Deutsch
 
Datenschutzhinweis Impressum
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Zeitschriftenartikel

Predicting areas suitable for wheat and maize cultivation under future climate change scenarios in Pakistan

Urheber*innen

Khubaib,  Nusaiba
External Organizations;

Asad,  Saeed A.
External Organizations;

Khalil,  Tayyaba
External Organizations;

Baig,  Ayesha
External Organizations;

Atif,  Salman
External Organizations;

Umar,  Muhammad
External Organizations;

/persons/resource/Juergen.Kropp

Kropp,  Jürgen P.
Potsdam Institute for Climate Impact Research;

/persons/resource/prajal.pradhan

Pradhan,  Prajal
Potsdam Institute for Climate Impact Research;

Baig,  Sofia
External Organizations;

Externe Ressourcen
Es sind keine externen Ressourcen hinterlegt
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte in PIKpublic verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Khubaib, N., Asad, S. A., Khalil, T., Baig, A., Atif, S., Umar, M., Kropp, J. P., Pradhan, P., Baig, S. (2021): Predicting areas suitable for wheat and maize cultivation under future climate change scenarios in Pakistan. - Climate Research, 83, 15-25.
https://doi.org/10.3354/cr01631


Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_24845
Zusammenfassung
Agriculture is vastly impacted by climate change which leads to the situation of food security or insecurity at both regional and global levels. Pakistan is predicted to go through an area reduction and geographical shifting of major crops in the near future. The present study asseses the potential future distribution of Wheat and Maize in Pakistan. Based on current location of these crops, Maxent species distribution model is used to predict future changes in crop distribution. 58 presence records for wheat and 48 presence records for maize are used. Model is simulated for current and future climate change scenarios (RCP 4.5 and RCP 8.5) using CMIP5 model, MPI-ESM-LR. Results from the model show a decline in production area, where wheat undergoes 30% to 35% reduction and maize 23% to 36% reduction depending upon climate change scenarios, RCP 4.5 and RCP 8.5. The model predictions are highly accurate with test AUC values of 0.88 for wheat and 0.89 for maize which are higher than 0.5 of a null-model. A Jackknife test for variable importance indicates that irrigation, precipitation seasonality and precipitation of warmest quarter are the most important environmental variables determining the potential geographic distribution of the crops. Due to the varying severity and nature of climate impacts, adaptation strategies are needed. The study can aid policy makers in devising policies which can help reduce the threat of future food insecurity in the region.