Journal of Environmental Science and Public Health

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Research ArticleOpen Access

Analysis of Spatial and Temporal Changes in Land Uses and its Implications to the Conservation of Eastern Selous-Niassa Transfrontier Conservation Areas (TFCA)

Adili Y. Zella1*, Saria Josephat2, and Yohana Lawi2

1Department of Economic Studies, The Mwalimu Nyerere Memorial Academy (MNMA)-Zanzibar, Zanzibar, Tanzania
2Department of Environmental Studies, Faculty of Science, Technology and Environmental Studies, Open University of Tanzania, Dar es Salaam, Tanzania

*Corresponding Author: Adili Y. Zella,  Department of Economic Studies, The Mwalimu Nyerere Memorial Academy (MNMA)-Zanzibar, P.O Box 307, Zanzibar, Tanzania, Tel: +255242250315 (or) +255787260448;

Received: 12 July 2017; Accepted: 22 August 2017; Published: 01 September 2017


Abstract:

This paper discusses the less known spatial and temporal changes that have occurred over a period of 30 years in land use and land cover and their impacts on terrestrial ecosystem services of Selous – Niassa TFCA. Objectives of the study were to analyze the spatial and temporal changes of land use/cover, estimate amount of trees loss, and analyse wood balance. The study employs field survey, remote sensing and GIS techniques were employed to assess spatio-temporal dynamic of land use/cover. The study has revealed that there has been a significant land use and vegetation cover transformation from one class to another. For the period between 1986 and 1997 the area under closed woodland, open woodland, grassland, built up area, and cultivated land increases by 1.14%, 0.62%, 2.92%, 0.06%, and 2.17% respectively. Likewise, bushland and water decreased by 6.86 and 0.04 respectively. For the period between 1997 and 2005, the closed woodland, open woodland, and bushland declined by 9.65%, 8.41%, and 5.23% respectively. For the same period of time, grassland, water, built up area, and cultivated land increased by 5.3%, 0.01%, 0.29%, and 17.7% respectively. Moreover, for the period between 2005 and 2016, the closed woodland, open woodland, grassland, water, and cultivated area declined by 0.91%, 4.65%, 8.25%, 0.02% and 1.53% respectively. For the same period of time, bushland and built up area increased by 15.27% and 0.08% respectively. Also, the results revealed gain of trees regenerated in the study area during the period 1986 – 1997 with an average of 3.5 million trees per year. Besides, there was rampant conversion of woodland in the study area during the period 1997 – 2016 with average loss of 27 million trees per year. Wood supply in the study area for the year 2016 is at least 25 times the average demand per year per capita. Conversely, the trend of wood supply from 1986 to 2016 shows dramatic deforestation of the area which implies tragedy of commons and is the public property where there are no control policies or rules. The study recommends an emergence of reviewing management and conservation strategies is unexceptional if we need sustainability of Selous-Niassa TFCA.


Keywords:

Land use and land cover change (LULCC), Ecosystem services, Tree loss, Wood balance

Untitled Document 1. Introduction

1.1 Background information
Land use and land cover change (LULCC) calls for special attention since humans have been modifying land to obtain food and other essentials for thousands of years, but current rates, extents and intensities of LULC changes are far greater than ever in history [1], driving unprecedented changes in ecosystems and environmental processes at local, regional and global scales. LULCC can occur through the direct and indirect consequences of anthropogenic activities to secure their economic and social needs. Burning of areas to develop the availability of wild game as well as cultivated land, resulting in extensive clearing such as deforestation and earth’s terrestrial surface management that takes place today [2]. Many transfrontier conservation areas (TFCAs) are unexceptional from these challenges as they consists of various levels of protected areas (PAs) from strict protection (includes national parks and game reserves) to weak protection (open areas, game controlled areas and wildlife management areas) which shape level of LULCC. For instance, most wildlife protected areas in East  Africa are unfenced and wildlife movements are borderless; hence, the dispersal areas connecting two or more PAs depends on the level of protection which can trigger sustainability level of wildlife, habitat and ecosystem services provided by that PA.

LULCC is a complex process which influenced by the jointly interactions between environmental and other social factors at different spatial and temporal scales [3, 4]. More recently, industrial activities and developments, the so-called industrialization, has encouraged the concentration of population within urban areas. This is called urbanization, which includes depopulation of rural regions along with intensive farming in the most productive lands and the abandonment of marginal lands [2]. These conversions and their consequences are obvious around the world and it has been becoming a disaster around the metropolitan areas in developing countries. These changes encompass the greatest environmental concerns of human populations today, including climate change, biodiversity loss and the pollution of water, soils and air. Monitoring and mediating the negative consequences of LULCC while sustaining the production of essential resources has therefore become a major priority of researchers and policymakers around the world.

1.2 Problem Statement
Households living in all terrestrial wildlife ecosystems like corridors depend heavily on services provided by those ecosystems for their livelihoods. LULCC can greatly alter the provision of ecosystem services. Land Conversion to human utilization introduces the risk of undermining human wellbeing and long term sustainability [5]. Particularly, it is considered to be one of the drivers of global environmental change [6]. Selous ? Niassa ecosystem is not exceptional from this scenario as it connect two terrestrial miombo protected areas (Selous Game Reserve in Tanzania and Niassa Game Reserve in Mozambique) to form transfrontier conservation area (TFCA) by a corridor which occupies an area of 14, 625.6 km2 that stretches for about 120?180 km and extending across southern Tanzania and the Mozambique border [7]. The corridor dwellers are the one responsible for conversion of habitat to suit their livelihood.

Transformation of ecosystems into other land use categories, primarily the conversion of various vegetation covers to agricultural land and urban areas, impacts water flows and the biogeochemical cycle, and is closely linked to climate change [8, 9]. The joint effects of land use and climate change are perceived as the most important driver of biodiversity loss. Because biodiversity is known to represent a key prerequisite for the functioning of an ecosystem and delivery of bundles of ecosystem services [10].Land use change may undermine regulatory capacities of the ecosystems for example in terms of the ability to avoid and minimize hazards [5]. A number of risks initiated by land use change or its consequences originate in diminished land productivity, land degradation, disruption of water regime, water contamination, or extra losses of biodiversity [6].

Biodiversity has been diminishing considerably by land change. While lands change from a primary forested land to a farming type, the loss of forest and wildlife species within deforested areas is immediate and huge [2].According to Ellis et al. [2] the habitat suitability of forests and other ecosystems surrounding those under intensive use are also impacted by the fragmenting of existing habitat into smaller pieces, which exposes forest edges to external influences and decreases core habitat area.

The conversion of tropical forest to grassland disrupts the herbivores food chain of different sizes according to their dependent feeding structure and altering of many wildlife species; for example disappearances of “ecotones” (area which separate grassland and wooded grass land) which is the living habitat of some antelopes [11]. LULCC, particularly natural forest alteration makes soils vulnerable to a massive increase in windy and water soil erosion forms, particularly on steep topography. When accompanied by fire, also pollutants to the atmosphere are released. Soil fertility degradation within time is not the only negative impact; it does not only cause damage to the land suitability for future farming, but also releases a huge amount of phosphorus, nitrogen, and sediments to aquatic ecosystems, causing multiple harmful impacts of sedimentation and eutrophication. Thus, this study intended to analyse spatial and temporal LULCC of eastern Selous-Niassa TFCA by estimating habitat conversion area into other activities, amount of trees loss and wood balance.

1.3 Objectives
1.3.1 Main objective: The main objective of this study was to analyse spatial and temporal habitat conversion of eastern Selous-Niassa TFCA.

1.3.2 Specific objectives: Specifically the study intends to:

  • analyse LULCC of eastern Selous-Niassa TFCA from 1986 to 2016
  • estimate amount of trees loss of eastern Selous-Niassa TFCA from 1986 to 2016
  • analyse wood balance of corridor dwellers of eastern Selous-Niassa TFCA

1.4 Justification of the study
1.4.1 Significance of study findings: The Study findings will help stakeholders of Transfrontier Conservation Areas (TFCAs) especially Selous-Niassa TFCA to reveal problems of land uses facing them. These stakeholders include the public, researchers, natural resources extension officers, agriculturalists, policy makers, planners, decision makers, game wardens, park rangers, conservators and all other environmental related experts. Furthermore, the study findings will be useful to stakeholders for knowledge generation and proposing solutions at local, national and international levels on issues related to management of TFCAs. Additionally, the study findings will provide room to researchers for further studies.

1.4.2 Why study transfrontier conservation areas (TFCAs): Political boundaries that demarcate country borders were historically drawn for reasons based on national security and strategic interests, colonial land claims, geological and other riches, and convenience, never with conscious thought of maintaining ecological integrity. And so today a political map of the world shows continents carved into a jig-saw puzzle of countries, each with its own pattern of land use, political priorities, and management styles. Even so, historical coincidence has often left conservation areas in different countries adjoining each other, separated by fences or varying ideologies, resulting in fragmented ecosystems or disrupted ecosystem processes. The fragmented systems lead to a loss of ecological resilience and a steady attrition of species over time. By taking a broader view, a regional view, and jointly managing these natural assets for regional benefit, the cons caused by arbitrary political lines drawn for historical reason can be trounced. Ecological benefits; socio-economic and cultural benefits; collaboration and partnerships; and regional peace, harmony and stability are some of the benefits which can be resulted from collaboration across boundaries and adopting a regional approach in natural resource management.

1.4.3 Why study Selous? Niassa TFCA: The study was done in Selous-Niassa TFCA due to the following reason: (i) scanty information of study area interests which is eastern part of the corridor also known as Selous ?Masasi compared to western part; (ii) huge area coverage in Africa as the largest trans-boundary natural dry forest eco-regions covering approximately 154.000 km2 with a critical gap between these protected areas that stretches for about 120?180 km and extending across southern Tanzania and the Mozambique border. Through a network of protected areas of various categories of protection, an area of 110,000 km2 of this ecosystem is presently under conservation [5]; (iii) wildlife migration and richness as it constitutes one of the largest elephant ranges in the world and contains half of the world remaining wild dog population, supports a large number of other globally significant, threatened and CITES listed fauna and flora species [1]; (iv) there was no legal protection of wildlife corridors before enaction of wildlife Act of  2009; (v) there was no signed memorandum of understanding between Tanzania and Mozambique concerned protection of the ecosystem before May 2015; and (vi)  established wildlife management areas (WMAs) which act as a buffer zone to core protected areas to help conservation of wildlife corridor by involving local communities. WMAs established are bordering Selous, Msanjesi and Lukwika-Lumesule game reserves (MAGINGO WMA, NDONDA and MCHIMALU proposed WMAs respectively) within Liwale, Nachingwea/Masasi and Nanyumbu districts respectively in Tanzania whereas people are living inside Niassa national reserve in Mozambique [12].

Materials and Methods

2.1 Materials

2.1.1 Description of the study area: The study was carried out in eastern Selous-Niassa TFCA with an area of 1, 462, 560 hectares called Selous-Niassa wildlife corridor (SNWC) which extends across southern Tanzania into northern Mozambique between 10°S to 11° 40’S with north-south length of 160 to 180 km (Figure 1).  SNWC comprises of two parts, western part (administratively passes in Namtumbo and Tunduru Districts of Ruvuma regions in southern Tanzania) and eastern part (administratively passes in Liwale, Nachingwea, Masasi, and Nanyumbu Districts). This study concentrated in eastern part. In eastern SNWC, migration of elephants, buffalos and zebras has been observed [12, 13]. Two migratory routes have been identified as follows:
  • From Selous through Nahimba, Nakalonji, Mbondo, Kilimarondo, Matekwe and Kipindimbi proposed game reserve (GR) in Nachingwea District and then via Msanjesi, Mkumbalu, Sengenya, Nangomba and Nanyumbu in Nanyumbu District to Lukwika-Lumesule  GR and then crosses Ruvuma River to the Niassa GR.
  • From Selous to Kiegei, Namatumu, Kilimarondo in Nachingwea then along Mbangala and Lumesule rivers to Mchenjeuka and Mitanga in the Lukwika-Lumesule GR, from where they  cross the Ruvuma River to the Niassa Reserve.

These routes forms SNWC called Selous-Masasi corridor includes the Msanjesi (2,125 ha) and the Lukwika-Lumesule (44,420 ha) GRs in Masasi and Nanyumbu Districts respectively and areas of Liwale, Nachingwea, Masasi and Tunduru Districts.

image

Figure 1: The Map of the study area.

The study area comprise wildlife management areas (WMAs) bordering Selous, Msanjesi and Lukwika-Lumesule game reserves (MAGINGO WMA, NDONDA and MCHIMALU proposed WMAs respectively) which are within Liwale, Nachingwea/Masasi and Nanyumbu Districts respectively. In this study three villages namely Mpigamiti, Kilimarondo,  andMpombe within MAGINGO WMA and NDONDA and MCHIMALU proposed WMA were purposely selected for ground Truthing for the study.

2.2 Methods

Spatial data includes satellite images and digital elevation model (DEM) downloaded from USGS ? GLOVIS.

2.2.1 Data analysis: To analyse spatial and temporal changes in land use and land cover in easternSelous ? Niassa TFCA from 1986?2016.The land cover change detection analysis was conducted based on the following steps:

(i)Satellite image selection and acquisition: Appropriate satellite imagery acquisition was done with highly consideration of cloud cover, the seasonality and phonological effects [14]. Clouds free satellite images with the interval not less than five years from 1986 to 2016 (Table 1) were used in assessing temporal and spatial variation of land use/cover change in the study area.

Year

Satellite

Sensor

Path/Row

Acquisition date

Cloud cover (%)

1986

Landsat 5

TM (SAM)

166/67

19/8/1986

0

Landsat 5

TM (SAM)

166/68

30/9/1984

0

Landsat 5

TM (SAM)

167/67

21/8/1990

5

1997

Landsat 5

TM (SAM)

166/67

14/6/1997

7

Landsat 5

TM (SAM)

166/68

20/8/1998

8

Landsat 5

TM (SAM)

167/67

27/12/1996

7

2005

Landsat 5

TM (BUMPER)

166/67

10/10/2005

10

Landsat 5

TM (BUMPER)

166/68

23/6/2006

1

Landsat 5

TM (BUMPER)

167/67

30/8/20058

8

2016

Landsat 8

OLI-TIRS

166/67

8/10/2006

0.28

Landsat 8

OLI-TIRS

166/68

8/10/2016

0

Landsat 8

OLI-TIRS

167/67

13/9/2006

0.8

Table 1: Satellite Imagery Data.

Image Pre-processing: To ensure accurate identification of temporal changes and geometric compatibility with other sources of information, images were pre-processed whereby geo-correction was conducted to rectify precisely matching of images. Band stacking and Images enhancement was performed using different color composite band combination and its contrast was stretched from minimum to maximum to reinforce the visual interpretability of images. Images were registered to the UTM map coordinate system, Zone 36 South, Datum Arc 1960.

(ii)Preliminary image classification and ground trothing:Supervised image classification using Maximum Likelihood Classifier (MLC) was conducted to create base map. Data from ground truth were used to formulate and confirm different cover classes existing in the study area. Training sites were identified by inspecting an enhanced color composite

Supervised classification by using Semi-automatic Classification Plug-in (SCP) available in QGIS 2.12.1 was conducted. The process involved selection of regions of interest (ROI) on the image, which represent specific land classes to be mapped. During Supervised Classification, maximum of seven distinct land cover classes were identified (Table 3) which are; Closed woodland (CWD), Open woodland (OWD), Bushland (BS), Grassland (GL), Water (WTR), Built up area (BLT) and Cultivated land (CL).

(iii)Final image classification and accuracy assessment:Kappa coefficient statistics was used to assess the accuracy of final image classification.
Where N is the total number of sites in the matrix, r is the number of rows in the matrix,

image                                           ...................................(1)

  xii is the number in row i and column i, x+iis the total for row i, and xi+ is the total for column.

The classified maps show good agreement with the real world as indicated in Table 2.


Year

1986

1997

2005

2016

Overall accuracy (%)

98%

82%

89%

92%

Kappa statistic

0.97

0.79

0.92

0.91

Table 2: Accuracy assessment.

Land cover class

Description

Closed woodland

Area of land covered low density trees forming open habitat with plenty of sunlight and limited shade

Open woodland

Area of land covered with low density and scattered trees with crop cultivation activities

Bushland

Area dominated with bushes and shrubs

Grassland

Land area dominated by grasses

Water

Area within body of land, of variable size, filled with water, localized in a basin, which rivers flow into or out of them (Lake/Dam)

Built up area

Man made infrastructure (roads and buildings) and settlement

Cultivated land

Farm with crops and harvested cropland

Unclassified

Area with no input data or insufficient information which has been missed due to several reason including clouds, clouds shadow, darkness, and sensor dysfunctioning

Table 3: Land use/cover classification scheme.

(iv) Landuse and land covers change detection:Post classification comparison was used to quantify the extent of land cover changes over the period 1986 ? 2016. Post classification comparison sidesteps the difficulties associated with the analysis of the images that are acquired at different times of the year, or by different sensors and results in high change detection accuracy [15]. The estimation for the rate of change for the different land covers was computed based on the following formulas [11].

% cover change =  image                                           .............. (2)

Annual rate of changeimage                                           .............. (3)

 

% Annual rate of changeimage                           .............. (4)

 

Area i year xis the area of cover i at the first date,
Area i year x+1is the area of cover i at the second date,
image Area i year xis the total cover area at the first
tyears is the period in years between the first and second scene acquisition dates

(v) To estimate amount of trees loss of eastern Selous-Niassa TFCA from 1986 to 2016: Amount of land (in hectares) in the study area that has been converted from closed and open woodlands to other socio-economic activities was used to estimate number trees loss. The study area belongs to southern zone as classified by URT[7]. The  number of trees and volume per hectare of the distribution of forest and woody vegetation resources have been classified by employing methodology used by NAFORMA [7]of measuring all trees with Dbh of one cm and above as shown in table 4.

Districts

Average mean volume m3/ha

Average number of trees/ha

Liwale, Nachingwea & Nanyumbu

49.3

1,654

Table 4: Distribution of forests and woody vegetation resources of the study area.

(vi) To analyse wood balance of corridor dwellers of eastern Selous-Niassa TFCA: Current human population of corridor dwellers was estimated based on NBS(National Bureau of Statistics), 2012 census and computing average demand for wood compared with supply from the corridor ecosystem. The study employed NAFORMA [7]baseline information that estimates Tanzania’s average demand for wood is 1.39 m3/year/capita while the annual allowable cut (the sustainable supply) was estimated at 0.95 m3/year/capita.

Results and Discussion

3.1 Spatial and temporal changes in land use and land cover of eastern Selous-Niassa TFCA for period 1986 ? 2016
3.1.1 Land use and land cover assessment: The land use land cover maps for the year 1986, 1997, 2005 and 2016 are presented in Figures 2, 3, 4 and 5. Generally, the maps show variations in cover coverage between the three periods under consideration. Table 5 represents the spatial distribution of land use/cover coverage for the period between 1986 and 2016.

LULC

1986

1997

2005

2016

(Ha)

(%)

(Ha)

(%)

(Ha)

(%)

(Ha)

(%)

Closed woodland

227731

15.57

244348

16.71

103198

7.06

89923

6.15

Open woodland

402201

27.50

411211

28.12

288176

19.70

220217

15.06

Bushland

433706

29.65

333399

22.80

256911

17.57

480269

32.84

Grassland

394960

27.00

437621

29.92

515143

35.22

394461

26.97

Water

1431

0.10

790

0.05

906

0.06

646

0.04

Built up area

2532

0.17

3391

0.23

7623

0.52

8851

0.61

Cultivated land

0

0.00

31799

2.17

290602

19.87

268193

18.34

TOTAL

1462560

100

1462560

100

1462560

100

1462560

100

Table 5: Land use/cover area distribution between 1986 and 2016.

image
Figure 2:Land use/cover map for eastern Selous ? Niassa TFCA 1986.
image
Figure 3: Land use/cover map for eastern Selous ? Niassa TFCA 1997.
image
Figure 4: Land use/cover map for eastern Selous ? Niassa TFCA 2005.
image
Figure 5: Land use/cover map for eastern Selous ? Niassa TFCA 2016.

3.1.2 Land use/cover changes between 1986 and 2016: The extent of land use land cover change including area, percentage area change and percentage annual rate of change are summarised on Table 6. The increased and decreased amount is represented by positive signs (+) and (-) respectively.

LULC

1986 ? 1997

1997 ? 2005

2005 ? 2016

Area change (Ha)

Percentage change (%)

Annual Rate of Change (Ha/year)

Area change (Ha)

Percentage change (%)

Annual Rate of Change (Ha/year)

Area change (Ha)

Percentage change (%)

Annual Rate of Change (Ha/year)

CWD

-16617

-1.14

-1511

141150

9.65

11762

13275

0.91

1207

OWD

-9010

-0.62

-819

123035

8.41

10253

67959

4.65

6178

BS

100306

6.86

9119

76488

5.23

6374

-223357

-15.27

-20305

GL

-42661

-2.92

-3878

-77522

-5.30

-6460

120682

8.25

10971

WTR

641

0.04

58

-116

-0.01

-10

260

0.02

24

BLT

-860

-0.06

-78

-4232

-0.29

-353

-1228

-0.08

-112

CL

-31799

-2.17

-2891

-258803

-17.70

-21567

22409

1.53

2037

CWD = Closed woodland, OWD = Open woodland, BS = Bushland, GL = Grassland, WTR = Water, BLT = Built Up area, and CL = Cultivated land.
Table 6: Land use/cover change between 1986 and 2016.

The results (Table 6), indicate that for the period between 1986 and 1997 the area under closed woodland, open woodland, grassland, built up area, and cultivated land increases by 1.14%, 0.62%, 2.92%, 0.06%, and 2.17% respectively. Likewise, bushland and water decreased by 6.86 and 0.04 respectively. For the period between 1997 and 2005, the closed woodland, open woodland, and bushland declined by 9.65%, 8.41%, and 5.23% respectively. For the same period of time, grassland, water, built up area, and cultivated land increased by 5.3%, 0.01%, 0.29%, and 17.7% respectively. Moreover, for the period between 2005 and 2016, the closed woodland, open woodland, grassland, water, and cultivated area declined by 0.91%, 4.65%, 8.25%, 0.02% and 1.53% respectively. For the same period of time, bushland and built up area increased by 15.27% and 0.08% respectively.

As revealed in Table 6, the decrease of closed woodland, open woodland, and bushland from 1997 to 2016 might be due human encroachments for timber, firewood and medicine, noticeable felling of trees for expansion of agricultural farms; whereas during 1986 to 1997 the increase of the closed and open woodlands happened as a result of famous operation “Uhai” done national wide to curb antipoaching and illegal harvesting of forest and wildlife resources. Also, the cashewnuts cultivated land was included in woodlands and thickets because the land cover is uncertain for this.

Also, the results supported by group discussants during focus group discussions emphasized that, wildfire, cutting trees; drying up trees are serious problems in recent years due to expansion of simsim farming, livestock immigrants, and commercial logging and timbering.

3.1.3 Change detection of different land use/cover: The net change of each land use/cover category is presented in Figure 6, and the change detection matrix for the period between 1986 and 2015 is presented in Tables 7 to 9, clearly reflecting on the land use transformation in the study area.

image

Figure 6: Gain and looses by each land use category between 1986 and 2016.

Cover in 1986

Cover in 1997(Ha)

CWD

OWD

BS

GL

WTR

BLT

CL

TOTAL

CWD

113076

65719

15637

17197

0

225

1526

213379

OWD

81872

165795

68741

84577

31

772

5194

406982

BS

20562

91588

169619

146223

9

514

7452

435967

GL

28746

87920

78420

187456

131

1826

17493

401992

WTR

42

25

255

616

489

3

1

1431

BLT

35

141

707

1529

104

153

31

2701

CL

1

0

1

6

0

0

100

107

TOTAL

244334

411188

333381

437604

763

3492

31798

1462560

CWD = Closed woodland, OWD = Open woodland, BS = Bushland, GL = Grassland, WTR = Water, BLT = Built Up area, and CL = Cultivated land.
Table 7: Change detection matrix for the period of 1986 to 1997.

Cover in 1997

Cover in 2005 (Ha)

CWD

OWD

BS

GL

WTR

BLT

CL

TOTAL

CWD

35521

71673

33529

62757

0

479

40457

244416

OWD

21869

115440

43831

127066

1

1970

101009

411188

BS

32885

39815

102169

104523

6

1063

52920

333381

GL

12481

57906

74047

200868

450

3376

88469

437596

WTR

0

0

0

343

447

0

0

790

BLT

80

229

292

1830

2

167

791

3391

CL

356

3178

3029

17727

0

568

6939

31797

TOTAL

103193

288242

256897

515114

906

7623

290586

1462560

CWD = Closed woodland, OWD = Open woodland, BS = Bushland, GL = Grassland, WTR = Water, BLT = Built Up area, and CL = Cultivated land.
Table 8: Change detection matrix for the period of 1997 to 2005.


Cover in 2005

Cover in 2016

    CWD

OWD

BS

      GL

WTR

BLT

CL

TOTAL

CWD

30929

20520

24539

16728

9

135

10415

103275

OWD

23689

73670

83706

62077

8

835

44175

288160

BS

9899

33202

113970

70239

31

538

29019

256897

GL

14772

64418

168122

170195

269

3999

93340

515114

WTR

0

0

0

587

320

0

0

906

BLT

148

452

1740

2809

1

410

2062

7623

CL

10482

28025

88165

71805

8

2933

89167

290586

TOTAL

89918

220287

480242

394439

646

8850

268178

1462560

CWD = Closed woodland, OWD = Open woodland, BS = Bushland, GL = Grassland, WTR = Water, BLT = Built Up area, and CL = Cultivated land.
Table 9:Change detection matrix for the period of 2005 to 2016 (Ha).

3.2 Amount of trees loss in eastern Selous-Niassa TFCA from 1986 to 2016
Table 10 shows amount of trees loss in eastern Selous- Niassa TFCA from 1986 to 2016. The results show that, there are intercernal changes of tree loss/gain from 1986 to 2016. The results revealed gain of trees regenerated in the study area during the period 1986 ? 1997 with an average of 3.5 million trees per year. The reason behind the results might be due to low population of the area, inaccessible roads, low markets of valuable forests and wildlife resources from the study area, lack of policies for conservation and protection of forest and wildlife resources, and national wide operation “Uhai” which was done in this period. Moreover, there was rampant conversion of woodland the study area during the period 1997?2016 with average loss of 27 million trees per year. This implies that, the loss was due to other socio-economic activities which are environmental harmful but economic rewarding like commercial farming of simsim, cashewnuts, sesame, logging and timbering, artisanal mining, and livestock keeping/gathering. These activities involves clearance of woodlands by using fire and drying of standing trees to remove leaves so as to allow sunlight for crops farming and livestock gathering, and reducing tsetse infections.

Years

Total area converted (ha)

Total volume
Million m3

Number of trees loss/gain (in millions)

1986 ? 1997

- 25, 627

- 1.3

- 42

1997 ? 2005

+ 264, 184

+ 13.1

+ 437

2005 ? 2016

+ 81, 234

+ 4.0

+ 134

Total

+ 319, 791

+ 15.8

+ 529

Table 10: Amount of trees loss from 1986 to 2016.

3.3Wood balance of corridor dwellers of eastern Selous-Niassa TFCA
Existing amount of trees from 1986 to 2016 (Table 11) used to estimate wood balance by using estimated population of the study area in these periods.

Year

Total woodland area  (ha)

Total volume
Million m3

Number of trees
 (in millions)

Estimated human population

Wood balance
(trees/capita/year)

Wood balance
(m3/year/capita)

1986

629, 932

31.1

1041.9

312, 081

3339

99.7

1997

655, 559

32.3

1084.3

351, 866

3082

91.8

2005

391, 374

19.3

647.3

381, 229

1698

50.6

2016

310, 140

15.3

513

437, 921

1172

34.9

Table 11: Existing amount of trees from 1986 to 2016.

The results reveled in Table 11 above shows that, wood supply in the study area for the year 2016 is at least 25 times the average demand per year per capita. This implies that the area is still virgin interms of wood balance that means wildlife habitat is still intact. However, the trend of wood supply from 1986 to 2016 shows dramatic deforestation of the area which implies tragedy of common and is the public property where there is no control policies or rules. The emergence of reviewing management and conservation strategies is unexceptional if we need sustainability of Selous-Niassa TFCA.

Conclusion and Recommendations

4.1 Conclusion
This study analysed land use and land cover changes in eastern Selous ? Niassa TFCA. The findings have revealed that the study area has undergone notable changes in terms of land use and land cover for the period between 1986 and 2016. Local knowledge revealed various factors associated to land use and cover change that includes fire, cultivation, and deforestation. The main factors mentioned as contributing to fire were beekeeping, hunting activities, and local beliefs, while for deforestation include commercial logging and timbering, charcoals production, population growth, expansion of commercial farming and food crops production.

The results indicate that land use and land cover change has a significant impact to the management of biodiversity and maintaining ecosystem services of the TFCA. The greater increase of land use conversion alters wildlife movements, gene flow and stochastic events like fire and climate change. The study concludes that the modification of the land use and cover has resulted in behavioral changes of some wild animals due to changes of their habitats. The study highlights the effects of land use and land-cover changes on number of trees loss and wood balance of the corridor dwellers which shows unsustainable supply.

4.2 Recommendations
The study provides the following recommendations for sustainable management and conservation of eastern Selous ? Niassa TFCA:

  • Formulate user friendly guidelines for protection of wildlife corridors as stipulated in Tanzania Wildlife Conservation Act No. 5 of 2009;
  • Formulate new and enhancing existing wildlife management areas (WMAs), participatory forests managements (PFMs) and joint forests managements (JFMs) so as accrued benefits should be higher than protection costs of the existing resources;
  • Formulate land use plans of the corridors so as to protect wildlife routes within the corridors;
  • Usage of alternatives wood resources so as offset the supply deficit and attain sustainability.
  • Disclosures

The authors declare that there is no conflict of interest regarding the publication of this paper

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