An alternative method for calf density and recruitment estimation using pregnancy on wild guanacos (Lama guanicoe).

Per capita recruitment is a parameter that determines most of the variation in population growth rate in wild temperate ungulates and it is generally estimated by young:female ratio. It has been proposed that this approach should be improved since only count data is used in most cases and the probability of observing calves at heel declines with the age of the calf because it is more independent of the mother. In this study, we propose an alternative method to estimate calf density (ACD) using pregnancy rate obtained from hormonal fecal metabolites and total density estimates. Then we use ACD to calculate recruitment by young:female ratio and compare the results with recruitment estimates using traditional count data (TCD). To set the parameters of ACD we used information of a partially-migratory guanaco (Lama guanicoe) population of La Payunia Provincial Reserve (Mendoza-Argentina). We calculated ACD by the following equation:A=p×h×s×D (eq. 1), where p is the pregnancy rate (0.32), s is the probability of survival (0.61), h is female's proportion (0.60), D is total density and A is calf density. First, we ran a data simulation to calculate A, using p, h, and s as deterministic parameters and D as a random parameter with a Log-Normal distribution. With the simulated data, we calculated per capita recruitment (R) and we adjusted a density-dependent model, as is expected for large ungulates: LogR=-0,179*D*[exp⁡(-0,013*D)] (eq. 2). Second, we used real data of four population surveys to estimate density by ACD. To do this we replaced the D term of the eq. 1 with field data and then, we calculated recruitment using those results. All the other terms of eq. 1 were kept the same because they belong to the population under study. Third, we estimated recruitment by young:female ratio using count data of the same surveys and compared real data recruitment estimations by ACD and TCD. Both estimations seem to follow the same pattern of the simulated data. However, recruitment obtained using ACD (0.09; 0.06; 0.07; 0.05) were lower than those calculated by TCD (0.36; 0.10; 0.31; 0.18). We hypothesized two main reasons: 1) our estimation is assuming a constant pregnancy rate; therefore, if new pregnant females entered the area under study from nearby regions from one year to the other, that information was not considered and could have led to an underestimation of recruitment by ACD. 2) In general, only a small number of calves is counted in population surveys, which may increase data dispersion, and as a consequence an overestimation of recruitment by TCD. Our innovative approach using total density estimations and pregnancy data might be useful to estimate young densities avoiding the problems of counting calves. As recruitment is one of the most important parameters to make management decisions like population control, our approach might be an alternative to reduce count data biases and should be tested in other ungulates populations.