RESUMO
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.
Assuntos
Carbono/análise , Monitoramento Ambiental/métodos , Solo/química , Austrália , Áreas AlagadasRESUMO
Numerical models are useful for predicting the transport and fate of contaminants in dynamic marine environments, and are increasingly a practical solution to environmental impact assessments. In this study, a three-dimensional hydrodynamic model and field data were used to validate a far-field dispersion model that, in turn, was used to determine the fate of treated wastewater (TWW) discharged to the ocean via a submarine ocean outfall under hypothetical TWW flows. The models were validated with respect to bottom and surface water current speed and direction, and in situ measurements of total nitrogen and faecal coliforms. Variations in surface and bottom currents were accurately predicted by the model as were nutrient and coliform concentrations. Results indicated that the ocean circulation was predominately wind driven, evidenced by relatively small oscillations in the current speeds along the time-scale of the tide, and that dilution mixing zones were orientated in a predominantly north-eastern direction from the outfall and parallel to the coastline. Outputs of the model were used to determine the 'footprint' of the TWW plume under a differing discharge scenario and, particularly, whether the resultant changes in TWW contaminants, total nitrogen and faecal coliforms would meet local environmental quality objectives (EQO) for ecosystem integrity, shellfish harvesting and primary recreation. Modelling provided a practical solution for predicting the dilution of contaminants under a hypothetical discharge scenario and a means for determining the aerial extent of exclusion zones, where the EQOs for shellfish harvesting and primary recreation may not always be met. Results of this study add to the understanding of regional discharge conditions and provide a practical case study for managing impacts to marine environments under a differing TWW discharge scenario, in comparison to an existing scenario.