This module utilizes a user-friendly database exploring data selection, box-and-whisker plot, and correlation analysis. It also guides students on how to make a poster of their data and conclusions.

The BOREAS TE-09 team collected several data sets related to chemical and photosynthetic properties of leaves. This data set contains canopy biochemistry data collected in 1994 in the NSA at the YJP, OJP, OBS, BS and OA sites including biochemistry lignin, nitrogen, cellulose, starch, and fiber concentrations. These data were collected to study the spatial and temporal changes in the canopy biochemistry of boreal forest cover types and how a high-resolution radiative transfer model in the mid-infrared could be applied in an effort to obtain better estimates of canopy biochemical properties using remote sensing.

This web mapping application shows the monitoring networks used to track drought conditions across Manitoba. Each tab displays a different source of data, including: streamflow and water level, groundwater, precipitation, reservoir supply status, and Canadian and United States Drought Monitor contours. Each of the data sources are explained in more detail below. Please note the following information when using the web mapping application: When you click on a data point on the River and Lake, Groundwater or Reservoir maps, a pop-up box will appear. This pop-up box contains information on the streamflow (in cubic feet per second; ft3/s), water level (in feet), groundwater level (in metres), storage volume (acre-feet), or supply status (in per cent of full supply level; %) for that location. Click on the Percentile Plot link at the bottom of the pop-up box to view a three-year time series of observed conditions (available for river and lake and groundwater conditions only). A toolbar is located in the top right corner of the web mapping application. The Query Tool can be used to search for a specific river, lake or reservoir monitoring station by name or aquifer type by location. The Layer List enables the user to toggle between precipitation conditions layers (1-month, 3-month, and 12-month) and increase or decrease the transparency of the layer. Data is current for the date indicated on the pop-up box, percentile plot, or map product. Near-real time data are preliminary and subject to change upon review. River and lake conditions are monitored to determine the severity of hydrological dryness in a watershed. River and lake measurements are converted to percentiles by comparing daily measurements from a specified day to historical measurements over the monitoring station’s period of record for that particular day. A percentile is a value on a scale of zero to 100 that indicates the percent of a distribution that is equal to or below it. In general: Streamflow (or lake level) which is greater than the 90th percentile is classified as “much above normal”. Streamflow (or lake level) which is between the 75th and 90th percentile is classified as “above normal”. Streamflow (or lake level) which is between the 25th and 75th percentiles is classified as “normal”. Streamflow (or lake level) which is between the 10th and 25th percentile is classified as “below normal”. Streamflow (or lake level) which is less than the 10th percentile is classified as “much below normal”. "Median" indicates the midpoint (or 50th percentile) of the distribution, whereby 50 per cent of the data falls below the given point, and 50 per cent falls above. Other flow categories include: "Lowest" indicates that the estimated streamflow (or lake level) is the lowest value ever measured for the day of the year. "Highest" indicates that the estimated streamflow (or lake level) is the highest value ever measured for the day of the year. Monitoring stations classified as “No Data” do not have current estimates of streamflow (or lake level) available. Click on the Percentile Plot link at the bottom of the pop-up box to view a graph (in PDF format) displaying a three-year time series of observed conditions relative to the historical percentiles described above. The period of record used to compute the percentiles is stated, alongside the station ID, and if the river or lake is regulated (i.e. controlled) or natural. Hydrometric data are obtained from Water Survey of Canada, Manitoba Infrastructure, and the United States Geological Survey. Near real-time data are preliminary as they can be impacted by ice, wind, or equipment malfunction. Preliminary data are subject to change upon review. Groundwater conditions are monitored to determine the severity of hydrological dryness in an aquifer. Water levels are converted to percentiles by comparing daily measurements from a specified day to historical measurements over the monitoring station’s period of record for that particular day. A percentile is a value on a scale of zero to 100 that indicates the percent of a distribution that is equal to or below it. In general: A groundwater level which is greater than the 90th percentile is classified as “much above normal”. A groundwater level which is between the 75th and 90th percentile is classified as “above normal”. A groundwater level which is between the 25th and 75th percentiles is classified as “normal”. A groundwater level which is between the 10th and 25th percentile is classified as “below normal”. A groundwater level which is less than the 10th percentile is classified as “much below normal”. Monitoring stations classified as “No Data” do not have current measurements of groundwater level available. "Median" indicates the midpoint (or 50th percentile) of the distribution, whereby 50 per cent of the data falls below the given point, and 50 per cent falls above. Click on the Percentile Plot link at the bottom of the pop-up box to view a graph (in PDF format) displaying a three-year time series of observed conditions relative to the historical percentiles described above. The period of record used to compute the percentiles is stated, alongside the station ID. Precipitation conditions maps are developed to determine the severity of meteorological dryness and are also an indirect measurement of agricultural dryness. Precipitation indicators are calculated at over 40 locations by comparing total precipitation over the time period to long-term (1971 – 2015) medians. Three different time periods are used to represent: (1) short-term conditions (the past month), (2) medium-term conditions (the past three months), and (3) long-term conditions (the past twelve months). These indicator values are then interpolated across the province to produce the maps provided here. Long-term and medium-term precipitation indicators provide the most appropriate assessment of dryness as the short term indicator is influenced by significant rainfall events and spatial variability in rainfall, particularly during summer storms. Due to large distances between meteorological stations in northern Manitoba, the interpolated contours in this region are based on limited observations and should be interpreted with caution. Precipitation conditions are classified as follows: Per cent of median greater than 115 per cent is classified as “above normal”. Per cent of median between 85 per cent and 115 per cent is classified as “normal”. Per cent of median between 60 per cent and 85 per cent is classified as “moderately dry”. Per cent of median between 40 per cent and 60 per cent is classified as a “severely dry”. Per cent of median less than 40 per cent is classified as an “extremely dry”. Precipitation data is obtained from Environment and Climate Change Canada, Manitoba Agriculture, and Manitoba Sustainable Development’s Fire Program. Reservoir conditions are monitored at 15 locations across southern Manitoba to track water availability, including possible water shortages. Conditions are reported both as a water level and as a “supply status”. The supply status is the current amount of water stored in the reservoir compared to the target storage volume of the reservoir (termed “full supply level”). A supply status greater than 100 per cent represents a reservoir that is exceeding full supply level. Canadian and U.S Drought Monitors: Several governments, agencies, and universities monitor the spatial extent and intensity of drought conditions across Canada and the United States, producing maps and data products available through the Canadian Drought Monitor and United States Drought Monitor websites. The Canadian Drought Monitor is managed through Agriculture and Agri-Food Canada, while the United States Drought Monitor is a joint effort between The National Drought Mitigation Centre (at the University of Nebraska-Lincoln), the United States Department of Agriculture, and the National Oceanic and Atmospheric Administration. The drought monitor assessments are based on a suite of drought indicators, impacts data and local reports as interpreted by federal, provincial/state and academic scientists. Both the Canadian and United States drought assessments have been amalgamated to form this map, and use the following drought classification system: D0 (Abnormally Dry) – represents an event that occurs every 3 - 5 years; D1 (Moderate Drought) – 5 to 10 year event; D2 (Severe Drought) – 10 to 20 year event; D3 (Extreme Drought) – 20 to 50 year event; and D4 (Exceptional Drought) – 50+ year event. Additionally, the map indicates whether drought impacts are: (1) short-term (S); typically less than six months, such as impacts to agriculture and grasslands, (2) long-term (L); typically more than six months, such as impacts to hydrology and ecology, or (3) a combination of both short-term and long-term impacts (SL). The Canadian Drought Monitor publishes its assessments monthly, and United States Drought Monitor maps are released weekly on Thursday mornings. The amalgamated map provided here will be updated on a monthly basis corresponding to the release of the Canadian Drought Monitor map. Care will be taken to ensure both maps highlight drought conditions for the same point in time; however the assessment dates may differ between Canada and the United States due to when the maps are published. Please click on an area of drought on the map to confirm the assessment date. Canadian Drought Monitor data are subject to the Government of Canada Open Data Licence Agreement: https://open.canada.ca/en/open-government-licence-canada. United States Drought Monitor data are available on the United States Drought Monitor website: https://droughtmonitor.unl.edu. For more information, please visit the Manitoba Drought Monitor website.

Ceptometer data from a Decagon AccuPAR (Model PAR-80) were collected at four sites in Botswana during the SAFARI 2000 Kalahari Transect Wet Season Campaign (March, 2000). These sites include Maun, Pandamentanga, Ghanzi/Okwa River Crossing, and Tshane. The measurements were taken near stake flags placed at 25 m intervals along three parallel 750 m transects located 250 m apart. The ceptometer contains 80 photosynthetically active radiation (PAR) sensors fixed at 1 cm intervals along a wand and connected to a control box. The sampling protocol followed in general was to first measure above canopy incident PAR, then canopy reflected PAR, then above canopy incident PAR again, and finally, canopy transmitted PAR. The data can be used to compute fraction of photosynthetically active radiation (FPAR), intercepted PAR, leaf area index (LAI), and gap fraction. These data currently exist in raw format, but can be processed using manufacturer-provided software to estimate the derived products.The data are stored as ASCII files, in csv format, organized by site, with one file per transect. Incident, transmitted, and reflected PAR radiation values for a transect and site are in the same file. The type of measurement for each data point is known due to comments in the data files. For the Maun and Pandamatenga sites, there is an additional file containing above canopy PAR irradiance. The PAR data units are micromols m-2 s-1, and the time is in Local Time. There is also a readme file, in txt format, for each site.

Data used to generate Figures 1-3 and Table 2 in the journal article entitled "Evaluating the Laboratory Performance of Pellet-Fueled Semigasifier Cookstoves" https://doi.org/10.1021/acs.est.4c10008 Figure 1. Box and whisker plots (with jittered points by ISO test phase) of emission factors based on energy delivered (EFd) for particle pollutants (a) fine particulate matter (PM2.5), (b) ultrafine particles (UFP), (c) organic carbon (OC), and (d) elemental carbon (EC). Figure 2. Box and whisker plots (with jittered points by the ISO test phase) of emission factors based on energy delivered (EFd) for gaseous pollutants: (a) carbon monoxide (CO), (b) total hydrocarbons (THC), (c) methane (CH4), and (d) nitrogen oxides (NOx). Figure 3. Emission factors (based on energy delivered) of fine particulate matter (PM2.5) and carbon monoxide (CO) plotted against ISO Tiers for distinct test phases (i.e., power levels) and overall (i.e., mean of phase-averaged) results for all three stoves (a−c). Error bars represent the 90% confidence intervals in the mean. Mean values are also plotted from the literature (d) for lab (L), test kitchen (K), and field (F) studies, as summarized in Tables S16 and S17. Table 1. Summary of Power Level Mean (i.e., Mean of All Stove/Fuel Combinations at a Given Power Level) and Standard Deviations (SD, Here Defined as Standard Deviations of All Stove/Fuel Combination Means at a Given Power Level) of Emission Factors Based on Energy Delivered (EFd) for All Pollutants Excluding Carbon Dioxide (CO2). This dataset is associated with the following publication: Champion, W., G. Shen, C. Williams, L. Virtaranta, M. Barnes, C. Christianson, M. Hays, and J. Jetter. Evaluating the Laboratory Performance of Pellet-fueled Semi-gasifier Cookstoves. ACS ES&T Air. American Chemical Society, Washington, DC, USA, 59(4): 0, (2025).

This data set of leaf, stem, and root biomass for various plant taxa was compiled from the primary literature of the 20th century with a significant portion derived from Cannell (1982). Recent allometric additions include measurements made by Niklas and colleagues (Niklas, 2003). This is a unique data set with which to evaluate allometric patterns of standing biomass within and across the broad spectrum of vascular plant species. Despite its importance to ecology, global climate research, and evolutionary and ecological theory, the general principles underlying how plant metabolic production is allocated to above- and below-ground biomass remain unclear. The resulting uncertainty severely limits the accuracy of models for many ecologically and evolutionarily important phenomena across taxonomically diverse communities. Thus, although quantitative assessments of biomass allocation patterns are central to biology, theoretical or empirical assessments of these patterns remain contentious.

The BOREAS TE-12 team collected several data sets in support of its efforts to characterize and interpret information on the reflectance, transmittance, and gas exchange of boreal vegetation. This data set contains measurements of leaf gas exchange conducted in the SSA during the growing seasons of 1994 and 1995 using a portable gas exchange system.

The purpose of the SNF study was to improve understanding of the relationship between remotely sensed observations and important biophysical parameters in the boreal forest. A key element of the experiment was the development of methodologies to measure forest stand characteristics to determine values of importance to both remote sensing and ecology. Parameters studied were biomass, leaf area index, above-ground net primary productivity, bark area index and ground coverage by vegetation. Thirty two quaking aspen and thirty one black spruce sites were studied. Sites were chosen in uniform stands of aspen or spruce. Use of multiple plots within each site allowed estimation of the importance of spatial variation in stand parameters. Deciduous vegetation undergoes dramatic changes over the seasonal cycle. The varying amount of green foliage in the canopy effects the transpiration and productivity of the forest. Measurements of changes in the canopy and subcanopy green foliage amount over the spring of 1984 have been made. From above the subcanopy, photographs of the aspen canopy were taken, pointing vertically up. The photographs were taken at two locations in sites 16 and 93 on several different days. Foliage coverage was determined by overlaying grids with 200 points onto the photos of the canopy. The number of points obscured by vegetation were counted. These counts were adjusted for the area of the branches, which had been determined by photos taken before leaf out. The number of foliage points were then scaled between zero, for no leaves, to one, for maximum coverage. Subcanopy leaf extension was measured for beaked hazelnut and mountain maple, the two most common understory shrubs. For selected branches on trees in sites 16 and 93, the length and width of all leaves were measured on several days. These measurements were used to calculate a total leaf area which was scaled between 0 and 1 as with the aspen. The aspen canopy measurements have been combined with the subcanopy measurements and are available in this data set (i.e., SNF Forest Phenology/Leaf Expansion Data). These measurements of leafout show that the subcanopy leaf expansion lags behind that of the canopy. Subcanopy leaf expansion only begins in earnest after the canopy has reached nearly full coverage.

LAI estimates computed from unweighted openness by the canopy program from digitized canopy photographs.

A box-and-whisker plot of point estimates of error rate and figures showing results of simulations.

The BOREAS TE-12 team collected water potential data in 1993 and 1994 from aspen, jack pine and black spruce leaves/needles. Collections were made at the SSA FEN, YJP, YA, OA, and OBS sites. Measurements were made using a pressure chamber on a platform in the field.

This data set provides mean leaf area index (LAI), dendrometry band measurements, and litterfall mass from samples collected at the km 67 research site, Topajos National Forest, Para, Brazil. Litterfall collections were from January 23, 2004 through December 3, 2004, dendrometer measurements were monthly between December 2003 and December 2004, and LAI measurements were collected from January 26, 2004 through November 3, 2004.

All measurements were taken at the km 67 site in the Tapajos National Forest. This site is situated in an area of Amazonian primary tropical forest belonging to the municipality of Belterra, Para, Brazil. The forest is mostly evergreen with a few deciduous species. The canopy is characterized by large emergent trees up to 55-m tall, with a closed canopy at approximately 40-m; there are few indications of recent anthropogenic disturbance other than hunting trails. Measurement plots (50) were established along 4 transects at the site and within each plot, 5 subplots were established. The longest transect (25 m x 500 m) was the location of 20 (25 m x 25 m) plots. The other 3 transects (25 m x 250 m) contain 10 plots per transect. Note that the assignment of plots to transects is not provided.

There are four comma-delimited data files (.csv) with this data set.

The BOREAS TF-11 team gathered a variety of data to complement their tower flux measurements collected at the SSA Fen site. This data set contains single-leaf gas exchange data from the SSA Fen site during 1994 and 1995. These leaf gas exchange properties were measured for the dominant vascular plants using portable gas exchange systems.

The goal of this study was to predict the global distribution of plant rooting depths based on data about global aboveground vegetation structure and climate. Vertical root distributions influence the fluxes of water, carbon, and soil nutrients and the distribution and activities of soil fauna. Roots transport nutrients and water upwards, but they are also pathways for carbon and nutrient transport into deeper soil layers and for deep water infiltration. Roots also affect the weathering rates of soil minerals. For calculating such processes on a global scale, data on vertical root distributions are needed as inputs to global biogeochemistry and vegetation models. In the Project for Intercomparison of Land Surface Parameterization Schemes (PILPS), rooting depth and vertical soil characteristics were the most important factors explaining scatter for simulated transpiration among 14 land-surface models. Recently, the Terrestrial Observation Panel for Climate of the Global Climate Observation System (GCOS) identified the 95% rooting depth as a key variable needed to quantify the interactions between the climate, soil, and plants, stating that the main challenge was to find the correlation between rooting depth and soil and climate features (GCOS/GTOS Terrestrial Observation Panel for Climate 1997). In response to this challenge, a data set of vertical rooting depths was collected from the literature in order to construct maps of global ecosystem rooting depths.

The parameters included in these data sets are estimates for the soil depths containing 50% and 95% of all roots, termed 50% and 95% rooting depths (D50 and D95, respectively). Together, these variables can be used to calculate estimates for vertical root distributions, using a logistic equation provided in this documentation. The data represent mean ecosystem rooting depths for 1 by 1 degree grid cells.

Related data sets:Â The ORNL DAAC offers related data sets by Jackson et al. (2003), Gordon and Jackson (2003), Schenk and Jackson (2003), and Gill and Jackson (2003).

This data set is one of the products of the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) data collection which contains 50 global time series data sets for the ten-year period 1986 to 1995. Selected data sets span even longer periods. ISLSCP II is a consistent collection of data sets that were compiled from existing data sources and algorithms, and were designed to satisfy the needs of modelers and investigators of the global carbon, water and energy cycle. The data were acquired from a number of U.S. and international agencies, universities, and institutions. The global data sets were mapped at consistent spatial (1, 0.5 and 0.25 degrees) and temporal (monthly, with meteorological data at finer (e.g., 3-hour)) resolutions and reformatted into a common ASCII format. The data and documentation have undergone two peer reviews.

ISLSCP is one of several projects of Global Energy and Water Cycle Experiment (GEWEX) [http://www.gewex.org/] and has the lead role in addressing land-atmosphere interactions -- process modeling, data retrieval algorithms, field experiment design and execution, and the development of global data sets.

The BOREAS TE-06 team collected several data sets in support of its efforts to characterize and interpret information on the plant biomass, allometry, biometry, sapwood, leaf area index, net primatry production, soil temperature, leaf water potential, soil CO2 flux, and multivegetation imagery of boreal vegetation. This data set includes tree measurements conducted on the above gound biomass of trees in the BOREAS NSA and SSA during the growing seasons of 1994 and 1995 and the derived allometric relationships/equations.

Measurements of light, CO2, temperature, and humidity response curves were made by the BOREAS TE-04 team during the summary of 1994 using intact attached leaves of boreal forest species located in the BOREAS SSA. These measurements were conducted to calibrate models used to predict photosynthesis, stomatal conductance, and leaf respiration. The data can be used to construct plots of response functions or for parameterizing models. Parameter values suitable for application in SiB2 (Sellers et al., 1996) or the leaf model of Collatz et al. (1991) and programs can be obtained from the investigators.

This research uses numerical simulations and mathematical theories to simulate and analyze the spread of the influenza virus. The existence, uniqueness, positivity, and boundedness of the solution are established. We investigate the fundamental reproduction number guaranteeing the asymptotic stability of equilibrium points that are endemic and disease-free. We also examine the qualitative behavior of the models. Using the Lyapunov method, Routh-Hurwitz, and other criteria, we explore the local and global stability of these states and present our findings graphically. Our research assesses control policies and proposes alternatives, performing bifurcation analyses to establish prevention strategies. We investigate transcritical, Hopf, and backward bifurcations analytically and numerically to demonstrate disease transmission dynamics, which is novel to our study. Contour plots, box plots, and phase portraits highlight key characteristics for controlling epidemics. The disease’s persistence depends on its fundamental reproduction quantity. To validate our outcomes, we fit the model to clinical data from influenza cases in Mexico and Colombia (October 1, 2020, to March 31, 2023), aiming to analyze trends, identify critical factors, and forecast influenza trajectories at national levels. Additionally, we assess the efficacy of implemented control policies.

This global data set of photosynthetic rates and leaf nutrient traits was compiled from a comprehensive literature review. It includes estimates of Vcmax (maximum rate of carboxylation), Jmax (maximum rate of electron transport), leaf nitrogen content (N), leaf phosphorus content (P), and specific leaf area (SLA) data from both experimental and ambient field conditions, for a total of 325 species and treatment combinations. Both the original published Vcmax and Jmax values as well as estimates at standard temperature are reported.

The maximum rate of carboxylation (Vcmax) and the maximum rate of electron transport (Jmax) are primary determinants of photosynthetic rates in plants, and modeled carbon fluxes are highly sensitive to these parameters. Previous studies have shown that Vcmax and Jmax correlate with leaf nitrogen across species and regions, and locally across species with leaf phosphorus and specific leaf area, yet no universal relationship suitable for global-scale models is currently available.

These data are suitable for exploring the general relationships of Vcmax and Jmax with each other and with leaf N, P and SLA. This data set contains one *.csv file.

The BOREAS TE-10 team collected several data sets in support of its efforts to characterize and interpret information on the reflectance, transmittance, gas exchange, chlorophyll content, carbon content, hydrogen content, and nitrogen content of boreal vegetation. This data set describes the relationship between sample location, age, chlorophyll content, and C-H-N concentrations at several sites in the SSA conducted during the growing seasons of 1994 and 1996.

Leaf area index was estimated in an 18 ha plot at the logged forest tower site, km 83, Tapajos National Forest, Para, Brazil. The plot was adjacent to the eddy flux tower at km 83, Tapajos National Forest, Para, Brazil. Thirty litter traps were placed at 25-m intervals along two east–west transects in the 18 ha block. Litter samples were collected biweekly from the traps and returned to the lab where they were sorted, air dried, and weighed. The leaf area of a subsample of air-dried leaves was determined using a computer scanner and image processing software. The subsample was then dried in an oven and the air-dried weights were corrected to oven-dried weight. The area of leaf litter collected during each sampling was calculated using the relationship between weight and area measured for the subsample (Goulden et al., 2004). There is one comma-delimited data file with this data set.