1 research outputs found
N-mixture models provide informative crocodile (Crocodylus moreletii) abundance estimates in dynamic environments
Estimates of animal abundance provide essential information for population
ecological studies. However, the recording of individuals in the field can be
challenging, and accurate estimates require analytical techniques which account for
imperfect detection. Here, we quantify local abundances and overall population
size of Morelet’s crocodiles (Crocodylus moreletii) in the region of Calakmul
(Campeche, Mexico), comparing traditional approaches for crocodylians (Minimum
Population Size—MPS; King’s Visible Fraction Method—VFM) with binomial
N-mixture models based on Poisson, zero-inflated Poisson (ZIP) and negative
binomial (NB) distributions. A total of 191 nocturnal spotlight surveys were
conducted across 40 representative locations (hydrologically highly dynamic
aquatic sites locally known as aguadas) over a period of 3 years (2017–2019). Local
abundance estimates revealed a median of 1 both through MPS (min–max: 0–89; first
and third quartiles, Q1–Q3: 0–7) and VFM (0–112; Q1–Q3: 0–9) non-hatchling
C. moreletii for each aguada, respectively. The ZIP based N-mixture approach shown
overall superior confidence over Poisson and NB, and revealed a median of 6 ± 3
individuals (min = 0; max = 120 ± 18; Q1 = 0; Q3 = 18 ± 4) jointly with higher
detectabilities in drying aguadas with low and intermediate vegetation cover.
Extrapolating these inferences across all waterbodies in the study area yielded an
estimated ~10,000 (7,000–11,000) C. moreletii present, highlighting Calakmul as
an important region for this species. Because covariates enable insights into
population responses to local environmental conditions, N-mixture models applied
to spotlight count data result in particularly insightful estimates of crocodylian
detection and abundance