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Canine fecal contamination in public green areas is difficult to control. Our objectives were to assess: (i) the relationship between fecal contamination in public green spaces of Buenos Aires (Argentina) and the type of green space (boulevard/square/park), considering their area, presence/absence of control measures, and human population density in the surroundings (high or low); (ii) the perception of people of such contamination and (iii) the frequency of parasites in dog feces. In each green space (n = 26), feces were counted in thirty 25-m2 plots randomly located. The opinion survey consisted of asking people (358) what their perception of fecal contamination was, whether it bothered them and whether they thought it was hazardous to the dogs’ or people’ health. Canine fecal samples randomly collected (n = 112) were concentrated and examined microscopically. Mixed-effect generalized linear models were fitted to evaluate the effect of selected variables on fecal contamination. People’s perception of human and canine health risks were assessed by logistic regression. Canine fecal contamination was lower in squares with control measures and in parks with control measures located in densely populated areas, and higher in boulevards located in densely populated areas. The visitor’s perception was that feces were associated with dirtiness (77%) and odor (30.8%). Parasites were detected in 51.8% of fecal samples. Our results confirm that environmental control measures decrease canine fecal contamination of public green spaces, and that more than 65% of the people interviewed do not relate fecal contamination to risks to human/dog health.

1. Information on resource selection by a species is essential for understanding the species' ecology, distribution and requirements for survival. Research on habitat selection frequently relies on animal detection at point locations to determine which resource units are used. A variety of approaches and statistical tools can be employed for assessing selection based on habitat variables measured in those units. The aim of this work is to evaluate the reliability of common sampling designs and statistical methods in detecting habitat selection at fine scales based on point data 2. We reviewed literature on microhabitat selection to determine characteristics of typical studies and analysed simulated small mammal live-trapping data as a case study. We considered various scenarios differing in the number of sampled units and sampling duration. For each scenario, a set of simulated surveys was analysed through two univariate Accepted ArticleThis article is protected by copyright. All rights reserved.tests (Welch's t-and Mann-Whitney U-test), generalised linear models (GLMs), mixed-effect models (GLMMs) and occupancy models (OMs). 3.Analysis of simulated data revealed that overall performance of all statistical methods improved with increased trapping effort. Univariate tests were especially sensitive to the number of sampling units, while modelling methods took also advantage of longer trapping sessions. Univariate tests and GLMs provided partially correct information in most cases, whereas GLMMs and OMs offered higher probabilities of fully describing simulated habitat preferences. 4.With typical sampling efforts, appropriate statistical analysis of point data is able to provide a moderately accurate description of habitat selection at small scales, in spite of the violation of closure and independence assumptions of applied models. Modelling approaches are proliferating; we encourage using models that can deal with multiple sources of variability, such as GLMMs and OMs, when data are hierarchically structured.There is no a priori best survey design; it should be chosen according to the scope and goals of the study, environment heterogeneity, species characteristics and practical constraints.Researchers should realise that sampling design and statistical methods likely affect conclusions regarding habitat selection.

Rodents are reservoirs of various types of hantavirus, some of which are agents of hantavirus pulmonary syndrome in humans. Each hantavirus is associated with a single rodent host species but successive spill‐over events may eventually lead to host‐switching and new species’ becoming host of a given pathogen. This study aims to gain an understanding of the spatial ecology of two hantavirus‐host species, Akodon azarae, and Oligoryzomys flavescens, by identifying factors modulating their home range sizes and stability, and by evaluating intra‐ and interspecific spatial aggregation for these species and a third one—Oxymycterus rufus—living in sympatry. For this, eleven capture‐mark‐recapture surveys were carried out, spanning 22 months. We found that A. azarae males have larger and more mobile home ranges than females, independently of the season. Consequently, males could likely have a more relevant role in the transmission of hantavirus because of their greater exposure both to a higher number of contacts between individuals and viral contamination of the environment. Contrasting, O. flavescens individuals showed negligible displacements of their home range through time, which could limit the range of hantavirus spread in host populations. Since O. flavescens is host to Lechiguanas hantavirus (pathogenic to humans) this result encompasses epidemiological relevance, for it may imply the existence of local foci of infection. Additionally, individuals of both species performed excursions outside their home ranges. These events could enable hantavirus spread over distances beyond the normal range of movements and lead to new hantavirus outbreaks in formerly non‐infected rodent populations, favoring the persistence of the virus in nature.

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Small‐mammal population densities can be regulated by bottom‐up (food availability) and top‐down (predation) forces. In 1993, an El Niño Southern Oscillation event was followed by a cluster of human hantavirus with pulmonary syndrome in the southwestern United States. An upward trophic cascade hypothesis was proposed as an explanation for the outbreak: Increased plant productivity as a consequence of El Niño precipitations led to an unusual increase in distribution and abundance of deer mice (Peromyscus maniculatus; reservoir host of Sin Nombre virus). Could such drastic events occur in mesic habitats, where plant productivity in response to climate conditions is likely to be much less dramatic? In this work, we investigate to what extent deer mouse populations follow a precipitation‐driven, bottom‐up model in central and western Montana and discuss important conditions for such a model to be possible. We found positive correlations between deer mouse abundance and on‐the‐ground measured plant productivity with a several‐month lag in three of six study sites. This effect was weaker when deer mouse populations were more abundant, indicating density‐dependent effects. Dispersal resulting from territoriality may be important in attenuating local density increments in spite of high food availability. In addition, there is evidence that population abundance in the study area could respond to other abiotic factors. In particular, precipitation in the form of snow may reduce deer mice survival, thus compensating the benefits of improved plant productivity. Deer mouse populations in Montana study sites follow complex dynamics determined by multiple limiting factors, leading to a damped precipitation‐driven bottom‐up regulation. This prevents dramatic changes in rodent abundances after sudden increments of food availability, such as those observed in other regions.

During the 20th century, there has been an ongoing agricultural expansion and global warming, two of the main determinants influencing biodiversity changes in Argentina. The red hocicudo mouse (Oxymycterus rufus) inhabits subtropical grasslands and riparian habitats and has increased its abundance in recent years in central Argentina agroecosystems. This paper describes the long‐term temporal changes in O. rufus abundance in Exaltación de la Cruz department, Buenos Aires province, Argentina, in relation to weather fluctuations and landscape features, as well as analyzes the spatio‐temporal structure of captures of animals. We used generalized liner models, semivariograms, the Mantel test, and autocorrelation functions for the analysis of rodent data obtained from trappings conducted between 1984 and 2014. O. rufus showed an increase in abundance across the years of study, with its distribution depending on landscape features, such as habitat types and the distance to floodplains. Capture rates showed a spatio‐temporal aggregation, suggesting expansion from previously occupied sites. O. rufus was more abundant at lower minimum temperatures in summer, higher precipitation in spring and summer, and lower precipitations in winter. Weather conditions affected O. rufus abundance, but there was local variation that differed from global patterns of climate change.

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