Combining N-mixture models with ecological niche modeling supplies a low-cost and fast procedure for estimating population size in remote areas

Monitoring population changes and trends is a central task in conservation. However, obtaining detailed information for wide and low accessible areas, such as remote islands, is challenging, and cannot be achieved with conventional approaches, such as capture-mark-recapture protocols (CMR). In this paper, we show that combining N-mixture models with ecological niche modeling allows assessing reliable estimates of population size over large target areas on short time intervals. We used it to estimate the population size of a subspecies of the Italian wall lizards (Podarcis siculus calabresiae) endemic to the Island of Montecristo (10.39 km(2) in surface). During a single week, we first generated a niche model of the species based on satellite images sampled few days before sampling. Then, we estimated lizard abundance through Bayesian N-mixture models on repeated counts (n=3) along transects (n=6), settled in different areas of habitat suitability defined on the basis of the niche model. Finally, we estimated in approximately 20.000 the total number of lizards living in the Island by extrapolating the values computed on transects to the areas of the islands with the same suitability estimated by the niche model. The procedure can be easily repeated allowing monitoring the status of conservation of the species in the island of Montecristo. More in general, this procedure has the potential to be applied to monitor any other species of conservation interest in remote areas whenever detailed satellite images are available.[GRAPHICS]

Opportunistic datasets perform poorly in Ecological Niche Modelling: a case study from a polymorphic lizard

Context. Among processes involved in colour polymorphism, geographic variation in morph composition and frequency has been attracting interest since it reflects morph local adaptation. A recent study in the Pyrenees associated the pattern of geographic variation in morph frequency of the common wall lizard with the divergence in climatic niches, supporting the hypothesis that morphs represent alternative local climatic adaptations. However, the Pyrenees represent only a small portion of the species range. Aims. We modelled the ecological niches of Italian morphs using the same procedure adopted for the Pyrenees to check whether the effects detected at local scales (i.e. the Pyrenees) were repeatable at regional scales (i.e. Italy). This generalisation is needed to investigate how natural selection maintains locally adapted polymorphisms. Methods. We classified each locality (120 populations) according to the presence/absence of morphs, and independent Ecological Niche Models (ENMs) against the same background were fitted. Receiver Operating Curves accounting for sampling biases, equivalency and similarity tests were used to check and compare models accounting for spatial distribution of data. Key results. Morph-specific ENMs did not reproduce any of the patterns detected in the Pyrenees. Any difference among morphs disappeared after controlling for morph spatial distribution. Since occurrence points of the rarest morphs were a subsample of the occurrence points of the most common morph, it is not possible to separate the effects of true ecological differences among morphs from the effects of the spatial distribution patterns of morph occurrence. Conclusions. Using presence data not specifically collected for ENM comparisons does not allow reliable assessments of morph niche segregation. Our analysis points out the need to be very cautious in ecological interpretations of ENMs built on presence/background or presence-only data when occurrences are spatially nested