Integrating Locals’ Importance-Performance Perception of Adaptation Behaviour into Invasive Alien Plant Species Management Surrounding Nyika National Park, Malawi

Abstract

Invasive species are a huge concern to environmental management across the world because they threaten ecosystems, habitats, and species biodiversity, with largely permanent consequences. This study investigates the aspects of community capital and community resilience for the management of Invasive Alien Plant Species (IAPS) under importance-performance analysis in communities surrounding Nyika National Park (Mhuju and Ntchenachena) in Malawi. The study used the binary logistic regression model to determine the locals’ management and adaptation behaviours to IAPS. The findings show that although both IAPS management and adaptation were considered highly important, their performance was only rated at a low level, indicating a significant gap between the importance of eight management and adaptation behaviours for IAPS and their actual performance. The results also show that IAPS management strategies such as ‘’promoting community awareness of common IAPS and their impacts on livelihood” and “incorporating IAPS issues into the school curriculum” are useful in nurturing the locals’ management behaviour. Furthermore, we have identified the following characteristics as having a significant influence on the locals’ participation in IAPS impact reduction and adaptation: (1) age, (2) residential area, (3) understanding the IAPS impacts, (4) membership of farmers’ club or Village Natural Resource Management Committee (VNRMC), and (5) discussion of IAPS in farmer club or VNRMC. These findings provide empirical evidence to policy makers for an effective IAPS management strategy.

1. Introduction

Invasive Alien Plant Species (IAPS) are one of the major drivers of biodiversity loss globally, affecting both humans and the environment [1,2,3,4]. Concisely, IAPS are plants that are introduced into an ecosystem mainly by human activities (trade, travel, and tourism) and have few local predators such as herbivores who feed on them [5,6]. Subsequently, IAPS tend to alter the local environment and colonize it in a short time [7,8] as a result, it becomes less suitable for the native species. The IAPS deplete supply densities of native species which makes it very difficult to control or reverse their environmental impacts [3,4,8,9,10,11]. IAPS have enormous effects, for example, they cause annual economic damage of USD 1.4 trillion (five percent of global GDP) around the world [5]. The total annual crop loss caused by IAPS in the United States of America is estimated to be between USD 2 and 3 billion [12]. In Southeast Asia, the invasive species caused a total annual loss of USD 33.5 billion (with agriculture accounting for nearly 90% of the total, or USD 23.4–33.9 billion) [13]. Consequently, IAPS are regarded as a hidden threat to sustainable development, as they have an equal impact on the achievement of sustainable development goals (SDGs) number 1 (poverty reduction); number 2 (zero hunger); number 3 (ensuring healthy lives); number 6 (sustainable water management); number 9 (industry innovation and infrastructure); number 14 (aquatic ecosystems); number 15 (terrestrial ecosystem); number 16 (peace justice and strong institutions); and number 17 (partnership for the SDGs) [4,14].

The problem of IAPS is similarly huge in Africa including Malawi despite considerable efforts in some countries to remove them [15]. IAPS were introduced in Sub-Saharan Africa primarily for economic and aesthetic reasons, but their environmental, social, and economic impacts are now more serious and outweigh their benefits [16]. IAPS are one of the major constraints to agricultural production and food security as they contribute to the reduction of crop yields, and medicinal plants through loss of biodiversity just to mention a few [4,9]. The enormous decline in crop yield caused by IAPS is of great concern in poor African countries with agro-based economies such as Malawi.

Global, regional, and country-specific commitments to invasive species management recognize the impacts of IAPS on biodiversity, ecosystem services, food security, human health, and economic development [8]. Regional, international, and global conventions, policies, and programs are thus geared toward the prevention, control, or eradication of IAPS. However, there have been few successes in reducing the spread of IAPS because massive global campaigns on tree planting aimed at mitigating climate change have resulted in the planting of trees regardless of biogeography status (native and non-native) presented as a panacea [17]. As a result, efforts to achieve IAPS control and impact reduction are deemed insufficient [5,17]. This is due to the fact that research in the field of invasion science has been more focused on natural and semi-natural environments rather than largely human-dominated ecosystems [5,11].

As such, there is a limited scholarly understanding in Malawi uncovering the locals’ adaptation behaviours into the management of IAPS. Encouragement of adaptive capacity becomes a critical issue in a situation where the community’s livelihood is endangered [18]. However, for locals’ adaptive capacity to be existent there is a need for resources. It is worth noting that the effects of IAPS are difficult to control and reverse hence adaptation becomes imperative [8,10,11]. On the other hand, some IAPS have been embraced by local communities and are crucial for livelihood and national economies through the services they provide [19]. These include pest control [20,21,22], building materials, medicine, timber, and firewood [4], which are the primary motivators for local adaptation behaviors to IAPS. This study assesses the eight indicators for the locals’ adaptive behavior under IAPS solutions throughout the literature review and stakeholders’ interview, in addition this study synthesizes the perspectives from locals’ feedbacks around Nyika National Park (NNP) in Malawi. Second, we determine the importance-performance (I-P) levels of the indicators among farmers and non-farmers, using geographical areas. The non-farmers in this study are those people whose main source of income is not from farming with a non-farming occupation. By comparing the perception of farmers and non-farmers towards IAPS adaptation and management, this exposes the interest and experience of both categories which are key for effective management interventions. Finally, this study analyzes the factors influencing locals’ participation behaviour in IAPS management strategies based on binary choice models.

2. Literature Review

2.1. Social-Economic and Ecological Impact of IAPS in Malawi

The IAPS in Malawi are negatively affecting the biodiversity of both local and international significance as well as natural habitats, the latter being national parks [2,4]. IAPS indirectly perpetuate poverty by affecting the livelihoods of millions of people in Malawi, an agro-economy-based country where 80% of the population is employed as small-scale farmers. IAPS encroach into the farmland where they compete for nutrients with crops thus leading to yield reduction, exacerbating food insecurity and malnutrition [4,10,23].

The impact of IAPS (Pinus patula, and Eucalyptus) on water resources in Malawi is potentially huge. Studies in southern Africa on water catchments with these IAPS have revealed adverse impacts on water availability in Mpumalanga, South Africa. The replacement of glass land and planting of Pinus patula, and Eucalyptus resulted in the drying up of rivers within 6–12 years [24]. Further studies reveal that the removal of dense stands of pines and wattles (Acacia mearnsii) in the riverbanks resulted in a 120% stream flow increase [25]. On the other hand, planting of pines in the Drakensberg in KwaZulu–Natal, South Africa resulted in reducing stream flow by 82% [26]. With similar IAPS being found in protected areas of Mulanje Mountain and NNP and its adjoining agro-ecosystems, both being major sources of rivers that supply water to most parts of Malawi, the risk of running into a serious water crisis for both domestic use and irrigation in areas that are supplied by water from these two sources cannot be undermined. Mulanje Mountain has a total of nine rivers and hundreds of streams that provide water to most of the population in southern Malawi [23]. This is similar to Nyika (which means where the water comes from) as it supplies water to the larger part of the northern region of Malawi and Zambia. Furthermore, Nyika is a major sponge area (it has four major rivers that flow into Lake Malawi) for Lake Malawi and Luangwa River, Zambia [23].

The availability of the IAPS in these water catchments and wetlands is one of the causes of a serious scarcity of water [27] for both domestic and economic use. In rural parts of Malawi, women and girls walk a long distance to fetch water [28]. This deprives them of time to engage in other productive activities such as education, income generation, cultural and political involvement, rest and recreation [28]. Furthermore, drying up rivers greatly affects the generation of hydro-electric power in Malawi due to low water levels in Lake Malawi consequently affecting industrial production and all economic activities that depend on electricity [29].

In addition, the presence of IAPS in these protected areas affects biodiversity equally threatening tourism. In Malawi, tourism is one of the major contributors to its GDP with an increasing trend from 8% to 13% in 2014 and 2018, respectively [23]. With biodiversity loss due IAPS impact, the NNP risks losing out its tourism destination potential to other equally competitive national parks within and outside Malawi.

These social-economic and ecological impacts make it imperative for the locals and the nation to devise adaptive strategies enhancing adaptivity capacity as the effects of IAPS are often irreversible.

2.2. The Theory of Adaptive Capacity

The concept of adaptive capacity is rooted in Sen’s capacity theory and the sustainable livelihoods assessments which were developed in the 1980s and 1990s [30]. Other scholars suggest that the adaptive capacity theory originates from sociology, business studies and organization management [31]. The studies on how humans adapt to environmental venerability (within which this study is situated) have their roots in anthropology [32]. From the academic arguments, three key issues stand out in measuring the community adaptive capacity and these include: the degree of change that the system can withstand while maintaining its function and structure; the system’s level of self-organization; and the system’s level that improves adaptive capacity through learning [18,33,34]. It is therefore from these basic elements that the validation scale for gauging community resilience emerged from [34].

The four perceptual aspects that can be used to assess community adaptive capacity and resilience include: the ability to recognize danger and change; the ability to reorganize, learn, and plan; the ability to cope with risk and change; and the degree of interest in change [34]. These aspects have been used in other environmental management studies including climate change and reef management [35,36,37]. However, the concept of adaptive capacity in IS management has limitedly been used in the field of invasions science. Much of this is the case in adaptive management, which is suggested as one of the viable options for controlling the risk invasive species pose to the environment [5,38]. This study used the four perceptual constructs [34] in exploring the locals’ adaptive behaviours into IAPS management which can be capitalized on when formulating IAPS management interventions. Even though adaptive capacity may be used in assessing vulnerability and actual adaptation, the adaptive capacity theory fails to explain how it is actually triggered and it is practiced across different scales and contexts [30,39,40]. In addition, it lacks interconnectedness to other theories that can connect adaptive capacity and adaptive outcomes [30,33] however, adaptive capacity has the potential to bring about social resilience when effectively integrated with the CC.

2.3. Social Resilience: The Role of Adaptation in IAPS Management

Social resilience is construed as s key idea in promotion of social ecological systems in environmental management [39,41,42,43,44]. Social resilience can be defined as a three-dimensional construct: 1. Coping capacities identify the social actors’ ability to cope with and overcome adversity of any kind; 2. Adaptive capacities—their ability to learn from past experiences and adjust to future challenges in their daily lives; 3. Transformative capacities—their ability to craft sets of institutions that foster individual welfare and long-term societal resilience in the face of future crises [45].

In the face of social or environmental vulnerability, adaptive capacity coupled with CC is the key element to bring about social resilience [31]. The adaptive capacity is a key asset in resilience-building through adaptive management, which the latter is called adaptable because it recognizes that human intervention will always modify managed resources, and this comes with surprises that are unavoidable resulting in the emergence of new uncertainty [44]. This is what necessities the understanding of government actions and more importantly human behaviours which is often critical for later in the formulation of policy and management response [42] to bring about community resilience. Evidence from studies reveals that the locals’ behaviours in management and adaptation of IAPS are mostly not supported by government actors [5]. Research studies indicate that locals’ characteristics such as their perceptions (that is dependent on locals’ awareness and experience) of invasive species are key in fostering a socially resilient community that can incorporate IAPS into a livelihood and national economy [4,19]. Several studies have shown that most local people were aware of IS in their areas of study [4,46]. The knowledge of invasive species helps them to use IAPS as medicines and timber with other uses such as building materials and fuelwood [4]. Such positive use of IAPS helps the community to understand these species better. Another study in Kenya has shown that the locals that were aware of the IAPS had a positive perception as they were able to put the IAPS into more productive positive use [47].

Furthermore, a perception assessment study conducted in an urban environment in the South African city of Cape Town revealed that socio-economic factors such as age, education, environmental knowledge, and ethnicity are key in shaping residents’ perception of IAPS [48]. Similarly, the results of another study showed that people who are knowledgeable of IAPS, educated, and older are more likely to be willing to change the current situation of invasive species [47]. On the other hand, another study indicates that older and more educated people held a negative perception of IAPS whilst those with environmental knowledge had a positive perception [49]. These contesting perceptions show how management interventions emanating from locals’ behaviours can be a challenge, however extensive education awareness programs with a clear communication strategy remain key in shaping locals’ perception to promote social resilience through management and adaptation of IAPS.

2.4. Management and Adaptation of IAPS

Broadly, management of IAPS should include interventions that help in controlling the introduction and spread and this should be coupled with robust technical guidance [50]. The three broad ways of controlling and removing IAPS are categorized as mechanical (e.g., felling, ring barking, mowing, hand-pulling etc.), biological (introduction of natural predators), and chemical (spraying of herbicides) [50]. In terms of time frame effectiveness of these methods, prevention or control is of short-term effect, while mechanical, follow up and rehabilitation are of medium-term impact with biological control having long term response and being more effective [51,52]. Another way of managing IAPS is quarantine which is the exclusion of new plant species from entering a country until there is knowledge of its species, pathways of dispersal and predators [53], however, much as this may prevent the spread of IAPS but IAPS still spread through illegal introductions and approved routes due to the uncertainty of predicting the movements of IS [53].

IAPS can also be controlled through detection and elimination [53]. This is done by conducting regular and thorough surveillance to detect new IAPS using risk maps based on climatic circumstances and the most likely pathways. However, according to general observations in the management of IAPS, this is not frequently done [53]. Effective implementation of such management strategies requires a collaborative approach [48]. A collaborative approach (technocrats and farmers) to IAPS management is greatly missing, especially in Malawi with other key government sectors (forestry, water, and agriculture) lacking proper guiding documents on IAPS management. This entails that controlling IAPS is in Malawi is an uphill task.

3. Materials and Methods

3.1. Study Area

This study was conducted in Mhuju and Ntchenachena communities along the NNP boundary in Rumphi district, northern Malawi (Figure 1). Mhuju and Ntchenachena have a population of 20,067 and 27,976, respectively [54]. The number of farming households in Mhuju for the 2020/2021 and 2021/2022 growing seasons were 9881 and 11,254 while Ntchenachena had 5159 and 6300 farming households, respectively [55]. The majority of farmers in the study areas are small-scale substance farmers with an average landholding size that ranges from 0.5 to 0.8 ha [55]. The staple crop grown in the study area is maize with tobacco and coffee grown for commercial purposes. Pineapples, bananas, beans, groundnuts, sugarcane, and cassava are minor crops grown in this area [55]. Livestock kept in this area include goats, chickens, pigs, and cattle [55]. The NNP and surrounding communities have several IAPS. This study focused on the major IAPS found in the NNP and the surrounding communities. According to [2,56], the major IAPS in the NNP include Pine-Pinus patula, Bracken fern-Pteridium acquillinium, Bluegum-Eucalyptus saligna, and Black wattle-Acacia mearnsii. In the study area there is a five-year (2018–2023) donor funded project being implemented in collaboration with the Malawi Government which seeks to introduce IAPS management practice [23].

3.2. Research Design

The attributes used in this study were derived from three key sources: the community resilience proposition [43], and insights which were acquired through key stakeholder interviews that appraised the existing situation regarding each capital using the Community Capital Framework (CCF). The key stakeholders who were members of the district environmental subcommittee (an agronomist, a forest officer, an environmental officer, a development planner, and a member of a non-governmental organization implementing an environmental project) used the CCF to reveal the state and use of each capital, which added to the understanding of the qualities and level progression. Finally, the IAPS management issues were developed alongside the indicators for management behaviours (

Table 1. The IAPS management and adaptation issues and indicators for management behaviours.

IAPS Management Issues	No.	Indicator of IAPS Management Behaviours (Abbreviation)	Literature
Locals’ knowledge of IAPS risks on rural livelihood (RISK)	A	Promoting community awareness of common IAPS and their impacts on livelihood (RISK1)	[4,19,51,57]
	B	Incorporating IAPS issues in the school curriculum (RISK2)	[4,51]
Locals’ ability to plan for IAPS management (PLAN)	C	Prioritizing IAPS for management (PLAN1)	[5,8,15]
	D	Formulating local IAPS management strategies (PLAN2)	[15]
Locals’ ability to cope with IAPS Impacts (COPE)	E	Using IAPS cuttings for medicine, timber, compositing and biomass (fuelwood, briquettes, charcoal) (COPE1)	[4,51]
	F	Venturing into economic activities other than farming (businesses, labour services) (COPE2)	[4,51]
Locals’ interest in adapting change to AIPS management (INTEREST)	G	Cooperating with local government to implement IAPS management projects (INTEREST1)	[5]
	H	Integrating IAPS management in extension services to reduce IAPS impact (INTEREST2)	[57]

).

A survey was conducted using a formal questionnaire and face-to-face interviews in a local language, Tumbuka. The questionnaire had three sections. The first section consisted of issues related to knowledge and management of IAPS (i.e., identification of IAPS from colour pictures, knowledge on: IAPS in the area, IAPS found in farms, benefits and problems associated with IAPS both in out of farms, membership of farmer club or VNRMC, and discussion of IAPS in the club, IAPS management methods used). The second section focused on the evaluation of importance and performance of eight IAPS adaptation indicators (Table 1) using a five-point Lickert scale (ranging from 1—“very unimportant/strongly dissatisfied” to 5 “very important/strongly satisfied”) [58,59]. The last section contained respondents’ socio-demographic data (i.e., age, gender, income, main source of income, occupation, location of stay and years of stay in the area). After the pre-test in April 2021 in Mhuju and Ntchenachena with 54 respondents, a team of trained data collectors conducted a full-time on-site survey in the two study sites between 8 July 2021 and 29 July 2021 using clustered sampling method. The population was clustered into ten Village Development Committees (VDCs) for each of the study locations. For Mhuju all 10 VDCs were selected, and these were Lubagha, Chilulu, Mhuju, Kauka, Chowe, Chivungulu, Kawembe, Chipopoma, Phwamphwa, and Nkhumano. As of Ntchenachena out of 36 VDCs, 10 VDCs were randomly selected and included Matchewe, Junju, Phoka, Gavala, Kajoni, Mahilu, Luwendela, Nkhomboli, Mweyeye, and Ntchenachena. Each VDC in both areas was assigned a sample of 26 respondents. The locals were chosen using simple random sampling to ensure that all participants had an equal and fair chance of being chosen. In total, 535 locals were interviewed.

Importance Performance Analysis

The importance-performance analysis (IPA) is a decision-making diagnostic tool that aids in the identification of areas for improvement and prioritization [60]. Developed by Martila and James in 1977, the IPA is used in analyzing the attributes’ importance and corresponding performance using a Likert scale [60,61]. The IPA analysis, therefore, helps in identifying areas or attributes that are rated high or low in terms of performance and importance for managers to act upon [61,62]. Traditional IPA results are presented in a grid format with four quadrants, which provides actionable clues such as (i) quadrant A, the attributes are rated with both high performance and importance (strength), so efforts should be maintained; (ii) quadrant B, the attributes are of high importance, but performance is low (threat), so more effort should be added to improve; (iii) In quadrant C, the attributes are of low importance and performance (weakness), and they do not necessitate further effort because they are considered low priority; and (iv) quadrant D, the concerns in this area are low priority but high performing (opportunity), and hence do not require further effort because they are already at risk of overinvestment [58,61,62]. The IPA approach has been widely employed in the services industries, such as tourism since its first application in the automotive industry in the 1970s [61,62]. The IPA, on the other hand, has been employed in studies on environmental management [57,61,62,63,64]. To evaluate the I-P locals’ perception of IAPS management and adaptation in areas near the NNP, this study used the IPA approach with a five-point Likert scale on IAPS adaptation and management behaviour indicators (Table 1 above).

The study has further integrated the traditional IPA with binary choice theory whereby the logistic regression method (LRM) was used to establish the respondents’ social-economic and environmental awareness characteristics and their I-P ranking of the IAPS management and adaptation indicators [4,47,48,49,52]. The locals’ selection of at least two choices or all three alternative solutions to the current situation was used as a dependent variable in LRM whereby 1 represents a stronger need for change and 0 otherwise. The independent variables were demographic attributes (i.e., age, income, education level and area of stay or site of the respondents), environmental awareness, and activism behaviours (i.e., understanding of problems that IAPS pose or concerns on impacts of IAPS, membership of FC or VNRMC, and discussion of IAPS in FC or VNRMC). The demographic and environmental awareness and activism behaviours were used as dummy variables while the mean importance and mean performance were treated as quantitative variables. Two models were built in this study, and both were based on the same dependent and independent variables. The study has managed to compare the probit and logit regression analysis through engagement with binary choice theory. The goodness of fit (GOF) of both models was determined using Akaike Information Criterion (AIC) and log-likelihood ratio (LLR) [57].

4. Results

4.1. Social Demographic Characteristics of the Respondents

This study involved 277 (51.8%) females and 258 (48.2%) males as shown in

Table 2. Definition of socio-economic variables of the respondents.

Variable	Level	All Respondents (n = 535)		Non-Farmers (n = 109)		Farmers (n = 426)
		Frequency	%	Frequency	%	Frequency	%
Location	Mhuju	268	50.1	45	41.3	223	52.3
	Ntchenachena	267	49.9	64	58.7	203	47.7
Years of stay in the location	<5	4	0.7	0	0	4	0.9
	5–10	9	1.7	5	4.6	4	0.9
	10–15	44	8.2	16	14.7	28	6.6
	15–20	91	17.1	31	28.4	60	14.1
	>20	387	72.3	57	52.3	330	77.5
Gender	Female	277	51.8	54	49.5	223	52.3
	Male	258	48.2	55	50.5	203	47.7
Age (years)	18–25	5	0.9	2	1.8	3	0.7
	26–35	74	13.8	18	16.5	56	13.1
	36–45	129	24.1	37	33.9	92	21.6
	46–55	149	27.9	37	33.9	112	26.3
	56–65	117	21.9	13	11.9	104	24.4
	66–75	49	9.2	1	1.0	48	11.3
	>76	12	2.2	1	1.0	11	2.6
Education	Illiterate	66	12.3	1	0.9	65	15.3
	Primary School	256	47.9	30	27.5	226	53.1
	Secondary School	188	35.1	60	55.1	128	30.0
	College cert. Diploma	25	4.7	18	16.5	7	1.6
Income (MWK 1/month)	<30,000	318	59.4	5	4.6	313	73.5
	30,001–50,000	99	18.5	20	18.3	79	18.5
	50,001–100,000	71	13.3	45	41.3	26	6.1
	100,001–150,000	38	7.1	32	29.4	6	1.4
	150,001–200,000	9	1.7	7	6.4	2	0.5
Identification of IAPS 2	Pinus patula	493	26.9	103	28.0	390	26.7
	Eucalyptus	515	28.1	108	29.3	407	27.8
	Acacia mearnsii	518	28.3	107	29.1	411	28.1
	Pteridium acquillinium	305	16.7	50	13.6	255	17.4

¹ NB: MWK = Malawi Kwacha; Exchange rate (July 2021): 1 USD = MWK 805.50. ² Multiple response questions.

below. The results show that there were more females than males in the category of farmers. However, in the group of non-farmers, there were more males (50.5%) than females (49.5%) that were involved in this study. The ages of the participants ranged from 18 years to over 76 years. The majority of respondents were between the ages of 46 and 55 (the average being 50.5). There were fewer respondents in the outermost age ranges of 18–25 years (0.9%) and over 76 years (2.2%) for all respondents and both non-farmers and farmers (18–25 years, 1.8% and 0.7%; over 76 years, 1% and 2.6%, respectively).

Most of the respondents had primary education (256 representing 47.9%). There were only 4.7% of respondents with a college diploma or certificate. A small percentage of respondents—12% of all respondents—were illiterate, with farmers having a higher percentage (15.5%) than non-farmers (0.9%). The majority of non-farmers (55.1%) had a secondary education. In this study, the majority of participants (50.5%) made less than MWK 30,000 (USD 4.27). Few (9%) respondents reported having a monthly income between MWK 150,000 and MWK 200,000 (USD 186.23 and 248.29). In contrast, more non-farmers (41.3%) had incomes between MWK 50,001 and MWK 100,000 (U$SD 62.07–124.15) than farmers (73.5%), who had a higher percentage of incomes below MWK 30,000 (USD 34.27).

Most respondents (97.2%) knew IAPS and they could identify the IAPS correctly from the colour pictures that were shown to them during the interviews whilst 2.8% did not know the IAPS.

According to the aggregated results of all respondents, the IAPS identified by the majority were Acacia mearnsii (28.3%), Eucalyptus (28.1%), Pinus patula (26.9%), and Brackern fern (16.7%). However, differences exist in the percentages of non-farmers and farmers identifying the IAPS from the pictures. More non-farmers were able to identify Eucalyptus (29.3%) followed by Acacia mearnsii (29.1%), Pinus patula (28.0%), and Pteridium acquillinium (16.7%). Farmers, on the other hand, identified the IAPS in the following order, from highest to lowest percentages: Acacia mearnsii (28.1%), Euculyptus (27.8%), Pinus Patula (26.7%), and Pteridium acquillinium (17.4%). Despite the differences, Acacia mearnsii and Euculyptus were easily identified IAPS, followed by Pinus patula and Pteridium acquillinium.

4.2. Matrix of I-P Level of IAPS Adaptation and Management by Residents

This study examined the IAPS adaptation and management perspectives from non-farmers and farmers using paired sample t-test, using this study generated evaluation framework for IAPS adaptation and management strategies and behaviours in IPA (Table 1). Using the IPA level matrix, this study has assessed the importance and performance respondents attach to issues of IAPS management. This study has categorized the respondents in terms of occupation and area of stay, namely non-farmers, farmers and Mhuju and Ntchenachena residents. In addition, this study assesses the I-P levels the groups attached to IAPS adaptation and management.

The results in

Table 3. Mean scores and paired-sample t-test among all respondents, non-farmers, and farmers for the IAPS adaptation and management indicators on importance and performance level.

No.	Indicator	Importance (Mean)	Performance (Mean)	Difference	t-Value	p-Value
All respondents (n = 535)
A	Risk1	4.88(1)	1.45(8)	3.43	98.399	0.000
B	Risk2	4.84(2)	1.71(3)	3.13	75.545	0.000
C	Plan1	4.70(7)	1.51(6)	3.19	77.634	0.000
D	Plan2	4.80(3)	1.55(5)	3.25	87.258	0.000
E	Cope1	4.75(5)	2.26(1)	2.49	43.739	0.000
F	Cope2	4.75(5)	2.25(2)	2.50	43.934	0.000
G	Interest1	4.77(4)	1.49(7)	3.28	91.403	0.000
H	Interest2	4.72(6)	1.57(4)	3.15	74.850	0.000
	Overall mean	4.78	1.72
Non-farmers (n = 109)
A	Risk1	4.92(1)	1.35(7)	3.57	54.362	0.000
B	Risk2	4.89(2)	1.89(3)	3.00	31.615	0.000
C	Plan1	4.83(5)	1.89(3)	2.94	42.571	0.000
D	Plan2	4.83(5)	1.52(5)	3.31	47.432	0.000
E	Cope1	4.78(6)	2.67(1)	2.11	15.140	0.000
F	Cope2	4.84(4)	2.12(2)	2.72	14.687	0.000
G	Interest1	4.87(3)	1.47(6)	3.40	56.822	0.000
H	Interest2	4.84(4)	1.63(4)	3.21	45.014	0.000
	Overall mean	4.85	1.82
Farmers (n = 426)
A	Risk1	4.88(1)	1.48(8)	3.40	84.270	0.000
B	Risk2	4.83(2)	1.67(3)	3.16	68.853	0.000
C	Plan1	4.66(7)	1.51(6)	3.15	66.485	0.000
D	Plan2	4.79(3)	1.55(5)	3.24	74.807	0.000
E	Cope1	4.74(4)	2.15(1)	2.59	42.295	0.000
F	Cope2	4.73(5)	2.12(2)	2.61	43.042	0.000
G	Interest1	4.74(4)	1.49(7)	3.25	76.836	0.000
H	Interest2	4.69(6)	1.56(4)	3.13	63.189	0.000
	Overall mean	4.76	1.69

below are summarized for all respondents. Overall, all respondents consider the issue of community awareness on the IAPS impact on livelihood (Mean = 4.78) as a very important issue followed by the inclusion of IAPS in schools $\mathrm{M}\mathrm{e}\mathrm{a}\mathrm{n}=4.88$). The issue considered as the least important by all respondents is the prioritization of IAPS for management ($\mathrm{M}\mathrm{e}\mathrm{a}\mathrm{n}=4.70$). On the other hand, the respondents considered the issues of community awareness on the IAPS impact on livelihood as the worst-performing indicator ($\mathrm{M}\mathrm{e}\mathrm{a}\mathrm{n}=1.45$) while consumptive use of IAPS cuttings for fuel, and biomass ($\mathrm{M}\mathrm{e}\mathrm{a}\mathrm{n}=2.26$) was the best performing indicator. The levels of importance are mostly significantly larger than that of performance at a 1% significance level, with a difference of 2.49 (Table 3).

4.2.1. Matrix of I-P Level of IAPS Adaptation and Management by Non-Farmers and Farmers

Across all the indicators as shown in Table 3, the non-farmers consider the following IAPS adaptation and management indicators as important: community awareness on IAPS impact on the livelihood $(\mathrm{M}\mathrm{e}\mathrm{a}\mathrm{n}=4.92$), incorporation of IAPS in schools (with mean of 4.89), cooperating with local government to implement projects (Mean = 4.87), engagement into other economic activities (Mean = 4.84), and integration of IAPS management in extension services (Mean = 4.84). With regards to performance, the non-farmers perceived the following issues are highly performing: consumptive use of IAPS cuttings (medicine, timber, compositing and biomass, fuelwood briquettes, charcoal) (Mean = 2.67), venturing into other economic activities (with mean of 2.21), incorporation of IAPS in school (Mean = 1.89), prioritize IAPS for management (Mean = 1.89), and integration of IAPS management in the extension service (Mean = 1.63). On the other hand, the least important indicators were consumptive use of IAPS, prioritizing IAPS for management, and developing local strategies for IAPS management (Mean = 4.78 and Mean = 4.83 for the last two, respectively). The least performing indicators according to non-farmers were community education and awareness of IAPS (Mean = 1.37), cooperation with local government to implement projects (Mean = 1.47), development of community strategies to manage IAPS (Mean = 1.52), and integration of IAPS in extension services (Mean = 1.63).

Being exposed to the same indicators as shown in Table 3 below, farmers were more concerned with issues of community education and awareness on the impact of IAPS on livelihood (mean of 4.88), incorporation of IAPS issues in school (Mean = 4.83), formulation of local strategies for IAPS management and promotion of IAPS use for firewood (Mean = 4.79) as they rated these issues as highly important. On the other hand, the farmers ranked the following indicators as the worst to worse-performing indicators: community education and awareness on the impact of IAPS on livelihood (Mean = 1.48), cooperation with local government to implement projects (Mean = 1.49), prioritizing IAPS for management (Mean = 1.51), and development of community strategies to manage IAPS (Mean = 1.55).

4.2.2. The IAPS Adaptation and Management Behaviours of Non-Farmers and Farmers

All eight IAPS adaptation and management indicators of the I-P level were analyzed and compared between non-farmers and farmers as shown in Figure 2 below. The results show that the issue of IAPS inclusion in the school curriculum from the non-farmers was in quadrant A. In addition, the issue of community awareness and education on the impact of IAPS on livelihood, incorporation of IAPS in school, formulation of community IAPS management strategies, and cooperating with the local council to implement projects from both non-farmers and farmers were in the first quadrant B. Furthermore, the issues of integrating IAPS issues into extension services (for both non-farmers and farmers), cooperating with the local government to implement projects, formulation of local IAPS management strategies and prioritization of IAPS for management was in quadrant C. Lastly, the use of IAPS as fuelwood or biomass, venturing into other economic activities other than farming and prioritization of IAPS for management were in quadrant D.

4.3. The IAPS Adaptation and Management Behaviour by Area of Residence

4.3.1. Matrix of I-P Level of IAPS Adaptation and Management Behaviour by Mhuju and Ntchenachena Residents

The I-P results (

Table 4. Differences in overall perceptions of Mhuju and Ntchenachena residents on IAPS management issues.

No.	Indicator	Importance (Mean)	Performance (Mean)	Difference	t-Value	p-Value
All respondents (n = 535)
A	Risk1	4.88(1)	1.45(8)	3.43	98.399	0.000
B	Risk2	4.84(2)	1.71(3)	3.13	75.545	0.000
C	Plan1	4.70(7)	1.51(6)	3.19	77.634	0.000
D	Plan2	4.80(3)	1.55(5)	3.25	87.258	0.000
E	Cope1	4.75(5)	2.26(1)	2.49	43.739	0.000
F	Cope2	4.75(5)	2.25(2)	2.50	43.934	0.000
G	Interest1	4.77(4)	1.49(7)	3.28	91.403	0.000
H	Interest2	4.72(6)	1.57(4)	3.15	74.850	0.000
	Overall mean	4.78	1.72
Mhuju residents (n = 272)
A	Risk1	4.81(1)	1.62(7)	3.19	57.372	0.000
B	Risk2	4.79(2)	1.87(3)	2.92	48.943	0.000
C	Plan1	4.55(7)	1.66(5)	2.89	43.811	0.000
D	Plan2	4.71(3)	1.66(5)	3.05	52.867	0.000
E	Cope1	4.69(4)	2.52(1)	2.17	27.632	0.000
F	Cope2	4.68(5)	2.51(2)	2.17	28.781	0.000
G	Interest1	4.68(5)	1.64(6)	3.04	54.559	0.000
H	Interest2	4.60(6)	1.69(4)	2.91	43.952	0.000
	Overall mean	4.69	1.90
Ntchenachena residents (n = 263)
A	Risk1	4.96(1)	1.29(8)	3.67	103.163	0.000
B	Risk2	4.90(2)	1.56(3)	3.34	61.569	0.000
C	Plan1	4.85(5)	1.35(6)	3.50	86.958	0.000
D	Plan2	4.88(3)	1.43(5)	3.45	79.745	0.000
E	Cope1	4.81(8)	1.99(1)	2.82	36.372	0.000
F	Cope2	4.82(7)	1.98(2)	2.84	35.258	0.000
G	Interest1	4.86(4)	1.33(7)	3.53	89.440	0.000
H	Interest2	4.84(6)	1.44(4)	3.40	72.563	0.000
	Overall mean	4.87	1.55

) in this category which was based on the area of stay (location) show that Mhuju residents considered the following issues as the most important; community education and awareness on the impact of IAPS on rural livelihood (with mean of 4.81), the inclusion of IAPS issues in the school curriculum (Mean = 4.79), formulation of local management strategies for IAPS (Mean = 4.71) and use of IAPS for timber, and biomass composite (Mean = 4.69). The very same Mhuju residents considered the issues of community education and awareness on the impact of IAPS on rural livelihood (Mean = 1.62), cooperation with local government to implement IAPS projects (Mean = 1.66), prioritization of IAPS for management (Mean = 1.66) as the poorly performing indicators while the use of IAPS for timber, biomass and compositing (Mean = 2.52) and local engagement into other non-farming business adventures (Mean = 2.51) were the best-performing indicators.

Like Mhuju residents, Ntchenachena residents view the issues of community education and awareness on the impact of IAPS on rural livelihood (Mean = 4.96), the inclusion of IAPS issues in the school curriculum (Mean = 4.90), and the formulation of local management strategies for IAPS (Mean = 4.88) as the most important amongst the eight indicators. Contrary to Mhuju residents, Ntchenachena residents consider cooperation with the local government to implement IAPS projects (Mean = 1.33) as an important indicator which residents of Mhuju did not rate as highly important. Results of Ntchenachena residents on assessment of the performance of the IAPS adaptation and management indicators show that consumptive use of IAPS as fuelwood and biomass (Mean = 1.99) and venturing into other economic activities other than farming (Mean = 1.98) are the best-performing indicators whilst community education and awareness on IAPS impact on livelihood (Mean = 1.29) and cooperation with the local government to implement IAPS projects (Mean = 1.33) were the worst-performing indicators as shown in Table 4 below.

4.3.2. The IAPS Adaptation and Management Behaviour of Mhuju and Ntchenachena Residents

The comparison of the eight IAPS adaptation and management indicators amongst the Mhuju and Ntchenachena residents shows that no indicator was found in quadrant A, however quadrant B had issues of community education and awareness on IAPS impacts on community livelihood, the inclusion of IAPS issues into the school curriculum, and the formulation of local IAPS management strategies. Issues that were in quadrant C included the prioritization of IAPS for management, cooperating with the local government to implement IAPS projects, and incorporation of IAPS issues in the extension services. Lastly, in quadrant D there are indicators on consumptive use of IAPS, and engagement of locals into other economic activities other than farming as shown in Figure 3 below.

4.4. Locals’ Participating Behavior towards Change in IAPS Management

The locals’ selection of alternative solutions (with the selection of two alternatives as a minimum) to change the current situation or their desire to see the current situation change in terms of management and adaptation of IAPS was used as a dependent variable, that interacted with demographic variables (i.e., age, income, education level and area of stay or site of the respondents), environmental knowledge and activism behaviours (i.e., understanding of problems that IAPS pose or concerns on impacts of IAPS, membership of FC or VNRMC, and discussion of IAPS in FC or VNRMC) and overall mean importance and mean performance of IAPS adaptation and management behaviours used in this study were used as the independent variables as well as quantitative variables. Likewise, the second model had the overall mean performance of the IAPS adaptation and management behaviours indicators with the aforementioned demographic variables, and the environmental knowledge and activism behaviours intergraded into the logit and probit regression models using the above dependent and independent variables, respectively (

Table 5. Estimation results of locals’ perception for acting towards IAPS management and adaptation behaviour.

Variable Names	Logit Model				Probit Model
	Importance on IAPS Management and Adaptation (Model I)		Performance on IAPS Management and Adaptation (Model II)		Importance on IAPS Management and Adaptation (Model I)		Performance on IAPS Management and Adaptation (Model II)
	Coeff.	Std Error	Coeff.	Std Error	Coeff.	Std Error	Coeff.	Std Error
Constant	−7.436 ***	1.969	−0.579	0.922	−3.825 ***	0.984	−0.184	0.497
Age (1 aged 50.5 years above, otherwise 0)	2.242 *	1.189	1.724 **	0.809	1.177 *	0.614	0.833 **	0.376
Income (1 above MWK 30,000, otherwise 0)	1.887	1.207	2.103 **	1.068	1.048 *	0.622	0.946 **	0.452
Education (1 literate, otherwise 0)	1.254	0.943	1.480 *	0.800	0.519	0.443	0.616 *	0.358
Site (1 Ntchenachena, otherwise 0)	6.873 ***	1.739	3.325 ***	1.083	3.380 ***	0.781	1.481 ***	0.430
Problem/Concern of IAPS (1 mentioned 2–7 problems of IAPS, otherwise 0)	1.821 *	1.013	1.584 **	0.702	0.928 *	0.481	0.828 ***	0.338
FC 1/VNRMC 2 member (1 member, otherwise 0)	−2.051 *	10.621	−0. 854	0.800	−1.003 *	0.553	−0.463	0.407
Discuss IAPS in FC/VNRMCS (1 discussed, otherwise 0)	2.459 *	1.062	1.523	0.927	1.091 *	0.605	0.773 *	0.453
Mean Importance	2.142 ***	0.470	-	-	1.091 *	0.233	-	-
Mean Performance	-	-	0.948 *	0.535	-	-	0.517 *	0.270
AIC 3	68.3		108.7		68.2		109.2
AIC/N	0.128		0.203		0.127		0.204
LLR 4	86.46		46.13		86.65		45.58
Chi-Square Value	χ2 (8, 0.01) = 20.09

Note: ***, **, * Significance at 1%, 5%, 10% level. ^1. Famer Club, ² Village Natural Resources Management Committee, ³ Akaike Information Criterion, ⁴ Log Likelihood Ratio.

).

The variable positively correlated with the locals’ IAPS adaptation and management behaviour as indicated in Model I. This was consistent with the logit and probit regression models. The results show that respondents that would like to see the change in the current IAPS management and adaptation as they had selected the alternative solution as opposed to the current situation were the ones that were over 50.5 years and the majority were from Ntchenachena. In terms of environmental awareness and activism, the results in Model I show that the ones that were able to mention more than one problem of IAPS or were more concerned with the impacts of IAPS, were non-members of FC or VNRMCs and from the FC or VNRMCs members, only those who were discussing IAPS issues in their groups were the ones that were more likely to put more effort towards the change of the current situation. In Model II, the respondents that were looking for an alternative solution to change the current IAPS management and adaptation practices were over 50.5 years old, earning over MWK 30,000 per month, literate, from Ntchenachena, and were more concerned with the problems (mentioned more than two IAPS problems) of IAPS. The results are contained in Table 5 above are in harmony with the binary choice model. The GOF for the model also meets the criterion of the LLR and AIC [37], and this demonstrates that the locals’ adaptation and management behaviour model for IAPS has a concrete result with model specifications under the binary choice model and the routine of probit model with sufficient sample size [56].

5. Discussion

5.1. Locals’ Awareness and Knowledge of IAPS and Management Behaviours

This study has established that most of the people involved in this study from Mhuju and Ntchenachena are aware of IAP. Another study in the communities surrounding the NNP has shown that 95% of the respondents know of the availability of IAPS [2]. The findings of a study in the Mulanje district in Malawi found that 96.7% of the study respondents were aware of IS in their area [4]. This demonstrates that the locals possess knowledge of their environments and can detect IAPS in their communities. The locals equally display knowledge of both the benefits (provision of fuelwood, timber, poles for house construction, composite manure, medicine, and fodder for animals) and problems (reduced water supply, reduced yield, and reduced farm size) [4] of IAPS which may shape the perception of IAPS in general [19]. This knowledge belongs to human capital hence once triggered can be put into action towards management and adaptation of IAPS. Much as the possession of knowledge is a plus, however, the level of knowledge of the respondents in management is considerably low as 96.5% of the respondents use physical destruction methods which, according to IAPS management efficiency, fall into the category of mechanical and chemical control which are considered low impact and short term [48]. This, therefore, demonstrates the strong need to improve locals’ knowledge of IAPS on management strategies that are geared towards biological management if the interventions are to be of long-term impact and sustainable.

5.2. Locals’ Evaluation of IAPS and Strategic IAPS Management and Adaptation Decisions from IPA Approach

This study has used the IPA approach to create an evaluation framework for IAPS management and adaptation, which included indicators that respondents were asked to score. The attributes making up these approaches were categorized into four groups: locals’ awareness of IAPS impact on rural livelihoods, locals’ ability to plan for IAPS management, locals’ ability to cope with IAPS impacts, and locals’ interest in adaptation to change. The attributes were further subdivided into eight (8) corresponding indicators namely, promoting of community awareness on IAPS impacts on livelihood [5,56,60,61]; incorporating IAPS issues in the school curriculum [4,48]; prioritizing IAPS for management [15]; formulating local IAPS management strategies [55,60]; venturing into other economic activities than farming (businesses, labour services) [4,19]; cooperating with the local government to implement IAPS management projects [28]; and integrating IAPS management in extension services to reduce IAPS impact [54].

The I-P matrix of management and adaptation indicators was used to compare the two pairs of respondents who were categorized as farmers and non-farmers, and the second group were Mhuju and Ntchenachena residents, revealing the differences in perception of each pair on the eight indicators under the IPA framework [4,5,8,15,48,49,54] with a sound theoretical foundation.

The IPA plot with the IAPS management and adaptation matrix gave robust and thorough guidance about the policy suggestions and priority on IAPS management and adaptation alongside giving out the locals’ viewpoints (preference through I-P ranking of IAPS management and adaptation strategies) from the various groups compared (thus farmers and non-farmers; Mhuju and Ntchenachena residents). The IPA results show the locals in both pairs regard information and knowledge gained through community awareness and formal education as a key aspect to enabling them to manage IAPS. A study on the impact of IAPS in Malawi has recommended the inclusion of IS issues in the education curriculum [61] to improve the locals’ adaptive capacity henceforth building the necessary human capital in the management of IAPS. The study results have shown a slight difference between the two pairs with regards to their I-P rating of local IAPS plan formulation with farmers considering this as a high priority issue while non-farmers consider it an issue of low priority. On the other hand, when comparing the results, it shows that the locals would like to act on IAPS management, thus residents of Mhuju and Ntchenachena both consider local planning for IAPS management important and believe that things are not being done as they ought to have been done with the plans in place. Furthermore, both the residents of Mhuju and Ntchenachena (whilst there is a difference of opinion on the part of farmers and non-farmers) would like to practically do the work required in IAPS management as they consider the introduction of IAPS management projects from local councils (thus recognition of both political, human, and economic capital) one of the viable ways into the strides of managing and adapting to IAPS. The IAPS management project in the study area entails the availability of expert knowledge and economic resources as the political capital is key in influencing the allocation of resources for community developments [31]. The non-market commodities (i.e., things that are not directly traded in markets) require government financing for conservation and management (in this case, IAPS) which requires the prior input of experts and the public’s views in order to allocate funds most appropriately [40]. These are the much-needed resources that are to be used alongside other capitals for a more socially resilient community.

In addition, the inclusion of the IAPS topics in the school curriculum is considered an important issue that needs attention from residents of both Mhuju and Ntchenachena, while the group farmers and non-farmers view this differently whereby farmers consider it a priority and non-farmers consider it as an issue that is being solved and does not require more effort. These complex conflicting perceptions of IAPS issues amongst stakeholders makes the efforts to manage them complicated [46]. However, it is evident in other studies that education plays a role in IS management decisions by the locals [2,4,44].

The study has also established the factors that affect locals’ management and adaptation on IAPS alongside the demographics, environmental knowledge, and activism (thus age, gender, education, concern with IAPS, membership of VNRMC or FC, and discussion of IAPS in the VNRMC and FC). This study used the probit and logit model under the GOF of model specification [55] and has shown that age, income, and level of education are demographic characteristics that influence locals’ willingness to change the current situation. This is consistent with findings that have shown that demographic characteristics such as age and education are critical in influencing the perception and action of IS management [18,44]. This study’s findings are consistent with another study that showed that respondents of over 35 years old were more willing to change the current situation of IAPS because the majority were older and could not find work elsewhere as such farming was the only source of income for them. These people are cautious about anything that may affect their only source of income, unlike the youth who could get jobs and supplement their income with farming.

Furthermore, from the findings of this research, the following IAPS management and policy implications have come to surface for relevant authorities to act upon; firstly, the central government through the Malawi Environmental Protection Authority should ensure that all environmental-related sectors affected by IS including IAPS should have management and adaptation strategies in their sectoral policies. Furthermore, the sectoral policy direction and interventions should trickle down into the local councils’ action plans through local IS management strategies. The extension services from agriculture, water, fisheries, and forestry should be well-coordinated at the local council level for effectiveness in creating a local system for IAPS management. Second, to effectively deliver IAPS management strategies through extension services, the use of already existing community environmental-related platforms such as the VNRMC, FC, would be ideal, as this study’s findings revealed that members of these clubs who discussed IAPS issues were more likely to want to change the status quo. Thirdly, the education authorities should consider incorporating issues of IAPS in schools as a long-term strategy of improving environmental knowledge on IAPS since there is strong evidence from this research and other studies [4,44,62] that educated people are more willing to support efforts in IAPS management. Similarly, environmental managers should endeavor to improve community IAPS management education programs, as the results of this study show that present management strategies are ineffective. It is also critical to put in place deliberate efforts that incorporates the youths (10–35 years) in IAPS management as this study results and another on public preference for controlling invasive plants in state parks [63] show that people older than 35 years have a higher preference for IAPS management. As of Malawi, the youths constitute over 50% of the population which is also the same in Rumphi [51] and leaving out this large section in IAPS management and adaptation means missing out on huge human capital that would not only provide labour but also innovations.

6. Conclusions

This study aimed at examining the locals’ adaptation behaviour into management of IAPS. Using the IPA method, the study has established the behaviours (using demographic data and environmental awareness and knowledge) that influence preference for management and adaptation of IAPS. Overall, the locals consider the following as important but least performing attributes: (1) community education and awareness on the impact of IAPS on livelihood, (2) incorporating IAPS issues in school, (3) formulation of local strategies for management of IAPS, (4) venturing into other economic activities other than farming, (5) cooperating with the local government to implement IAPS projects, and (6) incorporate IAPS in extension services. The observable behaviours from the statistical analysis in this study behind the prioritization of the attributes above include age, education level, concern with IAPS impacts, occupation, membership of VNRMCs or FC, and location of stay (thus either Mhuju or Ntchenachena). The results show that the literate locals, aged over 50.5 years, those with higher income, members of VNRMC and FCs that were discussing IAPS, those that were able to mention more IAPS problems (more concerned with IAPS) preferred to take action to change the current situation of IAPS in the Mhuju and Ntchenachena areas. On a comparative basis, the non-farmers supported the increase of knowledge to the locals while farmers were in support of incorporation of IAPS issues in extension services. All these behaviours are strongly linked to the CC including financial, social, cultural, and human capital. This, therefore, entails that the CC is key in building a socially resilient community to IAPS with the further potential of transformation since the main evidence from this study shows that IAPS have both negative and positive impacts.

Finally, because pine, blue gum, and acacia are IAPS, local species that are equally beneficial (have multiple uses) must be found and promoted to replace these IAPS. East African Mahogany trees—Khaya anthotheca, also known as the Mibawa trees in Malawi are suitable for both wet and dry areas, can grow well alongside river streams without affecting stream flow, and provide good hard wood (for furniture, flooring, paneling, boat building, musical instruments like guitars, and so on) could be a good replacement for these IAPS in the NNP and its surrounding communities.