Browsing by Author "Mbilinyi, B."
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Item Agriculture is the main driver of deforestation in Tanzania(Environmental Research Letters, 2020-02-26) Doggart, N.; Morgan-Brown, T.; Lyimo, E.; Mbilinyi, B.; Meshack, C. K.; Sallu, S. M.; Spracklen, D. V.Reducing deforestation can generate multiple economic, social and ecological benefits by safeguarding the climate and other ecosystem services provided by forests. Understanding the relative contribution of different drivers of deforestation is needed to guide policies seeking to maintain natural forest cover. We assessed 119 randomly selected plots from areas deforested between 2010 and 2017, in Tanzania. Through ground surveys and stakeholder interviews we assessed the proximate deforestation drivers at each point. Crop cultivation was the most commonly observed driver occurring in 89% of plots, compared to livestock grazing (69%) and charcoal (35%). There was evidence of fire in 77% of plots. Most deforestation events involved multiple drivers, with 83% of plots showing signs of two or more drivers. Stakeholder interviews identified agriculture as the primary deforestation driver in 81% of plots, substantially more than charcoal production (12%), timber harvesting (1%) and livestock (1%). Policy-makers in Tanzania have sought to reduce deforestation by reducing demand for charcoal. However, our work demonstrates that agriculture, not charcoal, is the main driver of deforestation in Tanzania. Beyond protected areas, there is no clear policy limiting the conversion of forests to agricultural land. Reducing deforestation in Tanzania requires greater inter-sectoral coordination between the agriculture, livestock, land, energy and forest sectors.Item The biological importance of the Eastern Arc Mountains of Tanzania and Kenya(Elsevier, 2006-10) Burgess, N.D.; Butynski, T.M.; Cordeiro, N.J.; Doggart, N.H.; Fjeldså, J.; Howell, K.M.; Kilahama, F.B.; Loader, S.P.; Lovett, J.C.; Mbilinyi, B.; Menegon, M.; Moyer, D.C.; Nashanda, E.; Perking, A.The Eastern Arc Mountains are renown in Africa for high concentrations of endemic Received 17 June 2005 species of animals and plants. Thirteen separate mountain blocks comprise the Eastern Received in revised Arc, supporting around 3300 km 2 of sub-montane, montane and upper montane forest, less form 29 June 2006 than 30% of the estimated original forested area. At least 96 vertebrate species are endemic, Accepted 8 August 2006 split as follows: 10 mammal, 19 bird, 29 reptile and 38 amphibian species. This includes Available online 12 October 2006 four endemic or nearly endemic species of primate – the Sanje Mangabey, the Iringa Red Colobus, the Mountain Galago and the new Kipunji monkey that forms its own monotypic Keywords: genus. A further 71 vertebrate species are near-endemic. At least 800 vascular plant species Biodiversity conservation are endemic, almost 10% of these being trees. These endemics include the majority of the Eastern Arc Mountains species of African violet – Saintpaulia, a well-known flowering plant in Western households. Protected areas An additional 32 species of bryophytes are also endemic. Many hundreds of invertebrates Diversity are also likely to be endemic, with data for butterflies, millipedes and dragonflies indicating Endemism potential trends in importance. Seventy-one of the endemic or near-endemic vertebrates are threatened by extinction (8 critical, 27 endangered, 36 vulnerable), with an additional seven wide ranging threatened species. Hundreds of plant species are also threatenedItem High resolution mapping of agricultural water productivity using SEBAL in a cultivated African catchment, Tanzania(Elsevier Ltd, 2019) Nyolei, D.; Nsaali, M.; Minaya, V.; van Griensven, A.; Mbilinyi, B.; Diels, J.; Hessels, T.; Kahimba, F.The application of remote sensing techniques for WPET mapping in data scarce regions is gaining more recognition since it can cover large areas with minimal field observations. Important concerns are the generation of high-resolution WPET maps and addressing the question on how accurate the results are. This study aims at high resolution (10 m) mapping and evaluation of the spatial variability of biomass, yield, ET and WPET in the Makanya river catchment using the automated Surface Energy Balance Algorithm for Land (pySEBAL) with SENTINEL-2 and LANDSAT-8 images, local land use map and locally calibrated leaf area index (LAI) inputs. A coupled phenological variability and supervised classification approach on high resolution images generated a high accuracy LULC layer which was used to map the WPET in the agricultural lands. The pySEBAL results were evaluated in view of local information on crop yields, water allocation and agricultural management practices in the different agro-ecological zones within the catchment. Calibration of high-resolution satellite LAI generated products with error estimates within acceptable levels of uncertainty. The simulated crop yields were in agreement with reported crop yields. The results showed relatively high WPET in the highlands and low WPET in the midland and lowland areas of the catchment. The latter was attributed to high transmission losses, low irrigation efficiencies, poor agricultural practices and pest/disease attack. When applying SEBAL in African cultivated catchments, it is highly recommended to use SENTINEL-2 data in addition to LANDSAT-8, and to use local information, especially for the ground truthing of land use maps, phenology, crop practices and crop yields.Item Land cover change and carbon emissions over 100 years in an African biodiversity hotspot(Wiley Researcher Academy., 2016) Willcock, S.; Phillips, O . l.; Platts, P. J.; Swetnam, R. D.; Balmford, A.; Burgess, N. D.; Ahrends, A.; Bayliss, J.; Doggart, N.; Doody, K.; Fanning, E.; Green, J. M. H.; Hall, J.; Howell, K. l.; Lovett, J. C.; Marchant, R.; Marshall, A. R.; Mbilinyi, B.; Munishi, P. K. T.; Owen, N.; Topp-Jorgensen, E. J.; Lewis, S. l.Agricultural expansion has resulted in both land use and land cover change (LULCC) across the tropics. However, the spatial and temporal patterns of such change and their resulting impacts are poorly understood, particularly for the presatellite era. Here, we quantify the LULCC history across the 33.9 million ha watershed of Tanzania’s Eastern Arc Mountains, using geo-referenced and digitized historical land cover maps (dated 1908, 1923, 1949 and 2000). Our time series from this biodiversity hotspot shows that forest and savanna area both declined, by 74% (2.8 million ha) and 10% (2.9 million ha), respectively, between 1908 and 2000. This vegetation was replaced by a fivefold increase in cropland, from 1.2 million ha to 6.7 million ha. This LULCC implies a committed release of 0.9 Pg C (95% CI: 0.4– 1.5) across the watershed for the same period, equivalent to 0.3 Mg C ha 1 yr 1. This is at least threefold higher than previous estimates from global models for the same study area. We then used the LULCC data from before and after protected area creation, as well as from areas where no protection was established, to analyse the effectiveness of legal protection on land cover change despite the underlying spatial variation in protected areas. We found that, between 1949 and 2000, forest expanded within legally protected areas, resulting in carbon uptake of 4.8 (3.8–5.7) Mg C ha 1, compared to a committed loss of 11.9 (7.2–16.6) Mg C ha 1 within areas lacking such protection. Furthermore, for nine protected areas where LULCC data are available prior to and following establishment, we show that protection reduces deforestation rates by 150% relative to unprotected portions of the watershed. Our results highlight that considerable LULCC occurred prior to the satellite era, thus other data sources are required to better understand long-term land cover trends in the tropics.Item Quantifying and understanding carbon storage and sequestration within the Eastern Arc mountains of Tanzania, a tropical biodiversity hotspot(Carbon Balance and Management., 2014) Willcock, S.; Phillips, O. L.; Platts, P. J.; Balmford, A.; Burgess, N. D.; Lovett, J .C.; Ahrends, A.; Bayliss, J.; Doggart, N.; Doody, K.; Fanning, E.; Green, J. M. H.; Hall, J.; Howell, K. L.; Marchant, R.; Marshall, A. R.; Mbilinyi, B.; Munishi, P. K .T.; Owen, N.; Swetnam, R. D.; Jorgensen, E. J. T.; Lewis, S. L.Background: The carbon stored in vegetation varies across tropical landscapes due to a complex mix of climatic and edaphic variables, as well as direct human interventions such as deforestation and forest degradation. Mapping and monitoring this variation is essential if policy developments such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation) are to be known to have succeeded or failed. Results: We produce a map of carbon storage across the watershed of the Tanzanian Eastern Arc Mountains (33.9 million ha) using 1,611 forest inventory plots, and correlations with associated climate, soil and disturbance data. As expected, tropical forest stores more carbon per hectare (182 Mg C ha-1) than woody savanna (51 Mg C ha-1). However, woody savanna is the largest aggregate carbon store, with 0.49 Pg C over 9.6 million ha. We estimate the whole landscape stores 1.3 Pg C, significantly higher than most previous estimates for the region. The 95% Confidence Interval for this method (0.9 to 3.2 Pg C) is larger than simpler look-up table methods (1.5 to 1.6 Pg C), suggesting simpler methods may underestimate uncertainty. Using a small number of inventory plots with two censuses (n = 43) to assess changes in carbon storage, and applying the same mapping procedures, we found that carbon storage in the tree-dominated ecosystems has decreased, though not significantly, at a mean rate of 1.47 Mg C ha-1 yr-1 (c. 2% of the stocks of carbon per year). Conclusions: The most influential variables on carbon storage in the region are anthropogenic, particularly historical logging, as noted by the largest coefficient of explanatory variable on the response variable. Of the non-anthropogenic factors, a negative correlation with air temperature and a positive correlation with water availability dominate, having smaller p-values than historical logging but also smaller influence. High carbon storage is typically found far from the commercial capital, in locations with a low monthly temperature range, without a strong dry season, and in areas that have not suffered from historical logging. The results imply that policy interventions could retain carbon stored in vegetation and likely successfully slow or reverse carbon emissions.