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The aim of this work is to develop and test a method for generation of information on vegetation dynamics from high-spatial resolution data, such as Sentinel-2. In order to accomplish this, Sentinel-2 data were simulated from existing SPOT HRG and HRVIR scenes over Sweden. We used TIMESAT, a well-tested computer package for generating smooth seasonal profiles and generation of seasonality paramete

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Aim: Climate change impacts forest functioning and services through two inter-related effects. First, it impacts tree growth, with effects, for example, on biomass production. Second, climate change also reshuffles community composition, with further effects on forest functioning. However, the relative importance of these two effects has rarely been studied. Here, we developed a new modelling appr

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Rising temperatures can influence ecosystem processes both directly and indirectly, through effects on plant species and communities. An improved understanding of direct versus indirect effects of warming on ecosystem processes is needed for robust predictions of the impacts of climate change on terrestrial ecosystem carbon (C) dynamics. To explore potential direct and indirect effects of warming

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The El Niño-Southern Oscillation (ENSO) is one of the most significant climate variability signals. Studying the changes in ENSO-induced precipitation variability (ENSO precipitation) in the past climate offers a possibility to a better understanding of how they may change under future climate conditions. This study uses simulations performed with the European community Earth-System Model (EC-Eart

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The long-term ecological interactions between fire and the composition of dominant trees and shrubs in boreal and cold temperate Fennoscandian forests are still under discussion. We hypothesized that fire-prone taxa should abound during periods and regions characterized by higher fire disturbance, while fire-intolerant taxa should dominate when and where fire activity is low. Biomass burning (BB)

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The savanna complex is a highly diverse global biome that occurs within the seasonally dry tropical to sub-tropical equatorial latitudes and are structurally and functionally distinct from grasslands and forests. Savannas are open-canopy environments that encompass a broad demographic continuum, often characterised by a changing dominance between C3-tree and C4-grass vegetation, where frequent env

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Land management for carbon storage is discussed as being indispensable for climate change mitigation because of its large potential to remove carbon dioxide from the atmosphere, and to avoid further emissions from deforestation. However, the acceptance and feasibility of land-based mitigation projects depends on potential side effects on other important ecosystem functions and their services. Here

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It is important that climate models can accurately simulate the terrestrial carbon cycle in the Arctic due to the large and potentially labile carbon stocks found in permafrost-affected environments, which can lead to a positive climate feedback, along with the possibility of future carbon sinks from northward expansion of vegetation under climate warming. Here we evaluate the simulation of tundra

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Many time-series smoothing methods can be used for reducing noise and extracting plant phenological parameters from remotely-sensed data, but there is still no conclusive evidence in favor of one method over others. Here we use moderate-resolution imaging spectroradiometer (MODIS) derived normalized difference vegetation index (NDVI) to investigate five smoothing methods: Savitzky-Golay fitting (S

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We present two novel earth observation products derived from the BESD and EMMA XCO2 products which were respectively retrieved from SCIAMACHY and GOSAT observations within the GreenHouse Gas project of ESA's Climate Change Initiative (GHG-CCI). These products are inferred by a Carbon Cycle Data Assimilation System (CCDAS) and consist of net and gross biosphere-atmosphere fluxes of carbon dioxide o

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In the 21st century, climate change in combination with increasing demand, mainly from population growth, will exert greater pressure on the ecosystems of the Sahel to supply food and feed resources. The balance between supply and demand, defined as the annual biomass required for human consumption, serves as a key metric for quantifying basic resource shortfalls over broad regions.Here we apply a

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To study global nitrogen (N) leaching from natural ecosystems under changing N deposition, climate, and atmospheric CO2, we performed a factorial model experiment for the period 1901-2006 with the N-enabled global terrestrial ecosystem model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator). In eight global simulations, we used either the true transient time series of N deposition, climate

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Context: Anthropogenic and environmental changes are reshaping landscapes across the globe. In this context, understanding the patterns, drivers, and consequences of these changes is one of the central challenges of humankind. Purpose: We aim to test the possibilities of combining modern multidisciplinary approaches to reconstruct the land-cover and linking the changes in land-cover to socioeconom

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Questions: We investigated the changing role of climate, forest fires and human population size in the broad-scale compositional changes in Holocene vegetation dynamics before and after the onset of farming in Sweden (at 6,000 cal yr BP) and in Finland (at 4,000 cal yr BP). Location: Southern and central Sweden, SW and SE Finland. Methods: Holocene regional plant abundances were reconstructed usin

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Time series from Landsat and Sentinel-2 satellites have great potential for modeling vegetation seasonality. However, irregular time sampling and frequent data loss due to clouds, snow, and short growing seasons, makes this modeling a challenge. We describe a new method for modeling seasonal vegetation index dynamics from satellite time series data. The method is based on box constrained separable

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Observations of vegetation phenology at regional-to-global scales provide important information regarding seasonal variation in the fluxes of energy, carbon, and water between the biosphere and the atmosphere. Numerous algorithms have been developed to estimate phenological transition dates using time series of remotely sensed spectral vegetation indices. A key challenge, however, is that differen

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Northern peatlands store nearly one-third of terrestrial carbon (C) stocks while covering only 3% of the global landmass; nevertheless, the drivers of C cycling in these often-waterlogged ecosystems are different from those that control C dynamics in upland forested soils. To explore how multiple abiotic and biotic characteristics of bogs interact to shape microbial activity in a northern, foreste

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Dynamic global vegetation models (DGVMs) are designed for the study of past, present and future vegetation patterns together with associated biogeochemical cycles and climate feedbacks. However, most DGVMs do not yet have detailed representations of permafrost and non-permafrost peatlands, which are an important store of carbon, particularly at high latitudes. We demonstrate a new implementation o

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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

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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