THE RESPONSE OF UK VEGETATION TO ELEVATED TEMPERATURES IN 2006: COUPLING ENVISAT MERIS TERRESTRIAL CHLOROPHYLL INDEX (MTCI) AND MEAN AIR TEMPERATURE

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1 THE RESPONSE OF UK VEGETATION TO ELEVATED TEMPERATURES IN 2006: COUPLING ENVISAT MERIS TERRESTRIAL CHLOROPHYLL INDEX (MTCI) AND MEAN AIR TEMPERATURE Samuel Almond a, Doreen S. Boyd b, Paul J. Curran c and Jadunandan Dash d a School of Conservation Sciences, Bournemouth University, Talbot Campus, Bournemouth BH12 5BB, UK salmond@bournemouth.ac.uk b School of Geography, University of Nottingham, University Park, Nottingham NG7 2RD, UK c Office of the Vice-Chancellor, Bournemouth University, Talbot Campus, Bournemouth BH12 5BB, UK d School of Geography, University of Southampton, Southampton SO17 1BJ, UK KEY WORDS: Envisat MTCI, index, vegetation growing season, phenology, senescence, chlorophyll, air temperature ABSTRACT: Climate is one of the key variables driving ecosystems at local to global scales. How and to what extent vegetation responds to climate variability is a challenging topic for global change analysis. Autumn 2006 was the warmest in the UK since records began in 1659 (Meteorological Office, 16th October 2006) and this delayed the seasonal senescence of vegetation. Earth observation data provides an opportunity to study this phenomenon and put it into the context of ecosystem dynamics over a longer time period. The European Space Agency (ESA) uses data recorded by the Medium Resolution Imaging Spectrometer (MERIS) in the red / NIR bands to produce an operational product called the MERIS Terrestrial Chlorophyll Index (MTCI). The MTCI is related to the position of the red edge in vegetation spectra and can be used to determine the chlorophyll content of vegetation and thus its phenology. The 2006 growing season was investigated using MTCI data. Weekly MTCI composites for were used to produce land-cover specific MTCI time series which were related to temporally-coincident temperature data. Analysis demonstrated that for forest and heath and grassland (i) the MTCI was sensitive to seasonal variation in inferred chlorophyll content, (ii) the high autumnal temperatures were related to an extended growing season and (ii) there was a strong relationship between seasonal temperature variation and MTCI. 1.1 Background 1. INTRODUCTION The most recent assessment report of the Intergovernmental Panel on Climate Change (IPCC 2001) predicted further increases in global mean temperature, climate variability and extreme events. Phenology is one of the main bio-indicators of climate change impacts on ecosystems (Schleip et al., 2006). Seasonal temperature change in temperate forests is known to start both tree growth and leafing (Sparks et al., 2005, Fisher et al., 2007) and senescence. The forecasted change in climate is likely to have consequences for land use practices (Thomas, 2006) and vegetation phenology is an important indicator of ecosystem response to climate change. It has been established that air temperature is the most important controlling factor related to trees phenology in the temperate latitudes, whereas precipitation and photoperiod play a less pronounced role in phenological development (Chen et al., 2005). Vegetation response to variation in seasonal temperature is likely to affect photosynthetic rates (Bassow and Bazzaz, 1998) however; autumn senescence in deciduous vegetation is triggered both by environmental conditions and leaf specific maturation processes. The effects of temperature on leaf senescence is difficult to identify because factors, such as air temperature, day length and rainfall, often change at the same time (Rosenthal and Camm, 1997). The ability to couple observations of vegetation phenology with climatic factors over large scales is vital to monitor, predict and manage impacts of climatic change on ecosystems. Remote sensing data have been used in the study of vegetation condition and seasonal vegetation dynamics for many years (Reed and Bradley, 2006). The ability to observe vegetation phenology remotely over large areas provides a unique opportunity to monitor the effects of climatic change on vegetated canopies at local to global scales. The vast majority of studies have used data from the Advanced Very High Resolution Radiometer (Zhang et al., 2006). A new generation of remote sensing data sources are now available and they improve greatly our ability to identify changes in ecosystem phenology. 1.2 Envisat MTCI One new remote sensing data source is the Envisat MERIS Terrestrial Chlorophyll Index (MTCI). The MTCI was designed to monitor vegetation condition via an estimation of chlorophyll content. Vegetation growth cycles can be characterised through changes in chlorophyll concentration and leaf area index, which determine chlorophyll content (Curran et al. 2007). Methods used to determine chlorophyll content from remote sensing data have focused upon locating the red edge position (REP) between the red absorption feature and the near infrared reflectance maxima of a vegetation reflectance spectrum (Curran et al. 2007). However, such methods are time-

2 consuming and are not accurate indicators of chlorophyll content at high chlorophyll contents. The MTCI overcomes the potential limitations of using the REP to derive chlorophyll content. It is calculated using the ratio of the difference in reflectance between band 10 and band 9 and the difference in reflectance between band 9 and band 8 of the MERIS standard band setting: Site New Forest National Park, Hampshire Vegetation type Ancient deciduous forest heath and grassland area of Bodmin Moor, Cornwall Wildwood, Kent heathland MTCI = R R / R R where R753.75, R708.75, R are reflectance in the centre wavelengths (nm) of the MERIS standard band setting. The MTCI is very simple to calculate yet it is sensitive to all and notably, high values of chlorophyll content. This coupled with the virtues of the MERIS sensor (e.g., radiometrically it is the most accurate imaging spectrometer in space (Curran and Steele, 2004)); fine spectral resolution, moderate spatial resolution (300m) and three-day repeat cycle) (Delwart et al., 2007) has lead to the adoption of the MTCI as an ESA Level 2 land product. Given that the MTCI is the only available chlorophyll index from a spaceborne sensor there is now real opportunity for monitoring vegetation function and condition systemically and reliably and thus the MTCI has now been used in several applications with success (Curran and Dash, 2006; Dash and Curran, 2007). Initial evaluation of the MTCI demonstrates a strong positive relationship with chlorophyll content as measured in the field (r2 of 0.8) (Dash and Curran 2007). The Meteorological Office and the Royal Netherlands Meteorological Institute recorded May to October 2006 as the warmest on record in the UK since These observed temperatures led to reports of an extended growing season and thus delayed senescence (BBC News accessed 30th October 2006). This paper aims to explore the response of natural vegetation at selected sites in England to this anomaly using a 2003 to 2006 time-series of the MTCI. 2. STUDY SITES AND AUXILIARY DATA Bringwood, Hereforeshire Area 571km2, of which 223km2 is and ancient, 164.5km2 is designated heath and grassland 14.0km2 14.2km2 14.5km2 Table 1. Locations of natural vegetation used in this study 2.1 Satellite sensor data High spatial resolution Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and aerial imagery (25cm true colour composites) were used to confirm both the accuracy of the GIS and that no change in land cover had taken place during Envisat MERIS reduced resolution (1.2km) data was used to produce 8 day MTCI composites. Radiometric and geometric corrections using BEAM software (the UK-MM-PAF) preceded the derivation of a level 2 product. An arithmetic mean composite was produced from the imagery for each 8 day period during the growing season (March to November) of the vegetation for The composites were then stacked chronologically for each year. Areas of interest were derived from the GIS layers and used to locate pixels located inside the chosen sites. The pixels were then averaged to produce a single value for each 8 day composite in the layer stack and a temporal profile produced for each site. The selected study sites were located in Hampshire, Cornwall, Herefordshire and Kent, England (Figure 1). Sites were relatively flat with near homogeneous vegetation cover and were larger than 3.6km2 (approximately 3x3 MERIS pixel in reduced resolution) and at geographical locations throughout England. GIS vector layers produced by English Nature were used to determine cover type and site size (Table 1). Figure 1. Location of the study sites within England Figure 2. A summary of the methodology used to monitor vegetation phenology

3 2.2 Metrological data Climate data within 20 km of each study site (local station) together with the Central England Temperature (CET) series was provided by the Metrological Office (UK). Average daily temperatures (T mean ) were calculated as the mean of the daily maximum (T max ) and the daily minimum (T min ) for both the local station and CET series and used in this study. The CET is often used in broad UK studies to typify the English climate as it is strongly correlated (p < 0.001) with local station observations throughout the UK (Croxton et al., 2006). 3. RESULTS AND DISCUSSION Temporal MTCI profile for all sites indicated an increase MTCI (and thus inferred chlorophyll content) for the autumnal period of 2006 compared to the same period for each of the earlier three years. Late October 2006 MTCI values were comparable with mid September values for the years 2003 and 2004 indicating a delay in senescence of the vegetation canopies. As an example Figure 3 illustrates the temporal MTCI profiles for the (a) lowland heath and grassland and (b) lowland in the New Forest National Park. Similar trends were observed in all three forest sites; there was a very strong positive correlation between MTCI for all forest sites in each year (e.g., r 2 = 0.97 in 2006). Indicating that changes in MTCI is a response to regional and national rather than local factors. Figure 3. Seasonal MTCI derived from layer stacks for the New Forest study site (a) lowland heath and grassland (b) Both the local T mean and CET T mean data were correlated with MTCI for each study site. A strong positive correlation between local T mean and MTCI was observed at all sites. Figure 4a shows this relationship for forest and heath and grassland for the New Forest site for the year of 2006 and Figure 4b shows this relationship for the period for forest at the New Forest site. Correlation analysis demonstrated a strong positive relationship between T mean and MTCI for all study sites (mean r 2 for period ; Bodmin moor 0.92, Bringwood 0.90 and Wildwood 0.88), indicating that the inferred chlorophyll canopy content is correlated strongly to mean monthly temperature, carbon dioxide, when water/nutrients and light are not limiting growth of vegetation is controlled by temperature (Deng et al. 2007). T mean is potentially a limiting factor to vegetation growth. Recent climate change has been found to affect species phenology, especially in the earlier onset of spring events in mid- and higher latitudes, whilst there is not enough information on autumn events to draw firm conclusions (Menzel et al. 2006). Findings in this paper support the notion of delayed senescence due to favourable growing conditions. Figure 4. (a) Relationship between MTCI and local T mean for woodland and grass / heath land sites in the New Forest using 2006 data; (b) the correlation between MTCI and local T mean for woodland sites in the New Forest for years , demonstrating the consistent relationship between MTCI and local T mean. Investigation of the difference between both MTCI and CET mean for 2006 and MTCI and CET mean for the previous three years

4 revealed a marked increase in temperature and inferred chlorophyll content for all sites. From the period July November 2006 mean inferred chlorophyll content was higher, delaying seasonal senescence. Statistical analysis needs to determine whether inferred chlorophyll content was significantly higher throughout the autumn period. However, during mid-october the mean inferred chlorophyll content for all sites was 54% greater than in previous years. This trend (Figure 5) follows that of T mean, however a response lag of approximately two weeks between temperature and MTCI was observed. Figure 5 also suggests that a seasonal shift may have occurred. Rather than experiencing only an extended growing season in 2006, the vegetation canopies may also have experienced a delay in the greening-up period. This is suggested by the below average inferred chlorophyll content until the month of July. Figures 3a&b also indicates the same trend of a slower greening up period in A longer running average of yearly observations would be needed to confirm this observation. 5. ACKNOWLEDGEMENTS We thank all those who helped with the data acquisition and processing; in particular Infoterra for providing the majority of the MTCI weekly composites used, the Meteorological Office (UK) for climate data and Bournemouth University for a studentship to SA. 6. REFERENCES Bassow, S.L. and Bazzaz, F.A., How environmental conditions affect canopy leaf-level photosynthesis in four deciduous tree species. Ecology, 79, pp BBC News, 2006, Britain blooms in extended summer, Available at (accessed 30th October 2006). Case, M.J., Peterson, D.L. and David, L., Growth climate relations of Lodgepole Pine in the North Cascades National Park, Washington. Northwest Science, 81, pp Chen, X., Q., Hu, B. and Yu, R., Spatial and temporal variation of phenological growing season and climate change impacts in temperate eastern China. Global Change Biology, 11, pp Croxton, P.J., Huber, K., Collinson, N. and Sparks, T., How well do the Central England temperature and the England and Wales precipitation series represent the climate of the UK? International Journal of Climatology, 26, pp Curran, P.J. and Steele, C.M., MERIS: The re-branding of an ocean sensor. International Journal of Remote Sensing, 26, Figure 5. The variation in MTCI and temperature in 2006 compared to the running average for all sites. MTCI was compared to the CET mean. The monthly mean temperature was above average for the duration of the autumnal 2006 period 4. CONCLUSIONS The MTCI was sensitive to seasonal variations in inferred canopy chlorophyll content and could be a valuable tool for phenological studies. Higher than average autumnal temperatures in 2006 delayed observed senescence and resulted in an extended growing season at all four sites. There was a strong positive correlation between temperature and MTCI, from which we can infer that chlorophyll content was sensitive to temperature. Long term monitoring is required to determine whether climatic warming is leading to changing phenology and an increase in the growing season. However, a continual increase in mean monthly temperatures may not consequentially lead to an increase in canopy chlorophyll content as other growth conditions will become limiting. The use of the MERIS MTCI affords the ability to carry out long term monitoring. Curran, P.J., Dash, J. and Llewellyn, G.M., Indian Ocean tsunami: The use of MERIS (MTCI) data to infer salt stress in coastal vegetation. International Journal of Remote Sensing, 28, pp Dash, J. and Curran, P.J., The MERIS Terrestrial Chlorophyll Index. International Journal of Remote Sensing, 25, pp Dash, J. and Curran, P.J., Evaluation of the MERIS terrestrial chlorophyll index (MTCI). Advances in Space Research, 39, pp Delward, S., Preusker, R., Bourg, L., Santer, R., Ramon, D. and Fischer, J., MERIS in flight calibration. International Journal of Remote Sensing, 28, pp Deng, F.P., Su, G.L. and Liu, C., Seasonal variation of MODIS vegetation indexes and their statistical relationship with climate over the subtropic evergreen forest in Zhejiang, China. IEEE Geoscience and Remote Sensing Letters, 4, pp Houghton, J.T., Ding, Y., Griggs, D.J., Noguer, M., van der Linden, P.J., Dai, X., Maskell, K., Johnson, (eds) Intergovernmental Panel on Climate Change, The Scientific Basis. Contribution of Working Group I to the Third assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, Cambridge UK.

5 Meteorological Office, Exceptionally warm extended summer Available at (accessed 18th October 2006). Menzel, A., Sparks, T. H., Estrella, N. and Roy, D.B., 2006, Altered geographic and temporal variability in phenology in response to climate change. Global Ecology and Biogeography, 15, pp Reed, B.C., Trend analysis of time series phenology of North America derived from satellite data. GIScience and Remote Sensing, 43, pp Rosenthal, S.I. and Camm, E.L., Photosynthetic decline and pigment loss during autumn foliar senescence in western larch (Larix occidentalis). Tree Physiology,17, pp Schleip, C., Menzel, A., Estrella, N. and Dose, V., The use of Bayesian analysis to detect recent changes in phenological events throughout the year. Agricultural and Forest Meteorology, 141, pp Sparks, T.H., Croxton, P.J., Collinson, N. and Taylor, P., Example of phonological change, past and present, in UK farming, Annals of Applied Biology, 146, pp Thomas, A., 2006, Climatic change and potential agricultural productivity in China, Erdkunde, 60, van Oldenborgh, G.J. 2006, Extraordinarily mild European autumn 2006 due to global warming. Global Change Newsletter, 67, pp Zhang, X.Y., Friedl, M.A., Schaaf, C.B., Global vegetation phenology from Moderate Resolution Imaging Spectroradiometer (MODIS): Evaluation of global patterns and comparison with in situ measurements. Journal of Geophysical Research, 111: Article number G04017.