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*For correspondence. (e
-mail: vikramsnegii@gmail.com;
envsuresh09@gmail.com
)
Long-term ecological monitoring and
observation: a review in the context of
Indian Himalaya
Vikram S. Negi*, Suresh K. Rana*, Bhawana Dangwal, Shinny Thakur,
K. Chandra Sekar and I. D. Bhatt
G.B. Pant National Institute of Himalayan Environment (GBP-NIHE), Almora 263 643, India
Long-term experiments are essential in understanding
the ecological consequences of global land use and cli-
mate change. Further, it is well established that long-
term data sets are prerequisites for effective management
of forest resources and biodiversity conservation. In
view of this, the present study attempts to contribute to
major global long-term ecological monitoring (LTEM)
networks and the status of LTEM studies in India with
a special focus on Indian Himalayan Region. Over the
last 40 years, around 103 countries from the America,
Europe, Africa, Asia and Australia have been engaged
in LTEM studies on various aspects of biodiversity, mon-
itoring and predicting climate change impacts in a
range of ecosystems, including the mountains. The
temporal distribution of past studies on the subject
shows a gradual increasing pattern (3 papers in 1992)
with a peak during 2021 (105 papers). The established
LTEM networks across the globe provide a significant
empirical basis for understanding ecosystem structure
and dynamics. Literature indicates plenty of perma-
nent monitoring plots from India, mostly from southern
India, and their significant contribution to ecosystem
understanding. Himalayan regions are important sites
for monitoring biological and socio-ecological responses
to environmental perturbations, including climate change.
LTEM studies are lacking in the IHR; only a few sites
have been established, mostly in alpine ecosystems. This
review identifies research gaps, opportunities with respect
to LTEM studies, and the possibilities for strengthen-
ing long-term research and observation in India in
general and the Himalaya in particular.
Keywords: Alpine ecosystem, biodiversity conservation,
forest management, Himalaya, long-term ecological moni-
toring, long-term observations.
LONG-TERM studies are essential in understanding the eco-
logical consequences of global land use and climate
change1,2. Long-term ecological monitoring (LTEM), focus-
ing on forest and alpine ecosystems, is globally contributing
in understanding the impacts of land use and climate change
on biodiversity3–5. LTEM generally refers to monitoring a
particular system, i.e. forests, alpine vegetation, and oceans,
for over 10 years. Establishing permanent monitoring plots
(PMPs) is a robust approach of LTEM for observing
changes in plant species richness and population parameters
such as growth, biomass, recruitment, mortality, etc.6,7.
Further, LTEM not only improves our understanding of
the relationship between vegetation and the environment,
but also helps in understanding the ecosystem responses to
global climate change8,9. PMPs established in forests provide
baseline data, trends and processes of vegetation change
and engender hypotheses on its pace and causes10. In addi-
tion, long-term studies provide essential information for
forest ecological research, adaptation and conservation
planning across the globe11–13.
Globally, long-term monitoring and research have led to
developing networks to share and collect data, and foster
collaboration among researchers and institutions. The Natio-
nal Ecological Observatory Network (NEON), DIVERSITAS
(an international programme of biodiversity science), South
African Environmental Observation Network (SAEON), Ter-
restrial Ecosystem Research Network (TERN), Long-term
Ecological Research Network (LTERN), LTER-Europe,
Tropical Ecology Assessment and Monitoring (TEAM),
Chinese Terrestrial Ecosystem Observation and Experiment
Network (CEOBEX), National Center for Ecological Ana-
lysis and Synthesis (NCEAS), the Global Observation Res-
earch Initiative in Alpine Environments (GLORIA),
Chinese Ecosystem Research Network (CERN), the Center
for Tropical Forest Science-Forest Global Earth Observatory
(CTFSForest GEO) are such network examples14–16. Among
others, RAINFOR in tropical forests of Amazonia, Hub-
bard Brook Experiment in the US and Biodiversity Explora-
tories in Germany are reported as the most recognized and
globally accepted LTEM networks. Literature indicates
around 45 countries engaged in LTEM studies on various as-
pects of biodiversity and environmental monitoring4,5,17. India
is also part of a few LTEM networks and significantly
contributing to understanding forest dynamics and ecologi-
cal processes18,19. Most information on long-term monitoring
in India is available from Mudumalai, southern India18,20–24.
The available records show that there are 309 preservation
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plots in the country, of which 187 are located in natural
forests and 122 in plantations covering a total area of ap-
proximately 8500 ha (ref. 18). It was reported that LTEM
studies were carried out in many parts/regions of India
such as Uttar Pradesh, Tamil Nadu, Andhra Pradesh, As-
sam, Maharashtra, Bihar, Kerala, West Bengal, however,
published information in the form of research papers is
mostly available from Mudumalai.
In India, Himalayan biodiversity is well reported to be
highly sensitive to global warming due to its unique vertical
gradient, and in turn, this would define the future of forest
ecosystems and local people in the region25,26. The Himala-
yan region, with only 18% of land area of country, houses
81.4% of gymnosperms, 47% of angiosperms, 59.5% of
lichens, 58.7% of pteridophytes, 43.9% of bryophytes and
53.07% of fungi found in India27. The Intergovernmental
Panel for Climate Change28 described the Himalayan region
as ‘data-deficient in observing climate change impacts on
ecosystem and biodiversity’. The main reasons for this are
a limited number of long-term research stations, automatic
weather stations, systematic collection of information/data
set, and mechanism to share data/information among exist-
ing institutions and stakeholders11,29. Only a few LTEM
plots/sites in the forest and alpine ecosystems of the Indian
Himalayan states, i.e. Himachal Pradesh and Uttarakhand,
have been established8,11. Therefore, there is an urgent need
to synthesize and compile the status of long-term monitoring
and research to find gaps and scope for their establishments
in India, particularly in the IHR. In view of this, the present
study is an attempt to (i) highlight the contribution of global
long-term monitoring and research networks and (ii) to
synthesize the status and information on LTEM in India
with a special focus on the IHR.
Methods
A systematic approach for synthesizing information through
a step-wise process was applied for extracting the relevant
peer-reviewed literature. The peer-reviewed articles were
searched using Boolean operators with a combination of the
following keywords (long-term AND ecological AND
monitoring AND plants) on the Scopus database (www.
scopus.com). In addition, general search keywords were
used to review the relevant research using the keywords long-
term ecological monitoring and research on forest and alpine
vegetation on Google Scholar (http://scholar.google.com).
All publications in the English language, irrespective of the
number of citations, were selected for further systematic re-
view. From each publication, information on the publica-
tion year, name of the journal/publisher, name of the
author/s, country of the author/s, subject area of the publi-
cation etc. was compiled for the spatial and temporal trend
analysis in this research field. In this article, LTEM refers
to monitoring vegetation and forest ecosystems for more
than 10 years.
Results and discussion
Importance of global long-term ecological
research networks
The review of literature provides a total of 1561 studies on
long-term monitoring and research across the globe (Fig-
ure 1). The temporal distribution of LTEM shows a grad-
ual increasing pattern over the years, with a peak in 2021.
The maximum number of studies on LTEM are reported
from the United States (332), followed by China (123) and
the United Kingdom (92) (Figure 2). The International
Long-Term Ecological Research (ILTER) network is the
‘network of networks’ of 103 countries and currently con-
sists of more than 600 sites worldwide in different types of
ecosystems4,5. The network has produced over 24,000 papers,
theses and books through observing data sets of 40 years30.
The Amazon Forest Inventory Network was conceived in
1999 with the name RAINFOR to understand the dynamics
of tropical forests29. RAINFOR plays a critical role in sup-
porting Peru government with their submission to the
United Nations Framework on Climate Change (UNFCCC)
in 2021 and is officially a ‘nationally determined contribu-
tion (NDC)’ to climate change adaptation. The networks
have been adapted in Africa (AfriTRON) and Southeast Asia
(T-FORCES) and globally supported with ForestPlots.
net31,32.
The LTEM network provides globally distributed long-
term research sites for multiple purposes and uses in the
fields of ecosystem, biodiversity, critical zone and socio-
ecological research5. Data from various networks revealed
some generalities and long-term trends of change in for-
ests worldwide. The key findings from global LTEM net-
works include: (i) forests generally, and in particular
tropical forests, are highly dynamic16, (ii) forest composition
in terms of species and functional groups has changed in
different directions at different sites33, (iii) environmental
variability is the most important factor driving tree popu-
lation dynamics on decadal time scales34, (iv) species diversity
promotes ecosystem productivity and stability, and that of
nutrient supply and herbivory control diversity via changes
in composition35, (v) the inadvertent addition of atmos-
pheric nitrogen by human activities is currently a domi-
nant driver of global grassland productivity36, (vi) tree
species composition and dominance strongly control forest
functions31, (vii) herbivores safeguard plant diversity by re-
ducing variability in dominance37, (viii) biomass in north-
eastern Amazonia is higher than elsewhere due to reduced
mortality risk and bigger trees35, and (ix) intact tropical
forests remain major stores of carbon and are key centres
of biodiversity12. The results of global networks also showed
that mature forests of Amazonia have experienced accel-
erated tree turnover during the past three decades35. LTER
network helps to understand climate change, loss of bio-
diversity and changes in patterns of land use. LTER sites
enable the detection of both slow, but significant and
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Figure 1. Temporal trend of global LTEM studies.
Figure 2. Country-wise distribution of LTEM studies (here we have listed only those countries
where number of LTEM plots/sites are higher than five).
extreme changes in ecosystem functioning, responding to
the presence, absence and intensity of pressures/drivers5.
LTEM networks suggest that forest carbon mapping has
the potential to reduce uncertainties in the global carbon
budget and facilitate effective emissions mitigation stra-
tegies38.
Most of the LTEM network initially focused on monitoring
a few parameters, such as growth, richness and biomass in
the forest ecosystems. However, with the advancement of
technologies, methods, instrumentations and understanding
the importance of long-term data sets, LTEM is focusing on
additional ecological parameters to understand forest dyna-
mics and the role of environmental perturbations. Moni-
toring of functional traits, phenology, diameter growth using
dendrometer bands, species-level flower and seed produc-
tion, seedling establishment, growth and survival16 are exam-
ples of some ecological parameters. Camera trapping is
used to monitor terrestrial mammals and the phenology of
the plants. Recently, short DNA sequences from a standard
position within the genome were used to construct phyloge-
nies and distinguish individual species using long-term data
sets. The Eddy covariance technique was used to continu-
ously measure CO2, H2O and energy exchange between the
ecosystem and the atmosphere.
Long-term ecological research in India
The urgency of the LTEM network in India was highlighted
in earlier studies11,39. Long-term forest research sites in
India were often recognized by different terminologies
and names like linear tree increment plots, linear increment
plots, linear sample plots and permanent preservation
plots, which covered diverse plant communities and envi-
ronmental conditions18. India has also initiated the Long-term
Ecological Observatories (LTEO) programme through the
Ministry of Environment, Forest and Climate Change
(MoEF&CC), Government of India (GoI)40. Department
of Science and Technology (DST), GoI has established
INDOFLUX, a coordinated multidisciplinary environmental
monitoring network that integrates terrestrial, coastal and
oceanic environments41. Long-term research programmes
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on specific taxa have also been operated by different
agencies such as the Indian Institute of Science, Dakshin
Foundation (marine turtles), Wildlife Institute of India (ti-
gers) and Nature Conservation Foundation (coral reefs).
National Forest Inventories (NFIs) are working to manage
and effectively plan forests in the country. The Ashoka Trust
for Research in Ecology and the Environment (ATREE) was
initiated to focus on using forest resources by indigenous
groups in the Biligiri-Rangana Hills of southern India19.
PMPs of India were studied by Mathauda20 between 1978
and 1993 in collaboration with global partners. Rai23 has
reported a total of 309 PMPs in different forest types of
the country. A permanent plot of 50 ha was established in
1988 to understand forest dynamics (i.e. species diversity,
density and basal area) in tropical dry deciduous forests of
Western Ghats18,24,42. The major aim of monitoring sites
was to study (i) the pattern of mortality, (ii) the rate of di-
ameter increment and (iii) the rate of diameter and basal
area increment. LTEM studies from India have contribut-
ed to two-decadal changes in forest structure and tree di-
versity of tropical dry evergreen forests18. Data set on the
demography of trees was monitored over 20 years in
Uppangala PMPs located within the Pushpagiri Wildlife
Sanctuary, Karnataka43. It was reported that many PMPs esta-
blished in India were maintained in good condition up to
1996 and serve as one of the oldest long-term research sites
in the world18. However, records of the majority of the re-
ported plots are not available18. Few studies42,44,45 from
well-managed PMPs indicated the potential of these plots
in biodiversity and forest dynamics monitoring in India.
Long-term ecological monitoring in IHR forests
Only a few permanent LTEM plots in the forests of two
states, i.e. Himachal Pradesh and Uttarakhand, have been
established8,11 (Table 1, Figure 3). These are the only
studies published that provided details of plots/sites and
baseline information collected so far. Apart from these,
the Himalayan Forest Research Institute, Shimla (Himachal
Pradesh), established two forest observational plots. They are
(i) the Shimla site established in 2015 and (ii) the Shikari
Devi site, started in 2016 (ref. 46). These plots are used for
practical demonstration for establishing long-term plots
and documentation of information on biodiversity moni-
toring. In western Himalaya, a total of six LTEM plots were
established along an elevation gradient (1000–3800 m
above sea level) in the Pithoragarh district of Uttarakhand11.
Recently, four LTEM plots were established in 2018 by the
G.B. Pant National Institute of Himalayan Environment
(GBP-NIHE) in Uttarakhand under its in-house project47
(Table 1, Figure 3). The advantage of these monitoring
plots is the support of meteorological observation stations
to relate possible changes in plant biodiversity with climate
change. One site was also established by the Sikkim Regional
Centre of the above institute under the Khangchendzonga
Landscape Conservation and Development Initiative
(KLCDI) programme to monitor ecological and socio-eco-
nomic parameters. A permanent plot of 30 ha (600 ×
500 m2) was established for long-term ecological research
on biodiversity and forest functioning in a tropical ever-
green forest at Varagalaiar, Anamalais, Western Ghats48.
Lately, the Zoological Survey of India (ZSI) started a bio-
diversity assessment through long-term monitoring plots
in the Indian Himalayan landscape in collaboration with
the Botanical Survey of India. The broad focus of these
plots is to evaluate the present status and trend of biodi-
versity in the IHR and to understand local stakeholders’
needs for sustainable utilization of bioresources. Notably,
many new LTEM plots have been initiated in recent years
in various parts of the IHR, although the information and
findings are yet to be published.
Long-term ecological monitoring in IHR alpines
High mountain environments are often characterized by low
temperatures and short growing seasons, yet they support
high plant endemism and biodiversity. However, these
ecosystems are considered among the most vulnerable to
climatic change49. In order to design appropriate policies
and strategies to manage such environments in the long-term,
data and information are needed. The standardized proto-
col for long-term ecological observations in alpines was
developed as the ‘Global Observation Research Initiative
in Alpine Environments’ (GLORIA). The major focus of
GLORIA47,50 is to monitor the changes in species richness
(number of species), patterns of vegetation (changes in per
cent cover), species composition (loss or gain of individual
species) and soil temperatures of microhabitats50. The
network found that: (i) changes in plant diversity happened
over time in a water-limited and isolated high-mountain
range in Sierra Nevada, Spain51, (ii) climate change affected
vegetation differently on siliceous and calcareous summits
of the European Alps52, (iii) despite increase in species
richness over time, there was an overall decline in diversity
through biotic homogenization across the Australian alpine
summits over time53, (iv) significant diversity changes in
higher summits in Mediterranean mountains were related to
various aspects53. Surprisingly, the Indian Himalaya re-
mained a major gap for monitoring the alpine ecosystems
up to 2014. The first GLORIA site was established in
2014 by GBP-NIHE in Chaudans Valley, Uttarakhand, and
second in 2015, in Byans Valley of Pithoragarh, Uttarak-
hand, under Kailash Sacred Landscape Conservation and
Development Initiative, and National Mission on Sustaining
the Ecosystem (NMSHE) Task Force 3 ‘Forest Resources
and Plant Biodiversity’54 (Table 2). The observation sites
consisted of four summits exposed to the same regional
macroclimate along an altitudinal gradient above the natural
treeline up to the uppermost vegetation zone. A multi-sum-
mit-based long-term measurement network known as
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Figure 3. Map showing established LTEM plots/sites in the Indian Himalayan Region.
HIMADRI (Himalayan Alpine Dynamics Research Initia-
tive) has also been conceptualized for understanding long-
term alpine vegetation dynamics in the IHR states coordinated
by Space Applications Centre, ISRO, Ahmedabad. A total
of 20 summits with more than 1000 quadrats have been esta-
blished along an elevation gradient (3200–4200 m) in the
alpine ecosystem under the network54–60 (Table 2).
Contributions of long-term ecological monitoring
in India
There can be uncertainties regarding the consequences of
various drivers of change due to lack of long-term data,
sporadic and scattered research, limited access, unreliabi-
lity and incomparability of existing data29,39. The long-term
forest plots have been extremely successful in achieving
the primary aim of improving our knowledge of forest
ecology. In India, forest plots cover diverse forest types and
environmental conditions. Presently, some PMPs and LTEM
sites are functional, some are disturbed, and many have
almost been lost18. The data/information generated from
LTEM plots in India is becoming increasingly important
in the context of environmental modelling and climate
change. Mathauda20 studied patterns of mortality and dia-
meter increment through LTEM, while Rai23 investigated
the diameter and basal area growth of 95 species from trop-
ical rain forests of Karnataka. The studies commonly con-
cluded that: (i) the pioneer species showed higher rates of
basal area increment, (ii) moving away from protected area
boundaries enhanced conservation practice in the larger
landscape, (iii) long-term scientific data is key to influenc-
ing the right decisions in management and conservation
and (iv) the knowledge of basal area increment of a spe-
cies or forest community is of paramount importance in
forest management. These studies contributed to classifying
trees into three crown classes and four social classes18.
These studies were also intended to observe the effect of
silvicultural treatments on the rate of growth of studied
species. These studies further contributed to forest manage-
ment and conservation.
The Mudumalai forests in Tamil Nadu (eastern foothills
of the Western Ghats of southern India) are well known
for LTEM studies in India and have significantly contributed
to the understanding of forest dynamics. These plots were
established by the Centre for Ecological Sciences of the
Indian Institute of Science, Bengaluru. The LTEM plots in
Mudumalai are surveyed every year for recruitment and
mortality. Sukumar et al.24 investigated the relationship of
various environmental drivers with diameter and growth
of the basal area. The observation of the plots revealed
that leaves were shed by January–February; new leaves
emerged by the end of April, and the majority of the tree
species produced leaves and flowers simultaneously61. The
relationship between annual rainfall and tree mortality in a
tropical dry forest was assessed based on a 19-year LTEM
study at Mudumalai46. These studies play an important role
in understanding the impact of fire and elephants on forest
regeneration and dynamics18. The influence of climatic
variability on tree phenology in the tropical dry forests of
Mudumalai was assessed based on the long-term data
sets62. Condit et al.63–65, using the data from Mudumalai
plots, explained the importance of demographic niches to
tree diversity and species–area and species–individual re-
lationships for tropical trees using PMPs. Growth models
developed from LTEM studies are used for projecting and
generating reasonable scenarios at landscape level18.
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Figure 4. Suggested parameters and indicators for long-term ecological monitoring.
Research gaps and recommendations
Literature indicates a wide network of PMPs in India;
however, they were not considered very suitable for long-
term ecological monitoring and planning because of: (i)
their relatively small size, (ii) limited representation of
ecosystem diversity, (iii) dominant economic tree species,
(iv) existence of high anthropogenic pressure, (v) poor
management, (vi) availability of data sets generated for
only few plots and (vi) paucity of funds. This kind of situa-
tion calls for urgent attention of researchers towards gene-
rating robust data sets by following globally compatible
protocols. Lack of collaborations with global networks
and issues of data sharing creates a wide gap in understand-
ing long-term dynamics in the Indian and South Asian re-
gions19. De Lima et al.66 suggested solutions for the data
sharing issues. Setting priorities, criteria and indicators
has been suggested as the first step for establishing LTEM
plots/sites in any region, which would provide a tool for as-
sessing changes in given forestry situations11. The present
study identified the criteria and indicators used globally
for LTEM studies based on the literature (Figure 4).
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The dimensions of LTEM plots are another important
factors to consider in understanding the relationship between
biodiversity and climate change. In addition, the sample
size (number of plots) depends on the area of forest pro-
posed for monitoring and the standard protocol to be fol-
lowed35. In pure or homogenous forests, fewer plots can
represent the ecosystem; however, in mixed forests, a sig-
nificantly higher number of plots is important for repre-
senting the ecosystem. For example, the size of plots used
for monitoring were 20 × 20 m, 50 × 50 m and 100 ×
100 m in some of the earlier studies. Further, logistics is
also an important factor to consider while selecting the
plots in a particular forest. Thus, the sampling size of the plot
should be of standard unit or measure following global moni-
toring protocols. For example, the plot size was taken as
one hectare (100 × 100 m) for permanent monitoring14,11
in a few studies, while a few other studies8,24,63,64 used
20 × 20 m and 50 × 50 m PMPs. Also, trade-offs related to
the choice of plot size, shape, orientation, etc. have been
well-studied38,67,68. Most of the studies suggested for col-
lecting climatic data to support the LTEM studies to trace
the impacts of climate change. It is also recommended that
all the LTEM plots/sites should be supported with an auto-
matic weather station for monitoring basic environmental pa-
rameters, i.e. temperature, rainfall, humidity, carbon flux,
etc. The size of the plots should be according to the objec-
tives of the study and the feasibility or accessibility of the
sites. A skilled workforce is needed to maintain the LTEM
plots and data recording.
The merits and limitations of long-term studies carried
out in IHR are provided in Table 3. The frequency of obser-
vation, i.e. 10, 20 and >20 years, is recommended in many
studies; however, PMPs should be monitored yearly for
predicting change in herb composition, i.e. change in native/
endemic and threatened species, invasion by alien invasive
species, etc.11. Further, data management is especially critical
for long-term monitoring as there is likely to be a turnover
of working staff, i.e. researchers, scientists1,3. Therefore,
the organization/institute working on LTEM should update
the information/findings through their web portal. Consid-
ering the larger extents of IHR, knowledge gaps on LTEM
still exist in the region.
Funding for long-term research and monitoring in India
is becoming increasingly difficult to obtain19. In India,
most funding agencies provide funds for three or five
years; however, initial two or three years are spent to esta-
blish just the LTEM plots. Even when donors are attracted
to the long-term presence of researchers in a landscape, the
money is targeted at short-term action and impact. This
makes the maintenance of existing data and extensions of
the monitoring schemes challenging. Thus, the mainte-
nance of the LTEM plots and documentation of the obser-
vations have become tough. In the case of IHR, it becomes
further difficult to establish LTEM plots due to tough ter-
rain and requiring a higher and more skilled workforce.
Among other things, this often involves submitting a set
of published papers to appraise the new team on the work
done on the site over the years. Getting permission for
long-term monitoring (above five years) from the state
forest administration is difficult in India. This has affected
work and produced gaps in research when we have had to
wait for permission. Strengthening partnerships among orga-
nizations, including the state forest department is required
for biodiversity monitoring and knowledge networking.
Conclusion
Global interest in LTEM is increasing for a better under-
standing of the fate of biodiversity to various drivers and
threats, including global warming. These studies provide
key insight into forest management and biodiversity con-
servation across the globe. However, the literature indicates
that the local climate data are inadequate, as the instrumenta-
tion is not sufficiently standardized in India, particularly in
IHR. Thus, there is a strong need to strengthen automatic
weather stations to establish the impacts of climate change
on biodiversity. Few scientific institutions have started the
establishment of LTEM plots in forests and alpine ecosys-
tems in the IHR; however, continuous monitoring of these
plots requires a lot of funds and support. The assessment
methods in the LTEM are usually not uniform; thus, there
is a need to develop or follow existing global protocols and
parameters to make studies comparable across diverse re-
gions. The information generated by LTEM not only helps
frame national environmental policies but also plays an in-
creasingly relevant role for international conventions and
the broader scientific community.
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ACKNOWLEDGEMENTS. We thank Prof. Sunil Nautiyal (Director,
G.B. Pant National Institute of Himalayan Environment, Almora) for
facilities and support. Partial funding from Department of Science and
Technology, Govt of India under NMSHE-Task Force-3 Phase II ‘Forest
Resources and Plant Biodiversity’ is acknowledged.
Received 12 October 2020; revised accepted 24 May 2023
doi: 10.18520/cs/v125/i6/623-634
