unit of measure
The rate or amount of precipitation (liquid or solid) deposited from the atmosphere.
Abiotic parameters are physical and chemical environmental factors that influence an ecosystem, such as temperature, light, water, soil, and chemical composition, independent of living organisms.
The animal's heart rate. Units: beats per minute; Entity described: event
Biotic parameters are environmental factors related to living organisms and their interactions, including competition, predation, mutualism, and population density within an ecosystem.
The amount of water vapour (relative humidity, dew point temperature) in the atmosphere.
Non displonible
Depth is the vertical distance below the surface.
A spatial region or named place.
Quantity (i.e. number of moles) of acid-neutralising bases per unit mass of the water column.
Concentration of arsenic per unit volume of the water body
Concentration of cadmium per unit volume of the water body
The quantity (i.e. number of moles) of organic carbon (i.e. carbon not in carbonate or bicarbonate molecules) dissolved per unit volume of the water column
Volume of oxygen dissolved per unit volume of the water column.
The concentration of dissolved oxygen expressed as a proportion of the oxygen concentration in water that is in equilibrium with the atmosphere.
Minus the log of the hydrogen ion concentration (moles per litre) in the water column.
Concentration of inorganic carbon per unit volume of the water body, filtration and method unknown.
Acquiring information about an object/area from a distance, typically with satellites.
The standing biomass Virtual Research Environment (BIOMASS VRE) addresses the response of aquatic ecosystems, and in particular of the standing biomass, to environmental change. The standing biomass dynamics are studied by integrating data resources, services and modelling tools of different environmental Research Infrastructures.
Quantity (i.e. number of moles) of inorganic nitrogen (i.e. nitrogen not in carbon compounds) dissolved per unit volume of the water column.
The amount (volume or mass) of suspended particule material per amount (volume or mass) of a body of water.
The speed of air relative to the ground or sea surface.
Concentration of ammonium per unit volume of a river, estuary, sea or ocean by any method in filtered or unfiltered water.
Concentrations of dissolved inorganic silicon usually as hydrosilicic acid (often called silicate) and biogenic silica.
The mass of sodium chloride dissolved per unit mass of the water column (definition prior to introduction of PSS-78 Practical Salinity Scale).
Term to be used when the property reported is a characteristic of a survey (for example its area, its duration). A survey is a sampling activity which can be made up of a single or multiple sampling events.
An action that occurs at some location during some time.
One of six chemical elements classified as an alkaline earth metal. Its atomic number is 20.
Non displonible.
A radioactive isotope of the chemical element carbon; also known as radiocarbon.
The amount of living organic matter per unit area or per unit volume. It can be expressed in terms of biovolume, weight or carbon content and can be measured at different organisational levels.
Total carbon fixed over a day, integrated over depth or time.
Average latent heat flux from the surface, often linked to evaporation and transpiration processes.
Index derived from satellite reflectance (NIR and red) indicating the amount of green vegetation or density over a given area and vegetation health.
A remotely sensed index to quantify the presence, density, and health of vegetation.
MODIS surface reflectance, band 7 (2105–2155 nm).
The total amount or weight, or energy content, of (a portion of) organisms existing in a specific area at a particular time. In plants, biomass of the aboveground parts of plants (stems, leaves, branches).
Total biomass of living organisms in terrestrial environments. Biomass from Terrestrial Environments.
Land surface temperature, measured using thermal satellite data.
The process that is used to produce a specific research result in a concrete domain. A workflow comprises a series of components that are arranged in a directed graph to set the order of execution of such components. Therefore, a workflow is usually a complex process and may involve both automatic and manual procedures for dealing with research objects and documenting them. Workflows may need instantiation in terms of input data and process parameters.
Centring variables consists of transforming a variable X by subtracting a reference value, usually the mean.
Systematic examination of data.
It is a hyperparameter of the XGBoosting. It educes (“shrinkage”) the contribution of each new tree/step.
Tests for a monotonic trend in a time series evaluate whether the series changes consistently in one direction, nondecreasing or nonincreasing, without assuming linearity.
Number of hours in a photoperiod.
The number of trees is a hyperparameter of the Random Forest algorithm that determines how many decision trees are grown in the ensemble.
MODIS surface reflectance, band 6 (1628–1652 nm).
Sea surface temperature estimated from satellite thermal infrared measurements.
Maximum amount of evapotranspiration that could occur under conditions of unlimited water availability.
R-squared represents the proportion of variance in the dependent variable that can be predicted from the independent variables.
It is a hyperparameter of the XGBoosting. itis the number of boosting iterations (i.e., how many trees/steps you add) in X Gradient Boosting. Lower learning rate usually need more rounds. Whereas, Higher learning rate usually need fewer rounds.
Volume of oxygen consumed per unit time, indicator of metabolic rate.
A recurrence plot (RP) is an advanced technique of nonlinear data analysis. It is a visualisation (or a graph) of a square matrix, in which the matrix elements correspond to those times at which a state of a dynamical system recurs (columns and rows correspond then to a certain pair of times). Techniqually, the RP reveals all the times when the phase space trajectory of the dynamical system visits roughly the same area in the phase space.
It is a hyperparameter of the XGBoosting. It controls the fraction of features randomly sampled for each tree (column subsampling at the tree level).
MAE represents the average absolute difference between the predicted value of the machine learning algorithm and the values of the dataset used to train the algorithm.
Rate of respiration in darkness (no photosynthesis), reflects metabolic costs.
Carbon fixation rate per unit chlorophyll per hour, indicates photosynthetic efficiency.
Concentration of chlorophyll a, main photosynthetic pigment in aquatic and terrestrial biomass.
MODIS surface reflectance, band 2 (841–876 nm).
The sum of the absolute dynamic components of tri-axial body acceleration, commonly used as a proxy for energy expenditure in animals.
It is a hyperparameter of the Neural Network.
Fraction of photosynthetically active radiation absorbed by vegetation.
Recurrence Rate (RR) is the density of recurrence points in a recurrence plot, i.e., the proportion of time-index pairs (i,j) where the system’s states are “close” (within a threshold ε).
The VIF measures how much multicollinearity a predictor has with the other predictors in a linear regression. VIF = 1: no collinearity; ≈ 2–5: moderate collinearity; > 5 (or > 10, depending on convention): problematic collinearity.
NDII is a widely-used index to remotely sense Equivalent Water Thickness (EWT) of leaves and canopies.
Belowground biomass refers to the portion of plant biomass that is allocated below the ground, including roots and storage organs, which is crucial for plant survival strategies, especially under conditions of recurrent disturbance.
MODIS surface reflectance, band 4 (545–565 nm).
Biomass from herbaceous (non-woody) plants.
It is a hyperparameter of the XGBoosting. It is the proportion of instances (rows) that are randomly sampled for each tree.
Amount of carbon fixed by photosynthesis per day.
MODIS surface reflectance, band 5 (1230–1250 nm).
A subset of original dataset used for training the model. Training data teaches a model how to make predictions.
Total leaf area per unit of ground surface; an indicator of vegetation cover and productivity.
Model selection balancing fit and parsimony, with a stronger penalty than AIC. Lower is better (comparable only between models estimated on the same data and with the same likelihood).
MODIS surface reflectance, band 1 ( 620–670 nm).
A remote sensing metric of chlorophyll fluorescence, indicating phytoplankton physiological status.
Analysis of variance (ANOVA) is the statistical procedure of comparing the means of a variable. It does this across several groups of individuals.
Phytoplankton are the main primary producers responsible for converting inorganic carbon into organic matter through photosynthesis in aquatic ecosystems. They form the base of these ecosystems' food webs.
Total biomass of planktonic organisms (phytoplankton and zooplankton).
Total biomass of living organisms in aquatic environments.
A version of VGPM using the Eppley parameterization for maximum production as a function of temperature.
It is a hyperparameter of the Neural Network. it is the number of units/neurons per layer.
Selection of models balancing goodness of fit and complexity. Lower is better (comparable only between models estimated on the same data).
It is the Random Forest hyperparameter that indicates how many variables (features) are considered at each split of each tree. A low mtry value results in trees that are more diverse from each other, with higher bias and lower variance (less correlation among trees). A high mtry results in stronger and more similar trees, as well as a lower bias and higher variance (greater correlation).
A subset of original datased used for validating the model. Test data checks how well the model has learned.
RMSE represents the square root of the mean squared difference between the predicted value from the machine learning algorithm and the values of the dataset used to train the algorithm. A low value indicates good performance.
It is a hyperparameter of the XGBoosting. It controls or set how complex each tree can get.
SHAP are techniques that can help to explain the influence of environmental variables on model outputs.
Seasonal AutoRegressive Integrated Moving Average (SARIMA) is a time-series model that captures both nonseasonal and seasonal patterns by combining: AR (AutoRegressive) terms: dependence on past values, I (Integrated): differencing to remove trends, MA (Moving Average) terms: dependence on past forecast errors.
The horizontal distance measured from the shoreline toward the open sea.
It is a hyperparameter of the XGBoosting Minimum sum of instance weight (Hessian) needed in a child (leaf).
A model estimating oceanic primary productivity from chlorophyll, light, and temperature data.
It is a hyperparameter of the Support Vector Machine. This hyperparameter trades off a wide margin against classification errors. High C produces weak regularisation, resulting in a 'harder' margin, fewer training errors and a higher risk of overfitting. Low C produces stronger regularisation, resulting in a 'softer' margin that tolerates training errors and is typically more robust in terms of generalisation.
A model estimating oceanic primary productivity using carbon-based methods and satellite measurements.
Rate at which light at 490 nm is attenuated in water, indicator of water clarity.
A spline is a function made up of piecewise polynomials joined at certain points called knots, so that the curve remains smooth (continuous with continuous derivatives) while still being flexible.
The vegetation index uses NIR, red and blue bands to improve sensitivity in regions with high biomass, while minimising the influence of soil and atmosphere.
Average potential latent heat flux, calculated under optimal moisture conditions.
Redundancy Analysis (RDA) is a constrained ordination method for multivariate data (widely used in ecology). It can be viewed as multivariate multiple regression followed by a PCA of the fitted values.
Evapotranspiration is the sum of evaporation and plant transpiration from the Earth's land and ocean surface to the atmosphere.
MODIS surface reflectance, band 3 (459–479 nm).
It is a hyperparameter of the Support Vector Machine. Gamma (SVM) is the kernel coefficient (γ) for RBF, polynomial, and sigmoid kernels. It controls how “close” a point must be to influence the decision.
Biomass of all living forest components (trees, understory, etc.).
The degree of hotness of an object, a measurement matrix, an environment, expressed against a standard scale.
Degré de chaleur d'un objet, d'une matrice, d'un environnement, exprimé selon une échelle standard.
Total carbon fixed by photosynthesis in an ecosystem.
Organic carbon suspended in water as particles, including phytoplankton and detritus, per unit volume of the water column.
SARIMAX (Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors) is a seasonal extension of ARIMA that incorporates external regressors to model and forecast time series influenced by both internal dynamics and exogenous factors.Exogenous regressors (X): additional predictors that influence the series but are not lagged values of the series itself.
Any behavioral, morphological, phenological, or physiological trait, which impacts phytoplankton fitness.
The IUCN conservation status records whether animal or plant species is threatened with extinction in their native home.These include 'least concern', 'near threatened', 'vulnerable', 'endangered', 'critically endangered', 'extinct in the wild', and 'extinct'.
The spectral range of solar radiation from 400 to 700 nanometers that organisms are able to use for photosynthesis.
The metabolic rates of ectothermal organisms, measured under conditions of rest, tranquility, absence of stress, and fasting. It is the ectotherm equivalent of Basal Metabolic Rate (BMR) in endotherms
The rate of energy expenditure per unit time by endothermic animals at rest.
e-Service is an automated service that responds to requests via an information network by receiving inputs, manipulating them, and sending back appropriate outputs.
A data template is a standardized structure for organizing and recording data in a consistent and reproducible manner.
The full name, with authorship and date information if known, of the currently valid (zoological) or accepted (botanical) taxon.
A group of organisms (sensu http://purl.obolibrary.org/obo/OBI_0100026) considered by taxonomists to form a homogeneous unit.
The full scientific name of the class in which the taxon is classified.
Identifier assigned to a specific sampling event by a cruise.
The geographic latitude (in decimal degrees, using the spatial reference system) of the geographic center of a location. Positive values are north of the Equator, negative values are south of it. Legal values lie between -90 and 90, inclusive.
The geographic longitude (in decimal degrees, using the spatial reference system) of the geographic center of a location. Positive values are east of the Greenwich Meridian, negative values are west of it. Legal values lie between -180 and 180, inclusive.
The full scientific name of the genus in which the taxon is classified.
The full scientific name of the kingdom in which the taxon is classified.
The full scientific name of the order in which the taxon is classified.
The full scientific name of the phylum or division in which the taxon is classified.
The full scientific name, with authorship and date information if known. When forming part of a identification, this should be the name in lowest level taxonomic rank that can be determined.
The four-digit year in which the event occurred, according to the Common Era Calendar.
Concentration or amount of chloride ions.
Size-fractionated phytoplankton biomass for microplankton.
Size-fractionated phytoplankton biomass for nanoplankton.
Inorganic phosphorus available for biological uptake (usually orthophosphate).
Concentration or amount of iron.
Concentration or amount of lead
Power of electromagnetic radiation per unit area (light received).
Concentration or amount of magnesium ions.
Concentration or amount of manganese.
Highest rate of photosynthesis under optimal light conditions.
Concentration or amount of mercury.
The rate at which photosynthetic organisms produce net useful chemical energy after accounting for respiration.
Concentration of nitrate nitrogen per unit volume of the water column.
Concentration of nitrite nitrogen per unit volume of the water column.
Concentration or amount of potassium ions.
Primary production for microplankton.
Primary production for nanoplankton.
Primary production for picoplankton.
All of the processes used by organisms to generate metabolically usable energy, chieﬂy in the form of ATP, from the oxidative breakdown of foodstuffs. May refer to processes ranging from the exchange of oxygen and carbon dioxide between organism and environ­ment, to the biochemical processes gen­erating ATP at the cellular level. a. respiratory, pert. or involved in re­spiration. see also aerobic respiration, anaerobic respiration, glycolysis, oxidative phosphorylation.
Concentration or amount of sulfate ions.
Water temperature measured in situ.
Variables associated with the determination of the air temperature near the Earth's surface.
Total concentration of dissolved substances (such as calcium, magnesium, sodium, chlorides, sulfates, and bicarbonates) and small amounts of dissolved organic matter in water.
Sum of all nitrogen forms (organic, nitrate, nitrite, ammonia) in a sample.
Total phosphorus in all forms (organic, inorganic, particulate, dissolved).
Total concentration of suspended solid particles in water.
Depth of visible light penetration, often measured with Secchi disk.
Rainfall
biomass vre thesaurus
Abiotic Parameter
heart rate
Biotic Parameter
Humidity
Humidité
depth
Location
ALKALINITY
Arsenic in water body
Cadmium in water body
DISSOLVED ORGANIC CARBON
DISSOLVED OXYGEN
OXYGEN SATURATION
PARTICULATE INORGANIC CARBON
Remote sensing
BIOMASS VRE
DISSOLVED INORGANIC NITROGEN
Conductivity
Turbidity
Wind speed
Water body ammonium
Silicates
Salinity
survey
Event
calcium
Calcium
carbon-14
Biomass
Longevity
Locomotion
Body mass
Habitat
Food type
Integrated daily carbon fixation
Thermoregulation
Average Latent Heat Flux
Normalized Difference Vegetation Index
Vegetation Index
MODIS Surface Reflectance Band 7
Aboveground biomass
Terrestrial biomass
Land Surface Temperature
Workflow
Center
Data analysis
Learning rate
Mann-Kendall Test
Day Length
Number of Trees
MODIS Surface Reflectance Band 6
Sea Surface Temperature
Total Potential Evapotranspiration
R-squared
Number of boosting rounds/iterations
Respiration Oxygen Consumption
Recurrence plot
Column sample by tree
Mean Absolute Error
Dark Respiration Rate
Chlorophyll normalized mean hourly Carbon Fixation rate
Chlorophyll a Content
MODIS Surface Reflectance Band 2
Overall Dynamic Body Acceleration
Learning rate decay
Fraction of Photosynthetically Active Radiation
Recurrence rate
Variance inflation factor
Normalized Difference Infrared Index
Belowground biomass
MODIS Surface Reflectance Band 4
Maximum number of iterations
Herbaceous biomass
Subsample ratio of the training instances
Daily carbon fixation
MODIS Surface Reflectance Band 5
Training set
Leaf Area Index
Bayesian Information Criterion
MODIS Surface Reflectance Band 1
Normalized Fluorescence Line Height
Analysis of variance
Phytoplankton biomass
Planktonic biomass
Aquatic biomass
Epply Vertically Generalized Production Model
Hidden layer size
Akaike Information Criterio
Number of variables tested
Test set
Root Mean Squared Error
Maximum tree depth
SHapley Additive exPlanations
Seasonal AutoRegressive Integrated Moving Average
Distance from coast
Min child weight
Vertically Generalized Production Model
Regularization parameter C
Carbon-based Productivity Model
Diffuse Attenuation Coefficient at 490 nm
Spline
Enhanced Vegetation Index
Average Potential Latent Heat Flux
Redundancy analysis
Total Evapotranspiration
MODIS Surface Reflectance Band 3
Gamma_svm
Forest biomass
Temperature
température
Gross Primary Production
Particulate Organic Carbon
Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors
zooplankton biomass
Functional Trait
Conservation status
Photosynthetically Active Radiation
Standard metabolic rate
Basal metabolic rate
e-Service
Data Template
Accepted Name Usage
Taxon
Class
Cruise
Decimal Latitude
Decimal Longitude
Family
Genus
Kingdom
Month
Order
Phylum
Scientific Name
Year
Chloride
Chlorophyll Microplankton
Chlorophyll Nanoplankton
Chlorophyll Picoplankton
Dissolved Inorganic Phosphorus
Iron
Lead
Light intensity (irradiance)
Magnesium
Manganese
Maximum photosynthetic rate
Mercury
Net Primary Production
Nitrate
Nitrite
Potassium
Primary Production Microplankton
Primary Production Nanoplankton
Primary Production Picoplankton
Respiration
Sulfate
Water Temperature
Air temperature
Température de l'air
Total Dissolved Solids
Total Nitrogen
Total Phosphorus
Total Suspended Solids
Transparency
Water Body
Standing biomass Virtual Research Environment
IPP
NDVI
sur_refl_b07
LST
eta
KENDAL TEST
ntree
sur_refl_b06
SST
PET
nrounds
VO2
colsample_bytree
MAE
Chl
Chl a
Chl-a
sur_refl_b02
ODBA
decay
Fpar
VIF
NDII
sur_refl_b04
maxit
subsample
sur_refl_b05
LAI
BIC
sur_refl_b01
FHL
ANOVA
Epply VGPM
size
AIC
mtry
RMSE
max_depth
SHAP
SARIMA
min_child_weight
VGPM
Cost
CbPM
EVI
PLE
RDA
sur_refl_b03
GPP
POC
SARIMAX
PAR
SMR
BMR
Resting metabolic rate
base metabolic rate
base metabolic rate measurement
acceptedNameUsage
class
dec LAT
decimalLatitude
dec LONG
decimalLongitude
family
genus
kingdom
month
order
phylum
scientificName
year
Cl⁻
Chl micro
Chl nano
Chl pico
DIP
Orthophosphate
PO₄³⁻
Irr
Mg²⁺
NPP
NO₃⁻
NO₂⁻
PP micro
PP nano
PP pico
SO₄²⁻
TDS
TSS
Secchi disk
Transp
accepted
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Hardisky, M. A., Klemas, V., & Smart, R. M. (1983). The influences of soil salinity, growth form, and leaf moisture on the spectral reflectance of Spartina alterniflora canopies. Photogrammetric Engineering & Remote Sensing, 49, 77−83.
Hardesty L (14 April 2017). "Explained: Neural networks". MIT News Office. Archived from the original on 18 March 2024. Retrieved 2 June 2022.
Falkowski, P. G., & Raven, J. A. (2007). Aquatic Photosynthesis. Princeton University Press.
Akaike, H. (1973), "Information theory and an extension of the maximum likelihood principle", in Petrov, B. N.; Csáki, F. (eds.), 2nd International Symposium on Information Theory, Tsahkadsor, Armenia, USSR, September 2-8, 1971, Budapest: Akadémiai Kiadó, pp. 267–281. Republished in Kotz, S.; Johnson, N. L., eds. (1992), Breakthroughs in Statistics, vol. I, Springer-Verlag, pp. 610–624.
de Boor, Carl. 2001. A practical guide to splines. Springer.