Environmental spatial assessment at ranch scale: a tool for optimizing livestock management in Argentine forests

By

Varela, Santiago Agustín
Calamari, Noelia Cecilia
Trinco, Fabio Daniel
Diez, Juan Pablo
Weigandt, Mariana
Barzán, Flavia Roxana
Lezana, Lucrecia
Eclesia, Roxana Paola
López, Dardo Rubén
Coria, Rubén Darío
Peri, Pablo Luís
Umaña, Fernando Javier
Raffo, Fernando
Gazzotti, Juan Ignacio
De La Peña, Carlos
Wilson, Marcelo
Gabioud, Emmanuel
Hernández, Hernán
Canavelli, Sonia Beatriz

Type

Article

Date of Publication

2025-7-24

Original Publication

Vegetation classification and survey

Volume

6

Pages

163--179

Subjects

Argentina , environmental degradation , environmental health index (EHI) , integrated forest and livestock management , Remote sensing , vegetation assessment

Contributed by

Pensoft Publishers

Language

English

Published by

Sofia Pensoft Publishers 2020-

Identifiers

DOI: https://doi.org/10.3897/VCS.141917

 

Abstract

Question: Effective environmental management depends on accurate and efficient assessments of ecological conditions. This study introduces a method that combines remote sensing with a Rapid Assessment Method (RAM) to evaluate the environmental status of land units at the ranch scale. We ask whether this integrated approach can generate spatially explicit information to support the implementation and monitoring of sustainable livestock grazing in native forests. Study area: The study was conducted in three livestock ranches in Argentina. These ranches encompass heterogeneous landscapes characterized by varying soil types, vegetation cover, and topographic features that influence ecological conditions. Methods: Remote sensing imagery was used to delineate Ecological Sites (ESi) based on bio-geomorphic attributes such as soil, topography, and vegetation. These spatial units guided field sampling, where RAM was applied to assess environmental indicators. Field data were integrated into an Environmental Health Index (EHI), summarizing the ecological status of each ESi. Ordinary kriging interpolated EHI values across the landscape, enabling spatial visualization of environmental health patterns and spatial variability. Results: Mapping of EHI values showed that most land units exhibited intermediate to high environmental health, suggesting generally favorable ecological conditions across the ranches. However, some areas had low EHI values associated with signs of disturbance or degradation, including fire, flooding, invasive species, or overgrazing. Conclusions: The integration of remote sensing with RAM provided a detailed overview of ecological conditions at the ranch scale. The results can guide more focused and efficient fieldwork in areas requiring closer monitoring due to potential environmental degradation or changes linked to livestock management. This approach supports the implementation and evaluation of sustainable grazing management in native forests, offering a robust, scalable tool for environmental assessment. Additionally, by optimizing the allocation of sampling effort, it enables more informed decision-making to maintain and enhance ecological health in these production systems.<br> Taxonomic reference: Anton and Zuloaga (2023).<br> Abbreviations: EHI = environmental health index; ESi = ecological site; RAM = rapid assessment methodology; MBGI = silvo pastoral or forest management with integrated livestock.