Articoli di riviste: "Vegetation dynamics"

1

VAN DER MAAREL, EDDY. "Vegetation dynamics and dynamic vegetation science*". Acta Botanica Neerlandica 45, n. 4 (dicembre 1996): 421–42. http://dx.doi.org/10.1111/j.1438-8677.1996.tb00804.x.

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Marani, Marco, Tommaso Zillio, Enrica Belluco, Sonia Silvestri e Amos Maritan. "Non-Neutral Vegetation Dynamics". PLoS ONE 1, n. 1 (20 dicembre 2006): e78. http://dx.doi.org/10.1371/journal.pone.0000078.

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He, Dong, Xianglin Huang, Qingjiu Tian e Zhichao Zhang. "Changes in Vegetation Growth Dynamics and Relations with Climate in Inner Mongolia under More Strict Multiple Pre-Processing (2000–2018)". Sustainability 12, n. 6 (24 marzo 2020): 2534. http://dx.doi.org/10.3390/su12062534.

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Inner Mongolia Autonomous Region (IMAR) is related to China’s ecological security and the improvement of ecological environment; thus, the vegetation’s response to climate changes in IMAR has become an important part of current global change research. As existing achievements have certain deficiencies in data preprocessing, technical methods and research scales, we correct the incomplete data pre-processing and low verification accuracy; use grey relational analysis (GRA) to study the response of Enhanced Vegetation Index (EVI) in the growing season to climate factors on the pixel scale; explore the factors that affect the response speed and response degree from multiple perspectives, including vegetation type, longitude, latitude, elevation and local climate type; and solve the problems of excessive ignorance of details and severe distortion of response results due to using average values of the wide area or statistical data. The results show the following. 1. The vegetation status of IMAR in 2000-2018 was mainly improved. The change rates were 0.23/10° N and 0.25/10° E, respectively. 2. The response speed and response degree of forests to climatic factors are higher than that of grasslands. 3. The lag time of response for vegetation growth to precipitation, air temperature and relative humidity in IMAR is mainly within 2 months. The speed of vegetation‘s response to climate change in IMAR is mainly affected by four major factors: vegetation type, altitude gradient, local climate type and latitude. 4. Vegetation types and altitude gradients are the two most important factors affecting the degree of vegetation’s response to climate factors. It is worth noting that when the altitude rises to 2500 m, the dominant factor for the vegetation growth changes from precipitation to air temperature in terms of hydrothermal combination in the environment. Vegetation growth in areas with relatively high altitudes is more dependent on air temperature.

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Okin, Gregory S. "The contribution of brown vegetation to vegetation dynamics". Ecology 91, n. 3 (marzo 2010): 743–55. http://dx.doi.org/10.1890/09-0302.1.

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TELESCA, LUCIANO, ROSA LASAPONARA e ANTONIO LANORTE. "DISCRIMINATING FLUCTUATION DYNAMICS IN BURNED AND UNBURNED VEGETATIONAL COVERS". Fluctuation and Noise Letters 05, n. 04 (dicembre 2005): L479—L487. http://dx.doi.org/10.1142/s0219477505002914.

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Fluctuation dynamics of time series of satellite SPOT-VEGETATION Normalized Difference of Vegetation Index (NDVI) data from 1998 to 2003 were analyzed to discriminate fire-induced variability in the vegetational dynamics of shrub-land in southern Italy. We used detrended fluctuation analysis (DFA), which permits the detection of persistent properties in nonstationary signal fluctuations. We analyzed two shrub-land covers, one in "healthy conditions" (fire-unaffected) and the other in "ill conditions" (fire-affected). Our findings suggest that fires play an important role in the temporal evolution of the shrub-land, increasing the persistence of the vegetation dynamics.

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Seo, Hocheol, e Yeonjoo Kim. "Interactive impacts of fire and vegetation dynamics on global carbon and water budget using Community Land Model version 4.5". Geoscientific Model Development 12, n. 1 (29 gennaio 2019): 457–72. http://dx.doi.org/10.5194/gmd-12-457-2019.

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Abstract. Fire plays an important role in terrestrial ecosystems. The burning of biomass affects carbon and water fluxes and vegetation distribution. To understand the effect of interactive processes of fire and ecological succession on surface carbon and water fluxes, this study employed the Community Land Model version 4.5 to conduct a series of experiments that included and excluded fire and dynamic vegetation processes. Results of the experiments that excluded the vegetation dynamics showed a global increase in net ecosystem production (NEP) in post-fire regions, whereas the inclusion of vegetation dynamics revealed a fire-induced decrease in NEP in some regions, which was depicted when the dominant vegetation type was changed from trees to grass. Carbon emissions from fires are enhanced by reduction in NEP when vegetation dynamics are considered; however, this effect is somewhat mitigated by the increase in NEP when vegetation dynamics are not considered. Fire-induced changes in vegetation modify the soil moisture profile because grasslands are more dominant in post-fire regions. This results in less moisture within the top soil layer than that in unburned regions, even though transpiration is reduced overall. These findings are different from those of previous fire model evaluations that ignored vegetation dynamics and thus highlight the importance of interactive processes between fires and vegetation dynamics in evaluating recent model developments.

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Арефьев, С. П., e S. P. Arefiev. "Model and Analysis of Vegetative Cover Climathogenic Dynamics on the Example of the Yamal Peninsula Data". Mathematical Biology and Bioinformatics 12, n. 2 (11 agosto 2017): 256–72. http://dx.doi.org/10.17537/2017.12.256.

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The rule of geoinformation design of vegetation cover dynamics model due to temperature variations is considered. The construction is based on the geobotanical map of vegetation formations that determines spatial analysis detail level, and on the table of the species quantity in the surveyed area. According to the postulated assumptions, with the warming the vegetation cover state vector of the northern zone will acquire values corresponding to the vegetative image of the formation of the conjugated southern zone if they belong to the same landscape-like group. The computational analysis results of the tundra vegetation dynamics are presented for the dominant plant species of the Yamal peninsula northern subarctic zone.

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Pott, Richard. "Palaeoclimate and vegetation - long-term vegetation dynamics in central Europe with particular reference to beech". Phytocoenologia 30, n. 3-4 (24 novembre 2000): 285–333. http://dx.doi.org/10.1127/phyto/30/2000/285.

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Thevs, Niels, Stefan Zerbe, Jan Peper e Michael Succow. "Vegetation and vegetation dynamics in the Tarim River floodplain of continental-arid Xinjiang, NW China". Phytocoenologia 38, n. 1-2 (25 agosto 2008): 65–84. http://dx.doi.org/10.1127/0340-269x/2008/0038-0065.

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Pastor, John. "Vegetation Dynamics and Climate Change". Ecology 75, n. 7 (ottobre 1994): 2145–46. http://dx.doi.org/10.2307/1941620.

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Prentice, I. C., O. van Tongeren e J. T. De Smidt. "Simulation of Heathland Vegetation Dynamics". Journal of Ecology 75, n. 1 (marzo 1987): 203. http://dx.doi.org/10.2307/2260546.

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Chambers, F. M., A. M. Solomon e H. H. Shugart. "Vegetation Dynamics and Global Change." Journal of Ecology 81, n. 4 (dicembre 1993): 834. http://dx.doi.org/10.2307/2261689.

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13

Zhou, Chan, Jian Guo, Zhuo Zhang e Hong Lou. "Quantity Dynamics of Vegetation Characteristics". Advanced Materials Research 955-959 (giugno 2014): 810–13. http://dx.doi.org/10.4028/www.scientific.net/amr.955-959.810.

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Characteristics of vegetation under meadow, typical steppe and desert steppe were comparatively studied, such as aboveground biomass, height, total carbon and total nitrogen. The results demonstrated that the aboveground biomass and height of vegetation under these three types of steppes were the lowest in the early growing season of May, and reached their highest in the peak season, usually in July or August. Variance analysis showed that the differences among these three steppes in aboveground biomass, height, total carbon and total nitrogen were highly significant. Therefore, the variances and irregularity in vegetation characteristics of these three steppes were affected by moisture and other ecological factors, of which moisture was the primary ecological factor.

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14

Bakker, J. P., J. H. Willems e M. Zobel. "Long-term vegetation dynamics: Introduction". Journal of Vegetation Science 7, n. 2 (aprile 1996): 146. http://dx.doi.org/10.1111/j.1654-1103.1996.tb01958.x.

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15

Franklin, Oskar, Sandy P. Harrison, Roderick Dewar, Caroline E. Farrior, Åke Brännström, Ulf Dieckmann, Stephan Pietsch et al. "Organizing principles for vegetation dynamics". Nature Plants 6, n. 5 (maggio 2020): 444–53. http://dx.doi.org/10.1038/s41477-020-0655-x.

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16

Archer, S. "Vegetation Dynamics in Changing Environments." Rangeland Journal 15, n. 1 (1993): 104. http://dx.doi.org/10.1071/rj9930104.

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Human-induced changes in atmospheric chemistry and meteorology have the potential to alter a broad array of ecosystem processes over a range of temporal and spatial scales. These may have direct and indirect effects that could influence management strategies and landscape response to disturbances associated with natural events and land use. The extent to which forecasted global changes are effective in altering local ecosystem properties will depend upon a variety of factors. In this paper, I address species life history traits and community and landscape properties that can be used by land managers to evaluate potential manifestations of global change on a local scale.

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Woodwell, George M. "Vegetation dynamics and global change". Trends in Ecology & Evolution 8, n. 10 (ottobre 1993): 381. http://dx.doi.org/10.1016/0169-5347(93)90229-i.

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18

Cannell, Melvin G. R. "Vegetation dynamics and global change". Forest Ecology and Management 72, n. 1 (marzo 1995): 86–87. http://dx.doi.org/10.1016/0378-1127(95)90028-4.

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19

Hulst, Robert. "Invasion models of vegetation dynamics". Vegetatio 69, n. 1-3 (aprile 1987): 123–31. http://dx.doi.org/10.1007/bf00038693.

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20

Port, U., V. Brovkin e M. Claussen. "The influence of vegetation dynamics on anthropogenic climate change". Earth System Dynamics Discussions 3, n. 2 (5 luglio 2012): 485–522. http://dx.doi.org/10.5194/esdd-3-485-2012.

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Abstract. In this study, vegetation-climate and vegetation-carbon cycle interactions during anthropogenic climate change are assessed by using the Earth System Model MPI ESM including a module for vegetation dynamics. We assume anthropogenic CO2 emissions according to the RCP 8.5 scenario in the period from 1850 to 2120 and shut them down afterwards to evaluate the equilibrium response of the Earth System by 2300. Our results suggest that vegetation dynamics have a considerable influence on the changing global and regional climate. In the simulations, global mean tree cover extends by 2300 due to increased atmospheric CO2 concentration and global warming. Thus, land carbon uptake is higher and atmospheric CO2 concentration is lower by about 40 ppm when considering dynamic vegetation compared to a static pre-industrial vegetation cover. The reduced atmospheric CO2 concentration is equivalent to a lower global mean temperature. Moreover, biogeophysical effects of vegetation cover shifts influence the climate on a regional scale. Expanded tree cover in the northern high latitudes results in a reduced albedo and additional warming. In the Amazon region, declined tree cover causes a higher temperature as evapotranspiration is reduced. In total, we find that vegetation dynamics have a slight attenuating effect on global climate change as the global climate cools by 0.22 K in 2300 due to natural vegetation cover shifts.

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21

Ivanova, Natalya, Valery Fomin e Antonín Kusbach. "Experience of Forest Ecological Classification in Assessment of Vegetation Dynamics". Sustainability 14, n. 6 (14 marzo 2022): 3384. http://dx.doi.org/10.3390/su14063384.

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Due to global climate change and increased forest transformation by humans, accounting for the dynamics of forest ecosystems is becoming a central problem in forestry. We reviewed the success of considering vegetation dynamics in the most influential ecological forest classifications in Russia, the European Union, and North America. Out of the variety of approaches to forest classification, only those that are widely used in forestry and forest inventory were selected. It was found that the system of diagnostic signs developed by genetic forest typology based on the time-stable characteristics of habitats as well as the developed concept of dynamic series of cenosis formation allows us to successfully take into account the dynamics of vegetation. While forest dynamics in European classifications is assessed at a theoretical level, it is also possible to assess forest dynamics in practice due to information obtained from EUNIS habitat classification. In ecological classifications in North America, the problem of vegetation dynamics is most fully solved with ecological site description (ESD), which includes potential vegetation and disturbance factors in the classification features. In habitat type classification (HTC) and biogeoclimatic ecosystem classification (BEC), vegetation dynamics is accounted based on testing the diagnostic species and other signs of potential vegetation for resistance to natural and anthropogenic disturbances. Understanding of vegetation–environment associations is fundamental in forming proper forest management methods and improving existing classification structures. We believe that this topic is relevant as part of the ongoing search for new solutions within all significant forest ecological classifications.

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Gonzales, Howell B., John Tatarko, Mark E. Casada, Ronaldo G. Maghirang, Lawrence J. Hagen e Charles J. Barden. "Computational Fluid Dynamics Simulation of Airflow through Standing Vegetation". Transactions of the ASABE 62, n. 6 (2019): 1713–22. http://dx.doi.org/10.13031/trans.13449.

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Abstract. Maintaining vegetative cover on the soil surface is the most widely used method for control of soil loss by wind erosion. We numerically modeled airflow through artificial standing vegetation (i.e., simulated wheat plants) using computational fluid dynamics (CFD). A solver (simpleFoam within the OpenFOAM software architecture) was used to simulate airflow through various three-dimensional (3D) canopy structures in a wind tunnel, which were created using another open-source CAD geometry software (Salomé ver. 7.2). This study focused on two specific objectives: (1) model airflow through standing vegetation using CFD, and (2) compare the results of a previous wind tunnel study with various artificial vegetation configurations to the results of the CFD model. Wind speeds measured in the wind tunnel experiment differed slightly from the numerical simulation using CFD, especially near positions where simulated vegetation was present. Effective drag coefficients computed using wind profiles did not differ significantly (p <0.05) between the experimental and simulated results. Results of this study will provide information for research into other types of simulated stubble or sparse vegetation during wind erosion events.HighlightsMeasured airflow through a simulated canopy was successfully modeled using CFD software.Effective drag coefficients did not differ between the experimental and simulated results.Results of this study provide 3-D simulation data of wind flow through a plant canopy. Keywords: 3-D canopy structure, OpenFOAM, Wind erosion, Wind tunnel studies.

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Islam, K. K., S. Patricia e RinchenY. "Broadleaved regeneration dynamics in the Pine plantation". Journal of Forest Science 57, No. 10 (17 ottobre 2011): 432–38. http://dx.doi.org/10.17221/78/2010-jfs.

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  In an Island of the Netherlands, Pine (Pinus nigra) was planted to stabilize the dunes and to protect the arable lands from the blowing sand. This research was conducted to understand the most important environmental factors responsible for a vegetation change in the Pine plantation and effect of this change on the rare orchid population: Goodyera repens and Listera cordata. Vegetation sampling was carried out according to the Braun-Blanquet phytosociologic method within the three sites of this Island. Twinspan analysis confirmed the definition of three site types and redundancy analysis showed a significant difference between the pure Pine stands and the plots with regeneration. The results revealed that the most significant explanatory variables were litter cover, broadleaved tree cover, and shrub cover indicating the vegetation change under the Pine plantation. The abundance of Goodyera repens is strongly associated with the Pine forest and negatively related to broadleaved cover. Listera cordata could apparently cope with vegetation change. Controlling the herbaceous layer in the Pine plantation can promote the orchid population but on the contrary, promoting the natural regeneration of broadleaved species might endanger them.

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Feng, Biao, Huang Yong Zhang, Tou Sheng Huang e Fei Fan Zhang. "Dynamics on the Interactions between Vegetable Growth and Water Erosion". Advanced Materials Research 864-867 (dicembre 2013): 2550–53. http://dx.doi.org/10.4028/www.scientific.net/amr.864-867.2550.

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This research investigates the interaction between vegetation growth and water erosion by a new dynamic model. According to the theoretical and numerical analysis of the research, there are three cases of equilibrium distribution and their dynamics over time. And the dynamics between vegetation and erosion is disparate under the condition of different parameters. Every equilibrium point also has a unique distribution under every set of parameters. When there are two interior equilibriums, a critical curve exists and divides the system into two areas, one is coexistence area and another is dominated by vegetation or erosion.

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Port, U., V. Brovkin e M. Claussen. "The influence of vegetation dynamics on anthropogenic climate change". Earth System Dynamics 3, n. 2 (27 novembre 2012): 233–43. http://dx.doi.org/10.5194/esd-3-233-2012.

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Abstract. In this study, vegetation–climate and vegetation–carbon cycle interactions during anthropogenic climate change are assessed by using the Earth System Model of the Max Planck Institute for Meteorology (MPI ESM) that includes vegetation dynamics and an interactive carbon cycle. We assume anthropogenic CO2 emissions according to the RCP 8.5 scenario in the time period from 1850 to 2120. For the time after 2120, we assume zero emissions to evaluate the response of the stabilising Earth System by 2300. Our results suggest that vegetation dynamics have a considerable influence on the changing global and regional climate. In the simulations, global mean tree cover extends by 2300 due to increased atmospheric CO2 concentration and global warming. Thus, land carbon uptake is higher and atmospheric CO2 concentration is lower by about 40 ppm when considering dynamic vegetation compared to the static pre-industrial vegetation cover. The reduced atmospheric CO2 concentration is equivalent to a lower global mean temperature. Moreover, biogeophysical effects of vegetation cover shifts influence the climate on a regional scale. Expanded tree cover in the northern high latitudes results in a reduced albedo and additional warming. In the Amazon region, declined tree cover causes a regional warming due to reduced evapotranspiration. As a net effect, vegetation dynamics have a slight attenuating effect on global climate change as the global climate cools by 0.22 K due to natural vegetation cover shifts in 2300.

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Tahvildari, Navid. "NUMERICAL MODELING OF THE INTERACTIONS BETWEEN NONLINEAR WAVES AND ARBITRARILY FLEXIBLE VEGETATION". Coastal Engineering Proceedings, n. 35 (23 giugno 2017): 32. http://dx.doi.org/10.9753/icce.v35.waves.32.

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Coastal wetlands are among the natural features with the capability to dissipate wave energy and reduce storm damage. Inadequate representation of wave and vegetation characteristics in numerical models may reduce their capability in predicting wave processes over wetlands. Previous numerical wave models have typically applied simplifications on vegetation behavior. For instance, vegetation stems were usually assumed to be rigid or semi-flexible and thus extreme stem deflections could not be captured. In this study, a time-domain nonlinear numerical model based on extended Boussinesq formulation is developed and coupled with a numerical model for vegetation blade dynamics that allows for arbitrary flexibility. Comparison with analytical and laboratory experiments show that the coupled model can adequately predict flow as well as vegetation blade dynamics without the need for any parameter tuning. The model is then used to obtain wave-induced forces on a stem and vegetation blade orientation. Model results indicate that the variation of the vegetative drag coefficient with wave frequency is non-monotonic.

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Wegehenkel, M. "Modeling of vegetation dynamics in hydrological models for the assessment of the effects of climate change on evapotranspiration and groundwater recharge". Advances in Geosciences 21 (12 agosto 2009): 109–15. http://dx.doi.org/10.5194/adgeo-21-109-2009.

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Abstract. Vegetation affects water balance of the land surface by e.g. storage of precipitation water in the canopy and soil water extraction by transpiration. Therefore, it is essential to consider the role of vegetation in affecting water balance by taking into account the temporal dynamics of e.g. leaf area index, rooting depth and stomatal conductance in hydrological models. However until now, most conceptual hydrological models do not treat vegetation as a dynamic component. This paper presents an analysis of the effects of the application of two different complex vegetation models combined with a hydrological model on the model outputs evapotranspiration and groundwater recharge. Both model combinations were used for the assessment of the effects of climate change on water balance in a mesoscale catchment loctated in the Northeastern German Lowlands. One vegetation model assumes a static vegetation development independent from environmental conditions. The other vegetation model calculates dynamic development of vegetation based on photosynthesis, respiration, allocation, and phenology. The analysis of the results obtained from both model combinations indicated the importance of taking into account vegetation dynamics in hydrological models especially if such models are used for the assessment of the impacts of climate change on water balance components.

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Baniya, Binod, Narayan Prasad Gaire, Qua-anan Techato, Yubraj Dhakal e Yam Prasad Dhital. "High altitudinal vegetation dynamics including treeline ecotone in Langtang National Park, Nepal". Nepal Journal of Environmental Science 9, n. 2 (27 dicembre 2021): 13–24. http://dx.doi.org/10.3126/njes.v9i2.36605.

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Identification of high altitudinal vegetation dynamics using remote sensing is important because of the complex topography and environment in the Himalayas. Langtang National Park is the first Himalayan park in Nepal representing the best area to study vegetation change in the central Himalaya region because of the high altitudinal gradient and relatively less disturbed region. This study aimed at mapping vegetation in Langtang National Park and its treeline ecotone using Moderate Resolution Imaging Spectroradiometer (MODIS), Normalized Difference Vegetation Index (NDVI). Two treeline sites with an altitude of 3927 and 3802 meters above sea level (masl) were selected, and species density was measured during the field survey. The linear slope for each pixel and the Mann Kendall test to measure significant trends were used. The results showed that NDVI has significantly increased at the rate of 0.002yr-1 in Langtang National Park and 0.003yr-1 in treeline ecotone during 2000-2017. The average 68.73% equivalents to 1463 km2 of Langtang National Park are covered by vegetation. At the same time, 16.45% equivalents to 350.43 km2 are greening, and 0.25%, i.e., 5.43 km2 are found browning. In treeline ecotone, the vegetation is mostly occupied by grasses, shrublands and small trees where the NDVI was found from 0.1 to 0.5. The relative changes of NDVI in barren lands are negative and vegetative lands above 0.5 NDVI are positive between 2000 and 2017. The dominant treeline vegetation were Abies spectabilis, Rhododendron campanulatum, Betula utilis and Sorbus microphyla, with the vegetation density of 839.28 and 775 individuals per hectare in sites A and B, respectively. The higher average NDVI values, significantly increased NDVI, and higher density of vegetation in both A and B sites indicate that the vegetation in treeline ecotone is obtaining a good environment in the Himalayas of Nepal.

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Baniya, Mahendra B., Takashi Asaeda, Takeshi Fujino, Senavirathna M. D. H. Jayasanka, Guligena Muhetaer e Jinghao Li. "Mechanism of Riparian Vegetation Growth and Sediment Transport Interaction in Floodplain: A Dynamic Riparian Vegetation Model (DRIPVEM) Approach". Water 12, n. 1 (24 dicembre 2019): 77. http://dx.doi.org/10.3390/w12010077.

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The ecological dynamics of riparian areas interact with sediment transport in river systems, which plays an active role in riparian vegetation growth in the floodplain. The fluvial dynamics, hydraulics, hydro-meteorological and geomorphological characteristics of rivers are associated with sediment transport in river systems and around the riparian area. The flood disturbance, sediment with nutrients and seeds transported by river, sediment deposition, and erosion phenomena in the floodplain change the bare land area to vegetation area and vice versa. The difference in riparian vegetation area in the river floodplain is dependent on the sediment grain size distribution which is deposited in the river floodplain. Mathematical models describing vegetation growth in a short period exist in literature, but long-term modelling and validations are still lacking. In order to cover long-term vegetation growth modelling, a Dynamic Riparian Vegetation Model (DRIPVEM) was proposed. This paper highlights the existing modelling technique of DRIPVEM coupled with a Dynamic Herbaceous Model used to establish the interactive relationship of sediment grain sizes and riparian vegetation in the floodplain.

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Rumiantsev, Boris, Sofya Dzhatdoeva, Vasily Zotov e Azret Kochkarov. "Analysis of the Potato Vegetation Stages Based on the Dynamics of Water Consumption in the Closed Urban Vertical Farm with Automated Microclimate Control". Agronomy 13, n. 4 (23 marzo 2023): 954. http://dx.doi.org/10.3390/agronomy13040954.

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One of the promising trends in modern agronomy is the development of automated closed urban vertical farms with controlled environmental conditions, which can improve dynamics of the crop vegetation process. In the frame of this work, the analysis of the vegetative stages of potato seed material (minitubers and microplants) grown in the conditions of the automated vertical farm was conducted. The study was performed at the vertical farm of the Federal Research Center “Fundamentals of Biotechnology” of the Russian Academy of Sciences by the analysis of water consumption dynamics. It was established that the 20-day reduction in the vegetative period of the vertical-farm-grown potatoes in comparison with the field-grown ones occurred due to the reduction in the final stage of vegetation (mass gain of newly formed tubers) under the minitubers planting. The same reduction occurred due to both final and initial vegetative stage (absence of tubers germination) under the planting of microplants. The obtained result shed new light on the vegetation dynamics of potato grown under controlled conditions of the urban vertical farms and demonstrated a possibility to perform the study of plant development process using automated diagnostics systems of vertical farms.

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Yu, Wenjuan, Weiqi Zhou, Zhaxi Dawa, Jia Wang, Yuguo Qian e Weimin Wang. "Quantifying Urban Vegetation Dynamics from a Process Perspective Using Temporally Dense Landsat Imagery". Remote Sensing 13, n. 16 (13 agosto 2021): 3217. http://dx.doi.org/10.3390/rs13163217.

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Urban vegetation can be highly dynamic due to the complexity of different anthropogenic drivers. Quantifying such dynamics is crucially important as it is a prerequisite to understanding its social and ecological consequences. Previous studies have mostly focused on the urban vegetation dynamics through monotonic trends analysis in certain intervals, but not considered the process which provides important insights for urban vegetation management. Here, we developed an approach that integrates trends with dynamic analysis to measure the vegetation dynamics from the process perspective based on the time-series Landsat imagery and applied it in Shenzhen, a coastal megacity in southern China, as an example. Our results indicated that Shenzhen was turning green from 2000–2020, even though a large-scale urban expansion occurred during this period. Approximately half of the city (49.5%) showed consistent trends in greening, most of which were located in the areas within the ecological protection baseline. We also found that 35.3% of the Shenzhen city experienced at least a one-time change in urban greenness that was mostly caused by changes in land cover types (e.g., vegetation to developed land). Interestingly, 61.5% of these lands showed trends in greening in the recent change period and most of them were distributed in build-up areas. Our approach that integrates trends analysis and dynamic process reveals information that cannot be discovered by monotonic trends analysis alone, and such information can provide insights for urban vegetation planning and management.

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Djoharam, Veybi, Widiatmaka Widiatmaka, Marimin Marimin, Dyah Retno Panuju e Suria Darma Tarigan. "Vegetation dynamics of Sangkub watershed in North Sulawesi Province indicated by NDVI of Landsat data". Journal of Degraded and Mining Lands Management 10, n. 1 (1 ottobre 2022): 3991. http://dx.doi.org/10.15243/jdmlm.2022.101.3991.

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<p>Vegetation can be an important indicator of ecosystem change, the influence of anthropogenic and non-anthropogenic factors. Therefore, it is important to study the dynamics of vegetation changes. One technique that can be used for vegetation analysis is the Normalized Difference Vegetation Index (NDVI). NDVI is an indicator of the active biomass that helps distinguish vegetation from other land cover and can provide information about changes in Spatio-temporal vegetation dynamics, thus allowing for assessment of the ecological conditions. This study aimed to investigate the dynamic of vegetation in the Sangkub watershed area located in North Sulawesi Province. This analysis used geospatial technology with the NDVI method, utilizing Landsat 5 and Landsat 8 satellite imagery data in three periods the year 2000, 2015, and 2020. The results showed that vegetation cover of the Sangkub watershed decreased substantially, whereas the non-vegetated area increased gradually over time.</p>

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Kenkel, N. C. "Structure and dynamics of jack pine stands near Elk Lake, Ontario: a multivariate approach". Canadian Journal of Botany 64, n. 3 (1 marzo 1986): 486–97. http://dx.doi.org/10.1139/b86-063.

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Multivariate techniques were utilized to examine even-aged jack pine stands on upland sandy sites at the southern edge of the boreal forest near Elk Lake, Ontario. Cluster analysis of 180 stands led to the recognition of 10 vegetation types, each showing a unique combination of floristics, physiognomy, and environmental components. Classification of common species led to the recognition of five ecological groupings, which show varying degrees of association with the vegetation types. Nonmetric multidimensional scaling of the stands suggested a vegetational continuum in response to overall moisture availability. A corresponding ordination of common species indicated the development of interspecific associations related to soil moisture conditions. It is suggested that the vegetational composition of upland jack pine forests is determined by both probabilistic and deterministic effects, and this is discussed in the context of vegetation structure and dynamics.

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34

Gouveia, C. M., A. Bastos, R. M. Trigo e C. C. DaCamara. "Drought impacts on vegetation in the pre- and post-fire events over Iberian Peninsula". Natural Hazards and Earth System Sciences 12, n. 10 (19 ottobre 2012): 3123–37. http://dx.doi.org/10.5194/nhess-12-3123-2012.

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Abstract. The present work aims to study the combined effect of drought and large wildfires in the Iberian Peninsula relying on remotely sensed data of vegetation dynamics and leaf moisture content, in particular monthly NDVI, NDWI and NDDI time series from 1999–2009, derived from VEGETATION dataset. The impact of the exceptional 2004/2005 drought on vegetation was assessed for vegetation recovering from the extraordinary fire season of 2003 and on the conditions that contributed to the onsetting of the fire season of 2005. Drought severity was estimated by the cumulative negative effect on photosynthetic activity (NDVI) and vegetation dryness (NDDI), with about 2/3 of Iberian Peninsula presenting vegetative stress and low water availability conditions, in spring and early summer of 2005. Furthermore, NDDI has shown to be very useful to assess drought, since it combines information on vegetation and water conditions. Moreover, we show that besides looking at the inter-annual variability of NDVI and NDDI, it is useful to evaluate intra-annual changes (δNDVI and δNDDI), as indicators of change in vegetation greenness, allowing a detailed picture of the ability of the different land-cover types to resist to short-term dry conditions. In order to assess drought impact on post-fire regeneration, recovery times were evaluated by a mono-parametric model based on NDVI data and values corresponding to drought months were set to no value. Drought has shown to delay recovery times for several months in all the selected scars from 2003. The analysis of vegetation dynamics and fire selectivity in 2005 suggests that fires tended to occur in pixels presenting lower vegetative and water stress conditions during spring and early summer months. Additionally, pre-fire vegetation dynamics, in particular vegetation density and water availability during spring and early summer, has shown to influence significantly the levels of fire damage. These results stress the role of fuel availability in fire occurrence and impact on the Iberian Peninsula.

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Maneta, M. P., e N. L. Silverman. "A Spatially Distributed Model to Simulate Water, Energy, and Vegetation Dynamics Using Information from Regional Climate Models". Earth Interactions 17, n. 11 (1 agosto 2013): 1–44. http://dx.doi.org/10.1175/2012ei000472.1.

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Abstract Studies seeking to understand the impacts of climate variability and change on the hydrology of a region need to take into account the dynamics of vegetation and its interaction with the hydrologic and energy cycles. Yet, most of the hydrologic models used for these kinds of studies assume that vegetation is static. This paper presents a dynamic, spatially explicit model that couples a vertical energy balance scheme (surface and canopy layer) to a hydrologic model and a forest growth component to capture the dynamic interactions between energy, vegetation, and hydrology at hourly to daily time scales. The model is designed to be forced with outputs from regional climate models. Lateral water transfers are simulated using a 1D kinematic wave model. Infiltration is simulated using the Green and Ampt approximation to Richard's equation. The dynamics of soil moisture and energy drives carbon assimilation and forest growth, which in turn affect the distribution of energy and water through leaf dynamics by altering light interception, shading, and enhanced transpiration. The model is demonstrated in two case studies simulating energy, water, and vegetation dynamics at two different spatial and temporal scales.

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Delire, Christine, Nathalie de Noblet-Ducoudré, Adriana Sima e Isabelle Gouirand. "Vegetation Dynamics Enhancing Long-Term Climate Variability Confirmed by Two Models". Journal of Climate 24, n. 9 (1 maggio 2011): 2238–57. http://dx.doi.org/10.1175/2010jcli3664.1.

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Abstract Two different coupled climate–vegetation models, the Community Climate Model version 3 coupled to the Integrated Biosphere Simulator (CCM3–IBIS) and the Laboratoire de Météorologie Dynamique’s climate model coupled to the Organizing Carbon and Hydrology in Dynamic Ecosystems model (LMDz–ORCHIDEE), are used to study the effects of vegetation dynamics on climate variability. Two sets of simulations of the preindustrial climate are performed using fixed climatological sea surface temperatures: one set taking into account vegetation cover dynamics and the other keeping the vegetation cover fixed. Spectral analysis of the simulated precipitation and temperature over land shows that for both models the interactions between vegetation dynamics and the atmosphere enhance the low-frequency variability of the biosphere–atmosphere system at time scales ranging from a few years to a century. Despite differences in the magnitude of the signal between the two models, this confirms that vegetation dynamics introduces a long-term memory into the climate system by slowly modifying the physical characteristics of the land surface (albedo, roughness evapotranspiration). Unrealistic modeled feedbacks between the vegetation and the atmosphere would cast doubts on this result. The simulated feedback processes in the models used in this work are compared to the observed using a recently developed statistical approach. The models simulate feedbacks of the right sign and order of magnitude over large regions of the globe: positive temperature feedback in the mid- to high latitudes, negative feedback in semiarid regions, and positive precipitation feedback in semiarid regions. The models disagree in the tropics, where there is no statistical significance in the observations. The realistic modeled vegetation–atmosphere feedback gives us confidence that the vegetation dynamics enhancement of the long-term climate variability is not a model artifact.

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Zribi, Mehrez, Erwan Motte, Pascal Fanise e Walid Zouaoui. "Low-Cost GPS Receivers for the Monitoring of Sunflower Cover Dynamics". Journal of Sensors 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/6941739.

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The aim of this research is to analyze the potential use of Global Navigation Satellite System (GNSS) signals for the monitoring of in situ vegetation characteristics. An instrument, based on the use of a pair of low-cost receivers and antennas, providing continuous measurements of all the available Global Positioning System (GPS) satellite signals is proposed for the determination of signal attenuation caused by a sunflower cover. Experimental campaigns with this instrument, combined with ground truth measurements of the vegetation, were performed over a nonirrigated sunflower test field for a period of more than two months, corresponding to a significant portion of the vegetation cycle. A method is proposed for the analysis of the signal attenuation data as a function of elevation and azimuth angles. A high correlation is observed between the vegetation’s water content and the GPS signals attenuation, and an empirical modeling is tested for the retrieval of signal behavior as a function of vegetation water content (VWC). The VWC was estimated from GNSS signals on a daily basis, over the full length of the study period.

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Priya, M. V., R. Kalpana, S. Pazhanivelan, R. Kumaraperumal, K. P. Ragunath, G. Vanitha, Ashmitha Nihar, P. J. Prajesh e Vasumathi V. "Monitoring vegetation dynamics using multi-temporal Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images of Tamil Nadu". Journal of Applied and Natural Science 15, n. 3 (19 settembre 2023): 1170–77. http://dx.doi.org/10.31018/jans.v15i3.4803.

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Vegetation indices serve as an essential tool in monitoring variations in vegetation. The vegetation indices used often, viz., normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were computed from MODIS vegetation index products. The present study aimed to monitor vegetation's seasonal dynamics by using time series NDVI and EVI indices in Tamil Nadu from 2011 to 2021. Two products characterize the global range of vegetation states and processes more effectively. The data sources were processed and the values of NDVI and EVI were extracted using ArcGIS software. There was a significant difference in vegetation intensity and status of vegetation over time, with NDVI having a larger value than EVI, indicating that biomass intensity varies over time in Tamil Nadu. Among the land cover classes, the deciduous forest showed the highest mean values for NDVI (0.83) and EVI (0.38), followed by cropland mean values of NDVI (0.71) and EVI (0.31) and the lowest NDVI (0.68) and EVI (0.29) was recorded in the scrubland. The study demonstrated that vegetation indices extracted from MODIS offered valuable information on vegetation status and condition at a short temporal time period.

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Najafi, Z., P. Fatehi e A. A. Darvishsefat. "VEGETATION DYNAMICS TREND USING SATELLITE TIME SERIES IMAGERY". ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W18 (18 ottobre 2019): 783–88. http://dx.doi.org/10.5194/isprs-archives-xlii-4-w18-783-2019.

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Abstract. In this study, the trend of vegetation dynamics in Kermanshah city assessed using NDVI MOD13Q1 product over the time period of 2000–2017. Based on time series imagery the pick of vegetation phenology stage (maximum NDVI) identified, then the trend of vegetation dynamic was investigated using the Ordinary Least Square regression and the Theil-Sen approaches. To generate a pixel-wise trend map, a pixel-based vegetation dynamics was also implemented. A non-parametric Mann-Kendall statistics approach was used to examine a statistically significant trend analysis. The mean maximum NDVI observed for the first half or second half of April. Trend analysis using regression and Theil-Sen methods indicated a no-trend in vegetation fractions. The pixel-based trend assessment using regression showed that a 50% of the study area faced a positive trend and reaming part faced a negative trend. The Theil-Sen method revealed the no-trend for a large majority of area. The Mann-Kendall test indicated that only 20 percent of the area shows a statistically significant trend.

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40

Saco, P. M., G. R. Willgoose e G. R. Hancock. "Eco-geomorphology and vegetation patterns in arid and semi-arid regions". Hydrology and Earth System Sciences Discussions 3, n. 4 (30 agosto 2006): 2559–93. http://dx.doi.org/10.5194/hessd-3-2559-2006.

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Abstract. The interaction between vegetation and hydrologic processes is particularly tight in water-limited environments where a positive-feedback links water redistribution and vegetation. The vegetation of these systems is commonly patterned, that is, arranged in a two phase mosaic composed of patches with high biomass cover interspersed within a low-cover or bare soil component. These patterns are strongly linked to the redistribution of runoff and resources from source areas (bare patches) to sink areas (vegetation patches) and play an important role in controlling erosion. In this paper a new modeling framework that couples landform evolution and dynamic vegetation for water-limited ecosystems is presented. The model explicitly accounts for the dynamics of runon-runoff areas that controls the evolution of vegetation and erosion/deposition patterns in water limited ecosystems. The analysis presented here focuses on the interaction between vegetation patterns, flow dynamics and sediment redistribution for areas with mild slopes where sheet flow occurs and banded vegetation patterns emerge. Model results successfully reproduce the dynamics of both migrating and stationary banded vegetation patterns (commonly known as tiger bush). Modeling results show strong feedbacks effects between vegetation patterns, runoff redistribution and geomorphic changes. The success at generating not only the observed patterns of vegetation but also patterns of runoff and erosion redistribution, which gives rise to modeled microtopography similar to that observed in several field sites, suggests that the hydrologic and erosion mechanisms represented in the model are correctly capturing the essential processes driving these ecosystems.

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41

Lyubenova, Mariyana, Roumen Nedkov, Nadejda Georgieva e Snejana Dineva. "Space Models of Oak Vegetation Dynamics in Protected Zone, Bulgaria". Indian Journal of Applied Research 4, n. 7 (1 ottobre 2011): 23–30. http://dx.doi.org/10.15373/2249555x/july2014/7.

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42

Mueller-Dombois, Dieter. "Vegetation dynamics and the evolution of Metrosideros polymorpha in Hawaii". Phytocoenologia 24, n. 1-4 (8 aprile 1994): 609–14. http://dx.doi.org/10.1127/phyto/24/1994/609.

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43

Forkel, M., N. Carvalhais, S. Schaphoff, W. v. Bloh, M. Migliavacca, M. Thurner e K. Thonicke. "Identifying environmental controls on vegetation greenness phenology through model–data integration". Biogeosciences 11, n. 23 (11 dicembre 2014): 7025–50. http://dx.doi.org/10.5194/bg-11-7025-2014.

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Abstract. Existing dynamic global vegetation models (DGVMs) have a limited ability in reproducing phenology and decadal dynamics of vegetation greenness as observed by satellites. These limitations in reproducing observations reflect a poor understanding and description of the environmental controls on phenology, which strongly influence the ability to simulate longer-term vegetation dynamics, e.g. carbon allocation. Combining DGVMs with observational data sets can potentially help to revise current modelling approaches and thus enhance the understanding of processes that control seasonal to long-term vegetation greenness dynamics. Here we implemented a new phenology model within the LPJmL (Lund Potsdam Jena managed lands) DGVM and integrated several observational data sets to improve the ability of the model in reproducing satellite-derived time series of vegetation greenness. Specifically, we optimized LPJmL parameters against observational time series of the fraction of absorbed photosynthetic active radiation (FAPAR), albedo and gross primary production to identify the main environmental controls for seasonal vegetation greenness dynamics. We demonstrated that LPJmL with new phenology and optimized parameters better reproduces seasonality, inter-annual variability and trends of vegetation greenness. Our results indicate that soil water availability is an important control on vegetation phenology not only in water-limited biomes but also in boreal forests and the Arctic tundra. Whereas water availability controls phenology in water-limited ecosystems during the entire growing season, water availability co-modulates jointly with temperature the beginning of the growing season in boreal and Arctic regions. Additionally, water availability contributes to better explain decadal greening trends in the Sahel and browning trends in boreal forests. These results emphasize the importance of considering water availability in a new generation of phenology modules in DGVMs in order to correctly reproduce observed seasonal-to-decadal dynamics of vegetation greenness.

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44

Forkel, M., N. Carvalhais, S. Schaphoff, W. v. Bloh, M. Migliavacca, M. Thurner e K. Thonicke. "Identifying environmental controls on vegetation greenness phenology through model-data integration". Biogeosciences Discussions 11, n. 7 (17 luglio 2014): 10917–1025. http://dx.doi.org/10.5194/bgd-11-10917-2014.

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Abstract. Existing dynamic global vegetation models (DGVMs) have a~limited ability in reproducing phenology and decadal dynamics of vegetation greenness as observed by satellites. These limitations in reproducing observations reflect a poor understanding and description of the environmental controls on phenology, which strongly influence the ability to simulate longer term vegetation dynamics, e.g. carbon allocation. Combining DGVMs with observational data sets can potentially help to revise current modelling approaches and thus to enhance the understanding of processes that control seasonal to long-term vegetation greenness dynamics. Here we implemented a~new phenology model within the LPJmL (Lund Potsdam Jena managed lands) DGVM and integrated several observational data sets to improve the ability of the model in reproducing satellite-derived time series of vegetation greenness. Specifically, we optimized LPJmL parameters against observational time series of the fraction of absorbed photosynthetic active radiation (FAPAR), albedo and gross primary production to identify the main environmental controls for seasonal vegetation greenness dynamics. We demonstrated that LPJmL with new phenology and optimized parameters better reproduces seasonality, inter-annual variability and trends of vegetation greenness. Our results indicate that soil water availability is an important control on vegetation phenology not only in water-limited biomes but also in boreal forests and the arctic tundra. Whereas water availability controls phenology in water-limited ecosystems during the entire growing season, water availability co-modulates jointly with temperature the beginning of the growing season in boreal and arctic regions. Additionally, water availability contributes to better explain decadal greening trends in the Sahel and browning trends in boreal forests. These results emphasize the importance of considering water availability in a new generation of phenology modules in DGVMs in order to correctly reproduce observed seasonal to decadal dynamics of vegetation greenness.

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Rossi, Mattia, Georg Niedrist, Sarah Asam, Giustino Tonon, Enrico Tomelleri e Marc Zebisch. "A Comparison of the Signal from Diverse Optical Sensors for Monitoring Alpine Grassland Dynamics". Remote Sensing 11, n. 3 (1 febbraio 2019): 296. http://dx.doi.org/10.3390/rs11030296.

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Grasslands cover up to 40% of the mountain areas globally and 23% of the European Alps and affect numerous key ecological processes. An increasing number of optical sensors offer a great opportunity to monitor and address dynamic changes in the growth and status of grassland vegetation due to climatic and anthropogenic influences. Vegetation indices (VI) calculated from optical sensor data are a powerful tool in analyzing vegetation dynamics. However, different sensors have their own characteristics, advantages, and challenges in monitoring vegetation over space and time that require special attention when compared to or combined with each other. We used the Normalized Difference Vegetation Index (NDVI) derived from handheld spectrometers, station-based Spectral Reflectance Sensors (SRS), and Phenocams as well as the spaceborne Sentinel-2 Multispectral Instrument (MSI) for assessing growth and dynamic changes in four alpine meadows. We analyzed the similarity of the NDVI on diverse spatial scales and to what extent grassland dynamics of alpine meadows can be detected. We found that NDVI across all sensors traces the growing phases of the vegetation although we experienced a notable variability in NDVI signals among sensors and differences among the sites and plots. We noticed differences in signal saturation, sensor specific offsets, and in the detectability of short-term events. These NDVI inconsistencies depended on sensor-specific spatial and spectral resolutions and acquisition geometries, as well as on grassland management activities and vegetation growth during the year. We demonstrated that the combination of multiple-sensors enhanced the possibility for detecting short-term dynamic changes throughout the year for each of the stations. The presented findings are relevant for building and evaluating a combined sensor approach for consistent vegetation monitoring.

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Tamás, András, Elza Kovács, Éva Horváth, Csaba Juhász, László Radócz, Tamás Rátonyi e Péter Ragán. "Assessment of NDVI Dynamics of Maize (Zea mays L.) and Its Relation to Grain Yield in a Polyfactorial Experiment Based on Remote Sensing". Agriculture 13, n. 3 (15 marzo 2023): 689. http://dx.doi.org/10.3390/agriculture13030689.

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Remote sensing is an efficient tool to detect vegetation heterogeneity and dynamics of crop development in real-time. In this study, the performance of three maize hybrids (Fornad FAO-420, Merida FAO-380, and Corasano FAO-490-510) was monitored as a function of nitrogen dose (0, 80 and 160 kg N ha−1), soil tillage technologies (winter ploughing, strip-tillage, and ripping), and irrigation (rainfed and 3 × 25 mm) in a warm temperature dry region of East-Central Europe. Dynamics of the Normalized Difference Vegetation Index (NDVI) were followed in the vegetation period of 2021, a year of drought, by using sensors mounted on an unmanned aerial vehicle. N-fertilization resulted in significantly higher NDVI throughout the entire vegetation period (p < 0.001) in each experimental combination. A significant positive effect of irrigation was observed on the NDVI during the drought period (77–141 days after sowing). For both the tillage technologies and hybrids, NDVI was found to be significantly different between treatments, but showing different dynamics. Grain yield was in strong positive correlation with the NDVI between the late vegetative and the early generative stages (r = 0.80–0.84). The findings suggest that the NDVI dynamics is an adequate indicator for evaluating the impact of different treatments on plant development and yield prediction.

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Hua, Li, Huidong Wang, Haigang Sui, Brian Wardlow, Michael J. Hayes e Jianxun Wang. "Mapping the Spatial-Temporal Dynamics of Vegetation Response Lag to Drought in a Semi-Arid Region". Remote Sensing 11, n. 16 (10 agosto 2019): 1873. http://dx.doi.org/10.3390/rs11161873.

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Drought, as an extreme climate event, affects the ecological environment for vegetation and agricultural production. Studies of the vegetative response to drought are paramount to providing scientific information for drought risk mitigation. In this paper, the spatial-temporal pattern of drought and the response lag of vegetation in Nebraska were analyzed from 2000 to 2015. Based on the long-term Daymet data set, the standard precipitation index (SPI) was computed to identify precipitation anomalies, and the Gaussian function was applied to obtain temperature anomalies. Vegetation anomaly was identified by dynamic time warping technique using a remote sensing Normalized Difference Vegetation Index (NDVI) time series. Finally, multilayer correlation analysis was applied to obtain the response lag of different vegetation types. The results show that Nebraska suffered severe drought events in 2002 and 2012. The response lag of vegetation to drought typically ranged from 30 to 45 days varying for different vegetation types and human activities (water use and management). Grasslands had the shortest response lag (~35 days), while forests had the longest lag period (~48 days). For specific crop types, the response lag of winter wheat varied among different regions of Nebraska (35–45 days), while soybeans, corn and alfalfa had similar response lag times of approximately 40 days.

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Uhl, Christopher, Kathleen Clark, Nelda Dezzeo e Pedro Maquirino. "Vegetation Dynamics in Amazonian Treefall Gaps". Ecology 69, n. 3 (giugno 1988): 751–63. http://dx.doi.org/10.2307/1941024.

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Raposo, Mauro, e Carlos Pinto-Gomes. "Dynamics of Vegetation and Climate Change". Environments 9, n. 3 (17 marzo 2022): 36. http://dx.doi.org/10.3390/environments9030036.

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A set of climatic events that have occurred throughout the Paleolithic ages and all the way up to the present day have led to profound changes in the biosphere, such as periods of glaciation and global warming [...]

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Govorkov, Denis Aleksandrovich, Victor Petrovich Novikov, Ilya Georgievich Solovyev e Vladimir Romanovich Tsibulsky. "Interval analysis of vegetation cover dynamics". Computer Research and Modeling 12, n. 5 (ottobre 2020): 1191–205. http://dx.doi.org/10.20537/2076-7633-2020-12-5-1191-1205.

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