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Spatiotemporal variation of NDVI in the vegetation growing season in the source region of the yellow river, China / Mingyue Wang in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)
[article]
Titre : Spatiotemporal variation of NDVI in the vegetation growing season in the source region of the yellow river, China Type de document : Article/Communication Auteurs : Mingyue Wang, Auteur ; Jun’e Fu, Auteur ; Zhitao Wu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 17 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] coefficient de corrélation
[Termes IGN] données météorologiques
[Termes IGN] données spatiotemporelles
[Termes IGN] écosystème
[Termes IGN] Fleuve jaune (Chine)
[Termes IGN] image Aqua-MODIS
[Termes IGN] image SPOT
[Termes IGN] image Terra-MODIS
[Termes IGN] modèle de simulation
[Termes IGN] modèle dynamique
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] précipitation
[Termes IGN] série temporelle
[Termes IGN] température
[Termes IGN] variation saisonnièreRésumé : (auteur) Research on vegetation variation is an important aspect of global warming studies. The quantification of the relationship between vegetation change and climate change has become a central topic and challenge in current global change studies. The source region of the Yellow River (SRYR) is an appropriate area to study global change because of its unique natural conditions and vulnerable terrestrial ecosystem. Therefore, we chose the SRYR for a case study to determine the driving forces behind vegetation variation under global warming. Using the Normalized Difference Vegetation Index (NDVI) and climate data, we investigated the NDVI variation in the growing season in the region from 1998 to 2016 and its response to climate change based on trend analysis, the Mann–Kendall trend test and partial correlation analysis. Finally, an NDVI–climate mathematical model was built to predict the NDVI trends from 2020 to 2038. The results indicated the following: (1) over the past 19 years, the NDVI showed an increasing trend, with a growth rate of 0.00204/a. There was an upward trend in NDVI over 71.40% of the region. (2) Both the precipitation and temperature in the growing season showed upward trends over the last 19 years. NDVI was positively correlated with precipitation and temperature. The areas with significant relationships with precipitation covered 31.01% of the region, while those with significant relationships with temperature covered 56.40%. The sensitivity of the NDVI to temperature was higher than that to precipitation. Over half (56.58%) of the areas were found to exhibit negative impacts of human activities on the NDVI. (3) According to the simulation, the NDVI will increase slightly over the next 19 years, with a linear tendency of 0.00096/a. From the perspective of spatiotemporal changes, we combined the past and future variations in vegetation, which could adequately reflect the long-term vegetation trends. The results provide a theoretical basis and reference for the sustainable development of the natural environment and a response to vegetation change under the background of climate change in the study area. Numéro de notice : A2020-262 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9040282 Date de publication en ligne : 24/04/2020 En ligne : https://doi.org/10.3390/ijgi9040282 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95022
in ISPRS International journal of geo-information > vol 9 n° 4 (April 2020) . - 17 p.[article]Warming effects on morphological and physiological performances of four subtropical montane tree species / Yiyong Li in Annals of Forest Science, Vol 77 n° 1 (March 2020)
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Titre : Warming effects on morphological and physiological performances of four subtropical montane tree species Type de document : Article/Communication Auteurs : Yiyong Li, Auteur ; Yue Xu, Auteur ; Ting Wu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 11 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] changement climatique
[Termes IGN] croissance des arbres
[Termes IGN] diagnostic foliaire
[Termes IGN] effet thermique
[Termes IGN] forêt tropicale
[Termes IGN] hauteur des arbres
[Termes IGN] montagne
[Termes IGN] photosynthèse
[Termes IGN] phytobiologie
[Termes IGN] stress hydrique
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Key message: In a downward transplantation experiment, warming stimulated growth and photosynthesis of Schima superba Gardn. et Champ., Syzygium rehderianum Merr. et Perry and Itea chinensis Hook. et Arn. via increased stomatal conductance. Warming had no effect on growth of Machilus breviflora (Benth.) Hemsl., indicating species-specific differences in response to warming. Context: Climate change has been shown to shift species composition and community structure in subtropical forests. Thus, understanding the species-specific responses of growth and physiological processes to warming is essential. Aims:
To investigate how climate warming affects growth, morphological and physiological performance of co-occurring tree species when they are growing at different altitudes. Methods: Soils and 1-year-old seedlings of four subtropical co-occurring tree species (Schima superba Gardn. et Champ., Syzygium rehderianum Merr. et Perry, Itea chinensis Hook. et Arn. and Machilus breviflora (Benth.) Hemsl.) were transplanted to three altitudes (600 m, 300 m and 30 m a.s.l.), inducing an effective warming of 1.0 °C and 1.5 °C. Growth, morphological, and physiological performances of these seedlings were monitored. Results: When exposed to warmer conditions, aboveground growth of the four species except M. breviflora was strongly promoted, accompanied by increased light-saturated photosynthetic rate and stomatal conductance. Warming also significantly increased concentrations of non-structural carbohydrates in leaves of S. rehderianum and M. breviflora, stems of S. superba and S. rehderianum, and roots of I. chinensis. However, we did not detect any effect of warming on stomatal length and stomatal density. Conclusion:
Our results provide evidence that climate warming could have species-specific impacts on co-occurring tree species, which might subsequently shift species composition and forest structure.Numéro de notice : A2020-037 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0910-3 Date de publication en ligne : 10/01/2020 En ligne : https://doi.org/10.1007/s13595-019-0910-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94491
in Annals of Forest Science > Vol 77 n° 1 (March 2020) . - 11 p.[article]Can Carbon Sequestration in Tasmanian “Wet” Eucalypt Forests Be Used to Mitigate Climate Change? Forest Succession, the Buffering Effects of Soils, and Landscape Processes Must Be Taken into Account / Peter D. McIntosh in International journal of forestry research, vol 2020 ([01/02/2020])
[article]
Titre : Can Carbon Sequestration in Tasmanian “Wet” Eucalypt Forests Be Used to Mitigate Climate Change? Forest Succession, the Buffering Effects of Soils, and Landscape Processes Must Be Taken into Account Type de document : Article/Communication Auteurs : Peter D. McIntosh, Auteur ; James L. Hardcastle, Auteur ; Tobias Klöffe, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 16 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse forestière
[Termes IGN] changement climatique
[Termes IGN] écosystème forestier
[Termes IGN] Eucalyptus (genre)
[Termes IGN] forêt équatoriale
[Termes IGN] matière organique
[Termes IGN] peuplement mélangé
[Termes IGN] puits de carbone
[Termes IGN] Tasmanie
[Termes IGN] zone humide
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Small areas of the wetter parts of southeast Australia including Tasmania support high-biomass “wet” eucalypt forests, including “mixed” forests consisting of mature eucalypts up to 100 m high with a rainforest understorey. In Tasmania, mixed forests transition to lower biomass rainforests over time. In the scientific and public debate on ways to mitigate climate change, these forests have received attention for their ability to store large amounts of carbon (C), but the contribution of soil C stocks to the total C in these two ecosystems has not been systematically researched, and consequently, the potential of wet eucalypt forests to serve as long-term C sinks is uncertain. This study compared soil C stocks to 1 m depth at paired sites under rainforest and mixed forests and found that there was no detectable difference of mean total soil C between the two forest types, and on average, both contained about 200 Mg·ha−1 of C. Some C in subsoil under rainforests is 3000 years old and retains a chemical signature of pyrogenic C, detectable in NMR spectra, indicating that soil C stocks are buffered against the effects of forest succession. The mean loss of C in biomass as mixed forests transition to rainforests is estimated to be about 260 Mg·ha−1 over a c. 400-year period, so the mature mixed forest ecosystem emits about 0.65 Mg·ha−1·yr−1 of C during its transition to rainforest. For this reason and because of the risk of forest fires, setting aside large areas of wet eucalypt forests as reserves in order to increase landscape C storage is not a sound strategy for long-term climate change mitigation. Maintaining a mosaic of managed native forests, including regenerating eucalypts, mixed forests, rainforests, and reserves, is likely to be the best strategy for maintaining landscape C stocks. Numéro de notice : A2020-627 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1155/2020/6509659 Date de publication en ligne : 30/07/2020 En ligne : https://doi.org/10.1155/2020/6509659 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96030
in International journal of forestry research > vol 2020 [01/02/2020] . - 16 p.[article]Estimating wheat yields in Australia using climate records, satellite image time series and machine learning methods / Elisa Kamir in ISPRS Journal of photogrammetry and remote sensing, vol 160 (February 2020)
[article]
Titre : Estimating wheat yields in Australia using climate records, satellite image time series and machine learning methods Type de document : Article/Communication Auteurs : Elisa Kamir, Auteur ; François Waldner, Auteur ; Zvi Hochman, Auteur Année de publication : 2020 Article en page(s) : pp 124 - 135 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] Australie
[Termes IGN] blé (céréale)
[Termes IGN] carte agricole
[Termes IGN] climat
[Termes IGN] estimation de précision
[Termes IGN] fonction de base radiale
[Termes IGN] image satellite
[Termes IGN] modèle de croissance végétale
[Termes IGN] modèle non linéaire
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] régression
[Termes IGN] rendement agricole
[Termes IGN] série temporelle
[Termes IGN] variation saisonnièreRésumé : (Auteur) Closing the yield gap between actual and potential wheat yields in Australia is important to meet the growing global demand for food. The identification of hotspots of the yield gap, where the potential for improvement is the greatest, is a necessary step towards this goal. While crop growth models are well suited to quantify potential yields, they lack the ability to provide accurate large-scale estimates of actual yields, owing to the sheer quantity of data they require for parameterisation. In this context, we sought to provide accurate estimates of actual wheat yields across the Australian wheat belt based on machine-learning regression methods, climate records and satellite image time series. Out of nine base learners and two ensembles, support vector regression with radial basis function emerged as the single best learner (root mean square error of 0.55 t ha−1 and R2 of 0.77 at the pixel level). At national scale, this model explained 73% of the yield variability observed across statistical units. Benchmark approaches based on peak Normalised Difference Vegetation Index (NDVI) and on a harvest index were largely outperformed by the machine-learning regression models (R2 Numéro de notice : A2020-046 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.11.008 Date de publication en ligne : 20/12/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.11.008 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94556
in ISPRS Journal of photogrammetry and remote sensing > vol 160 (February 2020) . - pp 124 - 135[article]Réservation
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[article]
Titre : Impact of precipitation, air temperature and abiotic emissions on gross primary production in Mediterranean ecosystems in Europe Type de document : Article/Communication Auteurs : S. Bartsch, Auteur ; A.I. Stegehuis, Auteur ; C. Boissard, Auteur ; et al., Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] biomasse
[Termes IGN] climat méditerranéen
[Termes IGN] écosystème
[Termes IGN] Europe (géographie politique)
[Termes IGN] précipitation
[Termes IGN] production primaire brute
[Termes IGN] puits de carbone
[Termes IGN] température de l'air
[Termes IGN] teneur en carbone
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Mediterranean ecosystems are significant carbon sinks and are particularly sensitive to climate change. However, the carbon dynamics in such ecosystems are still not fully understood. An improved understanding of the drivers of carbon fixation by vegetation is needed to better predict how these ecosystems will respond to climate change. In this study, a large dataset collected through the FLUXNET network is used to estimate how the gross primary production (GPP) of different Mediterranean ecosystems was affected by air temperature and precipitation between 1996 and 2013. We showed that annual precipitation and temperature were not significant drivers of annual GPP. However, inter-annual variations of GPP seemed largely controlled by the precipitation during early spring (March–April). Late spring and early summer temperature also had a positive effect on annual GPP. We furthermore show that GPP may also have been influenced by both summer rainfall pulses and abiotic emissions due to carbonates precipitation/dissolution. Finally, the sensitivity of GPP in the Mediterranean region to climate drivers seemed not to be ecosystem-type dependent. Our results can provide general information for modeling exercises and improve future biomass projections on a regional scale. Numéro de notice : A2020-228 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s10342-019-01246-7 Date de publication en ligne : 30/11/2019 En ligne : https://doi.org/10.1007/s10342-019-01246-7 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94965
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