Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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The Importance of Consistent Global Forest Aboveground Biomass Product Validation
Duncanson, L. ; Armston, J. ; Disney, M. ; Avitabile, V. ; Barbier, N. ; Calders, K. ; Carter, S. ; Chave, J. ; Herold, M. ; Crowther, T.W. ; Falkowski, M. ; Kellner, J.R. ; Labrière, N. ; Lucas, R. ; Macbean, N. ; Mcroberts, R.E. ; Meyer, V. ; Næsset, E. ; Nickeson, J.E. ; Paul, K.I. ; Phillips, O.L. ; Réjou-méchain, M. ; Román, M. ; Roxburgh, S. ; Saatchi, S. ; Schepaschenko, D. ; Scipal, K. ; Siqueira, P.R. ; Whitehurst, A. ; Williams, M. - \ 2019
Surveys in Geophysics 40 (2019)4. - ISSN 0169-3298 - p. 979 - 999.
Several upcoming satellite missions have core science requirements to produce data for accurate forest aboveground biomass mapping. Largely because of these mission datasets, the number of available biomass products is expected to greatly increase over the coming decade. Despite the recognized importance of biomass mapping for a wide range of science, policy and management applications, there remains no community accepted standard for satellite-based biomass map validation. The Committee on Earth Observing Satellites (CEOS) is developing a protocol to fill this need in advance of the next generation of biomass-relevant satellites, and this paper presents a review of biomass validation practices from a CEOS perspective. We outline the wide range of anticipated user requirements for product accuracy assessment and provide recommendations for the validation of biomass products. These recommendations include the collection of new, high-quality in situ data and the use of airborne lidar biomass maps as tools toward transparent multi-resolution validation. Adoption of community-vetted validation standards and practices will facilitate the uptake of the next generation of biomass products.
Using a Finer Resolution Biomass Map to Assess the Accuracy of a Regional, Map-Based Estimate of Forest Biomass
McRoberts, Ronald E. ; Næsset, Erik ; Liknes, Greg C. ; Chen, Qi ; Walters, Brian F. ; Saatchi, Sassan ; Herold, Martin - \ 2019
Surveys in Geophysics 40 (2019)4. - ISSN 0169-3298 - p. 1001 - 1015.
Design-based inference - Greenhouse gas inventory - Hybrid inference - IPCC good practice guidelines - Model-based inference

National greenhouse gas inventories often use variations of the gain–loss approach whereby emissions are estimated as the products of estimates of areas of land-use change characterized as activity data and estimates of emissions per unit area characterized as emission factors. Although the term emissions is often intuitively understood to mean release of greenhouse gases from terrestrial sources to the atmosphere, in fact, emission factors can also be negative, meaning removal of the gases from the atmosphere to terrestrial sinks. For remote and inaccessible forests for which ground sampling is difficult if not impossible, emission factors may be based on map-based estimates of biomass or biomass change obtained from regional maps. For the special case of complete deforestation, the emission factor for the aboveground biomass pool is simply mean aboveground, live-tree, biomass per unit area prior to the deforestation. If biomass maps are used for these purposes, estimates must still comply with the first IPCC good practice guideline regarding accuracy relative to the true value and the second guideline regarding uncertainty. Accuracy assessment for a map-based estimate entails comparison of the estimate to a second estimate obtained using independent reference data. Assuming ground sampling is not feasible, a map of greater quality than the regional map may be considered as a source of reference data where greater quality connotes attributes such as finer resolution and/or greater accuracy. For a local, sub-regional study area in Minnesota in the USA, the accuracy of an estimate of mean aboveground, live-tree biomass per unit area (AGB, Mg/ha) obtained from a coarser resolution, regional, MODIS-based biomass map was assessed using reference data sampled from a finer resolution, local, airborne laser scanning (ALS)-based biomass map. The rationale for a local assessment of a regional map is that, although assessment of a regional map would be difficult for the entire extent of the map, it can likely be assessed for multiple local sub-regions in which case expected local regional accuracy for the entire map can perhaps be inferred. For this study, the local assessment was in the form of a test of the hypothesis that the local sub-regional estimate from the regional map did not deviate from the local true value. A hybrid approach to inference was used whereby design-based inferential techniques were used to estimate uncertainty due to sampling from the finer resolution map, and model-based inferential techniques were used to estimate uncertainty resulting from using the finer resolution map unit values which were subject to prediction error as reference data. The test revealed no statistically significant difference between the MODIS-based and ALS-based map estimates, thereby indicating that for the local sub-region, the regional, MODIS-based estimate complied with the first IPCC good practice guideline for accuracy.

The Role and Need for Space-Based Forest Biomass-Related Measurements in Environmental Management and Policy
Herold, Martin ; Carter, Sarah ; Avitabile, Valerio ; Espejo, Andrés B. ; Jonckheere, Inge ; Lucas, Richard ; McRoberts, Ronald E. ; Næsset, Erik ; Nightingale, Joanne ; Petersen, Rachael ; Reiche, Johannes ; Romijn, Erika ; Rosenqvist, Ake ; Rozendaal, Danaë M.A. ; Seifert, Frank Martin ; Sanz, María J. ; Sy, V. de - \ 2019
Surveys in Geophysics 40 (2019)4. - ISSN 0169-3298 - p. 757 - 778.
The achievement of international goals and national commitments related to forest conservation and management, climate change, and sustainable development requires credible, accurate, and reliable monitoring of stocks and changes in forest biomass and carbon. Most prominently, the Paris Agreement on Climate Change and the United Nations’ Sustainable Development Goals in particular require data on biomass to monitor progress. Unprecedented opportunities to provide forest biomass data are created by a series of upcoming space-based missions, many of which provide open data targeted at large areas and better spatial resolution biomass monitoring than has previously been achieved. We assess various policy needs for biomass data and recommend a long-term collaborative effort among forest biomass data producers and users to meet these needs. A gap remains, however, between what can be achieved in the research domain and what is required to support policy making and meet reporting requirements. There is no single biomass dataset that serves all users in terms of definition and type of biomass measurement, geographic area, and uncertainty requirements, and whether there is need for the most recent up-to-date biomass estimate or a long-term biomass trend. The research and user communities should embrace the potential strength of the multitude of upcoming missions in combination to provide for these varying needs and to ensure continuity for long-term data provision which one-off research missions cannot provide. International coordination bodies such as Global Forest Observations Initiative (GFOI), Committee on Earth Observation Satellites (CEOS), and Global Observation of Forest Cover and Land Dynamics (GOFC‐GOLD) will be integral in addressing these issues in a way that fulfils these needs in a timely fashion. Further coordination work should particularly look into how space-based data can be better linked with field reference data sources such as forest plot networks, and there is also a need to ensure that reference data cover a range of forest types, management regimes, and disturbance regimes worldwide.
Forest Inventory-based Projection Systems for Wood and Biomass Availability
Barreiro, Susana ; Schelhaas, M. ; McRoberts, Ronald E. ; Kändler, Gerald - \ 2017
Springer (Managing Forest Ecosystems ) - ISBN 9783319561998 - 329 p.
Well-managed forests and woodlands are a renewable resource, producing essential
raw material with minimum waste and energy use. Rich in habitat and species diversity, forests may contribute to increased ecosystem stability. They can absorb the effects of unwanted deposition and other disturbances and protect neighbouring ecosystems by maintaining stable nutrient and energy cycles and by preventing soil degradation and erosion. They provide much-needed recreation and their continued existence contributes to stabilizing rural communities.
Forests are managed for timber production and species, habitat and process conservation. A subtle shift from multiple-use management to ecosystems management is being observed and the new ecological perspective of multi-functional forest management is based on the principles of ecosystem diversity, stability and elasticity, and the dynamic equilibrium of primary and secondary production. Making full use of new technology is one of the challenges facing forest management today. Resource information must be obtained with a limited budget. This requires better timing of resource assessment activities and improved use of multiple data sources. Sound ecosystems management, like any other management activity, relies on effective forecasting and operational control.
The aim of the book series Managing Forest Ecosystems is to present state-ofthe-art research results relating to the practice of forest management. Contributions are solicited from prominent authors. Each reference book, monograph or proceedings volume will be focused to deal with a specific context. Typical issues of the series are: resource assessment techniques, evaluating sustainability for evenaged and uneven-aged forests, multi-objective management, predicting forest development, optimizing forest management, biodiversity management and monitoring, risk assessment and economic analysis.
The Netherlands
Schelhaas, M. ; Clerkx, A.P.P.M. - \ 2017
In: Forest inventory-based projection systems for wood and biomass availability / Barreiro, Susana, Schelhaas, Mart-Jan, McRoberts, Ronald E., Kändler, Gerald, Springer (Managing forest ecosystems ) - ISBN 9783319561998 - p. 241 - 249.
Forest coverage in the Netherlands has expanded from 2% at the beginning of the nineteenth century to 11% nowadays (370,000 ha). Wood production is only one function among many others including recreation and nature protection. Consequently, the harvest level is low relative to the increment (~55%), and the wood-based industry is not an important economic activity. Forests are inventoried at irregular time intervals, with the last inventory in 2012–2013.

There is no regular program for making projections for the forest-based sector. In 2005, the Dutch Ministry for Agriculture, Nature and Food safety requested a projection for demand and supply of wood for the period 2005–2025, aiming at mapping risks and opportunities for forest owners as well as the woodworking industries. This study includes resource projections using two models, one is the individual tree-based model ForGEM and the other is the large scale scenario model EFISCEN.

Both models used data from the 5th National Forest Inventory (2001–2005) as a starting point and focussed on the 240,000 ha that were classified as production forest (i.e. excluding areas that are likely managed for different purposes). For the ForGEM simulations, plots were classified into 19 representative groups based on species and stand structure, and simulations were done for each group. For the EFISCEN simulations, the data were aggregated into eight groups based on dominant species. Both models simulated low and high harvesting scenarios, roughly aiming at removal of 40% and 80% of the increment, respectively. A simple supply estimation was done for the remaining 120,000 ha of other forest and trees outside forest.

The model outcomes differed substantially due to differences in treatment of increment. Additional uncertainty arises from the rather subjective judgement of the field crew as to whether a plot belongs to the production forest category or other forest category. With the sixth National Forest Inventory (NFI6) recently being completed, a better assessment of actual increment and forest management is possible, and more accurate projections can be made. Preferably, future projections should include additional information such as GIS analysis and estimates of costs and revenues. However, the most uncertain factor will remain the forest owners’ behaviour, especially how they will react to changes in prices and policies.
Forest resource projection tools at the European level
Schelhaas, M. ; Nabuurs, G.J. ; Verkerk, P.J. ; Hengeveld, G.M. ; Packalen, Tuula ; Sallnäs, O. ; Pilli, Roberto ; Grassi, J. ; Forsell, Nicklas ; Frank, S. ; Gusti, Mykola ; Havlik, Petr - \ 2017
In: Forest inventory-based projection systems for wood and biomass availability / Barreiro, Susana, Schelhaas, Mart-Jan, McRoberts, Ronald E., Kändler, Gerald, Springer (Managing forest ecosystems ) - ISBN 9783319561998 - p. 49 - 68.
Many countries have developed their own systems for projecting forest resources and wood availability. Although studies using these tools are helpful for developing national policies, they do not provide a consistent assessment for larger regions such as the European Union or Europe as a whole. Individual national-scale studies differ considerably in timing, underlying methodology and scenarios, and reports are not issued for all countries in the region. However, a clear demand for consistent projections at European scale still remains. This chapter describes the resource simulators and forest sector models EFISCEN, EFDM, CBM-CFS3, and GLOBIOM/G4M that can all be applied to individual European countries, as well as to Europe as a whole.
Future challenges for woody biomass projections
Schadauer, K. ; Barreiro, Susana ; Schelhaas, M. ; McRoberts, Ronald E. - \ 2017
In: Forest inventory-based projection systems for wood and biomass availability Springer (Managing forest ecosystems ) - ISBN 9783319561998 - p. 69 - 76.
Many drivers affect woody biomass projections including forest available for wood supply, market behavior, forest ownership, distributions by age and yield classes, forest typologies resulting from different edaphic, climatic conditions, and last but not least, how these factors are incorporated into projection systems. Net annual increment has been considered a useful variable for estimating future wood and biomass supply, but it can be misleading. In Europe, two different approaches have been used: a common European-level tool for all countries (“top-down” approach); and national tools (“bottom-up” approach). The trade-offs are that the “top-down” approach produces comparable results among countries, but ignores most of the topographic, climatic, vegetative and socio-economic conditions that are unique to countries and regions. The “bottom-up” approach better accommodates national and regional conditions but at the cost of comparability among country level results. A brief discussion of how these issues are handled in North America provides insights into different approaches and their linkages to national circumstances regarding country sizes, ownerships and general political frameworks. Another challenge lies in accommodating climate change and uncertainty in projections. Finally, working closely with experts from the demand side to minimize possible misunderstandings is also required. The first step towards increasing comparability of results from country-level projection systems is to understand the differences among these tools. Only then, can progress be made in terms of harmonizing the input and output variables or even progressing towards a common methodological approach and software structure.
Introduction
Barreiro, Susana ; Schelhaas, M. ; Kändler, Gerald ; McRoberts, Ronald E. - \ 2017
In: Forest Inventory-based Projection Systems for Wood and Biomass Availability / Barreiro, Susana, Schelhaas, Mart-Jan, McRoberts, Ronald E., Kändler, Gerald, Springer (Managing Forest Ecosystems ) - ISBN 9783319561998 - p. 3 - 15.
Past severe deforestation and over-exploitation of forest resources experienced by many countries have led to the need for accurate information on the state, growth and harvesting of forests which, in turn, led to the implementation of forest inventory systems. In the eighteenth century, the sustainability concept emerged, and regular forest management featuring Standwise Forest Inventory (SFI) was established for the primary purpose of ensuring adequate wood production. Unlike SFIs, National Forest Inventories (NFI) use systematic sampling designs which enable use of unbiased estimators and uncertainty measures. Forest inventory has been the base for national and international reporting, and data from both SFIs and NFIs are used as input to projections systems. Therefore, the accuracy of inventory data influences the reliability of future wood availability projections. Recent developments in the bioenergy and bio-economy sectors are expected to lead to continuous increases in biomass consumption and will require additional and more comprehensive projection studies to support policy makers. This chapter presents an overview of the current state of European and North American forests and forest resources and a brief summary of the wood consumption trends for both continents. Some background information is also presented for the two different kinds of forest inventories whose data are used in future projections. Finally, the book structure is also presented.
A method for classifying land parcels as receptive or unreceptive to nitrate leaching
Pebesma, E. ; Gruijter, J.J. de; Heuvelink, G.B.M. - \ 2004
In: Proceedings of the 6th international symposium on spatial accuracy assessment in natural resources and environmental sciences. - Portland, Maine, USA : McRoberts R. - p. 53 - 53.
Uncertainty Analysis of an Environmental Model Chain
Leopold, U. ; Heuvelink, G.B.M. ; Tiktak, A. - \ 2004
In: Proceedings of the sixth Int. Symp. on spatial Acc. Assess. in Nat. Res. and Env. Sc., Portland 28 June - 1 July 2004. - Portland Main, USE : R. McRoberts - p. 44 - 44.
An integrated framework for assessing uncertainties in environmental data, illustrated for different types of data and different complexities of problem
Brown, J. ; Heuvelink, G.B.M. - \ 2004
In: Accuracy 2004. - Portland, Maine U.S.A. : R.E. McRoberts - p. 26 - 26.
Understanding the limitations of environmental data is essential both for managing environmental systems effectively and for encouraging the responsible use of scientific research when knowledge is limited and priorities varied. Explicit assessments of data quality, and the uncertainties associated with data quality, are important in this context. Using a combination of quantitative and qualitative techniques for assessing probabilities, and acknowledging the importance of possibilistic techniques where probabilities are inappropriate, an integrated methodology is presented for handling uncertainties about environmental data. The methodology is based on a three-fold distinction between the magnitudes of uncertainty in data (and the ancillary information, such as data ‘support’, required to interpret this correctly), the sources of uncertainty in data, and the ‘goodness’ of an uncertainty model (critical self-reflection). In particular, emphasis is placed upon the conditions and parameters required for estimating quantitative probability models, for which a number of data categories are introduced, and on the application of simplifying assumptions to quantitative models of uncertainty. The methodology is illustrated with examples for different types of environmental data, including a discrete time-series, a categorical spatial variable and a continuous space-time variable, and for different complexities of problem. Here, three scenarios are introduced, including an ‘information-rich’ case, where probabilistic estimates of uncertainty are easily made, an ‘intermediate case’, and an ‘information-poor’ case, where the perceived quality of data, as well as the ‘goodness’ of an uncertainty model, becomes more case (person) dependent.
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