A blueprint for the estimation of seagrass carbon stock using remote sensing-enabled proxies

Seagrass ecosystems sequester carbon at disproportionately high rates compared to terrestrial ecosystems and represent a powerful potential contributor to climate change mitigation and adaptation projects. However, at a local scale, rich heterogeneity in seagrass ecosystems may lead to variability in carbon sequestration. Differences in carbon sequestration rates, both within and between seagrass meadows, are related to a wide range of interrelated biophysical and environmental variables that are difficult to measure holistically using traditional field surveys. Improved methods for producing robust, spatially explicit estimates of seagrass carbon storage across large areas would be highly valuable, but must capture complex biophysical heterogeneity and variability to be accurate and useful. Here, we review the current and emerging literature on biophysical processes which shape carbon storage in seagrass beds, alongside studies that map seagrass characteristics using satellite remote sensing data, to create a blueprint for the development of remote sensing-enabled proxies for seagrass carbon stock and sequestration. Applications of satellite remote sensing included measuring seagrass meadow extent, estimating above-ground biomass, mapping species composition, quantifying patchiness and patch connectivity, determining broader landscape environmental contexts, and characterising seagrass life cycles. All of these characteristics may contribute to variability in seagrass carbon storage. As such, remote sensing methods are uniquely placed to enable proxy-based estimates of seagrass carbon stock by capturing their biophysical characteristics, in addition to the spatiotemporal heterogeneity and variability of these characteristics. Though the outlined approach is complex, it is suitable for accurately and efficiently producing a full picture of seagrass carbon stock. This review has drawn links between the processes of seagrass carbon sequestration and the capabilities of remote sensing to detect and characterise these processes. These links will facilitate the development of remote sensing-enabled proxies and support spatially explicit estimates of carbon stock, ensuring climate change mitigation and adaptation projects involving seagrass are accounted for with increased accuracy and reliability

Physical soil quality indicators for monitoring British soils

The condition or quality of soils determines its ability to deliver a range of functions that support ecosystem services, human health and wellbeing. The increasing policy imperative to implement successful soil monitoring programmes has resulted in the demand for reliable soil quality indicators (SQIs) for physical, biological and chemical soil properties. The selection of these indicators needs to ensure that they are sensitive and responsive to pressure and change e.g. they change across space and time in relation to natural perturbations and land management practices. Using a logical sieve approach based on key policy-related soil functions, this research assessed whether physical soil properties can be used to indicate the quality of British soils in terms of its capacity to deliver ecosystem goods and services. The resultant prioritised list of physical SQIs were tested for robustness, spatial and temporal variability and expected rate of change using statistical analysis and modelling. Six SQIs were prioritised; packing density, soil water retention characteristics, aggregate stability, rate of erosion, depth of soil and soil sealing. These all have direct relevance to current and likely future soil and environmental policy and are appropriate for implementation in soil monitoring programs

Utilizing Colored Dissolved Organic Matter to Derive Dissolved Black Carbon Export by Arctic Rivers

Wildfires have produced black carbon (BC) since land plants emerged. Condensed aromatic compounds, a form of BC, have accumulated to become a major component of the soil carbon pool. Condensed aromatics leach from soils into rivers, where they are termed dissolved black carbon (DBC). The transport of DBC by rivers to the sea is a major term in the global carbon and BC cycles. To estimate Arctic river DBC export, 25 samples collected from the six largest Arctic rivers (Kolyma, Lena, Mackenzie, Ob’, Yenisey and Yukon) were analyzed for dissolved organic carbon (DOC), colored dissolved organic matter (CDOM), and DBC. A simple, linear regression between DOC and DBC indicated that DBC accounted for 8.9 ± 0.3% DOC exported by Arctic rivers. To improve upon this estimate, an optical proxy for DBC was developed based upon the linear correlation between DBC concentrations and CDOM light absorption coefficients at 254 nm (a254). Relatively easy to measure a254 values were determined for 410 Arctic river samples between 2004 and 2010. Each of these a254 values was converted to a DBC concentration based upon the linear correlation, providing an extended record of DBC concentration. The extended DBC record was coupled with daily discharge data from the six rivers to estimate riverine DBC loads using the LOADEST modeling program. The six rivers studied cover 53% of the pan-Arctic watershed and exported 1.5 ± 0.1 million tons of DBC per year. Scaling up to the full area of the pan-Arctic watershed, we estimate that Arctic rivers carry 2.8 ± 0.3 million tons of DBC from land to the Arctic Ocean each year. This equates to ~8% of Arctic river DOC export, slightly less than indicated by the simpler DBC vs DOC correlation-based estimate. Riverine discharge is predicted to increase in a warmer Arctic. DBC export was positively correlated with river runoff, suggesting that the export of soil BC to the Arctic Ocean is likely to increase as the Arctic warms

Combining Crop Models and Remote Sensing for Yield Prediction: Concepts, Applications and Challenges for Heterogeneous Smallholder Environments

JRC, CCAFS jointly sponsored the workshop on June 13-14, 2012, at the JRC in Ispra, Italy, to identify avenues for exploiting remote sensing information to improving crop forecasting in smallholder farming environments. The workshop’s objectives were: 1) To advance the state-of-knowledge of data assimilation for crop yield forecasting; 2) To address challenges and needs for successful applications of data assimilation in forecasting crop yields in heterogeneous, smallholder environments; and, 3) To enhance collaboration and exchange of knowledge among data assimilation and crop forecasting groups. The workshop succeeded in bringing together scientists from around the world. This has enabled discussions on research and results and has greatly enhanced collaboration and exchange of knowledge, especially about data assimilation and crop forecasting

Assessing the utility of geospatial technologies to investigate environmental change within lake systems

Over 50% of the world's population live within 3. km of rivers and lakes highlighting the on-going importance of freshwater resources to human health and societal well-being. Whilst covering c. 3.5% of the Earth's non-glaciated land mass, trends in the environmental quality of the world's standing waters (natural lakes and reservoirs) are poorly understood, at least in comparison with rivers, and so evaluation of their current condition and sensitivity to change are global priorities. Here it is argued that a geospatial approach harnessing existing global datasets, along with new generation remote sensing products, offers the basis to characterise trajectories of change in lake properties e.g., water quality, physical structure, hydrological regime and ecological behaviour. This approach furthermore provides the evidence base to understand the relative importance of climatic forcing and/or changing catchment processes, e.g. land cover and soil moisture data, which coupled with climate data provide the basis to model regional water balance and runoff estimates over time. Using examples derived primarily from the Danube Basin but also other parts of the World, we demonstrate the power of the approach and its utility to assess the sensitivity of lake systems to environmental change, and hence better manage these key resources in the future

Combining Crop Models and Remote Sensing for Yield Prediction: Concepts, Applications and Challenges for Heterogeneous Smallholder Environments

JRC and CCAFS jointly organized a workshop on June 13-14, 2012 in Ispra, Italy with the aim to advance the state-of-knowledge of data assimilation for crop yield forecasting in general, to address challenges and needs for successful applications of data assimilation in forecasting crop yields in heterogeneous, smallholder environments, and to enhance collaboration and exchange of knowledge among data assimilation and crop forecasting groups. The workshop showed that advances made in crop science are widely applicable to crop forecasting. The presentations of the participants approached the challenge from many sides, leading to ideas for improvement that can be implemented in real-time, operational crop yield forecasting. When applied, this knowledge has the potential to benefit the livelihoods of smallholder farmers in the developing world.JRC.H.4-Monitoring Agricultural Resource

An acoustic view of ocean mixing

Knowledge of the parameter K (turbulent diffusivity/"mixing intensity") is a key to understand transport processes of matter and energy in the ocean. Especially the almost vertical component of K across the ocean stratification (diapycnal diffusivity) is vital for research on biogeochemical cycles or greenhouse gas budgets. Recent boost in precision of water velocity data that can be obtained from vessel-mounted acoustic instruments (vmADCP) allows identifying ocean regions of elevated diapycnal diffusivity during research cruises - in high horizontal resolution and without extra ship time needed. This contribution relates acoustic data from two cruises in the Tropical North East Atlantic Oxygen Minimum Zone to simultaneous field observations of diapycnal diffusivity: pointwise measurements by a microstructure profiler as well as one integrative value from a large scale Tracer Release Experiment

Soil carbon estimation from eucalyptus grandis using canopy spectra

Mapping soil fertility parameters, such as soil carbon (C), is fundamentally important for forest management and research related to forest growth and climate change. This study seeks to establish the link between  Eucalyptus grandis canopy spectra and soil carbon using raw and continuum-removed spectra. Canopy-level  spectra were collected using a hand-held 350-2500nm spectroradiometer and soil samples obtained at depths from 0-1.2m and analysed for carbon content. Partial least squares (PLS) selection was used to selected  optimal bands for soil carbon assessment and further bootstrapped to select 35 Variable Importance in  Projection (VIP) parameters, based on correlation (r) and standard error (SE). Results indicated that  continuum-removed spectra and soil C yielded stronger significant correlations, when compared to soil C and  raw spectra. The predictive models developed for future soil C estimation showed that continuum-removed  spectra exhibited improved adjusted R2 values in both instances, i.e., when using all significant bands and the  most significant 35 VIP bands. The results indicate a distinct potential for forest managers to monitor the  status of soil C in commercial forestry compartments using canopy-level spectra and determine how much  fertilizer is required to optimize tree growth.Keywords: Soil carbon, Canopy spectr

Overview: Integrative and Comprehensive Understanding on Polar Environments (iCUPE) – concept and initial results

The role of polar regions is increasing in terms of megatrends such as globalization, new transport routes, demography, and the use of natural resources with consequent effects on regional and transported pollutant concentrations. We set up the ERA-PLANET Strand 4 project “iCUPE – integrative and Comprehensive Understanding on Polar Environments” to provide novel insights and observational data on global grand challenges with an Arctic focus. We utilize an integrated approach combining in situ observations, satellite remote sensing Earth observations (EOs), and multi-scale modeling to synthesize data from comprehensive long-term measurements, intensive campaigns, and satellites to deliver data products, metrics, and indicators to stakeholders concerning the environmental status, availability, and extraction of natural resources in the polar areas. The iCUPE work consists of thematic state-of-the-art research and the provision of novel data in atmospheric pollution, local sources and transboundary transport, the characterization of arctic surfaces and their changes, an assessment of the concentrations and impacts of heavy metals and persistent organic pollutants and their cycling, the quantification of emissions from natural resource extraction, and the validation and optimization of satellite Earth observation (EO) data streams. In this paper we introduce the iCUPE project and summarize initial results arising out of the integration of comprehensive in situ observations, satellite remote sensing, and multi-scale modeling in the Arctic context