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Understanding of relative distribution of avifauna provides insights for the conservation and management of wildlife in the community managed areas. This study examined relative diversity, abundance, and distribution of avifauna in selected habitat types across five Wildlife Management Areas of the Ruvuma landscape in miombo vegetation, southern Tanzania. Five habitat types were surveyed during the study: farmland, swamps, riverine forest, dense and open woodland. Transect lines, mist-netting, and point count methods were used to document 156 species of birds in the study sites. Descriptive statistics and Kruskal-Wallis tests were used to compare species richness and diversity across habitat types. We found differences in avifaunal species distribution in the study area whereby farmland had the highest abundance of avifauna species and lowest in the riverine forest. These results suggest that variations of avifauna species abundance, diversity, and distribution could be attributed by human activities across habitat types; due to the reason that habitats with less human encroachment had good species diversity and richness. Therefore, to improve avitourism and avoid local extinction of species, we urge for prompt action to mitigate species loss by creating awareness in the adjacent community through conservation education on the importance of protecting such biodiversity resources.
Department of Biosciences, Centre for Ecological and Evolutionary Synthesis (CEES), University of Oslo, Norway
Pius Y. Kavana
Mahale-Gombe Wildlife Research Centre, Tanzania
Tanzania Wildlife Research Institute, Tanzania
*Address all correspondence to: ally.nkwabi@tawiri.or.tz
1. Introduction
The miombo ecosystems are known worldwide for their higher biodiversity [1, 2]. Woodlands in the miombo ecosystems are dominated by trees of the genera Brachystegia, Julbernardia, and Isoberlinia Leguminosae, subfamily Caesalpinioideae [1, 3]. The woodlands cover between 2.7 and 3.6 million km2 in 11 African countries [2, 4, 5, 6]. In Tanzania, this vegetation type covers more than 90% of forested land [4, 7, 8, 9, 10], and some of the miombo woodlands are found within several of the iconic protected areas including Selous Game Reserves and the Mikumi, Ruaha, Nyerere National Park as well as the Ruvuma Landscape in southern Tanzania. The ecological services it provides include: the provision of forage for wild and domestic animals, nesting sites for birds, water catchments, carbon sequestration, and biodiversity conservation in general and is archived due to the presence of habitat heterogeneity in particular flora diversity that exists in the miombo areas [3, 4].
Floral species compositions are a very important component to determine the distribution and diversity of avifauna communities [11]. Bird species diversity in savannah landscapes increases with an increase in vegetation/habitat heterogeneity in the miombo woodlands [5, 6]. In heterogeneous habitats, some avian species tend to show preference on certain habitat types, which also influence avifaunal diversity, abundance, and distribution across landscapes [7, 8, 12]. For example, miombo pied barbet (Tricholaema frontata), miombo rock thrush (Monticola angolensis), stierling’s wren warbler (Calamonastes stierlingi), racket-tailed roller (Coracias spatulatus) and white-tailed blue-flycatcher (Elminia albicauda) prefer miombo woodland, only stierling’s wren warbler and racket-tailed roller were observed during data collection other species listed here were not recorded during this study possibly due to habitat degradation.
The Ruvuma landscape in Tunduru District, in southern Tanzania encompasses five Wildlife Management Areas (WMAs) namely: Mbarang’andu, Kimbanda, and Kisungule in Namtumbo District, Nalika and Chingoli WMAs in Tunduru District (Figure 1). It borders the Selous Game Reserve and Nyerere National Park in the north and the Niassa National Reserve (Mozambique) to the south. The Ruvuma River forms an international boundary between Tanzania and Mozambique within Namtumbo and Tunduru districts [13]. The two protected areas rely on the presence of the five Wildlife Management Areas as they provide dispersal and movement area (corridor) to Niassa National Reserve in Mozambique and to Nyerere National Park. Habitat destruction by humans is a serious threat that alters the integrity of ecosystems [8], also affects vegetation cover. It is possible that human activities occurring in the miombo woodland resulted in land cover change [7, 9, 10, 14, 15]. Currently, the Wildlife Management Areas (WMAs) of the Ruvuma region in southern Tanzania undergo fragmentations caused by human activities which include uncontrolled wildfires, collection of fuel wood, charcoal, timber, illegal hunting, cattle grazing, and agriculture. In this area, communities have formulated the Wildlife Management Area (WMA), which is the form of community-based conservation which ensures villagers or communities rich in wildlife sustainably conserve, utilize and benefit from wildlife. Wildlife Management Areas are formed within village land from which villagers set aside a piece of land purposely for sustainable conservation and utilization of wildlife resources. The Tanzania government actualized WMAs for the local community to participate in wildlife management and conserve wildlife habitats in the communal land.
Figure 1.
Map of Ruvuma WMAs showing the location of the sampling sites.
Apart from the study investigated on abundance, nesting and habitat of the white-browed sparrow-weaver (Plocepasser mahali) conducted by Ngongolo and Mtoka [16] no other study attempted to describe the diversity, abundance, and distribution of avifaunal species across the habitat gradient, and assess the implication of ongoing human activities to the conservation of avifauna species across the Ruvuma Landscape. This gives an opportunity to assess avifauna diversity and distribution in relation to habitat disturbance and how avifauna responded to this habitat destruction. Studying avifauna in Ruvuma landscape will open a room for avitourim activities and conserve from habitat degradation. Therefore, this chapter aimed at presenting the diversity of avifauna species in the Wildlife Management Areas in the Ruvuma Landscape in relation to human activities. It is predicted that avian species diversity and abundance would be higher in protected habitats inside WMA than in areas dominated by human activities namely farmlands.
In this study we treated the presence of farmlands in WMAs where they are not supposed to be as disturbance, because all WMAs in Tanzania have land use planning. The land use planning in all WMAs provides guidelines by zoning communal land where different activities can be conducted, such cattle grazing, settlements, farming and wildlife conservation area (tourist areas). All plots selected in this study were from wildlife conservation zones where also farms existed. Potential actions for intervention have been highlighted.
The rainfall pattern is unimodal spanning from late November to May with a mean annual rainfall of 800–1200 mm in a north–south gradient. The mean annual temperature is 21°C, following the Köppen system [17]. The area consists of extensive miombo woodland, including Brachystegia sp., Julbernardia sp., Isoberlinia sp., Afzelia quanzensis, Pterocarpus angolensis, and rare and threatened plant species such as Dalbergia melanoxylon, which forms dense miombo along the hills and rivers [18]. Also, there are seasonal and permanent wetlands (swamps), riverine forests along numerous perennial and seasonal streams. Due to the increasing anthropogenic activities, the area currently has farmlands and patches of wooded with scattered trees and grazing land.
2.2 Sampling design
Five sites of 200 m x 200 m were established in each WMA, making a total of 25 sites. We selected different habitat types for each of the five sites, namely miombo woodland (open and dense), farmland, swamps, and riverine forest.
2.3 Avifauna survey
Each site was sampled using three complementary methods to maximize the sample size. First, in each habitat type, avifauna counts were carried out using the point transects technique [6, 19]. This method consists of standing at a particular point or walking slowly across the site back and forth several times, to detect cryptic and skulking species in the area. These counts were repeated for 3 days, based on results from our pilot study, and the numbers for each site were averaged. A 20-minute counting period was used at each site, and the starting time (between 6:30 and 10:30 h) was rotated among the sites to reduce bias. Avifauna was identified by both sight and call, and numbers were recorded [20].
Secondly, the transect method was used. Three transects 40 km in length each were established in every WMA using existing roads. The locations of all transects were based on accessibility and were sampled using a vehicle driven at a speed of 20 km/hr. or less that stopped for each individual or group of birds encountered [21]. Two observers sighted and recorded all avifauna on either side of the vehicle and notes on habitat type were also taken [21].
Thirdly, mist-netting was used to the targeted cryptic, understory, and lower canopy avian species. Nets were erected and checked every 15 min in the early morning (between 6:30–10:30 h) and late afternoon (between 16:00–18:00 h). The total number of each species caught, and the associated habitat type was recorded. Each bird was marked with a drop of red permanent spray paints at the base of its toes on the right tarsi for verification, if recaptured, to avoid double counting [22].
2.4 Statistical analysis
The biodiversity indices in different habitats or within these WMAs were obtained following Magurran [23]. This index uses three biodiversity indices including, diversity, richness, and abundance. A non-parametric Kruskal-Wallis test was used to assess whether there were significant differences in mean species abundance among five WMAs, and across each habitat type [24]. Differences in mean bird numbers between habitats in each WMA were tested using Mann–Whitney tests to assess whether the number of species was significantly lower in human-encroached habitat (farmland), i.e., farmland, compared to riverine forest, and dense and open miombo woodland habitats. Statistical tests were computed using the software package PAST [24]. For all these analyses, farmland habitat in this study represented human encroachment into protected areas and was used to compare with other habitat types found in the WMAs. We further calculated the Jaccard similarity index (Ji) between different habitat types to determine the level of similarities in species composition using the formulae [24]:
Jaccard similarity coefficientJ;J=A/A+B+CE1
Where A = number of species found in both communities, B = number of species only found in community 1 and C = number of species found in community 2. The equation returns a number between 0 and 1, where a number close to 1 indicates a higher similarity in species composition [23]. We then multiplied J by 100 to obtain a percent, to easily interpret the results.
3.1 Avian species diversity, distribution, and richness
A total of 156 avian species representing 18 orders and 61 families were recorded in the five WMAs. The overall avian species Shannon diversity (H′) for all the habitat types ranged from 2.28–4.08, except for dense miombo woodland which had H′ = 1.69 (Table 1). Riverine forest habitat had higher species richness (n = 101 species), representing almost 45% of the total recorded individuals (Table 1). Avian species diversity was highest in riverine forest and lowest in dense miombo woodlands (Table 1; Figure 2). The Shannon Index of diversity revealed that species evenness for the five habitats surveyed was relatively low ranging from 0.29–0.59 (Table 1).
Habitat type
Number of avian species
Overall abundance
Mean abundance
Shannon diversity (H′)
Shannon evenness (EH)
Dense miombo
14
105
7.50 ± 3.91
1.69
0.39
Farmland
40
580
14.50 ± 5.82
2.46
0.29
Open miombo
98
1338
13.65 ± 2.08
3.9
0.51
Riverine forest
101
759
7.52 ± 0.97
4.08
0.59
Swamp areas
20
188
9.40 ± 3.26
2.28
0.49
Table 1.
Avian species diversity, abundance, and evenness in different habitats of WMAs in Ruvuma landscape (± standard error).
Figure 2.
Avian species diversity in different habitats.
Values bearing different letters within column are significantly different (p < 0.05) and values with similar letters within column are not significantly different (p > 0.05; Table 2). Dense miombo woodland, farm and swamp exhibited higher number of birds per point count than in open miombo woodland and riverine forest implying that the avian species were more scattered in open miombo woodlands and riverine forests.
Habitats
Average bird count
Dense miombo woodland
6.18a
Farm
6.11a
Open miombo woodland
3.71b
Riverine forest
3.45b
swamp
6.48a
Table 2.
Average number of birds per point count in different habitats.
The overall mean abundance of avifauna in the WMAs differed significantly (Kruskal-Wallis test, χ2 = 50.13, df = 4, P = 0.03). Kimbanda had the highest mean abundance of species followed by Kisungule (Figure 3). There was a significant difference in the mean abundance of avifauna across the five habitats (Kruskal-Wallis test, χ2 = 13.18, df = 4, P = 0.010). Mean abundance of species was significantly higher in farmland than in dense miombo (Mann–Whitney tests, U = 19, P < 0.0001), open miombo woodland (U = 66.5, P < 0.0003), riverine forest (U = 157, P < 0.019) and swamps (U = 93.5, P < 0.004) (Figure 3).
Figure 3.
Avian abundance in different habitats of wildlife management areas in southern Tanzania.
The distribution of the 2970 avifauna species recorded in the five habitat types is given in (Table 1 above; Figure 4). Some species were found in more than one habitat type, a total of six species with bronze mannikin (Lonchura cucullata) the most abundant (Figure 5). Tawny-flanked prinia (Prinia subflava), blue-spotted wood dove (Turtur afer), common bulbul (Pycnonotus barbatus), violet-backed starling (Cinnyricinclus leucogaster), and Jameson’s firefinch (Lagonosticta rhodopareia) were observed in four habitat types, except swamp habitat (see Figure 5; Appendix Table A1). Southern cordon-bleu (Uraeginthus bengalus) was observed in three habitat types and was the second most abundant species recorded during this study (Figure 5). Other species including pied crow (Corvus albus), brown-headed parrot (Poicephalus cryptoxanthus), and red-necked francolin (Pternistis afer) were observed in three habitat types (see Appendix Table A1) whereas black-faced waxbill (Estrilda erythronotos) and African pied wagtail (Motacilla aguimp), were observed only in farmland areas.
Figure 4.
Avifauna species observed foraging in different habitats. Definition of abbreviation used (Demiwo = dense miombo woodland, riverfore = riverine forest, farmland = farmland habitat, opemiwo = open miombo woodland).
Figure 5.
Distribution of avian species in different habitats within WMAs of the Ruvuma landscape in southern Tanzania.
Cryptic species like African broadbill (Smithornis capensis) and red-capped robin-chat (Cossypha natalensis) and understory bird species including red-throated twinspot (Hypargos niveoguttatus) were observed only in the riverine forest using mist-nets and point count methods (Appendix Table A1). Palearctic migrants including European nightjar (Caprimulgus europaeus), European swift (Apus apus), and European bee-eater (Merops apiaster) were also recorded. Trumpeter hornbill (Bycanistes bucinator) is a bird of conservation status that was observed during the study in forest patches.
3.2 Species composition and similarities between different habitat types
We found strong contrast in species composition among habitat types (Table 3). The highest species similarities were between open woodland vs. Riverine forest (41%), Farmland vs. Open woodland (24%) and Farmland vs. Riverine forest (21%) while dense woodland vs. Swamp areas had no similarity in composition (0%), Open woodland vs. Swamp area (1%) and Farmland vs. Swamp area (2%; Table 3). The Jaccard similarity indices among various pairs of habitat types compared (Table 3; Figure 6).
Habitat types
Dense woodland
Open woodland
Farmland
Riverine
Swamp area
—
—
—
—
—
Open woodland
11
—
—
—
—
Farmland
15
24
—
—
—
Riverine forest
8
41
21
—
—
Swamp area
0
1
2
5
—
Table 3.
Jaccard species composition similarity index (J) between habitat types of the WMAs in Ruvuma landscape, in southern Tanzania. In this table the similarity presented in percentage (%).
Figure 6.
Plotted trend line to show species composition similarities between habitat types of the WMAs in Ruvuma landscape, in southern Tanzania. Definition of abbreviation used (dw vs. sw = dense woodland vs. swamp area; dw vs. fm = dense woodland vs. farmland; dw vs. ow = dense woodland vs. open woodland; dw vs. rf = dense woodland vs. riverine forest; fm vs.ow = farmland vs. open woodland; fm vs. rf = farmland vs. riverine forest; fm vs. sw = farmland vs. swamp area; ow vs. rf = open woodland vs. riverine forest; ow vs. sw = open woodland vs. swamp area; rf vs. sw = riverine forest vs. swamp area).
From the results, avian species adapted to open miombo woodlands and those adapted to riverine forest were very closely related and far from avian species adapted to swamps (Figure 7). Avian species adapted to swamps were separated from all other avian species adapted other habitats (Figure 7). Indeed, this entails a need for conservation of swamps to avoid local distinction of swamp adapted species.
Figure 7.
Cluster analysis of different habitat types based on bird species composition (presence/absence). Definition of abbreviation used (Demiwo = dense miombo woodland, riverfore = riverine forest, farmland = farmland habitat, opemiwo = open miombo woodland).
4.1 Avian species diversity, distribution, and richness
Farmland habitats were observed in all WMAs except in Mbarang’andu where we did not encounter cultivated areas inside the core WMA. Possibly due to the presence of an anti-poaching office established inside WMA by Tanzania Wildlife Management Authority (TAWA, formerly Wildlife Division). In our study, we predicted that there would be higher avian diversity, richness, and abundance in WMAs than in human-modified areas named here as farmlands. We found strong support for this prediction for the species diversity and richness of avifauna but not for abundance. This suggested that the differing occurrence of avifauna species across given habitats could be attributed to some reasons including food requirement as well as heat tolerance [25].
The richness and diversity imply a variety of taxa that exist in an area, many taxa should, therefore, survive in habitats that have a variety of favorable conditions and resources such as the presence of food, nesting areas, shade and water that might contribute to higher species richness and diversity. Therefore, low species diversity in the farmland might be contributed by the insufficient supply of food as well as insufficient cover for birds to hide against predators, lack of shade to hide from diurnal temperature [12, 26] low food supply compared to forests and woodlands. Suggesting that farmlands have reached maximum disturbance, as in lower farmlands heterogeneous vegetation offer foods and shelter for birds encouraging higher diversity and abundance [8]. Thus the granivores which are largely seed eaters such as the bronze mannikin, southern cordon-bleu, and red-billed quelea were dominant in farmlands than in other habitats because farmlands were rich in seed types vegetation, in line with the findings of others [12, 26]. Furthermore, for similar reasons, the abundance of the granivores species was also higher in open miombo where grassland patches are dominant than in forest areas. Birds that preferred mixed habitat of tree-covered vegetation and open areas chose forest and woodlands but are not water-bound and avoided farmlands such as red-throated twinspot, pygmy kingfisher and red-capped robin-chat, they co-existed in riverine forest and woodland, together with birds that prefer evergreen or lowland forest, dense deciduous thickets, or other dense woodlands such as black-throated wattle-eye and the African broadbill.
4.2 Species composition and similarities between different habitat types
The presence of higher species composition and similarities among habitat types suggests that miombo woodlands harbor unique avifauna species. Some avian species are observed to occur in more than one habitat type indicating that avian species are not habitat specialists. In this study, such patterns were observed; some species existed in more than 4 habitat types suggesting areas visited they provide similar resource abundance, types, and habitat heterogeneity.
Therefore, under no intervention strategies, the Ruvuma Landscape will result in a marked loss of avian richness and diversity. This suggests that measures that will reduce land clearance for agriculture need to be promptly implemented to reduce the ecological impacts on avifauna. Wildlife management areas should involve adjacent communities that are the key stakeholders of the habitats and species biodiversity conservation. Such measures can enhance the resilience of wildlife management areas and complement the goals of community-based conservation measures [27, 28]. Unfortunately, any proposed measures may be challenged by increasing human pressure due to agricultural intensification needs as well as a rapidly changing climate that may be beyond the WMA’s management control. Examining the links of these threats to avian biodiversity and addressing such in an urgent manner is likely to abate current human disturbance in the WMAs of Ruvuma region.
We thank the District Game Officers of Namtumbo and Tunduru as well as Community Based Conservation Training Centre (CBCTC) staff for their assistance and positive cooperation they have rendered for the success of this project. We thank the Village Game Scouts (VGSs) and all WMA leaders for their guidance during data collection. Furthermore, we recognize the materials and technical support offered by the Tanzania Wildlife Research Institute (TAWIRI). This study was funded by the WWF Tanzania grant to Geo Network Ltd. based at Dar es Salaam.
List of avifauna species observed in different habitats of WMAs in Ruvuma.
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Written By
Ally K. Nkwabi, John K. Bukombe, Hamza K. Kija, Steven D. Liseki, Sood A. Ndimuligo and Pius Y. Kavana
Submitted: 07 December 2020Reviewed: 19 March 2021Published: 06 May 2021
Open access peer-reviewed chapter
