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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    We will mail you new results for this query: keywords==conterminous united-states
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A high-resolution bioclimate map of the world: a unifying framework for global biodiversity research and monitoring
Metzger, M.J. ; Bunce, R.G.H. ; Jongman, R.H.G. ; Sayre, R. ; Trabucco, A. ; Zomer, R. - \ 2013
Global Ecology and Biogeography 22 (2013)5. - ISSN 1466-822X - p. 630 - 638.
conterminous united-states - climate-change - land classification - observing system - europe - stratification - ecoregions - impacts - regions - trends
Aim To develop a novel global spatial framework for the integration and analysis of ecological and environmental data. Location The global land surface excluding Antarctica. Methods A broad set of climate-related variables were considered for inclusion in a quantitative model, which partitions geographic space into bioclimate regions. Statistical screening produced a subset of relevant bioclimate variables, which were further compacted into fewer independent dimensions using principal components analysis (PCA). An ISODATA clustering routine was then used to classify the principal components into relatively homogeneous environmental strata. The strata were aggregated into global environmental zones based on the attribute distances between strata to provide structure and support a consistent nomenclature. Results The global environmental stratification (GEnS) consists of 125 strata, which have been aggregated into 18 global environmental zones. The stratification has a 30 arcsec resolution (equivalent to 0.86 km2 at the equator). Aggregations of the strata were compared with nine existing global, continental and national bioclimate and ecosystem classifications using the Kappa statistic. Values range between 0.54 and 0.72, indicating good agreement in bioclimate and ecosystem patterns between existing maps and the GEnS. Main conclusions The GEnS provides a robust spatial analytical framework for the aggregation of local observations, identification of gaps in current monitoring efforts and systematic design of complementary and new monitoring and research. The dataset is available for non-commercial use through the GEO portal (
Global Multimodel Analsysis of Drought in Runoff for the Second Half of the Twentieth Century
Huijgevoort, M.H.J. van; Hazenberg, P. ; Lanen, H.A.J. van; Teuling, A.J. ; Clark, D.B. ; Folwell, S. ; Gosling, S. ; Uijlenhoet, R. - \ 2013
Journal of Hydrometeorology 14 (2013)5. - ISSN 1525-755X - p. 1535 - 1552.
environment simulator jules - conterminous united-states - hydrological drought - model description - scale - ensemble - streamflow - europe - variability - algorithm
During the past decades large-scale models have been developed to simulate global and continental terrestrial water cycles. It is an open question whether these models are suitable to capture hydrological drought, in terms of runoff, on a global scale. A multimodel ensemble analysis was carried out to evaluate if 10 such large-scale models agree on major drought events during the second half of the twentieth century. Time series of monthly precipitation, monthly total runoff from 10 global hydrological models, and their ensemble median have been used to identify drought. Temporal development of area in drought for various regions across the globe was investigated. Model spread was largest in regions with low runoff and smallest in regions with high runoff. In vast regions, correlation between runoff drought derived from the models and meteorological drought was found to be low. This indicated that models add information to the signal derived from precipitation and that runoff drought cannot directly be determined from precipitation data alone in global drought analyses with a constant aggregation period. However, duration and spatial extent of major drought events differed between models. Some models showed a fast runoff response to rainfall, which led to deviations from reported drought events in slowly responding hydrological systems. By using an ensemble of models, this fast runoff response was partly overcome and delay in drought propagating from meteorological drought to drought in runoff was included. Finally, an ensemble of models also allows for consideration of uncertainty associated with individual model structures.
The use of forest stand age information in an atmospheric CO2 inversion applied to North America
Deng, F. ; Chen, J.M. ; Pan, Y. ; Peters, W. ; Birdsey, R. ; McCullough, K. ; Xiao, J. - \ 2013
Biogeosciences 10 (2013)8. - ISSN 1726-4170 - p. 5335 - 5348.
terrestrial carbon metabolism - conterminous united-states - general-circulation model - ponderosa pine - interannual variability - disturbance history - satellite imagery - flux inversion - climate-change - transport
Atmospheric inversions have become an important tool in quantifying carbon dioxide (CO2) sinks and sources at a variety of spatiotemporal scales, but associated large uncertainties restrain the inversion research community from reaching agreement on many important subjects. We enhanced an atmospheric inversion of the CO2 flux for North America by introducing spatially explicit information on forest stand age for US and Canada as an additional constraint, since forest carbon dynamics are closely related to time since disturbance. To use stand age information in the inversion, we converted stand age into an age factor, and included the covariances between subcontinental regions in the inversion based on the similarity of the age factors. Our inversion results show that, considering age factors, regions with recently disturbed or old forests are often nudged towards carbon sources, while regions with middle-aged productive forests are shifted towards sinks. This conforms to stand age effects observed in flux networks. At the subcontinental level, our inverted carbon fluxes agree well with continuous estimates of net ecosystem carbon exchange (NEE) upscaled from eddy covariance flux data based on MODIS data. Inverted fluxes with the age constraint exhibit stronger correlation to these upscaled NEE estimates than those inverted without the age constraint. While the carbon flux at the continental and subcontinental scales is predominantly determined by atmospheric CO2 observations, the age constraint is shown to have potential to improve the inversion of the carbon flux distribution among subcontinental regions, especially for regions lacking atmospheric CO2 observations
Environmental stratifications as the basis for national, European and global ecological monitoring
Metzger, M.J. ; Brus, D.J. ; Bunce, R.G.H. ; Carey, P.D. ; Goncalves, J. ; Honrado, J. ; Jongman, R.H.G. ; Trabucco, A. ; Zomer, R. - \ 2013
Ecological Indicators 33 (2013). - ISSN 1470-160X - p. 26 - 35.
conterminous united-states - countryside survey - observing system - temporal trend - biodiversity - classification - design - earth - land - landscapes
There is growing urgency for integration and coordination of global environmental and ecological data and indicators required to respond to the ‘grand challenges’ the planet is facing, including climate change and biodiversity decline. A consistent stratification of land into relatively homogenous strata provides a valuable spatial framework for comparison and analysis of ecological and environmental data across large heterogeneous areas. We discuss how statistical stratification can be used to design national, European and global biodiversity observation networks. The value of strategic ecological survey based on stratified samples is first illustrated using the United Kingdom (UK) Countryside Survey, a national monitoring programme that has measured ecological change in the UK countryside for the last 35 years. We then present a design for a European-wide sampling design for monitoring common habitats, and discuss ways of extending these approaches globally, supported by the recently developed Global Environmental Stratification. The latter provides a robust spatial analytical framework for the identification of gaps in current monitoring efforts, and systematic design of new complementary monitoring and research. Examples from Portugal and the transboundary Kailash Sacred Landscape in the Himalayas illustrate the potential use of this stratification, which has been identified as a focal geospatial dataset within the Group on Earth Observation Biodiversity Observation Network (GEO BON).
A generic method for hydrological drought identification across different climate regions
Huijgevoort, M.H.J. van; Hazenberg, P. ; Lanen, H.A.J. van; Uijlenhoet, R. - \ 2012
Hydrology and Earth System Sciences 16 (2012). - ISSN 1027-5606 - p. 2437 - 2451.
environment simulator jules - conterminous united-states - soil-moisture - model description - multimodel ensemble - land-surface - 20th-century - precipitation - temperature - definition
The identification of hydrological drought at global scale has received considerable attention during the last decade. However, climate-induced variation in runoff across the world makes such analyses rather complicated. This especially holds for the drier regions of the world (both cold and warm), where, for a considerable period of time, zero runoff can be observed. In the current paper, we present a method that enables to identify drought at global scale across climate regimes in a consistent manner. The method combines the characteristics of the classical variable threshold level method that is best applicable in regions with non-zero runoff most of the time, and the consecutive dry days (period) method that is better suited for areas where zero runoff occurs. The newly presented method allows a drought in periods with runoff to continue in the following period without runoff. The method is demonstrated by identifying droughts from discharge observations of four rivers situated within different climate regimes, as well as from simulated runoff data at global scale obtained from an ensemble of five different land surface models. The identified drought events obtained by the new approach are compared to those resulting from application of the variable threshold level method or the consecutive dry period method separately. Results show that, in general, for drier regions, the threshold level method overestimates drought duration, because zero runoff periods are included in a drought, according to the definition used within this method. The consecutive dry period method underestimates drought occurrence, since it cannot identify droughts for periods with runoff. The developed method especially shows its relevance in transitional areas, because, in wetter regions, results are identical to the classical threshold level method. By combining both methods, the new method is able to identify single drought events that occur during positive and zero runoff periods, leading to a more realistic global drought characterization, especially within drier environments.
A comparison of time series similarity measures for classification and change detection of ecosystem dynamics
Lhermitte, S. ; Verbesselt, J. ; Verstraeten, W.W. ; Coppin, P. - \ 2011
Remote Sensing of Environment 115 (2011)12. - ISSN 0034-4257 - p. 3129 - 3152.
land-cover classification - conterminous united-states - nino-southern oscillation - rangeland vegetation type - finding coupled patterns - change-vector analysis - satellite sensor data - sub-saharan africa - leaf-area index - avhrr ndvi data
Time series of remote sensing imagery or derived vegetation indices and biophysical products have been shown particularly useful to characterize land ecosystem dynamics. Various methods have been developed based on temporal trajectory analysis to characterize, classify and detect changes in ecosystem dynamics. Although time series similarity measures play an important role in these methods, a quantitative comparison of the similarity measures is lacking. The objective of this study was to provide an overview and quantitative comparison of the similarity measures in function of varying time series and ecosystem characteristics, such as amplitude, timing and noise effects. For this purpose, the performance was evaluated for the commonly used similarity measures (D), ranging from Manhattan (DMan), Euclidean (DE) and Mahalanobis (DMah) distance measures, to correlation (DCC), Principal Component Analysis (PCA; DPCA) and Fourier based (DFFT,D¿,DFk) similarities. The quantitative comparison consists of a series of Monte-Carlo simulations based on subsets of global MODIS Normalized Difference Vegetation index (NDVI) and Enhanced Vegetation Index (EVI) and Leaf Area Index (LAI) data. Results of the simulations reveal four main groups of time series similarity measures with different sensitivities: (i) DMan, DE, DPCA, DFk quantify the difference in time series values, (ii) DMah accounts for temporal correlation and non-stationarity of variance, (iii) DCC measures the temporal correlation, and (iv) the Fourier based DFFT and D¿ show their specific sensitivity based on the selected Fourier components. The difference measures show relatively the highest sensitivity to amplitude effects, whereas the correlation based measures are highly sensitive to variations in timing and noise. The Fourier based measures, finally, depend highly on the signal to noise ratio and the balance between amplitude and phase dominance. The heterogeneity in sensitivity of each D stresses the importance of (i) understanding the time series characteristics before applying any classification of change detection approach and (ii) defining the variability one wants to identify/account for. This requires an understanding of the ecosystem dynamics and time series characteristics related to the baseline, amplitude, timing, noise and variability of the ecosystem time series. This is also illustrated in the quantitative comparison, where the different sensitivities of D for the NDVI, EVI, and LAI data relate specifically to the temporal characteristics of each data set. Additionally, the effect of noise and intra- and interclass variability is demonstrated in a case study based on land cover classification.
Challenges in using land use and land cover data for global change studies
Verburg, P.H. ; Neumann, K. ; Nol, L. - \ 2011
Global Change Biology 17 (2011)2. - ISSN 1354-1013 - p. 974 - 989.
conterminous united-states - terrestrial ecosystems - accuracy assessment - satellite imagery - dependent errors - water-resources - uncertainty - climate - maps - system
Land use and land cover data play a central role in climate change assessments. These data originate from different sources and inventory techniques. Each source of land use/cover data has its own domain of applicability and quality standards. Often data are selected without explicitly considering the suitability of the data for the specific application, the bias originating from data inventory and aggregation, and the effects of the uncertainty in the data on the results of the assessment. Uncertainties due to data selection and handling can be in the same order of magnitude as uncertainties related to the representation of the processes under investigation. While acknowledging the differences in data sources and the causes of inconsistencies, several methods have been developed to optimally extract information from the data and document the uncertainties. These methods include data integration, improved validation techniques and harmonization of classification systems. Based on the data needs of global change studies and the data availability, recommendations are formulated aimed at optimal use of current data and focused efforts for additional data collection. These include: improved documentation using classification systems for land use/cover data; careful selection of data given the specific application and the use of appropriate scaling and aggregation methods. In addition, the data availability may be improved by the combination of different data sources to optimize information content while collection of additional data must focus on validation of available data sets and improved coverage of regions and land cover types with a high level of uncertainty. Specific attention in data collection should be given to the representation of land management (systems) and mosaic landscapes
Sectoral approaches to improve regional carbon budgets
Smith, P. ; Nabuurs, G.J. ; Janssens, I.A. ; Reis, S. ; Marland, G. ; Soussana, J.F. ; Christensen, T.R. ; Heath, L. ; Apps, M. ; Alexeyev, V. ; Fang, J. ; Gattuso, J.P. ; Guerschman, J.P. ; Huang, Y. ; Jobbagy, E. ; Murdiyarso, D. ; Ni, J. ; Nobre, A. ; Peng, C. ; Walcroft, A. ; Wang, S.Q. ; Pan, Y. ; Zhou, G.S. - \ 2008
Climatic Change 88 (2008)3-4. - ISSN 0165-0009 - p. 209 - 249.
soil organic-matter - net primary production - agricultural land-use - long-term experiments - conterminous united-states - northern hardwood forests - nitrous-oxide emissions - peat bog growth - climate-change - european forests
Humans utilise about 40% of the earth¿s net primary production (NPP) but the products of this NPP are often managed by different sectors, with timber and forest products managed by the forestry sector and food and fibre products from croplands and grasslands managed by the agricultural sector. Other significant anthropogenic impacts on the global carbon cycle include human utilization of fossil fuels and impacts on less intensively managed systems such as peatlands, wetlands and permafrost. A great deal of knowledge, expertise and data is available within each sector. We describe the contribution of sectoral carbon budgets to our understanding of the global carbon cycle. Whilst many sectors exhibit similarities for carbon budgeting, some key differences arise due to differences in goods and services provided, ecology, management practices used, land-management personnel responsible, policies affecting land management, data types and availability, and the drivers of change. We review the methods and data sources available for assessing sectoral carbon budgets, and describe some of key data limitations and uncertainties for each sector in different regions of the world. We identify the main gaps in our knowledge/data, show that coverage is better for the developed world for most sectors, and suggest how sectoral carbon budgets could be improved in the future. Research priorities include the development of shared protocols through site networks, a move to full carbon accounting within sectors, and the assessment of full greenhouse gas budgets
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