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With ongoing climate change, there is a pressing need to better understand how much water is stored as ground ice in areas with extensive permafrost occurrence, as well as how the regional water balance may alter in response to the potential generation of meltwater from permafrost degradation. However, field-based data on permafrost in remote and mountainous areas such as the South American Andes are scarce. Most current ground ice estimates are based on broadly generalized assumptions such as volume–area scaling and mean ground ice content estimates of rock glaciers. In addition, ground ice contents in permafrost areas outside of rock glaciers are usually not considered, resulting in a significant uncertainty regarding the volume of ground ice in the Andes and its hydrological role. In Part 1 of this contribution, present an extensive geophysical data set based on electrical resistivity tomography and refraction seismic tomography surveys to detect and quantify ground ice of different landforms and surface types in several study regions in the semi-arid Andes of Chile and Argentina with the aim to contribute to the reduction of this data scarcity. In Part 2 we focus on the development of a strategy for the upscaling of geophysics-based ground ice quantification to an entire catchment to estimate the total ground ice volume (and its approximate water equivalent) in the study areas. In addition to the geophysical data, the upscaling approach is based on a permafrost distribution model and classifications of surface and landform types. In this paper, we introduce our upscaling strategy, and we demonstrate that the estimation of large-scale ground ice volumes can be improved by including (i) non-rock-glacier permafrost occurrences and (ii) field evidence through a large number of geophysical surveys and ground truthing information. The results of our study indicate that (i) conventional ground ice estimates for rock-glacier-dominated catchments without in situ data may significantly overestimate ground ice contents and (ii) substantial volumes of ground ice may also be present in catchments where rock glaciers are lacking. [ABSTRACT FROM AUTHOR]

Andes south virus (ANDV) is the etiologic agent of hantavirus cardiopulmonary syndrome (HCPS) in Chile and southern Argentina. Farm and forestry workers have been identified as a group at high risk of acquiring HCPS caused by ANDV due to their close exposure to rodents or their secretions in rural areas. Therefore, investigation on the effect of landscape composition on ANDV in wild rodents becomes relevant for disease prevention and control. In this study, we analyzed the influence of Monterey pine (Pinus radiata) plantations, an important monoculture in the global forest industry, on small mammal assemblage and on ANDV seroprevalence and abundance of seropositive rodents from central Chile. Small mammals were sampled seasonally during 2 years in native forests, adult pine plantations and young pine plantations. A total of 1630 samples from seven rodent species were analyzed for antibody detection. ANDV seroprevalence and abundance of seropositive rodents were significantly higher in the native forest compared to pine plantations. Furthermore, Monterey pine plantations decrease the abundance and relative abundance of Oligoryzomys longicaudatus (the principal reservoir of ANDV) and do not change sex ratio and distribution of age classes of this rodent species, which are variables that are important for ANDV transmission. Our findings indicate that Monterey pine plantations would not pose a higher risk of human exposure to ANDV compared to the temperate native forest. Our results can be useful for hantavirus risks assessment in human-dominated areas where ANDV is endemic. [ABSTRACT FROM AUTHOR]

Background. Climate change is one of the greatest threats to biodiversity, pushing species to shift their distribution ranges and making existing protected areas inadequate. Estimating species distribution and potential modifications under climate change are then necessary for adjusting conservation and management plans; this is especially true for endangered species. An example of this issue is the huemul (Hippocamelus bisulcus), an endemic endangered deer from the southern Andes Range, with less than 2,000 individuals. It is distributed in fragmented populations along a 2,000 km latitudinal gradient, in Chile and Argentina. Several threats have reduced its distribution to <50% of its former range. Methods. To estimate its potential distribution and protected areas effectiveness, we constructed a species distribution model using 2,813 huemul presence points throughout its whole distribution range, together with 19 bioclimatic layers and altitude information from Worldclim. Its current distribution was projected for years 2050 and 2070 using five different Global Climate Models estimated for scenarios representing two carbon Representative Concentration Routes (RCP)RCP4.5 and RCP6.0. Results. Based on current huemul habitat variables, we estimated 91,617 km² of suitable habitat. In future scenarios of climate change, there was a loss of suitable habitat due to altitudinal and latitudinal variation. Future projections showed a decrease of 59.86-60.26% for the year 2050 and 58.57-64.34% for the year 2070 according to RCP4.5 and RCP6.0, respectively. Protected areas only covered only 36.18% of the present distribution, 38.57-34.94% for the year 2050 and 30.79-31.94% for 2070 under climate change scenarios. Discussion. Modeling current and future huemul distributions should allow the establishment of priority conservation areas in which to focus efforts and funds, especially areas without official protection. In this way, we can improve management in areas heavily affected by climate change to help ensure the persistence of this deer and other species under similar circumstances worldwide. [ABSTRACT FROM AUTHOR]