Coping with heterogeneity to detect species on a large scale: N-mixture modeling applied to red-legged partridge abundance

Abstract

The reliability of long‐term population estimates is crucial for conservation and management purposes. Most game species population monitoring programs assume that count indices are proportionally related to abundance. However, this assumption is untenable when detection varies spatially and temporally. We assessed whether N‐mixture models, which allow detection modeling using spatially and temporally repeated count data, were relevant for monitoring the population of red‐legged partridge (Alectoris rufa). Unbiased estimates are needed for calculating hunting quotas for this game species. We used the simple aural playback point‐count method and a dataset of 121 point‐transects (n = 16,288 counts) collected from 1992 to 2010. Covariates such as date, hour, wind, rain, and vegetation density influenced detection probability. Estimated abundance ranged from 0 to 15 males per point and exhibited variable coefficients of variation depending on sites (range: 0.14–1.31, mean: 0.44). We found a positive and linear relationship between the abundance estimated by the N‐mixture model and the densities provided by 2 other counting methods, square sampling and kilometric abundance index, but not with blank beat. We established a maximum detection radius for the playback surveys, which enabled conversion of abundance at the points into density. The N‐mixture modeling approach is more cost‐effective for game species monitoring than capture–recapture methods or square sampling, and more reliable than indices of relative abundances. © 2014 The Wildlife Society, 2014.

Post-release habitat utilisation by Francolinus bicalcaratus ayesha, a critically endangered subspecies endemic to Morocco: implications for optimising future release programmes

“…We conducted breeding season surveys in March 2014 and as the Double-spurred Francolin is territorial (the male sings to attract the female and to defend its territory), we used the point count method enhanced by playback (Hanane and Qninba 2014). Nowadays this technique is commonly used to increase the detection of many secretive bird species (Conway et al 1993, Zuberogoitia and Campos 1998, Brambilla and Rubolini 2004), such as Galliformes (Evans et al 2007, Ponce-Boutin 1992, Kasprzykowski and Goławski 2009, Jakob et al 2010, 2014, Fuller et al 2012). Ten permanent transects were established (1.2–1.5 km), on each of which 4–5 points were identified as being sufficiently far apart (0.2–0.3 km) to avoid double counting.…”

Improved analysis of lek count data using N‐mixture models

“…Furthermore, extensions of this model across seasons allow for explicit estimation of population trend (Kéry et al , Dail and Madsen ). To date, N ‐mixture models have been applied to a variety of species, including birds (Kéry et al , Kéry and Royle , Deluca and King , Jakob et al ), reptiles (Kéry et al ), fish (Kanno et al ), mammals (Priol et al ), and amphibians (Dodd and Dorazio ) to answer a variety of questions in basic and applied population ecology.…”

Temporal patterns of three sympatric pheasant species in the Nanling Mountains: N-mixture modeling applied to detect abundance

“…Moreover, the use of camera-trapping and N-mixture models for monitoring is more cost efficient than classical observation methods. A further point is that potential sources of detection heterogeneity are systematically surveyed and included in the model (Jakob et al 2014). In cases where local abundance is highly heterogeneous, different habitat covariates might be related to abundance to reduce the confidence interval of the estimates.…”

“…Since all three species are sympatrically distributed in several national nature reserves in the areas, estimating their population abundances locally in the nature reserves is particularly important for their conservation management. Reliable long-term count data are crucial for conservation status assessment and spatio-temporal prediction of bird abundance or population size (Chandler et al 2009;Jakob et al 2014). This is particularly true for Galliformes species in China (e.g.…”

“…Their use has been mainly restricted to studies of scrub-shrub bird species and certain game bird species (Chandler et al 2009) or as a basis for subsequent methodological development (Joseph et al 2009). For galliformes species, these models only have been used in studies of Red-legged Partridge (Alectoris rufa) (Jakob et al 2014), because of the difficulty of monitoring these endangered pheasants, and the relative lack of reliable and cost-effective replicated counts. In this study, we explored the potential of N-mixture modeling for estimating population abundance and detection probability of three sympatric pheasant species with a spatial distribution and examined the associated major management implications.…”