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Date of publication: May 30, 2024

Version 1

Date of publication: May 30, 2024

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Pasture production model

by Carlos Javier Navarro

This pasture production model provides a map of Available Metabolic Energy (EMD) for a region in Andalusia. The model is based on the doctoral thesis of Passera Sassi from 1999, where equations were calibrated using field measurements.
The objective of this work was to spatially model pasture production using available spatial information layers for the region, while also identifying limitations and ways to enhance these models. This was ...(continue reading)

10.25829/82ef2e
Data: netCDF (1.18GB)
Metadata: ACDD (JSON) | EML (XML)

pasture productionAvailable Metabolic EnergyAndalusia

69
The title of the dataset. Pasture production model
The date on which this version of the data was created in YYYY-MM-DD format.
A paragraph describing the dataset.
Hover to see a suggestion for a good description. Allowed:
This pasture production model provides a map of Available Metabolic Energy (EMD) for a region in Andalusia. The model is based on the doctoral thesis of Passera Sassi from 1999, where equations were calibrated using field measurements.
The objective of this work was to spatially model pasture production using available spatial information layers for the region, while also identifying limitations and ways to enhance these models. This was achieved using Google Earth Engine, which facilitates cloud-based processing.
The final maps generated are those of available metabolic energy and also the parameters resulting from the equations used, that is, the number of pasture species considered in the original studies (n) in addition to indicators of the goodness of fit of the model to the observed data, given by the coefficient of determination (r2).
The maps were masked using a certainty layer, presenting data only in the sites that have the greatest environmental similarity with the study sites where the equations were calibrated. For this, the Mahalanobis distance of environmental variables (accumulated precipitation, average temperature, evapotranspiration and height) was calculated in relation to the original study sites.
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N/A

The method of production of the original data.
Hover to see a suggestion for a minimum description. We calculated Available Metabolic Energy (EMD), by applying a series of equations from the study of Passera Sassi 1999 that relate parameters of precipitation (mm) and vegetation cover (%), where the bioclimatic floors to which each type belongs are taken into account of pasture.

For the precipitation values we use local information available in the Andalusian Environmental Information Network (REDIAM) that provides layers of spatialized climate information obtained from meteorological stations integrated into the Environmental Climatology Information Subsystem. These layers present data with a pixel resolution of 500 meters.
For the vegetation cover we use map comes from the Information System on the Natural Heritage of Andalusia (SIPNA) developed for REDIAM. The system brings together geographic and alphanumeric information from a series of layers at a detailed scale (1:10,000). From these maps we created raster versions of the shrub and herbaceous cover. We use two versions of the map, SIPNA 2022 and SIPNA 2023.
Then we apply the corresponding equation for each site according to the type of bioclimatic floor, described in Passera's doctoral thesis.
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The name of the Project.
The URL from the project website. https://smartecomountains.lifewatch.dev/
The name of the person or other creator type principally responsible for creating this data.
The email of the person or other creator type principally responsible for creating this data. carlosnavarro@go.ugr.es
carlosnavarro@go.ugr.es
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Please select the CC license from the list. We recommend the use of CC BY 4.0

Essential Biodiversity Variables

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Genetic composition
Intraspecific genetic diversity
Genetic differentiation
Effective population size
Inbreeding
Other
Species populations
Species distributions
Species abundances
Other
Species traits
Morphology
Physiology
Phenology
Movement
Other
Community composition
Community abundance
Taxonomic and phylogenetic diversity
Trait diversity
Interaction diversity
Other
Ecosystem functioning
Primary productivity
Ecosystem phenology
Ecosystem disturbances
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Ecosystem structure
Live cover fraction
Ecosystem distribution
Ecosystem Vertical Profile
Other
Ecosystem services
Pollination
Other
Cross-cutting

Biological entity

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Species
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Ecosystems
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None
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Scenario

Spatial domain

Global
Continental/Regional
National
Sub-national/Local
Name of the continent/region/country/area, separated by comma
degree
southWest lat: 35.9, lon: -7.5
northEast lat: 38.7, lon: -1.6

Temporal domain

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decadal
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monthly
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daily
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Environmental domain *

Terrestrial
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Miscellaneous information about the data, not captured elsewhere. This research is part of the project “Thematic Center on Mountain Ecosystem & Remote sensing, Deep learning-AI e-Services University of Granada-Sierra Nevada” (LIFEWATCH-2019-10-UGR-4), which has been co-funded by the Ministry of Science and Innovation through the FEDER funds from the Spanish Pluriregional Operational Program 2014-2020 (POPE), LifeWatch-ERIC action line. The project has also been co-financed by the Provincial Council of Granada. Website: https://digibug.ugr.es/handle/10481/37511