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Spectral measures and mixed models as valuable tools for investigating controls on land surface phenology in high arctic Greenland.

Tamstorf MP, Illeris L, Hansen BU, Wisz M - BMC Ecol. (2007)

Bottom Line: We find several non-linear growth responses to the environmental variables.We conclude that the uses of GAMMs are valuable for investigating growth dynamics in the Arctic.This indicates that although greening might occur wide-spread in the Arctic there are variations on the local scale that might influence the regional trends on the longer term.

View Article: PubMed Central - HTML - PubMed

Affiliation: University of Aarhus, National Environmental Research Institute, Dep, for Arctic Environment, Frederiksborgvej 399, PO Box 358, DK-4000 Roskilde, Denmark. mpt@dmu.dk

ABSTRACT

Background: Changes in land surface phenology are of major importance to the understanding of the impact of recent and future climate changes in the Arctic. This paper presents an extensive study from Zackenberg Ecological Research Operations (ZERO) where snow melt, climate and growing season characteristics of six major high arctic vegetation types has been monitored during 1999 to 2005. We investigate the growth dynamics for dry, mesic and wet types using hand held measurements of far red normalised difference vegetation index (NDVI-FR) and generalized additive mixed models (GAMM).

Results: Snow melt and temperature are of major importance for the timing of the maximum growth as well as for the seasonal growth. More than 85% of the variance in timing of the maximum growth is explained by the models and similar for the seasonal growth of mesic and wet vegetation types. We find several non-linear growth responses to the environmental variables.

Conclusion: We conclude that the uses of GAMMs are valuable for investigating growth dynamics in the Arctic. Contrary to several other studies in the Arctic we found a significant decreasing trend of the seasonally integrated NDVI-FR (SINDVI) in some vegetation types. This indicates that although greening might occur wide-spread in the Arctic there are variations on the local scale that might influence the regional trends on the longer term.

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Zackenberg valley area and location of NDVI-FR plots. Location of the Zackenberg Ecological Research Operations (ZERO) station and the climate station (star) is shown. The NDVI-FR plots shown as triangles have not been used in this study due to very early snow melt (see text). NDVI-FR plots (naming, area etc) are described in detail in Meltofte and Berg (2004). Background image is a grey-scale ortho photo from 7 August 2000.
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Figure 1: Zackenberg valley area and location of NDVI-FR plots. Location of the Zackenberg Ecological Research Operations (ZERO) station and the climate station (star) is shown. The NDVI-FR plots shown as triangles have not been used in this study due to very early snow melt (see text). NDVI-FR plots (naming, area etc) are described in detail in Meltofte and Berg (2004). Background image is a grey-scale ortho photo from 7 August 2000.

Mentions: In this paper we present a seven year field study of land surface phenology in the High Arctic and use mixed models to investigate the possible controls of the growth dynamics. The NDVI-FR measurements are obtained from 26 individual plots within the Zackenberg Ecological Research Operations (ZERO) area (Figure 1) using a hand held Skye Instruments sensor at six vegetation types that range over dry, mesic and wet types. This sensor uses the red and far red bands instead of the traditional red and near-infrared bands. We investigate the seasonally integrated far red normalised difference vegetation index (NDVI-FR) using the nomenclature of Hope et al. (SINDVI) [21], the timing of the maximum NDVI-FR (DOYmax) and the level of maximum NDVI-FR (MaxNDVI). We hypothesize that the main explanatory variables controlling the seasonal growth dynamics of the six main vegetation types are timing of the snow melt, temperature during the growing season, light in the form of photosynthetic active radiation, rain during the growing season, the general state of the vegetation as expressed by the SINDVI in the previous growing season and the temperature during the previous year growing season. We expect that the different vegetation types will show different response from the explanatory variables.


Spectral measures and mixed models as valuable tools for investigating controls on land surface phenology in high arctic Greenland.

Tamstorf MP, Illeris L, Hansen BU, Wisz M - BMC Ecol. (2007)

Zackenberg valley area and location of NDVI-FR plots. Location of the Zackenberg Ecological Research Operations (ZERO) station and the climate station (star) is shown. The NDVI-FR plots shown as triangles have not been used in this study due to very early snow melt (see text). NDVI-FR plots (naming, area etc) are described in detail in Meltofte and Berg (2004). Background image is a grey-scale ortho photo from 7 August 2000.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2164935&req=5

Figure 1: Zackenberg valley area and location of NDVI-FR plots. Location of the Zackenberg Ecological Research Operations (ZERO) station and the climate station (star) is shown. The NDVI-FR plots shown as triangles have not been used in this study due to very early snow melt (see text). NDVI-FR plots (naming, area etc) are described in detail in Meltofte and Berg (2004). Background image is a grey-scale ortho photo from 7 August 2000.
Mentions: In this paper we present a seven year field study of land surface phenology in the High Arctic and use mixed models to investigate the possible controls of the growth dynamics. The NDVI-FR measurements are obtained from 26 individual plots within the Zackenberg Ecological Research Operations (ZERO) area (Figure 1) using a hand held Skye Instruments sensor at six vegetation types that range over dry, mesic and wet types. This sensor uses the red and far red bands instead of the traditional red and near-infrared bands. We investigate the seasonally integrated far red normalised difference vegetation index (NDVI-FR) using the nomenclature of Hope et al. (SINDVI) [21], the timing of the maximum NDVI-FR (DOYmax) and the level of maximum NDVI-FR (MaxNDVI). We hypothesize that the main explanatory variables controlling the seasonal growth dynamics of the six main vegetation types are timing of the snow melt, temperature during the growing season, light in the form of photosynthetic active radiation, rain during the growing season, the general state of the vegetation as expressed by the SINDVI in the previous growing season and the temperature during the previous year growing season. We expect that the different vegetation types will show different response from the explanatory variables.

Bottom Line: We find several non-linear growth responses to the environmental variables.We conclude that the uses of GAMMs are valuable for investigating growth dynamics in the Arctic.This indicates that although greening might occur wide-spread in the Arctic there are variations on the local scale that might influence the regional trends on the longer term.

View Article: PubMed Central - HTML - PubMed

Affiliation: University of Aarhus, National Environmental Research Institute, Dep, for Arctic Environment, Frederiksborgvej 399, PO Box 358, DK-4000 Roskilde, Denmark. mpt@dmu.dk

ABSTRACT

Background: Changes in land surface phenology are of major importance to the understanding of the impact of recent and future climate changes in the Arctic. This paper presents an extensive study from Zackenberg Ecological Research Operations (ZERO) where snow melt, climate and growing season characteristics of six major high arctic vegetation types has been monitored during 1999 to 2005. We investigate the growth dynamics for dry, mesic and wet types using hand held measurements of far red normalised difference vegetation index (NDVI-FR) and generalized additive mixed models (GAMM).

Results: Snow melt and temperature are of major importance for the timing of the maximum growth as well as for the seasonal growth. More than 85% of the variance in timing of the maximum growth is explained by the models and similar for the seasonal growth of mesic and wet vegetation types. We find several non-linear growth responses to the environmental variables.

Conclusion: We conclude that the uses of GAMMs are valuable for investigating growth dynamics in the Arctic. Contrary to several other studies in the Arctic we found a significant decreasing trend of the seasonally integrated NDVI-FR (SINDVI) in some vegetation types. This indicates that although greening might occur wide-spread in the Arctic there are variations on the local scale that might influence the regional trends on the longer term.

Show MeSH
Related in: MedlinePlus