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

Herrieth MACHIWA, Bo TIAN, Dhritiraj SENGUPTA, Qian CHEN, Michael MEADOWS, Yunxuan ZHOU

PDF(1202 KB)
PDF(1202 KB)
Front. Earth Sci. ›› 2021, Vol. 15 ›› Issue (3) : 595-605. DOI: 10.1007/s11707-021-0916-7
RESEARCH ARTICLE
RESEARCH ARTICLE

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

Author information +
History +

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

Cite this article

Download citation ▾
Herrieth MACHIWA, Bo TIAN, Dhritiraj SENGUPTA, Qian CHEN, Michael MEADOWS, Yunxuan ZHOU. Vegetation dynamics in response to human and climatic factors in the Tanzanian Coast. Front. Earth Sci., 2021, 15(3): 595‒605 https://doi.org/10.1007/s11707-021-0916-7

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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[6]
Choumert-Nkolo J (2018). Developing a socially inclusive and sustainable natural gas sector in Tanzania. Energ Policy, 118: 356–371
CrossRef Google scholar
[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
CrossRef Pubmed Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[53]
Sen P K (1968). Estimates of the regression coefficient based on Kendall’s Tau. J Am Stat Assoc, 63(324): 1379–1389
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[59]
Sweya L N, Wilkinson S, Chang-Richard A (2018). Understanding water systems resilience problems in Tanzania. Procedia Eng, 212: 488–495
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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

Acknowledgments

This work was funded by the National Natural Science Foundation of China (Grant No. 41476151) and “China-Africa Universities 20+20 Cooperation Plan” by the Ministry of Education of China. We gratefully acknowledge Prof. Jun Chen and Dr. Shu Peng from the National Geomatics Centre of China for the provision of their processed remote sensing data. We also appreciate all sort of assistance given by our colleagues, as well as their valuable suggestions which helped in improving the manuscript. The first author wishes to thank the Chinese Scholarship Council for sponsoring her studies in China.

Electronic supplementary material

ƒis available in the online version of this article at http:/dx./doi.org/10.1007/s11707-021-0916-7 and is accessible for authorized users.

RIGHTS & PERMISSIONS

2021 Higher Education Press
AI Summary AI Mindmap
PDF(1202 KB)

Accesses

Citations

Detail

Sections
Recommended

/