Living on the Edge: The Impacts of Buffer Zones on Wetland Carnivores in Vietnam

doi:10.21203/rs.3.rs-2695110/v1

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Research Article

Living on the Edge: The Impacts of Buffer Zones on Wetland Carnivores in Vietnam

https://doi.org/10.21203/rs.3.rs-2695110/v1

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Wetlands in the Mekong Delta of southern Vietnam support populations of globally threatened species, including Hairy-nosed otter (Lutra sumatrana) and, historically, Fishing cat (Prionailurus viverrinus). However, protected areas in the southern wetlands have become terrestrial islands, surrounded by aquaculture and agriculture, leading to intensified interactions between humans and wildlife. This research explored different human-wildlife interactions to assess whether they bear potential threats to populations of threatened, wetland-dwelling carnivores such as otters, wild cats, and other small carnivores. 400 semi-structured interviews were conducted in communities living in the buffer zones of two protected areas: U Minh Thuong National Park and U Minh Ha National Park. Our results revealed that fish farmers who live closer to protected area boundaries were more likely to experience conflict with otters, wild cats, and other small carnivores. While the effect of distance to the protected area’s edge on small carnivore impacts were similar in both study sites, prior impacts were found to influence increasingly severe actions of respondents against the impacting wildlife. Overall, most locals had little-to-no knowledge of Fishing cats. This evidence corresponds with other studies which suspect the Fishing cat to be in extremely low densities or potentially extirpated from the wetlands in the last few decades. High prices of wildlife have driven intensive illegal hunting in the region. More people in U Minh Thuong were aware of illegal wildlife trade activities than in U Minh Ha and men tended to have more knowledge and willingness to share about those illicit activities. Our results suggested community engagement activities to tackle human-otter conflict and illegal activities related to wildlife should target mostly men, older villagers, and fish farmers living near the edges of both protected areas. Education and outreach campaigns to improve community awareness of wildlife should target women and young people, who were significantly less aware of wildlife issues in the area overall.

Fishing cat

Prionailurus viverrinus

Hairy-nosed otter

Lutra sumatrana

Lutrinae

human-otter conflict

The Mekong Delta in Vietnam: An Overview

Vietnam is part of the Indo-Burma biodiversity hotspot (Tordoff, A. W. et al. 2012); The country is ranked 25th in the world for plant, bird and mammal species richness per unit area due to its diverse habitats and ecosystems across its latitude (Groombridge & Jenkins 2003). Among these habitats, wetlands play an important role in supporting biodiversity conservation as well as providing resources for local communities and contributing to the social and economic development of Vietnam. The largest wetland areas located in the Mekong Delta of southern Vietnam, encompass a diversity of different biomes, ranging from wide river channels interspersed with islands and mudflats, to marshes, peat swamps, and riparian forests (Khai & Yabe 2014; Olson & Morton 2018). Historically, these areas supported at least 194 bird species, 14 of which were identified to be globally threatened in the late 1990s (Buckton 1999).

The Mekong Delta contributes approximately 54% of the country’s rice production and 71% of its aquaculture production (World Bank 2020). However, this growth in agriculture has also resulted in the degradation and removal of natural wetland forests such as Melaleuca swamps and mangrove ecosystems. In 1986, an economic reform known as the “Doi Moi” policy was introduced with the intention of increasing the area of land available for agriculture and aquaculture (Hill 1984). Following the policy, many swamps, marshes and forests in the western part of the Mekong Delta were converted into shrimp ponds (Benthem et al. 1999; de Graaf & Xuan 1998). Large-scale development projects constructed dams, dykes, and canals to drain wetlands and intensify rice production (Marchand et al. 2011). Alongside these large-scale infrastructure changes, the government also implemented a resettlement policy with the intention of increasing populations in more isolated areas which were (at the time) mostly covered by Melaleuca forests and swamp grasslands. These resettlement schemes created a feedback loop, where increased population and agricultural trade led to still greater demand for infrastructure development. Consequently, more wetlands were drained and converted to human dominated land use types (Huu Nguyen et al. 2016). The increase in population not only resulted in degradation of the wetlands but also placed more pressure on the remaining natural resources. Limited habitat and natural resources have been shown to escalate conflicts between wildlife and local people (Gemeda & Meles 2018), human-wildlife conflicts increase the likelihood of hunting the opposing animals (Kloskowski 2011; Liordos et al. 2017; Rao et al. 2010), and increased hunting coupled with high wildlife demand threatens the sustainability of wild populations (Hemson 2004).

Status of Target Species

Three otter species have been recorded from the U Minh wetlands: the Hairy-nosed otter (Lutra sumatrana), Smooth coated otter (Lutrogale perspicillata), and the Asian small-clawed otter (Aonyx cinereus). While all otter species were of interest within the scope of our research, due to its rarity and global conservation status, the Hairy-nosed otter was the target species.

Hairy-nosed otter (Lutra sumatrana)

The Hairy-nosed otter is endemic to Southeast Asia and it occurs in Vietnam, Thailand, Cambodia, Myanmar, Malaysia, Brunei and Indonesia (Kanchanasaka & Duplaix 2011; Sasaki et al. 2020; Wright et al. 2008). The species has been recorded in peat swamp forest, flooded forest, lowland dipterocarp forest, hill evergreen forest and mangrove forest (Duckworth & Hills 2008; Pain 2020; Sasaki et al. 2020). Populations of Hairy-nosed otters are suspected to have declined across Southeast Asia driven by habitat loss, trade-driven illegal hunting and human-otter conflict (Gomez & Shepherd 2019; Poole 2003; Shepherd & Nijman 2014). In Vietnam, Hairy-nosed otters have been recorded in U Minh Thuong National Park, Kien Giang province and U Minh Ha National Park, Ca Mau province (Gray et al. 2022). Historical records from the 1970s exist from Ngoc Hien district where Mui Ca Mau National Park is located in Ca Mau province and from central Vietnam (“Annam” and Thua Thien-Hue province) (Table 1: Dang et al. 2001). Although hunting and trading Hairy-nosed otters is prohibited for commercial purposes under Decree 84/2021/ND-CP in Vietnam, the species has been illegally exploited for its skins, meat, and for use in traditional medicines in both national and international markets (Dang 2006). Another threat to the populations of this species in Vietnam is human disturbance due to the high density of humans surrounding their habitats, and fishing activities can cause competition for resources, leading to a lack of available prey. Finally, pesticides, herbicides and poisonous rat baits from agricultural practices could also be a potential threat to the species (Dang et al. 2001).

Fishing cats ( Prionailurus viverrinus )

Fishing cats are a typical inhabitant of wetlands in Asia. The species is discontinuously distributed in South and Southeast Asia and occurs in Pakistan, India, Nepal, Bangladesh, Sri Lanka, Vietnam, Lao PDR, Thailand, Myanmar, Cambodia and Java, Indonesia (Cutter 2009; Mukherjee et al. 2016; Pocock 1939). The species is listed as Vulnerable on The IUCN Red List of Threatened Species (Mukherjee et al. 2016). Vietnam categorises Fishing cats as an Endangered species and prohibits all hunting and trading activities associated with this species for commercial purposes under Decree 84/2021/ND-CP, Category IB. Fishing cats are strongly associated with wetland areas and can be found in marshes, swamps, oxbow lakes, reed beds, mangroves, and tidal creeks (Macdonald & Loveridge 2010). In Vietnam, Fishing cats were last recorded in 2000 in U Minh Thuong national park (Dang et al. 2004), despite intensive targeted camera trapping efforts since (Gray et al. 2022).

Context of Human-Wildlife Conflict

Human-wildlife conflict is a complex and pressing topic in conservation, especially in areas where there are limited resources to support the coexistence of humans and wildlife (Dickman 2010). Several drivers contribute to the escalation of human-wildlife conflict worldwide including: human resource consumption, land use transformation, species habitat degradation and loss, increase in ecotourism interest and natural reserves access, growth of livestock population and grazing activities, development of wildlife population due to conservation programs, climatic factors, and stochastic events (Distefano 2005). Zimmermann et al., (2020) described human and wildlife conflict occurring at three levels of intensification: disputes, underlying conflicts, and deep-rooted conflicts. Conflicts with wildlife take many forms from livestock killing, crop raiding, serious or fatal attacks (Reidinger & Miller 2013; Ripple et al. 2015; Treves & Karanth 2003), agricultural pests (Waterfield & Zilberman 2012) and disease transmission (Nyhus 2016). Among those groups of conflicts, problems with carnivores receive more concern because they play an important role in altering the structure and function of the entire ecosystem (Treves & Karanth 2003). This type of conflict is widespread and occurs across continents involving lions in Africa to dingoes in Australia (Butler 2001; Distefano 2005; Musiani et al. 2003; Naughton-Treves et al. 2003; Patterson et al. 2004; Van Eeden et al. 2018; Vijayan & Pati 2002). In Vietnam, however, both research and public attention has largely been focussed on the impacts of Asian elephants including crop-raiding and human deaths (Ly 2011), and there has been very little focus on human-carnivore conflicts.

Similarly, conflicts between humans and small to medium-sized carnivores receive less attention because the majority of them are not priorities for species conservation, as of 2019, 72.7% of recognized small carnivore species are listed as Least Concern or Near Threatened on the International Union for Conservation of Nature (IUCN) Red List of Threatened Species (Willcox 2020). There are records of both Hairy-nosed otters and Fishing cats having an impact on local communities in Southeast Asia, India and Nepal. Hairy-nosed otters have been documented as inflicting losses on fish in the river and causing damage to fish cages and nets in Sungai Merbok of Malaysia (Hotta & Yahaya 1985). Fishermen in Pru Toa Daeng Peat Swamp Forest, Southern Thailand reported fish loss in the fish traps caused by this species in the wet season (Kanchanasaka¹ & Duplaix 2011). There are no documented attacks of Hairy-nosed otters on humans; however, bite attacks and even human fatalities have been attributed to other otter species occurring in India, North and South America (Govind & Jayson 2018; Mcturk & Spelman 2005; Potter et al. 2007). Fishing cats consume both livestock and fish, thus, they can come into conflict with both fishermen and farmers. In Bangladesh, Fishing cats were killed while foraging near human settlements and fisheries during the dry season (Chowdhury et al. 2015). The species is reported to steal fish from fishing nets, cause fish loss in aqua-farms, and kill poultry and lambs belonging to villagers in Godavari Mangroves of India (Sathiyaselvam et al. 2016).

For this study, we conducted community interviews to better understand the context of human-wildlife interactions in the buffer zones of two wetland protected areas of southern Vietnam, and assess whether those interactions were threats to wild populations of Hairy-nosed otters and Fishing cats. To do this, we tried to answer several research questions: 1) are the wild cats that impact locals actually the elusive Fishing cat, and how well do local people actually know the species; 2) what are the impacts of otters and wild cats on local livelihoods, and what factors influence the probability of these impacts; 3) what actions are taken against otters and wild cats in the area, and what factors motivate increasingly hostile actions; and 4) what factors motivate hunting and trade of otters and wild cats in the area?

Study areas

U Minh Thuong National Park (UMT) is one of the most important peat swamp areas remaining in the Mekong Delta in southern Vietnam. The park comprises two parts: a core zone of 80.4 km² and a buffer zone of 130.7 km² (Ramsar Information Sheet 2015). A system of two dykes and artificial canals defines the park’s boundaries. The core protected area is surrounded by an inner dyke, containing Melaleuca forest, seasonally flooded grassland, sedge communities and open swamp (Stuart 2004); though much of the Melaleuca forest has gone or is re-growing following severe forest fires (D. Willcox pers. obs.). The buffer zone lies between the inner dyke and the outer dyke, consisting of cultivated paddy fields, scattered Melaleuca forests and human settlements (Buckton 1999). The buffer zone is under the management of two communes: An Minh Bac and Minh Thuan. In 2013, this area was home to 3,675 households and 18,852 people, consisting of three ethnic groups: Kinh (92.4%), Khmer (7.56%) and Hoa (0.027%) (Tuyen 2013). The residents live along 22 artificial canals running between the canals of the inner and outer dyke (Dzung 2002). Each household in the buffer zone was allocated an average area of 4 ha of land by the province for Melaleuca plantation, crop production and fish ponds (Cuong et al. 2019). Generally, households are distributed linearly along the canals with thin strips of land behind each house creating a herringbone pattern in the landscape.

U Minh Ha National Park (UMH) is another remaining peat swamp area in the Mekong delta, located about 80 km to the south from UMT. The park has a core zone of 85.3 km² covered by Melaleuca forest and seasonally flooded grassland, and a buffer zone of 250 km² (Du et al. 2019). As with UMT the boundary between the protected core area and the buffer zone is defined by a system of dykes and artificial canals. The buffer zone spreads over five communes of two districts: Khanh An, Khanh Lam, Nguyen Phich of U Minh district and Tran Hoi, Khanh Binh Tay Bac of Tran Van Thoi district. In 2007, there were 4,077 households and 18,823 people living in this area (Anh 2013). Kinh is the major ethnic group in the buffer zone while the Khmer ethnic group only accounts for 4.86% (U Minh Ha National Park 2018). Each migrant household to the buffer zone from 1998 to 2005 was allocated an amount of land by the province for Melaleuca plantation and crop production. The area of allocated land varies from 10 ha to 3 ha according to the time of arrival (Anh 2013). Some forest parts of the buffer zone are properties of U Minh Ha Forest enterprise, Minh Hai Flooded Forest Research Centre and Cai Tau K1 Prison.

Both study sites have been significantly degraded over the years from large fires along with agricultural and aquaculture encroachment on buffer zone habitats and protected area boundaries; local respondents were interviewed within these degraded buffer zones (Fig. 1). Even still, both sites support populations of highly threatened species such as Sunda pangolins (Manis javanica), Hairy-nosed otters, and Fishing cats (Buckton 1999; Dang et al. 2004; Nuwer & Bell 2013). Surveys of Dang et al., (2001) and Nuwer & Bell (2013) in both areas recorded conflicts occurring between otters, civets and local people due to high density of settled humans in the buffer zone areas.

Data collection

The survey team was composed of a Vietnamese researcher and an assistant. The investigator came from the north of Vietnam while the assistant varied between the two surveyed sites. Both assistants either originated or stayed a long time in southern Vietnam ensuring that they were familiar with the local accents and customs of the south to assist the investigator in interviewing. In UMT, a member of the national park’s staff accompanied the survey team to one hamlet. To gain people’s trust and be able to conduct the survey in UMH, the team obtained permission from the head of each hamlet. Neither the head of the hamlets, nor the national park staff member took part in the interviews. The information on the hamlets in the buffer zone and local names of target species, as well as other wildlife, were collected from the national parks’ scientific departments before the interviews occurred.

A quota sampling approach was applied for the surveys in both protected areas (Robinson 2014), and 200 participants were interviewed at each site. The number of participants interviewed in each hamlet in each site was designed based on its population size (Tables 1 and 2). Available and voluntary households living near to the national park boundaries and hamlet heads were selected for the interviews. In UMT, between 10 and 13 households per hamlet were interviewed in Minh Thuan commune while this figure in An Minh Bac commune is between 10 and 11 (Table 1). In UMH, 100 households were selected for the interviews in Tran Hoi commune due to its large population and long border with the national park. In Khanh An, Khanh Binh Tay Bac and Khanh Lam commune, 50, 30 and 20 households respectively were interviewed (Table 1).

Table 1

Breakdown of site interview samples for UMT and UMH
Site	Commune	Hamlet	Number of interviewed households
U Minh Thuong	Minh Thuan	Minh Tien A	10
		Minh Tien	10
		Kenh Sau	11
		Minh Dung A	13
		Minh Dung	10
		Minh Kien	12
		Minh Kien A	12
		Minh Thuong B	10
		Minh Thuong A	11
		Minh Thuong	10
	An Minh Bac	Minh Trung	10
		Trung Doan	10
		Cong Su	11
		Kinh Nam	10
		An Hoa	10
		An Hung	10
		Minh Hung	10
		An Thoai	10
		An Thanh	10
U Minh Ha	Tran Hoi	Vo Doi	100
	Khanh An	Hamlet 14	30
		Hamlet 17	20
	Khanh Binh Tay Bac	Hamlet 3	10
		Hamlet 4	20
	Khanh Lam	Hamlet 11	20

For all surveys we used a face-to-face semi-structured interview method to collect data from the participants (Torkar et al. 2011). The interviews were conducted as one-on-one talks between an interviewer and participants and in some stages of the interview, respondents were shown sets of images, some of which were of species that were historically present but now locally extirpated, and others were superficially similar, but ranged far outside of the study area. Talks were recorded using a digital audio recorder, and took about 20 minutes on average, ranging from 5 to 137 minutes. As a backup to the digital recording, the assistant interviewer took notes of the key responses throughout all interviews. The questionnaire was designed to contain both closed and open-ended questions and were framed so as to avoid leading respondents towards any particular answer (see Supplementary Material). The survey allowed us to collect demographic information on participants, local knowledge of target species, conflicts between humans and those species, their actions to the conflicts and dynamics of wildlife hunting and trade in the areas (Bryman 2012). In addition, the coordinates of selected households were recorded as spatial data. The interview records were transcribed by the primary investigator and three Vietnamese volunteers who have experience in social research. After transcription, data from open-end questions were anonymised and coded by the investigator for further analysis

While questions were asked relating to otters and wild cats, it should be noted that many respondents could not differentiate between wild cats and civets, since the local name is the same for both (Chồn), so responses about wild cat impacts, actions, and perspectives may also include civets. To assess the local knowledge of Fishing cats, the questionnaire included a set of identification questions along with three images of Fishing cats and four other cat species; each image was presented individually and in random order. These four species comprised of an extant species known to occur in the area (Leopard Cat Prionailurus bengalensis), two species that were historically present but now extinct (Asiatic Golden Cat Catopuma temminickii and Tiger Panthera tigris), and one which was only known to occur in Sundaic South-east Asia and is absent from Vietnam (Flat-headed Cat Prionailurus planiceps) (See Supplementary Material). The first question in the set was whether or not respondents knew about wild cats and civets in the area; if the answer was “yes”, the following question required respondents to list all the names of wild cat and civet species in their areas. Respondents who referred to Fishing cats or “Chồn cáo cộc” (the local name for Fishing cats) in their list were then asked to describe the species and identify it from a set of images that included the four other felid species. If the respondent correctly identified the Fishing cat from the set of images, we recorded the instance as “1”; if the respondent could not identify the Fishing cat, we recorded the answer as “0”.

Analysis

In accordance with the informed consent provisions, some respondents declined to answer certain questions. In such cases non-responders were excluded from any analysis relating to that particular question although their responses were retained (where complete) for other questions. Because respondents could not always reliably distinguish between wild cats and civets, these two taxa are grouped here as “other small carnivores” / “small carnivores”. This grouping does not include otters; respondents were able to distinguish this carnivore taxon from the others present in the landscape.

Binomial Generalised Linear Models (GLM) were run with the base function of program R (R Core Team 2021) to test the influence of demographic, land use, and spatial factors on the following: 1) the impacts of otters and other small carnivores on local people’s properties, 2) knowledge and perceptions of otters and fishing cats in the area, and 3) the potential of local people to hunt and trade otters and other small carnivores. To assess impact probability. a “global model” (model with all potentially relevant variables) was established using binary dependent variables to indicate presence or absence of 1) reported impacts, whether or not the respondent hunted otters or other small carnivores, and knowledge of, ability to describe, and ability to identify Fishing cats. The dependent variables in the impact model global model included 1) number of years living in the area (ordinally categorised in 15-year breaks), 2) gender (male/female), 3) education level (categorised into four ordinal categories), 4) quantity of people in household, 5) distance from the protected area (metres), 6) whether or not the household operated a fish farm on their property (yes/no), and whether or not the household kept poultry livestock (yes/no). Only distance from the protected area, and whether or not the location was a fish farm or kept poultry livestock was used for the impact models, as demographic variables were irrelevant to the question (See Supplementary Material).

Global models were run through a Generalised Variance Inflation Factor (GVIF) check by the car package (Fox & Weisberg 2018) with a threshold of 10 to ensure there were no variance inflation/multicollinearity issues (Fox 2016; Fox & Monette 1992); if any variables exceeded the threshold they were removed from the model. The global models were then run through a dredge function (a model selection function that compiles all possible combinations of the data) provided by the MuMin package (Barton 2020), and the “best model” was selected based on the lowest Akaike Information Criterion (AIC). If a model fell within 2 ΔAIC (< 2 AIC difference from the lowest AIC model), model averaging and 95% Confidence Intervals (CI) were used to identify potentially uninformative parameters (Arnold 2010). The next best fit model was then selected on omission of uninformative parameters and higher log likelihood ratio. A secondary binomial logit-link GLM was made to test for marginal effects of land use categories and reported otter or wild cat impacts. All selected models with categorical variables were analysed for marginal effects (a method of scaling and centring predictor variables to see the extent of their effects on the independent variable) using the margins package (Leeper 2021) and were run using a binomial logit-link function as a multinomial model. Multinomial models with categorical data rely on the binary dependent variable to weight the categories rather than the standard logistic distribution of numerical models. If the intercept was shown to be the best fit model, or if a singular Hessian error was thrown by the best fit model, the model was considered void, meaning the explanatory variables failed to explain the dependent variable. Regression analysis results were reported following guidelines from (Zuur & Ieno 2016). All R code and model selection table outputs can be found in the Supplementary Material.

Finally, Cumulative Link Models (CLM), a flexible regression model used to analyse ordinal score data, were run using R package “ordinal” (Christensen 2019) to analyse if any of the demographic, landscape, or spatial variables influenced the respondent’ knowledge of Fishing cats or their actions taken against otters and other small carnivores in the area. Respondents’ knowledge of Fishing cats was divided into four levels: 0 – having no knowledge of Fishing cats, 1 - knowing the name of Fishing cats, 2 – knowing the name and being able to describe Fishing cats, and 3 - being able to identify Fishing cats through given images among other wild cats. Actions against wild cats and otters and other small carnivores were ordinally ranked from 0–4 and represented: 0 – ignoring the animals, 1 – being unable to address the problems, 2 – proactively preventing damages by using light, nets and/or dogs, 3 – chasing the animals away, 4 – beating, trapping, and/or killing the animals. Since it was assumed that respondents would be less likely to admit injuring or killing wildlife, they were encouraged to answer the question rankings based both for themselves and for people they know in their community as a proxy. For the CLM on ranked Fishing cat knowledge and perceptions, a global model was made using the variables: 1) age, 2) years living in the area, 3) gender, 4) education level and site (UMT, UMH), For the global model on actions against wildlife a CLM was created using the variables: 1) respondent age, 2) gender 3) land use, 4) distance from protected area (m), whether or not they were impacted from otters (0 = not impacted, 1 = impacted). The same model selection process was used for both CLM and GLM models.

Demographics

Of the 400 respondents interviewed, 55.75% of respondents were male and 44.25% of them were female. Respondents of the survey belonged to two ethnic groups with the dominance of Kinh (92.7%) and a small number of Khmer (7.3%). Age of respondents at the year of interview (2020) ranged from 18 to 92 (mean = 53.8 ± 13.7, N = 399). The average number of years they lived in the buffer zone was 24.7 ± 8.7 (N = 390). The majority of respondents only completed primary school or had basic literacy skills (41%, 140/338), followed by secondary school (36.4%, 123/338), and high school and above (13.6%, 46/338). Only 8.6% (29/338) of respondents were illiterate. The household size ranged from 1 to 17 people (median = 4, N = 391).

The average distance from respondents’ houses to the border of the protected areas is 0.78 ± 0.7 km (N = 399). This figure varied largely by site due to the different patterns of settlements in two national parks’ buffer zones: 0.5 ± 0.8 km (range: 12.59–4082.61) in UMT and 1.1 ± 0.3 km (range: 81.31–2591.14) in UMH. On average, each household owned approximately 4.1 ± 2 hectares. The most common land use was the combination of crop and fish farming (47.8%), followed by crop, timber and fishing farming (21%), crop and timber farming (9.6%), crop farming (8.3%), timber and fish farming (5.8%), timber farming (4.3%), crop and shrimp farming (2.8%), and crop, timber and shrimp farming (0.25%).

Respondents’ knowledge of Fishing cats

Overall, 32% (150/400) of respondents knew the name “Fishing cats” (Vietnamese name: Mèo Cá; local name: Chồn Cáo Cộc). The local name given to Fishing cats in the region, ‘Chồn Cáo Cộc’, means “aggressive cat”. Only around half of the respondents (58.67%, 88/150) attempted to describe the species, and half of this amount (55.7%, 49/88) could identify Fishing cats when provided images. However, no respondent could confidently identify Fishing cats from all three images, and 48.9% (24/49) of those who could identify Fishing cat from at least one image, would then go on to make identification errors in other sets of images, including those of Leopard cat (Table 2). Out of 25 respondents who identified Fishing cat and didn't make errors on extinct or absent cat species, 84% couldn't identify or didn't know Leopard Cat - the most common wild cat in both areas. Essentially, only four respondents could identify Leopard cat in both of the two images provided, identify at least one of the three images of Fishing cat correctly, and not produce errors on the images of Asiatic golden cat, Flat-headed cat, or Tiger. As the responses were so variable, and no one could identify Fishing Cat correctly from all three images used, no further analysis on these results was undertaken.

Table 2

Responses to Fishing cat image identification question. Fishing cat responses are emphasised in bold text to show the number of respondents to identifying and misidentifying each image.
Animal in Photo	Response	n	%
Leopard cat (1)	Big wild cat	1	0.7
	Cat	4	2.9
	Civets	1	0.7
	Crab-eating mongoose	2	1.4
	Fishing cat	5	3.6
	Leopard cat	99	72.8
	Palm civet	18	19.6
	Tiger	2	2
	Wild cats	1	1
	Wild cats and civet	7	6.9
Leopard cat (2)	Big wild cat	1	1.1
	Civets	1	1.1
	Crab-eating mongoose	2	2.1
	Fishing cat	4	3.5
	Leopard	1	0.7
	Leopard cat	55	35.9
	Palm civet	28	28.3
	Tiger	1	1.4
	Wild cats and civet	1	1.3
Fishing cat (1)	Cats	1	1.4
	Civets	2	2.7
	Fishing cat	22	19.8
	Leopard cat	34	37.8
	Palm civet	9	10.6
	Tiger	1	1.3
	Wild cats and civet	3	3.1
Fishing cat (2)	Civets	4	3.7
	Fishing cat	38	36.2
	Leopard	1	1.5
	Leopard cat	29	42.6
	Otter	1	2.1
	Palm civet	20	25.6
	Tiger	8	12.1
	Wild cats	1	1.6
	Wild cats and civet	6	9.5
Fishing cat (3)	Big wild cat	1	1.9
	Civets	1	1.8
	Crab-eating mongoose	1	1.8
	Fishing cat	9	13
	Leopard cat	31	50
	Palm civet	8	25
	Wild cats and civet	3	12
Flat-headed cat (1)	Crab-eating mongoose	3	12
	Fishing cat	1	4.3
	Leopard cat	14	50
	Otter	2	9.5
	Owl	1	3.7
	Palm civet	1	2.9
	Tiger	1	2.6
	Wild cats	1	2.6
	Wild cats and civet	1	2.6
Flat-headed cat (2)	Civets	1	2.6
	Crab-eating mongoose	6	15
	Fishing cat	7	16.3
	Leopard cat	8	21.6
	Otter	8	16.3
	Palm civet	5	11.9
	Squirrel	1	2.6
	Tiger	1	2.6
	Wild cats and civet	1	2.5
Asiatic golden cat (1)	Cats	3	7.7
	Fishing cat	9	22.5
	Leopard	1	3.1
	Leopard cat	20	48.8
	Lion	1	3.8
	Tiger	2	7.7
	Wild cats	1	4
	Wild cats and civet	2	7.7
Asiatic golden cat (2)	Cats	4	15.4
	Crab-eating mongoose	1	1.3
	Fishing cat	10	12.7
	Leopard cat	5	7.2
	Lion	1	1.6
	Palm civet	1	1.6
	Tiger	2	3.2
	Wild cats and civet	2	3.3
Tiger	Tiger	58	100

Impacts of otters and other small carnivores on people

Overall, around half of respondents reported experiencing problems with otters (48.1% 190/395). Most of them farmed fish (185/190) and encountered fish loss because of otters. 27.8% (110/395) of respondents never experienced problems with otters even though they farmed fish. A few fishermen (5/190, 2.6%) reported otters taking fish and destroying fish traps in the rivers. Furthermore, 63.5% of respondents farming fish in UMT’s buffer zone had problems with otters while this number in UMH was slightly smaller (60.5%).

The best models to explain our data on otter and small carnivore impacts showed that otters impact fish farms significantly more than non-fish farms, and probability of impacts grew with proximity to the protected areas at both sites; wild cats and other small carnivores showed similar, yet much weaker trends in their impacts, and were more associated with households that kept poultry livestock (Fig. 2).

The model with lowest AIC for wild cats, and other small carnivores was the same as the best fit model for otters, with an additional binary covariate explaining whether or not the household kept poultry livestock; however, the model with only distance and poultry livestock was within 2 ΔAIC and had a greater log likelihood ratio (indicating redundancy in the best fit model by lowest AIC), so it was selected instead (Table 3; Supplementary Material). For each site, distance from protected area and fish farms were the significant indicators of otter impacts, while for other small carnivores, distance was the significant factor overall, but mostly for U Minh Thuong. According to the marginal effects of the GLM run with land use types (Fig. 2. D), both otters and other small carnivores were significantly more likely to impact fish farms than other non-fish farm land use types in the buffer zones.

Table 3

Coefficient estimates, standard error, z-values, and p-values for GLM model outputs on otters, wild cats, and other small carnivores impacts for both sites, U Minh Ha, and U Minh Thuong.
Otters
Formula: formula = impact_from_otters ~ distance (m) + fishing_farm + 1, family = "binomial"
Both Sites
	Estimate	Std..Error	z.value	Pr...z..
(Intercept)	-2.768	0.601	-4.607	< 0.001
distance (m)	-0.001	0	-3.976	< 0.001
fishing_farm	3.752	0.602	6.235	< 0.001
U Minh Ha
(Intercept)	-2.892	0.754	-3.835	< 0.001
distance (m)	-0.001	0	-2.055	0.04
fishing_farm	3.897	0.745	5.228	< 0.001
U Minh Thuong
(Intercept)	-2.504	1.039	-2.411	0.016
distance (m)	-0.001	0.0005	-3.075	0.002
fishing_farm	3.633	1.038	3.499	< 0.001
Wild Cats
Formula: impact_from_wild_cats ~ distance (m) + keep_poultry + 1, family = "binomial"
Both Sites
	Estimate	Std..Error	z.value	Pr...z..
(Intercept)	-1.281	0.343	-3.737	< 0.001
distance (m)	0	0	-2.377	0.017
keep_poultry	0.437	0.238	1.838	0.066
U Minh Ha
(Intercept)	-0.738	0.333	-2.217	0.027
distance (m)	-0.0004	0.0003	-1.719	0.086
keep_poultry	0.418	0.344	1.216	0.224
U Minh Thuong
(Intercept)	-0.593	0.338	-1.756	0.079
distance (m)	-0.002	0.001	-2.379	0.017
keep_poultry	0.459	0.337	1.362	0.173

Actions Taken in Response to Human-Wildlife Conflict

Actions of respondents who encountered issues with otters reported: 0 – ignoring (15.1%), 1 – being unable to address problems (47.6%), 2 – proactively preventing damages from otters by using light, nets and/or dogs (6.1%), 3 – chasing otters away (10.4%), 4 – beating, trapping and/or killing otters (20.8%). Substantially more respondents reported otters being beaten or killed around impacted sites (n = 37) than in non-impacted sites (n = 6). The best fit model of the CLM for both sites indicated that elevated actions being taken against otters was significantly explained by whether or not the site was impacted by otters; for UMH the best fit model indicated that there was a highly significant declining trend for age, and timber or timber + fish farm land uses in relation to actions taken against otters; and for UMT the best fit model indicated that actions against otters increased with impacted households, and more severe actions with distance, age was included it was not shown to be significant (Table 4).

Table 4

Coefficient estimates, standard error, z-values, and p-values for GLM model outputs on otter and wild cat impacts for both sites, U Minh Ha, and U Minh Thuong.
Both Sites
Formula: otter_actions ~ impact_from_otters + 1
	Estimate	Std. Error	Z value	P-value
0\|1	-1.359	0.277	-4.903	< 0.001
1\|2	0.955	0.262	3.649	< 0.001
2\|3	1.204	0.267	4.517	< 0.001
3\|4	1.799	0.285	6.316	< 0.001
impact_from_otters	0.555	0.294	1.888	0.059
U Minh Ha
Formula: otter_actions ~ age_to_2020 + land_use + 1
0\|1	-5.808	1.133	-5.127	< 0.001
1\|2	-2.849	0.997	-2.859	0.004
2\|3	-2.492	0.989	-2.521	0.012
3\|4	-1.604	0.978	-1.641	0.101
age_to_2020	-0.051	0.016	-3.164	0.002
crop + timber	0.020	0.777	0.026	0.979
crop + timber + fish farming	-0.925	0.603	-1.534	0.125
crop + timber + shrimp farming	-1.340	1.902	-0.705	0.481
timber	-2.812	0.947	-2.969	0.003
timber + fish farming	-1.604	0.740	-2.170	0.030
timber + shrimp farming	-0.478	1.577	-0.303	0.762
U Minh Thuong
Formula: otter_actions ~ age + distance_m + impact_from_otters + 1
0\|1	0.246	0.789	0.312	0.755
1\|2	2.463	0.815	3.021	0.003
2\|3	2.714	0.823	3.297	0.001
3\|4	3.181	0.841	3.783	< 0.001
age_to_2020	0.021	0.012	1.696	0.090
distance_m	0.001	0.000	1.962	0.050
impact_from_otters	0.875	0.439	1.994	0.046

Actions of respondents who encountered issues with other small carnivores reported: 0 – ignoring (4.6%), 1 – being unable to address problems (35.1%), 2 – proactively preventing damages from other small carnivores by using light, nets and/or dogs (22.9%), 3 – chasing other small carnivores away (4.6%), 4 – beating, trapping and/or killing other small carnivores (32.8%). A similar number of respondents reported other small carnivores being beaten or killed around both impacted sites (n = 21) and non-impacted sites (n = 22). There was no best-fit model with significant factors explaining actions against other small carnivores using any combination of our recorded variables for UMT, UMH, or data from both sites combined.

Illegal hunting and trade

A fifth of interviewees (20.75%) hesitated to answer the question of illegal wildlife activities. Among those who responded to the question, 64.56% (204/317) of them revealed knowing of illegal wildlife hunting inside the protected area. Approximately 30.25% (121/400) of respondents mentioned illegal wildlife snaring in the buffer zone. Animals and their products that were reported to be illegally harvested or collected included pangolins (52.7%, 99/188), wild pigs (10.1%), sambars (12.2%), wild cats/civets (14.9%), otters (5.3%), macaques (0.5%), squirrels (0.5%), birds (3.2%), bats (0.5%), pythons (14.9%), other snakes (15.4%), turtles (5.3%), monitor lizards (0.5%), fish (28.7%), eels (5.8%), and honey (30.3%). About 32.9% (108/328) of respondents reported price of wildlife in the local markets surrounding both wetland protected areas (Table 5).

Table 5

Price of wildlife reported by respondents in both study sites. The range was identified by the minimum and maximum numbers given by respondents
Wildlife	Price (USD)
Sunda pangolin (Manus javanica)	$43.5 - $521/kg
Fishing cat (Prionailurus viverrinus)	$43.5 - $391/individual
Leopard cat (Prionailurus bengalensis)	$8.7 - $87/kg
Hairy-nosed otter (Lutra sumatrana)	$130 - $174/kg
Otters (general)	$43.48/pelt; $3.49 – $17.4/kg
Sambar deer (Rusa unicolor)	$4.3 – $8.7/kg
Wild pig (Sus scrofa)	434.8/individual
Small Indian civet (Viverricula indica)	$21.7 - $217/kg
Masked palm civet (Paguma larvata)	$15.2 - $16.5/kg
Squirrels (general)	$3/individual
Bats (general)	$0.09– $0.22/individual
Monocled cobras (Naja kouthia)	$17.4/kg
Sunbeam snake (Xenopeltis unicolor)	$10.86/kg
Oriental rat snake (Ptyas mucosa)	$6.5/kg
Bocourt's water snake (Subsessor bocourti)	$17.4/kg
Pythons (Python/Malayopython spp.)	$4.34/kg
Monitor lizards (Varanus spp.)	$2.17/individual

Our best fit model on hunting reports showed that men living on fish farms reported hunting activities significantly more than females, even though female respondents interviewed were closer to protected areas on average (mean = 709.76 m) than male respondents (mean = 830.63 m), and were interviewed at nearly equal land use types as males; there was also an increasing trend in probability of reporting with increasing distance from the protected area (Fig. 3). There were no recorded variables that significantly explained reasons for hunting otters or wild cats, including all collected demographic data, distance from the protected areas, and living on fish farms impacted by otters.

Our survey found that conflict between humans and otters, and humans and other small carnivores (wild cats/civets) is primarily related to the distance of households from the protected areas and the availability of prey items that humans keep as livestock. Households farming fish near the edge of the protected areas were more susceptible to problems with otters, as were households that kept chickens with other small carnivores. This result concurs with those of previous studies that proximity to the forest’s edge is a strong predictor for problems caused by mammals (Linkie et al. 2007; Naughton-Treves 1998). A similar proportion of households farming fish encountered problems with otters (> 60%) in both sites indicating the existence of conflict between otters and humans in their distributions. We observed a similar upper limit on the distance that otters stray from the park’s boundary in the two study sites. Fish farmers who live beyond 2.5 km reported no impact from otters. Assuming that otter dens are located within the park boundaries, we estimate the linear extent of otter dispersal distances to be approximately 3 km to 7.5 km from the protected area boundaries to local areas of high human density.

Otters foraging outside of the forests could be explained by low prey abundance inside the protected area due to poor management of the wetlands’ fish diversity and stocks. Another possible driver for this activity is the higher foraging success in limited areas like a fish pond with high density of prey. Some respondents also reported that otters preferred basa (Pangasius bocourti) and striped catfish (Pangasianodon hypophthalmus) in the farming ponds which are less active and slower than other kinds of fish. Stocking fish species less preferred by otters could also be the reason for more than 27% of respondents not encountering problems with otters despite farming fish.

Hairy-nosed otters and Asian small-clawed otters are confirmed to occur in both U Minh Ha and U Minh Thuong (Buckton 1999; Dang et al. 2001; Willcox et al. 2017). Hairy-nosed otters and Asian small-clawed otters were reconfirmed from U Minh Ha in 2021, and Hairy-nosed Otter from U Minh Thuong in 2020 (Gray et al. 2022). While dietary information remains deficient for all Asian otter species, fish are speculated to be the main prey of Hairy-nosed otters, while Asian small-clawed otters have a more diverse diet dominated by freshwater crabs in some localities (Kruuk 2006). Hairy-nosed otters, therefore, are more likely to raid local fish ponds and cause conflict with fish farmers, which is all the more concerning because of the two species, Hairy-nosed otters are more threatened with extinction.

While there was no significant evidence that respondents’ demographic characteristics, or distance affected their actions to conflicts with otters in our statistical models, there was a significant trend in increasing actions taken on behalf of impacted households compared to non-impacted households, and our initial models have established that impacted households are closely associated with proximity to the protected areas. This disparity in reported actions being directly associated with distance could simply be a reluctance on part of the respondents to make such claims. Other factors such as social norms, species management, and regulations may be involved in people’s responses to conflicts and actions taken against animals (Dickman 2010). In this initial study, around a half of respondents (46%) had no actions to address problems with otters due to either lack of effective tools or fear of strict retributions from law enforcement if causing harm to protected species. On the other hand, nearly equal amounts of respondents reported taking no action (35%), and taking the harshest actions (33%) against wild cats/civets.

Local ecological knowledge has been used to investigate species distribution and collect qualitative information of their abundance and population trends (Anadón et al. 2009; Gandiwa 2012; Mohd-Azlan et al. 2013). However, its application in identifying the status of ecologically / physically similar species, is very challenging, particularly if relying on ambiguous local names. The results from this survey provide further evidence that the use of interview-based methods must be applied extremely carefully when assessing the status of wildlife species (Balestrieri et al. 2011; Fitzpatrick et al. 2009; Mcclintock et al. 2010; Meijaard et al. 2011). Respondents in both localities were unable to accurately identify all Fishing Cat images, and made a large number of errors with images of other cat species, this made interpreting their local ecological knowledge on the target species impossible. Camera-trapping and other techniques that produce verifiable data will always be needed when surveying areas with rich carnivore assemblages. Camera-trapping surveys targeted at small carnivores (including cats) in U Minh Ha and U Minh Thuong have failed to record Fishing Cat (Gray et al. 2022; Willcox et al. 2017); low awareness and an inability of people to consistently identify the species, may also be a reflection of its increasing rarity and possible local extinction in the area.

Vietnam’s wildlife continues to suffer from demand for the wildlife trade and it is a major cause of species loss in the country (Van Song 2008). In this survey, trade values were reported for several taxa, including civets, otters, snakes, and bats. Pangolins had the highest reported trade value of 512 USD / kg. (Newton et al. 2008) reported that hunters valued pangolins at around US $94/kg in 2007 while (Challender et al. 2020) reported pangolin prices at restaurants in Ho Chi Minh city were US $300/kg in 2018. The survey results support pangolins’ status as one of the most sought-after species groups for the illegal wildlife trade (Baillie et al. 2014; Liu & Weng 2014). There was a large range of prices reported, for all taxa, including for pangolins (43.5 - $521 / kg). A wide price range may include wholesale and retail values, which vary by respondents’ knowledge in different stages of trade: from hunters, brokers to markets, restaurants and Chinese traditional medicine shops. Accurate price data for illegally traded wildlife is difficult to capture: the trade is illegal, and respondents will, for obvious reasons, not always be willing to give accurate answers. The price data obtained in this survey can be used to assess the relative trade demands on certain taxa, but may not necessarily be reflective of the species’s or the taxon’s actual market value.

There is some evidence that men were more likely to report illegal wildlife activities than women which aligns with the findings of previous studies as differences in labour division and social norms restricted women’s knowledge of illegal wildlife activities (Afriyie et al. 2021; Bitanyi et al. 2012). Respondents in UMT were more likely to report illicit hunting in the area than those in UMH. This may indicate a higher number and frequency of illegal activities on this site. Some respondents in UMT reported hunters from Ca Mau had conducted hunting in this park. In addition to this, a hunter in UMH stated that his father and he went to UMT for hunting because it had a higher density of wildlife than their area. There was another notable trend of reports of illegal activity occurring more often further from protected areas, this may simply be due to respondents’ unwillingness to report crimes close to a protected area in fear of repercussions by law enforcement. Asking people to report illegal activities can be considered a sensitive line of questioning and so some respondents may have been reluctant to answer honestly for fear of being criminally charged. People also may give information considered to be socially desirable rather than reporting the truth (Kuncel & Tellegen 2009).

This study had some methodological constraints and limitations of available data. Quota sampling is a convenient method to collect data, however, it can limit the external validity of our results. The reliability of questionnaires is not guaranteed due to the lack of pre-testing and pilot survey (Bryman 2012). Non-response or dishonest answers to some sensitive questions on illegal wildlife hunting and trade may result in under-reporting of those activities (Fisher 1993; Groves 2006). While neither the head of the hamlets, nor the national park staff member took part in the interviews, their presence may have potential impacts on interviewees’ responses, an effect known as social desirability bias (Grimm 2010). Unavailable data of social norms or perception of law and regulations limited our understanding of factors that influenced people’s reactions to problems with otters and wild cats.

In conclusion, our study provides baseline information on the interactions between humans and wildlife in two isolated wetland protected areas to assess existing and potential threats to populations of otters and other small carnivores. Our research found that human settlements (particularly fish and poultry farms) proximal to the two wetland protected areas in this study may be significant drivers of human-wildlife conflict, hunting, and trade. It should be noted that both human-wildlife conflict and illegal hunting of these threatened species are likely to be exacerbated by the island effect of agriculture and human settlements completely surrounding both wetland protected areas, and this effect may increase over time with further encroachments if effort is not made to increase connectivity between them and remaining natural areas of the Mekong Delta. Based on the findings of this study, we recommend:

Further studies on hairy-nosed otter ecology, behaviour and human attitudes to the problems with this species to mitigate conflict between fish farmers and otters, focusing on households adjacent to the edge of the protected areas.

More conservation efforts in UMT to reduce illegal hunting and trade. Those programs should engage local communities and focus on men to gain positive responses in tackling those problems.

Education programs and outreach campaigns targeting women and young people to improve community awareness of wildlife and conservation.

ACKNOWLEDGEMENTS

We would like to thank National Geographic for financial support under grant NGS-5949C-19 for our projects in the U Minh Wetlands. We also thank Tran Van Thang, former director of U Minh Thuong, and Huỳnh Minh Nguyên director of U Minh Ha for facilitating and coordinating our work with local commune leaders and communities.

AUTHOR CONTRIBUTIONS

HTTN and DW conceived the study concept, methodology, and design. HTTN, DVL, TanVN, TTN, TVT collected the data and facilitated the work. RJG and HTTN analyzed the data. HTTN, RJG, DW, TVP, and LNC wrote and edited drafts of the manuscript. EM acted as an advisor to the first author. ThaiVN facilitated the research.

DATA AVAILABILITY

The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.

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No competing interests reported.

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Living on the Edge: The Impacts of Buffer Zones on Wetland Carnivores in Vietnam

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Abstract

Figures

Introduction

The Mekong Delta in Vietnam: An Overview

Status of Target Species

Context of Human-Wildlife Conflict

Methods

Study areas

Data collection

Analysis

Results

Demographics

Respondents’ knowledge of Fishing cats

Impacts of otters and other small carnivores on people

Actions Taken in Response to Human-Wildlife Conflict

Illegal hunting and trade

Discussion

Conclusion

Declarations

References

Additional Declarations

Supplementary Files

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