92
vation about species-level impacts of CC in the Himalayan. Furthermore, mountain
ecosystems have largely been spared from invasions, mostly because of harsh climatic conditions (Pauchard et al. 2016). However, the diversity and abundance of
alien plants in mountain ranges has been increasing over the last few years (Pickering
et al. 2008; Pauchard et al. 2016; Carboni et al. 2018) with climate warming, suggesting that the potential for invasion impacts to increase in the future. The information available on CC and impact of climate change in IHR is still not well understood
and the current scientific research requires a much more cohesive approach. It must
be emphasized that most of the climate projection studies have been centred on the
HKH region, which is largely dominated by grasslands of the Tibetan plateau.
Grassland occupies an area of about 1.39 million km
2
, and constitutes about two
thirds (58%) of the total plateau area, while forest cover is very limited i.e. 9.5% of
the total area (Table 1). Further, grassland & shrub land occupy 54.1%, forest 14.2%
while agricultural land cover 26.4% area of the HKH (Table 1).
On the other hand, IHR covers an area of approximately 533,604 km
2
with more
than 41.5% of its geographical area under forest cover (representing one-third of the
total forest cover of the country) followed by 34.1% area under grassland & shrub
land, and 24.7% area under agriculture (Table 1). Therefore, CC prediction in IHR
based on data of HKH region, which comprise predominantly the Tibetan plateau,
may not reflect true IHR scenarios as the latter is vastly forested landscape. The CC
vulnerability studies in India (Sathaye et al. 2006) have high degree of uncertainty
in the assessment due to ‘limited understanding of many critical processes in the
climate system, existence of multiple climatic and non-climatic stresses. Intensive
investigations in IHR which is largely dominated by forests would be necessary to
give CC projections in this region. Forests are important sources of livelihoods to
millions of people and contribute to national economic development of many countries. In addition, they are vital sources and sinks of carbon and contribute to the rate
of CC. The sensitivity of forests to local climate and the long time periods required
in the forest management have been highlighted by Nelson et al. (2016). Hence,
modeling and mapping the climatic niches of forest tree species and projecting their
potential shift in geographic distribution under future climates are essential steps in
assessing the impact of CC on forests and in developing adaptive forest management strategies (Wang et al. 2016).
4 Model Based Projection on Climate Change in IHR
The forests in the Himalayan region are vulnerable to CC as well as are subjected to
severe decline in ecological services due to anthropogenic pressures (Ma et al.
2012). Most of the literature on CC confirms that climate is an important driver that
could influence forests in this region, and subsequently the ecosystem services to
dependent communities. This includes changes in vegetation structure and composition to the past climate data (Biswas et al. 2016), changes in phenology (Shrestha
et al. 2012; Singh et al. 2015; Bajpai et al. 2016; Negi et al. 2016), and shifts in
S. K. Nandi et al.
vation about species-level impacts of CC in the Himalayan. Furthermore, mountain
ecosystems have largely been spared from invasions, mostly because of harsh climatic conditions (Pauchard et al. 2016). However, the diversity and abundance of
alien plants in mountain ranges has been increasing over the last few years (Pickering
et al. 2008; Pauchard et al. 2016; Carboni et al. 2018) with climate warming, suggesting that the potential for invasion impacts to increase in the future. The information available on CC and impact of climate change in IHR is still not well understood
and the current scientific research requires a much more cohesive approach. It must
be emphasized that most of the climate projection studies have been centred on the
HKH region, which is largely dominated by grasslands of the Tibetan plateau.
Grassland occupies an area of about 1.39 million km
2
, and constitutes about two
thirds (58%) of the total plateau area, while forest cover is very limited i.e. 9.5% of
the total area (Table 1). Further, grassland & shrub land occupy 54.1%, forest 14.2%
while agricultural land cover 26.4% area of the HKH (Table 1).
On the other hand, IHR covers an area of approximately 533,604 km
2
with more
than 41.5% of its geographical area under forest cover (representing one-third of the
total forest cover of the country) followed by 34.1% area under grassland & shrub
land, and 24.7% area under agriculture (Table 1). Therefore, CC prediction in IHR
based on data of HKH region, which comprise predominantly the Tibetan plateau,
may not reflect true IHR scenarios as the latter is vastly forested landscape. The CC
vulnerability studies in India (Sathaye et al. 2006) have high degree of uncertainty
in the assessment due to ‘limited understanding of many critical processes in the
climate system, existence of multiple climatic and non-climatic stresses. Intensive
investigations in IHR which is largely dominated by forests would be necessary to
give CC projections in this region. Forests are important sources of livelihoods to
millions of people and contribute to national economic development of many countries. In addition, they are vital sources and sinks of carbon and contribute to the rate
of CC. The sensitivity of forests to local climate and the long time periods required
in the forest management have been highlighted by Nelson et al. (2016). Hence,
modeling and mapping the climatic niches of forest tree species and projecting their
potential shift in geographic distribution under future climates are essential steps in
assessing the impact of CC on forests and in developing adaptive forest management strategies (Wang et al. 2016).
4 Model Based Projection on Climate Change in IHR
The forests in the Himalayan region are vulnerable to CC as well as are subjected to
severe decline in ecological services due to anthropogenic pressures (Ma et al.
2012). Most of the literature on CC confirms that climate is an important driver that
could influence forests in this region, and subsequently the ecosystem services to
dependent communities. This includes changes in vegetation structure and composition to the past climate data (Biswas et al. 2016), changes in phenology (Shrestha
et al. 2012; Singh et al. 2015; Bajpai et al. 2016; Negi et al. 2016), and shifts in
S. K. Nandi et al.