1,136 Matching Annotations
  1. Sep 2018
    1. Given that the foot length in H. sapiens is generally about 14% to 16% of stature (Tuttle [1987], and references therein), we computed two estimates for the Laetoli hominins assuming that their feet were, respectively, 14% and 16% of their body height (Tables 2–3). This method, however, is not fully reliable because it is based on the body proportions of modern humans, and because it does not take into account that the footprint length does not accurately reflect the foot length.

      The authors used two different methods to estimate the stature of the hominin trackmakers. One used modern Homo sapiens body proportions. This was considered to be less accurate since the body proportions of the hominids were likely different from those of modern humans.

    2. The following morphometric measures were taken on the contour maps: footprint length – maximum distance between the anterior tip of the hallux and the posterior tip of the heel; footprint max width – width across the distal metatarsal region; footprint heel width; angle of gait – angle between the midline of the trackway and the longitudinal axis of the foot; step length – distance between the posterior tip of the heel in two successive tracks; stride length – distance between the posterior tip of the heel in two successive tracks on the same side.

      The authors gathered the following data on tracks from both G and S.

    3. Data acquisition and processing (Supplementary file 4) were performed following the workflow described above for the Site S test-pits. We positioned four perimeter control points and 11 inner targets. The latter were used to model in detail six selected tracks (G2/G3–29, G1–35, G1–34, G2/3–26, G2/3–25 and G2/3–18, listed in the direction of walking)

      The authors used the same data gathering and visualization techniques on the fiberglass casts as they had used on the tracks at S.

    4. Data processing started by checking measurements in plan and height. This step is preliminary to the definition of the control point coordinates

      The authors checked their measurements and used STAR*NET software to combine their conventional observations with GPS vectors. They used the leveling observations the software provided to make 3D adjustments in the footprint images.

    5. The photographic survey was carried out by three shooting modes:

      Each test-pit was surveyed and photographed in order to determine its relationship to the other test-pits and to Site G.

    6. n the second step, the perimeter target positions were measured. We placed two rods equipped with a spherical level on successive pairs of targets and we marked points at the same height on the rods for each pair by using the water level device

      The authors carefully measured distances between targets so that the location and depth of each of the modeled footprints could be precisely determined.

    7. Each test-pit was entirely surveyed at lower resolution and then detailed 3D models of some inner portions (single prints or groups of close prints) were acquired (Figures 4–6).

      The authors made 3D models of selected footprints and sets of footprints. Models of some of the footprints were not made due to their poor state of preservation.

    1. we used 20k random projections for the fly to equate the number of mathematical operations used by the fly and LSH

      As stated earlier in the article, the authors could only fairly compare the LSH and fly algorithms if each used the same number of mathematical operations.

      They determined that if they used 20k random projections in the fly algorithm (where k is the length of the output tag, or hash) then the total number of operations for the fly and LSH algorithms would be equal.

      For more detail, see the second paragraph under "Materials and Methods" in the Supplementary Materials document.

    2. we selected 1000 random query inputs from the 10,000 and compared true versus predicted nearest neighbors

      From the 10,000 vectors, the authors randomly chose 1,000 of them to be query inputs (images or words that they would test against the rest of the feature vectors to find which ones represent similar images or words).

    3. We used a subset of each data set with 10,000 inputs each, in which each input was represented as a feature vector in d-dimensional space

      They chose 10,000 vectors of length d from each data set. Each vector represented an image (SIFT, MNIST), or word (GLOVE).

    4. computed the overlap between the ranked lists of true and predicted nearest neighbors

      This is a method of measuring how well an algorithm performed. The more overlap between the two lists, the more similar they are. If they are exactly the same, this means that the algorithm performed perfectly.

      For example, it might mean that it found the closest match to all query images, or that it correctly found all the correct features that match part of an image (see picture below).

    5. determined on the basis of Euclidean distance between feature vectors

      Each feature vector contains a row of values representing features of an image or word (depending on the data set). Because the data is arranged so that similar features are near each other, measuring the straight-line (Euclidean) distance between two vectors allows the authors to determine the similarity between them.

      That is, the closer the vectors, the more similar their features. The vectors closest to one another are the "true nearest neighbors," or the images/words in the data set most similar to one another.

    1. We explored a low, moderate, and high scenario for atmospheric CO2 concentration (550, 850, and 950 ppm, respectively: EPA and IPCC 2007) and each climate driver: mean annual air temperature (+1, +2.5, and +4.2°C; IPCC 2013) and precipitation (−2, +7, and +14%; IPCC 2013) (Fig. 4).

      Here, the authors explains how they ran different scenarios in the simulation system with the data they had collected in the field, making for more realistic results.

    2. Fig. 2. Long-term daily weather data from the NCDC Royal Palm Ranger Station from 1963 to 2012. In climate change simulations weather data variability during 2000 to 2100 was based on variability at the Royal Palm weather station during 1963 to 2011 and weather data from TS and SRS in 2012.

      These data collected from 1963-2012 wereinputted into the DAYCENT system to simulate conditions during the next 100 years (from 2000-2100).

    3. Table 1. DAYCENT site characteristics for Taylor Slough (TS) and Shark River Slough (SRS). Site data was obtained from the Florida coastal Everglades Long-term Ecological Research (FCE LTER sites TS-1 and SRS-2), AmeriFlux and the literature.

      This table shows the two different sites, Taylor Slough (TS) and Shark River Slough (SRS) along with their exact location using the coordinate system, characteristics of each site, such as root:shoot ratio, soil composition, depth of roots, Nitrogen deposition along with the amount of Carbon found at each site.

    1. All islands were sampled at the completion of the growing season (August) between 2001 and 2003. We established a 30 m by 30 m plot at each of the grid crosspoints (12 to 32 per island, depending on island size) (12), within which we sampled plant species presence and cover; aboveground plant biomass; total soil N, P, and δ15N; and %N and δ15N from a common grass (in most cases Leymus mollis but in some instances Calamagrostis nutkanensis) and forb (Achillea borealis) (12).

      In this experiment, grids were designated over the island and 30 x 30 meter plots were established to sample within. In these plots the total soil nitrogen, phosphorous, amount of stable nitrogen isotope, and percentage nitrogen were sampled across grasses, forbs, dipterans, arachnids, passerines, and mollusks to determine how much of these nutrients were derived from the ocean. Organisms and soil that derive their nitrogen from a local source will have fewer amounts of nitrogen isotopes than those that get their nitrogen from higher trophic levels as is shown in Figure 3.

    2. Experimental nutrient additions to a community representative of fox-infested islands over 3 years caused a 24-fold increase in grass biomass (24.33 ± 6.05 g m–2) compared with control plots (0.51 ± 0.38 g m–2 increase; two-factor analysis of variance, F1,20 = 23.96, P < 0.001) and a rapid shift in the plant community to a grass-dominated state. In fertilized plots, grass increased from 22 (±2.7%) to 96 (±17.3%) of total plant biomass, whereas grass biomass in control plots was relatively unchanged (11.4 ± 3.0% and 12.1 ± 1.2% of total biomass at the start and end of the experiment, respectively) (12). In a parallel experiment (18), we disturbed and fertilized plots to mimic the effects of both seabird burrowing and guano addition. Here we found that disturbance negatively rather than positively affected grass biomass; the effects of fertilization alone were far greater than the joint effects of disturbance and fertilization. These results confirm the importance of nutrient limitation in these ecosystems and establish that nutrient delivery in the form of seabird guano is sufficient to explain observed differences in terrestrial plant communities between islands with and without foxes.

      In this experiment, nutrients were added to a community that represented the fox-infested islands which increased the grass biomass and also created a more grass dominated environment overall.

      The nutrient additions were meant to represent the spread of guano by the seabirds. In the fox-infested islands the seabird populations were scarce, which decreased guano accumulation. Therefore, the added nutrients represented the guano production by seabirds in the absence of seabird on the island that is fox-infested.

      These nutrient additions are similar to the nutrient states of fox-free islands and show what the changes in ecosystem could have been like during the introduction of foxes.

      In another experiment, they tried to mimic the disturbance in soil of seabirds burrowing, this negatively impacted the grass biomass and it was shown that fertilization by itself had the greatest positive effect on grass biomass and distribution. This helps explain the higher incidence of grasses in the fox-free islands.

    3. Fig. 1. The Aleutian archipelago with sample islands indicated in red (fox-infested) and blue (fox-free). Adak Island, the location of fertilization experiments, is indicated with a yellow dot.

      This figure shows the islands that were studied and their relative position on Earth. There are 9 fox-infested areas shown in red and 9 fox-free areas shown in blue, the sample size of islands is the same so the results cannot be attributed to the sample size difference. The yellow dot is the location of fertilization experiments.

    4. We use this experiment to show how differing seabird densities on islands with and without foxes affect soil and plant nutrients; plant abundance, composition, and productivity; and nutrient flow to higher trophic levels

      This is very broadly what the experiment seeks to discover through looking at fox-infested and fox-free islands. This experiment is designed to assess effects of sea bird densities on soil nutrients and composition, plant abundance, primary productivity, and the flow of nutrients from lower organisms to higher ones (i.e. from plants to herbivores to carnivores.)

    1. PGLS models

      Phylogenetic Generalized Least Squares (PGLS) is a method that accounts for phylogenetic relationships within a group of species (phylogeny reveals how closely related species are to each other). This method will determine if variables of interest are closely related.

      In this table, models of trait evolution indicated whether traits are ancestral and kept over evolutionary time. Species’ upper thermal limit (one of the traits studies here) was found to be shared by close relatives. The authors pointed out in this paper that niche conservatism (i.e. the tendency for species to keep their ancestral traits) could explain such findings.

    2. applications accounted for changes in bumblebee species’ range or thermal limits (table S3)

      Without also testing competing theories (land-use and pesticides), the authors would not be able to say how important the effects of climate change were in influencing range limits. Remember that the scientific method does not allow us to definitively prove a theory, only add to the evidence that one hypothesis is more likely than the alternatives.

    3. We investigated whether land use affected these results. Finally, we used high-resolution pesticide application data available in the United States after 1991 to investigate whether total pesticide or

      Because climate change is not the only possible explanation for changes in species' latitudinal and thermal range limits, the authors also tested other competing theories, like land-use changes and pesticides.

    1. Physics had to be modified

      It would be more accurate to say that the models used to describe physics had to be modified.

      As physics progressed, physicists revised their theories in light of new evidence and knowledge (and they continue to do so today). Here, Einstein describes how the special theory of relativity came about, in part, to solve the problem of classical mechanics' compatibility with electromagnetic theory.

      Modern physicists consider classical mechanics an approximate theory that is useful for the study of non-quantum mechanical, low-energy particles in weak gravitational fields. It is usually the starting point for students learning physics.

  2. Aug 2018
    1. Fig. 1 High-resolution melting profiles showing the resolved Symbiodinium strain genotypes.

      Different genetic sequences melt at slightly different rates. Therefore, they can be analyzed using these melting point curves, where fluorescence is plotted on the y-axis and temperature on the x-axis.

      If the DNA strand is composed of many guanine and cytosine bases, it will take a higher temperature to break the hydrogen bonds apart as opposed to adenine and thymine bases. This is why the E2 clade fluoresced at a higher temperature than the other clades.

    2. denaturing gradient gel electrophoresis (DGGE)

      Denaturing Gradient Gel Electrophoresis (DGGE) has been used, along with yeast cultures, to analyze saliva samples of 24 adults to study the bacteria present. This study showed ample variation of bacteria among individuals. The conclusion obtained from this experiment was that there is a lack of association between yeasts and bacterial DGGE fingerprint clusters in saliva, implying a significant ecological specificity.

    3. In this study, we evaluated the effectiveness of HRMas a tool to rapidly and precisely genotype monotypic Symbiodinium populations using the internal transcribed spacer, region 2, ribosomal DNA (ITS2 rDNA).

      This study (experiment) wanted to identify the effectiveness of high-resolution melting for the genotype (genetic makeup) of the Symbiodinium. Symbiodinium are single-celled algae that can be found in the endoderm (innermost layer of cells or tissue of an embryo in early development) of tropical cnidarians such as corals, sea anemones, and jellyfish.

    4. High-resolution melting

      A technique that detects mutations, and differences in DNA samples. HRM has been used to target various microbial communities on tadpole intestines and feces. In this study, HRS targeted a short amplicon (piece of DNA or RNA that is the source of amplification or replication events) of the 16S rRNA gene, which was the sequence being tested. Along with the HRM, gel electrophoreses and DNA sequencing were also used in order to study the results more closely. All three methods revealed several types of bacteria living in a tadpole's intestines and feces.

    1. We were unable to accurately calculate pollinator importance confidence intervals as we only estimated the relative frequency data (see above).

      Since much of the calculations were done using estimations, the authors could not provide a range of values that's likely to encompass the true value. For example, when scientists say this value falls within the 95% confidence interval it means that the intervals contain the true value 95 percent of the time and fail to contain the true value the other 5 percent of the time.

    2. Foraging behaviour was categorized by following visitor movements after they visited A. berteroi flowers. Visitation frequency of the floral visitors was estimated by counting the number of visits of each of the visitor groups to A. berteroi flowers during the observation periods where at least one visitor was seen, and calculating the corresponding percentage of the total visits observed in those periods.

      In order to determine the pollination efficiency of the insects, the authors tracked how often a specific visitor groups arrived and how long each individual stayed. Then the authors calculated an “efficiency” by estimating pollen on the visitors’ mouthparts. This was calculated as the average number of pollen grains per individual visitor of each group.

    3. Pollen grains were collected from the insect bodies to see whether visitors carried A. berteroi and/or other pollen.

      The reason behind this technique is to determine what species the carriers favored.

    4. We conducted pollinator watches weekly, for 3 h per week per site (12 intervals of 15 min per day), from 9:00 am to 12:00 pm (the hours with the highest visitation rates, B. B. Roque, personal observations) during the flowering period (April–June)

      The author monitored when the pollinators came around and interacted with the plants. Reason behind this is to determine how frequently the flower will have visitors. Another reason why the author monitored the plants, was to determine the period of time when the flower had the most visitors. With both of these factors being monitored, the author can determine more or less how frequently these plants can have their pollen spread throughout an area.

    1. Total genomic DNA of fresh leaves of a single individual of C. argentata was also isolated with the DNeasy Mini Plant kit. This DNA sample was subsequently used to obtain microsatellite loci that were developed by the Georgia Genomics Facility at the University of Georgia (Athens, Georgia, USA).

      This experiment isolated the genome of an individual C. argentata sample using the same method described in the previous experiment (DNeasy). The DNA sample obtained from this group was then taken to the Georgia Genomics Facility at the University of Georgia to develop microsatellite loci which are single sequence repeats that allows researchers to see any variability in the genome of this specific plant compared to the others. The researchers then used an Illumina HiSeq 2000 to see the microsatellite markers. The process through which they obtained these microsatellite loci is not described in the paper; however, the significance of this step when comparing different samples of DNA is described in the video below: https://www.youtube.com/watch?v=9bEAJYnVVBA

    1. Finally, knowing object distance is a prerequisite (or corequisite) in the model for deconfounding size, impedance and shape, so these features would first appear in the torus and higher areas. Although this proposal is not yet based on quantitative simulation or modeling, we believe it may be a useful working hypothesis for interpreting and further exploring parts of the electrosensory nervous system.

      Here, the authors are hypothesizing that the EOD pattern incorporated into electrosensory nervous system of the electric fish uses the information of size, shape, and distance of the objects in an algorithm to process and relay information to the electric fish brain.

    2. we have focused on reconstructing quantitatively the entire pattern of currents resulting from the fish’s discharge and environment.

      The authors here talk about the premise of their experiment and how they want to take all the data that the team has collected visually and through pattern tracking and turn it into data that has numbers. That is why in the chart that follows there is system mapping for EOD of both "wave" and "pulse" fish.

    1. Table 1. Evolution of spread-relevant traits as a function of landscape patchiness.

      Table 1 shows data indicating linear relationships between variables that changed in an evolving population based on the variability of the environment. The P column explains whether the data is statistically significant, meaning it can be concluded as a relationship between data and not just due to random chance. The two values observed for each variable are Y intercept (which indicates whether the trait changed from the original population) and the slope (which indicates how much the trait changed). These values are calculated as P values to determine if they are significant.

    2. Fig. 3. Genotypes and traits at the invasion fronts.

      Figure 3 shows the initial and final genotype compositions as well as trait changes among the different conditions (A. continuous, B. gap size of four times the mean dispersal rate, C. gap size of eight times the dispersal rate, and D. gap size of 12 times the dispersal rate). The central pie chart found in each of the four graphs shows the equal frequency of genotypes in the founding population, while the other pie charts are used to represent the genotypic make-up of the top 10 leading individuals after 6 generations of spreading within the different conditions. The placement of the pie charts is based on rankings of three traits: the competitive ability of the plant (dominance of the plant in ways that do not directly affect it's ability to spread offspring), dispersal (the average distance of the farthest dispersed seed from the plant it was dispersed from), and the height of the plant.

      These values show that even as the gap size increases, the trait values hardly increased at all. Similarly, as can be seen by the color of the pinwheels, the genotype composition change between the different gap sizes was rather consistent. The only outlier is the continuous condition that has random trait values and genotype compositions.

    3. We initiated each replicate invasion in the leftmost pot of the array by sowing equal fractions of 14

      In the first experiment, the authors simulated invasion by planting 14 genotypes on one side of the pot array. The plants were allowed to proceed for several generations to follow evolution in A. thaliana. Habitat patchiness was tested by putting space between the pots at varying distances.

    1. Error bars reflect the 95% confidence interval of the mean or expert judgment

      Notice that each bar in the figure has small capped lines that extend above and below the bar. These lines represent error bars for the various VOC emission factors. Error bars reflect the experimental uncertainty in determining VOC emission factors. The error bars in this figure are 95% confidence intervals, meaning that we are 95% certain that the true value lies somewhere in between the top and bottom of the error bar. Any measurement made has uncertainty associated with it.

      In scientific communication it is important to give the value that was found and the uncertainty in that value. We typically talk about uncertainty as being the precision of the measurement, where a smaller uncertainty is a more precise measurement and a larger uncertainty is a less precise measurement.

    2. We used energy and chemical production statistics, together with near-roadway and laboratory measurements, to construct the mass balance shown in Fig. 1 (17).

      Economic data was used to estimate the mass of various chemical products used in the United States. You can see how the estimates were derived in Tables S2 and S3 of the supporting information.

      Tables S2 and S3 can be found on pages 23 and 24 of the Supplementary Materials document

    3. California has an extensive regulatory reporting program for consumer products (34), including residential and commercial uses, which we used to speciate emissions. These speciation profiles provided us with target compounds to characterize in both outdoor and indoor environments. We also accounted for industrial emissions from VCPs (e.g., degreasing, adhesives, and coatings). The reporting data are in agreement with a U.S. database of chemicals (35) used as key constituents in chemical products (table S7). The VOC speciation profiles of VCPs (table S8) are distinguishable from those of fossil fuels (table S9), although there is some overlap in species present.

      Every emission source of VOCs emits different compounds. Many databases of the different emission profiles exist. The emission profiles allow the researchers to determine what activities (driving a car, painting a house, spraying perfume, etc.) lead to the presence of different VOCs in the air. The researchers use these profiles to differentiate between sources that come from fossil fuels (e.g. driving a car) and those that come from VCPs (e.g. painting or perfume).

    4. If chemical products are an important source of urban air pollution, then their chemical fingerprint (fig. S3) should be consistent with ambient and indoor air quality measurements.

      Previous studies have measured volatile organic compounds in outdoor and indoor air around Los Angeles, California. This study is using that data to see how it agrees with model calculations when accounting for volatile organic compounds from different sources. The video below gives an overview of how atmospheric modeling helps us understand what is occurring.

      https://youtu.be/rOClF26-Bo8?t=1m

      The study looks at two different environments (indoor air and outdoor air) that can influence each other.

      See Figure S4 on page 18 from the Supplementary Materials document

    5. The fraction that can be emitted to the atmosphere depends strongly on product type and use (table S4).

      Emissions from volatile chemical products was determined by looking at the composition of chemicals in a particular product and how readily those chemicals evaporate into the air. The authors compiled information from various other researchers to perform these calculations.

    6. In 2012, the amount of oil and natural gas used as fuel in the United States was ~15 times the amount used as chemical feedstocks (Fig. 1A).

      United States government data was compiled to look at the amount of oil and natural gas supplied and what these sources are used for. See Table S1 of the supporting information to see the breakdown.

      Table S1 can be found on page 22 of the Supplementary Materials document

    7. Although U.S. sales of VCPs are substantially smaller than for gasoline and diesel fuel, VOC emissions from VCPs (7.6 ± 1.5 Tg) are twice as large as from mobile sources (3.5 ± 1.1 Tg) (Fig. 1E, light green, dark green, and blue bars) because of differences in emission factors.

      The authors use different calculations to determine VOC emissions from mobile sources and VCPs. This is due to the different end uses. Oil and natural gas used for mobile sources undergo combustion that causes much of the carbon to be emitted as carbon dioxide and not VOC. VCPs are primarily used directly and remain as intact organic molecules.

    8. We consider four key pieces of evidence to support this finding: (i) energy and chemical production statistics; (ii) near-roadway measurements of transportation emissions, together with laboratory testing of chemical products; (iii) ambient air measurements away from roads; and (iv) indoor air measurements.

      Many experiments from other researchers are utilized in this study to compare model calculations with experimental data.

      The authors in this study utilize all of these different sources of information to build a better understanding of the sources of air pollution.

    1. formed on the PET film upon culturing

      After collecting the samples the authors provided the samples with water, an appropriate temperature, and a food source of PET film. They later used microscopy to observe what samples were able to use the PET film as an energy source.

    2. To explore the genes involved in PET hydrolysis in I. sakaiensis 201-F6, we assembled a draft sequence of its genome

      The authors took the DNA from Ideonella sakaiensis and created a list of the order of the DNA bases A, G, C, and T. Next, they used a computer program to compare the sequence to sequences from other organisms that were already known to degrade PET.

    3. limiting dilutions

      A lab technique that isolates a single species of bacteria from a sample with more than one species of bacteria.

    1. Fig. 2. Changing bumble bee community composition, bumble bee tongue length distributions, and tube depth distributions of visited flowers over time. (A and B) Bumble bee community composition. (C and D) Bumble bee tongue length. (E and F) Flower tube depth distribution. Bombus species abundance in alpine communities is indicated by the proportion of total foragers (15). Species are ordered by increasing tongue length [in (A), species’ names follow (18)]. Bimodality of the density functions (15) indicates that bumble bee communities contain two predominant phenotypes, short-tongued and long-tongued [(C) and (D)]. (E) and (F) show the tube depth density functions for flowers visited by, respectively, B. balteatus and B. sylvicola in the Front Range [Mount Evans and Niwot Ridge (15)]. For tongue length [(C) and (D)] and tube depth [(E) and (F)], representative density functions for simulated communities (15) are shown.

      These results suggest that bumble bee tongue lengths are decreasing and corolla tube lengths are also decreasing in response to climate change.

    2. On Pennsylvania Mountain, alpine bumble bees forage over hundreds of meters to provision their nests (28). To ask how warming has affected floral resources at this scale, we measured PFD of six bumble bee host plants from 1977–1980 and 2012–2014 in five habitats along a 400-m altitudinal span (table S5). Land surface area decreases with altitude above tree line in the Rocky Mountains (29), declining by more than an order of magnitude on Pennsylvania Mountain, where 58% of habitable terrain is found below 3800 m and only 4% above 3938 m on the summit (Fig. 3Aand table S5). Because bumble bees forage across the 400-m altitudinal range (28), we evaluated the temporal change in flower production at this landscape scale. For each habitat, we multiplied PFD (flowers per square meter) within sampling plots by surface area (square meters) to estimate of total flower production (15)

      From 2012-2014, researchers analyzed the change of flower production of six bumble bee host plants over time at a altitude of 400m. This is where the bumble bees most commonly forage. The flower abundance was measured as flowers per square meter across five different habitats. It was then compared to data from 1977-1984 to determine change over time.

    3. Climate records from Niwot Ridge show warming summer minimum temperatures over the past 56 years (27).We see similar changes on Mount Evans (R2 = 0.383, t1,52 = 5.68, P < 0.0001) and Pennsylvania Mountain (R2 = 0.341, t1,52 = 5.20, P < 0.0001) (fig. S3, A and B), where summer minimums have increased ~2°C since 1960. We used a nonlinear model to characterize the relationship between peak flower density (PFD; flowers per square meter) and summer minimum temperature.

      Over the past 56 years, climate change has caused summer temperatures at Niwot Ridge, Mount Evans, and Pennsylvania Mountain to rise. To understand the relationship between summer temperatures and flower density, four bumble bee host species were analyzed for change in average flower density between 1977 and 2014.

    4. (i) decreasing body size, (ii) coevolution with floral traits, (iii) competition from subalpine invaders, and (iv) diminishing floral resources.

      The author listed four possible processes responsible for the tongue length changes in the bees studied:

      1) Decreased body size over time has correlated to a shorter tongue - The authors compared the body size measurements with the tongue length measurements over time.

      2) Coevolution between the flowers and bees - The tube depth of the flowers were measured and compared to the tongue length of the bees over time.

      3) Competition from other bees in the same region affected tongue length - The authors compared other bee species to the bees studied and determine which species had the advantage and if these advantaged affected the other species.

      4) Diminishing floral resources - The authors analyzed the effects of lower amounts of flowers due to increased temperatures on the foraging habits of bees. They then concluded if this could have impacted tongue length.

    1. JH synthesis was analyzed

      Scientists started using fluorescent tags as a natural way to accurately detect low concentration of metabolites in insects. This method proved to be sensitive and effective and most importantly stable. Being stable was an important factor in this method because if it was not stable it would start to degrade after about 15 minutes. The new method has lasted over an hour, which is in benefit of being detectable by HPLC-FD (High-Performance Light Chromatography with Fluorescent Detection).

    2. JH and insulin regulate reproductive output in mosquitoes; both hormones are involved in a complex regulatory network, in which they influence each other and in which the mosquito's nutritional status is a crucial determinant of the network's output.

      The hypothesis is saying the mosquitoes' nutrition has an effect on "insulin sensitivity" and "juvenile hormone synthesis." Insulin is a hormone that works with the amount of glucose (sugar) in blood. A juvenile hormone is a hormone in insects that work with maturation and reproduction. So the researchers are saying that the amount of nutrition (food) the mosquitoes eat will determine the amount of these two hormones, insulin and juvenile, are produced.

      Since the researchers hypothesize that how much the mosquitoes eat determines how much insulin and juvenile hormones work, this means how much insects reproduce is also affected. So the researchers are saying if the insects eat enough, they will reproduce with better conditions than if they were not eating enough. This is because the hormones that control reproduction are controlled by the insects' nutrition.

    1. we measured the position and bearing of the fish swimming at a constant velocity with no acceleration; the position and bearing at time zero was then converted into Cartesian coordinates using the range of the center acoustic beam as a reference distance.

      Certain variables in the frame of these barracuda, as they were being detected, was used through complicated physics and mathematics to calculate their stride lengths.

    2. ensuring stimulation of the white muscle tissue

      Ensuring the white muscle tissue were stimulated by the electric pulse to contract, tighten.

    3. time from initial lure strike to landing was minimized and never exceeded 15 min.

      The time it took to hook a fish, reel it in, and brought on board was never more than 15 minutes.

    4. x-axis is percentage of total length

      The x-axis shows where along the length of each fish the contraction times were collected from, starting from the head (0%) to the tail (100%).

    5. P<0.001

      In statistics, 'P' is the p-value. The p-value is the probability that the null hypothesis is true, and if it's below .05 that usually means the null hypothesis (there is no correlation between the two variables being observed) is rejected as not true.

      In the case of this section of the paper, a statistical test was run to see if the mean temperatures of the fishes (taken from the muscles being observed) were significantly different from each other. It was found that the probability of this was so low (below .05), they were not significantly different.

      This is important because it implies that all the muscles of all the fish had close enough temperatures to each other that the researchers wouldn't have to worry about slightly different muscle temperatures making the contraction times collected in each fish faster or slower in relation to each other.

      Basically, they checked that the muscle temperatures in each fish were close enough to each other that the variable temperature would be (close enough) to being a "constant" in all the tested subjects in the experiment.

    6. forces needed to reach a certain swimming speed

      This refers primarily to effects of strong and weak water currents, as discussed in the last few annotations.

    7. Here we investigated maximum speed of sailfish, and three other large marine

      Sailfish, barracuda, little tunny, and dorado are four marine predatory fish species known for their extremely high swimming speeds.

      The researchers decided to reconsider how accurate the previously predicted estimates of each of those species' maximum swimming speeds truly is, hypothesizing that they may be over-estimations.

      They did this by using a different method than that used to make the estimates they're investigating. Their method was to measure the time it takes for every contraction of swimming muscle (that doesn't use oxygen) when it twitches.

    1. Both results suggest that chemically distinct species are more likely to co-occur. In contrast, we found a significant negative relationship between species phylogenetic distance and presence/absence co-occurrence (r = −0.16, P = 0.01). Thus, more closely related species are more likely to co-occur.

      The Mantel tests allowed the authors to determine the amount of difference between species. The test uses estimated distances to measure difference.

      In this case, it is testing chemical differences between species. The results indicated Piper species that are more chemically different are more likely to exist within the same environmental patch.

    2. Mantel test

      A Mantel test measures the correlation between two matrices. In this case the Mantel test was used to estimate the correlation between species phylogenetic distance and their co-occurrence.

      Using this test, the researchers were able to statistically verify that there is a negative relationship between how closely related two species are their co-occurrence.

    3. Pianka's index

      Pianka's Index is used for field measurements of the niches. They can measure microhabitat, resource usage, and spatial activity. The values range from 0 to 1, no resources used in common between species to complete overlap in resource use, respectively.

    4. Gotelli's c score

      Gotelli's c-score measures co-occurrence between species. A binary matrix is used to represent the absence (0) or presence (1) of a species. Each column represents a site and each row represents a species. Once the c-score is calculated a high value indicates less co-occurrence and a low values indicates there is more likely to be co-occurrence.

    5. only -NRI was significantly different from zero (-NRI, t = 1.83, df = 80, P = 0.03; -NTI, t = 0.77, df = 80, P = 0.22). In contrast, species composition within the plots was phylogenetically underdispersed. Both -NRI and -NTI were significantly different from zero (t = −5.24, df = 80, P = 0.0001 and t = −2.26, df = 80, P = 0.01, respectively; Fig. 2).

      Here, the author’s evaluated whether or not similar species tend to coexist together using the inverse nearest relative index (-NRI), which asses clusters of species, as well as the inverse nearest taxon index (-NTI), which asses cluster taxonomy of clustered species.

      Along with data obtained by the chemical dendrogram the clusters were analyzed and diversity in relation to clustering was discovered.

    6. In our community-based approach, we found that Piper species were, on average, more overdispersed with respect to their secondary chemical composition than expected

      In order to assess the dispersion of Piper species, the authors analyzed the secondary chemical composition of the plants. In plants, secondary composition are organic compounds used for plant defense. They are secondary because their absence does not cause immediate death of the plant.

      The analysis of the secondary chemical composition was performed using a chromatography technique: GC-MS. This technique does not detect all secondary metabolites but it detects most of them (86% of the metabolites).

      After the secondary metabolites were detected, a library was created for all species and the library was compared to references in the AMDIS (Automated Mass Spectral Deconvolution and Identification System -a mass spectra identification system). The library created was a mass spectra library.

      Mass spectrometry is an analytical technique that identifies molecular weights of compounds which helps in the identification process. The particular identification method allowed the researchers to assess chemical similarities between individual plants and species.

      This analysis allowed the researchers to conclude that the Piper species were more spread apart than expected when their secondary metabolites was the point of comparison.

    7. species coexistence

      In order to asses species coexistence, the amount of niche overlap needed to be found. Niche overlap occurs when two or more organismal units use the same resources. More overlap would mean that more species exploit each resource. This was done using Pianka's Index.

    8. K = 0.03

      K statistic is a statistical analysis of the phylogenetic signal based off a Brownian motion metric that determines the strength of the phylogenetic signal.

    9. Phylogenetic analysis yielded a local species phylogeny that concurs with the current phylogenetic Piper data

      Piper is a very species rich genera of flowering plants. Molecular phylogenetics has been crucial in identifying the monophyletic groups of this genus.

      The researchers amplified the ITS region and the psbJ-pet A intron of each of the sampled species they collected to conduct a phylogenetic analysis. They were able to construct a phylogenetic tree of the Piper species that were found within the patches they sampled.

    10. The hierarchical clustering showed five discrete chemical clusters

      The authors collected data regarding chemicals produced by the plants used in their experiment using a multi-step process.

      They first preserved leaves they collected within silica gel before transporting the leaves to the University of Missouri, St. Louis. There, the researchers crushed the leaves under liquid nitrogen. Next, a methanol-chloroform solution was used to extract volatile compounds along with a small addition of piperine. The authors then filtered and stored the compounds so that they could later be analyzed.

    11. The GC-MS analysis yielded more than 1,100 chromatographic features. Approximately 40% of all features were present in all Piper species (e.g., phytol, stigmasterol, sitorterol, and tocopherol).

      The authors used previously collected extracts from leaves and analyzed them using gas chromatography mass spectroscopy (GC-MS), which determines chemicals within an extract based off particular peaks given off by those chemicals. They were able to find that 40% of all Piper species contained the same types of chemicals.

    12. We sampled a total of 2,035 individuals from 27 species of Piper across the 81 sampled plots (Appendix S1: Table S1). The number of individuals present per plot was 25.2 ± 1.1 (mean ± SE; max–min = 4–51), and the number of Piper species per plot was 5.2 ± 1.4 (max–min = 3–11).

      In order to conduct the experiment, patches needed to be sampled and the average number of Piper per patch needed to be calculated. The researchers created transects located between 50 and 100 m from the trail and a large space separated each transect (more than 250 m). Then in a different transect, 81 plots of 20m in diameter were created. The standardization of the plots is important for an accurate calculation of the average number of Piper per plot.

      Piper had different sizes, so for a better standardization, only Piper that are more than 1cm in diameter were selected for calculating the mean number of Piper per plot. The researchers than identified the species of each Piper. A total of 2,035 individuals were counted. The mean per plot was calculated by dividing the number of individuals by the total number of plots. (2,035/ 81 = 25.123) The number of species per plot was calculated by determining the mean of the average of species per plot. The average was found to be 5.2 species per plot.

    13. Pianka's Index

      In the process of his research, Pianka came up with a universal formula for calculating the overlap of pairs of niches.

    1. in situ topographic measurements

      Here, in situ means "in place." Measurements were made of the actual footprint contours left by the individuals striding along the trackway.

    2. The eye-scale characteristics of the profiles exposed in the test-pits are reported here from the top downwards.

      For each test-pit, the authors analyzed the soil profile.This established how the different areas were related geologically and provided information about how to proceed with the analysis of hominin and wildlife print present.

    3. Small amounts of water were used during the excavation, in order to soften the sediment and darken its hue to better distinguish it from the surrounding tuff. The infill was finally removed by small dental tools, trying not to damage the very thin calcite film covering the original footprint surface (White and Suwa, 1987).

      The degree of fossilization of the footprints varied in different locations. In order to study the shape and structure of a footprint, soil had to be carefully removed from the depression.

    4. The preservation state of the tracks varies considerably along the trackway, depending on the depth of the Footprint Tuff from the surface.

      The trackway footprints are extremely fragile. Clearing and preserving them had to be done with the utmost care. Unlike fossil bones that are solid, the footprints are only empty spaces. Depending on the substrate, an incorrect move could cause the soil to crumble and the footprint to be destroyed. The author had to do a careful analysis of the trackway soils to be able to know how to best preserve and analyze each footprint.

    5. Following the code used for the Site G prints (Leakey, 1981), we refer to the new individual as S1 (footprint numbers S1-1–7 in L8, S1-1–4 in M9 and S1-1–2 in TP2). At the end of the September 2015 field season, we discovered one more track referable to a second individual (S2), in the SW corner of TP2

      Site G is the code used by Leakey to identify the trackway her group discovered. The three individuals leaving the footprints are referred to as G-1, G-2, and G-2. Keeping with this code system, the authors identified the new trackway area as Site S. The footprints are attributed to individuals S-1 leaving foot prints numbered S-1-1 through S-1-7 in location L8. Individual S-1 also traveled through locations M9 and TP2.

  3. Jul 2018
    1. His clear and wide ideas will for ever retain their significance as the foundation on which our modern conceptions of physics have been built.

      It is only by embracing Newton's ideas that physicists such as Einstein were able to consider exceptions and, in doing so, build on them.

      Although we don't often think about it, scientists improve on each others' ideas all the time and revise theories in light of new evidence generated by new technologies and methodologies.

    2. The interpretation seemed obvious, but classical mechanics forbade it.

      Einstein introduces the need for a concept of general relativity, which describes motion with respect to any two coordinate systems, not just inertial coordinate systems.

    3. What has nature to do with the coordinate systems that we propose and with their motions?

      Einstein's question points out that coordinate systems are not a product of nature, but a way of understanding nature. It is because of this that physicists are able to revise the tools and methodologies they use in light of new evidence.

  4. Jun 2018
    1. Fab only lightly marked the nucleus, suggesting very little KDM5B had been synthesized (Fig. 1D). Fab also colocalized and co-moved with many MCP-labeled mRNA in the cytoplasm

      After determining that neither the SM tag nor Fab would disrupt cellular processes, the authors wanted to determine how soon Fab would mark KDM5B. To do this, the authors repeated their first trial but imaged at 6 hours instead of 24.

    2. 24 hours after transfection, MCP marked mRNA in the cytoplasm and Fab marked KDM5B in the nucleus

      Preliminary testing was conducted twenty-four hours after the plasmid was transiently transferred to ensure that the methods of coupling the FLAG SM tag (that can be labeled with the anti-fluorescein antibody, anti-FLAG Fab) and the MS2 stem-loop (that can be identified with a MS2 coat protein) would not inhibit transcription, translation, or the movement of SM-KDM5B mRNAs throughout the cell.

      The results are highlighted in Fig. 1C with the SM-KDM5B protein in green and the MCP-labeled mRNAs in red.

    3. labeled with the far-red JF646 fluorophore

      JF646 produces a brighter fluorescence than other proteins.

    4. MS2 stem-loop repeat allows visualization with labeled MS2 coat protein

      MS2 is a protein from the coat of bacteriophages. It has a high affinity for "stem-loop" structures, which are hairpin-like shapes formed by DNA. The authors took advantage of this high affinity by using labeled MS2 to detect certain sequences.

    5. sensitivity and versatility of NCT make it a powerful new tool

      Scientists are always working to improve existing techniques to be more precise and versatile.

    1. indicates, for each point, the number of scenarios different from the simulated present. Yellow areas indicate when only RCP8.5 is different; orange areas denote when RCP4.5 and RCP8.5 are different; red areas indicate when RCP2.6, RCP4.5, and RCP8.5 are different; and blue circles mark areas in which the biome type at 4700 yr B.P. is different from the present biome type.

      The final map, 3H, uses a different color coding key, and shows the grid points that are different between the past, present, and future scenarios. Grid points that differ between the 4700 B.P. scenario and the present scenario are marked with blue circles. The filled dots all indicate differences in the biomes between the present and certain future scenarios. Yellow dots are grid points that are only different in the 4.0°C scenario, RCP8.5. The orange dots are different in both the RCP4.5 and RCP8.8 scenarios, and the red dots are different in the RCP2.6, RCP4.5, and RCP7.5 scenarios.

    2. simulated by the BIOME4 model for the present

      The third map, 3C, was generated by putting the current climate data into the BIOME4 model, running in "forward" mode. This does differ from the first map, based on pollen core samples. The biggest difference is that the first map shows warm mixed forest whereas the third map shows Temperate Deciduous Forest; this is likely caused by pine pollen being over-represented in the pollen core data.

    3. reconstructed from pollen for 4700 yr B.P.

      The second map, 3B, comes from putting the 4700 B.P. pollen core data (covering the years 4650–4750 B.P.) into the BIOME4 model. This time slice was picked to represent the past Holocene because it had the highest variation from the present distribution - this is the bar that extends above the 99th percentile line in Figure 2.

    4. Horizontal lines represent the 50th, 80th, 90th, and 99th percentiles of the Holocene values

      These lines, marked below in purple, provide information about the distribution of the black bars, which show the proportional biome change in past Holocene compared to the current period. Half of the values are at or below the lowest line, whereas all but 1% of the past values fall at or below the top line.

      Here's the figure with the lines more prominently marked:

    5. For the future, the forward application of the same model yields ecosystem distributions from climate projections

      To calculate future values, BIOME4 was run in its normal mode—using climate inputs to generate biome predictions. The climate inputs come from the models and time-series data found in the Coupled Model Intercomparison Project (CMIP5), which "promotes a standard set of model simulations." This way, research is done using the same underlying models, which allows for better comparisons across projects. Researchers update these models approximately every 5 years, incorporating new information.

    6. Given the confidence with which past ecosystems and climate change can be reconstructed from numerous pollen profiles, the development and validation of more reliable numerical models for the ecosystem-climate relationship have become possible. We apply such an approach to future climate conditions, using simulations from the Coupled Model Intercomparison Project phase 5 (CMIP5) for three different greenhouse gas (GHG) forcings

      The researchers use two main methods to generate the information about the Mediterranean Basin in this paper—for the past, the model uses data from pollen cores to generate information about the climate and ecosystems found over the past 10,000 years. For the future, the model uses different CO<sub>2</sub> emissions pathways to generate projections about the ecosystems and climate.

    7. The vertical bars represent the ±1 SDs provided by the reconstruction method

      The error bars for the Holocene and 1901–2009 data points are based on standard deviations. This is a different method from what the researchers used to calculate the future predicted values.

  5. May 2018
    1. Ants, particularly P. gracilis, may pose a significant threat to butterfly eggs and larvae, but butterflies have developed ways to cope with such predators

      Authors found that this species of ants are more efficient at being predators.

    2. Early instar caterpillars suffered the most damage when interacting with P. gracilis (n = 15 trials, 86.7% mortality); late instar caterpillars successfully foiled P. gracilis advances (n = 15 trials, 0% mortality).

      The ant species C. floridanus death rate is at 56.3% during this experiment. They have forced some or all instar caterpillars to leave their habitat.

    3. Exclusion experiments revealed that early instar caterpillars were vulnerable to both crawling and non-crawling predators.

      The instar caterpillars were vulnerable to be eaten, or killed by other predators.

    4. However, individual parameters (tree groups) were investigated to determine significance using non-host trees as the baseline group to compare the frequency of P. gracilis collected for each tree group.

      Each species was investigated to determine and compare each tree group.

    5. Percentage of ant species captured in pitfall traps at Elliott and Adams Keys (tree canopy, trunk, and base). Overall, 1418 total ants comprising 25 ant species were captured and identified from pitfall traps

      The experiment was conducted at Biscayne National Park and was split into three parts. The first part was using pitfall traps to collect ants at Biscayne Park near the host plants. Secondly, the host plants with known caterpillars were protected with various combinations of cages and tanglefoots. Concluding the author was keeping track of how long it take for certain species of ants to first find the caterpillars. Authors assumed that the ants would interact with caterpillars more frequently than other predators.

    6. Ants collected in pitfall traps at Elliott and Adams Keys: number of individuals of each species, and status

      All of the ants found in pitfall traps that were placed all around the canopy in the keys. 11 out of 25 species were found to be exotic and 735 out of 1418 of the total amount of ants were exotic.

    7. Pseudomyrmex gracilis and C. floridanus were more aggressive towards caterpillars in comparison to other ant species;

      After the experiment was finished, they have found that the Pseudomyrmex gracilis and C. floridanus interacted more aggressively toward the subject compared to another species.

    1. fear conditioning

      A learned association between a stimulus and negative outcomes, in this case represented by pictures associated with an electric shock.

      Learn more about fear conditioning (animal study): https://www.youtube.com/watch?v=ozkpK-nhz04

    2. appetitive learning

      Reinforcement that allows the association of a symbol with a positive outcome, in this case money. After trials, the objective was to teach participants to respond to the animal pictures associated with a reward.

    3. avoidance responses

      This task establishes an association between a neutral stimulus and a negative outcome with the hope that the repetitive task will teach participants to avoid the stimulus.

      In this study, the negative stimulus was an electric shock over four stages of learning.

    4. coefficient of determination

      The determination of the correlation coefficient.

      In this study, the authors used both Pearson (r) and Spearman (rho) correlations. Pearson correlation is used when there is an assumed normal distribution (distribution that shows symmetry around the mean), while Spearman is used when it is assumed the distribution will not be normal.

      Learn more about coefficient determination:

      http://blog.uwgb.edu/bansalg/statistics-data-analytics/linear-regression/what-does-coefficient-of-determination-explain-in-terms-of-variation/

    5. trial and error

      The eight blocks (96 trials) where participants were tested and learned from the feedback that they received after their response to the presentation of the pictures.

    6. urine screen

      A urine screen is performed to rule out medical conditions and/or drug use. In this case, the authors used it to determine if the volunteers were appropriate for their study and to see if they tested positive for drug use for the different types of drugs involved.

    7. square-root transformation

      A test that makes it easier to analyze data that aren’t normally distributed. The authors performed this analysis to reduce skewness (effects due to asymmetry in a probability distribution) and stabilize variance from the questionnaires and demographic responses.

      To learn more about transformation: http://fmwww.bc.edu/repec/bocode/t/transint.html

    1. in human skin grafted to severe combined immunodeficiency disease mice

      In this experiment, skin from a human was grafted onto mice with depressed immune systems. This means a piece of human skin was transplanted onto mice whose immune systems could not protect them from diseases.

    2. The treatment of mouse NC cells carrying Kitl mutations with Edn3

      In this study, the cells from the neural crest of mice that carried the specific mutation Kitl were treated with endothelin 3.

    3. Treatment of quail NC cultures with Edn3

      The study described here consisted of treating quail (type of bird) neural crest cultures with Edn3. This study was in vitro, meaning the embryonic neural crest was removed and treated outside of the organism. This study showed the role that Edn3 plays in development as stated in the paper.

    1. We estimated the annual input of plastic to the ocean from waste generated by coastal populations worldwide.

      Exact numbers are not available for the mass of plastic waste entering the ocean, so the authors used a series of estimates in their calculations.

    2. We calculate that 275 million metric tons (MT) of plastic waste was generated in 192 coastal countries in 2010, with 4.8 to 12.7 million MT entering the ocean.

      The range of 4.8 to 12.7 million Metric Tons of waste comes from uncertainty in the total amount of waste generated, the amount of that waste that is plastic, and the amount of mismanaged waste that enters the ocean.

    1. the narrow strip of Mediterranean vegetation on the Libyan and Egyptian coast, which is below the spatial resolution of our climatic data

      For the reconstructions of the past Holocene ecosystems based on the pollen cores, the initial model outputs are at a lower resolution than the 0.5° by 0.5° resolution of the future projected biomes. The resolution of the reconstructions was a grid of 2° latitude and 4° longitude.

      To allow more direct comparisons between past and future, the researchers interpolated the reconstruction data to fill in a 0.5° by 0.5° grid. However, this may miss some features at scales smaller than the original gird.

    1. First, we test a range of plot sizes and shapes to determine the most accurate (least bias and greatest precision) and most efficient (accuracy per unit effort) method to estimate AGB and tree biodiversity. Second, we evaluate whether there exists a general trade-off among methods in the accuracy of information they provide for tree diversity vs. aboveground biomass estimates. Third, we analyze the extent to which different inventory methods may be appropriate among forests differing in structure and floristic composition.

      How the authors obtained AGB and tree biodiversity, evaluated trade off among tree diversity and aboveground biomass

    2. Several alternatives to 1 ha plots have been suggested, differing primarily in their sizes, shapes, and the minimum size of trees inventoried

      Table 1 shows the different types of plots used and how they differed in size, area covered, areas inventories, shape, and number of days used.

    1. (Nowak et al. 2004),

      Fundamental paper which shows how plants will uptake more CO2 when it is present in higher and higher quantities.

      At 600 parts CO2 per million parts air, plant carbon uptake is limited due to low levels of CO2 present in atmosphere.

    2. Fig. 6. Observed (solid) versus modeled (hollow) CO2 exchange rates (NEE, Reco and GEE) at TS (A) and SRS (B). Atmospheric convention is used here and positive numbers indicate a loss of C to the atmosphere.

      The solid bars show the actual data gathered. They measure the different rates of carbon exchange.

    3. Fig. 7. The effect of elevated atmospheric CO2 concentration (550 ppm, 850 ppm and 950 ppm) on cumulative (A) NEE, (B) Reco and (G) GEE, at TS. The influence of rising temperatures (1°C, 2.7°C and 4.2°C) on cumulative (B) NEE, (E) Reco and (H) GEE and shifts in seasonal and annual precipitation patterns (−2%, +7% and +14%) on cumulative (C) NEE, (F) Reco and (I) GEE. Atmospheric convention is used here and positive numbers indicate a loss of C to the atmosphere. All simulations were compared to current weather and atmospheric CO2concentration (red line).

      Figures displays projections for the effect of three climate-induced environmental changes on ecosystem processes (NEE, Reco, GEE).

      As CO2 levels and temperature increase, the ecosystem will uptake more and more CO2, and will retain more carbon.

    4. Fig. 5. Observed versus modeled soil temperature at (A) TS and (B) SRS, and soil volumetric water content (VWC) at (C) TS and (D) SRS.

      The figures show what happened to the actual data vs the data from the model. They are very close and show that the model is reliable, in other words, the data is precise.

    5. ran the model for 100 years (1) under climate change projections,

      Remember, this is a simulation! It was done on the DAYCENT simulation model.

    6. Fig. 4. Climate change scalars for (A) elevated atmospheric CO2 concentration, (B) air temperature, and (C) precipitation. The distributions for (D) minimum temperature, (E) maximum temperature and (F) precipitation were modified to match projected seasonal change.

      These charts show the different magnitudes, at differing scales of CO2, temperature, and rainfall, respectively, projected out to the year 2076.

  6. Apr 2018
    1. We computed anomaly fields using all data and compared these results with computed fields on the basis of data that did not include values exceeding 3 SDs.

      By comparing a modeled map using every data point available and comparing that map to one that excludes outliers exceeding 3 standard deviations, the authors realized they were actually excluding some ocean temperature features that occurred. Thus by changing the data cut-off to 6 standard deviations it was possible to more accurately model ocean conditions.

    2. we used a 6-SD check to flag data as not being usable in this study as compared to the 3-SD check used earlier.

      By broadening the cutoff criteria the authors of this study were able to distinguish real-life changes in ocean temperatures. Their previous data cutoff of 3 standard deviations (which are a measure of variance around a mean), was too strict and deleting real data points.

      Broadening the pool of what was considered "good" or "realistic" data to 6 standard deviations was necessary in order to properly document temperatures that actually occurred in the oceans.

    1. biological, rather than physical, processes drove reach-scale rates (table S5)

      Biological factors that drive the decomposition of carbon include the consumption and respiration from microbes, vertebrates, and in-vertebrates.

      Physical factors include temperature, flow of water, and sediment.

      The alignment of the reach-litterbag scale rates show that the bags represent the actual rates, and that the bags were not simply filtered by increased water flow or torn apart because of temperature.

    2. litterbag

      The litterbag technique can be used to measure the density lost due to composition by microbes and fungi.

      A known type and amount of litter is stuffed in the bag and is left for a certain amount of time in the stream. The bag is then later taken out and weighed while wet. The bag is allowed to dry and then the dry weight is taken.

    3. pools of benthic fine and coarse POC declined

      Benthic fine and coarse particulate organic carbon can be used as a measurement when observing loss of carbon caused by detrivores.

    4. consideration of differences among litter species and potential divergence in rates due to the degree of biological processing

      In this experiment, leaf litter from different types of trees were used. The results are in Figure 3.

      The structure and chemistry of leaves are different and this determines how fast they may decompose.

      For example, tulip poplar decomposes the quickest and has a low carbon to nitrogen ratio. Comparatively, oak decomposes slowly and has a higher carbon to nitrogen ratio.

    5. Our results generally support the use of litterbags to measure larger-scale C dynamics

      It is often necessary to use a simpler model version of a larger system because it is easier to observe.

      It is difficult to observe the effects on a whole stream, but the litter bags are observed and represent the carbon loss in streams.

    6. Higher C loss rates at the litterbag scale than the reach scale are expected, because litterbags track distinct parcels of C, whereas reaches receive additional C inputs over time.

      Litter in the litter bags have a higher concentration of carbon than the stream, which has carbon more spread out. The litter will have higher loss of carbon but generally represents reach-scales.

    7. We conducted two manipulative experiments at large spatial and temporal scales and focused our measurements on forest-derived leaf litter, because it is the most biologically active pool of terrestrial C in forest streams and is renewed annually (7).

      Two experiments were done separately to test the effects of nitrogen to phosphorus ratios on streams.

      Pre-treatment of streams include recording the levels of nutrients and typical conditions throughout a year.

      The first experiment had two watersheds with one being the control and the other having an addition of nitrogen and phosphorus to match a ratio that was decided by the scientists.

      The second experiment was done on five streams with different combinations of the nitrogen and phosphorus ratio.

    8. not been previously assessed in response to human-influenced stressors

      Although this experiment focuses on microbial and fungal effects on streams, humans sometimes also have an impact.

      These effects may include the leaking of septic tanks into bodies of water that increase human waste and phosphorus levels. Fishing and polluting also affect stream ecosystems.

    9. We measured the response of terrestrial C loss rates in whole 70- to 150-m stream reaches (tables S1 and S2).

      The experiments were conducted on streams in the Appalachian Mountains of North Carolina.

      Because of the elevation, there are little to no fish influencing the data. Mainly microbes and fungi influence the nutrient levels of the streams.

    10. flow-proportional nitrogen (N) and phosphorus (P)

      An irrigation line was used along the 70-150 meter streams to pump in liquid nutrients. The nutrients were pumped proportional to the flow of the water.

    1. using primers specific to the cDNA encoding each of these proteins, we performed RT-PCR on 7 tissues of the adult host, including those that are and those that are not dedicated to light modulation

      Using reverse transcription polymerase chain reaction (RT-PCR), the authors amplified sequences for the genes coding for opsin, arrestin, and rhodopsin kinase (RK). Transcripts were extracted from the tissues of the light organ, eye, gills, mantle, tentacle, and arm.

    2. To determine whether they also co-localize in light-organ tissues, we applied 2 independent analyses of these 3 components: localization of message by PCR and of protein by immunocytochemistry.

      The authors used two methods to discover if opsin, arrestin, and rhodopsin kinase also occur in the light organ.

      In the first method (message expression), the authors looked for the molecular signals of these proteins in tissues from the light organ, eye, gills, mantle, tentacle, and arm.

      In the second method (immunocytochemistry), the authors looked for evidence of protein production in the tissues of the light organ using confocal microscopy.

    1. A GWAS analysis with linear mixed models, controlling for age, sex, and genetic relatedness (9), identified four regions with multiple significant associations

      The authors do a Genome-Wide Association Study (GWAS) analysis, which is a study of whether any particular loci in the genome are associated with a particular phenotype (in this case, skin pigmentation levels).

      GWAS analyses look at variants (alleles) across the whole genome, rather than focusing only on regions that are thought to be associated with a phenotype. This way, new regions of the genome can be discovered as being involved in the genetic architecture of a trait.

      The authors control for age, sex, and genetic relatedness, because these are variables that could confound (confuse) the results by affecting the phenotype of interest, in this case skin pigmentation. To avoid confusion, the authors take these variables into account when they look for associations between SNPs and skin pigmentation.

    2. using the Illumina Infinium Omni5 Genotyping array

      The authors used the Illumina Infinium Omni5 Genotyping array, a specific type of SNP array.

      The array has a set of oligos (short stretches of single-stranded DNA) on a chip that is complementary to the DNA right next to the SNP of interest. DNA taken from the person being genotyped gets broken up into small pieces and put on the chip, where it will stick to the complementary oligo.

      Next, nucleotides (A, C, G, T) labeled with different color dyes get put on the chip and will bind to the DNA that is attached to the oligos. A scanner reads what color is found at each spot on the chip, which tells the investigator what nucleotide the person has at that locus—which is also known as what allele the person has.

    3. To estimate the proportion of pigmentation variance explained by the top eight candidate SNPs at SLC24A5, MFSD12, DDB1/TMEM138 and OCA2/HERC2, we used a linear mixed model with two genetic random effect terms, one based on the genome-wide kinship matrix, and the other based on the kinship matrix derived from the set of significant variants.

      The authors estimate how much pigmentation variation can be explained by their top predicted variants.

      A mixed model has both fixed effects and random effects. In this case the authors looked at random effect terms based on looking at the whole genome as well as looking at only variants that were identified as significant. The mixed model gives an estimation of how much each of the variants contributes to skin pigmentation in their study.

    4. We do not detect evidence for positive selection at MFSD12 using Tajima’s D

      Directional selection occurs when one trait is favored over others, leading to a shift in allele frequency toward the allele associated with the favored trait. This also leads to an excess of low-frequency alleles, and a negative value of Tajima's D.

      Balancing selection is a process by which multiple alleles are maintained in the population, for example when heterozygotes are at an advantage (which keeps both of their alleles at a relatively high frequency). This leads to a lack of rare alleles, and a positive Tajima's D.

      Tajima's D statistic of approximately zero indicates that the population is evolving with little or no selection.

    5. luciferase expression assays

      The luciferase expression assay is also known as the luciferase reporter assay, and is a method to detect how much expression can be driven by a particular enhancer.

      The assay is described in detail here: https://bitesizebio.com/10774/the-luciferase-reporter-assay-how-it-works/. Briefly, the authors put DNA that corresponds to the predicted, potentially causal regulatory regions into a vector that also has the luciferase gene, and then put this vector into cells. In this experiment, the authors use WM88 melanoma cells, which are a cell line grown from a patient who had melanoma.

      The luciferase gene will only get expressed (and the luciferase protein made) if the regulatory region ahead of it gets expressed in these cells. To detect whether there is luciferase in the cells, the authors break open the cells to release their proteins, add additional reagents that interact with luciferase (if it is present), and use a detector to see how much light gets emitted. More light emitted means more luciferase was present, which means that there was more expression being driven by the regulatory region.

    6. CRISPR/Cas9 was used to generate a Mfsd12 null allele in a wild-type mouse background

      The authors extend their previous experiments in mouse cells to make mice that are missing Mfsd12 in all of their cells.

      They use CRISPR/Cas9 to make a null allele of the gene, which is a nonfunctional copy of a gene due to genetic mutation. They do this in mice that are otherwise wild-type, or have typical genetic and phenotypic characteristics.

    7. We silenced expression of the mouse ortholog of MFSD12 (Mfsd12) using small hairpin RNAs (shRNAs) in immortalized melan-Ink4a mouse melanocytes derived from C57BL/6J-Ink4a−/−mice

      In this experiment, the authors use a genetic tool called shRNA (small hairpin RNAs) to turn off expression of the gene in mice that is homologous to one of the genes they identified in the previous section as being associated with skin pigmentation. An ortholog is a homologous gene from a different species.

      An shRNA is an artificial RNA molecule that is shaped like a hairpin—a strand with a tight turn as it folds back on itself. shRNAs are processed by mammalian cells into small interfering RNAs (siRNAs), which suppress gene expression of a particular gene that it is complementary to—in this case, the authors use shRNA that will silence the gene Mfsd12.

    8. using local imputation of high coverage sequencing data from a subset of 135 individuals and data from the Thousand Genomes Project (TGP)

      To perform fine-mapping, the authors need more data than they have from their SNP arrays. To get more precise data, they performed full-coverage sequencing of a small subset of people from their original populations, sequencing only the regions of the genome they identified with the GWAS. Sequencing allows researchers to discover the order of nucleotides across a given region of the genome.

      The authors also used previously published work from a data set called the Thousand Genomes Project, which looked at the sequences of the whole genome for over 1000 people.

      Local imputation uses patterns of association between SNPs in the data sets with higher coverage, as well as known patterns of linkage disequilibrium (nonrandom association of alleles in a particular population) between SNPs, to predict what alleles a person has at those regions. This means that it is possible to confidently predict the alleles for each of the >1500 people in the current study, even for loci with SNPs that aren't included in the original genotyping array.

    9. We then performed fine-mapping

      The authors use fine-mapping to narrow down the larger regions identified in their GWAS results, allowing them to identify specific SNPs that are likely to be causal, so they can study these SNPs further. Fine-mapping uses a variety of methods to pinpoint the precise location of a gene or regulatory region that is associated with variation in a phenotype.

    10. We genotyped 1,570 African individuals with quantified pigmentation levels

      The authors determined the genotypes (the set of alleles in an organism's genome) of the people for whom they had quantified skin pigmentation.

      They use a SNP array for genotyping, which is a tool that allows researchers to study small differences between genomes. A SNP (pronounced "snip") is a single nucleotide polymorphism, or a change to a single base (nucleotide) at a particular DNA locus.

    11. To identify genes affecting skin pigmentation in Africa, we used a DSM II ColorMeter to quantify light reflectance from the inner arm as a proxy for melanin levels in 2,092 ethnically and genetically diverse Africans living in Ethiopia, Tanzania, and Botswana

      The authors wanted to study a wide variety of Africans, and used a handheld battery operated tool called the DSM II ColorMeter to get a quantification of how much pigment was in each person's skin.

      The DSM II ColorMeter works by shining light at skin and detecting how much light reflects back, and at what wavelengths. They used a particular wavelength to determine how much melanin was present in the skin.

    12. Exome sequencing of an archived gr/gr DNA sample, subsequently confirmed by Sanger sequencing in an independent colony,

      The authors look at the exome (all of the protein coding parts of the genome) by gene sequencing, to see what differences exist between gr/gr mice that are gray and wild-type mice with the usual agouti color.

      They sequence a saved sample they had, and confirm that they can find the same mutation in a gr/gr mouse from a different colony, to be sure that the mutation they found in Mfsd12 wasn't a random mutation that arose in their colony.

      For confirmation of the mutation, they use Sanger sequencing of the specific region around the mutation. Sanger sequencing is a method of sequencing shorter pieces of DNA, instead of the whole exome.

    13. We targeted transmembrane domain 2 (TMD2) in the highly conserved zebrafish ortholog of mfsd12a with CRISPR/Cas9

      Here, the authors investigate the effect of losing the zebrafish ortholog of MFSD12 by using a technique called CRISPR/Cas9.

      Cas9 is an enzyme that cuts DNA, and is guided to particular DNA sequences by a guide RNA (gRNA). Researchers can use different gRNAs to make cuts to particular DNA regions in order to disrupt expression of genes.

      The authors use CRISPR/Cas9 with gRNAs targeting the part of the zebrafish ortholog mfsd12a that spans the cell membrane so that the protein will no longer function properly. They then examined the zebrafish for what impact the knockdown of the gene has had, if any.

    14. We assessed the localization of human MFSD12 isoform c (RefSeq NM_174983.4) tagged at the C terminus with the HA epitope (MFSD12-HA). By immunofluorescence microscopy,

      The authors look for what part of the cell the MFSD12 protein they're interested in is located. To find the protein, they first "tag" it at the C terminus with an HA epitope.

      The C terminus is the end of the protein. Tags are often put on the end of the protein because in some cases they are less likely to interfere with expression or function if they're at the end.

      HA stands for human influenza hemagglutinin, which is a protein on the surface of human cells. A particular part of it, the HA epitope, can be used to tag proteins in cells because it's small, so it's unlikely to interfere with protein function or location.

      An epitope is a part of a protein that is recognized by an antibody, which can be bound to fluorescent molecules so it can be visualized by a technique called immunofluorescence microscopy.

    15. Analyses of gene expression using RNA-sequencing data from 106 primary melanocyte cultures

      RNA-sequencing, or RNA-seq for short, is a method to quantify the amount of specific sequences of RNA in a sample.

      To perform RNA-seq, the authors extracted the RNA from primary melanocyte cultures (melanocytes growing in a dish after being taken from human skin). Next they made complementary DNA, or cDNA, that corresponds to each RNA fragment from the cells. The more RNA there is for a particular gene, the more cDNA there will be.

      Then, the authors sequence the cDNA, and determine how many times they detect each molecule of cDNA. The number of times they see each cDNA (the number of reads) corresponds to how much RNA for that gene was in the sample, and the authors compare the amount of RNA for different genes in different groups of people from whom they collected melanocytes.

    16. We ranked potential causal variants within each locus using CAVIAR

      Next, the authors ranked the known and predicted variants using a method called CAVIAR (CAusal Variants Identification in Associated Regions). CAVIAR is a statistical method used to determine the likely DNA variants causing differences in a trait. This method is better than previous methods used to determine causal variants, because it allows for the idea that there may be multiple causal variants in a region. This is likely to be the case for many traits, possibly including skin pigmentation.

    17. Association tests using a permutation approach indicated that, of the 35 protein-coding genes with a transcription start site within 1Mb of rs7948623, expression of DDB1 is most strongly associated with a SNP in an intron of DDB1, rs7120594, at marginal statistical significance after correction for ancestry and multiple testing (Padj = 0.06

      The authors use a statistical approach to determine which gene within 1 Mb (1 million basepairs) of a variant of interest, rs7948623, has expression levels most strongly associated with the variant.

      1 Mb is used as the distance to look for genes within because most regulatory regions act on genes that start within 1 Mb.

    18. Allele-specific expression (ASE) analysis

      The authors use allele-specific expression (ASE) analysis, a method to determine how much expression occurs from each allele at a particular locus in an individual.

      ASE looks at the amount of RNA that gets transcribed from each copy of a gene (the copy inherited from the mother and the copy inherited from the father).

      The authors use this analysis to determine whether people who are heterozygous for the allele of interest (people who have different variants in their two copies of the allele) have different levels of expression from the two copies of the gene, which would indicate that this particular variant could affect the expression level directly.

    1. The resulting database contained 4140 individuals and over 2500 herbarium vouchers.

      These numbers refer to the total sample size in the experiment.

    2. We therefore stratified our study design such that each habitat was sampled once within each of the six combinations of two topographic positions (hilltop and slope) and three taxonomic blocks, for a total of 18 samples.

      In statistics, stratification allows a researcher to divide entire populations in to subgroups.

      The authors divide the data set into hilltop and slope, and 3 differently identified groups.

    3. Paracou experimental site (5°18′N, 52°55′W), a lowland tropical rain forest near Sinnamary, French Guiana (Gourlet-Fleury et al. 2004)

      The Paracou experimental site is located near the Paracou Field Station in French Guiana.

      Read more about the field station at: https://paracou.cirad.fr/station/overview

    4. (i) How does logging disturbance affect tropical tree community structure, in terms of diversity, evenness and composition? (ii) How do the taxonomic and functional responses of tree communities to logging differ? (iii) What guidelines can we give to timber harvesters to improve biodiversity conservation in selectively logged forests?

      The objective of the study is to address whether logging affects the forest species; is there a difference between what types of species and what each species contributes to the community when logged; and how this information can be used to improve how the forest is logged.

    1. We performed a x2 test on the proportions of individuals with the A or B chloroplast haplotype per site (table 1) to verify that our type designations, which were classified according to the results of the Williams studies (Williams et al. 2005, 2007) and following their site locality sampling, were correct.

      Geiger et al. utilized the Pearson's chi-squared test (χ2), a statistical test applied to sets of categorical data to evaluate how likely it is that any observed difference between the sets arose by chance, to conclude the accuracy of the type designations given.

    1. homozygosity mapping provides an important approach to dissect this heterogeneity

      Families that share a larger part of their genome are more likely to be homozygous for certain genes. Studying these families can make it easier to identify and isolate the effects of certain genes.

    2. we sequenced NHE9 in other patients with autism and epilepsy

      The authors compared the genotypes of patients who have both autism and epilepsy to determine if these patients had similar mutations to NHE9 and surrounding genes.

    3. binomial test

      A statistical measure of the probability that experimental results are due to chance. It is calculated by looking at the difference between the observed (experimental) results and the expected results (i.e. the results that would be expected if only chance were involved).

      The results of the test are reported as a P value, which is a probability. In general, a P of less than 0.05 means that the results of an experiment are statistically significant (and not a result of chance).

    4. neuronal membrane depolarization by elevated KCl

      This technique is used to study enhanced neuronal activity that may result from changes in gene expression.

      Elevated KCl (an increase in potassium outside the cell) results in a sustained depolarized state in three ways:

      1. Normally, potassium ions flow out of the cell, resulting in hyperpolarization. Elevated KCl outside the cell disrupts this gradient and slows the outward flow of potassium. At the same time potassium ions are flowing out of the cell, sodium ions are flowing into the cell. The flow of sodium ions into the cell does not slow down.
      2. The increase in the cell's membrane potential (the difference in charge on one side of the membrane versus the other) causes sodium channels to open. This allows more sodium ions into the cell and results in further depolarization.
      3. Partial activation of sodium ion channels prevents the neuron from triggering a full action potential.
    5. hippocampal neurons

      The hippocampus is a major component of the human brain and those of other vertebrates. It is part of the limbic system and has a crucial role in the consolidation of information, including short- and long-term memory and spatial navigation.

      Rat and mouse hippocampal neurons are widely used in neurobiological studies. By isolating and growing individual neurons, researchers are able to analyze properties related to cellular trafficking, cellular structure, and individual protein localization.

    6. microarray screens

      An array is a grid of DNA samples that is used to identify and map genes.

      In this experimental setup, the cDNA derived from the mRNA of known genes is immobilized. The expression pattern is then compared to the expression pattern of a gene responsible for a disease.

      https://www.youtube.com/watch?v=pWk_zBpKt_w

    7. independently identified

      Because the three genes were identified by independent screens, it increases the reliability of the authors' conclusions.

    8. screens

      A technique used to detect a mutation or abnormality and provide important information on its function. In this case, the authors screened for genes associated with autism.

      There are many different types of screens depending on a researcher's needs, and they are widely used in scientific research.

    9. two sensitive methods for detecting them

      Both the single nucleotide polymorphism array and BAC Comparative Genomic Hybridization arrays are used to detect the number of copies of a specific locus in a subject's DNA. This allows us to find out whether the locus is present on one or both chromosomes of a subject.

      To do this, control DNA and experimental DNA are labeled with different fluorescent molecules of different colors (in the picture below, the control is red and the experimental is green).

      If the experimental DNA and the control DNA are identical (i.e. the target variant is present on both chromosomes), the sample will appear orange. If the control DNA has deletions, the solution will appear red. It it has insertions, it will appear green.

    10. we reasoned that a prominent involvement of autosomal recessive genes in autism would be signaled by differences in the male-to-female (M/F) ratio of affected children in consanguineous (related) versus nonconsanguineous marriages (although recessive causes of autism may still retain some gender-specific difference in penetrance)

      Based on studies of other neurological birth defects, the authors hypothesized that differences between consanguineous and non-consanguineous families in the M/F ratio of affected children would suggest that autosomal recessive genes play a large part in incidence.

    11. The Homozygosity Mapping Collaborative for Autism (HMCA) (21) has recruited 104 families (79 simplex and 25 multiplex) from the Arabic Middle East, Turkey, and Pakistan (table S1 and fig. S1), of which 88 pedigrees (69 simplex and 19 multiplex) have cousin marriages (i.e., parental consanguinity).

      The authors selected families with one or more individuals affected by autism.

      Among those families, about half have cousin marriages, which are referred to as consanguineous pedigrees.

      A simplex family is one in which there is only one person with autism. A multiplex family has multiple people with autism.

    12. Reliability between clinician assessments was high

      In order to ensure that the results obtained from this study are reliable, the authors ensured that all of the teams were using the same clinical protocol in the same way.

    13. homozygosity mapping

      To improve the quality of results, the authors chose consanguineous families (families that share a very recent ancestor), because of their high risk of having autistic children.

      Researchers at Johns Hopkins University reasoned that families with multiple females with autism must have special genetic variants for autism that can be more easily identified than when comparing other groups.

      For more information, see the Hub at Johns Hopkins.

    14. de novo

      In this article, the authors focus on patients who inherited long deletions or additions from their parents.

      However, this is not the only approach to understanding the genetics of autism. Some look directly at the appearance of de novo single nucleotide polymorphisms (mutations to a single base).

    1. Table 4. Proboscis measurements (mean and standard error) for flower visitors to A. berteroi. Proboscis width and length with the same letters are not significantly different with Tukey comparisons.

      In this table, the author describes how the width and length of the insects proboscis play a role in pollination.

      This chart was made to determine the differences in proboscis.

    2. We then used monofilament nylon fishing line of four different diameters (4 lb, 0.20 mm diameter; 6 lb, 0.23 mm diameter; 8 lb, 0.28 mm diameter and 25 lb, 0.53 mm diameter) inserted into single flowers to simulate flower visits.

      Fishing line was used to simulate repeatedly the collecting of nectar. This could then be used to see which line (stand-in for proboscis) collected the most pollen, and if it correlated with thickness.

    3. Table 1. Flower visitors of A. berteroi observed in the study sites, and presence/absence of pollen on the proboscis.

      In this table, the author describes various interactions the visitor encountered with plants.

    4. Angadenia berteroi bears large, showy, yellow, tubular flowers. They have the typical complex floral arrangement

      This species that will be studied shows complex floral arrangements.

    1. The Homozygosity Mapping Collaborative for Autism (HMCA) (21) has recruited 104 families (79 simplex and 25 multiplex) from the Arabic Middle East, Turkey, and Pakistan (table S1 and fig. S1), of which 88 pedigrees (69 simplex and 19 multiplex) have cousin marriages (i.e., parental consanguinity)

      The authors selected families with one or more individuals affected by autism.

      Among those families, about half have cousin marriages, which are referred to as consanguineous pedigrees.

      A simplex family is one in which there is only one person with autism. A multiplex family has multiple people with autism.

    1. we tested six sgRNAs targeting enhanced green fluorescent protein (EGFP)

      The authors used sgRNAs to target enhanced green fluorescent protein (EGFP) cells.

      The EGFP cells allow the cell to express fluorescent color. sgRNAs target these cells and destroy them. In cells where the sgRNA removed the EGFP gene, there is no fluorescent color.

  7. Mar 2018
    1. The two known populations of this species were included in our study, and we sampled 18–30 individuals per population (Table 1). All of the individuals (18) from the Dominican Republic population were included in the analyses. Leaf material was fast dried in the field using Drierite (W. A. Hammond Drierite Co. Ltd., Xenia, Ohio, USA), subsequently this material was used for DNA isolations using the DNeasy Mini Plant kit (QIAGEN, Venlo Limburg, The Netherlands).

      For the first part of their experiment, the authors gathered samples of 18-30 plants from two known populations of C. jimenezii. They then dried the leaf material of the Dominican Republic sample, using Drierite (an all-purpose drying agent most commonly used in storage spaces as it dries the air in the atmosphere). The DNA from these populations was isolated from the dried material using the DNeasy Mini Plant kit; the procedure was similar to the one described in the following video https://www.youtube.com/watch?v=rY-Qbrw9KMc

    2. The high levels of genetic differentiation detected within C. jimenezii raise questions whether these two populations can be treated as different varieties/subspecies

      In this study, the researchers found some questions as to whether the two species of C. jimenezii could be grouped with the same taxa.

      The authors used molecular tools which have found a large amount of differentiation. This was not what the authors hoped and in turn it was concluded that they were to remain in separate taxa.

    3. Fig 2. Principal coordinate and STRUCTURE (K = 2) analyses of DNA microsatellite data for the two known populations of Coccothrinax jimenezii. The scatter diagram shows PCO values along the first two coordinates with their respective percentages of variance. Inset in upper right corner shows results yielded by STRUCTURE. Color and box sizes indicate the cluster type of each individual and the number of plants sampled per site. The vertical lines indicate the probability that each individual belongs to an inferred cluster. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

      This figure describes the 2 populations of Coccothrinax Jimenezii and it shows the results that are yielded by the processing computer software called STRUCTURE that is used for analysis of microsattelites.

    4. The Bayesian clustering program STRUCTURE v.2.3.4

      In this experiment the authors used The Bayesian clustering program STRUCTURE v.2.3.4 as a way to estimate the underlying genetic structure among populations.

    5. A Monte Carlo Markov chain method was applied with 100,000 iterations, a burn-in of 10,000 and the significance level set at P < 0.001. Principal coordinate analysis (PCO) among all the individuals included in our study was computed with GenAlEx based on the algorithm developed by Orloci (1978) after conversion of the individual-by-individual genetic distance matrix, as defined by Smouse and Peakall (1999), to a covariance matrix and data standardization.

      This experiment was conducted with the purpose of producing a scatter diagram that summarized the original multidimensional data set and revealed the presence of groups. They also used GenAIEx to analyze the principal coordinate among all individuals in the study. This experiment also allowed them to detect the genetic structure of populations projected in a continuous space.

    6. Tests for Hardy–Weinberg Equilibrium (HWE) and the U test (Rousset and Raymond, 1995) for heterozygote excess or deficiency were run with GenePop v. 4.2 (Raymond and Rousset, 1995, 2008) using 10,000 Monte Carlo Markov chain iterations (Guo and Thompson, 1992).

      This experiment was done with GenePop v. 4.2 using 10,000 Monte Carlo Markov chain interactions. Throughout this experiment the researcher tested for Hardy–Weinberg Equilibrium, which says that the genotype frequencies in a population tend to remain constant throughout generations if no evolutionary influences are present. They also used GenePop v.4.2. to do a U test and to look for heterozygote excess or deficiency.

    7. The program Micro-Checker v. 2.2.3 (Van Oosterhout et al., 2004) was used to evaluate the presence of null alleles and allelic dropouts, employing 3000 randomizations. Descriptive statistics

      This experiment was carried out with the purpose of identifying null alleles which are those that express the same trait whether they are homozygous or heterozygous, and allelic dropouts which are copies of a locus that are not amplified by the primer. This part of the experiment was completed through the use of Micro-Checker v. 2.2.3.

    8. PERL script program PAL_FINDER_v0.02.03 to identify potential 4 bp microsatellite repeat elements among the reads (Castoe et al., 2012; Slashdot Media, San Jose, California, USA). Among these SSR loci we selected six that cross-amplified with samples of C. jimenezii and that were polymorphic with different samples of this species.

      This experiment was conducted using the PERL script program PAL_FINDER v0.02.03 and the 100bp Illumina sequences from the previous experiment. This experiment resulted in the identification of potential 4bp microsatellite repeat elements. Of these microsatellite repeats, only six were selected which had different phenotypes than C.jimenezii.

    1. he peptide was a mixture of phosphorylated and unphosphorylated serine in position #357, so that antibodies might be generated to both the activated and non-activated forms of the molecule

      Proteins in the phototransduction cascade can be in either an "on" (activated) or "off" (inactivated) state. The authors created antibodies to bind to either state to ensure that they would be able to detect the protein regardless of what form it was in.

    2. Using the cDNA sequences, we first used NCBI BLASTX analyses to identify the closest matches to the derived amino acid sequences

      Basic Local Alignment Search Tool (BLASTX) is a search algorithm developed by the National Center for Biotechnology Information (NCBI)

      For more information about BLASTX, go to: NCBI: BLAST

    3. RACE primers (Table S2) were constructed from the EST sequences identified as having similarity to a transcript of interest.

      Primers are short, single-stranded sequences of DNA used to amplify RNA sequences of interest using polymerase chain reaction (PCR). Amplifying a sequence means exponentially increasing the number of copies.

    4. Retinal tissues of E. scolopes were used as a positive control for the cross reactivity of these antibodies in regions known to produce these proteins

      A positive control is used to verify that your experiment is working the way you want.

      In this study, the authors tested their immunocytochemical test by using it on tissues that they already knew contained the three proteins.

    5. we used antibodies raised against cephalopod opsin, arrestin, and rhodopsin kinase (25, 26) to localize the protein in host tissues.

      The authors created antibodies against the three proteins so they could detect them in specific tissues using immunocytochemistry.

      They incubated squid eyes and light organs with the antibodies and stained with secondary antibodies that were tagged with a fluorescent molecule.

      The stained eyes and light-organs were mounted on microscope slides and viewed with a confocal microscope. A fluorescent signal identified the presence of the proteins.

    6. we performed electroretinograms (ERGs) (21, 22), which extracellularly record photoreceptor membrane potential, of both eyes and light organs of juvenile E. scolopes.

      Electroretinograms (ERGs) measure the change in voltage across cells when exposed to a light stimulus. The authors compared the response of photoreceptive tissues in both the eyes and light organs of juvenile Euprymna.

      Electrical signals of rhabdomeric photoreceptors typically respond by depolarizing, that is, becoming more negative.

      Electrical signals of ciliary photoreceptors typically respond by hyperpolarizing, that is becoming less negative.

    7. We identified 11 such cDNAs (Fig. 2; Table S1), including the gene encoding the visual pigment opsin itself, as well as molecules involved in subsequent activation and deactivation of the cascades.

      The authors looked for evidence that the light organ produces proteins similar to those found in the eye that could generate a phototransduction cascade.

      The authors identified 11 sequences that code for proteins similar to those responsible for phototransduction in the eye.

    8. tissues that modulate the intensity and direction of symbiont light emission

      The authors determined that light organs have tissues that are similar to the eye: a lens that is able to focus light, reflective tissue that is able to reflect light, and an iris that can control the amount of light entering or leaving the light organ.

    1. Much greater variation is associated with differences among species within a taxonomic group than between taxonomic groups (Fig. 2 and table S2)

      The latitudinal range shift variation among species within four typical taxonomic groups was evaluated in Figure 2. This was compared to the overall variation among all the latitude taxonomic groups in the meta-analysis.

      The authors also calculated the percentage of species in each taxonomic group which moved in a direction opposite to that expected based on temperature change.

    2. nearly as many studies of observed latitudinal changes fall above as below the observed = expected line in Fig. 1A

      If species are tracking climate change, then the observed range shifts should equal the expected range shifts. The authors did a chi-square (goodness-of-fit) statistical test to measure how well this 1:1 relationship describes the data.

    3. To estimate the expected shifts, we calculated the distances in latitude (kilometers) and elevation (meters) that species in a given region would have been required to move to track temperature changes and thus to experience the same average temperature at the end of the recording period as encountered at the start (18) (table S1)

      This correlation test examined the relationship between observed range shifts and expected range shifts (based on temperature change patterns).

      For an explanation of how the expected range shifts were calculated, please see the notes for Table S1.

    4. mean latitudinal shift versus average temperature increase

      The authors conducted a statistical correlation test to determine if there is a linear correlation (relationship) between range shifts and temperature changes.

    5. whereas the rates of range shift that we found were significantly greater [N = 22 species groups × regions, one-sample ttest versus 6.1 km decade−1, t = 3.99, P = 0.0007 for latitude; N = 30 groups × regions, one-sample t test versus 6.1 m decade−1, t = 3.49, P = 0.002 for elevation

      The authors did a one-sample t test to compare their range shift rates to those in Reference 14.