English
 
Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

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

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

Item is

Files

show Files
hide Files
:
khubaib_et_al.pdf (Preprint), 2MB
 
File Permalink:
-
Name:
khubaib_et_al.pdf
Description:
-
Visibility:
Private
MIME-Type / Checksum:
application/pdf
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Khubaib, Nusaiba1, Author
Asad, Saeed A.1, Author
Khalil, Tayyaba1, Author
Baig, Ayesha1, Author
Atif, Salman1, Author
Umar, Muhammad1, Author
Kropp, Jürgen P.2, Author              
Pradhan, Prajal2, Author              
Baig, Sofia1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

Content

show
hide
Free keywords: -
 Abstract: 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.

Details

show
hide
Language(s):
 Dates: 2020-12-032021-02-252021-04-10
 Publication Status: Finally published
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: MDB-ID: No data to archive
PIKDOMAIN: RD2 - Climate Resilience
Organisational keyword: RD2 - Climate Resilience
DOI: 10.3354/cr01631
Research topic keyword: Climate impacts
Research topic keyword: Food & Agriculture
Regional keyword: Asia
Model / method: Open Source Software
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Climate Research
Source Genre: Journal, SCI, Scopus, p3
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 83 Sequence Number: - Start / End Page: 15 - 25 Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/journals79
Publisher: Inter-Research Science Publisher