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Disentangling remotely-sensed plant phenology and snow seasonality at northern Europe using MODIS and the plant phenology index

Land surface phenology is frequently derived from remotely sensed data. However, over regions with seasonal snow cover, remotely-sensed land surface phenology may be dominated by snow seasonality, rather than showing true plant phenology. Overlooking snow influences may lead to inaccurate plant phenology estimation, and consequently to misinterpretation of climate-vegetation interactions. To addre

Climate data induced uncertainty in model-based estimations of terrestrial primary productivity

Model-based estimations of historical fluxes and pools of the terrestrial biosphere differ substantially. These differences arise not only from differences between models but also from differences in the environmental and climatic data used as input to the models. Here we investigate the role of uncertainties in historical climate data by performing simulations of terrestrial gross primary product

Understanding the weather signal in national crop-yield variability

Year-to-year variations in crop yields can have major impacts on the livelihoods of subsistence farmers and may trigger significant global price fluctuations, with severe consequences for people in developing countries. Fluctuations can be induced by weather conditions, management decisions, weeds, diseases, and pests. Although an explicit quantification and deeper understanding of weather-induced

Comparing field inventory with mechanistic modelling and light-use efficiency modelling based approaches for estimating forest net primary productivity at a regional level

Monitoring of forest carbon fluxes for the purpose of national greenhouse-gas inventorying and reporting are commonly based on repeated large-scale field measurements. Alternate approaches based on modelling of forest growth offers potential benefits such as cost savings and detailed assessments of involved carbon fluxes. We calculated the net primary productivity (NPP) of Swedish forests using tw

Coreference Resolution for Swedish and German using Distant Supervision

Coreference resolution is the identification of phrases that refer to the same entity in a text. Current techniques to solve coreferences use machine-learning algorithms, which require large annotated data sets. Such annotated Resources are no tavailable for most languages today. In this paper, we describe a method for solving coreferences for Swedish and German using distant supervision that does

Docforia: A Multilayer Document Model

In this paper, we describe Docforia, a multilayer document model and application programming interface (API) to store formatting, lexical, syntactic, and semantic annotations on Wikipedia and other kinds of text and visualize them. While Wikipedia has become a major NLP resource, its scale and heterogeneity makes it relatively difficult to do experimentations on the whole corpus. These experimentat

The benefits of investing into improved carbon flux monitoring

Operationalizing a Global Carbon Observing and Analysis System (www.geocarbon.net) would provide a sound basis for monitoring actual carbon fluxes and thus getting quantities right when pricing carbon - be it in a cap-and-trade scheme or under a tax regime. However, such monitoring systems are expensive and-especially in times of economic weakness-budgets for science and environmental policy are u

Hydrologic resilience and Amazon productivity

The Amazon rainforest is disproportionately important for global carbon storage and biodiversity. The system couples the atmosphere and land, with moist forest that depends on convection to sustain gross primary productivity and growth. Earth system models that estimate future climate and vegetation show little agreement in Amazon simulations. Here we show that biases in internally generated clima

Impacts of climate mitigation strategies in the energy sector on global land use and carbon balance

Reducing greenhouse gas emissions to limit damage to the global economy climate-change-induced and secure the livelihoods of future generations requires ambitious mitigation strategies. The introduction of a global carbon tax on fossil fuels is tested here as a mitigation strategy to reduce atmospheric CO2 concentrations and radiative forcing. Taxation of fossil fuels potentially leads to changed

Spatial variability of CO2 uptake in polygonal tundra : Assessing low-frequency disturbances in eddy covariance flux estimates

The large spatial variability in Arctic tundra complicates the representative assessment of CO2 budgets. Accurate measurements of these heterogeneous landscapes are, however, essential to understanding their vulnerability to climate change. We surveyed a polygonal tundra lowland on Svalbard with an unmanned aerial vehicle (UAV) that mapped ice-wedge morphology to complement eddy covariance (EC) fl

A high arctic experience of uniting research and monitoring

Monitoring is science keeping our thumb on the pulse of the environment to detect any changes of concern for societies. Basic science is the question-driven search for fundamental processes and mechanisms. Given the firm root of monitoring in human interests and needs, basic sciences have often been regarded as scientifically "purer"-particularly within university-based research communities. We ar

Generating ActiGraph Counts from Raw Acceleration Recorded by an Alternative Monitor

PURPOSE: To implement an aggregation method in Matlab for generating ActiGraph counts from raw acceleration recorded with an alternative accelerometer device and to investigate the validity of the method. METHODS: The aggregation method including the frequency band-pass filter was implemented and optimized based on standardized sinusoidal acceleration signals generated in Matlab and processed in t

Applications of Machine Learning on Natural Language Processing and Biomedical Data

Machine learning is ubiquitous in today’s society, with promising applicationsin the field of natural language processing (NLP), so that computers can handlehuman language better, and within the medical community, with the promiseof better treatments. Machine learning can be seen as a subfield of artificialintelligence (AI), where AI is used to describe a machine that mimics cognitivefunctions tha

Degradation potentials of dissolved organic carbon (DOC) from thawed permafrost peat

Global warming can substantially affect the export of dissolved organic carbon (DOC) from peat-permafrost to aquatic systems. The direct degradability of such peat-derived DOC, however, is poorly constrained because previous permafrost thaw studies have mainly addressed mineral soil catchments or DOC pools that have already been processed in surface waters. We incubated peat cores from a palsa mir

Impact of religion on understanding the world: development of tense and modality

This paper analyses an impact of religious practice on the development of the tense system, in particular the future tense. There have been rich typological studies on the tense, which reveal that a basic tense distinction is either past vs. non-past or past vs. present vs. future in most languages. From evolutionary/historical perspectives, the former case is older than the latter one, i.e. the f