Records 1 - 50 / 361
Comprehensive mass spectrometry-guided phenotyping of plant specialized metabolites reveals metabolic diversity in the cosmopolitan plant family Rhamnaceae
Kang, Kyo Bin ; Ernst, Madeleine ; Hooft, Justin J.J. van der; Silva, Ricardo R. da; Park, Junha ; Medema, Marnix H. ; Sung, Sang Hyun ; Dorrestein, Pieter C. - \ 2019
The Plant Journal (2019). - ISSN 0960-7412
annotation - classification - mass spectrometry - Rhamnaceae - specialized metabolites - technical advance
Plants produce a myriad of specialized metabolites to overcome their sessile habit and combat biotic as well as abiotic stresses. Evolution has shaped the diversity of specialized metabolites, which then drives many other aspects of plant biodiversity. However, until recently, large-scale studies investigating the diversity of specialized metabolites in an evolutionary context have been limited by the impossibility of identifying chemical structures of hundreds to thousands of compounds in a time-feasible manner. Here we introduce a workflow for large-scale, semi-automated annotation of specialized metabolites and apply it to over 1000 metabolites of the cosmopolitan plant family Rhamnaceae. We enhance the putative annotation coverage dramatically, from 2.5% based on spectral library matches alone to 42.6% of total MS/MS molecular features, extending annotations from well-known plant compound classes into dark plant metabolomics. To gain insights into substructural diversity within this plant family, we also extract patterns of co-occurring fragments and neutral losses, so-called Mass2Motifs, from the dataset; for example, only the Ziziphoid clade developed the triterpenoid biosynthetic pathway, whereas the Rhamnoid clade predominantly developed diversity in flavonoid glycosides, including 7-O-methyltransferase activity. Our workflow provides the foundations for the automated, high-throughput chemical identification of massive metabolite spaces, and we expect it to revolutionize our understanding of plant chemoevolutionary mechanisms.
Potato Virus Y Detection in Seed Potatoes Using Deep Learning on Hyperspectral Images
Polder, G. ; Blok, P.M. ; Villiers, H.A.C. de; Wolf, J.M. van der; Kamp, J.A.L.M. - \ 2019
Frontiers in Plant Science 10 (2019). - ISSN 1664-462X
crop resistance - Phenotyping - hyperspectral imaging - classification - Convolutional neural network - Solanum tuberosum
Virus diseases are of high concern in the cultivation of seed potatoes. Once found inthe field, virus diseased plants lead to declassification or even rejection of the seed lotsresulting in a financial loss. Farmers put in a lot of effort to detect diseased plants andremove virus-diseased plants from the field. Nevertheless, dependent on the cultivar,virus diseased plants can be missed during visual observations in particular in an earlystage of cultivation. Therefore, there is a need for fast and objective disease detection.Early detection of diseased plants with modern vision techniques can significantlyreduce costs. Laboratory experiments in previous years showed that hyperspectral imaging clearly could distinguish healthy from virus infected potato plants. This paper reports on our first real field experiment. A new imaging setup was designed, consisting of a hyperspectral line-scan camera. Hyperspectral images were taken in the field with a line interval of 5 mm. A fully convolutional neural network was adapted for hyperspectral images and trained on two experimental rows in the field. The trained network was validated on two other rows, with different potato cultivars. For three of the four row/date combinations the precision and recall compared to conventional disease assessment exceeded 0.78 and 0.88, respectively. This proves the suitability of this method for real world disease detection.
Dense semantic labeling of subdecimeter resolution images with convolutional neural networks
Volpi, Michele ; Tuia, Devis - \ 2017
IEEE Transactions on Geoscience and Remote Sensing 55 (2017)2. - ISSN 0196-2892 - p. 881 - 893.
Aerial images - classification - convolutional neural networks (CNNs) - deconvolution networks - deep learning - semantic labeling - subdecimeter resolution
Semantic labeling (or pixel-level land-cover classification) in ultrahigh-resolution imagery (<10 cm) requires statistical models able to learn high-level concepts from spatial data, with large appearance variations. Convolutional neural networks (CNNs) achieve this goal by learning discriminatively a hierarchy of representations of increasing abstraction. In this paper, we present a CNN-based system relying on a downsample-then-upsample architecture. Specifically, it first learns a rough spatial map of high-level representations by means of convolutions and then learns to upsample them back to the original resolution by deconvolutions. By doing so, the CNN learns to densely label every pixel at the original resolution of the image. This results in many advantages, including: 1) the state-of-the-art numerical accuracy; 2) the improved geometric accuracy of predictions; and 3) high efficiency at inference time. We test the proposed system on the Vaihingen and Potsdam subdecimeter resolution data sets, involving the semantic labeling of aerial images of 9- and 5-cm resolution, respectively. These data sets are composed by many large and fully annotated tiles, allowing an unbiased evaluation of models making use of spatial information. We do so by comparing two standard CNN architectures with the proposed one: standard patch classification, prediction of local label patches by employing only convolutions, and full patch labeling by employing deconvolutions. All the systems compare favorably or outperform a state-of-the-art baseline relying on superpixels and powerful appearance descriptors. The proposed full patch labeling CNN outperforms these models by a large margin, also showing a very appealing inference time.
Optimal Transport for Domain Adaptation
Courty, Nicolas ; Flamary, Remi ; Tuia, Devis ; Rakotomamonjy, Alain - \ 2017
IEEE Transactions on Pattern Analysis and Machine Intelligence 39 (2017)9. - ISSN 0162-8828 - p. 1853 - 1865.
classification - optimal transport - transfer learning - Unsupervised domain adaptation - visual adaptation
Domain adaptation is one of the most challenging tasks of modern data analytics. If the adaptation is done correctly, models built on a specific data representation become more robust when confronted to data depicting the same classes, but described by another observation system. Among the many strategies proposed, finding domain-invariant representations has shown excellent properties, in particular since it allows to train a unique classifier effective in all domains. In this paper, we propose a regularized unsupervised optimal transportation model to perform the alignment of the representations in the source and target domains. We learn a transportation plan matching both PDFs, which constrains labeled samples of the same class in the source domain to remain close during transport. This way, we exploit at the same time the labeled samples in the source and the distributions observed in both domains. Experiments on toy and challenging real visual adaptation examples show the interest of the method, that consistently outperforms state of the art approaches. In addition, numerical experiments show that our approach leads to better performances on domain invariant deep learning features and can be easily adapted to the semi-supervised case where few labeled samples are available in the target domain.
Spatial classification with fuzzy lattice reasoning
Mavridis, Constantinos ; Athanasiadis, I.N. - \ 2017
In: Proceedings of the 1st International Conference on Internet of Things and Machine Learning. - ACM - ISBN 9781450352437
Fuzzy Lattice Reasoning - classification - spatial data - spatial data mining - spatial classification - linear arrangement - data mining
This work extends the Fuzzy Lattice Reasoning (FLR) Classifier to manage spatial attributes, and spatial relationships. Specifically, we concentrate on spatial entities, as countries, cities, or states. Lattice Theory requires the elements of a Lattice to be partially ordered. To match such requirement, spatial entities are represented as a graph, whose number of nodes is equal to the amount of unique values of the spatial attribute elements. Then, the graph nodes are linearly arranged to formulate a partially ordered set; and thus be included in the Fuzzy Lattice classifier. The overall problem of incorporating spatial attributes in FLR was deduced to a Minimum Linear Arrangement problem. A corresponding open-source implementation in R has been made available on CRAN repository. The proposed method was evaluated using an open spatial dataset from the National Ambient Air Quality Standards (NAAQS). We investigated whether the addition of the spatial attribute contributed to any improvements in classification accuracy; and how linear arrangement alternatives may affect it. Experimental results showed that classification accuracy is above 85% in all cases, and the use of spatial attributes resulted to an increased accuracy of 92%. Alternative linear arrangements did not contribute significantly in improving classification accuracy in this case study.
Trajectories of agricultural change in southern Mali
Falconnier, G.N. - \ 2016
Wageningen University. Promotor(en): Ken Giller, co-promotor(en): Katrien Descheemaeker; T.A. van Mourik. - Wageningen : Wageningen University - ISBN 9789462577596 - 209
agriculture - agricultural development - farms - classification - self sufficiency - food - income - intensification - farming systems - intensive production - mali - landbouw - landbouwontwikkeling - landbouwbedrijven - classificatie - zelfvoorziening - voedsel - inkomen - intensivering - bedrijfssystemen - intensieve productie - mali
Key words: longitudinal study, farm typology, food self-sufficiency, income, legumes, ex-ante analysis, participatory research, scenario.
Smallholder agriculture in sub-Saharan Africa provides basis of rural livelihoods and food security, yet farmers have to cope with land constraints, variable rainfall and unstable institutional support. This study integrates a diversity of approaches (household typology and understanding of farm trajectories, on-farm trials, participatory ex-ante trade-off analysis) to design innovative farming systems to confront these challenges. We explored farm trajectories during two decades (1994 to 2010) in the Koutiala district in southern Mali, an area experiencing the land constraints that exert pressure in many other parts of sub-Saharan Africa. We classified farms into four types differing in land and labour productivity and food self-sufficiency status. During the past two decades, 17% of the farms stepped up to a farm type with greater productivity, while 70% of the farms remained in the same type, and only 13% of the farms experienced deteriorating farming conditions. Crop yields did not change significantly over time for any farm type and labour productivity decreased. Together with 132 farmers in the Koutiala district, we tested a range of options for sustainable intensification, including intensification of cereal (maize and sorghum) and legume (groundnut, soyabean and cowpea) sole crops and cereal-legume intercropping over three years and cropping seasons (2012-2014) through on-farm trials. Experiments were located across three soil types that farmers identified – namely black, sandy and gravelly soils. Enhanced agronomic performance was achieved when targeting legumes to a given soil type and/or place in the rotation: the biomass production of the cowpea fodder variety was doubled on black soils compared with gravelly soils and the additive maize/cowpea intercropping option after cotton or maize resulted in no maize grain penalty, and 1.38 t ha−1 more cowpea fodder production compared with sole maize. Farm systems were re-designed together with the farmers involved in the trials. A cyclical learning model combining the on-farm testing and participatory ex-ante analysis was used during four years (2012-2015). In the first cycle of 2012-2014, farmers were disappointed by the results of the ex-ante trade-off analysis, i.e marginal improvement in gross margin when replacing sorghum with soybean and food self-sufficiency trade-offs when intercropping maize with cowpea. In a second cycle in 2014-2015 the farm systems were re-designed using the niche-specific (soil type/previous crop combinations) information on yield and gross margin, which solved the concerns voiced by farmers during the first cycle. Farmers highlighted the saliency of the niches and the re-designed farm systems that increased farm gross margin by 9 to 29% (depending on farm type and options considered) without compromising food self-sufficiency. The involvement of farmers in the co-learning cycles allowed establishment of legitimate, credible and salient farm reconfiguration guidelines that could be scaled-out to other communities within the “old cotton basin”. Five medium-term contrasting socio-economic scenarios were built towards the year 2027, including hypothetical trends in policy interventions and change towards agricultural intensification. A simulation framework was built to account for household demographic dynamics and crop/livestock production variability. In the current situation, 45% of the 99 households of the study village were food self-sufficient and above the 1.25 US$ day-1 poverty line. Without change in farmer practices and additional policy intervention, only 16% of the farms would be both food self-sufficient and above the poverty line in 2027. In the case of diversification with legumes combined with intensification of livestock production and support to the milk sector, 27% of farms would be food self-sufficient and above the poverty line. Additional broader policy interventions to favour out-migration would be needed to lift 69% of the farms out of poverty. Other additional subsidies to favour yield gap narrowing of the main crops would lift 92% of the farm population out of poverty. Whilst sustainable intensification of farming clearly has a key role to play in ensuring food self-sufficiency, and is of great interest to local farmers, in the face of increasing population pressure other approaches are required to address rural poverty. These require strategic and multi-sectoral approaches that address employment within and beyond agriculture, in both rural and urban areas.
Een evaluatie van de maatlatten R6 en R7 voor de Kader Richtlijn Water
Griffioen, A.B. ; Vries, I. de - \ 2016
IMARES (Rapport / IMARES C087/15) - 28
rivieren - kaderrichtlijn water - waterbeheer - classificatie - waterkwaliteit - aquatische ecologie - monitoring - rivers - water framework directive - water management - classification - water quality - aquatic ecology - monitoring
De watertypes R6 en R7 in de Kader Richtlijn Water (KRW) classificering verschillen qua grootte van het waterlichaam en structuur. Het watertype R7 staat voor de grote rivieren met een hoofdstroom en nevengeulen. Rivieren als de Rijn, Waal en IJssel zijn hier voorbeelden van. Het watertype R6 staat voor langzaam stromende kleinere rivieren. In de praktijk kunnen beide riviertypen in elkaar overgaan en is het goed mogelijk dat het visbestand een grote overlap kent, maar volgens verschillende maatlatten worden beoordeeld. Dit onderzoek heeft tot doel het inzichtelijk maken van de indeling in beide watertypes. Ook wordt er gekeken naar de verschillen tussen de watertypen R6 en R7.
Identifying and naming plant-pathogenic fungi: past, present, and future
Crous, P.W. ; Hawksworth, D.L. ; Wingfield, M.J. - \ 2015
Annual Review of Phytopathology 53 (2015). - ISSN 0066-4286 - p. 247 - 267.
molecular systematics - polyphyletic nature - polyphasic approach - mycorrhizal fungi - species concepts - taxonomy - genus - classification - identification - chromatography
Scientific names are crucial in communicating knowledge about fungi. In plant pathology, they link information regarding the biology, host range, distribution, and potential risk. Our understanding of fungal biodiversity and fungal systematics has undergone an exponential leap, incorporating genomics, web-based systems, and DNA data for rapid identification to link species to metadata. The impact of our ability to recognize hitherto unknown organisms on plant pathology and trade is enormous and continues to grow. Major challenges for phytomycology are intertwined with the Genera of Fungi project, which adds DNA barcodes to known biodiversity and corrects the application of old, established names via epi- or neotypification. Implementing the one fungus–one name system and linking names to validated type specimens, cultures, and reference sequences will provide the foundation on which the future of plant pathology and the communication of names of plant pathogens will rest.
NSO-typering 2015; Typering van agrarische bedrijven in Nederland
Everdingen, W.H. van - \ 2015
Den Haag : LEI Wageningen UR (Nota / LEI 2015-084) - 36
landbouw bedrijven - bedrijven - bedrijfsvergelijking in de landbouw - bedrijfsvoering - opbrengsten - inkomsten uit het landbouwbedrijf - bedrijfsgrootte in de landbouw - bedrijfsgegevens - standaardisering - classificatie - agrarische economie - farming - businesses - farm comparisons - management - yields - farm income - farm size - farm accountancy data - standardization - classification - agricultural economics
In 2014 is voor de Nederlandse variant een nieuw kengetal geïntroduceerd: de Standaard Verdiencapaciteit (SVC) van bedrijven. Dat kengetal is ontwikkeld vanwege verschillen in marge tussen de sectoren. Met de SVC is de bedrijfsgrootte van bedrijven over bedrijfstypen heen meer gerelateerd aan arbeidsinzet en resultaat dan bij de Standaardopbrengst (SO) het geval is. De classificatie is gekoppeld aan de Landbouwtelling. De normen worden berekend voor de categorieën dieren en gewassen die in de Landbouwtelling worden uitgevraagd. Het doel van dit document is inzicht verschaffen in de achtergronden, rekenschema’s, indelingen en normen die bij de typering in gebruik zijn rond de Landbouwtelling van 2015. Achtereenvolgens komen in de volgende paragrafen de Standaardopbrengst (1), de NSO-typering (2), de Standaard Verdiencapaciteit (3) en het gebruik van de gegevens (4) aan bod.
Mapping Soil Properties of Africa at 250 m resolution: random forest significantly improve current predictions
Hengl, T. ; Heuvelink, G.B.M. ; Kempen, B. ; Leenaars, J.G.B. ; Walsh, M.G. ; Shepherd, K.D. ; Sila, A. ; Macmillan, R.A. ; Mendes de Jesus, J.S. ; Tamene, L. ; Tondoh, J.E. - \ 2015
PLoS ONE 10 (2015)6. - ISSN 1932-6203
continental-scale - maps - classification - surveillance - management - models - carbon - trees
80% of arable land in Africa has low soil fertility and suffers from physical soil problems. Additionally, significant amounts of nutrients are lost every year due to unsustainable soil management practices. This is partially the result of insufficient use of soil management knowledge. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS) project was established in 2008. Over the period 2008–2014, the AfSIS project compiled two point data sets: the Africa Soil Profiles (legacy) database and the AfSIS Sentinel Site database. These data sets contain over 28 thousand sampling locations and represent the most comprehensive soil sample data sets of the African continent to date. Utilizing these point data sets in combination with a large number of covariates, we have generated a series of spatial predictions of soil properties relevant to the agricultural management—organic carbon, pH, sand, silt and clay fractions, bulk density, cation-exchange capacity, total nitrogen, exchangeable acidity, Al content and exchangeable bases (Ca, K, Mg, Na). We specifically investigate differences between two predictive approaches: random forests and linear regression. Results of 5-fold cross-validation demonstrate that the random forests algorithm consistently outperforms the linear regression algorithm, with average decreases of 15–75% in Root Mean Squared Error (RMSE) across soil properties and depths. Fitting and running random forests models takes an order of magnitude more time and the modelling success is sensitive to artifacts in the input data, but as long as quality-controlled point data are provided, an increase in soil mapping accuracy can be expected. Results also indicate that globally predicted soil classes (USDA Soil Taxonomy, especially Alfisols and Mollisols) help improve continental scale soil property mapping, and are among the most important predictors. This indicates a promising potential for transferring pedological knowledge from data rich countries to countries with limited soil data.
A Bayesian approach to combine Landsat and ALOS PALSAR time series for near real-time deforestation detection
Reiche, J. ; Bruin, S. de; Hoekman, D.H. ; Verbesselt, J. ; Herold, M. - \ 2015
Remote Sensing 7 (2015). - ISSN 2072-4292 - p. 4973 - 4996.
conditional-probability networks - remotely-sensed images - forest cover loss - tropical deforestation - brazilian amazon - accuracy assessment - classification - sar - disturbance - fusion
To address the need for timely information on newly deforested areas at medium resolution scale, we introduce a Bayesian approach to combine SAR and optical time series for near real-time deforestation detection. Once a new image of either of the input time series is available, the conditional probability of deforestation is computed using Bayesian updating, and deforestation events are indicated. Future observations are used to update the conditional probability of deforestation and, thus, to confirm or reject an indicated deforestation event. A proof of concept was demonstrated using Landsat NDVI and ALOS PALSAR time series acquired at an evergreen forest plantation in Fiji. We emulated a near real-time scenario and assessed the deforestation detection accuracies using three-monthly reference data covering the entire study site. Spatial and temporal accuracies for the fused Landsat-PALSAR case (overall accuracy = 87.4%; mean time lag of detected deforestation = 1.3 months) were consistently higher than those of the Landsat- and PALSAR-only cases. The improvement maintained even for increasing missing data in the Landsat time series.
Hypothesis: the sound of the individual metabolic phenotype? Acoustic detection of NMR experiments
Cacciatore, S. ; Saccenti, E. ; Piccioli, M. - \ 2015
OMICS - A Journal of Integrative Biology 19 (2015)3. - ISSN 1536-2310 - p. 147 - 156.
breast-cancer - personalized medicine - disease - profiles - models - health - time - classification - identification - metabonomics
We present here an innovative hypothesis and report preliminary evidence that the sound of NMR signals could provide an alternative to the current representation of the individual metabolic fingerprint and supply equally significant information. The NMR spectra of the urine samples provided by four healthy donors were converted into audio signals that were analyzed in two audio experiments by listeners with both musical and non-musical training. The listeners were first asked to cluster the audio signals of two donors on the basis of perceived similarity and then to classify unknown samples after having listened to a set of reference signals. In the clustering experiment, the probability of obtaining the same results by pure chance was 7.04% and 0.05% for non-musicians and musicians, respectively. In the classification experiment, musicians scored 84% accuracy which compared favorably with the 100% accuracy attained by sophisticated pattern recognition methods. The results were further validated and confirmed by analyzing the NMR metabolic profiles belonging to two other different donors. These findings support our hypothesis that the uniqueness of the metabolic phenotype is preserved even when reproduced as audio signal and warrants further consideration and testing in larger study samples
Remote sensing of epibenhtic shellfish using synthetic aperture radar satellite imagery
Nieuwhof, S. ; Herman, P.M.J. ; Dankers, N.M.J.A. ; Troost, K. ; Wal, D. van der - \ 2015
Remote Sensing 7 (2015)4. - ISSN 2072-4292 - p. 3710 - 3734.
bare soil surfaces - mussel beds - wadden sea - ecosystem engineers - intertidal flats - tidal flats - sar data - roughness - classification - moisture
On intertidal mudflats, reef-building shellfish, like the Pacific oyster and the blue mussel, provide a myriad of ecosystem services. Monitoring intertidal shellfish with high spatiotemporal resolution is important for fisheries, coastal management and ecosystem studies. Here, we explore the potential of X- (TerraSAR-X) and C-band (Radarsat-2) dual-polarized SAR data to map shellfish densities, species and coverage. We investigated two backscatter models (the integral equation model (IEM) and Oh’s model) for inversion possibilities. Surface roughness (vertical roughness RMSz and correlation length L) was measured of bare sediments and shellfish beds, which was then linked to shellfish density, presence and species. Oysters, mussels and bare sediments differed in RMSz, but because the backscatter saturates at relatively low RMSz values, it was not possible to retrieve shellfish density or species composition from X- and C-band SAR. Using a classification based on univariate and multivariate logistic regression of the field and SAR image data, we constructed maps of shellfish presence (Kappa statistics for calibration 0.56–0.74 for dual-polarized SAR), which were compared with independent field surveys of the contours of the beds (Kappa statistics of agreement 0.29–0.53 when using dual-polarized SAR). We conclude that spaceborne SAR allows one to monitor the contours of shellfish-beds (thus, distinguishing shellfish substrates from bare sediment and dispersed single shellfish), but not densities and species. Although spaceborne SAR cannot replace ground surveys entirely, it could very well offer a significant improvement in efficiency.
Discrimination of Polish unifloral honeys using overall PTR-MS and HPLC fingerprints combined with chemometrics
Kus, P.M. ; Ruth, S.M. van - \ 2015
Food Science and Technology = Lebensmittel-Wissenschaft und Technologie 62 (2015)1. - ISSN 0023-6438 - p. 69 - 75.
reaction-mass spectrometry - origin determination - botanical origin - electronic nose - floral markers - l. honey - volatile - classification - identification - flavonoids
A total of 62 honey samples of six floral origins (rapeseed, lime, heather, cornflower, buckwheat and black locust) were analysed by means of proton transfer reaction mass spectrometry (PTR-MS) and HPLC-DAD. The data were evaluated by principal component analysis and k-nearest neighbours classification in order to examine consistent differences in analytical fingerprints between various honeys allowing their discrimination. The study revealed, that both techniques were able to distinguish the floral origins, however the HPLC shows advantage over PTR-MS providing substantially better differentiation of all analysed honey types. Especially HPLC fingerprints recorded at 210 nm were most suitable for discrimination of botanical origin with the use of chemometric analysis. The obtained classification rates were: 100%, 93%, 100%, 83%, 100%, 100% (HPLC) and 69%, 67%, 78%, 67%, 100%, 88% (PTR-MS) for rapeseed, lime, heather, cornflower, buckwheat and black locust, respectively. Even if performance of PTR-MS in general was lower than HPLC, it might be useful for fast on-line screening of buckwheat honey.
Multi-model radiometric slope correction of SAR images of complex terrain using a two-stage semi-empirical approach
Hoekman, D.H. ; Reiche, J. - \ 2015
Remote Sensing of Environment 156 (2015). - ISSN 0034-4257 - p. 1 - 10.
radar imagery - topography - forest - classification - backscatter - validation
Practical approaches for the implementation of terrain type dependent radiometric slope correction for SAR data are introduced. Radiometric slope effects are modelled as the products of two models. The first is a simple physical model based on the assumption of a uniform opaque layer of isotropic scatterers, which is independent of terrain type, frequency and polarization. It accounts for the slope-induced variation in the number of scatterers per resolution cell. The second is a semi-empirical model, which accounts for the variation in scattering mechanisms, dependent on terrain type, frequency and polarization. PALSAR FBD (L-band, HH- and HV-polarization) data are used at two test sites in Brazil and Fiji. Results for the Brazilian area, which has slopes up to 25°, show that remaining slope effects for the multi-model case are much smaller than 0.1 dB, for all land cover types. This is much better than the best single-model approach where remaining slope effects can be very small for forests but be as large as 1.77 dB for woodland in HH-polarization. Results for the Fiji area, which has different vegetation types, are very similar. The potential large improvement, using this multi-model approach, in the accuracy of biomass estimation for transparent or open canopies is discussed. It is also shown that biomass change on slopes can be systematically under- or overestimated because of associated change in scattering mechanism.
Fusing Landsat and SAR time series to detect deforestation in the tropics
Reiche, J. ; Verbesselt, J. ; Hoekman, D.H. ; Herold, M. - \ 2015
Remote Sensing of Environment 156 (2015). - ISSN 0034-4257 - p. 276 - 293.
forest cover loss - alos palsar data - operational performance - accuracy assessment - multiscale texture - brazilian amazonia - missing data - jers-1 sar - satellite - classification
Fusion of optical and SAR time series imagery has the potential to improve forest monitoring in tropical regions, where cloud cover limits optical satellite time series observations. We present a novel pixel-based Multi-sensor Time-series correlation and Fusion approach (MulTiFuse) that exploits the full observation density of optical and SAR time series. We model the relationship of two overlapping univariate time series using an optimized weighted correlation. The resulting optimized regression model is used to predict and fuse two time series. Using the MulTiFuse approach we fused Landsat NDVI and ALOS PALSAR L-band backscatter time series. We subsequently used the fused time series in a multi-sensor change detection framework to detect deforestation between 01/2008 - 09/2010 at a managed forest plantation in the tropics (Pinus caribea; 2859 ha). 3-monthly reference data covering the entire study area was used to validate and assess spatial and temporal accuracy. We tested the impact of persistent cloud cover by increasing the per-pixel missing data percentage of the NDVI time series stepwise from ~ 53% (~ 6 observations/year) up to 95% (~ 0.5 observation/year) while fusing with a consistent PALSAR time series of ~ 2 observations/year. A significant linear correlation was found between the Landsat NDVI and ALOS PALSAR L-band SAR time series observables for logged forest. The multi-temporal filtered PALSAR HVHH backscatter ratio time series (HVHHmt) was most strongly correlated with the NDVI time series. While for Landsat-only the spatial and temporal accuracy of detected deforestation decreased significantly with increasing missing data, the accuracies for the fused NDVI-PALSAR case remained high and were observed to be above the NDVI- and PALSAR-only cases for all missing data percentages. For the fused NDVI-HVHHmt time series the overall accuracy was 95.5% with a 1.59 month mean time lag of detected changes. The MulTiFuse approach is robust and automated, and it provides the opportunity to use the upcoming data streams of free-of charge, medium resolution optical and SAR satellite imagery in a beneficial way for improved tropical forest monitoring.
Non-linear low-rank and sparse representation for hyperspectral image analysis
Morsier, Frank De; Tuia, Devis ; Borgeaucft, Maurice ; Gass, Volker ; Thiran, Jean Philippe - \ 2014
In: International Geoscience and Remote Sensing Symposium (IGARSS). - Institute of Electrical and Electronics Engineers Inc. (International Geoscience and Remote Sensing Symposium (IGARSS) ) - ISBN 9781479957750 - p. 4648 - 4651.
classification - kernel - low-rank - manifold clustering - sparse - unsupervised
In this paper, we tackle the problem of unsupervised classification of hyperspectral images. We propose a clustering method based on graphs representing the data structure, which is assumed to be an union of multiple manifolds. The method constraints the pixels to be expressed as a low-rank and sparse combination of the others in a reproducing kernel Hilbert spaces (RKHS). This captures the global (low-rank) and local (sparse) structures. Spectral clustering is applied on the graph to assign the pixels to the different manifolds. A large scale approach is proposed, in which the optimization is first performed on a subset of the data and then it is applied to the whole image using a non-linear collaborative representation respecting the manifolds structure. Experiments on two hyperspectral images show very good unsupervised classification results compared to competitive approaches.
Importance of bistatic SAR features from TanDEM-X for forest mapping and monitoring
Schlund, M. ; Poncet, F. von; Hoekman, D.H. ; Kuntz, S. ; Schmullius, C. - \ 2014
Remote Sensing of Environment 151 (2014)sp. issue. - ISSN 0034-4257 - p. 16 - 26.
land-cover - southeast-asia - feature-selection - polarimetric sar - tropical-forest - decision tree - alos palsar - rain-forest - sir-c - classification
Deforestation and forest degradation are one of the important sources for human induced carbon dioxide emissions and their rates are highest in tropical forests. For man-kind, it is of great importance to track land-use conversions like deforestation, e.g. for sustainable forest management and land use planning, for carbon balancing and to support the implementation of international initiatives like REDD + (Reducing Emissions from Deforestation and Degradation). SAR (synthetic aperture radar) sensors are suitable to reliably and frequently monitor tropical forests due to their weather independence. The TanDEM-X mission (which is mainly aimed to create a unique global high resolution digital elevation model) currently operates two X-band SAR satellites, acquiring interferometric SAR data for the Earth's entire land surface multiple times. The operational mission provides interferometric data as well as mono- and bistatic scattering coefficients. These datasets are homogenous, globally consistent and are acquired in high spatial resolution. Hence, they may offer a unique basic dataset which could be useful in land cover monitoring. Based on first datasets available from the TanDEM-X mission, the main goal of this research is to investigate the information content of TanDEM-X data for mapping forests and other land cover classes in a tropical peatland area. More specifically, the study explores the utility of bistatic features for distinguishing between open and closed forest canopies, which is of relevance in the context of deforestation and forest degradation monitoring. To assess the predominant information content of TanDEM-X data, the importance of information derived from the bistatic system is compared against the monostatic case, usually available from SAR systems. The usefulness of the TanDEM-X mission data, i.e. scattering coefficients, derived textural information and interferometric coherence is investigated via a feature selection process. The resulting optimal feature sets representing a monostatic and a bistatic SAR dataset were used in a subsequent classification to assess the added value of the bistatic TanDEM-X features in the separability of land cover classes. The results obtained indicated that especially the interferometric coherence significantly improved the separability of thematic classes compared to a dataset of monostatic acquisition. The bistatic coherence was mainly governed by volume decorrelation of forest canopy constituents and carries information about the canopy structure which is related to canopy cover. In contrast, the bistatic scattering coefficient had no significant contribution to class separability. The classification with coherence and textural information outperformed the classification with the monostatic scattering coefficient and texture by more than 10% and achieved an overall accuracy of 85%. These results indicate that TanDEM-X can serve as a valuable and consistent source for mapping and monitoring tropical forests.
Do Current European Policies Prevent Soil Threats and Support Soil Functions?
Glaesner, N. ; Helming, K. ; Vries, W. de - \ 2014
Sustainability 6 (2014)12. - ISSN 2071-1050 - p. 9538 - 9563.
ecosystem services - sustainable intensification - management - agriculture - protection - framework - quality - carbon - classification - conservation
There is currently no legislation at the European level that focuses exclusively on soil conservation. A cross-policy analysis was carried out to identify gaps and overlaps in existing EU legislation that is related to soil threats and functions. We found that three soil threats, namely compaction, salinization and soil sealing, were not addressed in any of the 19 legislative policies that were analyzed. Other soil threats, such as erosion, decline in organic matter, loss of biodiversity and contamination, were covered in existing legislation, but only a few directives provided targets for reducing the soil threats. Existing legislation addresses the reduction of the seven soil functions that were analyzed, but there are very few directives for improving soil functions. Because soil degradation is ongoing in Europe, it raises the question whether existing legislation is sufficient for maintaining soil resources. Addressing soil functions individually in various directives fails to account for the multifunctionality of soil. This paper suggests that a European Soil Framework Directive would increase the effectiveness of conserving soil functions in the EU.
Agroforestry solutions to address climate change and food security challenges in Africa
Mbow, C. ; Neufeldt, H. ; Noordwijk, M. van; Minang, P.A. ; Kowero, G. ; Luedeling, E. - \ 2014
Current Opinion in Environmental Sustainability 6 (2014). - ISSN 1877-3435 - p. 61 - 67.
sub-saharan africa - forest degradation - land degradation - climate-change - west-africa - agriculture - systems - intensification - classification - security
Trees inside and outside forests contribute to food security in Africa in the face of climate variability and change. They also provide environmental and social benefits as part of farming livelihoods. Varied ecological and socio-economic conditions have given rise to specific forms of agroforestry in different parts of Africa. Policies that institutionally segregate forest from agriculture miss opportunities for synergy at landscape scale. More explicit inclusion of agroforestry and the integration of agriculture and forestry agendas in global initiatives on climate change adaptation and mitigation can increase their effectiveness. We identify research gaps and overarching research questions for the contributions in this special issue that may help shape current opinion in environmental sustainability.
Groenestein, C.M. ; Bruggen, C. van; Luesink, H.H. - \ 2014
Wageningen : Wettelijke Onderzoekstaken Natuur & Milieu (WOt-technical report 16) - 36
vee - classificatie - stikstof - fosfor - dierlijke meststoffen - wetgeving - nederland - rundvee - varkens - pluimvee - schapen - geiten - paarden - ezels - livestock - classification - nitrogen - phosphorus - animal manures - legislation - netherlands - cattle - pigs - poultry - sheep - goats - horses - donkeys
Voor wettelijke regelingen, tellingen en monitoringstudies worden in Nederland verschillende indelingen gebruikt voor landbouwhuisdieren. Dat leidt soms tot verwarring en is inefficiënt, vooral omdat gegevens niet eenvoudig uitgewisseld kunnen worden en er aparte bestanden beheerd moeten worden. Op verzoek van het ministerie van Economische Zaken heeft de Commissie van Deskundigen Meststoffenwet (CDM) een voorstel gemaakt voor een geharmoniseerde en vereenvoudigde indeling van diercategorieën, vooral voor de Uitvoeringsregeling Meststoffenwet. In het voorstel is de huidige indeling van diercategorieën van de Landbouwtelling en de Farm Structure Survey (FSS) van de Europese Commissie als uitgangspunt genomen. In totaal zijn 117 diercategorieën verdeeld over zeven hoofdcategorieën onder de loep genomen. Per hoofdcategorie is een nieuwe, vereenvoudigde indeling voorgesteld. Het resultaat is een voorstel met 60 diercategorieën van in Nederland gehouden landbouwhuisdieren. Het aantal hoofdcategorieën (7) is gelijk gebleven, maar het aantal subcategorieën is fors verminderd. De grootste veranderingen worden voorgesteld bij varkens, van de oorspronkelijke tien categorieën blijven er zes over
A fully traits-based approach to modeling global vegetation distribution
Bodegom, P.M. van; Douma, J.C. ; Verheijen, L.M. - \ 2014
Proceedings of the National Academy of Sciences of the United States of America 111 (2014)38. - ISSN 0027-8424 - p. 13733 - 13738.
earth system model - climate-change - plant traits - economics spectrum - functional traits - amazonian forest - photosynthesis - classification - co2 - acclimation
Dynamic Global Vegetation Models (DGVMs) are indispensable for our understanding of climate change impacts. The application of traits in DGVMs is increasingly refined. However, a comprehensive analysis of the direct impacts of trait variation on global vegetation distribution does not yet exist. Here, we present such analysis as proof of principle. We run regressions of trait observations for leaf mass per area, stem-specific density, and seed mass from a global database against multiple environmental drivers, making use of findings of global trait convergence. This analysis explained up to 52% of the global variation of traits. Global trait maps, generated by coupling the regression equations to gridded soil and climate maps, showed up to orders of magnitude variation in trait values. Subsequently, nine vegetation types were characterized by the trait combinations that they possess using Gaussian mixture density functions. The trait maps were input to these functions to determine global occurrence probabilities for each vegetation type. We prepared vegetation maps, assuming that the most probable (and thus, most suited) vegetation type at each location will be realized. This fully traits-based vegetation map predicted 42% of the observed vegetation distribution correctly. Our results indicate that a major proportion of the predictive ability of DGVMs with respect to vegetation distribution can be attained by three traits alone if traits like stem-specific density and seed mass are included. We envision that our traits-based approach, our observation-driven trait maps, and our vegetation maps may inspire a new generation of powerful traits-based DGVMs.
Effects of selective digestive decontamination (SDD) on the gut resistome
Buelow, E. ; Bello Gonzalez, T.D.G. ; Versluis, D. ; Oostdijk, E.A.N. ; Ogilvie, L.A. ; Mourik, M.S.M. van; Oosterink, L. ; Passel, M.W.J. van; Smidt, H. ; D’Andrea, M.M. ; Been, M. de; Jones, B.V. ; Willems, R.J.L. ; Bonten, M.J.M. ; Schaik, W. - \ 2014
Journal of Antimicrobial Chemotherapy 69 (2014)8. - ISSN 0305-7453 - p. 2215 - 2223.
intensive-care units - antimicrobial resistance - microbiota - tract - microarray - metagenome - sequences - bacterial - classification - generation
Objectives Selective digestive decontamination (SDD) is an infection prevention measure for critically ill patients in intensive care units (ICUs) that aims to eradicate opportunistic pathogens from the oropharynx and intestines, while sparing the anaerobic flora, by the application of non-absorbable antibiotics. Selection for antibiotic-resistant bacteria is still a major concern for SDD. We therefore studied the impact of SDD on the reservoir of antibiotic resistance genes (i.e. the resistome) by culture-independent approaches. Methods We evaluated the impact of SDD on the gut microbiota and resistome in a single ICU patient during and after an ICU stay by several metagenomic approaches. We also determined by quantitative PCR the relative abundance of two common aminoglycoside resistance genes in longitudinally collected samples from 12 additional ICU patients who received SDD. Results The patient microbiota was highly dynamic during the hospital stay. The abundance of antibiotic resistance genes more than doubled during SDD use, mainly due to a 6.7-fold increase in aminoglycoside resistance genes, in particular aph(2¿)-Ib and an aadE-like gene. We show that aph(2¿)-Ib is harboured by anaerobic gut commensals and is associated with mobile genetic elements. In longitudinal samples of 12 ICU patients, the dynamics of these two genes ranged from a ~104 fold increase to a ~10-10 fold decrease in relative abundance during SDD. Conclusions ICU hospitalization and the simultaneous application of SDD has large, but highly individualized, effects on the gut resistome of ICU patients. Selection for transferable antibiotic resistance genes in anaerobic commensal bacteria could impact the risk of transfer of antibiotic resistance genes to opportunistic pathogens.
Influence of setup and carbon source on the bacterial community of biocathodes in microbial electrolysis cells
Croesea, E. ; Jeremiasse, A.W. ; Marshall, I.P.G. ; Spormann, A.M. ; Euverink, G.J.W. ; Geelhoed, J.S. ; Stams, A.J.M. ; Plugge, C.M. - \ 2014
Enzyme and Microbial Technology 61-62 (2014). - ISSN 0141-0229 - p. 67 - 75.
hydrogen-production - fuel-cells - desulfovibrio-vulgaris - sp-nov. - sequence data - gen. nov. - diversity - system - classification - acetate
The microbial electrolysis cell (MEC) biocathode has shown great potential as alternative for expensive metals as catalyst for H2 synthesis. Here, the bacterial communities at the biocathode of five hydrogen producing MECs using molecular techniques were characterized. The setups differed in design (large versus small) including electrode material and flow path and in carbon source provided at the cathode (bicarbonate or acetate). A hydrogenase gene-based DNA microarray (Hydrogenase Chip) was used to analyze hydrogenase genes present in the three large setups. The small setups showed dominant groups of Firmicutes and two of the large setups showed dominant groups of Proteobacteria and Bacteroidetes. The third large setup received acetate but no sulfate (no sulfur source). In this setup an almost pure culture of a Promicromonospora sp. developed. Most of the hydrogenase genes detected were coding for bidirectional Hox-type hydrogenases, which have shown to be involved in cytoplasmatic H2 production.
A Unimodal Species Response Model Relating Traits to Environment with Application to Phytoplankton Communities.
Jamil, T. ; Kruk, C. ; Braak, C.J.F. ter - \ 2014
PLoS ONE 9 (2014)5. - ISSN 1932-6203 - 14 p.
bayesian variable selection - climate-change - ecology - lake - variability - strategies - diversity - habitat - classification - regression
In this paper we attempt to explain observed niche differences among species (i.e. differences in their distribution along environmental gradients) by differences in trait values (e.g. volume) in phytoplankton communities. For this, we propose the trait-modulated Gaussian logistic model in which the niche parameters (optimum, tolerance and maximum) are made linearly dependent on species traits. The model is fitted to data in the Bayesian framework using OpenBUGS (Bayesian inference Using Gibbs Sampling) to identify according to which environmental variables there is niche differentiation among species and traits. We illustrate the method with phytoplankton community data of 203 lakes located within four climate zones and associated measurements on 11 environmental variables and six morphological species traits of 60 species. Temperature and chlorophyll-a (with opposite signs) described well the niche structure of all species. Results showed that about 25% of the variance in the niche centres with respect to chlorophyll-a were accounted for by traits, whereas niche width and maximum could not be predicted by traits. Volume, mucilage, flagella and siliceous exoskeleton are found to be the most important traits to explain the niche centres. Species were clustered in two groups with different niches structures, group 1 high temperature-low chlorophyll-a species and group 2 low temperature-high chlorophyll-a species. Compared to group 2, species in group 1 had larger volume but lower surface area, had more often flagella but neither mucilage nor siliceous exoskeleton. These results might help in understanding the effect of environmental changes on phytoplankton community. The proposed method, therefore, can also apply to other aquatic or terrestrial communities for which individual traits and environmental conditioning factors are available.
Biogeographic patterns of base-rich fen vegetation across Europe
Jiménez-Alfaro, B. ; Hájek, M. ; Ejrnaes, R. ; Rodwell, J. ; Pawlikowski, P. ; Weeda, E.J. - \ 2014
Applied Vegetation Science 17 (2014)2. - ISSN 1402-2001 - p. 367 - 380.
environmental gradients - ecological gradients - plant associations - vascular plants - temperate zone - plot size - north - classification - mires - water
Questions What is the distribution of base-rich fen vegetation and the specialist species along European biogeographic regions? How do the gradients in species composition correlate to geography and climate at continental scale? What are the implications of such patterns for the classification of these habitats? Location Fifteen countries of Central, Western and Northern Europe. Methods We compiled a vegetation plot database of base-rich fens and related communities including vascular plants and bryophytes. The initial data set with 6943 plots was filtered according to the presence of specialists using discriminant analysis. We used DCA to analyse the correlation of species composition with geography and climate, and kriging interpolation for mapping gradients in the study area. Modified TWINSPAN was used to detect major vegetation groups. The results of the whole data set (plot size 1–100 m2) were compared with those obtained from two subsets with plots of 1–5 m2 and 6–30 m2. Results Most of the specialists were distributed among all the biogeographic regions, but many were more represented in the Alpine than in the Atlantic, Boreal and Continental regions. Variation in species composition was mainly correlated to temperature, precipitation and latitude in the three data sets, showing a major gradient from (1) alpine belt fens characterized by spring species to (2) small sedge fens mainly distributed in mountain regions and (3) boreo-temperate fens reflecting waterlogged conditions. Conclusions Base-rich fen communities are widely distributed across European biogeographic regions, but the Alpine region can be considered as the compositional centre of this vegetation type. Large-scale gradients of species composition are mainly explained by climate, while the influence of latitude is probably correlated to increasing water table in the boreo-temperate regions. These gradients can be better understood by differentiating three major vegetation types, which should be considered when establishing classification systems of base-rich fens in Europe.
Fusion of pan-tropical biomass maps using weighted averaging and regional calibration data
Ge, Y. ; Avitabile, V. ; Heuvelink, G.B.M. ; Wang, J. ; Herold, M. - \ 2014
International Journal of applied Earth Observation and Geoinformation 31 (2014). - ISSN 0303-2434 - p. 13 - 24.
remotely-sensed imagery - land-cover datasets - multisensor data - forest biomass - carbon-dioxide - sensing data - soil maps - classification - deforestation - validation
Biomass is a key environmental variable that influences many biosphere–atmosphere interactions. Recently, a number of biomass maps at national, regional and global scales have been produced using different approaches with a variety of input data, such as from field observations, remotely sensed imagery and other spatial datasets. However, the accuracy of these maps varies regionally and is largely unknown. This research proposes a fusion method to increase the accuracy of regional biomass estimates by using higher-quality calibration data. In this fusion method, the biases in the source maps were first adjusted to correct for over- and underestimation by comparison with the calibration data. Next, the biomass maps were combined linearly using weights derived from the variance–covariance matrix associated with the accuracies of the source maps. Because each map may have different biases and accuracies for different land use types, the biases and fusion weights were computed for each of the main land cover types separately. The conceptual arguments are substantiated by a case study conducted in East Africa. Evaluation analysis shows that fusing multiple source biomass maps may produce a more accurate map than when only one biomass map or unweighted averaging is used.
Genome analyses of the carboxydotrophic sulfate-reducers Desulfotomaculum nigrificans and Desulfotomaculum carboxydivorans and reclassification of Desulfotomaculum caboxydivorans as a later synonym of Desulfotomaculum nigrificans
Visser, M. ; Parshina, S.N. ; Alves, J.I. ; Sousa, D.Z. ; Pereira, I.A.C. ; Muyzer, G. ; Kuever, J. ; Lebedinsky, A.V. ; Koehorst, J.J. ; Worm, P. ; Plugge, C.M. ; Schaap, P.J. ; Goodwin, L.A. ; Lapidus, A. ; Kyrpides, N.C. ; Detter, J.C. ; Woyke, T. ; Chain, P. ; Davenport, K.W. ; Spring, S. ; Rohde, M. ; Klenk, H.P. ; Stams, A.J.M. - \ 2014
Standards in Genomic Sciences 9 (2014)3. - ISSN 1944-3277 - p. 655 - 675.
reducing bacterium - sp nov. - sequence - growth - classification - hydrogenase - evolution - standard - archaea - system
Desulfotomaculum nigrificans and D. carboxydivorans are moderately thermophilic members of the polyphyletic spore-forming genus Desulfotomaculum in the family Peptococcaceae. They are phylogenetically very closely related and belong to ‘subgroup a’ of the Desulfotomaculum cluster 1. D. nigrificans and D. carboxydivorans have a similar growth substrate spectrum; they can grow with glucose and fructose as electron donors in the presence of sulfate. Additionally, both species are able to ferment fructose, although fermentation of glucose is only reported for D. carboxydivorans. D. nigrificans is able to grow with 20% carbon monoxide (CO) coupled to sulfate reduction, while D. carboxydivorans can grow at 100% CO with and without sulfate. Hydrogen is produced during growth with CO by D. carboxydivorans. Here we present a summary of the features of D. nigrificans and D. carboxydivorans together with the description of the complete genome sequencing and annotation of both strains. Moreover, we compared the genomes of both strains to reveal their differences. This comparison led us to propose a reclassification of D. carboxydivorans as a later heterotypic synonym of D. nigrificans
Ecosystem Services as a Contested Concept: A Synthesis of Critique and Counter-arguments
Schröter, M. ; Zanden, E.H. van der; Oudenhoven, A.P.E. van; Remme, R.P. ; Serna-Chavez, H.M. ; Groot, R.S. de; Opdam, P. - \ 2014
Conservation Letters 7 (2014)6. - ISSN 1755-263X - p. 514 - 523.
sustainability research - saving nature - biodiversity - conservation - science - policy - benefits - classification - agriculture - valuation
We describe and reflect on seven recurring critiques of the concept of ecosystem services and respective counter-arguments. First, the concept is criticized for being anthropocentric while others argue that it goes beyond instrumental values. Second, some argue that the concept promotes an exploitative human-nature relationship, while others state that it re-connects society to ecosystems, emphasizing humanity's dependence on nature. Third, concerns exist that the concept may conflict with biodiversity conservation objectives while others emphasize complementarity. Fourth, the concept is questioned because of its supposed focus on economic valuation, while others argue that ecosystem services science includes many values. Fifth, the concept is criticized for promoting commodification of nature, while others point out that most ecosystem services are not connected to market-based instruments. Sixth, vagueness of definitions and classifications are stated to be a weakness, while others argue that vagueness enhances transdisciplinary collaboration. Seventh, some criticize the normative nature of the concept implying that all outcomes of ecosystem processes are desirable. The normative nature is indeed typical for the concept, but should not be problematic when acknowledged. By disentangling and contrasting different arguments we hope to contribute to a more structured debate between opponents and proponents of the ecosystem services concept.
Mapping a priori defined plant associations using remotely sensed vegetation characteristics
Roelofsen, H.D. ; Kooistra, L. ; Bodegom, P.M. van; Verrelst, J. ; Krol, J. ; Witte, J.M.P. - \ 2014
Remote Sensing of Environment 140 (2014). - ISSN 0034-4257 - p. 639 - 651.
ellenberg indicator values - continuous floristic gradients - hyperspectral imagery - imaging spectroscopy - endmember selection - tropical forests - aviris data - classification - regression - moisture
Incorporation of a priori defined plant associations into remote sensing products is a major challenge that has only recently been confronted by the remote sensing community. We present an approach to map the spatial distribution of such associations by using plant indicator values (IVs) for salinity, moisture and nutrients as an intermediate between spectral reflectance and association occurrences. For a 12 km2 study site in the Netherlands, the relations between observed IVs at local vegetation plots and visible and near-infrared (VNIR) and short-wave infrared (SWIR) airborne reflectance data were modelled using Gaussian Process Regression (GPR) (R2 0.73, 0.64 and 0.76 for salinity, moisture and nutrients, respectively). These relations were applied to map IVs for the complete study site. Association occurrence probabilities were modelled as function of IVs using a large database of vegetation plots with known association and IVs. Using the mapped IVs, we calculated occurrence probabilities of 19 associations for each pixel, resulting in both a crisp association map with the most likely occurring association per pixel, as well as occurrence probability maps per association. Association occurrence predictions were assessed by a local vegetation expert, which revealed that the occurrences of associations situated at frequently predicted indicator value combinations were over predicted. This seems primarily due to biases in the GPR predicted IVs, resulting in associations with envelopes located in extreme ends of IVs being scarcely predicted. Although the results of this particular study were not fully satisfactory, the method potentially offers several advantages compared to current vegetation classification techniques, like site-independent calibration of association probabilities, site-independent selection of associations and the provision of IV maps and occurrence probabilities per association. If the prediction of IVs can be improved, this method may thus provide a viable roadmap to bring a priori defined plant associations into the domain of remote sensing.
Accounting for capacity and flow of ecosystem services: A conceptual model and a case study for Telemark, Norway
Schroter, M. ; Barton, D.N. ; Remme, R.P. ; Hein, L.G. - \ 2014
Ecological Indicators 36 (2014). - ISSN 1470-160X - p. 539 - 551.
supply-and-demand - decision-making - framework - classification - indicators - scales - land - sustainability - management - valuation
Understanding the flow of ecosystem services and the capacity of ecosystems to generate these services is an essential element for understanding the sustainability of ecosystem use as well as developing ecosystem accounts. We conduct spatially explicit analyses of nine ecosystem services in Telemark County, Southern Norway. The ecosystem services included are moose hunting, sheep grazing, timber harvest, forest carbon sequestration and storage, snow slide prevention, recreational residential amenity, recreational hiking and existence of areas without technical interference. We conceptually distinguish capacity to provide ecosystem services from the actual flow of services, and empirically assess both. This is done by means of different spatial models, developed with various available datasets and methods, including (multiple layer) look-up tables, causal relations between datasets (including satellite images), environmental regression and indicators derived from direct measurements. Capacity and flow differ both in spatial extent and in quantities. We discuss five conditions for a meaningful spatial capacity–flow-balance. These are (1) a conceptual difference between capacity and flow, (2) spatial explicitness of capacity and flow, (3) the same spatial extent of both, (4) rivalry or congestion, and (5) measurement with aligned indicators. We exemplify spatially explicit balances between capacity and flow for two services, which meet these five conditions. Research in the emerging field of mapping ES should focus on the development of compatible indicators for capacity and flow. The distinction of capacity and flow of ecosystem services provides a parsimonious estimation of over- or underuse of the respective service. Assessment of capacity and flow in a spatially explicit way can thus support monitoring sustainability of ecosystem use, which is an essential element of ecosystem accounting.
Active learning: Any value for classification of remotely sensed data?
Crawford, Melba M. ; Tuia, Devis ; Yang, Hsiuhan Lexie - \ 2013
Proceedings of the IEEE 101 (2013)3. - ISSN 0018-9219 - p. 593 - 608.
Active learning - adaptation - classification - high-resolution multispectral - hyperspectral - multiview - spatial learning - support vector machines (SVMs)
Active learning, which has a strong impact on processing data prior to the classification phase, is an active research area within the machine learning community, and is now being extended for remote sensing applications. To be effective, classification must rely on the most informative pixels, while the training set should be as compact as possible. Active learning heuristics provide capability to select unlabeled data that are the 'most informative' and to obtain the respective labels, contributing to both goals. Characteristics of remotely sensed image data provide both challenges and opportunities to exploit the potential advantages of active learning. We present an overview of active learning methods, then review the latest techniques proposed to cope with the problem of interactive sampling of training pixels for classification of remotely sensed data with support vector machines (SVMs). We discuss remote sensing specific approaches dealing with multisource and spatially and time-varying data, and provide examples for high-dimensional hyperspectral imagery.
Phylogeny and systematics of Demospongiae in light of new small-subunit ribosomal DNA (18S) sequences
Redmond, N.E. ; Morrow, C. ; Thacker, R.W. ; Diaz, M.C. ; Boury-Esnaul, N. ; Cardenas, P.D. ; Hajdu, E. ; Lobo-Hajdu, G. ; Picton, B.E. ; Pomponi, S.A. ; Kayal, E. ; Collins, A.G. - \ 2013
Integrative and Comparative Biology 53 (2013)3. - ISSN 1540-7063 - p. 388 - 415.
glass sponges porifera - phylum porifera - molecular phylogeny - animal phylogeny - gene-sequences - fossil record - evolution - hexactinellida - classification - verongida
The most diverse and species-rich class of the phylum Porifera is Demospongiae. In recent years, the systematics of this clade, which contains more than 7000 species, has developed rapidly in light of new studies combining molecular and morphological observations. We add more than 500 new, nearly complete 18S sequences (an increase of more than 200%) in an attempt to further enhance understanding of the phylogeny of Demospongiae. Our study specifically targets representation of type species and genera that have never been sampled for any molecular data in an effort to accelerate progress in classifying this diverse lineage. Our analyses recover four highly supported subclasses of Demospongiae: Keratosa, Myxospongiae, Haploscleromorpha, and Heteroscleromorpha. Within Keratosa, neither Dendroceratida, nor its two families, Darwinellidae and Dictyodendrillidae, are monophyletic and Dictyoceratida is divided into two lineages, one predominantly composed of Dysideidae and the second containing the remaining families (Irciniidae, Spongiidae, Thorectidae, and Verticillitidae). Within Myxospongiae, we find Chondrosida to be paraphyletic with respect to the Verongida. We amend the latter to include species of the genus Chondrosia and erect a new order Chondrillida to contain remaining taxa from Chondrosida, which we now discard. Even with increased taxon sampling of Haploscleromorpha, our analyses are consistent with previous studies; however, Haliclona species are interspersed in even more clades. Haploscleromorpha contains five highly supported clades, each more diverse than previously recognized, and current families are mostly polyphyletic. In addition, we reassign Janulum spinispiculum to Haploscleromorpha and resurrect Reniera filholi as Janulum filholi comb. nov. Within the large clade Heteroscleromorpha, we confirmed 12 recently identified clades based on alternative data, as well as a sister-group relationship between the freshwater Spongillida and the family Vetulinidae. We transfer Stylissa flabelliformis to the genus Scopalina within the family Scopalinidae, which is of uncertain position. Our analyses uncover a large, strongly supported clade containing all heteroscleromorphs other than Spongillida, Vetulinidae, and Scopalinidae. Within this clade, there is a major division separating Axinellidae, Biemnida, Tetractinellida, Bubaridae, Stelligeridae, Raspailiidae, and some species of Petromica, Topsentia, and Axinyssa from Agelasida, Polymastiidae, Placospongiidae, Clionaidae, Spirastrellidae, Tethyidae, Poecilosclerida, Halichondriidae, Suberitidae, and Trachycladus. Among numerous results: (1) Spirophorina and its family Tetillidae are paraphyletic with respect to a strongly supported Astrophorina within Tetractinellida; (2) Agelasida is the earliest diverging lineage within the second clade listed above; and (3) Merlia and Desmacella appear to be the earliest diverging lineages of Poecilosclerida.
Segmentation of Rumex obtusifolius using Gaussian Markov random fields
Atni Hiremath, S. ; Tolpekin, V.A. ; Heijden, G. van der; Stein, A. - \ 2013
Machine Vision Applications 24 (2013)4. - ISSN 0932-8092 - p. 845 - 854.
energy minimization - texture features - weed-control - graph cuts - classification - systems - imagery - vision
Rumex obtusifolius is a common weed that is difficult to control. The most common way to control weeds-using herbicides-is being reconsidered because of its adverse environmental impact. Robotic systems are regarded as a viable non-chemical alternative for treating R. obtusifolius and also other weeds. Among the existing systems for weed control, only a few are applicable in real-time and operate in a controlled environment. In this study, we develop a new algorithm for segmentation of R. obtusifolius using texture features based on Markov random fields that works in real-time under natural lighting conditions. We show its performance by comparing it with an existing real-time algorithm that uses spectral power as texture feature. We show that the new algorithm is not only accurate with detection rate of 97.8 % and average error of 56 mm in estimating the location of the tap-root of the plant, but is also fast taking just 0.18 s to process an image of size pixels making it feasible for real-time applications.
Long-Term Physical Functioning and Its Association With Somatic Comorbidity and Comorbid Depression in Patients With Established Rheumatoid Arthritis: A Longitudinal Study
Hoek, J. ; Roorda, L.D. ; Boshuizen, H.C. ; Hees, J. van; Rupp, I. ; Tijhuis, G.J. ; Dekker, J. ; Bos, G.A.M. van den - \ 2013
Arthritis Care & Research 65 (2013)7. - ISSN 2151-464X - p. 1157 - 1165.
quality-of-life - chronic disease - health survey - co-morbidity - metaanalysis - prevalence - classification - outcomes - impact - sf-36
ObjectiveTo describe long-term physical functioning and its association with somatic comorbidity and comorbid depression in patients with established rheumatoid arthritis (RA). MethodsLongitudinal data over a period of 11 years were collected from 882 patients with RA at study inclusion. Patient-reported outcomes were collected in 1997, 1998, 1999, 2002, and 2008. Physical functioning was measured with the Health Assessment Questionnaire and the physical component summary score of the Short Form 36 health survey. Somatic comorbidity was measured by a questionnaire including 12 chronic diseases. Comorbid depression was measured with the Center for Epidemiologic Studies Depression Scale. We distinguished 4 groups of patients based on comorbidity at baseline. ResultsSeventy-two percent of the patients at baseline were women. The mean +/- SD age was 59.3 +/- 14.8 years and the median disease duration was 5.0 years (interquartile range 2.0-14.0 years). For the total group of patients with RA, physical functioning improved over time. Patients with somatic comorbidity, comorbid depression, or both demonstrated worse physical functioning than patients without comorbidity at all data collection points. Both groups with comorbid depression had the lowest scores. Only patients with both somatic comorbidity and comorbid depression showed significantly less improvement in physical functioning over time. ConclusionBoth somatic comorbidity and comorbid depression were negatively associated with physical functioning during an 11-year followup period. Furthermore, their combination seems to be especially detrimental to physical functioning over time. These results emphasize the need to take somatic comorbidity and comorbid depression into account in the screening and treatment of patients with RA.
Red list assessment of European habitat types. A feasibility study
Rodwell, J.S. ; Janssen, J.A.M. ; Gubbay, S. ; Schaminee, J.H.J. - \ 2013
European Commission DG Environment - 78
habitats - biodiversiteit - flora - bedreigde soorten - classificatie - europese unie - biodiversity - endangered species - classification - european union
This report presents an achievable methodology for the Red List assessment of European habitats in terrestrial, freshwater and marine realms, outlines a process that will deliver such evaluations and gives an indication of resources needed. It shows how the EUNIS habitat classification can be employed as an assessment typology, recommends criteria for quantity and quality, assessment of the past trend and current state, and advises including supplementary information on drivers, threats and restorability. The report recommends thresholds and assessment categories that are fully compatible with developing IUCN proposals. As a basis for its recommendations, the report reviews the kinds of typology that are used for habitat description – classifications based on fine-scale species assemblages, mid-scale habitat/biotope classifications and broad-scale ecosystem typologies. It reviews how far each typology has been used for Red List assessment and discusses the various scales on which such evaluations have been made. Relationships between these typologies and classifications used in the Habitats Directive and Marine Strategy Framework Directive are discussed. The report then outlines the core criteria and the thresholds that have been used so far for Red List assessment: quantity (Area of Occupancy, Extent of Occurrence, dispersal/fragmentation, endemism and stand size), quality (speciesrichness, presence of rare, threatened or endemic species, structure, function & landscape context) and trends (in both quantity and quality, both back in time and forwards). It also considers various supplementary criteria that have been used for some Red List assessments: scales of naturalness/hemeroby, drivers and threats, degrees of resilience and restoration capacity. Actual Red List evaluation processes are then described, in the developing IUCN programme for ecosystems and among other approaches, and the role of expert judgment and peer review in assessment is discussed. There is then a critical review of the assessment categories employed for Red Listing: extinct (completely destroyed, extirpated), critically endangered (immediately threatened, severely declined), endangered (threatened, significantly declined), vulnerable (potentially endangered), least concern (secure, not endangered), increasing and data-deficient. The report outlines some of the major data sources available to inform expert judgement: vegetation plot data for terrestrial and freshwater habitats, the Map of the Natural Vegetation of Europe, other terrestrial maps, marine data sources and the Article 17 reporting database. It then outlines relationships between Red List assessment and ecosystem services. The report provides an assessment Fact Sheet and provides two Case Studies which outline available data, deficiencies of information and feasibility of assessment. Finally, there is a comprehensive bibliography of all references.
Sodiomyces alkalinus, a new holomorphic alkaliphilic ascomycete within the Plectoshaerellaceae
Grum-Grzhimaylo, A. ; Debets, A.J.M. ; Diepeningen, A.D. van; Georgieva, M.L. ; Bilanenko, E.N. - \ 2013
Persoonia 31 (2013). - ISSN 0031-5850 - p. 147 - 158.
classification - inference - trees - fungi
In this study we reassess the taxonomic reference of the previously described holomorphic alkaliphilic fungus Heleococcum alkalinum isolated from soda soils in Russia, Mongolia and Tanzania. We show that it is not an actual member of the genus Heleococcum (order Hypocreales) as stated before and should, therefore, be excluded from it and renamed. Multi-locus gene phylogeny analyses (based on nuclear ITS, 5.8S rDNA, 28S rDNA, 18S rDNA, RPB2 and TEF1-alpha) have displayed this fungus as a new taxon at the genus level within the family Plectosphaerellaceae, Hypocreomycetidae, Ascomycota. The reference species of actual Heleococcum members showed clear divergence from the strongly supported Heleococcum alkalinum position within the Plectosphaerellaceae, sister to the family Glomerellaceae. Eighteen strains isolated from soda lakes around the world show remarkable genetic similarity promoting speculations on their possible evolution in harsh alkaline environments. We established the pH growth optimum of this alkaliphilic fungus at c. pH 10 and tested growth on 30 carbon sources at pH 7 and 10. The new genus and species, Sodiomyces alkalinus gen. nov. comb. nov., is the second holomorphic fungus known within the family, the first one being Plectosphaerella – some members of this genus are known to be alkalitolerant. We propose the Plectosphaerellaceae family to be the source of alkaliphilic filamentous fungi as also the species known as Acremonium alcalophilum belongs to this group
Typology and indicators of ecosystem services for marine spatial planning and management
Bohnke-Henrichs, A. ; Baulcomb, C. ; Koss, R. ; Hussain, S. ; Groot, R.S. de - \ 2013
Journal of Environmental Management 130 (2013)11. - ISSN 0301-4797 - p. 135 - 145.
economic valuation - biodiversity - coastal - goods - area - classification - conservation - benefits
The ecosystem services concept provides both an analytical and communicative tool to identify and quantify the link between human welfare and the environment, and thus to evaluate the ramifications of management interventions. Marine spatial planning (MSP) and Ecosystem-based Management (EBM) are a form of management intervention that has become increasingly popular and important globally. The ecosystem service concept is rarely applied in marine planning and management to date which we argue is due to the lack of a well-structured, systematic classification and assessment of marine ecosystem services. In this paper we not only develop such a typology but also provide guidance to select appropriate indicators for all relevant ecosystem services. We apply this marine-specific ecosystem service typology to MSP and EBM. We thus provide not only a novel theoretical construct but also show how the ecosystem services concept can be used in marine planning and management.
Feature level fusion of multi-temporal ALOS PALSAR and Landsat data for mapping and monitoring of tropical deforestation and forest degradation
Reiche, J. ; Souza, C. ; Hoekman, D.H. ; Verbesselt, J. ; Haimwant, P. ; Herold, M. - \ 2013
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 6 (2013)5. - ISSN 1939-1404 - p. 2159 - 2173.
brazilian amazonia - sar - imagery - classification - emissions - countries - accuracy - band
Many tropical countries suffer from persistent cloud cover inhibiting spatially consistent reporting of deforestation and forest degradation for REDD+. Data gaps remain even when compositing Landsat-like optical satellite imagery over one or two years. Instead, medium resolution SAR is capable of providing reliable deforestation information but shows limited capacity to identify forest degradation. This paper describes an innovative approach for feature fusion of multi-temporal and medium-resolution SAR and optical sub-pixel fraction information. After independently processing SAR and optical input data streams the extracted SAR and optical sub-pixel fraction features are fused using a decision tree classifier. ALOS PALSAR Fine Bean Dual and Landsat imagery of 2007 and 2010 acquired over the main mining district in central Guyana have been used for a proof-of-concept demonstration observing overall accuracies of 88% and 89.3% formapping forest land cover and detecting deforestation and forest degradation, respectively. Deforestation and degradation rates of 0.1% and 0.08% are reported for the observation period. Data gaps due to mainly clouds and Landsat ETM+ SLC-off that remained after compositing a set of single-period Landsat scenes, but also due to SAR layover and shadow could be reduced from 7.9% to negligible 0.01% while maintaining the desired thematic detail of detecting deforestation and degradation. The paper demonstrates the increase of both spatial completeness and thematic detail when applying the methodology, compared with potential Landsat-only or PALSAR-only approaches for a heavy cloud contaminated tropical environment. It indicates the potential for providing the required accuracy of activity data for REDD+ MRV.
Co-existence of Distinct Prion Types Enables Conformational Evolution of Human PrPSc by Competitive Selection
Haldiman, T. ; Kim, C. ; Cohen, Y. ; Chen, W. ; Blevins, J. ; Qing, L. ; Cohen, M.L. ; Langeveld, J.P.M. ; Telling, G.C. ; Kong, Q. ; Safar, J.G. - \ 2013
Journal of Biological Chemistry 288 (2013). - ISSN 0021-9258 - p. 29846 - 29861.
creutzfeldt-jakob-disease - transmissible mink encephalopathy - chronic wasting disease - dependent immunoassay - strain variation - transgenic mice - molecular-basis - protein - scrapie - classification
The unique phenotypic characteristics of mammalian prions are thought to be encoded in the conformation of pathogenic prion proteins (PrPSc). The molecular mechanism responsible for the adaptation, mutation, and evolution of prions observed in cloned cells and upon crossing the species barrier remains unsolved. Using biophysical techniques and conformation-dependent immunoassays in tandem, we isolated two distinct populations of PrPSc particles with different conformational stabilities and aggregate sizes, which frequently co-exist in the most common human prion disease, sporadic Creutzfeldt-Jakob disease (sCJD). The protein misfolding cyclic amplification (PMCA) replicates each of the PrPSc particle types independently, and leads to the competitive selection of those with lower initial conformational stability. In serial propagation with a nonglycosylated mutant PrPC substrate, the dominant PrPSc conformers are subject to further evolution by natural selection of the subpopulation with the highest replication rate due to its lowest stability. Cumulatively, the data show that sCJD PrPSc is not a single conformational entity, but a dynamic collection of two distinct populations of particles. This implies the co-existence of different prions, whose adaptation and evolution are governed by the selection of progressively less stable, faster replicating PrPSc conformers.
Automated identification of animal species in camera trap images
Yu, X. ; Wang, J. ; Kays, R. ; Jansen, P.A. ; Wang, T. ; Huang, T. - \ 2013
EURASIP Journal on Image and Video Processing 2013 (2013). - ISSN 1687-5281 - 10 p.
Image sensors are increasingly being used in biodiversity monitoring, with each study generating many thousands or millions of pictures. Efficiently identifying the species captured by each image is a critical challenge for the advancement of this field. Here, we present an automated species identification method for wildlife pictures captured by remote camera traps. Our process starts with images that are cropped out of the background. We then use improved sparse coding spatial pyramid matching (ScSPM), which extracts dense SIFT descriptor and cell-structured LBP (cLBP) as the local features, that generates global feature via weighted sparse coding and max pooling using multi-scale pyramid kernel, and classifies the images by a linear support vector machine algorithm. Weighted sparse coding is used to enforce both sparsity and locality of encoding in feature space. We tested the method on a dataset with over 7,000 camera trap images of 18 species from two different field cites, and achieved an average classification accuracy of 82%. Our analysis demonstrates that the combination of SIFT and cLBP can serve as a useful technique for animal species recognition in real, complex scenarios.
An evaluation of WRF's ability to reproduce the surface wind over complex terrain based on typical circulation patterns.
Jiménez, P.A. ; Dudhia, J. ; González-Rouco, J.F. ; Montávez, J.P. ; Garcia-Bustamante, E. ; Navarro, J. ; Vilà-Guerau de Arellano, J. ; Munoz-Roldán, A. - \ 2013
Journal of Geophysical Research: Atmospheres 118 (2013)14. - ISSN 2169-897X - p. 7651 - 7669.
regional climate model - cluster-analysis - quality-assurance - mesoscale model - united-states - variability - validation - reanalysis - classification - simulation
 The performance of the Weather Research and Forecasting (WRF) model to reproduce the surface wind circulations over complex terrain is examined. The atmospheric evolution is simulated using two versions of the WRF model during an over 13¿year period (1992 to 2005) over a complex terrain region located in the northeast of the Iberian Peninsula. A high horizontal resolution of 2km is used to provide an accurate representation of the terrain features. The multiyear evaluation focuses on the analysis of the accuracy displayed by the WRF simulations to reproduce the wind field of the six typical wind patterns (WPs) identified over the area in a previous observational work. Each pattern contains a high number of days which allows one to reach solid conclusions regarding the model performance. The accuracy of the simulations to reproduce the wind field under representative synoptic situations, or pressure patterns (PPs), of the Iberian Peninsula is also inspected in order to diagnose errors as a function of the large-scale situation. The evaluation is accomplished using daily averages in order to inspect the ability of WRF to reproduce the surface flow as a result of the interaction between the synoptic scale and the regional topography. Results indicate that model errors can originate from problems in the initial and lateral boundary conditions, misrepresentations at the synoptic scale, or the realism of the topographic features.
Phylogeny of Tetillidae (Porifera, Demospongiae, Spirophorida) based on three molecular markers
Szitenberg, A. ; Becking, L.E. ; Vargas, S. ; Fernandez, J. ; Santodomingo, N. - \ 2013
Molecular Phylogenetics and Evolution 67 (2013)2. - ISSN 1055-7903 - p. 509 - 519.
multiple sequence alignment - antarctic sponges - mixed models - mitochondrial - tree - dna - classification - astrophorida - evolution - alloclada
Tetillidae are spherical to elliptical cosmopolitan demosponges. The family comprises eight genera: namely, Acanthotetilla Burton, 1959, Amphitethya Lendenfeld, 1907, CinachyraSollas, 1886, CinachyrellaWilson, 1925, Craniella Schmidt, 1870, Fangophilina Schmidt, 1880, Paratetilla Dendy, 1905, and Tetilla Schmidt, 1868. These genera are characterized by few conflicting morphological characters, resulting in an ambiguity of phylogenetic relationships. The phylogeny of tetillid genera was investigated using the cox1, 18S rRNA and 28S rRNA (C1–D2 domains) genes in 88 specimens (8 genera, 28 species). Five clades were identified: (i) Cinachyrella, Paratetilla and Amphitethya species, (ii) Cinachyrella levantinensis, (iii) Tetilla, (iv) Craniella, Cinachyra and Fangophilina and (v) Acanthotetilla. Consequently, the phylogenetic analysis supports the monophyly of Tetilla, a genus lacking any known morphological synapomorphy. Acanthotetilla is also recovered. In contrast, within the first clade, species of the genera Paratetilla and Amphitethya were nested within Cinachyrella. Similarly, within the fourth clade, species of the genera Cinachyra and Fangophilina were nested within Craniella. As previously postulated by taxonomists, the loss of ectodermal specialization (i.e., a cortex) has occurred several times independently. Nevertheless, the presence or absence of a cortex and its features carry a phylogenetic signal. Surprisingly, the common view that assumes close relationships among sponges with porocalices (i.e., surface depressions) is refuted.
Hydrological drought across the world: impact of climate and physical catchment structure
Lanen, H.A.J. van; Wanders, N. ; Tallaksen, L.M. ; Loon, A.F. van - \ 2013
Hydrology and Earth System Sciences 17 (2013)5. - ISSN 1027-5606 - p. 1715 - 1732.
water availability - european runoff - united-states - groundwater - flow - model - simulations - trends - classification - propagation
Large-scale hydrological drought studies have demonstrated spatial and temporal patterns in observed trends, and considerable difference exists among global hydrological models in their ability to reproduce these patterns. In this study a controlled modeling experiment has been set up to systematically explore the role of climate and physical catchment structure (soils and groundwater systems) to better understand underlying drought-generating mechanisms. Daily climate data (1958-2001) of 1495 grid cells across the world were selected that represent Koppen-Geiger major climate types. These data were fed into a conceptual hydrological model. Nine realizations of physical catchment structure were defined for each grid cell, i.e., three soils with different soil moisture supply capacity and three groundwater systems (quickly, intermediately and slowly responding). Hydrological drought characteristics (number, duration and standardized deficit volume) were identified from time series of daily discharge. Summary statistics showed that the equatorial and temperate climate types (A-and C-climates) had about twice as many drought events as the arid and polar types (B-and E-climates), and the durations of more extreme droughts were about half the length. Selected soils under permanent grassland were found to have a minor effect on hydrological drought characteristics, whereas groundwater systems had major impact. Groundwater systems strongly controlled the hydrological drought characteristics of all climate types, but particularly those of the wetter A-, C-and D-climates because of higher recharge. The median number of droughts for quickly responding groundwater systems was about three times higher than for slowly responding systems. Groundwater systems substantially affected the duration, particularly of the more extreme drought events. Bivariate probability distributions of drought duration and standardized deficit for combinations of Koppen-Geiger climate, soil and groundwater system showed that the responsiveness of the groundwater system is as important as climate for hydrological drought development. This urges for an improvement of subsurface modules in global hydrological models to be more useful for water resources assessments. A foreseen higher spatial resolution in large-scale models would enable a better hydrogeological parameterization and thus inclusion of lateral flow.
Soil maps of The Netherlands
Hartemink, A.E. ; Sonneveld, M.P.W. - \ 2013
Geoderma 204-205 (2013). - ISSN 0016-7061 - p. 1 - 9.
water-table - seasonal fluctuation - survey information - classification - evaluate
The Netherlands has a long history of soil research. Over the past 150 years, seven national soil maps have been produced at scales ranging from 1:50,000 to 1:1,000,000. The maps were based on different conceptual models which reflected advances in soil science as well as societal demands. There are four phases in the development of soil mapping in The Netherlands. The first three are: (i) the geological phase (1837–1937), (ii) the physiographic phase (1937–1962) and (iii) the morphometric phase (1962–1995). The earliest soil maps, made in the mid-1800s, were largely based on surface geology. In 1950 the first national soil map was published based on physiographic soil mapping. From the 1960s onwards, mapping followed a pedogenetic–morphometric approach and these maps have been widely used in land use planning, hydrologic studies, re-allotments, and agricultural land evaluations. An increase in environmental awareness with the need to assess environmental impacts and developments in information technology induced the digital soil information phase (1995–present). New technologies have improved the collection, storage, analysis and presentation of soil geographic information. It is concluded that initial soil mapping in The Netherlands had a strong agricultural focus but that the current maps are used in a wide range of applications.
Gene Ontology consistent protein function prediction: the FALCON algorithm applied to six eukaryotic genomes
Kourmpetis, Y.A.I. ; Dijk, A.D.J. van; Braak, C.J.F. ter - \ 2013
Algorithms for Molecular Biology 8 (2013)1. - ISSN 1748-7188
arabidopsis-thaliana - integration - annotation - regression - network - classification - association - terms - tool
Gene Ontology (GO) is a hierarchical vocabulary for the description of biological functions and locations, often employed by computational methods for protein function prediction. Due to the structure of GO, function predictions can be self- contradictory. For example, a protein may be predicted to belong to a detailed functional class, but not in a broader class that, due to the vocabulary structure, includes the predicted one.We present a novel discrete optimization algorithm called Functional Annotation with Labeling CONsistency (FALCON) that resolves such contradictions. The GO is modeled as a discrete Bayesian Network. For any given input of GO term membership probabilities, the algorithm returns the most probable GO term assignments that are in accordance with the Gene Ontology structure. The optimization is done using the Differential Evolution algorithm. Performance is evaluated on simulated and also real data from Arabidopsis thaliana showing improvement compared to related approaches. We finally applied the FALCON algorithm to obtain genome-wide function predictions for six eukaryotic species based on data provided by the CAFA (Critical Assessment of Function Annotation) project
A high-resolution and harmonized model approach for reconstructing and analysing historic land changes in Europe
Fuchs, R. ; Herold, M. ; Verburg, P.H. ; Clevers, J.G.P.W. - \ 2013
Biogeosciences 10 (2013). - ISSN 1726-4170 - p. 1543 - 1559.
mediterranean landscapes - atmospheric co2 - cover changes - future - carbon - maps - classification - emissions - centuries
Human-induced land use changes are nowadays the second largest contributor to atmospheric carbon dioxide after fossil fuel combustion. Existing historic land change reconstructions on the European scale do not sufficiently meet the requirements of greenhouse gas (GHG) and climate assessments, due to insufficient spatial and thematic detail and the consideration of various land change types. This paper investigates if the combination of different data sources, more detailed modelling techniques, and the integration of land conversion types allow us to create accurate, high-resolution historic land change data for Europe suited for the needs of GHG and climate assessments. We validated our reconstruction with historic aerial photographs from 1950 and 1990 for 73 sample sites across Europe and compared it with other land reconstructions like Klein Goldewijk et al. (2010, 2011), Ramankutty and Foley (1999), Pongratz et al. (2008) and Hurtt et al. (2006). The results indicate that almost 700 000 km2 (15.5%) of land cover in Europe has changed over the period 1950–2010, an area similar to France. In Southern Europe the relative amount was almost 3.5% higher than average (19%). Based on the results the specific types of conversion, hot-spots of change and their relation to political decisions and socio-economic transitions were studied. The analysis indicates that the main drivers of land change over the studied period were urbanization, the reforestation program resulting from the timber shortage after the Second World War, the fall of the Iron Curtain, the Common Agricultural Policy and accompanying afforestation actions of the EU. Compared to existing land cover reconstructions, the new method considers the harmonization of different datasets by achieving a high spatial resolution and regional detail with a full coverage of different land categories. These characteristics allow the data to be used to support and improve ongoing GHG inventories and climate research
Mapping land cover gradients through analysis of hyper-temporal NDVI imagery
Ali, A. ; Bie, C.A.J.M. de; Skidmore, A.K. ; Scarrott, R.G. ; Hamad, A. ; Venus, V. ; Lymberakis, P. - \ 2013
International Journal of applied Earth Observation and Geoinformation 23 (2013). - ISSN 0303-2434 - p. 301 - 312.
multitemporal modis images - remotely-sensed imagery - time-series - fuzzy-sets - species composition - accuracy assessment - neural-networks - classification - vegetation - boundaries
The green cover of the earth exhibits various spatial gradients that represent gradual changes in space of vegetation density and/or in species composition. To date, land cover mapping methods differentiate at best, mapping units with different cover densities and/or species compositions, but typically fail to express such differences as gradients. Present interpretation techniques still make insufficient use of freely available spatial-temporal Earth Observation (EO) data that allow detection of existing land cover gradients. This study explores the use of hyper-temporal NDVI imagery to detect and delineate land cover gradients analyzing the temporal behavior of NDVI values. MODIS-Terra MVC-images (250 m, 16-day) of Crete, Greece, from February 2000 to July 2009 are used. The analysis approach uses an ISODATA unsupervised classification in combination with a Hierarchical Clustering Analysis (HCA). Clustering of class-specific temporal NDVI profiles through HCA resulted in the identification of gradients in landcover vegetation growth patterns. The detected gradients were arranged in a relational diagram, and mapped. Three groups of NDVI-classes were evaluated by correlating their class-specific annual average NDVI values with the field data (tree, shrub, grass, bare soil, stone, litter fraction covers). Multiple regression analysis showed that within each NDVI group, the fraction cover data were linearly related with the NDVI data, while NDVI groups were significantly different with respect to tree cover (adj. R 2 = 0.96), shrub cover (adj. R 2 = 0.83), grass cover (adj. R 2 = 0.71), bare soil (adj. R 2 = 0.88), stone cover (adj. R 2 = 0.83) and litter cover (adj. R 2 = 0.69) fractions. Similarly, the mean Sorenson dissimilarity values were found high and significant at confidence interval of 95% in all pairs of three NDVI groups. The study demonstrates that hyper-temporal NDVI imagery can successfully detect and map land cover gradients. The results may improve land cover assessment and aid in agricultural and ecological studies.
Use of agro-climatic zones to upscale simulated crop yield potential
Wart, J. van; Bussel, L.G.J. van; Wolf, J. ; Licker, R. ; Grassini, P. ; Nelson, A. ; Boogaard, H.L. ; Gerber, J. ; Mueller, N.D. ; Claessens, L.F.G. ; Ittersum, M.K. van; Cassman, K.G. - \ 2013
Field Crops Research 143 (2013). - ISSN 0378-4290 - p. 44 - 55.
global land areas - climate-change - agroecological zones - management - impacts - classification - agriculture - patterns - system - world
Yield gap analysis, which evaluates magnitude and variability of difference between crop yield potential (Yp) or water limited yield potential (Yw) and actual farm yields, provides a measure of untapped food production capacity. Reliable location-specific estimates of yield gaps, either derived from research plots or simulation models, are available only for a limited number of locations and crops due to cost and time required for field studies or for obtaining data on long-term weather, crop rotations and management practices, and soil properties. Given these constraints, we compare global agro-climatic zonation schemes for suitability to up-scale location-specific estimates of Yp and Yw, which are the basis for estimating yield gaps at regional, national, and global scales. Six global climate zonation schemes were evaluated for climatic homogeneity within delineated climate zones (CZs) and coverage of crop area. An efficient CZ scheme should strike an effective balance between zone size and number of zones required to cover a large portion of harvested area of major food crops. Climate heterogeneity was very large in CZ schemes with less than 100 zones. Of the other four schemes, the Global Yield Gap Atlas Extrapolation Domain (GYGA-ED) approach, based on a matrix of three categorical variables (growing degree days, aridity index, temperature seasonality) to delineate CZs for harvested area of all major food crops, achieved reasonable balance between number of CZs to cover 80% of global crop area and climate homogeneity within zones. While CZ schemes derived from two climate-related categorical variables require a similar number of zones to cover 80% of crop area, within-zone heterogeneity is substantially greater than for the GYGA-ED for most weather variables that are sensitive drivers of crop production. Some CZ schemes are crop-specific, which limits utility for up-scaling location-specific evaluation of yield gaps in regions with crop rotations rather than single crop species.
A proposal for including humus forms in the World Reference Base for soil resources (WRB-FAO)
Jabiol, B. ; Zanella, A. ; Ponge, J.F. ; Sarton, G. ; Englisch, M. ; Delft, S.P.J. van; Waal, R.W. de; Claire-Le Bayon, R. - \ 2013
Geoderma 192 (2013). - ISSN 0016-7061 - p. 286 - 294.
earthworm invasion - organic-matter - forest - classification - vegetation - france
The morpho-functional classification of humus forms proposed in a previous issue by Zanella and collaborators for Europe has been extended and modified, without any change in diagnostic horizons, in order to embrace a wide array of humus forms at worldwide level and to complete and make more effective the World Reference Base for Soil Resources. For that purpose 31 Humus Form Reference Groups (HFRGs) and a set of prefix and suffix qualifiers are proposed, following the rules erected for the WRB. An exhaustive classification key, respecting the principles of WRB, is suggested and examples of classification are given for some already well known humus forms.