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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Carbon storage potential in degraded forests of Kalimantan, Indonesia
Ferraz, António ; Saatchi, Sassan ; Xu, Liang ; Hagen, Stephen ; Chave, Jerome ; Yu, Yifan ; Meyer, Victoria ; Garcia, Mariano ; Silva, Carlos ; Roswintiart, Orbita ; Samboko, Ari ; Sist, Plinio ; Walker, Sarah ; Pearson, Timothy R.H. ; Wijaya, Arief ; Sullivan, Franklin B. ; Rutishauser, Ervan ; Hoekman, Dirk ; Ganguly, Sangram - \ 2018
Environmental Research Letters 13 (2018)9. - ISSN 1748-9318
aboveground biomass mapping - airborne lidar - carbon - forest degradation - Indonesia - Kalimantan - peat swamp forests

The forests of Kalimantan are under severe pressure from extensive land use activities dominated by logging, palm oil plantations, and peatland fires. To implement the forest moratorium for mitigating greenhouse gas emissions, Indonesia's government requires information on the carbon stored in forests, including intact, degraded, secondary, and peat swamp forests. We developed a hybrid approach of producing a wall-to-wall map of the aboveground biomass (AGB) of intact and degraded forests of Kalimantan at 1 ha grid cells by combining field inventory plots, airborne lidar samples, and satellite radar and optical imagery. More than 110 000 ha of lidar data were acquired to systematically capture variations of forest structure and more than 104 field plots to develop lidar-biomass models. The lidar measurements were converted into biomass using models developed for 66 439 ha of drylands and 44 250 ha of wetland forests. By combining the AGB map with the national land cover map, we found that 22.3 Mha (106 ha) of forest remain on drylands ranging in biomass from 357.2 ±12.3 Mgha-1 in relatively intact forests to 134.2 ±6.1 Mgha-1 in severely degraded forests. The remaining peat swamp forests are heterogeneous in coverage and degradation level, extending over 3.62 Mha and having an average AGB of 211.8 ±12.7 Mgha-1. Emission factors calculated from aboveground biomass only suggest that the carbon storage potential of more than 15 Mha of degraded and secondary dryland forests will be about 1.1 PgC.

An integrated pan-tropical biomass map using multiple reference datasets
Avitabile, V. ; Herold, M. ; Heuvelink, G.B.M. ; Lewis, S.L. ; Phillips, O.L. ; Asner, G.P. ; Armston, J. ; Asthon, P. ; Banin, L.F. ; Bayol, N. ; Berry, N. ; Boeckx, P. ; Jong, B. De; Devries, B. ; Girardin, C. ; Kearsley, E. ; Lindsell, J.A. ; Lopez-gonzalez, G. ; Lucas, R. ; Malhi, Y. ; Morel, A. ; Mitchard, E. ; Nagy, L. ; Qie, L. ; Quinones, M. ; Ryan, C.M. ; Slik, F. ; Sunderland, T. ; Vaglio Laurin, G. ; Valentini, R. ; Verbeeck, H. ; Wijaya, A. ; Willcock, S. - \ 2016
Global Change Biology 22 (2016)4. - ISSN 1354-1013 - p. 1406 - 1420.
We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N–23.4 S) of 375 Pg dry mass, 9–18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15–21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha−1 vs. 21 and 28 Mg ha−1 for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets.
Identification and analysis of uncertainty in disaster risk reduction and climate change adaptation in South and Southeast Asia
Keur, Peter van der; Bers, Caroline van; Henriksen, Hans Jørgen ; Nibanupudi, Hari Krishna ; Yadav, Shobha ; Wijaya, Rina ; Subiyono, Andreas ; Mukerjee, Nandan ; Hausmann, Hans Jakob ; Hare, Matt ; Scheltinga, Catharien Terwisscha van; Pearn, Gregory ; Jaspers, Fons - \ 2016
International Journal of Disaster Risk Reduction 16 (2016). - ISSN 2212-4209 - p. 208 - 214.
Best practices - Capacity development - Climate change adaptation - Disaster risk reduction - Natural hazard management - Uncertainty

This paper addresses the mainstreaming of uncertainty in Disaster Risk Reduction (DRR) and Climate Change Adaptation (CCA) using as a case South and Southeast Asia, a region highly vulnerable to a wide range of natural disasters. Improvements in the implementation of DRR and CCA at the community and regional levels can be realized when the underlying uncertainties are understood and made transparent by all those involved in the science, practice and decision making of natural hazard management. This theme has been explored in a think tank fashion through knowledge elicitation and sharing among experts in the research community as well as practitioners and policy advisers with extensive experience with and insight into DRR and CCA at the regional and/or local levels. The intended result has been the identification of the means by which the capacity to integrate uncertainty can be developed. In this elicitation process, sources of uncertainty associated with the implementation of best practices in DRR and CCA at the regional and local levels. The results of presented are considered by the stakeholders involved to be valuable in expanding capacity to plan and implement more effective DRR and CCA policies and measures particularly at the community level where uncertainty plays a central role for those most vulnerable to current and future climate extreme events, and socio-economic constraints and changes

Drivers of deforestation in REDD+ countries: Results from a pan-tropical remote sensing analysis
Sy, V. de; Herold, M. ; Achard, F. ; Beuchle, R. ; Besnard, S. ; Clevers, J.G.P.W. ; Lindquist, E. ; Verchot, Louis V. ; Wijaya, A. - \ 2015
Drivers of deforestation in South America: first results from a pan-tropical remote sensing analysis
Sy, V. de; Herold, M. ; Beuchle, R. ; Besnard, S. ; Clevers, J.G.P.W. ; Lindquist, E. ; Verchot, Louis V. ; Wijaya, A. - \ 2015
Consistent forest change maps 1981 – 2000 from the AVHRR time series. Case studies for South America and Indonesia
Eberenz, J. ; Herold, M. ; Verbesselt, J. ; Wijaya, A. ; Lindquist, E. ; Defourny, P. ; Gibbs, H.K. ; Arino, O. ; Achard, F. - \ 2015
This study predicts global forest cover change for the 1980s and 1990s from AVHRR time series metrics in order to show how the series of consistent land cover maps for climate modeling produced by the ESA climate change initiative land cover project can be extended back in time. A Random Forest model was trained on global Landsat derived samples. While the deforestation was underestimated by the model, major global patterns were effectively reproduced. Compared to reference data for the Amazon satisfying accuracies (>0.8) were achieved, but results are less promising for Indonesia.
Assessing change in national forest monitoring capacities of 99 tropical countries
Romijn, J.E. ; Lantican, C.B. ; Herold, M. ; Lindquist, E. ; Ochieng, R.M. ; Wijaya, A. ; Murdiyarso, D. ; Verchot, L. - \ 2015
Forest Ecology and Management 352 (2015). - ISSN 0378-1127 - p. 109 - 123.
Monitoring of forest cover and forest functions provides information necessary to support policies and decisions to conserve, protect and sustainably manage forests. Especially in the tropics where forests are declining at a rapid rate, national forest monitoring systems capable of reliably estimating forest cover, forest cover change and carbon stock change are of vital importance. As a large number of tropical countries had limited capacity in the past to implement such a system, capacity building efforts are now ongoing to strengthen the technical and political skillsets necessary to implement national forest monitoring at institutional levels. This paper assesses the current status and recent changes in national forest monitoring and reporting capacities in 99 tropical countries, using the Food and Agriculture Organization of the United Nations (FAO) Forest Resources Assessment (FRA) 2015 data, complemented with FRA 2010 and FRA 2005 data. Three indicators “Forest area change monitoring and remote sensing capacities”, “Forest inventory capacities” and “Carbon pool reporting capacities” were used to assess the countries’ capacities for the years 2005, 2010 and 2015 and the change in capacities between 2005–2010 and 2010–2015. Forest area change monitoring and remote sensing capacities improved considerably between 2005 and 2015. The total tropical forest area that is monitored with good to very good forest area change monitoring and remote sensing capacities increased from 69% in 2005 to 83% in 2015. This corresponds to 1435 million ha in 2005 and 1699 million ha in 2015. This effect is related to more free and open remote sensing data and availability of techniques to improve forest area change monitoring. The total tropical forest area that is monitored with good to very good forest inventory capacities increased from 38% in 2005 to 66% in 2015. This corresponds to 785 million ha in 2005 and 1350 million ha in 2015. Carbon pool reporting capacities did not show as much improvement and the majority of countries still report at Tier 1 level. This indicates the need for greater emphasis on producing accurate emission factors at Tier 2 or Tier 3 level and improved greenhouse gases reporting. It is further shown that there was a positive adjustment in the net change in forest area where countries with lower capacities in the past had the tendency to overestimate the area of forest loss. The results emphasized the effectiveness of capacity building programmes (such as those by FAO and REDD+ readiness) but also the need for continued capacity development efforts. It is important for countries to maintain their forest monitoring system and update their inventories on a regular basis. This will further improve accuracy and reliability of data and information on forest resources and will provide countries with the necessary input to refine policies and decisions and to further improve forest management. Keywords Tropical forests; Forest cover change; Monitoring systems; Carbon reporting; Capacity building; REDD+
Comparative analysis and fusion for improved global biomass mapping
Avitabile, V. ; Herold, M. ; Lewis, S.L. ; Phillips, O.L. ; Aguilar-Amuchastegui, N. ; Asner, G.P. ; Brienen, R.J.W. ; DeVries, B.R. ; Gazolla Gatti, R. ; Feldpausch, T.R. ; Girardin, C. ; Jong, B. de; Kearsley, E. ; Klop, E. ; Lin, X. ; Lindsell, J. ; Lopez-Gonzalez, G. ; Lucas, R. ; Malhi, Y. ; Morel, A. ; Mitchard, E. ; Pandey, D. ; Piao, S. ; Ryan, C. ; Sales, M. ; Santoro, M. ; Vaglio Laurin, G. ; Valentini, R. ; Verbeeck, H. ; Wijaya, A. ; Willcock, S. - \ 2014
In: Book of abstracts of the International Conference Global Vegetation Monitoring and Modeling (GV2M). - - p. 251 - 252.
Multiple remote sensing data sources for REDD+ monitoring
Sy, V. de; Herold, M. ; Wijaya, A. ; Verchot, Louis V. ; Lindquist, E. ; Achard, F. - \ 2013
Workshop Report: Science solutions to policy challenges for evolving REDD+ measuring, reporting and verification requirements: report from a multistakeholder workshop
Mulatu, K.A. ; Herold, M. ; Koster, H. ; Aguilar-Amuchastegui, N. ; Thompson, D. ; Mora, B. ; Wijaya, A. ; Skutsch, M. ; Calmel, M. - \ 2013
Carbon Management 4 (2013)6. - ISSN 1758-3004 - p. 587 - 590.
A workshop entitled 'REDD+ measuring, reporting and verification science solutions to policy challenges' was organized by the WWF Forest and Climate Initiative, WWF Netherlands and Wageningen University REDD@WUR network from 10th to 12th June 2013 in Zeist, The Netherlands. The purpose of this workshop was to assess the status and development of monitoring approaches in light of the evowlving REDD+ measuring, reporting and verification needs from different actors in the REDD+ measuring, reporting and verification process. Accordingly, the most important gaps were identified and led to the development of research priorities with focus on better linking local and national REDD+ efforts on five themes, namely: monitoring and measurement; reporting and verification; reference levels; measuring, reporting and verification of safeguards; and benefit sharing.
Exploring different forest definitions and their impact on developing REDD+ reference emission levels: A case study for Indonesia
Romijn, J.E. ; Ainembabazi, J.H. ; Wijaya, A. ; Herold, M. ; Angelsen, A. ; Verchot, L. ; Murdiyarso, D. - \ 2013
Environmental Science & Policy 33 (2013). - ISSN 1462-9011 - p. 246 - 259.
greenhouse-gas emissions - tropical forests - carbon emissions - oil palm - deforestation - degradation - land - opportunities - conversion - cover
Developing countries participating in the mitigation mechanism of reducing emissions from deforestation and forest degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks (REDD+), need to determine a national forest reference emission level (REL) as part of their national monitoring system, which serves as a benchmark to measure the impact of their REDD+ actions. Using data from Indonesia, we show that the choice of a forest definition can have a large impact on estimates of deforestation and forest degradation areas, on assessment of drivers of deforestation and on the development of a REL. The total area of deforestation between 2000 and 2009 was 4.9 million ha when using the FAO definition, 18% higher when using a ‘natural forest definition’ and 27% higher when using the national definition. Using the national and natural forest definitions, large areas (>50%) were classified as shrubland after deforestation. We used regression models to predict future deforestation. Deforestation was much better predicted than degradation (R2 of 0.81 vs. 0.52), with the natural forest definition giving the best prediction. Apart from historical deforestation and initial forest cover, gross domestic product and human population were important predictors of future deforestation in Indonesia. Degradation processes were less well modeled and predictions relied on estimates of historical degradation and forest cover.
Capacity development in national forest monitoring: Experiences and progress for REDD+
Mora, B. ; Herold, M. ; Sy, V. de; Wijaya, A. ; Verchot, L. ; Penman, J. - \ 2012
Bogor, Indonesia : CIFOR - ISBN 9786028693868 - 99 p.
A stepwise framework for developing REDD+ reference levels
Herold, M. ; Angelsen, A. ; Verchot, L. ; Wijaya, A. ; Ainembabazi, J.H. - \ 2012
In: Analysing REDD+: Challenges and choices / Angelsen, A., Brockhaus, M., Sunderlin, W.D., Verchot, L.V., Bogor, Indonesia : Center for International Forestry Research (CIFOR) - ISBN 9786028693806 - p. 279 - 299.
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