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 handbook for standardized field and laboratory measurements in terrestrial climate change experiments and observational studies (ClimEx)
    Halbritter, Aud H. ; Boeck, Hans J. De; Eycott, Amy E. ; Reinsch, Sabine ; Robinson, David A. ; Vicca, Sara ; Berauer, Bernd ; Christiansen, Casper T. ; Estiarte, Marc ; Grünzweig, José M. ; Gya, Ragnhild ; Hansen, Karin ; Jentsch, Anke ; Lee, Hanna ; Linder, Sune ; Marshall, John ; Peñuelas, Josep ; Kappel Schmidt, Inger ; Stuart-Haëntjens, Ellen ; Wilfahrt, Peter ; Vandvik, Vigdis ; Abrantes, Nelson ; Almagro, María ; Althuizen, Inge H.J. ; Barrio, Isabel C. ; Beest, Mariska Te; Beier, Claus ; Beil, Ilka ; Carter Berry, Z. ; Birkemoe, Tone ; Bjerke, Jarle W. ; Blonder, Benjamin ; Blume-Werry, Gesche ; Bohrer, Gil ; Campos, Isabel ; Cernusak, Lucas A. ; Chojnicki, Bogdan H. ; Cosby, Bernhard J. ; Dickman, Lee T. ; Djukic, Ika ; Filella, Iolanda ; Fuchslueger, Lucia ; Gargallo-Garriga, Albert ; Gillespie, Mark A.K. ; Goldsmith, Gregory R. ; Gough, Christopher ; Halliday, Fletcher W. ; Hegland, Stein Joar ; Ploeg, Martine van der; Verbruggen, Erik - \ 2020
    Methods in Ecology and Evolution 11 (2020)1. - ISSN 2041-210X - p. 22 - 37.
    best practice - coordinated experiments - data management and documentation - ecosystem - experimental macroecology - methodology - open science - vegetation

    Climate change is a world-wide threat to biodiversity and ecosystem structure, functioning and services. To understand the underlying drivers and mechanisms, and to predict the consequences for nature and people, we urgently need better understanding of the direction and magnitude of climate change impacts across the soil–plant–atmosphere continuum. An increasing number of climate change studies are creating new opportunities for meaningful and high-quality generalizations and improved process understanding. However, significant challenges exist related to data availability and/or compatibility across studies, compromising opportunities for data re-use, synthesis and upscaling. Many of these challenges relate to a lack of an established ‘best practice’ for measuring key impacts and responses. This restrains our current understanding of complex processes and mechanisms in terrestrial ecosystems related to climate change. To overcome these challenges, we collected best-practice methods emerging from major ecological research networks and experiments, as synthesized by 115 experts from across a wide range of scientific disciplines. Our handbook contains guidance on the selection of response variables for different purposes, protocols for standardized measurements of 66 such response variables and advice on data management. Specifically, we recommend a minimum subset of variables that should be collected in all climate change studies to allow data re-use and synthesis, and give guidance on additional variables critical for different types of synthesis and upscaling. The goal of this community effort is to facilitate awareness of the importance and broader application of standardized methods to promote data re-use, availability, compatibility and transparency. We envision improved research practices that will increase returns on investments in individual research projects, facilitate second-order research outputs and create opportunities for collaboration across scientific communities. Ultimately, this should significantly improve the quality and impact of the science, which is required to fulfil society's needs in a changing world.

    SDG reporting using land cover and land use data in the Sentinel era
    Carter, S.L. ; Herold, M. ; Tsendbazar, N.E. ; Romijn, J.E. ; Seifert, F.M. - \ 2019
    Tropical deforestation drivers and associated carbon emission factors derived from remote sensing data
    Sy, Veronique De; Herold, Martin ; Achard, Frederic ; Avitabile, Valerio ; Baccini, Alessandro ; Carter, Sarah ; Clevers, Jan G.P.W. ; Lindquist, Erik ; Pereira, Maria ; Verchot, Louis - \ 2019
    Environmental Research Letters 14 (2019)9. - ISSN 1748-9318 - 29 p.
    Reducing emissions from deforestation and forest degradation, and enhancing carbon stocks (REDD+) is a crucial component of global climate change mitigation. Remote sensing can provide continuous and spatially explicit above-ground biomass (AGB) estimates, which can be valuable for the quantification of carbon stocks and emission factors (EFs). Unfortunately, there is little information on the fate of the land following tropical deforestation and of the associated carbon stock. This study quantified post-deforestation land use across the tropics for the period 1990 – 2000. This dataset was then combined with a pan-tropical AGB map at 30 m resolution to refine EFs from forest conversion by matching deforestation areas with their carbon stock before and after clearing and to assess spatial dynamics of EFs by follow-up land use. In Latin America, pasture was the most common follow-up land use (72%), with large-scale cropland (11%) a distant second. In Africa deforestation was often followed by small-scale cropping (61%) with a smaller role for pasture (15%). In Asia, small-scale cropland was the dominant agricultural follow-up land use (35%), closely followed by tree crops (28%). Deforestation often occurred in forests with lower than average carbon stocks. EFs showed high spatial variation within eco-zones and countries. While our EFs are only representative for the studied time period, our results show that EFs are mainly determined by the initial forest carbon stock. The estimates of the fraction of carbon lost were less dependent on initial forest biomass, which offers opportunities for REDD+ countries to use these fractions in combination with recent good quality national forest biomass maps or inventory data to quantify emissions from specific forest conversions. Our study highlights that the co-location of data on forest loss, biomass and fate of the land provides more insight into the spatial dynamics of land-use change and can help in attributing carbon emissions to human activities.

    Estimating aboveground net biomass change for tropical and subtropical forests: refinement of IPCC default rates using forest plot data
    Requena Suarez, Daniela ; Rozendaal, Danaë M.A. ; Sy, Veronique De; Phillips, Oliver L. ; Alvarez‐Dávila, Esteban ; Anderson‐teixeira, Kristina ; Araujo‐murakami, Alejandro ; Arroyo, Luzmila ; Baker, Timothy R. ; Bongers, Frans ; Brienen, Roel J.W. ; Carter, Sarah ; Cook‐Patton, Susan C. ; Feldpausch, Ted R. ; Griscom, Bronson W. ; Harris, Nancy ; Hérault, Bruno ; Honorio Coronado, Eurídice N. ; Leavitt, Sara M. ; Lewis, Simon L. ; Marimon, Beatriz S. ; Monteagudo Mendoza, Abel ; N'dja, Justin Kassi ; N'guessan, Anny Estelle ; Poorter, Lourens ; Qie, Lan ; Rutishauser, Ervan ; Sist, Plinio ; Sonké, Bonaventure ; Sullivan, Martin J.P. ; Vilanova, Emilio ; Wang, Maria M.H. ; Martius, Christopher ; Herold, Martin - \ 2019
    Global Change Biology 25 (2019)11. - ISSN 1354-1013 - p. 3609 - 3624.
    As countries advance in greenhouse gas (GHG) accounting for climate change mitigation, consistent estimates of aboveground net biomass change (∆AGB) are needed. Countries with limited forest monitoring capabilities in the tropics and subtropics rely on IPCC 2006 default ∆AGB rates, which are values per ecological zone, per continent. Similarly, research on forest biomass change at large scale also make use of these rates. IPCC 2006 default rates come from a handful of studies, provide no uncertainty indications, and do not distinguish between older secondary forests and old‐growth forests. As part of the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, we incorporate ∆AGB data available from 2006 onwards, comprising 176 chronosequences in secondary forests and 536 permanent plots in old‐growth and managed/logged forests located in 42 countries in Africa, North and South America, and Asia. We generated ∆AGB rate estimates for younger secondary forests (≤20 years), older secondary forests (>20 years and up to 100 years) and old‐growth forests, and accounted for uncertainties in our estimates. In tropical rainforests, for which data availability was the highest, our ∆AGB rate estimates ranged from 3.4 (Asia) to 7.6 (Africa) Mg ha‐1 yr‐1 in younger secondary forests, from 2.3 (North and South Ameri09ca) to 3.5 (Africa) Mg ha‐1 yr‐1 in older secondary forests, and 0.7 (Asia) to 1.3 (Africa) Mg ha‐1 yr‐1 in old‐growth forests. We provide a rigorous and traceable refinement of the IPCC 2006 default rates in tropical and subtropical ecological zones, and identify which areas require more research on ∆AGB. In this respect, this study should be considered as an important step towards quantifying the role of tropical and subtropical forests as carbon sinks with higher accuracy; our new rates can be used for large‐scale GHG accounting by governmental bodies, non‐governmental organisations and in scientific research.
    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.
    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.
    Implications of crop model ensemble size and composition for estimates of adaptation effects and agreement of recommendations
    Rodríguez, A. ; Ruiz-Ramos, M. ; Palosuo, T. ; Carter, T.R. ; Fronzek, S. ; Lorite, I.J. ; Ferrise, R. ; Pirttioja, N. ; Bindi, M. ; Baranowski, P. ; Buis, S. ; Cammarano, D. ; Chen, Y. ; Dumont, B. ; Ewert, F. ; Gaiser, T. ; Hlavinka, P. ; Hoffmann, H. ; Höhn, J.G. ; Jurecka, F. ; Kersebaum, K.C. ; Krzyszczak, J. ; Lana, M. ; Mechiche-Alami, A. ; Minet, J. ; Montesino, M. ; Nendel, C. ; Porter, J.R. ; Ruget, F. ; Semenov, M.A. ; Steinmetz, Z. ; Stratonovitch, P. ; Supit, I. ; Tao, F. ; Trnka, M. ; Wit, A. de; Rötter, R.P. - \ 2019
    Agricultural and Forest Meteorology 264 (2019). - ISSN 0168-1923 - p. 351 - 362.
    Climate change - Decision support - Outcome confidence - Response surface - Uncertainty - Wheat adaptation

    Climate change is expected to severely affect cropping systems and food production in many parts of the world unless local adaptation can ameliorate these impacts. Ensembles of crop simulation models can be useful tools for assessing if proposed adaptation options are capable of achieving target yields, whilst also quantifying the share of uncertainty in the simulated crop impact resulting from the crop models themselves. Although some studies have analysed the influence of ensemble size on model outcomes, the effect of ensemble composition has not yet been properly appraised. Moreover, results and derived recommendations typically rely on averaged ensemble simulation results without accounting sufficiently for the spread of model outcomes. Therefore, we developed an Ensemble Outcome Agreement (EOA) index, which analyses the effect of changes in composition and size of a multi-model ensemble (MME) to evaluate the level of agreement between MME outcomes with respect to a given hypothesis (e.g. that adaptation measures result in positive crop responses). We analysed the recommendations of a previous study performed with an ensemble of 17 crop models and testing 54 adaptation options for rainfed winter wheat (Triticum aestivum L.) at Lleida (NE Spain) under perturbed conditions of temperature, precipitation and atmospheric CO2 concentration. Our results confirmed that most adaptations recommended in the previous study have a positive effect. However, we also showed that some options did not remain recommendable in specific conditions if different ensembles were considered. Using EOA, we were able to identify the adaptation options for which there is high confidence in their effectiveness at enhancing yields, even under severe climate perturbations. These include substituting spring wheat for winter wheat combined with earlier sowing dates and standard or longer duration cultivars, or introducing supplementary irrigation, the latter increasing EOA values in all cases. There is low confidence in recovering yields to baseline levels, although this target could be attained for some adaptation options under moderate climate perturbations. Recommendations derived from such robust results may provide crucial information for stakeholders seeking to implement adaptation measures.

    Determining sectoral and regional sensitivity to climate and socio-economic change in Europe using impact response surfaces
    Fronzek, Stefan ; Carter, Timothy R. ; Pirttioja, Nina ; Alkemade, Rob ; Audsley, Eric ; Bugmann, Harald ; Flörke, Martina ; Holman, Ian ; Honda, Yasushi ; Ito, Akihiko ; Janes-Bassett, Victoria ; Lafond, Valentine ; Leemans, Rik ; Mokrech, Marc ; Nunez, Sarahi ; Sandars, Daniel ; Snell, Rebecca ; Takahashi, Kiyoshi ; Tanaka, Akemi ; Wimmer, Florian ; Yoshikawa, Minoru - \ 2019
    Regional Environmental Change 19 (2019)3. - ISSN 1436-3798 - p. 679 - 693.
    Gross domestic product (GDP) - Impact model - Population - Precipitation - Sensitivity analysis - Temperature

    Responses to future changes in climatic and socio-economic conditions can be expected to vary between sectors and regions, reflecting differential sensitivity to these highly uncertain factors. A sensitivity analysis was conducted using a suite of impact models (for health, agriculture, biodiversity, land use, floods and forestry) across Europe with respect to changes in key climate and socio-economic variables. Depending on the indicators, aggregated grid or indicative site results are reported for eight rectangular sub-regions that together span Europe from northern Finland to southern Spain and from western Ireland to the Baltic States and eastern Mediterranean, each plotted as scenario-neutral impact response surfaces (IRSs). These depict the modelled behaviour of an impact variable in response to changes in two key explanatory variables. To our knowledge, this is the first time the IRS approach has been applied to changes in socio-economic drivers and over such large regions. The British Isles region showed the smallest sensitivity to both temperature and precipitation, whereas Central Europe showed the strongest responses to temperature and Eastern Europe to precipitation. Across the regions, sensitivity to temperature was lowest for the two indicators of river discharge and highest for Norway spruce productivity. Sensitivity to precipitation was lowest for intensive agricultural land use, maize and potato yields and Scots pine productivity, and highest for Norway spruce productivity. Under future climate projections, North-eastern Europe showed increases in yields of all crops and productivity of all tree species, whereas Central and East Europe showed declines. River discharge indicators and forest productivity (except Holm oak) were projected to decline over southern European regions. Responses were more sensitive to socio-economic than to climate drivers for some impact indicators, as demonstrated for heat-related mortality, coastal flooding and land use.

    Using data to understand the forest-agriculture nexus and to achieve climate-smart land use
    Carter, S.L. ; Herold, M. ; Sy, V. de; Brandt, Patric ; Pratihast, A.K. - \ 2018
    Land cover products for SDG monitoring
    Carter, Sarah - \ 2018
    Climate-smart agriculture : Will higher yields lead to lower deforestation?
    Ngoma, Hambulo ; Angelsen, Arild ; Carter, S.L. ; Roman Cuesta, Rosa Maria - \ 2018
    In: Transforming REDD+ / Angelsen, A., Martius, C., De Sy, V., Duchelle, A.E., Larson, A.M., Pham, T.T., Center for International Forestry Research (CIFOR) - ISBN 9786023870790 - p. 175 - 187.
    Unravelling the moons : Review of the genera paratetilla and cinachyrella in the indo-pacific (demospongiae, tetractinellida, tetillidae)
    Santodomingo, Nadiezhda ; Becking, Leontine E. - \ 2018
    ZooKeys 2018 (2018)791. - ISSN 1313-2989 - p. 1 - 46.
    Anchialine systems - Coral reef - Mangrove - Marine lake - Porifera

    Paratetilla bacca (Selenka, 1867) and Cinachyrella australiensis (Carter, 1886) occur in a broad range of marine environments and are allegedly widely distributed species in the Indo-Pacific. We coin the term ‘moon sponges’ for these species as they are spherical in shape with numerous porocalices resembling the lunar surface. Both species have a complex taxonomic history with high synonymization, in particular by Burton (1934, 1959). An examination of the junior synonyms proposed by Burton (1934, 1959) was conducted to establish the validity of the names. More than 230 specimens from Naturalis Biodiversity Center were reviewed that belong to the genera Paratetilla and Cinachyrella from marine lakes, coral reefs, and mangroves in Indonesia. The aim of the current study was to untangle the taxonomic history, describe the collection of moon sponges from Indonesia, and develop a key. We extensively reviewed the taxonomic literature as well as holotypes of most of the species synonymized by Burton. The taxonomic history of Paratetilla spp. and Cinachyrella australiensis showed some cases of misinterpreted synonyms, misidentifications, and lack of detailed descriptions for some species. The conclusion of the revision is that there are three valid species of Paratetilla (P. arcifera, P. bacca, and P. corrugata) and four valid species of Cinachyrella (C. australiensis, C. porosa, C. paterifera, and C. schulzei) in Indonesia. This is furthermore corroborated by molecular work from previous studies. Paratetilla arcifera Wilson 1925 and C. porosa (Lendenfeld, 1888) are resurrected. A full review of taxonomic history is provided as well as a key for identification of moon sponges from Indonesia. All species are sympatric and we expect that there are undescribed species remaining within the Tetillidae from the Indo-Pacific. Our current review provides the framework from which to describe new species in the genera Paratetilla and Cinachyrella from the Indo-Pacific.

    Climate-smart land use requires local solutions, transdisciplinary research, policy coherence and transparency
    Carter, Sarah ; Arts, Bas ; E. Giller, Ken ; Soto Golcher, Cinthia ; Kok, Kasper ; Koning, Jessica De; Noordwijk, Meine Van; Reidsma, Pytrik ; Rufino, Mariana C. ; Salvini, Giulia ; Verchot, Louis ; Wollenberg, Eva ; Herold, Martin - \ 2018
    Carbon Management 9 (2018)3. - ISSN 1758-3004 - p. 291 - 301.
    Successfully meeting the mitigation and adaptation targets of the Paris Climate Agreement (PA) will depend on strengthening the ties between forests and agriculture. Climate-smart land use can be achieved by integrating climate-smart agriculture (CSA) and REDD+. The focus on agriculture for food security within a changing climate, and on forests for climate change mitigation and adaptation, can be achieved simultaneously with a transformational change in the land-use sector. Striving for both independently will lead to competition for land, inefficiencies in monitoring and conflicting agendas. Practical solutions exist for specific contexts that can lead to increased agricultural output and forest protection. Landscape-level emissions accounting can be used to identify these practices. Transdisciplinary research agendas can identify and prioritize solutions and targets for integrated mitigation and adaptation interventions. Policy coherence must be achieved at a number of levels, from international to local, to avoid conflicting incentives. Transparency must lastly be integrated, through collaborative design of projects, and open data and methods. Climate-smart land use requires all these elements, and will increase the likelihood of successful REDD+ and CSA interventions. This will support the PA as well as other initiatives as part of the Sustainable Development Goals.
    Factors influencing the stay-exit intention of small livestock farmers : Empirical evidence from southern Chile
    Carter-Leal, Luis M. ; Oude-Lansink, Alfons ; Saatkamp, Helmut - \ 2018
    Spanish Journal of Agricultural Research 16 (2018)1. - ISSN 1695-971X
    Binary choice model - Exit intention - Family farming - Peasant - South America
    This study analyses the factors driving the stay-exit intention of small livestock farmers located in southern Chile. Technical, economic, and social characteristics from 212 farmers were included in this study. Through an empirical probit model we identified the variables that should be considered when developing rural policies aimed at increasing the likelihood to stay in farming. The results showed that 12 out of the 30 parameters were significant (p<0.10), with an extremely good fit of the model (McFadden pseudo-R2 = 0.25, Count R2 = 75.9%). Particularly, ‘female farmer’, ‘positive expectation about future farming life’, ‘capacity of farm income to cover the expenses of the whole family’, ‘mixed production’, ‘participation in an association’, and ‘distance to the nearest city’ were positively associated with the stay intention. Moreover, our study also indicates that ‘existence of a defined retirement age’, ‘existence of a defined sale price for the farm’, ‘a mixed farm focused on livestock production’, ‘the possibility to make own decisions’, ‘age squared’, and the ‘number of people living at the farm’ were negatively associated with the stay intention. Our empirical findings suggest that farmer characteristics (gender, family size), the farming system (multi-activity production, efficiency), and social aspects of the rural society (associations, protection of agricultural products) are also important aspects that should be considered by rural development policies aimed at improving the likelihood of staying, in addition to the technical characteristics of the farming which have been traditionally addressed in developing countries.
    Deforestation and agriculture in the tropics: carbon emissions and options for mitigation
    Carter, Sarah - \ 2018
    Wageningen University. Promotor(en): M. Herold; L. Kooistra, co-promotor(en): M.C. Rufino; L. Verchot. - Wageningen : Wageningen University - ISBN 9789463438322 - 164

    Agriculture is the largest driver of deforestation globally, and this conversion of land from forests to agriculture, results in emissions which are contributing to climate change. This thesis focuses on exploring agriculture-driven deforestation at the country level, from the perspective of quantifying emissions, estimating the potential for mitigation, including identifying potential barriers to success, and highlighting enabling conditions for mitigation of these emissions. Efforts to reduce deforestation are being undertaken, for example through the mechanism REDD+; reducing emissions from deforestation and forest degradation and the role of conservation, sustainable management of forests and enhancement of forest carbon stocks in developing countries. At the same time, efforts are underway to try to reduce hunger by increasing food security (for example through the sustainable development goals (SDGs)). Competition for land can result when both these goals are pursued at the same time, because forested land is protected for carbon storage, while agricultural land is expanded (often into forests) to provide sufficient land for growing food. There are several ways in which both goals, forest protection and food security might be achieved together, and we focus on assessing the potential of two approaches which can potentially spare forested land. These approaches are: increasing production on existing agricultural land, and expanding agriculture onto non-forested available land. Emerging phenomena such as Large Scale Land Acquisitions (LSLA, otherwise known as land grabs) add to the complexity of the challenge, and we discuss the potential threat which LSLA has on forested land, and how to avoid LSLA for agriculture in forested land. A transformational change of the land sector is proposed to ensure that both goals can be met. Several ingredients are required to achieve a transformational change, and linking REDD+ to Climate Smart Agriculture (CSA) approaches is discussed. CSA interventions are those which are able to reduce emissions or store carbon while increasing the adaptive capacity of agriculture to climate change and increasing food production.

    Chapter 2 provides new estimates of emissions from agriculture-driven deforestation in 91 countries using a data-driven approach. Latin America was found to have the highest emissions, and these emissions peaked between 2000 and 2005 and then declined. Emissions in Africa has been rising since 1990, with the countries in the Congo Basin being particular contributors to this rise in emissions. Uncertainties of these country emission estimates are ±62.4% (average for 1990-2015), and emissions from Asia are the most uncertain. The uncertainty of the input datasets was used to estimate the uncertainty of the emissions estimate, and the area of deforestation, and fraction which agriculture is driving deforestation were found to be the largest contributors to uncertainty of the emissions estimates. Increasing the certainty of these two data types should be a priority, and will lead to an increased certainty for the emissions estimates.

    Chapter 3 compares direct and indirect emissions from agriculture at the national level, where direct are emissions from existing agricultural land, and indirect emissions are those from agriculture-driven deforestation. A decision tree was produced which can be used to guide decision making by identifying priority countries for mitigation initiatives. The decision tree uses several indicators related to the potential for mitigation, enabling environment, and associated risks to livelihoods to identify countries which have the most potential for the mitigation of either direct or indirect agricultural emissions. Six priority countries are highlighted as having a good mitigation potential for agriculture-driven deforestation while having a good enabling environment (in this case engagement in REDD+) and which also have low risks to livelihoods from the implementation of interventions in the agriculture sector. They are: Panama, Paraguay, Ecuador, Mexico, Malaysia and Peru.

    Chapter 4 focusses on LSLA, and their potential impacts on forests. A country level analysis was carried out, and the characteristics which are typically found in countries which have LSLA were described. Countries which have these characteristics and which do not yet have LSLA are for example considered to be at risk from LSLA. Countries which have LSLA or are at risk from LSLA were assessed for the risk of LSLA-driven deforestation. Other key targets for interventions to reduce deforestation are highlighted, such as those countries with large numbers of LSLA and which already have a lot of agriculture-driven deforestation. The potential conflicts between LSLA and REDD+ are discussed, and investor-side policies such as zero deforestation pledges from commodity producers, green procurement policies, and initiatives such as the Roundtable For Sustainable Palm Oil are highlighted as potential solutions to these conflicts. Lessons learned from implementing REDD+, which has a number of shared characteristics with LSLA, can be applied in order to reduce the negative impacts of LSLA.

    Chapter 5 discusses the potential for forest-land sparing interventions to be implemented in the agriculture sector. A transformative change which incorporates multiple interventions and brings together the forest and agriculture sectors is proposed. Climate Smart Agriculture approaches should be considered, but only when they do not lead to expansion of agriculture into forests. The need for supporting policies to avoid this occurring is discussed. Policy coherence is a barrier to this change as policies favouring both conversion to agriculture (including those which enable LSLA), and forest protection can occur in the same place. The use of the landscape approach as a platform to address this challenge is discussed. Landscape-level emissions accounting, which takes into consideration both direct and indirect emissions from agriculture, can be used to evaluate the impact of mitigation interventions across sectors. The need for transparency in the land sector, in relation to emissions reporting in particular is introduced, and is a key requirement for access to carbon finance which can potentially support forest land-sparing interventions.

    Chapter 6 concludes the thesis, and discusses the wider implications for this work. The link between the findings in this thesis and the SDGs is explored. The SDGs may lead to future competition for land due to goals which focus on reducing hunger, protecting forests and increasing the proportion of renewable energy unless action is taken. Future data needs are discussed, as although we provide (in chapter 2) new data on agriculture-driven deforestation, they are still uncertain and data on potential future trends in agriculture-driven deforestation are not available. The need for consideration of emissions related to the impact of agriculture on forest degradation and on carbon losses in soils is another data gap, and relates to recent efforts to restore degraded land – which could be one of the most promising mitigation efforts which can also support the production of more food for growing global populations. The urgent need to address climate change highlights the opportunities in the land sector, not only to mitigate emissions, but also to promote food security.

    Agriculture-driven deforestation in the tropics from 1990 to-2015: emissions, trends and uncertainties
    Carter, Sarah ; Herold, Martin ; Avitabile, Valerio ; Bruin, Sytze de; Sy, Veronique de; Kooistra, Lammert ; Rufino, Mariana C. - \ 2018
    Environmental Research Letters 13 (2018)1. - ISSN 1748-9326
    Limited data exists on emissions from agriculture-driven deforestation, and available data are typically uncertain. In this paper, we provide comparable estimates of emissions from both all deforestation and agriculture-driven deforestation, with uncertainties for 91 countries across the tropics between 1990 and 2015. Uncertainties associated with input datasets (activity data and emissions factors) were used to combine the datasets, where most certain datasets contribute the most. This method utilizes all the input data, while minimizing the uncertainty of the emissions estimate. The uncertainty of input datasets was influenced by the quality of the data, the sample size (for sample-based datasets), and the extent to which the timeframe of the data matches the period of interest. Area of deforestation, and the agriculture-driver factor (extent to which agriculture drives deforestation), were the most uncertain components of the emissions estimates, thus improvement in the uncertainties related to these estimates will provide the greatest reductions in uncertainties of emissions estimates. Over the period of the study, Latin America had the highest proportion of deforestation driven by agriculture (78%), and Africa had the lowest (62%). Latin America had the highest emissions from agriculture-driven deforestation, and these peaked at 974 ± 148 Mt CO2 yr−1 in 2000–2005. Africa saw a continuous increase in emissions between 1990 and 2015 (from 154 ± 21–412 ± 75 Mt CO2 yr−1), so mitigation initiatives could be prioritized there. Uncertainties for emissions from agriculture-driven deforestation are ± 62.4% (average over 1990–2015), and uncertainties were highest in Asia and lowest in Latin America. Uncertainty information is crucial for transparency when reporting, and gives credibility to related mitigation initiatives. We demonstrate that uncertainty data can also be useful when combining multiple open datasets, so we recommend new data providers to include this information.
    Classifying multi-model wheat yield impact response surfaces showing sensitivity to temperature and precipitation change
    Fronzek, Stefan ; Pirttioja, Nina ; Carter, Timothy R. ; Bindi, Marco ; Hoffmann, Holger ; Palosuo, Taru ; Ruiz-Ramos, Margarita ; Tao, Fulu ; Trnka, Miroslav ; Acutis, Marco ; Asseng, Senthold ; Baranowski, Piotr ; Basso, Bruno ; Bodin, Per ; Buis, Samuel ; Cammarano, Davide ; Deligios, Paola ; Destain, Marie France ; Dumont, Benjamin ; Ewert, Frank ; Ferrise, Roberto ; François, Louis ; Gaiser, Thomas ; Hlavinka, Petr ; Jacquemin, Ingrid ; Kersebaum, Kurt Christian ; Kollas, Chris ; Krzyszczak, Jaromir ; Lorite, Ignacio J. ; Minet, Julien ; Minguez, M.I. ; Montesino, Manuel ; Moriondo, Marco ; Müller, Christoph ; Nendel, Claas ; Öztürk, Isik ; Perego, Alessia ; Rodríguez, Alfredo ; Ruane, Alex C. ; Ruget, Françoise ; Sanna, Mattia ; Semenov, Mikhail A. ; Slawinski, Cezary ; Stratonovitch, Pierre ; Supit, Iwan ; Waha, Katharina ; Wang, Enli ; Wu, Lianhai ; Zhao, Zhigan ; Rötter, Reimund P. - \ 2018
    Agricultural Systems 159 (2018). - ISSN 0308-521X - p. 209 - 224.
    Classification - Climate change - Crop model - Ensemble - Sensitivity analysis - Wheat

    Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (-2 to +9°C) and precipitation (-50 to +50%). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses.The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern.The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description.Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index.Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.

    Adaptation response surfaces for managing wheat under perturbed climate and CO2 in a Mediterranean environment
    Ruiz-Ramos, M. ; Ferrise, R. ; Rodríguez, A. ; Lorite, I.J. ; Bindi, M. ; Carter, T.R. ; Fronzek, S. ; Palosuo, T. ; Pirttioja, N. ; Baranowski, P. ; Buis, S. ; Cammarano, D. ; Chen, Y. ; Dumont, B. ; Ewert, F. ; Gaiser, T. ; Hlavinka, P. ; Hoffmann, H. ; Höhn, J.G. ; Jurecka, F. ; Kersebaum, K.C. ; Krzyszczak, J. ; Lana, M. ; Mechiche-Alami, A. ; Minet, J. ; Montesino, M. ; Nendel, C. ; Porter, J.R. ; Ruget, F. ; Semenov, M.A. ; Steinmetz, Z. ; Stratonovitch, P. ; Supit, I. ; Tao, F. ; Trnka, M. ; Wit, A. De; Rötter, R.P. - \ 2018
    Agricultural Systems 159 (2018). - ISSN 0308-521X - p. 260 - 274.
    Adaptation of crops to climate change has to be addressed locally due to the variability of soil, climate and the specific socio-economic settings influencing farm management decisions. Adaptation of rainfed cropping systems in the Mediterranean is especially challenging due to the projected decline in precipitation in the coming decades, which will increase the risk of droughts. Methods that can help explore uncertainties in climate projections and crop modelling, such as impact response surfaces (IRSs) and ensemble modelling, can then be valuable for identifying effective adaptations. Here, an ensemble of 17 crop models was used to simulate a total of 54 adaptation options for rainfed winter wheat (Triticum aestivum) at Lleida (NE Spain). To support the ensemble building, an ex post quality check of model simulations based on several criteria was performed. Those criteria were based on the “According to Our Current Knowledge” (AOCK) concept, which has been formalized here. Adaptations were based on changes in cultivars and management regarding phenology, vernalization, sowing date and irrigation. The effects of adaptation options under changed precipitation (P), temperature (T), [CO2] and soil type were analysed by constructing response surfaces, which we termed, in accordance with their specific purpose, adaptation response surfaces (ARSs). These were created to assess the effect of adaptations through a range of plausible P, T and [CO2] perturbations. The results indicated that impacts of altered climate were predominantly negative. No single adaptation was capable of overcoming the detrimental effect of the complex interactions imposed by the P, T and [CO2] perturbations except for supplementary irrigation (sI), which reduced the potential impacts under most of the perturbations. Yet, a combination of adaptations for dealing with climate change demonstrated that effective adaptation is possible at Lleida. Combinations based on a cultivar without vernalization requirements showed good and wide adaptation potential. Few combined adaptation options performed well under rainfed conditions. However, a single sI was sufficient to develop a high adaptation potential, including options mainly based on spring wheat, current cycle duration and early sowing date. Depending on local environment (e.g. soil type), many of these adaptations can maintain current yield levels under moderate changes in T and P, and some also under strong changes. We conclude that ARSs can offer a useful tool for supporting planning of field level adaptation under conditions of high uncertainty.
    Exploring urban adaptation practice : Focus on co-production and multi-level governance
    Carter, J. ; Lefebre, Filip ; Connelly, Angela ; Terenzi, Alberto ; Mendizabal, Maddalen ; Dumonteil, Margaux ; Sips, K. ; Pansaerts, Resi ; Feliu, Efrén ; Verstraeten, G. ; Coninx, I. - \ 2017
    In: Full Programme: ECCA (European Conference on Climate Adaptation) 2017. - - p. 267 - 270.
    co-production - collaboration - citizen participation - multi-level governance - science-policy interface - financing constraints - european cities
    Open land cover from OpenStreetMap and remote sensing
    Schultz, Michael ; Voss, Janek ; Auer, Michael ; Carter, Sarah ; Zipf, Alexander - \ 2017
    International Journal of applied Earth Observation and Geoinformation 63 (2017). - ISSN 0303-2434 - p. 206 - 213.
    OpenStreetMap (OSM) tags were used to produce a global Open Land Cover (OLC) product with fractional data gaps available at osmlanduse.org. Data gaps in the global OLC map were filled for a case study in Heidelberg, Germany using free remote sensing data, which resulted in a land cover (LC) prototype with complete coverage in this area. Sixty tags in the OSM were used to allocate a Corine Land Cover (CLC) level 2 land use classification to 91.8% of the study area, and the remaining gaps were filled with remote sensing data. For this case study, complete are coverage OLC overall accuracy was estimated 87%, which performed better than the CLC product (81% overall accuracy) of 2012. Spatial thematic overlap for the two products was 84%. OLC was in large parts found to be more detailed than CLC, particularly when LC patterns were heterogeneous, and outperformed CLC in the classification of 12 of the 14 classes. Our OLC product represented data created in different periods; 53% of the area was 2011–2016, and 46% of the area was representative of 2016–2017.
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