Browsing by Author "Miranda, Marcelo"

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    Chlorophyll-a MODIS mesoscale variability in the Inner Sea of Chiloe, Patagonia, Chile (41-43 degrees S): Patches and Gradients?
    (UNIV VALPARAISO, 2010) Lara, Carlos; Miranda, Marcelo; Montecino, Vivian; Luis Iriarte, Jose
    Satellite images are powerful tools to describe meso-and large-scale spatial structures, thus helping in the comprehension of the physical-biological processes taking place in the ocean. The objective of this study was to establish spatial (horizontal) and temporal (seasonal) variability of the autotrophic biomass measured as satellite chlorophyll concentrations (Chl-a) in the Inner Sea of Chiloe (41.0-43.5 degrees S). Remote sensing (MODIS) and geostatistics (Variograms) approaches were used to characterize Chl-a spatial-horizontal structure at the surface layer by anisotropic estimation of the Chl-a average values. A total of 27 selected images were analyzed and grouped into summer, spring, fall and winter seasons during the January 2003-December 2005 period. Image temporal analysis showed a classic pattern for the autotrophic biomass dynamics of cold temperate coastal areas, with highest Chl-a values occurring during the spring-summer period, and the lowest values during the fall-winter season. Image spatial analysis indicated that Chl-a is distributed into more homogeneous and larger than 50 km patches, during the fall-winter seasons, whereas during the spring-summer seasons more heterogeneous and smaller than 30 km patches were found. The anisotropy analysis showed a predominant angle in the East-West direction, suggesting the role of water column stratification as a modulating process of surface Chl-a spatial variability in the Inner Sea of Chiloe area.
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    Landscape trajectories and their effect on fragmentation for a Mediterranean semi-arid ecosystem in Central Chile
    (2016) Hernández, A.; Miranda, Marcelo; Arellano, Eduardo; Dobbs, Cynnamon
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    Nikolai Gogol's account of sleep paralysis in the tale "The Portrait"
    (2021) Aguirre, Carolina; Miranda, Marcelo; Stefani, Ambra
    Several classical writers had an impressive power of observation and often depicted medical conditions in their works long before medical literature did. Sleep paralysis is a common and frightening experience, in particular when occurring for the first time. Therefore, it is not surprising that it has been frequently described in the classical literature, eg by Dostoevsky, Kafka, Dickens, and Maupassant. In Nikolai Gogol's tale "The portrait" (1833) we could recognize an excellent description of a sleep paralysis, in which several components of this condition were depicted including motor paralysis, visual and auditory hallucinations, and autonomic manifestations. To the best of our knowledge, this account is the earliest description of a sleep paralysis in non-medical literature. (c) 2021 Elsevier B.V. All rights reserved.
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    Optimization of photovoltaic solar power plant locations in northern Chile
    (2017) Suuronen, A.; Lensu, A.; Kuitunen, M.; Andrade, R.; Guajardo, N.; Miranda, Marcelo; Perez, M.; Kukkonen, J.
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    Understanding landscape-primary productivity and biodiversity relationship through graph metrics
    (2020) Barra Poblete, Felipe de la; Miranda, Marcelo; Pontificia Universidad Católica de Chile. Facultad de Agronomía e Ingeniería Forestal
    Besides landscape ecological studies, the traditional approach to trying to understand ecological processes that occur in a landscape is the use of spatial statistics. However, this does not take into account that many of these processes cannot be observed without considering the multiple interactions that occur between patches of different land use in the landscape. The objective of this research was to explore the use of graph metrics in understanding the processes at the landscape scale, specifically its productivity and plant biodiversity, using three different landscapes. A bibliographic review of the graph metrics was performed, which was separated into landscape and local scales, and into groups within each scale. The usefulness and ecological significance of the metrics was evaluated, the relationship between them and with productivity and biodiversity was analysed. In total, 13 landscape scale metrics and 11 local scale metrics with ecological significance were selected. It was found that a large part of the metrics were able to identify differences between the three landscapes and between locations at local scale, but with different variabilities over time. The metrics had a higher relationship with productivity at both scales, achieving correlations over 70% between the predicted and actual values of productivity, while the biodiversity models achieved a correlation over 45%. Several metrics at both scales were important for predicting both productivity and biodiversity. This study highlights the utility and flexibility of graph theory to understand processes in landscapes, in the context of biodiversity conservation in agricultural landscapes and in landscape ecology.Besides landscape ecological studies, the traditional approach to trying to understand ecological processes that occur in a landscape is the use of spatial statistics. However, this does not take into account that many of these processes cannot be observed without considering the multiple interactions that occur between patches of different land use in the landscape. The objective of this research was to explore the use of graph metrics in understanding the processes at the landscape scale, specifically its productivity and plant biodiversity, using three different landscapes. A bibliographic review of the graph metrics was performed, which was separated into landscape and local scales, and into groups within each scale. The usefulness and ecological significance of the metrics was evaluated, the relationship between them and with productivity and biodiversity was analysed. In total, 13 landscape scale metrics and 11 local scale metrics with ecological significance were selected. It was found that a large part of the metrics were able to identify differences between the three landscapes and between locations at local scale, but with different variabilities over time. The metrics had a higher relationship with productivity at both scales, achieving correlations over 70% between the predicted and actual values of productivity, while the biodiversity models achieved a correlation over 45%. Several metrics at both scales were important for predicting both productivity and biodiversity. This study highlights the utility and flexibility of graph theory to understand processes in landscapes, in the context of biodiversity conservation in agricultural landscapes and in landscape ecology.Besides landscape ecological studies, the traditional approach to trying to understand ecological processes that occur in a landscape is the use of spatial statistics. However, this does not take into account that many of these processes cannot be observed without considering the multiple interactions that occur between patches of different land use in the landscape. The objective of this research was to explore the use of graph metrics in understanding the processes at the landscape scale, specifically its productivity and plant biodiversity, using three different landscapes. A bibliographic review of the graph metrics was performed, which was separated into landscape and local scales, and into groups within each scale. The usefulness and ecological significance of the metrics was evaluated, the relationship between them and with productivity and biodiversity was analysed. In total, 13 landscape scale metrics and 11 local scale metrics with ecological significance were selected. It was found that a large part of the metrics were able to identify differences between the three landscapes and between locations at local scale, but with different variabilities over time. The metrics had a higher relationship with productivity at both scales, achieving correlations over 70% between the predicted and actual values of productivity, while the biodiversity models achieved a correlation over 45%. Several metrics at both scales were important for predicting both productivity and biodiversity. This study highlights the utility and flexibility of graph theory to understand processes in landscapes, in the context of biodiversity conservation in agricultural landscapes and in landscape ecology.Besides landscape ecological studies, the traditional approach to trying to understand ecological processes that occur in a landscape is the use of spatial statistics. However, this does not take into account that many of these processes cannot be observed without considering the multiple interactions that occur between patches of different land use in the landscape. The objective of this research was to explore the use of graph metrics in understanding the processes at the landscape scale, specifically its productivity and plant biodiversity, using three different landscapes. A bibliographic review of the graph metrics was performed, which was separated into landscape and local scales, and into groups within each scale. The usefulness and ecological significance of the metrics was evaluated, the relationship between them and with productivity and biodiversity was analysed. In total, 13 landscape scale metrics and 11 local scale metrics with ecological significance were selected. It was found that a large part of the metrics were able to identify differences between the three landscapes and between locations at local scale, but with different variabilities over time. The metrics had a higher relationship with productivity at both scales, achieving correlations over 70% between the predicted and actual values of productivity, while the biodiversity models achieved a correlation over 45%. Several metrics at both scales were important for predicting both productivity and biodiversity. This study highlights the utility and flexibility of graph theory to understand processes in landscapes, in the context of biodiversity conservation in agricultural landscapes and in landscape ecology.Besides landscape ecological studies, the traditional approach to trying to understand ecological processes that occur in a landscape is the use of spatial statistics. However, this does not take into account that many of these processes cannot be observed without considering the multiple interactions that occur between patches of different land use in the landscape. The objective of this research was to explore the use of graph metrics in understanding the processes at the landscape scale, specifically its productivity and plant biodiversity, using three different landscapes. A bibliographic review of the graph metrics was performed, which was separated into landscape and local scales, and into groups within each scale. The usefulness and ecological significance of the metrics was evaluated, the relationship between them and with productivity and biodiversity was analysed. In total, 13 landscape scale metrics and 11 local scale metrics with ecological significance were selected. It was found that a large part of the metrics were able to identify differences between the three landscapes and between locations at local scale, but with different variabilities over time. The metrics had a higher relationship with productivity at both scales, achieving correlations over 70% between the predicted and actual values of productivity, while the biodiversity models achieved a correlation over 45%. Several metrics at both scales were important for predicting both productivity and biodiversity. This study highlights the utility and flexibility of graph theory to understand processes in landscapes, in the context of biodiversity conservation in agricultural landscapes and in landscape ecology.
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    Understanding the effect of three decades of land use change on soil quality and biomass productivity in a Mediterranean landscape in Chile
    (2016) Hernández, Angela; Arellano, Eduardo; Morales-Moraga, David; Miranda, Marcelo