The aim of this work was to explore the relationship between population density of Akodon azarae (Muridae: Sigmodontinae) and climatic and environmental variables, and determine which of them are associated to within and among-year changes in rodent abundance in agro-ecosystems from south Córdoba, Argentina. The study was carried out in a rural area of central Argentina, from 1983 to 2003. Density was estimated as a relative density index (RDI). Temperature, precipitation and humidity were obtained from records of the National University of Rio Cuarto. Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature were recorded from National Oceanic and Atmospheric Administration (1983)(1984)(1985)(1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998) and Landsat (1998Landsat ( -2003 imagery data sets. We performed simple correlations, multiple regressions and distributed lag analysis. Direct association of climatic and environmental variables with RDI was in general, low. The amount of variability in seasonal changes in density explained by climatic and environmental variables altogether varied from 10% to 70%. Seasonal population fluctuations were influenced by NDVI and rainfall with one and two seasons of delay. Autumn maximum density of the species was also associated with vegetation and rainfall of previous seasons. There also seemed to be an indirect influence of rainfall through vegetation given that we found a positive correlation between them. Results were consistent with basic aspects of the ecology of the species, such as its strong preference for highly covered areas, which provide food and protection from predators, likely increasing its reproductive success. Therefore, in the rural area central Argentina, A. azarae showed seasonal fluctuations with delayed influence of rainfall and vegetation and indirect effects of rainfall.

We constructed a model to predict the potential distribution of Oligoryzomys longicaudatus, the reservoir of Andes virus (Genus: Hantavirus), in Argentina. We developed an extensive database of occurrence records from published studies and our own surveys and compared two methods to model the probability of O. longicaudatus presence; logistic regression and MaxEnt algorithm. The environmental variables used were tree, grass and bare soil cover from MODIS imagery and, altitude and 19 bioclimatic variables from WorldClim database. The models performances were evaluated and compared both by threshold dependent and independent measures. The best models included tree and grass cover, mean diurnal temperature range, and precipitation of the warmest and coldest seasons. The potential distribution maps for O. longicaudatus predicted the highest occurrence probabilities along the Andes range, from 32°S and narrowing southwards. They also predicted high probabilities for the south-central area of Argentina, reaching the Atlantic coast. The Hantavirus Pulmonary Syndrome cases coincided with mean occurrence probabilities of 95 and 77% for logistic and MaxEnt models, respectively. HPS transmission zones in Argentine Patagonia matched the areas with the highest probability of presence. Therefore, colilargos presence probability may provide an approximate risk of transmission and act as an early tool to guide control and prevention plans.

Understanding the role of feedback structure (endogenous processes) and exogenous (climatic and environmental) factors in shaping the dynamics of natural populations is a central challenge within the field of population ecology. We attempted to explain the numerical fluctuations of two sympatric rodent species in agro-ecosystems of central Argentina using Royama's theoretical framework for analyzing the dynamics of populations influenced by exogenous climatic forces. We found that both rodent species show a first-order negative feedback structure, suggesting that these populations are regulated by intra-specific competition (limited by food, space, or enemy-free space). In Akodon azarae endogenous structure seems to be very strongly influenced by human land-use represented by annual minimum normalized difference vegetation index (NDVI), with spring and summer rainfall having little influence upon carrying capacity.Calomys venustus' population dynamics, on the other hand, seem to be more affected by local climate, also with spring and summer rainfall influencing the carrying capacity of the environment, but combined with spring mean temperature.

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We use a Species Distribution Modeling (SDM) approach along with Geographic Information Systems (GIS) techniques to examine the potential distribution of hantavirus pulmonary syndrome (HPS) caused by Andes virus (ANDV) in southern Argentina and, more precisely, define and estimate the area with the highest infection probability for humans, through the combination with the distribution map for the competent rodent host (Oligoryzomys longicaudatus). Sites with confirmed cases of HPS in the period 1995–2009 were mostly concentrated in a narrow strip (~90 km × 900 km) along the Andes range from northern Neuquén to central Chubut province. This area is characterized by high mean annual precipitation (~1,000 mm on average), but dry summers (less than 100 mm), very low percentages of bare soil (~10% on average) and low temperatures in the coldest month (minimum average temperature −1.5 °C), as compared to the HPS-free areas, features that coincide with sub-Antarctic forests and shrublands (especially those dominated by the invasive plant Rosa rubiginosa), where rodent host abundances and ANDV prevalences are known to be the highest. Through the combination of predictive distribution maps of the reservoir host and disease cases, we found that the area with the highest probability for HPS to occur overlaps only 28% with the most suitable habitat for O. longicaudatus. With this approach, we made a step forward in the understanding of the risk factors that need to be considered in the forecasting and mapping of risk at the regional/national scale. We propose the implementation and use of thematic maps, such as the one built here, as a basic tool allowing public health authorities to focus surveillance efforts and normally scarce resources for prevention and control actions in vast areas like southern Argentina.