|
View: |
Part 1: Document Description
|
|
Citation |
|
|---|---|
|
Title: |
Replication Data for: The impact of climate change on cacao production in Central America and the Caribbean |
|
Identification Number: |
doi:10.7910/DVN/QUKZTO |
|
Distributor: |
Harvard Dataverse |
|
Date of Distribution: |
2019-05-20 |
|
Version: |
2 |
|
Bibliographic Citation: |
Bunn, Christian; Lundy, Mark; Castro-Llanos, Fabio, 2019, "Replication Data for: The impact of climate change on cacao production in Central America and the Caribbean", https://doi.org/10.7910/DVN/QUKZTO, Harvard Dataverse, V2 |
|
Citation |
|
|
Title: |
Replication Data for: The impact of climate change on cacao production in Central America and the Caribbean |
|
Identification Number: |
doi:10.7910/DVN/QUKZTO |
|
Authoring Entity: |
Bunn, Christian (International Center for Tropical Agriculture - CIAT) |
|
Lundy, Mark (International Center for Tropical Agriculture - CIAT) |
|
|
Castro-Llanos, Fabio (International Center for Tropical Agriculture - CIAT) |
|
|
Producer: |
International Center for Tropical Agriculture |
|
Distributor: |
Harvard Dataverse |
|
Distributor: |
International Center for Tropical Agriculture |
|
Access Authority: |
CIAT Data and Research Methods |
|
Depositor: |
Castro-Llanos, Fabio |
|
Date of Deposit: |
2019-05-17 |
|
Holdings Information: |
https://doi.org/10.7910/DVN/QUKZTO |
|
Study Scope |
|
|
Keywords: |
Agricultural Sciences, Earth and Environmental Sciences, Climate change, Cocoa, Food security, Agriculture, Adaptation, Latin America and the Caribbean, Decision and Policy Analysis - DAPA |
|
Topic Classification: |
Climate change |
|
Abstract: |
These data correspond to the results of the agroclimatic zones of cocoa for the Central America and the Caribbean regions and per country. The data make reference to the ideal zones for cocoa production in three different periods of time (baseline 1970-2000, 2020 - 2049, 2040 - 2069), which allows us to know what would be the impact of climate change for the crop, and therefore, establish a first route for prospective planning in the different countries under study and the region. This analysis was done with a machine learning approach: Random Forest model, which took into account climatic variables, such as precipitation, temperature and evapotranspiration. The model was trained with presence data for construction. |
|
Geographic Coverage: |
Central America and the Caribbean |
|
Kind of Data: |
Geospatial Data |
|
Kind of Data: |
Climate Data |
|
Methodology and Processing |
|
|
Sources Statement |
|
|
Data Access |
|
|
Disclaimer: |
Whilst utmost care has been taken by CIAT and data authors while collecting and compiling the data, the data is however offered "as is" with no express or implied warranty. In no event shall the data authors, CIAT, or relevant funding agencies be liable for any actual, incidental or consequential damages arising from use of the data. <BR/><BR/> By using the CIAT Dataverse, the user expressly acknowledges that the Data may contain some nonconformities, defects, or errors. No warranty is given that the data will meet the user's needs or expectations or that all nonconformities, defects, or errors can or will be corrected. <BR/><BR/> The user should always verify actual data; therefore the user bears all responsibility in determining whether the data is fit for the user’s intended use. The user of the data should use the related publications as a baseline for their analysis whenever possible. Doing so will be an added safeguard against misinterpretation of the data. Related publications are listed in the metadata section of the Dataverse study. |
|
Notes: |
<P><a rel="license" href="http://creativecommons.org/licenses/by/4.0/" target="_blank"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br /> These data and documents are licensed under a <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank"> Creative Commons Attribution 4.0 International license.</a> You may copy, distribute and transmit the data as long as you acknowledge the source through proper <a href="http://best-practices.dataverse.org/data-citation/" target="_blank">data citation</a>.</P> <Strong>Disclaimer</Strong> <P> Whilst utmost care has been taken by CIAT and data authors while collecting and compiling the data, the data is however offered "as is" with no express or implied warranty. In no event shall the data authors, CIAT, or relevant funding agencies be liable for any actual, incidental or consequential damages arising from use of the data. <BR/><BR/> By using the CIAT Dataverse, the user expressly acknowledges that the Data may contain some nonconformities, defects, or errors. No warranty is given that the data will meet the user's needs or expectations or that all nonconformities, defects, or errors can or will be corrected. <BR/><BR/> The user should always verify actual data; therefore the user bears all responsibility in determining whether the data is fit for the user’s intended use. The user of the data should use the related publications as a baseline for their analysis whenever possible. Doing so will be an added safeguard against misinterpretation of the data. Related publications are listed in the metadata section of the Dataverse study. </P> |
|
Other Study Description Materials |
|
|
Related Publications |
|
|
Citation |
|
|
Title: |
Bunn, C; Lundy, M; Wiegel, J; Castro-Llanos, F. (2019). Impacto del cambio climático en la producción de cacao para Centroamérica y El Caribe. Centro Internacional de Agricultura Tropical (CIAT), Cali, CO. 34 p. |
|
Identification Number: |
10568/101293 |
|
Bibliographic Citation: |
Bunn, C; Lundy, M; Wiegel, J; Castro-Llanos, F. (2019). Impacto del cambio climático en la producción de cacao para Centroamérica y El Caribe. Centro Internacional de Agricultura Tropical (CIAT), Cali, CO. 34 p. |
|
Label: |
Maps.zip |
|
Notes: |
application/zip |
|
Label: |
Raster_Data.zip |
|
Notes: |
application/zip |