Andres Hernandez Serna

Mr. Andres Hernandez Serna

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Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 October 2017 in Remote Sensing
Verified
Journal Article
Open access
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TAT. Mitchell Aide
T. Mitchell Aide
ASAndres Hernandez Serna
Andres Hernandez Serna
MCMarconi Campos-Cerqueira
Marconi Campos-Cerqueira
Orlando Acevedo-CharryOrlando Acevedo-Charry
Orlando Acevedo-Charry
JDJessica Deichmann
Jessica Deichmann
Acoustic ecology, or ecoacoustics, is a growing field that uses sound as a tool to evaluate animal communities. In this manuscript, we evaluate recordings from eight tropical forest sites that vary in species richness, from a relatively low diversity Caribbean forest to a megadiverse Amazonian forest, with the goal of understanding the relationship between acoustic space use (ASU) and species diversity across different taxonomic groups. For each site, we determined the acoustic morphospecies richness and composition of the biophony, and we used a global biodiversity dataset to estimate the regional richness of birds. Here, we demonstrate how detailed information on activity patterns of the acoustic community (8000 Hz), which contributed to greater ASU. This novel approach for analyzing the presence and acoustic activity of multiple taxonomic groups contributes to our understanding of ecological community dynamics and provides a useful tool for monitoring species in the context of restoration ecology, climate change and conservation biology.

4 November 2014 in PeerJ
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Journal Article
Open access
ASAndres Hernandez Serna
Andres Hernandez Serna
LJLuz Fernanda Jiménez-Segura
Luz Fernanda Jiménez-Segura
A new automatic identification system using photographic images has been designed to recognize fish, plant, and butterfly species from Europe and South America. The automatic classification system integrates multiple image processing tools to extract the geometry, morphology, and texture of the images. Artificial neural networks (ANNs) were used as the pattern recognition method. We tested a data set that included 740 species and 11,198 individuals. Our results show that the system performed with high accuracy, reaching 91.65% of true positive fish identifications, 92.87% of plants and 93.25% of butterflies. Our results highlight how the neural networks are complementary to species identification.

7 December 2013 in Journal of Applied Ichthyology
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Journal Article
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ASAndres Hernandez Serna
Andres Hernandez Serna
VMV. Márquez-Velásquez
V. Márquez-Velásquez
JCJ. D. Carvajal-Quintero
J. D. Carvajal-Quintero
AGA. Gulfo
A. Gulfo
CGCarlos Granado-Lorencio
Carlos Granado-Lorencio
LJL. F. Jiménez-Segura
L. F. Jiménez-Segura
This study reports length–weight relationships for 38 fish species belonging to 18 families inhabiting the Magdalena River floodplain lakes of Colombia. Samples were taken during the high water season of 2008, 2010 and 2011. Two species are presented for the first time. Maximum total length records for 24 species exceed those in FishBase.