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. 2022 Dec 13;10:e14401. doi: 10.7717/peerj.14401

Animal movement ecology in India: insights from 2011–2021 and prospective for the future

Harish Prakash 1,, R Suresh Kumar 2, Bibhuti Lahkar 3, Raman Sukumar 1, Abi T Vanak 4,5, Maria Thaker 1,
Editor: Randeep Singh
PMCID: PMC9756863  PMID: 36530402

Abstract

The field of animal movement ecology has advanced by leaps and bounds in the past few decades with the advent of sophisticated technology, advanced analytical tools, and multiple frameworks and paradigms to address key ecological problems. Unlike the longer history and faster growth of the field in North America, Europe, and Africa, movement ecology in Asia has only recently been gaining momentum. Here, we provide a review of the field from studies based in India over the last 11 years (2011–2021) curated from the database, Scopus, and search engine, Google Scholar. We identify current directions in the research objectives, taxa studied, tracking technology and the biogeographic regions in which animals were tracked, considering the years since the last systematic review of movement ecology research in the country. As an indication of the growing interest in this field, there has been a rapid increase in the number of publications over the last decade. Class Mammalia continues to dominate the taxa tracked, with tiger and leopard being the most common species studied across publications. Invertebrates and other small and medium-sized animals, as well as aquatic animals, in comparison, are understudied and remain among the important target taxa for tracking in future studies. As in the previous three decades, researchers have focussed on characterising home ranges and habitat use of animals. There is, however, a notable shift to examine the movement decision of animals in human-modified landscapes, although efforts to use movement ecology to understand impacts of climate change remain missing. Given the biogeographic and taxonomic diversity of India, and the fact that the interface between anthropogenic activity and wildlife interactions is increasing, we suggest ways in which the field of movement ecology can be expanded to facilitate ecological insights and conservation efforts. With the advancement of affordable technologies and the availability of analytical tools, the potential to expand the field of movement ecology, shift research foci, and gain new insights is now prime.

Keywords: Movement ecology, Tracking, Telemetry, Home-range, Protected areas, Anthropogenic, Climate change, Wildlife conflict, Conservation, India

Introduction

Animals travel a wide range of distances during their lifetime primarily in order to feed, find mates and seek refuge, among other critical behaviours (Bell, 1990). The terrestrial caribou Rangifer tarandus, for example, travels a total of ~4,000 km in a year (Joly et al., 2019) while the airborne arctic tern Sterna paradisaea, travels ~80,000 km during the same period (Egevang et al., 2010). In contrast to these long-distance migrants, the near stream-dwelling fire salamander Salamandra Salamandra, has a maximum annual displacement of only ~0.5 km (Schulte, Küsters & Steinfartz, 2007). Ecologists have, for decades, been interested in understanding the drivers of such travel distances (Holyoak et al., 2008). The movement ecology paradigm provides an explicit framework to understand movement patterns and drivers, considering the role of the abiotic environment, as well as the animal’s internal physiology, capacity to process information and navigate, and biomechanical capability to move (Nathan et al., 2008). This multi-faceted and unifying framework that enables the study of animal movement is complemented with recent technological developments of bio-loggers embedded with multiple sensors (Börger et al., 2020). Loggers not only track movement with GPS and accelerometery across space and time, but can also collect information on the animal’s external environment (e.g., ambient temperature, salinity, and light levels), and its internal physiological condition (e.g., body temperature, heart rate, and neurological state) (reviewed in Sherub et al., 2017). The latest low-cost miniature tags (~3 g in weight) also allow fine scale animal tracking at a global scale using satellites (Jetz et al., 2022). Thus, the integration of conceptual and analytical frameworks with current technological developments have been critical for gaining valuable insights into animal movement decisions of taxa inhabiting diverse environments across the globe.

Movement ecology has direct implications for understanding survival strategies of species, community structures and biodiversity (Jeltsch et al., 2013), and for generating conservation plans (Fraser et al., 2018). For example, movement data from the Carnaby’s cockatoo Calyptorhynchus latirostris, shows how travel distances for foraging are lower in contiguous habitats than in fragmented habitats, and this behaviour correlates with greater breeding success for the bird in contiguous habitats (Doherty & Driscoll, 2018). Movement of individuals can have larger ecological consequences beyond individual fitness or species distribution. The movement patterns of sea birds result in the deposition of carcasses, food scrapes, and guano on islands, which directly influences the availability of nutrition for terrestrial scavengers, as well as the productivity of primary producers on those islands (Stapp, Polis & Sânchez Pinero, 1999). To formalise an association between animal movement, conservation, and ecosystem function, Allen & Singh (2016) suggest a framework that incorporates the movement attributes of a species, the impact it has on the ecosystem, and the formulation of management plans. Given that animal movement is crucial for species survival and ecosystem function, climate change and land transformation are two of the major global changes that will impact animals in the Anthropocene (Sage, 2019).

Being forced to stay in inhospitable environments could lead to local population exterpation. In such scenarios, movement decisions such as dispersal and niche shifts become important and can lower extinction risk in the face of the climate change crisis (Román-Palacios & Wiens, 2020). However, adaptative response to climate change is not as simple as vulnerable animals shifting to suitable areas. Climate change affects the environmental cues that animals use for migration, increases their encounters with harsh climatic conditions that impact their physiology, and, in some cases, turn them sedentary (Seehacher & Post, 2015). Multiple examples of migratory birds advancing their arrival date at breeding sites in response to temperature shifts have already been documented (Kentie et al., 2018; Radchuk et al., 2019). Additionally, animals are known to respond to extreme events that climate change is likely to exacerbate, such as droughts (move to greener pastures), wildfires (move away from burnt areas), storms (move to refugia), and floods (move to highpoints) (Buchholz et al., 2019). The frequent occurrence and duration of extreme events could have implications for ecosystem functions that animals provide. For example, seed dispersal services provided by frugivores could be reduced as a consequence of global change, and this is expected to have consequences for plant species distribution (Mokany, Prasad & Westcott, 2014). Moreover, decrease of environmental predictability can impact crucial ecological processes that are dependent on animal movement, such as disease transmission, population dynamics of plants and animals, range distribution & interactions, and ecosystem functioning (Riotte-Lambert & Matthiopoulos, 2020).

Species moving in response to climate change can further be hindered by anthropogenic modifications that act as barriers (Chazdon et al., 2009). Increasing the size of urban areas can act as a barrier if suitable habitats are not available as stepping stones for animals to disperse (Leidner & Haddad, 2011). In addition to restricting dispersal, human activity can directly alter animal movement. Mammals living in areas with high human footprint reduced their median displacement by half compared to mammals in areas with a lower human footprint (Tucker et al., 2018). Animal populations that face rapid human-induced landscape changes, such as the development of roads or buildings, are predicted to be at risk of mortality since they have no a priori experience on how to respond to such modifications in the environment (Fahrig, 2007).

In the past decade, there has been a growing trend to review and synthesize studies in the field of movement ecology. For example, reviews tracking specific organisms such as bumblebees (Mola & Williams, 2019) or wild boar Sus scrofa (Morelle, Lehaire & Lejeune, 2014; Morelle et al., 2015) have highlighted technological advances and synthesized the state of knowledge for those species. Other reviews have identified gaps relating to our understanding of movement of a broad group of organisms, such as amphibians (Pittman, Osbourn & Semlitsch, 2014) and marine megafauna (Hays et al., 2016). There have also been reviews that examine the potential for animal tracking studies to contribute to conservation (Allen & Singh, 2016; Doherty & Driscoll, 2018; Katzner & Arlettaz, 2020). Additionally, there are reviews related to the increasingly advancing tracking technology (Sherub et al., 2017; Hofman et al., 2019), and the analytical methods to analyse fine-scale spatial data (Long & Nelson, 2013; Thums et al., 2018; Joo et al., 2020). Very few publications have explicitly reflected on the field at regional or country-wide scales, except for the Arctic region, where reviews have highlighted changes in terrestrial mammal migration patterns (Berteaux & Lai, 2021) and movements under threat of rapid climate change (Davidson et al., 2020).

Some of the most populated countries in the world, such as the Indian subcontinent are also biodiversity hotspots, and contain the largest populations of wild fauna, such as elephants, tigers, and other charismatic endangered wildlife. Species in countries such as India, face a double whammy of having to deal with global change in an environment with amongst the highest densities of people, and rapidly shrinking natural habitats. Given that movement ecology studies are essential to understand the ways in which animals respond to the environment, including anthropogenic modification and climate change, it is critical to synthesize the current state and advancements in the field for the country. Therefore, we take this opportunity to review how researchers have studied movement ecology in India. India is varied both in its geography and climate. The country hosts four biodiversity hotspots—from the Himalayas in the north and the Indo-Burma region in the northeast, to the Sundalands (Andaman & Nicobar Islands) in the southeast, and Western ghats in the southwest. The subcontinent varies climatically with glaciers in the north to deserts in the west, and rainforests in the northeast and southwest. India occupies 2.2% of the world’s land area but is home to 8.42% of all mammals, 13.66% of all birds, 8.05% of all reptiles, and 5.07% of all the amphibians (Ministry of Environment and Forests, Kalpavriksh, 2004). However, only 5.03% of the total land area of India falls under Protected Areas (PAs) (Forest Survey of India, 2019).

Two major environmental challenges that animals face in India are rapid and extensive changes to land cover and climate change. Although land-use changes have slowed since the 1980s with forest protection laws (Tian et al., 2014), certain regions, such as the Himalayas still face the threat of land-use change and fragmentation (Batar, Watanabe & Kumar, 2017). Changes in land use and land cover not only act as barrier for animal movement, but also contribute to changes in the climatic conditions of the region. Increasing urbanization in the southern parts of India increases surface temperature and seem to contribute to heavy rainfall events (Boyaj et al., 2020). Increasing agriculturalization in the western parts of India is likely to exacerbate desertification in the arid region (Varghese & Singh, 2016). Increasing urbanization has resulted in urban heat islands, in which urban areas are hotter than peripheral areas, in multiple Indian cities (Singh, Kikon & Verma, 2017; Swain et al., 2017; Puppala & Singh, 2021). Climate change projections from the country also indicate shifts in forest types (Ravindranath et al., 2006), and the forest vegetation itself being vulnerable in parts of western ghats, central India and upper Himalayas (Chaturvedi et al., 2011). Besides changes in vegetation that might require animals to disperse to suitable habitats, animals might also face the more immediate unpredictability of seasonality. The monsoon, a major seasonal phenomenon in the country, is expected to be delayed in the future by 10–15 days in many parts, and precipitation levels are expected to be 70% less than normal (Loo, Billa & Singh, 2015). These current and future environmental changes clearly show that it is crucial for animals to track changes and utilise movement strategies that facilitate their immediate survival, or even disperse into suitable habitats for sustained persistence.

This review aims to examine the last decade (2011–2021) of movement ecology studies in India and re-evaluates the extent of research gaps highlighted by Habib et al. (2014). By taking stock of all the animal tracking studies across India, we will also identify gaps in the taxa studied, landscapes where they are carried out, and research objectives. We conclude by identifying prospective research directions and proposing ways in which new studies could potentially contribute to the field of movement ecology, especially in an anthropogenically-changing India.

Survey methodology

Movement ecology studies (peer-reviewed publications and reports) published between 2011–2021 were curated using two search engines: Google Scholar and Scopus. The primary keywords used for gathering these studies were ‘radio telemetry’, ‘satellite telemetry’, ‘GPS telemetry’, ‘home range’, ‘habitat use’, and ‘movement patterns’. Other keywords used in conjugation were ‘dispersal’ AND ‘distance’, ‘movement’ AND ‘animal’. All searches were screened with the keyword ‘India’ to narrow down the studies from the country. The criteria for selecting the publications from the search results were (1) the movement of the animal should be tracked within the country (2) individual animals (or group) must be identified with the tracking device attached to it, or through visual identification or genetic data (3) animals tagged outside the country but migrating into India were not included in the study, but global studies that include movement data from animals in India as well as other countries were included, and (4) movement of animals in laboratory conditions were not included. The search criteria for the Scopus database were restricted to ‘Title’, ‘Abstract’ and ‘Keywords’ of the publication. For the Google Scholar search engine, no such search restriction was imposed, but the search results were restricted to the first 10 pages (or 100 studies) (see Table S1 for details related to the search results). For additional information on the search process see the PRISMA 2020 flowchart and checklist in the supplementary (Page et al., 2021).

We summarised the published studies of animal movement from India between 2011–2021 and compared these with the previous review by Habib et al. (2014). Specifically, we discuss the number of publications during this period, species of animal taxa studied, region of the country the animals were tracked in, technology used for tracking and research goals of the publications.

Results and discussion

Number of publications in the field of movement ecology from India

As expected, the number of publications (Figs. 1A and 1B) in the field of movement ecology from India has increased significantly over the years (Estimate = 0.082, P < 0.001, GLM: family=Poisson, link=log). This corresponds to the overall increase in the number of publications in the field due to advances in tools and technology—decreasing size and cost of tracking devices, the ability to collect finer-scaled spatio-temporal data and the development of appropriate and expansive statistical methods (Joo et al., 2018). The rapid increase in research publications in the field of movement ecology from India is also apparent when comparing the two different periods in which it is reviewed—Habib et al. (2014) reported 49 journal publications and reports between from 1985–2010 (26-year period) (Habib et al., 2014), and this study reports 82 between 2011–2021 (11-year period) (see Table S2).

Figure 1. Number of publications in the field of movement ecology across years (1985–2021) from India.

Figure 1

(A) Number of publications in the field of movement ecology across years (1985–2021) from India. The studies published between 1985–2010 were included in the review by Habib et al. (2014). (B) The trendline represents overall increase in number of publications in the field of movement ecology from India across years.

Taxa tracked across publications

Amongst the research published in the past decade, mammals are the dominant taxa studied (76%; 62/82), followed by birds (13/82) and then reptiles (7/82) (Fig. 2A). Among mammals, the tiger, Panthera tigris alone accounted for 27% of the studies (22/82). Mammals were also the most dominant taxa tracked during the period from 1985–2010, and the tiger was the most dominant species among these as well. Due to this species bias, 78% of the animals tracked in the publications fall under the ‘Endangered’ or ‘Vulnerable’ threat categories of the International Union for Conservation of Nature (IUCN). However, among the 51 species tracked across all publications, 28 were in the ‘Endangered’ or ‘Vulnerable’ category while the rest were under ‘Least Concern’ or ‘Near Threatened’ (Fig. 2B). Only three of the 82 studies in this review tracked marine animals (Fig. 2C).

Figure 2. Different taxa tracked in movement ecology studies across India from 2011 to 2021, their IUCN status, methodology used for tracking, and geographic distribution of the studies.

Figure 2

Between 2011–2021, from studies in India, (A) relative proportion of different taxa tracked in movement ecology studies (n = 82) (B) IUCN status of the 51 unique taxa tracked; EN, Endangered; VU, Vulnerable; NT, Near Threatened; LC, Least Concern (C) number of studies that tracked animal movement within terrestrial protected areas (PAs), in both protected areas and human-modified terrestrial landscapes (others), and in the ocean (D) methods employed for animal tracking, which include visual detection, non-invasive genetic tools, VHF and GPS collars. Shown also are the (E) geographical distribution of movement ecology studies in each state of India between 2011–2021 in India. In cases where a study is carried out in multiple states of the country the study is pseudo-replicated.

Number of publications across the country

The review reveals that movement ecology studies are unequally distributed across the country (Fig. 2E). Most studies come from parts of Central and Western India—Madhya Pradesh (17) Rajasthan (13) and Maharashtra (eight). Majority of the studies on the two big cats, tigers, and leopards (86%) also come from these states. Other states that dominate the publications are Karnataka (10), West Bengal (seven), Tamil Nadu (five) and Assam (five). Very few published studies have tracked species in the north of India specifically in the Himalayan regions—a trend that was also identified by Habib et al. (2014).

Methods for recording movement

The technology used for tracking animals in the studies included in this review fell into a few broad categories. Majority of studies (80%; 66/82) used Very High Frequency (VHF) radio transmitters, or GPS transmitters attached to animals for tracking movement (Fig. 2D). GPS transmitters (used in 37/82 studies) included devices that transmit spatial data to hand-held receivers, mobile networks, or satellites.

Non-invasive methods such as identifying individuals through visual encounters, through photographs from camera traps, or through genetic data from fur or fecal samples formed the rest of the movement studies (16/82). Non-invasive methods use unique intrinsic markers of individuals, such as coat patterns and genetic information for infer movement and displacement across the landscape (Hobson & Ryan Norris, 2008). For example, images from camera traps were used to identify and estimate the home ranges of leopards (Kumbhojkar et al., 2020), dispersal distance of tigers (Singh et al., 2013) and space acquisition of vacated sites in tigers (Singh et al., 2020). Genetic evidence from tigers have been crucial to infer movement (Reddy et al., 2012) and dispersal patterns (Gour et al., 2013), and to determine whether tiger populations were connected across human-modified landscapes in central India (Joshi et al., 2013). Studies on the home range of primates have used visual identification to record movement of the groups. For example, the home range of Eastern Hoolock Gibbon Hoolock leuconedys (Sarma & Kumar, 2016), Lion-tailed macaques Macaca Silenus (Erinjery, Kavana & Singh, 2015; Santhosh et al., 2015) and Rhesus macaque Macaca mulatta (Sengupta, McConkey & Radhakrishna, 2015) were recorded by observers using hand-held GPS devices.

Research goals across publications

Home range and monitoring

Over the last decade, the research goal in 60% (49/82) of the publications were predominantly centred on measuring the home ranges and/or habitat use of target species (see Table S2). Such a dominance towards examining species home range in studies was also observed by Habib et al. (2014). Unlike in the studies before 2010, recent studies investigated home-range sizes for different purposes (see Table S2). Several studies were designed to compare home range sizes across species based on body size to test allometric-based hypotheses (Namgail et al., 2014; Noonan et al., 2020; Katna et al., 2021), or for the same species across seasons (Erinjery, Kavana & Singh, 2015; Jha et al., 2018; Katna et al., 2021), or between sexes (Rana, Kalsi & Burra, 2012; Naha et al., 2016; Singh et al., 2016). These studies provide new insights, such as the observation that male tigers living in the mangroves of Sundarban had an average home range nearly twice that of females (Naha et al., 2016). Or that the home range size of the Bengal Florican Houbaropsis bengalensis tagged in Uttar Pradesh, India and Nepal, is greater in the non-breeding season than in the breeding season (Jha et al., 2018). Notably, newer studies have used home range data to understand how animals utilise human-modified landscapes (Kumbhojkar et al., 2020; Katna et al., 2021; Naha et al., 2021) or respond to new areas after translocation (see section on Movement ecology for conservation management below).

Besides information on the ranging behaviour of animals and how they use the landscape, recent studies have provided other valuable insights on target species through continuous monitoring of movement. For example, fecal glucocorticoid metabolites collected from tracked tigers show elevated stress levels in response to anthropogenic disturbance (Bhattacharjee et al., 2015). Continuous animal tracking also reveals information on inter-birth intervals in female tigers (Sadhu et al., 2017) which is essential for understanding the population dynamics of this endangered species.

Animals tracked in human-modified landscapes (HMLs)

Most animals are not confined to protected areas (PAs) and are likely to move in and out of HMLs. Among the publications since 2011, 54% (44/82) of studies were from animals tracked in PAs, while 43% (35/82) were of either animals that shuttled between PAs and HMLs or were moving exclusively in HMLs (Fig. 2C). In HMLs, animals make decisions on whether to use the remnant native vegetation or the human-modified agricultural areas. For example, in a semi-arid landscape of western India, the Indian fox Vulpes bengalensis range mainly in fragmented native grasslands, whereas Golden jackals Canis aureus and Jungle cats Felis chaus readily utilise plantations and other human-modified areas of the landscape (Katna et al., 2021). For the Lesser false vampire bat Megaderma spasma, remnant forest patches in the western Ghats were selected over plantations (Prakash et al., 2021). But such habitat selection might change across seasons. The Leopard Panthera pardus in a fragmented landscape in eastern India selects dense forest patches in the wet season but was found using plantations during the dry season (Naha et al., 2021). Besides habitat use, movement patterns and decisions of animals also differ based on whether the animal is found within the PAs or outside. For example, the hourly displacement of tigers outside PAs is greater than within PAs (Habib et al., 2021). Another challenging movement that large carnivores carry out in their lifetime is long-distance dispersal to suitable habitats, which in India, involves travelling through human-modified landscapes. Individual tigers can disperse nearly ~700 km (established through genetic analysis) but their dispersal is negatively affected by human settlements and roads (Joshi et al., 2013).

Consequences of animal movement

Another major development in the field of movement ecology has been to relate animal movement with consequences for the biotic community. Such studies are especially relevant for frugivores and the seeds of plant species they disperse. Naniwadekar et al. (2019) showed that the average seed dispersal distance (computed from animals’ movement & gut passage time) of the Great hornbill Buceros bicornis was lower than the dispersal distance of the Wreathed hornbill Rhyticeros undulatus. These birds also differ in distances they travel in the breeding and non-breeding season, which can directly influence dispersal distance (Naniwadekar et al., 2019, 2021). Studies like these have consequences for the management of invasive plant species in an area, since seed dispersal patterns are affected by the distance and movement strategies of dispersers, such as birds that consume the fruits (Ramaswami et al., 2016). Similarly, data from GPS-telemetry on Asian elephants in tropical moist forests of northern West Bengal were used to model fruit dispersal; this study showed that elephants were more effective dispersers of three tropical large-fruited species compared to other large mammals, such as bovids (Sekar, Lee & Sukumar, 2015, 2017). The seed dispersal function of Asian elephants may be essential for the persistence of these tree species when impacted by habitat fragmentation and climate change (Sekar, Lee & Sukumar, 2015, 2017). Humans can also affect seed dispersal patterns. Rhesus macaque Macaca mulatta, had shorter ranges when provisioned by humans than when they were not provisioned, resulting in shorter dispersal distances for the plant seeds the animals consumed (Sengupta, McConkey & Radhakrishna, 2015).

Movement ecology for conservation management

Studies examining the home range of animals, or habitat use in natural areas provide key information about what a species requires for its survival. Such information provides baseline data for conservation plans in a protected landscape. Particularly relevant among these are studies that track the movement of a reintroduced or translocated animal to understand how they use new environments (Jha, 2011; Sankar et al., 2013; Sarkar et al., 2016; Bhardwaj et al., 2021). Home range information has been used to monitor reintroduced or translocated species—tigers (Bhardwaj et al., 2021), leopard (Mondal et al., 2013) one-horned rhino Rhinoceros unicornis (Barman et al., 2014; Dutta et al., 2017), sloth bear Melursus ursinus (Arun et al., 2021) and translocated king cobra Ophiophagus hannah (Barve et al., 2013) to understand how they were acclimatising to their new environments. The recent introduction of the cheetah Acinonyx jubatus jubatus to Kuno National Park in India will also utilise movement data from satellite collars to determine home-range and habitat selection of these individuals in their new environment (see Table S3). When tigers were re-introduced to Panna Tiger Reserve, movement data across generations were key to understanding how tigers were using human-dominated areas and what factors could result in human-wildlife conflict (Kolipaka et al., 2018). Using animal tracking to understand and mitigate human-wildlife conflict is especially relevant in the case of elephant-human conflict, in which continuous monitoring and rapid response helps reducing crop loss or, threats to humans (Venkataraman et al., 2005) and prevents elephant mortality when they cross roads or railways (Datta et al., 2016). Asian elephants are being monitored in many parts of the country by the state forest departments to reduce conflict—from the state of Karnataka in the south to Uttarakhand in the north, and Odisha, West Bengal, Tripura and Assam in the east (see Table S3 for sources to newspaper articles), and the scientific findings of these are forthcoming.

Another significance of studying movement is the conservation implication it has for marine animals. Recent studies from India have tracked the post nesting migration routes of Olive ridley turtles Lepidochelys olivacea in Odisha coast (Behera et al., 2018) and Leatherback turtles Dermochelys coriacea from Andaman Islands (Swaminathan, Namboothri & Shanker, 2019). Such studies are not just useful for identifying the external factors such as sea surface temperature and chlorophyll concentration that influence turtle movement (Behera et al., 2018) but are also valuable to identify regions along the migratory route where protective measures, such as programs to reduce fishing pressure, can be implemented (Swaminathan, Namboothri & Shanker, 2019).

Besides reducing conflict, recent efforts to track animals in human-modified landscapes (Habib et al., 2021; Katna et al., 2021; Naha et al., 2021) are crucial to identify corridors and manage connectivity that facilitate species dispersal across landscape matrices. Facilitating connectivity, based on actual movement data, is an essential step towards enabling successful dispersal considering potential alterations to environments.

Animal movement in response to climate change

No study from India has explicitly explored how climate change might affect animal movement behaviour. Recent studies that have examined seasonal shifts in animal movement (Namgail et al., 2011; Erinjery, Kavana & Singh, 2015) provide critical indications of how temperature and precipitation patterns influence movement strategies. Newer studies are starting to also examine how species distributions are likely to shift with future climate change predictions (Jose & Nameer, 2020; Raman et al., 2020). For example, the Indian Peafowl Pavo cristatus is predicted to expand its distribution in response to changes in temperature and precipitation (Jose & Nameer, 2020). This species-level prediction does not, however, reveal how individuals may respond to climate change within their lifetime.

One particularly significant movement decision related to global change is migration patterns. Since animals use environmental cues to time migration and navigation (Seehacher & Post, 2015), migrating animals are expected to be amongst the first responders to changing climatic conditions. Recently published studies from India have identified migratory routes of Black kite Milvus migrans, (Kumar et al., 2020), Lesser florican Sypheotides indica (Sivakumar et al., 2016), Bar-headed geese Anser indicus (Hawkes et al., 2011; Mohit et al., 2011) and Leatherback sea turtle Dermochelys coriacea (Swaminathan, Namboothri & Shanker, 2019). Most studies used satellite transmitters to track animal migrations, however there are other techniques, such as quantifying stable isotopes from animal tissue to infer movement patterns (Hobson & Ryan Norris, 2008). Stable isotopes are used for tracking migration and space use patterns in a range of animals, including marine species (Ramos & González-Solís, 2012) and terrestrial species (Rubenstein & Hobson, 2004). However, we found no publications from India thus far that uses stable isotopes to answer questions relating to movement of animals. More such studies on migratory routes combined with long-term monitoring of arrival and departure times will provide the necessary information about climate-induced changes to movement decisions of animals, such as birds or butterflies. It would also be relevant to study migration patterns across years in relatively long-lived species, such as mammals (e.g., elephants) or marine taxa (e.g., sea turtles), to determine how individuals cope with the changes in the environment during their lifetime.

Conclusion

Potential research directions for India in the field of movement ecology

Given the rapid growth and current state of the field of movement ecology in India, the possibility for generating new knowledge is abundant. This literature review, spanning movement ecology research in India over the last 11 years, shows the disproportionate focus on some taxa (e.g., tigers) and some metrics of movement (e.g., home range). We take this opportunity to call for a broadening of the scope of movement ecology studies, bringing forth the most urgent needs of the field. We also seek to identify where the unique biogeography and biodiversity of India can provide interesting opportunities for research in this field (Table 1).

Table 1. Prospective research directions in the field of movement ecology and potential questions that can be investigated in India.

No. Research topics Potential questions to address
1. Tracking species across seasons and years
Inline graphic
How do animals in different biogeographic zones track climatic changes?
2. Tracking species across different landscapes
Inline graphic
How generalised are species responses, or are movement strategies driven mainly by the immediate environment?
3. Tracking many individuals
Inline graphic
How do conspecific interactions influence individual movement decisions?
4. Tracking species outside protected areas
Inline graphic
What are the strategies and limitations that enable animals to survive with anthropogenic alterations to their environment?
5. Tracking diverse taxa in the same area
Inline graphic
How do species traits individually or in combination affect the movement decisions of a taxa?
6. Tracking smaller taxa
Inline graphic
How do smaller animals make movement decisions, from daily foraging across habitats to long-distance migration across continents?
7. Tracking marine and freshwater taxa
Inline graphic
What are the migratory patterns of marine taxa? How do humans impact their movement? Are there eco-sensitive areas that need additional protection?
8. Tracking animals to reduce human-wildlife conflict
Inline graphic
Are there patterns of animal movement that enable proactive and anticipatory action to mitigate human-wildlife conflict?
9. Tracking animals and ecological processes
Inline graphic
How does animal movement impact various ecological processes, such as seed dispersal or pollination? How does global change affect these crucial functions?
10. Tracking animals with different sensors
Inline graphic
What environmental variables best track changing conditions and how do they influence animal movement?
  1. There is considerable insight that can be gained from tracking species over long periods of time, such as multiple seasons and years. Movement decisions of animals are driven in large part by distribution and availability of resources, which change with seasonality (Abrahms et al., 2021). Seasonality in India is influenced by various spatially explicit factors. Parts of India receive the bulk of the monsoon rains and these regions can be divided into the wet and dry seasons. Southern parts of the country are tropical, while the northern parts are sub-tropical to temperate. Some parts of India are also projected to face greater effects of climate change than others, compounding the impacts on environments. Understanding whether and in what ways animals can respond to natural and human-induced climatic shifts across years, through long-term studies, will enable us to determine how quickly animals, resources and their drivers can respond.

  2. Patterns of resource distribution varies across landscapes, and thus the same species in different environments are expected to differ in their movement decisions (Shepard et al., 2013). Monitoring animals across different landscapes enables us to infer the significant drivers of movement and their variation, to determine how much of movement strategies are inherent to the species, and how much are driven by local environmental conditions. From evergreen forests in the southwest and northeast to arid deserts in the west and snow-clad mountains in the north, India possesses diverse landscapes. Each landscape consists of species adapted to the region, but they also share some species. Thus, tracking the same species in different environments across seasons, is a powerful approach, especially in the context of global change.

  3. The movement strategies of individuals are not only driven by environmental conditions but are also influenced by interactions with conspecifics. Simultaneous tracking of many interacting individuals in an area will provide insights into how social interactions influence decision-making and space-use patterns (reviewed in Westley et al., 2018). Until now, most animal tracking in India has been confined to understanding the extent of space-use patterns of a few individuals of a species. Multiple individuals are rarely tracked together, and thus, the contribution of group members or conspecifics to movement decisions is an exciting research direction.

  4. Natural spaces for animals are reducing (Hirt et al., 2021) and animals are increasingly forced to utilise landscapes modified by humans. Many species might curtail their movement altogether in these altered landscapes (Tucker et al., 2018). Such impedance to movement may affect the animal’s dispersal (Chazdon et al., 2009) and in the long term, species distribution. India has a population of ~1.35 billion people spread across urban and rural areas, and thus, human-animal encounter rates are high. Dedicated wildlife habitats in India are fragmented and are flanked by either residential, agricultural, and/or industrial developments. Tracking species outside protected areas will generate a stronger understanding of the strategies and constraints that enable animals to survive in an era of global change, which includes a moving animal being able to tackle both climate change and land transformation (Sage, 2019).

  5. The movement behaviours and strategies of animals are influenced by multiple intrinsic factors, such as size (Jetz et al., 2004), morphology (Börger et al., 2020), and cognitive ability (Kashetsky, Avgar & Dukas, 2021). To make generalizable predictions of animal movement that examine the effects of intrinsic differences while controlling for extrinsic or environmental factors (Nathan et al., 2008), tracking different kinds of taxa in the same area is a powerful approach. India hosts ~400 mammals, ~1,400 birds, and ~600 reptiles and amphibian, and thus the opportunities to track diverse taxa that play key functional roles within an ecosystem is immense.

  6. Obtaining movement data from smaller vertebrates and invertebrates is a challenge, given that bio-loggers must be miniature and weigh a fraction of the animal’s weight. Animals as small as bumblebees (200–450 mg; Hagen, Wikelski & Kissling, 2011) and butterflies (300–700 mg; Fisher, Adelman & Bradbury, 2020), have been tracked to determine flight paths, space use, and migration patterns. Other technological advances with projects such as ICARUS (Belyaev et al., 2020; Jetz et al., 2022) and wireless network sensors (Ripperger et al., 2020) have made the fine-scale tracking of numerous small taxa more feasible today. Given that the technology to track the movement of smaller animals is rapidly advancing, future studies that track the movement of insects, smaller mammals, and birds in India, will provide key insights on species that have not been tracked before.

  7. The marine ecosystem offers an opportunity to address many key ecological questions—from the influence of memory or learning, and social interactions, to prey distribution, and the impact of global change (Hays et al., 2016). Marine animals with sensors can potentially act as sentinels and record environmental variables in regions in the ocean not commonly sampled, which will allow us to better understand climate and ocean variability (McMahon et al., 2021). With a coastline of ~7,500 km, there is immense potential to track the movement of various marine animals to provide relevant information for the conservation of species and ecologically sensitive marine zones of India.

  8. Animal tracking has a direct application in regions with human-wildlife conflict. Tracking animals is not only useful for understanding animal movement, but it helps reduce conflict by sending early warning signals to alert people to the location of the animal so they can take pre-emptive action (Venkataraman et al., 2005). In India, animal tracking studies on large carnivores (such as tigers and leopards), or herbivores (such as elephants, wild pigs Sus scrofa, and nilgai Boselaphus tragocamelus) can help mitigate direct and indirect human-wildlife conflict. Animal tracking information in combination with early warning signal alerts, can potentially prevent human deaths and infrastructure damages (Kumar & Raghunathan, 2014), reduce agricultural crop damages, and avoid railway collisions of wildlife (Datta et al., 2016). Such studies can also determine barriers and corridors to movement (Joshi et al., 2013). Additionally, citizen-science information of animal locations would be a valuable complement to telemetry data, enabling a better understanding of animal movement decisions, especially of species prone to human-wildlife conflict.

  9. Animal tracking studies are crucial for understanding how movement affects ecosystem processes in a landscape. Movement of frugivorous birds (Ramaswami et al., 2016; Naniwadekar et al., 2019, 2021) and mammals (Sekar, Lee & Sukumar, 2015) have implications for where plants species disperse their seeds and their future survival. Loss of this dispersal service will directly affect the capacity of plant species to respond to changing climatic conditions (Mokany, Prasad & Westcott, 2014). Landscape fragmentation also affects the movement of bees and butterflies, and therefore impacts plant pollination (Hadley & Betts, 2012). Additionally, megaherbivores like an elephant trampling through a forest can engineer ecosystems by changing vegetation patterns (Haynes, 2012). Given the latest advances in animal tracking devices (see (6) and (10) in this section) it is now possible to study how animal movement influences ecological processes in different climatic regions across India.

  10. Technological advances have spearheaded the field of movement ecology over the last two decades in ways that enable the tracking of species as well as their environments (Kays et al., 2015; Sherub et al., 2017). Innovations in technology, methods to analyse big data (Thums et al., 2018) and sensors that record different kinds of information (Sherub et al., 2017), have all expanded the scope to ask newer ecological questions related to the movement decisions of animals. This also allows for the standardisation of bio-logging devices for conservation management use (Sequeira et al., 2021). Additionally, collared animals themselves can now be used to collect fine-scaled data on the environments they utilise (Börger et al., 2020; Thaker et al., 2019). With the available tracking technologies, it’s now possible to understand and mitigate the impacts of global change, a direction that India is primed to pursue. Going beyond the focus of individual species or specific geographic regions in India, we can now track animal movement with environmental sensors that also track temperature, wind pressure, sound, and several other key parameters.

Limitations to this review and to the growth of movement ecology in India

To the best of our knowledge, we have conducted an exhaustive search of animal movement studies carried out in India over the last 11 years. We acknowledge that some studies may have been missed, especially if these were not published in peer-reviewed journals listed on SCOPUS or Google Scholar. For example, many state forest departments collar and track species of interest for general monitoring and to mitigate wildlife conflict. These data are typically not available for public access or published in scientific journals. Additionally, studies with low sample sizes are more likely summarised in reports to granting agencies or forest departments, which are also not accessible. Therefore, the taxa that we identify as having been collared or tagged over the last decade is likely to be missing species. There has, however, been a new push to tagging and tracking animals and many of these initiatives have been announced in newspapers or social media (see Table S3), and so the field of movement ecology in India is set to see a rapid period of growth. Overall, our review effectively captures the general trends and approaches in the field of movement ecology in the country and has allowed us to identify research gaps and future research directions. Some of the potential research directions that we propose, for example monitoring animal movement in human modified landscapes to reduce wildlife conflict, have already been initiated. Similarly, the tagging of migratory species, such as the endangered Great Indian Bustard, is also ongoing and is of urgent national importance. Although not included here, these studies reflect new and necessary directions for this field.

Among the shortcomings identified in the previous review from India, by Habib et al. (2014), a lack of animal tracking studies from the northern part of India, an emphasis on certain research goals (e.g., home-ranges and habitat selection), and the need for a centralised system to ease the permission to capture and collar animals, were highlighted. While there appears to be a positive trend to address some of these issues, most of the deficiencies still exist. One way to address these gaps is by forming a biologging group/forum/conclave that brings together both experts and stakeholders from various research institutions, state forest departments, and conservation organizations to share information, technology, and collaborate on future projects across the county. Collaborations between research institutions and government agencies might help reduce the difficulties in obtaining research permits for capturing and collaring animals and may directly facilitate conservation management goals. Additionally, we urge researchers from India to adopt an open data policy whenever possible, which would involve uploading animal movement data, both published and ongoing, to global databases, such as Movebank (Kays et al., 2022). By joining the global initiative of movement ecology, researchers from India have larger opportunities to collaborate on global-level analyses of animal movement. In the rapidly changing Anthropocene, where anthropogenic disturbance and climatic change are irreversibly altering the Earth, collaborative global approaches to tag, track, and understand animal movements is essential to understand species responses and to mitigate impacts on crucial ecosystem functions.

Supplemental Information

Supplemental Information 1. Search results from keywords, list of publications, and ongoing studies in the field of movement ecology.
DOI: 10.7717/peerj.14401/supp-1
Supplemental Information 2. Prisma Checklist for the systematic review.
DOI: 10.7717/peerj.14401/supp-2
Supplemental Information 3. Prisma flow diagram of the survey and the final number of studies retrieved for the review.
DOI: 10.7717/peerj.14401/supp-3

Funding Statement

Funding for this review was provided by the Long-term Ecological Observatories Program of the Ministry of Environment, Forests, and Climate-Change to Maria Thaker. Raman Sukumar is a National Science Chair supported by the Science and Engineering Research Board (SERB) of the Government of India. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Contributor Information

Harish Prakash, Email: harishp@iisc.ac.in.

Maria Thaker, Email: mthaker@iisc.ac.in.

Additional Information and Declarations

Competing Interests

The authors declare that they have no competing interests.

Author Contributions

Harish Prakash conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the article, and approved the final draft.

R. Suresh Kumar conceived and designed the experiments, authored or reviewed drafts of the article, and approved the final draft.

Bibhuti Lahkar conceived and designed the experiments, authored or reviewed drafts of the article, and approved the final draft.

Raman Sukumar conceived and designed the experiments, authored or reviewed drafts of the article, and approved the final draft.

Abi T. Vanak conceived and designed the experiments, authored or reviewed drafts of the article, and approved the final draft.

Maria Thaker conceived and designed the experiments, performed the experiments, prepared figures and/or tables, authored or reviewed drafts of the article, and approved the final draft.

Data Availability

The following information was supplied regarding data availability:

The data is available in the Supplemental File.

References

  • Abrahms et al. (2021).Abrahms B, Aikens EO, Armstrong JB, Deacy WW, Kauffman MJ, Merkle JA. Emerging perspectives on resource tracking and animal movement ecology. Trends in Ecology and Evolution. 2021;36(4):308–320. doi: 10.1016/j.tree.2020.10.018. [DOI] [PubMed] [Google Scholar]
  • Allen & Singh (2016).Allen AM, Singh NJ. Linking movement ecology with wildlife management and conservation. Frontiers in Ecology and Evolution. 2016;3:1–13. doi: 10.3389/fevo.2015.00155. [DOI] [Google Scholar]
  • Arun et al. (2021).Arun AS, Swaminathan S, Pannerselvam Y, Sharp TR, Stephens SR, Satyanarayan K, Seshamani G. Relocation of a GPS collared conflict Sloth Bear Melursus ursinus (Mammalia: Carnivora) in Karnataka, India. Journal of Threatened Taxa. 2021;13(3):17856–17864. doi: 10.11609/jott.5947.13.3.17856-17864. [DOI] [Google Scholar]
  • Barman et al. (2014).Barman R, Choudhury B, Ashraf N, Menon V. Rehabilitation of greater one-horned rhinoceros calves in Manas National Park, a World Heritage Site in India. Pachyderm. 2014;55:78–88. [Google Scholar]
  • Barve et al. (2013).Barve S, Bhaisare D, Giri A, Shankar PG, Whitaker R, Goode M. A preliminary study on translocation of “rescued” King Cobras (Ophiophagus hannah) Hamadryad. 2013;36:80–86. [Google Scholar]
  • Batar, Watanabe & Kumar (2017).Batar AK, Watanabe T, Kumar A. Assessment of land-use/land-cover change and forest fragmentation in the Garhwal Himalayan region of India. Environments. 2017;4(2):1–16. doi: 10.3390/environments4020034. [DOI] [Google Scholar]
  • Behera et al. (2018).Behera S, Tripathy B, Choudhury BC, Sivakumar K. Movements of Olive Ridley Turtles (Lepidochelys olivacea) in the Bay of Bengal, India, determined via satellite telemetry. Chelonian Conservation and Biology. 2018;17(1):44–53. doi: 10.2744/CCB-1245.1. [DOI] [Google Scholar]
  • Bell (1990).Bell WJ. Searching behaviour. Dordrecht: Springer. Science+Business Media; 1990. [Google Scholar]
  • Belyaev et al. (2020).Belyaev MY, Volkov ON, Solomina ON, Weppler J, Mueller U, Tertitski GM, Wikelski M, Pitz W. Development of technology for monitoring animal migration on earth using scientific equipment on the ISS RS. 27th Saint Petersburg International Conference on Integrated Navigation Systems, ICINS 2020—Proceedings; 2020. pp. 1–7. [Google Scholar]
  • Berteaux & Lai (2021).Berteaux D, Lai S. Walking on water: terrestrial mammal migrations in the warming Arctic. Animal Migration. 2021;8(1):65–73. doi: 10.1515/ami-2020-0111. [DOI] [Google Scholar]
  • Bhardwaj et al. (2021).Bhardwaj S, Selvi G, Agasti S, Kari B, Singh H, Kumar A, Gupta R, Reddy G. The spacing pattern of reintroduced tigers in human-dominated Sariska Tiger Reserve. Journal of Wildlife and Biodiversity. 2021;5:1–14. [Google Scholar]
  • Bhattacharjee et al. (2015).Bhattacharjee S, Kumar V, Chandrasekhar M, Malviya M, Ganswindt A, Ramesh K, Sankar K, Umapathy G. Glucocorticoid stress responses of reintroduced tigers in relation to anthropogenic disturbance in Sariska Tiger Reserve in India. PLOS ONE. 2015;10(6):e0127626. doi: 10.1371/journal.pone.0127626. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Börger et al. (2020).Börger L, Bijleveld AI, Fayet AL, Machovsky-Capuska GE, Patrick SC, Street GM, vander Wal E. Biologging special feature. Journal of Animal Ecology. 2020;89(1):6–15. doi: 10.1111/1365-2656.13163. [DOI] [PubMed] [Google Scholar]
  • Boyaj et al. (2020).Boyaj A, Dasari HP, Hoteit I, Ashok K. Increasing heavy rainfall events in south India due to changing land use and land cover. Quarterly Journal of the Royal Meteorological Society. 2020;146(732):3064–3085. doi: 10.1002/qj.3826. [DOI] [Google Scholar]
  • Buchholz et al. (2019).Buchholz R, Banusiewicz JD, Burgess S, Crocker-Buta S, Eveland L, Fuller L. Behavioural research priorities for the study of animal response to climate change. Animal Behaviour. 2019;150(A):127–137. doi: 10.1016/j.anbehav.2019.02.005. [DOI] [Google Scholar]
  • Chaturvedi et al. (2011).Chaturvedi RK, Gopalakrishnan R, Jayaraman M, Bala G, Joshi NV, Sukumar R, Ravindranath NH. Impact of climate change on Indian forests: a dynamic vegetation modeling approach. Mitigation and Adaptation Strategies for Global Change. 2011;16(2):119–142. doi: 10.1007/s11027-010-9257-7. [DOI] [Google Scholar]
  • Chazdon et al. (2009).Chazdon RL, Harvey CA, Komar O, Griffith DM, Ferguson BG, Mart M. Beyond reserves: a research agenda for conserving biodiversity in human-modified tropical landscapes. Biotropica. 2009;41(2):142–153. doi: 10.1111/j.1744-7429.2008.00471.x. [DOI] [Google Scholar]
  • Datta et al. (2016).Datta N, Kumar S, Mallick A, Punetha D. Eradication of elephant mortality and injury due to railway accidents through automatic tracking and alert system. Proceedings–2016 International Conference on Advances in Computing, Communication and Automation, ICACCA 2016; Piscataway: IEEE; 2016. pp. 4–7. [Google Scholar]
  • Davidson et al. (2020).Davidson S, Bohrer G, Gurarie E, Lapoint S, Mahoney P, Boelman N, Eitel J, Prugh L, Vierling L, Jennewein J, Davidson S, Bohrer G, Gurarie E, Lapoint S, Mahoney P. Ecological insights from three decades of animal movement tracking across a changing Arctic. Science. 2020;370(6517):712–715. doi: 10.1126/science.abb7080. [DOI] [PubMed] [Google Scholar]
  • Doherty & Driscoll (2018).Doherty TS, Driscoll DA. Coupling movement and landscape ecology for animal conservation in production landscapes. Proceedings of the Royal Society B: Biological Sciences. 2018;285(1870):20172272. doi: 10.1098/rspb.2017.2272. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Dutta et al. (2017).Dutta DK, Sharma A, Mahanta R, Swargowari A. Behaviour of post released translocated greater one-horned Rhinoceros (Rhinoceros unicornis) at Manas National Park, Assam, India. Pachyderm. 2017;2017:58–66. [Google Scholar]
  • Egevang et al. (2010).Egevang C, Stenhouse IJ, Phillips RA, Petersen A, Fox JW, Silk JRD. Tracking of Arctic terns Sterna paradisaea reveals longest animal migration. Proceedings of the National Academy of Sciences of the United States of America. 2010;107(5):2078–2081. doi: 10.1073/pnas.0909493107. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Erinjery, Kavana & Singh (2015).Erinjery JJ, Kavana TS, Singh M. Food resources, distribution and seasonal variations in ranging in lion-tailed macaques, Macaca silenus in the Western Ghats, India. Primates. 2015;56(1):45–54. doi: 10.1007/s10329-014-0447-x. [DOI] [PubMed] [Google Scholar]
  • Fahrig (2007).Fahrig L. Non-optimal animal movement in human-altered landscapes. Functional Ecology. 2007;21(6):1003–1015. doi: 10.1111/j.1365-2435.2007.01326.x. [DOI] [Google Scholar]
  • Fisher, Adelman & Bradbury (2020).Fisher KE, Adelman JS, Bradbury SP. Employing very high frequency (VHF) radio telemetry to recreate monarch butterfly flight paths. Environmental Entomology. 2020;49(2):312–323. doi: 10.1093/ee/nvaa019. [DOI] [PubMed] [Google Scholar]
  • Forest Survey of India (2019).Forest Survey of India Forest cover. 2019. pp. 13–52. ISFR VOLUME I. Forest Survey of India.
  • Fraser et al. (2018).Fraser KC, Davies KTA, Davy CM, Ford AT, Flockhart DTT, Martins EG. Tracking the conservation promise of movement ecology. Frontiers in Ecology and Evolution. 2018;6:1–8. doi: 10.3389/fevo.2018.00150. [DOI] [Google Scholar]
  • Gour et al. (2013).Gour DS, Bhagavatula J, Bhavanishankar M, Reddy PA, Gupta JA, Sarkar MS, Hussain SM, Harika S, Gulia R, Shivaji S. Philopatry and dispersal patterns in tiger (Panthera tigris) PLOS ONE. 2013;8(7):14–17. doi: 10.1371/journal.pone.0066956. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Habib et al. (2021).Habib B, Ghaskadbi P, Khan S, Hussain Z, Nigam P. Not a cakewalk: insights into movement of large carnivores in human-dominated landscapes in India. Ecology and Evolution. 2021;11(4):1653–1666. doi: 10.1002/ece3.7156. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Habib et al. (2014).Habib B, Shrotriya S, Sivakumar K, Sinha PR, Mathur VB. Three decades of wildlife radio telemetry in India: a review. Animal Biotelemetry. 2014;2(1):1–10. doi: 10.1186/2050-3385-2-4. [DOI] [Google Scholar]
  • Hadley & Betts (2012).Hadley AS, Betts MG. The effects of landscape fragmentation on pollination dynamics: absence of evidence not evidence of absence. Biological Reviews. 2012;87(3):526–544. doi: 10.1111/j.1469-185X.2011.00205.x. [DOI] [PubMed] [Google Scholar]
  • Hagen, Wikelski & Kissling (2011).Hagen M, Wikelski M, Kissling WD. Space use of bumblebees (Bombus spp.) revealed by radio-tracking. PLOS ONE. 2011;6(5):e19997. doi: 10.1371/journal.pone.0019997. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Hawkes et al. (2011).Hawkes LA, Balachandran S, Batbayar N, Butler PJ, Frappell PB, Milsom WK, Tseveenmyadag N, Newman SH, Scott GR, Sathiyaselvam P, Takekawa JY, Wikelski M, Bishop CM. The trans-Himalayan flights of bar-headed geese (Anser indicus) Proceedings of the National Academy of Sciences of the United States of America. 2011;108(23):9516–9519. doi: 10.1073/pnas.1017295108. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Haynes (2012).Haynes G. Elephants (and extinct relatives) as earth-movers and ecosystem engineers. Geomorphology. 2012;157–158(2–3):99–107. doi: 10.1016/j.geomorph.2011.04.045. [DOI] [Google Scholar]
  • Hays et al. (2016).Hays GC, Ferreira LC, Sequeira AMM, Meekan MG, Duarte CM, Bailey H, Bailleul F, Bowen WD, Caley MJ, Costa DP, Eguíluz VM, Fossette S, Friedlaender AS, Gales N, Gleiss AC, Gunn J, Harcourt R, Hazen EL, Heithaus MR, Heupel M, Holland K, Horning M, Jonsen I, Kooyman GL, Lowe CG, Madsen PT, Marsh H, Phillips RA, Righton D, Ropert-Coudert Y, Sato K, Shaffer SA, Simpfendorfer CA, Sims DW, Skomal G, Takahashi A, Trathan PN, Wikelski M, Womble JN, Thums M. Key questions in marine megafauna movement ecology. Trends in Ecology and Evolution. 2016;31(6):463–475. doi: 10.1016/j.tree.2016.02.015. [DOI] [PubMed] [Google Scholar]
  • Hirt et al. (2021).Hirt MR, Barnes AD, Gentile A, Pollock LJ, Rosenbaum B, Thuiller W, Tucker MA, Brose U. Environmental and anthropogenic constraints on animal space use drive extinction risk worldwide. Ecology Letters. 2021;24(12):1–10. doi: 10.1111/ele.13872. [DOI] [PubMed] [Google Scholar]
  • Hobson & Ryan Norris (2008).Hobson KA, Ryan Norris D. Animal migration: a context for using new techniques and approaches. In: Hobson KA, Wassenaar LI, editors. Tracking Animal Migration with Stable Isotopes. London: Academic Press; 2008. pp. 1–19. [Google Scholar]
  • Hofman et al. (2019).Hofman MPG, Hayward MW, Heim M, Marchand P, Rolandsen CM, Balkenhol N. Right on track? Performance of satellite telemetry in terrestrial wildlife research. PLOS ONE. 2019;14:e0216223. doi: 10.1371/journal.pone.0216223. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Holyoak et al. (2008).Holyoak M, Casagrandi R, Nathan R, Revilla E, Spiegel O. Trends and missing parts in the study of movement ecology. Proceedings of the National Academy of Sciences of the United States of America. 2008;105(49):19060–19065. doi: 10.1073/pnas.0800483105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Jeltsch et al. (2013).Jeltsch F, Bonte D, Pe’er G, Reineking B, Leimgruber P, Balkenhol N, Schröder B, Buchmann CM, Mueller T, Blaum N, Zurell D, Böhning-Gaese K, Wiegand T, Eccard JA, Hofer H, Reeg J, Eggers U, Bauer S. Integrating movement ecology with biodiversity research—exploring new avenues to address spatiotemporal biodiversity dynamics. Movement Ecology. 2013;1(1):1–13. doi: 10.1186/2051-3933-1-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Jetz et al. (2004).Jetz W, Carbone C, Fulford J, Brown JH. The scaling of animal space use. Science. 2004;306(5694):266–268. doi: 10.1126/science.1102138. [DOI] [PubMed] [Google Scholar]
  • Jetz et al. (2022).Jetz W, Tertitski G, Kays R, Mueller U, Wikelski M, Åkesson S, Anisimov Y, Antonov A, Arnold W, Bairlein F, Baltà O, Baum D, Beck M, Belonovich O, Belyaev M, Berger M, Berthold P, Bittner S, Blake S, Block B, Bloche D, Boehning-Gaese K, Bohrer G, Bojarinova J, Bommas G, Bourski O, Bragin A, Bragin A, Bristol R, Brlík V, Bulyuk V, Cagnacci F, Carlson B, Chapple TK, Chefira KF, Cheng Y, Chernetsov N, Cierlik G, Christiansen SS, Clarabuch O, Cochran W, Cornelius JM, Couzin I, Crofoot MC, Cruz S, Davydov A, Davidson S, Dech S, Dechmann D, Demidova E, Dettmann J, Dittmar S, Dorofeev D, Drenckhahn D, Dubyanskiy V, Egorov N, Ehnbom S, Ellis-Soto D, Ewald R, Feare C, Fefelov I, Fehérvári P, Fiedler W, Flack A, Froböse M, Fufachev I, Futoran P, Gabyshev V, Gagliardo A, Garthe S, Gashkov S, Gibson L, Goymann W, Gruppe G, Guglielmo C, Hartl P, Hedenström A, Hegemann A, Heine G, Ruiz MH, Hofer H, Huber F, Hurme E, Iannarilli F, Illa M, Isaev A, Jakobsen B, Jenni L, Jenni-Eiermann S, Jesmer B, Jiguet F, Karimova T, Kasdin NJ, Kazansky F, Kirillin R, Klinner T, Knopp A, Kölzsch A, Kondratyev A, Krondorf M, Ktitorov P, Kulikova O, Kumar RS, Künzer C, Larionov A, Larose C, Liechti F, Linek N, Lohr A, Lushchekina A, Mansfield K, Matantseva M, Markovets M, Marra P, Masello JF, Melzheimer J, Menz MHM, Menzie S, Meshcheryagina S, Miquelle D, Morozov V, Mukhin A, Müller I, Mueller T, Navedo JG, Nathan R, Nelson L, Németh Z, Newman S, Norris R, Nsengimana O, Okhlopkov I, Oleś W, Oliver R, O’Mara T, Palatitz P, Partecke J, Pavlick R, Pedenko A, Perry A, Pham J, Piechowski D, Pierce A, Piersma T, Pitz W, Plettemeier D, Pokrovskaya I, Pokrovskaya L, Pokrovsky I, Pot M, Procházka P, Quillfeldt P, Rakhimberdiev E, Ramenofsky M, Ranipeta A, Rapczyński J, Remisiewicz M, Rozhnov V, Rienks F, Rozhnov V, Rutz C, Sakhvon V, Sapir N, Safi K, Schäuffelhut F, Schimel D, Schmidt A, Shamoun-Baranes J, Sharikov A, Shearer L, Shemyakin E, Sherub S, Shipley R, Sica Y, Smith TB, Simonov S, Snell K, Sokolov A, Sokolov V, Solomina O, Soloviev M, Spina F, Spoelstra K, Storhas M, Sviridova T, Swenson G, Taylor P, Thorup K, Tsvey A, Tucker M, Tuppen S, Turner W, Twizeyimana I, van der Jeugd H, van Schalkwyk L, van Toor M, Viljoen P, Visser ME, Volkmer T, Volkov A, et al. Biological Earth observation with animal sensors. Trends in Ecology and Evolution. 2022;37:293–298. doi: 10.1016/j.tree.2021.11.011. [DOI] [PubMed] [Google Scholar]
  • Jha (2011).Jha AK. Release and reintroduction of captive-bred red pandas into Singalila National Park, Darjeeling, India. Red Panda. 2011;2011:435–446. doi: 10.1016/B978-1-4377-7813-7.00025-2. [DOI] [Google Scholar]
  • Jha et al. (2018).Jha RRS, Thakuri JJ, Rahmani AR, Dhakal M, Khongsai N, Pradhan NMB, Shinde N, Chauhan BK, Talegaonkar RK, Barber IP, Buchanan GM, Galligan TH, Donald PF. Distribution, movements, and survival of the critically endangered Bengal Florican Houbaropsis bengalensis in India and Nepal. Journal of Ornithology. 2018;159(3):851–866. doi: 10.1007/s10336-018-1552-1. [DOI] [Google Scholar]
  • Joly et al. (2019).Joly K, Gurarie E, Sorum MS, Kaczensky P, Cameron MD, Jakes AF, Borg BL, Nandintsetseg D, Hopcraft JGC, Buuveibaatar B, Jones PF, Mueller T, Walzer C, Olson KA, Payne JC, Yadamsuren A, Hebblewhite M. Longest terrestrial migrations and movements around the world. Scientific Reports. 2019;9(1):1–10. doi: 10.1038/s41598-019-51884-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Joo et al. (2020).Joo R, Boone ME, Clay TA, Patrick SC, Clusella-Trullas S, Basille M. Navigating through the r packages for movement. Journal of Animal Ecology. 2020;89(1):248–267. doi: 10.1111/1365-2656.13116. [DOI] [PubMed] [Google Scholar]
  • Joo et al. (2018).Joo R, Etienne MP, Bez N, Mahévas S. Metrics for describing dyadic movement: a review. Movement Ecology. 2018;6(1):1–17. doi: 10.1186/s40462-018-0144-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Jose & Nameer (2020).Jose VS, Nameer PO. The expanding distribution of the Indian Peafowl (Pavo cristatus) as an indicator of changing climate in Kerala, southern India: a modelling study using MaxEnt. Ecological Indicators. 2020;110(20):105930. doi: 10.1016/j.ecolind.2019.105930. [DOI] [Google Scholar]
  • Joshi et al. (2013).Joshi A, Vaidyanathan S, Mondol S, Edgaonkar A, Ramakrishnan U. Connectivity of Tiger (Panthera tigris) populations in the human-influenced Forest Mosaic of Central India. PLOS ONE. 2013;8(11):e77980. doi: 10.1371/journal.pone.0077980. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Kashetsky, Avgar & Dukas (2021).Kashetsky T, Avgar T, Dukas R. The cognitive ecology of animal movement: evidence from birds and mammals. Frontiers in Ecology and Evolution. 2021;9:1–23. doi: 10.3389/fevo.2021.724887. [DOI] [Google Scholar]
  • Katna et al. (2021).Katna A, Kulkarni A, Thaker M, Vanak AT. Habitat specificity drives differences in space use patterns of multiple mesocarnivores in an agro-ecosystem. Journal of Zoology. 2021;316(2):92–103. doi: 10.1111/jzo.12933. [DOI] [Google Scholar]
  • Katzner & Arlettaz (2020).Katzner TE, Arlettaz R. Evaluating contributions of recent tracking-based animal movement ecology to conservation management. Frontiers in Ecology and Evolution. 2020;7:166. doi: 10.3389/fevo.2019.00519. [DOI] [Google Scholar]
  • Kays et al. (2015).Kays R, Crofoot MC, Jetz W, Wikelski M. Terrestrial animal tracking as an eye on life and planet. Science. 2015;348(6240):aaa2478. doi: 10.1126/science.aaa2478. [DOI] [PubMed] [Google Scholar]
  • Kays et al. (2022).Kays R, Davidson SC, Berger M, Bohrer G, Fiedler W, Flack A, Hirt J, Hahn C, Gauggel D, Russell B, Kölzsch A, Lohr A, Partecke J, Quetting M, Safi K, Scharf A, Schneider G, Lang I, Schaeuffelhut F, Landwehr M, Storhas M, van Schalkwyk L, Vinciguerra C, Weinzierl R, Wikelski M. The Movebank system for studying global animal movement and demography. Methods in Ecology and Evolution. 2022;13(2):419–431. doi: 10.1111/2041-210X.13767. [DOI] [Google Scholar]
  • Kentie et al. (2018).Kentie R, Coulson T, Hooijmeijer JCEW, Howison RA, Loonstra AHJ, Verhoeven MA, Both C, Piersma T. Warming springs and habitat alteration interact to impact timing of breeding and population dynamics in a migratory bird. Global Change Biology. 2018;24(11):5292–5303. doi: 10.1111/gcb.14406. [DOI] [PubMed] [Google Scholar]
  • Kolipaka et al. (2018).Kolipaka SS, Tamis WLM, Van’t Zelfde M, Persoon GA, de Iongh HH. New insights into the factors influencing movements and spatial distribution of reintroduced Bengal tigers (Panthera tigris tigris) in the human-dominated buffer zone of Panna Tiger Reserve, India. Mammalia. 2018;82(3):207–217. doi: 10.1515/mammalia-2016-0126. [DOI] [Google Scholar]
  • Kumar et al. (2020).Kumar N, Gupta U, Jhala YV, Qureshi Q, Gosler AG, Sergio F. GPS-telemetry unveils the regular high-elevation crossing of the Himalayas by a migratory raptor: implications for definition of a Central Asian Flyway. Scientific Reports. 2020;10(1):1–9. doi: 10.1038/s41598-020-72970-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Kumar & Raghunathan (2014).Kumar AM, Raghunathan G. Human-Wildlife Conflict in the Mountains of SAARC Region—Compilation of Successful Management Strategies and Practices. Thimphu, Bhutan: SAARC Forestry Centre Office; 2014. Fostering human-elephant coexistence in the Valparai landscape, Anamalai Tiger Reserve, Tamil Nadu; pp. 14–26. [Google Scholar]
  • Kumbhojkar et al. (2020).Kumbhojkar S, Yosef R, Mehta A, Rakholia S. A camera-trap home-range analysis of the Indian Leopard (Panthera pardus fusca) in Jaipur, India. Animals. 2020;10(9):1–22. doi: 10.3390/ani10091600. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Leidner & Haddad (2011).Leidner AK, Haddad NM. Combining measures of dispersal to identify conservation strategies in fragmented landscapes. Conservation Biology. 2011;25(5):1022–1031. doi: 10.1111/j.1523-1739.2011.01720.x. [DOI] [PubMed] [Google Scholar]
  • Long & Nelson (2013).Long JA, Nelson TA. Measuring dynamic interaction in movement data. Transactions in GIS. 2013;17(1):62–77. doi: 10.1111/j.1467-9671.2012.01353.x. [DOI] [Google Scholar]
  • Loo, Billa & Singh (2015).Loo YY, Billa L, Singh A. Effect of climate change on seasonal monsoon in Asia and its impact on the variability of monsoon rainfall in Southeast Asia. Geoscience Frontiers. 2015;6(6):817–823. doi: 10.1016/j.gsf.2014.02.009. [DOI] [Google Scholar]
  • McMahon et al. (2021).McMahon CR, Roquet F, Baudel S, Belbeoch M, Bestley S, Blight C, Boehme L, Carse F, Costa DP, Fedak MA, Guinet C, Harcourt R, Heslop E, Hindell MA, Hoenner X, Holland K, Holland M, Jaine FRA, Jeanniard du Dot T, Jonsen I, Keates TR, Kovacs KM, Labrousse S, Lovell P, Lydersen C, March D, Mazloff M, McKinzie MK, Muelbert MMC, O’Brien K, Phillips L, Portela E, Pye J, Rintoul S, Sato K, Sequeira AMM, Simmons SE, Tsontos VM, Turpin V, van Wijk E, Vo D, Wege M, Whoriskey FG, Wilson K, Woodward B. Animal borne ocean sensors—AniBOS—an essential component of the global ocean observing system. Frontiers in Marine Science. 2021;8:1–21. doi: 10.3389/fmars.2021.751840. [DOI] [Google Scholar]
  • Ministry of Environment and Forests, Kalpavriksh (2004).Ministry of Environment and Forests, Kalpavriksh Chapter 4. Profile of Biodiversity in India. National Biodiversity Strategy and Action Plan, India: Final Technical Report of the UNDP/GEF Sponsored Project. Ministry of Environment and Forests, Government of India, and Kalpavriksh, New Delhi/Pune. 2004. https://kalpavriksh.org/publication/nbsap-full-report-chapter-4-profile-of-biodiversity-in-india/ https://kalpavriksh.org/publication/nbsap-full-report-chapter-4-profile-of-biodiversity-in-india/
  • Mohit et al. (2011).Mohit K, Kumar S, Rahmani AR, Khan JA, Belal SM, Khan AM. Satellite tracking of Bar-headed Geese Anser indicus wintering in Uttar Pradesh, India. Journal of the Bombay Natural History Society. 2011;108:79–94. [Google Scholar]
  • Mokany, Prasad & Westcott (2014).Mokany K, Prasad S, Westcott DA. Loss of frugivore seed dispersal services under climate change. Nature Communications. 2014;5(1):1–7. doi: 10.1038/ncomms4971. [DOI] [PubMed] [Google Scholar]
  • Mola & Williams (2019).Mola JM, Williams NM. A review of methods for the study of bumble bee movement. Apidologie. 2019;50(4):497–514. doi: 10.1007/s13592-019-00662-3. [DOI] [Google Scholar]
  • Mondal et al. (2013).Mondal K, Bhattacharjee S, Gupta S, Sankar K, Qureshi Q. Home range and resource selection of problem leopards trans-located to forested habitat. Current Science. 2013;105:338–345. [Google Scholar]
  • Morelle, Lehaire & Lejeune (2014).Morelle K, Lehaire F, Lejeune P. Is wild boar heading towards movement ecology? A review of trends and gaps. Wildlife Biology. 2014;20(4):196–205. doi: 10.2981/wlb.00017. [DOI] [Google Scholar]
  • Morelle et al. (2015).Morelle K, Podgórski T, Prévot C, Keuling O, Lehaire F, Lejeune P. Towards understanding wild boar Sus scrofa movement: a synthetic movement ecology approach. Mammal Review. 2015;45(1):15–29. doi: 10.1111/mam.12028. [DOI] [Google Scholar]
  • Naha et al. (2021).Naha D, Dash SK, Kupferman C, Beasley JC, Sathyakumar S. Movement behavior of a solitary large carnivore within a hotspot of human-wildlife conflicts in India. Scientific Reports. 2021;11(1):1–14. doi: 10.1038/s41598-021-83262-5. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Naha et al. (2016).Naha D, Jhala Y, Qureshi Q, Roy M, Sankar K, Gopal R. Ranging, activity and habitat use by tigers in the Mangrove Forests of the Sundarban. PLOS ONE. 2016;11(4):e0152119. doi: 10.1371/journal.pone.0152119. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Namgail et al. (2014).Namgail T, Takekawa JY, Bala S, Sathiyaselvam P, Mundkur T, Scott H. Space use of wintering waterbirds in India: influence of trophic ecology on home-range size. Current Zoology. 2014;60:616–621. doi: 10.1093/czoolo/60.5.616. [DOI] [Google Scholar]
  • Namgail et al. (2011).Namgail T, Takekawa JY, Sivananinthaperumal B, Sathiyaselvam P, Areendran G, Mundkur T, Mccracken T, Newman S. Ruddy Shelduck Tadorna ferruginea home range and habitat use during the non-breeding season in Assam, India. Wildfowl. 2011;61:182–193. [Google Scholar]
  • Naniwadekar et al. (2019).Naniwadekar R, Rathore A, Shukla U, Chaplod S, Datta A. How far do Asian forest hornbills disperse seeds? Acta Oecologica. 2019;101:103482. doi: 10.1016/j.actao.2019.103482. [DOI] [Google Scholar]
  • Naniwadekar et al. (2021).Naniwadekar R, Rathore A, Shukla U, Datta A. Roost site use by Great (Buceros bicornis) and Wreathed (Rhyticeros undulatus) Hornbill and its implications for seed dispersal. Biotropica. 2021;155(4):1–5. doi: 10.1111/btp.13039. [DOI] [Google Scholar]
  • Nathan et al. (2008).Nathan R, Getz WM, Revilla E, Holyoak M, Kadmon R, Saltz D, Smouse PE. A movement ecology paradigm for unifying organismal movement research. Proceedings of the National Academy of Sciences of the United States of America. 2008;105(49):19052–19059. doi: 10.1073/pnas.0800375105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Noonan et al. (2020).Noonan MJ, Fleming CH, Tucker MA, Kays R, Harrison A, Crofoot MC, Abrahms B, Alberts SC, Ali AH, Altmann J, Antunes PC, Attias N, Belant JL, Jr, Bidner DEB, Blaum LR, Boone N, Caillaud RB, Paula R.C.de D, de Torre JA, Dekker J, Deperno CS, Farhadinia M, Fennessy J, Fichtel C, Fischer C, Ford A, Goheen JR, Havmøller RW, Hirsch BT, Kaneko Y, Kappeler P, Katna A, Kauffman M, Koch F, Kulkarni A, Lapoint S, Leimgruber P, Macdonald DW, Markham AC, Mcmahon L, Mertes K, Moorman CE, Morato RG, Moßbrucker AM, Mourão G, Connor DO, Oliveira-santos LGR, Pastorini J, Patterson BD, Rachlow J, Ranglack DH, Reid N, Scantlebury DM, Scott DM, Selva N, Sergiel A, Songer M, Songsasen N, Stabach JA, Stacy-dawes J, Swingen MB, Wilson JW, Yamazaki K, Yarnell RW, Zieba F, Zwijacz-kozica T, Fagan WF, Mueller T, Calabrese JM. Effects of body size on estimation of mammalian area requirements. Conservation Biology. 2020;34:1017–1028. doi: 10.1111/cobi.13495. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Page et al. (2021).Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, Chou R, Glanville J, Grimshaw JM, Hróbjartsson A, Lalu MM, Li T, Loder EW, Mayo-Wilson E, McDonald S, McGuinness LA, Stewart LA, Thomas J, Tricco AC, Welch VA, Whiting P, Moher D. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. The BMJ. 2021;372:n71. doi: 10.1136/bmj.n71. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Pittman, Osbourn & Semlitsch (2014).Pittman SE, Osbourn MS, Semlitsch RD. Movement ecology of amphibians: a missing component for understanding population declines. Biological Conservation. 2014;169:44–53. doi: 10.1016/j.biocon.2013.10.020. [DOI] [Google Scholar]
  • Prakash et al. (2021).Prakash H, Saha K, Sahu S, Balakrishnan R. Ecological drivers of selection for remnant forest habitats by an insectivorous bat in a tropical, human-modified landscape. Forest Ecology and Management. 2021;496(104):119451. doi: 10.1016/j.foreco.2021.119451. [DOI] [Google Scholar]
  • Puppala & Singh (2021).Puppala H, Singh AP. Analysis of urban heat island effect in Visakhapatnam, India, using multi-temporal satellite imagery: causes and possible remedies. Environment, Development and Sustainability. 2021;23(8):11475–11493. doi: 10.1007/s10668-020-01122-0. [DOI] [Google Scholar]
  • Radchuk et al. (2019).Radchuk V, Reed T, Teplitsky C, van de Pol M, Charmantier A, Hassall C, Adamík P, Adriaensen F, Ahola MP, Arcese P, Miguel Avilés J, Balbontin J, Berg KS, Borras A, Burthe S, Clobert J, Dehnhard N, de Lope F, Dhondt AA, Dingemanse NJ, Doi H, Eeva T, Fickel J, Filella I, Fossøy F, Goodenough AE, Hall SJG, Hansson B, Harris M, Hasselquist D, Hickler T, Joshi J, Kharouba H, Martínez JG, Mihoub JB, Mills JA, Molina-Morales M, Moksnes A, Ozgul A, Parejo D, Pilard P, Poisbleau M, Rousset F, Rödel MO, Scott D, Senar JC, Stefanescu C, Stokke BG, Kusano T, Tarka M, Tarwater CE, Thonicke K, Thorley J, Wilting A, Tryjanowski P, Merilä J, Sheldon BC, Pape Møller A, Matthysen E, Janzen F, Dobson FS, Visser ME, Beissinger SR, Courtiol A, Kramer-Schadt S. Adaptive responses of animals to climate change are most likely insufficient. Nature Communications. 2019;10:1–14. doi: 10.1038/s41467-019-10924-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Raman et al. (2020).Raman S, Shameer TT, Sanil R, Usha P, Kumar S. Protrusive influence of climate change on the ecological niche of endemic brown mongoose (Herpestes fuscus fuscus): a MaxEnt approach from Western Ghats, India. Modeling Earth Systems and Environment. 2020;6(3):1795–1806. doi: 10.1007/s40808-020-00790-1. [DOI] [Google Scholar]
  • Ramaswami et al. (2016).Ramaswami G, Kaushik M, Prasad S, Sukumar R, Westcott D. Dispersal by generalist frugivores affects management of an invasive plant. Biotropica. 2016;48(5):638–644. doi: 10.1111/btp.12343. [DOI] [Google Scholar]
  • Ramos & González-Solís (2012).Ramos R, González-Solís J. Trace me if you can: the use of intrinsic biogeochemical markers in marine top predators. Frontiers in Ecology and the Environment. 2012;10(5):258–266. doi: 10.1890/110140. [DOI] [Google Scholar]
  • Rana, Kalsi & Burra (2012).Rana S, Kalsi RS, Burra MR. Home range comparison of male and female Grey francolin (Francolinus pondicerianus) using radiotelemetry. Records of the Zoological Survey of India. 2012;112(3):13–18. doi: 10.26515/rzsi/v112/i3/2012/122036. [DOI] [Google Scholar]
  • Ravindranath et al. (2006).Ravindranath NH, Joshi NV, Sukumar R, Saxena A. Impact of climate change on forests in India. Current Science. 2006;90:354–361. doi: 10.1007/978-94-007-0186-1_11. [DOI] [Google Scholar]
  • Reddy et al. (2012).Reddy PA, Gour DS, Bhavanishankar M, Jaggi K, Hussain SM, Harika K, Shivaji S. Genetic evidence of tiger population structure and migration within an isolated and fragmented landscape in northwest India. PLoS ONE. 2012;7(1):e29827. doi: 10.1371/journal.pone.0029827. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Riotte-Lambert & Matthiopoulos (2020).Riotte-Lambert L, Matthiopoulos J. Environmental predictability as a cause and consequence of animal movement. Trends in Ecology & Evolution. 2020;35(2):163–174. doi: 10.1016/j.tree.2019.09.009. [DOI] [PubMed] [Google Scholar]
  • Ripperger et al. (2020).Ripperger SP, Carter GG, Page Supervision RA, Duda N, Koelpin A, Weigel R, Hartmann M, Nowak T, Thielecke J, Schadhauser M, Robert J, Herbst S, Meyer-Wegener K, Wägemann P, Preikschat WS, Cassens B, Kapitza R, Dressler F, Mayer F. Thinking small: next-generation sensor networks close the size gap in vertebrate biologging. PLOS Biology. 2020;18(4):1–25. doi: 10.1371/journal.pbio.3000655. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Román-Palacios & Wiens (2020).Román-Palacios C, Wiens JJ. Recent responses to climate change reveal the drivers of species extinction and survival. Proceedings of the National Academy of Sciences of the United States of America. 2020;117(8):4211–4217. doi: 10.1073/pnas.1913007117. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Rubenstein & Hobson (2004).Rubenstein DR, Hobson KA. From birds to butterflies: animal movement patterns and stable isotopes. Trends in Ecology and Evolution. 2004;19(5):256–263. doi: 10.1016/j.tree.2004.03.017. [DOI] [PubMed] [Google Scholar]
  • Sadhu et al. (2017).Sadhu A, Jayam PPC, Qureshi Q, Shekhawat RS, Sharma S, Jhala YV. Demography of a small, isolated tiger (Panthera tigris tigris) population in a semi-arid region of western India. BMC Zoology. 2017;2(1):1–13. doi: 10.1186/s40850-017-0025-y. [DOI] [Google Scholar]
  • Sage (2019).Sage RF. Global change biology: a primer. Global Change Biology. 2019;26(1):3–30. doi: 10.1111/gcb.14893. [DOI] [PubMed] [Google Scholar]
  • Sankar et al. (2013).Sankar K, Pabla HS, Patil CK, Nigam P, Qureshi Q, Navaneethan B, Manjreakar M, Virkar PS, Mondal K. Home range, habitat use and food habits of re-introduced gaur (Bos gaurus gaurus) in Bandhavgarh Tiger Reserve, Central India. Tropical Conservation Science. 2013;6(1):50–69. doi: 10.1177/194008291300600108. [DOI] [Google Scholar]
  • Santhosh et al. (2015).Santhosh K, Kumara HN, Velankar AD, Sinha A. Ranging behavior and resource use by Lion-tailed Macaques (Macaca silenus) in selectively logged forests. International Journal of Primatology. 2015;36(2):288–310. doi: 10.1007/s10764-015-9824-6. [DOI] [Google Scholar]
  • Sarkar et al. (2016).Sarkar MS, Ramesh K, Johnson JA, Sen S, Nigam P, Gupta SK. Movement and home range characteristics of reintroduced Tiger (Panthera tigris) population in Panna Tiger Reserve, central India. European Journal of Wildlife Research. 2016;62(5):537–547. doi: 10.1007/s10344-016-1026-9. [DOI] [Google Scholar]
  • Sarma & Kumar (2016).Sarma K, Kumar A. The day range and home range of the Eastern Hoolock Gibbon Hoolock leuconedys (Mammalia: Primates: Hylobatidae) in Lower Dibang Valley District in Arunachal Pradesh, India. Journal of Threatened Taxa. 2016;8(4):8641–8651. doi: 10.11609/jott.2739.8.4.8641-8651. [DOI] [Google Scholar]
  • Schulte, Küsters & Steinfartz (2007).Schulte U, Küsters D, Steinfartz S. A PIT tag based analysis of annual movement patterns of adult fire salamanders (Salamandra salamandra) in a Middle European habitat. Amphibia-Reptilia. 2007;28(4):531–536. doi: 10.1163/156853807782152543. [DOI] [Google Scholar]
  • Seehacher & Post (2015).Seehacher F, Post E. Climate change impacts on animal migration. Climate Change Responses. 2015;2:5. doi: 10.1186/s40665-015-0013-9. [DOI] [Google Scholar]
  • Sekar, Lee & Sukumar (2015).Sekar N, Lee C-L, Sukumar R. In the elephant’s seed shadow: the prospects of domestic bovids as replacement dispersers of three tropical Asian trees. Ecology. 2015;96(8):2093–2105. doi: 10.1890/14-1543.1. [DOI] [PubMed] [Google Scholar]
  • Sekar, Lee & Sukumar (2017).Sekar N, Lee C-L, Sukumar R. Functional nonredundancy of elephants in a disturbed tropical forest. Conservation Biology. 2017;31(5):1152–1162. doi: 10.1111/cobi.12907. [DOI] [PubMed] [Google Scholar]
  • Sengupta, McConkey & Radhakrishna (2015).Sengupta A, McConkey KR, Radhakrishna S. Primates, provisioning and plants: impacts of human cultural behaviours on primate ecological functions. PLOS ONE. 2015;10(11):1–13. doi: 10.1371/journal.pone.0140961. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Sequeira et al. (2021).Sequeira AMM, O’Toole M, Keates TR, McDonnell LH, Braun CD, Hoenner X, Jaine FRA, Jonsen ID, Newman P, Pye J, Bograd SJ, Hays GC, Hazen EL, Holland M, Tsontos VM, Blight C, Cagnacci F, Davidson SC, Dettki H, Duarte CM, Dunn DC, Eguíluz VM, Fedak M, Gleiss AC, Hammerschlag N, Hindell MA, Holland K, Janekovic I, McKinzie MK, Muelbert MMC, Pattiaratchi C, Rutz C, Sims DW, Simmons SE, Townsend B, Whoriskey F, Woodward B, Costa DP, Heupel MR, McMahon CR, Harcourt R, Weise M. A standardisation framework for bio-logging data to advance ecological research and conservation. Methods in Ecology and Evolution. 2021;12(6):996–1007. doi: 10.1111/2041-210X.13593. [DOI] [Google Scholar]
  • Shepard et al. (2013).Shepard ELC, Wilson RP, Rees WG, Grundy E, Lambertucci SA, Vosper SB. Energy landscapes shape animal movement ecology. American Naturalist. 2013;182(3):298–312. doi: 10.1086/671257. [DOI] [PubMed] [Google Scholar]
  • Sherub et al. (2017).Sherub S, Fiedler W, Duriez O, Wikelski M. Bio-logging, new technologies to study conservation physiology on the move: a case study on annual survival of Himalayan vultures. Journal of Comparative Physiology A. 2017;203(6–7):531–542. doi: 10.1007/s00359-017-1180-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • Singh, Kikon & Verma (2017).Singh P, Kikon N, Verma P. Impact of land use change and urbanization on urban heat island in Lucknow city, Central India. A remote sensing based estimate. Sustainable Cities and Society. 2017;32(3):100–114. doi: 10.1016/j.scs.2017.02.018. [DOI] [Google Scholar]
  • Singh et al. (2020).Singh R, Pandey P, Qureshi Q, Sankar K, Krausman PR, Goyal SP. Acquisition of vacated home ranges by tigers. Current Science. 2020;119(9):1549–1554. doi: 10.18520/cs/v119/i9/1549-1554. [DOI] [Google Scholar]
  • Singh et al. (2013).Singh R, Qureshi Q, Sankar K, Krausman PR, Goyal SP. Use of camera traps to determine dispersal of tigers in semi-arid landscape, western India. Journal of Arid Environments. 2013;98(1):105–108. doi: 10.1016/j.jaridenv.2013.08.005. [DOI] [Google Scholar]
  • Singh et al. (2016).Singh R, Sharma K, Gogate N, Malik PK, Tamim A. Size matters: scale mismatch between space use patterns of tigers and protected area size in a Tropical Dry Forest. Biological Conservation. 2016;197(80-.):146–153. doi: 10.1016/j.biocon.2016.03.004. [DOI] [Google Scholar]
  • Sivakumar et al. (2016).Sivakumar K, Jhala YV, Bhardwaj GS, Mohan A. Chandrabani, Dehradun: Wildlife Institute of India; 2016. A study on ecology and migration of the lesser florican (Sypheotides indica) in Western India using satellite techniques. Project Report. [DOI] [Google Scholar]
  • Stapp, Polis & Sânchez Pinero (1999).Stapp P, Polis GA, Sânchez Pinero F. Stable isotopes reveal strong marine and El Nino effects on island food webs. Nature. 1999;401(6752):467–469. doi: 10.1038/46769. [DOI] [Google Scholar]
  • Swain et al. (2017).Swain D, Roberts GJ, Dash J, Lekshmi K, Vinoj V, Tripathy S. Impact of rapid urbanization on the City of Bhubaneswar, India. Proceedings of the National Academy of Sciences, India Section A: Physical Sciences. 2017;87(4):845–853. doi: 10.1007/s40010-017-0453-7. [DOI] [Google Scholar]
  • Swaminathan, Namboothri & Shanker (2019).Swaminathan A, Namboothri N, Shanker K. Tracking leatherback turtles from Little Andaman. Indian Ocean Turtle Newsletter. 2019;29:8–10. [Google Scholar]
  • Thaker et al. (2019).Thaker M, Gupte PR, Prins HH, Slotow R, Vanak AT. Fine-scale tracking of ambient temperature and movement reveals shuttling behavior of elephants to water. Frontiers in Ecology and Evolution. 2019;25;7:4. doi: 10.3389/fevo.2019.00004. [DOI] [Google Scholar]
  • Thums et al. (2018).Thums M, Fernández-Gracia J, Sequeira AMM, Eguíluz VM, Duarte CM, Meekan MG. How big data fast tracked human mobility research and the lessons for animal movement ecology. Frontiers in Marine Science. 2018;5:1–12. doi: 10.3389/fmars.2018.00021. [DOI] [Google Scholar]
  • Tian et al. (2014).Tian H, Banger K, Bo T, Dadhwal VK. History of land use in India during 1880–2010: large-scale land transformations reconstructed from satellite data and historical archives. Global and Planetary Change. 2014;121(10):78–88. doi: 10.1016/j.gloplacha.2014.07.005. [DOI] [Google Scholar]
  • Tucker et al. (2018).Tucker MA, Böhning-gaese K, Fagan WF, Fryxell JM, Van Moorter B, Alberts SC, Ali AH, Allen AM, Attias N, Avgar T, Bartlam-brooks H, Bayarbaatar B, Belant JL, Bertassoni A, Beyer D, Bidner L, Van Beest FM, Blake S, Blaum N, Bracis C, Brown D, De Bruyn PJN, Cagnacci F, Diefenbach D, Douglas-hamilton I, Fennessy J, Fichtel C, Fiedler W, Fischer C, Fischhoff I, Fleming CH, Ford AT, Fritz SA, Gehr B, Goheen JR, Gurarie E, Hebblewhite M, Heurich M, Hewison AJM, Hof C, Hurme E, Isbell LA, Janssen R, Jeltsch F, Kaczensky P, Kane A, Kappeler PM, Kauffman M, Kays R, Kimuyu D, Koch F, Kranstauber B, Lapoint S, Mattisson J, Medici EP, Mellone U, Merrill E, Morrison TA, Díaz-muñoz SL, Mysterud A, Nandintsetseg D, Nathan R, Niamir A, Odden J, Hara RBO, Oliveira-santos LGR, Olson KA, Patterson BD, De Paula RC, Pedrotti L, Reineking B, Rimmler M. Moving in the Anthropocene: global reductions in terrestrial mammalian movements. Science. 2018;359(6374):466–469. doi: 10.1126/science.aam9712. [DOI] [PubMed] [Google Scholar]
  • Varghese & Singh (2016).Varghese N, Singh NP. Linkages between land use changes, desertification and human development in the Thar Desert Region of India. Land Use Policy. 2016;51(50):18–25. doi: 10.1016/j.landusepol.2015.11.001. [DOI] [Google Scholar]
  • Venkataraman et al. (2005).Venkataraman AB, Saandeep R, Baskaran N, Roy M, Madhivanan A, Sukumar R. Using satellite telemetry to mitigate elephant-human conflict: an experiment in northern West Bengal, India. Current Science. 2005;88:1827–1831. [Google Scholar]
  • Westley et al. (2018).Westley PAH, Berdahl AM, Torney CJ, Biro D. Collective movement in ecology: from emerging technologies to conservation and management. Philosophical Transactions of the Royal Society B: Biological Sciences. 2018;373(1746):20170004. doi: 10.1098/rstb.2017.0004. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental Information 1. Search results from keywords, list of publications, and ongoing studies in the field of movement ecology.
DOI: 10.7717/peerj.14401/supp-1
Supplemental Information 2. Prisma Checklist for the systematic review.
DOI: 10.7717/peerj.14401/supp-2
Supplemental Information 3. Prisma flow diagram of the survey and the final number of studies retrieved for the review.
DOI: 10.7717/peerj.14401/supp-3

Data Availability Statement

The following information was supplied regarding data availability:

The data is available in the Supplemental File.


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