Double Sampling Methods in Biomass Estimates of Andean Shrubs and Tussocks
The natural Andean vegetation environment is the most important resource available to local pastoralist economies. Knowledge of its attributes is vital in assessing ecosystem properties and improves management decision making. However, there is a lack of research on models that estimate species and...
| Autores: | , , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2017 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/64633 |
| Acceso en línea: | http://hdl.handle.net/11336/64633 |
| Access Level: | acceso abierto |
| Palabra clave: | Biomass Puna Shrubs Tussocks Vegetation https://purl.org/becyt/ford/1.6 https://purl.org/becyt/ford/1 |
| Sumario: | The natural Andean vegetation environment is the most important resource available to local pastoralist economies. Knowledge of its attributes is vital in assessing ecosystem properties and improves management decision making. However, there is a lack of research on models that estimate species and life-form biomass for the Puna. We developed a series of models that facilitated the estimation of biomass while avoiding the direct harvesting of the most representative Puna steppe plant species in Jujuy, Argentina. The models thus developed are useful tools in the evaluation of changes in ecosystem dynamics through time and space. Allometric equations were developed for the dominant shrubs (Baccharis boliviensis, Fabiana densa, Parastrephia quadrangularis, Tetraglochin cristatum, Ocyroe armata, and Adesmia sp.) and tussock grasses (Jarava ichu, Festuca crysophylla, and Cenchrus chilense). A field record of the maximum diameter, perpendicular diameter, and height of each plant; number of individuals per plot; and tussock grasses and shrub cover across all vegetation communities was undertaken. Linear regressions including plant measures demonstrated a good fit (R2 > 0.7, P < 0.001) to the biomass for individual plants and surface area. The predictive equations developed allow for the rapid and accurate estimation of shrub and tussock biomass. This is essential to monitor the effects of grazing for impact assessment of the different management practices and vegetation dynamics. |
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