Monitoring species abundance and distribution is a prerequisite when assessing species status and population viability, a difficult task to achieve for large herbivores at ecologically meaningful scales. Co-occurrence patterns can be used to infer mechanisms of community organization (such as biotic interactions), although it has been traditionally applied to binary presence/absence data. Here, we combine density surface and null models of abundance data as a novel approach to analyze the spatial and seasonal dynamics of abundance and distribution of guanacos (Lama guanicoe) and domestic herbivores in northern Patagonia, in order to visually and analytically compare the dispersion and co-occurrence pattern of ungulates. We found a marked seasonal pattern in abundance and spatial distribution of L. guanicoe. The guanaco population reached its maximum annual size and spatial dispersion in spring-summer, decreasing up to 6.5 times in size and occupying few sites of the study area in fall-winter. These results are evidence of the seasonal migration process of guanaco populations, an increasingly rare event for terrestrial mammals worldwide. The maximum number of guanacos estimated for spring (25951) is higher than the total population size (10000) 20 years ago, probably due to both counting methodology and population growth. Livestock were mostly distributed near human settlements, as expected by the sedentary management practiced by local people. Herbivore distribution was non-random; i.e., guanaco and livestock abundances co-varied negatively in all seasons, more than expected by chance. Segregation degree of guanaco and small-livestock (goats and sheep) was comparatively stronger than that of guanaco and large-livestock, suggesting a competition mechanism between ecologically similar herbivores, although various environmental factors could also contribute to habitat segregation. The new and compelling combination of methods used here is highly useful for researchers who conduct counts of animals to simultaneously estimate population sizes, distributions, assess temporal trends and characterize multi-species spatial interactions.
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Species occurrence depends on both environmental and biotic factors (species interactions). Consideration of species interactions when estimating functions of population distribution is unusual, and may be crucial to understand and predict how species use space and resources. In this study, we combine resource selection probability functions (RSPFs) with a model selection approach based on information theory to evaluate how biotic (interspecific interactions) and abiotic (environmental) factors affect resource selection of guanacos Lama guanicoe and livestock (goats, sheep, cattle and horses) in two seasonal periods. We first test different a priori hypotheses of the environmental effects on guanacos and livestock occurrence (i.e. foraging, predation/topography and human effect hypotheses), then we assess model performance with independent data, and finally we use validated models of each species as predictors of the interaction between them. In all seasons, L. guanicoe occurrence was influenced by both environment and livestock interactions, especially small livestock (goats and sheep). Guanacos selected for habitats characterized by high temporal variability in plant productivity and away from potential human contact. In all seasons, L. guanicoe was negatively related to the RSPF of small livestock, but the reverse was not the case, suggesting that L. guanicoe avoids sites used by goats and sheep. In contrast, livestock was mainly affected by environmental variables related to human presence and was not affected by the interactions with herbivores. Contrary to our predictions, goats and sheep were also associated with less productive sites, probably indicating strong degradation of the sites to which they are restricted. Our results suggest a spatial segregation between L. guanicoe and domestic herbivores throughout the year, which is explained by competitive interactions of L. guanicoe with small livestock but also in response to vegetation productivity and human pressure. This study shows the importance of including species interaction effects in habitat modeling.
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