Vegetation dynamics in response to human and climatic factors in the Tanzanian Coast

Abstract

This study of vegetation dynamics in the coastal region of Tanzania provides a fundamental basis to better understand the nature of the factors that underlie observed changes. The Tanzanian coast, rich in biodiversity, is economically and environmentally important although the understanding of the nature and causes of vegetation change is very limited. This paper presents an investigation of the relationship between vegetation dynamics in response to climate variations and human activities using Moderate Resolution Imaging Spectroradiometer (MODIS), Normalized Difference Vegetation Index (NDVI), meteorological, and Globeland30 Landsat data sets. Spatio-temporal trends and the relationship of NDVI to selected meteorological variables were statistically analyzed for the period 2000–2018 using the Mann-Kendall test and Pearson correlation respectively. The results reveal a significant positive trend in temperature (β>0, Z = 2.87) and a non-significant trend in precipitation (|Z|<1.96). A positive relationship between NDVI and precipitation is observed. Coastal Tanzania has therefore experienced increased temperatures and variable moisture conditions which threaten natural vegetation and ecosystems at large. Classified land cover maps obtained from GlobeLand30 were analyzed to identify the nature and scale of human impact on the land. The analysis of land use and land cover in the region reveals an increase in cultivated land, shrubland, grassland, built-up land and bare land, while forests, wetland and water all decreased between 2000 and 2020. The decrease in forest vegetation is attributable to the fact that most livelihoods in the region are dependent on agriculture and harvesting of forest products (firewood, timber, charcoal). The findings of this study highlight the need for appropriate land-use planning and sustainable utilization of forest resources.

Graphical abstract

Keywords

remote sensing / NDVI / climate variations / spatio-temporal changes / LULCC / coastal Tanzania

References

[1] Abonyo C, Isabirye M, Mfitumukiza D, Magunda M, Poesen J, Deckers J, Kasedde A C (2007). Land use change and local people’s perception of the effects of change in Ssese islands, Uganda. National Agricultural Research Organisation, Uganda, 1–25

[2] Aheto D W, Kankam S, Okyere I, Mensah E, Osman A, Jonah F E, Mensah J C (2016). Community-based mangrove forest management: implications for local livelihoods and coastal resource conservation along the Volta estuary catchment area of Ghana. Ocean Coast Manage, 127: 43–54

[3] Cao R, Jiang W, Yuan L, Wang W, Lv Z, Chen Z (2014). Inter-annual variations in vegetation and their response to climatic factors in the upper catchments of the Yellow River from 2000 to 2010. J Geogr Sci, 24(6): 963–979

[4] Chang’a L B, Yanda P Z, Ngana J (2010). Spatial and temporal analysis of recent climatological data in Tanzania. J Geogr Reg Plan, 3(3): 44–65

[5] Chen J, Cao X, Peng S, Ren H (2017). Analysis and applications of GlobeLand30: a review. ISPRS Int J Geoinf, 6(8): 230

[6] Choumert-Nkolo J (2018). Developing a socially inclusive and sustainable natural gas sector in Tanzania. Energ Policy, 118: 356–371

[7] Cockx L, Colen L, De Weerdt J, Gomez Y, Paloma S (2019). Urbanization as a driver of changing food demand in Africa: evidence from rural-urban migration in Tanzania. JRC 107918. Luxembourg: Publications Office of the European Union

[8] Cui L, Wang L, Singh R P, Lai Z, Jiang L, Yao R (2018). Association analysis between spatiotemporal variation of vegetation greenness and precipitation/temperature in the Yangtze River Basin (China). Environ Sci Pollut Res Int, 25(22): 21867–21878

[9] Daham A, Han D, Rico-Ramirez M, Marsh A (2018). Analysis of NDVI variability in response to precipitation and air temperature in different regions of Iraq, using MODIS vegetation indices. Environ Earth Sci, 77(389): 1–24

[10] Danladi I B, Kore B M, Gül M (2017). Vulnerability of the Nigerian coast: an insight into sea level rise owing to climate change and anthropogenic activities. J Afr Earth Sci, 134: 493–503

[11] Detsch F, Otte I, Appelhans T, Hemp A, Nauss T (2016). Seasonal and long-term vegetation dynamics from 1-km GIMMS-based NDVI time series at Mt. Kilimanjaro, Tanzania. Remote Sens Environ, 178: 70–83

[12] Dubayah R, Blair J B, Goetz S, Fatoyinbo L, Hansen M, Healey S, Hofton M, Hurtt G, Kellner J, Luthcke S, Armston J, Tang H, Duncanson L, Hancock S, Jantz P, Marselis S, Patterson P L, Qi W, Silva C (2020). The global ecosystem dynamics investigation: high-resolution laser ranging of the Earth’s forests and topography. Sci Remote Sens, 1: 100002

[13] Eludoyin O, Wokocha C, Ayolagha G (2011). GIS assessment of land use and land cover changes in OBIO/AKPOR LGA, Rivers State, Nigeria. Res J Environ Earth Sci, 3(4): 307–313

[14] Fensholt R, Proud S R (2012). Evaluation of earth observation based global long term vegetation trends—comparing GIMMS and MODIS global NDVI time series. Remote Sens Environ, 119: 131–147

[15] Funk C, Husak G J, Michaelsen J, Shukla S, Hoell A, Lyon B, Hoerling M P, Liebmann B, Zhang T, Verdin JGalu G, Eilerts G, Rowland (2013). Attribution of 2012 and 2003–12 rainfall deficits in eastern Kenya and southern Somalia. In: Explaining Extreme Events of 2012 from a Climate Perspective. Peterson T C, Hoerling M P, Stott P A, Herring S C, eds., Bull Am Meteorol Soc, 94(9): S45–S48

[16] Gorelick N, Hancher M, Dixon M, Ilyushchenko S, Thau D, Moore R (2017). Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sens Environ, 202: 18–27

[17] Hassan I H, Mdemu M V, Shemdoe R S, Stordal F (2014). Drought pattern along the coastal forest zone of Tanzania. Atmos Clim Sci, 4(03): 369–384

[18] Hosonuma N, Herold M, De Sy V, De Fries R S, Brockhaus M, Verchot L, Angelsen A, Romijn E (2012). An assessment of deforestation and forest degradation drivers in developing countries. Environ Res Lett, 7(4): 044009

[19] Huang F, Mo X, Lin Z, Hu S (2016). Dynamics and responses of vegetation to climatic variations in Ziya-Daqing basins, China. Chin Geogr Sci, 26(4): 478–494

[20] Idukunda C, Haule C B M, Nahayo L (2020). Vulnerability of coastal vegetation to human activities in Tanzania. Am J Geophys Geochem Geosyst, 6(3): 74–81

[21] Igbawua T, Zhang J, Chang Q, Yao F (2016). Vegetation dynamics in relation with climate over Nigeria from 1982 to 2011. Environ Earth Sci, 75(6): 518

[22] IPCC (2 014 a). Climate Change 2014: Synthesis Report. In: Core Writing Team, Pachauri R K, Meyer L A, eds. Contribution of Working Groups I, II and III to the Fifth Assessment Report of Intergovernmental Panel on Climate Change. IPCC, Geneva, Switzerland

[23] IPCC (2014b). Summary for Policymakers. In: Edenhofer O R, Pichs-Madruga Y, Sokona E, Farahani S, Kadner K, Seyboth A, Adler I, Baum S, Brunner P, Eickemeier B, Kriemann J, Savolainen S, Schlömer C, von Stechow T, Zwickel J, Minx C, eds. Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press

[24] Jones P (2017). Formalizing the informal: Understanding the position of informal settlements and slums in sustainable urbanization policies and strategies in Bandung, Indonesia. Sustainability, 9(8): 1436

[25] Kashaigili J, Levira P, Liwenga E, Mdemu M (2014). Analysis of climate variability, perceptions and coping strategies of Tanzanian coastal forest dependent communities. Am J Clim Chan, 3, 212–222

[26] Kebede A S, Nicholls R J (2012). Exposure and vulnerability to climate extremes: population and asset exposure to coastal flooding in Dar es Salaam, Tanzania. Reg Environ Change, 12(1): 81–94

[27] Kijazi A L, Reason C (2005). Relationships between intraseasonal rainfall variability of coastal Tanzania and ENSO. Theor Appl Climatol, 82(3–4): 153–176

[28] Kijazi A L, Reason C (2009). Analysis of the 1998 to 2005 drought over the northeastern highlands of Tanzania. Clim Res, 38(3): 209–223

[29] Kimaro J, Lulandala L (2013). Human influences on tree diversity and composition of a coastal forest ecosystem: the case of Ngumburuni Forest Reserve, Rufiji, Tanzania. Int J For Res, 2013: 305874, 1–7

[30] Kirui K, Kairo J, Bosire J, Viergever K, Rudra S, Huxham M, Briers R (2013). Mapping of mangrove forest land cover change along the Kenya coastline using Landsat imagery. Ocean Coast Manage, 83: 19–24

[31] Lambin E F, Geist H J (2006). Land-Use and Land-Cover Change: Local Processes and Global Impacts. Berlin Heidelberg: Springer-Verlag

[32] Liu Q, Yang Z, Han F, Wang Z, Wang C (2016). NDVI-based vegetation dynamics and their response to recent climate change: a case study in the Tianshan Mountains, China. Environ Earth Sci, 75(16): 1189

[33] López-Carr D, Pricope N G, Aukema J E, Jankowska M M, Funk C, Husak G, Michaelsen J (2014). A spatial analysis of population dynamics and climate change in Africa: potential vulnerability hot spots emerge where precipitation declines and demographic pressures coincide. Popul Environ, 35(3): 323–339

[34] Lyimo J G, Ngana J O, Liwenga E, Maganga F (2013). Climate change, impacts and adaptations in the coastal communities in Bagamoyo District, Tanzania. Environ Econ, 4(1): 63–71

[35] Masalu D C (2000). Coastal and marine resource use conflicts and sustainable development in Tanzania. Ocean Coast Manage, 43(6): 475–494

[36] Matsa M, Muringaniza K (2011). An assessment of the land use and land cover changes in Shurugwi District, Midlands Province, Zimbabwe. Ethiop J Environ Stud Manag, 4(2): 88–100

[37] Mberego S, Sanga-Ngoie K, Kobayashi S (2013). Vegetation dynamics of Zimbabwe investigated using NOAA-AVHRR NDVI from 1982 to 2006: a principal component analysis. Int J Remote Sens, 34(19): 6764–6779

[38] Mligo C (2011). Anthropogenic disturbance on the vegetation in Makurunge woodland, Bagamoyo district, Tanzania. Tanzan J Sci, 37: 94–108

[39] Mongi H, Majule A E, Lyimo J G (2010). Vulnerability and adaptation of rain fed agriculture to climate change and variability in semi-arid Tanzania. Afr J Environ Sci Technol, 4(6): 371–381

[40] NBS and OCGS (2013). 2012 Population and Housing Census: Population Distribution by Administrative Areas. National Bureau of Statistics (NBS), Ministry of Finance, Dar es Salaam and Office of Chief Government Statistician (OCGS), President’s Office, Finance, Economy and Development Planning, Zanzibar, The United Republic of Tanzania

[41] Nordic Development Fund (2014). Coastal Profile for Tanzania 2014. In: Investment Prioritization for Resilient Livelihoods and Ecosystems in Coastal Zones of Tanzania. Volume IV—Mitigation of Threats. Helsinki: Nordic Development Fund

[42] Nwaga D, Jansa J, Angue M A, Frossard E (2010). The potential of soil beneficial micro-organisms for slash-and-burn agriculture in the Humid Forest Zone of Sub-Saharan Africa. In: Dion P, ed. Soil Biology and Agriculture in the Tropics. Soil Biology 21, Berlin Heidelberg: Springer, 81–107

[43] Pacheco F A L, Sanches Fernandes L F, Valle Junior R F, Valera C A, Pissarra T C T (2018). Land degradation: multiple environmental consequences and routes to neutrality. Curr Opin Environ Sci Health, 5: 79–86

[44] Park S, Kang D, Yoo C, Im J, Lee M I (2020). Recent ENSO influence on East African drought during rainy seasons through the synergistic use of satellite and reanalysis data. ISPRS J Photogramm Remote Sens, 162: 17–26

[45] Patel N N, Angiuli E, Gamba P, Gaughan A, Lisini G, Stevens F R, Tatem A J, Trianni G (2015). Multitemporal settlement and population mapping from Landsat using Google Earth Engine. Int J Appl Earth Obs Geoinf, 35: 199–208

[46] Rautiainen A, Virtanen T, Kauppi P E (2016). Land cover change on the Isthmus of Karelia 1939–2005: agricultural abandonment and natural succession. Environ Sci Policy, 55: 127–134

[47] Reddy D S, Prasad P R C (2018). Prediction of vegetation dynamics using NDVI time series data and LSTM. Model Earth Syst Environ, 4(1): 409–419

[48] Ricci L (2012). Peri-urban livelihood and adaptive capacity: urban development in Dar es Salaam. Consilience. J Sustain Dev, 7(1): 46–63

[49] Richard Y, Poccard I (1998). A statistical study of NDVI sensitivity to seasonal and interannual rainfall variations in Southern Africa. Int J Remote Sens, 19(15): 2907–2920

[50] Robbins G, Perkins D (2012). Mining FDI and infrastructure development on Africa’s East Coast: examining the recent experience of Tanzania and Mozambique. J Int Dev, 24(2): 220–236

[51] Saha D, Sundriyal R (2012). Utilization of non-timber forest products in humid tropics: implications for management and livelihood. For Policy Econ, 14(1): 28–40

[52] Sarakikya H, Ibrahim I, Kiplagat J (2015). Renewable energy policies and practice in Tanzania: their contribution to Tanzania economy and poverty alleviation. Int J Energ Power Eng, 4(6): 333–341

[53] Sen P K (1968). Estimates of the regression coefficient based on Kendall’s Tau. J Am Stat Assoc, 63(324): 1379–1389

[54] Shackleton S, Delang C O, Angelsen A (2011). From subsistence to safety nets and cash income: exploring the diverse values of non-timber forest products for livelihoods and poverty alleviation. In: Shackleton S, Shackleton C, Shanley P, eds. Non-Timber Forest Products in the Global Context. Tropical Forestry 7. Berlin Heidelberg: Springer, 55–81

[55] Shukla S, McNally A, Husak G, Funk C (2014). A seasonal agricultural drought forecast system for food-insecure regions of East Africa. Hydrol Earth Syst Sci, 18(10): 3907–3921

[56] Sruthi S, Aslam M M (2015). Agricultural drought analysis using the NDVI and land surface temperature data; a case study of Raichur district. Aquat Procedia, 4: 1258–1264

[57] Sun Y, Yang Y, Zhang Y, Wang Z (2015). Assessing vegetation dynamics and their relationships with climatic variability in northern China. Phys Chem Earth Parts ABC, 87–88: 79–86

[58] Sutton P C, Anderson S J, Costanza R, Kubiszewski I (2016). The ecological economics of land degradation: impacts on ecosystem service values. Ecol Econ, 129: 182–192

[59] Sweya L N, Wilkinson S, Chang-Richard A (2018). Understanding water systems resilience problems in Tanzania. Procedia Eng, 212: 488–495

[60] Theil H (1950). A rank invariant method of linear and polynomial regression analysis, I, II, III. In: Proceedings of the Koninklijke Nederlandse Akademie Wetenschappen, Series. Math Sci, 53: 386–392, 521–525, 1397–1412

[61] Wang J, Rich P M, Price K P (2003a). Temporal responses of NDVI to precipitation and temperature in the central Great Plains, USA. Int J Remote Sens, 24(11): 2345–2364

[62] Wang Y, Bonynge G, Nugranad J, Traber M, Ngusaru A, Tobey J, Hale L, Bowen R, Makota V (2003b). Remote sensing of mangrove change along the Tanzania coast. Mar Geod, 26(1–2): 35–48

[63] Williams D S, Máñez Costa M, Sutherland C, Celliers L, Scheffran J (2019). Vulnerability of informal settlements in the context of rapid urbanization and climate change. Environ Urban, 31(1): 157–176

[64] Zhang H, Chang J, Zhang L, Wang Y, Li Y, Wang X (2018). NDVI dynamic changes and their relationship with meteorological factors and soil moisture. Environ Earth Sci, 77(16): 582

[65] Zhao L, Dai A, Dong B (2018). Changes in global vegetation activity and its driving factors during 1982–2013. Agric Meteorol, 249: 198–209

[66] Kashaigili J, Levira P, Liwenga E, Mdemu M (2014). Analysis of climate variability, perceptions and coping strategies of Tanzanian coastal forest dependent communities. Am J Clim Chan, 3: 212–222

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