A potential cause for extensive dieback of Acacia mearnsii plantation in highland districts of Awi zone, northwestern Ethiopia

Abstract

Although Acacia mearnsii De Wild has rapidly expanded for economic and ecological purposes in the highland districts of the Awi zone, northwestern Ethiopia, recent plantations have suffered from severe defoliation, dieback, and stunted growth. We conducted this study in four districts that hold potential for A. mearnsii plantations. The study examined the identification of the causal agent, its occurrence, and local community perceptions of the plantation's significant dieback. Most respondents (75.8 %) indicated that the substantial dieback began in the rainy season of 2020 and spread rapidly. They also noted that close spacing of plantings and limited silvicultural measures exacerbated the damage. We discovered in this study that the wattle rust disease caused by the Uromycladium acacia fungus was the root cause of significant dieback for A. mearnsii plantations. The incidence and severity of this wattle rust varied significantly (p = 0.001) between districts, seasons, and plantation age groups. In Fegita-Lekuma district, the maximum disease severity was over 72 % in plantations up to two years after planting during the rainy season. The progression of the wattle rust disease caused by U. acacia has led to the loss of A. mearnsii plantations in the Awi zone, resulting in a severe economic and environmental crisis. Consequently, we should apply fungicides to seedlings at nursery sites in the short term. Eventually, however, the focus should shift towards prioritizing disease-resistant species and implementing proper forest management practices. This should be achieved through scientific initiatives that engage key stakeholders in areas where this tree species could potentially grow.

Highlights

• •Socioeconomic, biophysical, and laboratory data were obtained from planation and analysis with ANOVA and X² test.
• •Substantial dieback of Acacia mearnsii plantation spread rapidly, and plantings with closer spacing and low silvicultural measures aggravated the damage.
• •Wattle rust disease caused by Uromycladium acacia fungus.
• •The maximum disease severity was high at seedlings to two years of plantation.
• •Chemical, biological, and silvicultural management should be required for prevention and control the disease.

1. Introduction

Acacia mearnsii De W, a fast-growing tree native to Australia, can reach a height of 12 m. The leaves are pinnate and the flowers are compound golden yellow heads that form thin pods that break on one side when ripe [1]. The tree is extensively distributed around the world and grows at an elevation of 1600–3500 m above sea level. In Ethiopia, farmers cultivate it in humid, high-altitude agroclimatic zones [1]. Farmers in the highland areas of Ethiopia's Awi zone have widely planted A. mearnsii on degraded mountain slopes and farmlands because of its rapid growth and short rotation time. In four highland districts of the Awi zone (Fegita-Lekuma, Ankesha-Guagusa, Banja, and Guagusa-Shikudad), farmers are currently converting the cropping system to Taungya agroforestry practice [2]. The study [3] found that the forest area in these Awi highland districts has increased by 1.2 % per year since the 2000s, while the cropland area has decreased by 1 % per year. Nonetheless, researchers detected signs of a severe shoot and leaf rust disease on the black wattle [4]. Hence, it is necessary to understand the local community's perception, evaluate the incidence and severity, and confirm the actual cause.

Furthermore, the tree provides a variety of functions, including providing poles and posts, feeding bees, giving shade, improving aesthetics, fixing nitrogen, saving soil, functioning as a windbreak, or living fence, and tanning [[5], [6], [7]]. The Acacia mearnsii plantations, which are expanding quickly, contribute significantly to the income from charcoal production in the Awi highlands [8].

Compared to species-rich plantations and natural forests, many species-poor plantations are more susceptible to diseases and pests [[9], [10], [11]]. Pests and pathogens, introduced into new environments and encountering new hosts, are increasingly threatening Acacia species planted as non-native species in different parts of the world in the tropics [12,13].

According to numerous reports from field workers and agricultural officials, A. mearnsii plantations in many parts of the Awi zone are showing signs of extensive dieback [4]. Many investigations [[13], [14], [15], [16]], as well as the initial report in Ethiopia [4] have conclude that wattle rust is the cause of this widespread dieback. If we do not solve this issue, it may become difficult to cultivate A. mearnsii in the highlands of the Awi Zone, which could jeopardize the livelihoods of farmers who rely on charcoal and firewood production, as well as others involved in the charcoal value chain.

This tree species is notably vulnerable to diverse types of black rust fungi, which can inflict substantial harm on the tree, impeding its growth and compromising its overall vitality. In Australia and South Africa, researchers and forest managers are investigating the relationship between trees and fungal diseases with the aim of creating efficient strategies for disease prevention and control. They are studying the susceptibility of A. mearnsii to rust fungus in order to safeguard this crucial tree species and maintain its ecological significance in its native habitats [[13], [14], [15], [16], [17]].

This species holds substantial economic importance for local communities. It serves as a crucial income source for farmers, enabling them to maintain their livelihoods and care for their families. The species also offers economic advantages to brokers and traders by providing opportunities for its distribution and sale. Small businesses also derive value from this species through processing or usage, thereby enhancing the local economy. Under a 5-year sharecropping agreement, leaseholders typically receive an initial rent of approximately 7338 ETB per hectare from the plantation [6]. Nonetheless, widespread dieback has the potential to eliminate all aforementioned stakeholders' reliable income sources, resulting in youth unemployment and an indirect influence on the national GDP [18].

Therefore, there is an immediate need to scientifically investigate the problem to determine the cause and recommend actions. The research questions are what factors contribute to the widespread dieback, as determined by field observations, laboratory analyses, and the perceptions of the local community; and does the extent and severity of dieback vary according to district, season, and age of the plantation. To address these research questions, the primary goals of this study were to: a) Explore the local community's views on the extensive dieback of A. mearnsii plantations; b) Identify the root cause of the extensive dieback in the youngest A. mearnsii plantations; c) Assess the severity of the identified pathogen responsible for the extensive dieback of A. mearnsii plantations. This research will play a key role in management measures to protect the A. mearnsii plantation to address the massive damage to the plantation and livelihood. The research is limited to four prospective highland districts in the Awi zone, which are known for their substantial A. mearnsii plantation. The study particularly focuses on the local communities' understanding of the widespread dieback, its causes, and the severity and frequency of these causes.

2. Material and methods

2.1. Study area description

The research took place in four highland districts of the Awi zone, which have seen a significant expansion of A. mearnsii plantations over the last 20 years (Fig. 1).

Fig. 1.

Map of the study areas.

The Awi zone is home to 1,159,386 people. Among them, 13 % reside in urban areas, while the majority live in rural regions, sustaining themselves through mixed farming [19]. The highlands of the research area are currently witnessing the practice of Taungya agroforestry, which is based on A. mearnsii. Fegita-Lekuma leads in terms of plantation numbers, contributing 42.9 %, followed by Banja with 39.13 % and Guagusa-Shikudad with 25.05 %. The predominant land use in the study area is plantations, followed by agriculture. In Fegita-Lekuma and Banja, forest husbandry is emerging as a significant income source (Table 1).

Table 1.

Land use systems of the study districts (Awi zone Agricultural office, 2021).

S. No	Districts	Total area (ha)	Cropland (%)	Forest (%)		Grazing (%)
				Natural forest	Plantation
1	Fegita-Lekuma	67, 750	52.3	3.35	42.69	21.3
2	Banja	47, 915.8	52	5.59	39.13	–
3	Ankesha-Guagusa	47, 915.8	65	8.27	16.78	17
4	Guagusa-Shikudad	29, 604	–	8.16	25.05	–

Every district under investigation belongs to the highland and moderate-altitude agroclimatic zones [1]. These areas have a consistent rainfall pattern and intensity, suitable for forestry land use plans (Table 2).

Table 2.

Agroclimatology of the study district [20].

S. No	Districts	Rainfall (mm)	Temperature (0C)	Altitude (m.a.sl.)
1	Fegita-Lekuma	1700	22–26	1888–2915
2	Banja	2115.3	9.4–26	1870–2570
3	Ankesha-Guagusa	2200–2400	15–26	1900–3300
4	Guagusa-Shikudad	1140–3572	10–25	2451–2537

2.2. Sampling and data collection

We chose four highland districts in the Awi zone, where A. mearnsii is commonly grown. In each district, we selected three kebeles (the last and smallest administrative level, also known as rural farmers’ associations) based on the extent of A. mearnsii plantations in each kebele. We then randomly selected three plantation sites of different ages. From the 12 kebeles, we randomly selected 5 % of households, which included both those cultivating A. mearnsii and those not cultivating it (Supplementary Table 1) [21]. As a result, we chose and conducted interviews with 150 individuals from each kebele. We gathered primary and secondary data through field observations, surveys based on questionnaires, and documented reports from agricultural offices at the regional, zonal, district, and kebele levels. We employed these methods to gather data on plantation age, local community perceptions, damage extent, occurrence time, and disease severity. We evaluated the questionnaire before performing the actual survey. We then validated it through a variety of approaches, including having experts examine the questionnaire, evaluating it with a small sample group, running correlational analysis, holding focus group discussions, interviewing key informants, and conducting direct on-site inspections.

2.3. Disease assessment method

We selected 128 random (10 m × 10 m) plots from A. mearnsii plantations during both wet and dry seasons. We recorded relevant symptoms of disease and their distribution across each plantation. Our assessment includes counting the number of damaged trees on a numerical scale (0–3), as outlined in Refs. [22,23]. Table 3 provides a detailed explanation of the numerical scale specifics and the methods used for field scoring. We gathered samples from diseased trees that were exhibiting symptoms and brought them to a laboratory for further testing. In the laboratory, we hoped to identify the pathogen responsible for the infection by analyzing these samples. We took great care when collecting plant infections such as sporophores, infected stems, and leaves. This meticulous compilation guaranteed the quality and dependability of our samples. Details of the diseases and infected hosts were recorded, and all samples were properly packed in plastic bags and taken to the plant pathology laboratory of Injibara University for culture and identification.

Table 3.

Disease scoring scale for A. mearnsii rust severity and its description from Refs. [29,30].

Scoring scale	Severity in present	Description
0	0	Immune
1	1–25	Brown rust pustules on a young branch
2	26–65	Brown rust spores and pustules cover infected branches and lead to malformation
3	>65	Defoliation of leaves and brown rust spores and pustules covering the pinnules cause dry

2.4. Pathogen identification

2.4.1. Specimen collection

We took infected plant samples from the leaves and stems of the trees at one, two, and three years of plantation. Using sterilized scissors, we collected a 9-mm square sample of plant tissue (stem and leaf) [24]. We surface sterilized a piece (5 × 5 mm) of sporophore context with 70 % ethanol for 1 min before rinsing it in distilled water (Fig. 2). We followed the procedures of [25,26], for the sampling and specimen collection.

Fig. 2.

Specimen collection and laboratory identification.

Preparation of the artificial culture medium and identification of the pathogen.

We placed infected tree leaf and stem samples on petri plates containing Sabouraud dextrose agar (manufactured by Agarindo Biological Company, Jakarta, Indonesia) and 0.5 % streptopenicillin (manufactured by Biological Industries, London, UK). We kept the inoculated Petri plates in an incubation room with a temperature of 25.2⁰C and humidity higher than 90 %. We provided darkness for 12 h and light for 12 h for proper growth and sporulation of fungal colonies. After seven days of inoculation, we purified fungal isolates from Petri plates by subculturing to obtain pure cultures. We made sections of the sporophores and recorded details of the context, hymenium, texture, color, and hyphae, along with slides for taxonomic identification. The morphology of the culture was evaluated using a basic and binocular compound microscope. The identification process was completed with laboratory data. This data includes information about the fungal colony, such as its growth rate, texture, and odor. These findings were then compared to previously reported data and photos of the same species from Australia, South Africa, and Ethiopia, with genetic analysis carried out by research [4,25], and [27].

2.5. Data analysis

The questionnaire survey results were examined using X² (chi-square) and Pearson correlation analysis. Due to inherent assumptions and limits, the Chi-square (X²) analysis requires categorical, independent variables with large sample sizes. In this study, the variables—local community perceptions and districts—met these requirements. They are categorical, independent, and meet the minimal sample size for X² testing [28].

The disease incidence percentage was estimated with the:

$$\text{Disease}\text{incidenc}(\text{DI})=\frac{\text{number}\text{of}\text{infected}\text{trees}}{\text{total}\text{number}\text{of}\text{trees}\text{assessed}}\times 100$$ (1)

Diseases severity assessment was rated on a numerical scale (0–3) with:

$$\text{Disease}\text{Severity}\text{Index}(\text{DSI})=\frac{\text{nL}\times 1+\text{nM}\times 2+\text{nS}\times 3}{\mathrm{N}}$$ (2)

Where: nL, nM, nS = Total number of trees with Low, Medium, and Severe Disease severity; 1, 2, 3 = Low, Medium, and Severe respectively; N = Total number of trees assessed in all the observation plots (Table 3). ANOVA is a statistical analysis technique that looks for statistical variations in the distribution of data among various groups. It makes the following assumptions: uniformity, normality of data distribution, and sample independence. We verify our data using these presumptions, and the test is suitable for the dataset. As a result, we used SPSS Ver.25 Statistical software to perform inferential statistics (ANOVA) and descriptive statistics (mean and standard error of the mean, or SE).

3. Results

3.1. Local community perception on dieback of A. mearnsii plantation

A significant variation (p = 0.026) occurred in how locals interpreted the widespread dieback of A. mearnsii plantations. Most individuals (89.6 %) associate this phenomenon with fungal disease. The local people (75.6 %) also agreed that considerable dieback is most severe during the rainy season and less severe during the dry season (Table 4).

Table 4.

Time of dieback.

Characteristics	Category	Starting time of dieback			Frequency	X2
		2019 wet season	2019 dry season	2020 wet season
Starting year of dieback	Fegita-Lekuma	3	0	33	36	131.69*(df = 9; p < 0.000
	Banja	8	1	31	40
	Guagusa-Shikudad	2	0	37	39
	Ankesha-Guagusa	2	0	37	39
Characteristics	Category	Causes of dieback			Frequency	X2
		Disease	Frost
Cause of dieback	Fegita-Lekuma	32	4		36	9.226*(df = 3; p < 0.026
	Banja	39	0		39
	Guagusa-Shikudad	34	0		34
	Ankesha-Guagusa	38	1		39
Characteristics	Category	Sever dieback season			Frequency	X2
		Dry season	Wet season
severe dieback season	Fegita-Lekuma	0	36		36	58.3*(df = 3; p < 0.000
	Banja	9	31		40
	Guagusa-Shikudad	1	33		34
	Ankesha-Guagusa	26	13		39

The perception of the level of damage and the seriously damaged age of the plantation among the surrounding communities varied significantly (p = 0.000) due to substantial dieback. According to most respondents (97.3 %) and field observations, considerable dieback severely harmed one-to three-year plantations, but four-year plantations withstood the effects. Most respondents (75.8 %) stated that the considerable dieback impacted more than 70 % of the youngest plantations (Table 5).

Table 5.

Level of damaging.

Characteristics	Category	Level of damaging			Frequency	X2
		<50 %	50–60 %	>60 %
Dieback level of damage	Fegita-Lekuma	0	1	35	36	21.7*(df = 9; p < 0.010
	Banja	4	12	24	40
	Guagusa-Shikudad	2	8	24	34
	Ankesha-Guagusa	0	9	30	39
Characteristics	Category	Sever damaging age of planation				Frequency	X2
		Seedling	1 year	2 years	3 years
Sever dieback age of plantation	Fegita-Lekuma	22	13	1	0	36	79.4*(df = 12; p < 0.000
	Banja	17	13	6	2	40
	Guagusa-Shikudad	14	12	8	0	34
	Ankesha-Guagusa	17	14	10	2	39

There was no significant difference (p = 0.1) in local populations' perceptions of different land uses and plantation management; nevertheless, there was a significant difference (p = 0.036) in plantation spacing. Most respondents (75.8 %) agreed that frequent planting with narrower spacing without silvicultural management aggravated plantation damages (Table 6).

Table 6.

Land use history and damaging level.

Characteristics	Category	Level of damaging			Frequency	X2
		<50 %	50–60 %	>60 %
Land use before plantation	After crop	4	20	55	80	6.27*(df = 3; p > 0.1
	At the range	1	8	30	39
	After plantation	1	2	27	30
Spacing of plantation	30 cm × 30 cm	0	0	7	7	17.89*(df = 9; p < 0.036
	50 cm × 50 cm	4	5	47	56
	75 cm × 75 cm	0	6	15	22
	1 m × 1 m	2	18	43	63
After planting management	Cleaning/weeding/Fencing	0	19	64	83	10.8*(df = 6; p < 0.095
	Thinning/pruning	0	1	2	3
	No management	6	10	47	63

3.2. Causes of Acacia mearnsii plantation extensive dieback

Field observations and laboratory tests (Fig. 3) revealed that wattle rust, a fungal disease caused by the Uromycladium acacia fungus, was the primary cause of considerable dieback in A. mearnsii plantations. This outcome is consistent with investigation by Refs. [30,31] (Fig. 4).

Fig. 3.

Symptoms at the field and cultured fungus at lab of wattle rust of this study.

Fig. 4.

Symptoms of wattle rust identified by [31,32].

After analyzing laboratory results and symptoms, we discovered that a fungus identified as Wattle rust caused for most of the damage to the A. mearnsii plantations in the study area.

3.3. The incidence and severity of wattle rust disease

The incidence and severity of wattle rust disease varied significantly (p = 0.000) throughout the districts studied. The Fegita-Lekuma district has the greatest disease incidence (63.9 %) and severity (36.7 %). The mean incidence and severity of the disease in all districts were 45 % and 25.6 %, respectively. Wattle rust disease severity ranged between 10 % and 36.8 % (Table 7).

Table 7.

Wattle rust disease incidence and severity (mean ± standard error (SE), n = 128) across the district (the different uppercase letters indicate the significant difference in disease incidence and severity; ** indicate significant differences at 0.01 level of significance).

Districts	Incidence (%)	Severity (%)
Guagusa-Shikudad	50.34 ± 2.8B	25.5 ± 1.9B
Banja	50.86 ± 2.7B	30.2 ± 1.88AB
Fegita-Lekuma	63.9 ± 2.7A	36.8 ± 1.88A
Ankesha-Guagusa	14.06 ± 2.7C	10 ± 1.88C
Mean	45 ± 1.4**	25.6 ± 0.94**
p-value	0.000	0.000

Certain districts had greater infection rates than others. This suggests that the disease impacted about two-thirds of the wattle trees in that district, and the infection was moderately severe. These overall averages provide a fuller picture of disease impact across the entire study area. As a result, wattle rust disease spreads unevenly throughout areas, and its impact varies substantially. The Fegita-Lekuma district appears to be the most impacted; however, the disease affects 45 % of the wattle trees in the investigated areas. The severity might vary from mild to moderate, depending on the specific location.

Although the severity of the disease varied (p = 0.04), the incidence of wattle rust disease on seedlings did not alter between districts (p = 0.06). Wattle rust completely damaged all the 6-month-old A. mearnsii seedlings planted in Ethiopia during the 2020/2021 growing season (June to July) (Table 8).

Table 8.

Effect of Wattle rust on seedlings of A. mearnsii.

Districts	Incidence (%)	Severity (%)
Guagusa-Shikudad	90A	100
Banja	70B	100
Fegita-Lekuma	100A	100
Ankesha-Guagusa	50C	100
Mean	78*	100
p-value	0.04	0.08

There was a highly significant (p = 0.000) difference in the incidence and severity of the disease among the different age groups of the plantations (Table 9). The incidence of lichen rust disease was highest at age one (72.8 %) and lowest at age four (12.6 %). The severity of lichen rust disease was highest in one- and two-year-old A. mearnsii plantations (39.2 %) and lowest in four-year-old A. mearnsii plantations (9.1 %) (Table 9).

Table 9.

Wattle rust disease incidence and severity (mean ± standard error, n = 128) on A. mearnsii plantation ages.

Age of planation	Incidence (%)	Severity (%)
One year	72.8 ± 2.7A	39.8 ± 1.9A
Two years	61.8 ± 2.7AB	38.6 ± 1.9A
Three years	32 ± 2.8BC	15.1 ± 1.93B
Four years	12.6 ± 2.7D	9.1 ± 1.9B
Mean	45 ± 1.4**	25.6 ± 0.94**
p-value	0.000	0.000

Note: The different uppercase letters indicate the significant difference of mean disease incidence and severity; ** indicate significant differences at 0.01 level of significance).

There were significant differences (p = 0.024) in disease incidence and severity between seasons (Table 10). Wattle rust was widespread and severe on the A. mearnsii plantation during the rainy/wet season. Eight months of data (from April to November) for both seasons reveal a significant correlation (p = 0.000) between the disease severity, temperature, and rainfall. The disease severity increases during months with high rainfall and lower temperatures, and it gradually decreases with gradual temperature increases and rainfall decreases. However, Elevation difference did not significantly correlate (p = 0.449) with disease severity (Table 12 and Supplementary Fig. 1).

Table 10.

Disease severity across the season (mean ± SE n = 128).

S. No	Seasons	Incidence (%)	Severity (%)
1	Wet season	52.3 ± 4.7A	35 ± 3.4A
2	Dry season	37.6 ± 4.3B	16.4 ± 1.7B
Mean		44.95*	25.7*
p-value		0.024	0.000
Significance		*	**

Note: Different uppercase letters indicate significant differences between seasons and * indicates significance difference at 0.05 and ** shows highly significant at 0.01).

Table 12.

Correlation of elevation, Rainfall, temperature, and wattle rust disease severity.

Characters		Elevation (m)	Rainfall (mm/year)	Temperature (0C)	Disease severity (%)
Elevation (m)	Pearson Correlation	1	−0.017	−0.229	0.054
	Sig. (1-tailed)		0.484	0.293	0.449
Rainfall (mm/year)	Pearson Correlation	−0.017	1	−0.958a	0.944a
	Sig. (1-tailed)	0.484		0.000	0.000
Temperature (0C)	Pearson Correlation	−0.229	−0.958a	1	−0.934a
	Sig. (1-tailed)	0.293	0.000		0.000
Disease severity (%)	Pearson Correlation	0.054	0.944a	−0.934a	1
	Sig. (1-tailed)	0.449	0.000	0.000

^aCorrelation is significant at the 0.01 level (1-tailed).

The incidence and severity of wattle rust disease were shown to be influenced by an interaction effect (p = 0.044) across districts, plantation age, and season. However, there was no interaction effect (p = 0.66) between seasons and plantation age on wattle rust disease occurrence. During the wet season, wattle rust disease is severe in the Fegita-Lekuma district at plantation ages of one to two years (Table 11 and Supplementary Table 2).

Table 11.

p-values for the main and interaction effects of districts, age of plantation, and seasons on the incidence and severity of Wattle rust (n = 128) (* shows main and interaction effects).

Effects	Incidence	Severity
Districts	0.000*	0.000*
Age of plantation	0.000*	0.000*
Seasons	0.024*	0.000*
Districts*Age of plantation	0.000*	0.000*
Districts*seasons	0.000*	0.040*
Age of plantation*Seasons	0.66	0.68
Districts*Age of plantation*Seasons	0.044*	0.008*

Rainfall shows a significant positive association (0.944, p = 0.000), whereas temperature has a strong negative correlation (−0.934, p = 0.000) with disease severity. However, elevation has a lesser association with the other variables (Table 12). Temperature reduces the disease's severity whereas precipitation worsens it. The severity of the disease is more correlated with rainfall and temperature than with elevation. As a result, both rainfall and temperature play important roles in disease severity, although elevation has a less pronounced effect.

4. Discussion

4.1. Sympathetic of the local community to extensive dieback of A. mearnsii plantation

Since its introduction to Ethiopia in the 1990s, A. mearnsii has grown to be a significant source of revenue from the production of charcoal and the rehabilitation of acid soil, especially in the highland highlands of the Awi zone. However, since the onset of the rainy season in 2020, the plantation has experienced severe dieback, which begins at the apical meristem and spreads to branches and stems, accompanied by mass leaf shedding. This has impacted more than 70 % of the plantation's annual revenue, resulting in considerable economic loss at the local, regional, and national levels (Table 3, Table 4, Table 9, Table 10) [5].

Most participants, as shown in Table 3, attribute the extensive dieback to a fungal disease. This supports the claim made in Ref. [33] that pest and disease outbreaks pose a significant challenge due to the expansion of exotic plantations in Eastern and Southern Africa. The first cause of disease and pest outbreaks could be dense plantations and a lack of silvicultural management. In the study area, A. mearnsii plantation is becoming a commercial tree crop, spreading even on irrigated fertile agricultural lands. The second possibility entails continuously rotating the plantation on the same land unit, which may cause infections and disease outbreaks through the soil [2].

It has been confirmed by field observations, interviewee arguments, and laboratory tests that fungal disease is the cause of severe plantation dieback. This is consistent with a study by Ref. [13] that found pests and diseases in the tropics are posing a growing danger to acacia species that are planted as non-native plants throughout the world. Ethiopia is currently experiencing a large-scale dieback of A. mearnsii plantations, which was initially reported in South Africa [34]. The disease started with powdery brown telia on the apical meristem and spread to the trees' leaves, trunks, and heart. In 1988, modest symptoms on leaves induced by the ‘young stage of rust on A. mearnsii were recognized as U. alpinum with an altered life cycle and increased disease severity, it has since become a concern to A. mearnsii youngest plantations [15]. However the study concentrated merely at four districts in the Awi zone, which is the main growing area for this species. To overcome these limitations and gain a deeper understanding of the species’ growth conditions and variations, we will extend the geographic scope to include more districts outside of the Awi zone. We will conduct research over multiple growing seasons to account for yearly differences in climate and other environmental factors. Use a range of techniques, interdisciplinary approaches, and community involvement to achieve more comprehensive results. Furthermore, we will do additional genetic analysis using modern laboratories, remote sensing, and GIS mapping, as well as comparative studies of relevant mitigation strategies.

4.1.1. Incidence and severity of wattle rust disease

The youngest A. mearnsii plantation in the study area experienced severe dieback, defoliation, and stunted growth, according to field observations and laboratory findings. The fungus Wattle rusts, which is carried with the Uromycladium acacia, was found to be the primary cause. Disease severity of U. acacia on the A. mearnsii plantation in Fegita-Lekuma district was extremely high, exceeding 70 %, resulting in leaf loss and drying. The severity of wattle rust disease was 61–63 %, resulting in stunted growth in Banja and Guagusa-Shikudad districts. In Ankesha-Guagusa district, the disease severity was less than 25 % and affected only the youngest leaves [22]. In the Ankesha-Guagusa district, the disease severity was below 25 %, affecting only the youngest leaves. Similarly [22], reported that the disease severity and incidence were 28 % for similar species in Bhutan. Intense management measures and frequent planting in the Fegita-Lekuma district might have contributed to the severity of the Wattle rust disease. It is worth noting that Fegita-Lekuma pioneered the growth of commercial and mass plantations with spacings of less than 30 cm. This could aggravate the infestation of the plantations with wattle rust disease.

The Awi Zone Agriculture office report, community evidence, and field observations all confirm the complete loss of seedlings that were six months old [20]. In the first three to four years of plantation life, the wattle rust disease was at an exceptionally high severity; nevertheless, after four years, the plantation was able to withstand the damage. As a result, the disease inhibited the growth of the young A. mearnsii plantations. During the first and second years of the plantation, the disease caused the branches to dry up and become defoliated. It damaged the plantation during the wet season of the third year, after which it was revegetated. The disease causes comparable damage in the youngest A. mearnsii plantations, according to Ref. [15] and it has recently become a threat to exotic acacia species plantations by changing the life cycle and making the disease more severe. Wattle rust disease caused moderate dieback during the dry season, allowing the plantation to regenerate. However, the condition occasionally worsened as the rainy season approached. During the rainy season, there was intense rainfall (366 mm/month) and hot temperatures (16.5 °C) in the last four years (Table 12).

The significant interaction effect (Table 11) indicates that the incidence and severity of wattle rust disease are not uniform but vary depending on the combination of district, plantation age, and season. This suggests that localized environmental conditions and plantation management practices play a crucial role in disease dynamics [35]. The lack of a significant interaction effect between seasons and plantation age (Table 11) implies that these two factors independently influence the occurrence of wattle rust disease. This means that while both factors are important, their combined effect does not significantly alter disease incidence. The observation that wattle rust disease is severe during the wet season in the Fegita-Lekuma district for plantations aged one to two years highlights the vulnerability of young plantations to the disease under wet conditions. This could be due to higher humidity and moisture levels, which are conducive to the growth and spread of rust fungi [36].

The disease severity increases during the rainy or wet season due to high rainfall and low temperatures, and it gradually diminishes during the dry season as rainfall declines with an increase in temperature (Table 12). The amount of rainwater during the rainy season promotes disease severity by encouraging growth and spore generation. Cooler temperatures during the wet season encourage disease development, whereas the dry season inhibits pathogen activity [17]. Therefore, the humid and wet season is ideal for the spread of the fungal disease caused by U. acacia. This finding is similar to Ref. [27], who discovered that high humidity and rainfall levels increased the prevalence and severity of U. acacia disease. Furthermore, climate change influences the occurrence and severity of tree diseases in both plantations and natural forests. Understanding these consequences necessitates considering unique interactions between diseases and hosts, as well as the effects on hosts and other species. Long-term patterns are essential to understand plant and pathogen evolutionary adaptation, as well as the impact of future climate change [37].

5. Conclusion

Severe dieback and defoliation of the youngest A. mearnsii plantation occurred in the Fegita-Lekuma district during the 2020 rainy season, spreading quickly to the other three districts by wind, according to official reports from local, regional, and national agencies, local community witnesses, and field observations.

The significant dieback completely wounded 6-month seedlings, produced leaf defoliation in one to two-year plantations, and injured the branches and apical meristem in three-year plantations; however, four-year plantations survived the damage. According to the local people, frequent planting with closer spacing without silvicultural treatments exacerbates plantation damage.

Field observations and laboratory investigations found that the U. acacia fungus, which causes wattle rust, is the principal cause of significant dieback in younger A. mearnsii plantations. The history of introduction, management strategies, and planting area might cause the severity of the wattle rust fungal disease, caused by U. acacia, to vary among districts, seasons, and plantation age.

The U. acacia fungus, which causes wattle rust disease, is currently threatening the adaptable, fast-growing A. mearnsii plantation. This plantation provides a living for local, regional, national, and international communities. The survey results reveal that the disease's progression is dangerous and could lead to the loss of A. mearnsii plantations in the research area, resulting in a severe ecological and economic problem. As a result, concerned stakeholders should intervene to save these locally called “black gold” resources.

Further outlook: integrated pest management (IPM)

Currently, nothing is taking preventative efforts to manage and reduce the devastating dieback caused by the wattle rust fungal disease. In the near term, nurseries should use fungicides with both botanical and chemical components to decrease disease severity. Long-term resource sustainability and improved livelihoods necessitate disease-resistant species and effective forest management. Key stakeholders should implement these solutions through scientific and systematic approaches.

The most successful approach to managing wattle rust outbreaks and related pests is to use integrated tree pest management strategies. These strategies use a variety of approaches to avoid, control, and eliminate pest and disease outbreaks that afflict this tree. Before starting seedlings, it is critical to select clear and responsible seed suppliers. High-quality seeds from disease-resistant trees result in healthier forests. Avoiding seeds from affected plants helps to slow the spread of wattle rust. Secondly, silvicultural practices such as optimizing tree spacing, fallowing (allowing land to rest), and cleaning (removing weeds, dead or sick trees) might help avoid and manage wattle rust on A. mearnsii plantations [38].

To control the disease once infected, use herbal and fungicide treatments. At nursery sites, use herbal remedies (such as plant extracts) and fungicides to prevent or control wattle rust. Proper administration of these treatments promotes healthy seedlings while reducing disease spread.

After planting, keep animals away to prevent harming young trees and introducing pests. Excluding animals from plantations preserves seedlings and reduces pest infestation. Other techniques for integrated pest management, particularly for soil-borne diseases, include proper soil management, which helps to keep trees healthy by balancing nutrients and managing moisture. Healthy trees are less susceptible to wattle rust. When applied effectively, these strategies contribute to healthier forests and better pest management.

Ethical approval statement

This research did not use animals or humans and is not a clinical study. Thus, an ethical statement is not applicable for this research.

Data availability statement

The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials. The data is shared in Mekonen (2024), “Acacia mearnsii supplementary data”, Mendeley Data, V1, https://doi.org/10.17632/6krb6g2547.1.

Funding

This research did not receive any specific funding.

CRediT authorship contribution statement

Mulugeta Tamer: Writing – review & editing, Project administration, Investigation, Formal analysis, Conceptualization. Melkamu Kassaye: Writing – original draft, Investigation, Formal analysis, Data curation, Conceptualization. Tigest Molla: Writing – review & editing, Methodology, Investigation, Data curation. Kelelaw Kebede: Writing – review & editing, Methodology, Investigation, Formal analysis, Data curation. Yehizbalem Azmeraw: Writing – review & editing, Validation, Supervision, Investigation.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary data

The following is the Supplementary data to this article: