However, when there is no parallel relationship between the present climate and
future climate, well-documented phenological data become useless in predicting
future changes (Corlett and Lafrankie 1998).
The Intergovernmental Panel on Climate Change (IPCC), in its sixth report,
predicted, by using climate models, that climate change will lead to an increase in
mean temperature in most land and ocean regions, hot extremes in most inhabited
regions, heavy rainfall in several regions, and the probability of precipitation shortage and drought in some regions. Changes in these factors could lead to disturbance
of different phenophases such as leaf emergence, leaf area, life span of the foliage,
growth period, abscission of foliage, and the onset of flowering of individual trees.
Many researchers have shown that plant phenology might act as one of the most
receptive and simply noticeable features found in nature that change with respect to
climate change. Therefore, plant phenology data are widely being used as an
indicator of climate change, because climate change (increase in average temperature and change in rainfall pattern) primarily affects the phenology of biological
organisation (Stöckli et.al, 2003). Such changes are easily perceptible with a longterm phenological database.
The sensible features of phenological observation towards regional climate conditions and to climate change mean that phenological records become the most
reasonable data for climate change and thus have recently emerged as a major area
of research in ecology. Different methods had been chosen by scholars to discover
the phenological patterns in leafing and other phenomena, some of which are
ground-level observation, spatial photography observation. and satellite imagery.
Ground-based observations actually gave rise to the science of phenology in the first
place when people kept noticing the changes that plants underwent over time. These
methods rely on volunteers to collect observations of the various phenophases of
wild plants, fruit trees, and agricultural crops at numerous locations (Cleland et al.
2007). Ground-level observations become hard to follow in difficult terrains such as
regions of alpine, arctic, tundra, and desert ecosystems (Richardson et al. 2013).
To study a large forest area and to estimate forest biophysical parameters,
information collected by the amalgamation of forest resources inventory and remote
sensing technique are two approaches (Krankina et al. 2004). Application of new
technologies to study the phenology of plants has contributed to diversify the field
and bring about a revival in its application to study major changes across Earth’s
systems. One such technology combines remote sensing and the Geographical
Information Systems (GIS). With the help of satellite imagery, it is possible to
collect a large number of phenological records across a large spatial and temporal
scale. Changes such as leaf emergence, leaf fall, plant responses to environmental
changes, and changes in the greening of the biosphere can be easily observed
(Myneni et al. 1997). The most important index used in remote sensing data to
measure the temporal changes taking place in vegetation is the normalised difference
vegetative index (NDVI), which is based on the low reflectance of red colour
(a green plant absorbs more of the red and blue region of electromagnetic radiation)
and the strong reflectance of near-infrared radiation (Huemmrich et al. 1999). The
NDVI has been related to canopy cover (Yoder and Waring 1994), leaf area index,
8 Forest Phenology as an Indicator of Climate Change: Impact and Mitigation. . .
187
future climate, well-documented phenological data become useless in predicting
future changes (Corlett and Lafrankie 1998).
The Intergovernmental Panel on Climate Change (IPCC), in its sixth report,
predicted, by using climate models, that climate change will lead to an increase in
mean temperature in most land and ocean regions, hot extremes in most inhabited
regions, heavy rainfall in several regions, and the probability of precipitation shortage and drought in some regions. Changes in these factors could lead to disturbance
of different phenophases such as leaf emergence, leaf area, life span of the foliage,
growth period, abscission of foliage, and the onset of flowering of individual trees.
Many researchers have shown that plant phenology might act as one of the most
receptive and simply noticeable features found in nature that change with respect to
climate change. Therefore, plant phenology data are widely being used as an
indicator of climate change, because climate change (increase in average temperature and change in rainfall pattern) primarily affects the phenology of biological
organisation (Stöckli et.al, 2003). Such changes are easily perceptible with a longterm phenological database.
The sensible features of phenological observation towards regional climate conditions and to climate change mean that phenological records become the most
reasonable data for climate change and thus have recently emerged as a major area
of research in ecology. Different methods had been chosen by scholars to discover
the phenological patterns in leafing and other phenomena, some of which are
ground-level observation, spatial photography observation. and satellite imagery.
Ground-based observations actually gave rise to the science of phenology in the first
place when people kept noticing the changes that plants underwent over time. These
methods rely on volunteers to collect observations of the various phenophases of
wild plants, fruit trees, and agricultural crops at numerous locations (Cleland et al.
2007). Ground-level observations become hard to follow in difficult terrains such as
regions of alpine, arctic, tundra, and desert ecosystems (Richardson et al. 2013).
To study a large forest area and to estimate forest biophysical parameters,
information collected by the amalgamation of forest resources inventory and remote
sensing technique are two approaches (Krankina et al. 2004). Application of new
technologies to study the phenology of plants has contributed to diversify the field
and bring about a revival in its application to study major changes across Earth’s
systems. One such technology combines remote sensing and the Geographical
Information Systems (GIS). With the help of satellite imagery, it is possible to
collect a large number of phenological records across a large spatial and temporal
scale. Changes such as leaf emergence, leaf fall, plant responses to environmental
changes, and changes in the greening of the biosphere can be easily observed
(Myneni et al. 1997). The most important index used in remote sensing data to
measure the temporal changes taking place in vegetation is the normalised difference
vegetative index (NDVI), which is based on the low reflectance of red colour
(a green plant absorbs more of the red and blue region of electromagnetic radiation)
and the strong reflectance of near-infrared radiation (Huemmrich et al. 1999). The
NDVI has been related to canopy cover (Yoder and Waring 1994), leaf area index,
8 Forest Phenology as an Indicator of Climate Change: Impact and Mitigation. . .
187