Jörg Kaduk

Next generation of elevated [CO2] experiments with crops: A critical investment for feeding the future world

A rising global population and demand for protein-rich diets are increasing pressure to maximize agricultural productivity. Rising atmospheric [CO(2)] is altering global temperature and precipitation patterns, which challenges agricultural productivity. While rising [CO(2)] provides a unique opportunity to increase the productivity of C(3) crops, average yield stimulation observed to date is well below potential gains. Thus, there is room for improving productivity. However, only a fraction of available germplasm of crops has been tested for CO(2) responsiveness. Yield is a complex phenotypic trait determined by the interactions of a genotype with the environment. Selection of promising genotypes and characterization of response mechanisms will only be effective if crop improvement and systems biology approaches are closely linked to production environments, that is, on the farm within major growing regions. Free air CO(2) enrichment (FACE) experiments can provide the platform upon which to conduct genetic screening and elucidate the inheritance and mechanisms that underlie genotypic differences in productivity under elevated [CO(2)]. We propose a new generation of large-scale, low-cost per unit area FACE experiments to identify the most CO(2)-responsive genotypes and provide starting lines for future breeding programmes. This is necessary if we are to realize the potential for yield gains in the future.

Ground-Based Optical Measurements at European Flux Sites: A Review of Methods, Instruments and Current Controversies

This paper reviews the currently available optical sensors, their limitations and opportunities for deployment at Eddy Covariance (EC) sites in Europe. This review is based on the results obtained from an online survey designed and disseminated by the Co-cooperation in Science and Technology (COST) Action ESO903—“Spectral Sampling Tools for Vegetation Biophysical Parameters and Flux Measurements in Europe” that provided a complete view on spectral sampling activities carried out within the different research teams in European countries. The results have highlighted that a wide variety of optical sensors are in use at flux sites across Europe, and responses further demonstrated that users were not always fully aware of the key issues underpinning repeatability and the reproducibility of their spectral measurements. The key findings of this survey point towards the need for greater awareness of the need for standardisation and development of a common protocol of optical sampling at the European EC sites.

Effect of climate on interannual variability of terrestrial CO2 fluxes

This paper was published as Global Biogeochemical Cycles, 2002, 16 (4), GB1102. Copyright

An observation-based estimate of the strength of rainfall-vegetation interactions in the Sahel

Over the course of the twentieth century the African Sahel experienced large variations in annual precipitation; including the wet period during the 1950s and 1960s and the long-term drought during the 1970s and 1980s. Feedbacks between the land surface and atmosphere can affect rainfall variability at monthly, annual and decadal time scales. However, the strength of the coupling between the land surface and precipitation is still highly uncertain, with climate-model derived estimates differing by an order of magnitude. Here a statistical model of vegetation greenness is used to estimate the vegetation-rainfall coupling strength in the Sahel, based on monthly satellite-derived vegetation index and meteorological data. Evidence is found for a positive feedback between vegetation and rainfall at the monthly time scale, and for a vegetation memory operating at the annual time scale. These vegetation-rainfall interactions increase the interannual variation in Sahelian precipitation; accounting for as much as 30% of the variability in annual precipitation in some hot spot regions between 15° and 20°N.

Land Degradation Assessment Using Residual Trend Analysis of GIMMS NDVI3g, Soil Moisture and Rainfall in Sub-Saharan West Africa from 1982 to 2012

Areas affected by land degradation in Sub-Saharan West Africa between 1982 and 2012 are identified using time-series analysis of vegetation index data derived from satellites. The residual trend (RESTREND) of a Normalized Difference Vegetation Index (NDVI) time-series is defined as the fraction of the difference between the observed NDVI and the NDVI predicted from climate data. It has been widely used to study desertification and other forms of land degradation in drylands. The method works on the assumption that a negative trend of vegetation photosynthetic capacity is an indication of land degradation if it is independent from climate variability. In the past, many scientists depended on rainfall data as the major climatic factor controlling vegetation productivity in drylands when applying the RESTREND method. However, the water that is directly available to vegetation is stored as soil moisture, which is a function of cumulative rainfall, surface runoff, infiltration and evapotranspiration. In this study, the new NDVI third generation (NDVI3g), which was generated by the National Aeronautics and Space Administration-Goddard Space Flight Center Global Inventory Modeling and Mapping Studies (NASA-GSFC GIMMS) group, was used as a satellite-derived proxy of vegetation productivity, together with the soil moisture index product from the Climate Prediction Center (CPC) and rainfall data from the Climate Research Unit (CRU). The results show that the soil moisture/NDVI pixel-wise residual trend indicates land degraded areas more clearly than rainfall/NDVI. The spatial and temporal trends of the RESTREND in the region follow the patterns of drought episodes, reaffirming the difficulties in separating the impacts of drought and land degradation on vegetation photosynthetic capacity. Therefore, future studies of land degradation and desertification in drylands should go beyond using rainfall as a sole predictor of vegetation condition, and include soil moisture index datasets in the analysis.

The carbon balance of an old-growth forest: Building across approaches

The carbon budget of the Wind River old-growth forest is being addressed from a variety of perspectives and with a range of approaches. The goal of this comprehensive analysis is developing a thorough, general, and validated understanding of the carbon balance, as well as the processes controlling it. The initial results from studies addressing annual carbon (C) balance with ground-based methods, eddy flux, leaf-based models, and ecosystem models are consistent in some, but not all, respects. Net primary production is 500–600 g C m−2 y−1 (5–6 Mg C ha−1 y−1), consistent with estimates based on climate alone. The site appears to be close to carbon equilibrium, as a multiyear average, using ground-based methods but a sink of approximately 150–190 g C m−2 y−1 from eddy flux for a single year. An overview of the mechanisms that can drive forest carbon sinks illustrates why methods emphasizing different temporal and spatial scales, as well as different processes, can come to different conclusions, and it highlights opportunities in moving toward a truly integrated approach.

Streambed scour and fill in low-order dryland channels

This research has been funded by the Natural Environment Research Council (grant GR3/12754).

Data assimilation into land surface models: the implications for climate feedbacks

Land surface models (LSMs) are integral components of general circulation models (GCMs), consisting of a complex framework of mathematical representations of coupled biophysical processes. Considerable variability exists between different models, with much uncertainty in their respective representations of processes and their sensitivity to changes in key variables. Data assimilation is a powerful tool that is increasingly being used to constrain LSM predictions with available observation data. The technique involves the adjustment of the model state at observation times with measurements of a predictable uncertainty, to minimize the uncertainties in the model simulations. By assimilating a single state variable into a sophisticated LSM, this article investigates the effect this has on terrestrial feedbacks to the climate system, thereby taking a wider view on the process of data assimilation and the implications for biogeochemical cycling, which is of considerable relevance to the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report.

Improving estimates of tropical peatland area, carbon storage, and greenhouse gas fluxes

Our limited knowledge of the size of the carbon pool and exchange fluxes in forested lowland tropical peatlands represents a major gap in our understanding of the global carbon cycle. Peat deposits in several regions (e.g. the Congo Basin, much of Amazonia) are only just beginning to be mapped and characterised. Here we consider the extent to which methodological improvements and improved coordination between researchers could help to fill this gap. We review the literature on measurement of the key parameters required to calculate carbon pools and fluxes, including peatland area, peat bulk density, carbon concentration, above-ground carbon stocks, litter inputs to the peat, gaseous carbon exchange, and waterborne carbon fluxes. We identify areas where further research and better coordination are particularly needed in order to reduce the uncertainties in estimates of tropical peatland carbon pools and fluxes, thereby facilitating better-informed management of these exceptionally carbon-rich ecosystems.Our limited knowledge of the size of the carbon pool and exchange fluxes in forested lowland tropical peatlands represents a major gap in our understanding of the global carbon cycle. Peat deposits in several regions (e.g. the Congo Basin, much of Amazonia) are only just beginning to be mapped and characterised. Here we consider the extent to which methodological improvements and improved coordination between researchers could help to fill this gap. We review the literature on measurement of the key parameters required to calculate carbon pools and fluxes, including peatland area, peat bulk density, carbon concentration, above-ground carbon stocks, litter inputs to the peat, gaseous carbon exchange, and waterborne carbon fluxes. We identify areas where further research and better coordination are particularly needed in order to reduce the uncertainties in estimates of tropical peatland carbon pools and fluxes, thereby facilitating better-informed management of these exceptionally carbon-rich ecosystems.

An approach to classification of airborne laser scanning point cloud data in an urban environment

Digital topographic data, including detailed maps required for urban planning, are still unavailable in many parts of the world. Airborne laser scanning (ALS) has the unique ability to provide geo-referenced three-dimensional data useful for the mapping of urban features. This article examines the performance of decision tree classifiers on two ALS data sets, collected in different seasons from different flying heights with different scanners using laser beams at different wavelengths – 1550 and 1064 nm – for the same study area. Classification was undertaken on the point clouds based on attributes derived from the triangulated irregular network (TIN) triangles attached to a point, as well as attributes of the individual points. Classification accuracies of 0.68 and 0.92 (kappa coefficient) could be achieved for the two data sets. Decision tree seems to be a classification method that is particularly suitable for geographic information system (GIS), as it can be converted to ‘if–then’ rules that can be implemented fully within a GIS environment. Grass and paved areas could be distinguished better using intensity from one data set than the other, which could be related to the wavelengths of the lasers, and need to be explored further.