Vegetation phenology dynamics as an indicator of energy and productivity functions in semi-arid savannah protected areas: a case study of Gonarezhou National Park in south-eastern Zimbabwe

REFERENCES

• Adole, T., Atkinson, P.M. & Dash, J. 2016. A systematic review of vegetation phenology in Africa. Ecological Informatics 34: 117–128.
   Web of Science ®Google Scholar
• Archibold, S. & Scholes, R.J. 2007. Leaf green-up in a semi- arid savanna separating tree and grass responses to environmental cues. Journal of Vegetation Science 18: 583–594.
   Web of Science ®Google Scholar
• Ariano, O., Ramos, P.J.J., Kalogirou, V., Bontemps, S., Defourny, P. & Van Bogaert, E. 2012. Global Land Cover Map for 2009 (GlobCover 2009). Pangea: European Space Agency and Universite Catholique de Louvain (UCL).
   Google Scholar
• Beck, P.S.A. & Goetz, S. 2011. Satellite observations of high Northern latitude vegetation productivity changes between 1982 and 2008: ecological variability and regional differences. Environmental Research Letters 6: 1–15.
   Web of Science ®Google Scholar
• Braget, A.R. 2017. Time series analysis of phenometrics and long-term vegetation trends for the Flint Hills ecoregion using moderate resolution satellite imagery. MA Thesis., Kansas State University.
   Google Scholar
• Carlson, T.N. & Ripley, D.A. 1997. On the relation between NDVI fractional vegetation cover and leaf area index. Remote Sensing of Environment 62: 241–252.
   Web of Science ®Google Scholar
• Chen, J.M. & Black, T.A. 1992. Defining leaf area index for non-flat leaves. Plant, Cell and Environment 15: 421–429.
   Web of Science ®Google Scholar
• Cho, M.A., Ramoelo, A. & Dziba, L. 2017. Response of land surface phenology to variation in tree cover during green-up and senescence periods in the semi-arid savanna of Southern Africa. Remote Sensing 9: 1–19.
   Web of Science ®Google Scholar
• Clegg, B.W. & O’connor, T.G. 2012. The vegetation of Malilangwe wildlife reserve, South-Eastern Zimbabwe. African Journal of Range and Forage Science 29: 109–131.
   Web of Science ®Google Scholar
• Cunliffe, R., Muller, T. & Mapaura, A. 2012. Vegetation Survey of Gonarezhou National Park, Zimbabwe. Chiredzi: Parks &Wildlife Management Authority and Frankfurt Zoological Society.
   Google Scholar
• Davis, C.L., Hoffman, M.T. & Roberts, W. 2017. Long term trends in vegetation phenology and productivity over Namaqualand using GIMMS AVHRR NDVI3g data from 1982–2011. South African Journal of Botany 111: 76–85.
   Web of Science ®Google Scholar
• Davis-Reddy, C. 2018. Assessing vegetation dynamics in response to climate variability and change across Sub-Saharan Africa. DPhil. Thesis., Stellenbosch University.
   Google Scholar
• Dunham, K.M. & Gandiwa, E. 2009. Aerial Survey of Elephants and Other Large Herbivores in Gonarezhou National Park (Zimbabwe), Zinave National Park (Mozambique) and surrounds: 2009 Report. Chiredzi: Parks &Wildlife Management Authority and Frankfurt Zoological Society.
   Google Scholar
• Dunham, K.M., Van Der Westhuzein, E., Van Der Westhuzein, H.F. & Ndaimani, H. 2013. Aerial Survey of Elephants and Other Large Herbivores in Gonarezhou National Park (Zimbabwe) and Surrounding Areas: 2013 Report. Chiredzi: Parks &Wildlife Management Authority and Frankfurt Zoological Society.
   Google Scholar
• Dye, D.G., Middleton, B.R., Vogel, J.M., Wu, Z. & Velasco, M. 2016. Exploiting differential vegetation phenology for satellite-based mapping of semiarid grass vegetation in the southwestern United States and Northern Mexico. Remote Sensing 8: 1–33.
   Web of Science ®Google Scholar
• Eklundh, L. & Jonsson, P. 2017. TIMESAT 3.3 with Seasonal Trend Decomposition and Parrallel Processing Software Manual. Malmo University.
   Google Scholar
• Fernandez, M., Gill, M. & Skidmore, E. 2017. Monitoring Key EBV with Remote Sensing. (Eds. GOFC-GOLD) A Sourcebook of Methods and Procedures for Monitoring Essential Biodiversity Variables in Tropical forests with Remote Sensing. Wageningen.
   Google Scholar
• Frouin, R. 1993. Estimating photosynthetically available radiation (PAR) at the earth’s surface from satellite observations. Remote Sensing Environment 94: 1–18.
   Google Scholar
• Gandiwa, E. 2011. Preliminary assessment of illegal hunting by communities adjacent to the Northern Gonarezhou National Park, Zimbabwe. Tropical Conservation Science 4: pp. 445–467.
   Web of Science ®Google Scholar
• Gandiwa, E. 2013.Vegetation factors influencing density and distribution of wild large herbivores in Southern African savanna. African Journal of Ecology 52: 274–283.
   Web of Science ®Google Scholar
• Gandiwa, E., Heitkonig, I.M.A., Gandiwa, P., Matsvayi, W., Van Der Westhuizen, H. & Ngwenya, M.M. 2013. Large herbivore dynamics in Northern Gonarezhou National Park, Zimbabwe. Tropical Ecology 54: 345–354.
   Web of Science ®Google Scholar
• Gandiwa, P., Matsvayi, W., Ngwenya, M.M. & Gandiwa, E. 2011. Assessment of livestock and human settlement encroachment into the Northern Gonarezhou National Park, Zimbabwe. Journal of Sustainable Development in Africa 13: 19–33.
   Google Scholar
• Guan, K., Wood, E.F., Medvigy, D., Kimball, J., Pan, M., Caylor, K.K., Sheffield, J., Xu, X. & Jones, M.O. 2014. Terrestrial hydrological controls on land surface phenology of African savannas and woodlands: hydrology controls on African phenology. Journal of Geophysical Research: Biogeosciences 119: 1652–1669.
   Web of Science ®Google Scholar
• Jeganathan, C., Dash, J. & Atkinson, M. 2010. Mapping the phenology of natural vegetation in India using a remote sensing derived chlorophyll Index. International Journal of RS 31: 5777–5796.
   Web of Science ®Google Scholar
• Knyazikhin, Y., Martonchik, J.V., Diner, D.J., Myneni, R.B. & Running, S.W., 1998. Synergistic algorithm for estimating vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from MODIS and MISR data. Journal of Geophysical Research: Atmospheres 103: 32257–32275.
   Web of Science ®Google Scholar
• Knyazikhin, Y., Martonchik, J.V., Diner, D.J., Myneni, R.B., Verstracte, M., Pinty, B. & Gobron, N. 1998. Estimation of vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from atmosphere-corrected MISR data. Journal of Geophysical Research: Atmospheres 103: 32239–32256.
   Web of Science ®Google Scholar
• Markon, C.J. & Peterson, K.M. 2010. The utility of estimating net primary productivity over Alaska using baseline AVHRR data. International Journal of Remote Sensing 23: 4571–4596.
   Google Scholar
• Martin, F., Cunliffe, R., Farcomeni, A., De Sanctis, M., D’ammando, G. & Attore, F. 2016. Classification and mapping of the woody vegetation of Gonarezhou National Park, Zimbabwe. Koedoe 58: 1–10.
   Web of Science ®Google Scholar
• Militino, A.F., Ugarte, M.D. & Perez-Goya, U. 2017. Stochastic spatio-temporal models for analysing NDVI distribution of GIMMS NDVI3g images. Remote Sensing 9: 1–17.
   Web of Science ®Google Scholar
• More, R.S., Manjunath, K.R., Jain, N.K., Panigrahy, S. & Parihar, J.S. 2016. Derivation of rice crop calendar and evaluation of crop phenometrics and latitudinal relationship for major south and south-east Asian countries: a remote sensing approach. Computers and Electronics in Agriculture 127: 336–350.
   Web of Science ®Google Scholar
• Olsen, J. L., Miehe, S., Cecato, P. & Fensholt, R., 2015. Does EO NDVI seasonal metrics capture variations in species composition and biomass due to grazing in Semi-arid grassland Savannas? Biogeosciences 12: 4407–4419.
   Web of Science ®Google Scholar
• Pachavo, G., 2013. Remote sensing patterns of net primary productivity in the Great Limpopo Transfrontier Conservation Area (GLTFCA) in relation to land use and land tenure. MPhil thesis. Harare, University of Zimbabwe.
   Google Scholar
• Park, T., Ganguly, S., Tommervik, H., Euskirchen, E.S., Hogda, K., Karlsen, S.R., Brovkin, V., Nemani, R.R. & Myneni, R.B. 2016. Changes in growing season duration and productivity of Northern vegetation inferred from long term remote sensing data. Environmental Letters 11: 1–11.
   Google Scholar
• Pettorelli, N., Vik, J.O., Mysterud, A., Gaillard, J.M., Tucker, C.J., & Stenseth, N.C.H.R. 2005. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology & Evolution 20: 503–510.
   PubMed Web of Science ®Google Scholar
• Pinzon, J.E. & Tucker, J.C. 2014. A non-stationary 1981–2012 AVHRR NDVI3g time series. Remote Sensing 6: 6929–6960.
   Web of Science ®Google Scholar
• Prasad, V.K., Badarinath, K.V.S. & Euture, A. 2007. Spatial patterns of vegetation phenology metrics and related climatic controls of eight contrasting forest types in India- Analysis from remote sensing datasets. Theoretical and Applied Climatology 89: 95–107.
   Web of Science ®Google Scholar
• Rossini, M., Cogliati, S., Meroni, M., Migliavacla, M., Gaivagno, M., Busetto, L., Cremonese, E., Julitta, T., Siniscieco, C., Mora Di Cella, U. & Colombo, R. 2012. Remote sensing-based estimation of gross primary production in a subalpine grassland. Biogeosciences 9: 2565–2584.
   Web of Science ®Google Scholar
• Senna, M.C.A., Costa, M.H. & Shimabukuro, Y.E. 2006. Fraction of photosynthetically active radiation absorbed by amazon tropical forest: a comparison of field measurements, modeling and remote sensing. Journal of Geophysical Research 110: 1–8.
   Web of Science ®Google Scholar
• Tafangenyasha, C. 1997. Tree loss in the Gonarezhou National Park (Zimbabwe) between 1970 and 1983. Journal of Environmental Management 49(3): 355–366.
   Web of Science ®Google Scholar
• Tan, B., Morisette, J., Wolfe, R., Esaias, W., Gao, Ederer, G., Nightangle, J., Nickeson, J.E., Ma, P. & Pedely, J. 2008. Vegetation phenology metrics derived from temporally smoothed and gap-filled MODIS data. 2008 IEEE International Geoscience and Remote Sensing Symposium. Boston, MA: IEEE, pp. 593–596.
   Google Scholar
• Tong, S., Zhang, J., Bao, Y., Wurena, Terigele, Walesi & Lianxiao, 2017. Spatial and temporal variations of vegetation cover and the relationships with climate factors in Inner Mongolia based on GIMMS NDVI3g data. Journal of Arid Land 9: 394–407.
   Web of Science ®Google Scholar
• Uyeda, K.A., Stow, D.A., Roberts, D.A. & Riggan, P.J. 2017. Combining ground based measurements and MODIS-based spectral vegetation indices to track biomass accumulation in post-fire Chaparral. International Journal of Remote Sensing 38: 728–741.
   Web of Science ®Google Scholar
• Wang, J., Dong, J., Liu, J., Huang, M., Li, G., Running, S.W., Smith, W.K., Harris, W., Saigusa, N., Kondo, H., Liu, Y., Hirano, T. & Xiao, X. 2014. Comparison of gross primary productivity derived from GIMMS NDVI3g, GIMMS, and MODIS in Southeast Asia. Remote Sensing 6: 2108–2133.
   Web of Science ®Google Scholar
• Wang, L. & Fensholt, R. 2017. Temporal changes in coupled vegetation phenology and productivity are biome-specific in the Northern hemisphere. Remote Sensing 9: 1–19.
   Web of Science ®Google Scholar
• Wang, J., Rich, P.M., Price, K.P. & kettle, W.K. 2004. Relations between NDVI and tree productivity in the central Great Plains. International Journal of Remote Sensing 25: 3127–3138.
   Web of Science ®Google Scholar
• Weiss, J.L., Guzler, D.S., Julia, E., Coonrod, A. & Dahm, C.N. 2004. Long-term vegetation monitoring with NDVI in a diverse semi-arid setting, central New Mexico, USA. Journal of Arid Environments 58: 249–272.
   Web of Science ®Google Scholar
• Wessels, K., Steenkamp, K., Von Maltitz, G. & Archibald, G. 2008. Modelling vegetation phenology from 20 years daily satellite data. Sciencescope. 1–5.
   Google Scholar
• Wessels, K., Steenkamp, K., Von Maltitz, G. & Archibald, S. 2011. Remotely sensed vegetation phenology for describing and predicting the biomes of South Africa. Applied Vegetation Science 14: 49–66.
   Web of Science ®Google Scholar
• Zhu, W., Chen, G., Hayes, D.J., Fan, D. & Jiang, N. 2017. Vegetation phenology. In GOFC-GOLD-GEO BON (Eds.). A Sourcebook of Methods and Procedures for Monitoring Essential Biodiversity Variables in Tropical Forests with Remote Sensing. Wageningen, 26–51.
   Google Scholar
• Zhu, Q., Zhao, J., Zhu, Z., Zhang, H., Zhang, Z., Guo, X., Bi, Y. & Sun, L. 2017. Remotely sensed estimation of net primary productivity (NPP) and its spatial and temporal variations in the Greater Khingan Mountain region, China. Sustainability 9: 1–16.
   Web of Science ®Google Scholar