Determinants of Distribution of Large Mammals in Seti River Basin, Tanahun District of Western Nepal

Adhikari, Jagan Nath; Bhattarai, Bishnu Prasad; Thapa, Tej Bahadur

doi:10.3126/jist.v24i1.24638

Cited by 6 publications

(4 citation statements)

References 33 publications

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“…Wildlife can't face a shortage of water in critical seasons (Najafi et al, 2019). Large mammals visit frequently to the water bodies, hence the sign and sightings of the large mammals are closer to the water sources (Cramer and Willig, 2002;Bhattarai and Kindlmann, 2012a;Adhikari et al, 2019a) similar to our study. Similar results also found in the study of Bhattarai and Kindlmann (2012a) and Thapa (2011) in Chitwan National Park; in Bardia National Park of Nepal.…”

Section: Distribution Of Mammals In Habitat Gradientssupporting

confidence: 83%

Determinants of abundance and habitat association of mammals in Barandabhar Corridor Forest, Chitwan, Nepal

2021

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Barandabhar Corridor Forest (BCF), the biologically functional corridor, is surrounded by the large human settlements that exploit the corridor where large mammals such as tigers, leopards and their prey such as ungulates, primates, and rhinoceros occur. This study aimed to evaluate major determinants that affect the distribution of large mammals in BCF, Chitwan, Nepal that connects the biologically significant Chitwan National Park with the Mahabharat range. The status and distribution of large mammals along the habitat and disturbance gradients were determined by using 29 line transects (mean length = 4.59 ± 0.38 km) that covered a linear distance of 133.13 km. The chital were the most abundant mammals (density per km2 (D) = 8.9095 ± 1.4570 and encounter rate per km (ER) = 1.49) followed by rhesus monkey (D = 38.896 ± 16.013, ER = 0.28), wild boar (D = 14.814 ± 3.57, ER = 0.62), northern red muntjac (D = 9.6566 ± 2.9514, ER = 0.62) and sambar (D = 5.392 ± 2.319, ER = 0.38). Similarly, the sign encounter rate of tiger and leopard was 0.435 and 0.503 respectively. Habitat types, human disturbances, and coverage of invasive and alien plant species (IAPs) played a key role in the distribution of large mammals. The occurrence of mammals was low nearer to the settlements and roads and coverage of IAPs and more nearer to the water resources. However, degradation of foraging grounds such as grasslands by succession and invasion of alien plant species added more threats to the survival of large mammals. Therefore, such a situation can be improved through the scientific management of forests and grasslands.

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Section: Distribution Of Mammals In Habitat Gradientssupporting

confidence: 83%

Determinants of abundance and habitat association of mammals in Barandabhar Corridor Forest, Chitwan, Nepal

2021

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“…Among the land cover classes, Sal dominated forest was the most common in the Barandabhar Corridor Forest and some parts of Tanahun and Kaski districts. The tropical and subtropical climate with high temperature and precipitation support the Sal dominated forest ( Adhikari, Bhattarai & Thapa, 2019 ; Reddy et al, 2018 ). Similarly, the riverine forest was found in the flood plains of major river systems (Rapti, Narayani, Marshyandi, Kaligandaki, Seti river basin).…”

Section: Discussionmentioning

confidence: 99%

Land use/land cover changes in the central part of the Chitwan Annapurna Landscape, Nepal

Adhikari

Bhattarai

Rokaya

et al. 2022

PeerJ

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Background Land use/land cover assessment and monitoring of the land cover dynamics are essential to know the ecological, physical and anthropogenic processes in the landscape. Previous studies have indicated changes in the landscape of mid-hills of Nepal in the past few decades. But there is a lack of study in the Chitwan Annapurna Landscape; hence, this study was carried out to fill in study gap that existed in the area. Methods This study evaluates land use/land cover dynamics between 2000 to 2020 in the central part of the Chitwan Annapurna Landscape, Nepal by using Landsat images. The Landsat images were classified into eight different classes using remote sensing and geographic information system (GIS). The accuracy assessment of classified images was evaluated by calculating actual accuracy, producer’s accuracy, user’s accuracy and kappa coefficient based on the ground-truthing points for 2020 and Google Earth and topographic maps for images of 2010 and 2000. Results The results of land use/land cover analysis of Landsat image 2020 showed that the study area was composed of grassland (1.73%), barren area (1.76%), riverine forest (1.93%), water body (1.97%), developed area (4.13%), Sal dominated forest (15.4%), cropland (28.13%) and mixed forest (44.95%). The results of land cover change between 2000 to 2020 indicated an overall increase in Sal dominated forest (7.6%), developed area (31.34%), mixed forest (37.46%) and decrease in riverine forest (11.29%), barren area (20.03%), croplands (29.87%) and grasslands (49.71%). The classification of the images of 2000, 2010 and 2020 had 81%, 81.6% and 84.77% overall accuracy, respectively. This finding can be used as a baseline information for the development of a proper management plan to protect wildlife habitats and forecasting possible future changes, if needed.

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“…In addition to hunting preferences for some species, body mass has a synergetic effect because hunters often prefer larger species to obtain a greater energetic return (Peres et al., 2016 ). The distribution of mammals around human settlements may indicate the species' resilience to anthropogenic disturbances (Adhikari et al., 2019 ). Hunting is not random, with some species being preferentially hunted for bushmeat, mainly medium to large mammals (>20 kg), which have higher levels of defaunation than other mammal groups (Benítez‐López et al., 2019 ).…”

Section: Introductionmentioning

confidence: 99%

“…Studies have shown the relationship between distance to settlements and the decay in large mammal distribution in different parts of the Amazon basin and worldwide. Some remarkable examples in the Amazon basin are in the Northern Brazilian Amazon (Melo et al., 2015 ), Eastern Brazilian Amazon (Mesquita & Barreto, 2015 ) or Peruvian Amazonia (Ohl‐Schacherer et al., 2007 ), as well as other parts of the world, including global biodiversity hotspots such as East Africa (Cavada et al., 2019 ), Thailand (Ngoprasert et al., 2007 ), Sumatra (Widodo et al., 2022 ), Malaysian Borneo (Deith & Brodie, 2020 ) and Western Nepal (Adhikari et al., 2019 ). Some studies have even reported that distance to human settlements is a robust predictor of poaching that is more important than forest management in regions such as Central Africa (Lhoest et al., 2020 ), in the sense that areas further away from settlements, and therefore less degraded, would act as a source of individuals to repopulate more defaunated areas closer to settlements (Begazo & Bodmer, 1998 ).…”

Section: Introductionmentioning

confidence: 99%

The distribution of bushmeat mammals in unflooded forests of the Central Amazon is influenced by poaching proxies

de Souza Ferreira Neto,

Baccaro,

Phillips

et al. 2023

Ecology and Evolution

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Medium to large rainforest mammals are key conservation flagship groups that offer non‐redundant ecosystem functions, but anthropic pressures, such as illegal hunting, may strongly affect their occupancy in Amazonia. We combined camera traps and occupancy models to assess the influence of distance from human settlements, the number of families per settlement and the synergetic effect of the average weight of 27 species on the occupancy probability of mammals. Specifically, we classified mammal species according to the game preferences of hunters (i.e. a group of species depleted for bushmeat, a group of species hunted for retaliation and a group of non‐hunted species). We also accounted for the influence on the detection probability of each group of both the number of days each camera operated and the body weight of mammals. The occupancy probability of the bushmeat group (i.e. deer, peccaries, agoutis, pacas and armadillos) was lower at locations closer to human settlements. Still, the number of families correlated positively with occupancy, with the occupancy probability of the group being slightly higher at sites with more families. This difference was probably due to larger and more abundant crops and fruiting trees attracting wildlife at such sites. Conversely, the occupancy probability of the retaliation group (i.e. carnivores) and the non‐hunted group (i.e. opossums, spiny rats, squirrels and anteaters) were indifferent to anthropogenic stressors. The detection probability of the non‐hunted and particularly the most depleted species correlated negatively with body weight. This may suggest that larger species, especially those from the bushmeat group, are rarer or less abundant in the system, possibly because they are the preferable target of hunters. In the long term, locals will likely need to travel long distances to find harvest meat. Poaching also threatens food security since game bushmeat is an essential source of protein for isolated rural Amazonians.

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Determinants of Distribution of Large Mammals in Seti River Basin, Tanahun District of Western Nepal

Cited by 6 publications

References 33 publications

Determinants of abundance and habitat association of mammals in Barandabhar Corridor Forest, Chitwan, Nepal

Determinants of abundance and habitat association of mammals in Barandabhar Corridor Forest, Chitwan, Nepal

Land use/land cover changes in the central part of the Chitwan Annapurna Landscape, Nepal

The distribution of bushmeat mammals in unflooded forests of the Central Amazon is influenced by poaching proxies

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