Plataformas de modelado de servicios ecosistémicos: El norte de la Patagonia como un ejemplo de caso aplicando k.LAB

Facundo J. Oddi; Alba Márquez Torres; João A. Pompeu; Ainhoa Magrach; Stefano Balbi; Ferdinando Villa; Lucas A. Garibaldi

doi:10.25260/EA.23.33.3.0.2257

Autores/as

Facundo J. Oddi Universidad Nacional de Río Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina
Alba Márquez Torres Basque Centre for Climate Change-BC3, Parque Científico UPV-EHU. Leioa, España
João A. Pompeu Basque Centre for Climate Change-BC3, Parque Científico UPV-EHU. Leioa, España
Ainhoa Magrach Basque Centre for Climate Change-BC3, Parque Científico UPV-EHU. Leioa, España
Stefano Balbi Basque Centre for Climate Change-BC3, Parque Científico UPV-EHU. Leioa, España
Ferdinando Villa Basque Centre for Climate Change-BC3, Parque Científico UPV-EHU. Leioa, España
Lucas A. Garibaldi Universidad Nacional de Río Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina

DOI:

https://doi.org/10.25260/EA.23.33.3.0.2257

Palabras clave:

calentamiento global, k.LAB, ARIES, InVEST, Google Earth Engine, Patagonia norte, secuestro de carbono, polinización, turismo

Resumen

Los avances tecnológicos y metodológicos de las últimas décadas (e.g., información satelital, potencia de los ordenadores, análisis geoespacial, desarrollo de algoritmos) facilitaron buscar soluciones a problemas complejos como el cambio global. Estos avances permitieron que surjan plataformas informáticas para modelar servicios ecosistémicos, que cuantifican los beneficios de la naturaleza y evalúan cómo son o serán afectados por acciones humanas. Actualmente, existen variadas plataformas con diferentes grados de aptitud según el contexto, destacándose k.LAB por ser gratuita, de código abierto y presentar un enfoque de ciencia colaborativa, además de integrar diferentes técnicas de modelado con inteligencia artificial. k.LAB es muy versátil para responder a las demandas de diferentes usos, desde programar y modelar SE hasta tomar decisiones. Sin embargo, quienes cuantifican y mapean SE, especialmente en Latinoamérica, tienen escaso conocimiento de k.LAB; esto dificulta aprovechar su potencial, tal como sucedió con herramientas de acceso libre y código abierto (e.g., la adopción de R requirió tiempo, revisiones, discusiones y materiales didácticos en revistas especializadas). Este trabajo presenta las capacidades de k.LAB en el contexto de las plataformas de modelado de SE. Primero, introducimos estas plataformas en términos generales, con énfasis en las más usadas. Luego, caracterizamos k.LAB técnica y filosóficamente. Después, presentamos un caso de estudio en el norte de la Patagonia argentina, ilustrando la obtención de mapas de tres SE (captura de carbono, polinización y recreación al aire libre) utilizando aplicaciones de modelado dirigidas a personas sin experiencia en programación. Finalmente, establecemos características deseables en las plataformas de modelado de SE para discutir ventajas y limitaciones de k.LAB en relación con otras alternativas. Esperamos brindar un marco general útil para el modelado de SE y ampliar el conjunto de herramientas para abordar problemáticas vinculadas al cambio global en la Argentina y otros países de la región.

Biografía del autor/a

Facundo J. Oddi, Universidad Nacional de Río Negro. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural. Río Negro, Argentina

Facundo José Oddi, Universidad Nacional de Río Negro. IRNAD, UNRN-CONICET.

Investigador CONICET y Jefe de Trabajos Prácticos de Estádistica en la UNRN.

Ingeniero Forestal. Facultad de Ciencias Agrarias y Forestales. Universidad Nacional de La Plata.
Doctor en Biología. Universidad Nacional del Comahue.

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