates (resampled trees) in which a particular branch is supported.

Answer 78

concept in plant ecology that describes a set of correlated leaf traits observed across various plant species. These traits are thought to be indicative of fundamental trade-offs in resource allocation and physiological strategies employed by plants to adapt to their environments. The leaf economic spectrum provides insights into the functional and ecological strategies that plants employ to optimize their growth and survival in different ecological niches. H

Answer 79

- Leaf Longevity: The duration a leaf remains attached to a plant. - Leaf Mass per Area (LMA): The mass of a leaf per unit leaf area, providing information about leaf thickness and structural density. - Photosynthetic Rate (Amax): The maximum rate of photosynthesis, indicating the leaf's capacity for carbon assimilation. - Leaf Nitrogen Content (N): The concentration of nitrogen in the leaf, reflecting the plant's nutrient status and photosynthetic capacity. - Leaf Phosphorus Content (P): The concentration of phosphorus in the leaf, influencing nutrient utilization and growth.

Answer 80

Brownian Motion: - stochastic model where trait evolution is described as a random walk with no specific direction. It assumes that changes in traits accumulate over time due to random processes. - implies continuous and random fluctuations in trait values across the branches of a phylogenetic tree. (null model against which other models are compared) Trend: - introduces a directional component to evolution. It suggests that there is a consistent trend in trait evolution, indicating a gradual shift in trait values over time. Lambda (λ): - Pagel's λ model, is a scaling model that assumes a constant rate of trait evolution across the phylogeny. It introduces a scaling parameter (λ) that represents the degree of phylogenetic signal in the trait. - λ value of 0 indicates no phylogenetic signal (similar to a Brownian Motion model), while a λ value of 1 indicates strong phylogenetic signal, with closely related species having more similar trait values. Ornstein-Uhlenbeck (OU): - stochastic and deterministic components. It assumes that trait evolution is influenced by both random processes and an attraction toward an optimal or equilibrium trait value. - introduces an optimum trait value and a parameter (α) that measures the strength of attraction toward this optimum. Used to model traits that are subject to stabilising selection. Early Burst: - suggests the rate of trait evolution is not constant across the entire phylogeny. Instead, it proposes an early period of rapid evolution, followed by a slowdown in the rate of change.

Kew Internship Flashcards

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