Home > Research > Publications & Outputs > A Bayesian geostatistical Moran curve model for...

Links

Text available via DOI:

View graph of relations

A Bayesian geostatistical Moran curve model for estimating net changes of Tsetse populations in Zambia

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published

Standard

A Bayesian geostatistical Moran curve model for estimating net changes of Tsetse populations in Zambia. / Sedda, Luigi; Mweempwa, Cornelius; Ducheyne, Els et al.
In: PLoS ONE, Vol. 9, No. 4, 96002, 22.04.2014.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Sedda, L, Mweempwa, C, Ducheyne, E, De Pus, C, Hendrickx, G & Rogers, DJ 2014, 'A Bayesian geostatistical Moran curve model for estimating net changes of Tsetse populations in Zambia', PLoS ONE, vol. 9, no. 4, 96002. https://doi.org/10.1371/journal.pone.0096002

APA

Sedda, L., Mweempwa, C., Ducheyne, E., De Pus, C., Hendrickx, G., & Rogers, D. J. (2014). A Bayesian geostatistical Moran curve model for estimating net changes of Tsetse populations in Zambia. PLoS ONE, 9(4), Article 96002. https://doi.org/10.1371/journal.pone.0096002

Vancouver

Sedda L, Mweempwa C, Ducheyne E, De Pus C, Hendrickx G, Rogers DJ. A Bayesian geostatistical Moran curve model for estimating net changes of Tsetse populations in Zambia. PLoS ONE. 2014 Apr 22;9(4):96002. doi: 10.1371/journal.pone.0096002

Author

Sedda, Luigi ; Mweempwa, Cornelius ; Ducheyne, Els et al. / A Bayesian geostatistical Moran curve model for estimating net changes of Tsetse populations in Zambia. In: PLoS ONE. 2014 ; Vol. 9, No. 4.

Bibtex

@article{96a49fdf2fa1443c8000f80807cefbc2,
title = "A Bayesian geostatistical Moran curve model for estimating net changes of Tsetse populations in Zambia",
abstract = "For the first time a Bayesian geostatistical version of the Moran Curve, a logarithmic form of the Ricker stock recruitment curve, is proposed that is able to give an estimate of net change in population demographic rates considering components such as fertility and density dependent and density independent mortalities. The method is applied to spatio-temporally referenced count data of tsetse flies obtained from fly-rounds. The model is a linear regression with three components: population rate of change estimated from the Moran curve, an explicit spatio-temporal covariance, and the observation error optimised within a Bayesian framework. The model was applied to the three main climate seasons of Zambia (rainy January to April, cold-dry-May to August, and hot-dry-September to December) taking into account land surface temperature and (seasonally changing) cattle distribution. The model shows a maximum positive net change during the hot-dry season and a minimum between the rainy and cold-dry seasons. Density independent losses are correlated positively with day-time land surface temperature and negatively with night-time land surface temperature and cattle distribution. The inclusion of density dependent mortality increases considerably the goodness of fit of the model. Cross validation with an independent dataset taken from the same area resulted in a very accurate estimate of tsetse catches. In general, the overall framework provides an important tool for vector control and eradication by identifying vector population concentrations and local vector demographic rates. It can also be applied to the case of sustainable harvesting of natural populations.",
keywords = "GLOSSINA-MORSITANS-MORSITANS, ROBINEAU-DESVOIDY DIPTERA, LINEAR MIXED MODELS, LOCAL VARIATION, DYNAMICS, VARIABILITY, CONVERGENCE, UNCERTAINTY, ZIMBABWE, FLIES",
author = "Luigi Sedda and Cornelius Mweempwa and Els Ducheyne and {De Pus}, Claudia and Guy Hendrickx and Rogers, {David J.}",
year = "2014",
month = apr,
day = "22",
doi = "10.1371/journal.pone.0096002",
language = "English",
volume = "9",
journal = "PLoS ONE",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "4",

}

RIS

TY - JOUR

T1 - A Bayesian geostatistical Moran curve model for estimating net changes of Tsetse populations in Zambia

AU - Sedda, Luigi

AU - Mweempwa, Cornelius

AU - Ducheyne, Els

AU - De Pus, Claudia

AU - Hendrickx, Guy

AU - Rogers, David J.

PY - 2014/4/22

Y1 - 2014/4/22

N2 - For the first time a Bayesian geostatistical version of the Moran Curve, a logarithmic form of the Ricker stock recruitment curve, is proposed that is able to give an estimate of net change in population demographic rates considering components such as fertility and density dependent and density independent mortalities. The method is applied to spatio-temporally referenced count data of tsetse flies obtained from fly-rounds. The model is a linear regression with three components: population rate of change estimated from the Moran curve, an explicit spatio-temporal covariance, and the observation error optimised within a Bayesian framework. The model was applied to the three main climate seasons of Zambia (rainy January to April, cold-dry-May to August, and hot-dry-September to December) taking into account land surface temperature and (seasonally changing) cattle distribution. The model shows a maximum positive net change during the hot-dry season and a minimum between the rainy and cold-dry seasons. Density independent losses are correlated positively with day-time land surface temperature and negatively with night-time land surface temperature and cattle distribution. The inclusion of density dependent mortality increases considerably the goodness of fit of the model. Cross validation with an independent dataset taken from the same area resulted in a very accurate estimate of tsetse catches. In general, the overall framework provides an important tool for vector control and eradication by identifying vector population concentrations and local vector demographic rates. It can also be applied to the case of sustainable harvesting of natural populations.

AB - For the first time a Bayesian geostatistical version of the Moran Curve, a logarithmic form of the Ricker stock recruitment curve, is proposed that is able to give an estimate of net change in population demographic rates considering components such as fertility and density dependent and density independent mortalities. The method is applied to spatio-temporally referenced count data of tsetse flies obtained from fly-rounds. The model is a linear regression with three components: population rate of change estimated from the Moran curve, an explicit spatio-temporal covariance, and the observation error optimised within a Bayesian framework. The model was applied to the three main climate seasons of Zambia (rainy January to April, cold-dry-May to August, and hot-dry-September to December) taking into account land surface temperature and (seasonally changing) cattle distribution. The model shows a maximum positive net change during the hot-dry season and a minimum between the rainy and cold-dry seasons. Density independent losses are correlated positively with day-time land surface temperature and negatively with night-time land surface temperature and cattle distribution. The inclusion of density dependent mortality increases considerably the goodness of fit of the model. Cross validation with an independent dataset taken from the same area resulted in a very accurate estimate of tsetse catches. In general, the overall framework provides an important tool for vector control and eradication by identifying vector population concentrations and local vector demographic rates. It can also be applied to the case of sustainable harvesting of natural populations.

KW - GLOSSINA-MORSITANS-MORSITANS

KW - ROBINEAU-DESVOIDY DIPTERA

KW - LINEAR MIXED MODELS

KW - LOCAL VARIATION

KW - DYNAMICS

KW - VARIABILITY

KW - CONVERGENCE

KW - UNCERTAINTY

KW - ZIMBABWE

KW - FLIES

U2 - 10.1371/journal.pone.0096002

DO - 10.1371/journal.pone.0096002

M3 - Journal article

VL - 9

JO - PLoS ONE

JF - PLoS ONE

SN - 1932-6203

IS - 4

M1 - 96002

ER -