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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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Relationship between NDVI-FR and NDVI. Each data point is marked by a letter indicating the vegetation type for that plot measurement. C: Cassiope heath, D: Dryas heath, F: Fen, G: Grassland, S: Salix heath. The linear relation is shown in solid (R2 = 0.79, n = 390, p < 0.0001) and the 1:1 line in dashed.
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Figure 6: Relationship between NDVI-FR and NDVI. Each data point is marked by a letter indicating the vegetation type for that plot measurement. C: Cassiope heath, D: Dryas heath, F: Fen, G: Grassland, S: Salix heath. The linear relation is shown in solid (R2 = 0.79, n = 390, p < 0.0001) and the 1:1 line in dashed.

Mentions: All data used in this study originated from the BioBasis and ClimateBasis monitoring programs under Zackenberg Ecological Research Operations (ZERO). Field measurements were done in 26 plots scattered around in the valley (Figure 1) covering the six major vegetation types: Fell field, Dryas heath, Cassiope heath, Salix heath, grassland and fen. All plots were closer than 1 km from the central climate station. This study included 22 plant plots from the BioBasis program where NDVI-FR is measured regularly. At Dry1, Sil1, Sil2 and Sal1, the snow melted so early that the time of snow melt was not possible to estimate. The plots varied in size from 2 m2 to 300 m2 and were not all homogenously vegetated. They differed in size because the plots were originally intended for flowering studies of species monitored under most of the occurring habitat conditions (biotic and abiotic), with a possibility of counting 50 or more flowers at each location. NDVI-FR measurements were done in each corner of 4 or 8 sub areas in each plot depending on the setup of the plot [42]. Measurements were performed once every week during the field season (1 June to 31 August) from 1999 to 2005. A Skye SKR110 instrument with narrow band filters centred at 660 nm and 730 nm were used for the measurements. The field of view for the instrument was approximately 3 m2 when used at a height of 1 m. Each measurement was carried out at the same position with nadir viewing. The instrument was calibrated every second year to avoid drift. Standard NDVI use measurements with a band centre around 900 nm instead of 730 nm. Hence, this paper therefore uses NDVI-FR instead of NDVI. Measurements in 2004 of both NDVI-FR (Skye sensor) and NDVI (ASD inc. Fieldspec Hand-held radiometer) showed a 79% correlation between the datasets (R2 = 0.79, n = 390, p < 0.0001) (Figure 6). Hence, 21% of the variance cannot be explained by the other parameter. This is due to the use of different instruments and especially the location of the far-red (FR) band. FR is situated on the red-edge slope. Any changes in NDVI-FR compared to NDVI other than from changes in absorption by pigments will therefore be due to changes in the position of the red-edge slope. Senescence and water stress have been shown to cause a blue shift of the red edge [43] resulting in a higher FR and hence a NDVI-FR increase. Near-infrared (NIR) bands on the other hand will experience a decrease during senescence leading to opposite trends in the two indices although depending also on the slope of the red-edge and absorption in the red bands. However, the two indices are closely related and results from this NDVI-FR study are therefore also valuable for comparison with similar NDVI studies.


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)

Relationship between NDVI-FR and NDVI. Each data point is marked by a letter indicating the vegetation type for that plot measurement. C: Cassiope heath, D: Dryas heath, F: Fen, G: Grassland, S: Salix heath. The linear relation is shown in solid (R2 = 0.79, n = 390, p < 0.0001) and the 1:1 line in dashed.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 6: Relationship between NDVI-FR and NDVI. Each data point is marked by a letter indicating the vegetation type for that plot measurement. C: Cassiope heath, D: Dryas heath, F: Fen, G: Grassland, S: Salix heath. The linear relation is shown in solid (R2 = 0.79, n = 390, p < 0.0001) and the 1:1 line in dashed.
Mentions: All data used in this study originated from the BioBasis and ClimateBasis monitoring programs under Zackenberg Ecological Research Operations (ZERO). Field measurements were done in 26 plots scattered around in the valley (Figure 1) covering the six major vegetation types: Fell field, Dryas heath, Cassiope heath, Salix heath, grassland and fen. All plots were closer than 1 km from the central climate station. This study included 22 plant plots from the BioBasis program where NDVI-FR is measured regularly. At Dry1, Sil1, Sil2 and Sal1, the snow melted so early that the time of snow melt was not possible to estimate. The plots varied in size from 2 m2 to 300 m2 and were not all homogenously vegetated. They differed in size because the plots were originally intended for flowering studies of species monitored under most of the occurring habitat conditions (biotic and abiotic), with a possibility of counting 50 or more flowers at each location. NDVI-FR measurements were done in each corner of 4 or 8 sub areas in each plot depending on the setup of the plot [42]. Measurements were performed once every week during the field season (1 June to 31 August) from 1999 to 2005. A Skye SKR110 instrument with narrow band filters centred at 660 nm and 730 nm were used for the measurements. The field of view for the instrument was approximately 3 m2 when used at a height of 1 m. Each measurement was carried out at the same position with nadir viewing. The instrument was calibrated every second year to avoid drift. Standard NDVI use measurements with a band centre around 900 nm instead of 730 nm. Hence, this paper therefore uses NDVI-FR instead of NDVI. Measurements in 2004 of both NDVI-FR (Skye sensor) and NDVI (ASD inc. Fieldspec Hand-held radiometer) showed a 79% correlation between the datasets (R2 = 0.79, n = 390, p < 0.0001) (Figure 6). Hence, 21% of the variance cannot be explained by the other parameter. This is due to the use of different instruments and especially the location of the far-red (FR) band. FR is situated on the red-edge slope. Any changes in NDVI-FR compared to NDVI other than from changes in absorption by pigments will therefore be due to changes in the position of the red-edge slope. Senescence and water stress have been shown to cause a blue shift of the red edge [43] resulting in a higher FR and hence a NDVI-FR increase. Near-infrared (NIR) bands on the other hand will experience a decrease during senescence leading to opposite trends in the two indices although depending also on the slope of the red-edge and absorption in the red bands. However, the two indices are closely related and results from this NDVI-FR study are therefore also valuable for comparison with similar NDVI studies.

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