Leveraging browse and grazing forage estimates to optimize index-based livestock insurance

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cg.authorship.typesCGIAR and advanced research instituteen
cg.contributor.affiliationNew Mexico State Universityen
cg.contributor.affiliationInternational Livestock Research Instituteen
cg.contributor.affiliationUniversità degli Studi di Milanoen
cg.contributor.affiliationUniversity of Edinburghen
cg.contributor.crpLivestock
cg.contributor.donorCGIAR Trust Funden
cg.contributor.donorNational Academies of Sciencesen
cg.coverage.regionAfrica
cg.coverage.regionEastern Africa
cg.creator.identifierNathaniel Jensen: 0000-0002-2946-5771
cg.howPublishedFormally Publisheden
cg.identifier.doihttps://doi.org/10.1038/s41598-024-62893-4en
cg.isijournalISI Journalen
cg.issn2045-2322en
cg.issue1en
cg.journalScientific Reportsen
cg.reviewStatusPeer Reviewen
cg.subject.ilriANIMAL FEEDINGen
cg.subject.ilriCLIMATE CHANGEen
cg.subject.ilriDROUGHTen
cg.subject.ilriINSURANCEen
cg.subject.ilriLIVESTOCKen
cg.subject.ilriPASTORALISMen
cg.volume14en
dc.contributor.authorKahiu, Njokien
dc.contributor.authorAnchang, J.en
dc.contributor.authorAlulu, Vincenten
dc.contributor.authorFava, Francesco P.en
dc.contributor.authorJensen, Nathaniel D.en
dc.contributor.authorHanan, N.P.en
dc.date.accessioned2024-07-05T06:15:28Zen
dc.date.available2024-07-05T06:15:28Zen
dc.identifier.urihttps://hdl.handle.net/10568/148937
dc.titleLeveraging browse and grazing forage estimates to optimize index-based livestock insuranceen
dcterms.abstractAfrican pastoralists suffer recurrent droughts that cause high livestock mortality and vulnerability to climate change. The index-based livestock insurance (IBLI) program offers protection against drought impacts. However, the current IBLI design relying on the normalized difference vegetation index (NDVI) may pose limitation because it does not consider the mixed composition of rangelands (including herbaceous and woody plants) and the diverse feeding habits of grazers and browsers. To enhance IBLI, we assessed the efficacy of utilizing distinct browse and grazing forage estimates from woody LAI (LAIW) and herbaceous LAI (LAIH), respectively, derived from aggregate leaf area index (LAIA), as an alternative to NDVI for refined IBLI design. Using historical livestock mortality data from northern Kenya as reference ground dataset, our analysis compared two competing models for (1) aggregate forage estimates including sub-models for NDVI, LAI (LAIA); and (2) partitioned biomass model (LAIP) comprising LAIH and LAIW. By integrating forage estimates with ancillary environmental variables, we found that LAIP, with separate forage estimates, outperformed the aggregate models. For total livestock mortality, LAIP yielded the lowest RMSE (5.9 TLUs) and higher R2 (0.83), surpassing NDVI and LAIA models RMSE (9.3 TLUs) and R2 (0.6). A similar pattern was observed for species-specific livestock mortality. The influence of environmental variables across the models varied, depending on level of mortality aggregation or separation. Overall, forage availability was consistently the most influential variable, with species-specific models showing the different forage preferences in various animal types. These results suggest that deriving distinct browse and grazing forage estimates from LAIP has the potential to reduce basis risk by enhancing IBLI index accuracy.en
dcterms.accessRightsOpen Access
dcterms.audienceCGIARen
dcterms.audienceScientistsen
dcterms.available2024-06-27
dcterms.bibliographicCitationKahiu, N., Anchang, J., Alulu, V., Fava, F.P., Jensen, N. and Hanan, N.P. 2024. Leveraging browse and grazing forage estimates to optimize index-based livestock insurance. Scientific Reports 14:14834.en
dcterms.issued2024
dcterms.languageen
dcterms.licenseCC-BY-4.0
dcterms.publisherSpringeren
dcterms.subjectanimal feedingen
dcterms.subjectclimate changeen
dcterms.subjectdroughten
dcterms.subjectinsuranceen
dcterms.subjectpastoralismen
dcterms.subjectforageen
dcterms.typeJournal Article

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