Optimal soil carbon sampling designs to achieve cost-effectiveness: a case study in blue carbon ecosystems
| Autor: | Daniel Ierodiaconou, Emily Nicholson, Clare Duncan, Peter I. Macreadie, Oscar Serrano, Carlos M. Duarte, Paul E. Carnell, Glenn R. Shiell, Mary Young, Jeff Baldock |
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| Rok vydání: | 2018 |
| Předmět: |
0106 biological sciences
010504 meteorology & atmospheric sciences Cost effectiveness 010604 marine biology & hydrobiology Australia Special Feature Sampling (statistics) Variance (accounting) Soil carbon 15. Life on land Biology 01 natural sciences Agricultural and Biological Sciences (miscellaneous) Carbon Blue carbon Soil Wetlands Sampling design Ecosystem Natural ecosystem Physical geography General Agricultural and Biological Sciences 0105 earth and related environmental sciences Environmental Monitoring |
| Zdroj: | Biology letters. 14(9) |
| ISSN: | 1744-957X |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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