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.
Highlights
There are several ways of analysing animal and plant population data
Rogers, studying tsetse flies in Africa [3], was the first to connect these two approaches by applying the density dependent and density independent losses concepts of the Varley and Gradwell approach to the logarithmic form of Ricker curve, called a Moran curve
Field Methods Analysis was applied to data for tsetse flies (Glossina morsitans morsitans Westwood) from South-Eastern Zambia
Summary
The simplest involves an actuarial approach as applied to human populations where the likelihood of death and the expectation of future life are assumed to depend only upon age. For many animal and plant populations, mortality comes about from both density independent and density dependent effects and the simple actuarial approach is no longer valid. Whilst Varley and Gradwell’s life-table approach [1] was developed for species with non-overlapping generations, the Ricker curve [2] can be applied to species with overlapping generations. Tsetse have continuous overlapping generations and the Moran curve approach was shown, through its application to the output of a simple tsetse population model, to be able to quantify (as k-values) the mean monthly density dependent and density independent losses of tsetse in Nigeria and Zambia
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