Optimal soil carbon sampling designs to achieve cost-effectiveness: a case study in blue carbon ecosystems.
Biol Lett
; 14(9)2018 09 26.
Article
en En
| MEDLINE
| ID: mdl-30258032
ABSTRACT
Researchers are increasingly studying carbon (C) storage by natural ecosystems for climate mitigation, including coastal 'blue carbon' ecosystems. Unfortunately, little guidance on how to achieve robust, cost-effective estimates of blue C stocks to inform inventories exists. We use existing data (492 cores) to develop recommendations on the sampling effort required to achieve robust estimates of blue C. Using a broad-scale, spatially explicit dataset from Victoria, Australia, we applied multiple spatial methods to provide guidelines for reducing variability in estimates of soil C stocks over large areas. With a separate dataset collected across Australia, we evaluated how many samples are needed to capture variability within soil cores and the best methods for extrapolating C to 1 m soil depth. We found that 40 core samples are optimal for capturing C variance across 1000's of kilometres but higher density sampling is required across finer scales (100-200 km). Accounting for environmental variation can further decrease required sampling. The within core analyses showed that nine samples within a core capture the majority of the variability and log-linear equations can accurately extrapolate C. These recommendations can help develop standardized methods for sampling programmes to quantify soil C stocks at national scales.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Suelo
/
Carbono
/
Monitoreo del Ambiente
Tipo de estudio:
Health_economic_evaluation
País/Región como asunto:
Oceania
Idioma:
En
Revista:
Biol Lett
Asunto de la revista:
BIOLOGIA
Año:
2018
Tipo del documento:
Article
País de afiliación:
Australia