| 121. |
- Tian, Feng, et al.
(författare)
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Calibrating vegetation phenology from Sentinel-2 using eddy covariance, PhenoCam, and PEP725 networks across Europe
- 2021
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Ingår i: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257. ; 260
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Tidskriftsartikel (refereegranskat)abstract
- Vegetation phenology obtained from time series of remote sensing data is relevant for a range of ecological applications. The freely available Sentinel-2 imagery at a 10 m spatial resolution with a ~ 5-day repeat cycle provides an opportunity to map vegetation phenology at an unprecedented fine spatial scale. To facilitate the production of a Europe-wide Copernicus Land Monitoring Sentinel-2 based phenology dataset, we design and evaluate a framework based on a comprehensive set of ground observations, including eddy covariance gross primary production (GPP), PhenoCam green chromatic coordinate (GCC), and phenology phases from the Pan-European Phenological database (PEP725). We test three vegetation indices (VI) — the normalized difference vegetation index (NDVI), the two-band enhanced vegetation index (EVI2), and the plant phenology index (PPI) — regarding their capability to track the seasonal trajectories of GPP and GCC and their performance in reflecting spatial variabilities of the corresponding GPP and GCC phenometrics, i.e., start of season (SOS) and end of season (EOS). We find that for GPP phenology, PPI performs the best, in particular for evergreen coniferous forest areas where the seasonal variations in leaf area are small and snow is prevalent during wintertime. Results are inconclusive for GCC phenology, for which no index is consistently better than the others. When comparing to PEP725 phenology phases, PPI and EVI2 perform better than NDVI regarding the spatial correlation and consistency (i.e., lower standard deviation). We also link VI phenometrics at various amplitude thresholds to the PEP725 phenophases and find that PPI SOS at 25% and PPI EOS at 15% provide the best matches with the ground-observed phenological stages. Finally, we demonstrate that applying bidirectional reflectance distribution function correction to Sentinel-2 reflectance is a step that can be excluded for phenology mapping in Europe.
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| 122. |
- Tian, Feng, et al.
(författare)
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Coupling of ecosystem-scale plant water storage and leaf phenology observed by satellite
- 2018
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Ingår i: Nature Ecology and Evolution. - : Springer Science and Business Media LLC. - 2397-334X. ; 2:9, s. 1428-1435
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Tidskriftsartikel (refereegranskat)abstract
- Plant water storage is fundamental to the functioning of terrestrial ecosystems by participating in plant metabolism, nutrient and sugar transport, and maintenance of the integrity of the hydraulic system of the plant. However, a global view of the size and dynamics of the water pools stored in plant tissues is still lacking. Here, we report global patterns of seasonal variations in ecosystem-scale plant water storage and their relationship with leaf phenology, based on space-borne measurements of L-band vegetation optical depth. We find that seasonal variations in plant water storage are highly synchronous with leaf phenology for the boreal and temperate forests, but asynchronous for the tropical woodlands, where the seasonal development of plant water storage lags behind leaf area by up to 180 days. Contrasting patterns of the time lag between plant water storage and terrestrial groundwater storage are also evident in these ecosystems. A comparison of the water cycle components in seasonally dry tropical woodlands highlights the buffering effect of plant water storage on the seasonal dynamics of water supply and demand. Our results offer insights into ecosystem-scale plant water relations globally and provide a basis for an improved parameterization of eco-hydrological and Earth system models.
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| 123. |
- Tian, Feng, et al.
(författare)
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Seasonal co-variation of plant water storage, canopy greenness, and groundwater storage across the globe
- 2018
-
Konferensbidrag (refereegranskat)abstract
- Plant water storage is fundamental to the functioning of terrestrial ecosystems by participating in plant metabolism, nutrient and sugar transport, and maintenance of the integrity of the hydraulic system of the plant. However, a global view of the size and dynamics of the water pools stored in plant tissues is still lacking. Here, we report global patterns of seasonal variations in ecosystem-scale plant water storage and their relationship with leaf phenology and groundwater variability, based on space-borne measurements of L-band vegetation optical depth. We find that seasonal variations in plant water storage are highly synchronous with leaf phenology for the boreal and temperate forests, but asynchronous for the tropical woodlands, where the seasonal development of plant water storage lags behind leaf area by up to 180 days. Contrasting patterns of the time lag between plant water storage and terrestrial groundwater storage are also evident in these ecosystems. A comparison of the water cycle components in seasonally dry tropical woodlands highlights the buffering effect of plant water storage on the seasonal dynamics of water supply and demand. Our results offer insights into ecosystem-scale plant water relations globally and provide a basis for an improved parameterization of eco-hydrological and Earth system models.
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| 124. |
- Verbruggen, Wim, et al.
(författare)
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Contrasting responses of woody and herbaceous vegetation to altered rainfall characteristics in the Sahel
- 2021
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Ingår i: Biogeosciences. - : Copernicus GmbH. - 1726-4170 .- 1726-4189. ; 18:1, s. 77-93
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Tidskriftsartikel (refereegranskat)abstract
- Dryland ecosystems are a major source of land cover, account for about 40% of Earth's terrestrial surface and net primary productivity, and house more than 30% of the human population. These ecosystems are subject to climate extremes (e.g. large-scale droughts and extreme floods) that are projected to increase in frequency and severity under most future climate scenarios. In this modelling study we assessed the impact of single years of extreme (high or low) rainfall on dryland vegetation in the Sahel. The magnitude and legacy of these impacts were quantified on both the plant functional type and the ecosystem levels. In order to understand the impact of differences in the rainfall distribution over the year, these rainfall anomalies were driven by changing either rainfall intensity, event frequency or rainy-season length. The Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model was parameterized to represent dryland plant functional types (PFTs) and was validated against flux tower measurements across the Sahel. Different scenarios of extreme rainfall were derived from existing Sahel rainfall products and applied during a single year of the model simulation timeline. Herbaceous vegetation responded immediately to the different scenarios, while woody vegetation had a weaker and slower response, integrating precipitation changes over a longer timeframe. An increased season length had a larger impact than increased intensity or frequency, while impacts of decreased rainfall scenarios were strong and independent of the season characteristics. Soil control on surface water balance explains these contrasts between the scenarios. None of the applied disturbances caused a permanent vegetation shift in the simulations. Dryland ecosystems are known to play a dominant role in the trend and variability of the global terrestrial CO2 sink. We showed that single extremely dry and wet years can have a strong impact on the productivity of drylands ecosystems, which typically lasts an order of magnitude longer than the duration of the disturbance. Therefore, this study sheds new light on potential drivers and mechanisms behind this variability.
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| 125. |
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| 126. |
- Vicente-Serrano, Sergio M., et al.
(författare)
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Challenges for drought mitigation in Africa: The potential use of geospatial data and drought information systems
- 2012
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Ingår i: Applied Geography. - : Elsevier BV. - 1873-7730 .- 0143-6228. ; 34, s. 471-486
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Tidskriftsartikel (refereegranskat)abstract
- Understanding, monitoring and mitigating drought is a very difficult task as a consequence of the intrinsic nature of the phenomenon. In addition, assessing the impact of drought on ecosystems and societies is also a complex task, because the same drought severity may have different consequences in different regions and systems due to the underlying vulnerabilities. New technologies based on geospatial information are available to determine the risk and vulnerability of a system to a drought and to develop monitoring and early warning systems based on real-time information to support decision making. To improve drought preparedness and mitigation, geospatial datasets based on climate information, Earth Observation Systems and statistical and dynamical modelling methodologies can make a noticeably difference in mitigating drought impacts in Africa. In this article we illustrate how the development of drought information systems based on geospatial technology, that combines static and real-time information, could improve the possibilities of drought mitigation in Africa. We stress that it is necessary to go beyond past attempts to manage drought risk based on a reactive crisis-response approach, by promoting drought mitigation and preparedness at the national and regional levels. For this purpose the development of drought information tools is fundamental for the implementation of drought management plans and to support real-time decision-making. (C) 2012 Elsevier Ltd. All rights reserved.
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| 127. |
- Wiktelius, S, et al.
(författare)
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Desert locust control in ecologically sensitive areas: Need for guidelines.
- 2003
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Ingår i: Ambio: a Journal of Human Environment. - : Royal Swedish Academy of Sciences. - 0044-7447. ; 32:7, s. 463-468
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Tidskriftsartikel (refereegranskat)abstract
- Chemical control of desert locust (DL) is carried out over large areas of land, covering a range of different landscapes and ecosystems. There are no real restrictions for spraying in or close to environmentally sensitive areas and awareness of sensitivity is not always obvious to the people involved in control. However, concern about environmental issues in connection with DL control is growing and clear guidelines are needed. The objectives were: to identify and delineate areas particularly sensitive to pesticide contamination in northeastern Africa, e.g. protected areas, wetlands, populated places, oases, and areas with concentrations of migratory birds. These areas were matched with actual DL control during 1986-1998. The conclusion is that chemical control occurred in environmentally sensitive areas especially wetlands, e.g. temporary waters and mangroves; close to human settlements; and, to some extent, in or near protected areas and areas with numerous migratory birds.
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| 128. |
- Wu, Chaoyang, et al.
(författare)
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An underestimated role of precipitation frequency in regulating summer soil moisture
- 2012
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Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 7:2, s. 1-9
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Tidskriftsartikel (refereegranskat)abstract
- Soil moisture induced droughts are expected to become more frequent under future global climate change. Precipitation has been previously assumed to be mainly responsible for variability in summer soil moisture. However, little is known about the impacts of precipitation frequency on summer soil moisture, either interannually or spatially. To better understand the temporal and spatial drivers of summer drought, 415 site yr measurements observed at 75 flux sites world wide were used to analyze the temporal and spatial relationships between summer soil water content (SWC) and the precipitation frequencies at various temporal scales, i.e., from half-hourly, 3, 6, 12 and 24 h measurements. Summer precipitation was found to be an indicator of interannual SWC variability with r of 0.49 (p < 0.001) for the overall dataset. However, interannual variability in summer SWC was also significantly correlated with the five precipitation frequencies and the sub-daily precipitation frequencies seemed to explain the interannual SWC variability better than the total of precipitation. Spatially, all these precipitation frequencies were better indicators of summer SWC than precipitation totals, but these better performances were only observed in non-forest ecosystems. Our results demonstrate that precipitation frequency may play an important role in regulating both interannual and spatial variations of summer SWC, which has probably been overlooked or underestimated. However, the spatial interpretation should carefully consider other factors, such as the plant functional types and soil characteristics of diverse ecoregions.
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| 129. |
- Wu, Zhendong, et al.
(författare)
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Climate data induced uncertainty in model-based estimations of terrestrial primary productivity
- 2017
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Ingår i: Environmental Research Letters. - : IOP Publishing. - 1748-9326. ; 12:6
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Tidskriftsartikel (refereegranskat)abstract
- 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 productivity (GPP) using a process-based dynamic vegetation model (LPJ-GUESS) forced by six different climate datasets. We find that the climate induced uncertainty, defined as the range among historical simulations in GPP when forcing the model with the different climate datasets, can be as high as 11 Pg C yr-1 globally (9 % of mean GPP). We also assessed a hypothetical maximum climate data induced uncertainty by combining climate variables from different datasets, which resulted in significantly larger uncertainties of 41 Pg C yr-1 globally or 32 % of mean GPP. The uncertainty is partitioned into components associated to the three main climatic drivers, temperature, precipitation, and shortwave radiation. Additionally, we illustrate how the uncertainty due to a given climate driver depends both on the magnitude of the forcing data uncertainty (climate data range) and the apparent sensitivity of the modeled GPP to the driver (apparent model sensitivity). We find that LPJ-GUESS overestimates GPP compared to empirically based GPP data product in all land cover classes except for tropical forests. Tropical forests emerge as a disproportionate source of uncertainty in GPP estimation both in the simulations and empirical data products. The tropical forest uncertainty is most strongly associated with shortwave radiation and precipitation forcing, of which climate data range contributes higher to overall uncertainty than apparent model sensitivity to forcing. Globally, precipitation dominates the climate induced uncertainty over nearly half of the vegetated land area, which is mainly due to climate data range and less so due to the apparent model sensitivity. Overall, climate data ranges are found to contribute more to the climate induced uncertainty than apparent model sensitivity to forcing. Our study highlights the need to better constrain tropical climate, and demonstrates that uncertainty caused by climatic forcing data must be considered when comparing and evaluating carbon cycle model results and empirical datasets.
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| 130. |
- Wu, Zhendong, et al.
(författare)
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Effect of climate dataset selection on simulations of terrestrial GPP: Highest uncertainty for tropical regions
- 2018
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 13:6
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Tidskriftsartikel (refereegranskat)abstract
- Biogeochemical models use meteorological forcing data derived with different approaches(e.g. based on interpolation or reanalysis of observation data or a hybrid hereof) to simulateecosystem processes such as gross primary productivity (GPP). This study assesses theimpact of different widely used climate datasets on simulated gross primary productivity andevaluates the suitability of them for reproducing the global and regional carbon cycle asmapped from independent GPP data. We simulate GPP with the biogeochemical modelLPJ-GUESS using six historical climate datasets (CRU, CRUNCEP, ECMWF, NCEP,PRINCETON, and WFDEI). The simulated GPP is evaluated using an observation-basedGPP product derived from eddy covariance measurements in combination with remotelysensed data. Our results show that all datasets tested produce relatively similar GPP simulationsat a global scale, corresponding fairly well to the observation-based data with a differencebetween simulations and observations ranging from -50 to 60 g m-2 yr-1. However, allsimulations also show a strong underestimation of GPP (ranging from -533 to -870 g m-2 yr-1)and low temporal agreement (r < 0.4) with observations over tropical areas. As the shortwaveradiation for tropical areas was found to have the highest uncertainty in the analyzed historicalclimate datasets, we test whether simulation results could be improved by a correction ofthe tested shortwave radiation for tropical areas using a new radiation product from the InternationalSatellite Cloud Climatology Project (ISCCP). A large improvement (up to 48%) insimulated GPP magnitude was observed with bias corrected shortwave radiation, as well asan increase in spatio-temporal agreement between the simulated GPP and observationbasedGPP. This study conducts a spatial inter-comparison and quantification of the performancesof climate datasets and can thereby facilitate the selection of climate forcing dataover any given study area for modelling purposes.
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