Journal of Threatened
Taxa | www.threatenedtaxa.org | 26 January 2026 | 18(1): 28186–28193
ISSN 0974-7907 (Online) | ISSN 0974-7893 (Print)
https://doi.org/10.11609/jott.10202.18.1.28186-28193
#10202 | Received 08 October 2025 | Final received 19 November 2025 |
Finally accepted 16 December 2025
People’s perceptions on the
impacts of select linear infrastructure projects on avifauna in Chhattisgarh,
India
C.P. Ashwin 1, J.M.
Alby 2 & P.R. Arun 3
1–3 Sálim Ali Centre for Ornithology and
Natural History, South India Centre of WII, Anaikatty
Post, Coimbatore, Tamil Nadu 641108, India.
1–3 Bharathiar University, Coimbatore, Tamil
Nadu 641046, India.
1 ashwincp95@gmail.com (corresponding
author), 2 albyjacob.jm@gmail.com, 3 eiasacon@gmail.com
Editor: H. Byju,
Coimbatore, Tamil Nadu, India. Date of
publication: 26 January 2026 (online & print)
Citation:
Ashwin, C.P., J.M. Alby & P.R. Arun (2026). People’s
perceptions on the impacts of select linear infrastructure projects on avifauna
in Chhattisgarh, India. Journal of
Threatened Taxa 18(1):
28186–28193. https://doi.org/10.11609/jott.10202.18.1.28186-28193
Copyright: © Ashwin et al. 2026. Creative Commons Attribution 4.0 International License.
JoTT allows unrestricted use, reproduction, and
distribution of this article in any medium by providing adequate credit to the
author(s) and the source of publication.
Funding: No funding was received for this study. Part of Bharathiar University PhD work to the first author.
Competing interests: The authors declare no competing interests.
Author details: Ashwin C.P., PhD scholar at the Salim Ali Centre for Ornithology and Natural History (SACON) and Bharathiar University, Coimbatore, India. Specializes in wildlife management, ecology, and impact assessment of developmental projects, with strong analytical skills and a strategic approach to harmonize ecological conservation with applied research. Alby J. Mattathil, PhD scholar at SACON and Bharathiar University, Coimbatore, India. Research focuses on ornithology, behavioral ecology, conservation biology, and environmental impact assessment, with specialization in human–elephant negative interactions. Dr. P.R. Arun, senior principal scientist and head of the Environmental Impact Assessment Division at SACON, India. The division provides expert consultancy on environmental and biodiversity issues, balancing development with conservation through applied research, Environmental Impact Assessments (EIA), and development of Environment Management Plans (EMPs). His research interests include environmental impact assessment, entomology, butterfly ecology, and environmental science. He has led numerous research projects, supervised multiple PhD scholars, and contributed scientific expertise to environmental policy and sustainable management strategies.
Author contributions: CPA—lead in conceptualization, data collection, data analysis, manuscript drafting, and visualization; contributed equally to manuscript review and editing. JMA—contributed equally to data collection, interpretation of results, and manuscript review and editing. PRA—contributed equally to methodology and statistical inputs; lead supervision and manuscript review and editing
Acknowledgements: We are grateful to the Forest Department, Chhattisgarh and the Sálim Ali Centre for Ornithology and Natural History for supporting this study. We sincerely thank our friends especially Nandu V. S. and Avadhoot Velankar for their encouragement and constant support. We are also thankful to all the field personnels who assisted us during the surveys and made the fieldwork possible.
Abstract: India’s rapid economic growth has
led to widespread expansion of linear infrastructure (LI) such as roads,
railways, and power lines, often with significant ecological impacts on
wildlife, including avifauna. Understanding public perceptions of these impacts
is crucial for participatory conservation and sustainable infrastructure
planning. This study assessed people’s perceptions of avifaunal impacts from
four major LI projects in Chhattisgarh: Ranchi–Dharamjaigarh
(765 kV), Korba–Jabalpur (765 kV), and Champa–Kurukshetra (800 kV) transmission lines, as well as
the East Rail Corridor. Structured interviews were conducted with 868 rural
residents using close-ended questions. Responses were analysed
using binary scoring, chi-square tests, and multinomial logistic regression.
Overall, 56.6% perceived negative impacts on avifauna, with 51.7% reporting
declines in common bird species. While 58.5% of respondents observed no change
in migratory birds, 41.5% reported a decline; 43.5% noted electrocution and
collision risks. Perceptions varied significantly with respondents’ age,
education, tribal status, occupation, and proximity to LI. Older,
less-educated, and non-tribal individuals expressed more negative views, and
those living closer to LI exhibited heightened concern. Despite these, neutral
views were prevalent, reflecting a lack of definitive environmental awareness
or LI’s impact on avifauna. These findings underscore the need for integrating
biodiversity safeguards into infrastructure planning and enhancing public
awareness through targeted environmental education.
Keywords: Biodiversity impacts, bird
responses, community perceptions, conservation planning, electrocution and
collision risks, environmental awareness, rural residents, socio-demographic factors.
Introduction
Tropical forests are among the
most biodiverse and ecologically significant ecosystems, yet they are
increasingly threatened by land-use change and fragmentation. One major driver
of this fragmentation is the expansion of linear infrastructure (LI), which traverses
landscapes in elongated forms, often bisecting habitats. This includes roads,
railways, transmission lines, pipelines, and canals (Geist & Lambin 2002; Geneletti 2004; Laurance et al. 2014; Nayak et al. 2020). While LI play a
vital role in economic development and connectivity (van der Grift et al.
2015), they also contribute to environmental degradation through habitat loss,
increased wildlife mortality, and pollution (Forman & Alexander 1998; De Jonge et al. 2022; Ashwin et al. 2023). Avifauna are
particularly vulnerable to LI through electrocution, collisions, and
displacement (Bevanger 1998; Loss et al. 2014; van
der Grift et al. 2015; Manigandan et al. 2022). While
several studies have linked LIs to declines in biodiversity, including bird populations,
some studies have also indicated that certain bird species may exploit LI
corridors for foraging or perching (van der Grift et al. 2015) and nesting (Byju et al. 2023), highlighting the complexity of
ecological responses to the LIs.
People’s perceptions of such
impacts are critical in shaping conservation and development strategies.
Perceived risks and benefits are influenced by individual opinions,
environmental knowledge, and sociodemographic factors such as age, education,
and occupation (Kaczensky et al. 2004; Viklund 2004; Manigandan et al.
2024). People’s perceptions, defined as how individuals interpret and evaluate
environmental issues, can provide insights into local ecological knowledge and
guide effective conservation interventions (Berkes et
al. 2000; Huntington 2011; Bennett 2016) and identify knowledge gaps, plan
awareness programs, and guide participatory approaches to conservation (Caily-Arnulphi et al. 2017; Champness
et al. 2023).
Despite the recognized importance
of perception studies in conservation, the views of local communities regarding
LI impacts, especially on avifauna, remain underexplored in India. Particularly
in Chhattisgarh, driven by the energy and mining sectors, little is known about
how local communities perceive LI impacts on birds (Gajera
et al. 2013). Projects such as thermal power plants, transmission lines, and
railway corridors are transforming landscapes, raising concerns about
ecological consequences and social acceptance. Such rapid development and
intrusion of several LI can have potential impacts on both people and the
environment. Understanding LI’s impacts on people and the surrounding
environment is crucial for scientifically managing these impacts. There are
very few systematic studies on birds in this region, and research on avifaunal
responses to infrastructure expansion in Chhattisgarh is especially limited.
This study, therefore, represents one of the first structured attempts to
document community perceptions of bird impacts associated with major LI
corridors in the state. Avifauna are particularly relevant in this context
because birds are highly sensitive to habitat alteration, fragmentation, and
electrocution or collision risks, making them strong ecological indicators of
infrastructure impacts. Several stretches of the studied LI corridors pass
through forest patches, agricultural landscapes, and open woodlands, where
canopy removal, vegetation clearing, and disturbance have been reported. The
heightened public awareness will lead to more effective conversation efforts
geared towards lessening adverse consequences for both sides. Knowing more
about people’s views of the influence of LI could lead to better landscape and
regional design and management. However, public perception alone cannot guide conservation
or infrastructure planning and must be complemented with ecological assessments
to ensure scientifically sound decisions.
Study area
Four selected linear
infrastructures in the state of Chhattisgarh, India, were surveyed for the
cause: the Ranchi–Dharamjaigarh Transmission Line
(765 kV S/C Power Grid Transmission Line), Champa–Kurukshetra
(800 kV S/C Power Grid Transmission Line), Korba–Jabalpur
(765 kV S/C Power Grid Transmission Line), and the East Rail corridor (Figure
1). These linear infrastructures intersect six districts in Chhattisgarh,
namely Korba, Bilaspur, Gaurela-Pendra-Marwahi,
Raigarh, Jangir-Champa, and
Jashpur, with an approximate length of 711 km in
total.
Chhattisgarh state covers
1,35,191 km2, accounting for 4.1% of the country’s total area. The
LI routes cut across predominantly tropical dry deciduous forests, characterised by Sal Shorea
robusta and associated mixed deciduous species,
classified as northern tropical dry mixed deciduous forests (5B/C2; Champion
& Seth 1968) (Forest Survey 2021). Chhattisgarh is home to a varied
population with diverse ethnic, social, and religious backgrounds. It has the
highest tribal population among all Indian states; one-third of the people in
the state are officially categorized as scheduled castes or scheduled tribes
(Dixit et al. 2023). Chhattisgarh has a total population of 2,55,45,198 people,
with 12,832,895 males and 12,712,303 females. The literacy rate in Chhattisgarh
is 70.28%. Male literacy rates are 80.27%, while female literacy rates are
60.24% (Census 2011). Rural areas are home to 76.76% of the total population,
and most of them are farmers who primarily depend on paddy cultivation.
Methods
A structured, close-ended
questionnaire was designed to assess
public perceptions of linear infrastructure (LI) impacts on avifauna, based on
established guidelines, and expert review. The finalized survey comprised ten
simple questions administered through face-to-face interviews, following
Patton’s (2002). Interviews, lasting 5–10 minutes, were conducted with 868
willing participants between October 2021 and July 2023 across 166 villages
near selected LI routes in Korba, Bilaspur, Gaurela-Pendra-Marwahi, Raigarh, Janjgir-Champa, and Jashpur.
Villages were selected based on proximity to LI to ensure locally grounded
responses. Participants included a diverse group: farmers, students, government
employees, housewives, business owners, and daily wage workers. Prior to
interviews, participants were briefed on the study’s objectives and verbal
consent was obtained.
The questionnaire had two
sections: (1) socio-demographic data (gender, age, education, occupation,
tribal affiliation, proximity to LI, and duration of residence) (Naha et al.
2014; Chin et al. 2019) and (2) perception of LI impacts on avifauna. In this
study, the term ‘perception’ refers specifically to respondents’ views on the
impact of LI on avifauna, including perceived effects on bird mortality, behaviour, and habitat. While the questionnaire was
developed in English and Hindi, most interviews were conducted in local
dialects with field support. Close-ended formats were preferred for efficiency
and analytical clarity.
To help participants accurately
identify bird species, a photo-elicitation approach was used during interviews.
Photographs of commonly occurring birds from the region were shown to
respondents. In addition, the Merlin Bird ID application (Cornell Lab of
Ornithology) was used to display high-resolution images and, when required, to
play bird calls to aid recall and confirmation. Responses were categorized as
positive, neutral, or negative based on participants’ observations and
opinions. Perception was quantified using a binary scoring system: “Yes” = 1
and “No” = 0, resulting in a cumulative score from 0–10 (Darawsheh
2020; Ruan et al. 2022). Scores were categorized into
three groups for multinomial logistic regression: negative (0–3), neutral
(4–6), and positive (7–10). Data categorization followed standard practices,
and all the ethical guidelines were strictly adhered to throughout the study
(Gubbi 2006).
Data analysis
Analysis of qualitative data was
done through content analysis (coding) or thematic analysis by categorizing
themes according to the way they relate to research objectives and building
relationships and implications as provided by Patton (2002). After data
collection in the field, the data were organised,
coded, classified, and tabulated using Microsoft Excel and descriptive
statistics. In SPSS 23.0, data were cross-tabulated, and a chi-square test
(notation: x2 df) was applied to all combinations of
independent and dependent variables. To determine the factors that could
predict the perceptions of people, a multinomial logistic regression model was
fitted to the responses and was used to predict the probabilities of the
different possible outcomes (Umaña-Hermosilla et al.
2020). Multinomial logistic regression utilizes maximum likelihood estimation
to assess the likelihood of belonging to a specific category, allowing us to
characterize the probability of a respondent’s decision for a particular
multinomial discrete choice, conditional on the values of the explanatory
variables (Clark 2009; Umaña-Hermosilla et al. 2020).
We use the multinominal function from the net package
to estimate a multinomial logistic regression model in R.
Respondent demographics
Most of the respondents (34.4%)
were in the age group of 46–70, followed by 31–45 years (34%), 15–30 years
(28.1%), and more than 70 years old (3.5%). Occupation-wise, 50% were farmers.
Respondents were predominantly male (77.6%) since most of the female
participants were reluctant to respond. In terms of tribal affiliation, 51.8%
were non-tribal and 48.2% tribal. Education levels varied: 50% had primary
education, 32.4% high school, 13.6% graduate or above, and 4% were uneducated.
Regarding proximity to LI, 57.8% lived or owned land within 0–300 m, and 40.8%
within 301–600 m. A majority (54.8%) had resided in the area for 31–60 years
(Table 1).
Results
Participant’s response – summary
The study assessed public
perceptions of LI impacts on avifauna. Overall, 56.6% of respondents perceived
LI as having a negative effect on local bird populations, while 43.4% did not.
A decline in common bird species post-installation was noted by 51.7%, whereas
48.3% reported no such change. Regarding migratory birds, 41.5% observed a
decline, while 58.5% did not. Concerns about bird electrocution or collision
were raised by 43.5% of respondents. Only 23.3% reported birds avoiding LI
structures during flight, and 34.2% noted an increase in human–bird negative
interactions after installation; 65.8% did not. A vast majority (91.6%) did not
observe invasive plant proliferation post-installation. While 80.8% did not
believe LI had positive effects on birds, 19.2% perceived some benefits.
Increased sightings of birds of prey were reported by 10.7%, and 30.8% observed
birds using LI pylons for perching, nesting, roosting, or foraging (Table 2).
People perception
People’s perception on the impact
of LI on avifauna
Chi-square tests revealed
significant associations between perception of LI impacts on avifauna and
multiple socio-demographic variables (Table 3). Age was significantly
associated with perception (p < 0.001), with younger respondents (15–45
years) tending to be more neutral, while older groups (46+ years) expressed a
mix of views. Education level also influenced perceptions (p < 0.001);
uneducated individuals more frequently expressed negative views, whereas those
with formal education showed more neutral or varied responses. Tribal
affiliation was strongly associated with perception (p < 0.001), with tribal
respondents mostly neutral and non-tribal respondents more evenly distributed
across categories. Occupation significantly affected perception (p < 0.001),
with labourers showing a slightly more positive
outlook. Proximity to LI was also significant (p = 0.040), with those living
nearer expressing greater concern, though neutral views still dominated. Gender
(p = 0.188) and years of residency (p = 0.084) were not significantly
associated with perception.
Factors determining
the people’s perception of LI.
Multinomial logistic regression
results for people’s perception on the impact of LI on avifauna (Reference
category: Neutral)
Multinomial logistic regression
analysis (Table 4) revealed several significant predictors of perception.
Individuals aged 30–45 had slightly lower odds of negative perception compared
to neutral (β = -0.636, p < 0.1). Males were not significantly associated
with negative perception responses but showed a significant negative
association with positive responses (β = -0.544, p < 0.1), indicating that
males were less likely to report positive perceptions. Non-tribal respondents
had significantly higher odds of both negative (β = 1.212, p < 0.01) and
positive (β = 0.858, p < 0.01) perceptions, suggesting that non-tribal
individuals were more likely to express stronger opinions in either direction.
High school-educated individuals had slightly lower odds of negative perception
(β = -0.799, p < 0.1), while graduates and above had significantly lower
odds (β = -1.163, p < 0.01). Labourers had
increased odds of negative perception (β = 1.551, p < 0.01) and suggesting
that labourers were more likely to express negative
views. Proximity to LI was a strong predictor; individuals living closer to the
LI (0–900 m) were significantly more likely to express negative views, with
extremely high coefficients (β = 11.515, p < 0.01). Residency of 31–60 years
showed slightly lower odds of negative perception (β = -0.493), while those
residing for 61–90 years had significantly higher odds of positive perception
(β = -1.377, p < 0.05), suggesting that very long-term residents were less
likely to express positive views.
Discussion
This study reveals the multifaceted
impacts of LI on avifauna, with respondents expressing mixed but predominantly
neutral to negative perceptions. Key concerns include bird mortality from
collisions and electrocutions, consistent with earlier studies (Bevanger 1998; Raman 2011; Loss et al. 2014; Serratosa et al. 2024). Environmentally conscious
respondents emphasize the need for ecological integration in infrastructure
planning (Kaltenborn & Bjerke 2002).
Socio-demographic factors significantly influence perceptions. Younger individuals
tend to be neutral, likely due to limited experience (Milfont
et al. 2010), while tribal affiliation correlates with more neutral or positive
views, reflecting cultural influences (Shelley et al. 2011; Bain 2017). Higher
education corresponds to fewer negative perceptions, highlighting education’s
role in environmental awareness (Harris et al. 2016). Proximity to LI and
occupation also affect attitudes, with those living closer and in labour-intensive jobs showing more negativity (Batel et al. 2015).
Multinomial logistic regression
confirms that proximity to the LI had a very strong and significant association
with negative responses across all distance categories. This indicates that
individuals residing closer to the LI were substantially more likely to report
negative responses, likely reflecting direct exposure to environmental, social,
or economic externalities, and this supports the prior findings of spatial
proximity to infrastructure often intensifying perceptions of risk (Dear 1992;
Devine-Wright & Batel 2013). Non-tribal
respondents showed higher odds of both negative and positive responses,
suggesting greater polarization and engagement within this group. This
contrasts with tribal populations, who may be structurally marginalized or less
empowered to express dissent—a pattern noted in participatory governance
literature (Cornwall 2008). Lower education increases the odds of negative
perceptions, whereas both high school and graduate-level education
significantly reduce the likelihood of negative responses. This finding may
reflect greater resilience, access to information, or broader worldview among
more educated individuals, allowing them to contextualize or mitigate concerns
(Dietz et al. 2007). Similarly, long-term residents showed more positive views,
indicating perceptual shifts linked to socioeconomic change (Manfredo et al. 2009; George et al. 2016). Local ecological
knowledge accrued through experience remains vital for conservation (Ruan et al. 2022). Integrating avian conservation into LI
planning supports critical ecosystem services like pollination, seed dispersal,
pest control, enhancing biodiversity, ecosystem resilience, and community
well-being.
Conclusion
This study reveals varied
community perceptions on the impacts of LI on birds. Many of the respondents
recognized negative effects like electrocution and collisions, but neutral
views were common, indicating gaps in awareness and the influence of multiple
socio-demographic factors. Perceptions varied by age, education, culture,
occupation, and proximity to LI. Younger and tribal individuals tend to be more
neutral in their perception of impacts, while uneducated and non-tribal
respondents are likely to perceive more negative impacts. Those living closer
to LI show greater concern about the impacts, whereas long-term residents are
relatively less concerned, possibly suggesting shifting attitudes over time,
and acclimatization.
These perception patterns do not
necessarily reflect the full ecological impacts, as several bird groups—particularly
raptors, hornbills, storks, and owls—are known from existing literature to be
highly vulnerable to electrocution and collision. Strengthening environmental
awareness among local communities, especially in areas undergoing rapid
infrastructure expansion, will help bridge these gaps. The prevalence of
neutral views points to a need for improved environmental education and
awareness. Measures such as insulating power lines, installing bird diverters,
and maintaining habitat buffers can substantially reduce risks. Incorporating
bird conservation concerns into infrastructure development and involving local
communities are essential to harmonize development with biodiversity
conservation and overall ecosystem health.
Table 1. Respondent
demographics.
|
Demographic variables (M ± SD) |
Categories |
Frequency (Percentage) n = 868 |
|
Age (1.13 ± 0.86) |
15–30 years |
244 (28.1) |
|
31–45 years |
295 (34) |
|
|
46–70 years |
299 (34.4) |
|
|
> 71 |
30 (3.5) |
|
|
Gender (0.22 ± 0.42) |
Male |
674 (77.6) |
|
Female |
194 (22.4) |
|
|
Tribe/non-tribe (0.52 ± 0.50) |
Tribe |
418 (48.2) |
|
Non-tribe |
450 (51.8) |
|
|
Education level (1.56 ± 0.78) |
Uneducated |
35 (4) |
|
Primary |
434 (50) |
|
|
High school |
281 (32.4) |
|
|
Graduate and above |
118 (13.6) |
|
|
Occupation (3.35 ± 1.58) |
Business |
16 (1.8) |
|
Farmer |
436 (50.2) |
|
|
Government staff |
34 (3.9) |
|
|
Homemaker |
100 (11.5) |
|
|
Labour |
174 (20) |
|
|
Students |
108 (12.4) |
|
|
Proximity to the LI (0.44 ±
0.52) |
0–300 m |
502 (57.8) |
|
>300–600 m |
354 (40.8) |
|
|
>600–900 m |
12 (1.4) |
|
|
Years of residency (0.66 ±
0.58) |
0–30 years |
343 (39.5) |
|
>30–60 years |
476 (54.8) |
|
|
>60–90 years |
49 (5.6) |
Table 2. Participant’s
response summary.
|
|
Variables |
Yes |
No |
|
|
People’s perception on the
impact of LI on avifauna |
||
|
1 |
There is a negative impact of
LI on the local Avifauna |
491 (56.6%) |
377 (43.4%) |
|
2 |
Absence of regular/common bird
species after the LI installation |
449 (51.7%) |
419 (48.3%) |
|
3 |
Reduction in migratory birds
after the LI installation? |
360 (41.5%) |
508 (58.5%) |
|
4 |
LI is imposing significant
threats to birds by Electrocution/Collision |
378 (43.5%) |
490 (56.5%) |
|
5 |
Birds avoid LI during their
flight |
202 (23.3%) |
666 (76.7%) |
|
6 |
Human-wildlife conflict (birds)
increased after the installation |
297 (34.2%) |
571 (65.8%) |
|
7 |
Invasive plant species
proliferation increased after the installation of LI |
73 (8.4%) |
795 (91.6%) |
|
8 |
LI can positively affect the
birds |
167 (19.2%) |
701 (80.8%) |
|
9 |
Increased number of birds of
prey after the installations |
93 (10.7%) |
775 (89.3%) |
|
10 |
Birds utilising
the LI pylon for perch, nest, roost, & foraging |
267 (30.8%) |
601 (69.2%) |
Table 3. Peoples’
perception on the impact of
LI on avifauna.
|
People’s perception on the
impact of LI on avifauna |
Negative (n) |
Neutral (n) |
Positive (n) |
|
|
|
Age |
15–30 years |
75 (30.7%) |
95 (38.9%) |
74 (30.3%) |
χ2 = 25.569, df = 6, p = 0.000 |
|
31–45 years |
57 (19.3%) |
142 (48.1%) |
96 (32.5%) |
||
|
46–70 years |
75 (25.1%) |
102 (34.1%) |
122 (40.8%) |
||
|
> 71 |
11 (36.7%) |
15 (50.0%) |
4 (13.3%) |
||
|
Gender |
Male |
58 (29.9%) |
77 (39.7%) |
59 (30.4%) |
χ2 = 3.345, df = 2, p = 0.188 |
|
Female |
160 (23.7%) |
277 (41.1%) |
237 (35.2%) |
||
|
Tribe/non-tribe |
Tribe |
69 (16.5%) |
224 (53.6%) |
125 (29.9%) |
χ2 = 60.369, df = 2, p = 0.000 |
|
Non-tribe |
149 (33.1%) |
130 (28.9%) |
171 (38.0%) |
||
|
Education level |
Uneducated |
17 (48.6%) |
10 (28.6%) |
8 (22.9%) |
χ2 = 25.696, df = 6, p = 0.000 |
|
Primary |
102 (23.5%) |
168 (38.7%) |
164 (37.8%) |
||
|
High school |
57 (20.3%) |
133 (47.3%) |
91 (32.4%) |
||
|
Graduate and above |
42 (35.6%) |
43 (36.4%) |
33 (28.0%) |
||
|
Occupation |
Business |
2 (12.5%) |
8 (50.0%) |
6 (37.5%) |
χ2 = 38.216, df = 10, p = 0.000 |
|
Farmer |
86 (19.7%) |
183 (42.0%) |
167 (38.3%) |
||
|
Government staff |
11 (32.4%) |
12 (35.3%) |
11 (32.4%) |
||
|
Homemaker |
31 (31.0%) |
46 (46.0%) |
23 (23.0%) |
||
|
Labour |
57 (32.8%) |
49 (28.2%) |
68 (39.1%) |
||
|
Students |
31 (28.7%) |
56 (51.9%) |
21 (19.4%) |
||
|
Proximity to the LI |
0–300 m |
95 (21.4%) |
184 (41.5%) |
164 (37.0%) |
χ2 = 10.038, df = 4, p = 0.040 |
|
301–600 m |
122 (29.5%) |
164 (39.7%) |
127 (30.8%) |
||
|
601–900 m |
1 (8.3%) |
6 (50.0%) |
5 (41.7%) |
||
|
Years of living in the locality |
0–30 |
65 (19.0%) |
53 (15.5%) |
225 (65.6%) |
χ2 = 8.228, df = 4, p = 0.084 |
|
31–60 |
102 (21.4%) |
57 (12.0%) |
317 (66.6%) |
||
|
61–90 |
13 (26.5%) |
1 (2%) |
35 (71.4%) |
||
Table 4. Multinomial
logistic regression results for people’s perception on the
impact of LI on avifauna.
|
Dependent variable |
Negative (Odds Ratio) |
Positive (Odds Ratio) |
|
Age (31–45) |
-0.636* (-0.334) |
-0.495 (-0.304) |
|
Gender (Male) |
-0.4 (-0.306) |
-0.544* (-0.288) |
|
Non-tribe |
1.212*** (-0.198) |
0.858*** (-0.176) |
|
Education (High school) |
-0.799* (-0.446) |
0.334 (-0.51) |
|
Education (Graduate and above) |
-1.163** (-0.47) |
0.03 (-0.524) |
|
Occupation (labour) |
1.551* (-0.834) |
0.725 (-0.591) |
|
Proximity to the LI (0–300 m) |
11.306*** (-0.385) |
-0.359 (-1.317) |
|
Proximity to the LI (301–600 m) |
11.515*** (-0.384) |
-0.599 (-1.319) |
|
Proximity to the LI (601–900 m) |
10.296*** (-0.882) |
-0.493 (-1.454) |
|
Years of living in the locality
(31–60) |
-0.493* (-0.267) |
-0.295 (-0.235) |
|
Years of living in the locality
(61–90) |
0.452 (-0.51) |
-1.377** (-0.6) |
|
Constant |
-12.041*** (-0.794) |
0.195 (-1.557) |
AIC (Akaike information
criterion) value—1,786.93 | *—p < 0.1 | **—p < 0.05 | ***—p < 0.01.
For
figure & image - - click here for full PDF
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